| DVP-MVS++ | | | 98.06 1 | 97.99 1 | 98.28 10 | 98.67 67 | 95.39 12 | 99.29 1 | 98.28 52 | 94.78 61 | 98.93 20 | 98.87 31 | 96.04 2 | 99.86 9 | 97.45 46 | 99.58 23 | 99.59 32 |
|
| SED-MVS | | | 98.05 2 | 97.99 1 | 98.24 11 | 99.42 10 | 95.30 18 | 98.25 40 | 98.27 55 | 95.13 40 | 99.19 13 | 98.89 28 | 95.54 5 | 99.85 21 | 97.52 42 | 99.66 10 | 99.56 40 |
|
| TestfortrainingZip a | | | 97.92 3 | 97.70 10 | 98.58 3 | 99.56 1 | 96.08 5 | 98.69 11 | 98.70 16 | 93.45 118 | 98.73 30 | 98.53 51 | 95.46 7 | 99.86 9 | 96.63 69 | 99.58 23 | 99.80 1 |
|
| MED-MVS | | | 97.91 4 | 97.88 4 | 98.00 23 | 99.56 1 | 94.50 35 | 98.69 11 | 98.70 16 | 94.23 87 | 98.73 30 | 98.53 51 | 95.46 7 | 99.86 9 | 97.40 50 | 99.58 23 | 99.65 20 |
|
| DVP-MVS |  | | 97.91 4 | 97.81 5 | 98.22 14 | 99.45 6 | 95.36 14 | 98.21 47 | 97.85 137 | 94.92 50 | 98.73 30 | 98.87 31 | 95.08 10 | 99.84 26 | 97.52 42 | 99.67 6 | 99.48 56 |
| 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 |
| DPE-MVS |  | | 97.86 6 | 97.65 11 | 98.47 6 | 99.17 38 | 95.78 8 | 97.21 195 | 98.35 42 | 95.16 38 | 98.71 35 | 98.80 38 | 95.05 12 | 99.89 3 | 96.70 68 | 99.73 1 | 99.73 12 |
| Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025 |
| APDe-MVS |  | | 97.82 7 | 97.73 9 | 98.08 19 | 99.15 39 | 94.82 29 | 98.81 8 | 98.30 48 | 94.76 64 | 98.30 43 | 98.90 25 | 93.77 19 | 99.68 75 | 97.93 29 | 99.69 3 | 99.75 7 |
| Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition |
| CNVR-MVS | | | 97.68 8 | 97.44 24 | 98.37 8 | 98.90 59 | 95.86 7 | 97.27 186 | 98.08 93 | 95.81 20 | 97.87 58 | 98.31 81 | 94.26 15 | 99.68 75 | 97.02 57 | 99.49 43 | 99.57 36 |
|
| fmvsm_l_conf0.5_n | | | 97.65 9 | 97.75 8 | 97.34 61 | 98.21 106 | 92.75 92 | 97.83 98 | 98.73 10 | 95.04 45 | 99.30 7 | 98.84 36 | 93.34 24 | 99.78 49 | 99.32 7 | 99.13 98 | 99.50 52 |
|
| fmvsm_l_conf0.5_n_3 | | | 97.64 10 | 97.60 13 | 97.79 34 | 98.14 113 | 93.94 56 | 97.93 83 | 98.65 24 | 96.70 8 | 99.38 5 | 99.07 11 | 89.92 91 | 99.81 35 | 99.16 14 | 99.43 53 | 99.61 30 |
|
| fmvsm_l_conf0.5_n_a | | | 97.63 11 | 97.76 7 | 97.26 68 | 98.25 99 | 92.59 100 | 97.81 103 | 98.68 19 | 94.93 48 | 99.24 10 | 98.87 31 | 93.52 22 | 99.79 46 | 99.32 7 | 99.21 83 | 99.40 66 |
|
| SteuartSystems-ACMMP | | | 97.62 12 | 97.53 18 | 97.87 28 | 98.39 88 | 94.25 44 | 98.43 27 | 98.27 55 | 95.34 32 | 98.11 47 | 98.56 47 | 94.53 14 | 99.71 67 | 96.57 73 | 99.62 17 | 99.65 20 |
| Skip Steuart: Steuart Systems R&D Blog. |
| fmvsm_l_conf0.5_n_9 | | | 97.59 13 | 97.79 6 | 96.97 86 | 98.28 94 | 91.49 144 | 97.61 138 | 98.71 13 | 97.10 5 | 99.70 1 | 98.93 22 | 90.95 76 | 99.77 52 | 99.35 6 | 99.53 33 | 99.65 20 |
|
| MSP-MVS | | | 97.59 13 | 97.54 17 | 97.73 42 | 99.40 14 | 93.77 61 | 98.53 19 | 98.29 50 | 95.55 27 | 98.56 38 | 97.81 134 | 93.90 17 | 99.65 79 | 96.62 70 | 99.21 83 | 99.77 3 |
| 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 |
| lecture | | | 97.58 15 | 97.63 12 | 97.43 58 | 99.37 19 | 92.93 86 | 98.86 7 | 98.85 5 | 95.27 34 | 98.65 36 | 98.90 25 | 91.97 52 | 99.80 40 | 97.63 38 | 99.21 83 | 99.57 36 |
|
| test_fmvsm_n_1920 | | | 97.55 16 | 97.89 3 | 96.53 105 | 98.41 85 | 91.73 130 | 98.01 66 | 99.02 1 | 96.37 13 | 99.30 7 | 98.92 23 | 92.39 44 | 99.79 46 | 99.16 14 | 99.46 46 | 98.08 226 |
|
| ME-MVS | | | 97.54 17 | 97.39 27 | 98.00 23 | 99.21 36 | 94.50 35 | 97.75 110 | 98.34 44 | 94.23 87 | 98.15 46 | 98.53 51 | 93.32 27 | 99.84 26 | 97.40 50 | 99.58 23 | 99.65 20 |
|
| reproduce-ours | | | 97.53 18 | 97.51 20 | 97.60 51 | 98.97 53 | 93.31 73 | 97.71 120 | 98.20 69 | 95.80 21 | 97.88 55 | 98.98 18 | 92.91 30 | 99.81 35 | 97.68 33 | 99.43 53 | 99.67 15 |
|
| our_new_method | | | 97.53 18 | 97.51 20 | 97.60 51 | 98.97 53 | 93.31 73 | 97.71 120 | 98.20 69 | 95.80 21 | 97.88 55 | 98.98 18 | 92.91 30 | 99.81 35 | 97.68 33 | 99.43 53 | 99.67 15 |
|
| reproduce_model | | | 97.51 20 | 97.51 20 | 97.50 54 | 98.99 52 | 93.01 82 | 97.79 106 | 98.21 67 | 95.73 24 | 97.99 51 | 99.03 15 | 92.63 39 | 99.82 33 | 97.80 31 | 99.42 56 | 99.67 15 |
|
| test_fmvsmconf_n | | | 97.49 21 | 97.56 16 | 97.29 64 | 97.44 165 | 92.37 107 | 97.91 85 | 98.88 4 | 95.83 19 | 98.92 23 | 99.05 14 | 91.45 61 | 99.80 40 | 99.12 16 | 99.46 46 | 99.69 14 |
|
| TSAR-MVS + MP. | | | 97.42 22 | 97.33 29 | 97.69 46 | 99.25 32 | 94.24 45 | 98.07 60 | 97.85 137 | 93.72 103 | 98.57 37 | 98.35 72 | 93.69 20 | 99.40 133 | 97.06 56 | 99.46 46 | 99.44 61 |
| Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition |
| SD-MVS | | | 97.41 23 | 97.53 18 | 97.06 82 | 98.57 78 | 94.46 38 | 97.92 84 | 98.14 83 | 94.82 57 | 99.01 17 | 98.55 49 | 94.18 16 | 97.41 392 | 96.94 58 | 99.64 14 | 99.32 74 |
| 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 |
| SF-MVS | | | 97.39 24 | 97.13 31 | 98.17 16 | 99.02 48 | 95.28 20 | 98.23 44 | 98.27 55 | 92.37 169 | 98.27 44 | 98.65 45 | 93.33 25 | 99.72 65 | 96.49 75 | 99.52 35 | 99.51 49 |
|
| SMA-MVS |  | | 97.35 25 | 97.03 40 | 98.30 9 | 99.06 44 | 95.42 11 | 97.94 81 | 98.18 76 | 90.57 254 | 98.85 27 | 98.94 21 | 93.33 25 | 99.83 31 | 96.72 66 | 99.68 4 | 99.63 26 |
| 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 |
| HPM-MVS++ |  | | 97.34 26 | 96.97 43 | 98.47 6 | 99.08 42 | 96.16 4 | 97.55 149 | 97.97 121 | 95.59 25 | 96.61 97 | 97.89 117 | 92.57 41 | 99.84 26 | 95.95 99 | 99.51 38 | 99.40 66 |
|
| fmvsm_s_conf0.5_n_9 | | | 97.33 27 | 97.57 15 | 96.62 101 | 98.43 82 | 90.32 202 | 97.80 104 | 98.53 30 | 97.24 4 | 99.62 2 | 99.14 2 | 88.65 109 | 99.80 40 | 99.54 1 | 99.15 95 | 99.74 9 |
|
| fmvsm_s_conf0.5_n_8 | | | 97.32 28 | 97.48 23 | 96.85 88 | 98.28 94 | 91.07 169 | 97.76 108 | 98.62 26 | 97.53 2 | 99.20 12 | 99.12 5 | 88.24 117 | 99.81 35 | 99.41 3 | 99.17 91 | 99.67 15 |
|
| fmvsm_s_conf0.5_n_11 | | | 97.30 29 | 97.59 14 | 96.43 119 | 98.42 83 | 91.37 151 | 98.04 63 | 98.00 117 | 97.30 3 | 99.45 4 | 99.21 1 | 89.28 97 | 99.80 40 | 99.27 10 | 99.35 69 | 98.12 218 |
|
| NCCC | | | 97.30 29 | 97.03 40 | 98.11 18 | 98.77 62 | 95.06 26 | 97.34 177 | 98.04 108 | 95.96 15 | 97.09 79 | 97.88 121 | 93.18 28 | 99.71 67 | 95.84 104 | 99.17 91 | 99.56 40 |
|
| fmvsm_s_conf0.5_n_10 | | | 97.29 31 | 97.40 26 | 96.97 86 | 98.24 100 | 91.96 126 | 97.89 88 | 98.72 12 | 96.77 7 | 99.46 3 | 99.06 12 | 87.78 127 | 99.84 26 | 99.40 4 | 99.27 75 | 99.12 92 |
|
| MM | | | 97.29 31 | 96.98 42 | 98.23 12 | 98.01 123 | 95.03 27 | 98.07 60 | 95.76 348 | 97.78 1 | 97.52 62 | 98.80 38 | 88.09 119 | 99.86 9 | 99.44 2 | 99.37 67 | 99.80 1 |
|
| ACMMP_NAP | | | 97.20 33 | 96.86 49 | 98.23 12 | 99.09 40 | 95.16 23 | 97.60 139 | 98.19 74 | 92.82 154 | 97.93 54 | 98.74 42 | 91.60 59 | 99.86 9 | 96.26 80 | 99.52 35 | 99.67 15 |
|
| XVS | | | 97.18 34 | 96.96 45 | 97.81 32 | 99.38 17 | 94.03 54 | 98.59 17 | 98.20 69 | 94.85 53 | 96.59 99 | 98.29 84 | 91.70 56 | 99.80 40 | 95.66 108 | 99.40 61 | 99.62 27 |
|
| MCST-MVS | | | 97.18 34 | 96.84 51 | 98.20 15 | 99.30 29 | 95.35 16 | 97.12 202 | 98.07 98 | 93.54 112 | 96.08 125 | 97.69 147 | 93.86 18 | 99.71 67 | 96.50 74 | 99.39 63 | 99.55 43 |
|
| fmvsm_s_conf0.5_n_3 | | | 97.15 36 | 97.36 28 | 96.52 107 | 97.98 126 | 91.19 161 | 97.84 95 | 98.65 24 | 97.08 6 | 99.25 9 | 99.10 6 | 87.88 125 | 99.79 46 | 99.32 7 | 99.18 90 | 98.59 169 |
|
| HFP-MVS | | | 97.14 37 | 96.92 47 | 97.83 30 | 99.42 10 | 94.12 50 | 98.52 20 | 98.32 46 | 93.21 127 | 97.18 73 | 98.29 84 | 92.08 49 | 99.83 31 | 95.63 113 | 99.59 19 | 99.54 45 |
|
| test_fmvsmconf0.1_n | | | 97.09 38 | 97.06 35 | 97.19 73 | 95.67 305 | 92.21 114 | 97.95 80 | 98.27 55 | 95.78 23 | 98.40 42 | 99.00 16 | 89.99 89 | 99.78 49 | 99.06 18 | 99.41 59 | 99.59 32 |
|
| fmvsm_s_conf0.5_n_6 | | | 97.08 39 | 97.17 30 | 96.81 89 | 97.28 170 | 91.73 130 | 97.75 110 | 98.50 31 | 94.86 52 | 99.22 11 | 98.78 40 | 89.75 94 | 99.76 54 | 99.10 17 | 99.29 73 | 98.94 121 |
|
| MTAPA | | | 97.08 39 | 96.78 59 | 97.97 27 | 99.37 19 | 94.42 40 | 97.24 188 | 98.08 93 | 95.07 44 | 96.11 123 | 98.59 46 | 90.88 79 | 99.90 2 | 96.18 92 | 99.50 40 | 99.58 35 |
|
| region2R | | | 97.07 41 | 96.84 51 | 97.77 38 | 99.46 5 | 93.79 59 | 98.52 20 | 98.24 63 | 93.19 130 | 97.14 76 | 98.34 75 | 91.59 60 | 99.87 7 | 95.46 119 | 99.59 19 | 99.64 25 |
|
| ACMMPR | | | 97.07 41 | 96.84 51 | 97.79 34 | 99.44 9 | 93.88 57 | 98.52 20 | 98.31 47 | 93.21 127 | 97.15 75 | 98.33 78 | 91.35 65 | 99.86 9 | 95.63 113 | 99.59 19 | 99.62 27 |
|
| CP-MVS | | | 97.02 43 | 96.81 56 | 97.64 49 | 99.33 26 | 93.54 64 | 98.80 9 | 98.28 52 | 92.99 140 | 96.45 111 | 98.30 83 | 91.90 53 | 99.85 21 | 95.61 115 | 99.68 4 | 99.54 45 |
|
| SR-MVS | | | 97.01 44 | 96.86 49 | 97.47 56 | 99.09 40 | 93.27 75 | 97.98 71 | 98.07 98 | 93.75 102 | 97.45 64 | 98.48 61 | 91.43 63 | 99.59 95 | 96.22 83 | 99.27 75 | 99.54 45 |
|
| fmvsm_s_conf0.5_n_5 | | | 97.00 45 | 96.97 43 | 97.09 79 | 97.58 161 | 92.56 101 | 97.68 124 | 98.47 35 | 94.02 93 | 98.90 25 | 98.89 28 | 88.94 103 | 99.78 49 | 99.18 12 | 99.03 107 | 98.93 125 |
|
| ZNCC-MVS | | | 96.96 46 | 96.67 64 | 97.85 29 | 99.37 19 | 94.12 50 | 98.49 24 | 98.18 76 | 92.64 161 | 96.39 113 | 98.18 91 | 91.61 58 | 99.88 4 | 95.59 118 | 99.55 30 | 99.57 36 |
|
| APD-MVS |  | | 96.95 47 | 96.60 66 | 98.01 21 | 99.03 47 | 94.93 28 | 97.72 118 | 98.10 91 | 91.50 204 | 98.01 50 | 98.32 80 | 92.33 45 | 99.58 98 | 94.85 135 | 99.51 38 | 99.53 48 |
| Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
| MSLP-MVS++ | | | 96.94 48 | 97.06 35 | 96.59 102 | 98.72 64 | 91.86 128 | 97.67 125 | 98.49 32 | 94.66 69 | 97.24 72 | 98.41 67 | 92.31 47 | 98.94 195 | 96.61 71 | 99.46 46 | 98.96 114 |
|
| DeepC-MVS_fast | | 93.89 2 | 96.93 49 | 96.64 65 | 97.78 36 | 98.64 73 | 94.30 41 | 97.41 167 | 98.04 108 | 94.81 59 | 96.59 99 | 98.37 70 | 91.24 68 | 99.64 87 | 95.16 124 | 99.52 35 | 99.42 65 |
| Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
| SPE-MVS-test | | | 96.89 50 | 97.04 39 | 96.45 118 | 98.29 93 | 91.66 137 | 99.03 4 | 97.85 137 | 95.84 18 | 96.90 83 | 97.97 109 | 91.24 68 | 98.75 229 | 96.92 59 | 99.33 70 | 98.94 121 |
|
| SR-MVS-dyc-post | | | 96.88 51 | 96.80 57 | 97.11 78 | 99.02 48 | 92.34 108 | 97.98 71 | 98.03 110 | 93.52 115 | 97.43 67 | 98.51 56 | 91.40 64 | 99.56 106 | 96.05 94 | 99.26 78 | 99.43 63 |
|
| CS-MVS | | | 96.86 52 | 97.06 35 | 96.26 135 | 98.16 112 | 91.16 166 | 99.09 3 | 97.87 132 | 95.30 33 | 97.06 80 | 98.03 101 | 91.72 54 | 98.71 239 | 97.10 55 | 99.17 91 | 98.90 130 |
|
| mPP-MVS | | | 96.86 52 | 96.60 66 | 97.64 49 | 99.40 14 | 93.44 66 | 98.50 23 | 98.09 92 | 93.27 126 | 95.95 131 | 98.33 78 | 91.04 73 | 99.88 4 | 95.20 122 | 99.57 29 | 99.60 31 |
|
| fmvsm_s_conf0.5_n | | | 96.85 54 | 97.13 31 | 96.04 149 | 98.07 120 | 90.28 203 | 97.97 77 | 98.76 9 | 94.93 48 | 98.84 28 | 99.06 12 | 88.80 106 | 99.65 79 | 99.06 18 | 98.63 123 | 98.18 211 |
|
| GST-MVS | | | 96.85 54 | 96.52 70 | 97.82 31 | 99.36 23 | 94.14 49 | 98.29 34 | 98.13 84 | 92.72 157 | 96.70 91 | 98.06 98 | 91.35 65 | 99.86 9 | 94.83 138 | 99.28 74 | 99.47 58 |
|
| balanced_conf03 | | | 96.84 56 | 96.89 48 | 96.68 93 | 97.63 153 | 92.22 113 | 98.17 53 | 97.82 143 | 94.44 79 | 98.23 45 | 97.36 177 | 90.97 75 | 99.22 151 | 97.74 32 | 99.66 10 | 98.61 166 |
|
| patch_mono-2 | | | 96.83 57 | 97.44 24 | 95.01 223 | 99.05 45 | 85.39 366 | 96.98 215 | 98.77 8 | 94.70 66 | 97.99 51 | 98.66 43 | 93.61 21 | 99.91 1 | 97.67 37 | 99.50 40 | 99.72 13 |
|
| APD-MVS_3200maxsize | | | 96.81 58 | 96.71 63 | 97.12 76 | 99.01 51 | 92.31 110 | 97.98 71 | 98.06 101 | 93.11 136 | 97.44 65 | 98.55 49 | 90.93 77 | 99.55 108 | 96.06 93 | 99.25 80 | 99.51 49 |
|
| PGM-MVS | | | 96.81 58 | 96.53 69 | 97.65 47 | 99.35 25 | 93.53 65 | 97.65 129 | 98.98 2 | 92.22 175 | 97.14 76 | 98.44 64 | 91.17 71 | 99.85 21 | 94.35 161 | 99.46 46 | 99.57 36 |
|
| MP-MVS |  | | 96.77 60 | 96.45 77 | 97.72 43 | 99.39 16 | 93.80 58 | 98.41 28 | 98.06 101 | 93.37 122 | 95.54 149 | 98.34 75 | 90.59 83 | 99.88 4 | 94.83 138 | 99.54 32 | 99.49 54 |
| Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
| PHI-MVS | | | 96.77 60 | 96.46 76 | 97.71 45 | 98.40 86 | 94.07 52 | 98.21 47 | 98.45 37 | 89.86 272 | 97.11 78 | 98.01 104 | 92.52 42 | 99.69 73 | 96.03 97 | 99.53 33 | 99.36 72 |
|
| fmvsm_s_conf0.5_n_4 | | | 96.75 62 | 97.07 34 | 95.79 173 | 97.76 142 | 89.57 232 | 97.66 128 | 98.66 22 | 95.36 30 | 99.03 16 | 98.90 25 | 88.39 114 | 99.73 61 | 99.17 13 | 98.66 121 | 98.08 226 |
|
| fmvsm_s_conf0.5_n_a | | | 96.75 62 | 96.93 46 | 96.20 140 | 97.64 151 | 90.72 185 | 98.00 67 | 98.73 10 | 94.55 73 | 98.91 24 | 99.08 8 | 88.22 118 | 99.63 88 | 98.91 21 | 98.37 136 | 98.25 206 |
|
| MGCNet | | | 96.74 64 | 96.31 81 | 98.02 20 | 96.87 203 | 94.65 31 | 97.58 140 | 94.39 415 | 96.47 12 | 97.16 74 | 98.39 68 | 87.53 136 | 99.87 7 | 98.97 20 | 99.41 59 | 99.55 43 |
|
| test_fmvsmvis_n_1920 | | | 96.70 65 | 96.84 51 | 96.31 129 | 96.62 230 | 91.73 130 | 97.98 71 | 98.30 48 | 96.19 14 | 96.10 124 | 98.95 20 | 89.42 95 | 99.76 54 | 98.90 22 | 99.08 102 | 97.43 266 |
|
