| fmvsm_l_conf0.5_n_a | | | 99.09 1 | 99.08 1 | 99.11 61 | 99.43 63 | 97.48 89 | 98.88 127 | 99.30 14 | 98.47 18 | 99.85 11 | 99.43 43 | 96.71 19 | 99.96 4 | 99.86 1 | 99.80 25 | 99.89 6 |
|
| SED-MVS | | | 99.09 1 | 98.91 4 | 99.63 5 | 99.71 24 | 99.24 6 | 99.02 84 | 98.87 85 | 97.65 39 | 99.73 22 | 99.48 33 | 97.53 9 | 99.94 14 | 98.43 67 | 99.81 16 | 99.70 67 |
|
| DVP-MVS++ | | | 99.08 3 | 98.89 5 | 99.64 4 | 99.17 111 | 99.23 8 | 99.69 1 | 98.88 78 | 97.32 63 | 99.53 37 | 99.47 35 | 97.81 3 | 99.94 14 | 98.47 63 | 99.72 68 | 99.74 50 |
|
| fmvsm_l_conf0.5_n | | | 99.07 4 | 99.05 2 | 99.14 57 | 99.41 66 | 97.54 87 | 98.89 120 | 99.31 13 | 98.49 17 | 99.86 8 | 99.42 44 | 96.45 27 | 99.96 4 | 99.86 1 | 99.74 59 | 99.90 5 |
|
| DVP-MVS |  | | 99.03 5 | 98.83 10 | 99.63 5 | 99.72 17 | 99.25 3 | 98.97 95 | 98.58 177 | 97.62 41 | 99.45 39 | 99.46 40 | 97.42 11 | 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 |
| MED-MVS | | | 99.02 6 | 98.85 8 | 99.52 13 | 99.77 2 | 98.86 22 | 99.32 22 | 99.24 20 | 97.00 89 | 99.30 50 | 99.35 60 | 97.61 6 | 99.92 43 | 98.30 75 | 99.80 25 | 99.79 28 |
|
| TestfortrainingZip a | | | 99.02 6 | 98.79 12 | 99.70 2 | 99.77 2 | 99.30 2 | 99.32 22 | 99.24 20 | 96.41 121 | 99.30 50 | 99.35 60 | 97.61 6 | 99.92 43 | 98.35 72 | 99.80 25 | 99.88 10 |
|
| APDe-MVS |  | | 99.02 6 | 98.84 9 | 99.55 10 | 99.57 39 | 98.96 17 | 99.39 11 | 98.93 65 | 97.38 60 | 99.41 42 | 99.54 20 | 96.66 20 | 99.84 88 | 98.86 39 | 99.85 6 | 99.87 11 |
| 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 30 | 99.43 10 | 99.38 8 | 97.60 44 | 99.58 33 | 99.47 35 | 95.36 64 | 99.93 34 | 98.87 38 | 99.57 100 | 99.78 33 |
|
| reproduce_model | | | 98.94 10 | 98.81 11 | 99.34 31 | 99.52 45 | 98.26 54 | 98.94 105 | 98.84 96 | 98.06 25 | 99.35 46 | 99.61 5 | 96.39 30 | 99.94 14 | 98.77 42 | 99.82 14 | 99.83 18 |
|
| reproduce-ours | | | 98.93 11 | 98.78 14 | 99.38 23 | 99.49 52 | 98.38 40 | 98.86 134 | 98.83 98 | 98.06 25 | 99.29 53 | 99.58 16 | 96.40 28 | 99.94 14 | 98.68 45 | 99.81 16 | 99.81 24 |
|
| our_new_method | | | 98.93 11 | 98.78 14 | 99.38 23 | 99.49 52 | 98.38 40 | 98.86 134 | 98.83 98 | 98.06 25 | 99.29 53 | 99.58 16 | 96.40 28 | 99.94 14 | 98.68 45 | 99.81 16 | 99.81 24 |
|
| test_fmvsmconf_n | | | 98.92 13 | 98.87 6 | 99.04 67 | 98.88 147 | 97.25 111 | 98.82 147 | 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 3 | 99.58 37 | 99.20 10 | 98.42 260 | 98.91 72 | 97.58 45 | 99.54 36 | 99.46 40 | 97.10 14 | 99.94 14 | 97.64 119 | 99.84 11 | 99.83 18 |
| 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 12 | 99.24 45 | 99.34 71 | 97.83 78 | 98.70 188 | 99.26 16 | 98.85 6 | 99.92 1 | 99.51 26 | 93.91 106 | 99.95 9 | 99.86 1 | 99.79 35 | 99.92 2 |
|
| fmvsm_l_conf0.5_n_3 | | | 98.90 15 | 98.74 18 | 99.37 27 | 99.36 68 | 98.25 55 | 98.89 120 | 99.24 20 | 98.77 10 | 99.89 3 | 99.59 13 | 93.39 112 | 99.96 4 | 99.78 10 | 99.76 48 | 99.89 6 |
|
| SteuartSystems-ACMMP | | | 98.90 15 | 98.75 17 | 99.36 29 | 99.22 106 | 98.43 38 | 99.10 68 | 98.87 85 | 97.38 60 | 99.35 46 | 99.40 47 | 97.78 5 | 99.87 79 | 97.77 107 | 99.85 6 | 99.78 33 |
| Skip Steuart: Steuart Systems R&D Blog. |
| test_fmvsm_n_1920 | | | 98.87 18 | 99.01 3 | 98.45 123 | 99.42 64 | 96.43 155 | 98.96 101 | 99.36 10 | 98.63 13 | 99.86 8 | 99.51 26 | 95.91 46 | 99.97 1 | 99.72 14 | 99.75 55 | 98.94 226 |
|
| ME-MVS | | | 98.83 19 | 98.60 24 | 99.52 13 | 99.58 37 | 98.86 22 | 98.69 191 | 98.93 65 | 97.00 89 | 99.17 62 | 99.35 60 | 96.62 23 | 99.90 64 | 98.30 75 | 99.80 25 | 99.79 28 |
|
| TSAR-MVS + MP. | | | 98.78 20 | 98.62 22 | 99.24 45 | 99.69 29 | 98.28 53 | 99.14 59 | 98.66 154 | 96.84 96 | 99.56 34 | 99.31 71 | 96.34 31 | 99.70 142 | 98.32 74 | 99.73 63 | 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 20 | 98.47 247 | 98.81 107 | 97.72 34 | 98.76 95 | 99.16 103 | 97.05 15 | 99.78 124 | 98.06 89 | 99.66 79 | 99.69 70 |
|
| MSP-MVS | | | 98.74 22 | 98.55 29 | 99.29 38 | 99.75 6 | 98.23 56 | 99.26 32 | 98.88 78 | 97.52 48 | 99.41 42 | 98.78 182 | 96.00 42 | 99.79 121 | 97.79 106 | 99.59 96 | 99.85 15 |
| 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 66 | 99.35 70 | 97.27 105 | 98.80 156 | 99.23 28 | 98.93 3 | 99.79 15 | 99.59 13 | 92.34 129 | 99.95 9 | 99.82 6 | 99.71 70 | 99.92 2 |
|
| XVS | | | 98.70 24 | 98.49 36 | 99.34 31 | 99.70 27 | 98.35 49 | 99.29 27 | 98.88 78 | 97.40 57 | 98.46 118 | 99.20 92 | 95.90 48 | 99.89 68 | 97.85 102 | 99.74 59 | 99.78 33 |
|
| fmvsm_s_conf0.5_n_10 | | | 98.66 25 | 98.54 31 | 99.02 68 | 99.36 68 | 97.21 114 | 98.86 134 | 99.23 28 | 98.90 5 | 99.83 12 | 99.59 13 | 91.57 160 | 99.94 14 | 99.79 9 | 99.74 59 | 99.89 6 |
|
| fmvsm_s_conf0.5_n_6 | | | 98.65 26 | 98.55 29 | 98.95 77 | 98.50 187 | 97.30 101 | 98.79 164 | 99.16 40 | 98.14 23 | 99.86 8 | 99.41 46 | 93.71 109 | 99.91 56 | 99.71 15 | 99.64 87 | 99.65 83 |
|
| MCST-MVS | | | 98.65 26 | 98.37 45 | 99.48 17 | 99.60 36 | 98.87 20 | 98.41 261 | 98.68 146 | 97.04 86 | 98.52 116 | 98.80 176 | 96.78 18 | 99.83 90 | 97.93 96 | 99.61 92 | 99.74 50 |
|
| SD-MVS | | | 98.64 28 | 98.68 19 | 98.53 112 | 99.33 74 | 98.36 48 | 98.90 116 | 98.85 95 | 97.28 67 | 99.72 25 | 99.39 48 | 96.63 22 | 97.60 420 | 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 | 98.54 109 | 99.40 67 | 95.83 199 | 98.79 164 | 99.17 38 | 98.94 2 | 99.92 1 | 99.61 5 | 92.49 124 | 99.93 34 | 99.86 1 | 99.76 48 | 99.86 12 |
|
| HFP-MVS | | | 98.63 29 | 98.40 42 | 99.32 37 | 99.72 17 | 98.29 52 | 99.23 37 | 98.96 60 | 96.10 138 | 98.94 77 | 99.17 100 | 96.06 39 | 99.92 43 | 97.62 120 | 99.78 40 | 99.75 48 |
|
| ACMMP_NAP | | | 98.61 31 | 98.30 60 | 99.55 10 | 99.62 35 | 98.95 18 | 98.82 147 | 98.81 107 | 95.80 152 | 99.16 66 | 99.47 35 | 95.37 63 | 99.92 43 | 97.89 100 | 99.75 55 | 99.79 28 |
|
| region2R | | | 98.61 31 | 98.38 44 | 99.29 38 | 99.74 12 | 98.16 62 | 99.23 37 | 98.93 65 | 96.15 134 | 98.94 77 | 99.17 100 | 95.91 46 | 99.94 14 | 97.55 128 | 99.79 35 | 99.78 33 |
|
| NCCC | | | 98.61 31 | 98.35 48 | 99.38 23 | 99.28 92 | 98.61 31 | 98.45 249 | 98.76 125 | 97.82 33 | 98.45 121 | 98.93 154 | 96.65 21 | 99.83 90 | 97.38 149 | 99.41 129 | 99.71 63 |
|
| SF-MVS | | | 98.59 34 | 98.32 59 | 99.41 22 | 99.54 41 | 98.71 26 | 99.04 78 | 98.81 107 | 95.12 201 | 99.32 49 | 99.39 48 | 96.22 33 | 99.84 88 | 97.72 110 | 99.73 63 | 99.67 79 |
|
| ACMMPR | | | 98.59 34 | 98.36 46 | 99.29 38 | 99.74 12 | 98.15 63 | 99.23 37 | 98.95 61 | 96.10 138 | 98.93 81 | 99.19 97 | 95.70 52 | 99.94 14 | 97.62 120 | 99.79 35 | 99.78 33 |
|
| fmvsm_s_conf0.5_n_11 | | | 98.58 36 | 98.57 26 | 98.62 99 | 99.42 64 | 97.16 117 | 98.97 95 | 98.86 91 | 98.91 4 | 99.87 4 | 99.66 3 | 91.82 152 | 99.95 9 | 99.82 6 | 99.82 14 | 98.75 247 |
|
| test_fmvsmconf0.1_n | | | 98.58 36 | 98.44 40 | 98.99 70 | 97.73 296 | 97.15 118 | 98.84 143 | 98.97 57 | 98.75 11 | 99.43 41 | 99.54 20 | 93.29 114 | 99.93 34 | 99.64 20 | 99.79 35 | 99.89 6 |
|
| SMA-MVS |  | | 98.58 36 | 98.25 63 | 99.56 9 | 99.51 46 | 99.04 16 | 98.95 102 | 98.80 114 | 93.67 295 | 99.37 45 | 99.52 23 | 96.52 25 | 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 29 | 98.90 116 | 98.74 129 | 97.27 71 | 98.02 147 | 99.39 48 | 94.81 87 | 99.96 4 | 97.91 98 | 99.79 35 | 99.77 40 |
|
| HPM-MVS++ |  | | 98.58 36 | 98.25 63 | 99.55 10 | 99.50 48 | 99.08 12 | 98.72 183 | 98.66 154 | 97.51 49 | 98.15 132 | 98.83 173 | 95.70 52 | 99.92 43 | 97.53 130 | 99.67 76 | 99.66 82 |
|
| SR-MVS | | | 98.57 41 | 98.35 48 | 99.24 45 | 99.53 42 | 98.18 60 | 99.09 69 | 98.82 101 | 96.58 112 | 99.10 68 | 99.32 69 | 95.39 61 | 99.82 97 | 97.70 115 | 99.63 89 | 99.72 59 |
|
| CP-MVS | | | 98.57 41 | 98.36 46 | 99.19 50 | 99.66 31 | 97.86 74 | 99.34 17 | 98.87 85 | 95.96 144 | 98.60 112 | 99.13 110 | 96.05 40 | 99.94 14 | 97.77 107 | 99.86 2 | 99.77 40 |
|
| MSLP-MVS++ | | | 98.56 43 | 98.57 26 | 98.55 107 | 99.26 95 | 96.80 133 | 98.71 184 | 99.05 50 | 97.28 67 | 98.84 87 | 99.28 76 | 96.47 26 | 99.40 206 | 98.52 61 | 99.70 72 | 99.47 115 |
|
| DeepC-MVS_fast | | 96.70 1 | 98.55 44 | 98.34 54 | 99.18 52 | 99.25 96 | 98.04 68 | 98.50 242 | 98.78 121 | 97.72 34 | 98.92 83 | 99.28 76 | 95.27 70 | 99.82 97 | 97.55 128 | 99.77 42 | 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 58 | 99.49 52 | 97.86 74 | 99.11 65 | 98.80 114 | 96.49 116 | 99.17 62 | 99.35 60 | 95.34 66 | 99.82 97 | 97.72 110 | 99.65 82 | 99.71 63 |
|
| fmvsm_s_conf0.5_n_5 | | | 98.53 46 | 98.35 48 | 99.08 63 | 99.07 126 | 97.46 93 | 98.68 194 | 99.20 34 | 97.50 50 | 99.87 4 | 99.50 29 | 91.96 149 | 99.96 4 | 99.76 11 | 99.65 82 | 99.82 22 |
|
| fmvsm_s_conf0.5_n_3 | | | 98.53 46 | 98.45 39 | 98.79 85 | 99.23 104 | 97.32 98 | 98.80 156 | 99.26 16 | 98.82 7 | 99.87 4 | 99.60 10 | 90.95 193 | 99.93 34 | 99.76 11 | 99.73 63 | 99.12 196 |
|
| APD-MVS_3200maxsize | | | 98.53 46 | 98.33 58 | 99.15 56 | 99.50 48 | 97.92 73 | 99.15 56 | 98.81 107 | 96.24 130 | 99.20 59 | 99.37 54 | 95.30 68 | 99.80 109 | 97.73 109 | 99.67 76 | 99.72 59 |
|
| MM | | | 98.51 49 | 98.24 65 | 99.33 35 | 99.12 120 | 98.14 65 | 98.93 111 | 97.02 407 | 98.96 1 | 99.17 62 | 99.47 35 | 91.97 148 | 99.94 14 | 99.85 5 | 99.69 73 | 99.91 4 |
|
| mPP-MVS | | | 98.51 49 | 98.26 62 | 99.25 44 | 99.75 6 | 98.04 68 | 99.28 29 | 98.81 107 | 96.24 130 | 98.35 128 | 99.23 86 | 95.46 58 | 99.94 14 | 97.42 144 | 99.81 16 | 99.77 40 |
|
| ZNCC-MVS | | | 98.49 51 | 98.20 71 | 99.35 30 | 99.73 16 | 98.39 39 | 99.19 49 | 98.86 91 | 95.77 154 | 98.31 131 | 99.10 118 | 95.46 58 | 99.93 34 | 97.57 127 | 99.81 16 | 99.74 50 |
|
| SPE-MVS-test | | | 98.49 51 | 98.50 34 | 98.46 122 | 99.20 109 | 97.05 123 | 99.64 4 | 98.50 199 | 97.45 56 | 98.88 84 | 99.14 107 | 95.25 72 | 99.15 251 | 98.83 40 | 99.56 108 | 99.20 180 |
|
| PGM-MVS | | | 98.49 51 | 98.23 67 | 99.27 43 | 99.72 17 | 98.08 67 | 98.99 91 | 99.49 5 | 95.43 177 | 99.03 69 | 99.32 69 | 95.56 55 | 99.94 14 | 96.80 182 | 99.77 42 | 99.78 33 |
|
| EI-MVSNet-Vis-set | | | 98.47 54 | 98.39 43 | 98.69 93 | 99.46 58 | 96.49 152 | 98.30 274 | 98.69 143 | 97.21 74 | 98.84 87 | 99.36 58 | 95.41 60 | 99.78 124 | 98.62 49 | 99.65 82 | 99.80 27 |
|
| MVS_111021_HR | | | 98.47 54 | 98.34 54 | 98.88 82 | 99.22 106 | 97.32 98 | 97.91 331 | 99.58 3 | 97.20 75 | 98.33 129 | 99.00 142 | 95.99 43 | 99.64 156 | 98.05 91 | 99.76 48 | 99.69 70 |
|
| balanced_conf03 | | | 98.45 56 | 98.35 48 | 98.74 89 | 98.65 176 | 97.55 85 | 99.19 49 | 98.60 165 | 96.72 106 | 99.35 46 | 98.77 185 | 95.06 82 | 99.55 179 | 98.95 35 | 99.87 1 | 99.12 196 |
|
| test_fmvsmvis_n_1920 | | | 98.44 57 | 98.51 32 | 98.23 144 | 98.33 218 | 96.15 169 | 98.97 95 | 99.15 42 | 98.55 16 | 98.45 121 | 99.55 18 | 94.26 100 | 99.97 1 | 99.65 18 | 99.66 79 | 98.57 272 |
|
| CS-MVS | | | 98.44 57 | 98.49 36 | 98.31 136 | 99.08 125 | 96.73 137 | 99.67 3 | 98.47 206 | 97.17 78 | 98.94 77 | 99.10 118 | 95.73 51 | 99.13 256 | 98.71 44 | 99.49 119 | 99.09 204 |
|
| GST-MVS | | | 98.43 59 | 98.12 75 | 99.34 31 | 99.72 17 | 98.38 40 | 99.09 69 | 98.82 101 | 95.71 158 | 98.73 98 | 99.06 133 | 95.27 70 | 99.93 34 | 97.07 159 | 99.63 89 | 99.72 59 |
|
| fmvsm_s_conf0.5_n | | | 98.42 60 | 98.51 32 | 98.13 160 | 99.30 83 | 95.25 232 | 98.85 139 | 99.39 7 | 97.94 29 | 99.74 21 | 99.62 4 | 92.59 123 | 99.91 56 | 99.65 18 | 99.52 114 | 99.25 173 |
|
| EI-MVSNet-UG-set | | | 98.41 61 | 98.34 54 | 98.61 101 | 99.45 61 | 96.32 162 | 98.28 277 | 98.68 146 | 97.17 78 | 98.74 96 | 99.37 54 | 95.25 72 | 99.79 121 | 98.57 52 | 99.54 111 | 99.73 55 |
|
| DELS-MVS | | | 98.40 62 | 98.20 71 | 98.99 70 | 99.00 134 | 97.66 80 | 97.75 352 | 98.89 75 | 97.71 36 | 98.33 129 | 98.97 144 | 94.97 84 | 99.88 77 | 98.42 69 | 99.76 48 | 99.42 130 |
| 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 | 98.27 138 | 99.09 124 | 95.41 222 | 98.86 134 | 99.37 9 | 97.69 38 | 99.78 17 | 99.61 5 | 92.38 127 | 99.91 56 | 99.58 23 | 99.43 127 | 99.49 111 |
|
| TSAR-MVS + GP. | | | 98.38 63 | 98.24 65 | 98.81 84 | 99.22 106 | 97.25 111 | 98.11 306 | 98.29 266 | 97.19 76 | 98.99 75 | 99.02 136 | 96.22 33 | 99.67 149 | 98.52 61 | 98.56 183 | 99.51 104 |
|
| HPM-MVS_fast | | | 98.38 63 | 98.13 74 | 99.12 60 | 99.75 6 | 97.86 74 | 99.44 9 | 98.82 101 | 94.46 249 | 98.94 77 | 99.20 92 | 95.16 77 | 99.74 134 | 97.58 123 | 99.85 6 | 99.77 40 |
|
| patch_mono-2 | | | 98.36 66 | 98.87 6 | 96.82 270 | 99.53 42 | 90.68 384 | 98.64 205 | 99.29 15 | 97.88 30 | 99.19 61 | 99.52 23 | 96.80 17 | 99.97 1 | 99.11 31 | 99.86 2 | 99.82 22 |
|
| HPM-MVS |  | | 98.36 66 | 98.10 78 | 99.13 58 | 99.74 12 | 97.82 79 | 99.53 6 | 98.80 114 | 94.63 236 | 98.61 111 | 98.97 144 | 95.13 79 | 99.77 129 | 97.65 118 | 99.83 13 | 99.79 28 |
| 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 | 97.90 184 | 99.16 115 | 95.08 241 | 98.75 169 | 99.24 20 | 98.39 19 | 99.81 13 | 99.52 23 | 92.35 128 | 99.90 64 | 99.74 13 | 99.51 116 | 98.71 253 |
