| LCM-MVSNet | | | 95.70 1 | 96.40 1 | 93.61 3 | 98.67 1 | 85.39 37 | 95.54 5 | 97.36 1 | 96.97 1 | 99.04 1 | 99.05 1 | 96.61 1 | 95.92 16 | 85.07 71 | 99.27 1 | 99.54 1 |
|
| mamv4 | | | 95.37 2 | 94.51 2 | 97.96 1 | 96.31 10 | 98.41 1 | 91.05 51 | 97.23 2 | 95.32 2 | 99.01 2 | 97.26 9 | 80.16 151 | 98.99 1 | 95.15 1 | 99.14 2 | 96.47 35 |
|
| TDRefinement | | | 93.52 3 | 93.39 5 | 93.88 2 | 95.94 15 | 90.26 4 | 95.70 4 | 96.46 3 | 90.58 9 | 92.86 54 | 96.29 23 | 88.16 36 | 94.17 106 | 86.07 56 | 98.48 18 | 97.22 18 |
|
| LTVRE_ROB | | 86.10 1 | 93.04 4 | 93.44 4 | 91.82 22 | 93.73 69 | 85.72 34 | 96.79 1 | 95.51 10 | 88.86 16 | 95.63 10 | 96.99 13 | 84.81 80 | 93.16 150 | 91.10 2 | 97.53 81 | 96.58 33 |
| 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 |
| reproduce_model | | | 92.89 5 | 93.18 8 | 92.01 13 | 94.20 54 | 88.23 9 | 92.87 13 | 94.32 22 | 90.25 11 | 95.65 9 | 95.74 34 | 87.75 43 | 95.72 39 | 89.60 5 | 98.27 28 | 92.08 237 |
|
| reproduce-ours | | | 92.86 6 | 93.22 6 | 91.76 23 | 94.39 46 | 87.71 11 | 92.40 28 | 94.38 20 | 89.82 13 | 95.51 12 | 95.49 43 | 89.64 22 | 95.82 29 | 89.13 7 | 98.26 30 | 91.76 248 |
|
| our_new_method | | | 92.86 6 | 93.22 6 | 91.76 23 | 94.39 46 | 87.71 11 | 92.40 28 | 94.38 20 | 89.82 13 | 95.51 12 | 95.49 43 | 89.64 22 | 95.82 29 | 89.13 7 | 98.26 30 | 91.76 248 |
|
| HPM-MVS_fast | | | 92.50 8 | 92.54 10 | 92.37 6 | 95.93 16 | 85.81 33 | 92.99 12 | 94.23 28 | 85.21 44 | 92.51 62 | 95.13 53 | 90.65 10 | 95.34 59 | 88.06 16 | 98.15 39 | 95.95 46 |
|
| lecture | | | 92.43 9 | 93.50 3 | 89.21 66 | 94.43 44 | 79.31 84 | 92.69 19 | 95.72 8 | 88.48 22 | 94.43 20 | 95.73 35 | 91.34 4 | 94.68 82 | 90.26 4 | 98.44 20 | 93.63 147 |
|
| SR-MVS-dyc-post | | | 92.41 10 | 92.41 11 | 92.39 5 | 94.13 60 | 88.95 6 | 92.87 13 | 94.16 33 | 88.75 18 | 93.79 33 | 94.43 77 | 88.83 27 | 95.51 50 | 87.16 38 | 97.60 75 | 92.73 193 |
|
| SR-MVS | | | 92.23 11 | 92.34 12 | 91.91 17 | 94.89 38 | 87.85 10 | 92.51 25 | 93.87 52 | 88.20 24 | 93.24 43 | 94.02 101 | 90.15 17 | 95.67 41 | 86.82 43 | 97.34 85 | 92.19 232 |
|
| HPM-MVS |  | | 92.13 12 | 92.20 14 | 91.91 17 | 95.58 26 | 84.67 46 | 93.51 8 | 94.85 16 | 82.88 72 | 91.77 76 | 93.94 109 | 90.55 13 | 95.73 38 | 88.50 12 | 98.23 33 | 95.33 62 |
| Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
| APD-MVS_3200maxsize | | | 92.05 13 | 92.24 13 | 91.48 25 | 93.02 88 | 85.17 39 | 92.47 27 | 95.05 15 | 87.65 28 | 93.21 47 | 94.39 82 | 90.09 18 | 95.08 70 | 86.67 45 | 97.60 75 | 94.18 115 |
|
| COLMAP_ROB |  | 83.01 3 | 91.97 14 | 91.95 15 | 92.04 11 | 93.68 70 | 86.15 24 | 93.37 10 | 95.10 14 | 90.28 10 | 92.11 68 | 95.03 55 | 89.75 21 | 94.93 74 | 79.95 134 | 98.27 28 | 95.04 75 |
| Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
| ACMMP |  | | 91.91 15 | 91.87 20 | 92.03 12 | 95.53 27 | 85.91 28 | 93.35 11 | 94.16 33 | 82.52 75 | 92.39 65 | 94.14 94 | 89.15 26 | 95.62 42 | 87.35 33 | 98.24 32 | 94.56 91 |
| 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 |
| mPP-MVS | | | 91.69 16 | 91.47 27 | 92.37 6 | 96.04 13 | 88.48 8 | 92.72 18 | 92.60 117 | 83.09 69 | 91.54 78 | 94.25 88 | 87.67 46 | 95.51 50 | 87.21 37 | 98.11 40 | 93.12 176 |
|
| CP-MVS | | | 91.67 17 | 91.58 24 | 91.96 14 | 95.29 31 | 87.62 13 | 93.38 9 | 93.36 74 | 83.16 68 | 91.06 88 | 94.00 102 | 88.26 33 | 95.71 40 | 87.28 36 | 98.39 23 | 92.55 207 |
|
| XVS | | | 91.54 18 | 91.36 29 | 92.08 9 | 95.64 24 | 86.25 22 | 92.64 20 | 93.33 78 | 85.07 45 | 89.99 111 | 94.03 100 | 86.57 59 | 95.80 31 | 87.35 33 | 97.62 73 | 94.20 112 |
|
| MTAPA | | | 91.52 19 | 91.60 23 | 91.29 30 | 96.59 4 | 86.29 21 | 92.02 38 | 91.81 144 | 84.07 55 | 92.00 71 | 94.40 81 | 86.63 58 | 95.28 62 | 88.59 11 | 98.31 26 | 92.30 224 |
|
| UA-Net | | | 91.49 20 | 91.53 25 | 91.39 27 | 94.98 35 | 82.95 58 | 93.52 7 | 92.79 108 | 88.22 23 | 88.53 148 | 97.64 6 | 83.45 94 | 94.55 90 | 86.02 60 | 98.60 13 | 96.67 30 |
|
| ACMMPR | | | 91.49 20 | 91.35 31 | 91.92 16 | 95.74 20 | 85.88 30 | 92.58 23 | 93.25 84 | 81.99 78 | 91.40 80 | 94.17 93 | 87.51 47 | 95.87 20 | 87.74 22 | 97.76 60 | 93.99 123 |
|
| LPG-MVS_test | | | 91.47 22 | 91.68 21 | 90.82 37 | 94.75 41 | 81.69 63 | 90.00 67 | 94.27 25 | 82.35 76 | 93.67 38 | 94.82 61 | 91.18 5 | 95.52 48 | 85.36 67 | 98.73 7 | 95.23 67 |
|
| region2R | | | 91.44 23 | 91.30 35 | 91.87 19 | 95.75 19 | 85.90 29 | 92.63 22 | 93.30 82 | 81.91 80 | 90.88 95 | 94.21 89 | 87.75 43 | 95.87 20 | 87.60 27 | 97.71 63 | 93.83 132 |
|
| HFP-MVS | | | 91.30 24 | 91.39 28 | 91.02 33 | 95.43 29 | 84.66 47 | 92.58 23 | 93.29 83 | 81.99 78 | 91.47 79 | 93.96 106 | 88.35 32 | 95.56 45 | 87.74 22 | 97.74 62 | 92.85 190 |
|
| ZNCC-MVS | | | 91.26 25 | 91.34 32 | 91.01 34 | 95.73 21 | 83.05 56 | 92.18 32 | 94.22 30 | 80.14 101 | 91.29 84 | 93.97 103 | 87.93 42 | 95.87 20 | 88.65 10 | 97.96 51 | 94.12 119 |
|
| APDe-MVS |  | | 91.22 26 | 91.92 16 | 89.14 68 | 92.97 90 | 78.04 96 | 92.84 16 | 94.14 37 | 83.33 66 | 93.90 29 | 95.73 35 | 88.77 28 | 96.41 3 | 87.60 27 | 97.98 48 | 92.98 186 |
| Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition |
| PGM-MVS | | | 91.20 27 | 90.95 45 | 91.93 15 | 95.67 23 | 85.85 31 | 90.00 67 | 93.90 49 | 80.32 98 | 91.74 77 | 94.41 80 | 88.17 35 | 95.98 13 | 86.37 49 | 97.99 46 | 93.96 125 |
|
| SteuartSystems-ACMMP | | | 91.16 28 | 91.36 29 | 90.55 41 | 93.91 65 | 80.97 70 | 91.49 45 | 93.48 72 | 82.82 73 | 92.60 61 | 93.97 103 | 88.19 34 | 96.29 6 | 87.61 26 | 98.20 36 | 94.39 106 |
| Skip Steuart: Steuart Systems R&D Blog. |
| MP-MVS |  | | 91.14 29 | 90.91 46 | 91.83 20 | 96.18 11 | 86.88 17 | 92.20 31 | 93.03 98 | 82.59 74 | 88.52 149 | 94.37 83 | 86.74 57 | 95.41 57 | 86.32 50 | 98.21 34 | 93.19 171 |
| Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
| GST-MVS | | | 90.96 30 | 91.01 42 | 90.82 37 | 95.45 28 | 82.73 59 | 91.75 43 | 93.74 59 | 80.98 91 | 91.38 81 | 93.80 113 | 87.20 51 | 95.80 31 | 87.10 40 | 97.69 65 | 93.93 126 |
|
| MP-MVS-pluss | | | 90.81 31 | 91.08 39 | 89.99 50 | 95.97 14 | 79.88 77 | 88.13 110 | 94.51 19 | 75.79 160 | 92.94 51 | 94.96 56 | 88.36 31 | 95.01 72 | 90.70 3 | 98.40 22 | 95.09 74 |
| MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
| ACMH+ | | 77.89 11 | 90.73 32 | 91.50 26 | 88.44 83 | 93.00 89 | 76.26 122 | 89.65 80 | 95.55 9 | 87.72 27 | 93.89 31 | 94.94 57 | 91.62 3 | 93.44 141 | 78.35 156 | 98.76 4 | 95.61 55 |
|
| ACMMP_NAP | | | 90.65 33 | 91.07 41 | 89.42 62 | 95.93 16 | 79.54 82 | 89.95 71 | 93.68 64 | 77.65 137 | 91.97 72 | 94.89 58 | 88.38 30 | 95.45 55 | 89.27 6 | 97.87 56 | 93.27 166 |
|
| ACMM | | 79.39 9 | 90.65 33 | 90.99 43 | 89.63 58 | 95.03 34 | 83.53 51 | 89.62 81 | 93.35 77 | 79.20 114 | 93.83 32 | 93.60 123 | 90.81 8 | 92.96 157 | 85.02 74 | 98.45 19 | 92.41 214 |
| Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
| LS3D | | | 90.60 35 | 90.34 55 | 91.38 28 | 89.03 204 | 84.23 49 | 93.58 6 | 94.68 18 | 90.65 8 | 90.33 105 | 93.95 108 | 84.50 82 | 95.37 58 | 80.87 124 | 95.50 158 | 94.53 95 |
|
| ACMP | | 79.16 10 | 90.54 36 | 90.60 53 | 90.35 45 | 94.36 51 | 80.98 69 | 89.16 92 | 94.05 42 | 79.03 118 | 92.87 53 | 93.74 118 | 90.60 12 | 95.21 65 | 82.87 102 | 98.76 4 | 94.87 79 |
| Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
| DPE-MVS |  | | 90.53 37 | 91.08 39 | 88.88 71 | 93.38 79 | 78.65 90 | 89.15 93 | 94.05 42 | 84.68 49 | 93.90 29 | 94.11 96 | 88.13 37 | 96.30 5 | 84.51 84 | 97.81 58 | 91.70 252 |
| Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025 |
| MED-MVS | | | 90.48 38 | 91.14 36 | 88.50 80 | 94.38 48 | 76.12 126 | 92.12 33 | 93.85 53 | 83.72 60 | 93.24 43 | 93.18 132 | 87.06 52 | 95.85 24 | 84.99 75 | 97.69 65 | 93.54 157 |
|
| SED-MVS | | | 90.46 39 | 91.64 22 | 86.93 109 | 94.18 55 | 72.65 156 | 90.47 60 | 93.69 62 | 83.77 58 | 94.11 27 | 94.27 84 | 90.28 15 | 95.84 27 | 86.03 57 | 97.92 52 | 92.29 226 |
|
| SMA-MVS |  | | 90.31 40 | 90.48 54 | 89.83 55 | 95.31 30 | 79.52 83 | 90.98 52 | 93.24 85 | 75.37 169 | 92.84 55 | 95.28 49 | 85.58 72 | 96.09 8 | 87.92 18 | 97.76 60 | 93.88 129 |
| 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 |
| SF-MVS | | | 90.27 41 | 90.80 48 | 88.68 78 | 92.86 94 | 77.09 111 | 91.19 49 | 95.74 6 | 81.38 86 | 92.28 67 | 93.80 113 | 86.89 56 | 94.64 85 | 85.52 66 | 97.51 82 | 94.30 111 |
|
| v7n | | | 90.13 42 | 90.96 44 | 87.65 99 | 91.95 122 | 71.06 190 | 89.99 69 | 93.05 95 | 86.53 35 | 94.29 23 | 96.27 24 | 82.69 103 | 94.08 109 | 86.25 53 | 97.63 71 | 97.82 8 |
|
| ME-MVS | | | 90.09 43 | 90.66 51 | 88.38 85 | 92.82 97 | 76.12 126 | 89.40 90 | 93.70 61 | 83.72 60 | 92.39 65 | 93.18 132 | 88.02 40 | 95.47 53 | 84.99 75 | 97.69 65 | 93.54 157 |
|
| PMVS |  | 80.48 6 | 90.08 44 | 90.66 51 | 88.34 87 | 96.71 3 | 92.97 2 | 90.31 64 | 89.57 222 | 88.51 21 | 90.11 107 | 95.12 54 | 90.98 7 | 88.92 281 | 77.55 170 | 97.07 92 | 83.13 409 |
| Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
| DVP-MVS++ | | | 90.07 45 | 91.09 38 | 87.00 107 | 91.55 140 | 72.64 158 | 96.19 2 | 94.10 40 | 85.33 42 | 93.49 40 | 94.64 69 | 81.12 139 | 95.88 18 | 87.41 31 | 95.94 138 | 92.48 210 |
|
| DVP-MVS |  | | 90.06 46 | 91.32 33 | 86.29 121 | 94.16 58 | 72.56 162 | 90.54 57 | 91.01 172 | 83.61 63 | 93.75 35 | 94.65 66 | 89.76 19 | 95.78 35 | 86.42 47 | 97.97 49 | 90.55 289 |
| 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 |
| PS-CasMVS | | | 90.06 46 | 91.92 16 | 84.47 173 | 96.56 6 | 58.83 362 | 89.04 94 | 92.74 110 | 91.40 6 | 96.12 5 | 96.06 30 | 87.23 50 | 95.57 44 | 79.42 144 | 98.74 6 | 99.00 2 |
|
| PEN-MVS | | | 90.03 48 | 91.88 19 | 84.48 172 | 96.57 5 | 58.88 359 | 88.95 95 | 93.19 87 | 91.62 5 | 96.01 7 | 96.16 28 | 87.02 54 | 95.60 43 | 78.69 152 | 98.72 9 | 98.97 3 |
|
