| MED-MVS | | | 99.12 1 | 98.97 4 | 99.56 9 | 99.77 2 | 98.86 23 | 99.32 22 | 99.24 20 | 97.87 31 | 99.30 52 | 99.54 20 | 97.61 6 | 99.92 43 | 98.30 75 | 99.80 25 | 99.90 5 |
|
| fmvsm_l_conf0.5_n_a | | | 99.09 2 | 99.08 1 | 99.11 62 | 99.43 63 | 97.48 90 | 98.88 131 | 99.30 14 | 98.47 18 | 99.85 11 | 99.43 45 | 96.71 18 | 99.96 4 | 99.86 1 | 99.80 25 | 99.89 8 |
|
| SED-MVS | | | 99.09 2 | 98.91 5 | 99.63 5 | 99.71 24 | 99.24 5 | 99.02 86 | 98.87 85 | 97.65 41 | 99.73 23 | 99.48 35 | 97.53 8 | 99.94 14 | 98.43 67 | 99.81 16 | 99.70 67 |
|
| DVP-MVS++ | | | 99.08 4 | 98.89 6 | 99.64 4 | 99.17 111 | 99.23 7 | 99.69 1 | 98.88 78 | 97.32 65 | 99.53 38 | 99.47 37 | 97.81 3 | 99.94 14 | 98.47 63 | 99.72 66 | 99.74 50 |
|
| fmvsm_l_conf0.5_n | | | 99.07 5 | 99.05 2 | 99.14 58 | 99.41 66 | 97.54 88 | 98.89 124 | 99.31 13 | 98.49 17 | 99.86 8 | 99.42 46 | 96.45 28 | 99.96 4 | 99.86 1 | 99.74 57 | 99.90 5 |
|
| TestfortrainingZip a | | | 99.05 6 | 98.85 9 | 99.65 2 | 99.77 2 | 99.13 11 | 99.32 22 | 99.01 52 | 97.87 31 | 99.74 21 | 99.54 20 | 96.71 18 | 99.92 43 | 98.35 72 | 99.33 139 | 99.90 5 |
|
| DVP-MVS |  | | 99.03 7 | 98.83 11 | 99.63 5 | 99.72 17 | 99.25 2 | 98.97 98 | 98.58 176 | 97.62 43 | 99.45 40 | 99.46 42 | 97.42 10 | 99.94 14 | 98.47 63 | 99.81 16 | 99.69 70 |
| Zhenlong Yuan, Jinguo Luo, Fei Shen, Zhaoxin Li, Cong Liu, Tianlu Mao, Zhaoqi Wang: DVP-MVS: Synergize Depth-Edge and Visibility Prior for Multi-View Stereo. AAAI2025 |
| APDe-MVS |  | | 99.02 8 | 98.84 10 | 99.55 11 | 99.57 39 | 98.96 18 | 99.39 11 | 98.93 65 | 97.38 62 | 99.41 44 | 99.54 20 | 96.66 20 | 99.84 88 | 98.86 39 | 99.85 6 | 99.87 12 |
| Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition |
| lecture | | | 98.95 9 | 98.78 14 | 99.45 19 | 99.75 6 | 98.63 31 | 99.43 10 | 99.38 8 | 97.60 46 | 99.58 34 | 99.47 37 | 95.36 64 | 99.93 34 | 98.87 38 | 99.57 98 | 99.78 33 |
|
| reproduce_model | | | 98.94 10 | 98.81 12 | 99.34 32 | 99.52 45 | 98.26 55 | 98.94 108 | 98.84 96 | 98.06 25 | 99.35 48 | 99.61 5 | 96.39 31 | 99.94 14 | 98.77 42 | 99.82 14 | 99.83 19 |
|
| reproduce-ours | | | 98.93 11 | 98.78 14 | 99.38 24 | 99.49 52 | 98.38 41 | 98.86 142 | 98.83 98 | 98.06 25 | 99.29 54 | 99.58 16 | 96.40 29 | 99.94 14 | 98.68 45 | 99.81 16 | 99.81 25 |
|
| our_new_method | | | 98.93 11 | 98.78 14 | 99.38 24 | 99.49 52 | 98.38 41 | 98.86 142 | 98.83 98 | 98.06 25 | 99.29 54 | 99.58 16 | 96.40 29 | 99.94 14 | 98.68 45 | 99.81 16 | 99.81 25 |
|
| test_fmvsmconf_n | | | 98.92 13 | 98.87 7 | 99.04 68 | 98.88 147 | 97.25 112 | 98.82 155 | 99.34 11 | 98.75 11 | 99.80 14 | 99.61 5 | 95.16 77 | 99.95 9 | 99.70 17 | 99.80 25 | 99.93 1 |
|
| DPE-MVS |  | | 98.92 13 | 98.67 20 | 99.65 2 | 99.58 37 | 99.20 9 | 98.42 267 | 98.91 72 | 97.58 47 | 99.54 37 | 99.46 42 | 97.10 13 | 99.94 14 | 97.64 122 | 99.84 11 | 99.83 19 |
| Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025 |
| fmvsm_l_conf0.5_n_9 | | | 98.90 15 | 98.79 13 | 99.24 46 | 99.34 71 | 97.83 79 | 98.70 196 | 99.26 16 | 98.85 6 | 99.92 1 | 99.51 28 | 93.91 106 | 99.95 9 | 99.86 1 | 99.79 34 | 99.92 2 |
|
| fmvsm_l_conf0.5_n_3 | | | 98.90 15 | 98.74 18 | 99.37 28 | 99.36 68 | 98.25 56 | 98.89 124 | 99.24 20 | 98.77 10 | 99.89 3 | 99.59 13 | 93.39 112 | 99.96 4 | 99.78 10 | 99.76 47 | 99.89 8 |
|
| SteuartSystems-ACMMP | | | 98.90 15 | 98.75 17 | 99.36 30 | 99.22 106 | 98.43 39 | 99.10 69 | 98.87 85 | 97.38 62 | 99.35 48 | 99.40 49 | 97.78 5 | 99.87 79 | 97.77 110 | 99.85 6 | 99.78 33 |
| Skip Steuart: Steuart Systems R&D Blog. |
| test_fmvsm_n_1920 | | | 98.87 18 | 99.01 3 | 98.45 124 | 99.42 64 | 96.43 156 | 98.96 104 | 99.36 10 | 98.63 13 | 99.86 8 | 99.51 28 | 95.91 46 | 99.97 1 | 99.72 14 | 99.75 53 | 98.94 236 |
|
| ME-MVS | | | 98.83 19 | 98.60 24 | 99.52 14 | 99.58 37 | 98.86 23 | 98.69 199 | 98.93 65 | 97.00 91 | 99.17 63 | 99.35 62 | 96.62 23 | 99.90 64 | 98.30 75 | 99.80 25 | 99.79 29 |
|
| TSAR-MVS + MP. | | | 98.78 20 | 98.62 22 | 99.24 46 | 99.69 29 | 98.28 54 | 99.14 60 | 98.66 153 | 96.84 98 | 99.56 35 | 99.31 71 | 96.34 32 | 99.70 143 | 98.32 74 | 99.73 61 | 99.73 55 |
| Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition |
| CNVR-MVS | | | 98.78 20 | 98.56 28 | 99.45 19 | 99.32 77 | 98.87 21 | 98.47 254 | 98.81 107 | 97.72 36 | 98.76 96 | 99.16 110 | 97.05 14 | 99.78 124 | 98.06 89 | 99.66 77 | 99.69 70 |
|
| MSP-MVS | | | 98.74 22 | 98.55 29 | 99.29 39 | 99.75 6 | 98.23 57 | 99.26 33 | 98.88 78 | 97.52 50 | 99.41 44 | 98.78 192 | 96.00 42 | 99.79 121 | 97.79 109 | 99.59 94 | 99.85 16 |
| Zhenlong Yuan, Cong Liu, Fei Shen, Zhaoxin Li, Jingguo luo, Tianlu Mao and Zhaoqi Wang: MSP-MVS: Multi-granularity Segmentation Prior Guided Multi-View Stereo. AAAI2025 |
| fmvsm_s_conf0.5_n_8 | | | 98.73 23 | 98.62 22 | 99.05 67 | 99.35 70 | 97.27 106 | 98.80 164 | 99.23 27 | 98.93 3 | 99.79 15 | 99.59 13 | 92.34 129 | 99.95 9 | 99.82 6 | 99.71 68 | 99.92 2 |
|
| XVS | | | 98.70 24 | 98.49 36 | 99.34 32 | 99.70 27 | 98.35 50 | 99.29 28 | 98.88 78 | 97.40 59 | 98.46 119 | 99.20 95 | 95.90 48 | 99.89 68 | 97.85 104 | 99.74 57 | 99.78 33 |
|
| fmvsm_s_conf0.5_n_10 | | | 98.66 25 | 98.54 31 | 99.02 69 | 99.36 68 | 97.21 115 | 98.86 142 | 99.23 27 | 98.90 5 | 99.83 12 | 99.59 13 | 91.57 160 | 99.94 14 | 99.79 9 | 99.74 57 | 99.89 8 |
|
| fmvsm_s_conf0.5_n_6 | | | 98.65 26 | 98.55 29 | 98.95 78 | 98.50 187 | 97.30 102 | 98.79 172 | 99.16 39 | 98.14 23 | 99.86 8 | 99.41 48 | 93.71 109 | 99.91 56 | 99.71 15 | 99.64 85 | 99.65 83 |
|
| MCST-MVS | | | 98.65 26 | 98.37 45 | 99.48 17 | 99.60 36 | 98.87 21 | 98.41 268 | 98.68 145 | 97.04 88 | 98.52 117 | 98.80 186 | 96.78 17 | 99.83 90 | 97.93 96 | 99.61 90 | 99.74 50 |
|
| SD-MVS | | | 98.64 28 | 98.68 19 | 98.53 113 | 99.33 74 | 98.36 49 | 98.90 120 | 98.85 95 | 97.28 69 | 99.72 26 | 99.39 50 | 96.63 22 | 97.60 446 | 98.17 84 | 99.85 6 | 99.64 86 |
| Zhenlong Yuan, Jiakai Cao, Zhaoxin Li, Hao Jiang and Zhaoqi Wang: SD-MVS: Segmentation-driven Deformation Multi-View Stereo with Spherical Refinement and EM optimization. AAAI2024 |
| fmvsm_s_conf0.5_n_9 | | | 98.63 29 | 98.66 21 | 98.54 110 | 99.40 67 | 95.83 203 | 98.79 172 | 99.17 37 | 98.94 2 | 99.92 1 | 99.61 5 | 92.49 124 | 99.93 34 | 99.86 1 | 99.76 47 | 99.86 13 |
|
| HFP-MVS | | | 98.63 29 | 98.40 42 | 99.32 38 | 99.72 17 | 98.29 53 | 99.23 38 | 98.96 60 | 96.10 141 | 98.94 78 | 99.17 107 | 96.06 39 | 99.92 43 | 97.62 123 | 99.78 39 | 99.75 48 |
|
| ACMMP_NAP | | | 98.61 31 | 98.30 60 | 99.55 11 | 99.62 35 | 98.95 19 | 98.82 155 | 98.81 107 | 95.80 157 | 99.16 67 | 99.47 37 | 95.37 63 | 99.92 43 | 97.89 101 | 99.75 53 | 99.79 29 |
|
| region2R | | | 98.61 31 | 98.38 44 | 99.29 39 | 99.74 12 | 98.16 63 | 99.23 38 | 98.93 65 | 96.15 136 | 98.94 78 | 99.17 107 | 95.91 46 | 99.94 14 | 97.55 135 | 99.79 34 | 99.78 33 |
|
| NCCC | | | 98.61 31 | 98.35 48 | 99.38 24 | 99.28 92 | 98.61 32 | 98.45 256 | 98.76 125 | 97.82 35 | 98.45 122 | 98.93 164 | 96.65 21 | 99.83 90 | 97.38 157 | 99.41 128 | 99.71 63 |
|
| SF-MVS | | | 98.59 34 | 98.32 59 | 99.41 23 | 99.54 41 | 98.71 27 | 99.04 80 | 98.81 107 | 95.12 211 | 99.32 51 | 99.39 50 | 96.22 33 | 99.84 88 | 97.72 113 | 99.73 61 | 99.67 79 |
|
| ACMMPR | | | 98.59 34 | 98.36 46 | 99.29 39 | 99.74 12 | 98.15 64 | 99.23 38 | 98.95 61 | 96.10 141 | 98.93 82 | 99.19 102 | 95.70 52 | 99.94 14 | 97.62 123 | 99.79 34 | 99.78 33 |
|
| fmvsm_s_conf0.5_n_11 | | | 98.58 36 | 98.57 26 | 98.62 100 | 99.42 64 | 97.16 118 | 98.97 98 | 98.86 91 | 98.91 4 | 99.87 4 | 99.66 3 | 91.82 152 | 99.95 9 | 99.82 6 | 99.82 14 | 98.75 259 |
|
| test_fmvsmconf0.1_n | | | 98.58 36 | 98.44 40 | 98.99 71 | 97.73 307 | 97.15 119 | 98.84 151 | 98.97 57 | 98.75 11 | 99.43 42 | 99.54 20 | 93.29 114 | 99.93 34 | 99.64 20 | 99.79 34 | 99.89 8 |
|
| SMA-MVS |  | | 98.58 36 | 98.25 63 | 99.56 9 | 99.51 46 | 99.04 17 | 98.95 105 | 98.80 114 | 93.67 306 | 99.37 47 | 99.52 25 | 96.52 26 | 99.89 68 | 98.06 89 | 99.81 16 | 99.76 47 |
| Yufeng Yin; Xiaoyan Liu; Zichao Zhang: SMA-MVS: Segmentation-Guided Multi-Scale Anchor Deformation Patch Multi-View Stereo. IEEE Transactions on Circuits and Systems for Video Technology |
| MTAPA | | | 98.58 36 | 98.29 61 | 99.46 18 | 99.76 5 | 98.64 30 | 98.90 120 | 98.74 129 | 97.27 73 | 98.02 152 | 99.39 50 | 94.81 87 | 99.96 4 | 97.91 99 | 99.79 34 | 99.77 40 |
|
| HPM-MVS++ |  | | 98.58 36 | 98.25 63 | 99.55 11 | 99.50 48 | 99.08 12 | 98.72 191 | 98.66 153 | 97.51 51 | 98.15 136 | 98.83 183 | 95.70 52 | 99.92 43 | 97.53 138 | 99.67 74 | 99.66 82 |
|
| SR-MVS | | | 98.57 41 | 98.35 48 | 99.24 46 | 99.53 42 | 98.18 61 | 99.09 70 | 98.82 101 | 96.58 114 | 99.10 69 | 99.32 69 | 95.39 61 | 99.82 97 | 97.70 118 | 99.63 87 | 99.72 59 |
|
| CP-MVS | | | 98.57 41 | 98.36 46 | 99.19 51 | 99.66 31 | 97.86 75 | 99.34 17 | 98.87 85 | 95.96 148 | 98.60 113 | 99.13 117 | 96.05 40 | 99.94 14 | 97.77 110 | 99.86 2 | 99.77 40 |
|
| MSLP-MVS++ | | | 98.56 43 | 98.57 26 | 98.55 108 | 99.26 95 | 96.80 134 | 98.71 192 | 99.05 49 | 97.28 69 | 98.84 88 | 99.28 76 | 96.47 27 | 99.40 207 | 98.52 61 | 99.70 70 | 99.47 116 |
|
| DeepC-MVS_fast | | 96.70 1 | 98.55 44 | 98.34 54 | 99.18 53 | 99.25 96 | 98.04 69 | 98.50 249 | 98.78 121 | 97.72 36 | 98.92 84 | 99.28 76 | 95.27 70 | 99.82 97 | 97.55 135 | 99.77 41 | 99.69 70 |
| Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
| SR-MVS-dyc-post | | | 98.54 45 | 98.35 48 | 99.13 59 | 99.49 52 | 97.86 75 | 99.11 66 | 98.80 114 | 96.49 118 | 99.17 63 | 99.35 62 | 95.34 66 | 99.82 97 | 97.72 113 | 99.65 80 | 99.71 63 |
|
| fmvsm_s_conf0.5_n_5 | | | 98.53 46 | 98.35 48 | 99.08 64 | 99.07 127 | 97.46 94 | 98.68 202 | 99.20 33 | 97.50 52 | 99.87 4 | 99.50 31 | 91.96 149 | 99.96 4 | 99.76 11 | 99.65 80 | 99.82 23 |
|
| fmvsm_s_conf0.5_n_3 | | | 98.53 46 | 98.45 39 | 98.79 86 | 99.23 104 | 97.32 99 | 98.80 164 | 99.26 16 | 98.82 7 | 99.87 4 | 99.60 10 | 90.95 194 | 99.93 34 | 99.76 11 | 99.73 61 | 99.12 206 |
|
| APD-MVS_3200maxsize | | | 98.53 46 | 98.33 58 | 99.15 57 | 99.50 48 | 97.92 74 | 99.15 57 | 98.81 107 | 96.24 132 | 99.20 60 | 99.37 56 | 95.30 68 | 99.80 109 | 97.73 112 | 99.67 74 | 99.72 59 |
|
| MM | | | 98.51 49 | 98.24 65 | 99.33 36 | 99.12 121 | 98.14 66 | 98.93 114 | 97.02 428 | 98.96 1 | 99.17 63 | 99.47 37 | 91.97 148 | 99.94 14 | 99.85 5 | 99.69 71 | 99.91 4 |
|
| mPP-MVS | | | 98.51 49 | 98.26 62 | 99.25 45 | 99.75 6 | 98.04 69 | 99.28 30 | 98.81 107 | 96.24 132 | 98.35 131 | 99.23 87 | 95.46 58 | 99.94 14 | 97.42 152 | 99.81 16 | 99.77 40 |
|
| ZNCC-MVS | | | 98.49 51 | 98.20 71 | 99.35 31 | 99.73 16 | 98.39 40 | 99.19 50 | 98.86 91 | 95.77 159 | 98.31 135 | 99.10 125 | 95.46 58 | 99.93 34 | 97.57 134 | 99.81 16 | 99.74 50 |
|
| SPE-MVS-test | | | 98.49 51 | 98.50 34 | 98.46 123 | 99.20 109 | 97.05 124 | 99.64 4 | 98.50 199 | 97.45 58 | 98.88 85 | 99.14 114 | 95.25 72 | 99.15 261 | 98.83 40 | 99.56 106 | 99.20 189 |
|
| PGM-MVS | | | 98.49 51 | 98.23 67 | 99.27 44 | 99.72 17 | 98.08 68 | 98.99 94 | 99.49 5 | 95.43 186 | 99.03 70 | 99.32 69 | 95.56 55 | 99.94 14 | 96.80 191 | 99.77 41 | 99.78 33 |
|
| EI-MVSNet-Vis-set | | | 98.47 54 | 98.39 43 | 98.69 94 | 99.46 58 | 96.49 153 | 98.30 281 | 98.69 142 | 97.21 76 | 98.84 88 | 99.36 60 | 95.41 60 | 99.78 124 | 98.62 49 | 99.65 80 | 99.80 28 |
|
| MVS_111021_HR | | | 98.47 54 | 98.34 54 | 98.88 83 | 99.22 106 | 97.32 99 | 97.91 342 | 99.58 3 | 97.20 77 | 98.33 133 | 99.00 152 | 95.99 43 | 99.64 157 | 98.05 91 | 99.76 47 | 99.69 70 |
|
| BridgeMVS | | | 98.45 56 | 98.35 48 | 98.74 90 | 98.65 176 | 97.55 86 | 99.19 50 | 98.60 164 | 96.72 108 | 99.35 48 | 98.77 195 | 95.06 82 | 99.55 181 | 98.95 34 | 99.87 1 | 99.12 206 |
|
| test_fmvsmvis_n_1920 | | | 98.44 57 | 98.51 32 | 98.23 146 | 98.33 221 | 96.15 171 | 98.97 98 | 99.15 41 | 98.55 16 | 98.45 122 | 99.55 18 | 94.26 100 | 99.97 1 | 99.65 18 | 99.66 77 | 98.57 284 |
|
| CS-MVS | | | 98.44 57 | 98.49 36 | 98.31 137 | 99.08 126 | 96.73 138 | 99.67 3 | 98.47 206 | 97.17 80 | 98.94 78 | 99.10 125 | 95.73 51 | 99.13 266 | 98.71 44 | 99.49 117 | 99.09 214 |
|
| GST-MVS | | | 98.43 59 | 98.12 75 | 99.34 32 | 99.72 17 | 98.38 41 | 99.09 70 | 98.82 101 | 95.71 163 | 98.73 99 | 99.06 141 | 95.27 70 | 99.93 34 | 97.07 167 | 99.63 87 | 99.72 59 |
|
| fmvsm_s_conf0.5_n | | | 98.42 60 | 98.51 32 | 98.13 164 | 99.30 83 | 95.25 243 | 98.85 147 | 99.39 7 | 97.94 29 | 99.74 21 | 99.62 4 | 92.59 123 | 99.91 56 | 99.65 18 | 99.52 112 | 99.25 182 |
|
| EI-MVSNet-UG-set | | | 98.41 61 | 98.34 54 | 98.61 102 | 99.45 61 | 96.32 163 | 98.28 284 | 98.68 145 | 97.17 80 | 98.74 97 | 99.37 56 | 95.25 72 | 99.79 121 | 98.57 52 | 99.54 109 | 99.73 55 |
|
| DELS-MVS | | | 98.40 62 | 98.20 71 | 98.99 71 | 99.00 135 | 97.66 81 | 97.75 364 | 98.89 75 | 97.71 38 | 98.33 133 | 98.97 154 | 94.97 84 | 99.88 77 | 98.42 69 | 99.76 47 | 99.42 133 |
| Christian Sormann, Emanuele Santellani, Mattia Rossi, Andreas Kuhn, Friedrich Fraundorfer: DELS-MVS: Deep Epipolar Line Search for Multi-View Stereo. Winter Conference on Applications of Computer Vision (WACV), 2023 |
| fmvsm_s_conf0.5_n_a | | | 98.38 63 | 98.42 41 | 98.27 139 | 99.09 125 | 95.41 229 | 98.86 142 | 99.37 9 | 97.69 40 | 99.78 17 | 99.61 5 | 92.38 127 | 99.91 56 | 99.58 23 | 99.43 126 | 99.49 112 |
|
| TSAR-MVS + GP. | | | 98.38 63 | 98.24 65 | 98.81 85 | 99.22 106 | 97.25 112 | 98.11 317 | 98.29 277 | 97.19 78 | 98.99 76 | 99.02 146 | 96.22 33 | 99.67 150 | 98.52 61 | 98.56 184 | 99.51 104 |
|
| HPM-MVS_fast | | | 98.38 63 | 98.13 74 | 99.12 61 | 99.75 6 | 97.86 75 | 99.44 9 | 98.82 101 | 94.46 259 | 98.94 78 | 99.20 95 | 95.16 77 | 99.74 134 | 97.58 130 | 99.85 6 | 99.77 40 |
|
| patch_mono-2 | | | 98.36 66 | 98.87 7 | 96.82 283 | 99.53 42 | 90.68 407 | 98.64 212 | 99.29 15 | 97.88 30 | 99.19 62 | 99.52 25 | 96.80 16 | 99.97 1 | 99.11 30 | 99.86 2 | 99.82 23 |
|
| HPM-MVS |  | | 98.36 66 | 98.10 77 | 99.13 59 | 99.74 12 | 97.82 80 | 99.53 6 | 98.80 114 | 94.63 247 | 98.61 112 | 98.97 154 | 95.13 79 | 99.77 129 | 97.65 121 | 99.83 13 | 99.79 29 |
| Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
| fmvsm_s_conf0.5_n_4 | | | 98.35 68 | 98.50 34 | 97.90 194 | 99.16 115 | 95.08 253 | 98.75 177 | 99.24 20 | 98.39 19 | 99.81 13 | 99.52 25 | 92.35 128 | 99.90 64 | 99.74 13 | 99.51 114 | 98.71 265 |
|
| APD-MVS |  | | 98.35 68 | 98.00 83 | 99.42 22 | 99.51 46 | 98.72 26 | 98.80 164 | 98.82 101 | 94.52 254 | 99.23 59 | 99.25 86 | 95.54 57 | 99.80 109 | 96.52 200 | 99.77 41 | 99.74 50 |
| Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