|
| APD-MVS |  | | 98.35 68 | 98.00 84 | 99.42 21 | 99.51 46 | 98.72 25 | 98.80 156 | 98.82 101 | 94.52 244 | 99.23 58 | 99.25 85 | 95.54 57 | 99.80 109 | 96.52 191 | 99.77 42 | 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 95 | 99.27 93 | 96.90 129 | 97.95 324 | 99.58 3 | 97.14 81 | 98.44 123 | 99.01 140 | 95.03 83 | 99.62 163 | 97.91 98 | 99.75 55 | 99.50 106 |
|
| PHI-MVS | | | 98.34 70 | 98.06 79 | 99.18 52 | 99.15 118 | 98.12 66 | 99.04 78 | 99.09 45 | 93.32 312 | 98.83 90 | 99.10 118 | 96.54 24 | 99.83 90 | 97.70 115 | 99.76 48 | 99.59 94 |
|
| MP-MVS |  | | 98.33 72 | 98.01 83 | 99.28 41 | 99.75 6 | 98.18 60 | 99.22 41 | 98.79 119 | 96.13 135 | 97.92 161 | 99.23 86 | 94.54 90 | 99.94 14 | 96.74 185 | 99.78 40 | 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 95 | 98.96 141 | 97.36 96 | 99.24 35 | 98.57 179 | 94.81 224 | 98.99 75 | 98.90 160 | 95.22 75 | 99.59 166 | 99.15 30 | 99.84 11 | 99.07 212 |
|
| MP-MVS-pluss | | | 98.31 73 | 97.92 86 | 99.49 16 | 99.72 17 | 98.88 19 | 98.43 257 | 98.78 121 | 94.10 260 | 97.69 181 | 99.42 44 | 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 | 98.57 104 | 99.25 96 | 97.11 120 | 98.66 201 | 99.20 34 | 98.82 7 | 99.79 15 | 99.60 10 | 89.38 234 | 99.92 43 | 99.80 8 | 99.38 134 | 98.69 255 |
|
| fmvsm_s_conf0.5_n_7 | | | 98.23 76 | 98.35 48 | 97.89 186 | 98.86 151 | 94.99 247 | 98.58 218 | 99.00 53 | 98.29 20 | 99.73 22 | 99.60 10 | 91.70 155 | 99.92 43 | 99.63 21 | 99.73 63 | 98.76 246 |
|
| MGCNet | | | 98.23 76 | 97.91 87 | 99.21 49 | 98.06 259 | 97.96 72 | 98.58 218 | 95.51 446 | 98.58 14 | 98.87 85 | 99.26 80 | 92.99 118 | 99.95 9 | 99.62 22 | 99.67 76 | 99.73 55 |
|
| ACMMP |  | | 98.23 76 | 97.95 85 | 99.09 62 | 99.74 12 | 97.62 83 | 99.03 81 | 99.41 6 | 95.98 143 | 97.60 193 | 99.36 58 | 94.45 95 | 99.93 34 | 97.14 156 | 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 | 98.49 119 | 98.34 215 | 97.26 110 | 99.61 5 | 98.43 222 | 96.78 99 | 98.87 85 | 98.84 169 | 93.72 108 | 99.01 280 | 98.91 37 | 99.50 117 | 99.19 184 |
|
| fmvsm_s_conf0.1_n | | | 98.18 80 | 98.21 69 | 98.11 165 | 98.54 185 | 95.24 233 | 98.87 130 | 99.24 20 | 97.50 50 | 99.70 26 | 99.67 1 | 91.33 172 | 99.89 68 | 99.47 25 | 99.54 111 | 99.21 179 |
|
| fmvsm_s_conf0.1_n_2 | | | 98.14 81 | 98.02 82 | 98.53 112 | 98.88 147 | 97.07 122 | 98.69 191 | 98.82 101 | 98.78 9 | 99.77 18 | 99.61 5 | 88.83 254 | 99.91 56 | 99.71 15 | 99.07 150 | 98.61 265 |
|
| fmvsm_s_conf0.1_n_a | | | 98.08 82 | 98.04 81 | 98.21 145 | 97.66 302 | 95.39 223 | 98.89 120 | 99.17 38 | 97.24 72 | 99.76 20 | 99.67 1 | 91.13 184 | 99.88 77 | 99.39 26 | 99.41 129 | 99.35 144 |
|
| dcpmvs_2 | | | 98.08 82 | 98.59 25 | 96.56 299 | 99.57 39 | 90.34 396 | 99.15 56 | 98.38 240 | 96.82 98 | 99.29 53 | 99.49 32 | 95.78 50 | 99.57 169 | 98.94 36 | 99.86 2 | 99.77 40 |
|
| NormalMVS | | | 98.07 84 | 97.90 88 | 98.59 103 | 99.75 6 | 96.60 143 | 98.94 105 | 98.60 165 | 97.86 31 | 98.71 101 | 99.08 128 | 91.22 179 | 99.80 109 | 97.40 146 | 99.57 100 | 99.37 139 |
|
| CANet | | | 98.05 85 | 97.76 91 | 98.90 81 | 98.73 161 | 97.27 105 | 98.35 264 | 98.78 121 | 97.37 62 | 97.72 178 | 98.96 149 | 91.53 165 | 99.92 43 | 98.79 41 | 99.65 82 | 99.51 104 |
|
| train_agg | | | 97.97 86 | 97.52 104 | 99.33 35 | 99.31 79 | 98.50 34 | 97.92 329 | 98.73 132 | 92.98 328 | 97.74 175 | 98.68 198 | 96.20 35 | 99.80 109 | 96.59 186 | 99.57 100 | 99.68 75 |
|
| ETV-MVS | | | 97.96 87 | 97.81 89 | 98.40 131 | 98.42 198 | 97.27 105 | 98.73 179 | 98.55 184 | 96.84 96 | 98.38 125 | 97.44 320 | 95.39 61 | 99.35 211 | 97.62 120 | 98.89 161 | 98.58 271 |
|
| UA-Net | | | 97.96 87 | 97.62 95 | 98.98 72 | 98.86 151 | 97.47 91 | 98.89 120 | 99.08 46 | 96.67 109 | 98.72 100 | 99.54 20 | 93.15 116 | 99.81 102 | 94.87 249 | 98.83 168 | 99.65 83 |
|
| CDPH-MVS | | | 97.94 89 | 97.49 106 | 99.28 41 | 99.47 56 | 98.44 36 | 97.91 331 | 98.67 151 | 92.57 344 | 98.77 94 | 98.85 168 | 95.93 45 | 99.72 136 | 95.56 227 | 99.69 73 | 99.68 75 |
|
| DeepPCF-MVS | | 96.37 2 | 97.93 90 | 98.48 38 | 96.30 325 | 99.00 134 | 89.54 412 | 97.43 374 | 98.87 85 | 98.16 22 | 99.26 57 | 99.38 53 | 96.12 38 | 99.64 156 | 98.30 75 | 99.77 42 | 99.72 59 |
|
| DeepC-MVS | | 95.98 3 | 97.88 91 | 97.58 97 | 98.77 87 | 99.25 96 | 96.93 127 | 98.83 145 | 98.75 127 | 96.96 92 | 96.89 225 | 99.50 29 | 90.46 204 | 99.87 79 | 97.84 104 | 99.76 48 | 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 | 97.54 103 | 98.83 83 | 95.48 426 | 96.83 132 | 98.95 102 | 98.60 165 | 98.58 14 | 98.93 81 | 99.55 18 | 88.57 259 | 99.91 56 | 99.54 24 | 99.61 92 | 99.77 40 |
|
| DP-MVS Recon | | | 97.86 92 | 97.46 109 | 99.06 65 | 99.53 42 | 98.35 49 | 98.33 266 | 98.89 75 | 92.62 341 | 98.05 142 | 98.94 152 | 95.34 66 | 99.65 153 | 96.04 207 | 99.42 128 | 99.19 184 |
|
| CSCG | | | 97.85 94 | 97.74 92 | 98.20 147 | 99.67 30 | 95.16 236 | 99.22 41 | 99.32 12 | 93.04 326 | 97.02 218 | 98.92 158 | 95.36 64 | 99.91 56 | 97.43 142 | 99.64 87 | 99.52 101 |
|
| SymmetryMVS | | | 97.84 95 | 97.58 97 | 98.62 99 | 99.01 132 | 96.60 143 | 98.94 105 | 98.44 211 | 97.86 31 | 98.71 101 | 99.08 128 | 91.22 179 | 99.80 109 | 97.40 146 | 97.53 246 | 99.47 115 |
|
| BP-MVS1 | | | 97.82 96 | 97.51 105 | 98.76 88 | 98.25 229 | 97.39 95 | 99.15 56 | 97.68 339 | 96.69 107 | 98.47 117 | 99.10 118 | 90.29 208 | 99.51 186 | 98.60 50 | 99.35 137 | 99.37 139 |
|
| MG-MVS | | | 97.81 97 | 97.60 96 | 98.44 125 | 99.12 120 | 95.97 180 | 97.75 352 | 98.78 121 | 96.89 95 | 98.46 118 | 99.22 88 | 93.90 107 | 99.68 148 | 94.81 253 | 99.52 114 | 99.67 79 |
|
| VNet | | | 97.79 98 | 97.40 114 | 98.96 75 | 98.88 147 | 97.55 85 | 98.63 208 | 98.93 65 | 96.74 103 | 99.02 70 | 98.84 169 | 90.33 207 | 99.83 90 | 98.53 55 | 96.66 269 | 99.50 106 |
|
| EIA-MVS | | | 97.75 99 | 97.58 97 | 98.27 138 | 98.38 205 | 96.44 154 | 99.01 86 | 98.60 165 | 95.88 148 | 97.26 204 | 97.53 314 | 94.97 84 | 99.33 214 | 97.38 149 | 99.20 146 | 99.05 213 |
|
| PS-MVSNAJ | | | 97.73 100 | 97.77 90 | 97.62 216 | 98.68 171 | 95.58 212 | 97.34 383 | 98.51 194 | 97.29 65 | 98.66 108 | 97.88 278 | 94.51 91 | 99.90 64 | 97.87 101 | 99.17 148 | 97.39 315 |
|
| casdiffmvs_mvg |  | | 97.72 101 | 97.48 108 | 98.44 125 | 98.42 198 | 96.59 147 | 98.92 113 | 98.44 211 | 96.20 132 | 97.76 172 | 99.20 92 | 91.66 158 | 99.23 238 | 98.27 82 | 98.41 203 | 99.49 111 |
| 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 | 97.32 120 | 98.92 78 | 99.64 33 | 97.10 121 | 99.12 63 | 98.81 107 | 92.34 352 | 98.09 137 | 99.08 128 | 93.01 117 | 99.92 43 | 96.06 206 | 99.77 42 | 99.75 48 |
|
| PVSNet_Blended_VisFu | | | 97.70 103 | 97.46 109 | 98.44 125 | 99.27 93 | 95.91 188 | 98.63 208 | 99.16 40 | 94.48 248 | 97.67 182 | 98.88 164 | 92.80 120 | 99.91 56 | 97.11 157 | 99.12 149 | 99.50 106 |
|
| mvsany_test1 | | | 97.69 104 | 97.70 93 | 97.66 212 | 98.24 230 | 94.18 290 | 97.53 368 | 97.53 360 | 95.52 172 | 99.66 28 | 99.51 26 | 94.30 98 | 99.56 172 | 98.38 70 | 98.62 178 | 99.23 175 |
|
| sasdasda | | | 97.67 105 | 97.23 129 | 98.98 72 | 98.70 166 | 98.38 40 | 99.34 17 | 98.39 235 | 96.76 101 | 97.67 182 | 97.40 324 | 92.26 133 | 99.49 190 | 98.28 79 | 96.28 287 | 99.08 208 |
|
| canonicalmvs | | | 97.67 105 | 97.23 129 | 98.98 72 | 98.70 166 | 98.38 40 | 99.34 17 | 98.39 235 | 96.76 101 | 97.67 182 | 97.40 324 | 92.26 133 | 99.49 190 | 98.28 79 | 96.28 287 | 99.08 208 |
|
| xiu_mvs_v2_base | | | 97.66 107 | 97.70 93 | 97.56 220 | 98.61 180 | 95.46 220 | 97.44 372 | 98.46 207 | 97.15 80 | 98.65 109 | 98.15 253 | 94.33 97 | 99.80 109 | 97.84 104 | 98.66 177 | 97.41 313 |
|
| GDP-MVS | | | 97.64 108 | 97.28 122 | 98.71 92 | 98.30 223 | 97.33 97 | 99.05 74 | 98.52 191 | 96.34 127 | 98.80 91 | 99.05 134 | 89.74 221 | 99.51 186 | 96.86 178 | 98.86 165 | 99.28 163 |
|
| baseline | | | 97.64 108 | 97.44 111 | 98.25 142 | 98.35 210 | 96.20 166 | 99.00 88 | 98.32 253 | 96.33 129 | 98.03 145 | 99.17 100 | 91.35 171 | 99.16 247 | 98.10 87 | 98.29 212 | 99.39 135 |
|
| casdiffmvs |  | | 97.63 110 | 97.41 113 | 98.28 137 | 98.33 218 | 96.14 170 | 98.82 147 | 98.32 253 | 96.38 125 | 97.95 156 | 99.21 90 | 91.23 178 | 99.23 238 | 98.12 86 | 98.37 205 | 99.48 113 |
| Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025 |
| MGCFI-Net | | | 97.62 111 | 97.19 132 | 98.92 78 | 98.66 173 | 98.20 58 | 99.32 22 | 98.38 240 | 96.69 107 | 97.58 195 | 97.42 323 | 92.10 142 | 99.50 189 | 98.28 79 | 96.25 290 | 99.08 208 |
|
| xiu_mvs_v1_base_debu | | | 97.60 112 | 97.56 100 | 97.72 201 | 98.35 210 | 95.98 175 | 97.86 341 | 98.51 194 | 97.13 82 | 99.01 72 | 98.40 225 | 91.56 161 | 99.80 109 | 98.53 55 | 98.68 173 | 97.37 317 |
|
| xiu_mvs_v1_base | | | 97.60 112 | 97.56 100 | 97.72 201 | 98.35 210 | 95.98 175 | 97.86 341 | 98.51 194 | 97.13 82 | 99.01 72 | 98.40 225 | 91.56 161 | 99.80 109 | 98.53 55 | 98.68 173 | 97.37 317 |
|
| xiu_mvs_v1_base_debi | | | 97.60 112 | 97.56 100 | 97.72 201 | 98.35 210 | 95.98 175 | 97.86 341 | 98.51 194 | 97.13 82 | 99.01 72 | 98.40 225 | 91.56 161 | 99.80 109 | 98.53 55 | 98.68 173 | 97.37 317 |
|
| diffmvs_AUTHOR | | | 97.59 115 | 97.44 111 | 98.01 177 | 98.26 228 | 95.47 219 | 98.12 303 | 98.36 246 | 96.38 125 | 98.84 87 | 99.10 118 | 91.13 184 | 99.26 227 | 98.24 83 | 98.56 183 | 99.30 158 |
|
| diffmvs |  | | 97.58 116 | 97.40 114 | 98.13 160 | 98.32 221 | 95.81 202 | 98.06 312 | 98.37 242 | 96.20 132 | 98.74 96 | 98.89 163 | 91.31 174 | 99.25 231 | 98.16 85 | 98.52 187 | 99.34 146 |
| 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 | | | 97.57 117 | 97.37 116 | 98.20 147 | 98.50 187 | 95.86 196 | 98.89 120 | 97.03 404 | 97.29 65 | 98.73 98 | 98.90 160 | 89.41 233 | 99.32 215 | 98.68 45 | 98.86 165 | 99.42 130 |
|
| MVSFormer | | | 97.57 117 | 97.49 106 | 97.84 188 | 98.07 256 | 95.76 206 | 99.47 7 | 98.40 230 | 94.98 213 | 98.79 92 | 98.83 173 | 92.34 129 | 98.41 354 | 96.91 166 | 99.59 96 | 99.34 146 |
|
| alignmvs | | | 97.56 119 | 97.07 140 | 99.01 69 | 98.66 173 | 98.37 47 | 98.83 145 | 98.06 318 | 96.74 103 | 98.00 151 | 97.65 301 | 90.80 195 | 99.48 195 | 98.37 71 | 96.56 273 | 99.19 184 |
|
| E3new | | | 97.55 120 | 97.35 118 | 98.16 151 | 98.48 192 | 95.85 197 | 98.55 231 | 98.41 227 | 95.42 179 | 98.06 140 | 99.12 113 | 92.23 136 | 99.24 234 | 97.43 142 | 98.45 193 | 99.39 135 |
|
| DPM-MVS | | | 97.55 120 | 96.99 147 | 99.23 48 | 99.04 128 | 98.55 32 | 97.17 400 | 98.35 247 | 94.85 223 | 97.93 160 | 98.58 208 | 95.07 81 | 99.71 141 | 92.60 328 | 99.34 138 | 99.43 127 |
|
| OMC-MVS | | | 97.55 120 | 97.34 119 | 98.20 147 | 99.33 74 | 95.92 187 | 98.28 277 | 98.59 172 | 95.52 172 | 97.97 154 | 99.10 118 | 93.28 115 | 99.49 190 | 95.09 244 | 98.88 162 | 99.19 184 |
|
| viewcassd2359sk11 | | | 97.53 123 | 97.32 120 | 98.16 151 | 98.45 195 | 95.83 199 | 98.57 227 | 98.42 226 | 95.52 172 | 98.07 138 | 99.12 113 | 91.81 153 | 99.25 231 | 97.46 140 | 98.48 192 | 99.41 133 |
|
| LuminaMVS | | | 97.49 124 | 97.18 133 | 98.42 129 | 97.50 317 | 97.15 118 | 98.45 249 | 97.68 339 | 96.56 115 | 98.68 103 | 98.78 182 | 89.84 218 | 99.32 215 | 98.60 50 | 98.57 182 | 98.79 238 |
|
| E2 | | | 97.48 125 | 97.25 124 | 98.16 151 | 98.40 202 | 95.79 203 | 98.58 218 | 98.44 211 | 95.58 165 | 98.00 151 | 99.14 107 | 91.21 183 | 99.24 234 | 97.50 135 | 98.43 197 | 99.45 122 |
|
| E3 | | | 97.48 125 | 97.25 124 | 98.16 151 | 98.38 205 | 95.79 203 | 98.58 218 | 98.44 211 | 95.58 165 | 98.00 151 | 99.14 107 | 91.25 177 | 99.24 234 | 97.50 135 | 98.44 194 | 99.45 122 |
|
| KinetiMVS | | | 97.48 125 | 97.05 142 | 98.78 86 | 98.37 208 | 97.30 101 | 98.99 91 | 98.70 141 | 97.18 77 | 99.02 70 | 99.01 140 | 87.50 289 | 99.67 149 | 95.33 234 | 99.33 140 | 99.37 139 |
|
| viewmanbaseed2359cas | | | 97.47 128 | 97.25 124 | 98.14 155 | 98.41 200 | 95.84 198 | 98.57 227 | 98.43 222 | 95.55 170 | 97.97 154 | 99.12 113 | 91.26 176 | 99.15 251 | 97.42 144 | 98.53 186 | 99.43 127 |
|
| PAPM_NR | | | 97.46 129 | 97.11 137 | 98.50 117 | 99.50 48 | 96.41 157 | 98.63 208 | 98.60 165 | 95.18 194 | 97.06 216 | 98.06 259 | 94.26 100 | 99.57 169 | 93.80 295 | 98.87 164 | 99.52 101 |
|
| EPP-MVSNet | | | 97.46 129 | 97.28 122 | 97.99 179 | 98.64 177 | 95.38 224 | 99.33 21 | 98.31 257 | 93.61 300 | 97.19 208 | 99.07 132 | 94.05 103 | 99.23 238 | 96.89 170 | 98.43 197 | 99.37 139 |
|
| 3Dnovator | | 94.51 5 | 97.46 129 | 96.93 151 | 99.07 64 | 97.78 290 | 97.64 81 | 99.35 16 | 99.06 48 | 97.02 87 | 93.75 343 | 99.16 103 | 89.25 238 | 99.92 43 | 97.22 155 | 99.75 55 | 99.64 86 |
|
| CNLPA | | | 97.45 132 | 97.03 144 | 98.73 90 | 99.05 127 | 97.44 94 | 98.07 311 | 98.53 188 | 95.32 187 | 96.80 230 | 98.53 213 | 93.32 113 | 99.72 136 | 94.31 276 | 99.31 141 | 99.02 217 |