| OurMVSNet-221017-0 | | | 90.01 49 | 89.74 60 | 90.83 36 | 93.16 86 | 80.37 74 | 91.91 41 | 93.11 91 | 81.10 89 | 95.32 14 | 97.24 10 | 72.94 255 | 94.85 76 | 85.07 71 | 97.78 59 | 97.26 16 |
|
| DTE-MVSNet | | | 89.98 50 | 91.91 18 | 84.21 182 | 96.51 7 | 57.84 370 | 88.93 96 | 92.84 106 | 91.92 4 | 96.16 4 | 96.23 25 | 86.95 55 | 95.99 12 | 79.05 148 | 98.57 15 | 98.80 6 |
|
| XVG-ACMP-BASELINE | | | 89.98 50 | 89.84 58 | 90.41 43 | 94.91 37 | 84.50 48 | 89.49 86 | 93.98 44 | 79.68 106 | 92.09 69 | 93.89 111 | 83.80 89 | 93.10 153 | 82.67 106 | 98.04 41 | 93.64 146 |
|
| TestfortrainingZip a | | | 89.97 52 | 90.77 49 | 87.58 100 | 94.38 48 | 73.21 150 | 92.12 33 | 93.85 53 | 77.53 141 | 93.24 43 | 93.18 132 | 87.06 52 | 95.85 24 | 87.89 19 | 97.69 65 | 93.68 141 |
|
| 3Dnovator+ | | 83.92 2 | 89.97 52 | 89.66 61 | 90.92 35 | 91.27 149 | 81.66 66 | 91.25 47 | 94.13 38 | 88.89 15 | 88.83 140 | 94.26 87 | 77.55 180 | 95.86 23 | 84.88 78 | 95.87 144 | 95.24 66 |
|
| WR-MVS_H | | | 89.91 54 | 91.31 34 | 85.71 138 | 96.32 9 | 62.39 301 | 89.54 84 | 93.31 81 | 90.21 12 | 95.57 11 | 95.66 38 | 81.42 136 | 95.90 17 | 80.94 123 | 98.80 3 | 98.84 5 |
|
| OPM-MVS | | | 89.80 55 | 89.97 56 | 89.27 64 | 94.76 40 | 79.86 78 | 86.76 137 | 92.78 109 | 78.78 121 | 92.51 62 | 93.64 122 | 88.13 37 | 93.84 120 | 84.83 80 | 97.55 78 | 94.10 120 |
| Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS). |
| mvs_tets | | | 89.78 56 | 89.27 67 | 91.30 29 | 93.51 73 | 84.79 44 | 89.89 73 | 90.63 182 | 70.00 258 | 94.55 19 | 96.67 18 | 87.94 41 | 93.59 132 | 84.27 86 | 95.97 134 | 95.52 56 |
|
| anonymousdsp | | | 89.73 57 | 88.88 77 | 92.27 8 | 89.82 185 | 86.67 18 | 90.51 59 | 90.20 204 | 69.87 259 | 95.06 15 | 96.14 29 | 84.28 85 | 93.07 154 | 87.68 24 | 96.34 115 | 97.09 20 |
|
| test_djsdf | | | 89.62 58 | 89.01 71 | 91.45 26 | 92.36 107 | 82.98 57 | 91.98 39 | 90.08 207 | 71.54 236 | 94.28 25 | 96.54 20 | 81.57 134 | 94.27 96 | 86.26 51 | 96.49 109 | 97.09 20 |
|
| XVG-OURS-SEG-HR | | | 89.59 59 | 89.37 65 | 90.28 46 | 94.47 43 | 85.95 27 | 86.84 133 | 93.91 48 | 80.07 102 | 86.75 198 | 93.26 129 | 93.64 2 | 90.93 218 | 84.60 83 | 90.75 317 | 93.97 124 |
|
| APD-MVS |  | | 89.54 60 | 89.63 62 | 89.26 65 | 92.57 100 | 81.34 68 | 90.19 66 | 93.08 94 | 80.87 93 | 91.13 86 | 93.19 131 | 86.22 66 | 95.97 14 | 82.23 112 | 97.18 90 | 90.45 291 |
| Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
| jajsoiax | | | 89.41 61 | 88.81 80 | 91.19 32 | 93.38 79 | 84.72 45 | 89.70 76 | 90.29 201 | 69.27 266 | 94.39 21 | 96.38 22 | 86.02 69 | 93.52 137 | 83.96 88 | 95.92 140 | 95.34 60 |
|
| CPTT-MVS | | | 89.39 62 | 88.98 73 | 90.63 40 | 95.09 33 | 86.95 16 | 92.09 37 | 92.30 126 | 79.74 105 | 87.50 182 | 92.38 168 | 81.42 136 | 93.28 146 | 83.07 98 | 97.24 88 | 91.67 253 |
|
| ACMH | | 76.49 14 | 89.34 63 | 91.14 36 | 83.96 190 | 92.50 103 | 70.36 199 | 89.55 82 | 93.84 56 | 81.89 81 | 94.70 17 | 95.44 45 | 90.69 9 | 88.31 299 | 83.33 94 | 98.30 27 | 93.20 170 |
| Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
| testf1 | | | 89.30 64 | 89.12 68 | 89.84 53 | 88.67 215 | 85.64 35 | 90.61 55 | 93.17 88 | 86.02 38 | 93.12 48 | 95.30 47 | 84.94 77 | 89.44 273 | 74.12 221 | 96.10 129 | 94.45 100 |
|
| APD_test2 | | | 89.30 64 | 89.12 68 | 89.84 53 | 88.67 215 | 85.64 35 | 90.61 55 | 93.17 88 | 86.02 38 | 93.12 48 | 95.30 47 | 84.94 77 | 89.44 273 | 74.12 221 | 96.10 129 | 94.45 100 |
|
| CP-MVSNet | | | 89.27 66 | 90.91 46 | 84.37 174 | 96.34 8 | 58.61 365 | 88.66 103 | 92.06 133 | 90.78 7 | 95.67 8 | 95.17 52 | 81.80 131 | 95.54 47 | 79.00 149 | 98.69 10 | 98.95 4 |
|
| XVG-OURS | | | 89.18 67 | 88.83 79 | 90.23 47 | 94.28 52 | 86.11 26 | 85.91 153 | 93.60 67 | 80.16 100 | 89.13 136 | 93.44 125 | 83.82 88 | 90.98 215 | 83.86 90 | 95.30 166 | 93.60 150 |
|
| DeepC-MVS | | 82.31 4 | 89.15 68 | 89.08 70 | 89.37 63 | 93.64 71 | 79.07 86 | 88.54 106 | 94.20 31 | 73.53 194 | 89.71 119 | 94.82 61 | 85.09 76 | 95.77 37 | 84.17 87 | 98.03 43 | 93.26 168 |
| Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
| UniMVSNet_ETH3D | | | 89.12 69 | 90.72 50 | 84.31 180 | 97.00 2 | 64.33 272 | 89.67 79 | 88.38 242 | 88.84 17 | 94.29 23 | 97.57 7 | 90.48 14 | 91.26 206 | 72.57 252 | 97.65 70 | 97.34 15 |
|
| MSP-MVS | | | 89.08 70 | 88.16 87 | 91.83 20 | 95.76 18 | 86.14 25 | 92.75 17 | 93.90 49 | 78.43 126 | 89.16 134 | 92.25 177 | 72.03 269 | 96.36 4 | 88.21 13 | 90.93 309 | 92.98 186 |
| 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 |
| SD-MVS | | | 88.96 71 | 89.88 57 | 86.22 125 | 91.63 134 | 77.07 112 | 89.82 74 | 93.77 58 | 78.90 119 | 92.88 52 | 92.29 175 | 86.11 67 | 90.22 246 | 86.24 54 | 97.24 88 | 91.36 261 |
| 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 |
| HPM-MVS++ |  | | 88.93 72 | 88.45 83 | 90.38 44 | 94.92 36 | 85.85 31 | 89.70 76 | 91.27 164 | 78.20 129 | 86.69 202 | 92.28 176 | 80.36 149 | 95.06 71 | 86.17 55 | 96.49 109 | 90.22 295 |
|
| Elysia | | | 88.71 73 | 88.89 75 | 88.19 90 | 91.26 150 | 72.96 152 | 88.10 111 | 93.59 68 | 84.31 51 | 90.42 100 | 94.10 97 | 74.07 232 | 94.82 77 | 88.19 14 | 95.92 140 | 96.80 27 |
|
| StellarMVS | | | 88.71 73 | 88.89 75 | 88.19 90 | 91.26 150 | 72.96 152 | 88.10 111 | 93.59 68 | 84.31 51 | 90.42 100 | 94.10 97 | 74.07 232 | 94.82 77 | 88.19 14 | 95.92 140 | 96.80 27 |
|
| test_0402 | | | 88.65 75 | 89.58 64 | 85.88 134 | 92.55 101 | 72.22 170 | 84.01 202 | 89.44 225 | 88.63 20 | 94.38 22 | 95.77 33 | 86.38 65 | 93.59 132 | 79.84 135 | 95.21 167 | 91.82 246 |
|
| DP-MVS | | | 88.60 76 | 89.01 71 | 87.36 102 | 91.30 147 | 77.50 104 | 87.55 119 | 92.97 102 | 87.95 26 | 89.62 123 | 92.87 151 | 84.56 81 | 93.89 117 | 77.65 168 | 96.62 104 | 90.70 281 |
|
| APD_test1 | | | 88.40 77 | 87.91 89 | 89.88 52 | 89.50 191 | 86.65 20 | 89.98 70 | 91.91 139 | 84.26 53 | 90.87 96 | 93.92 110 | 82.18 118 | 89.29 277 | 73.75 229 | 94.81 186 | 93.70 140 |
|
| Anonymous20231211 | | | 88.40 77 | 89.62 63 | 84.73 164 | 90.46 170 | 65.27 261 | 88.86 97 | 93.02 99 | 87.15 30 | 93.05 50 | 97.10 11 | 82.28 116 | 92.02 183 | 76.70 180 | 97.99 46 | 96.88 26 |
|
| PS-MVSNAJss | | | 88.31 79 | 87.90 90 | 89.56 60 | 93.31 81 | 77.96 99 | 87.94 115 | 91.97 136 | 70.73 248 | 94.19 26 | 96.67 18 | 76.94 194 | 94.57 88 | 83.07 98 | 96.28 118 | 96.15 38 |
|
| OMC-MVS | | | 88.19 80 | 87.52 94 | 90.19 48 | 91.94 124 | 81.68 65 | 87.49 122 | 93.17 88 | 76.02 154 | 88.64 145 | 91.22 217 | 84.24 86 | 93.37 144 | 77.97 166 | 97.03 93 | 95.52 56 |
|
| CS-MVS | | | 88.14 81 | 87.67 93 | 89.54 61 | 89.56 189 | 79.18 85 | 90.47 60 | 94.77 17 | 79.37 112 | 84.32 269 | 89.33 284 | 83.87 87 | 94.53 91 | 82.45 108 | 94.89 182 | 94.90 77 |
|
| TSAR-MVS + MP. | | | 88.14 81 | 87.82 91 | 89.09 69 | 95.72 22 | 76.74 115 | 92.49 26 | 91.19 167 | 67.85 293 | 86.63 203 | 94.84 60 | 79.58 157 | 95.96 15 | 87.62 25 | 94.50 195 | 94.56 91 |
| Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition |
| tt0805 | | | 88.09 83 | 89.79 59 | 82.98 221 | 93.26 83 | 63.94 276 | 91.10 50 | 89.64 219 | 85.07 45 | 90.91 92 | 91.09 223 | 89.16 25 | 91.87 188 | 82.03 113 | 95.87 144 | 93.13 173 |
|
| EC-MVSNet | | | 88.01 84 | 88.32 86 | 87.09 104 | 89.28 196 | 72.03 173 | 90.31 64 | 96.31 4 | 80.88 92 | 85.12 244 | 89.67 277 | 84.47 83 | 95.46 54 | 82.56 107 | 96.26 121 | 93.77 138 |
|
| RPSCF | | | 88.00 85 | 86.93 108 | 91.22 31 | 90.08 178 | 89.30 5 | 89.68 78 | 91.11 168 | 79.26 113 | 89.68 120 | 94.81 64 | 82.44 107 | 87.74 310 | 76.54 185 | 88.74 353 | 96.61 32 |
|
| AllTest | | | 87.97 86 | 87.40 98 | 89.68 56 | 91.59 135 | 83.40 52 | 89.50 85 | 95.44 11 | 79.47 108 | 88.00 164 | 93.03 142 | 82.66 104 | 91.47 196 | 70.81 266 | 96.14 126 | 94.16 116 |
|
| TranMVSNet+NR-MVSNet | | | 87.86 87 | 88.76 81 | 85.18 150 | 94.02 63 | 64.13 273 | 84.38 194 | 91.29 160 | 84.88 48 | 92.06 70 | 93.84 112 | 86.45 62 | 93.73 122 | 73.22 243 | 98.66 11 | 97.69 9 |
|
| nrg030 | | | 87.85 88 | 88.49 82 | 85.91 132 | 90.07 180 | 69.73 207 | 87.86 116 | 94.20 31 | 74.04 186 | 92.70 60 | 94.66 65 | 85.88 70 | 91.50 195 | 79.72 137 | 97.32 86 | 96.50 34 |
|
| CNVR-MVS | | | 87.81 89 | 87.68 92 | 88.21 89 | 92.87 92 | 77.30 110 | 85.25 171 | 91.23 165 | 77.31 144 | 87.07 192 | 91.47 207 | 82.94 99 | 94.71 81 | 84.67 82 | 96.27 120 | 92.62 201 |
|
| HQP_MVS | | | 87.75 90 | 87.43 97 | 88.70 77 | 93.45 75 | 76.42 119 | 89.45 87 | 93.61 65 | 79.44 110 | 86.55 204 | 92.95 148 | 74.84 219 | 95.22 63 | 80.78 126 | 95.83 146 | 94.46 98 |
|
| sc_t1 | | | 87.70 91 | 88.94 74 | 83.99 188 | 93.47 74 | 67.15 238 | 85.05 176 | 88.21 249 | 86.81 32 | 91.87 74 | 97.65 5 | 85.51 74 | 87.91 305 | 74.22 216 | 97.63 71 | 96.92 25 |
|
| MM | | | 87.64 92 | 87.15 100 | 89.09 69 | 89.51 190 | 76.39 121 | 88.68 102 | 86.76 280 | 84.54 50 | 83.58 288 | 93.78 115 | 73.36 250 | 96.48 2 | 87.98 17 | 96.21 122 | 94.41 105 |
|
| MVSMamba_PlusPlus | | | 87.53 93 | 88.86 78 | 83.54 207 | 92.03 120 | 62.26 305 | 91.49 45 | 92.62 114 | 88.07 25 | 88.07 161 | 96.17 27 | 72.24 264 | 95.79 34 | 84.85 79 | 94.16 208 | 92.58 205 |
|
| NCCC | | | 87.36 94 | 86.87 109 | 88.83 72 | 92.32 110 | 78.84 89 | 86.58 141 | 91.09 170 | 78.77 122 | 84.85 256 | 90.89 234 | 80.85 142 | 95.29 60 | 81.14 121 | 95.32 163 | 92.34 222 |
|
| DeepPCF-MVS | | 81.24 5 | 87.28 95 | 86.21 120 | 90.49 42 | 91.48 144 | 84.90 42 | 83.41 225 | 92.38 122 | 70.25 255 | 89.35 131 | 90.68 244 | 82.85 102 | 94.57 88 | 79.55 141 | 95.95 137 | 92.00 241 |
|
| SixPastTwentyTwo | | | 87.20 96 | 87.45 96 | 86.45 118 | 92.52 102 | 69.19 217 | 87.84 117 | 88.05 250 | 81.66 83 | 94.64 18 | 96.53 21 | 65.94 306 | 94.75 80 | 83.02 100 | 96.83 98 | 95.41 58 |
|