| MVS_111021_LR | | | 98.34 70 | 98.23 67 | 98.67 96 | 99.27 93 | 96.90 130 | 97.95 335 | 99.58 3 | 97.14 83 | 98.44 124 | 99.01 150 | 95.03 83 | 99.62 164 | 97.91 99 | 99.75 53 | 99.50 107 |
|
| PHI-MVS | | | 98.34 70 | 98.06 78 | 99.18 53 | 99.15 118 | 98.12 67 | 99.04 80 | 99.09 44 | 93.32 325 | 98.83 91 | 99.10 125 | 96.54 24 | 99.83 90 | 97.70 118 | 99.76 47 | 99.59 94 |
|
| MP-MVS |  | | 98.33 72 | 98.01 82 | 99.28 42 | 99.75 6 | 98.18 61 | 99.22 42 | 98.79 119 | 96.13 137 | 97.92 166 | 99.23 87 | 94.54 90 | 99.94 14 | 96.74 194 | 99.78 39 | 99.73 55 |
| Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
| MVSMamba_PlusPlus | | | 98.31 73 | 98.19 73 | 98.67 96 | 98.96 141 | 97.36 97 | 99.24 36 | 98.57 178 | 94.81 235 | 98.99 76 | 98.90 171 | 95.22 75 | 99.59 167 | 99.15 29 | 99.84 11 | 99.07 222 |
|
| MP-MVS-pluss | | | 98.31 73 | 97.92 85 | 99.49 16 | 99.72 17 | 98.88 20 | 98.43 264 | 98.78 121 | 94.10 271 | 97.69 189 | 99.42 46 | 95.25 72 | 99.92 43 | 98.09 88 | 99.80 25 | 99.67 79 |
| MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
| fmvsm_s_conf0.5_n_2 | | | 98.30 75 | 98.21 69 | 98.57 105 | 99.25 96 | 97.11 121 | 98.66 209 | 99.20 33 | 98.82 7 | 99.79 15 | 99.60 10 | 89.38 243 | 99.92 43 | 99.80 8 | 99.38 133 | 98.69 267 |
|
| fmvsm_s_conf0.5_n_7 | | | 98.23 76 | 98.35 48 | 97.89 196 | 98.86 151 | 94.99 259 | 98.58 225 | 99.00 53 | 98.29 20 | 99.73 23 | 99.60 10 | 91.70 155 | 99.92 43 | 99.63 21 | 99.73 61 | 98.76 258 |
|
| MGCNet | | | 98.23 76 | 97.91 86 | 99.21 50 | 98.06 270 | 97.96 73 | 98.58 225 | 95.51 469 | 98.58 14 | 98.87 86 | 99.26 80 | 92.99 118 | 99.95 9 | 99.62 22 | 99.67 74 | 99.73 55 |
|
| ACMMP |  | | 98.23 76 | 97.95 84 | 99.09 63 | 99.74 12 | 97.62 84 | 99.03 83 | 99.41 6 | 95.98 146 | 97.60 203 | 99.36 60 | 94.45 95 | 99.93 34 | 97.14 164 | 98.85 167 | 99.70 67 |
| Qingshan Xu, Weihang Kong, Wenbing Tao, Marc Pollefeys: Multi-Scale Geometric Consistency Guided and Planar Prior Assisted Multi-View Stereo. IEEE Transactions on Pattern Analysis and Machine Intelligence |
| EC-MVSNet | | | 98.21 79 | 98.11 76 | 98.49 120 | 98.34 217 | 97.26 111 | 99.61 5 | 98.43 226 | 96.78 101 | 98.87 86 | 98.84 179 | 93.72 108 | 99.01 294 | 98.91 37 | 99.50 115 | 99.19 193 |
|
| fmvsm_s_conf0.1_n | | | 98.18 80 | 98.21 69 | 98.11 169 | 98.54 185 | 95.24 244 | 98.87 134 | 99.24 20 | 97.50 52 | 99.70 27 | 99.67 1 | 91.33 172 | 99.89 68 | 99.47 25 | 99.54 109 | 99.21 188 |
|
| fmvsm_s_conf0.1_n_2 | | | 98.14 81 | 98.02 81 | 98.53 113 | 98.88 147 | 97.07 123 | 98.69 199 | 98.82 101 | 98.78 9 | 99.77 18 | 99.61 5 | 88.83 265 | 99.91 56 | 99.71 15 | 99.07 150 | 98.61 277 |
|
| fmvsm_s_conf0.1_n_a | | | 98.08 82 | 98.04 80 | 98.21 147 | 97.66 313 | 95.39 234 | 98.89 124 | 99.17 37 | 97.24 74 | 99.76 20 | 99.67 1 | 91.13 184 | 99.88 77 | 99.39 26 | 99.41 128 | 99.35 148 |
|
| dcpmvs_2 | | | 98.08 82 | 98.59 25 | 96.56 313 | 99.57 39 | 90.34 419 | 99.15 57 | 98.38 248 | 96.82 100 | 99.29 54 | 99.49 34 | 95.78 50 | 99.57 171 | 98.94 35 | 99.86 2 | 99.77 40 |
|
| NormalMVS | | | 98.07 84 | 97.90 87 | 98.59 104 | 99.75 6 | 96.60 144 | 98.94 108 | 98.60 164 | 97.86 33 | 98.71 102 | 99.08 136 | 91.22 179 | 99.80 109 | 97.40 154 | 99.57 98 | 99.37 143 |
|
| CANet | | | 98.05 85 | 97.76 90 | 98.90 82 | 98.73 161 | 97.27 106 | 98.35 271 | 98.78 121 | 97.37 64 | 97.72 186 | 98.96 159 | 91.53 165 | 99.92 43 | 98.79 41 | 99.65 80 | 99.51 104 |
|
| train_agg | | | 97.97 86 | 97.52 103 | 99.33 36 | 99.31 79 | 98.50 35 | 97.92 340 | 98.73 132 | 92.98 341 | 97.74 183 | 98.68 208 | 96.20 35 | 99.80 109 | 96.59 195 | 99.57 98 | 99.68 75 |
|
| ETV-MVS | | | 97.96 87 | 97.81 88 | 98.40 132 | 98.42 200 | 97.27 106 | 98.73 187 | 98.55 184 | 96.84 98 | 98.38 127 | 97.44 332 | 95.39 61 | 99.35 212 | 97.62 123 | 98.89 161 | 98.58 283 |
|
| UA-Net | | | 97.96 87 | 97.62 94 | 98.98 73 | 98.86 151 | 97.47 92 | 98.89 124 | 99.08 45 | 96.67 111 | 98.72 101 | 99.54 20 | 93.15 116 | 99.81 102 | 94.87 259 | 98.83 168 | 99.65 83 |
|
| CDPH-MVS | | | 97.94 89 | 97.49 105 | 99.28 42 | 99.47 56 | 98.44 37 | 97.91 342 | 98.67 150 | 92.57 358 | 98.77 95 | 98.85 178 | 95.93 45 | 99.72 137 | 95.56 237 | 99.69 71 | 99.68 75 |
|
| DeepPCF-MVS | | 96.37 2 | 97.93 90 | 98.48 38 | 96.30 341 | 99.00 135 | 89.54 435 | 97.43 389 | 98.87 85 | 98.16 22 | 99.26 58 | 99.38 55 | 96.12 38 | 99.64 157 | 98.30 75 | 99.77 41 | 99.72 59 |
|
| DeepC-MVS | | 95.98 3 | 97.88 91 | 97.58 96 | 98.77 88 | 99.25 96 | 96.93 128 | 98.83 153 | 98.75 127 | 96.96 93 | 96.89 235 | 99.50 31 | 90.46 208 | 99.87 79 | 97.84 106 | 99.76 47 | 99.52 101 |
| Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
| test_fmvsmconf0.01_n | | | 97.86 92 | 97.54 102 | 98.83 84 | 95.48 441 | 96.83 133 | 98.95 105 | 98.60 164 | 98.58 14 | 98.93 82 | 99.55 18 | 88.57 270 | 99.91 56 | 99.54 24 | 99.61 90 | 99.77 40 |
|
| DP-MVS Recon | | | 97.86 92 | 97.46 108 | 99.06 66 | 99.53 42 | 98.35 50 | 98.33 273 | 98.89 75 | 92.62 355 | 98.05 147 | 98.94 162 | 95.34 66 | 99.65 154 | 96.04 216 | 99.42 127 | 99.19 193 |
|
| CSCG | | | 97.85 94 | 97.74 91 | 98.20 149 | 99.67 30 | 95.16 248 | 99.22 42 | 99.32 12 | 93.04 339 | 97.02 228 | 98.92 169 | 95.36 64 | 99.91 56 | 97.43 150 | 99.64 85 | 99.52 101 |
|
| SymmetryMVS | | | 97.84 95 | 97.58 96 | 98.62 100 | 99.01 133 | 96.60 144 | 98.94 108 | 98.44 215 | 97.86 33 | 98.71 102 | 99.08 136 | 91.22 179 | 99.80 109 | 97.40 154 | 97.53 258 | 99.47 116 |
|
| BP-MVS1 | | | 97.82 96 | 97.51 104 | 98.76 89 | 98.25 237 | 97.39 96 | 99.15 57 | 97.68 357 | 96.69 109 | 98.47 118 | 99.10 125 | 90.29 216 | 99.51 187 | 98.60 50 | 99.35 136 | 99.37 143 |
|
| MG-MVS | | | 97.81 97 | 97.60 95 | 98.44 126 | 99.12 121 | 95.97 184 | 97.75 364 | 98.78 121 | 96.89 96 | 98.46 119 | 99.22 90 | 93.90 107 | 99.68 149 | 94.81 263 | 99.52 112 | 99.67 79 |
|
| VNet | | | 97.79 98 | 97.40 114 | 98.96 76 | 98.88 147 | 97.55 86 | 98.63 215 | 98.93 65 | 96.74 105 | 99.02 71 | 98.84 179 | 90.33 215 | 99.83 90 | 98.53 55 | 96.66 281 | 99.50 107 |
|
| EIA-MVS | | | 97.75 99 | 97.58 96 | 98.27 139 | 98.38 207 | 96.44 155 | 99.01 89 | 98.60 164 | 95.88 152 | 97.26 214 | 97.53 326 | 94.97 84 | 99.33 215 | 97.38 157 | 99.20 146 | 99.05 223 |
|
| PS-MVSNAJ | | | 97.73 100 | 97.77 89 | 97.62 227 | 98.68 171 | 95.58 217 | 97.34 398 | 98.51 194 | 97.29 67 | 98.66 109 | 97.88 290 | 94.51 91 | 99.90 64 | 97.87 103 | 99.17 148 | 97.39 330 |
|
| casdiffmvs_mvg |  | | 97.72 101 | 97.48 107 | 98.44 126 | 98.42 200 | 96.59 148 | 98.92 117 | 98.44 215 | 96.20 134 | 97.76 180 | 99.20 95 | 91.66 158 | 99.23 244 | 98.27 82 | 98.41 207 | 99.49 112 |
| Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025 |
| CPTT-MVS | | | 97.72 101 | 97.32 121 | 98.92 79 | 99.64 33 | 97.10 122 | 99.12 64 | 98.81 107 | 92.34 366 | 98.09 141 | 99.08 136 | 93.01 117 | 99.92 43 | 96.06 215 | 99.77 41 | 99.75 48 |
|
| PVSNet_Blended_VisFu | | | 97.70 103 | 97.46 108 | 98.44 126 | 99.27 93 | 95.91 192 | 98.63 215 | 99.16 39 | 94.48 258 | 97.67 191 | 98.88 174 | 92.80 120 | 99.91 56 | 97.11 165 | 99.12 149 | 99.50 107 |
|
| mvsany_test1 | | | 97.69 104 | 97.70 92 | 97.66 223 | 98.24 239 | 94.18 303 | 97.53 380 | 97.53 378 | 95.52 181 | 99.66 29 | 99.51 28 | 94.30 98 | 99.56 174 | 98.38 70 | 98.62 178 | 99.23 184 |
|
| sasdasda | | | 97.67 105 | 97.23 131 | 98.98 73 | 98.70 166 | 98.38 41 | 99.34 17 | 98.39 241 | 96.76 103 | 97.67 191 | 97.40 336 | 92.26 133 | 99.49 191 | 98.28 79 | 96.28 299 | 99.08 218 |
|
| canonicalmvs | | | 97.67 105 | 97.23 131 | 98.98 73 | 98.70 166 | 98.38 41 | 99.34 17 | 98.39 241 | 96.76 103 | 97.67 191 | 97.40 336 | 92.26 133 | 99.49 191 | 98.28 79 | 96.28 299 | 99.08 218 |
|
| xiu_mvs_v2_base | | | 97.66 107 | 97.70 92 | 97.56 231 | 98.61 180 | 95.46 226 | 97.44 386 | 98.46 207 | 97.15 82 | 98.65 110 | 98.15 265 | 94.33 97 | 99.80 109 | 97.84 106 | 98.66 177 | 97.41 328 |
|
| GDP-MVS | | | 97.64 108 | 97.28 124 | 98.71 93 | 98.30 226 | 97.33 98 | 99.05 76 | 98.52 191 | 96.34 128 | 98.80 92 | 99.05 143 | 89.74 230 | 99.51 187 | 96.86 187 | 98.86 165 | 99.28 172 |
|
| baseline | | | 97.64 108 | 97.44 110 | 98.25 143 | 98.35 212 | 96.20 168 | 99.00 91 | 98.32 263 | 96.33 130 | 98.03 150 | 99.17 107 | 91.35 171 | 99.16 257 | 98.10 87 | 98.29 218 | 99.39 138 |
|
| casdiffmvs |  | | 97.63 110 | 97.41 113 | 98.28 138 | 98.33 221 | 96.14 172 | 98.82 155 | 98.32 263 | 96.38 126 | 97.95 161 | 99.21 93 | 91.23 178 | 99.23 244 | 98.12 86 | 98.37 210 | 99.48 114 |
| Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025 |
| cashybrid2 | | | 97.62 111 | 97.43 112 | 98.19 153 | 98.48 192 | 95.83 203 | 99.07 72 | 98.42 230 | 96.27 131 | 98.09 141 | 99.26 80 | 91.00 191 | 99.30 221 | 97.81 108 | 98.48 193 | 99.44 126 |
|
| MGCFI-Net | | | 97.62 111 | 97.19 135 | 98.92 79 | 98.66 173 | 98.20 59 | 99.32 22 | 98.38 248 | 96.69 109 | 97.58 205 | 97.42 335 | 92.10 142 | 99.50 190 | 98.28 79 | 96.25 302 | 99.08 218 |
|
| xiu_mvs_v1_base_debu | | | 97.60 113 | 97.56 99 | 97.72 212 | 98.35 212 | 95.98 179 | 97.86 352 | 98.51 194 | 97.13 84 | 99.01 73 | 98.40 237 | 91.56 161 | 99.80 109 | 98.53 55 | 98.68 173 | 97.37 332 |
|
| xiu_mvs_v1_base | | | 97.60 113 | 97.56 99 | 97.72 212 | 98.35 212 | 95.98 179 | 97.86 352 | 98.51 194 | 97.13 84 | 99.01 73 | 98.40 237 | 91.56 161 | 99.80 109 | 98.53 55 | 98.68 173 | 97.37 332 |
|
| xiu_mvs_v1_base_debi | | | 97.60 113 | 97.56 99 | 97.72 212 | 98.35 212 | 95.98 179 | 97.86 352 | 98.51 194 | 97.13 84 | 99.01 73 | 98.40 237 | 91.56 161 | 99.80 109 | 98.53 55 | 98.68 173 | 97.37 332 |
|
| diffmvs_AUTHOR | | | 97.59 116 | 97.44 110 | 98.01 182 | 98.26 235 | 95.47 225 | 98.12 313 | 98.36 254 | 96.38 126 | 98.84 88 | 99.10 125 | 91.13 184 | 99.26 229 | 98.24 83 | 98.56 184 | 99.30 163 |
|
| diffmvs |  | | 97.58 117 | 97.40 114 | 98.13 164 | 98.32 224 | 95.81 207 | 98.06 323 | 98.37 250 | 96.20 134 | 98.74 97 | 98.89 173 | 91.31 174 | 99.25 233 | 98.16 85 | 98.52 188 | 99.34 150 |
| Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025 |
| guyue | | | 97.57 118 | 97.37 117 | 98.20 149 | 98.50 187 | 95.86 200 | 98.89 124 | 97.03 425 | 97.29 67 | 98.73 99 | 98.90 171 | 89.41 242 | 99.32 216 | 98.68 45 | 98.86 165 | 99.42 133 |
|
| MVSFormer | | | 97.57 118 | 97.49 105 | 97.84 199 | 98.07 267 | 95.76 211 | 99.47 7 | 98.40 235 | 94.98 224 | 98.79 93 | 98.83 183 | 92.34 129 | 98.41 369 | 96.91 175 | 99.59 94 | 99.34 150 |
|
| alignmvs | | | 97.56 120 | 97.07 148 | 99.01 70 | 98.66 173 | 98.37 48 | 98.83 153 | 98.06 330 | 96.74 105 | 98.00 156 | 97.65 313 | 90.80 196 | 99.48 196 | 98.37 71 | 96.56 285 | 99.19 193 |
|
| E3new | | | 97.55 121 | 97.35 119 | 98.16 155 | 98.48 192 | 95.85 201 | 98.55 238 | 98.41 232 | 95.42 188 | 98.06 145 | 99.12 120 | 92.23 136 | 99.24 240 | 97.43 150 | 98.45 196 | 99.39 138 |
|
| DPM-MVS | | | 97.55 121 | 96.99 155 | 99.23 49 | 99.04 129 | 98.55 33 | 97.17 417 | 98.35 255 | 94.85 234 | 97.93 165 | 98.58 219 | 95.07 81 | 99.71 142 | 92.60 349 | 99.34 137 | 99.43 130 |
|
| OMC-MVS | | | 97.55 121 | 97.34 120 | 98.20 149 | 99.33 74 | 95.92 191 | 98.28 284 | 98.59 171 | 95.52 181 | 97.97 159 | 99.10 125 | 93.28 115 | 99.49 191 | 95.09 254 | 98.88 162 | 99.19 193 |
|
| balanced_ft_v1 | | | 97.54 124 | 97.38 116 | 98.02 180 | 98.34 217 | 95.58 217 | 99.32 22 | 98.40 235 | 95.88 152 | 98.43 126 | 98.65 212 | 88.95 262 | 99.59 167 | 98.94 35 | 99.48 120 | 98.90 240 |
|
| viewcassd2359sk11 | | | 97.53 125 | 97.32 121 | 98.16 155 | 98.45 196 | 95.83 203 | 98.57 234 | 98.42 230 | 95.52 181 | 98.07 143 | 99.12 120 | 91.81 153 | 99.25 233 | 97.46 148 | 98.48 193 | 99.41 136 |
|
| hybridcas | | | 97.52 126 | 97.29 123 | 98.20 149 | 98.44 197 | 96.00 177 | 99.02 86 | 98.39 241 | 96.12 139 | 97.69 189 | 99.23 87 | 90.77 201 | 99.17 255 | 97.55 135 | 98.42 206 | 99.44 126 |
|
| LuminaMVS | | | 97.49 127 | 97.18 136 | 98.42 130 | 97.50 328 | 97.15 119 | 98.45 256 | 97.68 357 | 96.56 117 | 98.68 104 | 98.78 192 | 89.84 227 | 99.32 216 | 98.60 50 | 98.57 183 | 98.79 250 |
|
| E2 | | | 97.48 128 | 97.25 126 | 98.16 155 | 98.40 204 | 95.79 208 | 98.58 225 | 98.44 215 | 95.58 170 | 98.00 156 | 99.14 114 | 91.21 183 | 99.24 240 | 97.50 143 | 98.43 200 | 99.45 123 |
|
| E3 | | | 97.48 128 | 97.25 126 | 98.16 155 | 98.38 207 | 95.79 208 | 98.58 225 | 98.44 215 | 95.58 170 | 98.00 156 | 99.14 114 | 91.25 177 | 99.24 240 | 97.50 143 | 98.44 197 | 99.45 123 |
|
| KinetiMVS | | | 97.48 128 | 97.05 150 | 98.78 87 | 98.37 210 | 97.30 102 | 98.99 94 | 98.70 140 | 97.18 79 | 99.02 71 | 99.01 150 | 87.50 302 | 99.67 150 | 95.33 244 | 99.33 139 | 99.37 143 |
|
| viewmanbaseed2359cas | | | 97.47 131 | 97.25 126 | 98.14 159 | 98.41 202 | 95.84 202 | 98.57 234 | 98.43 226 | 95.55 177 | 97.97 159 | 99.12 120 | 91.26 176 | 99.15 261 | 97.42 152 | 98.53 187 | 99.43 130 |
|
| PAPM_NR | | | 97.46 132 | 97.11 145 | 98.50 118 | 99.50 48 | 96.41 158 | 98.63 215 | 98.60 164 | 95.18 204 | 97.06 226 | 98.06 271 | 94.26 100 | 99.57 171 | 93.80 308 | 98.87 164 | 99.52 101 |
|
| EPP-MVSNet | | | 97.46 132 | 97.28 124 | 97.99 184 | 98.64 177 | 95.38 235 | 99.33 21 | 98.31 268 | 93.61 312 | 97.19 218 | 99.07 140 | 94.05 103 | 99.23 244 | 96.89 179 | 98.43 200 | 99.37 143 |
|
| 3Dnovator | | 94.51 5 | 97.46 132 | 96.93 159 | 99.07 65 | 97.78 301 | 97.64 82 | 99.35 16 | 99.06 47 | 97.02 89 | 93.75 356 | 99.16 110 | 89.25 247 | 99.92 43 | 97.22 163 | 99.75 53 | 99.64 86 |
|
| CNLPA | | | 97.45 135 | 97.03 152 | 98.73 91 | 99.05 128 | 97.44 95 | 98.07 322 | 98.53 188 | 95.32 197 | 96.80 241 | 98.53 224 | 93.32 113 | 99.72 137 | 94.31 289 | 99.31 141 | 99.02 227 |
|
| lupinMVS | | | 97.44 136 | 97.22 133 | 98.12 167 | 98.07 267 | 95.76 211 | 97.68 369 | 97.76 354 | 94.50 257 | 98.79 93 | 98.61 214 | 92.34 129 | 99.30 221 | 97.58 130 | 99.59 94 | 99.31 159 |
|
| 3Dnovator+ | | 94.38 6 | 97.43 137 | 96.78 171 | 99.38 24 | 97.83 298 | 98.52 34 | 99.37 13 | 98.71 137 | 97.09 87 | 92.99 386 | 99.13 117 | 89.36 244 | 99.89 68 | 96.97 171 | 99.57 98 | 99.71 63 |
|
| Vis-MVSNet |  | | 97.42 138 | 97.11 145 | 98.34 135 | 98.66 173 | 96.23 167 | 99.22 42 | 99.00 53 | 96.63 113 | 98.04 149 | 99.21 93 | 88.05 288 | 99.35 212 | 96.01 218 | 99.21 145 | 99.45 123 |
| Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
| hybridnocas07 | | | 97.41 139 | 97.21 134 | 97.99 184 | 98.24 239 | 95.42 228 | 98.21 291 | 98.32 263 | 95.97 147 | 98.38 127 | 98.93 164 | 90.48 207 | 99.21 249 | 97.92 98 | 98.46 195 | 99.34 150 |
|
| API-MVS | | | 97.41 139 | 97.25 126 | 97.91 193 | 98.70 166 | 96.80 134 | 98.82 155 | 98.69 142 | 94.53 252 | 98.11 139 | 98.28 252 | 94.50 94 | 99.57 171 | 94.12 297 | 99.49 117 | 97.37 332 |