|
| lupinMVS | | | 97.44 133 | 97.22 131 | 98.12 163 | 98.07 256 | 95.76 206 | 97.68 357 | 97.76 336 | 94.50 247 | 98.79 92 | 98.61 203 | 92.34 129 | 99.30 220 | 97.58 123 | 99.59 96 | 99.31 154 |
|
| 3Dnovator+ | | 94.38 6 | 97.43 134 | 96.78 162 | 99.38 23 | 97.83 287 | 98.52 33 | 99.37 13 | 98.71 137 | 97.09 85 | 92.99 373 | 99.13 110 | 89.36 235 | 99.89 68 | 96.97 162 | 99.57 100 | 99.71 63 |
|
| Vis-MVSNet |  | | 97.42 135 | 97.11 137 | 98.34 134 | 98.66 173 | 96.23 165 | 99.22 41 | 99.00 53 | 96.63 111 | 98.04 144 | 99.21 90 | 88.05 276 | 99.35 211 | 96.01 209 | 99.21 145 | 99.45 122 |
| Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
| API-MVS | | | 97.41 136 | 97.25 124 | 97.91 183 | 98.70 166 | 96.80 133 | 98.82 147 | 98.69 143 | 94.53 242 | 98.11 135 | 98.28 240 | 94.50 94 | 99.57 169 | 94.12 284 | 99.49 119 | 97.37 317 |
|
| sss | | | 97.39 137 | 96.98 149 | 98.61 101 | 98.60 181 | 96.61 142 | 98.22 283 | 98.93 65 | 93.97 270 | 98.01 150 | 98.48 218 | 91.98 146 | 99.85 84 | 96.45 193 | 98.15 217 | 99.39 135 |
|
| test_cas_vis1_n_1920 | | | 97.38 138 | 97.36 117 | 97.45 224 | 98.95 142 | 93.25 328 | 99.00 88 | 98.53 188 | 97.70 37 | 99.77 18 | 99.35 60 | 84.71 345 | 99.85 84 | 98.57 52 | 99.66 79 | 99.26 171 |
|
| PVSNet_Blended | | | 97.38 138 | 97.12 136 | 98.14 155 | 99.25 96 | 95.35 227 | 97.28 388 | 99.26 16 | 93.13 322 | 97.94 158 | 98.21 248 | 92.74 121 | 99.81 102 | 96.88 172 | 99.40 132 | 99.27 164 |
|
| E4 | | | 97.37 140 | 97.13 135 | 98.12 163 | 98.27 227 | 95.70 208 | 98.59 214 | 98.44 211 | 95.56 167 | 97.80 169 | 99.18 98 | 90.57 202 | 99.26 227 | 97.45 141 | 98.28 214 | 99.40 134 |
|
| WTY-MVS | | | 97.37 140 | 96.92 152 | 98.72 91 | 98.86 151 | 96.89 131 | 98.31 271 | 98.71 137 | 95.26 190 | 97.67 182 | 98.56 212 | 92.21 138 | 99.78 124 | 95.89 211 | 96.85 263 | 99.48 113 |
|
| AstraMVS | | | 97.34 142 | 97.24 128 | 97.65 213 | 98.13 250 | 94.15 291 | 98.94 105 | 96.25 436 | 97.47 54 | 98.60 112 | 99.28 76 | 89.67 223 | 99.41 205 | 98.73 43 | 98.07 221 | 99.38 138 |
|
| viewmacassd2359aftdt | | | 97.32 143 | 97.07 140 | 98.08 168 | 98.30 223 | 95.69 209 | 98.62 211 | 98.44 211 | 95.56 167 | 97.86 166 | 99.22 88 | 89.91 216 | 99.14 254 | 97.29 152 | 98.43 197 | 99.42 130 |
|
| jason | | | 97.32 143 | 97.08 139 | 98.06 172 | 97.45 323 | 95.59 211 | 97.87 339 | 97.91 329 | 94.79 226 | 98.55 115 | 98.83 173 | 91.12 186 | 99.23 238 | 97.58 123 | 99.60 94 | 99.34 146 |
| jason: jason. |
| MVS_Test | | | 97.28 145 | 97.00 145 | 98.13 160 | 98.33 218 | 95.97 180 | 98.74 173 | 98.07 313 | 94.27 255 | 98.44 123 | 98.07 258 | 92.48 125 | 99.26 227 | 96.43 194 | 98.19 216 | 99.16 190 |
|
| EPNet | | | 97.28 145 | 96.87 154 | 98.51 114 | 94.98 435 | 96.14 170 | 98.90 116 | 97.02 407 | 98.28 21 | 95.99 265 | 99.11 116 | 91.36 170 | 99.89 68 | 96.98 161 | 99.19 147 | 99.50 106 |
| Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
| SSM_0404 | | | 97.26 147 | 97.00 145 | 98.03 174 | 98.46 193 | 95.99 174 | 98.62 211 | 98.44 211 | 94.77 227 | 97.24 205 | 98.93 154 | 91.22 179 | 99.28 224 | 96.54 188 | 98.74 172 | 98.84 234 |
|
| mvsmamba | | | 97.25 148 | 96.99 147 | 98.02 176 | 98.34 215 | 95.54 216 | 99.18 53 | 97.47 366 | 95.04 207 | 98.15 132 | 98.57 211 | 89.46 230 | 99.31 219 | 97.68 117 | 99.01 155 | 99.22 177 |
|
| viewdifsd2359ckpt13 | | | 97.24 149 | 96.97 150 | 98.06 172 | 98.43 196 | 95.77 205 | 98.59 214 | 98.34 250 | 94.81 224 | 97.60 193 | 98.94 152 | 90.78 199 | 99.09 266 | 96.93 165 | 98.33 208 | 99.32 153 |
|
| test_yl | | | 97.22 150 | 96.78 162 | 98.54 109 | 98.73 161 | 96.60 143 | 98.45 249 | 98.31 257 | 94.70 230 | 98.02 147 | 98.42 223 | 90.80 195 | 99.70 142 | 96.81 179 | 96.79 265 | 99.34 146 |
|
| DCV-MVSNet | | | 97.22 150 | 96.78 162 | 98.54 109 | 98.73 161 | 96.60 143 | 98.45 249 | 98.31 257 | 94.70 230 | 98.02 147 | 98.42 223 | 90.80 195 | 99.70 142 | 96.81 179 | 96.79 265 | 99.34 146 |
|
| IS-MVSNet | | | 97.22 150 | 96.88 153 | 98.25 142 | 98.85 154 | 96.36 160 | 99.19 49 | 97.97 323 | 95.39 181 | 97.23 206 | 98.99 143 | 91.11 187 | 98.93 292 | 94.60 264 | 98.59 180 | 99.47 115 |
|
| viewdifsd2359ckpt07 | | | 97.20 153 | 97.05 142 | 97.65 213 | 98.40 202 | 94.33 283 | 98.39 262 | 98.43 222 | 95.67 160 | 97.66 186 | 99.08 128 | 90.04 213 | 99.32 215 | 97.47 139 | 98.29 212 | 99.31 154 |
|
| PLC |  | 95.07 4 | 97.20 153 | 96.78 162 | 98.44 125 | 99.29 88 | 96.31 164 | 98.14 300 | 98.76 125 | 92.41 350 | 96.39 253 | 98.31 238 | 94.92 86 | 99.78 124 | 94.06 287 | 98.77 171 | 99.23 175 |
| Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
| CHOSEN 280x420 | | | 97.18 155 | 97.18 133 | 97.20 237 | 98.81 157 | 93.27 325 | 95.78 446 | 99.15 42 | 95.25 191 | 96.79 231 | 98.11 256 | 92.29 132 | 99.07 269 | 98.56 54 | 99.85 6 | 99.25 173 |
|
| SSM_0407 | | | 97.17 156 | 96.87 154 | 98.08 168 | 98.19 238 | 95.90 189 | 98.52 234 | 98.44 211 | 94.77 227 | 96.75 232 | 98.93 154 | 91.22 179 | 99.22 242 | 96.54 188 | 98.43 197 | 99.10 201 |
|
| LS3D | | | 97.16 157 | 96.66 171 | 98.68 94 | 98.53 186 | 97.19 115 | 98.93 111 | 98.90 73 | 92.83 335 | 95.99 265 | 99.37 54 | 92.12 141 | 99.87 79 | 93.67 299 | 99.57 100 | 98.97 222 |
|
| AdaColmap |  | | 97.15 158 | 96.70 167 | 98.48 120 | 99.16 115 | 96.69 139 | 98.01 318 | 98.89 75 | 94.44 250 | 96.83 226 | 98.68 198 | 90.69 200 | 99.76 130 | 94.36 272 | 99.29 142 | 98.98 221 |
|
| viewdifsd2359ckpt09 | | | 97.13 159 | 96.79 160 | 98.14 155 | 98.43 196 | 95.90 189 | 98.52 234 | 98.37 242 | 94.32 253 | 97.33 200 | 98.86 167 | 90.23 211 | 99.16 247 | 96.81 179 | 98.25 215 | 99.36 143 |
|
| mamv4 | | | 97.13 159 | 98.11 76 | 94.17 410 | 98.97 140 | 83.70 455 | 98.66 201 | 98.71 137 | 94.63 236 | 97.83 167 | 98.90 160 | 96.25 32 | 99.55 179 | 99.27 28 | 99.76 48 | 99.27 164 |
|
| Effi-MVS+ | | | 97.12 161 | 96.69 168 | 98.39 132 | 98.19 238 | 96.72 138 | 97.37 379 | 98.43 222 | 93.71 288 | 97.65 187 | 98.02 262 | 92.20 139 | 99.25 231 | 96.87 175 | 97.79 230 | 99.19 184 |
|
| CHOSEN 1792x2688 | | | 97.12 161 | 96.80 158 | 98.08 168 | 99.30 83 | 94.56 272 | 98.05 313 | 99.71 1 | 93.57 302 | 97.09 212 | 98.91 159 | 88.17 270 | 99.89 68 | 96.87 175 | 99.56 108 | 99.81 24 |
|
| F-COLMAP | | | 97.09 163 | 96.80 158 | 97.97 180 | 99.45 61 | 94.95 251 | 98.55 231 | 98.62 164 | 93.02 327 | 96.17 260 | 98.58 208 | 94.01 104 | 99.81 102 | 93.95 289 | 98.90 160 | 99.14 194 |
|
| RRT-MVS | | | 97.03 164 | 96.78 162 | 97.77 197 | 97.90 283 | 94.34 281 | 99.12 63 | 98.35 247 | 95.87 149 | 98.06 140 | 98.70 196 | 86.45 308 | 99.63 159 | 98.04 92 | 98.54 185 | 99.35 144 |
|
| TAMVS | | | 97.02 165 | 96.79 160 | 97.70 204 | 98.06 259 | 95.31 230 | 98.52 234 | 98.31 257 | 93.95 271 | 97.05 217 | 98.61 203 | 93.49 111 | 98.52 336 | 95.33 234 | 97.81 229 | 99.29 161 |
|
| viewmambaseed2359dif | | | 97.01 166 | 96.84 156 | 97.51 222 | 98.19 238 | 94.21 289 | 98.16 296 | 98.23 278 | 93.61 300 | 97.78 170 | 99.13 110 | 90.79 198 | 99.18 246 | 97.24 153 | 98.40 204 | 99.15 191 |
|
| CDS-MVSNet | | | 96.99 167 | 96.69 168 | 97.90 184 | 98.05 261 | 95.98 175 | 98.20 286 | 98.33 252 | 93.67 295 | 96.95 219 | 98.49 217 | 93.54 110 | 98.42 347 | 95.24 241 | 97.74 233 | 99.31 154 |
| Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
| CANet_DTU | | | 96.96 168 | 96.55 176 | 98.21 145 | 98.17 247 | 96.07 173 | 97.98 322 | 98.21 280 | 97.24 72 | 97.13 210 | 98.93 154 | 86.88 300 | 99.91 56 | 95.00 247 | 99.37 136 | 98.66 261 |
|
| 114514_t | | | 96.93 169 | 96.27 189 | 98.92 78 | 99.50 48 | 97.63 82 | 98.85 139 | 98.90 73 | 84.80 451 | 97.77 171 | 99.11 116 | 92.84 119 | 99.66 152 | 94.85 250 | 99.77 42 | 99.47 115 |
|
| MAR-MVS | | | 96.91 170 | 96.40 183 | 98.45 123 | 98.69 169 | 96.90 129 | 98.66 201 | 98.68 146 | 92.40 351 | 97.07 215 | 97.96 269 | 91.54 164 | 99.75 132 | 93.68 297 | 98.92 159 | 98.69 255 |
| 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 | | | 96.90 171 | 96.49 180 | 98.14 155 | 99.33 74 | 95.56 213 | 97.38 377 | 99.65 2 | 92.34 352 | 97.61 190 | 98.20 249 | 89.29 237 | 99.10 265 | 96.97 162 | 97.60 238 | 99.77 40 |
|
| Vis-MVSNet (Re-imp) | | | 96.87 172 | 96.55 176 | 97.83 189 | 98.73 161 | 95.46 220 | 99.20 47 | 98.30 264 | 94.96 215 | 96.60 241 | 98.87 165 | 90.05 212 | 98.59 331 | 93.67 299 | 98.60 179 | 99.46 120 |
|
| SDMVSNet | | | 96.85 173 | 96.42 181 | 98.14 155 | 99.30 83 | 96.38 158 | 99.21 44 | 99.23 28 | 95.92 145 | 95.96 267 | 98.76 190 | 85.88 320 | 99.44 202 | 97.93 96 | 95.59 302 | 98.60 266 |
|
| PAPR | | | 96.84 174 | 96.24 191 | 98.65 97 | 98.72 165 | 96.92 128 | 97.36 381 | 98.57 179 | 93.33 311 | 96.67 236 | 97.57 310 | 94.30 98 | 99.56 172 | 91.05 371 | 98.59 180 | 99.47 115 |
|
| HY-MVS | | 93.96 8 | 96.82 175 | 96.23 192 | 98.57 104 | 98.46 193 | 97.00 124 | 98.14 300 | 98.21 280 | 93.95 271 | 96.72 235 | 97.99 266 | 91.58 159 | 99.76 130 | 94.51 268 | 96.54 274 | 98.95 225 |
|
| mamba_0408 | | | 96.81 176 | 96.38 184 | 98.09 167 | 98.19 238 | 95.90 189 | 95.69 447 | 98.32 253 | 94.51 245 | 96.75 232 | 98.73 192 | 90.99 191 | 99.27 226 | 95.83 214 | 98.43 197 | 99.10 201 |
|
| UGNet | | | 96.78 177 | 96.30 188 | 98.19 150 | 98.24 230 | 95.89 194 | 98.88 127 | 98.93 65 | 97.39 59 | 96.81 229 | 97.84 282 | 82.60 374 | 99.90 64 | 96.53 190 | 99.49 119 | 98.79 238 |
| 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 | | | 96.74 178 | 96.64 172 | 97.05 252 | 97.99 270 | 92.82 340 | 98.45 249 | 98.27 267 | 95.16 195 | 97.30 201 | 98.79 178 | 91.53 165 | 99.06 270 | 94.74 255 | 97.54 242 | 99.27 164 |
|
| IMVS_0403 | | | 96.74 178 | 96.61 173 | 97.12 246 | 97.99 270 | 92.82 340 | 98.47 247 | 98.27 267 | 95.16 195 | 97.13 210 | 98.79 178 | 91.44 168 | 99.26 227 | 94.74 255 | 97.54 242 | 99.27 164 |
|
| PVSNet_BlendedMVS | | | 96.73 180 | 96.60 174 | 97.12 246 | 99.25 96 | 95.35 227 | 98.26 280 | 99.26 16 | 94.28 254 | 97.94 158 | 97.46 317 | 92.74 121 | 99.81 102 | 96.88 172 | 93.32 340 | 96.20 411 |
|
| SSM_04072 | | | 96.71 181 | 96.38 184 | 97.68 207 | 98.19 238 | 95.90 189 | 95.69 447 | 98.32 253 | 94.51 245 | 96.75 232 | 98.73 192 | 90.99 191 | 98.02 394 | 95.83 214 | 98.43 197 | 99.10 201 |
|
| test_vis1_n_1920 | | | 96.71 181 | 96.84 156 | 96.31 324 | 99.11 122 | 89.74 405 | 99.05 74 | 98.58 177 | 98.08 24 | 99.87 4 | 99.37 54 | 78.48 406 | 99.93 34 | 99.29 27 | 99.69 73 | 99.27 164 |
|
| mvs_anonymous | | | 96.70 183 | 96.53 178 | 97.18 240 | 98.19 238 | 93.78 301 | 98.31 271 | 98.19 284 | 94.01 267 | 94.47 299 | 98.27 243 | 92.08 144 | 98.46 342 | 97.39 148 | 97.91 225 | 99.31 154 |
|
| Elysia | | | 96.64 184 | 96.02 201 | 98.51 114 | 98.04 263 | 97.30 101 | 98.74 173 | 98.60 165 | 95.04 207 | 97.91 162 | 98.84 169 | 83.59 369 | 99.48 195 | 94.20 280 | 99.25 143 | 98.75 247 |
|
| StellarMVS | | | 96.64 184 | 96.02 201 | 98.51 114 | 98.04 263 | 97.30 101 | 98.74 173 | 98.60 165 | 95.04 207 | 97.91 162 | 98.84 169 | 83.59 369 | 99.48 195 | 94.20 280 | 99.25 143 | 98.75 247 |
|
| 1112_ss | | | 96.63 186 | 96.00 203 | 98.50 117 | 98.56 182 | 96.37 159 | 98.18 294 | 98.10 306 | 92.92 331 | 94.84 287 | 98.43 221 | 92.14 140 | 99.58 168 | 94.35 273 | 96.51 275 | 99.56 100 |
|
| PMMVS | | | 96.60 187 | 96.33 187 | 97.41 228 | 97.90 283 | 93.93 297 | 97.35 382 | 98.41 227 | 92.84 334 | 97.76 172 | 97.45 319 | 91.10 188 | 99.20 243 | 96.26 199 | 97.91 225 | 99.11 199 |
|
| DP-MVS | | | 96.59 188 | 95.93 206 | 98.57 104 | 99.34 71 | 96.19 168 | 98.70 188 | 98.39 235 | 89.45 422 | 94.52 297 | 99.35 60 | 91.85 150 | 99.85 84 | 92.89 323 | 98.88 162 | 99.68 75 |
|
| PatchMatch-RL | | | 96.59 188 | 96.03 200 | 98.27 138 | 99.31 79 | 96.51 151 | 97.91 331 | 99.06 48 | 93.72 287 | 96.92 223 | 98.06 259 | 88.50 264 | 99.65 153 | 91.77 353 | 99.00 157 | 98.66 261 |
|
| GeoE | | | 96.58 190 | 96.07 197 | 98.10 166 | 98.35 210 | 95.89 194 | 99.34 17 | 98.12 300 | 93.12 323 | 96.09 261 | 98.87 165 | 89.71 222 | 98.97 282 | 92.95 319 | 98.08 220 | 99.43 127 |
|
| icg_test_0407_2 | | | 96.56 191 | 96.50 179 | 96.73 276 | 97.99 270 | 92.82 340 | 97.18 397 | 98.27 267 | 95.16 195 | 97.30 201 | 98.79 178 | 91.53 165 | 98.10 385 | 94.74 255 | 97.54 242 | 99.27 164 |
|
| XVG-OURS | | | 96.55 192 | 96.41 182 | 96.99 255 | 98.75 160 | 93.76 302 | 97.50 371 | 98.52 191 | 95.67 160 | 96.83 226 | 99.30 74 | 88.95 252 | 99.53 182 | 95.88 212 | 96.26 289 | 97.69 306 |
|
| FIs | | | 96.51 193 | 96.12 196 | 97.67 209 | 97.13 347 | 97.54 87 | 99.36 14 | 99.22 33 | 95.89 147 | 94.03 328 | 98.35 231 | 91.98 146 | 98.44 345 | 96.40 195 | 92.76 348 | 97.01 325 |
|
| XVG-OURS-SEG-HR | | | 96.51 193 | 96.34 186 | 97.02 254 | 98.77 159 | 93.76 302 | 97.79 350 | 98.50 199 | 95.45 176 | 96.94 220 | 99.09 126 | 87.87 281 | 99.55 179 | 96.76 184 | 95.83 301 | 97.74 303 |