| fmvsm_s_conf0.5_n_9 | | | 87.04 97 | 87.02 105 | 87.08 105 | 89.67 187 | 75.87 129 | 84.60 187 | 89.74 214 | 74.40 183 | 89.92 115 | 93.41 126 | 80.45 147 | 90.63 233 | 86.66 46 | 94.37 201 | 94.73 88 |
|
| SPE-MVS-test | | | 87.00 98 | 86.43 116 | 88.71 76 | 89.46 192 | 77.46 105 | 89.42 89 | 95.73 7 | 77.87 135 | 81.64 330 | 87.25 329 | 82.43 108 | 94.53 91 | 77.65 168 | 96.46 111 | 94.14 118 |
|
| UniMVSNet (Re) | | | 86.87 99 | 86.98 107 | 86.55 116 | 93.11 87 | 68.48 227 | 83.80 212 | 92.87 104 | 80.37 96 | 89.61 125 | 91.81 193 | 77.72 176 | 94.18 104 | 75.00 209 | 98.53 16 | 96.99 24 |
|
| Vis-MVSNet |  | | 86.86 100 | 86.58 113 | 87.72 97 | 92.09 117 | 77.43 107 | 87.35 123 | 92.09 132 | 78.87 120 | 84.27 274 | 94.05 99 | 78.35 168 | 93.65 125 | 80.54 130 | 91.58 293 | 92.08 237 |
| Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
| UniMVSNet_NR-MVSNet | | | 86.84 101 | 87.06 103 | 86.17 128 | 92.86 94 | 67.02 242 | 82.55 252 | 91.56 150 | 83.08 70 | 90.92 90 | 91.82 192 | 78.25 169 | 93.99 111 | 74.16 219 | 98.35 24 | 97.49 13 |
|
| DU-MVS | | | 86.80 102 | 86.99 106 | 86.21 126 | 93.24 84 | 67.02 242 | 83.16 235 | 92.21 127 | 81.73 82 | 90.92 90 | 91.97 183 | 77.20 188 | 93.99 111 | 74.16 219 | 98.35 24 | 97.61 10 |
|
| casdiffmvs_mvg |  | | 86.72 103 | 87.51 95 | 84.36 176 | 87.09 267 | 65.22 262 | 84.16 198 | 94.23 28 | 77.89 133 | 91.28 85 | 93.66 121 | 84.35 84 | 92.71 163 | 80.07 131 | 94.87 185 | 95.16 72 |
| Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025 |
| test_fmvsmconf0.01_n | | | 86.68 104 | 86.52 114 | 87.18 103 | 85.94 306 | 78.30 92 | 86.93 130 | 92.20 128 | 65.94 313 | 89.16 134 | 93.16 137 | 83.10 97 | 89.89 262 | 87.81 21 | 94.43 199 | 93.35 161 |
|
| tt0320-xc | | | 86.67 105 | 88.41 84 | 81.44 266 | 93.45 75 | 60.44 336 | 83.96 204 | 88.50 238 | 87.26 29 | 90.90 94 | 97.90 3 | 85.61 71 | 86.40 336 | 70.14 278 | 98.01 45 | 97.47 14 |
|
| IS-MVSNet | | | 86.66 106 | 86.82 111 | 86.17 128 | 92.05 119 | 66.87 246 | 91.21 48 | 88.64 235 | 86.30 37 | 89.60 126 | 92.59 160 | 69.22 287 | 94.91 75 | 73.89 226 | 97.89 55 | 96.72 29 |
|
| tt0320 | | | 86.63 107 | 88.36 85 | 81.41 267 | 93.57 72 | 60.73 333 | 84.37 195 | 88.61 237 | 87.00 31 | 90.75 97 | 97.98 2 | 85.54 73 | 86.45 334 | 69.75 283 | 97.70 64 | 97.06 22 |
|
| v10 | | | 86.54 108 | 87.10 102 | 84.84 158 | 88.16 230 | 63.28 283 | 86.64 140 | 92.20 128 | 75.42 168 | 92.81 57 | 94.50 73 | 74.05 235 | 94.06 110 | 83.88 89 | 96.28 118 | 97.17 19 |
|
| pmmvs6 | | | 86.52 109 | 88.06 88 | 81.90 252 | 92.22 113 | 62.28 304 | 84.66 186 | 89.15 229 | 83.54 65 | 89.85 116 | 97.32 8 | 88.08 39 | 86.80 327 | 70.43 275 | 97.30 87 | 96.62 31 |
|
| NormalMVS | | | 86.47 110 | 85.32 143 | 89.94 51 | 94.43 44 | 80.42 72 | 88.63 104 | 93.59 68 | 74.56 178 | 85.12 244 | 90.34 257 | 66.19 303 | 94.20 101 | 76.57 183 | 98.44 20 | 95.19 69 |
|
| PHI-MVS | | | 86.38 111 | 85.81 130 | 88.08 92 | 88.44 224 | 77.34 108 | 89.35 91 | 93.05 95 | 73.15 207 | 84.76 258 | 87.70 318 | 78.87 162 | 94.18 104 | 80.67 128 | 96.29 117 | 92.73 193 |
|
| CSCG | | | 86.26 112 | 86.47 115 | 85.60 140 | 90.87 162 | 74.26 139 | 87.98 114 | 91.85 140 | 80.35 97 | 89.54 129 | 88.01 305 | 79.09 160 | 92.13 179 | 75.51 202 | 95.06 174 | 90.41 292 |
|
| DeepC-MVS_fast | | 80.27 8 | 86.23 113 | 85.65 136 | 87.96 95 | 91.30 147 | 76.92 113 | 87.19 125 | 91.99 135 | 70.56 249 | 84.96 251 | 90.69 243 | 80.01 153 | 95.14 68 | 78.37 155 | 95.78 150 | 91.82 246 |
| Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
| v8 | | | 86.22 114 | 86.83 110 | 84.36 176 | 87.82 238 | 62.35 303 | 86.42 144 | 91.33 159 | 76.78 148 | 92.73 59 | 94.48 75 | 73.41 247 | 93.72 123 | 83.10 97 | 95.41 159 | 97.01 23 |
|
| Anonymous20240529 | | | 86.20 115 | 87.13 101 | 83.42 209 | 90.19 175 | 64.55 269 | 84.55 189 | 90.71 179 | 85.85 40 | 89.94 114 | 95.24 51 | 82.13 120 | 90.40 241 | 69.19 290 | 96.40 114 | 95.31 63 |
|
| fmvsm_s_conf0.5_n_3 | | | 86.19 116 | 87.27 99 | 82.95 223 | 86.91 275 | 70.38 198 | 85.31 170 | 92.61 116 | 75.59 164 | 88.32 156 | 92.87 151 | 82.22 117 | 88.63 290 | 88.80 9 | 92.82 255 | 89.83 305 |
|
| test_fmvsmconf0.1_n | | | 86.18 117 | 85.88 128 | 87.08 105 | 85.26 322 | 78.25 93 | 85.82 157 | 91.82 142 | 65.33 328 | 88.55 147 | 92.35 174 | 82.62 106 | 89.80 264 | 86.87 42 | 94.32 203 | 93.18 172 |
|
| CDPH-MVS | | | 86.17 118 | 85.54 137 | 88.05 94 | 92.25 111 | 75.45 132 | 83.85 209 | 92.01 134 | 65.91 315 | 86.19 215 | 91.75 197 | 83.77 90 | 94.98 73 | 77.43 173 | 96.71 102 | 93.73 139 |
|
| NR-MVSNet | | | 86.00 119 | 86.22 119 | 85.34 147 | 93.24 84 | 64.56 268 | 82.21 266 | 90.46 188 | 80.99 90 | 88.42 152 | 91.97 183 | 77.56 179 | 93.85 118 | 72.46 253 | 98.65 12 | 97.61 10 |
|
| train_agg | | | 85.98 120 | 85.28 144 | 88.07 93 | 92.34 108 | 79.70 80 | 83.94 205 | 90.32 196 | 65.79 317 | 84.49 263 | 90.97 228 | 81.93 126 | 93.63 127 | 81.21 120 | 96.54 107 | 90.88 275 |
|
| KinetiMVS | | | 85.95 121 | 86.10 123 | 85.50 144 | 87.56 248 | 69.78 205 | 83.70 215 | 89.83 213 | 80.42 95 | 87.76 175 | 93.24 130 | 73.76 241 | 91.54 194 | 85.03 73 | 93.62 229 | 95.19 69 |
|
| FC-MVSNet-test | | | 85.93 122 | 87.05 104 | 82.58 234 | 92.25 111 | 56.44 381 | 85.75 158 | 93.09 93 | 77.33 143 | 91.94 73 | 94.65 66 | 74.78 221 | 93.41 143 | 75.11 208 | 98.58 14 | 97.88 7 |
|
| test_fmvsmconf_n | | | 85.88 123 | 85.51 138 | 86.99 108 | 84.77 331 | 78.21 94 | 85.40 168 | 91.39 157 | 65.32 329 | 87.72 177 | 91.81 193 | 82.33 111 | 89.78 265 | 86.68 44 | 94.20 206 | 92.99 184 |
|
| Effi-MVS+-dtu | | | 85.82 124 | 83.38 196 | 93.14 4 | 87.13 262 | 91.15 3 | 87.70 118 | 88.42 241 | 74.57 177 | 83.56 289 | 85.65 353 | 78.49 167 | 94.21 100 | 72.04 255 | 92.88 251 | 94.05 122 |
|
| TAPA-MVS | | 77.73 12 | 85.71 125 | 84.83 154 | 88.37 86 | 88.78 214 | 79.72 79 | 87.15 127 | 93.50 71 | 69.17 267 | 85.80 227 | 89.56 278 | 80.76 143 | 92.13 179 | 73.21 248 | 95.51 157 | 93.25 169 |
| Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
| FE-MVSNET1 | | | 85.67 126 | 86.73 112 | 82.51 238 | 91.76 132 | 62.23 308 | 86.13 151 | 90.45 189 | 79.10 115 | 90.40 102 | 96.73 17 | 82.17 119 | 89.96 261 | 67.47 308 | 96.33 116 | 95.34 60 |
|
| sasdasda | | | 85.50 127 | 86.14 121 | 83.58 203 | 87.97 232 | 67.13 239 | 87.55 119 | 94.32 22 | 73.44 197 | 88.47 150 | 87.54 321 | 86.45 62 | 91.06 213 | 75.76 198 | 93.76 220 | 92.54 208 |
|
| canonicalmvs | | | 85.50 127 | 86.14 121 | 83.58 203 | 87.97 232 | 67.13 239 | 87.55 119 | 94.32 22 | 73.44 197 | 88.47 150 | 87.54 321 | 86.45 62 | 91.06 213 | 75.76 198 | 93.76 220 | 92.54 208 |
|
| fmvsm_s_conf0.5_n_8 | | | 85.48 129 | 85.75 133 | 84.68 167 | 87.10 265 | 69.98 203 | 84.28 196 | 92.68 111 | 74.77 174 | 87.90 168 | 92.36 173 | 73.94 236 | 90.41 240 | 85.95 62 | 92.74 257 | 93.66 142 |
|
| EPP-MVSNet | | | 85.47 130 | 85.04 149 | 86.77 113 | 91.52 143 | 69.37 212 | 91.63 44 | 87.98 253 | 81.51 85 | 87.05 193 | 91.83 191 | 66.18 305 | 95.29 60 | 70.75 269 | 96.89 95 | 95.64 53 |
|
| GeoE | | | 85.45 131 | 85.81 130 | 84.37 174 | 90.08 178 | 67.07 241 | 85.86 156 | 91.39 157 | 72.33 225 | 87.59 179 | 90.25 262 | 84.85 79 | 92.37 173 | 78.00 164 | 91.94 282 | 93.66 142 |
|
| MGCNet | | | 85.37 132 | 84.58 166 | 87.75 96 | 85.28 321 | 73.36 144 | 86.54 143 | 85.71 297 | 77.56 140 | 81.78 328 | 92.47 166 | 70.29 281 | 96.02 11 | 85.59 65 | 95.96 135 | 93.87 130 |
|
| FIs | | | 85.35 133 | 86.27 118 | 82.60 233 | 91.86 126 | 57.31 374 | 85.10 175 | 93.05 95 | 75.83 159 | 91.02 89 | 93.97 103 | 73.57 243 | 92.91 161 | 73.97 225 | 98.02 44 | 97.58 12 |
|
| test_fmvsmvis_n_1920 | | | 85.22 134 | 85.36 142 | 84.81 160 | 85.80 309 | 76.13 125 | 85.15 174 | 92.32 125 | 61.40 364 | 91.33 82 | 90.85 237 | 83.76 91 | 86.16 342 | 84.31 85 | 93.28 238 | 92.15 235 |
|
| casdiffmvs |  | | 85.21 135 | 85.85 129 | 83.31 212 | 86.17 298 | 62.77 290 | 83.03 237 | 93.93 47 | 74.69 176 | 88.21 158 | 92.68 159 | 82.29 115 | 91.89 187 | 77.87 167 | 93.75 223 | 95.27 65 |
| Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025 |
| fmvsm_s_conf0.5_n_10 | | | 85.20 136 | 85.25 145 | 85.02 155 | 86.01 304 | 71.31 185 | 84.96 177 | 91.76 146 | 69.10 269 | 88.90 137 | 92.56 163 | 73.84 239 | 90.63 233 | 86.88 41 | 93.26 239 | 93.13 173 |
|
| baseline | | | 85.20 136 | 85.93 126 | 83.02 219 | 86.30 293 | 62.37 302 | 84.55 189 | 93.96 45 | 74.48 180 | 87.12 187 | 92.03 182 | 82.30 113 | 91.94 184 | 78.39 154 | 94.21 205 | 94.74 87 |
|
| SSM_0404 | | | 85.16 138 | 85.09 147 | 85.36 146 | 90.14 177 | 69.52 210 | 86.17 149 | 91.58 148 | 74.41 181 | 86.55 204 | 91.49 204 | 78.54 163 | 93.97 113 | 73.71 230 | 93.21 243 | 92.59 204 |
|
| K. test v3 | | | 85.14 139 | 84.73 156 | 86.37 119 | 91.13 156 | 69.63 209 | 85.45 166 | 76.68 382 | 84.06 56 | 92.44 64 | 96.99 13 | 62.03 333 | 94.65 84 | 80.58 129 | 93.24 240 | 94.83 84 |
|
| mmtdpeth | | | 85.13 140 | 85.78 132 | 83.17 217 | 84.65 333 | 74.71 135 | 85.87 155 | 90.35 195 | 77.94 132 | 83.82 281 | 96.96 15 | 77.75 174 | 80.03 401 | 78.44 153 | 96.21 122 | 94.79 86 |
|
| EI-MVSNet-Vis-set | | | 85.12 141 | 84.53 169 | 86.88 110 | 84.01 346 | 72.76 155 | 83.91 208 | 85.18 307 | 80.44 94 | 88.75 142 | 85.49 357 | 80.08 152 | 91.92 185 | 82.02 114 | 90.85 314 | 95.97 44 |
|
| fmvsm_l_conf0.5_n_3 | | | 85.11 142 | 84.96 151 | 85.56 141 | 87.49 251 | 75.69 131 | 84.71 184 | 90.61 184 | 67.64 297 | 84.88 254 | 92.05 181 | 82.30 113 | 88.36 297 | 83.84 91 | 91.10 302 | 92.62 201 |
|
| MGCFI-Net | | | 85.04 143 | 85.95 125 | 82.31 245 | 87.52 249 | 63.59 279 | 86.23 148 | 93.96 45 | 73.46 195 | 88.07 161 | 87.83 316 | 86.46 61 | 90.87 223 | 76.17 192 | 93.89 216 | 92.47 212 |
|