|
| sss | | | 97.39 141 | 96.98 157 | 98.61 102 | 98.60 181 | 96.61 143 | 98.22 290 | 98.93 65 | 93.97 281 | 98.01 155 | 98.48 230 | 91.98 146 | 99.85 84 | 96.45 202 | 98.15 227 | 99.39 138 |
|
| test_cas_vis1_n_1920 | | | 97.38 142 | 97.36 118 | 97.45 236 | 98.95 142 | 93.25 346 | 99.00 91 | 98.53 188 | 97.70 39 | 99.77 18 | 99.35 62 | 84.71 358 | 99.85 84 | 98.57 52 | 99.66 77 | 99.26 180 |
|
| PVSNet_Blended | | | 97.38 142 | 97.12 144 | 98.14 159 | 99.25 96 | 95.35 238 | 97.28 403 | 99.26 16 | 93.13 335 | 97.94 163 | 98.21 260 | 92.74 121 | 99.81 102 | 96.88 181 | 99.40 131 | 99.27 173 |
|
| E5new | | | 97.37 144 | 97.16 138 | 97.98 186 | 98.30 226 | 95.41 229 | 98.87 134 | 98.45 211 | 95.56 172 | 97.84 172 | 99.19 102 | 90.39 211 | 99.25 233 | 97.61 126 | 98.22 222 | 99.29 166 |
|
| E6new | | | 97.37 144 | 97.16 138 | 97.98 186 | 98.28 232 | 95.40 232 | 98.87 134 | 98.45 211 | 95.55 177 | 97.84 172 | 99.20 95 | 90.44 209 | 99.25 233 | 97.61 126 | 98.22 222 | 99.29 166 |
|
| E6 | | | 97.37 144 | 97.16 138 | 97.98 186 | 98.28 232 | 95.40 232 | 98.87 134 | 98.45 211 | 95.55 177 | 97.84 172 | 99.20 95 | 90.44 209 | 99.25 233 | 97.61 126 | 98.22 222 | 99.29 166 |
|
| E5 | | | 97.37 144 | 97.16 138 | 97.98 186 | 98.30 226 | 95.41 229 | 98.87 134 | 98.45 211 | 95.56 172 | 97.84 172 | 99.19 102 | 90.39 211 | 99.25 233 | 97.61 126 | 98.22 222 | 99.29 166 |
|
| E4 | | | 97.37 144 | 97.13 143 | 98.12 167 | 98.27 234 | 95.70 213 | 98.59 221 | 98.44 215 | 95.56 172 | 97.80 177 | 99.18 105 | 90.57 205 | 99.26 229 | 97.45 149 | 98.28 220 | 99.40 137 |
|
| WTY-MVS | | | 97.37 144 | 96.92 160 | 98.72 92 | 98.86 151 | 96.89 132 | 98.31 278 | 98.71 137 | 95.26 200 | 97.67 191 | 98.56 223 | 92.21 138 | 99.78 124 | 95.89 220 | 96.85 275 | 99.48 114 |
|
| hybrid | | | 97.34 150 | 97.16 138 | 97.88 197 | 98.25 237 | 95.18 247 | 98.18 303 | 98.33 260 | 95.36 194 | 98.35 131 | 99.06 141 | 90.61 203 | 99.18 253 | 97.88 102 | 98.40 208 | 99.27 173 |
|
| AstraMVS | | | 97.34 150 | 97.24 130 | 97.65 224 | 98.13 261 | 94.15 304 | 98.94 108 | 96.25 459 | 97.47 56 | 98.60 113 | 99.28 76 | 89.67 232 | 99.41 206 | 98.73 43 | 98.07 231 | 99.38 142 |
|
| viewmacassd2359aftdt | | | 97.32 152 | 97.07 148 | 98.08 172 | 98.30 226 | 95.69 214 | 98.62 218 | 98.44 215 | 95.56 172 | 97.86 171 | 99.22 90 | 89.91 225 | 99.14 264 | 97.29 160 | 98.43 200 | 99.42 133 |
|
| jason | | | 97.32 152 | 97.08 147 | 98.06 176 | 97.45 334 | 95.59 216 | 97.87 350 | 97.91 341 | 94.79 237 | 98.55 116 | 98.83 183 | 91.12 186 | 99.23 244 | 97.58 130 | 99.60 92 | 99.34 150 |
| jason: jason. |
| MVS_Test | | | 97.28 154 | 97.00 153 | 98.13 164 | 98.33 221 | 95.97 184 | 98.74 181 | 98.07 325 | 94.27 266 | 98.44 124 | 98.07 270 | 92.48 125 | 99.26 229 | 96.43 203 | 98.19 226 | 99.16 199 |
|
| EPNet | | | 97.28 154 | 96.87 162 | 98.51 115 | 94.98 450 | 96.14 172 | 98.90 120 | 97.02 428 | 98.28 21 | 95.99 277 | 99.11 123 | 91.36 170 | 99.89 68 | 96.98 170 | 99.19 147 | 99.50 107 |
| Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
| SSM_0404 | | | 97.26 156 | 97.00 153 | 98.03 178 | 98.46 194 | 95.99 178 | 98.62 218 | 98.44 215 | 94.77 238 | 97.24 215 | 98.93 164 | 91.22 179 | 99.28 226 | 96.54 197 | 98.74 172 | 98.84 245 |
|
| mvsmamba | | | 97.25 157 | 96.99 155 | 98.02 180 | 98.34 217 | 95.54 222 | 99.18 54 | 97.47 384 | 95.04 217 | 98.15 136 | 98.57 222 | 89.46 239 | 99.31 220 | 97.68 120 | 99.01 155 | 99.22 186 |
|
| viewdifsd2359ckpt13 | | | 97.24 158 | 96.97 158 | 98.06 176 | 98.43 198 | 95.77 210 | 98.59 221 | 98.34 258 | 94.81 235 | 97.60 203 | 98.94 162 | 90.78 200 | 99.09 276 | 96.93 174 | 98.33 214 | 99.32 158 |
|
| test_yl | | | 97.22 159 | 96.78 171 | 98.54 110 | 98.73 161 | 96.60 144 | 98.45 256 | 98.31 268 | 94.70 241 | 98.02 152 | 98.42 235 | 90.80 196 | 99.70 143 | 96.81 188 | 96.79 277 | 99.34 150 |
|
| DCV-MVSNet | | | 97.22 159 | 96.78 171 | 98.54 110 | 98.73 161 | 96.60 144 | 98.45 256 | 98.31 268 | 94.70 241 | 98.02 152 | 98.42 235 | 90.80 196 | 99.70 143 | 96.81 188 | 96.79 277 | 99.34 150 |
|
| IS-MVSNet | | | 97.22 159 | 96.88 161 | 98.25 143 | 98.85 154 | 96.36 161 | 99.19 50 | 97.97 335 | 95.39 190 | 97.23 216 | 98.99 153 | 91.11 187 | 98.93 307 | 94.60 277 | 98.59 180 | 99.47 116 |
|
| viewdifsd2359ckpt07 | | | 97.20 162 | 97.05 150 | 97.65 224 | 98.40 204 | 94.33 295 | 98.39 269 | 98.43 226 | 95.67 165 | 97.66 195 | 99.08 136 | 90.04 222 | 99.32 216 | 97.47 147 | 98.29 218 | 99.31 159 |
|
| PLC |  | 95.07 4 | 97.20 162 | 96.78 171 | 98.44 126 | 99.29 88 | 96.31 165 | 98.14 310 | 98.76 125 | 92.41 364 | 96.39 264 | 98.31 250 | 94.92 86 | 99.78 124 | 94.06 300 | 98.77 171 | 99.23 184 |
| Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
| CHOSEN 280x420 | | | 97.18 164 | 97.18 136 | 97.20 249 | 98.81 157 | 93.27 343 | 95.78 468 | 99.15 41 | 95.25 201 | 96.79 242 | 98.11 268 | 92.29 132 | 99.07 279 | 98.56 54 | 99.85 6 | 99.25 182 |
|
| SSM_0407 | | | 97.17 165 | 96.87 162 | 98.08 172 | 98.19 248 | 95.90 193 | 98.52 241 | 98.44 215 | 94.77 238 | 96.75 243 | 98.93 164 | 91.22 179 | 99.22 248 | 96.54 197 | 98.43 200 | 99.10 211 |
|
| LS3D | | | 97.16 166 | 96.66 180 | 98.68 95 | 98.53 186 | 97.19 116 | 98.93 114 | 98.90 73 | 92.83 349 | 95.99 277 | 99.37 56 | 92.12 141 | 99.87 79 | 93.67 312 | 99.57 98 | 98.97 232 |
|
| AdaColmap |  | | 97.15 167 | 96.70 176 | 98.48 121 | 99.16 115 | 96.69 140 | 98.01 329 | 98.89 75 | 94.44 260 | 96.83 237 | 98.68 208 | 90.69 202 | 99.76 130 | 94.36 285 | 99.29 142 | 98.98 231 |
|
| viewdifsd2359ckpt09 | | | 97.13 168 | 96.79 169 | 98.14 159 | 98.43 198 | 95.90 193 | 98.52 241 | 98.37 250 | 94.32 264 | 97.33 210 | 98.86 177 | 90.23 219 | 99.16 257 | 96.81 188 | 98.25 221 | 99.36 147 |
|
| Effi-MVS+ | | | 97.12 169 | 96.69 177 | 98.39 133 | 98.19 248 | 96.72 139 | 97.37 394 | 98.43 226 | 93.71 299 | 97.65 197 | 98.02 274 | 92.20 139 | 99.25 233 | 96.87 184 | 97.79 241 | 99.19 193 |
|
| CHOSEN 1792x2688 | | | 97.12 169 | 96.80 167 | 98.08 172 | 99.30 83 | 94.56 284 | 98.05 324 | 99.71 1 | 93.57 314 | 97.09 222 | 98.91 170 | 88.17 282 | 99.89 68 | 96.87 184 | 99.56 106 | 99.81 25 |
|
| F-COLMAP | | | 97.09 171 | 96.80 167 | 97.97 190 | 99.45 61 | 94.95 263 | 98.55 238 | 98.62 163 | 93.02 340 | 96.17 272 | 98.58 219 | 94.01 104 | 99.81 102 | 93.95 302 | 98.90 160 | 99.14 203 |
|
| RRT-MVS | | | 97.03 172 | 96.78 171 | 97.77 208 | 97.90 294 | 94.34 293 | 99.12 64 | 98.35 255 | 95.87 154 | 98.06 145 | 98.70 206 | 86.45 321 | 99.63 160 | 98.04 92 | 98.54 186 | 99.35 148 |
|
| TAMVS | | | 97.02 173 | 96.79 169 | 97.70 215 | 98.06 270 | 95.31 241 | 98.52 241 | 98.31 268 | 93.95 282 | 97.05 227 | 98.61 214 | 93.49 111 | 98.52 351 | 95.33 244 | 97.81 240 | 99.29 166 |
|
| viewmambaseed2359dif | | | 97.01 174 | 96.84 164 | 97.51 233 | 98.19 248 | 94.21 301 | 98.16 306 | 98.23 289 | 93.61 312 | 97.78 178 | 99.13 117 | 90.79 199 | 99.18 253 | 97.24 161 | 98.40 208 | 99.15 200 |
|
| dtuplus | | | 97.00 175 | 96.83 166 | 97.51 233 | 98.18 254 | 94.21 301 | 98.21 291 | 98.20 293 | 94.42 262 | 97.66 195 | 99.22 90 | 90.18 220 | 99.17 255 | 97.01 168 | 98.36 212 | 99.13 205 |
|
| CDS-MVSNet | | | 96.99 176 | 96.69 177 | 97.90 194 | 98.05 272 | 95.98 179 | 98.20 295 | 98.33 260 | 93.67 306 | 96.95 229 | 98.49 229 | 93.54 110 | 98.42 362 | 95.24 251 | 97.74 245 | 99.31 159 |
| Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
| casdiffseed414692147 | | | 96.97 177 | 96.55 185 | 98.25 143 | 98.26 235 | 96.28 166 | 98.93 114 | 98.33 260 | 94.99 222 | 96.87 236 | 99.09 133 | 88.97 260 | 99.07 279 | 95.70 233 | 97.77 243 | 99.39 138 |
|
| CANet_DTU | | | 96.96 178 | 96.55 185 | 98.21 147 | 98.17 258 | 96.07 176 | 97.98 333 | 98.21 291 | 97.24 74 | 97.13 220 | 98.93 164 | 86.88 313 | 99.91 56 | 95.00 257 | 99.37 135 | 98.66 273 |
|
| 114514_t | | | 96.93 179 | 96.27 199 | 98.92 79 | 99.50 48 | 97.63 83 | 98.85 147 | 98.90 73 | 84.80 476 | 97.77 179 | 99.11 123 | 92.84 119 | 99.66 153 | 94.85 260 | 99.77 41 | 99.47 116 |
|
| MAR-MVS | | | 96.91 180 | 96.40 193 | 98.45 124 | 98.69 169 | 96.90 130 | 98.66 209 | 98.68 145 | 92.40 365 | 97.07 225 | 97.96 281 | 91.54 164 | 99.75 132 | 93.68 310 | 98.92 159 | 98.69 267 |
| Zhenyu Xu, Yiguang Liu, Xuelei Shi, Ying Wang, Yunan Zheng: MARMVS: Matching Ambiguity Reduced Multiple View Stereo for Efficient Large Scale Scene Reconstruction. CVPR 2020 |
| HyFIR lowres test | | | 96.90 181 | 96.49 190 | 98.14 159 | 99.33 74 | 95.56 219 | 97.38 392 | 99.65 2 | 92.34 366 | 97.61 200 | 98.20 261 | 89.29 246 | 99.10 275 | 96.97 171 | 97.60 250 | 99.77 40 |
|
| Vis-MVSNet (Re-imp) | | | 96.87 182 | 96.55 185 | 97.83 200 | 98.73 161 | 95.46 226 | 99.20 48 | 98.30 275 | 94.96 226 | 96.60 252 | 98.87 175 | 90.05 221 | 98.59 346 | 93.67 312 | 98.60 179 | 99.46 121 |
|
| SDMVSNet | | | 96.85 183 | 96.42 191 | 98.14 159 | 99.30 83 | 96.38 159 | 99.21 45 | 99.23 27 | 95.92 149 | 95.96 279 | 98.76 200 | 85.88 333 | 99.44 203 | 97.93 96 | 95.59 314 | 98.60 278 |
|
| PAPR | | | 96.84 184 | 96.24 201 | 98.65 98 | 98.72 165 | 96.92 129 | 97.36 396 | 98.57 178 | 93.33 324 | 96.67 247 | 97.57 322 | 94.30 98 | 99.56 174 | 91.05 393 | 98.59 180 | 99.47 116 |
|
| HY-MVS | | 93.96 8 | 96.82 185 | 96.23 202 | 98.57 105 | 98.46 194 | 97.00 125 | 98.14 310 | 98.21 291 | 93.95 282 | 96.72 246 | 97.99 278 | 91.58 159 | 99.76 130 | 94.51 281 | 96.54 286 | 98.95 235 |
|
| mamba_0408 | | | 96.81 186 | 96.38 194 | 98.09 171 | 98.19 248 | 95.90 193 | 95.69 469 | 98.32 263 | 94.51 255 | 96.75 243 | 98.73 202 | 90.99 192 | 99.27 228 | 95.83 223 | 98.43 200 | 99.10 211 |
|
| UGNet | | | 96.78 187 | 96.30 198 | 98.19 153 | 98.24 239 | 95.89 198 | 98.88 131 | 98.93 65 | 97.39 61 | 96.81 240 | 97.84 294 | 82.60 387 | 99.90 64 | 96.53 199 | 99.49 117 | 98.79 250 |
| Wanjuan Su, Qingshan Xu, Wenbing Tao: Uncertainty-guided Multi-view Stereo Network for Depth Estimation. IEEE Transactions on Circuits and Systems for Video Technology, 2022 |
| IMVS_0407 | | | 96.74 188 | 96.64 181 | 97.05 264 | 97.99 281 | 92.82 360 | 98.45 256 | 98.27 278 | 95.16 205 | 97.30 211 | 98.79 188 | 91.53 165 | 99.06 281 | 94.74 265 | 97.54 254 | 99.27 173 |
|
| IMVS_0403 | | | 96.74 188 | 96.61 182 | 97.12 258 | 97.99 281 | 92.82 360 | 98.47 254 | 98.27 278 | 95.16 205 | 97.13 220 | 98.79 188 | 91.44 168 | 99.26 229 | 94.74 265 | 97.54 254 | 99.27 173 |
|
| PVSNet_BlendedMVS | | | 96.73 190 | 96.60 183 | 97.12 258 | 99.25 96 | 95.35 238 | 98.26 287 | 99.26 16 | 94.28 265 | 97.94 163 | 97.46 329 | 92.74 121 | 99.81 102 | 96.88 181 | 93.32 352 | 96.20 434 |
|
| SSM_04072 | | | 96.71 191 | 96.38 194 | 97.68 218 | 98.19 248 | 95.90 193 | 95.69 469 | 98.32 263 | 94.51 255 | 96.75 243 | 98.73 202 | 90.99 192 | 98.02 418 | 95.83 223 | 98.43 200 | 99.10 211 |
|
| test_vis1_n_1920 | | | 96.71 191 | 96.84 164 | 96.31 340 | 99.11 123 | 89.74 428 | 99.05 76 | 98.58 176 | 98.08 24 | 99.87 4 | 99.37 56 | 78.48 426 | 99.93 34 | 99.29 27 | 99.69 71 | 99.27 173 |
|
| mvs_anonymous | | | 96.70 193 | 96.53 188 | 97.18 252 | 98.19 248 | 93.78 314 | 98.31 278 | 98.19 296 | 94.01 278 | 94.47 311 | 98.27 255 | 92.08 144 | 98.46 357 | 97.39 156 | 97.91 236 | 99.31 159 |
|
| Elysia | | | 96.64 194 | 96.02 211 | 98.51 115 | 98.04 274 | 97.30 102 | 98.74 181 | 98.60 164 | 95.04 217 | 97.91 167 | 98.84 179 | 83.59 382 | 99.48 196 | 94.20 293 | 99.25 143 | 98.75 259 |
|
| StellarMVS | | | 96.64 194 | 96.02 211 | 98.51 115 | 98.04 274 | 97.30 102 | 98.74 181 | 98.60 164 | 95.04 217 | 97.91 167 | 98.84 179 | 83.59 382 | 99.48 196 | 94.20 293 | 99.25 143 | 98.75 259 |
|
| 1112_ss | | | 96.63 196 | 96.00 213 | 98.50 118 | 98.56 182 | 96.37 160 | 98.18 303 | 98.10 318 | 92.92 344 | 94.84 299 | 98.43 233 | 92.14 140 | 99.58 170 | 94.35 286 | 96.51 287 | 99.56 100 |
|
| PMMVS | | | 96.60 197 | 96.33 197 | 97.41 240 | 97.90 294 | 93.93 310 | 97.35 397 | 98.41 232 | 92.84 348 | 97.76 180 | 97.45 331 | 91.10 188 | 99.20 250 | 96.26 208 | 97.91 236 | 99.11 209 |
|
| DP-MVS | | | 96.59 198 | 95.93 216 | 98.57 105 | 99.34 71 | 96.19 170 | 98.70 196 | 98.39 241 | 89.45 437 | 94.52 309 | 99.35 62 | 91.85 150 | 99.85 84 | 92.89 337 | 98.88 162 | 99.68 75 |
|
| PatchMatch-RL | | | 96.59 198 | 96.03 210 | 98.27 139 | 99.31 79 | 96.51 152 | 97.91 342 | 99.06 47 | 93.72 298 | 96.92 233 | 98.06 271 | 88.50 275 | 99.65 154 | 91.77 375 | 99.00 157 | 98.66 273 |
|
| GeoE | | | 96.58 200 | 96.07 207 | 98.10 170 | 98.35 212 | 95.89 198 | 99.34 17 | 98.12 312 | 93.12 336 | 96.09 273 | 98.87 175 | 89.71 231 | 98.97 297 | 92.95 333 | 98.08 230 | 99.43 130 |
|
| icg_test_0407_2 | | | 96.56 201 | 96.50 189 | 96.73 289 | 97.99 281 | 92.82 360 | 97.18 414 | 98.27 278 | 95.16 205 | 97.30 211 | 98.79 188 | 91.53 165 | 98.10 403 | 94.74 265 | 97.54 254 | 99.27 173 |
|
| XVG-OURS | | | 96.55 202 | 96.41 192 | 96.99 267 | 98.75 160 | 93.76 315 | 97.50 383 | 98.52 191 | 95.67 165 | 96.83 237 | 99.30 74 | 88.95 262 | 99.53 183 | 95.88 221 | 96.26 301 | 97.69 321 |
|
| FIs | | | 96.51 203 | 96.12 206 | 97.67 220 | 97.13 358 | 97.54 88 | 99.36 14 | 99.22 32 | 95.89 151 | 94.03 340 | 98.35 243 | 91.98 146 | 98.44 360 | 96.40 204 | 92.76 360 | 97.01 340 |
|
| XVG-OURS-SEG-HR | | | 96.51 203 | 96.34 196 | 97.02 266 | 98.77 159 | 93.76 315 | 97.79 361 | 98.50 199 | 95.45 185 | 96.94 230 | 99.09 133 | 87.87 293 | 99.55 181 | 96.76 193 | 95.83 313 | 97.74 318 |
|
| PS-MVSNAJss | | | 96.43 205 | 96.26 200 | 96.92 278 | 95.84 429 | 95.08 253 | 99.16 56 | 98.50 199 | 95.87 154 | 93.84 351 | 98.34 247 | 94.51 91 | 98.61 342 | 96.88 181 | 93.45 347 | 97.06 338 |
|
| test_fmvs1 | | | 96.42 206 | 96.67 179 | 95.66 377 | 98.82 156 | 88.53 455 | 98.80 164 | 98.20 293 | 96.39 125 | 99.64 31 | 99.20 95 | 80.35 412 | 99.67 150 | 99.04 32 | 99.57 98 | 98.78 254 |
|
| FC-MVSNet-test | | | 96.42 206 | 96.05 208 | 97.53 232 | 96.95 367 | 97.27 106 | 99.36 14 | 99.23 27 | 95.83 156 | 93.93 343 | 98.37 241 | 92.00 145 | 98.32 381 | 96.02 217 | 92.72 361 | 97.00 341 |
|
| ab-mvs | | | 96.42 206 | 95.71 227 | 98.55 108 | 98.63 178 | 96.75 137 | 97.88 349 | 98.74 129 | 93.84 288 | 96.54 257 | 98.18 263 | 85.34 344 | 99.75 132 | 95.93 219 | 96.35 291 | 99.15 200 |
|
| FA-MVS(test-final) | | | 96.41 209 | 95.94 215 | 97.82 202 | 98.21 244 | 95.20 246 | 97.80 359 | 97.58 368 | 93.21 330 | 97.36 209 | 97.70 306 | 89.47 237 | 99.56 174 | 94.12 297 | 97.99 233 | 98.71 265 |
|
| PVSNet | | 91.96 18 | 96.35 210 | 96.15 203 | 96.96 273 | 99.17 111 | 92.05 380 | 96.08 461 | 98.68 145 | 93.69 302 | 97.75 182 | 97.80 300 | 88.86 264 | 99.69 148 | 94.26 291 | 99.01 155 | 99.15 200 |