|
| PS-MVSNAJss | | | 96.43 195 | 96.26 190 | 96.92 265 | 95.84 415 | 95.08 241 | 99.16 55 | 98.50 199 | 95.87 149 | 93.84 338 | 98.34 235 | 94.51 91 | 98.61 327 | 96.88 172 | 93.45 335 | 97.06 323 |
|
| test_fmvs1 | | | 96.42 196 | 96.67 170 | 95.66 354 | 98.82 156 | 88.53 432 | 98.80 156 | 98.20 282 | 96.39 124 | 99.64 30 | 99.20 92 | 80.35 394 | 99.67 149 | 99.04 33 | 99.57 100 | 98.78 242 |
|
| FC-MVSNet-test | | | 96.42 196 | 96.05 198 | 97.53 221 | 96.95 356 | 97.27 105 | 99.36 14 | 99.23 28 | 95.83 151 | 93.93 331 | 98.37 229 | 92.00 145 | 98.32 366 | 96.02 208 | 92.72 349 | 97.00 326 |
|
| ab-mvs | | | 96.42 196 | 95.71 217 | 98.55 107 | 98.63 178 | 96.75 136 | 97.88 338 | 98.74 129 | 93.84 277 | 96.54 246 | 98.18 251 | 85.34 331 | 99.75 132 | 95.93 210 | 96.35 279 | 99.15 191 |
|
| FA-MVS(test-final) | | | 96.41 199 | 95.94 205 | 97.82 191 | 98.21 234 | 95.20 235 | 97.80 348 | 97.58 350 | 93.21 317 | 97.36 199 | 97.70 294 | 89.47 228 | 99.56 172 | 94.12 284 | 97.99 222 | 98.71 253 |
|
| PVSNet | | 91.96 18 | 96.35 200 | 96.15 193 | 96.96 260 | 99.17 111 | 92.05 357 | 96.08 439 | 98.68 146 | 93.69 291 | 97.75 174 | 97.80 288 | 88.86 253 | 99.69 147 | 94.26 278 | 99.01 155 | 99.15 191 |
|
| Test_1112_low_res | | | 96.34 201 | 95.66 222 | 98.36 133 | 98.56 182 | 95.94 183 | 97.71 355 | 98.07 313 | 92.10 361 | 94.79 291 | 97.29 332 | 91.75 154 | 99.56 172 | 94.17 282 | 96.50 276 | 99.58 98 |
|
| viewdifsd2359ckpt11 | | | 96.30 202 | 96.13 194 | 96.81 271 | 98.10 253 | 92.10 353 | 98.49 245 | 98.40 230 | 96.02 140 | 97.61 190 | 99.31 71 | 86.37 310 | 99.29 222 | 97.52 131 | 93.36 339 | 99.04 214 |
|
| viewmsd2359difaftdt | | | 96.30 202 | 96.13 194 | 96.81 271 | 98.10 253 | 92.10 353 | 98.49 245 | 98.40 230 | 96.02 140 | 97.61 190 | 99.31 71 | 86.37 310 | 99.30 220 | 97.52 131 | 93.37 338 | 99.04 214 |
|
| Effi-MVS+-dtu | | | 96.29 204 | 96.56 175 | 95.51 359 | 97.89 285 | 90.22 397 | 98.80 156 | 98.10 306 | 96.57 114 | 96.45 251 | 96.66 389 | 90.81 194 | 98.91 295 | 95.72 221 | 97.99 222 | 97.40 314 |
|
| QAPM | | | 96.29 204 | 95.40 228 | 98.96 75 | 97.85 286 | 97.60 84 | 99.23 37 | 98.93 65 | 89.76 416 | 93.11 370 | 99.02 136 | 89.11 243 | 99.93 34 | 91.99 347 | 99.62 91 | 99.34 146 |
|
| Fast-Effi-MVS+ | | | 96.28 206 | 95.70 219 | 98.03 174 | 98.29 225 | 95.97 180 | 98.58 218 | 98.25 276 | 91.74 369 | 95.29 280 | 97.23 337 | 91.03 190 | 99.15 251 | 92.90 321 | 97.96 224 | 98.97 222 |
|
| nrg030 | | | 96.28 206 | 95.72 214 | 97.96 182 | 96.90 361 | 98.15 63 | 99.39 11 | 98.31 257 | 95.47 175 | 94.42 305 | 98.35 231 | 92.09 143 | 98.69 319 | 97.50 135 | 89.05 400 | 97.04 324 |
|
| 1314 | | | 96.25 208 | 95.73 213 | 97.79 193 | 97.13 347 | 95.55 215 | 98.19 289 | 98.59 172 | 93.47 306 | 92.03 399 | 97.82 286 | 91.33 172 | 99.49 190 | 94.62 263 | 98.44 194 | 98.32 286 |
|
| sd_testset | | | 96.17 209 | 95.76 212 | 97.42 227 | 99.30 83 | 94.34 281 | 98.82 147 | 99.08 46 | 95.92 145 | 95.96 267 | 98.76 190 | 82.83 373 | 99.32 215 | 95.56 227 | 95.59 302 | 98.60 266 |
|
| h-mvs33 | | | 96.17 209 | 95.62 223 | 97.81 192 | 99.03 129 | 94.45 274 | 98.64 205 | 98.75 127 | 97.48 52 | 98.67 104 | 98.72 195 | 89.76 219 | 99.86 83 | 97.95 94 | 81.59 450 | 99.11 199 |
|
| HQP_MVS | | | 96.14 211 | 95.90 207 | 96.85 268 | 97.42 325 | 94.60 270 | 98.80 156 | 98.56 182 | 97.28 67 | 95.34 276 | 98.28 240 | 87.09 295 | 99.03 275 | 96.07 203 | 94.27 310 | 96.92 333 |
|
| tttt0517 | | | 96.07 212 | 95.51 226 | 97.78 194 | 98.41 200 | 94.84 255 | 99.28 29 | 94.33 459 | 94.26 256 | 97.64 188 | 98.64 202 | 84.05 360 | 99.47 199 | 95.34 233 | 97.60 238 | 99.03 216 |
|
| MVSTER | | | 96.06 213 | 95.72 214 | 97.08 250 | 98.23 232 | 95.93 186 | 98.73 179 | 98.27 267 | 94.86 221 | 95.07 282 | 98.09 257 | 88.21 269 | 98.54 334 | 96.59 186 | 93.46 333 | 96.79 352 |
|
| thisisatest0530 | | | 96.01 214 | 95.36 233 | 97.97 180 | 98.38 205 | 95.52 217 | 98.88 127 | 94.19 461 | 94.04 262 | 97.64 188 | 98.31 238 | 83.82 367 | 99.46 200 | 95.29 238 | 97.70 235 | 98.93 227 |
|
| test_djsdf | | | 96.00 215 | 95.69 220 | 96.93 262 | 95.72 417 | 95.49 218 | 99.47 7 | 98.40 230 | 94.98 213 | 94.58 295 | 97.86 279 | 89.16 241 | 98.41 354 | 96.91 166 | 94.12 318 | 96.88 342 |
|
| EI-MVSNet | | | 95.96 216 | 95.83 209 | 96.36 320 | 97.93 281 | 93.70 308 | 98.12 303 | 98.27 267 | 93.70 290 | 95.07 282 | 99.02 136 | 92.23 136 | 98.54 334 | 94.68 259 | 93.46 333 | 96.84 348 |
|
| VortexMVS | | | 95.95 217 | 95.79 210 | 96.42 316 | 98.29 225 | 93.96 296 | 98.68 194 | 98.31 257 | 96.02 140 | 94.29 313 | 97.57 310 | 89.47 228 | 98.37 361 | 97.51 134 | 91.93 357 | 96.94 331 |
|
| ECVR-MVS |  | | 95.95 217 | 95.71 217 | 96.65 284 | 99.02 130 | 90.86 379 | 99.03 81 | 91.80 472 | 96.96 92 | 98.10 136 | 99.26 80 | 81.31 380 | 99.51 186 | 96.90 169 | 99.04 152 | 99.59 94 |
|
| BH-untuned | | | 95.95 217 | 95.72 214 | 96.65 284 | 98.55 184 | 92.26 349 | 98.23 282 | 97.79 335 | 93.73 285 | 94.62 294 | 98.01 264 | 88.97 251 | 99.00 281 | 93.04 316 | 98.51 188 | 98.68 257 |
|
| test1111 | | | 95.94 220 | 95.78 211 | 96.41 317 | 98.99 137 | 90.12 398 | 99.04 78 | 92.45 471 | 96.99 91 | 98.03 145 | 99.27 79 | 81.40 379 | 99.48 195 | 96.87 175 | 99.04 152 | 99.63 88 |
|
| MSDG | | | 95.93 221 | 95.30 240 | 97.83 189 | 98.90 145 | 95.36 225 | 96.83 426 | 98.37 242 | 91.32 385 | 94.43 304 | 98.73 192 | 90.27 209 | 99.60 165 | 90.05 385 | 98.82 169 | 98.52 274 |
|
| BH-RMVSNet | | | 95.92 222 | 95.32 238 | 97.69 205 | 98.32 221 | 94.64 264 | 98.19 289 | 97.45 371 | 94.56 240 | 96.03 263 | 98.61 203 | 85.02 336 | 99.12 259 | 90.68 376 | 99.06 151 | 99.30 158 |
|
| test_fmvs1_n | | | 95.90 223 | 95.99 204 | 95.63 355 | 98.67 172 | 88.32 436 | 99.26 32 | 98.22 279 | 96.40 123 | 99.67 27 | 99.26 80 | 73.91 445 | 99.70 142 | 99.02 34 | 99.50 117 | 98.87 231 |
|
| Fast-Effi-MVS+-dtu | | | 95.87 224 | 95.85 208 | 95.91 341 | 97.74 295 | 91.74 363 | 98.69 191 | 98.15 296 | 95.56 167 | 94.92 285 | 97.68 299 | 88.98 250 | 98.79 313 | 93.19 311 | 97.78 231 | 97.20 321 |
|
| LFMVS | | | 95.86 225 | 94.98 255 | 98.47 121 | 98.87 150 | 96.32 162 | 98.84 143 | 96.02 437 | 93.40 309 | 98.62 110 | 99.20 92 | 74.99 437 | 99.63 159 | 97.72 110 | 97.20 251 | 99.46 120 |
|
| baseline1 | | | 95.84 226 | 95.12 248 | 98.01 177 | 98.49 191 | 95.98 175 | 98.73 179 | 97.03 404 | 95.37 184 | 96.22 256 | 98.19 250 | 89.96 215 | 99.16 247 | 94.60 264 | 87.48 416 | 98.90 230 |
|
| OpenMVS |  | 93.04 13 | 95.83 227 | 95.00 253 | 98.32 135 | 97.18 344 | 97.32 98 | 99.21 44 | 98.97 57 | 89.96 412 | 91.14 408 | 99.05 134 | 86.64 303 | 99.92 43 | 93.38 305 | 99.47 122 | 97.73 304 |
|
| IMVS_0404 | | | 95.82 228 | 95.52 224 | 96.73 276 | 97.99 270 | 92.82 340 | 97.23 390 | 98.27 267 | 95.16 195 | 94.31 311 | 98.79 178 | 85.63 324 | 98.10 385 | 94.74 255 | 97.54 242 | 99.27 164 |
|
| VDD-MVS | | | 95.82 228 | 95.23 242 | 97.61 217 | 98.84 155 | 93.98 295 | 98.68 194 | 97.40 375 | 95.02 211 | 97.95 156 | 99.34 68 | 74.37 443 | 99.78 124 | 98.64 48 | 96.80 264 | 99.08 208 |
|
| UniMVSNet (Re) | | | 95.78 230 | 95.19 244 | 97.58 218 | 96.99 354 | 97.47 91 | 98.79 164 | 99.18 37 | 95.60 163 | 93.92 332 | 97.04 359 | 91.68 156 | 98.48 338 | 95.80 218 | 87.66 415 | 96.79 352 |
|
| VPA-MVSNet | | | 95.75 231 | 95.11 249 | 97.69 205 | 97.24 336 | 97.27 105 | 98.94 105 | 99.23 28 | 95.13 200 | 95.51 274 | 97.32 330 | 85.73 322 | 98.91 295 | 97.33 151 | 89.55 391 | 96.89 341 |
|
| HQP-MVS | | | 95.72 232 | 95.40 228 | 96.69 282 | 97.20 340 | 94.25 287 | 98.05 313 | 98.46 207 | 96.43 118 | 94.45 300 | 97.73 291 | 86.75 301 | 98.96 286 | 95.30 236 | 94.18 314 | 96.86 347 |
|
| hse-mvs2 | | | 95.71 233 | 95.30 240 | 96.93 262 | 98.50 187 | 93.53 313 | 98.36 263 | 98.10 306 | 97.48 52 | 98.67 104 | 97.99 266 | 89.76 219 | 99.02 278 | 97.95 94 | 80.91 456 | 98.22 289 |
|
| UniMVSNet_NR-MVSNet | | | 95.71 233 | 95.15 245 | 97.40 230 | 96.84 364 | 96.97 125 | 98.74 173 | 99.24 20 | 95.16 195 | 93.88 334 | 97.72 293 | 91.68 156 | 98.31 368 | 95.81 216 | 87.25 421 | 96.92 333 |
|
| PatchmatchNet |  | | 95.71 233 | 95.52 224 | 96.29 326 | 97.58 308 | 90.72 383 | 96.84 425 | 97.52 361 | 94.06 261 | 97.08 213 | 96.96 369 | 89.24 239 | 98.90 298 | 92.03 346 | 98.37 205 | 99.26 171 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
| OPM-MVS | | | 95.69 236 | 95.33 237 | 96.76 275 | 96.16 400 | 94.63 265 | 98.43 257 | 98.39 235 | 96.64 110 | 95.02 284 | 98.78 182 | 85.15 335 | 99.05 271 | 95.21 243 | 94.20 313 | 96.60 376 |
| Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS). |
| ACMM | | 93.85 9 | 95.69 236 | 95.38 232 | 96.61 292 | 97.61 305 | 93.84 300 | 98.91 115 | 98.44 211 | 95.25 191 | 94.28 314 | 98.47 219 | 86.04 319 | 99.12 259 | 95.50 230 | 93.95 323 | 96.87 345 |
| Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
| tpmrst | | | 95.63 238 | 95.69 220 | 95.44 363 | 97.54 313 | 88.54 431 | 96.97 411 | 97.56 353 | 93.50 304 | 97.52 197 | 96.93 373 | 89.49 226 | 99.16 247 | 95.25 240 | 96.42 278 | 98.64 263 |
|
| FE-MVS | | | 95.62 239 | 94.90 259 | 97.78 194 | 98.37 208 | 94.92 252 | 97.17 400 | 97.38 377 | 90.95 396 | 97.73 177 | 97.70 294 | 85.32 333 | 99.63 159 | 91.18 363 | 98.33 208 | 98.79 238 |
|
| LPG-MVS_test | | | 95.62 239 | 95.34 234 | 96.47 310 | 97.46 320 | 93.54 311 | 98.99 91 | 98.54 186 | 94.67 234 | 94.36 308 | 98.77 185 | 85.39 328 | 99.11 261 | 95.71 222 | 94.15 316 | 96.76 355 |
|
| CLD-MVS | | | 95.62 239 | 95.34 234 | 96.46 313 | 97.52 316 | 93.75 304 | 97.27 389 | 98.46 207 | 95.53 171 | 94.42 305 | 98.00 265 | 86.21 314 | 98.97 282 | 96.25 201 | 94.37 308 | 96.66 370 |
| Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
| thisisatest0515 | | | 95.61 242 | 94.89 260 | 97.76 198 | 98.15 249 | 95.15 238 | 96.77 427 | 94.41 457 | 92.95 330 | 97.18 209 | 97.43 321 | 84.78 342 | 99.45 201 | 94.63 261 | 97.73 234 | 98.68 257 |
|
| MonoMVSNet | | | 95.51 243 | 95.45 227 | 95.68 352 | 95.54 422 | 90.87 378 | 98.92 113 | 97.37 378 | 95.79 153 | 95.53 273 | 97.38 326 | 89.58 225 | 97.68 416 | 96.40 195 | 92.59 350 | 98.49 276 |
|
| thres600view7 | | | 95.49 244 | 94.77 263 | 97.67 209 | 98.98 138 | 95.02 243 | 98.85 139 | 96.90 414 | 95.38 182 | 96.63 238 | 96.90 375 | 84.29 352 | 99.59 166 | 88.65 409 | 96.33 280 | 98.40 280 |
|
| test_vis1_n | | | 95.47 245 | 95.13 246 | 96.49 307 | 97.77 291 | 90.41 393 | 99.27 31 | 98.11 303 | 96.58 112 | 99.66 28 | 99.18 98 | 67.00 459 | 99.62 163 | 99.21 29 | 99.40 132 | 99.44 125 |
|
| SCA | | | 95.46 246 | 95.13 246 | 96.46 313 | 97.67 300 | 91.29 371 | 97.33 384 | 97.60 349 | 94.68 233 | 96.92 223 | 97.10 344 | 83.97 362 | 98.89 299 | 92.59 330 | 98.32 211 | 99.20 180 |
|
| IterMVS-LS | | | 95.46 246 | 95.21 243 | 96.22 328 | 98.12 251 | 93.72 307 | 98.32 270 | 98.13 299 | 93.71 288 | 94.26 315 | 97.31 331 | 92.24 135 | 98.10 385 | 94.63 261 | 90.12 382 | 96.84 348 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
| testing3-2 | | | 95.45 248 | 95.34 234 | 95.77 350 | 98.69 169 | 88.75 427 | 98.87 130 | 97.21 391 | 96.13 135 | 97.22 207 | 97.68 299 | 77.95 414 | 99.65 153 | 97.58 123 | 96.77 267 | 98.91 229 |
|
| jajsoiax | | | 95.45 248 | 95.03 252 | 96.73 276 | 95.42 430 | 94.63 265 | 99.14 59 | 98.52 191 | 95.74 155 | 93.22 363 | 98.36 230 | 83.87 365 | 98.65 324 | 96.95 164 | 94.04 319 | 96.91 338 |
|
| CVMVSNet | | | 95.43 250 | 96.04 199 | 93.57 417 | 97.93 281 | 83.62 456 | 98.12 303 | 98.59 172 | 95.68 159 | 96.56 242 | 99.02 136 | 87.51 287 | 97.51 425 | 93.56 303 | 97.44 247 | 99.60 92 |
|
| anonymousdsp | | | 95.42 251 | 94.91 258 | 96.94 261 | 95.10 434 | 95.90 189 | 99.14 59 | 98.41 227 | 93.75 282 | 93.16 366 | 97.46 317 | 87.50 289 | 98.41 354 | 95.63 226 | 94.03 320 | 96.50 395 |
|
| DU-MVS | | | 95.42 251 | 94.76 264 | 97.40 230 | 96.53 381 | 96.97 125 | 98.66 201 | 98.99 56 | 95.43 177 | 93.88 334 | 97.69 296 | 88.57 259 | 98.31 368 | 95.81 216 | 87.25 421 | 96.92 333 |
|
| mvs_tets | | | 95.41 253 | 95.00 253 | 96.65 284 | 95.58 421 | 94.42 276 | 99.00 88 | 98.55 184 | 95.73 157 | 93.21 364 | 98.38 228 | 83.45 371 | 98.63 325 | 97.09 158 | 94.00 321 | 96.91 338 |
|
| thres100view900 | | | 95.38 254 | 94.70 268 | 97.41 228 | 98.98 138 | 94.92 252 | 98.87 130 | 96.90 414 | 95.38 182 | 96.61 240 | 96.88 376 | 84.29 352 | 99.56 172 | 88.11 412 | 96.29 284 | 97.76 301 |
|
| thres400 | | | 95.38 254 | 94.62 272 | 97.65 213 | 98.94 143 | 94.98 248 | 98.68 194 | 96.93 412 | 95.33 185 | 96.55 244 | 96.53 395 | 84.23 356 | 99.56 172 | 88.11 412 | 96.29 284 | 98.40 280 |
|
| BH-w/o | | | 95.38 254 | 95.08 250 | 96.26 327 | 98.34 215 | 91.79 360 | 97.70 356 | 97.43 373 | 92.87 333 | 94.24 317 | 97.22 338 | 88.66 257 | 98.84 305 | 91.55 359 | 97.70 235 | 98.16 292 |