| MP-MVS-pluss | | | 96.70 65 | 96.27 83 | 97.98 26 | 99.23 35 | 94.71 30 | 96.96 217 | 98.06 101 | 90.67 244 | 95.55 147 | 98.78 40 | 91.07 72 | 99.86 9 | 96.58 72 | 99.55 30 | 99.38 70 |
| MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
| TSAR-MVS + GP. | | | 96.69 67 | 96.49 71 | 97.27 67 | 98.31 92 | 93.39 67 | 96.79 240 | 96.72 295 | 94.17 89 | 97.44 65 | 97.66 151 | 92.76 34 | 99.33 139 | 96.86 62 | 97.76 162 | 99.08 98 |
|
| HPM-MVS |  | | 96.69 67 | 96.45 77 | 97.40 59 | 99.36 23 | 93.11 80 | 98.87 6 | 98.06 101 | 91.17 223 | 96.40 112 | 97.99 107 | 90.99 74 | 99.58 98 | 95.61 115 | 99.61 18 | 99.49 54 |
| Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
| MVS_111021_HR | | | 96.68 69 | 96.58 68 | 96.99 84 | 98.46 79 | 92.31 110 | 96.20 303 | 98.90 3 | 94.30 86 | 95.86 134 | 97.74 142 | 92.33 45 | 99.38 136 | 96.04 96 | 99.42 56 | 99.28 77 |
|
| fmvsm_s_conf0.5_n_2 | | | 96.62 70 | 96.82 55 | 96.02 151 | 97.98 126 | 90.43 195 | 97.50 153 | 98.59 27 | 96.59 10 | 99.31 6 | 99.08 8 | 84.47 202 | 99.75 58 | 99.37 5 | 98.45 133 | 97.88 239 |
|
| DELS-MVS | | | 96.61 71 | 96.38 80 | 97.30 63 | 97.79 140 | 93.19 78 | 95.96 317 | 98.18 76 | 95.23 35 | 95.87 133 | 97.65 152 | 91.45 61 | 99.70 72 | 95.87 100 | 99.44 52 | 99.00 109 |
| 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 |
| DeepPCF-MVS | | 93.97 1 | 96.61 71 | 97.09 33 | 95.15 214 | 98.09 116 | 86.63 332 | 96.00 315 | 98.15 81 | 95.43 28 | 97.95 53 | 98.56 47 | 93.40 23 | 99.36 137 | 96.77 63 | 99.48 44 | 99.45 59 |
|
| fmvsm_s_conf0.1_n | | | 96.58 73 | 96.77 60 | 96.01 154 | 96.67 228 | 90.25 204 | 97.91 85 | 98.38 38 | 94.48 77 | 98.84 28 | 99.14 2 | 88.06 120 | 99.62 89 | 98.82 23 | 98.60 125 | 98.15 215 |
|
| MVSMamba_PlusPlus | | | 96.51 74 | 96.48 72 | 96.59 102 | 98.07 120 | 91.97 124 | 98.14 54 | 97.79 145 | 90.43 259 | 97.34 70 | 97.52 167 | 91.29 67 | 99.19 154 | 98.12 28 | 99.64 14 | 98.60 167 |
|
| EI-MVSNet-Vis-set | | | 96.51 74 | 96.47 73 | 96.63 98 | 98.24 100 | 91.20 160 | 96.89 225 | 97.73 152 | 94.74 65 | 96.49 106 | 98.49 58 | 90.88 79 | 99.58 98 | 96.44 76 | 98.32 138 | 99.13 89 |
|
| HPM-MVS_fast | | | 96.51 74 | 96.27 83 | 97.22 70 | 99.32 27 | 92.74 93 | 98.74 10 | 98.06 101 | 90.57 254 | 96.77 88 | 98.35 72 | 90.21 86 | 99.53 112 | 94.80 142 | 99.63 16 | 99.38 70 |
|
| fmvsm_s_conf0.5_n_7 | | | 96.45 77 | 96.80 57 | 95.37 206 | 97.29 169 | 88.38 281 | 97.23 192 | 98.47 35 | 95.14 39 | 98.43 41 | 99.09 7 | 87.58 133 | 99.72 65 | 98.80 25 | 99.21 83 | 98.02 230 |
|
| EC-MVSNet | | | 96.42 78 | 96.47 73 | 96.26 135 | 97.01 192 | 91.52 143 | 98.89 5 | 97.75 149 | 94.42 80 | 96.64 96 | 97.68 148 | 89.32 96 | 98.60 255 | 97.45 46 | 99.11 101 | 98.67 164 |
|
| fmvsm_s_conf0.1_n_a | | | 96.40 79 | 96.47 73 | 96.16 142 | 95.48 314 | 90.69 186 | 97.91 85 | 98.33 45 | 94.07 91 | 98.93 20 | 99.14 2 | 87.44 141 | 99.61 90 | 98.63 26 | 98.32 138 | 98.18 211 |
|
| CANet | | | 96.39 80 | 96.02 88 | 97.50 54 | 97.62 154 | 93.38 68 | 97.02 208 | 97.96 122 | 95.42 29 | 94.86 170 | 97.81 134 | 87.38 143 | 99.82 33 | 96.88 60 | 99.20 88 | 99.29 75 |
|
| dcpmvs_2 | | | 96.37 81 | 97.05 38 | 94.31 270 | 98.96 55 | 84.11 387 | 97.56 144 | 97.51 191 | 93.92 97 | 97.43 67 | 98.52 55 | 92.75 35 | 99.32 141 | 97.32 54 | 99.50 40 | 99.51 49 |
|
| NormalMVS | | | 96.36 82 | 96.11 86 | 97.12 76 | 99.37 19 | 92.90 87 | 97.99 68 | 97.63 166 | 95.92 16 | 96.57 102 | 97.93 111 | 85.34 184 | 99.50 120 | 94.99 129 | 99.21 83 | 98.97 111 |
|
| EI-MVSNet-UG-set | | | 96.34 83 | 96.30 82 | 96.47 115 | 98.20 107 | 90.93 175 | 96.86 228 | 97.72 154 | 94.67 68 | 96.16 122 | 98.46 62 | 90.43 84 | 99.58 98 | 96.23 82 | 97.96 155 | 98.90 130 |
|
| fmvsm_s_conf0.1_n_2 | | | 96.33 84 | 96.44 79 | 96.00 155 | 97.30 168 | 90.37 201 | 97.53 150 | 97.92 127 | 96.52 11 | 99.14 15 | 99.08 8 | 83.21 224 | 99.74 59 | 99.22 11 | 98.06 150 | 97.88 239 |
|
| train_agg | | | 96.30 85 | 95.83 93 | 97.72 43 | 98.70 65 | 94.19 46 | 96.41 278 | 98.02 113 | 88.58 319 | 96.03 126 | 97.56 164 | 92.73 37 | 99.59 95 | 95.04 126 | 99.37 67 | 99.39 68 |
|
| ACMMP |  | | 96.27 86 | 95.93 89 | 97.28 66 | 99.24 33 | 92.62 98 | 98.25 40 | 98.81 6 | 92.99 140 | 94.56 180 | 98.39 68 | 88.96 102 | 99.85 21 | 94.57 155 | 97.63 163 | 99.36 72 |
| 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 |
| MVS_111021_LR | | | 96.24 87 | 96.19 85 | 96.39 124 | 98.23 105 | 91.35 153 | 96.24 300 | 98.79 7 | 93.99 95 | 95.80 136 | 97.65 152 | 89.92 91 | 99.24 149 | 95.87 100 | 99.20 88 | 98.58 170 |
|
| test_fmvsmconf0.01_n | | | 96.15 88 | 95.85 92 | 97.03 83 | 92.66 429 | 91.83 129 | 97.97 77 | 97.84 141 | 95.57 26 | 97.53 61 | 99.00 16 | 84.20 208 | 99.76 54 | 98.82 23 | 99.08 102 | 99.48 56 |
|
| DeepC-MVS | | 93.07 3 | 96.06 89 | 95.66 94 | 97.29 64 | 97.96 128 | 93.17 79 | 97.30 182 | 98.06 101 | 93.92 97 | 93.38 220 | 98.66 43 | 86.83 150 | 99.73 61 | 95.60 117 | 99.22 82 | 98.96 114 |
| Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
| CSCG | | | 96.05 90 | 95.91 90 | 96.46 117 | 99.24 33 | 90.47 192 | 98.30 33 | 98.57 29 | 89.01 301 | 93.97 201 | 97.57 162 | 92.62 40 | 99.76 54 | 94.66 149 | 99.27 75 | 99.15 87 |
|
| sasdasda | | | 96.02 91 | 95.45 101 | 97.75 40 | 97.59 157 | 95.15 24 | 98.28 35 | 97.60 171 | 94.52 75 | 96.27 117 | 96.12 257 | 87.65 130 | 99.18 157 | 96.20 88 | 94.82 254 | 98.91 127 |
|
| ETV-MVS | | | 96.02 91 | 95.89 91 | 96.40 122 | 97.16 176 | 92.44 105 | 97.47 162 | 97.77 148 | 94.55 73 | 96.48 107 | 94.51 339 | 91.23 70 | 98.92 198 | 95.65 111 | 98.19 144 | 97.82 247 |
|
| canonicalmvs | | | 96.02 91 | 95.45 101 | 97.75 40 | 97.59 157 | 95.15 24 | 98.28 35 | 97.60 171 | 94.52 75 | 96.27 117 | 96.12 257 | 87.65 130 | 99.18 157 | 96.20 88 | 94.82 254 | 98.91 127 |
|
| CDPH-MVS | | | 95.97 94 | 95.38 106 | 97.77 38 | 98.93 56 | 94.44 39 | 96.35 287 | 97.88 130 | 86.98 366 | 96.65 95 | 97.89 117 | 91.99 51 | 99.47 125 | 92.26 201 | 99.46 46 | 99.39 68 |
|
| UA-Net | | | 95.95 95 | 95.53 97 | 97.20 72 | 97.67 147 | 92.98 84 | 97.65 129 | 98.13 84 | 94.81 59 | 96.61 97 | 98.35 72 | 88.87 104 | 99.51 117 | 90.36 253 | 97.35 174 | 99.11 94 |
|
| SymmetryMVS | | | 95.94 96 | 95.54 96 | 97.15 74 | 97.85 136 | 92.90 87 | 97.99 68 | 96.91 282 | 95.92 16 | 96.57 102 | 97.93 111 | 85.34 184 | 99.50 120 | 94.99 129 | 96.39 219 | 99.05 102 |
|
| MGCFI-Net | | | 95.94 96 | 95.40 105 | 97.56 53 | 97.59 157 | 94.62 32 | 98.21 47 | 97.57 178 | 94.41 81 | 96.17 121 | 96.16 255 | 87.54 135 | 99.17 159 | 96.19 90 | 94.73 259 | 98.91 127 |
|
| BP-MVS1 | | | 95.89 98 | 95.49 98 | 97.08 81 | 96.67 228 | 93.20 77 | 98.08 58 | 96.32 321 | 94.56 72 | 96.32 114 | 97.84 128 | 84.07 211 | 99.15 163 | 96.75 64 | 98.78 116 | 98.90 130 |
|
| VNet | | | 95.89 98 | 95.45 101 | 97.21 71 | 98.07 120 | 92.94 85 | 97.50 153 | 98.15 81 | 93.87 99 | 97.52 62 | 97.61 158 | 85.29 186 | 99.53 112 | 95.81 105 | 95.27 245 | 99.16 85 |
|
| alignmvs | | | 95.87 100 | 95.23 111 | 97.78 36 | 97.56 163 | 95.19 22 | 97.86 91 | 97.17 246 | 94.39 83 | 96.47 108 | 96.40 242 | 85.89 169 | 99.20 153 | 96.21 87 | 95.11 250 | 98.95 118 |
|
| casdiffmvs_mvg |  | | 95.81 101 | 95.57 95 | 96.51 111 | 96.87 203 | 91.49 144 | 97.50 153 | 97.56 184 | 93.99 95 | 95.13 162 | 97.92 114 | 87.89 124 | 98.78 215 | 95.97 98 | 97.33 175 | 99.26 79 |
| Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025 |
| DPM-MVS | | | 95.69 102 | 94.92 124 | 98.01 21 | 98.08 119 | 95.71 10 | 95.27 359 | 97.62 170 | 90.43 259 | 95.55 147 | 97.07 197 | 91.72 54 | 99.50 120 | 89.62 269 | 98.94 111 | 98.82 146 |
|
| DP-MVS Recon | | | 95.68 103 | 95.12 116 | 97.37 60 | 99.19 37 | 94.19 46 | 97.03 206 | 98.08 93 | 88.35 328 | 95.09 163 | 97.65 152 | 89.97 90 | 99.48 124 | 92.08 212 | 98.59 126 | 98.44 188 |
|
| casdiffmvs |  | | 95.64 104 | 95.49 98 | 96.08 145 | 96.76 225 | 90.45 193 | 97.29 183 | 97.44 211 | 94.00 94 | 95.46 152 | 97.98 108 | 87.52 138 | 98.73 233 | 95.64 112 | 97.33 175 | 99.08 98 |
| Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025 |
| GDP-MVS | | | 95.62 105 | 95.13 114 | 97.09 79 | 96.79 214 | 93.26 76 | 97.89 88 | 97.83 142 | 93.58 107 | 96.80 85 | 97.82 132 | 83.06 231 | 99.16 161 | 94.40 158 | 97.95 156 | 98.87 140 |
|
| MG-MVS | | | 95.61 106 | 95.38 106 | 96.31 129 | 98.42 83 | 90.53 190 | 96.04 312 | 97.48 196 | 93.47 117 | 95.67 144 | 98.10 94 | 89.17 99 | 99.25 148 | 91.27 230 | 98.77 117 | 99.13 89 |
|
| baseline | | | 95.58 107 | 95.42 104 | 96.08 145 | 96.78 219 | 90.41 196 | 97.16 199 | 97.45 207 | 93.69 106 | 95.65 145 | 97.85 126 | 87.29 144 | 98.68 243 | 95.66 108 | 97.25 181 | 99.13 89 |
|
| CPTT-MVS | | | 95.57 108 | 95.19 112 | 96.70 92 | 99.27 31 | 91.48 146 | 98.33 31 | 98.11 89 | 87.79 347 | 95.17 161 | 98.03 101 | 87.09 148 | 99.61 90 | 93.51 179 | 99.42 56 | 99.02 103 |
|
| EIA-MVS | | | 95.53 109 | 95.47 100 | 95.71 184 | 97.06 184 | 89.63 228 | 97.82 100 | 97.87 132 | 93.57 108 | 93.92 202 | 95.04 311 | 90.61 82 | 98.95 193 | 94.62 151 | 98.68 120 | 98.54 173 |
|
| 3Dnovator+ | | 91.43 4 | 95.40 110 | 94.48 148 | 98.16 17 | 96.90 201 | 95.34 17 | 98.48 25 | 97.87 132 | 94.65 70 | 88.53 351 | 98.02 103 | 83.69 215 | 99.71 67 | 93.18 187 | 98.96 110 | 99.44 61 |
|
| PS-MVSNAJ | | | 95.37 111 | 95.33 108 | 95.49 200 | 97.35 167 | 90.66 188 | 95.31 356 | 97.48 196 | 93.85 100 | 96.51 105 | 95.70 282 | 88.65 109 | 99.65 79 | 94.80 142 | 98.27 141 | 96.17 305 |
|
| MVSFormer | | | 95.37 111 | 95.16 113 | 95.99 156 | 96.34 265 | 91.21 158 | 98.22 45 | 97.57 178 | 91.42 208 | 96.22 119 | 97.32 178 | 86.20 164 | 97.92 339 | 94.07 164 | 99.05 104 | 98.85 142 |
|
| diffmvs_AUTHOR | | | 95.33 113 | 95.27 110 | 95.50 199 | 96.37 263 | 89.08 259 | 96.08 310 | 97.38 222 | 93.09 138 | 96.53 104 | 97.74 142 | 86.45 158 | 98.68 243 | 96.32 78 | 97.48 166 | 98.75 155 |
|
| xiu_mvs_v2_base | | | 95.32 114 | 95.29 109 | 95.40 205 | 97.22 172 | 90.50 191 | 95.44 349 | 97.44 211 | 93.70 105 | 96.46 109 | 96.18 252 | 88.59 113 | 99.53 112 | 94.79 145 | 97.81 159 | 96.17 305 |
|
| E3new | | | 95.28 115 | 95.11 117 | 95.80 170 | 97.03 189 | 89.76 222 | 96.78 244 | 97.54 188 | 92.06 185 | 95.40 153 | 97.75 139 | 87.49 139 | 98.76 223 | 94.85 135 | 97.10 187 | 98.88 138 |
|
| PVSNet_Blended_VisFu | | | 95.27 116 | 94.91 125 | 96.38 125 | 98.20 107 | 90.86 178 | 97.27 186 | 98.25 61 | 90.21 263 | 94.18 194 | 97.27 184 | 87.48 140 | 99.73 61 | 93.53 178 | 97.77 161 | 98.55 172 |
|
| viewcassd2359sk11 | | | 95.26 117 | 95.09 118 | 95.80 170 | 96.95 198 | 89.72 224 | 96.80 239 | 97.56 184 | 92.21 177 | 95.37 154 | 97.80 136 | 87.17 147 | 98.77 219 | 94.82 140 | 97.10 187 | 98.90 130 |
|
| KinetiMVS | | | 95.26 117 | 94.75 134 | 96.79 90 | 96.99 194 | 92.05 120 | 97.82 100 | 97.78 146 | 94.77 63 | 96.46 109 | 97.70 145 | 80.62 286 | 99.34 138 | 92.37 200 | 98.28 140 | 98.97 111 |
|
| diffmvs |  | | 95.25 119 | 95.13 114 | 95.63 187 | 96.43 258 | 89.34 246 | 95.99 316 | 97.35 227 | 92.83 153 | 96.31 115 | 97.37 176 | 86.44 159 | 98.67 246 | 96.26 80 | 97.19 184 | 98.87 140 |
| Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025 |
| viewmanbaseed2359cas | | | 95.24 120 | 95.02 120 | 95.91 159 | 96.87 203 | 89.98 213 | 96.82 234 | 97.49 194 | 92.26 173 | 95.47 151 | 97.82 132 | 86.47 157 | 98.69 241 | 94.80 142 | 97.20 183 | 99.06 101 |
|
| Vis-MVSNet |  | | 95.23 121 | 94.81 129 | 96.51 111 | 97.18 175 | 91.58 141 | 98.26 39 | 98.12 86 | 94.38 84 | 94.90 169 | 98.15 93 | 82.28 252 | 98.92 198 | 91.45 227 | 98.58 127 | 99.01 106 |
| Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
| EPP-MVSNet | | | 95.22 122 | 95.04 119 | 95.76 177 | 97.49 164 | 89.56 233 | 98.67 15 | 97.00 272 | 90.69 242 | 94.24 190 | 97.62 157 | 89.79 93 | 98.81 211 | 93.39 184 | 96.49 214 | 98.92 126 |
|
| E2 | | | 95.20 123 | 95.00 121 | 95.79 173 | 96.79 214 | 89.66 225 | 96.82 234 | 97.58 175 | 92.35 170 | 95.28 156 | 97.83 130 | 86.68 152 | 98.76 223 | 94.79 145 | 96.92 193 | 98.95 118 |
|
| E3 | | | 95.20 123 | 95.00 121 | 95.79 173 | 96.77 221 | 89.66 225 | 96.82 234 | 97.58 175 | 92.35 170 | 95.28 156 | 97.83 130 | 86.69 151 | 98.76 223 | 94.79 145 | 96.92 193 | 98.95 118 |
|
| EPNet | | | 95.20 123 | 94.56 141 | 97.14 75 | 92.80 426 | 92.68 97 | 97.85 94 | 94.87 399 | 96.64 9 | 92.46 237 | 97.80 136 | 86.23 161 | 99.65 79 | 93.72 174 | 98.62 124 | 99.10 95 |
| Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
| 3Dnovator | | 91.36 5 | 95.19 126 | 94.44 150 | 97.44 57 | 96.56 241 | 93.36 70 | 98.65 16 | 98.36 39 | 94.12 90 | 89.25 333 | 98.06 98 | 82.20 254 | 99.77 52 | 93.41 183 | 99.32 71 | 99.18 84 |
|
| guyue | | | 95.17 127 | 94.96 123 | 95.82 168 | 96.97 196 | 89.65 227 | 97.56 144 | 95.58 360 | 94.82 57 | 95.72 139 | 97.42 173 | 82.90 236 | 98.84 207 | 96.71 67 | 96.93 192 | 98.96 114 |
|
| E4 | | | 95.09 128 | 94.86 128 | 95.77 176 | 96.58 236 | 89.56 233 | 96.85 229 | 97.56 184 | 92.50 164 | 95.03 166 | 97.86 124 | 86.03 167 | 98.78 215 | 94.71 148 | 96.65 207 | 98.96 114 |
|