|
| Test_1112_low_res | | | 96.34 211 | 95.66 232 | 98.36 134 | 98.56 182 | 95.94 187 | 97.71 367 | 98.07 325 | 92.10 376 | 94.79 303 | 97.29 344 | 91.75 154 | 99.56 174 | 94.17 295 | 96.50 288 | 99.58 98 |
|
| viewdifsd2359ckpt11 | | | 96.30 212 | 96.13 204 | 96.81 284 | 98.10 264 | 92.10 376 | 98.49 252 | 98.40 235 | 96.02 143 | 97.61 200 | 99.31 71 | 86.37 323 | 99.29 224 | 97.52 139 | 93.36 351 | 99.04 224 |
|
| viewmsd2359difaftdt | | | 96.30 212 | 96.13 204 | 96.81 284 | 98.10 264 | 92.10 376 | 98.49 252 | 98.40 235 | 96.02 143 | 97.61 200 | 99.31 71 | 86.37 323 | 99.30 221 | 97.52 139 | 93.37 350 | 99.04 224 |
|
| Effi-MVS+-dtu | | | 96.29 214 | 96.56 184 | 95.51 382 | 97.89 296 | 90.22 420 | 98.80 164 | 98.10 318 | 96.57 116 | 96.45 262 | 96.66 402 | 90.81 195 | 98.91 310 | 95.72 230 | 97.99 233 | 97.40 329 |
|
| QAPM | | | 96.29 214 | 95.40 238 | 98.96 76 | 97.85 297 | 97.60 85 | 99.23 38 | 98.93 65 | 89.76 431 | 93.11 383 | 99.02 146 | 89.11 252 | 99.93 34 | 91.99 368 | 99.62 89 | 99.34 150 |
|
| Fast-Effi-MVS+ | | | 96.28 216 | 95.70 229 | 98.03 178 | 98.29 230 | 95.97 184 | 98.58 225 | 98.25 287 | 91.74 384 | 95.29 292 | 97.23 349 | 91.03 190 | 99.15 261 | 92.90 335 | 97.96 235 | 98.97 232 |
|
| nrg030 | | | 96.28 216 | 95.72 224 | 97.96 192 | 96.90 372 | 98.15 64 | 99.39 11 | 98.31 268 | 95.47 184 | 94.42 317 | 98.35 243 | 92.09 143 | 98.69 334 | 97.50 143 | 89.05 413 | 97.04 339 |
|
| 1314 | | | 96.25 218 | 95.73 223 | 97.79 204 | 97.13 358 | 95.55 221 | 98.19 298 | 98.59 171 | 93.47 318 | 92.03 419 | 97.82 298 | 91.33 172 | 99.49 191 | 94.62 275 | 98.44 197 | 98.32 298 |
|
| sd_testset | | | 96.17 219 | 95.76 222 | 97.42 239 | 99.30 83 | 94.34 293 | 98.82 155 | 99.08 45 | 95.92 149 | 95.96 279 | 98.76 200 | 82.83 386 | 99.32 216 | 95.56 237 | 95.59 314 | 98.60 278 |
|
| h-mvs33 | | | 96.17 219 | 95.62 233 | 97.81 203 | 99.03 130 | 94.45 286 | 98.64 212 | 98.75 127 | 97.48 54 | 98.67 105 | 98.72 205 | 89.76 228 | 99.86 83 | 97.95 94 | 81.59 466 | 99.11 209 |
|
| HQP_MVS | | | 96.14 221 | 95.90 217 | 96.85 281 | 97.42 336 | 94.60 282 | 98.80 164 | 98.56 182 | 97.28 69 | 95.34 288 | 98.28 252 | 87.09 308 | 99.03 288 | 96.07 212 | 94.27 322 | 96.92 348 |
|
| tttt0517 | | | 96.07 222 | 95.51 236 | 97.78 205 | 98.41 202 | 94.84 267 | 99.28 30 | 94.33 486 | 94.26 267 | 97.64 198 | 98.64 213 | 84.05 373 | 99.47 200 | 95.34 243 | 97.60 250 | 99.03 226 |
|
| MVSTER | | | 96.06 223 | 95.72 224 | 97.08 262 | 98.23 242 | 95.93 190 | 98.73 187 | 98.27 278 | 94.86 232 | 95.07 294 | 98.09 269 | 88.21 281 | 98.54 349 | 96.59 195 | 93.46 345 | 96.79 367 |
|
| thisisatest0530 | | | 96.01 224 | 95.36 243 | 97.97 190 | 98.38 207 | 95.52 223 | 98.88 131 | 94.19 490 | 94.04 273 | 97.64 198 | 98.31 250 | 83.82 380 | 99.46 201 | 95.29 248 | 97.70 247 | 98.93 237 |
|
| test_djsdf | | | 96.00 225 | 95.69 230 | 96.93 275 | 95.72 431 | 95.49 224 | 99.47 7 | 98.40 235 | 94.98 224 | 94.58 307 | 97.86 291 | 89.16 250 | 98.41 369 | 96.91 175 | 94.12 330 | 96.88 357 |
|
| EI-MVSNet | | | 95.96 226 | 95.83 219 | 96.36 336 | 97.93 292 | 93.70 321 | 98.12 313 | 98.27 278 | 93.70 301 | 95.07 294 | 99.02 146 | 92.23 136 | 98.54 349 | 94.68 270 | 93.46 345 | 96.84 363 |
|
| VortexMVS | | | 95.95 227 | 95.79 220 | 96.42 331 | 98.29 230 | 93.96 309 | 98.68 202 | 98.31 268 | 96.02 143 | 94.29 325 | 97.57 322 | 89.47 237 | 98.37 376 | 97.51 142 | 91.93 370 | 96.94 346 |
|
| ECVR-MVS |  | | 95.95 227 | 95.71 227 | 96.65 298 | 99.02 131 | 90.86 402 | 99.03 83 | 91.80 503 | 96.96 93 | 98.10 140 | 99.26 80 | 81.31 398 | 99.51 187 | 96.90 178 | 99.04 152 | 99.59 94 |
|
| BH-untuned | | | 95.95 227 | 95.72 224 | 96.65 298 | 98.55 184 | 92.26 371 | 98.23 289 | 97.79 353 | 93.73 296 | 94.62 306 | 98.01 276 | 88.97 260 | 99.00 295 | 93.04 330 | 98.51 189 | 98.68 269 |
|
| test1111 | | | 95.94 230 | 95.78 221 | 96.41 332 | 98.99 138 | 90.12 421 | 99.04 80 | 92.45 502 | 96.99 92 | 98.03 150 | 99.27 79 | 81.40 397 | 99.48 196 | 96.87 184 | 99.04 152 | 99.63 88 |
|
| MSDG | | | 95.93 231 | 95.30 250 | 97.83 200 | 98.90 145 | 95.36 236 | 96.83 447 | 98.37 250 | 91.32 400 | 94.43 316 | 98.73 202 | 90.27 217 | 99.60 166 | 90.05 407 | 98.82 169 | 98.52 286 |
|
| BH-RMVSNet | | | 95.92 232 | 95.32 248 | 97.69 216 | 98.32 224 | 94.64 276 | 98.19 298 | 97.45 389 | 94.56 250 | 96.03 275 | 98.61 214 | 85.02 349 | 99.12 269 | 90.68 398 | 99.06 151 | 99.30 163 |
|
| test_fmvs1_n | | | 95.90 233 | 95.99 214 | 95.63 378 | 98.67 172 | 88.32 459 | 99.26 33 | 98.22 290 | 96.40 124 | 99.67 28 | 99.26 80 | 73.91 468 | 99.70 143 | 99.02 33 | 99.50 115 | 98.87 242 |
|
| Fast-Effi-MVS+-dtu | | | 95.87 234 | 95.85 218 | 95.91 362 | 97.74 306 | 91.74 386 | 98.69 199 | 98.15 308 | 95.56 172 | 94.92 297 | 97.68 311 | 88.98 259 | 98.79 328 | 93.19 324 | 97.78 242 | 97.20 336 |
|
| LFMVS | | | 95.86 235 | 94.98 266 | 98.47 122 | 98.87 150 | 96.32 163 | 98.84 151 | 96.02 460 | 93.40 322 | 98.62 111 | 99.20 95 | 74.99 460 | 99.63 160 | 97.72 113 | 97.20 263 | 99.46 121 |
|
| baseline1 | | | 95.84 236 | 95.12 258 | 98.01 182 | 98.49 191 | 95.98 179 | 98.73 187 | 97.03 425 | 95.37 193 | 96.22 268 | 98.19 262 | 89.96 224 | 99.16 257 | 94.60 277 | 87.48 430 | 98.90 240 |
|
| OpenMVS |  | 93.04 13 | 95.83 237 | 95.00 264 | 98.32 136 | 97.18 355 | 97.32 99 | 99.21 45 | 98.97 57 | 89.96 427 | 91.14 429 | 99.05 143 | 86.64 316 | 99.92 43 | 93.38 318 | 99.47 121 | 97.73 319 |
|
| IMVS_0404 | | | 95.82 238 | 95.52 234 | 96.73 289 | 97.99 281 | 92.82 360 | 97.23 405 | 98.27 278 | 95.16 205 | 94.31 323 | 98.79 188 | 85.63 337 | 98.10 403 | 94.74 265 | 97.54 254 | 99.27 173 |
|
| VDD-MVS | | | 95.82 238 | 95.23 252 | 97.61 228 | 98.84 155 | 93.98 308 | 98.68 202 | 97.40 393 | 95.02 221 | 97.95 161 | 99.34 68 | 74.37 466 | 99.78 124 | 98.64 48 | 96.80 276 | 99.08 218 |
|
| UniMVSNet (Re) | | | 95.78 240 | 95.19 254 | 97.58 229 | 96.99 365 | 97.47 92 | 98.79 172 | 99.18 36 | 95.60 168 | 93.92 344 | 97.04 371 | 91.68 156 | 98.48 353 | 95.80 227 | 87.66 429 | 96.79 367 |
|
| VPA-MVSNet | | | 95.75 241 | 95.11 259 | 97.69 216 | 97.24 347 | 97.27 106 | 98.94 108 | 99.23 27 | 95.13 210 | 95.51 286 | 97.32 342 | 85.73 335 | 98.91 310 | 97.33 159 | 89.55 404 | 96.89 356 |
|
| HQP-MVS | | | 95.72 242 | 95.40 238 | 96.69 295 | 97.20 351 | 94.25 299 | 98.05 324 | 98.46 207 | 96.43 120 | 94.45 312 | 97.73 303 | 86.75 314 | 98.96 301 | 95.30 246 | 94.18 326 | 96.86 362 |
|
| hse-mvs2 | | | 95.71 243 | 95.30 250 | 96.93 275 | 98.50 187 | 93.53 326 | 98.36 270 | 98.10 318 | 97.48 54 | 98.67 105 | 97.99 278 | 89.76 228 | 99.02 292 | 97.95 94 | 80.91 472 | 98.22 301 |
|
| UniMVSNet_NR-MVSNet | | | 95.71 243 | 95.15 255 | 97.40 242 | 96.84 375 | 96.97 126 | 98.74 181 | 99.24 20 | 95.16 205 | 93.88 346 | 97.72 305 | 91.68 156 | 98.31 383 | 95.81 225 | 87.25 435 | 96.92 348 |
|
| PatchmatchNet |  | | 95.71 243 | 95.52 234 | 96.29 342 | 97.58 319 | 90.72 406 | 96.84 446 | 97.52 379 | 94.06 272 | 97.08 223 | 96.96 381 | 89.24 248 | 98.90 313 | 92.03 367 | 98.37 210 | 99.26 180 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
| OPM-MVS | | | 95.69 246 | 95.33 247 | 96.76 288 | 96.16 412 | 94.63 277 | 98.43 264 | 98.39 241 | 96.64 112 | 95.02 296 | 98.78 192 | 85.15 348 | 99.05 282 | 95.21 253 | 94.20 325 | 96.60 393 |
| Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS). |
| ACMM | | 93.85 9 | 95.69 246 | 95.38 242 | 96.61 306 | 97.61 316 | 93.84 313 | 98.91 119 | 98.44 215 | 95.25 201 | 94.28 326 | 98.47 231 | 86.04 332 | 99.12 269 | 95.50 240 | 93.95 335 | 96.87 360 |
| Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
| tpmrst | | | 95.63 248 | 95.69 230 | 95.44 386 | 97.54 324 | 88.54 454 | 96.97 429 | 97.56 371 | 93.50 316 | 97.52 207 | 96.93 386 | 89.49 235 | 99.16 257 | 95.25 250 | 96.42 290 | 98.64 275 |
|
| FE-MVS | | | 95.62 249 | 94.90 270 | 97.78 205 | 98.37 210 | 94.92 264 | 97.17 417 | 97.38 395 | 90.95 411 | 97.73 185 | 97.70 306 | 85.32 346 | 99.63 160 | 91.18 385 | 98.33 214 | 98.79 250 |
|
| LPG-MVS_test | | | 95.62 249 | 95.34 244 | 96.47 325 | 97.46 331 | 93.54 324 | 98.99 94 | 98.54 186 | 94.67 245 | 94.36 320 | 98.77 195 | 85.39 341 | 99.11 271 | 95.71 231 | 94.15 328 | 96.76 370 |
|
| CLD-MVS | | | 95.62 249 | 95.34 244 | 96.46 328 | 97.52 327 | 93.75 317 | 97.27 404 | 98.46 207 | 95.53 180 | 94.42 317 | 98.00 277 | 86.21 327 | 98.97 297 | 96.25 210 | 94.37 320 | 96.66 385 |
| Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
| thisisatest0515 | | | 95.61 252 | 94.89 271 | 97.76 209 | 98.15 260 | 95.15 250 | 96.77 448 | 94.41 484 | 92.95 343 | 97.18 219 | 97.43 333 | 84.78 355 | 99.45 202 | 94.63 273 | 97.73 246 | 98.68 269 |
|
| MonoMVSNet | | | 95.51 253 | 95.45 237 | 95.68 375 | 95.54 437 | 90.87 401 | 98.92 117 | 97.37 396 | 95.79 158 | 95.53 285 | 97.38 338 | 89.58 234 | 97.68 442 | 96.40 204 | 92.59 362 | 98.49 288 |
|
| thres600view7 | | | 95.49 254 | 94.77 274 | 97.67 220 | 98.98 139 | 95.02 255 | 98.85 147 | 96.90 435 | 95.38 191 | 96.63 249 | 96.90 388 | 84.29 365 | 99.59 167 | 88.65 431 | 96.33 292 | 98.40 292 |
|
| test_vis1_n | | | 95.47 255 | 95.13 256 | 96.49 322 | 97.77 302 | 90.41 416 | 99.27 32 | 98.11 315 | 96.58 114 | 99.66 29 | 99.18 105 | 67.00 483 | 99.62 164 | 99.21 28 | 99.40 131 | 99.44 126 |
|
| SCA | | | 95.46 256 | 95.13 256 | 96.46 328 | 97.67 311 | 91.29 394 | 97.33 399 | 97.60 367 | 94.68 244 | 96.92 233 | 97.10 356 | 83.97 375 | 98.89 314 | 92.59 351 | 98.32 217 | 99.20 189 |
|
| IterMVS-LS | | | 95.46 256 | 95.21 253 | 96.22 344 | 98.12 262 | 93.72 320 | 98.32 277 | 98.13 311 | 93.71 299 | 94.26 327 | 97.31 343 | 92.24 135 | 98.10 403 | 94.63 273 | 90.12 395 | 96.84 363 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
| testing3-2 | | | 95.45 258 | 95.34 244 | 95.77 373 | 98.69 169 | 88.75 450 | 98.87 134 | 97.21 410 | 96.13 137 | 97.22 217 | 97.68 311 | 77.95 434 | 99.65 154 | 97.58 130 | 96.77 279 | 98.91 239 |
|
| jajsoiax | | | 95.45 258 | 95.03 263 | 96.73 289 | 95.42 445 | 94.63 277 | 99.14 60 | 98.52 191 | 95.74 160 | 93.22 376 | 98.36 242 | 83.87 378 | 98.65 339 | 96.95 173 | 94.04 331 | 96.91 353 |
|
| CVMVSNet | | | 95.43 260 | 96.04 209 | 93.57 440 | 97.93 292 | 83.62 482 | 98.12 313 | 98.59 171 | 95.68 164 | 96.56 253 | 99.02 146 | 87.51 300 | 97.51 451 | 93.56 316 | 97.44 259 | 99.60 92 |
|
| anonymousdsp | | | 95.42 261 | 94.91 269 | 96.94 274 | 95.10 449 | 95.90 193 | 99.14 60 | 98.41 232 | 93.75 293 | 93.16 379 | 97.46 329 | 87.50 302 | 98.41 369 | 95.63 236 | 94.03 332 | 96.50 418 |
|
| DU-MVS | | | 95.42 261 | 94.76 275 | 97.40 242 | 96.53 392 | 96.97 126 | 98.66 209 | 98.99 56 | 95.43 186 | 93.88 346 | 97.69 308 | 88.57 270 | 98.31 383 | 95.81 225 | 87.25 435 | 96.92 348 |
|
| mvs_tets | | | 95.41 263 | 95.00 264 | 96.65 298 | 95.58 436 | 94.42 288 | 99.00 91 | 98.55 184 | 95.73 162 | 93.21 377 | 98.38 240 | 83.45 384 | 98.63 340 | 97.09 166 | 94.00 333 | 96.91 353 |
|
| thres100view900 | | | 95.38 264 | 94.70 279 | 97.41 240 | 98.98 139 | 94.92 264 | 98.87 134 | 96.90 435 | 95.38 191 | 96.61 251 | 96.88 389 | 84.29 365 | 99.56 174 | 88.11 434 | 96.29 296 | 97.76 316 |
|
| thres400 | | | 95.38 264 | 94.62 283 | 97.65 224 | 98.94 143 | 94.98 260 | 98.68 202 | 96.93 433 | 95.33 195 | 96.55 255 | 96.53 408 | 84.23 369 | 99.56 174 | 88.11 434 | 96.29 296 | 98.40 292 |
|
| BH-w/o | | | 95.38 264 | 95.08 261 | 96.26 343 | 98.34 217 | 91.79 383 | 97.70 368 | 97.43 391 | 92.87 347 | 94.24 329 | 97.22 350 | 88.66 268 | 98.84 320 | 91.55 381 | 97.70 247 | 98.16 305 |
|
| VDDNet | | | 95.36 267 | 94.53 288 | 97.86 198 | 98.10 264 | 95.13 251 | 98.85 147 | 97.75 355 | 90.46 418 | 98.36 129 | 99.39 50 | 73.27 470 | 99.64 157 | 97.98 93 | 96.58 284 | 98.81 248 |
|
| TAPA-MVS | | 93.98 7 | 95.35 268 | 94.56 287 | 97.74 211 | 99.13 119 | 94.83 269 | 98.33 273 | 98.64 158 | 86.62 463 | 96.29 266 | 98.61 214 | 94.00 105 | 99.29 224 | 80.00 482 | 99.41 128 | 99.09 214 |
| Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
| ACMP | | 93.49 10 | 95.34 269 | 94.98 266 | 96.43 330 | 97.67 311 | 93.48 328 | 98.73 187 | 98.44 215 | 94.94 230 | 92.53 400 | 98.53 224 | 84.50 364 | 99.14 264 | 95.48 241 | 94.00 333 | 96.66 385 |
| Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
| COLMAP_ROB |  | 93.27 12 | 95.33 270 | 94.87 272 | 96.71 292 | 99.29 88 | 93.24 347 | 98.58 225 | 98.11 315 | 89.92 428 | 93.57 361 | 99.10 125 | 86.37 323 | 99.79 121 | 90.78 396 | 98.10 229 | 97.09 337 |
| Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
| UBG | | | 95.32 271 | 94.72 278 | 97.13 256 | 98.05 272 | 93.26 344 | 97.87 350 | 97.20 413 | 94.96 226 | 96.18 271 | 95.66 446 | 80.97 404 | 99.35 212 | 94.47 283 | 97.08 266 | 98.78 254 |
|
| tfpn200view9 | | | 95.32 271 | 94.62 283 | 97.43 238 | 98.94 143 | 94.98 260 | 98.68 202 | 96.93 433 | 95.33 195 | 96.55 255 | 96.53 408 | 84.23 369 | 99.56 174 | 88.11 434 | 96.29 296 | 97.76 316 |
|
| Anonymous202405211 | | | 95.28 273 | 94.49 290 | 97.67 220 | 99.00 135 | 93.75 317 | 98.70 196 | 97.04 424 | 90.66 414 | 96.49 259 | 98.80 186 | 78.13 430 | 99.83 90 | 96.21 211 | 95.36 318 | 99.44 126 |
|
| thres200 | | | 95.25 274 | 94.57 286 | 97.28 246 | 98.81 157 | 94.92 264 | 98.20 295 | 97.11 417 | 95.24 203 | 96.54 257 | 96.22 423 | 84.58 362 | 99.53 183 | 87.93 440 | 96.50 288 | 97.39 330 |
|
| AllTest | | | 95.24 275 | 94.65 282 | 96.99 267 | 99.25 96 | 93.21 348 | 98.59 221 | 98.18 299 | 91.36 396 | 93.52 363 | 98.77 195 | 84.67 359 | 99.72 137 | 89.70 414 | 97.87 238 | 98.02 310 |
|
| LCM-MVSNet-Re | | | 95.22 276 | 95.32 248 | 94.91 404 | 98.18 254 | 87.85 465 | 98.75 177 | 95.66 467 | 95.11 212 | 88.96 452 | 96.85 392 | 90.26 218 | 97.65 443 | 95.65 235 | 98.44 197 | 99.22 186 |
|
| EPNet_dtu | | | 95.21 277 | 94.95 268 | 95.99 355 | 96.17 410 | 90.45 414 | 98.16 306 | 97.27 405 | 96.77 102 | 93.14 382 | 98.33 248 | 90.34 214 | 98.42 362 | 85.57 456 | 98.81 170 | 99.09 214 |
| Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
| XXY-MVS | | | 95.20 278 | 94.45 296 | 97.46 235 | 96.75 382 | 96.56 150 | 98.86 142 | 98.65 157 | 93.30 327 | 93.27 375 | 98.27 255 | 84.85 353 | 98.87 317 | 94.82 262 | 91.26 381 | 96.96 343 |
|
| D2MVS | | | 95.18 279 | 95.08 261 | 95.48 383 | 97.10 360 | 92.07 379 | 98.30 281 | 99.13 43 | 94.02 275 | 92.90 387 | 96.73 398 | 89.48 236 | 98.73 332 | 94.48 282 | 93.60 344 | 95.65 449 |
|
| WR-MVS | | | 95.15 280 | 94.46 293 | 97.22 248 | 96.67 387 | 96.45 154 | 98.21 291 | 98.81 107 | 94.15 269 | 93.16 379 | 97.69 308 | 87.51 300 | 98.30 385 | 95.29 248 | 88.62 419 | 96.90 355 |