| EI-MVSNet-UG-set | | | 85.04 143 | 84.44 172 | 86.85 111 | 83.87 350 | 72.52 164 | 83.82 210 | 85.15 308 | 80.27 99 | 88.75 142 | 85.45 359 | 79.95 154 | 91.90 186 | 81.92 117 | 90.80 316 | 96.13 39 |
|
| X-MVStestdata | | | 85.04 143 | 82.70 215 | 92.08 9 | 95.64 24 | 86.25 22 | 92.64 20 | 93.33 78 | 85.07 45 | 89.99 111 | 16.05 478 | 86.57 59 | 95.80 31 | 87.35 33 | 97.62 73 | 94.20 112 |
|
| MSLP-MVS++ | | | 85.00 146 | 86.03 124 | 81.90 252 | 91.84 129 | 71.56 183 | 86.75 138 | 93.02 99 | 75.95 157 | 87.12 187 | 89.39 282 | 77.98 171 | 89.40 276 | 77.46 171 | 94.78 187 | 84.75 381 |
|
| F-COLMAP | | | 84.97 147 | 83.42 195 | 89.63 58 | 92.39 106 | 83.40 52 | 88.83 98 | 91.92 138 | 73.19 206 | 80.18 352 | 89.15 288 | 77.04 192 | 93.28 146 | 65.82 324 | 92.28 271 | 92.21 231 |
|
| SSM_0407 | | | 84.89 148 | 84.85 153 | 85.01 156 | 89.13 200 | 68.97 220 | 85.60 162 | 91.58 148 | 74.41 181 | 85.68 228 | 91.49 204 | 78.54 163 | 93.69 124 | 73.71 230 | 93.47 231 | 92.38 219 |
|
| balanced_conf03 | | | 84.80 149 | 85.40 140 | 83.00 220 | 88.95 207 | 61.44 314 | 90.42 63 | 92.37 124 | 71.48 238 | 88.72 144 | 93.13 138 | 70.16 283 | 95.15 67 | 79.26 146 | 94.11 209 | 92.41 214 |
|
| 3Dnovator | | 80.37 7 | 84.80 149 | 84.71 159 | 85.06 153 | 86.36 291 | 74.71 135 | 88.77 100 | 90.00 209 | 75.65 162 | 84.96 251 | 93.17 136 | 74.06 234 | 91.19 208 | 78.28 158 | 91.09 303 | 89.29 315 |
|
| SymmetryMVS | | | 84.79 151 | 83.54 190 | 88.55 79 | 92.44 105 | 80.42 72 | 88.63 104 | 82.37 342 | 74.56 178 | 85.12 244 | 90.34 257 | 66.19 303 | 94.20 101 | 76.57 183 | 95.68 154 | 91.03 269 |
|
| IterMVS-LS | | | 84.73 152 | 84.98 150 | 83.96 190 | 87.35 255 | 63.66 277 | 83.25 230 | 89.88 212 | 76.06 152 | 89.62 123 | 92.37 171 | 73.40 249 | 92.52 168 | 78.16 161 | 94.77 189 | 95.69 51 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
| MVS_111021_HR | | | 84.63 153 | 84.34 177 | 85.49 145 | 90.18 176 | 75.86 130 | 79.23 321 | 87.13 270 | 73.35 199 | 85.56 235 | 89.34 283 | 83.60 93 | 90.50 237 | 76.64 182 | 94.05 213 | 90.09 301 |
|
| HQP-MVS | | | 84.61 154 | 84.06 182 | 86.27 122 | 91.19 152 | 70.66 193 | 84.77 179 | 92.68 111 | 73.30 202 | 80.55 344 | 90.17 267 | 72.10 265 | 94.61 86 | 77.30 175 | 94.47 197 | 93.56 154 |
|
| v1192 | | | 84.57 155 | 84.69 161 | 84.21 182 | 87.75 240 | 62.88 287 | 83.02 238 | 91.43 154 | 69.08 270 | 89.98 113 | 90.89 234 | 72.70 259 | 93.62 130 | 82.41 109 | 94.97 179 | 96.13 39 |
|
| fmvsm_s_conf0.5_n_11 | | | 84.56 156 | 84.69 161 | 84.15 185 | 86.53 281 | 71.29 186 | 85.53 163 | 92.62 114 | 70.54 250 | 82.75 305 | 91.20 219 | 77.33 183 | 88.55 293 | 83.80 92 | 91.93 283 | 92.61 203 |
|
| fmvsm_s_conf0.5_n_5 | | | 84.56 156 | 84.71 159 | 84.11 186 | 87.92 235 | 72.09 172 | 84.80 178 | 88.64 235 | 64.43 338 | 88.77 141 | 91.78 195 | 78.07 170 | 87.95 304 | 85.85 63 | 92.18 275 | 92.30 224 |
|
| FMVSNet1 | | | 84.55 158 | 85.45 139 | 81.85 254 | 90.27 174 | 61.05 324 | 86.83 134 | 88.27 246 | 78.57 125 | 89.66 122 | 95.64 39 | 75.43 211 | 90.68 230 | 69.09 291 | 95.33 162 | 93.82 133 |
|
| v1144 | | | 84.54 159 | 84.72 158 | 84.00 187 | 87.67 244 | 62.55 294 | 82.97 240 | 90.93 175 | 70.32 254 | 89.80 117 | 90.99 227 | 73.50 244 | 93.48 139 | 81.69 119 | 94.65 193 | 95.97 44 |
|
| Gipuma |  | | 84.44 160 | 86.33 117 | 78.78 312 | 84.20 343 | 73.57 143 | 89.55 82 | 90.44 190 | 84.24 54 | 84.38 266 | 94.89 58 | 76.35 207 | 80.40 398 | 76.14 193 | 96.80 100 | 82.36 419 |
| S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
| fmvsm_s_conf0.5_n_4 | | | 84.38 161 | 84.27 178 | 84.74 163 | 87.25 258 | 70.84 192 | 83.55 220 | 88.45 240 | 68.64 279 | 86.29 214 | 91.31 213 | 74.97 217 | 88.42 295 | 87.87 20 | 90.07 332 | 94.95 76 |
|
| MCST-MVS | | | 84.36 162 | 83.93 186 | 85.63 139 | 91.59 135 | 71.58 181 | 83.52 221 | 92.13 130 | 61.82 357 | 83.96 279 | 89.75 275 | 79.93 155 | 93.46 140 | 78.33 157 | 94.34 202 | 91.87 245 |
|
| VDDNet | | | 84.35 163 | 85.39 141 | 81.25 269 | 95.13 32 | 59.32 350 | 85.42 167 | 81.11 353 | 86.41 36 | 87.41 183 | 96.21 26 | 73.61 242 | 90.61 235 | 66.33 317 | 96.85 96 | 93.81 136 |
|
| ETV-MVS | | | 84.31 164 | 83.91 187 | 85.52 142 | 88.58 220 | 70.40 197 | 84.50 193 | 93.37 73 | 78.76 123 | 84.07 277 | 78.72 432 | 80.39 148 | 95.13 69 | 73.82 228 | 92.98 249 | 91.04 268 |
|
| v1240 | | | 84.30 165 | 84.51 170 | 83.65 200 | 87.65 245 | 61.26 320 | 82.85 244 | 91.54 151 | 67.94 290 | 90.68 99 | 90.65 248 | 71.71 273 | 93.64 126 | 82.84 103 | 94.78 187 | 96.07 41 |
|
| MVS_111021_LR | | | 84.28 166 | 83.76 188 | 85.83 136 | 89.23 198 | 83.07 55 | 80.99 289 | 83.56 330 | 72.71 217 | 86.07 218 | 89.07 290 | 81.75 133 | 86.19 341 | 77.11 177 | 93.36 234 | 88.24 334 |
|
| h-mvs33 | | | 84.25 167 | 82.76 214 | 88.72 75 | 91.82 131 | 82.60 60 | 84.00 203 | 84.98 314 | 71.27 239 | 86.70 200 | 90.55 253 | 63.04 330 | 93.92 116 | 78.26 159 | 94.20 206 | 89.63 307 |
|
| v144192 | | | 84.24 168 | 84.41 173 | 83.71 199 | 87.59 247 | 61.57 313 | 82.95 241 | 91.03 171 | 67.82 294 | 89.80 117 | 90.49 254 | 73.28 251 | 93.51 138 | 81.88 118 | 94.89 182 | 96.04 43 |
|
| dcpmvs_2 | | | 84.23 169 | 85.14 146 | 81.50 264 | 88.61 219 | 61.98 310 | 82.90 243 | 93.11 91 | 68.66 278 | 92.77 58 | 92.39 167 | 78.50 166 | 87.63 313 | 76.99 179 | 92.30 268 | 94.90 77 |
|
| v1921920 | | | 84.23 169 | 84.37 175 | 83.79 195 | 87.64 246 | 61.71 312 | 82.91 242 | 91.20 166 | 67.94 290 | 90.06 108 | 90.34 257 | 72.04 268 | 93.59 132 | 82.32 110 | 94.91 180 | 96.07 41 |
|
| VDD-MVS | | | 84.23 169 | 84.58 166 | 83.20 215 | 91.17 155 | 65.16 264 | 83.25 230 | 84.97 315 | 79.79 104 | 87.18 186 | 94.27 84 | 74.77 222 | 90.89 221 | 69.24 287 | 96.54 107 | 93.55 156 |
|
| v2v482 | | | 84.09 172 | 84.24 179 | 83.62 201 | 87.13 262 | 61.40 315 | 82.71 247 | 89.71 217 | 72.19 228 | 89.55 127 | 91.41 208 | 70.70 279 | 93.20 148 | 81.02 122 | 93.76 220 | 96.25 37 |
|
| EG-PatchMatch MVS | | | 84.08 173 | 84.11 181 | 83.98 189 | 92.22 113 | 72.61 161 | 82.20 268 | 87.02 276 | 72.63 218 | 88.86 138 | 91.02 226 | 78.52 165 | 91.11 211 | 73.41 238 | 91.09 303 | 88.21 335 |
|
| E2 | | | 84.06 174 | 84.61 163 | 82.40 243 | 87.49 251 | 61.31 317 | 81.03 287 | 93.36 74 | 71.83 233 | 86.02 220 | 91.87 185 | 82.91 100 | 91.37 203 | 75.66 200 | 91.33 297 | 94.53 95 |
|
| E3 | | | 84.06 174 | 84.61 163 | 82.40 243 | 87.49 251 | 61.30 318 | 81.03 287 | 93.36 74 | 71.83 233 | 86.01 221 | 91.87 185 | 82.91 100 | 91.36 204 | 75.66 200 | 91.33 297 | 94.53 95 |
|
| fmvsm_s_conf0.5_n_6 | | | 84.05 176 | 84.14 180 | 83.81 193 | 87.75 240 | 71.17 188 | 83.42 224 | 91.10 169 | 67.90 292 | 84.53 261 | 90.70 242 | 73.01 254 | 88.73 287 | 85.09 70 | 93.72 225 | 91.53 258 |
|
| DP-MVS Recon | | | 84.05 176 | 83.22 199 | 86.52 117 | 91.73 133 | 75.27 133 | 83.23 232 | 92.40 120 | 72.04 230 | 82.04 319 | 88.33 301 | 77.91 173 | 93.95 115 | 66.17 318 | 95.12 172 | 90.34 294 |
|
| viewmacassd2359aftdt | | | 84.04 178 | 84.78 155 | 81.81 257 | 86.43 285 | 60.32 338 | 81.95 270 | 92.82 107 | 71.56 235 | 86.06 219 | 92.98 144 | 81.79 132 | 90.28 242 | 76.18 191 | 93.24 240 | 94.82 85 |
|
| TransMVSNet (Re) | | | 84.02 179 | 85.74 134 | 78.85 311 | 91.00 159 | 55.20 393 | 82.29 262 | 87.26 265 | 79.65 107 | 88.38 154 | 95.52 42 | 83.00 98 | 86.88 325 | 67.97 305 | 96.60 105 | 94.45 100 |
|
| Baseline_NR-MVSNet | | | 84.00 180 | 85.90 127 | 78.29 323 | 91.47 145 | 53.44 405 | 82.29 262 | 87.00 279 | 79.06 117 | 89.55 127 | 95.72 37 | 77.20 188 | 86.14 343 | 72.30 254 | 98.51 17 | 95.28 64 |
|
| fmvsm_l_conf0.5_n_9 | | | 83.98 181 | 84.46 171 | 82.53 237 | 86.11 301 | 70.65 195 | 82.45 257 | 89.17 228 | 67.72 296 | 86.74 199 | 91.49 204 | 79.20 158 | 85.86 352 | 84.71 81 | 92.60 261 | 91.07 267 |
|
| TSAR-MVS + GP. | | | 83.95 182 | 82.69 216 | 87.72 97 | 89.27 197 | 81.45 67 | 83.72 214 | 81.58 351 | 74.73 175 | 85.66 231 | 86.06 348 | 72.56 261 | 92.69 165 | 75.44 204 | 95.21 167 | 89.01 328 |
|
| LuminaMVS | | | 83.94 183 | 83.51 191 | 85.23 148 | 89.78 186 | 71.74 176 | 84.76 182 | 87.27 264 | 72.60 219 | 89.31 132 | 90.60 252 | 64.04 319 | 90.95 216 | 79.08 147 | 94.11 209 | 92.99 184 |
|
| alignmvs | | | 83.94 183 | 83.98 184 | 83.80 194 | 87.80 239 | 67.88 234 | 84.54 191 | 91.42 156 | 73.27 205 | 88.41 153 | 87.96 306 | 72.33 262 | 90.83 224 | 76.02 195 | 94.11 209 | 92.69 197 |
|
| Effi-MVS+ | | | 83.90 185 | 84.01 183 | 83.57 205 | 87.22 260 | 65.61 260 | 86.55 142 | 92.40 120 | 78.64 124 | 81.34 335 | 84.18 378 | 83.65 92 | 92.93 159 | 74.22 216 | 87.87 367 | 92.17 234 |
|
| fmvsm_s_conf0.1_n_2 | | | 83.82 186 | 83.49 192 | 84.84 158 | 85.99 305 | 70.19 201 | 80.93 290 | 87.58 260 | 67.26 303 | 87.94 167 | 92.37 171 | 71.40 275 | 88.01 301 | 86.03 57 | 91.87 284 | 96.31 36 |
|
| mvs5depth | | | 83.82 186 | 84.54 168 | 81.68 260 | 82.23 375 | 68.65 225 | 86.89 131 | 89.90 211 | 80.02 103 | 87.74 176 | 97.86 4 | 64.19 318 | 82.02 386 | 76.37 187 | 95.63 156 | 94.35 107 |
|
| CANet | | | 83.79 188 | 82.85 213 | 86.63 114 | 86.17 298 | 72.21 171 | 83.76 213 | 91.43 154 | 77.24 145 | 74.39 407 | 87.45 325 | 75.36 212 | 95.42 56 | 77.03 178 | 92.83 254 | 92.25 230 |
|
| pm-mvs1 | | | 83.69 189 | 84.95 152 | 79.91 297 | 90.04 182 | 59.66 347 | 82.43 258 | 87.44 261 | 75.52 166 | 87.85 171 | 95.26 50 | 81.25 138 | 85.65 356 | 68.74 297 | 96.04 131 | 94.42 104 |
|
| AdaColmap |  | | 83.66 190 | 83.69 189 | 83.57 205 | 90.05 181 | 72.26 169 | 86.29 146 | 90.00 209 | 78.19 130 | 81.65 329 | 87.16 331 | 83.40 95 | 94.24 99 | 61.69 360 | 94.76 190 | 84.21 391 |
|
| viewdifsd2359ckpt09 | | | 83.64 191 | 83.18 202 | 85.03 154 | 87.26 257 | 66.99 244 | 85.32 169 | 93.83 57 | 65.57 323 | 84.99 250 | 89.40 281 | 77.30 184 | 93.57 135 | 71.16 265 | 93.80 219 | 94.54 94 |
|