| OMC-MVS | | | 95.09 128 | 94.70 135 | 96.25 138 | 98.46 79 | 91.28 154 | 96.43 274 | 97.57 178 | 92.04 186 | 94.77 175 | 97.96 110 | 87.01 149 | 99.09 174 | 91.31 229 | 96.77 198 | 98.36 195 |
|
| viewmacassd2359aftdt | | | 95.07 130 | 94.80 130 | 95.87 162 | 96.53 246 | 89.84 219 | 96.90 224 | 97.48 196 | 92.44 166 | 95.36 155 | 97.89 117 | 85.23 187 | 98.68 243 | 94.40 158 | 97.00 191 | 99.09 96 |
|
| E6 | | | 95.04 131 | 94.88 126 | 95.52 195 | 96.60 233 | 89.02 261 | 97.29 183 | 97.57 178 | 92.54 162 | 95.04 164 | 97.90 116 | 85.66 176 | 98.77 219 | 94.92 132 | 96.44 217 | 98.78 149 |
|
| E5 | | | 95.04 131 | 94.88 126 | 95.52 195 | 96.62 230 | 89.02 261 | 97.29 183 | 97.57 178 | 92.54 162 | 95.04 164 | 97.89 117 | 85.65 177 | 98.77 219 | 94.92 132 | 96.44 217 | 98.78 149 |
|
| xiu_mvs_v1_base_debu | | | 95.01 133 | 94.76 131 | 95.75 179 | 96.58 236 | 91.71 133 | 96.25 297 | 97.35 227 | 92.99 140 | 96.70 91 | 96.63 229 | 82.67 242 | 99.44 129 | 96.22 83 | 97.46 167 | 96.11 311 |
|
| xiu_mvs_v1_base | | | 95.01 133 | 94.76 131 | 95.75 179 | 96.58 236 | 91.71 133 | 96.25 297 | 97.35 227 | 92.99 140 | 96.70 91 | 96.63 229 | 82.67 242 | 99.44 129 | 96.22 83 | 97.46 167 | 96.11 311 |
|
| xiu_mvs_v1_base_debi | | | 95.01 133 | 94.76 131 | 95.75 179 | 96.58 236 | 91.71 133 | 96.25 297 | 97.35 227 | 92.99 140 | 96.70 91 | 96.63 229 | 82.67 242 | 99.44 129 | 96.22 83 | 97.46 167 | 96.11 311 |
|
| PAPM_NR | | | 95.01 133 | 94.59 139 | 96.26 135 | 98.89 60 | 90.68 187 | 97.24 188 | 97.73 152 | 91.80 191 | 92.93 234 | 96.62 232 | 89.13 100 | 99.14 166 | 89.21 282 | 97.78 160 | 98.97 111 |
|
| lupinMVS | | | 94.99 137 | 94.56 141 | 96.29 133 | 96.34 265 | 91.21 158 | 95.83 325 | 96.27 326 | 88.93 307 | 96.22 119 | 96.88 211 | 86.20 164 | 98.85 205 | 95.27 121 | 99.05 104 | 98.82 146 |
|
| Effi-MVS+ | | | 94.93 138 | 94.45 149 | 96.36 127 | 96.61 232 | 91.47 147 | 96.41 278 | 97.41 217 | 91.02 231 | 94.50 183 | 95.92 266 | 87.53 136 | 98.78 215 | 93.89 170 | 96.81 197 | 98.84 145 |
|
| IS-MVSNet | | | 94.90 139 | 94.52 145 | 96.05 148 | 97.67 147 | 90.56 189 | 98.44 26 | 96.22 329 | 93.21 127 | 93.99 199 | 97.74 142 | 85.55 181 | 98.45 269 | 89.98 258 | 97.86 157 | 99.14 88 |
|
| LuminaMVS | | | 94.89 140 | 94.35 153 | 96.53 105 | 95.48 314 | 92.80 91 | 96.88 227 | 96.18 333 | 92.85 152 | 95.92 132 | 96.87 213 | 81.44 269 | 98.83 208 | 96.43 77 | 97.10 187 | 97.94 235 |
|
| MVS_Test | | | 94.89 140 | 94.62 138 | 95.68 185 | 96.83 209 | 89.55 235 | 96.70 252 | 97.17 246 | 91.17 223 | 95.60 146 | 96.11 261 | 87.87 126 | 98.76 223 | 93.01 195 | 97.17 185 | 98.72 159 |
|
| viewdifsd2359ckpt13 | | | 94.87 142 | 94.52 145 | 95.90 160 | 96.88 202 | 90.19 206 | 96.92 221 | 97.36 225 | 91.26 216 | 94.65 177 | 97.46 168 | 85.79 173 | 98.64 250 | 93.64 176 | 96.76 199 | 98.88 138 |
|
| PVSNet_Blended | | | 94.87 142 | 94.56 141 | 95.81 169 | 98.27 96 | 89.46 241 | 95.47 348 | 98.36 39 | 88.84 310 | 94.36 186 | 96.09 262 | 88.02 121 | 99.58 98 | 93.44 181 | 98.18 145 | 98.40 191 |
|
| jason | | | 94.84 144 | 94.39 151 | 96.18 141 | 95.52 312 | 90.93 175 | 96.09 309 | 96.52 310 | 89.28 292 | 96.01 129 | 97.32 178 | 84.70 198 | 98.77 219 | 95.15 125 | 98.91 113 | 98.85 142 |
| jason: jason. |
| API-MVS | | | 94.84 144 | 94.49 147 | 95.90 160 | 97.90 134 | 92.00 123 | 97.80 104 | 97.48 196 | 89.19 295 | 94.81 173 | 96.71 218 | 88.84 105 | 99.17 159 | 88.91 289 | 98.76 118 | 96.53 294 |
|
| AstraMVS | | | 94.82 146 | 94.64 137 | 95.34 208 | 96.36 264 | 88.09 293 | 97.58 140 | 94.56 408 | 94.98 46 | 95.70 142 | 97.92 114 | 81.93 262 | 98.93 196 | 96.87 61 | 95.88 226 | 98.99 110 |
|
| viewdifsd2359ckpt09 | | | 94.81 147 | 94.37 152 | 96.12 144 | 96.91 199 | 90.75 184 | 96.94 218 | 97.31 232 | 90.51 257 | 94.31 188 | 97.38 175 | 85.70 175 | 98.71 239 | 93.54 177 | 96.75 200 | 98.90 130 |
|
| test_yl | | | 94.78 148 | 94.23 156 | 96.43 119 | 97.74 143 | 91.22 156 | 96.85 229 | 97.10 253 | 91.23 220 | 95.71 140 | 96.93 206 | 84.30 205 | 99.31 143 | 93.10 188 | 95.12 248 | 98.75 155 |
|
| DCV-MVSNet | | | 94.78 148 | 94.23 156 | 96.43 119 | 97.74 143 | 91.22 156 | 96.85 229 | 97.10 253 | 91.23 220 | 95.71 140 | 96.93 206 | 84.30 205 | 99.31 143 | 93.10 188 | 95.12 248 | 98.75 155 |
|
| viewdifsd2359ckpt07 | | | 94.76 150 | 94.68 136 | 95.01 223 | 96.76 225 | 87.41 308 | 96.38 284 | 97.43 214 | 92.65 159 | 94.52 181 | 97.75 139 | 85.55 181 | 98.81 211 | 94.36 160 | 96.69 204 | 98.82 146 |
|
| SSM_0404 | | | 94.73 151 | 94.31 155 | 95.98 157 | 97.05 186 | 90.90 177 | 97.01 211 | 97.29 233 | 91.24 217 | 94.17 195 | 97.60 159 | 85.03 191 | 98.76 223 | 92.14 206 | 97.30 178 | 98.29 204 |
|
| WTY-MVS | | | 94.71 152 | 94.02 161 | 96.79 90 | 97.71 145 | 92.05 120 | 96.59 267 | 97.35 227 | 90.61 250 | 94.64 178 | 96.93 206 | 86.41 160 | 99.39 134 | 91.20 232 | 94.71 260 | 98.94 121 |
|
| mamv4 | | | 94.66 153 | 96.10 87 | 90.37 413 | 98.01 123 | 73.41 464 | 96.82 234 | 97.78 146 | 89.95 270 | 94.52 181 | 97.43 172 | 92.91 30 | 99.09 174 | 98.28 27 | 99.16 94 | 98.60 167 |
|
| mvsmamba | | | 94.57 154 | 94.14 158 | 95.87 162 | 97.03 189 | 89.93 217 | 97.84 95 | 95.85 344 | 91.34 211 | 94.79 174 | 96.80 214 | 80.67 284 | 98.81 211 | 94.85 135 | 98.12 148 | 98.85 142 |
|
| SSM_0407 | | | 94.54 155 | 94.12 160 | 95.80 170 | 96.79 214 | 90.38 198 | 96.79 240 | 97.29 233 | 91.24 217 | 93.68 206 | 97.60 159 | 85.03 191 | 98.67 246 | 92.14 206 | 96.51 210 | 98.35 197 |
|
| RRT-MVS | | | 94.51 156 | 94.35 153 | 94.98 227 | 96.40 259 | 86.55 335 | 97.56 144 | 97.41 217 | 93.19 130 | 94.93 168 | 97.04 199 | 79.12 314 | 99.30 145 | 96.19 90 | 97.32 177 | 99.09 96 |
|
| sss | | | 94.51 156 | 93.80 165 | 96.64 94 | 97.07 181 | 91.97 124 | 96.32 292 | 98.06 101 | 88.94 306 | 94.50 183 | 96.78 215 | 84.60 199 | 99.27 147 | 91.90 213 | 96.02 222 | 98.68 163 |
|
| test_cas_vis1_n_1920 | | | 94.48 158 | 94.55 144 | 94.28 272 | 96.78 219 | 86.45 338 | 97.63 135 | 97.64 164 | 93.32 125 | 97.68 60 | 98.36 71 | 73.75 377 | 99.08 177 | 96.73 65 | 99.05 104 | 97.31 273 |
|
| CANet_DTU | | | 94.37 159 | 93.65 171 | 96.55 104 | 96.46 256 | 92.13 118 | 96.21 301 | 96.67 302 | 94.38 84 | 93.53 214 | 97.03 204 | 79.34 310 | 99.71 67 | 90.76 242 | 98.45 133 | 97.82 247 |
|
| AdaColmap |  | | 94.34 160 | 93.68 170 | 96.31 129 | 98.59 75 | 91.68 136 | 96.59 267 | 97.81 144 | 89.87 271 | 92.15 248 | 97.06 198 | 83.62 218 | 99.54 110 | 89.34 276 | 98.07 149 | 97.70 252 |
|
| viewmambaseed2359dif | | | 94.28 161 | 94.14 158 | 94.71 245 | 96.21 269 | 86.97 322 | 95.93 319 | 97.11 252 | 89.00 302 | 95.00 167 | 97.70 145 | 86.02 168 | 98.59 259 | 93.71 175 | 96.59 209 | 98.57 171 |
|
| CNLPA | | | 94.28 161 | 93.53 176 | 96.52 107 | 98.38 89 | 92.55 102 | 96.59 267 | 96.88 286 | 90.13 267 | 91.91 256 | 97.24 186 | 85.21 188 | 99.09 174 | 87.64 317 | 97.83 158 | 97.92 236 |
|
| MAR-MVS | | | 94.22 163 | 93.46 181 | 96.51 111 | 98.00 125 | 92.19 117 | 97.67 125 | 97.47 200 | 88.13 336 | 93.00 229 | 95.84 270 | 84.86 197 | 99.51 117 | 87.99 302 | 98.17 146 | 97.83 246 |
| 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 |
| PAPR | | | 94.18 164 | 93.42 186 | 96.48 114 | 97.64 151 | 91.42 150 | 95.55 343 | 97.71 158 | 88.99 303 | 92.34 244 | 95.82 272 | 89.19 98 | 99.11 169 | 86.14 344 | 97.38 172 | 98.90 130 |
|
| SDMVSNet | | | 94.17 165 | 93.61 172 | 95.86 165 | 98.09 116 | 91.37 151 | 97.35 176 | 98.20 69 | 93.18 132 | 91.79 260 | 97.28 182 | 79.13 313 | 98.93 196 | 94.61 152 | 92.84 292 | 97.28 274 |
|
| test_vis1_n_1920 | | | 94.17 165 | 94.58 140 | 92.91 343 | 97.42 166 | 82.02 414 | 97.83 98 | 97.85 137 | 94.68 67 | 98.10 48 | 98.49 58 | 70.15 402 | 99.32 141 | 97.91 30 | 98.82 114 | 97.40 268 |
|
| h-mvs33 | | | 94.15 167 | 93.52 178 | 96.04 149 | 97.81 139 | 90.22 205 | 97.62 137 | 97.58 175 | 95.19 36 | 96.74 89 | 97.45 169 | 83.67 216 | 99.61 90 | 95.85 102 | 79.73 433 | 98.29 204 |
|
| CHOSEN 1792x2688 | | | 94.15 167 | 93.51 179 | 96.06 147 | 98.27 96 | 89.38 244 | 95.18 366 | 98.48 34 | 85.60 389 | 93.76 205 | 97.11 195 | 83.15 227 | 99.61 90 | 91.33 228 | 98.72 119 | 99.19 83 |
|
| Vis-MVSNet (Re-imp) | | | 94.15 167 | 93.88 164 | 94.95 231 | 97.61 155 | 87.92 297 | 98.10 56 | 95.80 347 | 92.22 175 | 93.02 228 | 97.45 169 | 84.53 201 | 97.91 342 | 88.24 298 | 97.97 154 | 99.02 103 |
|
| CDS-MVSNet | | | 94.14 170 | 93.54 175 | 95.93 158 | 96.18 277 | 91.46 148 | 96.33 291 | 97.04 267 | 88.97 305 | 93.56 211 | 96.51 236 | 87.55 134 | 97.89 343 | 89.80 263 | 95.95 224 | 98.44 188 |
| Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
| PLC |  | 91.00 6 | 94.11 171 | 93.43 184 | 96.13 143 | 98.58 77 | 91.15 167 | 96.69 254 | 97.39 219 | 87.29 361 | 91.37 270 | 96.71 218 | 88.39 114 | 99.52 116 | 87.33 325 | 97.13 186 | 97.73 250 |
| Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
| FIs | | | 94.09 172 | 93.70 169 | 95.27 210 | 95.70 303 | 92.03 122 | 98.10 56 | 98.68 19 | 93.36 124 | 90.39 291 | 96.70 220 | 87.63 132 | 97.94 336 | 92.25 203 | 90.50 333 | 95.84 319 |
|
| PVSNet_BlendedMVS | | | 94.06 173 | 93.92 163 | 94.47 259 | 98.27 96 | 89.46 241 | 96.73 248 | 98.36 39 | 90.17 264 | 94.36 186 | 95.24 305 | 88.02 121 | 99.58 98 | 93.44 181 | 90.72 329 | 94.36 407 |
|
| nrg030 | | | 94.05 174 | 93.31 188 | 96.27 134 | 95.22 337 | 94.59 33 | 98.34 30 | 97.46 202 | 92.93 147 | 91.21 280 | 96.64 225 | 87.23 146 | 98.22 289 | 94.99 129 | 85.80 381 | 95.98 315 |
|
| UGNet | | | 94.04 175 | 93.28 189 | 96.31 129 | 96.85 206 | 91.19 161 | 97.88 90 | 97.68 159 | 94.40 82 | 93.00 229 | 96.18 252 | 73.39 379 | 99.61 90 | 91.72 219 | 98.46 132 | 98.13 216 |
| 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 |
| TAMVS | | | 94.01 176 | 93.46 181 | 95.64 186 | 96.16 279 | 90.45 193 | 96.71 251 | 96.89 285 | 89.27 293 | 93.46 218 | 96.92 209 | 87.29 144 | 97.94 336 | 88.70 294 | 95.74 230 | 98.53 174 |
|
| Elysia | | | 94.00 177 | 93.12 194 | 96.64 94 | 96.08 289 | 92.72 95 | 97.50 153 | 97.63 166 | 91.15 225 | 94.82 171 | 97.12 193 | 74.98 364 | 99.06 183 | 90.78 240 | 98.02 151 | 98.12 218 |
|
| StellarMVS | | | 94.00 177 | 93.12 194 | 96.64 94 | 96.08 289 | 92.72 95 | 97.50 153 | 97.63 166 | 91.15 225 | 94.82 171 | 97.12 193 | 74.98 364 | 99.06 183 | 90.78 240 | 98.02 151 | 98.12 218 |
|
| IMVS_0403 | | | 93.98 179 | 93.79 166 | 94.55 255 | 96.19 273 | 86.16 347 | 96.35 287 | 97.24 240 | 91.54 199 | 93.59 210 | 97.04 199 | 85.86 170 | 98.73 233 | 90.68 245 | 95.59 236 | 98.76 151 |
|
| 114514_t | | | 93.95 180 | 93.06 197 | 96.63 98 | 99.07 43 | 91.61 138 | 97.46 164 | 97.96 122 | 77.99 455 | 93.00 229 | 97.57 162 | 86.14 166 | 99.33 139 | 89.22 281 | 99.15 95 | 98.94 121 |
|
| IMVS_0407 | | | 93.94 181 | 93.75 167 | 94.49 258 | 96.19 273 | 86.16 347 | 96.35 287 | 97.24 240 | 91.54 199 | 93.50 215 | 97.04 199 | 85.64 179 | 98.54 262 | 90.68 245 | 95.59 236 | 98.76 151 |
|
| FC-MVSNet-test | | | 93.94 181 | 93.57 173 | 95.04 221 | 95.48 314 | 91.45 149 | 98.12 55 | 98.71 13 | 93.37 122 | 90.23 294 | 96.70 220 | 87.66 129 | 97.85 345 | 91.49 225 | 90.39 334 | 95.83 320 |
|
| mvsany_test1 | | | 93.93 183 | 93.98 162 | 93.78 304 | 94.94 354 | 86.80 325 | 94.62 380 | 92.55 448 | 88.77 316 | 96.85 84 | 98.49 58 | 88.98 101 | 98.08 307 | 95.03 127 | 95.62 235 | 96.46 299 |
|
| GeoE | | | 93.89 184 | 93.28 189 | 95.72 183 | 96.96 197 | 89.75 223 | 98.24 43 | 96.92 281 | 89.47 286 | 92.12 250 | 97.21 188 | 84.42 203 | 98.39 277 | 87.71 311 | 96.50 213 | 99.01 106 |
|
| HY-MVS | | 89.66 9 | 93.87 185 | 92.95 202 | 96.63 98 | 97.10 180 | 92.49 104 | 95.64 340 | 96.64 303 | 89.05 300 | 93.00 229 | 95.79 276 | 85.77 174 | 99.45 128 | 89.16 285 | 94.35 262 | 97.96 233 |
|
| XVG-OURS-SEG-HR | | | 93.86 186 | 93.55 174 | 94.81 237 | 97.06 184 | 88.53 277 | 95.28 357 | 97.45 207 | 91.68 196 | 94.08 198 | 97.68 148 | 82.41 250 | 98.90 201 | 93.84 172 | 92.47 298 | 96.98 282 |
|
| VDD-MVS | | | 93.82 187 | 93.08 196 | 96.02 151 | 97.88 135 | 89.96 216 | 97.72 118 | 95.85 344 | 92.43 167 | 95.86 134 | 98.44 64 | 68.42 419 | 99.39 134 | 96.31 79 | 94.85 252 | 98.71 161 |
|
| mvs_anonymous | | | 93.82 187 | 93.74 168 | 94.06 282 | 96.44 257 | 85.41 364 | 95.81 327 | 97.05 265 | 89.85 274 | 90.09 304 | 96.36 244 | 87.44 141 | 97.75 359 | 93.97 166 | 96.69 204 | 99.02 103 |
|
| HQP_MVS | | | 93.78 189 | 93.43 184 | 94.82 235 | 96.21 269 | 89.99 211 | 97.74 113 | 97.51 191 | 94.85 53 | 91.34 271 | 96.64 225 | 81.32 271 | 98.60 255 | 93.02 193 | 92.23 301 | 95.86 316 |
|
| PS-MVSNAJss | | | 93.74 190 | 93.51 179 | 94.44 261 | 93.91 392 | 89.28 251 | 97.75 110 | 97.56 184 | 92.50 164 | 89.94 307 | 96.54 235 | 88.65 109 | 98.18 294 | 93.83 173 | 90.90 327 | 95.86 316 |
|
| XVG-OURS | | | 93.72 191 | 93.35 187 | 94.80 240 | 97.07 181 | 88.61 272 | 94.79 377 | 97.46 202 | 91.97 189 | 93.99 199 | 97.86 124 | 81.74 265 | 98.88 202 | 92.64 199 | 92.67 297 | 96.92 286 |
|
| mamba_0408 | | | 93.70 192 | 92.99 198 | 95.83 167 | 96.79 214 | 90.38 198 | 88.69 467 | 97.07 259 | 90.96 233 | 93.68 206 | 97.31 180 | 84.97 194 | 98.76 223 | 90.95 236 | 96.51 210 | 98.35 197 |