|
| TranMVSNet+NR-MVSNet | | | 95.14 281 | 94.48 291 | 97.11 260 | 96.45 399 | 96.36 161 | 99.03 83 | 99.03 50 | 95.04 217 | 93.58 360 | 97.93 284 | 88.27 280 | 98.03 417 | 94.13 296 | 86.90 440 | 96.95 345 |
|
| myMVS_eth3d28 | | | 95.12 282 | 94.62 283 | 96.64 302 | 98.17 258 | 92.17 372 | 98.02 328 | 97.32 399 | 95.41 189 | 96.22 268 | 96.05 429 | 78.01 432 | 99.13 266 | 95.22 252 | 97.16 264 | 98.60 278 |
|
| baseline2 | | | 95.11 283 | 94.52 289 | 96.87 280 | 96.65 388 | 93.56 323 | 98.27 286 | 94.10 492 | 93.45 319 | 92.02 420 | 97.43 333 | 87.45 305 | 99.19 251 | 93.88 305 | 97.41 261 | 97.87 314 |
|
| miper_enhance_ethall | | | 95.10 284 | 94.75 276 | 96.12 348 | 97.53 326 | 93.73 319 | 96.61 454 | 98.08 323 | 92.20 374 | 93.89 345 | 96.65 404 | 92.44 126 | 98.30 385 | 94.21 292 | 91.16 382 | 96.34 427 |
|
| Anonymous20240529 | | | 95.10 284 | 94.22 308 | 97.75 210 | 99.01 133 | 94.26 298 | 98.87 134 | 98.83 98 | 85.79 471 | 96.64 248 | 98.97 154 | 78.73 423 | 99.85 84 | 96.27 207 | 94.89 319 | 99.12 206 |
|
| test-LLR | | | 95.10 284 | 94.87 272 | 95.80 370 | 96.77 379 | 89.70 430 | 96.91 435 | 95.21 473 | 95.11 212 | 94.83 301 | 95.72 442 | 87.71 295 | 98.97 297 | 93.06 328 | 98.50 190 | 98.72 262 |
|
| dtuonly | | | 95.08 287 | 95.10 260 | 95.02 400 | 96.53 392 | 87.27 469 | 96.33 460 | 97.21 410 | 93.41 321 | 96.28 267 | 98.51 228 | 87.71 295 | 98.99 296 | 91.88 372 | 98.01 232 | 98.80 249 |
|
| WR-MVS_H | | | 95.05 288 | 94.46 293 | 96.81 284 | 96.86 374 | 95.82 206 | 99.24 36 | 99.24 20 | 93.87 287 | 92.53 400 | 96.84 393 | 90.37 213 | 98.24 391 | 93.24 322 | 87.93 425 | 96.38 426 |
|
| miper_ehance_all_eth | | | 95.01 289 | 94.69 280 | 95.97 359 | 97.70 309 | 93.31 340 | 97.02 427 | 98.07 325 | 92.23 371 | 93.51 365 | 96.96 381 | 91.85 150 | 98.15 398 | 93.68 310 | 91.16 382 | 96.44 424 |
|
| testing11 | | | 95.00 290 | 94.28 303 | 97.16 254 | 97.96 289 | 93.36 337 | 98.09 320 | 97.06 423 | 94.94 230 | 95.33 291 | 96.15 425 | 76.89 447 | 99.40 207 | 95.77 229 | 96.30 295 | 98.72 262 |
|
| ADS-MVSNet | | | 95.00 290 | 94.45 296 | 96.63 303 | 98.00 279 | 91.91 382 | 96.04 462 | 97.74 356 | 90.15 424 | 96.47 260 | 96.64 405 | 87.89 291 | 98.96 301 | 90.08 405 | 97.06 267 | 99.02 227 |
|
| VPNet | | | 94.99 292 | 94.19 310 | 97.40 242 | 97.16 356 | 96.57 149 | 98.71 192 | 98.97 57 | 95.67 165 | 94.84 299 | 98.24 259 | 80.36 411 | 98.67 338 | 96.46 201 | 87.32 434 | 96.96 343 |
|
| EPMVS | | | 94.99 292 | 94.48 291 | 96.52 319 | 97.22 349 | 91.75 385 | 97.23 405 | 91.66 504 | 94.11 270 | 97.28 213 | 96.81 395 | 85.70 336 | 98.84 320 | 93.04 330 | 97.28 262 | 98.97 232 |
|
| testing91 | | | 94.98 294 | 94.25 307 | 97.20 249 | 97.94 290 | 93.41 331 | 98.00 331 | 97.58 368 | 94.99 222 | 95.45 287 | 96.04 430 | 77.20 442 | 99.42 205 | 94.97 258 | 96.02 309 | 98.78 254 |
|
| NR-MVSNet | | | 94.98 294 | 94.16 313 | 97.44 237 | 96.53 392 | 97.22 114 | 98.74 181 | 98.95 61 | 94.96 226 | 89.25 450 | 97.69 308 | 89.32 245 | 98.18 395 | 94.59 279 | 87.40 432 | 96.92 348 |
|
| FMVSNet3 | | | 94.97 296 | 94.26 306 | 97.11 260 | 98.18 254 | 96.62 141 | 98.56 237 | 98.26 286 | 93.67 306 | 94.09 336 | 97.10 356 | 84.25 367 | 98.01 419 | 92.08 363 | 92.14 367 | 96.70 379 |
|
| usedtu_dtu_shiyan1 | | | 94.96 297 | 94.28 303 | 96.98 270 | 95.93 423 | 96.11 174 | 97.08 423 | 98.39 241 | 93.62 310 | 93.86 348 | 96.40 414 | 88.28 278 | 98.21 392 | 92.61 346 | 92.36 365 | 96.63 387 |
|
| FE-MVSNET3 | | | 94.96 297 | 94.28 303 | 96.98 270 | 95.93 423 | 96.11 174 | 97.08 423 | 98.39 241 | 93.62 310 | 93.86 348 | 96.40 414 | 88.28 278 | 98.21 392 | 92.61 346 | 92.36 365 | 96.63 387 |
|
| CostFormer | | | 94.95 299 | 94.73 277 | 95.60 380 | 97.28 345 | 89.06 443 | 97.53 380 | 96.89 437 | 89.66 433 | 96.82 239 | 96.72 399 | 86.05 330 | 98.95 306 | 95.53 239 | 96.13 307 | 98.79 250 |
|
| PAPM | | | 94.95 299 | 94.00 326 | 97.78 205 | 97.04 362 | 95.65 215 | 96.03 464 | 98.25 287 | 91.23 405 | 94.19 332 | 97.80 300 | 91.27 175 | 98.86 319 | 82.61 473 | 97.61 249 | 98.84 245 |
|
| CP-MVSNet | | | 94.94 301 | 94.30 302 | 96.83 282 | 96.72 384 | 95.56 219 | 99.11 66 | 98.95 61 | 93.89 285 | 92.42 406 | 97.90 287 | 87.19 307 | 98.12 402 | 94.32 288 | 88.21 422 | 96.82 366 |
|
| TR-MVS | | | 94.94 301 | 94.20 309 | 97.17 253 | 97.75 303 | 94.14 305 | 97.59 377 | 97.02 428 | 92.28 370 | 95.75 283 | 97.64 316 | 83.88 377 | 98.96 301 | 89.77 411 | 96.15 306 | 98.40 292 |
|
| RPSCF | | | 94.87 303 | 95.40 238 | 93.26 446 | 98.89 146 | 82.06 489 | 98.33 273 | 98.06 330 | 90.30 423 | 96.56 253 | 99.26 80 | 87.09 308 | 99.49 191 | 93.82 307 | 96.32 293 | 98.24 299 |
|
| testing99 | | | 94.83 304 | 94.08 318 | 97.07 263 | 97.94 290 | 93.13 350 | 98.10 319 | 97.17 415 | 94.86 232 | 95.34 288 | 96.00 434 | 76.31 450 | 99.40 207 | 95.08 255 | 95.90 310 | 98.68 269 |
|
| GA-MVS | | | 94.81 305 | 94.03 322 | 97.14 255 | 97.15 357 | 93.86 312 | 96.76 449 | 97.58 368 | 94.00 279 | 94.76 305 | 97.04 371 | 80.91 405 | 98.48 353 | 91.79 374 | 96.25 302 | 99.09 214 |
|
| c3_l | | | 94.79 306 | 94.43 298 | 95.89 364 | 97.75 303 | 93.12 352 | 97.16 419 | 98.03 332 | 92.23 371 | 93.46 369 | 97.05 370 | 91.39 169 | 98.01 419 | 93.58 315 | 89.21 411 | 96.53 409 |
|
| V42 | | | 94.78 307 | 94.14 315 | 96.70 294 | 96.33 404 | 95.22 245 | 98.97 98 | 98.09 322 | 92.32 368 | 94.31 323 | 97.06 367 | 88.39 276 | 98.55 348 | 92.90 335 | 88.87 417 | 96.34 427 |
|
| reproduce_monomvs | | | 94.77 308 | 94.67 281 | 95.08 398 | 98.40 204 | 89.48 436 | 98.80 164 | 98.64 158 | 97.57 48 | 93.21 377 | 97.65 313 | 80.57 410 | 98.83 323 | 97.72 113 | 89.47 407 | 96.93 347 |
|
| CR-MVSNet | | | 94.76 309 | 94.15 314 | 96.59 309 | 97.00 363 | 93.43 329 | 94.96 482 | 97.56 371 | 92.46 359 | 96.93 231 | 96.24 419 | 88.15 283 | 97.88 433 | 87.38 443 | 96.65 282 | 98.46 290 |
|
| v2v482 | | | 94.69 310 | 94.03 322 | 96.65 298 | 96.17 410 | 94.79 272 | 98.67 207 | 98.08 323 | 92.72 351 | 94.00 341 | 97.16 353 | 87.69 299 | 98.45 358 | 92.91 334 | 88.87 417 | 96.72 375 |
|
| pmmvs4 | | | 94.69 310 | 93.99 328 | 96.81 284 | 95.74 430 | 95.94 187 | 97.40 390 | 97.67 360 | 90.42 420 | 93.37 372 | 97.59 320 | 89.08 253 | 98.20 394 | 92.97 332 | 91.67 375 | 96.30 430 |
|
| cl22 | | | 94.68 312 | 94.19 310 | 96.13 347 | 98.11 263 | 93.60 322 | 96.94 431 | 98.31 268 | 92.43 363 | 93.32 374 | 96.87 391 | 86.51 317 | 98.28 389 | 94.10 299 | 91.16 382 | 96.51 416 |
|
| eth_miper_zixun_eth | | | 94.68 312 | 94.41 299 | 95.47 384 | 97.64 314 | 91.71 387 | 96.73 451 | 98.07 325 | 92.71 352 | 93.64 357 | 97.21 351 | 90.54 206 | 98.17 396 | 93.38 318 | 89.76 399 | 96.54 407 |
|
| PCF-MVS | | 93.45 11 | 94.68 312 | 93.43 364 | 98.42 130 | 98.62 179 | 96.77 136 | 95.48 475 | 98.20 293 | 84.63 477 | 93.34 373 | 98.32 249 | 88.55 273 | 99.81 102 | 84.80 465 | 98.96 158 | 98.68 269 |
| Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
| MVS | | | 94.67 315 | 93.54 359 | 98.08 172 | 96.88 373 | 96.56 150 | 98.19 298 | 98.50 199 | 78.05 495 | 92.69 394 | 98.02 274 | 91.07 189 | 99.63 160 | 90.09 404 | 98.36 212 | 98.04 309 |
|
| PS-CasMVS | | | 94.67 315 | 93.99 328 | 96.71 292 | 96.68 386 | 95.26 242 | 99.13 63 | 99.03 50 | 93.68 304 | 92.33 410 | 97.95 282 | 85.35 343 | 98.10 403 | 93.59 314 | 88.16 424 | 96.79 367 |
|
| cascas | | | 94.63 317 | 93.86 338 | 96.93 275 | 96.91 371 | 94.27 297 | 96.00 465 | 98.51 194 | 85.55 473 | 94.54 308 | 96.23 421 | 84.20 371 | 98.87 317 | 95.80 227 | 96.98 272 | 97.66 322 |
|
| tpmvs | | | 94.60 318 | 94.36 301 | 95.33 390 | 97.46 331 | 88.60 453 | 96.88 443 | 97.68 357 | 91.29 402 | 93.80 353 | 96.42 413 | 88.58 269 | 99.24 240 | 91.06 391 | 96.04 308 | 98.17 304 |
|
| LTVRE_ROB | | 92.95 15 | 94.60 318 | 93.90 334 | 96.68 296 | 97.41 339 | 94.42 288 | 98.52 241 | 98.59 171 | 91.69 387 | 91.21 428 | 98.35 243 | 84.87 352 | 99.04 285 | 91.06 391 | 93.44 348 | 96.60 393 |
| Andreas Kuhn, Heiko Hirschmüller, Daniel Scharstein, Helmut Mayer: A TV Prior for High-Quality Scalable Multi-View Stereo Reconstruction. International Journal of Computer Vision 2016 |
| v1144 | | | 94.59 320 | 93.92 331 | 96.60 308 | 96.21 406 | 94.78 273 | 98.59 221 | 98.14 310 | 91.86 383 | 94.21 331 | 97.02 374 | 87.97 289 | 98.41 369 | 91.72 376 | 89.57 402 | 96.61 391 |
|
| ADS-MVSNet2 | | | 94.58 321 | 94.40 300 | 95.11 396 | 98.00 279 | 88.74 451 | 96.04 462 | 97.30 401 | 90.15 424 | 96.47 260 | 96.64 405 | 87.89 291 | 97.56 449 | 90.08 405 | 97.06 267 | 99.02 227 |
|
| WBMVS | | | 94.56 322 | 94.04 320 | 96.10 349 | 98.03 276 | 93.08 354 | 97.82 358 | 98.18 299 | 94.02 275 | 93.77 355 | 96.82 394 | 81.28 399 | 98.34 378 | 95.47 242 | 91.00 385 | 96.88 357 |
|
| ACMH | | 92.88 16 | 94.55 323 | 93.95 330 | 96.34 338 | 97.63 315 | 93.26 344 | 98.81 163 | 98.49 204 | 93.43 320 | 89.74 444 | 98.53 224 | 81.91 391 | 99.08 278 | 93.69 309 | 93.30 353 | 96.70 379 |
| Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
| tt0805 | | | 94.54 324 | 93.85 339 | 96.63 303 | 97.98 287 | 93.06 355 | 98.77 176 | 97.84 344 | 93.67 306 | 93.80 353 | 98.04 273 | 76.88 448 | 98.96 301 | 94.79 264 | 92.86 358 | 97.86 315 |
|
| XVG-ACMP-BASELINE | | | 94.54 324 | 94.14 315 | 95.75 374 | 96.55 391 | 91.65 388 | 98.11 317 | 98.44 215 | 94.96 226 | 94.22 330 | 97.90 287 | 79.18 421 | 99.11 271 | 94.05 301 | 93.85 337 | 96.48 421 |
|
| AUN-MVS | | | 94.53 326 | 93.73 349 | 96.92 278 | 98.50 187 | 93.52 327 | 98.34 272 | 98.10 318 | 93.83 290 | 95.94 281 | 97.98 280 | 85.59 339 | 99.03 288 | 94.35 286 | 80.94 471 | 98.22 301 |
|
| DIV-MVS_self_test | | | 94.52 327 | 94.03 322 | 95.99 355 | 97.57 323 | 93.38 335 | 97.05 425 | 97.94 338 | 91.74 384 | 92.81 389 | 97.10 356 | 89.12 251 | 98.07 411 | 92.60 349 | 90.30 392 | 96.53 409 |
|
| cl____ | | | 94.51 328 | 94.01 325 | 96.02 351 | 97.58 319 | 93.40 334 | 97.05 425 | 97.96 337 | 91.73 386 | 92.76 391 | 97.08 362 | 89.06 254 | 98.13 400 | 92.61 346 | 90.29 393 | 96.52 412 |
|
| ETVMVS | | | 94.50 329 | 93.44 363 | 97.68 218 | 98.18 254 | 95.35 238 | 98.19 298 | 97.11 417 | 93.73 296 | 96.40 263 | 95.39 449 | 74.53 463 | 98.84 320 | 91.10 387 | 96.31 294 | 98.84 245 |
|
| GBi-Net | | | 94.49 330 | 93.80 342 | 96.56 313 | 98.21 244 | 95.00 256 | 98.82 155 | 98.18 299 | 92.46 359 | 94.09 336 | 97.07 363 | 81.16 400 | 97.95 424 | 92.08 363 | 92.14 367 | 96.72 375 |
|
| test1 | | | 94.49 330 | 93.80 342 | 96.56 313 | 98.21 244 | 95.00 256 | 98.82 155 | 98.18 299 | 92.46 359 | 94.09 336 | 97.07 363 | 81.16 400 | 97.95 424 | 92.08 363 | 92.14 367 | 96.72 375 |
|
| dmvs_re | | | 94.48 332 | 94.18 312 | 95.37 388 | 97.68 310 | 90.11 422 | 98.54 240 | 97.08 419 | 94.56 250 | 94.42 317 | 97.24 348 | 84.25 367 | 97.76 439 | 91.02 394 | 92.83 359 | 98.24 299 |
|
| v8 | | | 94.47 333 | 93.77 345 | 96.57 312 | 96.36 402 | 94.83 269 | 99.05 76 | 98.19 296 | 91.92 380 | 93.16 379 | 96.97 379 | 88.82 267 | 98.48 353 | 91.69 377 | 87.79 426 | 96.39 425 |
|
| FMVSNet2 | | | 94.47 333 | 93.61 355 | 97.04 265 | 98.21 244 | 96.43 156 | 98.79 172 | 98.27 278 | 92.46 359 | 93.50 366 | 97.09 360 | 81.16 400 | 98.00 421 | 91.09 388 | 91.93 370 | 96.70 379 |
|
| test2506 | | | 94.44 335 | 93.91 333 | 96.04 350 | 99.02 131 | 88.99 446 | 99.06 74 | 79.47 518 | 96.96 93 | 98.36 129 | 99.26 80 | 77.21 441 | 99.52 186 | 96.78 192 | 99.04 152 | 99.59 94 |
|
| Patchmatch-test | | | 94.42 336 | 93.68 353 | 96.63 303 | 97.60 317 | 91.76 384 | 94.83 486 | 97.49 383 | 89.45 437 | 94.14 334 | 97.10 356 | 88.99 256 | 98.83 323 | 85.37 459 | 98.13 228 | 99.29 166 |
|
| PEN-MVS | | | 94.42 336 | 93.73 349 | 96.49 322 | 96.28 405 | 94.84 267 | 99.17 55 | 99.00 53 | 93.51 315 | 92.23 412 | 97.83 297 | 86.10 329 | 97.90 428 | 92.55 354 | 86.92 439 | 96.74 372 |
|
| v144192 | | | 94.39 338 | 93.70 351 | 96.48 324 | 96.06 416 | 94.35 292 | 98.58 225 | 98.16 307 | 91.45 393 | 94.33 322 | 97.02 374 | 87.50 302 | 98.45 358 | 91.08 390 | 89.11 412 | 96.63 387 |
|
| Baseline_NR-MVSNet | | | 94.35 339 | 93.81 341 | 95.96 360 | 96.20 407 | 94.05 307 | 98.61 220 | 96.67 448 | 91.44 394 | 93.85 350 | 97.60 319 | 88.57 270 | 98.14 399 | 94.39 284 | 86.93 438 | 95.68 448 |
|
| miper_lstm_enhance | | | 94.33 340 | 94.07 319 | 95.11 396 | 97.75 303 | 90.97 398 | 97.22 407 | 98.03 332 | 91.67 388 | 92.76 391 | 96.97 379 | 90.03 223 | 97.78 438 | 92.51 356 | 89.64 401 | 96.56 404 |
|
| v1192 | | | 94.32 341 | 93.58 356 | 96.53 318 | 96.10 414 | 94.45 286 | 98.50 249 | 98.17 305 | 91.54 391 | 94.19 332 | 97.06 367 | 86.95 312 | 98.43 361 | 90.14 403 | 89.57 402 | 96.70 379 |
|
| UWE-MVS | | | 94.30 342 | 93.89 336 | 95.53 381 | 97.83 298 | 88.95 447 | 97.52 382 | 93.25 495 | 94.44 260 | 96.63 249 | 97.07 363 | 78.70 424 | 99.28 226 | 91.99 368 | 97.56 253 | 98.36 295 |
|
| ACMH+ | | 92.99 14 | 94.30 342 | 93.77 345 | 95.88 365 | 97.81 300 | 92.04 381 | 98.71 192 | 98.37 250 | 93.99 280 | 90.60 435 | 98.47 231 | 80.86 407 | 99.05 282 | 92.75 342 | 92.40 364 | 96.55 406 |
|
| v148 | | | 94.29 344 | 93.76 347 | 95.91 362 | 96.10 414 | 92.93 358 | 98.58 225 | 97.97 335 | 92.59 357 | 93.47 368 | 96.95 383 | 88.53 274 | 98.32 381 | 92.56 353 | 87.06 437 | 96.49 419 |
|
| v10 | | | 94.29 344 | 93.55 358 | 96.51 320 | 96.39 401 | 94.80 271 | 98.99 94 | 98.19 296 | 91.35 398 | 93.02 385 | 96.99 377 | 88.09 285 | 98.41 369 | 90.50 400 | 88.41 421 | 96.33 429 |
|
| SD_0403 | | | 94.28 346 | 94.46 293 | 93.73 437 | 98.02 277 | 85.32 477 | 98.31 278 | 98.40 235 | 94.75 240 | 93.59 358 | 98.16 264 | 89.01 255 | 96.54 470 | 82.32 474 | 97.58 252 | 99.34 150 |
|
| MVP-Stereo | | | 94.28 346 | 93.92 331 | 95.35 389 | 94.95 451 | 92.60 366 | 97.97 334 | 97.65 361 | 91.61 389 | 90.68 434 | 97.09 360 | 86.32 326 | 98.42 362 | 89.70 414 | 99.34 137 | 95.02 463 |
| Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
| UniMVSNet_ETH3D | | | 94.24 348 | 93.33 366 | 96.97 272 | 97.19 354 | 93.38 335 | 98.74 181 | 98.57 178 | 91.21 407 | 93.81 352 | 98.58 219 | 72.85 472 | 98.77 330 | 95.05 256 | 93.93 336 | 98.77 257 |
|
| OurMVSNet-221017-0 | | | 94.21 349 | 94.00 326 | 94.85 409 | 95.60 435 | 89.22 441 | 98.89 124 | 97.43 391 | 95.29 198 | 92.18 415 | 98.52 227 | 82.86 385 | 98.59 346 | 93.46 317 | 91.76 373 | 96.74 372 |
|
| v1921920 | | | 94.20 350 | 93.47 362 | 96.40 334 | 95.98 420 | 94.08 306 | 98.52 241 | 98.15 308 | 91.33 399 | 94.25 328 | 97.20 352 | 86.41 322 | 98.42 362 | 90.04 408 | 89.39 409 | 96.69 384 |
|
| WB-MVSnew | | | 94.19 351 | 94.04 320 | 94.66 417 | 96.82 377 | 92.14 373 | 97.86 352 | 95.96 463 | 93.50 316 | 95.64 284 | 96.77 397 | 88.06 287 | 97.99 422 | 84.87 462 | 96.86 273 | 93.85 485 |