| MIMVSNet1 | | | 83.63 192 | 84.59 165 | 80.74 280 | 94.06 62 | 62.77 290 | 82.72 246 | 84.53 322 | 77.57 139 | 90.34 104 | 95.92 32 | 76.88 200 | 85.83 353 | 61.88 358 | 97.42 83 | 93.62 148 |
|
| fmvsm_s_conf0.5_n_2 | | | 83.62 193 | 83.29 198 | 84.62 168 | 85.43 319 | 70.18 202 | 80.61 296 | 87.24 266 | 67.14 304 | 87.79 173 | 91.87 185 | 71.79 272 | 87.98 303 | 86.00 61 | 91.77 287 | 95.71 50 |
|
| test_fmvsm_n_1920 | | | 83.60 194 | 82.89 210 | 85.74 137 | 85.22 323 | 77.74 102 | 84.12 200 | 90.48 186 | 59.87 384 | 86.45 213 | 91.12 222 | 75.65 209 | 85.89 350 | 82.28 111 | 90.87 312 | 93.58 152 |
|
| WR-MVS | | | 83.56 195 | 84.40 174 | 81.06 274 | 93.43 78 | 54.88 394 | 78.67 330 | 85.02 312 | 81.24 87 | 90.74 98 | 91.56 202 | 72.85 256 | 91.08 212 | 68.00 304 | 98.04 41 | 97.23 17 |
|
| CNLPA | | | 83.55 196 | 83.10 205 | 84.90 157 | 89.34 195 | 83.87 50 | 84.54 191 | 88.77 232 | 79.09 116 | 83.54 290 | 88.66 298 | 74.87 218 | 81.73 388 | 66.84 312 | 92.29 270 | 89.11 321 |
|
| viewcassd2359sk11 | | | 83.53 197 | 83.96 185 | 82.25 246 | 86.97 274 | 61.13 322 | 80.80 294 | 93.22 86 | 70.97 245 | 85.36 239 | 91.08 224 | 81.84 130 | 91.29 205 | 74.79 211 | 90.58 328 | 94.33 109 |
|
| LCM-MVSNet-Re | | | 83.48 198 | 85.06 148 | 78.75 313 | 85.94 306 | 55.75 387 | 80.05 302 | 94.27 25 | 76.47 149 | 96.09 6 | 94.54 72 | 83.31 96 | 89.75 268 | 59.95 371 | 94.89 182 | 90.75 278 |
|
| hse-mvs2 | | | 83.47 199 | 81.81 231 | 88.47 82 | 91.03 158 | 82.27 61 | 82.61 248 | 83.69 328 | 71.27 239 | 86.70 200 | 86.05 349 | 63.04 330 | 92.41 171 | 78.26 159 | 93.62 229 | 90.71 280 |
|
| V42 | | | 83.47 199 | 83.37 197 | 83.75 197 | 83.16 369 | 63.33 282 | 81.31 281 | 90.23 203 | 69.51 263 | 90.91 92 | 90.81 239 | 74.16 231 | 92.29 177 | 80.06 132 | 90.22 330 | 95.62 54 |
|
| VPA-MVSNet | | | 83.47 199 | 84.73 156 | 79.69 302 | 90.29 173 | 57.52 373 | 81.30 283 | 88.69 234 | 76.29 150 | 87.58 181 | 94.44 76 | 80.60 146 | 87.20 319 | 66.60 315 | 96.82 99 | 94.34 108 |
|
| mamba_0408 | | | 83.44 202 | 82.88 211 | 85.11 151 | 89.13 200 | 68.97 220 | 72.73 405 | 91.28 161 | 72.90 211 | 85.68 228 | 90.61 250 | 76.78 201 | 93.97 113 | 73.37 240 | 93.47 231 | 92.38 219 |
|
| viewdifsd2359ckpt07 | | | 83.41 203 | 84.35 176 | 80.56 286 | 85.84 308 | 58.93 358 | 79.47 313 | 91.28 161 | 73.01 210 | 87.59 179 | 92.07 180 | 85.24 75 | 88.68 288 | 73.59 235 | 91.11 301 | 94.09 121 |
|
| PAPM_NR | | | 83.23 204 | 83.19 201 | 83.33 211 | 90.90 161 | 65.98 256 | 88.19 109 | 90.78 178 | 78.13 131 | 80.87 340 | 87.92 310 | 73.49 246 | 92.42 170 | 70.07 279 | 88.40 356 | 91.60 255 |
|
| CLD-MVS | | | 83.18 205 | 82.64 217 | 84.79 161 | 89.05 203 | 67.82 235 | 77.93 340 | 92.52 118 | 68.33 282 | 85.07 247 | 81.54 407 | 82.06 123 | 92.96 157 | 69.35 286 | 97.91 54 | 93.57 153 |
| Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
| ANet_high | | | 83.17 206 | 85.68 135 | 75.65 361 | 81.24 387 | 45.26 449 | 79.94 304 | 92.91 103 | 83.83 57 | 91.33 82 | 96.88 16 | 80.25 150 | 85.92 346 | 68.89 294 | 95.89 143 | 95.76 48 |
|
| FA-MVS(test-final) | | | 83.13 207 | 83.02 206 | 83.43 208 | 86.16 300 | 66.08 255 | 88.00 113 | 88.36 243 | 75.55 165 | 85.02 248 | 92.75 157 | 65.12 312 | 92.50 169 | 74.94 210 | 91.30 299 | 91.72 250 |
|
| 114514_t | | | 83.10 208 | 82.54 220 | 84.77 162 | 92.90 91 | 69.10 219 | 86.65 139 | 90.62 183 | 54.66 416 | 81.46 332 | 90.81 239 | 76.98 193 | 94.38 94 | 72.62 251 | 96.18 124 | 90.82 277 |
|
| RRT-MVS | | | 82.97 209 | 83.44 193 | 81.57 262 | 85.06 326 | 58.04 368 | 87.20 124 | 90.37 193 | 77.88 134 | 88.59 146 | 93.70 120 | 63.17 327 | 93.05 155 | 76.49 186 | 88.47 355 | 93.62 148 |
|
| viewmanbaseed2359cas | | | 82.95 210 | 83.43 194 | 81.52 263 | 85.18 324 | 60.03 343 | 81.36 280 | 92.38 122 | 69.55 262 | 84.84 257 | 91.38 209 | 79.85 156 | 90.09 255 | 74.22 216 | 92.09 277 | 94.43 103 |
|
| BP-MVS1 | | | 82.81 211 | 81.67 233 | 86.23 123 | 87.88 237 | 68.53 226 | 86.06 152 | 84.36 323 | 75.65 162 | 85.14 243 | 90.19 264 | 45.84 419 | 94.42 93 | 85.18 69 | 94.72 191 | 95.75 49 |
|
| UGNet | | | 82.78 212 | 81.64 234 | 86.21 126 | 86.20 297 | 76.24 123 | 86.86 132 | 85.68 298 | 77.07 146 | 73.76 411 | 92.82 153 | 69.64 284 | 91.82 190 | 69.04 293 | 93.69 226 | 90.56 288 |
| 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 |
| LF4IMVS | | | 82.75 213 | 81.93 229 | 85.19 149 | 82.08 376 | 80.15 76 | 85.53 163 | 88.76 233 | 68.01 287 | 85.58 234 | 87.75 317 | 71.80 271 | 86.85 326 | 74.02 224 | 93.87 217 | 88.58 331 |
|
| EI-MVSNet | | | 82.61 214 | 82.42 222 | 83.20 215 | 83.25 366 | 63.66 277 | 83.50 222 | 85.07 309 | 76.06 152 | 86.55 204 | 85.10 365 | 73.41 247 | 90.25 243 | 78.15 163 | 90.67 323 | 95.68 52 |
|
| QAPM | | | 82.59 215 | 82.59 219 | 82.58 234 | 86.44 284 | 66.69 247 | 89.94 72 | 90.36 194 | 67.97 289 | 84.94 253 | 92.58 162 | 72.71 258 | 92.18 178 | 70.63 272 | 87.73 370 | 88.85 329 |
|
| fmvsm_s_conf0.1_n_a | | | 82.58 216 | 81.93 229 | 84.50 171 | 87.68 243 | 73.35 145 | 86.14 150 | 77.70 371 | 61.64 362 | 85.02 248 | 91.62 199 | 77.75 174 | 86.24 338 | 82.79 104 | 87.07 378 | 93.91 128 |
|
| Fast-Effi-MVS+-dtu | | | 82.54 217 | 81.41 243 | 85.90 133 | 85.60 314 | 76.53 118 | 83.07 236 | 89.62 221 | 73.02 209 | 79.11 362 | 83.51 383 | 80.74 144 | 90.24 245 | 68.76 296 | 89.29 343 | 90.94 272 |
|
| MVS_Test | | | 82.47 218 | 83.22 199 | 80.22 293 | 82.62 374 | 57.75 372 | 82.54 253 | 91.96 137 | 71.16 243 | 82.89 301 | 92.52 165 | 77.41 181 | 90.50 237 | 80.04 133 | 87.84 369 | 92.40 216 |
|
| viewdifsd2359ckpt11 | | | 82.46 219 | 82.98 208 | 80.88 277 | 83.53 353 | 61.00 327 | 79.46 314 | 85.97 293 | 69.48 264 | 87.89 169 | 91.31 213 | 82.10 121 | 88.61 291 | 74.28 214 | 92.86 252 | 93.02 180 |
|
| viewmsd2359difaftdt | | | 82.46 219 | 82.99 207 | 80.88 277 | 83.52 354 | 61.00 327 | 79.46 314 | 85.97 293 | 69.48 264 | 87.89 169 | 91.31 213 | 82.10 121 | 88.61 291 | 74.28 214 | 92.86 252 | 93.02 180 |
|
| v148 | | | 82.31 221 | 82.48 221 | 81.81 257 | 85.59 315 | 59.66 347 | 81.47 278 | 86.02 291 | 72.85 213 | 88.05 163 | 90.65 248 | 70.73 278 | 90.91 220 | 75.15 207 | 91.79 285 | 94.87 79 |
|
| API-MVS | | | 82.28 222 | 82.61 218 | 81.30 268 | 86.29 294 | 69.79 204 | 88.71 101 | 87.67 259 | 78.42 127 | 82.15 315 | 84.15 379 | 77.98 171 | 91.59 193 | 65.39 327 | 92.75 256 | 82.51 418 |
|
| MVSFormer | | | 82.23 223 | 81.57 239 | 84.19 184 | 85.54 316 | 69.26 214 | 91.98 39 | 90.08 207 | 71.54 236 | 76.23 387 | 85.07 368 | 58.69 355 | 94.27 96 | 86.26 51 | 88.77 351 | 89.03 326 |
|
| viewdifsd2359ckpt13 | | | 82.22 224 | 81.98 228 | 82.95 223 | 85.48 318 | 64.44 270 | 83.17 234 | 92.11 131 | 65.97 312 | 83.72 284 | 89.73 276 | 77.60 178 | 90.80 226 | 70.61 273 | 89.42 341 | 93.59 151 |
|
| fmvsm_s_conf0.5_n_a | | | 82.21 225 | 81.51 242 | 84.32 179 | 86.56 280 | 73.35 145 | 85.46 165 | 77.30 375 | 61.81 358 | 84.51 262 | 90.88 236 | 77.36 182 | 86.21 340 | 82.72 105 | 86.97 383 | 93.38 160 |
|
| EIA-MVS | | | 82.19 226 | 81.23 250 | 85.10 152 | 87.95 234 | 69.17 218 | 83.22 233 | 93.33 78 | 70.42 251 | 78.58 367 | 79.77 423 | 77.29 185 | 94.20 101 | 71.51 261 | 88.96 349 | 91.93 244 |
|
| GDP-MVS | | | 82.17 227 | 80.85 258 | 86.15 130 | 88.65 217 | 68.95 223 | 85.65 161 | 93.02 99 | 68.42 280 | 83.73 283 | 89.54 279 | 45.07 430 | 94.31 95 | 79.66 139 | 93.87 217 | 95.19 69 |
|
| fmvsm_s_conf0.1_n | | | 82.17 227 | 81.59 237 | 83.94 192 | 86.87 278 | 71.57 182 | 85.19 173 | 77.42 374 | 62.27 356 | 84.47 265 | 91.33 211 | 76.43 204 | 85.91 348 | 83.14 95 | 87.14 376 | 94.33 109 |
|
| PCF-MVS | | 74.62 15 | 82.15 229 | 80.92 256 | 85.84 135 | 89.43 193 | 72.30 168 | 80.53 297 | 91.82 142 | 57.36 400 | 87.81 172 | 89.92 272 | 77.67 177 | 93.63 127 | 58.69 376 | 95.08 173 | 91.58 256 |
| Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
| PLC |  | 73.85 16 | 82.09 230 | 80.31 265 | 87.45 101 | 90.86 163 | 80.29 75 | 85.88 154 | 90.65 181 | 68.17 285 | 76.32 386 | 86.33 343 | 73.12 253 | 92.61 167 | 61.40 363 | 90.02 334 | 89.44 310 |
| Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
| fmvsm_l_conf0.5_n | | | 82.06 231 | 81.54 241 | 83.60 202 | 83.94 347 | 73.90 141 | 83.35 227 | 86.10 287 | 58.97 386 | 83.80 282 | 90.36 256 | 74.23 229 | 86.94 324 | 82.90 101 | 90.22 330 | 89.94 303 |
|
| fmvsm_s_conf0.5_n_7 | | | 82.04 232 | 82.05 226 | 82.01 250 | 86.98 273 | 71.07 189 | 78.70 328 | 89.45 224 | 68.07 286 | 78.14 369 | 91.61 200 | 74.19 230 | 85.92 346 | 79.61 140 | 91.73 288 | 89.05 325 |
|
| GBi-Net | | | 82.02 233 | 82.07 224 | 81.85 254 | 86.38 288 | 61.05 324 | 86.83 134 | 88.27 246 | 72.43 220 | 86.00 222 | 95.64 39 | 63.78 323 | 90.68 230 | 65.95 320 | 93.34 235 | 93.82 133 |
|
| test1 | | | 82.02 233 | 82.07 224 | 81.85 254 | 86.38 288 | 61.05 324 | 86.83 134 | 88.27 246 | 72.43 220 | 86.00 222 | 95.64 39 | 63.78 323 | 90.68 230 | 65.95 320 | 93.34 235 | 93.82 133 |
|
| OpenMVS |  | 76.72 13 | 81.98 235 | 82.00 227 | 81.93 251 | 84.42 338 | 68.22 229 | 88.50 107 | 89.48 223 | 66.92 307 | 81.80 326 | 91.86 188 | 72.59 260 | 90.16 249 | 71.19 264 | 91.25 300 | 87.40 351 |
|
| KD-MVS_self_test | | | 81.93 236 | 83.14 204 | 78.30 322 | 84.75 332 | 52.75 409 | 80.37 299 | 89.42 226 | 70.24 256 | 90.26 106 | 93.39 127 | 74.55 228 | 86.77 328 | 68.61 299 | 96.64 103 | 95.38 59 |
|
| fmvsm_s_conf0.5_n | | | 81.91 237 | 81.30 247 | 83.75 197 | 86.02 303 | 71.56 183 | 84.73 183 | 77.11 378 | 62.44 353 | 84.00 278 | 90.68 244 | 76.42 205 | 85.89 350 | 83.14 95 | 87.11 377 | 93.81 136 |
|
| SDMVSNet | | | 81.90 238 | 83.17 203 | 78.10 326 | 88.81 212 | 62.45 300 | 76.08 374 | 86.05 290 | 73.67 191 | 83.41 291 | 93.04 140 | 82.35 110 | 80.65 395 | 70.06 280 | 95.03 175 | 91.21 263 |