|
| HyFIR lowres test | | | 93.66 193 | 92.92 203 | 95.87 162 | 98.24 100 | 89.88 218 | 94.58 382 | 98.49 32 | 85.06 399 | 93.78 204 | 95.78 277 | 82.86 237 | 98.67 246 | 91.77 218 | 95.71 232 | 99.07 100 |
|
| LFMVS | | | 93.60 194 | 92.63 217 | 96.52 107 | 98.13 115 | 91.27 155 | 97.94 81 | 93.39 436 | 90.57 254 | 96.29 116 | 98.31 81 | 69.00 412 | 99.16 161 | 94.18 163 | 95.87 227 | 99.12 92 |
|
| icg_test_0407_2 | | | 93.58 195 | 93.46 181 | 93.94 294 | 96.19 273 | 86.16 347 | 93.73 417 | 97.24 240 | 91.54 199 | 93.50 215 | 97.04 199 | 85.64 179 | 96.91 412 | 90.68 245 | 95.59 236 | 98.76 151 |
|
| F-COLMAP | | | 93.58 195 | 92.98 201 | 95.37 206 | 98.40 86 | 88.98 263 | 97.18 197 | 97.29 233 | 87.75 350 | 90.49 289 | 97.10 196 | 85.21 188 | 99.50 120 | 86.70 335 | 96.72 203 | 97.63 254 |
|
| ab-mvs | | | 93.57 197 | 92.55 221 | 96.64 94 | 97.28 170 | 91.96 126 | 95.40 350 | 97.45 207 | 89.81 276 | 93.22 226 | 96.28 248 | 79.62 307 | 99.46 126 | 90.74 243 | 93.11 289 | 98.50 178 |
|
| LS3D | | | 93.57 197 | 92.61 219 | 96.47 115 | 97.59 157 | 91.61 138 | 97.67 125 | 97.72 154 | 85.17 397 | 90.29 293 | 98.34 75 | 84.60 199 | 99.73 61 | 83.85 380 | 98.27 141 | 98.06 228 |
|
| FA-MVS(test-final) | | | 93.52 199 | 92.92 203 | 95.31 209 | 96.77 221 | 88.54 276 | 94.82 376 | 96.21 331 | 89.61 281 | 94.20 192 | 95.25 304 | 83.24 223 | 99.14 166 | 90.01 257 | 96.16 221 | 98.25 206 |
|
| SSM_04072 | | | 93.51 200 | 92.99 198 | 95.05 219 | 96.79 214 | 90.38 198 | 88.69 467 | 97.07 259 | 90.96 233 | 93.68 206 | 97.31 180 | 84.97 194 | 96.42 423 | 90.95 236 | 96.51 210 | 98.35 197 |
|
| viewdifsd2359ckpt11 | | | 93.46 201 | 93.22 192 | 94.17 275 | 96.11 286 | 85.42 362 | 96.43 274 | 97.07 259 | 92.91 148 | 94.20 192 | 98.00 105 | 80.82 282 | 98.73 233 | 94.42 156 | 89.04 348 | 98.34 201 |
|
| viewmsd2359difaftdt | | | 93.46 201 | 93.23 191 | 94.17 275 | 96.12 284 | 85.42 362 | 96.43 274 | 97.08 256 | 92.91 148 | 94.21 191 | 98.00 105 | 80.82 282 | 98.74 231 | 94.41 157 | 89.05 346 | 98.34 201 |
|
| Fast-Effi-MVS+ | | | 93.46 201 | 92.75 211 | 95.59 190 | 96.77 221 | 90.03 208 | 96.81 238 | 97.13 248 | 88.19 331 | 91.30 274 | 94.27 357 | 86.21 163 | 98.63 252 | 87.66 316 | 96.46 216 | 98.12 218 |
|
| hse-mvs2 | | | 93.45 204 | 92.99 198 | 94.81 237 | 97.02 191 | 88.59 273 | 96.69 254 | 96.47 313 | 95.19 36 | 96.74 89 | 96.16 255 | 83.67 216 | 98.48 268 | 95.85 102 | 79.13 437 | 97.35 271 |
|
| QAPM | | | 93.45 204 | 92.27 231 | 96.98 85 | 96.77 221 | 92.62 98 | 98.39 29 | 98.12 86 | 84.50 407 | 88.27 359 | 97.77 138 | 82.39 251 | 99.81 35 | 85.40 357 | 98.81 115 | 98.51 177 |
|
| UniMVSNet_NR-MVSNet | | | 93.37 206 | 92.67 215 | 95.47 203 | 95.34 326 | 92.83 89 | 97.17 198 | 98.58 28 | 92.98 145 | 90.13 299 | 95.80 273 | 88.37 116 | 97.85 345 | 91.71 220 | 83.93 410 | 95.73 330 |
|
| 1112_ss | | | 93.37 206 | 92.42 228 | 96.21 139 | 97.05 186 | 90.99 170 | 96.31 293 | 96.72 295 | 86.87 369 | 89.83 311 | 96.69 222 | 86.51 156 | 99.14 166 | 88.12 299 | 93.67 283 | 98.50 178 |
|
| UniMVSNet (Re) | | | 93.31 208 | 92.55 221 | 95.61 189 | 95.39 320 | 93.34 71 | 97.39 172 | 98.71 13 | 93.14 135 | 90.10 303 | 94.83 322 | 87.71 128 | 98.03 318 | 91.67 223 | 83.99 409 | 95.46 339 |
|
| OPM-MVS | | | 93.28 209 | 92.76 209 | 94.82 235 | 94.63 370 | 90.77 182 | 96.65 258 | 97.18 244 | 93.72 103 | 91.68 264 | 97.26 185 | 79.33 311 | 98.63 252 | 92.13 209 | 92.28 300 | 95.07 368 |
| Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS). |
| VPA-MVSNet | | | 93.24 210 | 92.48 226 | 95.51 197 | 95.70 303 | 92.39 106 | 97.86 91 | 98.66 22 | 92.30 172 | 92.09 252 | 95.37 297 | 80.49 289 | 98.40 272 | 93.95 167 | 85.86 380 | 95.75 328 |
|
| test_fmvs1 | | | 93.21 211 | 93.53 176 | 92.25 366 | 96.55 243 | 81.20 421 | 97.40 171 | 96.96 274 | 90.68 243 | 96.80 85 | 98.04 100 | 69.25 410 | 98.40 272 | 97.58 41 | 98.50 128 | 97.16 279 |
|
| MVSTER | | | 93.20 212 | 92.81 208 | 94.37 264 | 96.56 241 | 89.59 231 | 97.06 205 | 97.12 249 | 91.24 217 | 91.30 274 | 95.96 264 | 82.02 258 | 98.05 314 | 93.48 180 | 90.55 331 | 95.47 338 |
|
| test1111 | | | 93.19 213 | 92.82 207 | 94.30 271 | 97.58 161 | 84.56 381 | 98.21 47 | 89.02 467 | 93.53 113 | 94.58 179 | 98.21 88 | 72.69 381 | 99.05 186 | 93.06 191 | 98.48 131 | 99.28 77 |
|
| ECVR-MVS |  | | 93.19 213 | 92.73 213 | 94.57 254 | 97.66 149 | 85.41 364 | 98.21 47 | 88.23 469 | 93.43 120 | 94.70 176 | 98.21 88 | 72.57 382 | 99.07 181 | 93.05 192 | 98.49 129 | 99.25 80 |
|
| HQP-MVS | | | 93.19 213 | 92.74 212 | 94.54 256 | 95.86 295 | 89.33 247 | 96.65 258 | 97.39 219 | 93.55 109 | 90.14 295 | 95.87 268 | 80.95 276 | 98.50 265 | 92.13 209 | 92.10 306 | 95.78 324 |
|
| CHOSEN 280x420 | | | 93.12 216 | 92.72 214 | 94.34 267 | 96.71 227 | 87.27 312 | 90.29 457 | 97.72 154 | 86.61 373 | 91.34 271 | 95.29 299 | 84.29 207 | 98.41 271 | 93.25 185 | 98.94 111 | 97.35 271 |
|
| sd_testset | | | 93.10 217 | 92.45 227 | 95.05 219 | 98.09 116 | 89.21 253 | 96.89 225 | 97.64 164 | 93.18 132 | 91.79 260 | 97.28 182 | 75.35 361 | 98.65 249 | 88.99 287 | 92.84 292 | 97.28 274 |
|
| Effi-MVS+-dtu | | | 93.08 218 | 93.21 193 | 92.68 354 | 96.02 292 | 83.25 397 | 97.14 201 | 96.72 295 | 93.85 100 | 91.20 281 | 93.44 396 | 83.08 229 | 98.30 284 | 91.69 222 | 95.73 231 | 96.50 296 |
|
| test_djsdf | | | 93.07 219 | 92.76 209 | 94.00 286 | 93.49 408 | 88.70 269 | 98.22 45 | 97.57 178 | 91.42 208 | 90.08 305 | 95.55 290 | 82.85 238 | 97.92 339 | 94.07 164 | 91.58 313 | 95.40 346 |
|
| VDDNet | | | 93.05 220 | 92.07 235 | 96.02 151 | 96.84 207 | 90.39 197 | 98.08 58 | 95.85 344 | 86.22 381 | 95.79 137 | 98.46 62 | 67.59 422 | 99.19 154 | 94.92 132 | 94.85 252 | 98.47 183 |
|
| thisisatest0530 | | | 93.03 221 | 92.21 233 | 95.49 200 | 97.07 181 | 89.11 258 | 97.49 161 | 92.19 450 | 90.16 265 | 94.09 197 | 96.41 241 | 76.43 352 | 99.05 186 | 90.38 252 | 95.68 233 | 98.31 203 |
|
| EI-MVSNet | | | 93.03 221 | 92.88 205 | 93.48 322 | 95.77 301 | 86.98 321 | 96.44 272 | 97.12 249 | 90.66 246 | 91.30 274 | 97.64 155 | 86.56 154 | 98.05 314 | 89.91 260 | 90.55 331 | 95.41 343 |
|
| CLD-MVS | | | 92.98 223 | 92.53 223 | 94.32 268 | 96.12 284 | 89.20 254 | 95.28 357 | 97.47 200 | 92.66 158 | 89.90 308 | 95.62 286 | 80.58 287 | 98.40 272 | 92.73 198 | 92.40 299 | 95.38 348 |
| Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
| tttt0517 | | | 92.96 224 | 92.33 230 | 94.87 234 | 97.11 179 | 87.16 318 | 97.97 77 | 92.09 451 | 90.63 248 | 93.88 203 | 97.01 205 | 76.50 349 | 99.06 183 | 90.29 255 | 95.45 242 | 98.38 193 |
|
| ACMM | | 89.79 8 | 92.96 224 | 92.50 225 | 94.35 265 | 96.30 267 | 88.71 268 | 97.58 140 | 97.36 225 | 91.40 210 | 90.53 288 | 96.65 224 | 79.77 303 | 98.75 229 | 91.24 231 | 91.64 311 | 95.59 334 |
| Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
| LPG-MVS_test | | | 92.94 226 | 92.56 220 | 94.10 280 | 96.16 279 | 88.26 285 | 97.65 129 | 97.46 202 | 91.29 212 | 90.12 301 | 97.16 190 | 79.05 316 | 98.73 233 | 92.25 203 | 91.89 309 | 95.31 353 |
|
| BH-untuned | | | 92.94 226 | 92.62 218 | 93.92 298 | 97.22 172 | 86.16 347 | 96.40 282 | 96.25 328 | 90.06 268 | 89.79 312 | 96.17 254 | 83.19 225 | 98.35 280 | 87.19 328 | 97.27 180 | 97.24 276 |
|
| DU-MVS | | | 92.90 228 | 92.04 237 | 95.49 200 | 94.95 352 | 92.83 89 | 97.16 199 | 98.24 63 | 93.02 139 | 90.13 299 | 95.71 280 | 83.47 219 | 97.85 345 | 91.71 220 | 83.93 410 | 95.78 324 |
|
| PatchMatch-RL | | | 92.90 228 | 92.02 239 | 95.56 191 | 98.19 109 | 90.80 180 | 95.27 359 | 97.18 244 | 87.96 338 | 91.86 259 | 95.68 283 | 80.44 290 | 98.99 191 | 84.01 375 | 97.54 165 | 96.89 287 |
|
| VortexMVS | | | 92.88 230 | 92.64 216 | 93.58 317 | 96.58 236 | 87.53 307 | 96.93 220 | 97.28 236 | 92.78 156 | 89.75 313 | 94.99 312 | 82.73 241 | 97.76 357 | 94.60 153 | 88.16 357 | 95.46 339 |
|
| PMMVS | | | 92.86 231 | 92.34 229 | 94.42 263 | 94.92 355 | 86.73 328 | 94.53 384 | 96.38 319 | 84.78 404 | 94.27 189 | 95.12 310 | 83.13 228 | 98.40 272 | 91.47 226 | 96.49 214 | 98.12 218 |
|
| OpenMVS |  | 89.19 12 | 92.86 231 | 91.68 252 | 96.40 122 | 95.34 326 | 92.73 94 | 98.27 37 | 98.12 86 | 84.86 402 | 85.78 405 | 97.75 139 | 78.89 323 | 99.74 59 | 87.50 322 | 98.65 122 | 96.73 291 |
|
| Test_1112_low_res | | | 92.84 233 | 91.84 246 | 95.85 166 | 97.04 188 | 89.97 215 | 95.53 345 | 96.64 303 | 85.38 392 | 89.65 318 | 95.18 306 | 85.86 170 | 99.10 171 | 87.70 312 | 93.58 288 | 98.49 180 |
|
| baseline1 | | | 92.82 234 | 91.90 244 | 95.55 193 | 97.20 174 | 90.77 182 | 97.19 196 | 94.58 407 | 92.20 178 | 92.36 241 | 96.34 245 | 84.16 209 | 98.21 290 | 89.20 283 | 83.90 413 | 97.68 253 |
|
| 1314 | | | 92.81 235 | 92.03 238 | 95.14 215 | 95.33 329 | 89.52 238 | 96.04 312 | 97.44 211 | 87.72 351 | 86.25 400 | 95.33 298 | 83.84 213 | 98.79 214 | 89.26 279 | 97.05 190 | 97.11 280 |
|
| DP-MVS | | | 92.76 236 | 91.51 260 | 96.52 107 | 98.77 62 | 90.99 170 | 97.38 174 | 96.08 336 | 82.38 430 | 89.29 330 | 97.87 122 | 83.77 214 | 99.69 73 | 81.37 404 | 96.69 204 | 98.89 136 |
|
| test_fmvs1_n | | | 92.73 237 | 92.88 205 | 92.29 363 | 96.08 289 | 81.05 422 | 97.98 71 | 97.08 256 | 90.72 241 | 96.79 87 | 98.18 91 | 63.07 447 | 98.45 269 | 97.62 40 | 98.42 135 | 97.36 269 |
|
| BH-RMVSNet | | | 92.72 238 | 91.97 241 | 94.97 229 | 97.16 176 | 87.99 295 | 96.15 307 | 95.60 358 | 90.62 249 | 91.87 258 | 97.15 192 | 78.41 329 | 98.57 260 | 83.16 382 | 97.60 164 | 98.36 195 |
|
| ACMP | | 89.59 10 | 92.62 239 | 92.14 234 | 94.05 283 | 96.40 259 | 88.20 288 | 97.36 175 | 97.25 239 | 91.52 203 | 88.30 357 | 96.64 225 | 78.46 328 | 98.72 238 | 91.86 216 | 91.48 315 | 95.23 360 |
| Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
| LCM-MVSNet-Re | | | 92.50 240 | 92.52 224 | 92.44 356 | 96.82 211 | 81.89 415 | 96.92 221 | 93.71 433 | 92.41 168 | 84.30 418 | 94.60 334 | 85.08 190 | 97.03 406 | 91.51 224 | 97.36 173 | 98.40 191 |
|
| TranMVSNet+NR-MVSNet | | | 92.50 240 | 91.63 253 | 95.14 215 | 94.76 363 | 92.07 119 | 97.53 150 | 98.11 89 | 92.90 151 | 89.56 321 | 96.12 257 | 83.16 226 | 97.60 373 | 89.30 277 | 83.20 419 | 95.75 328 |
|
| thres600view7 | | | 92.49 242 | 91.60 254 | 95.18 213 | 97.91 133 | 89.47 239 | 97.65 129 | 94.66 404 | 92.18 182 | 93.33 221 | 94.91 317 | 78.06 336 | 99.10 171 | 81.61 397 | 94.06 277 | 96.98 282 |
|
| IMVS_0404 | | | 92.44 243 | 91.92 243 | 94.00 286 | 96.19 273 | 86.16 347 | 93.84 414 | 97.24 240 | 91.54 199 | 88.17 363 | 97.04 199 | 76.96 346 | 97.09 403 | 90.68 245 | 95.59 236 | 98.76 151 |
|
| thres100view900 | | | 92.43 244 | 91.58 255 | 94.98 227 | 97.92 132 | 89.37 245 | 97.71 120 | 94.66 404 | 92.20 178 | 93.31 222 | 94.90 318 | 78.06 336 | 99.08 177 | 81.40 401 | 94.08 273 | 96.48 297 |
|
| jajsoiax | | | 92.42 245 | 91.89 245 | 94.03 285 | 93.33 416 | 88.50 278 | 97.73 115 | 97.53 189 | 92.00 188 | 88.85 343 | 96.50 237 | 75.62 359 | 98.11 301 | 93.88 171 | 91.56 314 | 95.48 336 |
|
| thres400 | | | 92.42 245 | 91.52 258 | 95.12 217 | 97.85 136 | 89.29 249 | 97.41 167 | 94.88 396 | 92.19 180 | 93.27 224 | 94.46 344 | 78.17 332 | 99.08 177 | 81.40 401 | 94.08 273 | 96.98 282 |
|
| tfpn200view9 | | | 92.38 247 | 91.52 258 | 94.95 231 | 97.85 136 | 89.29 249 | 97.41 167 | 94.88 396 | 92.19 180 | 93.27 224 | 94.46 344 | 78.17 332 | 99.08 177 | 81.40 401 | 94.08 273 | 96.48 297 |
|
| test_vis1_n | | | 92.37 248 | 92.26 232 | 92.72 351 | 94.75 364 | 82.64 404 | 98.02 65 | 96.80 292 | 91.18 222 | 97.77 59 | 97.93 111 | 58.02 457 | 98.29 285 | 97.63 38 | 98.21 143 | 97.23 277 |
|
| WR-MVS | | | 92.34 249 | 91.53 257 | 94.77 242 | 95.13 345 | 90.83 179 | 96.40 282 | 97.98 120 | 91.88 190 | 89.29 330 | 95.54 291 | 82.50 247 | 97.80 352 | 89.79 264 | 85.27 389 | 95.69 331 |
|
| NR-MVSNet | | | 92.34 249 | 91.27 268 | 95.53 194 | 94.95 352 | 93.05 81 | 97.39 172 | 98.07 98 | 92.65 159 | 84.46 416 | 95.71 280 | 85.00 193 | 97.77 356 | 89.71 265 | 83.52 416 | 95.78 324 |
|
| mvs_tets | | | 92.31 251 | 91.76 248 | 93.94 294 | 93.41 413 | 88.29 283 | 97.63 135 | 97.53 189 | 92.04 186 | 88.76 346 | 96.45 239 | 74.62 369 | 98.09 306 | 93.91 169 | 91.48 315 | 95.45 341 |
|
| TAPA-MVS | | 90.10 7 | 92.30 252 | 91.22 271 | 95.56 191 | 98.33 91 | 89.60 230 | 96.79 240 | 97.65 162 | 81.83 434 | 91.52 266 | 97.23 187 | 87.94 123 | 98.91 200 | 71.31 458 | 98.37 136 | 98.17 214 |
| Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
| thisisatest0515 | | | 92.29 253 | 91.30 266 | 95.25 211 | 96.60 233 | 88.90 265 | 94.36 393 | 92.32 449 | 87.92 339 | 93.43 219 | 94.57 335 | 77.28 343 | 99.00 190 | 89.42 274 | 95.86 228 | 97.86 243 |
|
| Fast-Effi-MVS+-dtu | | | 92.29 253 | 91.99 240 | 93.21 333 | 95.27 333 | 85.52 360 | 97.03 206 | 96.63 306 | 92.09 183 | 89.11 337 | 95.14 308 | 80.33 293 | 98.08 307 | 87.54 320 | 94.74 258 | 96.03 314 |
|
| IterMVS-LS | | | 92.29 253 | 91.94 242 | 93.34 327 | 96.25 268 | 86.97 322 | 96.57 270 | 97.05 265 | 90.67 244 | 89.50 324 | 94.80 324 | 86.59 153 | 97.64 368 | 89.91 260 | 86.11 379 | 95.40 346 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