|
| v7n | | | 94.19 351 | 93.43 364 | 96.47 325 | 95.90 426 | 94.38 291 | 99.26 33 | 98.34 258 | 91.99 378 | 92.76 391 | 97.13 355 | 88.31 277 | 98.52 351 | 89.48 419 | 87.70 427 | 96.52 412 |
|
| tpm2 | | | 94.19 351 | 93.76 347 | 95.46 385 | 97.23 348 | 89.04 444 | 97.31 401 | 96.85 441 | 87.08 456 | 96.21 270 | 96.79 396 | 83.75 381 | 98.74 331 | 92.43 359 | 96.23 304 | 98.59 281 |
|
| TESTMET0.1,1 | | | 94.18 354 | 93.69 352 | 95.63 378 | 96.92 369 | 89.12 442 | 96.91 435 | 94.78 481 | 93.17 332 | 94.88 298 | 96.45 412 | 78.52 425 | 98.92 308 | 93.09 327 | 98.50 190 | 98.85 243 |
|
| dp | | | 94.15 355 | 93.90 334 | 94.90 405 | 97.31 344 | 86.82 471 | 96.97 429 | 97.19 414 | 91.22 406 | 96.02 276 | 96.61 407 | 85.51 340 | 99.02 292 | 90.00 409 | 94.30 321 | 98.85 243 |
|
| ET-MVSNet_ETH3D | | | 94.13 356 | 92.98 374 | 97.58 229 | 98.22 243 | 96.20 168 | 97.31 401 | 95.37 471 | 94.53 252 | 79.56 495 | 97.63 318 | 86.51 317 | 97.53 450 | 96.91 175 | 90.74 387 | 99.02 227 |
|
| tpm | | | 94.13 356 | 93.80 342 | 95.12 395 | 96.50 395 | 87.91 464 | 97.44 386 | 95.89 466 | 92.62 355 | 96.37 265 | 96.30 418 | 84.13 372 | 98.30 385 | 93.24 322 | 91.66 376 | 99.14 203 |
|
| testing222 | | | 94.12 358 | 93.03 373 | 97.37 245 | 98.02 277 | 94.66 274 | 97.94 338 | 96.65 450 | 94.63 247 | 95.78 282 | 95.76 437 | 71.49 473 | 98.92 308 | 91.17 386 | 95.88 311 | 98.52 286 |
|
| IterMVS-SCA-FT | | | 94.11 359 | 93.87 337 | 94.85 409 | 97.98 287 | 90.56 413 | 97.18 414 | 98.11 315 | 93.75 293 | 92.58 397 | 97.48 328 | 83.97 375 | 97.41 453 | 92.48 358 | 91.30 379 | 96.58 400 |
|
| Anonymous20231211 | | | 94.10 360 | 93.26 369 | 96.61 306 | 99.11 123 | 94.28 296 | 99.01 89 | 98.88 78 | 86.43 465 | 92.81 389 | 97.57 322 | 81.66 396 | 98.68 337 | 94.83 261 | 89.02 415 | 96.88 357 |
|
| IterMVS | | | 94.09 361 | 93.85 339 | 94.80 413 | 97.99 281 | 90.35 418 | 97.18 414 | 98.12 312 | 93.68 304 | 92.46 404 | 97.34 339 | 84.05 373 | 97.41 453 | 92.51 356 | 91.33 378 | 96.62 390 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
| test-mter | | | 94.08 362 | 93.51 360 | 95.80 370 | 96.77 379 | 89.70 430 | 96.91 435 | 95.21 473 | 92.89 346 | 94.83 301 | 95.72 442 | 77.69 436 | 98.97 297 | 93.06 328 | 98.50 190 | 98.72 262 |
|
| test0.0.03 1 | | | 94.08 362 | 93.51 360 | 95.80 370 | 95.53 439 | 92.89 359 | 97.38 392 | 95.97 462 | 95.11 212 | 92.51 402 | 96.66 402 | 87.71 295 | 96.94 460 | 87.03 446 | 93.67 340 | 97.57 326 |
|
| v1240 | | | 94.06 364 | 93.29 368 | 96.34 338 | 96.03 418 | 93.90 311 | 98.44 262 | 98.17 305 | 91.18 408 | 94.13 335 | 97.01 376 | 86.05 330 | 98.42 362 | 89.13 425 | 89.50 406 | 96.70 379 |
|
| X-MVStestdata | | | 94.06 364 | 92.30 390 | 99.34 32 | 99.70 27 | 98.35 50 | 99.29 28 | 98.88 78 | 97.40 59 | 98.46 119 | 43.50 540 | 95.90 48 | 99.89 68 | 97.85 104 | 99.74 57 | 99.78 33 |
|
| DTE-MVSNet | | | 93.98 366 | 93.26 369 | 96.14 346 | 96.06 416 | 94.39 290 | 99.20 48 | 98.86 91 | 93.06 338 | 91.78 421 | 97.81 299 | 85.87 334 | 97.58 448 | 90.53 399 | 86.17 444 | 96.46 423 |
|
| pm-mvs1 | | | 93.94 367 | 93.06 372 | 96.59 309 | 96.49 396 | 95.16 248 | 98.95 105 | 98.03 332 | 92.32 368 | 91.08 430 | 97.84 294 | 84.54 363 | 98.41 369 | 92.16 361 | 86.13 447 | 96.19 435 |
|
| MS-PatchMatch | | | 93.84 368 | 93.63 354 | 94.46 427 | 96.18 409 | 89.45 437 | 97.76 363 | 98.27 278 | 92.23 371 | 92.13 417 | 97.49 327 | 79.50 418 | 98.69 334 | 89.75 412 | 99.38 133 | 95.25 455 |
|
| tfpnnormal | | | 93.66 369 | 92.70 380 | 96.55 317 | 96.94 368 | 95.94 187 | 98.97 98 | 99.19 35 | 91.04 409 | 91.38 427 | 97.34 339 | 84.94 351 | 98.61 342 | 85.45 458 | 89.02 415 | 95.11 459 |
|
| EU-MVSNet | | | 93.66 369 | 94.14 315 | 92.25 459 | 95.96 422 | 83.38 484 | 98.52 241 | 98.12 312 | 94.69 243 | 92.61 396 | 98.13 267 | 87.36 306 | 96.39 475 | 91.82 373 | 90.00 397 | 96.98 342 |
|
| our_test_3 | | | 93.65 371 | 93.30 367 | 94.69 415 | 95.45 443 | 89.68 432 | 96.91 435 | 97.65 361 | 91.97 379 | 91.66 424 | 96.88 389 | 89.67 232 | 97.93 427 | 88.02 438 | 91.49 377 | 96.48 421 |
|
| pmmvs5 | | | 93.65 371 | 92.97 375 | 95.68 375 | 95.49 440 | 92.37 368 | 98.20 295 | 97.28 404 | 89.66 433 | 92.58 397 | 97.26 345 | 82.14 390 | 98.09 407 | 93.18 325 | 90.95 386 | 96.58 400 |
|
| SSC-MVS3.2 | | | 93.59 373 | 93.13 371 | 94.97 402 | 96.81 378 | 89.71 429 | 97.95 335 | 98.49 204 | 94.59 249 | 93.50 366 | 96.91 387 | 77.74 435 | 98.37 376 | 91.69 377 | 90.47 390 | 96.83 365 |
|
| test_fmvs2 | | | 93.43 374 | 93.58 356 | 92.95 452 | 96.97 366 | 83.91 481 | 99.19 50 | 97.24 407 | 95.74 160 | 95.20 293 | 98.27 255 | 69.65 475 | 98.72 333 | 96.26 208 | 93.73 339 | 96.24 432 |
|
| tpm cat1 | | | 93.36 375 | 92.80 377 | 95.07 399 | 97.58 319 | 87.97 463 | 96.76 449 | 97.86 343 | 82.17 484 | 93.53 362 | 96.04 430 | 86.13 328 | 99.13 266 | 89.24 423 | 95.87 312 | 98.10 307 |
|
| JIA-IIPM | | | 93.35 376 | 92.49 386 | 95.92 361 | 96.48 397 | 90.65 408 | 95.01 480 | 96.96 431 | 85.93 469 | 96.08 274 | 87.33 505 | 87.70 298 | 98.78 329 | 91.35 383 | 95.58 316 | 98.34 296 |
|
| SixPastTwentyTwo | | | 93.34 377 | 92.86 376 | 94.75 414 | 95.67 432 | 89.41 439 | 98.75 177 | 96.67 448 | 93.89 285 | 90.15 441 | 98.25 258 | 80.87 406 | 98.27 390 | 90.90 395 | 90.64 388 | 96.57 402 |
|
| USDC | | | 93.33 378 | 92.71 379 | 95.21 392 | 96.83 376 | 90.83 404 | 96.91 435 | 97.50 381 | 93.84 288 | 90.72 433 | 98.14 266 | 77.69 436 | 98.82 325 | 89.51 418 | 93.21 355 | 95.97 441 |
|
| IB-MVS | | 91.98 17 | 93.27 379 | 91.97 394 | 97.19 251 | 97.47 330 | 93.41 331 | 97.09 422 | 95.99 461 | 93.32 325 | 92.47 403 | 95.73 440 | 78.06 431 | 99.53 183 | 94.59 279 | 82.98 459 | 98.62 276 |
| Christian Sormann, Mattia Rossi, Andreas Kuhn and Friedrich Fraundorfer: IB-MVS: An Iterative Algorithm for Deep Multi-View Stereo based on Binary Decisions. BMVC 2021 |
| MIMVSNet | | | 93.26 380 | 92.21 391 | 96.41 332 | 97.73 307 | 93.13 350 | 95.65 471 | 97.03 425 | 91.27 404 | 94.04 339 | 96.06 428 | 75.33 456 | 97.19 456 | 86.56 449 | 96.23 304 | 98.92 238 |
|
| ppachtmachnet_test | | | 93.22 381 | 92.63 381 | 94.97 402 | 95.45 443 | 90.84 403 | 96.88 443 | 97.88 342 | 90.60 415 | 92.08 418 | 97.26 345 | 88.08 286 | 97.86 434 | 85.12 461 | 90.33 391 | 96.22 433 |
|
| Patchmtry | | | 93.22 381 | 92.35 389 | 95.84 369 | 96.77 379 | 93.09 353 | 94.66 489 | 97.56 371 | 87.37 455 | 92.90 387 | 96.24 419 | 88.15 283 | 97.90 428 | 87.37 444 | 90.10 396 | 96.53 409 |
|
| testing3 | | | 93.19 383 | 92.48 387 | 95.30 391 | 98.07 267 | 92.27 369 | 98.64 212 | 97.17 415 | 93.94 284 | 93.98 342 | 97.04 371 | 67.97 480 | 96.01 479 | 88.40 432 | 97.14 265 | 97.63 323 |
|
| FMVSNet1 | | | 93.19 383 | 92.07 392 | 96.56 313 | 97.54 324 | 95.00 256 | 98.82 155 | 98.18 299 | 90.38 421 | 92.27 411 | 97.07 363 | 73.68 469 | 97.95 424 | 89.36 421 | 91.30 379 | 96.72 375 |
|
| LF4IMVS | | | 93.14 385 | 92.79 378 | 94.20 432 | 95.88 427 | 88.67 452 | 97.66 371 | 97.07 421 | 93.81 291 | 91.71 422 | 97.65 313 | 77.96 433 | 98.81 326 | 91.47 382 | 91.92 372 | 95.12 458 |
|
| mmtdpeth | | | 93.12 386 | 92.61 382 | 94.63 419 | 97.60 317 | 89.68 432 | 99.21 45 | 97.32 399 | 94.02 275 | 97.72 186 | 94.42 460 | 77.01 446 | 99.44 203 | 99.05 31 | 77.18 484 | 94.78 468 |
|
| testgi | | | 93.06 387 | 92.45 388 | 94.88 407 | 96.43 400 | 89.90 424 | 98.75 177 | 97.54 377 | 95.60 168 | 91.63 425 | 97.91 286 | 74.46 465 | 97.02 458 | 86.10 452 | 93.67 340 | 97.72 320 |
|
| PatchT | | | 93.06 387 | 91.97 394 | 96.35 337 | 96.69 385 | 92.67 365 | 94.48 493 | 97.08 419 | 86.62 463 | 97.08 223 | 92.23 487 | 87.94 290 | 97.90 428 | 78.89 488 | 96.69 280 | 98.49 288 |
|
| RPMNet | | | 92.81 389 | 91.34 400 | 97.24 247 | 97.00 363 | 93.43 329 | 94.96 482 | 98.80 114 | 82.27 483 | 96.93 231 | 92.12 488 | 86.98 311 | 99.82 97 | 76.32 495 | 96.65 282 | 98.46 290 |
|
| UWE-MVS-28 | | | 92.79 390 | 92.51 385 | 93.62 439 | 96.46 398 | 86.28 472 | 97.93 339 | 92.71 500 | 94.17 268 | 94.78 304 | 97.16 353 | 81.05 403 | 96.43 473 | 81.45 477 | 96.86 273 | 98.14 306 |
|
| myMVS_eth3d | | | 92.73 391 | 92.01 393 | 94.89 406 | 97.39 340 | 90.94 399 | 97.91 342 | 97.46 385 | 93.16 333 | 93.42 370 | 95.37 450 | 68.09 479 | 96.12 477 | 88.34 433 | 96.99 269 | 97.60 324 |
|
| TransMVSNet (Re) | | | 92.67 392 | 91.51 399 | 96.15 345 | 96.58 390 | 94.65 275 | 98.90 120 | 96.73 444 | 90.86 412 | 89.46 449 | 97.86 291 | 85.62 338 | 98.09 407 | 86.45 450 | 81.12 469 | 95.71 447 |
|
| ttmdpeth | | | 92.61 393 | 91.96 396 | 94.55 421 | 94.10 463 | 90.60 412 | 98.52 241 | 97.29 402 | 92.67 353 | 90.18 439 | 97.92 285 | 79.75 416 | 97.79 436 | 91.09 388 | 86.15 446 | 95.26 454 |
|
| Syy-MVS | | | 92.55 394 | 92.61 382 | 92.38 455 | 97.39 340 | 83.41 483 | 97.91 342 | 97.46 385 | 93.16 333 | 93.42 370 | 95.37 450 | 84.75 356 | 96.12 477 | 77.00 494 | 96.99 269 | 97.60 324 |
|
| K. test v3 | | | 92.55 394 | 91.91 397 | 94.48 425 | 95.64 433 | 89.24 440 | 99.07 72 | 94.88 480 | 94.04 273 | 86.78 469 | 97.59 320 | 77.64 439 | 97.64 444 | 92.08 363 | 89.43 408 | 96.57 402 |
|
| DSMNet-mixed | | | 92.52 396 | 92.58 384 | 92.33 456 | 94.15 461 | 82.65 487 | 98.30 281 | 94.26 488 | 89.08 443 | 92.65 395 | 95.73 440 | 85.01 350 | 95.76 481 | 86.24 451 | 97.76 244 | 98.59 281 |
|
| TinyColmap | | | 92.31 397 | 91.53 398 | 94.65 418 | 96.92 369 | 89.75 427 | 96.92 433 | 96.68 447 | 90.45 419 | 89.62 446 | 97.85 293 | 76.06 453 | 98.81 326 | 86.74 447 | 92.51 363 | 95.41 452 |
|
| gg-mvs-nofinetune | | | 92.21 398 | 90.58 407 | 97.13 256 | 96.75 382 | 95.09 252 | 95.85 466 | 89.40 510 | 85.43 474 | 94.50 310 | 81.98 511 | 80.80 408 | 98.40 375 | 92.16 361 | 98.33 214 | 97.88 313 |
|
| FMVSNet5 | | | 91.81 399 | 90.92 403 | 94.49 424 | 97.21 350 | 92.09 378 | 98.00 331 | 97.55 376 | 89.31 440 | 90.86 432 | 95.61 447 | 74.48 464 | 95.32 485 | 85.57 456 | 89.70 400 | 96.07 439 |
|
| pmmvs6 | | | 91.77 400 | 90.63 406 | 95.17 394 | 94.69 457 | 91.24 395 | 98.67 207 | 97.92 340 | 86.14 467 | 89.62 446 | 97.56 325 | 75.79 454 | 98.34 378 | 90.75 397 | 84.56 452 | 95.94 442 |
|
| Anonymous20231206 | | | 91.66 401 | 91.10 402 | 93.33 444 | 94.02 467 | 87.35 467 | 98.58 225 | 97.26 406 | 90.48 417 | 90.16 440 | 96.31 417 | 83.83 379 | 96.53 471 | 79.36 485 | 89.90 398 | 96.12 437 |
|
| Patchmatch-RL test | | | 91.49 402 | 90.85 404 | 93.41 442 | 91.37 491 | 84.40 478 | 92.81 500 | 95.93 465 | 91.87 382 | 87.25 465 | 94.87 456 | 88.99 256 | 96.53 471 | 92.54 355 | 82.00 463 | 99.30 163 |
|
| blended_shiyan8 | | | 91.42 403 | 89.89 415 | 96.01 352 | 91.50 488 | 93.30 341 | 97.48 384 | 97.83 345 | 86.93 458 | 92.57 399 | 92.37 485 | 82.46 388 | 98.13 400 | 92.86 340 | 74.99 492 | 96.61 391 |
|
| blended_shiyan6 | | | 91.37 404 | 89.84 416 | 95.98 358 | 91.49 489 | 93.28 342 | 97.48 384 | 97.83 345 | 86.93 458 | 92.43 405 | 92.36 486 | 82.44 389 | 98.06 412 | 92.74 345 | 74.82 495 | 96.59 396 |
|
| test_0402 | | | 91.32 405 | 90.27 410 | 94.48 425 | 96.60 389 | 91.12 396 | 98.50 249 | 97.22 408 | 86.10 468 | 88.30 461 | 96.98 378 | 77.65 438 | 97.99 422 | 78.13 490 | 92.94 357 | 94.34 471 |
|
| dtuonlycased | | | 91.29 406 | 91.26 401 | 91.36 463 | 95.63 434 | 84.25 480 | 96.93 432 | 97.21 410 | 92.16 375 | 88.34 460 | 96.47 410 | 79.56 417 | 95.18 488 | 87.37 444 | 87.70 427 | 94.64 469 |
|
| test_vis1_rt | | | 91.29 406 | 90.65 405 | 93.19 448 | 97.45 334 | 86.25 473 | 98.57 234 | 90.90 508 | 93.30 327 | 86.94 468 | 93.59 471 | 62.07 492 | 99.11 271 | 97.48 146 | 95.58 316 | 94.22 475 |
|
| PVSNet_0 | | 88.72 19 | 91.28 408 | 90.03 413 | 95.00 401 | 97.99 281 | 87.29 468 | 94.84 485 | 98.50 199 | 92.06 377 | 89.86 443 | 95.19 452 | 79.81 415 | 99.39 210 | 92.27 360 | 69.79 510 | 98.33 297 |
|
| mvs5depth | | | 91.23 409 | 90.17 411 | 94.41 429 | 92.09 483 | 89.79 426 | 95.26 478 | 96.50 453 | 90.73 413 | 91.69 423 | 97.06 367 | 76.12 452 | 98.62 341 | 88.02 438 | 84.11 455 | 94.82 465 |
|
| Anonymous20240521 | | | 91.18 410 | 90.44 408 | 93.42 441 | 93.70 468 | 88.47 456 | 98.94 108 | 97.56 371 | 88.46 449 | 89.56 448 | 95.08 455 | 77.15 444 | 96.97 459 | 83.92 468 | 89.55 404 | 94.82 465 |
|
| wanda-best-256-512 | | | 91.17 411 | 89.60 420 | 95.88 365 | 91.33 492 | 92.99 356 | 96.89 440 | 97.82 348 | 86.89 461 | 92.36 407 | 91.75 492 | 81.83 392 | 98.06 412 | 92.75 342 | 74.82 495 | 96.59 396 |
|
| FE-blended-shiyan7 | | | 91.17 411 | 89.60 420 | 95.88 365 | 91.33 492 | 92.99 356 | 96.89 440 | 97.82 348 | 86.89 461 | 92.36 407 | 91.75 492 | 81.83 392 | 98.06 412 | 92.75 342 | 74.82 495 | 96.59 396 |
|
| EG-PatchMatch MVS | | | 91.13 413 | 90.12 412 | 94.17 434 | 94.73 456 | 89.00 445 | 98.13 312 | 97.81 352 | 89.22 441 | 85.32 479 | 96.46 411 | 67.71 481 | 98.42 362 | 87.89 442 | 93.82 338 | 95.08 460 |
|
| TDRefinement | | | 91.06 414 | 89.68 418 | 95.21 392 | 85.35 518 | 91.49 391 | 98.51 248 | 97.07 421 | 91.47 392 | 88.83 456 | 97.84 294 | 77.31 440 | 99.09 276 | 92.79 341 | 77.98 482 | 95.04 462 |
|
| gbinet_0.2-2-1-0.02 | | | 91.03 415 | 89.37 426 | 96.01 352 | 91.39 490 | 93.41 331 | 97.19 412 | 97.82 348 | 87.00 457 | 92.18 415 | 91.87 491 | 78.97 422 | 98.04 416 | 93.13 326 | 74.75 499 | 96.60 393 |
|
| sc_t1 | | | 91.01 416 | 89.39 422 | 95.85 368 | 95.99 419 | 90.39 417 | 98.43 264 | 97.64 363 | 78.79 492 | 92.20 414 | 97.94 283 | 66.00 485 | 98.60 345 | 91.59 380 | 85.94 448 | 98.57 284 |
|
| UnsupCasMVSNet_eth | | | 90.99 417 | 89.92 414 | 94.19 433 | 94.08 464 | 89.83 425 | 97.13 421 | 98.67 150 | 93.69 302 | 85.83 475 | 96.19 424 | 75.15 459 | 96.74 464 | 89.14 424 | 79.41 476 | 96.00 440 |
|
| 0.4-1-1-0.1 | | | 90.89 418 | 88.97 432 | 96.67 297 | 94.15 461 | 92.76 364 | 95.28 477 | 95.03 478 | 89.11 442 | 90.43 437 | 89.57 500 | 75.41 455 | 99.04 285 | 94.70 269 | 77.06 485 | 98.20 303 |
|
| test20.03 | | | 90.89 418 | 90.38 409 | 92.43 454 | 93.48 471 | 88.14 462 | 98.33 273 | 97.56 371 | 93.40 322 | 87.96 462 | 96.71 400 | 80.69 409 | 94.13 495 | 79.15 486 | 86.17 444 | 95.01 464 |
|
| usedtu_blend_shiyan5 | | | 90.87 420 | 89.15 427 | 96.01 352 | 91.33 492 | 93.35 338 | 98.12 313 | 97.36 397 | 81.93 486 | 92.36 407 | 91.75 492 | 81.83 392 | 98.09 407 | 92.88 338 | 74.82 495 | 96.59 396 |
|
| blend_shiyan4 | | | 90.76 421 | 89.01 430 | 95.99 355 | 91.69 487 | 93.35 338 | 97.44 386 | 97.83 345 | 86.93 458 | 92.23 412 | 91.98 489 | 75.19 458 | 98.09 407 | 92.88 338 | 74.96 493 | 96.52 412 |
|