|
| tfpnnormal | | | 81.79 239 | 82.95 209 | 78.31 321 | 88.93 208 | 55.40 389 | 80.83 293 | 82.85 337 | 76.81 147 | 85.90 226 | 94.14 94 | 74.58 226 | 86.51 332 | 66.82 313 | 95.68 154 | 93.01 183 |
|
| AstraMVS | | | 81.67 240 | 81.40 244 | 82.48 240 | 87.06 270 | 66.47 250 | 81.41 279 | 81.68 348 | 68.78 275 | 88.00 164 | 90.95 232 | 65.70 308 | 87.86 309 | 76.66 181 | 92.38 265 | 93.12 176 |
|
| c3_l | | | 81.64 241 | 81.59 237 | 81.79 259 | 80.86 393 | 59.15 355 | 78.61 331 | 90.18 205 | 68.36 281 | 87.20 185 | 87.11 333 | 69.39 285 | 91.62 192 | 78.16 161 | 94.43 199 | 94.60 90 |
|
| guyue | | | 81.57 242 | 81.37 246 | 82.15 247 | 86.39 286 | 66.13 254 | 81.54 277 | 83.21 332 | 69.79 260 | 87.77 174 | 89.95 270 | 65.36 311 | 87.64 312 | 75.88 196 | 92.49 263 | 92.67 198 |
|
| PVSNet_Blended_VisFu | | | 81.55 243 | 80.49 263 | 84.70 166 | 91.58 138 | 73.24 149 | 84.21 197 | 91.67 147 | 62.86 347 | 80.94 338 | 87.16 331 | 67.27 297 | 92.87 162 | 69.82 282 | 88.94 350 | 87.99 341 |
|
| fmvsm_l_conf0.5_n_a | | | 81.46 244 | 80.87 257 | 83.25 213 | 83.73 352 | 73.21 150 | 83.00 239 | 85.59 300 | 58.22 392 | 82.96 300 | 90.09 269 | 72.30 263 | 86.65 330 | 81.97 116 | 89.95 335 | 89.88 304 |
|
| SSM_04072 | | | 81.44 245 | 82.88 211 | 77.10 341 | 89.13 200 | 68.97 220 | 72.73 405 | 91.28 161 | 72.90 211 | 85.68 228 | 90.61 250 | 76.78 201 | 69.94 438 | 73.37 240 | 93.47 231 | 92.38 219 |
|
| DELS-MVS | | | 81.44 245 | 81.25 248 | 82.03 249 | 84.27 342 | 62.87 288 | 76.47 368 | 92.49 119 | 70.97 245 | 81.64 330 | 83.83 380 | 75.03 215 | 92.70 164 | 74.29 213 | 92.22 274 | 90.51 290 |
| 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 |
| FMVSNet2 | | | 81.31 247 | 81.61 236 | 80.41 289 | 86.38 288 | 58.75 363 | 83.93 207 | 86.58 282 | 72.43 220 | 87.65 178 | 92.98 144 | 63.78 323 | 90.22 246 | 66.86 310 | 93.92 215 | 92.27 228 |
|
| TinyColmap | | | 81.25 248 | 82.34 223 | 77.99 329 | 85.33 320 | 60.68 334 | 82.32 261 | 88.33 244 | 71.26 241 | 86.97 194 | 92.22 179 | 77.10 191 | 86.98 323 | 62.37 352 | 95.17 169 | 86.31 364 |
|
| diffmvs_AUTHOR | | | 81.24 249 | 81.55 240 | 80.30 291 | 80.61 398 | 60.22 339 | 77.98 339 | 90.48 186 | 67.77 295 | 83.34 293 | 89.50 280 | 74.69 224 | 87.42 315 | 78.78 151 | 90.81 315 | 93.27 166 |
|
| AUN-MVS | | | 81.18 250 | 78.78 288 | 88.39 84 | 90.93 160 | 82.14 62 | 82.51 254 | 83.67 329 | 64.69 337 | 80.29 348 | 85.91 352 | 51.07 394 | 92.38 172 | 76.29 190 | 93.63 228 | 90.65 285 |
|
| IMVS_0407 | | | 81.08 251 | 81.23 250 | 80.62 285 | 85.76 310 | 62.46 296 | 82.46 255 | 87.91 254 | 65.23 330 | 82.12 316 | 87.92 310 | 77.27 186 | 90.18 248 | 71.67 257 | 90.74 318 | 89.20 316 |
|
| tttt0517 | | | 81.07 252 | 79.58 278 | 85.52 142 | 88.99 206 | 66.45 251 | 87.03 129 | 75.51 390 | 73.76 190 | 88.32 156 | 90.20 263 | 37.96 451 | 94.16 108 | 79.36 145 | 95.13 170 | 95.93 47 |
|
| Fast-Effi-MVS+ | | | 81.04 253 | 80.57 260 | 82.46 241 | 87.50 250 | 63.22 284 | 78.37 334 | 89.63 220 | 68.01 287 | 81.87 322 | 82.08 401 | 82.31 112 | 92.65 166 | 67.10 309 | 88.30 362 | 91.51 259 |
|
| BH-untuned | | | 80.96 254 | 80.99 254 | 80.84 279 | 88.55 221 | 68.23 228 | 80.33 300 | 88.46 239 | 72.79 216 | 86.55 204 | 86.76 337 | 74.72 223 | 91.77 191 | 61.79 359 | 88.99 348 | 82.52 417 |
|
| IMVS_0403 | | | 80.93 255 | 81.00 253 | 80.72 282 | 85.76 310 | 62.46 296 | 81.82 271 | 87.91 254 | 65.23 330 | 82.07 318 | 87.92 310 | 75.91 208 | 90.50 237 | 71.67 257 | 90.74 318 | 89.20 316 |
|
| eth_miper_zixun_eth | | | 80.84 256 | 80.22 269 | 82.71 231 | 81.41 385 | 60.98 329 | 77.81 342 | 90.14 206 | 67.31 302 | 86.95 195 | 87.24 330 | 64.26 316 | 92.31 175 | 75.23 206 | 91.61 291 | 94.85 83 |
|
| xiu_mvs_v1_base_debu | | | 80.84 256 | 80.14 271 | 82.93 226 | 88.31 225 | 71.73 177 | 79.53 309 | 87.17 267 | 65.43 324 | 79.59 354 | 82.73 395 | 76.94 194 | 90.14 252 | 73.22 243 | 88.33 358 | 86.90 358 |
|
| xiu_mvs_v1_base | | | 80.84 256 | 80.14 271 | 82.93 226 | 88.31 225 | 71.73 177 | 79.53 309 | 87.17 267 | 65.43 324 | 79.59 354 | 82.73 395 | 76.94 194 | 90.14 252 | 73.22 243 | 88.33 358 | 86.90 358 |
|
| xiu_mvs_v1_base_debi | | | 80.84 256 | 80.14 271 | 82.93 226 | 88.31 225 | 71.73 177 | 79.53 309 | 87.17 267 | 65.43 324 | 79.59 354 | 82.73 395 | 76.94 194 | 90.14 252 | 73.22 243 | 88.33 358 | 86.90 358 |
|
| IterMVS-SCA-FT | | | 80.64 260 | 79.41 279 | 84.34 178 | 83.93 348 | 69.66 208 | 76.28 370 | 81.09 354 | 72.43 220 | 86.47 211 | 90.19 264 | 60.46 340 | 93.15 151 | 77.45 172 | 86.39 389 | 90.22 295 |
|
| BH-RMVSNet | | | 80.53 261 | 80.22 269 | 81.49 265 | 87.19 261 | 66.21 253 | 77.79 343 | 86.23 285 | 74.21 185 | 83.69 285 | 88.50 299 | 73.25 252 | 90.75 227 | 63.18 348 | 87.90 366 | 87.52 349 |
|
| VortexMVS | | | 80.51 262 | 80.63 259 | 80.15 295 | 83.36 362 | 61.82 311 | 80.63 295 | 88.00 252 | 67.11 305 | 87.23 184 | 89.10 289 | 63.98 320 | 88.00 302 | 73.63 234 | 92.63 260 | 90.64 286 |
|
| Anonymous202405211 | | | 80.51 262 | 81.19 252 | 78.49 318 | 88.48 222 | 57.26 375 | 76.63 363 | 82.49 340 | 81.21 88 | 84.30 272 | 92.24 178 | 67.99 293 | 86.24 338 | 62.22 353 | 95.13 170 | 91.98 243 |
|
| DIV-MVS_self_test | | | 80.43 264 | 80.23 267 | 81.02 275 | 79.99 403 | 59.25 352 | 77.07 356 | 87.02 276 | 67.38 299 | 86.19 215 | 89.22 285 | 63.09 328 | 90.16 249 | 76.32 188 | 95.80 148 | 93.66 142 |
|
| cl____ | | | 80.42 265 | 80.23 267 | 81.02 275 | 79.99 403 | 59.25 352 | 77.07 356 | 87.02 276 | 67.37 300 | 86.18 217 | 89.21 286 | 63.08 329 | 90.16 249 | 76.31 189 | 95.80 148 | 93.65 145 |
|
| diffmvs |  | | 80.40 266 | 80.48 264 | 80.17 294 | 79.02 416 | 60.04 341 | 77.54 347 | 90.28 202 | 66.65 310 | 82.40 309 | 87.33 328 | 73.50 244 | 87.35 317 | 77.98 165 | 89.62 339 | 93.13 173 |
| Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025 |
| EPNet | | | 80.37 267 | 78.41 296 | 86.23 123 | 76.75 430 | 73.28 147 | 87.18 126 | 77.45 373 | 76.24 151 | 68.14 441 | 88.93 292 | 65.41 310 | 93.85 118 | 69.47 285 | 96.12 128 | 91.55 257 |
| Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
| miper_ehance_all_eth | | | 80.34 268 | 80.04 274 | 81.24 271 | 79.82 406 | 58.95 357 | 77.66 344 | 89.66 218 | 65.75 320 | 85.99 225 | 85.11 364 | 68.29 292 | 91.42 200 | 76.03 194 | 92.03 278 | 93.33 162 |
|
| MG-MVS | | | 80.32 269 | 80.94 255 | 78.47 319 | 88.18 228 | 52.62 412 | 82.29 262 | 85.01 313 | 72.01 231 | 79.24 361 | 92.54 164 | 69.36 286 | 93.36 145 | 70.65 271 | 89.19 346 | 89.45 309 |
|
| mvsmamba | | | 80.30 270 | 78.87 285 | 84.58 170 | 88.12 231 | 67.55 236 | 92.35 30 | 84.88 316 | 63.15 345 | 85.33 240 | 90.91 233 | 50.71 396 | 95.20 66 | 66.36 316 | 87.98 365 | 90.99 270 |
|
| VPNet | | | 80.25 271 | 81.68 232 | 75.94 357 | 92.46 104 | 47.98 436 | 76.70 361 | 81.67 349 | 73.45 196 | 84.87 255 | 92.82 153 | 74.66 225 | 86.51 332 | 61.66 361 | 96.85 96 | 93.33 162 |
|
| MAR-MVS | | | 80.24 272 | 78.74 290 | 84.73 164 | 86.87 278 | 78.18 95 | 85.75 158 | 87.81 258 | 65.67 322 | 77.84 373 | 78.50 433 | 73.79 240 | 90.53 236 | 61.59 362 | 90.87 312 | 85.49 374 |
| 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 |
| PM-MVS | | | 80.20 273 | 79.00 284 | 83.78 196 | 88.17 229 | 86.66 19 | 81.31 281 | 66.81 446 | 69.64 261 | 88.33 155 | 90.19 264 | 64.58 313 | 83.63 377 | 71.99 256 | 90.03 333 | 81.06 437 |
|
| Anonymous20240521 | | | 80.18 274 | 81.25 248 | 76.95 343 | 83.15 370 | 60.84 331 | 82.46 255 | 85.99 292 | 68.76 276 | 86.78 196 | 93.73 119 | 59.13 352 | 77.44 412 | 73.71 230 | 97.55 78 | 92.56 206 |
|
| LFMVS | | | 80.15 275 | 80.56 261 | 78.89 310 | 89.19 199 | 55.93 383 | 85.22 172 | 73.78 402 | 82.96 71 | 84.28 273 | 92.72 158 | 57.38 364 | 90.07 257 | 63.80 342 | 95.75 151 | 90.68 282 |
|
| DPM-MVS | | | 80.10 276 | 79.18 283 | 82.88 229 | 90.71 166 | 69.74 206 | 78.87 326 | 90.84 176 | 60.29 380 | 75.64 396 | 85.92 351 | 67.28 296 | 93.11 152 | 71.24 263 | 91.79 285 | 85.77 370 |
|
| MSDG | | | 80.06 277 | 79.99 276 | 80.25 292 | 83.91 349 | 68.04 233 | 77.51 348 | 89.19 227 | 77.65 137 | 81.94 320 | 83.45 385 | 76.37 206 | 86.31 337 | 63.31 347 | 86.59 386 | 86.41 362 |
|
| FE-MVS | | | 79.98 278 | 78.86 286 | 83.36 210 | 86.47 283 | 66.45 251 | 89.73 75 | 84.74 320 | 72.80 215 | 84.22 276 | 91.38 209 | 44.95 431 | 93.60 131 | 63.93 340 | 91.50 294 | 90.04 302 |
|
| sd_testset | | | 79.95 279 | 81.39 245 | 75.64 362 | 88.81 212 | 58.07 367 | 76.16 373 | 82.81 338 | 73.67 191 | 83.41 291 | 93.04 140 | 80.96 141 | 77.65 411 | 58.62 377 | 95.03 175 | 91.21 263 |
|
| ab-mvs | | | 79.67 280 | 80.56 261 | 76.99 342 | 88.48 222 | 56.93 377 | 84.70 185 | 86.06 289 | 68.95 273 | 80.78 341 | 93.08 139 | 75.30 213 | 84.62 364 | 56.78 386 | 90.90 310 | 89.43 311 |
|
| VNet | | | 79.31 281 | 80.27 266 | 76.44 351 | 87.92 235 | 53.95 401 | 75.58 380 | 84.35 324 | 74.39 184 | 82.23 313 | 90.72 241 | 72.84 257 | 84.39 369 | 60.38 369 | 93.98 214 | 90.97 271 |
|
| thisisatest0530 | | | 79.07 282 | 77.33 306 | 84.26 181 | 87.13 262 | 64.58 267 | 83.66 217 | 75.95 385 | 68.86 274 | 85.22 242 | 87.36 327 | 38.10 448 | 93.57 135 | 75.47 203 | 94.28 204 | 94.62 89 |
|
| cl22 | | | 78.97 283 | 78.21 298 | 81.24 271 | 77.74 420 | 59.01 356 | 77.46 351 | 87.13 270 | 65.79 317 | 84.32 269 | 85.10 365 | 58.96 354 | 90.88 222 | 75.36 205 | 92.03 278 | 93.84 131 |
|
| patch_mono-2 | | | 78.89 284 | 79.39 280 | 77.41 338 | 84.78 330 | 68.11 231 | 75.60 378 | 83.11 334 | 60.96 372 | 79.36 358 | 89.89 273 | 75.18 214 | 72.97 427 | 73.32 242 | 92.30 268 | 91.15 265 |
|
| RPMNet | | | 78.88 285 | 78.28 297 | 80.68 284 | 79.58 407 | 62.64 292 | 82.58 250 | 94.16 33 | 74.80 173 | 75.72 394 | 92.59 160 | 48.69 403 | 95.56 45 | 73.48 237 | 82.91 425 | 83.85 396 |