| PVSNet | | 86.66 18 | 92.24 256 | 91.74 251 | 93.73 305 | 97.77 141 | 83.69 394 | 92.88 437 | 96.72 295 | 87.91 340 | 93.00 229 | 94.86 320 | 78.51 327 | 99.05 186 | 86.53 336 | 97.45 171 | 98.47 183 |
|
| VPNet | | | 92.23 257 | 91.31 265 | 94.99 225 | 95.56 310 | 90.96 172 | 97.22 194 | 97.86 136 | 92.96 146 | 90.96 282 | 96.62 232 | 75.06 362 | 98.20 291 | 91.90 213 | 83.65 415 | 95.80 322 |
|
| thres200 | | | 92.23 257 | 91.39 261 | 94.75 244 | 97.61 155 | 89.03 260 | 96.60 266 | 95.09 385 | 92.08 184 | 93.28 223 | 94.00 372 | 78.39 330 | 99.04 189 | 81.26 407 | 94.18 269 | 96.19 304 |
|
| anonymousdsp | | | 92.16 259 | 91.55 256 | 93.97 290 | 92.58 431 | 89.55 235 | 97.51 152 | 97.42 216 | 89.42 289 | 88.40 353 | 94.84 321 | 80.66 285 | 97.88 344 | 91.87 215 | 91.28 319 | 94.48 402 |
|
| XXY-MVS | | | 92.16 259 | 91.23 270 | 94.95 231 | 94.75 364 | 90.94 174 | 97.47 162 | 97.43 214 | 89.14 296 | 88.90 339 | 96.43 240 | 79.71 304 | 98.24 287 | 89.56 270 | 87.68 362 | 95.67 332 |
|
| BH-w/o | | | 92.14 261 | 91.75 249 | 93.31 328 | 96.99 194 | 85.73 357 | 95.67 335 | 95.69 353 | 88.73 317 | 89.26 332 | 94.82 323 | 82.97 234 | 98.07 311 | 85.26 360 | 96.32 220 | 96.13 310 |
|
| testing3-2 | | | 92.10 262 | 92.05 236 | 92.27 364 | 97.71 145 | 79.56 441 | 97.42 166 | 94.41 414 | 93.53 113 | 93.22 226 | 95.49 293 | 69.16 411 | 99.11 169 | 93.25 185 | 94.22 267 | 98.13 216 |
|
| Anonymous202405211 | | | 92.07 263 | 90.83 287 | 95.76 177 | 98.19 109 | 88.75 267 | 97.58 140 | 95.00 388 | 86.00 384 | 93.64 209 | 97.45 169 | 66.24 434 | 99.53 112 | 90.68 245 | 92.71 295 | 99.01 106 |
|
| FE-MVS | | | 92.05 264 | 91.05 276 | 95.08 218 | 96.83 209 | 87.93 296 | 93.91 411 | 95.70 351 | 86.30 378 | 94.15 196 | 94.97 313 | 76.59 348 | 99.21 152 | 84.10 373 | 96.86 195 | 98.09 225 |
|
| WR-MVS_H | | | 92.00 265 | 91.35 262 | 93.95 292 | 95.09 347 | 89.47 239 | 98.04 63 | 98.68 19 | 91.46 206 | 88.34 355 | 94.68 329 | 85.86 170 | 97.56 375 | 85.77 352 | 84.24 407 | 94.82 386 |
|
| Anonymous20240529 | | | 91.98 266 | 90.73 293 | 95.73 182 | 98.14 113 | 89.40 243 | 97.99 68 | 97.72 154 | 79.63 448 | 93.54 213 | 97.41 174 | 69.94 404 | 99.56 106 | 91.04 235 | 91.11 322 | 98.22 208 |
|
| MonoMVSNet | | | 91.92 267 | 91.77 247 | 92.37 358 | 92.94 422 | 83.11 400 | 97.09 204 | 95.55 362 | 92.91 148 | 90.85 284 | 94.55 336 | 81.27 273 | 96.52 421 | 93.01 195 | 87.76 361 | 97.47 265 |
|
| PatchmatchNet |  | | 91.91 268 | 91.35 262 | 93.59 316 | 95.38 321 | 84.11 387 | 93.15 432 | 95.39 368 | 89.54 283 | 92.10 251 | 93.68 385 | 82.82 239 | 98.13 297 | 84.81 364 | 95.32 244 | 98.52 175 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
| testing91 | | | 91.90 269 | 91.02 277 | 94.53 257 | 96.54 244 | 86.55 335 | 95.86 323 | 95.64 357 | 91.77 193 | 91.89 257 | 93.47 395 | 69.94 404 | 98.86 203 | 90.23 256 | 93.86 280 | 98.18 211 |
|
| CP-MVSNet | | | 91.89 270 | 91.24 269 | 93.82 301 | 95.05 348 | 88.57 274 | 97.82 100 | 98.19 74 | 91.70 195 | 88.21 361 | 95.76 278 | 81.96 259 | 97.52 383 | 87.86 304 | 84.65 398 | 95.37 349 |
|
| SCA | | | 91.84 271 | 91.18 273 | 93.83 300 | 95.59 308 | 84.95 377 | 94.72 378 | 95.58 360 | 90.82 236 | 92.25 246 | 93.69 383 | 75.80 356 | 98.10 302 | 86.20 342 | 95.98 223 | 98.45 185 |
|
| FMVSNet3 | | | 91.78 272 | 90.69 296 | 95.03 222 | 96.53 246 | 92.27 112 | 97.02 208 | 96.93 277 | 89.79 277 | 89.35 327 | 94.65 332 | 77.01 344 | 97.47 386 | 86.12 345 | 88.82 349 | 95.35 350 |
|
| AUN-MVS | | | 91.76 273 | 90.75 291 | 94.81 237 | 97.00 193 | 88.57 274 | 96.65 258 | 96.49 312 | 89.63 280 | 92.15 248 | 96.12 257 | 78.66 325 | 98.50 265 | 90.83 238 | 79.18 436 | 97.36 269 |
|
| X-MVStestdata | | | 91.71 274 | 89.67 341 | 97.81 32 | 99.38 17 | 94.03 54 | 98.59 17 | 98.20 69 | 94.85 53 | 96.59 99 | 32.69 484 | 91.70 56 | 99.80 40 | 95.66 108 | 99.40 61 | 99.62 27 |
|
| MVS | | | 91.71 274 | 90.44 304 | 95.51 197 | 95.20 339 | 91.59 140 | 96.04 312 | 97.45 207 | 73.44 465 | 87.36 379 | 95.60 287 | 85.42 183 | 99.10 171 | 85.97 349 | 97.46 167 | 95.83 320 |
|
| EPNet_dtu | | | 91.71 274 | 91.28 267 | 92.99 340 | 93.76 397 | 83.71 393 | 96.69 254 | 95.28 375 | 93.15 134 | 87.02 388 | 95.95 265 | 83.37 222 | 97.38 394 | 79.46 420 | 96.84 196 | 97.88 239 |
| Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
| testing11 | | | 91.68 277 | 90.75 291 | 94.47 259 | 96.53 246 | 86.56 334 | 95.76 331 | 94.51 411 | 91.10 229 | 91.24 279 | 93.59 390 | 68.59 416 | 98.86 203 | 91.10 233 | 94.29 265 | 98.00 232 |
|
| FE-MVSNET3 | | | 91.65 278 | 90.67 297 | 94.60 248 | 93.65 403 | 90.95 173 | 94.86 375 | 97.12 249 | 89.69 279 | 89.21 334 | 93.62 388 | 81.17 274 | 97.67 364 | 87.54 320 | 89.14 345 | 95.17 366 |
|
| baseline2 | | | 91.63 279 | 90.86 283 | 93.94 294 | 94.33 381 | 86.32 340 | 95.92 320 | 91.64 455 | 89.37 290 | 86.94 391 | 94.69 328 | 81.62 267 | 98.69 241 | 88.64 295 | 94.57 261 | 96.81 289 |
|
| testing99 | | | 91.62 280 | 90.72 294 | 94.32 268 | 96.48 253 | 86.11 352 | 95.81 327 | 94.76 401 | 91.55 198 | 91.75 262 | 93.44 396 | 68.55 417 | 98.82 209 | 90.43 250 | 93.69 282 | 98.04 229 |
|
| test2506 | | | 91.60 281 | 90.78 288 | 94.04 284 | 97.66 149 | 83.81 390 | 98.27 37 | 75.53 485 | 93.43 120 | 95.23 159 | 98.21 88 | 67.21 425 | 99.07 181 | 93.01 195 | 98.49 129 | 99.25 80 |
|
| miper_ehance_all_eth | | | 91.59 282 | 91.13 274 | 92.97 341 | 95.55 311 | 86.57 333 | 94.47 387 | 96.88 286 | 87.77 348 | 88.88 341 | 94.01 371 | 86.22 162 | 97.54 379 | 89.49 271 | 86.93 370 | 94.79 391 |
|
| v2v482 | | | 91.59 282 | 90.85 285 | 93.80 302 | 93.87 394 | 88.17 290 | 96.94 218 | 96.88 286 | 89.54 283 | 89.53 322 | 94.90 318 | 81.70 266 | 98.02 319 | 89.25 280 | 85.04 395 | 95.20 361 |
|
| V42 | | | 91.58 284 | 90.87 282 | 93.73 305 | 94.05 389 | 88.50 278 | 97.32 180 | 96.97 273 | 88.80 315 | 89.71 314 | 94.33 352 | 82.54 246 | 98.05 314 | 89.01 286 | 85.07 393 | 94.64 400 |
|
| PCF-MVS | | 89.48 11 | 91.56 285 | 89.95 329 | 96.36 127 | 96.60 233 | 92.52 103 | 92.51 442 | 97.26 237 | 79.41 449 | 88.90 339 | 96.56 234 | 84.04 212 | 99.55 108 | 77.01 434 | 97.30 178 | 97.01 281 |
| Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
| UBG | | | 91.55 286 | 90.76 289 | 93.94 294 | 96.52 249 | 85.06 373 | 95.22 362 | 94.54 409 | 90.47 258 | 91.98 254 | 92.71 407 | 72.02 385 | 98.74 231 | 88.10 300 | 95.26 246 | 98.01 231 |
|
| PS-CasMVS | | | 91.55 286 | 90.84 286 | 93.69 309 | 94.96 351 | 88.28 284 | 97.84 95 | 98.24 63 | 91.46 206 | 88.04 366 | 95.80 273 | 79.67 305 | 97.48 385 | 87.02 332 | 84.54 404 | 95.31 353 |
|
| miper_enhance_ethall | | | 91.54 288 | 91.01 278 | 93.15 335 | 95.35 325 | 87.07 320 | 93.97 406 | 96.90 283 | 86.79 370 | 89.17 335 | 93.43 399 | 86.55 155 | 97.64 368 | 89.97 259 | 86.93 370 | 94.74 396 |
|
| myMVS_eth3d28 | | | 91.52 289 | 90.97 279 | 93.17 334 | 96.91 199 | 83.24 398 | 95.61 341 | 94.96 392 | 92.24 174 | 91.98 254 | 93.28 400 | 69.31 409 | 98.40 272 | 88.71 293 | 95.68 233 | 97.88 239 |
|
| PAPM | | | 91.52 289 | 90.30 310 | 95.20 212 | 95.30 332 | 89.83 220 | 93.38 428 | 96.85 289 | 86.26 380 | 88.59 349 | 95.80 273 | 84.88 196 | 98.15 296 | 75.67 439 | 95.93 225 | 97.63 254 |
|
| ET-MVSNet_ETH3D | | | 91.49 291 | 90.11 320 | 95.63 187 | 96.40 259 | 91.57 142 | 95.34 353 | 93.48 435 | 90.60 252 | 75.58 460 | 95.49 293 | 80.08 297 | 96.79 417 | 94.25 162 | 89.76 339 | 98.52 175 |
|
| TR-MVS | | | 91.48 292 | 90.59 300 | 94.16 278 | 96.40 259 | 87.33 309 | 95.67 335 | 95.34 374 | 87.68 352 | 91.46 268 | 95.52 292 | 76.77 347 | 98.35 280 | 82.85 387 | 93.61 286 | 96.79 290 |
|
| tpmrst | | | 91.44 293 | 91.32 264 | 91.79 381 | 95.15 343 | 79.20 447 | 93.42 427 | 95.37 370 | 88.55 322 | 93.49 217 | 93.67 386 | 82.49 248 | 98.27 286 | 90.41 251 | 89.34 343 | 97.90 237 |
|
| test-LLR | | | 91.42 294 | 91.19 272 | 92.12 369 | 94.59 371 | 80.66 425 | 94.29 398 | 92.98 441 | 91.11 227 | 90.76 286 | 92.37 415 | 79.02 318 | 98.07 311 | 88.81 290 | 96.74 201 | 97.63 254 |
|
| MSDG | | | 91.42 294 | 90.24 314 | 94.96 230 | 97.15 178 | 88.91 264 | 93.69 420 | 96.32 321 | 85.72 388 | 86.93 392 | 96.47 238 | 80.24 294 | 98.98 192 | 80.57 411 | 95.05 251 | 96.98 282 |
|
| c3_l | | | 91.38 296 | 90.89 281 | 92.88 345 | 95.58 309 | 86.30 341 | 94.68 379 | 96.84 290 | 88.17 332 | 88.83 345 | 94.23 360 | 85.65 177 | 97.47 386 | 89.36 275 | 84.63 399 | 94.89 380 |
|
| GA-MVS | | | 91.38 296 | 90.31 309 | 94.59 249 | 94.65 369 | 87.62 305 | 94.34 394 | 96.19 332 | 90.73 240 | 90.35 292 | 93.83 376 | 71.84 387 | 97.96 330 | 87.22 327 | 93.61 286 | 98.21 209 |
|
| v1144 | | | 91.37 298 | 90.60 299 | 93.68 311 | 93.89 393 | 88.23 287 | 96.84 232 | 97.03 269 | 88.37 327 | 89.69 316 | 94.39 346 | 82.04 257 | 97.98 323 | 87.80 306 | 85.37 386 | 94.84 382 |
|
| GBi-Net | | | 91.35 299 | 90.27 312 | 94.59 249 | 96.51 250 | 91.18 163 | 97.50 153 | 96.93 277 | 88.82 312 | 89.35 327 | 94.51 339 | 73.87 373 | 97.29 398 | 86.12 345 | 88.82 349 | 95.31 353 |
|
| test1 | | | 91.35 299 | 90.27 312 | 94.59 249 | 96.51 250 | 91.18 163 | 97.50 153 | 96.93 277 | 88.82 312 | 89.35 327 | 94.51 339 | 73.87 373 | 97.29 398 | 86.12 345 | 88.82 349 | 95.31 353 |
|
| UniMVSNet_ETH3D | | | 91.34 301 | 90.22 317 | 94.68 246 | 94.86 359 | 87.86 300 | 97.23 192 | 97.46 202 | 87.99 337 | 89.90 308 | 96.92 209 | 66.35 432 | 98.23 288 | 90.30 254 | 90.99 325 | 97.96 233 |
|
| FMVSNet2 | | | 91.31 302 | 90.08 321 | 94.99 225 | 96.51 250 | 92.21 114 | 97.41 167 | 96.95 275 | 88.82 312 | 88.62 348 | 94.75 326 | 73.87 373 | 97.42 391 | 85.20 361 | 88.55 354 | 95.35 350 |
|
| reproduce_monomvs | | | 91.30 303 | 91.10 275 | 91.92 373 | 96.82 211 | 82.48 408 | 97.01 211 | 97.49 194 | 94.64 71 | 88.35 354 | 95.27 302 | 70.53 397 | 98.10 302 | 95.20 122 | 84.60 401 | 95.19 364 |
|
| D2MVS | | | 91.30 303 | 90.95 280 | 92.35 359 | 94.71 367 | 85.52 360 | 96.18 305 | 98.21 67 | 88.89 308 | 86.60 395 | 93.82 378 | 79.92 301 | 97.95 334 | 89.29 278 | 90.95 326 | 93.56 422 |
|
| v8 | | | 91.29 305 | 90.53 303 | 93.57 319 | 94.15 385 | 88.12 292 | 97.34 177 | 97.06 264 | 88.99 303 | 88.32 356 | 94.26 359 | 83.08 229 | 98.01 320 | 87.62 318 | 83.92 412 | 94.57 401 |
|
| CVMVSNet | | | 91.23 306 | 91.75 249 | 89.67 422 | 95.77 301 | 74.69 459 | 96.44 272 | 94.88 396 | 85.81 386 | 92.18 247 | 97.64 155 | 79.07 315 | 95.58 439 | 88.06 301 | 95.86 228 | 98.74 158 |
|
| cl22 | | | 91.21 307 | 90.56 302 | 93.14 336 | 96.09 288 | 86.80 325 | 94.41 391 | 96.58 309 | 87.80 346 | 88.58 350 | 93.99 373 | 80.85 281 | 97.62 371 | 89.87 262 | 86.93 370 | 94.99 371 |
|
| PEN-MVS | | | 91.20 308 | 90.44 304 | 93.48 322 | 94.49 375 | 87.91 299 | 97.76 108 | 98.18 76 | 91.29 212 | 87.78 370 | 95.74 279 | 80.35 292 | 97.33 396 | 85.46 356 | 82.96 420 | 95.19 364 |
|
| Baseline_NR-MVSNet | | | 91.20 308 | 90.62 298 | 92.95 342 | 93.83 395 | 88.03 294 | 97.01 211 | 95.12 384 | 88.42 326 | 89.70 315 | 95.13 309 | 83.47 219 | 97.44 389 | 89.66 268 | 83.24 418 | 93.37 426 |
|
| cascas | | | 91.20 308 | 90.08 321 | 94.58 253 | 94.97 350 | 89.16 257 | 93.65 422 | 97.59 174 | 79.90 447 | 89.40 325 | 92.92 405 | 75.36 360 | 98.36 279 | 92.14 206 | 94.75 257 | 96.23 301 |
|
| CostFormer | | | 91.18 311 | 90.70 295 | 92.62 355 | 94.84 360 | 81.76 416 | 94.09 404 | 94.43 412 | 84.15 410 | 92.72 236 | 93.77 380 | 79.43 309 | 98.20 291 | 90.70 244 | 92.18 304 | 97.90 237 |
|
| tt0805 | | | 91.09 312 | 90.07 324 | 94.16 278 | 95.61 307 | 88.31 282 | 97.56 144 | 96.51 311 | 89.56 282 | 89.17 335 | 95.64 285 | 67.08 429 | 98.38 278 | 91.07 234 | 88.44 355 | 95.80 322 |
|
| v1192 | | | 91.07 313 | 90.23 315 | 93.58 317 | 93.70 398 | 87.82 302 | 96.73 248 | 97.07 259 | 87.77 348 | 89.58 319 | 94.32 354 | 80.90 280 | 97.97 326 | 86.52 337 | 85.48 384 | 94.95 372 |
|
| v144192 | | | 91.06 314 | 90.28 311 | 93.39 325 | 93.66 401 | 87.23 315 | 96.83 233 | 97.07 259 | 87.43 357 | 89.69 316 | 94.28 356 | 81.48 268 | 98.00 321 | 87.18 329 | 84.92 397 | 94.93 376 |
|
| v10 | | | 91.04 315 | 90.23 315 | 93.49 321 | 94.12 386 | 88.16 291 | 97.32 180 | 97.08 256 | 88.26 330 | 88.29 358 | 94.22 362 | 82.17 255 | 97.97 326 | 86.45 339 | 84.12 408 | 94.33 408 |
|
| eth_miper_zixun_eth | | | 91.02 316 | 90.59 300 | 92.34 361 | 95.33 329 | 84.35 383 | 94.10 403 | 96.90 283 | 88.56 321 | 88.84 344 | 94.33 352 | 84.08 210 | 97.60 373 | 88.77 292 | 84.37 406 | 95.06 369 |
|
| v148 | | | 90.99 317 | 90.38 306 | 92.81 348 | 93.83 395 | 85.80 354 | 96.78 244 | 96.68 300 | 89.45 288 | 88.75 347 | 93.93 375 | 82.96 235 | 97.82 349 | 87.83 305 | 83.25 417 | 94.80 389 |
|
| LTVRE_ROB | | 88.41 13 | 90.99 317 | 89.92 331 | 94.19 274 | 96.18 277 | 89.55 235 | 96.31 293 | 97.09 255 | 87.88 341 | 85.67 406 | 95.91 267 | 78.79 324 | 98.57 260 | 81.50 398 | 89.98 336 | 94.44 405 |
| 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 |