|
| VDDNet | | | 95.36 257 | 94.53 277 | 97.86 187 | 98.10 253 | 95.13 239 | 98.85 139 | 97.75 337 | 90.46 403 | 98.36 126 | 99.39 48 | 73.27 447 | 99.64 156 | 97.98 93 | 96.58 272 | 98.81 237 |
|
| TAPA-MVS | | 93.98 7 | 95.35 258 | 94.56 276 | 97.74 200 | 99.13 119 | 94.83 257 | 98.33 266 | 98.64 159 | 86.62 439 | 96.29 255 | 98.61 203 | 94.00 105 | 99.29 222 | 80.00 456 | 99.41 129 | 99.09 204 |
| Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
| ACMP | | 93.49 10 | 95.34 259 | 94.98 255 | 96.43 315 | 97.67 300 | 93.48 315 | 98.73 179 | 98.44 211 | 94.94 219 | 92.53 386 | 98.53 213 | 84.50 351 | 99.14 254 | 95.48 231 | 94.00 321 | 96.66 370 |
| Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
| COLMAP_ROB |  | 93.27 12 | 95.33 260 | 94.87 261 | 96.71 279 | 99.29 88 | 93.24 329 | 98.58 218 | 98.11 303 | 89.92 413 | 93.57 348 | 99.10 118 | 86.37 310 | 99.79 121 | 90.78 374 | 98.10 219 | 97.09 322 |
| Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
| UBG | | | 95.32 261 | 94.72 267 | 97.13 244 | 98.05 261 | 93.26 326 | 97.87 339 | 97.20 392 | 94.96 215 | 96.18 259 | 95.66 429 | 80.97 386 | 99.35 211 | 94.47 270 | 97.08 254 | 98.78 242 |
|
| tfpn200view9 | | | 95.32 261 | 94.62 272 | 97.43 226 | 98.94 143 | 94.98 248 | 98.68 194 | 96.93 412 | 95.33 185 | 96.55 244 | 96.53 395 | 84.23 356 | 99.56 172 | 88.11 412 | 96.29 284 | 97.76 301 |
|
| Anonymous202405211 | | | 95.28 263 | 94.49 279 | 97.67 209 | 99.00 134 | 93.75 304 | 98.70 188 | 97.04 403 | 90.66 399 | 96.49 248 | 98.80 176 | 78.13 410 | 99.83 90 | 96.21 202 | 95.36 306 | 99.44 125 |
|
| thres200 | | | 95.25 264 | 94.57 275 | 97.28 234 | 98.81 157 | 94.92 252 | 98.20 286 | 97.11 396 | 95.24 193 | 96.54 246 | 96.22 407 | 84.58 349 | 99.53 182 | 87.93 417 | 96.50 276 | 97.39 315 |
|
| AllTest | | | 95.24 265 | 94.65 271 | 96.99 255 | 99.25 96 | 93.21 330 | 98.59 214 | 98.18 287 | 91.36 381 | 93.52 350 | 98.77 185 | 84.67 346 | 99.72 136 | 89.70 392 | 97.87 227 | 98.02 296 |
|
| LCM-MVSNet-Re | | | 95.22 266 | 95.32 238 | 94.91 380 | 98.18 244 | 87.85 442 | 98.75 169 | 95.66 444 | 95.11 202 | 88.96 428 | 96.85 379 | 90.26 210 | 97.65 417 | 95.65 225 | 98.44 194 | 99.22 177 |
|
| EPNet_dtu | | | 95.21 267 | 94.95 257 | 95.99 336 | 96.17 398 | 90.45 391 | 98.16 296 | 97.27 386 | 96.77 100 | 93.14 369 | 98.33 236 | 90.34 206 | 98.42 347 | 85.57 431 | 98.81 170 | 99.09 204 |
| Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
| XXY-MVS | | | 95.20 268 | 94.45 285 | 97.46 223 | 96.75 371 | 96.56 149 | 98.86 134 | 98.65 158 | 93.30 314 | 93.27 362 | 98.27 243 | 84.85 340 | 98.87 302 | 94.82 252 | 91.26 368 | 96.96 328 |
|
| D2MVS | | | 95.18 269 | 95.08 250 | 95.48 360 | 97.10 349 | 92.07 356 | 98.30 274 | 99.13 44 | 94.02 264 | 92.90 374 | 96.73 385 | 89.48 227 | 98.73 317 | 94.48 269 | 93.60 332 | 95.65 425 |
|
| WR-MVS | | | 95.15 270 | 94.46 282 | 97.22 236 | 96.67 376 | 96.45 153 | 98.21 284 | 98.81 107 | 94.15 258 | 93.16 366 | 97.69 296 | 87.51 287 | 98.30 370 | 95.29 238 | 88.62 406 | 96.90 340 |
|
| TranMVSNet+NR-MVSNet | | | 95.14 271 | 94.48 280 | 97.11 248 | 96.45 387 | 96.36 160 | 99.03 81 | 99.03 51 | 95.04 207 | 93.58 347 | 97.93 272 | 88.27 268 | 98.03 393 | 94.13 283 | 86.90 426 | 96.95 330 |
|
| myMVS_eth3d28 | | | 95.12 272 | 94.62 272 | 96.64 288 | 98.17 247 | 92.17 350 | 98.02 317 | 97.32 380 | 95.41 180 | 96.22 256 | 96.05 413 | 78.01 412 | 99.13 256 | 95.22 242 | 97.16 252 | 98.60 266 |
|
| baseline2 | | | 95.11 273 | 94.52 278 | 96.87 267 | 96.65 377 | 93.56 310 | 98.27 279 | 94.10 463 | 93.45 307 | 92.02 400 | 97.43 321 | 87.45 292 | 99.19 244 | 93.88 292 | 97.41 249 | 97.87 299 |
|
| miper_enhance_ethall | | | 95.10 274 | 94.75 265 | 96.12 332 | 97.53 315 | 93.73 306 | 96.61 433 | 98.08 311 | 92.20 360 | 93.89 333 | 96.65 391 | 92.44 126 | 98.30 370 | 94.21 279 | 91.16 369 | 96.34 404 |
|
| Anonymous20240529 | | | 95.10 274 | 94.22 296 | 97.75 199 | 99.01 132 | 94.26 286 | 98.87 130 | 98.83 98 | 85.79 447 | 96.64 237 | 98.97 144 | 78.73 403 | 99.85 84 | 96.27 198 | 94.89 307 | 99.12 196 |
|
| test-LLR | | | 95.10 274 | 94.87 261 | 95.80 347 | 96.77 368 | 89.70 407 | 96.91 416 | 95.21 449 | 95.11 202 | 94.83 289 | 95.72 426 | 87.71 283 | 98.97 282 | 93.06 314 | 98.50 189 | 98.72 250 |
|
| WR-MVS_H | | | 95.05 277 | 94.46 282 | 96.81 271 | 96.86 363 | 95.82 201 | 99.24 35 | 99.24 20 | 93.87 276 | 92.53 386 | 96.84 380 | 90.37 205 | 98.24 376 | 93.24 309 | 87.93 412 | 96.38 403 |
|
| miper_ehance_all_eth | | | 95.01 278 | 94.69 269 | 95.97 338 | 97.70 298 | 93.31 324 | 97.02 409 | 98.07 313 | 92.23 357 | 93.51 352 | 96.96 369 | 91.85 150 | 98.15 381 | 93.68 297 | 91.16 369 | 96.44 401 |
|
| testing11 | | | 95.00 279 | 94.28 292 | 97.16 242 | 97.96 278 | 93.36 323 | 98.09 309 | 97.06 402 | 94.94 219 | 95.33 279 | 96.15 409 | 76.89 427 | 99.40 206 | 95.77 220 | 96.30 283 | 98.72 250 |
|
| ADS-MVSNet | | | 95.00 279 | 94.45 285 | 96.63 289 | 98.00 268 | 91.91 359 | 96.04 440 | 97.74 338 | 90.15 409 | 96.47 249 | 96.64 392 | 87.89 279 | 98.96 286 | 90.08 383 | 97.06 255 | 99.02 217 |
|
| VPNet | | | 94.99 281 | 94.19 298 | 97.40 230 | 97.16 345 | 96.57 148 | 98.71 184 | 98.97 57 | 95.67 160 | 94.84 287 | 98.24 247 | 80.36 393 | 98.67 323 | 96.46 192 | 87.32 420 | 96.96 328 |
|
| EPMVS | | | 94.99 281 | 94.48 280 | 96.52 305 | 97.22 338 | 91.75 362 | 97.23 390 | 91.66 473 | 94.11 259 | 97.28 203 | 96.81 382 | 85.70 323 | 98.84 305 | 93.04 316 | 97.28 250 | 98.97 222 |
|
| testing91 | | | 94.98 283 | 94.25 295 | 97.20 237 | 97.94 279 | 93.41 318 | 98.00 320 | 97.58 350 | 94.99 212 | 95.45 275 | 96.04 414 | 77.20 422 | 99.42 204 | 94.97 248 | 96.02 297 | 98.78 242 |
|
| NR-MVSNet | | | 94.98 283 | 94.16 301 | 97.44 225 | 96.53 381 | 97.22 113 | 98.74 173 | 98.95 61 | 94.96 215 | 89.25 427 | 97.69 296 | 89.32 236 | 98.18 379 | 94.59 266 | 87.40 418 | 96.92 333 |
|
| FMVSNet3 | | | 94.97 285 | 94.26 294 | 97.11 248 | 98.18 244 | 96.62 140 | 98.56 230 | 98.26 275 | 93.67 295 | 94.09 324 | 97.10 344 | 84.25 354 | 98.01 395 | 92.08 342 | 92.14 354 | 96.70 364 |
|
| FE-MVSNET3 | | | 94.96 286 | 94.28 292 | 96.98 258 | 95.93 411 | 96.11 172 | 97.08 406 | 98.39 235 | 93.62 299 | 93.86 336 | 96.40 400 | 88.28 267 | 98.21 377 | 92.61 326 | 92.36 353 | 96.63 372 |
|
| CostFormer | | | 94.95 287 | 94.73 266 | 95.60 357 | 97.28 334 | 89.06 420 | 97.53 368 | 96.89 416 | 89.66 418 | 96.82 228 | 96.72 386 | 86.05 317 | 98.95 291 | 95.53 229 | 96.13 295 | 98.79 238 |
|
| PAPM | | | 94.95 287 | 94.00 314 | 97.78 194 | 97.04 351 | 95.65 210 | 96.03 442 | 98.25 276 | 91.23 390 | 94.19 320 | 97.80 288 | 91.27 175 | 98.86 304 | 82.61 448 | 97.61 237 | 98.84 234 |
|
| CP-MVSNet | | | 94.94 289 | 94.30 291 | 96.83 269 | 96.72 373 | 95.56 213 | 99.11 65 | 98.95 61 | 93.89 274 | 92.42 391 | 97.90 275 | 87.19 294 | 98.12 384 | 94.32 275 | 88.21 409 | 96.82 351 |
|
| TR-MVS | | | 94.94 289 | 94.20 297 | 97.17 241 | 97.75 292 | 94.14 292 | 97.59 365 | 97.02 407 | 92.28 356 | 95.75 271 | 97.64 304 | 83.88 364 | 98.96 286 | 89.77 389 | 96.15 294 | 98.40 280 |
|
| RPSCF | | | 94.87 291 | 95.40 228 | 93.26 423 | 98.89 146 | 82.06 462 | 98.33 266 | 98.06 318 | 90.30 408 | 96.56 242 | 99.26 80 | 87.09 295 | 99.49 190 | 93.82 294 | 96.32 281 | 98.24 287 |
|
| testing99 | | | 94.83 292 | 94.08 306 | 97.07 251 | 97.94 279 | 93.13 332 | 98.10 308 | 97.17 394 | 94.86 221 | 95.34 276 | 96.00 418 | 76.31 430 | 99.40 206 | 95.08 245 | 95.90 298 | 98.68 257 |
|
| GA-MVS | | | 94.81 293 | 94.03 310 | 97.14 243 | 97.15 346 | 93.86 299 | 96.76 428 | 97.58 350 | 94.00 268 | 94.76 293 | 97.04 359 | 80.91 387 | 98.48 338 | 91.79 352 | 96.25 290 | 99.09 204 |
|
| c3_l | | | 94.79 294 | 94.43 287 | 95.89 343 | 97.75 292 | 93.12 334 | 97.16 402 | 98.03 320 | 92.23 357 | 93.46 356 | 97.05 358 | 91.39 169 | 98.01 395 | 93.58 302 | 89.21 398 | 96.53 387 |
|
| V42 | | | 94.78 295 | 94.14 303 | 96.70 281 | 96.33 392 | 95.22 234 | 98.97 95 | 98.09 310 | 92.32 354 | 94.31 311 | 97.06 355 | 88.39 265 | 98.55 333 | 92.90 321 | 88.87 404 | 96.34 404 |
|
| reproduce_monomvs | | | 94.77 296 | 94.67 270 | 95.08 375 | 98.40 202 | 89.48 413 | 98.80 156 | 98.64 159 | 97.57 46 | 93.21 364 | 97.65 301 | 80.57 392 | 98.83 308 | 97.72 110 | 89.47 394 | 96.93 332 |
|
| CR-MVSNet | | | 94.76 297 | 94.15 302 | 96.59 295 | 97.00 352 | 93.43 316 | 94.96 455 | 97.56 353 | 92.46 345 | 96.93 221 | 96.24 403 | 88.15 271 | 97.88 408 | 87.38 420 | 96.65 270 | 98.46 278 |
|
| v2v482 | | | 94.69 298 | 94.03 310 | 96.65 284 | 96.17 398 | 94.79 260 | 98.67 199 | 98.08 311 | 92.72 337 | 94.00 329 | 97.16 341 | 87.69 286 | 98.45 343 | 92.91 320 | 88.87 404 | 96.72 360 |
|
| pmmvs4 | | | 94.69 298 | 93.99 316 | 96.81 271 | 95.74 416 | 95.94 183 | 97.40 375 | 97.67 342 | 90.42 405 | 93.37 359 | 97.59 308 | 89.08 244 | 98.20 378 | 92.97 318 | 91.67 362 | 96.30 407 |
|
| cl22 | | | 94.68 300 | 94.19 298 | 96.13 331 | 98.11 252 | 93.60 309 | 96.94 413 | 98.31 257 | 92.43 349 | 93.32 361 | 96.87 378 | 86.51 304 | 98.28 374 | 94.10 286 | 91.16 369 | 96.51 393 |
|
| eth_miper_zixun_eth | | | 94.68 300 | 94.41 288 | 95.47 361 | 97.64 303 | 91.71 364 | 96.73 430 | 98.07 313 | 92.71 338 | 93.64 344 | 97.21 339 | 90.54 203 | 98.17 380 | 93.38 305 | 89.76 386 | 96.54 385 |
|
| PCF-MVS | | 93.45 11 | 94.68 300 | 93.43 352 | 98.42 129 | 98.62 179 | 96.77 135 | 95.48 452 | 98.20 282 | 84.63 452 | 93.34 360 | 98.32 237 | 88.55 262 | 99.81 102 | 84.80 440 | 98.96 158 | 98.68 257 |
| Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
| MVS | | | 94.67 303 | 93.54 347 | 98.08 168 | 96.88 362 | 96.56 149 | 98.19 289 | 98.50 199 | 78.05 464 | 92.69 381 | 98.02 262 | 91.07 189 | 99.63 159 | 90.09 382 | 98.36 207 | 98.04 295 |
|
| PS-CasMVS | | | 94.67 303 | 93.99 316 | 96.71 279 | 96.68 375 | 95.26 231 | 99.13 62 | 99.03 51 | 93.68 293 | 92.33 392 | 97.95 270 | 85.35 330 | 98.10 385 | 93.59 301 | 88.16 411 | 96.79 352 |
|
| cascas | | | 94.63 305 | 93.86 326 | 96.93 262 | 96.91 360 | 94.27 285 | 96.00 443 | 98.51 194 | 85.55 448 | 94.54 296 | 96.23 405 | 84.20 358 | 98.87 302 | 95.80 218 | 96.98 260 | 97.66 307 |
|
| tpmvs | | | 94.60 306 | 94.36 290 | 95.33 367 | 97.46 320 | 88.60 430 | 96.88 422 | 97.68 339 | 91.29 387 | 93.80 340 | 96.42 399 | 88.58 258 | 99.24 234 | 91.06 369 | 96.04 296 | 98.17 291 |
|
| LTVRE_ROB | | 92.95 15 | 94.60 306 | 93.90 322 | 96.68 283 | 97.41 328 | 94.42 276 | 98.52 234 | 98.59 172 | 91.69 372 | 91.21 407 | 98.35 231 | 84.87 339 | 99.04 274 | 91.06 369 | 93.44 336 | 96.60 376 |
| 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 | | | 94.59 308 | 93.92 319 | 96.60 294 | 96.21 394 | 94.78 261 | 98.59 214 | 98.14 298 | 91.86 368 | 94.21 319 | 97.02 362 | 87.97 277 | 98.41 354 | 91.72 354 | 89.57 389 | 96.61 375 |
|
| ADS-MVSNet2 | | | 94.58 309 | 94.40 289 | 95.11 373 | 98.00 268 | 88.74 428 | 96.04 440 | 97.30 382 | 90.15 409 | 96.47 249 | 96.64 392 | 87.89 279 | 97.56 423 | 90.08 383 | 97.06 255 | 99.02 217 |
|
| WBMVS | | | 94.56 310 | 94.04 308 | 96.10 333 | 98.03 265 | 93.08 336 | 97.82 347 | 98.18 287 | 94.02 264 | 93.77 342 | 96.82 381 | 81.28 381 | 98.34 363 | 95.47 232 | 91.00 372 | 96.88 342 |
|
| ACMH | | 92.88 16 | 94.55 311 | 93.95 318 | 96.34 322 | 97.63 304 | 93.26 326 | 98.81 155 | 98.49 204 | 93.43 308 | 89.74 421 | 98.53 213 | 81.91 376 | 99.08 268 | 93.69 296 | 93.30 341 | 96.70 364 |
| Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
| tt0805 | | | 94.54 312 | 93.85 327 | 96.63 289 | 97.98 276 | 93.06 337 | 98.77 168 | 97.84 332 | 93.67 295 | 93.80 340 | 98.04 261 | 76.88 428 | 98.96 286 | 94.79 254 | 92.86 346 | 97.86 300 |
|
| XVG-ACMP-BASELINE | | | 94.54 312 | 94.14 303 | 95.75 351 | 96.55 380 | 91.65 365 | 98.11 306 | 98.44 211 | 94.96 215 | 94.22 318 | 97.90 275 | 79.18 402 | 99.11 261 | 94.05 288 | 93.85 325 | 96.48 398 |
|
| AUN-MVS | | | 94.53 314 | 93.73 337 | 96.92 265 | 98.50 187 | 93.52 314 | 98.34 265 | 98.10 306 | 93.83 279 | 95.94 269 | 97.98 268 | 85.59 326 | 99.03 275 | 94.35 273 | 80.94 455 | 98.22 289 |
|
| DIV-MVS_self_test | | | 94.52 315 | 94.03 310 | 95.99 336 | 97.57 312 | 93.38 321 | 97.05 407 | 97.94 326 | 91.74 369 | 92.81 376 | 97.10 344 | 89.12 242 | 98.07 391 | 92.60 328 | 90.30 379 | 96.53 387 |
|
| cl____ | | | 94.51 316 | 94.01 313 | 96.02 335 | 97.58 308 | 93.40 320 | 97.05 407 | 97.96 325 | 91.73 371 | 92.76 378 | 97.08 350 | 89.06 245 | 98.13 383 | 92.61 326 | 90.29 380 | 96.52 390 |
|
| ETVMVS | | | 94.50 317 | 93.44 351 | 97.68 207 | 98.18 244 | 95.35 227 | 98.19 289 | 97.11 396 | 93.73 285 | 96.40 252 | 95.39 432 | 74.53 440 | 98.84 305 | 91.10 365 | 96.31 282 | 98.84 234 |
|