| MDA-MVSNet_test_wron | | | 90.71 422 | 89.38 424 | 94.68 416 | 94.83 453 | 90.78 405 | 97.19 412 | 97.46 385 | 87.60 453 | 72.41 503 | 95.72 442 | 86.51 317 | 96.71 467 | 85.92 454 | 86.80 441 | 96.56 404 |
|
| YYNet1 | | | 90.70 423 | 89.39 422 | 94.62 420 | 94.79 455 | 90.65 408 | 97.20 409 | 97.46 385 | 87.54 454 | 72.54 502 | 95.74 438 | 86.51 317 | 96.66 468 | 86.00 453 | 86.76 442 | 96.54 407 |
|
| ArgMatch-SfM | | | 90.55 424 | 89.69 417 | 93.14 449 | 95.91 425 | 86.12 474 | 97.20 409 | 96.81 443 | 92.91 345 | 91.39 426 | 96.95 383 | 65.65 487 | 97.72 441 | 88.03 437 | 82.36 460 | 95.57 450 |
|
| 0.4-1-1-0.2 | | | 90.43 425 | 88.45 436 | 96.38 335 | 93.34 473 | 92.12 374 | 93.88 498 | 95.04 477 | 88.62 448 | 90.00 442 | 88.31 503 | 75.31 457 | 99.03 288 | 94.61 276 | 76.91 487 | 98.01 312 |
|
| KD-MVS_self_test | | | 90.38 426 | 89.38 424 | 93.40 443 | 92.85 478 | 88.94 448 | 97.95 335 | 97.94 338 | 90.35 422 | 90.25 438 | 93.96 468 | 79.82 414 | 95.94 480 | 84.62 467 | 76.69 489 | 95.33 453 |
|
| pmmvs-eth3d | | | 90.36 427 | 89.05 429 | 94.32 431 | 91.10 496 | 92.12 374 | 97.63 376 | 96.95 432 | 88.86 445 | 84.91 480 | 93.13 477 | 78.32 427 | 96.74 464 | 88.70 429 | 81.81 465 | 94.09 478 |
|
| 0.3-1-1-0.015 | | | 90.29 428 | 88.21 440 | 96.51 320 | 93.56 470 | 92.44 367 | 94.41 494 | 95.03 478 | 88.71 446 | 89.20 451 | 88.50 502 | 73.12 471 | 99.04 285 | 94.67 272 | 76.70 488 | 98.05 308 |
|
| FE-MVSNET2 | | | 90.29 428 | 88.94 433 | 94.36 430 | 90.48 501 | 92.27 369 | 98.45 256 | 97.82 348 | 91.59 390 | 84.90 481 | 93.10 478 | 73.92 467 | 96.42 474 | 87.92 441 | 82.26 461 | 94.39 470 |
|
| tt0320 | | | 90.26 430 | 88.73 435 | 94.86 408 | 96.12 413 | 90.62 410 | 98.17 305 | 97.63 364 | 77.46 496 | 89.68 445 | 96.04 430 | 69.19 477 | 97.79 436 | 88.98 426 | 85.29 450 | 96.16 436 |
|
| CL-MVSNet_self_test | | | 90.11 431 | 89.14 428 | 93.02 450 | 91.86 485 | 88.23 461 | 96.51 457 | 98.07 325 | 90.49 416 | 90.49 436 | 94.41 461 | 84.75 356 | 95.34 484 | 80.79 479 | 74.95 494 | 95.50 451 |
|
| new_pmnet | | | 90.06 432 | 89.00 431 | 93.22 447 | 94.18 459 | 88.32 459 | 96.42 459 | 96.89 437 | 86.19 466 | 85.67 476 | 93.62 470 | 77.18 443 | 97.10 457 | 81.61 476 | 89.29 410 | 94.23 474 |
|
| MDA-MVSNet-bldmvs | | | 89.97 433 | 88.35 438 | 94.83 412 | 95.21 447 | 91.34 392 | 97.64 373 | 97.51 380 | 88.36 451 | 71.17 504 | 96.13 426 | 79.22 420 | 96.63 469 | 83.65 469 | 86.27 443 | 96.52 412 |
|
| tt0320-xc | | | 89.79 434 | 88.11 441 | 94.84 411 | 96.19 408 | 90.61 411 | 98.16 306 | 97.22 408 | 77.35 497 | 88.75 458 | 96.70 401 | 65.94 486 | 97.63 445 | 89.31 422 | 83.39 457 | 96.28 431 |
|
| CMPMVS |  | 66.06 21 | 89.70 435 | 89.67 419 | 89.78 467 | 93.19 476 | 76.56 496 | 97.00 428 | 98.35 255 | 80.97 487 | 81.57 488 | 97.75 302 | 74.75 462 | 98.61 342 | 89.85 410 | 93.63 342 | 94.17 476 |
| M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
| MIMVSNet1 | | | 89.67 436 | 88.28 439 | 93.82 436 | 92.81 479 | 91.08 397 | 98.01 329 | 97.45 389 | 87.95 452 | 87.90 463 | 95.87 436 | 67.63 482 | 94.56 493 | 78.73 489 | 88.18 423 | 95.83 445 |
|
| KD-MVS_2432*1600 | | | 89.61 437 | 87.96 445 | 94.54 422 | 94.06 465 | 91.59 389 | 95.59 472 | 97.63 364 | 89.87 429 | 88.95 453 | 94.38 463 | 78.28 428 | 96.82 462 | 84.83 463 | 68.05 511 | 95.21 456 |
|
| miper_refine_blended | | | 89.61 437 | 87.96 445 | 94.54 422 | 94.06 465 | 91.59 389 | 95.59 472 | 97.63 364 | 89.87 429 | 88.95 453 | 94.38 463 | 78.28 428 | 96.82 462 | 84.83 463 | 68.05 511 | 95.21 456 |
|
| MVStest1 | | | 89.53 439 | 87.99 444 | 94.14 435 | 94.39 458 | 90.42 415 | 98.25 288 | 96.84 442 | 82.81 480 | 81.18 490 | 97.33 341 | 77.09 445 | 96.94 460 | 85.27 460 | 78.79 477 | 95.06 461 |
|
| MVS-HIRNet | | | 89.46 440 | 88.40 437 | 92.64 453 | 97.58 319 | 82.15 488 | 94.16 497 | 93.05 499 | 75.73 500 | 90.90 431 | 82.52 509 | 79.42 419 | 98.33 380 | 83.53 470 | 98.68 173 | 97.43 327 |
|
| OpenMVS_ROB |  | 86.42 20 | 89.00 441 | 87.43 449 | 93.69 438 | 93.08 477 | 89.42 438 | 97.91 342 | 96.89 437 | 78.58 493 | 85.86 474 | 94.69 457 | 69.48 476 | 98.29 388 | 77.13 493 | 93.29 354 | 93.36 488 |
|
| mvsany_test3 | | | 88.80 442 | 88.04 442 | 91.09 464 | 89.78 506 | 81.57 490 | 97.83 357 | 95.49 470 | 93.81 291 | 87.53 464 | 93.95 469 | 56.14 495 | 97.43 452 | 94.68 270 | 83.13 458 | 94.26 472 |
|
| FE-MVSNET | | | 88.56 443 | 87.09 450 | 92.99 451 | 89.93 505 | 89.99 423 | 98.15 309 | 95.59 468 | 88.42 450 | 84.87 482 | 92.90 480 | 74.82 461 | 94.99 490 | 77.88 491 | 81.21 468 | 93.99 481 |
|
| new-patchmatchnet | | | 88.50 444 | 87.45 448 | 91.67 461 | 90.31 503 | 85.89 475 | 97.16 419 | 97.33 398 | 89.47 436 | 83.63 485 | 92.77 482 | 76.38 449 | 95.06 489 | 82.70 472 | 77.29 483 | 94.06 480 |
|
| APD_test1 | | | 88.22 445 | 88.01 443 | 88.86 471 | 95.98 420 | 74.66 504 | 97.21 408 | 96.44 455 | 83.96 479 | 86.66 471 | 97.90 287 | 60.95 493 | 97.84 435 | 82.73 471 | 90.23 394 | 94.09 478 |
|
| PM-MVS | | | 87.77 446 | 86.55 452 | 91.40 462 | 91.03 498 | 83.36 485 | 96.92 433 | 95.18 475 | 91.28 403 | 86.48 473 | 93.42 473 | 53.27 497 | 96.74 464 | 89.43 420 | 81.97 464 | 94.11 477 |
|
| dmvs_testset | | | 87.64 447 | 88.93 434 | 83.79 483 | 95.25 446 | 63.36 517 | 97.20 409 | 91.17 505 | 93.07 337 | 85.64 477 | 95.98 435 | 85.30 347 | 91.52 505 | 69.42 504 | 87.33 433 | 96.49 419 |
|
| test_fmvs3 | | | 87.17 448 | 87.06 451 | 87.50 474 | 91.21 495 | 75.66 499 | 99.05 76 | 96.61 451 | 92.79 350 | 88.85 455 | 92.78 481 | 43.72 504 | 93.49 497 | 93.95 302 | 84.56 452 | 93.34 489 |
|
| UnsupCasMVSNet_bld | | | 87.17 448 | 85.12 456 | 93.31 445 | 91.94 484 | 88.77 449 | 94.92 484 | 98.30 275 | 84.30 478 | 82.30 486 | 90.04 498 | 63.96 490 | 97.25 455 | 85.85 455 | 74.47 502 | 93.93 483 |
|
| N_pmnet | | | 87.12 450 | 87.77 447 | 85.17 478 | 95.46 442 | 61.92 520 | 97.37 394 | 70.66 531 | 85.83 470 | 88.73 459 | 96.04 430 | 85.33 345 | 97.76 439 | 80.02 480 | 90.48 389 | 95.84 444 |
|
| pmmvs3 | | | 86.67 451 | 84.86 457 | 92.11 460 | 88.16 510 | 87.19 470 | 96.63 453 | 94.75 482 | 79.88 489 | 87.22 466 | 92.75 483 | 66.56 484 | 95.20 487 | 81.24 478 | 76.56 490 | 93.96 482 |
|
| test_f | | | 86.07 452 | 85.39 454 | 88.10 472 | 89.28 508 | 75.57 500 | 97.73 366 | 96.33 457 | 89.41 439 | 85.35 478 | 91.56 495 | 43.31 506 | 95.53 482 | 91.32 384 | 84.23 454 | 93.21 490 |
|
| MASt3R-SfM | | | 85.54 453 | 85.89 453 | 84.50 481 | 90.13 504 | 66.13 515 | 92.89 499 | 95.33 472 | 85.73 472 | 88.77 457 | 96.36 416 | 52.50 498 | 94.89 491 | 86.66 448 | 84.65 451 | 92.50 494 |
|
| WB-MVS | | | 84.86 454 | 85.33 455 | 83.46 484 | 89.48 507 | 69.56 509 | 98.19 298 | 96.42 456 | 89.55 435 | 81.79 487 | 94.67 458 | 84.80 354 | 90.12 506 | 52.44 512 | 80.64 473 | 90.69 498 |
|
| usedtu_dtu_shiyan2 | | | 84.80 455 | 82.31 460 | 92.27 458 | 86.38 515 | 85.55 476 | 97.77 362 | 96.56 452 | 78.34 494 | 83.90 484 | 93.50 472 | 54.16 496 | 95.32 485 | 77.55 492 | 72.62 503 | 95.92 443 |
|
| DenseAffine | | | 84.37 456 | 82.38 459 | 90.31 466 | 94.17 460 | 82.89 486 | 94.98 481 | 94.23 489 | 82.16 485 | 79.68 494 | 94.33 466 | 46.28 500 | 94.25 494 | 80.01 481 | 75.62 491 | 93.78 486 |
|
| SSC-MVS | | | 84.27 457 | 84.71 458 | 82.96 489 | 89.19 509 | 68.83 510 | 98.08 321 | 96.30 458 | 89.04 444 | 81.37 489 | 94.47 459 | 84.60 361 | 89.89 507 | 49.80 515 | 79.52 475 | 90.15 499 |
|
| RoMa-SfM | | | 83.81 458 | 82.08 461 | 89.00 470 | 93.33 474 | 79.94 493 | 95.51 474 | 92.48 501 | 79.75 490 | 79.89 493 | 95.69 445 | 46.23 501 | 93.20 500 | 78.90 487 | 76.93 486 | 93.87 484 |
|
| LoFTR | | | 83.16 459 | 80.62 463 | 90.80 465 | 92.28 482 | 80.01 492 | 95.35 476 | 94.33 486 | 80.44 488 | 70.79 505 | 92.93 479 | 46.38 499 | 98.17 396 | 75.01 497 | 78.03 481 | 94.24 473 |
|
| dongtai | | | 82.47 460 | 81.88 462 | 84.22 482 | 95.19 448 | 76.03 497 | 94.59 492 | 74.14 523 | 82.63 481 | 87.19 467 | 96.09 427 | 64.10 489 | 87.85 511 | 58.91 510 | 84.11 455 | 88.78 505 |
|
| DKM | | | 81.60 461 | 79.57 464 | 87.68 473 | 92.65 481 | 78.36 494 | 94.65 490 | 91.17 505 | 79.69 491 | 76.11 497 | 93.98 467 | 37.88 515 | 91.54 504 | 79.64 484 | 70.38 507 | 93.15 491 |
|
| MatchFormer | | | 80.21 462 | 77.20 470 | 89.24 469 | 91.79 486 | 77.21 495 | 95.16 479 | 93.59 494 | 72.46 504 | 67.08 508 | 89.93 499 | 43.14 507 | 97.90 428 | 67.07 506 | 74.55 501 | 92.61 493 |
|
| test_vis3_rt | | | 79.22 463 | 77.40 469 | 84.67 479 | 86.44 514 | 74.85 503 | 97.66 371 | 81.43 516 | 84.98 475 | 67.12 507 | 81.91 512 | 28.09 527 | 97.60 446 | 88.96 427 | 80.04 474 | 81.55 515 |
|
| test_method | | | 79.03 464 | 78.17 465 | 81.63 490 | 86.06 516 | 54.40 531 | 82.75 519 | 96.89 437 | 39.54 524 | 80.98 491 | 95.57 448 | 58.37 494 | 94.73 492 | 84.74 466 | 78.61 478 | 95.75 446 |
|
| testf1 | | | 79.02 465 | 77.70 466 | 82.99 487 | 88.10 511 | 66.90 513 | 94.67 487 | 93.11 496 | 71.08 506 | 74.02 499 | 93.41 474 | 34.15 520 | 93.25 498 | 72.25 501 | 78.50 479 | 88.82 503 |
|
| APD_test2 | | | 79.02 465 | 77.70 466 | 82.99 487 | 88.10 511 | 66.90 513 | 94.67 487 | 93.11 496 | 71.08 506 | 74.02 499 | 93.41 474 | 34.15 520 | 93.25 498 | 72.25 501 | 78.50 479 | 88.82 503 |
|
| LCM-MVSNet | | | 78.70 467 | 76.24 473 | 86.08 476 | 77.26 533 | 71.99 506 | 94.34 495 | 96.72 445 | 61.62 510 | 76.53 496 | 89.33 501 | 33.91 523 | 92.78 502 | 81.85 475 | 74.60 500 | 93.46 487 |
|
| kuosan | | | 78.45 468 | 77.69 468 | 80.72 491 | 92.73 480 | 75.32 501 | 94.63 491 | 74.51 522 | 75.96 498 | 80.87 492 | 93.19 476 | 63.23 491 | 79.99 520 | 42.56 522 | 81.56 467 | 86.85 512 |
|
| Gipuma |  | | 78.40 469 | 76.75 472 | 83.38 485 | 95.54 437 | 80.43 491 | 79.42 520 | 97.40 393 | 64.67 509 | 73.46 501 | 80.82 513 | 45.65 503 | 93.14 501 | 66.32 507 | 87.43 431 | 76.56 518 |
| S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
| PMMVS2 | | | 77.95 470 | 75.44 474 | 85.46 477 | 82.54 522 | 74.95 502 | 94.23 496 | 93.08 498 | 72.80 502 | 74.68 498 | 87.38 504 | 36.36 518 | 91.56 503 | 73.95 499 | 63.94 513 | 89.87 500 |
|
| FPMVS | | | 77.62 471 | 77.14 471 | 79.05 494 | 79.25 528 | 60.97 522 | 95.79 467 | 95.94 464 | 65.96 508 | 67.93 506 | 94.40 462 | 37.73 516 | 88.88 510 | 68.83 505 | 88.46 420 | 87.29 509 |
|
| ELoFTR | | | 75.37 472 | 72.33 475 | 84.51 480 | 84.48 520 | 68.41 512 | 91.57 504 | 88.78 511 | 73.84 501 | 62.84 512 | 90.14 497 | 27.38 528 | 94.11 496 | 71.45 503 | 60.46 516 | 91.00 496 |
|
| EGC-MVSNET | | | 75.22 473 | 69.54 477 | 92.28 457 | 94.81 454 | 89.58 434 | 97.64 373 | 96.50 453 | 1.82 545 | 5.57 546 | 95.74 438 | 68.21 478 | 96.26 476 | 73.80 500 | 91.71 374 | 90.99 497 |
|
| PMatch-SfM | | | 73.49 474 | 70.32 476 | 83.00 486 | 85.01 519 | 68.63 511 | 90.17 511 | 79.05 519 | 71.64 505 | 63.27 511 | 91.93 490 | 17.27 536 | 89.10 509 | 74.59 498 | 59.95 517 | 91.26 495 |
|
| PDCNetPlus | | | 71.79 475 | 69.26 478 | 79.39 493 | 85.67 517 | 69.92 508 | 90.34 509 | 62.32 533 | 72.62 503 | 65.36 510 | 90.26 496 | 39.20 512 | 86.38 512 | 75.32 496 | 42.24 526 | 81.88 514 |
|
| SP-DiffGlue | | | 70.13 476 | 69.16 479 | 73.04 503 | 77.73 531 | 57.48 526 | 88.44 514 | 74.91 521 | 50.96 516 | 66.64 509 | 85.99 506 | 41.44 508 | 73.46 526 | 64.21 508 | 72.15 504 | 88.19 508 |
|
| ANet_high | | | 69.08 477 | 65.37 484 | 80.22 492 | 65.99 546 | 71.96 507 | 90.91 508 | 90.09 509 | 82.62 482 | 49.93 526 | 78.39 520 | 29.36 526 | 81.75 517 | 62.49 509 | 38.52 530 | 86.95 511 |
|
| tmp_tt | | | 68.90 478 | 66.97 480 | 74.68 496 | 50.78 548 | 59.95 523 | 87.13 516 | 83.47 515 | 38.80 525 | 62.21 513 | 96.23 421 | 64.70 488 | 76.91 522 | 88.91 428 | 30.49 534 | 87.19 510 |
|
| SP-LightGlue | | | 68.17 479 | 66.54 482 | 73.06 502 | 91.08 497 | 55.79 527 | 91.09 506 | 72.78 525 | 48.55 520 | 60.77 515 | 79.95 517 | 38.55 513 | 74.10 524 | 45.47 517 | 70.64 506 | 89.28 501 |
|
| SP-SuperGlue | | | 68.14 480 | 66.58 481 | 72.81 504 | 90.65 500 | 55.53 528 | 91.37 505 | 73.04 524 | 49.07 519 | 61.03 514 | 80.24 516 | 38.13 514 | 74.06 525 | 45.46 518 | 70.26 508 | 88.84 502 |
|
| ALIKED-LG | | | 67.40 481 | 65.16 485 | 74.11 498 | 93.21 475 | 62.30 518 | 88.98 512 | 71.99 526 | 55.04 511 | 59.47 518 | 82.33 510 | 39.27 511 | 85.49 514 | 32.61 528 | 63.58 515 | 74.55 519 |
|
| SP-NN | | | 67.39 482 | 65.69 483 | 72.49 506 | 90.68 499 | 55.34 529 | 90.33 510 | 71.01 529 | 46.77 522 | 59.09 519 | 79.83 518 | 37.26 517 | 73.38 527 | 44.68 519 | 71.51 505 | 88.74 506 |
|
| ALIKED-NN | | | 66.93 483 | 64.81 486 | 73.32 500 | 93.41 472 | 62.03 519 | 87.55 515 | 71.25 527 | 50.21 517 | 59.98 517 | 82.57 508 | 39.72 510 | 84.03 516 | 34.94 526 | 63.64 514 | 73.90 520 |
|
| SP-MNN | | | 66.66 484 | 64.70 487 | 72.53 505 | 90.32 502 | 55.08 530 | 91.01 507 | 71.05 528 | 44.81 523 | 56.48 522 | 79.62 519 | 35.87 519 | 74.11 523 | 43.13 521 | 69.98 509 | 88.39 507 |
|
| PMVS |  | 61.03 23 | 65.95 485 | 63.57 489 | 73.09 501 | 57.90 547 | 51.22 533 | 85.05 518 | 93.93 493 | 54.45 512 | 44.32 528 | 83.57 507 | 13.22 542 | 89.15 508 | 58.68 511 | 81.00 470 | 78.91 517 |
| Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
| ALIKED-MNN | | | 65.35 486 | 62.68 491 | 73.35 499 | 93.70 468 | 61.07 521 | 88.63 513 | 70.76 530 | 47.76 521 | 57.06 521 | 80.59 514 | 34.03 522 | 85.39 515 | 32.73 527 | 58.87 518 | 73.59 521 |
|
| E-PMN | | | 64.94 487 | 64.25 488 | 67.02 507 | 82.28 523 | 59.36 524 | 91.83 503 | 85.63 513 | 52.69 513 | 60.22 516 | 77.28 521 | 41.06 509 | 80.12 519 | 46.15 516 | 41.14 527 | 61.57 524 |
|
| EMVS | | | 64.07 488 | 63.26 490 | 66.53 508 | 81.73 524 | 58.81 525 | 91.85 502 | 84.75 514 | 51.93 515 | 59.09 519 | 75.13 524 | 43.32 505 | 79.09 521 | 42.03 523 | 39.47 528 | 61.69 523 |
|
| MVE |  | 62.14 22 | 63.28 489 | 59.38 492 | 74.99 495 | 74.33 538 | 65.47 516 | 85.55 517 | 80.50 517 | 52.02 514 | 51.10 524 | 75.00 525 | 10.91 547 | 80.50 518 | 51.60 514 | 53.40 520 | 78.99 516 |
| Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
| GLUNet-SfM | | | 61.12 490 | 56.63 493 | 74.58 497 | 69.78 543 | 53.99 532 | 78.71 521 | 76.81 520 | 49.09 518 | 49.42 527 | 80.47 515 | 24.43 529 | 85.82 513 | 51.80 513 | 29.17 535 | 83.92 513 |
|
| XFeat-NN | | | 56.16 491 | 56.10 494 | 56.36 510 | 72.10 540 | 42.54 543 | 76.45 523 | 61.18 534 | 38.16 526 | 53.08 523 | 76.48 522 | 32.95 524 | 65.67 529 | 44.15 520 | 50.31 523 | 60.87 525 |
|
| XFeat-MNN | | | 55.84 492 | 55.19 495 | 57.82 509 | 69.33 544 | 43.25 538 | 78.25 522 | 62.64 532 | 37.53 527 | 50.90 525 | 76.32 523 | 32.43 525 | 68.13 528 | 42.00 524 | 47.26 525 | 62.07 522 |
|