| DIV-MVS_self_test | | | 90.97 319 | 90.33 307 | 92.88 345 | 95.36 324 | 86.19 346 | 94.46 389 | 96.63 306 | 87.82 344 | 88.18 362 | 94.23 360 | 82.99 232 | 97.53 381 | 87.72 309 | 85.57 383 | 94.93 376 |
|
| cl____ | | | 90.96 320 | 90.32 308 | 92.89 344 | 95.37 323 | 86.21 344 | 94.46 389 | 96.64 303 | 87.82 344 | 88.15 364 | 94.18 363 | 82.98 233 | 97.54 379 | 87.70 312 | 85.59 382 | 94.92 378 |
|
| pmmvs4 | | | 90.93 321 | 89.85 333 | 94.17 275 | 93.34 415 | 90.79 181 | 94.60 381 | 96.02 337 | 84.62 405 | 87.45 375 | 95.15 307 | 81.88 263 | 97.45 388 | 87.70 312 | 87.87 360 | 94.27 412 |
|
| XVG-ACMP-BASELINE | | | 90.93 321 | 90.21 318 | 93.09 337 | 94.31 383 | 85.89 353 | 95.33 354 | 97.26 237 | 91.06 230 | 89.38 326 | 95.44 296 | 68.61 415 | 98.60 255 | 89.46 272 | 91.05 323 | 94.79 391 |
|
| v1921920 | | | 90.85 323 | 90.03 326 | 93.29 329 | 93.55 404 | 86.96 324 | 96.74 247 | 97.04 267 | 87.36 359 | 89.52 323 | 94.34 351 | 80.23 295 | 97.97 326 | 86.27 340 | 85.21 390 | 94.94 374 |
|
| CR-MVSNet | | | 90.82 324 | 89.77 337 | 93.95 292 | 94.45 377 | 87.19 316 | 90.23 458 | 95.68 355 | 86.89 368 | 92.40 238 | 92.36 418 | 80.91 278 | 97.05 405 | 81.09 408 | 93.95 278 | 97.60 259 |
|
| v7n | | | 90.76 325 | 89.86 332 | 93.45 324 | 93.54 405 | 87.60 306 | 97.70 123 | 97.37 223 | 88.85 309 | 87.65 372 | 94.08 369 | 81.08 275 | 98.10 302 | 84.68 366 | 83.79 414 | 94.66 399 |
|
| RPSCF | | | 90.75 326 | 90.86 283 | 90.42 412 | 96.84 207 | 76.29 457 | 95.61 341 | 96.34 320 | 83.89 413 | 91.38 269 | 97.87 122 | 76.45 350 | 98.78 215 | 87.16 330 | 92.23 301 | 96.20 303 |
|
| MVP-Stereo | | | 90.74 327 | 90.08 321 | 92.71 352 | 93.19 418 | 88.20 288 | 95.86 323 | 96.27 326 | 86.07 383 | 84.86 414 | 94.76 325 | 77.84 339 | 97.75 359 | 83.88 379 | 98.01 153 | 92.17 447 |
| Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
| pm-mvs1 | | | 90.72 328 | 89.65 343 | 93.96 291 | 94.29 384 | 89.63 228 | 97.79 106 | 96.82 291 | 89.07 298 | 86.12 403 | 95.48 295 | 78.61 326 | 97.78 354 | 86.97 333 | 81.67 425 | 94.46 403 |
|
| v1240 | | | 90.70 329 | 89.85 333 | 93.23 331 | 93.51 407 | 86.80 325 | 96.61 264 | 97.02 271 | 87.16 364 | 89.58 319 | 94.31 355 | 79.55 308 | 97.98 323 | 85.52 355 | 85.44 385 | 94.90 379 |
|
| EPMVS | | | 90.70 329 | 89.81 335 | 93.37 326 | 94.73 366 | 84.21 385 | 93.67 421 | 88.02 470 | 89.50 285 | 92.38 240 | 93.49 393 | 77.82 340 | 97.78 354 | 86.03 348 | 92.68 296 | 98.11 224 |
|
| WBMVS | | | 90.69 331 | 89.99 328 | 92.81 348 | 96.48 253 | 85.00 374 | 95.21 364 | 96.30 323 | 89.46 287 | 89.04 338 | 94.05 370 | 72.45 384 | 97.82 349 | 89.46 272 | 87.41 367 | 95.61 333 |
|
| Anonymous20231211 | | | 90.63 332 | 89.42 348 | 94.27 273 | 98.24 100 | 89.19 256 | 98.05 62 | 97.89 128 | 79.95 446 | 88.25 360 | 94.96 314 | 72.56 383 | 98.13 297 | 89.70 266 | 85.14 391 | 95.49 335 |
|
| DTE-MVSNet | | | 90.56 333 | 89.75 339 | 93.01 339 | 93.95 390 | 87.25 313 | 97.64 133 | 97.65 162 | 90.74 239 | 87.12 383 | 95.68 283 | 79.97 300 | 97.00 409 | 83.33 381 | 81.66 426 | 94.78 393 |
|
| ACMH | | 87.59 16 | 90.53 334 | 89.42 348 | 93.87 299 | 96.21 269 | 87.92 297 | 97.24 188 | 96.94 276 | 88.45 325 | 83.91 426 | 96.27 249 | 71.92 386 | 98.62 254 | 84.43 369 | 89.43 342 | 95.05 370 |
| Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
| ETVMVS | | | 90.52 335 | 89.14 356 | 94.67 247 | 96.81 213 | 87.85 301 | 95.91 321 | 93.97 427 | 89.71 278 | 92.34 244 | 92.48 413 | 65.41 440 | 97.96 330 | 81.37 404 | 94.27 266 | 98.21 209 |
|
| OurMVSNet-221017-0 | | | 90.51 336 | 90.19 319 | 91.44 390 | 93.41 413 | 81.25 419 | 96.98 215 | 96.28 325 | 91.68 196 | 86.55 397 | 96.30 246 | 74.20 372 | 97.98 323 | 88.96 288 | 87.40 368 | 95.09 367 |
|
| miper_lstm_enhance | | | 90.50 337 | 90.06 325 | 91.83 378 | 95.33 329 | 83.74 391 | 93.86 412 | 96.70 299 | 87.56 355 | 87.79 369 | 93.81 379 | 83.45 221 | 96.92 411 | 87.39 323 | 84.62 400 | 94.82 386 |
|
| COLMAP_ROB |  | 87.81 15 | 90.40 338 | 89.28 351 | 93.79 303 | 97.95 129 | 87.13 319 | 96.92 221 | 95.89 343 | 82.83 426 | 86.88 394 | 97.18 189 | 73.77 376 | 99.29 146 | 78.44 425 | 93.62 285 | 94.95 372 |
| Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
| testing222 | | | 90.31 339 | 88.96 358 | 94.35 265 | 96.54 244 | 87.29 310 | 95.50 346 | 93.84 431 | 90.97 232 | 91.75 262 | 92.96 404 | 62.18 452 | 98.00 321 | 82.86 385 | 94.08 273 | 97.76 249 |
|
| IterMVS-SCA-FT | | | 90.31 339 | 89.81 335 | 91.82 379 | 95.52 312 | 84.20 386 | 94.30 397 | 96.15 334 | 90.61 250 | 87.39 378 | 94.27 357 | 75.80 356 | 96.44 422 | 87.34 324 | 86.88 374 | 94.82 386 |
|
| MS-PatchMatch | | | 90.27 341 | 89.77 337 | 91.78 382 | 94.33 381 | 84.72 380 | 95.55 343 | 96.73 294 | 86.17 382 | 86.36 399 | 95.28 301 | 71.28 391 | 97.80 352 | 84.09 374 | 98.14 147 | 92.81 432 |
|
| tpm | | | 90.25 342 | 89.74 340 | 91.76 384 | 93.92 391 | 79.73 440 | 93.98 405 | 93.54 434 | 88.28 329 | 91.99 253 | 93.25 401 | 77.51 342 | 97.44 389 | 87.30 326 | 87.94 359 | 98.12 218 |
|
| AllTest | | | 90.23 343 | 88.98 357 | 93.98 288 | 97.94 130 | 86.64 329 | 96.51 271 | 95.54 363 | 85.38 392 | 85.49 408 | 96.77 216 | 70.28 399 | 99.15 163 | 80.02 415 | 92.87 290 | 96.15 308 |
|
| dmvs_re | | | 90.21 344 | 89.50 346 | 92.35 359 | 95.47 318 | 85.15 370 | 95.70 334 | 94.37 417 | 90.94 235 | 88.42 352 | 93.57 391 | 74.63 368 | 95.67 436 | 82.80 388 | 89.57 341 | 96.22 302 |
|
| ACMH+ | | 87.92 14 | 90.20 345 | 89.18 354 | 93.25 330 | 96.48 253 | 86.45 338 | 96.99 214 | 96.68 300 | 88.83 311 | 84.79 415 | 96.22 251 | 70.16 401 | 98.53 263 | 84.42 370 | 88.04 358 | 94.77 394 |
|
| test-mter | | | 90.19 346 | 89.54 345 | 92.12 369 | 94.59 371 | 80.66 425 | 94.29 398 | 92.98 441 | 87.68 352 | 90.76 286 | 92.37 415 | 67.67 421 | 98.07 311 | 88.81 290 | 96.74 201 | 97.63 254 |
|
| IterMVS | | | 90.15 347 | 89.67 341 | 91.61 386 | 95.48 314 | 83.72 392 | 94.33 395 | 96.12 335 | 89.99 269 | 87.31 381 | 94.15 365 | 75.78 358 | 96.27 426 | 86.97 333 | 86.89 373 | 94.83 383 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
| TESTMET0.1,1 | | | 90.06 348 | 89.42 348 | 91.97 372 | 94.41 379 | 80.62 427 | 94.29 398 | 91.97 453 | 87.28 362 | 90.44 290 | 92.47 414 | 68.79 413 | 97.67 364 | 88.50 297 | 96.60 208 | 97.61 258 |
|
| SD_0403 | | | 90.01 349 | 90.02 327 | 89.96 419 | 95.65 306 | 76.76 454 | 95.76 331 | 96.46 314 | 90.58 253 | 86.59 396 | 96.29 247 | 82.12 256 | 94.78 448 | 73.00 453 | 93.76 281 | 98.35 197 |
|
| tpm2 | | | 89.96 350 | 89.21 353 | 92.23 367 | 94.91 357 | 81.25 419 | 93.78 415 | 94.42 413 | 80.62 444 | 91.56 265 | 93.44 396 | 76.44 351 | 97.94 336 | 85.60 354 | 92.08 308 | 97.49 263 |
|
| UWE-MVS | | | 89.91 351 | 89.48 347 | 91.21 395 | 95.88 294 | 78.23 452 | 94.91 374 | 90.26 463 | 89.11 297 | 92.35 243 | 94.52 338 | 68.76 414 | 97.96 330 | 83.95 377 | 95.59 236 | 97.42 267 |
|
| IB-MVS | | 87.33 17 | 89.91 351 | 88.28 368 | 94.79 241 | 95.26 336 | 87.70 304 | 95.12 369 | 93.95 428 | 89.35 291 | 87.03 387 | 92.49 412 | 70.74 396 | 99.19 154 | 89.18 284 | 81.37 427 | 97.49 263 |
| 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 |
| ADS-MVSNet | | | 89.89 353 | 88.68 363 | 93.53 320 | 95.86 295 | 84.89 378 | 90.93 453 | 95.07 386 | 83.23 424 | 91.28 277 | 91.81 428 | 79.01 320 | 97.85 345 | 79.52 417 | 91.39 317 | 97.84 244 |
|
| WB-MVSnew | | | 89.88 354 | 89.56 344 | 90.82 404 | 94.57 374 | 83.06 401 | 95.65 339 | 92.85 443 | 87.86 343 | 90.83 285 | 94.10 366 | 79.66 306 | 96.88 413 | 76.34 435 | 94.19 268 | 92.54 438 |
|
| FMVSNet1 | | | 89.88 354 | 88.31 367 | 94.59 249 | 95.41 319 | 91.18 163 | 97.50 153 | 96.93 277 | 86.62 372 | 87.41 377 | 94.51 339 | 65.94 437 | 97.29 398 | 83.04 384 | 87.43 365 | 95.31 353 |
|
| pmmvs5 | | | 89.86 356 | 88.87 361 | 92.82 347 | 92.86 424 | 86.23 343 | 96.26 296 | 95.39 368 | 84.24 409 | 87.12 383 | 94.51 339 | 74.27 371 | 97.36 395 | 87.61 319 | 87.57 363 | 94.86 381 |
|
| tpmvs | | | 89.83 357 | 89.15 355 | 91.89 376 | 94.92 355 | 80.30 432 | 93.11 433 | 95.46 367 | 86.28 379 | 88.08 365 | 92.65 408 | 80.44 290 | 98.52 264 | 81.47 400 | 89.92 337 | 96.84 288 |
|
| test_fmvs2 | | | 89.77 358 | 89.93 330 | 89.31 429 | 93.68 400 | 76.37 456 | 97.64 133 | 95.90 341 | 89.84 275 | 91.49 267 | 96.26 250 | 58.77 455 | 97.10 402 | 94.65 150 | 91.13 321 | 94.46 403 |
|
| SSC-MVS3.2 | | | 89.74 359 | 89.26 352 | 91.19 398 | 95.16 340 | 80.29 433 | 94.53 384 | 97.03 269 | 91.79 192 | 88.86 342 | 94.10 366 | 69.94 404 | 97.82 349 | 85.29 358 | 86.66 375 | 95.45 341 |
|
| mmtdpeth | | | 89.70 360 | 88.96 358 | 91.90 375 | 95.84 300 | 84.42 382 | 97.46 164 | 95.53 366 | 90.27 262 | 94.46 185 | 90.50 437 | 69.74 408 | 98.95 193 | 97.39 53 | 69.48 466 | 92.34 441 |
|
| tfpnnormal | | | 89.70 360 | 88.40 366 | 93.60 315 | 95.15 343 | 90.10 207 | 97.56 144 | 98.16 80 | 87.28 362 | 86.16 401 | 94.63 333 | 77.57 341 | 98.05 314 | 74.48 443 | 84.59 402 | 92.65 435 |
|
| ADS-MVSNet2 | | | 89.45 362 | 88.59 364 | 92.03 371 | 95.86 295 | 82.26 412 | 90.93 453 | 94.32 420 | 83.23 424 | 91.28 277 | 91.81 428 | 79.01 320 | 95.99 428 | 79.52 417 | 91.39 317 | 97.84 244 |
|
| Patchmatch-test | | | 89.42 363 | 87.99 370 | 93.70 308 | 95.27 333 | 85.11 371 | 88.98 465 | 94.37 417 | 81.11 438 | 87.10 386 | 93.69 383 | 82.28 252 | 97.50 384 | 74.37 445 | 94.76 256 | 98.48 182 |
|
| test0.0.03 1 | | | 89.37 364 | 88.70 362 | 91.41 391 | 92.47 433 | 85.63 358 | 95.22 362 | 92.70 446 | 91.11 227 | 86.91 393 | 93.65 387 | 79.02 318 | 93.19 465 | 78.00 427 | 89.18 344 | 95.41 343 |
|
| SixPastTwentyTwo | | | 89.15 365 | 88.54 365 | 90.98 400 | 93.49 408 | 80.28 434 | 96.70 252 | 94.70 403 | 90.78 237 | 84.15 421 | 95.57 288 | 71.78 388 | 97.71 362 | 84.63 367 | 85.07 393 | 94.94 374 |
|
| RPMNet | | | 88.98 366 | 87.05 380 | 94.77 242 | 94.45 377 | 87.19 316 | 90.23 458 | 98.03 110 | 77.87 457 | 92.40 238 | 87.55 462 | 80.17 296 | 99.51 117 | 68.84 464 | 93.95 278 | 97.60 259 |
|
| TransMVSNet (Re) | | | 88.94 367 | 87.56 373 | 93.08 338 | 94.35 380 | 88.45 280 | 97.73 115 | 95.23 379 | 87.47 356 | 84.26 419 | 95.29 299 | 79.86 302 | 97.33 396 | 79.44 421 | 74.44 455 | 93.45 425 |
|
| USDC | | | 88.94 367 | 87.83 372 | 92.27 364 | 94.66 368 | 84.96 376 | 93.86 412 | 95.90 341 | 87.34 360 | 83.40 428 | 95.56 289 | 67.43 423 | 98.19 293 | 82.64 392 | 89.67 340 | 93.66 421 |
|
| dp | | | 88.90 369 | 88.26 369 | 90.81 405 | 94.58 373 | 76.62 455 | 92.85 438 | 94.93 393 | 85.12 398 | 90.07 306 | 93.07 402 | 75.81 355 | 98.12 300 | 80.53 412 | 87.42 366 | 97.71 251 |
|
| PatchT | | | 88.87 370 | 87.42 374 | 93.22 332 | 94.08 388 | 85.10 372 | 89.51 463 | 94.64 406 | 81.92 433 | 92.36 241 | 88.15 458 | 80.05 298 | 97.01 408 | 72.43 454 | 93.65 284 | 97.54 262 |
|
| our_test_3 | | | 88.78 371 | 87.98 371 | 91.20 397 | 92.45 434 | 82.53 406 | 93.61 424 | 95.69 353 | 85.77 387 | 84.88 413 | 93.71 381 | 79.99 299 | 96.78 418 | 79.47 419 | 86.24 376 | 94.28 411 |
|
| EU-MVSNet | | | 88.72 372 | 88.90 360 | 88.20 433 | 93.15 419 | 74.21 461 | 96.63 263 | 94.22 422 | 85.18 396 | 87.32 380 | 95.97 263 | 76.16 353 | 94.98 446 | 85.27 359 | 86.17 377 | 95.41 343 |
|
| Patchmtry | | | 88.64 373 | 87.25 376 | 92.78 350 | 94.09 387 | 86.64 329 | 89.82 462 | 95.68 355 | 80.81 442 | 87.63 373 | 92.36 418 | 80.91 278 | 97.03 406 | 78.86 423 | 85.12 392 | 94.67 398 |
|
| MIMVSNet | | | 88.50 374 | 86.76 384 | 93.72 307 | 94.84 360 | 87.77 303 | 91.39 448 | 94.05 424 | 86.41 376 | 87.99 367 | 92.59 411 | 63.27 446 | 95.82 433 | 77.44 428 | 92.84 292 | 97.57 261 |
|
| tpm cat1 | | | 88.36 375 | 87.21 378 | 91.81 380 | 95.13 345 | 80.55 428 | 92.58 441 | 95.70 351 | 74.97 461 | 87.45 375 | 91.96 426 | 78.01 338 | 98.17 295 | 80.39 413 | 88.74 352 | 96.72 292 |
|
| ppachtmachnet_test | | | 88.35 376 | 87.29 375 | 91.53 387 | 92.45 434 | 83.57 395 | 93.75 416 | 95.97 338 | 84.28 408 | 85.32 411 | 94.18 363 | 79.00 322 | 96.93 410 | 75.71 438 | 84.99 396 | 94.10 413 |
|
| JIA-IIPM | | | 88.26 377 | 87.04 381 | 91.91 374 | 93.52 406 | 81.42 418 | 89.38 464 | 94.38 416 | 80.84 441 | 90.93 283 | 80.74 472 | 79.22 312 | 97.92 339 | 82.76 389 | 91.62 312 | 96.38 300 |
|
| testgi | | | 87.97 378 | 87.21 378 | 90.24 415 | 92.86 424 | 80.76 423 | 96.67 257 | 94.97 390 | 91.74 194 | 85.52 407 | 95.83 271 | 62.66 450 | 94.47 451 | 76.25 436 | 88.36 356 | 95.48 336 |
|
| LF4IMVS | | | 87.94 379 | 87.25 376 | 89.98 418 | 92.38 436 | 80.05 438 | 94.38 392 | 95.25 378 | 87.59 354 | 84.34 417 | 94.74 327 | 64.31 444 | 97.66 367 | 84.83 363 | 87.45 364 | 92.23 444 |
|
| gg-mvs-nofinetune | | | 87.82 380 | 85.61 393 | 94.44 261 | 94.46 376 | 89.27 252 | 91.21 452 | 84.61 479 | 80.88 440 | 89.89 310 | 74.98 475 | 71.50 389 | 97.53 381 | 85.75 353 | 97.21 182 | 96.51 295 |
|
| pmmvs6 | | | 87.81 381 | 86.19 389 | 92.69 353 | 91.32 441 | 86.30 341 | 97.34 177 | 96.41 317 | 80.59 445 | 84.05 425 | 94.37 348 | 67.37 424 | 97.67 364 | 84.75 365 | 79.51 435 | 94.09 415 |
|