| GBi-Net | | | 94.49 318 | 93.80 330 | 96.56 299 | 98.21 234 | 95.00 244 | 98.82 147 | 98.18 287 | 92.46 345 | 94.09 324 | 97.07 351 | 81.16 382 | 97.95 400 | 92.08 342 | 92.14 354 | 96.72 360 |
|
| test1 | | | 94.49 318 | 93.80 330 | 96.56 299 | 98.21 234 | 95.00 244 | 98.82 147 | 98.18 287 | 92.46 345 | 94.09 324 | 97.07 351 | 81.16 382 | 97.95 400 | 92.08 342 | 92.14 354 | 96.72 360 |
|
| dmvs_re | | | 94.48 320 | 94.18 300 | 95.37 365 | 97.68 299 | 90.11 399 | 98.54 233 | 97.08 398 | 94.56 240 | 94.42 305 | 97.24 336 | 84.25 354 | 97.76 414 | 91.02 372 | 92.83 347 | 98.24 287 |
|
| v8 | | | 94.47 321 | 93.77 333 | 96.57 298 | 96.36 390 | 94.83 257 | 99.05 74 | 98.19 284 | 91.92 365 | 93.16 366 | 96.97 367 | 88.82 256 | 98.48 338 | 91.69 355 | 87.79 413 | 96.39 402 |
|
| FMVSNet2 | | | 94.47 321 | 93.61 343 | 97.04 253 | 98.21 234 | 96.43 155 | 98.79 164 | 98.27 267 | 92.46 345 | 93.50 353 | 97.09 348 | 81.16 382 | 98.00 397 | 91.09 366 | 91.93 357 | 96.70 364 |
|
| test2506 | | | 94.44 323 | 93.91 321 | 96.04 334 | 99.02 130 | 88.99 423 | 99.06 72 | 79.47 485 | 96.96 92 | 98.36 126 | 99.26 80 | 77.21 421 | 99.52 185 | 96.78 183 | 99.04 152 | 99.59 94 |
|
| Patchmatch-test | | | 94.42 324 | 93.68 341 | 96.63 289 | 97.60 306 | 91.76 361 | 94.83 459 | 97.49 365 | 89.45 422 | 94.14 322 | 97.10 344 | 88.99 247 | 98.83 308 | 85.37 434 | 98.13 218 | 99.29 161 |
|
| PEN-MVS | | | 94.42 324 | 93.73 337 | 96.49 307 | 96.28 393 | 94.84 255 | 99.17 54 | 99.00 53 | 93.51 303 | 92.23 394 | 97.83 285 | 86.10 316 | 97.90 404 | 92.55 333 | 86.92 425 | 96.74 357 |
|
| v144192 | | | 94.39 326 | 93.70 339 | 96.48 309 | 96.06 404 | 94.35 280 | 98.58 218 | 98.16 295 | 91.45 378 | 94.33 310 | 97.02 362 | 87.50 289 | 98.45 343 | 91.08 368 | 89.11 399 | 96.63 372 |
|
| Baseline_NR-MVSNet | | | 94.35 327 | 93.81 329 | 95.96 339 | 96.20 395 | 94.05 294 | 98.61 213 | 96.67 426 | 91.44 379 | 93.85 337 | 97.60 307 | 88.57 259 | 98.14 382 | 94.39 271 | 86.93 424 | 95.68 424 |
|
| miper_lstm_enhance | | | 94.33 328 | 94.07 307 | 95.11 373 | 97.75 292 | 90.97 375 | 97.22 392 | 98.03 320 | 91.67 373 | 92.76 378 | 96.97 367 | 90.03 214 | 97.78 413 | 92.51 335 | 89.64 388 | 96.56 382 |
|
| v1192 | | | 94.32 329 | 93.58 344 | 96.53 304 | 96.10 402 | 94.45 274 | 98.50 242 | 98.17 293 | 91.54 376 | 94.19 320 | 97.06 355 | 86.95 299 | 98.43 346 | 90.14 381 | 89.57 389 | 96.70 364 |
|
| UWE-MVS | | | 94.30 330 | 93.89 324 | 95.53 358 | 97.83 287 | 88.95 424 | 97.52 370 | 93.25 465 | 94.44 250 | 96.63 238 | 97.07 351 | 78.70 404 | 99.28 224 | 91.99 347 | 97.56 241 | 98.36 283 |
|
| ACMH+ | | 92.99 14 | 94.30 330 | 93.77 333 | 95.88 344 | 97.81 289 | 92.04 358 | 98.71 184 | 98.37 242 | 93.99 269 | 90.60 414 | 98.47 219 | 80.86 389 | 99.05 271 | 92.75 325 | 92.40 352 | 96.55 384 |
|
| v148 | | | 94.29 332 | 93.76 335 | 95.91 341 | 96.10 402 | 92.93 338 | 98.58 218 | 97.97 323 | 92.59 343 | 93.47 355 | 96.95 371 | 88.53 263 | 98.32 366 | 92.56 332 | 87.06 423 | 96.49 396 |
|
| v10 | | | 94.29 332 | 93.55 346 | 96.51 306 | 96.39 389 | 94.80 259 | 98.99 91 | 98.19 284 | 91.35 383 | 93.02 372 | 96.99 365 | 88.09 273 | 98.41 354 | 90.50 378 | 88.41 408 | 96.33 406 |
|
| SD_0403 | | | 94.28 334 | 94.46 282 | 93.73 414 | 98.02 266 | 85.32 451 | 98.31 271 | 98.40 230 | 94.75 229 | 93.59 345 | 98.16 252 | 89.01 246 | 96.54 444 | 82.32 449 | 97.58 240 | 99.34 146 |
|
| MVP-Stereo | | | 94.28 334 | 93.92 319 | 95.35 366 | 94.95 436 | 92.60 345 | 97.97 323 | 97.65 343 | 91.61 374 | 90.68 413 | 97.09 348 | 86.32 313 | 98.42 347 | 89.70 392 | 99.34 138 | 95.02 438 |
| Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
| UniMVSNet_ETH3D | | | 94.24 336 | 93.33 354 | 96.97 259 | 97.19 343 | 93.38 321 | 98.74 173 | 98.57 179 | 91.21 392 | 93.81 339 | 98.58 208 | 72.85 448 | 98.77 315 | 95.05 246 | 93.93 324 | 98.77 245 |
|
| OurMVSNet-221017-0 | | | 94.21 337 | 94.00 314 | 94.85 385 | 95.60 420 | 89.22 418 | 98.89 120 | 97.43 373 | 95.29 188 | 92.18 396 | 98.52 216 | 82.86 372 | 98.59 331 | 93.46 304 | 91.76 360 | 96.74 357 |
|
| v1921920 | | | 94.20 338 | 93.47 350 | 96.40 319 | 95.98 408 | 94.08 293 | 98.52 234 | 98.15 296 | 91.33 384 | 94.25 316 | 97.20 340 | 86.41 309 | 98.42 347 | 90.04 386 | 89.39 396 | 96.69 369 |
|
| WB-MVSnew | | | 94.19 339 | 94.04 308 | 94.66 393 | 96.82 366 | 92.14 351 | 97.86 341 | 95.96 440 | 93.50 304 | 95.64 272 | 96.77 384 | 88.06 275 | 97.99 398 | 84.87 437 | 96.86 261 | 93.85 457 |
|
| v7n | | | 94.19 339 | 93.43 352 | 96.47 310 | 95.90 412 | 94.38 279 | 99.26 32 | 98.34 250 | 91.99 363 | 92.76 378 | 97.13 343 | 88.31 266 | 98.52 336 | 89.48 397 | 87.70 414 | 96.52 390 |
|
| tpm2 | | | 94.19 339 | 93.76 335 | 95.46 362 | 97.23 337 | 89.04 421 | 97.31 386 | 96.85 420 | 87.08 438 | 96.21 258 | 96.79 383 | 83.75 368 | 98.74 316 | 92.43 338 | 96.23 292 | 98.59 269 |
|
| TESTMET0.1,1 | | | 94.18 342 | 93.69 340 | 95.63 355 | 96.92 358 | 89.12 419 | 96.91 416 | 94.78 454 | 93.17 319 | 94.88 286 | 96.45 398 | 78.52 405 | 98.92 293 | 93.09 313 | 98.50 189 | 98.85 232 |
|
| dp | | | 94.15 343 | 93.90 322 | 94.90 381 | 97.31 333 | 86.82 447 | 96.97 411 | 97.19 393 | 91.22 391 | 96.02 264 | 96.61 394 | 85.51 327 | 99.02 278 | 90.00 387 | 94.30 309 | 98.85 232 |
|
| ET-MVSNet_ETH3D | | | 94.13 344 | 92.98 362 | 97.58 218 | 98.22 233 | 96.20 166 | 97.31 386 | 95.37 448 | 94.53 242 | 79.56 466 | 97.63 306 | 86.51 304 | 97.53 424 | 96.91 166 | 90.74 374 | 99.02 217 |
|
| tpm | | | 94.13 344 | 93.80 330 | 95.12 372 | 96.50 383 | 87.91 441 | 97.44 372 | 95.89 443 | 92.62 341 | 96.37 254 | 96.30 402 | 84.13 359 | 98.30 370 | 93.24 309 | 91.66 363 | 99.14 194 |
|
| testing222 | | | 94.12 346 | 93.03 361 | 97.37 233 | 98.02 266 | 94.66 262 | 97.94 327 | 96.65 428 | 94.63 236 | 95.78 270 | 95.76 421 | 71.49 449 | 98.92 293 | 91.17 364 | 95.88 299 | 98.52 274 |
|
| IterMVS-SCA-FT | | | 94.11 347 | 93.87 325 | 94.85 385 | 97.98 276 | 90.56 390 | 97.18 397 | 98.11 303 | 93.75 282 | 92.58 384 | 97.48 316 | 83.97 362 | 97.41 427 | 92.48 337 | 91.30 366 | 96.58 378 |
|
| Anonymous20231211 | | | 94.10 348 | 93.26 357 | 96.61 292 | 99.11 122 | 94.28 284 | 99.01 86 | 98.88 78 | 86.43 441 | 92.81 376 | 97.57 310 | 81.66 378 | 98.68 322 | 94.83 251 | 89.02 402 | 96.88 342 |
|
| IterMVS | | | 94.09 349 | 93.85 327 | 94.80 389 | 97.99 270 | 90.35 395 | 97.18 397 | 98.12 300 | 93.68 293 | 92.46 390 | 97.34 327 | 84.05 360 | 97.41 427 | 92.51 335 | 91.33 365 | 96.62 374 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
| test-mter | | | 94.08 350 | 93.51 348 | 95.80 347 | 96.77 368 | 89.70 407 | 96.91 416 | 95.21 449 | 92.89 332 | 94.83 289 | 95.72 426 | 77.69 416 | 98.97 282 | 93.06 314 | 98.50 189 | 98.72 250 |
|
| test0.0.03 1 | | | 94.08 350 | 93.51 348 | 95.80 347 | 95.53 424 | 92.89 339 | 97.38 377 | 95.97 439 | 95.11 202 | 92.51 388 | 96.66 389 | 87.71 283 | 96.94 434 | 87.03 422 | 93.67 328 | 97.57 311 |
|
| v1240 | | | 94.06 352 | 93.29 356 | 96.34 322 | 96.03 406 | 93.90 298 | 98.44 255 | 98.17 293 | 91.18 393 | 94.13 323 | 97.01 364 | 86.05 317 | 98.42 347 | 89.13 403 | 89.50 393 | 96.70 364 |
|
| X-MVStestdata | | | 94.06 352 | 92.30 378 | 99.34 31 | 99.70 27 | 98.35 49 | 99.29 27 | 98.88 78 | 97.40 57 | 98.46 118 | 43.50 480 | 95.90 48 | 99.89 68 | 97.85 102 | 99.74 59 | 99.78 33 |
|
| DTE-MVSNet | | | 93.98 354 | 93.26 357 | 96.14 330 | 96.06 404 | 94.39 278 | 99.20 47 | 98.86 91 | 93.06 325 | 91.78 401 | 97.81 287 | 85.87 321 | 97.58 422 | 90.53 377 | 86.17 430 | 96.46 400 |
|
| pm-mvs1 | | | 93.94 355 | 93.06 360 | 96.59 295 | 96.49 384 | 95.16 236 | 98.95 102 | 98.03 320 | 92.32 354 | 91.08 409 | 97.84 282 | 84.54 350 | 98.41 354 | 92.16 340 | 86.13 433 | 96.19 412 |
|
| MS-PatchMatch | | | 93.84 356 | 93.63 342 | 94.46 403 | 96.18 397 | 89.45 414 | 97.76 351 | 98.27 267 | 92.23 357 | 92.13 397 | 97.49 315 | 79.50 399 | 98.69 319 | 89.75 390 | 99.38 134 | 95.25 430 |
|
| tfpnnormal | | | 93.66 357 | 92.70 368 | 96.55 303 | 96.94 357 | 95.94 183 | 98.97 95 | 99.19 36 | 91.04 394 | 91.38 406 | 97.34 327 | 84.94 338 | 98.61 327 | 85.45 433 | 89.02 402 | 95.11 434 |
|
| EU-MVSNet | | | 93.66 357 | 94.14 303 | 92.25 434 | 95.96 410 | 83.38 458 | 98.52 234 | 98.12 300 | 94.69 232 | 92.61 383 | 98.13 255 | 87.36 293 | 96.39 449 | 91.82 351 | 90.00 384 | 96.98 327 |
|
| our_test_3 | | | 93.65 359 | 93.30 355 | 94.69 391 | 95.45 428 | 89.68 409 | 96.91 416 | 97.65 343 | 91.97 364 | 91.66 404 | 96.88 376 | 89.67 223 | 97.93 403 | 88.02 415 | 91.49 364 | 96.48 398 |
|
| pmmvs5 | | | 93.65 359 | 92.97 363 | 95.68 352 | 95.49 425 | 92.37 346 | 98.20 286 | 97.28 385 | 89.66 418 | 92.58 384 | 97.26 333 | 82.14 375 | 98.09 389 | 93.18 312 | 90.95 373 | 96.58 378 |
|
| SSC-MVS3.2 | | | 93.59 361 | 93.13 359 | 94.97 378 | 96.81 367 | 89.71 406 | 97.95 324 | 98.49 204 | 94.59 239 | 93.50 353 | 96.91 374 | 77.74 415 | 98.37 361 | 91.69 355 | 90.47 377 | 96.83 350 |
|
| test_fmvs2 | | | 93.43 362 | 93.58 344 | 92.95 428 | 96.97 355 | 83.91 454 | 99.19 49 | 97.24 388 | 95.74 155 | 95.20 281 | 98.27 243 | 69.65 451 | 98.72 318 | 96.26 199 | 93.73 327 | 96.24 409 |
|
| tpm cat1 | | | 93.36 363 | 92.80 365 | 95.07 376 | 97.58 308 | 87.97 440 | 96.76 428 | 97.86 331 | 82.17 459 | 93.53 349 | 96.04 414 | 86.13 315 | 99.13 256 | 89.24 401 | 95.87 300 | 98.10 294 |
|
| JIA-IIPM | | | 93.35 364 | 92.49 374 | 95.92 340 | 96.48 385 | 90.65 385 | 95.01 454 | 96.96 410 | 85.93 445 | 96.08 262 | 87.33 470 | 87.70 285 | 98.78 314 | 91.35 361 | 95.58 304 | 98.34 284 |
|
| SixPastTwentyTwo | | | 93.34 365 | 92.86 364 | 94.75 390 | 95.67 418 | 89.41 416 | 98.75 169 | 96.67 426 | 93.89 274 | 90.15 419 | 98.25 246 | 80.87 388 | 98.27 375 | 90.90 373 | 90.64 375 | 96.57 380 |
|
| USDC | | | 93.33 366 | 92.71 367 | 95.21 369 | 96.83 365 | 90.83 381 | 96.91 416 | 97.50 363 | 93.84 277 | 90.72 412 | 98.14 254 | 77.69 416 | 98.82 310 | 89.51 396 | 93.21 343 | 95.97 418 |
|
| IB-MVS | | 91.98 17 | 93.27 367 | 91.97 382 | 97.19 239 | 97.47 319 | 93.41 318 | 97.09 405 | 95.99 438 | 93.32 312 | 92.47 389 | 95.73 424 | 78.06 411 | 99.53 182 | 94.59 266 | 82.98 444 | 98.62 264 |
| 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 | | | 93.26 368 | 92.21 379 | 96.41 317 | 97.73 296 | 93.13 332 | 95.65 449 | 97.03 404 | 91.27 389 | 94.04 327 | 96.06 412 | 75.33 435 | 97.19 430 | 86.56 424 | 96.23 292 | 98.92 228 |
|
| ppachtmachnet_test | | | 93.22 369 | 92.63 369 | 94.97 378 | 95.45 428 | 90.84 380 | 96.88 422 | 97.88 330 | 90.60 400 | 92.08 398 | 97.26 333 | 88.08 274 | 97.86 409 | 85.12 436 | 90.33 378 | 96.22 410 |
|
| Patchmtry | | | 93.22 369 | 92.35 377 | 95.84 346 | 96.77 368 | 93.09 335 | 94.66 462 | 97.56 353 | 87.37 437 | 92.90 374 | 96.24 403 | 88.15 271 | 97.90 404 | 87.37 421 | 90.10 383 | 96.53 387 |
|
| testing3 | | | 93.19 371 | 92.48 375 | 95.30 368 | 98.07 256 | 92.27 347 | 98.64 205 | 97.17 394 | 93.94 273 | 93.98 330 | 97.04 359 | 67.97 456 | 96.01 453 | 88.40 410 | 97.14 253 | 97.63 308 |
|
| FMVSNet1 | | | 93.19 371 | 92.07 380 | 96.56 299 | 97.54 313 | 95.00 244 | 98.82 147 | 98.18 287 | 90.38 406 | 92.27 393 | 97.07 351 | 73.68 446 | 97.95 400 | 89.36 399 | 91.30 366 | 96.72 360 |
|
| LF4IMVS | | | 93.14 373 | 92.79 366 | 94.20 408 | 95.88 413 | 88.67 429 | 97.66 359 | 97.07 400 | 93.81 280 | 91.71 402 | 97.65 301 | 77.96 413 | 98.81 311 | 91.47 360 | 91.92 359 | 95.12 433 |
|
| mmtdpeth | | | 93.12 374 | 92.61 370 | 94.63 395 | 97.60 306 | 89.68 409 | 99.21 44 | 97.32 380 | 94.02 264 | 97.72 178 | 94.42 443 | 77.01 426 | 99.44 202 | 99.05 32 | 77.18 467 | 94.78 443 |
|
| testgi | | | 93.06 375 | 92.45 376 | 94.88 383 | 96.43 388 | 89.90 401 | 98.75 169 | 97.54 359 | 95.60 163 | 91.63 405 | 97.91 274 | 74.46 442 | 97.02 432 | 86.10 427 | 93.67 328 | 97.72 305 |
|
| PatchT | | | 93.06 375 | 91.97 382 | 96.35 321 | 96.69 374 | 92.67 344 | 94.48 465 | 97.08 398 | 86.62 439 | 97.08 213 | 92.23 464 | 87.94 278 | 97.90 404 | 78.89 460 | 96.69 268 | 98.49 276 |
|
| RPMNet | | | 92.81 377 | 91.34 388 | 97.24 235 | 97.00 352 | 93.43 316 | 94.96 455 | 98.80 114 | 82.27 458 | 96.93 221 | 92.12 465 | 86.98 298 | 99.82 97 | 76.32 466 | 96.65 270 | 98.46 278 |
|
| UWE-MVS-28 | | | 92.79 378 | 92.51 373 | 93.62 416 | 96.46 386 | 86.28 448 | 97.93 328 | 92.71 470 | 94.17 257 | 94.78 292 | 97.16 341 | 81.05 385 | 96.43 447 | 81.45 452 | 96.86 261 | 98.14 293 |
|
| myMVS_eth3d | | | 92.73 379 | 92.01 381 | 94.89 382 | 97.39 329 | 90.94 376 | 97.91 331 | 97.46 367 | 93.16 320 | 93.42 357 | 95.37 433 | 68.09 455 | 96.12 451 | 88.34 411 | 96.99 257 | 97.60 309 |
|
| TransMVSNet (Re) | | | 92.67 380 | 91.51 387 | 96.15 329 | 96.58 379 | 94.65 263 | 98.90 116 | 96.73 422 | 90.86 397 | 89.46 426 | 97.86 279 | 85.62 325 | 98.09 389 | 86.45 425 | 81.12 453 | 95.71 423 |
|