|
| PAPR | | | 78.84 286 | 78.10 299 | 81.07 273 | 85.17 325 | 60.22 339 | 82.21 266 | 90.57 185 | 62.51 349 | 75.32 400 | 84.61 373 | 74.99 216 | 92.30 176 | 59.48 374 | 88.04 364 | 90.68 282 |
|
| viewmambaseed2359dif | | | 78.80 287 | 78.47 295 | 79.78 298 | 80.26 402 | 59.28 351 | 77.31 353 | 87.13 270 | 60.42 378 | 82.37 310 | 88.67 297 | 74.58 226 | 87.87 308 | 67.78 307 | 87.73 370 | 92.19 232 |
|
| PVSNet_BlendedMVS | | | 78.80 287 | 77.84 300 | 81.65 261 | 84.43 336 | 63.41 280 | 79.49 312 | 90.44 190 | 61.70 361 | 75.43 397 | 87.07 334 | 69.11 288 | 91.44 198 | 60.68 367 | 92.24 272 | 90.11 300 |
|
| FMVSNet3 | | | 78.80 287 | 78.55 292 | 79.57 304 | 82.89 373 | 56.89 379 | 81.76 272 | 85.77 296 | 69.04 271 | 86.00 222 | 90.44 255 | 51.75 392 | 90.09 255 | 65.95 320 | 93.34 235 | 91.72 250 |
|
| test_yl | | | 78.71 290 | 78.51 293 | 79.32 307 | 84.32 340 | 58.84 360 | 78.38 332 | 85.33 304 | 75.99 155 | 82.49 307 | 86.57 339 | 58.01 358 | 90.02 259 | 62.74 349 | 92.73 258 | 89.10 322 |
|
| DCV-MVSNet | | | 78.71 290 | 78.51 293 | 79.32 307 | 84.32 340 | 58.84 360 | 78.38 332 | 85.33 304 | 75.99 155 | 82.49 307 | 86.57 339 | 58.01 358 | 90.02 259 | 62.74 349 | 92.73 258 | 89.10 322 |
|
| test1111 | | | 78.53 292 | 78.85 287 | 77.56 335 | 92.22 113 | 47.49 438 | 82.61 248 | 69.24 434 | 72.43 220 | 85.28 241 | 94.20 90 | 51.91 390 | 90.07 257 | 65.36 328 | 96.45 112 | 95.11 73 |
|
| FE-MVSNET | | | 78.46 293 | 79.36 281 | 75.75 359 | 86.53 281 | 54.53 396 | 78.03 336 | 85.35 303 | 69.01 272 | 85.41 238 | 90.68 244 | 64.27 315 | 85.73 354 | 62.59 351 | 92.35 267 | 87.00 357 |
|
| icg_test_0407_2 | | | 78.46 293 | 79.68 277 | 74.78 369 | 85.76 310 | 62.46 296 | 68.51 434 | 87.91 254 | 65.23 330 | 82.12 316 | 87.92 310 | 77.27 186 | 72.67 428 | 71.67 257 | 90.74 318 | 89.20 316 |
|
| ECVR-MVS |  | | 78.44 295 | 78.63 291 | 77.88 331 | 91.85 127 | 48.95 432 | 83.68 216 | 69.91 430 | 72.30 226 | 84.26 275 | 94.20 90 | 51.89 391 | 89.82 263 | 63.58 343 | 96.02 132 | 94.87 79 |
|
| pmmvs-eth3d | | | 78.42 296 | 77.04 309 | 82.57 236 | 87.44 254 | 74.41 138 | 80.86 292 | 79.67 362 | 55.68 409 | 84.69 259 | 90.31 261 | 60.91 338 | 85.42 357 | 62.20 354 | 91.59 292 | 87.88 345 |
|
| mvs_anonymous | | | 78.13 297 | 78.76 289 | 76.23 356 | 79.24 413 | 50.31 428 | 78.69 329 | 84.82 318 | 61.60 363 | 83.09 299 | 92.82 153 | 73.89 238 | 87.01 320 | 68.33 303 | 86.41 388 | 91.37 260 |
|
| TAMVS | | | 78.08 298 | 76.36 316 | 83.23 214 | 90.62 167 | 72.87 154 | 79.08 322 | 80.01 361 | 61.72 360 | 81.35 334 | 86.92 336 | 63.96 322 | 88.78 285 | 50.61 425 | 93.01 248 | 88.04 340 |
|
| miper_enhance_ethall | | | 77.83 299 | 76.93 310 | 80.51 287 | 76.15 437 | 58.01 369 | 75.47 382 | 88.82 231 | 58.05 394 | 83.59 287 | 80.69 411 | 64.41 314 | 91.20 207 | 73.16 249 | 92.03 278 | 92.33 223 |
|
| Vis-MVSNet (Re-imp) | | | 77.82 300 | 77.79 301 | 77.92 330 | 88.82 211 | 51.29 422 | 83.28 228 | 71.97 418 | 74.04 186 | 82.23 313 | 89.78 274 | 57.38 364 | 89.41 275 | 57.22 385 | 95.41 159 | 93.05 179 |
|
| CANet_DTU | | | 77.81 301 | 77.05 308 | 80.09 296 | 81.37 386 | 59.90 345 | 83.26 229 | 88.29 245 | 69.16 268 | 67.83 444 | 83.72 381 | 60.93 337 | 89.47 270 | 69.22 289 | 89.70 338 | 90.88 275 |
|
| OpenMVS_ROB |  | 70.19 17 | 77.77 302 | 77.46 303 | 78.71 314 | 84.39 339 | 61.15 321 | 81.18 285 | 82.52 339 | 62.45 352 | 83.34 293 | 87.37 326 | 66.20 302 | 88.66 289 | 64.69 335 | 85.02 405 | 86.32 363 |
|
| SSC-MVS | | | 77.55 303 | 81.64 234 | 65.29 435 | 90.46 170 | 20.33 482 | 73.56 398 | 68.28 436 | 85.44 41 | 88.18 160 | 94.64 69 | 70.93 277 | 81.33 390 | 71.25 262 | 92.03 278 | 94.20 112 |
|
| MDA-MVSNet-bldmvs | | | 77.47 304 | 76.90 311 | 79.16 309 | 79.03 415 | 64.59 266 | 66.58 446 | 75.67 388 | 73.15 207 | 88.86 138 | 88.99 291 | 66.94 298 | 81.23 391 | 64.71 334 | 88.22 363 | 91.64 254 |
|
| jason | | | 77.42 305 | 75.75 322 | 82.43 242 | 87.10 265 | 69.27 213 | 77.99 338 | 81.94 346 | 51.47 436 | 77.84 373 | 85.07 368 | 60.32 342 | 89.00 279 | 70.74 270 | 89.27 345 | 89.03 326 |
| jason: jason. |
| CDS-MVSNet | | | 77.32 306 | 75.40 326 | 83.06 218 | 89.00 205 | 72.48 165 | 77.90 341 | 82.17 344 | 60.81 373 | 78.94 364 | 83.49 384 | 59.30 350 | 88.76 286 | 54.64 405 | 92.37 266 | 87.93 344 |
| Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
| IMVS_0404 | | | 77.24 307 | 77.75 302 | 75.73 360 | 85.76 310 | 62.46 296 | 70.84 420 | 87.91 254 | 65.23 330 | 72.21 419 | 87.92 310 | 67.48 295 | 75.53 420 | 71.67 257 | 90.74 318 | 89.20 316 |
|
| xiu_mvs_v2_base | | | 77.19 308 | 76.75 313 | 78.52 317 | 87.01 271 | 61.30 318 | 75.55 381 | 87.12 274 | 61.24 369 | 74.45 406 | 78.79 431 | 77.20 188 | 90.93 218 | 64.62 337 | 84.80 412 | 83.32 405 |
|
| MVSTER | | | 77.09 309 | 75.70 323 | 81.25 269 | 75.27 445 | 61.08 323 | 77.49 350 | 85.07 309 | 60.78 374 | 86.55 204 | 88.68 295 | 43.14 440 | 90.25 243 | 73.69 233 | 90.67 323 | 92.42 213 |
|
| PS-MVSNAJ | | | 77.04 310 | 76.53 315 | 78.56 316 | 87.09 267 | 61.40 315 | 75.26 383 | 87.13 270 | 61.25 368 | 74.38 408 | 77.22 445 | 76.94 194 | 90.94 217 | 64.63 336 | 84.83 411 | 83.35 404 |
|
| IterMVS | | | 76.91 311 | 76.34 317 | 78.64 315 | 80.91 391 | 64.03 274 | 76.30 369 | 79.03 365 | 64.88 336 | 83.11 297 | 89.16 287 | 59.90 346 | 84.46 367 | 68.61 299 | 85.15 403 | 87.42 350 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
| D2MVS | | | 76.84 312 | 75.67 324 | 80.34 290 | 80.48 400 | 62.16 309 | 73.50 399 | 84.80 319 | 57.61 398 | 82.24 312 | 87.54 321 | 51.31 393 | 87.65 311 | 70.40 276 | 93.19 244 | 91.23 262 |
|
| CL-MVSNet_self_test | | | 76.81 313 | 77.38 305 | 75.12 365 | 86.90 276 | 51.34 420 | 73.20 402 | 80.63 358 | 68.30 283 | 81.80 326 | 88.40 300 | 66.92 299 | 80.90 392 | 55.35 399 | 94.90 181 | 93.12 176 |
|
| TR-MVS | | | 76.77 314 | 75.79 321 | 79.72 301 | 86.10 302 | 65.79 258 | 77.14 354 | 83.02 335 | 65.20 334 | 81.40 333 | 82.10 399 | 66.30 301 | 90.73 229 | 55.57 396 | 85.27 399 | 82.65 412 |
|
| MonoMVSNet | | | 76.66 315 | 77.26 307 | 74.86 367 | 79.86 405 | 54.34 398 | 86.26 147 | 86.08 288 | 71.08 244 | 85.59 233 | 88.68 295 | 53.95 382 | 85.93 345 | 63.86 341 | 80.02 441 | 84.32 387 |
|
| USDC | | | 76.63 316 | 76.73 314 | 76.34 353 | 83.46 357 | 57.20 376 | 80.02 303 | 88.04 251 | 52.14 432 | 83.65 286 | 91.25 216 | 63.24 326 | 86.65 330 | 54.66 404 | 94.11 209 | 85.17 376 |
|
| BH-w/o | | | 76.57 317 | 76.07 320 | 78.10 326 | 86.88 277 | 65.92 257 | 77.63 345 | 86.33 283 | 65.69 321 | 80.89 339 | 79.95 420 | 68.97 290 | 90.74 228 | 53.01 415 | 85.25 400 | 77.62 448 |
|
| Patchmtry | | | 76.56 318 | 77.46 303 | 73.83 375 | 79.37 412 | 46.60 442 | 82.41 259 | 76.90 379 | 73.81 189 | 85.56 235 | 92.38 168 | 48.07 406 | 83.98 374 | 63.36 346 | 95.31 165 | 90.92 273 |
|
| PVSNet_Blended | | | 76.49 319 | 75.40 326 | 79.76 300 | 84.43 336 | 63.41 280 | 75.14 384 | 90.44 190 | 57.36 400 | 75.43 397 | 78.30 434 | 69.11 288 | 91.44 198 | 60.68 367 | 87.70 372 | 84.42 386 |
|
| miper_lstm_enhance | | | 76.45 320 | 76.10 319 | 77.51 336 | 76.72 431 | 60.97 330 | 64.69 450 | 85.04 311 | 63.98 341 | 83.20 296 | 88.22 302 | 56.67 368 | 78.79 408 | 73.22 243 | 93.12 245 | 92.78 192 |
|
| lupinMVS | | | 76.37 321 | 74.46 335 | 82.09 248 | 85.54 316 | 69.26 214 | 76.79 359 | 80.77 357 | 50.68 443 | 76.23 387 | 82.82 393 | 58.69 355 | 88.94 280 | 69.85 281 | 88.77 351 | 88.07 337 |
|
| cascas | | | 76.29 322 | 74.81 331 | 80.72 282 | 84.47 335 | 62.94 286 | 73.89 396 | 87.34 262 | 55.94 407 | 75.16 402 | 76.53 450 | 63.97 321 | 91.16 209 | 65.00 331 | 90.97 308 | 88.06 339 |
|
| SD_0403 | | | 76.08 323 | 76.77 312 | 73.98 373 | 87.08 269 | 49.45 431 | 83.62 218 | 84.68 321 | 63.31 342 | 75.13 403 | 87.47 324 | 71.85 270 | 84.56 365 | 49.97 427 | 87.86 368 | 87.94 343 |
|
| WB-MVS | | | 76.06 324 | 80.01 275 | 64.19 438 | 89.96 184 | 20.58 481 | 72.18 409 | 68.19 437 | 83.21 67 | 86.46 212 | 93.49 124 | 70.19 282 | 78.97 406 | 65.96 319 | 90.46 329 | 93.02 180 |
|
| thres600view7 | | | 75.97 325 | 75.35 328 | 77.85 333 | 87.01 271 | 51.84 418 | 80.45 298 | 73.26 407 | 75.20 170 | 83.10 298 | 86.31 345 | 45.54 421 | 89.05 278 | 55.03 402 | 92.24 272 | 92.66 199 |
|
| GA-MVS | | | 75.83 326 | 74.61 332 | 79.48 306 | 81.87 378 | 59.25 352 | 73.42 400 | 82.88 336 | 68.68 277 | 79.75 353 | 81.80 404 | 50.62 397 | 89.46 271 | 66.85 311 | 85.64 396 | 89.72 306 |
|
| MVP-Stereo | | | 75.81 327 | 73.51 344 | 82.71 231 | 89.35 194 | 73.62 142 | 80.06 301 | 85.20 306 | 60.30 379 | 73.96 409 | 87.94 307 | 57.89 362 | 89.45 272 | 52.02 419 | 74.87 459 | 85.06 378 |
| Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
| test_fmvs3 | | | 75.72 328 | 75.20 329 | 77.27 339 | 75.01 448 | 69.47 211 | 78.93 323 | 84.88 316 | 46.67 450 | 87.08 191 | 87.84 315 | 50.44 399 | 71.62 433 | 77.42 174 | 88.53 354 | 90.72 279 |
|
| thres100view900 | | | 75.45 329 | 75.05 330 | 76.66 349 | 87.27 256 | 51.88 417 | 81.07 286 | 73.26 407 | 75.68 161 | 83.25 295 | 86.37 342 | 45.54 421 | 88.80 282 | 51.98 420 | 90.99 305 | 89.31 313 |
|
| ET-MVSNet_ETH3D | | | 75.28 330 | 72.77 353 | 82.81 230 | 83.03 372 | 68.11 231 | 77.09 355 | 76.51 383 | 60.67 376 | 77.60 378 | 80.52 415 | 38.04 449 | 91.15 210 | 70.78 268 | 90.68 322 | 89.17 320 |
|
| thres400 | | | 75.14 331 | 74.23 337 | 77.86 332 | 86.24 295 | 52.12 414 | 79.24 319 | 73.87 400 | 73.34 200 | 81.82 324 | 84.60 374 | 46.02 414 | 88.80 282 | 51.98 420 | 90.99 305 | 92.66 199 |
|
| wuyk23d | | | 75.13 332 | 79.30 282 | 62.63 441 | 75.56 441 | 75.18 134 | 80.89 291 | 73.10 409 | 75.06 172 | 94.76 16 | 95.32 46 | 87.73 45 | 52.85 473 | 34.16 471 | 97.11 91 | 59.85 469 |
|