| testing3 | | | 87.67 382 | 86.88 383 | 90.05 417 | 96.14 282 | 80.71 424 | 97.10 203 | 92.85 443 | 90.15 266 | 87.54 374 | 94.55 336 | 55.70 462 | 94.10 454 | 73.77 449 | 94.10 272 | 95.35 350 |
|
| K. test v3 | | | 87.64 383 | 86.75 385 | 90.32 414 | 93.02 421 | 79.48 445 | 96.61 264 | 92.08 452 | 90.66 246 | 80.25 447 | 94.09 368 | 67.21 425 | 96.65 420 | 85.96 350 | 80.83 429 | 94.83 383 |
|
| Patchmatch-RL test | | | 87.38 384 | 86.24 388 | 90.81 405 | 88.74 460 | 78.40 451 | 88.12 472 | 93.17 438 | 87.11 365 | 82.17 437 | 89.29 449 | 81.95 260 | 95.60 438 | 88.64 295 | 77.02 444 | 98.41 190 |
|
| FMVSNet5 | | | 87.29 385 | 85.79 392 | 91.78 382 | 94.80 362 | 87.28 311 | 95.49 347 | 95.28 375 | 84.09 411 | 83.85 427 | 91.82 427 | 62.95 448 | 94.17 453 | 78.48 424 | 85.34 388 | 93.91 419 |
|
| myMVS_eth3d | | | 87.18 386 | 86.38 387 | 89.58 423 | 95.16 340 | 79.53 442 | 95.00 371 | 93.93 429 | 88.55 322 | 86.96 389 | 91.99 424 | 56.23 461 | 94.00 455 | 75.47 441 | 94.11 270 | 95.20 361 |
|
| Syy-MVS | | | 87.13 387 | 87.02 382 | 87.47 437 | 95.16 340 | 73.21 465 | 95.00 371 | 93.93 429 | 88.55 322 | 86.96 389 | 91.99 424 | 75.90 354 | 94.00 455 | 61.59 471 | 94.11 270 | 95.20 361 |
|
| Anonymous20231206 | | | 87.09 388 | 86.14 390 | 89.93 420 | 91.22 442 | 80.35 430 | 96.11 308 | 95.35 371 | 83.57 420 | 84.16 420 | 93.02 403 | 73.54 378 | 95.61 437 | 72.16 455 | 86.14 378 | 93.84 420 |
|
| usedtu_blend_shiyan5 | | | 87.06 389 | 84.84 403 | 93.69 309 | 88.54 462 | 88.70 269 | 95.83 325 | 95.54 363 | 78.74 452 | 85.92 404 | 86.89 466 | 73.03 380 | 97.55 376 | 87.73 307 | 71.36 462 | 94.83 383 |
|
| EG-PatchMatch MVS | | | 87.02 390 | 85.44 394 | 91.76 384 | 92.67 428 | 85.00 374 | 96.08 310 | 96.45 315 | 83.41 423 | 79.52 449 | 93.49 393 | 57.10 459 | 97.72 361 | 79.34 422 | 90.87 328 | 92.56 437 |
|
| blend_shiyan4 | | | 86.87 391 | 84.61 408 | 93.67 312 | 88.87 457 | 88.70 269 | 95.17 367 | 96.30 323 | 82.80 427 | 86.16 401 | 87.11 464 | 65.12 443 | 97.55 376 | 87.73 307 | 72.21 460 | 94.75 395 |
|
| TinyColmap | | | 86.82 392 | 85.35 397 | 91.21 395 | 94.91 357 | 82.99 402 | 93.94 408 | 94.02 426 | 83.58 419 | 81.56 439 | 94.68 329 | 62.34 451 | 98.13 297 | 75.78 437 | 87.35 369 | 92.52 439 |
|
| UWE-MVS-28 | | | 86.81 393 | 86.41 386 | 88.02 435 | 92.87 423 | 74.60 460 | 95.38 352 | 86.70 475 | 88.17 332 | 87.28 382 | 94.67 331 | 70.83 395 | 93.30 463 | 67.45 465 | 94.31 264 | 96.17 305 |
|
| mvs5depth | | | 86.53 394 | 85.08 399 | 90.87 402 | 88.74 460 | 82.52 407 | 91.91 446 | 94.23 421 | 86.35 377 | 87.11 385 | 93.70 382 | 66.52 430 | 97.76 357 | 81.37 404 | 75.80 449 | 92.31 443 |
|
| TDRefinement | | | 86.53 394 | 84.76 405 | 91.85 377 | 82.23 478 | 84.25 384 | 96.38 284 | 95.35 371 | 84.97 401 | 84.09 423 | 94.94 315 | 65.76 438 | 98.34 283 | 84.60 368 | 74.52 454 | 92.97 429 |
|
| sc_t1 | | | 86.48 396 | 84.10 413 | 93.63 313 | 93.45 411 | 85.76 356 | 96.79 240 | 94.71 402 | 73.06 466 | 86.45 398 | 94.35 349 | 55.13 463 | 97.95 334 | 84.38 371 | 78.55 440 | 97.18 278 |
|
| test_0402 | | | 86.46 397 | 84.79 404 | 91.45 389 | 95.02 349 | 85.55 359 | 96.29 295 | 94.89 395 | 80.90 439 | 82.21 436 | 93.97 374 | 68.21 420 | 97.29 398 | 62.98 469 | 88.68 353 | 91.51 453 |
|
| Anonymous20240521 | | | 86.42 398 | 85.44 394 | 89.34 428 | 90.33 446 | 79.79 439 | 96.73 248 | 95.92 339 | 83.71 418 | 83.25 430 | 91.36 433 | 63.92 445 | 96.01 427 | 78.39 426 | 85.36 387 | 92.22 445 |
|
| FE-MVSNET2 | | | 86.36 399 | 84.68 407 | 91.39 392 | 87.67 466 | 86.47 337 | 96.21 301 | 96.41 317 | 87.87 342 | 79.31 451 | 89.64 446 | 65.29 441 | 95.58 439 | 82.42 393 | 77.28 443 | 92.14 448 |
|
| DSMNet-mixed | | | 86.34 400 | 86.12 391 | 87.00 441 | 89.88 450 | 70.43 467 | 94.93 373 | 90.08 464 | 77.97 456 | 85.42 410 | 92.78 406 | 74.44 370 | 93.96 457 | 74.43 444 | 95.14 247 | 96.62 293 |
|
| CL-MVSNet_self_test | | | 86.31 401 | 85.15 398 | 89.80 421 | 88.83 458 | 81.74 417 | 93.93 409 | 96.22 329 | 86.67 371 | 85.03 412 | 90.80 436 | 78.09 335 | 94.50 449 | 74.92 442 | 71.86 461 | 93.15 428 |
|
| pmmvs-eth3d | | | 86.22 402 | 84.45 409 | 91.53 387 | 88.34 463 | 87.25 313 | 94.47 387 | 95.01 387 | 83.47 421 | 79.51 450 | 89.61 447 | 69.75 407 | 95.71 434 | 83.13 383 | 76.73 447 | 91.64 450 |
|
| test_vis1_rt | | | 86.16 403 | 85.06 400 | 89.46 425 | 93.47 410 | 80.46 429 | 96.41 278 | 86.61 476 | 85.22 395 | 79.15 452 | 88.64 453 | 52.41 467 | 97.06 404 | 93.08 190 | 90.57 330 | 90.87 459 |
|
| test20.03 | | | 86.14 404 | 85.40 396 | 88.35 431 | 90.12 447 | 80.06 437 | 95.90 322 | 95.20 380 | 88.59 318 | 81.29 440 | 93.62 388 | 71.43 390 | 92.65 466 | 71.26 459 | 81.17 428 | 92.34 441 |
|
| UnsupCasMVSNet_eth | | | 85.99 405 | 84.45 409 | 90.62 409 | 89.97 449 | 82.40 411 | 93.62 423 | 97.37 223 | 89.86 272 | 78.59 455 | 92.37 415 | 65.25 442 | 95.35 444 | 82.27 395 | 70.75 463 | 94.10 413 |
|
| KD-MVS_self_test | | | 85.95 406 | 84.95 401 | 88.96 430 | 89.55 453 | 79.11 448 | 95.13 368 | 96.42 316 | 85.91 385 | 84.07 424 | 90.48 438 | 70.03 403 | 94.82 447 | 80.04 414 | 72.94 458 | 92.94 430 |
|
| ttmdpeth | | | 85.91 407 | 84.76 405 | 89.36 427 | 89.14 454 | 80.25 435 | 95.66 338 | 93.16 440 | 83.77 416 | 83.39 429 | 95.26 303 | 66.24 434 | 95.26 445 | 80.65 410 | 75.57 450 | 92.57 436 |
|
| YYNet1 | | | 85.87 408 | 84.23 411 | 90.78 408 | 92.38 436 | 82.46 410 | 93.17 430 | 95.14 383 | 82.12 432 | 67.69 468 | 92.36 418 | 78.16 334 | 95.50 442 | 77.31 430 | 79.73 433 | 94.39 406 |
|
| MDA-MVSNet_test_wron | | | 85.87 408 | 84.23 411 | 90.80 407 | 92.38 436 | 82.57 405 | 93.17 430 | 95.15 382 | 82.15 431 | 67.65 470 | 92.33 421 | 78.20 331 | 95.51 441 | 77.33 429 | 79.74 432 | 94.31 410 |
|
| CMPMVS |  | 62.92 21 | 85.62 410 | 84.92 402 | 87.74 436 | 89.14 454 | 73.12 466 | 94.17 401 | 96.80 292 | 73.98 462 | 73.65 464 | 94.93 316 | 66.36 431 | 97.61 372 | 83.95 377 | 91.28 319 | 92.48 440 |
| M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
| PVSNet_0 | | 82.17 19 | 85.46 411 | 83.64 414 | 90.92 401 | 95.27 333 | 79.49 444 | 90.55 456 | 95.60 358 | 83.76 417 | 83.00 433 | 89.95 443 | 71.09 392 | 97.97 326 | 82.75 390 | 60.79 477 | 95.31 353 |
|
| tt0320 | | | 85.39 412 | 83.12 415 | 92.19 368 | 93.44 412 | 85.79 355 | 96.19 304 | 94.87 399 | 71.19 468 | 82.92 434 | 91.76 430 | 58.43 456 | 96.81 416 | 81.03 409 | 78.26 441 | 93.98 417 |
|
| MDA-MVSNet-bldmvs | | | 85.00 413 | 82.95 418 | 91.17 399 | 93.13 420 | 83.33 396 | 94.56 383 | 95.00 388 | 84.57 406 | 65.13 474 | 92.65 408 | 70.45 398 | 95.85 431 | 73.57 450 | 77.49 442 | 94.33 408 |
|
| MIMVSNet1 | | | 84.93 414 | 83.05 416 | 90.56 410 | 89.56 452 | 84.84 379 | 95.40 350 | 95.35 371 | 83.91 412 | 80.38 445 | 92.21 423 | 57.23 458 | 93.34 462 | 70.69 461 | 82.75 423 | 93.50 423 |
|
| tt0320-xc | | | 84.83 415 | 82.33 423 | 92.31 362 | 93.66 401 | 86.20 345 | 96.17 306 | 94.06 423 | 71.26 467 | 82.04 438 | 92.22 422 | 55.07 464 | 96.72 419 | 81.49 399 | 75.04 453 | 94.02 416 |
|
| KD-MVS_2432*1600 | | | 84.81 416 | 82.64 419 | 91.31 393 | 91.07 443 | 85.34 368 | 91.22 450 | 95.75 349 | 85.56 390 | 83.09 431 | 90.21 441 | 67.21 425 | 95.89 429 | 77.18 432 | 62.48 475 | 92.69 433 |
|
| miper_refine_blended | | | 84.81 416 | 82.64 419 | 91.31 393 | 91.07 443 | 85.34 368 | 91.22 450 | 95.75 349 | 85.56 390 | 83.09 431 | 90.21 441 | 67.21 425 | 95.89 429 | 77.18 432 | 62.48 475 | 92.69 433 |
|
| OpenMVS_ROB |  | 81.14 20 | 84.42 418 | 82.28 424 | 90.83 403 | 90.06 448 | 84.05 389 | 95.73 333 | 94.04 425 | 73.89 464 | 80.17 448 | 91.53 432 | 59.15 454 | 97.64 368 | 66.92 467 | 89.05 346 | 90.80 460 |
|
| FE-MVSNET | | | 83.85 419 | 81.97 425 | 89.51 424 | 87.19 468 | 83.19 399 | 95.21 364 | 93.17 438 | 83.45 422 | 78.90 453 | 89.05 451 | 65.46 439 | 93.84 459 | 69.71 463 | 75.56 451 | 91.51 453 |
|
| mvsany_test3 | | | 83.59 420 | 82.44 422 | 87.03 440 | 83.80 473 | 73.82 462 | 93.70 418 | 90.92 461 | 86.42 375 | 82.51 435 | 90.26 440 | 46.76 472 | 95.71 434 | 90.82 239 | 76.76 446 | 91.57 452 |
|
| PM-MVS | | | 83.48 421 | 81.86 427 | 88.31 432 | 87.83 465 | 77.59 453 | 93.43 426 | 91.75 454 | 86.91 367 | 80.63 443 | 89.91 444 | 44.42 473 | 95.84 432 | 85.17 362 | 76.73 447 | 91.50 455 |
|
| test_fmvs3 | | | 83.21 422 | 83.02 417 | 83.78 446 | 86.77 470 | 68.34 472 | 96.76 246 | 94.91 394 | 86.49 374 | 84.14 422 | 89.48 448 | 36.04 477 | 91.73 468 | 91.86 216 | 80.77 430 | 91.26 458 |
|
| new-patchmatchnet | | | 83.18 423 | 81.87 426 | 87.11 439 | 86.88 469 | 75.99 458 | 93.70 418 | 95.18 381 | 85.02 400 | 77.30 458 | 88.40 455 | 65.99 436 | 93.88 458 | 74.19 447 | 70.18 464 | 91.47 456 |
|
| new_pmnet | | | 82.89 424 | 81.12 429 | 88.18 434 | 89.63 451 | 80.18 436 | 91.77 447 | 92.57 447 | 76.79 459 | 75.56 461 | 88.23 457 | 61.22 453 | 94.48 450 | 71.43 457 | 82.92 421 | 89.87 463 |
|
| MVS-HIRNet | | | 82.47 425 | 81.21 428 | 86.26 443 | 95.38 321 | 69.21 470 | 88.96 466 | 89.49 465 | 66.28 472 | 80.79 442 | 74.08 477 | 68.48 418 | 97.39 393 | 71.93 456 | 95.47 241 | 92.18 446 |
|
| MVStest1 | | | 82.38 426 | 80.04 430 | 89.37 426 | 87.63 467 | 82.83 403 | 95.03 370 | 93.37 437 | 73.90 463 | 73.50 465 | 94.35 349 | 62.89 449 | 93.25 464 | 73.80 448 | 65.92 472 | 92.04 449 |
|
| UnsupCasMVSNet_bld | | | 82.13 427 | 79.46 432 | 90.14 416 | 88.00 464 | 82.47 409 | 90.89 455 | 96.62 308 | 78.94 451 | 75.61 459 | 84.40 470 | 56.63 460 | 96.31 425 | 77.30 431 | 66.77 471 | 91.63 451 |
|
| dmvs_testset | | | 81.38 428 | 82.60 421 | 77.73 452 | 91.74 440 | 51.49 487 | 93.03 435 | 84.21 480 | 89.07 298 | 78.28 456 | 91.25 434 | 76.97 345 | 88.53 475 | 56.57 475 | 82.24 424 | 93.16 427 |
|
| test_f | | | 80.57 429 | 79.62 431 | 83.41 447 | 83.38 476 | 67.80 474 | 93.57 425 | 93.72 432 | 80.80 443 | 77.91 457 | 87.63 461 | 33.40 478 | 92.08 467 | 87.14 331 | 79.04 438 | 90.34 462 |
|
| pmmvs3 | | | 79.97 430 | 77.50 435 | 87.39 438 | 82.80 477 | 79.38 446 | 92.70 440 | 90.75 462 | 70.69 469 | 78.66 454 | 87.47 463 | 51.34 468 | 93.40 461 | 73.39 451 | 69.65 465 | 89.38 464 |
|
| APD_test1 | | | 79.31 431 | 77.70 434 | 84.14 445 | 89.11 456 | 69.07 471 | 92.36 445 | 91.50 456 | 69.07 470 | 73.87 463 | 92.63 410 | 39.93 475 | 94.32 452 | 70.54 462 | 80.25 431 | 89.02 465 |
|
| N_pmnet | | | 78.73 432 | 78.71 433 | 78.79 451 | 92.80 426 | 46.50 490 | 94.14 402 | 43.71 492 | 78.61 453 | 80.83 441 | 91.66 431 | 74.94 366 | 96.36 424 | 67.24 466 | 84.45 405 | 93.50 423 |
|
| WB-MVS | | | 76.77 433 | 76.63 436 | 77.18 453 | 85.32 471 | 56.82 485 | 94.53 384 | 89.39 466 | 82.66 429 | 71.35 466 | 89.18 450 | 75.03 363 | 88.88 473 | 35.42 482 | 66.79 470 | 85.84 467 |
|
| SSC-MVS | | | 76.05 434 | 75.83 437 | 76.72 457 | 84.77 472 | 56.22 486 | 94.32 396 | 88.96 468 | 81.82 435 | 70.52 467 | 88.91 452 | 74.79 367 | 88.71 474 | 33.69 483 | 64.71 473 | 85.23 468 |
|
| test_vis3_rt | | | 72.73 435 | 70.55 438 | 79.27 450 | 80.02 479 | 68.13 473 | 93.92 410 | 74.30 487 | 76.90 458 | 58.99 478 | 73.58 478 | 20.29 486 | 95.37 443 | 84.16 372 | 72.80 459 | 74.31 475 |
|
| LCM-MVSNet | | | 72.55 436 | 69.39 440 | 82.03 448 | 70.81 488 | 65.42 477 | 90.12 460 | 94.36 419 | 55.02 478 | 65.88 472 | 81.72 471 | 24.16 485 | 89.96 469 | 74.32 446 | 68.10 469 | 90.71 461 |
|
| FPMVS | | | 71.27 437 | 69.85 439 | 75.50 458 | 74.64 483 | 59.03 483 | 91.30 449 | 91.50 456 | 58.80 475 | 57.92 479 | 88.28 456 | 29.98 481 | 85.53 478 | 53.43 476 | 82.84 422 | 81.95 471 |
|
| PMMVS2 | | | 70.19 438 | 66.92 442 | 80.01 449 | 76.35 482 | 65.67 476 | 86.22 473 | 87.58 472 | 64.83 474 | 62.38 475 | 80.29 474 | 26.78 483 | 88.49 476 | 63.79 468 | 54.07 479 | 85.88 466 |
|
| dongtai | | | 69.99 439 | 69.33 441 | 71.98 461 | 88.78 459 | 61.64 481 | 89.86 461 | 59.93 491 | 75.67 460 | 74.96 462 | 85.45 467 | 50.19 469 | 81.66 480 | 43.86 479 | 55.27 478 | 72.63 476 |
|
| testf1 | | | 69.31 440 | 66.76 443 | 76.94 455 | 78.61 480 | 61.93 479 | 88.27 470 | 86.11 477 | 55.62 476 | 59.69 476 | 85.31 468 | 20.19 487 | 89.32 470 | 57.62 472 | 69.44 467 | 79.58 472 |
|
| APD_test2 | | | 69.31 440 | 66.76 443 | 76.94 455 | 78.61 480 | 61.93 479 | 88.27 470 | 86.11 477 | 55.62 476 | 59.69 476 | 85.31 468 | 20.19 487 | 89.32 470 | 57.62 472 | 69.44 467 | 79.58 472 |
|
| EGC-MVSNET | | | 68.77 442 | 63.01 448 | 86.07 444 | 92.49 432 | 82.24 413 | 93.96 407 | 90.96 460 | 0.71 489 | 2.62 490 | 90.89 435 | 53.66 465 | 93.46 460 | 57.25 474 | 84.55 403 | 82.51 470 |
|
| Gipuma |  | | 67.86 443 | 65.41 445 | 75.18 459 | 92.66 429 | 73.45 463 | 66.50 481 | 94.52 410 | 53.33 479 | 57.80 480 | 66.07 480 | 30.81 479 | 89.20 472 | 48.15 478 | 78.88 439 | 62.90 480 |
| S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
| test_method | | | 66.11 444 | 64.89 446 | 69.79 462 | 72.62 486 | 35.23 494 | 65.19 482 | 92.83 445 | 20.35 484 | 65.20 473 | 88.08 459 | 43.14 474 | 82.70 479 | 73.12 452 | 63.46 474 | 91.45 457 |
|
| kuosan | | | 65.27 445 | 64.66 447 | 67.11 464 | 83.80 473 | 61.32 482 | 88.53 469 | 60.77 490 | 68.22 471 | 67.67 469 | 80.52 473 | 49.12 470 | 70.76 486 | 29.67 485 | 53.64 480 | 69.26 478 |