| SIFT-NN | | | 49.27 493 | 49.25 496 | 49.32 511 | 83.88 521 | 45.20 534 | 74.57 524 | 53.44 535 | 32.44 528 | 42.88 529 | 64.93 526 | 20.60 530 | 61.35 530 | 16.59 530 | 53.96 519 | 41.40 526 |
|
| SIFT-MNN | | | 47.78 494 | 47.47 497 | 48.69 512 | 81.04 525 | 44.17 535 | 73.46 525 | 53.36 536 | 31.82 529 | 38.54 530 | 63.76 527 | 18.11 534 | 61.27 531 | 15.96 532 | 51.17 521 | 40.64 529 |
|
| SIFT-NN-NCMNet | | | 47.55 495 | 47.18 498 | 48.67 513 | 79.60 527 | 44.09 536 | 73.43 526 | 52.90 537 | 31.82 529 | 38.38 531 | 63.56 530 | 18.47 531 | 61.19 532 | 15.91 533 | 50.50 522 | 40.74 528 |
|
| SIFT-NN-CMatch | | | 45.31 496 | 44.49 499 | 47.75 514 | 76.46 534 | 42.98 541 | 70.17 530 | 49.20 540 | 31.63 532 | 37.94 532 | 63.68 529 | 18.19 533 | 59.32 535 | 15.91 533 | 37.27 531 | 40.95 527 |
|
| SIFT-NCM-Cal | | | 44.98 497 | 44.20 500 | 47.33 515 | 79.81 526 | 43.05 539 | 72.12 527 | 49.31 539 | 30.81 534 | 25.90 538 | 61.87 535 | 15.80 537 | 60.28 533 | 14.09 541 | 48.07 524 | 38.66 532 |
|
| SIFT-NN-UMatch | | | 44.69 498 | 43.84 501 | 47.24 516 | 74.56 537 | 42.59 542 | 71.89 528 | 49.78 538 | 31.80 531 | 29.27 535 | 63.70 528 | 18.26 532 | 59.43 534 | 15.86 535 | 39.43 529 | 39.71 530 |
|
| SIFT-ConvMatch | | | 43.26 499 | 42.18 503 | 46.50 517 | 78.34 530 | 43.05 539 | 68.67 532 | 47.17 541 | 31.06 533 | 30.28 534 | 62.56 532 | 15.43 538 | 58.95 537 | 14.92 537 | 31.22 533 | 37.51 534 |
|
| SIFT-NN-PointCN | | | 43.09 500 | 42.61 502 | 44.51 520 | 72.48 539 | 37.95 547 | 70.10 531 | 46.55 542 | 30.16 538 | 34.48 533 | 61.93 534 | 18.02 535 | 55.90 540 | 15.40 536 | 34.41 532 | 39.69 531 |
|
| SIFT-UMatch | | | 42.35 501 | 41.04 504 | 46.29 518 | 76.09 535 | 41.80 544 | 70.21 529 | 45.21 543 | 30.75 535 | 27.33 537 | 62.62 531 | 15.13 539 | 59.11 536 | 14.72 538 | 27.30 536 | 37.95 533 |
|
| SIFT-CM-Cal | | | 41.25 502 | 40.03 505 | 44.88 519 | 77.37 532 | 41.08 545 | 65.71 536 | 41.18 545 | 30.42 537 | 28.83 536 | 61.42 536 | 14.88 540 | 56.40 538 | 14.13 540 | 26.37 538 | 37.16 535 |
|
| SIFT-UM-Cal | | | 39.93 503 | 38.61 506 | 43.88 521 | 76.08 536 | 39.30 546 | 68.10 533 | 37.89 546 | 30.49 536 | 22.74 540 | 62.27 533 | 13.89 541 | 56.16 539 | 14.17 539 | 21.90 539 | 36.17 536 |
|
| SIFT-PointCN | | | 37.89 504 | 37.50 507 | 39.07 522 | 71.45 541 | 31.31 548 | 66.27 535 | 41.69 544 | 27.82 539 | 22.63 541 | 56.73 538 | 12.00 545 | 50.56 542 | 12.18 543 | 26.71 537 | 35.34 537 |
|
| SIFT-PCN-Cal | | | 36.85 505 | 36.40 508 | 38.19 523 | 71.43 542 | 30.42 549 | 64.34 537 | 37.72 547 | 27.48 540 | 22.98 539 | 57.03 537 | 12.99 543 | 51.22 541 | 12.51 542 | 21.13 540 | 32.92 538 |
|
| SIFT-NCMNet | | | 32.45 506 | 31.84 510 | 34.30 524 | 68.74 545 | 28.10 550 | 57.85 538 | 24.54 548 | 27.25 541 | 19.31 542 | 52.59 539 | 9.75 548 | 45.69 543 | 10.92 544 | 15.56 542 | 29.13 539 |
|
| wuyk23d | | | 30.17 507 | 30.18 511 | 30.16 525 | 78.61 529 | 43.29 537 | 66.79 534 | 14.21 549 | 17.31 542 | 14.82 545 | 11.93 545 | 11.55 546 | 41.43 544 | 37.08 525 | 19.30 541 | 5.76 542 |
|
| cdsmvs_eth3d_5k | | | 23.98 508 | 31.98 509 | 0.00 528 | 0.00 551 | 0.00 553 | 0.00 539 | 98.59 171 | 0.00 546 | 0.00 547 | 98.61 214 | 90.60 204 | 0.00 547 | 0.00 545 | 0.00 545 | 0.00 543 |
|
| testmvs | | | 21.48 509 | 24.95 512 | 11.09 527 | 14.89 549 | 6.47 552 | 96.56 455 | 9.87 550 | 7.55 543 | 17.93 543 | 39.02 541 | 9.43 549 | 5.90 546 | 16.56 531 | 12.72 543 | 20.91 541 |
|
| test123 | | | 20.95 510 | 23.72 513 | 12.64 526 | 13.54 550 | 8.19 551 | 96.55 456 | 6.13 551 | 7.48 544 | 16.74 544 | 37.98 542 | 12.97 544 | 6.05 545 | 16.69 529 | 5.43 544 | 23.68 540 |
|
| ab-mvs-re | | | 8.20 511 | 10.94 514 | 0.00 528 | 0.00 551 | 0.00 553 | 0.00 539 | 0.00 552 | 0.00 546 | 0.00 547 | 98.43 233 | 0.00 550 | 0.00 547 | 0.00 545 | 0.00 545 | 0.00 543 |
|
| pcd_1.5k_mvsjas | | | 7.88 512 | 10.50 515 | 0.00 528 | 0.00 551 | 0.00 553 | 0.00 539 | 0.00 552 | 0.00 546 | 0.00 547 | 0.00 546 | 94.51 91 | 0.00 547 | 0.00 545 | 0.00 545 | 0.00 543 |
|
| mmdepth | | | 0.00 513 | 0.00 516 | 0.00 528 | 0.00 551 | 0.00 553 | 0.00 539 | 0.00 552 | 0.00 546 | 0.00 547 | 0.00 546 | 0.00 550 | 0.00 547 | 0.00 545 | 0.00 545 | 0.00 543 |
|
| monomultidepth | | | 0.00 513 | 0.00 516 | 0.00 528 | 0.00 551 | 0.00 553 | 0.00 539 | 0.00 552 | 0.00 546 | 0.00 547 | 0.00 546 | 0.00 550 | 0.00 547 | 0.00 545 | 0.00 545 | 0.00 543 |
|
| test_blank | | | 0.00 513 | 0.00 516 | 0.00 528 | 0.00 551 | 0.00 553 | 0.00 539 | 0.00 552 | 0.00 546 | 0.00 547 | 0.00 546 | 0.00 550 | 0.00 547 | 0.00 545 | 0.00 545 | 0.00 543 |
|
| uanet_test | | | 0.00 513 | 0.00 516 | 0.00 528 | 0.00 551 | 0.00 553 | 0.00 539 | 0.00 552 | 0.00 546 | 0.00 547 | 0.00 546 | 0.00 550 | 0.00 547 | 0.00 545 | 0.00 545 | 0.00 543 |
|
| DCPMVS | | | 0.00 513 | 0.00 516 | 0.00 528 | 0.00 551 | 0.00 553 | 0.00 539 | 0.00 552 | 0.00 546 | 0.00 547 | 0.00 546 | 0.00 550 | 0.00 547 | 0.00 545 | 0.00 545 | 0.00 543 |
|
| sosnet-low-res | | | 0.00 513 | 0.00 516 | 0.00 528 | 0.00 551 | 0.00 553 | 0.00 539 | 0.00 552 | 0.00 546 | 0.00 547 | 0.00 546 | 0.00 550 | 0.00 547 | 0.00 545 | 0.00 545 | 0.00 543 |
|
| sosnet | | | 0.00 513 | 0.00 516 | 0.00 528 | 0.00 551 | 0.00 553 | 0.00 539 | 0.00 552 | 0.00 546 | 0.00 547 | 0.00 546 | 0.00 550 | 0.00 547 | 0.00 545 | 0.00 545 | 0.00 543 |
|
| uncertanet | | | 0.00 513 | 0.00 516 | 0.00 528 | 0.00 551 | 0.00 553 | 0.00 539 | 0.00 552 | 0.00 546 | 0.00 547 | 0.00 546 | 0.00 550 | 0.00 547 | 0.00 545 | 0.00 545 | 0.00 543 |
|
| Regformer | | | 0.00 513 | 0.00 516 | 0.00 528 | 0.00 551 | 0.00 553 | 0.00 539 | 0.00 552 | 0.00 546 | 0.00 547 | 0.00 546 | 0.00 550 | 0.00 547 | 0.00 545 | 0.00 545 | 0.00 543 |
|
| uanet | | | 0.00 513 | 0.00 516 | 0.00 528 | 0.00 551 | 0.00 553 | 0.00 539 | 0.00 552 | 0.00 546 | 0.00 547 | 0.00 546 | 0.00 550 | 0.00 547 | 0.00 545 | 0.00 545 | 0.00 543 |
|
| MED-MVS test | | | | | 99.52 14 | 99.77 2 | 98.86 23 | 99.32 22 | 99.24 20 | 96.41 123 | 99.30 52 | 99.35 62 | | 99.92 43 | 98.30 75 | 99.80 25 | 99.79 29 |
|
| TestfortrainingZip | | | | | 99.43 21 | 99.13 119 | 99.06 15 | 99.32 22 | 98.57 178 | 96.88 97 | 99.42 43 | 99.05 143 | 96.54 24 | 99.73 136 | | 98.59 180 | 99.51 104 |
|
| WAC-MVS | | | | | | | 90.94 399 | | | | | | | | 88.66 430 | | |
|
| FOURS1 | | | | | | 99.82 1 | 98.66 29 | 99.69 1 | 98.95 61 | 97.46 57 | 99.39 46 | | | | | | |
|
| MSC_two_6792asdad | | | | | 99.62 7 | 99.17 111 | 99.08 12 | | 98.63 161 | | | | | 99.94 14 | 98.53 55 | 99.80 25 | 99.86 13 |
|
| PC_three_1452 | | | | | | | | | | 95.08 216 | 99.60 33 | 99.16 110 | 97.86 2 | 98.47 356 | 97.52 139 | 99.72 66 | 99.74 50 |
|
| No_MVS | | | | | 99.62 7 | 99.17 111 | 99.08 12 | | 98.63 161 | | | | | 99.94 14 | 98.53 55 | 99.80 25 | 99.86 13 |
|
| test_one_0601 | | | | | | 99.66 31 | 99.25 2 | | 98.86 91 | 97.55 49 | 99.20 60 | 99.47 37 | 97.57 7 | | | | |
|
| eth-test2 | | | | | | 0.00 551 | | | | | | | | | | | |
|
| eth-test | | | | | | 0.00 551 | | | | | | | | | | | |
|
| ZD-MVS | | | | | | 99.46 58 | 98.70 28 | | 98.79 119 | 93.21 330 | 98.67 105 | 98.97 154 | 95.70 52 | 99.83 90 | 96.07 212 | 99.58 97 | |
|
| RE-MVS-def | | | | 98.34 54 | | 99.49 52 | 97.86 75 | 99.11 66 | 98.80 114 | 96.49 118 | 99.17 63 | 99.35 62 | 95.29 69 | | 97.72 113 | 99.65 80 | 99.71 63 |
|
| IU-MVS | | | | | | 99.71 24 | 99.23 7 | | 98.64 158 | 95.28 199 | 99.63 32 | | | | 98.35 72 | 99.81 16 | 99.83 19 |
|
| OPU-MVS | | | | | 99.37 28 | 99.24 103 | 99.05 16 | 99.02 86 | | | | 99.16 110 | 97.81 3 | 99.37 211 | 97.24 161 | 99.73 61 | 99.70 67 |
|
| test_241102_TWO | | | | | | | | | 98.87 85 | 97.65 41 | 99.53 38 | 99.48 35 | 97.34 12 | 99.94 14 | 98.43 67 | 99.80 25 | 99.83 19 |
|
| test_241102_ONE | | | | | | 99.71 24 | 99.24 5 | | 98.87 85 | 97.62 43 | 99.73 23 | 99.39 50 | 97.53 8 | 99.74 134 | | | |
|
| 9.14 | | | | 98.06 78 | | 99.47 56 | | 98.71 192 | 98.82 101 | 94.36 263 | 99.16 67 | 99.29 75 | 96.05 40 | 99.81 102 | 97.00 169 | 99.71 68 | |
|
| save fliter | | | | | | 99.46 58 | 98.38 41 | 98.21 291 | 98.71 137 | 97.95 28 | | | | | | | |
|
| test_0728_THIRD | | | | | | | | | | 97.32 65 | 99.45 40 | 99.46 42 | 97.88 1 | 99.94 14 | 98.47 63 | 99.86 2 | 99.85 16 |
|
| test_0728_SECOND | | | | | 99.71 1 | 99.72 17 | 99.35 1 | 98.97 98 | 98.88 78 | | | | | 99.94 14 | 98.47 63 | 99.81 16 | 99.84 18 |
|
| test0726 | | | | | | 99.72 17 | 99.25 2 | 99.06 74 | 98.88 78 | 97.62 43 | 99.56 35 | 99.50 31 | 97.42 10 | | | | |
|
| GSMVS | | | | | | | | | | | | | | | | | 99.20 189 |
|
| test_part2 | | | | | | 99.63 34 | 99.18 10 | | | | 99.27 57 | | | | | | |
|
| sam_mvs1 | | | | | | | | | | | | | 89.45 240 | | | | 99.20 189 |
|
| sam_mvs | | | | | | | | | | | | | 88.99 256 | | | | |
|
| ambc | | | | | 89.49 468 | 86.66 513 | 75.78 498 | 92.66 501 | 96.72 445 | | 86.55 472 | 92.50 484 | 46.01 502 | 97.90 428 | 90.32 401 | 82.09 462 | 94.80 467 |
|
| MTGPA |  | | | | | | | | 98.74 129 | | | | | | | | |
|
| test_post1 | | | | | | | | 96.68 452 | | | | 30.43 544 | 87.85 294 | 98.69 334 | 92.59 351 | | |
|
| test_post | | | | | | | | | | | | 31.83 543 | 88.83 265 | 98.91 310 | | | |
|
| patchmatchnet-post | | | | | | | | | | | | 95.10 454 | 89.42 241 | 98.89 314 | | | |
|
| GG-mvs-BLEND | | | | | 96.59 309 | 96.34 403 | 94.98 260 | 96.51 457 | 88.58 512 | | 93.10 384 | 94.34 465 | 80.34 413 | 98.05 415 | 89.53 417 | 96.99 269 | 96.74 372 |
|
| MTMP | | | | | | | | 98.89 124 | 94.14 491 | | | | | | | | |
|
| gm-plane-assit | | | | | | 95.88 427 | 87.47 466 | | | 89.74 432 | | 96.94 385 | | 99.19 251 | 93.32 321 | | |
|
| test9_res | | | | | | | | | | | | | | | 96.39 206 | 99.57 98 | 99.69 70 |
|
| TEST9 | | | | | | 99.31 79 | 98.50 35 | 97.92 340 | 98.73 132 | 92.63 354 | 97.74 183 | 98.68 208 | 96.20 35 | 99.80 109 | | | |
|
| test_8 | | | | | | 99.29 88 | 98.44 37 | 97.89 348 | 98.72 134 | 92.98 341 | 97.70 188 | 98.66 211 | 96.20 35 | 99.80 109 | | | |
|
| agg_prior2 | | | | | | | | | | | | | | | 95.87 222 | 99.57 98 | 99.68 75 |
|
| agg_prior | | | | | | 99.30 83 | 98.38 41 | | 98.72 134 | | 97.57 206 | | | 99.81 102 | | | |
|
| TestCases | | | | | 96.99 267 | 99.25 96 | 93.21 348 | | 98.18 299 | 91.36 396 | 93.52 363 | 98.77 195 | 84.67 359 | 99.72 137 | 89.70 414 | 97.87 238 | 98.02 310 |
|
| test_prior4 | | | | | | | 98.01 71 | 97.86 352 | | | | | | | | | |
|
| test_prior2 | | | | | | | | 97.80 359 | | 96.12 139 | 97.89 170 | 98.69 207 | 95.96 44 | | 96.89 179 | 99.60 92 | |
|
| test_prior | | | | | 99.19 51 | 99.31 79 | 98.22 58 | | 98.84 96 | | | | | 99.70 143 | | | 99.65 83 |
|
| 旧先验2 | | | | | | | | 97.57 379 | | 91.30 401 | 98.67 105 | | | 99.80 109 | 95.70 233 | | |
|
| æ–°å‡ ä½•2 | | | | | | | | 97.64 373 | | | | | | | | | |
|
| æ–°å‡ ä½•1 | | | | | 99.16 56 | 99.34 71 | 98.01 71 | | 98.69 142 | 90.06 426 | 98.13 138 | 98.95 161 | 94.60 89 | 99.89 68 | 91.97 370 | 99.47 121 | 99.59 94 |
|
| 旧先验1 | | | | | | 99.29 88 | 97.48 90 | | 98.70 140 | | | 99.09 133 | 95.56 55 | | | 99.47 121 | 99.61 90 |
|
| æ— å…ˆéªŒ | | | | | | | | 97.58 378 | 98.72 134 | 91.38 395 | | | | 99.87 79 | 93.36 320 | | 99.60 92 |
|
| 原ACMM2 | | | | | | | | 97.67 370 | | | | | | | | | |
|
| 原ACMM1 | | | | | 98.65 98 | 99.32 77 | 96.62 141 | | 98.67 150 | 93.27 329 | 97.81 176 | 98.97 154 | 95.18 76 | 99.83 90 | 93.84 306 | 99.46 124 | 99.50 107 |
|
| test222 | | | | | | 99.23 104 | 97.17 117 | 97.40 390 | 98.66 153 | 88.68 447 | 98.05 147 | 98.96 159 | 94.14 102 | | | 99.53 111 | 99.61 90 |
|
| testdata2 | | | | | | | | | | | | | | 99.89 68 | 91.65 379 | | |
|
| segment_acmp | | | | | | | | | | | | | 96.85 15 | | | | |
|
| testdata | | | | | 98.26 142 | 99.20 109 | 95.36 236 | | 98.68 145 | 91.89 381 | 98.60 113 | 99.10 125 | 94.44 96 | 99.82 97 | 94.27 290 | 99.44 125 | 99.58 98 |
|
| testdata1 | | | | | | | | 97.32 400 | | 96.34 128 | | | | | | | |
|
| test12 | | | | | 99.18 53 | 99.16 115 | 98.19 60 | | 98.53 188 | | 98.07 143 | | 95.13 79 | 99.72 137 | | 99.56 106 | 99.63 88 |
|
| plane_prior7 | | | | | | 97.42 336 | 94.63 277 | | | | | | | | | | |
|
| plane_prior6 | | | | | | 97.35 343 | 94.61 280 | | | | | | 87.09 308 | | | | |
|
| plane_prior5 | | | | | | | | | 98.56 182 | | | | | 99.03 288 | 96.07 212 | 94.27 322 | 96.92 348 |
|
| plane_prior4 | | | | | | | | | | | | 98.28 252 | | | | | |
|
| plane_prior3 | | | | | | | 94.61 280 | | | 97.02 89 | 95.34 288 | | | | | | |
|
| plane_prior2 | | | | | | | | 98.80 164 | | 97.28 69 | | | | | | | |
|
| plane_prior1 | | | | | | 97.37 342 | | | | | | | | | | | |
|
| plane_prior | | | | | | | 94.60 282 | 98.44 262 | | 96.74 105 | | | | | | 94.22 324 | |
|
| n2 | | | | | | | | | 0.00 552 | | | | | | | | |
|
| nn | | | | | | | | | 0.00 552 | | | | | | | | |
|
| door-mid | | | | | | | | | 94.37 485 | | | | | | | | |
|
| lessismore_v0 | | | | | 94.45 428 | 94.93 452 | 88.44 457 | | 91.03 507 | | 86.77 470 | 97.64 316 | 76.23 451 | 98.42 362 | 90.31 402 | 85.64 449 | 96.51 416 |
|
| LGP-MVS_train | | | | | 96.47 325 | 97.46 331 | 93.54 324 | | 98.54 186 | 94.67 245 | 94.36 320 | 98.77 195 | 85.39 341 | 99.11 271 | 95.71 231 | 94.15 328 | 96.76 370 |
|
| test11 | | | | | | | | | 98.66 153 | | | | | | | | |
|
| door | | | | | | | | | 94.64 483 | | | | | | | | |
|
| HQP5-MVS | | | | | | | 94.25 299 | | | | | | | | | | |
|
| HQP-NCC | | | | | | 97.20 351 | | 98.05 324 | | 96.43 120 | 94.45 312 | | | | | | |
|
| ACMP_Plane | | | | | | 97.20 351 | | 98.05 324 | | 96.43 120 | 94.45 312 | | | | | | |
|
| BP-MVS | | | | | | | | | | | | | | | 95.30 246 | | |
|
| HQP4-MVS | | | | | | | | | | | 94.45 312 | | | 98.96 301 | | | 96.87 360 |
|
| HQP3-MVS | | | | | | | | | 98.46 207 | | | | | | | 94.18 326 | |
|
| HQP2-MVS | | | | | | | | | | | | | 86.75 314 | | | | |
|
| NP-MVS | | | | | | 97.28 345 | 94.51 285 | | | | | 97.73 303 | | | | | |
|
| MDTV_nov1_ep13_2view | | | | | | | 84.26 479 | 96.89 440 | | 90.97 410 | 97.90 169 | | 89.89 226 | | 93.91 304 | | 99.18 198 |
|
| MDTV_nov1_ep13 | | | | 95.40 238 | | 97.48 329 | 88.34 458 | 96.85 445 | 97.29 402 | 93.74 295 | 97.48 208 | 97.26 345 | 89.18 249 | 99.05 282 | 91.92 371 | 97.43 260 | |
|
| ACMMP++_ref | | | | | | | | | | | | | | | | 92.97 356 | |
|
| ACMMP++ | | | | | | | | | | | | | | | | 93.61 343 | |
|
| Test By Simon | | | | | | | | | | | | | 94.64 88 | | | | |
|
| ITE_SJBPF | | | | | 95.44 386 | 97.42 336 | 91.32 393 | | 97.50 381 | 95.09 215 | 93.59 358 | 98.35 243 | 81.70 395 | 98.88 316 | 89.71 413 | 93.39 349 | 96.12 437 |
|
| DeepMVS_CX |  | | | | 86.78 475 | 97.09 361 | 72.30 505 | | 95.17 476 | 75.92 499 | 84.34 483 | 95.19 452 | 70.58 474 | 95.35 483 | 79.98 483 | 89.04 414 | 92.68 492 |
|