| ttmdpeth | | | 92.61 381 | 91.96 384 | 94.55 397 | 94.10 446 | 90.60 389 | 98.52 234 | 97.29 383 | 92.67 339 | 90.18 417 | 97.92 273 | 79.75 398 | 97.79 411 | 91.09 366 | 86.15 432 | 95.26 429 |
|
| Syy-MVS | | | 92.55 382 | 92.61 370 | 92.38 431 | 97.39 329 | 83.41 457 | 97.91 331 | 97.46 367 | 93.16 320 | 93.42 357 | 95.37 433 | 84.75 343 | 96.12 451 | 77.00 465 | 96.99 257 | 97.60 309 |
|
| K. test v3 | | | 92.55 382 | 91.91 385 | 94.48 401 | 95.64 419 | 89.24 417 | 99.07 71 | 94.88 453 | 94.04 262 | 86.78 443 | 97.59 308 | 77.64 419 | 97.64 418 | 92.08 342 | 89.43 395 | 96.57 380 |
|
| DSMNet-mixed | | | 92.52 384 | 92.58 372 | 92.33 432 | 94.15 445 | 82.65 460 | 98.30 274 | 94.26 460 | 89.08 427 | 92.65 382 | 95.73 424 | 85.01 337 | 95.76 455 | 86.24 426 | 97.76 232 | 98.59 269 |
|
| TinyColmap | | | 92.31 385 | 91.53 386 | 94.65 394 | 96.92 358 | 89.75 404 | 96.92 414 | 96.68 425 | 90.45 404 | 89.62 423 | 97.85 281 | 76.06 433 | 98.81 311 | 86.74 423 | 92.51 351 | 95.41 427 |
|
| gg-mvs-nofinetune | | | 92.21 386 | 90.58 394 | 97.13 244 | 96.75 371 | 95.09 240 | 95.85 444 | 89.40 478 | 85.43 449 | 94.50 298 | 81.98 473 | 80.80 390 | 98.40 360 | 92.16 340 | 98.33 208 | 97.88 298 |
|
| FMVSNet5 | | | 91.81 387 | 90.92 390 | 94.49 400 | 97.21 339 | 92.09 355 | 98.00 320 | 97.55 358 | 89.31 425 | 90.86 411 | 95.61 430 | 74.48 441 | 95.32 459 | 85.57 431 | 89.70 387 | 96.07 416 |
|
| pmmvs6 | | | 91.77 388 | 90.63 393 | 95.17 371 | 94.69 442 | 91.24 372 | 98.67 199 | 97.92 328 | 86.14 443 | 89.62 423 | 97.56 313 | 75.79 434 | 98.34 363 | 90.75 375 | 84.56 437 | 95.94 419 |
|
| Anonymous20231206 | | | 91.66 389 | 91.10 389 | 93.33 421 | 94.02 450 | 87.35 444 | 98.58 218 | 97.26 387 | 90.48 402 | 90.16 418 | 96.31 401 | 83.83 366 | 96.53 445 | 79.36 458 | 89.90 385 | 96.12 414 |
|
| Patchmatch-RL test | | | 91.49 390 | 90.85 391 | 93.41 419 | 91.37 461 | 84.40 452 | 92.81 469 | 95.93 442 | 91.87 367 | 87.25 439 | 94.87 439 | 88.99 247 | 96.53 445 | 92.54 334 | 82.00 447 | 99.30 158 |
|
| test_0402 | | | 91.32 391 | 90.27 397 | 94.48 401 | 96.60 378 | 91.12 373 | 98.50 242 | 97.22 389 | 86.10 444 | 88.30 435 | 96.98 366 | 77.65 418 | 97.99 398 | 78.13 462 | 92.94 345 | 94.34 445 |
|
| test_vis1_rt | | | 91.29 392 | 90.65 392 | 93.19 425 | 97.45 323 | 86.25 449 | 98.57 227 | 90.90 476 | 93.30 314 | 86.94 442 | 93.59 452 | 62.07 467 | 99.11 261 | 97.48 138 | 95.58 304 | 94.22 448 |
|
| PVSNet_0 | | 88.72 19 | 91.28 393 | 90.03 400 | 95.00 377 | 97.99 270 | 87.29 445 | 94.84 458 | 98.50 199 | 92.06 362 | 89.86 420 | 95.19 435 | 79.81 397 | 99.39 209 | 92.27 339 | 69.79 473 | 98.33 285 |
|
| mvs5depth | | | 91.23 394 | 90.17 398 | 94.41 405 | 92.09 458 | 89.79 403 | 95.26 453 | 96.50 430 | 90.73 398 | 91.69 403 | 97.06 355 | 76.12 432 | 98.62 326 | 88.02 415 | 84.11 440 | 94.82 440 |
|
| Anonymous20240521 | | | 91.18 395 | 90.44 395 | 93.42 418 | 93.70 451 | 88.47 433 | 98.94 105 | 97.56 353 | 88.46 431 | 89.56 425 | 95.08 438 | 77.15 424 | 96.97 433 | 83.92 443 | 89.55 391 | 94.82 440 |
|
| EG-PatchMatch MVS | | | 91.13 396 | 90.12 399 | 94.17 410 | 94.73 441 | 89.00 422 | 98.13 302 | 97.81 334 | 89.22 426 | 85.32 453 | 96.46 397 | 67.71 457 | 98.42 347 | 87.89 419 | 93.82 326 | 95.08 435 |
|
| TDRefinement | | | 91.06 397 | 89.68 402 | 95.21 369 | 85.35 478 | 91.49 368 | 98.51 241 | 97.07 400 | 91.47 377 | 88.83 432 | 97.84 282 | 77.31 420 | 99.09 266 | 92.79 324 | 77.98 465 | 95.04 437 |
|
| sc_t1 | | | 91.01 398 | 89.39 404 | 95.85 345 | 95.99 407 | 90.39 394 | 98.43 257 | 97.64 345 | 78.79 462 | 92.20 395 | 97.94 271 | 66.00 461 | 98.60 330 | 91.59 358 | 85.94 434 | 98.57 272 |
|
| UnsupCasMVSNet_eth | | | 90.99 399 | 89.92 401 | 94.19 409 | 94.08 447 | 89.83 402 | 97.13 404 | 98.67 151 | 93.69 291 | 85.83 449 | 96.19 408 | 75.15 436 | 96.74 438 | 89.14 402 | 79.41 460 | 96.00 417 |
|
| test20.03 | | | 90.89 400 | 90.38 396 | 92.43 430 | 93.48 452 | 88.14 439 | 98.33 266 | 97.56 353 | 93.40 309 | 87.96 436 | 96.71 387 | 80.69 391 | 94.13 465 | 79.15 459 | 86.17 430 | 95.01 439 |
|
| MDA-MVSNet_test_wron | | | 90.71 401 | 89.38 406 | 94.68 392 | 94.83 438 | 90.78 382 | 97.19 396 | 97.46 367 | 87.60 435 | 72.41 473 | 95.72 426 | 86.51 304 | 96.71 441 | 85.92 429 | 86.80 427 | 96.56 382 |
|
| YYNet1 | | | 90.70 402 | 89.39 404 | 94.62 396 | 94.79 440 | 90.65 385 | 97.20 394 | 97.46 367 | 87.54 436 | 72.54 472 | 95.74 422 | 86.51 304 | 96.66 442 | 86.00 428 | 86.76 428 | 96.54 385 |
|
| KD-MVS_self_test | | | 90.38 403 | 89.38 406 | 93.40 420 | 92.85 455 | 88.94 425 | 97.95 324 | 97.94 326 | 90.35 407 | 90.25 416 | 93.96 449 | 79.82 396 | 95.94 454 | 84.62 442 | 76.69 468 | 95.33 428 |
|
| pmmvs-eth3d | | | 90.36 404 | 89.05 409 | 94.32 407 | 91.10 463 | 92.12 352 | 97.63 364 | 96.95 411 | 88.86 429 | 84.91 454 | 93.13 457 | 78.32 407 | 96.74 438 | 88.70 407 | 81.81 449 | 94.09 451 |
|
| FE-MVSNET2 | | | 90.29 405 | 88.94 411 | 94.36 406 | 90.48 465 | 92.27 347 | 98.45 249 | 97.82 333 | 91.59 375 | 84.90 455 | 93.10 458 | 73.92 444 | 96.42 448 | 87.92 418 | 82.26 445 | 94.39 444 |
|
| tt0320 | | | 90.26 406 | 88.73 413 | 94.86 384 | 96.12 401 | 90.62 387 | 98.17 295 | 97.63 346 | 77.46 465 | 89.68 422 | 96.04 414 | 69.19 453 | 97.79 411 | 88.98 404 | 85.29 436 | 96.16 413 |
|
| CL-MVSNet_self_test | | | 90.11 407 | 89.14 408 | 93.02 426 | 91.86 460 | 88.23 438 | 96.51 436 | 98.07 313 | 90.49 401 | 90.49 415 | 94.41 444 | 84.75 343 | 95.34 458 | 80.79 454 | 74.95 470 | 95.50 426 |
|
| new_pmnet | | | 90.06 408 | 89.00 410 | 93.22 424 | 94.18 444 | 88.32 436 | 96.42 438 | 96.89 416 | 86.19 442 | 85.67 450 | 93.62 451 | 77.18 423 | 97.10 431 | 81.61 451 | 89.29 397 | 94.23 447 |
|
| MDA-MVSNet-bldmvs | | | 89.97 409 | 88.35 415 | 94.83 388 | 95.21 432 | 91.34 369 | 97.64 361 | 97.51 362 | 88.36 433 | 71.17 474 | 96.13 410 | 79.22 401 | 96.63 443 | 83.65 444 | 86.27 429 | 96.52 390 |
|
| tt0320-xc | | | 89.79 410 | 88.11 417 | 94.84 387 | 96.19 396 | 90.61 388 | 98.16 296 | 97.22 389 | 77.35 466 | 88.75 433 | 96.70 388 | 65.94 462 | 97.63 419 | 89.31 400 | 83.39 442 | 96.28 408 |
|
| CMPMVS |  | 66.06 21 | 89.70 411 | 89.67 403 | 89.78 439 | 93.19 453 | 76.56 465 | 97.00 410 | 98.35 247 | 80.97 460 | 81.57 461 | 97.75 290 | 74.75 439 | 98.61 327 | 89.85 388 | 93.63 330 | 94.17 449 |
| M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
| MIMVSNet1 | | | 89.67 412 | 88.28 416 | 93.82 413 | 92.81 456 | 91.08 374 | 98.01 318 | 97.45 371 | 87.95 434 | 87.90 437 | 95.87 420 | 67.63 458 | 94.56 464 | 78.73 461 | 88.18 410 | 95.83 421 |
|
| KD-MVS_2432*1600 | | | 89.61 413 | 87.96 421 | 94.54 398 | 94.06 448 | 91.59 366 | 95.59 450 | 97.63 346 | 89.87 414 | 88.95 429 | 94.38 446 | 78.28 408 | 96.82 436 | 84.83 438 | 68.05 474 | 95.21 431 |
|
| miper_refine_blended | | | 89.61 413 | 87.96 421 | 94.54 398 | 94.06 448 | 91.59 366 | 95.59 450 | 97.63 346 | 89.87 414 | 88.95 429 | 94.38 446 | 78.28 408 | 96.82 436 | 84.83 438 | 68.05 474 | 95.21 431 |
|
| MVStest1 | | | 89.53 415 | 87.99 420 | 94.14 412 | 94.39 443 | 90.42 392 | 98.25 281 | 96.84 421 | 82.81 455 | 81.18 463 | 97.33 329 | 77.09 425 | 96.94 434 | 85.27 435 | 78.79 461 | 95.06 436 |
|
| MVS-HIRNet | | | 89.46 416 | 88.40 414 | 92.64 429 | 97.58 308 | 82.15 461 | 94.16 468 | 93.05 469 | 75.73 469 | 90.90 410 | 82.52 472 | 79.42 400 | 98.33 365 | 83.53 445 | 98.68 173 | 97.43 312 |
|
| OpenMVS_ROB |  | 86.42 20 | 89.00 417 | 87.43 425 | 93.69 415 | 93.08 454 | 89.42 415 | 97.91 331 | 96.89 416 | 78.58 463 | 85.86 448 | 94.69 440 | 69.48 452 | 98.29 373 | 77.13 464 | 93.29 342 | 93.36 459 |
|
| mvsany_test3 | | | 88.80 418 | 88.04 418 | 91.09 438 | 89.78 468 | 81.57 463 | 97.83 346 | 95.49 447 | 93.81 280 | 87.53 438 | 93.95 450 | 56.14 470 | 97.43 426 | 94.68 259 | 83.13 443 | 94.26 446 |
|
| FE-MVSNET | | | 88.56 419 | 87.09 426 | 92.99 427 | 89.93 467 | 89.99 400 | 98.15 299 | 95.59 445 | 88.42 432 | 84.87 456 | 92.90 459 | 74.82 438 | 94.99 462 | 77.88 463 | 81.21 452 | 93.99 454 |
|
| new-patchmatchnet | | | 88.50 420 | 87.45 424 | 91.67 436 | 90.31 466 | 85.89 450 | 97.16 402 | 97.33 379 | 89.47 421 | 83.63 458 | 92.77 461 | 76.38 429 | 95.06 461 | 82.70 447 | 77.29 466 | 94.06 453 |
|
| APD_test1 | | | 88.22 421 | 88.01 419 | 88.86 441 | 95.98 408 | 74.66 473 | 97.21 393 | 96.44 432 | 83.96 454 | 86.66 445 | 97.90 275 | 60.95 468 | 97.84 410 | 82.73 446 | 90.23 381 | 94.09 451 |
|
| PM-MVS | | | 87.77 422 | 86.55 428 | 91.40 437 | 91.03 464 | 83.36 459 | 96.92 414 | 95.18 451 | 91.28 388 | 86.48 447 | 93.42 453 | 53.27 471 | 96.74 438 | 89.43 398 | 81.97 448 | 94.11 450 |
|
| dmvs_testset | | | 87.64 423 | 88.93 412 | 83.79 450 | 95.25 431 | 63.36 482 | 97.20 394 | 91.17 474 | 93.07 324 | 85.64 451 | 95.98 419 | 85.30 334 | 91.52 472 | 69.42 471 | 87.33 419 | 96.49 396 |
|
| test_fmvs3 | | | 87.17 424 | 87.06 427 | 87.50 443 | 91.21 462 | 75.66 468 | 99.05 74 | 96.61 429 | 92.79 336 | 88.85 431 | 92.78 460 | 43.72 474 | 93.49 466 | 93.95 289 | 84.56 437 | 93.34 460 |
|
| UnsupCasMVSNet_bld | | | 87.17 424 | 85.12 431 | 93.31 422 | 91.94 459 | 88.77 426 | 94.92 457 | 98.30 264 | 84.30 453 | 82.30 459 | 90.04 467 | 63.96 465 | 97.25 429 | 85.85 430 | 74.47 472 | 93.93 456 |
|
| N_pmnet | | | 87.12 426 | 87.77 423 | 85.17 447 | 95.46 427 | 61.92 483 | 97.37 379 | 70.66 488 | 85.83 446 | 88.73 434 | 96.04 414 | 85.33 332 | 97.76 414 | 80.02 455 | 90.48 376 | 95.84 420 |
|
| pmmvs3 | | | 86.67 427 | 84.86 432 | 92.11 435 | 88.16 472 | 87.19 446 | 96.63 432 | 94.75 455 | 79.88 461 | 87.22 440 | 92.75 462 | 66.56 460 | 95.20 460 | 81.24 453 | 76.56 469 | 93.96 455 |
|
| test_f | | | 86.07 428 | 85.39 429 | 88.10 442 | 89.28 470 | 75.57 469 | 97.73 354 | 96.33 434 | 89.41 424 | 85.35 452 | 91.56 466 | 43.31 476 | 95.53 456 | 91.32 362 | 84.23 439 | 93.21 461 |
|
| WB-MVS | | | 84.86 429 | 85.33 430 | 83.46 451 | 89.48 469 | 69.56 477 | 98.19 289 | 96.42 433 | 89.55 420 | 81.79 460 | 94.67 441 | 84.80 341 | 90.12 473 | 52.44 477 | 80.64 457 | 90.69 464 |
|
| SSC-MVS | | | 84.27 430 | 84.71 433 | 82.96 455 | 89.19 471 | 68.83 478 | 98.08 310 | 96.30 435 | 89.04 428 | 81.37 462 | 94.47 442 | 84.60 348 | 89.89 474 | 49.80 479 | 79.52 459 | 90.15 465 |
|
| dongtai | | | 82.47 431 | 81.88 434 | 84.22 449 | 95.19 433 | 76.03 466 | 94.59 464 | 74.14 487 | 82.63 456 | 87.19 441 | 96.09 411 | 64.10 464 | 87.85 477 | 58.91 475 | 84.11 440 | 88.78 469 |
|
| test_vis3_rt | | | 79.22 432 | 77.40 439 | 84.67 448 | 86.44 476 | 74.85 472 | 97.66 359 | 81.43 483 | 84.98 450 | 67.12 476 | 81.91 474 | 28.09 484 | 97.60 420 | 88.96 405 | 80.04 458 | 81.55 474 |
|
| test_method | | | 79.03 433 | 78.17 435 | 81.63 456 | 86.06 477 | 54.40 488 | 82.75 477 | 96.89 416 | 39.54 480 | 80.98 464 | 95.57 431 | 58.37 469 | 94.73 463 | 84.74 441 | 78.61 462 | 95.75 422 |
|
| testf1 | | | 79.02 434 | 77.70 436 | 82.99 453 | 88.10 473 | 66.90 479 | 94.67 460 | 93.11 466 | 71.08 471 | 74.02 469 | 93.41 454 | 34.15 480 | 93.25 467 | 72.25 469 | 78.50 463 | 88.82 467 |
|
| APD_test2 | | | 79.02 434 | 77.70 436 | 82.99 453 | 88.10 473 | 66.90 479 | 94.67 460 | 93.11 466 | 71.08 471 | 74.02 469 | 93.41 454 | 34.15 480 | 93.25 467 | 72.25 469 | 78.50 463 | 88.82 467 |
|
| LCM-MVSNet | | | 78.70 436 | 76.24 442 | 86.08 445 | 77.26 484 | 71.99 475 | 94.34 466 | 96.72 423 | 61.62 475 | 76.53 467 | 89.33 468 | 33.91 482 | 92.78 470 | 81.85 450 | 74.60 471 | 93.46 458 |
|
| kuosan | | | 78.45 437 | 77.69 438 | 80.72 457 | 92.73 457 | 75.32 470 | 94.63 463 | 74.51 486 | 75.96 467 | 80.87 465 | 93.19 456 | 63.23 466 | 79.99 481 | 42.56 481 | 81.56 451 | 86.85 473 |
|
| Gipuma |  | | 78.40 438 | 76.75 441 | 83.38 452 | 95.54 422 | 80.43 464 | 79.42 478 | 97.40 375 | 64.67 474 | 73.46 471 | 80.82 475 | 45.65 473 | 93.14 469 | 66.32 473 | 87.43 417 | 76.56 477 |
| S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
| PMMVS2 | | | 77.95 439 | 75.44 443 | 85.46 446 | 82.54 479 | 74.95 471 | 94.23 467 | 93.08 468 | 72.80 470 | 74.68 468 | 87.38 469 | 36.36 479 | 91.56 471 | 73.95 467 | 63.94 476 | 89.87 466 |
|
| FPMVS | | | 77.62 440 | 77.14 440 | 79.05 459 | 79.25 482 | 60.97 484 | 95.79 445 | 95.94 441 | 65.96 473 | 67.93 475 | 94.40 445 | 37.73 478 | 88.88 476 | 68.83 472 | 88.46 407 | 87.29 470 |
|
| EGC-MVSNET | | | 75.22 441 | 69.54 444 | 92.28 433 | 94.81 439 | 89.58 411 | 97.64 361 | 96.50 430 | 1.82 485 | 5.57 486 | 95.74 422 | 68.21 454 | 96.26 450 | 73.80 468 | 91.71 361 | 90.99 463 |
|
| ANet_high | | | 69.08 442 | 65.37 446 | 80.22 458 | 65.99 486 | 71.96 476 | 90.91 473 | 90.09 477 | 82.62 457 | 49.93 481 | 78.39 476 | 29.36 483 | 81.75 478 | 62.49 474 | 38.52 480 | 86.95 472 |
|