|
| ANet_high | | | 63.94 446 | 59.58 449 | 77.02 454 | 61.24 490 | 66.06 475 | 85.66 475 | 87.93 471 | 78.53 454 | 42.94 482 | 71.04 479 | 25.42 484 | 80.71 481 | 52.60 477 | 30.83 483 | 84.28 469 |
|
| PMVS |  | 53.92 22 | 58.58 447 | 55.40 450 | 68.12 463 | 51.00 491 | 48.64 488 | 78.86 478 | 87.10 474 | 46.77 480 | 35.84 486 | 74.28 476 | 8.76 489 | 86.34 477 | 42.07 480 | 73.91 456 | 69.38 477 |
| Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
| E-PMN | | | 53.28 448 | 52.56 452 | 55.43 466 | 74.43 484 | 47.13 489 | 83.63 477 | 76.30 484 | 42.23 481 | 42.59 483 | 62.22 482 | 28.57 482 | 74.40 483 | 31.53 484 | 31.51 482 | 44.78 481 |
|
| MVE |  | 50.73 23 | 53.25 449 | 48.81 454 | 66.58 465 | 65.34 489 | 57.50 484 | 72.49 480 | 70.94 488 | 40.15 483 | 39.28 485 | 63.51 481 | 6.89 491 | 73.48 485 | 38.29 481 | 42.38 481 | 68.76 479 |
| Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
| EMVS | | | 52.08 450 | 51.31 453 | 54.39 467 | 72.62 486 | 45.39 491 | 83.84 476 | 75.51 486 | 41.13 482 | 40.77 484 | 59.65 483 | 30.08 480 | 73.60 484 | 28.31 486 | 29.90 484 | 44.18 482 |
|
| tmp_tt | | | 51.94 451 | 53.82 451 | 46.29 468 | 33.73 492 | 45.30 492 | 78.32 479 | 67.24 489 | 18.02 485 | 50.93 481 | 87.05 465 | 52.99 466 | 53.11 487 | 70.76 460 | 25.29 485 | 40.46 483 |
|
| wuyk23d | | | 25.11 452 | 24.57 456 | 26.74 469 | 73.98 485 | 39.89 493 | 57.88 483 | 9.80 493 | 12.27 486 | 10.39 487 | 6.97 489 | 7.03 490 | 36.44 488 | 25.43 487 | 17.39 486 | 3.89 486 |
|
| cdsmvs_eth3d_5k | | | 23.24 453 | 30.99 455 | 0.00 472 | 0.00 495 | 0.00 497 | 0.00 484 | 97.63 166 | 0.00 490 | 0.00 491 | 96.88 211 | 84.38 204 | 0.00 491 | 0.00 490 | 0.00 489 | 0.00 487 |
|
| testmvs | | | 13.36 454 | 16.33 457 | 4.48 471 | 5.04 493 | 2.26 496 | 93.18 429 | 3.28 494 | 2.70 487 | 8.24 488 | 21.66 485 | 2.29 493 | 2.19 489 | 7.58 488 | 2.96 487 | 9.00 485 |
|
| test123 | | | 13.04 455 | 15.66 458 | 5.18 470 | 4.51 494 | 3.45 495 | 92.50 443 | 1.81 495 | 2.50 488 | 7.58 489 | 20.15 486 | 3.67 492 | 2.18 490 | 7.13 489 | 1.07 488 | 9.90 484 |
|
| ab-mvs-re | | | 8.06 456 | 10.74 459 | 0.00 472 | 0.00 495 | 0.00 497 | 0.00 484 | 0.00 496 | 0.00 490 | 0.00 491 | 96.69 222 | 0.00 494 | 0.00 491 | 0.00 490 | 0.00 489 | 0.00 487 |
|
| pcd_1.5k_mvsjas | | | 7.39 457 | 9.85 460 | 0.00 472 | 0.00 495 | 0.00 497 | 0.00 484 | 0.00 496 | 0.00 490 | 0.00 491 | 0.00 490 | 88.65 109 | 0.00 491 | 0.00 490 | 0.00 489 | 0.00 487 |
|
| mmdepth | | | 0.00 458 | 0.00 461 | 0.00 472 | 0.00 495 | 0.00 497 | 0.00 484 | 0.00 496 | 0.00 490 | 0.00 491 | 0.00 490 | 0.00 494 | 0.00 491 | 0.00 490 | 0.00 489 | 0.00 487 |
|
| monomultidepth | | | 0.00 458 | 0.00 461 | 0.00 472 | 0.00 495 | 0.00 497 | 0.00 484 | 0.00 496 | 0.00 490 | 0.00 491 | 0.00 490 | 0.00 494 | 0.00 491 | 0.00 490 | 0.00 489 | 0.00 487 |
|
| test_blank | | | 0.00 458 | 0.00 461 | 0.00 472 | 0.00 495 | 0.00 497 | 0.00 484 | 0.00 496 | 0.00 490 | 0.00 491 | 0.00 490 | 0.00 494 | 0.00 491 | 0.00 490 | 0.00 489 | 0.00 487 |
|
| uanet_test | | | 0.00 458 | 0.00 461 | 0.00 472 | 0.00 495 | 0.00 497 | 0.00 484 | 0.00 496 | 0.00 490 | 0.00 491 | 0.00 490 | 0.00 494 | 0.00 491 | 0.00 490 | 0.00 489 | 0.00 487 |
|
| DCPMVS | | | 0.00 458 | 0.00 461 | 0.00 472 | 0.00 495 | 0.00 497 | 0.00 484 | 0.00 496 | 0.00 490 | 0.00 491 | 0.00 490 | 0.00 494 | 0.00 491 | 0.00 490 | 0.00 489 | 0.00 487 |
|
| sosnet-low-res | | | 0.00 458 | 0.00 461 | 0.00 472 | 0.00 495 | 0.00 497 | 0.00 484 | 0.00 496 | 0.00 490 | 0.00 491 | 0.00 490 | 0.00 494 | 0.00 491 | 0.00 490 | 0.00 489 | 0.00 487 |
|
| sosnet | | | 0.00 458 | 0.00 461 | 0.00 472 | 0.00 495 | 0.00 497 | 0.00 484 | 0.00 496 | 0.00 490 | 0.00 491 | 0.00 490 | 0.00 494 | 0.00 491 | 0.00 490 | 0.00 489 | 0.00 487 |
|
| uncertanet | | | 0.00 458 | 0.00 461 | 0.00 472 | 0.00 495 | 0.00 497 | 0.00 484 | 0.00 496 | 0.00 490 | 0.00 491 | 0.00 490 | 0.00 494 | 0.00 491 | 0.00 490 | 0.00 489 | 0.00 487 |
|
| Regformer | | | 0.00 458 | 0.00 461 | 0.00 472 | 0.00 495 | 0.00 497 | 0.00 484 | 0.00 496 | 0.00 490 | 0.00 491 | 0.00 490 | 0.00 494 | 0.00 491 | 0.00 490 | 0.00 489 | 0.00 487 |
|
| uanet | | | 0.00 458 | 0.00 461 | 0.00 472 | 0.00 495 | 0.00 497 | 0.00 484 | 0.00 496 | 0.00 490 | 0.00 491 | 0.00 490 | 0.00 494 | 0.00 491 | 0.00 490 | 0.00 489 | 0.00 487 |
|
| MED-MVS test | | | | | 98.00 23 | 99.56 1 | 94.50 35 | 98.69 11 | 98.70 16 | 93.45 118 | 98.73 30 | 98.53 51 | | 99.86 9 | 97.40 50 | 99.58 23 | 99.65 20 |
|
| TestfortrainingZip | | | | | | | | 98.69 11 | | | | | | | | | |
|
| WAC-MVS | | | | | | | 79.53 442 | | | | | | | | 75.56 440 | | |
|
| FOURS1 | | | | | | 99.55 4 | 93.34 71 | 99.29 1 | 98.35 42 | 94.98 46 | 98.49 39 | | | | | | |
|
| MSC_two_6792asdad | | | | | 98.86 1 | 98.67 67 | 96.94 1 | | 97.93 125 | | | | | 99.86 9 | 97.68 33 | 99.67 6 | 99.77 3 |
|
| PC_three_1452 | | | | | | | | | | 90.77 238 | 98.89 26 | 98.28 86 | 96.24 1 | 98.35 280 | 95.76 106 | 99.58 23 | 99.59 32 |
|
| No_MVS | | | | | 98.86 1 | 98.67 67 | 96.94 1 | | 97.93 125 | | | | | 99.86 9 | 97.68 33 | 99.67 6 | 99.77 3 |
|
| test_one_0601 | | | | | | 99.32 27 | 95.20 21 | | 98.25 61 | 95.13 40 | 98.48 40 | 98.87 31 | 95.16 9 | | | | |
|
| eth-test2 | | | | | | 0.00 495 | | | | | | | | | | | |
|
| eth-test | | | | | | 0.00 495 | | | | | | | | | | | |
|
| ZD-MVS | | | | | | 99.05 45 | 94.59 33 | | 98.08 93 | 89.22 294 | 97.03 81 | 98.10 94 | 92.52 42 | 99.65 79 | 94.58 154 | 99.31 72 | |
|
| RE-MVS-def | | | | 96.72 62 | | 99.02 48 | 92.34 108 | 97.98 71 | 98.03 110 | 93.52 115 | 97.43 67 | 98.51 56 | 90.71 81 | | 96.05 94 | 99.26 78 | 99.43 63 |
|
| IU-MVS | | | | | | 99.42 10 | 95.39 12 | | 97.94 124 | 90.40 261 | 98.94 19 | | | | 97.41 49 | 99.66 10 | 99.74 9 |
|
| OPU-MVS | | | | | 98.55 4 | 98.82 61 | 96.86 3 | 98.25 40 | | | | 98.26 87 | 96.04 2 | 99.24 149 | 95.36 120 | 99.59 19 | 99.56 40 |
|
| test_241102_TWO | | | | | | | | | 98.27 55 | 95.13 40 | 98.93 20 | 98.89 28 | 94.99 13 | 99.85 21 | 97.52 42 | 99.65 13 | 99.74 9 |
|
| test_241102_ONE | | | | | | 99.42 10 | 95.30 18 | | 98.27 55 | 95.09 43 | 99.19 13 | 98.81 37 | 95.54 5 | 99.65 79 | | | |
|
| 9.14 | | | | 96.75 61 | | 98.93 56 | | 97.73 115 | 98.23 66 | 91.28 215 | 97.88 55 | 98.44 64 | 93.00 29 | 99.65 79 | 95.76 106 | 99.47 45 | |
|
| save fliter | | | | | | 98.91 58 | 94.28 42 | 97.02 208 | 98.02 113 | 95.35 31 | | | | | | | |
|
| test_0728_THIRD | | | | | | | | | | 94.78 61 | 98.73 30 | 98.87 31 | 95.87 4 | 99.84 26 | 97.45 46 | 99.72 2 | 99.77 3 |
|
| test_0728_SECOND | | | | | 98.51 5 | 99.45 6 | 95.93 6 | 98.21 47 | 98.28 52 | | | | | 99.86 9 | 97.52 42 | 99.67 6 | 99.75 7 |
|
| test0726 | | | | | | 99.45 6 | 95.36 14 | 98.31 32 | 98.29 50 | 94.92 50 | 98.99 18 | 98.92 23 | 95.08 10 | | | | |
|
| GSMVS | | | | | | | | | | | | | | | | | 98.45 185 |
|
| test_part2 | | | | | | 99.28 30 | 95.74 9 | | | | 98.10 48 | | | | | | |
|
| sam_mvs1 | | | | | | | | | | | | | 82.76 240 | | | | 98.45 185 |
|
| sam_mvs | | | | | | | | | | | | | 81.94 261 | | | | |
|
| ambc | | | | | 86.56 442 | 83.60 475 | 70.00 469 | 85.69 474 | 94.97 390 | | 80.60 444 | 88.45 454 | 37.42 476 | 96.84 415 | 82.69 391 | 75.44 452 | 92.86 431 |
|
| MTGPA |  | | | | | | | | 98.08 93 | | | | | | | | |
|
| test_post1 | | | | | | | | 92.81 439 | | | | 16.58 488 | 80.53 288 | 97.68 363 | 86.20 342 | | |
|
| test_post | | | | | | | | | | | | 17.58 487 | 81.76 264 | 98.08 307 | | | |
|
| patchmatchnet-post | | | | | | | | | | | | 90.45 439 | 82.65 245 | 98.10 302 | | | |
|
| GG-mvs-BLEND | | | | | 93.62 314 | 93.69 399 | 89.20 254 | 92.39 444 | 83.33 481 | | 87.98 368 | 89.84 445 | 71.00 393 | 96.87 414 | 82.08 396 | 95.40 243 | 94.80 389 |
|
| MTMP | | | | | | | | 97.86 91 | 82.03 482 | | | | | | | | |
|
| gm-plane-assit | | | | | | 93.22 417 | 78.89 450 | | | 84.82 403 | | 93.52 392 | | 98.64 250 | 87.72 309 | | |
|
| test9_res | | | | | | | | | | | | | | | 94.81 141 | 99.38 64 | 99.45 59 |
|
| TEST9 | | | | | | 98.70 65 | 94.19 46 | 96.41 278 | 98.02 113 | 88.17 332 | 96.03 126 | 97.56 164 | 92.74 36 | 99.59 95 | | | |
|
| test_8 | | | | | | 98.67 67 | 94.06 53 | 96.37 286 | 98.01 116 | 88.58 319 | 95.98 130 | 97.55 166 | 92.73 37 | 99.58 98 | | | |
|
| agg_prior2 | | | | | | | | | | | | | | | 93.94 168 | 99.38 64 | 99.50 52 |
|
| agg_prior | | | | | | 98.67 67 | 93.79 59 | | 98.00 117 | | 95.68 143 | | | 99.57 105 | | | |
|
| TestCases | | | | | 93.98 288 | 97.94 130 | 86.64 329 | | 95.54 363 | 85.38 392 | 85.49 408 | 96.77 216 | 70.28 399 | 99.15 163 | 80.02 415 | 92.87 290 | 96.15 308 |
|
| test_prior4 | | | | | | | 93.66 62 | 96.42 277 | | | | | | | | | |
|
| test_prior2 | | | | | | | | 96.35 287 | | 92.80 155 | 96.03 126 | 97.59 161 | 92.01 50 | | 95.01 128 | 99.38 64 | |
|
| test_prior | | | | | 97.23 69 | 98.67 67 | 92.99 83 | | 98.00 117 | | | | | 99.41 132 | | | 99.29 75 |
|
| 旧先验2 | | | | | | | | 95.94 318 | | 81.66 436 | 97.34 70 | | | 98.82 209 | 92.26 201 | | |
|
| æ–°å‡ ä½•2 | | | | | | | | 95.79 329 | | | | | | | | | |
|
| æ–°å‡ ä½•1 | | | | | 97.32 62 | 98.60 74 | 93.59 63 | | 97.75 149 | 81.58 437 | 95.75 138 | 97.85 126 | 90.04 88 | 99.67 77 | 86.50 338 | 99.13 98 | 98.69 162 |
|
| 旧先验1 | | | | | | 98.38 89 | 93.38 68 | | 97.75 149 | | | 98.09 96 | 92.30 48 | | | 99.01 108 | 99.16 85 |
|
| æ— å…ˆéªŒ | | | | | | | | 95.79 329 | 97.87 132 | 83.87 415 | | | | 99.65 79 | 87.68 315 | | 98.89 136 |
|
| 原ACMM2 | | | | | | | | 95.67 335 | | | | | | | | | |
|
| 原ACMM1 | | | | | 96.38 125 | 98.59 75 | 91.09 168 | | 97.89 128 | 87.41 358 | 95.22 160 | 97.68 148 | 90.25 85 | 99.54 110 | 87.95 303 | 99.12 100 | 98.49 180 |
|
| test222 | | | | | | 98.24 100 | 92.21 114 | 95.33 354 | 97.60 171 | 79.22 450 | 95.25 158 | 97.84 128 | 88.80 106 | | | 99.15 95 | 98.72 159 |
|
| testdata2 | | | | | | | | | | | | | | 99.67 77 | 85.96 350 | | |
|
| segment_acmp | | | | | | | | | | | | | 92.89 33 | | | | |
|
| testdata | | | | | 95.46 204 | 98.18 111 | 88.90 265 | | 97.66 160 | 82.73 428 | 97.03 81 | 98.07 97 | 90.06 87 | 98.85 205 | 89.67 267 | 98.98 109 | 98.64 165 |
|
| testdata1 | | | | | | | | 95.26 361 | | 93.10 137 | | | | | | | |
|
| test12 | | | | | 97.65 47 | 98.46 79 | 94.26 43 | | 97.66 160 | | 95.52 150 | | 90.89 78 | 99.46 126 | | 99.25 80 | 99.22 82 |
|
| plane_prior7 | | | | | | 96.21 269 | 89.98 213 | | | | | | | | | | |
|
| plane_prior6 | | | | | | 96.10 287 | 90.00 209 | | | | | | 81.32 271 | | | | |
|
| plane_prior5 | | | | | | | | | 97.51 191 | | | | | 98.60 255 | 93.02 193 | 92.23 301 | 95.86 316 |
|
| plane_prior4 | | | | | | | | | | | | 96.64 225 | | | | | |
|
| plane_prior3 | | | | | | | 90.00 209 | | | 94.46 78 | 91.34 271 | | | | | | |
|
| plane_prior2 | | | | | | | | 97.74 113 | | 94.85 53 | | | | | | | |
|
| plane_prior1 | | | | | | 96.14 282 | | | | | | | | | | | |
|
| plane_prior | | | | | | | 89.99 211 | 97.24 188 | | 94.06 92 | | | | | | 92.16 305 | |
|
| n2 | | | | | | | | | 0.00 496 | | | | | | | | |
|
| nn | | | | | | | | | 0.00 496 | | | | | | | | |
|
| door-mid | | | | | | | | | 91.06 459 | | | | | | | | |
|
| lessismore_v0 | | | | | 90.45 411 | 91.96 439 | 79.09 449 | | 87.19 473 | | 80.32 446 | 94.39 346 | 66.31 433 | 97.55 376 | 84.00 376 | 76.84 445 | 94.70 397 |
|
| LGP-MVS_train | | | | | 94.10 280 | 96.16 279 | 88.26 285 | | 97.46 202 | 91.29 212 | 90.12 301 | 97.16 190 | 79.05 316 | 98.73 233 | 92.25 203 | 91.89 309 | 95.31 353 |
|
| test11 | | | | | | | | | 97.88 130 | | | | | | | | |
|
| door | | | | | | | | | 91.13 458 | | | | | | | | |
|
| HQP5-MVS | | | | | | | 89.33 247 | | | | | | | | | | |
|
| HQP-NCC | | | | | | 95.86 295 | | 96.65 258 | | 93.55 109 | 90.14 295 | | | | | | |
|
| ACMP_Plane | | | | | | 95.86 295 | | 96.65 258 | | 93.55 109 | 90.14 295 | | | | | | |
|
| BP-MVS | | | | | | | | | | | | | | | 92.13 209 | | |
|
| HQP4-MVS | | | | | | | | | | | 90.14 295 | | | 98.50 265 | | | 95.78 324 |
|
| HQP3-MVS | | | | | | | | | 97.39 219 | | | | | | | 92.10 306 | |
|
| HQP2-MVS | | | | | | | | | | | | | 80.95 276 | | | | |
|
| NP-MVS | | | | | | 95.99 293 | 89.81 221 | | | | | 95.87 268 | | | | | |
|
| MDTV_nov1_ep13_2view | | | | | | | 70.35 468 | 93.10 434 | | 83.88 414 | 93.55 212 | | 82.47 249 | | 86.25 341 | | 98.38 193 |
|
| MDTV_nov1_ep13 | | | | 90.76 289 | | 95.22 337 | 80.33 431 | 93.03 435 | 95.28 375 | 88.14 335 | 92.84 235 | 93.83 376 | 81.34 270 | 98.08 307 | 82.86 385 | 94.34 263 | |
|
| ACMMP++_ref | | | | | | | | | | | | | | | | 90.30 335 | |
|
| ACMMP++ | | | | | | | | | | | | | | | | 91.02 324 | |
|
| Test By Simon | | | | | | | | | | | | | 88.73 108 | | | | |
|
| ITE_SJBPF | | | | | 92.43 357 | 95.34 326 | 85.37 367 | | 95.92 339 | 91.47 205 | 87.75 371 | 96.39 243 | 71.00 393 | 97.96 330 | 82.36 394 | 89.86 338 | 93.97 418 |
|
| DeepMVS_CX |  | | | | 74.68 460 | 90.84 445 | 64.34 478 | | 81.61 483 | 65.34 473 | 67.47 471 | 88.01 460 | 48.60 471 | 80.13 482 | 62.33 470 | 73.68 457 | 79.58 472 |
|