| tmp_tt | | | 68.90 443 | 66.97 445 | 74.68 461 | 50.78 488 | 59.95 485 | 87.13 474 | 83.47 482 | 38.80 481 | 62.21 477 | 96.23 405 | 64.70 463 | 76.91 483 | 88.91 406 | 30.49 481 | 87.19 471 |
|
| PMVS |  | 61.03 23 | 65.95 444 | 63.57 448 | 73.09 462 | 57.90 487 | 51.22 489 | 85.05 476 | 93.93 464 | 54.45 476 | 44.32 482 | 83.57 471 | 13.22 485 | 89.15 475 | 58.68 476 | 81.00 454 | 78.91 476 |
| Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
| E-PMN | | | 64.94 445 | 64.25 447 | 67.02 463 | 82.28 480 | 59.36 486 | 91.83 472 | 85.63 480 | 52.69 477 | 60.22 478 | 77.28 477 | 41.06 477 | 80.12 480 | 46.15 480 | 41.14 478 | 61.57 479 |
|
| EMVS | | | 64.07 446 | 63.26 449 | 66.53 464 | 81.73 481 | 58.81 487 | 91.85 471 | 84.75 481 | 51.93 479 | 59.09 479 | 75.13 478 | 43.32 475 | 79.09 482 | 42.03 482 | 39.47 479 | 61.69 478 |
|
| MVE |  | 62.14 22 | 63.28 447 | 59.38 450 | 74.99 460 | 74.33 485 | 65.47 481 | 85.55 475 | 80.50 484 | 52.02 478 | 51.10 480 | 75.00 479 | 10.91 488 | 80.50 479 | 51.60 478 | 53.40 477 | 78.99 475 |
| Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
| wuyk23d | | | 30.17 448 | 30.18 452 | 30.16 465 | 78.61 483 | 43.29 490 | 66.79 479 | 14.21 489 | 17.31 482 | 14.82 485 | 11.93 485 | 11.55 487 | 41.43 484 | 37.08 483 | 19.30 482 | 5.76 482 |
|
| cdsmvs_eth3d_5k | | | 23.98 449 | 31.98 451 | 0.00 468 | 0.00 491 | 0.00 493 | 0.00 480 | 98.59 172 | 0.00 486 | 0.00 487 | 98.61 203 | 90.60 201 | 0.00 487 | 0.00 486 | 0.00 485 | 0.00 483 |
|
| testmvs | | | 21.48 450 | 24.95 453 | 11.09 467 | 14.89 489 | 6.47 492 | 96.56 434 | 9.87 490 | 7.55 483 | 17.93 483 | 39.02 481 | 9.43 489 | 5.90 486 | 16.56 485 | 12.72 483 | 20.91 481 |
|
| test123 | | | 20.95 451 | 23.72 454 | 12.64 466 | 13.54 490 | 8.19 491 | 96.55 435 | 6.13 491 | 7.48 484 | 16.74 484 | 37.98 482 | 12.97 486 | 6.05 485 | 16.69 484 | 5.43 484 | 23.68 480 |
|
| ab-mvs-re | | | 8.20 452 | 10.94 455 | 0.00 468 | 0.00 491 | 0.00 493 | 0.00 480 | 0.00 492 | 0.00 486 | 0.00 487 | 98.43 221 | 0.00 490 | 0.00 487 | 0.00 486 | 0.00 485 | 0.00 483 |
|
| pcd_1.5k_mvsjas | | | 7.88 453 | 10.50 456 | 0.00 468 | 0.00 491 | 0.00 493 | 0.00 480 | 0.00 492 | 0.00 486 | 0.00 487 | 0.00 486 | 94.51 91 | 0.00 487 | 0.00 486 | 0.00 485 | 0.00 483 |
|
| mmdepth | | | 0.00 454 | 0.00 457 | 0.00 468 | 0.00 491 | 0.00 493 | 0.00 480 | 0.00 492 | 0.00 486 | 0.00 487 | 0.00 486 | 0.00 490 | 0.00 487 | 0.00 486 | 0.00 485 | 0.00 483 |
|
| monomultidepth | | | 0.00 454 | 0.00 457 | 0.00 468 | 0.00 491 | 0.00 493 | 0.00 480 | 0.00 492 | 0.00 486 | 0.00 487 | 0.00 486 | 0.00 490 | 0.00 487 | 0.00 486 | 0.00 485 | 0.00 483 |
|
| test_blank | | | 0.00 454 | 0.00 457 | 0.00 468 | 0.00 491 | 0.00 493 | 0.00 480 | 0.00 492 | 0.00 486 | 0.00 487 | 0.00 486 | 0.00 490 | 0.00 487 | 0.00 486 | 0.00 485 | 0.00 483 |
|
| uanet_test | | | 0.00 454 | 0.00 457 | 0.00 468 | 0.00 491 | 0.00 493 | 0.00 480 | 0.00 492 | 0.00 486 | 0.00 487 | 0.00 486 | 0.00 490 | 0.00 487 | 0.00 486 | 0.00 485 | 0.00 483 |
|
| DCPMVS | | | 0.00 454 | 0.00 457 | 0.00 468 | 0.00 491 | 0.00 493 | 0.00 480 | 0.00 492 | 0.00 486 | 0.00 487 | 0.00 486 | 0.00 490 | 0.00 487 | 0.00 486 | 0.00 485 | 0.00 483 |
|
| sosnet-low-res | | | 0.00 454 | 0.00 457 | 0.00 468 | 0.00 491 | 0.00 493 | 0.00 480 | 0.00 492 | 0.00 486 | 0.00 487 | 0.00 486 | 0.00 490 | 0.00 487 | 0.00 486 | 0.00 485 | 0.00 483 |
|
| sosnet | | | 0.00 454 | 0.00 457 | 0.00 468 | 0.00 491 | 0.00 493 | 0.00 480 | 0.00 492 | 0.00 486 | 0.00 487 | 0.00 486 | 0.00 490 | 0.00 487 | 0.00 486 | 0.00 485 | 0.00 483 |
|
| uncertanet | | | 0.00 454 | 0.00 457 | 0.00 468 | 0.00 491 | 0.00 493 | 0.00 480 | 0.00 492 | 0.00 486 | 0.00 487 | 0.00 486 | 0.00 490 | 0.00 487 | 0.00 486 | 0.00 485 | 0.00 483 |
|
| Regformer | | | 0.00 454 | 0.00 457 | 0.00 468 | 0.00 491 | 0.00 493 | 0.00 480 | 0.00 492 | 0.00 486 | 0.00 487 | 0.00 486 | 0.00 490 | 0.00 487 | 0.00 486 | 0.00 485 | 0.00 483 |
|
| uanet | | | 0.00 454 | 0.00 457 | 0.00 468 | 0.00 491 | 0.00 493 | 0.00 480 | 0.00 492 | 0.00 486 | 0.00 487 | 0.00 486 | 0.00 490 | 0.00 487 | 0.00 486 | 0.00 485 | 0.00 483 |
|
| MED-MVS test | | | | | 99.52 13 | 99.77 2 | 98.86 22 | 99.32 22 | 99.24 20 | 96.41 121 | 99.30 50 | 99.35 60 | | 99.92 43 | 98.30 75 | 99.80 25 | 99.79 28 |
|
| TestfortrainingZip | | | | | | | | 99.32 22 | | | | | | | | | |
|
| WAC-MVS | | | | | | | 90.94 376 | | | | | | | | 88.66 408 | | |
|
| FOURS1 | | | | | | 99.82 1 | 98.66 28 | 99.69 1 | 98.95 61 | 97.46 55 | 99.39 44 | | | | | | |
|
| MSC_two_6792asdad | | | | | 99.62 7 | 99.17 111 | 99.08 12 | | 98.63 162 | | | | | 99.94 14 | 98.53 55 | 99.80 25 | 99.86 12 |
|
| PC_three_1452 | | | | | | | | | | 95.08 206 | 99.60 32 | 99.16 103 | 97.86 2 | 98.47 341 | 97.52 131 | 99.72 68 | 99.74 50 |
|
| No_MVS | | | | | 99.62 7 | 99.17 111 | 99.08 12 | | 98.63 162 | | | | | 99.94 14 | 98.53 55 | 99.80 25 | 99.86 12 |
|
| test_one_0601 | | | | | | 99.66 31 | 99.25 3 | | 98.86 91 | 97.55 47 | 99.20 59 | 99.47 35 | 97.57 8 | | | | |
|
| eth-test2 | | | | | | 0.00 491 | | | | | | | | | | | |
|
| eth-test | | | | | | 0.00 491 | | | | | | | | | | | |
|
| ZD-MVS | | | | | | 99.46 58 | 98.70 27 | | 98.79 119 | 93.21 317 | 98.67 104 | 98.97 144 | 95.70 52 | 99.83 90 | 96.07 203 | 99.58 99 | |
|
| RE-MVS-def | | | | 98.34 54 | | 99.49 52 | 97.86 74 | 99.11 65 | 98.80 114 | 96.49 116 | 99.17 62 | 99.35 60 | 95.29 69 | | 97.72 110 | 99.65 82 | 99.71 63 |
|
| IU-MVS | | | | | | 99.71 24 | 99.23 8 | | 98.64 159 | 95.28 189 | 99.63 31 | | | | 98.35 72 | 99.81 16 | 99.83 18 |
|
| OPU-MVS | | | | | 99.37 27 | 99.24 103 | 99.05 15 | 99.02 84 | | | | 99.16 103 | 97.81 3 | 99.37 210 | 97.24 153 | 99.73 63 | 99.70 67 |
|
| test_241102_TWO | | | | | | | | | 98.87 85 | 97.65 39 | 99.53 37 | 99.48 33 | 97.34 13 | 99.94 14 | 98.43 67 | 99.80 25 | 99.83 18 |
|
| test_241102_ONE | | | | | | 99.71 24 | 99.24 6 | | 98.87 85 | 97.62 41 | 99.73 22 | 99.39 48 | 97.53 9 | 99.74 134 | | | |
|
| 9.14 | | | | 98.06 79 | | 99.47 56 | | 98.71 184 | 98.82 101 | 94.36 252 | 99.16 66 | 99.29 75 | 96.05 40 | 99.81 102 | 97.00 160 | 99.71 70 | |
|
| save fliter | | | | | | 99.46 58 | 98.38 40 | 98.21 284 | 98.71 137 | 97.95 28 | | | | | | | |
|
| test_0728_THIRD | | | | | | | | | | 97.32 63 | 99.45 39 | 99.46 40 | 97.88 1 | 99.94 14 | 98.47 63 | 99.86 2 | 99.85 15 |
|
| test_0728_SECOND | | | | | 99.71 1 | 99.72 17 | 99.35 1 | 98.97 95 | 98.88 78 | | | | | 99.94 14 | 98.47 63 | 99.81 16 | 99.84 17 |
|
| test0726 | | | | | | 99.72 17 | 99.25 3 | 99.06 72 | 98.88 78 | 97.62 41 | 99.56 34 | 99.50 29 | 97.42 11 | | | | |
|
| GSMVS | | | | | | | | | | | | | | | | | 99.20 180 |
|
| test_part2 | | | | | | 99.63 34 | 99.18 11 | | | | 99.27 56 | | | | | | |
|
| sam_mvs1 | | | | | | | | | | | | | 89.45 231 | | | | 99.20 180 |
|
| sam_mvs | | | | | | | | | | | | | 88.99 247 | | | | |
|
| ambc | | | | | 89.49 440 | 86.66 475 | 75.78 467 | 92.66 470 | 96.72 423 | | 86.55 446 | 92.50 463 | 46.01 472 | 97.90 404 | 90.32 379 | 82.09 446 | 94.80 442 |
|
| MTGPA |  | | | | | | | | 98.74 129 | | | | | | | | |
|
| test_post1 | | | | | | | | 96.68 431 | | | | 30.43 484 | 87.85 282 | 98.69 319 | 92.59 330 | | |
|
| test_post | | | | | | | | | | | | 31.83 483 | 88.83 254 | 98.91 295 | | | |
|
| patchmatchnet-post | | | | | | | | | | | | 95.10 437 | 89.42 232 | 98.89 299 | | | |
|
| GG-mvs-BLEND | | | | | 96.59 295 | 96.34 391 | 94.98 248 | 96.51 436 | 88.58 479 | | 93.10 371 | 94.34 448 | 80.34 395 | 98.05 392 | 89.53 395 | 96.99 257 | 96.74 357 |
|
| MTMP | | | | | | | | 98.89 120 | 94.14 462 | | | | | | | | |
|
| gm-plane-assit | | | | | | 95.88 413 | 87.47 443 | | | 89.74 417 | | 96.94 372 | | 99.19 244 | 93.32 308 | | |
|
| test9_res | | | | | | | | | | | | | | | 96.39 197 | 99.57 100 | 99.69 70 |
|
| TEST9 | | | | | | 99.31 79 | 98.50 34 | 97.92 329 | 98.73 132 | 92.63 340 | 97.74 175 | 98.68 198 | 96.20 35 | 99.80 109 | | | |
|
| test_8 | | | | | | 99.29 88 | 98.44 36 | 97.89 337 | 98.72 134 | 92.98 328 | 97.70 180 | 98.66 201 | 96.20 35 | 99.80 109 | | | |
|
| agg_prior2 | | | | | | | | | | | | | | | 95.87 213 | 99.57 100 | 99.68 75 |
|
| agg_prior | | | | | | 99.30 83 | 98.38 40 | | 98.72 134 | | 97.57 196 | | | 99.81 102 | | | |
|
| TestCases | | | | | 96.99 255 | 99.25 96 | 93.21 330 | | 98.18 287 | 91.36 381 | 93.52 350 | 98.77 185 | 84.67 346 | 99.72 136 | 89.70 392 | 97.87 227 | 98.02 296 |
|
| test_prior4 | | | | | | | 98.01 70 | 97.86 341 | | | | | | | | | |
|
| test_prior2 | | | | | | | | 97.80 348 | | 96.12 137 | 97.89 165 | 98.69 197 | 95.96 44 | | 96.89 170 | 99.60 94 | |
|
| test_prior | | | | | 99.19 50 | 99.31 79 | 98.22 57 | | 98.84 96 | | | | | 99.70 142 | | | 99.65 83 |
|
| 旧先验2 | | | | | | | | 97.57 367 | | 91.30 386 | 98.67 104 | | | 99.80 109 | 95.70 224 | | |
|
| æ–°å‡ ä½•2 | | | | | | | | 97.64 361 | | | | | | | | | |
|
| æ–°å‡ ä½•1 | | | | | 99.16 55 | 99.34 71 | 98.01 70 | | 98.69 143 | 90.06 411 | 98.13 134 | 98.95 151 | 94.60 89 | 99.89 68 | 91.97 349 | 99.47 122 | 99.59 94 |
|
| 旧先验1 | | | | | | 99.29 88 | 97.48 89 | | 98.70 141 | | | 99.09 126 | 95.56 55 | | | 99.47 122 | 99.61 90 |
|
| æ— å…ˆéªŒ | | | | | | | | 97.58 366 | 98.72 134 | 91.38 380 | | | | 99.87 79 | 93.36 307 | | 99.60 92 |
|
| 原ACMM2 | | | | | | | | 97.67 358 | | | | | | | | | |
|
| 原ACMM1 | | | | | 98.65 97 | 99.32 77 | 96.62 140 | | 98.67 151 | 93.27 316 | 97.81 168 | 98.97 144 | 95.18 76 | 99.83 90 | 93.84 293 | 99.46 125 | 99.50 106 |
|
| test222 | | | | | | 99.23 104 | 97.17 116 | 97.40 375 | 98.66 154 | 88.68 430 | 98.05 142 | 98.96 149 | 94.14 102 | | | 99.53 113 | 99.61 90 |
|
| testdata2 | | | | | | | | | | | | | | 99.89 68 | 91.65 357 | | |
|
| segment_acmp | | | | | | | | | | | | | 96.85 16 | | | | |
|
| testdata | | | | | 98.26 141 | 99.20 109 | 95.36 225 | | 98.68 146 | 91.89 366 | 98.60 112 | 99.10 118 | 94.44 96 | 99.82 97 | 94.27 277 | 99.44 126 | 99.58 98 |
|
| testdata1 | | | | | | | | 97.32 385 | | 96.34 127 | | | | | | | |
|
| test12 | | | | | 99.18 52 | 99.16 115 | 98.19 59 | | 98.53 188 | | 98.07 138 | | 95.13 79 | 99.72 136 | | 99.56 108 | 99.63 88 |
|
| plane_prior7 | | | | | | 97.42 325 | 94.63 265 | | | | | | | | | | |
|
| plane_prior6 | | | | | | 97.35 332 | 94.61 268 | | | | | | 87.09 295 | | | | |
|
| plane_prior5 | | | | | | | | | 98.56 182 | | | | | 99.03 275 | 96.07 203 | 94.27 310 | 96.92 333 |
|
| plane_prior4 | | | | | | | | | | | | 98.28 240 | | | | | |
|
| plane_prior3 | | | | | | | 94.61 268 | | | 97.02 87 | 95.34 276 | | | | | | |
|
| plane_prior2 | | | | | | | | 98.80 156 | | 97.28 67 | | | | | | | |
|
| plane_prior1 | | | | | | 97.37 331 | | | | | | | | | | | |
|
| plane_prior | | | | | | | 94.60 270 | 98.44 255 | | 96.74 103 | | | | | | 94.22 312 | |
|
| n2 | | | | | | | | | 0.00 492 | | | | | | | | |
|
| nn | | | | | | | | | 0.00 492 | | | | | | | | |
|
| door-mid | | | | | | | | | 94.37 458 | | | | | | | | |
|
| lessismore_v0 | | | | | 94.45 404 | 94.93 437 | 88.44 434 | | 91.03 475 | | 86.77 444 | 97.64 304 | 76.23 431 | 98.42 347 | 90.31 380 | 85.64 435 | 96.51 393 |
|
| LGP-MVS_train | | | | | 96.47 310 | 97.46 320 | 93.54 311 | | 98.54 186 | 94.67 234 | 94.36 308 | 98.77 185 | 85.39 328 | 99.11 261 | 95.71 222 | 94.15 316 | 96.76 355 |
|
| test11 | | | | | | | | | 98.66 154 | | | | | | | | |
|
| door | | | | | | | | | 94.64 456 | | | | | | | | |
|
| HQP5-MVS | | | | | | | 94.25 287 | | | | | | | | | | |
|
| HQP-NCC | | | | | | 97.20 340 | | 98.05 313 | | 96.43 118 | 94.45 300 | | | | | | |
|
| ACMP_Plane | | | | | | 97.20 340 | | 98.05 313 | | 96.43 118 | 94.45 300 | | | | | | |
|
| BP-MVS | | | | | | | | | | | | | | | 95.30 236 | | |
|
| HQP4-MVS | | | | | | | | | | | 94.45 300 | | | 98.96 286 | | | 96.87 345 |
|
| HQP3-MVS | | | | | | | | | 98.46 207 | | | | | | | 94.18 314 | |
|
| HQP2-MVS | | | | | | | | | | | | | 86.75 301 | | | | |
|
| NP-MVS | | | | | | 97.28 334 | 94.51 273 | | | | | 97.73 291 | | | | | |
|
| MDTV_nov1_ep13_2view | | | | | | | 84.26 453 | 96.89 421 | | 90.97 395 | 97.90 164 | | 89.89 217 | | 93.91 291 | | 99.18 189 |
|
| MDTV_nov1_ep13 | | | | 95.40 228 | | 97.48 318 | 88.34 435 | 96.85 424 | 97.29 383 | 93.74 284 | 97.48 198 | 97.26 333 | 89.18 240 | 99.05 271 | 91.92 350 | 97.43 248 | |
|
| ACMMP++_ref | | | | | | | | | | | | | | | | 92.97 344 | |
|
| ACMMP++ | | | | | | | | | | | | | | | | 93.61 331 | |
|
| Test By Simon | | | | | | | | | | | | | 94.64 88 | | | | |
|
| ITE_SJBPF | | | | | 95.44 363 | 97.42 325 | 91.32 370 | | 97.50 363 | 95.09 205 | 93.59 345 | 98.35 231 | 81.70 377 | 98.88 301 | 89.71 391 | 93.39 337 | 96.12 414 |
|
| DeepMVS_CX |  | | | | 86.78 444 | 97.09 350 | 72.30 474 | | 95.17 452 | 75.92 468 | 84.34 457 | 95.19 435 | 70.58 450 | 95.35 457 | 79.98 457 | 89.04 401 | 92.68 462 |
|