| EU-MVSNet | | | 75.12 333 | 74.43 336 | 77.18 340 | 83.11 371 | 59.48 349 | 85.71 160 | 82.43 341 | 39.76 470 | 85.64 232 | 88.76 293 | 44.71 433 | 87.88 307 | 73.86 227 | 85.88 395 | 84.16 392 |
|
| HyFIR lowres test | | | 75.12 333 | 72.66 355 | 82.50 239 | 91.44 146 | 65.19 263 | 72.47 407 | 87.31 263 | 46.79 449 | 80.29 348 | 84.30 376 | 52.70 387 | 92.10 182 | 51.88 424 | 86.73 384 | 90.22 295 |
|
| CMPMVS |  | 59.41 20 | 75.12 333 | 73.57 342 | 79.77 299 | 75.84 440 | 67.22 237 | 81.21 284 | 82.18 343 | 50.78 441 | 76.50 383 | 87.66 319 | 55.20 378 | 82.99 380 | 62.17 356 | 90.64 327 | 89.09 324 |
| M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
| pmmvs4 | | | 74.92 336 | 72.98 351 | 80.73 281 | 84.95 327 | 71.71 180 | 76.23 371 | 77.59 372 | 52.83 426 | 77.73 377 | 86.38 341 | 56.35 371 | 84.97 361 | 57.72 384 | 87.05 379 | 85.51 373 |
|
| tfpn200view9 | | | 74.86 337 | 74.23 337 | 76.74 348 | 86.24 295 | 52.12 414 | 79.24 319 | 73.87 400 | 73.34 200 | 81.82 324 | 84.60 374 | 46.02 414 | 88.80 282 | 51.98 420 | 90.99 305 | 89.31 313 |
|
| 1112_ss | | | 74.82 338 | 73.74 340 | 78.04 328 | 89.57 188 | 60.04 341 | 76.49 367 | 87.09 275 | 54.31 417 | 73.66 412 | 79.80 421 | 60.25 343 | 86.76 329 | 58.37 378 | 84.15 416 | 87.32 352 |
|
| EGC-MVSNET | | | 74.79 339 | 69.99 383 | 89.19 67 | 94.89 38 | 87.00 15 | 91.89 42 | 86.28 284 | 1.09 479 | 2.23 481 | 95.98 31 | 81.87 129 | 89.48 269 | 79.76 136 | 95.96 135 | 91.10 266 |
|
| ppachtmachnet_test | | | 74.73 340 | 74.00 339 | 76.90 345 | 80.71 396 | 56.89 379 | 71.53 415 | 78.42 367 | 58.24 391 | 79.32 360 | 82.92 392 | 57.91 361 | 84.26 371 | 65.60 326 | 91.36 296 | 89.56 308 |
|
| Patchmatch-RL test | | | 74.48 341 | 73.68 341 | 76.89 346 | 84.83 329 | 66.54 248 | 72.29 408 | 69.16 435 | 57.70 396 | 86.76 197 | 86.33 343 | 45.79 420 | 82.59 381 | 69.63 284 | 90.65 326 | 81.54 428 |
|
| PatchMatch-RL | | | 74.48 341 | 73.22 348 | 78.27 324 | 87.70 242 | 85.26 38 | 75.92 376 | 70.09 428 | 64.34 339 | 76.09 390 | 81.25 409 | 65.87 307 | 78.07 410 | 53.86 407 | 83.82 418 | 71.48 457 |
|
| XXY-MVS | | | 74.44 343 | 76.19 318 | 69.21 410 | 84.61 334 | 52.43 413 | 71.70 412 | 77.18 377 | 60.73 375 | 80.60 342 | 90.96 230 | 75.44 210 | 69.35 441 | 56.13 391 | 88.33 358 | 85.86 369 |
|
| test2506 | | | 74.12 344 | 73.39 345 | 76.28 354 | 91.85 127 | 44.20 452 | 84.06 201 | 48.20 477 | 72.30 226 | 81.90 321 | 94.20 90 | 27.22 476 | 89.77 266 | 64.81 333 | 96.02 132 | 94.87 79 |
|
| reproduce_monomvs | | | 74.09 345 | 73.23 347 | 76.65 350 | 76.52 432 | 54.54 395 | 77.50 349 | 81.40 352 | 65.85 316 | 82.86 303 | 86.67 338 | 27.38 474 | 84.53 366 | 70.24 277 | 90.66 325 | 90.89 274 |
|
| CR-MVSNet | | | 74.00 346 | 73.04 350 | 76.85 347 | 79.58 407 | 62.64 292 | 82.58 250 | 76.90 379 | 50.50 444 | 75.72 394 | 92.38 168 | 48.07 406 | 84.07 373 | 68.72 298 | 82.91 425 | 83.85 396 |
|
| SSC-MVS3.2 | | | 73.90 347 | 75.67 324 | 68.61 418 | 84.11 345 | 41.28 460 | 64.17 452 | 72.83 410 | 72.09 229 | 79.08 363 | 87.94 307 | 70.31 280 | 73.89 426 | 55.99 392 | 94.49 196 | 90.67 284 |
|
| Test_1112_low_res | | | 73.90 347 | 73.08 349 | 76.35 352 | 90.35 172 | 55.95 382 | 73.40 401 | 86.17 286 | 50.70 442 | 73.14 413 | 85.94 350 | 58.31 357 | 85.90 349 | 56.51 388 | 83.22 422 | 87.20 354 |
|
| test20.03 | | | 73.75 349 | 74.59 334 | 71.22 396 | 81.11 389 | 51.12 424 | 70.15 426 | 72.10 417 | 70.42 251 | 80.28 350 | 91.50 203 | 64.21 317 | 74.72 424 | 46.96 445 | 94.58 194 | 87.82 347 |
|
| test_fmvs2 | | | 73.57 350 | 72.80 352 | 75.90 358 | 72.74 462 | 68.84 224 | 77.07 356 | 84.32 325 | 45.14 456 | 82.89 301 | 84.22 377 | 48.37 404 | 70.36 437 | 73.40 239 | 87.03 380 | 88.52 332 |
|
| SCA | | | 73.32 351 | 72.57 357 | 75.58 363 | 81.62 382 | 55.86 385 | 78.89 325 | 71.37 423 | 61.73 359 | 74.93 404 | 83.42 386 | 60.46 340 | 87.01 320 | 58.11 382 | 82.63 430 | 83.88 393 |
|
| baseline1 | | | 73.26 352 | 73.54 343 | 72.43 389 | 84.92 328 | 47.79 437 | 79.89 305 | 74.00 398 | 65.93 314 | 78.81 365 | 86.28 346 | 56.36 370 | 81.63 389 | 56.63 387 | 79.04 448 | 87.87 346 |
|
| 1314 | | | 73.22 353 | 72.56 358 | 75.20 364 | 80.41 401 | 57.84 370 | 81.64 275 | 85.36 302 | 51.68 435 | 73.10 414 | 76.65 449 | 61.45 335 | 85.19 359 | 63.54 344 | 79.21 446 | 82.59 413 |
|
| MVS | | | 73.21 354 | 72.59 356 | 75.06 366 | 80.97 390 | 60.81 332 | 81.64 275 | 85.92 295 | 46.03 454 | 71.68 422 | 77.54 440 | 68.47 291 | 89.77 266 | 55.70 395 | 85.39 397 | 74.60 454 |
|
| HY-MVS | | 64.64 18 | 73.03 355 | 72.47 359 | 74.71 370 | 83.36 362 | 54.19 399 | 82.14 269 | 81.96 345 | 56.76 406 | 69.57 436 | 86.21 347 | 60.03 344 | 84.83 363 | 49.58 432 | 82.65 428 | 85.11 377 |
|
| thisisatest0515 | | | 73.00 356 | 70.52 375 | 80.46 288 | 81.45 384 | 59.90 345 | 73.16 403 | 74.31 397 | 57.86 395 | 76.08 391 | 77.78 437 | 37.60 452 | 92.12 181 | 65.00 331 | 91.45 295 | 89.35 312 |
|
| EPNet_dtu | | | 72.87 357 | 71.33 369 | 77.49 337 | 77.72 421 | 60.55 335 | 82.35 260 | 75.79 386 | 66.49 311 | 58.39 472 | 81.06 410 | 53.68 383 | 85.98 344 | 53.55 410 | 92.97 250 | 85.95 367 |
| Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
| CVMVSNet | | | 72.62 358 | 71.41 368 | 76.28 354 | 83.25 366 | 60.34 337 | 83.50 222 | 79.02 366 | 37.77 474 | 76.33 385 | 85.10 365 | 49.60 402 | 87.41 316 | 70.54 274 | 77.54 454 | 81.08 435 |
|
| CHOSEN 1792x2688 | | | 72.45 359 | 70.56 374 | 78.13 325 | 90.02 183 | 63.08 285 | 68.72 433 | 83.16 333 | 42.99 464 | 75.92 392 | 85.46 358 | 57.22 366 | 85.18 360 | 49.87 430 | 81.67 432 | 86.14 365 |
|
| testgi | | | 72.36 360 | 74.61 332 | 65.59 432 | 80.56 399 | 42.82 457 | 68.29 435 | 73.35 406 | 66.87 308 | 81.84 323 | 89.93 271 | 72.08 267 | 66.92 455 | 46.05 449 | 92.54 262 | 87.01 356 |
|
| thres200 | | | 72.34 361 | 71.55 367 | 74.70 371 | 83.48 356 | 51.60 419 | 75.02 385 | 73.71 403 | 70.14 257 | 78.56 368 | 80.57 414 | 46.20 412 | 88.20 300 | 46.99 444 | 89.29 343 | 84.32 387 |
|
| FPMVS | | | 72.29 362 | 72.00 361 | 73.14 380 | 88.63 218 | 85.00 40 | 74.65 389 | 67.39 440 | 71.94 232 | 77.80 375 | 87.66 319 | 50.48 398 | 75.83 418 | 49.95 428 | 79.51 442 | 58.58 471 |
|
| FMVSNet5 | | | 72.10 363 | 71.69 363 | 73.32 378 | 81.57 383 | 53.02 408 | 76.77 360 | 78.37 368 | 63.31 342 | 76.37 384 | 91.85 189 | 36.68 453 | 78.98 405 | 47.87 441 | 92.45 264 | 87.95 342 |
|
| our_test_3 | | | 71.85 364 | 71.59 364 | 72.62 386 | 80.71 396 | 53.78 402 | 69.72 429 | 71.71 422 | 58.80 388 | 78.03 370 | 80.51 416 | 56.61 369 | 78.84 407 | 62.20 354 | 86.04 394 | 85.23 375 |
|
| PAPM | | | 71.77 365 | 70.06 381 | 76.92 344 | 86.39 286 | 53.97 400 | 76.62 364 | 86.62 281 | 53.44 421 | 63.97 461 | 84.73 372 | 57.79 363 | 92.34 174 | 39.65 461 | 81.33 436 | 84.45 385 |
|
| ttmdpeth | | | 71.72 366 | 70.67 372 | 74.86 367 | 73.08 459 | 55.88 384 | 77.41 352 | 69.27 433 | 55.86 408 | 78.66 366 | 93.77 117 | 38.01 450 | 75.39 421 | 60.12 370 | 89.87 336 | 93.31 164 |
|
| IB-MVS | | 62.13 19 | 71.64 367 | 68.97 393 | 79.66 303 | 80.80 395 | 62.26 305 | 73.94 395 | 76.90 379 | 63.27 344 | 68.63 440 | 76.79 447 | 33.83 457 | 91.84 189 | 59.28 375 | 87.26 374 | 84.88 379 |
| 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 |
| UnsupCasMVSNet_eth | | | 71.63 368 | 72.30 360 | 69.62 407 | 76.47 434 | 52.70 411 | 70.03 427 | 80.97 355 | 59.18 385 | 79.36 358 | 88.21 303 | 60.50 339 | 69.12 442 | 58.33 380 | 77.62 453 | 87.04 355 |
|
| testing3 | | | 71.53 369 | 70.79 371 | 73.77 376 | 88.89 210 | 41.86 459 | 76.60 366 | 59.12 466 | 72.83 214 | 80.97 336 | 82.08 401 | 19.80 482 | 87.33 318 | 65.12 330 | 91.68 290 | 92.13 236 |
|
| test_vis3_rt | | | 71.42 370 | 70.67 372 | 73.64 377 | 69.66 469 | 70.46 196 | 66.97 445 | 89.73 215 | 42.68 466 | 88.20 159 | 83.04 388 | 43.77 435 | 60.07 467 | 65.35 329 | 86.66 385 | 90.39 293 |
|
| Anonymous20231206 | | | 71.38 371 | 71.88 362 | 69.88 404 | 86.31 292 | 54.37 397 | 70.39 424 | 74.62 393 | 52.57 428 | 76.73 382 | 88.76 293 | 59.94 345 | 72.06 430 | 44.35 453 | 93.23 242 | 83.23 407 |
|
| test_vis1_n_1920 | | | 71.30 372 | 71.58 366 | 70.47 399 | 77.58 423 | 59.99 344 | 74.25 390 | 84.22 326 | 51.06 438 | 74.85 405 | 79.10 427 | 55.10 379 | 68.83 444 | 68.86 295 | 79.20 447 | 82.58 414 |
|
| MIMVSNet | | | 71.09 373 | 71.59 364 | 69.57 408 | 87.23 259 | 50.07 429 | 78.91 324 | 71.83 419 | 60.20 382 | 71.26 423 | 91.76 196 | 55.08 380 | 76.09 416 | 41.06 458 | 87.02 381 | 82.54 416 |
|
| test_fmvs1_n | | | 70.94 374 | 70.41 378 | 72.53 388 | 73.92 450 | 66.93 245 | 75.99 375 | 84.21 327 | 43.31 463 | 79.40 357 | 79.39 425 | 43.47 436 | 68.55 446 | 69.05 292 | 84.91 408 | 82.10 422 |
|
| MS-PatchMatch | | | 70.93 375 | 70.22 379 | 73.06 381 | 81.85 379 | 62.50 295 | 73.82 397 | 77.90 369 | 52.44 429 | 75.92 392 | 81.27 408 | 55.67 375 | 81.75 387 | 55.37 398 | 77.70 452 | 74.94 453 |
|
| pmmvs5 | | | 70.73 376 | 70.07 380 | 72.72 384 | 77.03 428 | 52.73 410 | 74.14 391 | 75.65 389 | 50.36 445 | 72.17 420 | 85.37 362 | 55.42 377 | 80.67 394 | 52.86 416 | 87.59 373 | 84.77 380 |
|
| testing3-2 | | | 70.72 377 | 70.97 370 | 69.95 403 | 88.93 208 | 34.80 473 | 69.85 428 | 66.59 447 | 78.42 127 | 77.58 379 | 85.55 354 | 31.83 463 | 82.08 385 | 46.28 446 | 93.73 224 | 92.98 186 |
|
| PatchT | | | 70.52 378 | 72.76 354 | 63.79 440 | 79.38 411 | 33.53 474 | 77.63 345 | 65.37 451 | 73.61 193 | 71.77 421 | 92.79 156 | 44.38 434 | 75.65 419 | 64.53 338 | 85.37 398 | 82.18 421 |
|
| test_vis1_n | | | 70.29 379 | 69.99 383 | 71.20 397 | 75.97 439 | 66.50 249 | 76.69 362 | 80.81 356 | 44.22 459 | 75.43 397 | 77.23 444 | 50.00 400 | 68.59 445 | 66.71 314 | 82.85 427 | 78.52 447 |
|
| N_pmnet | | | 70.20 380 | 68.80 395 | 74.38 372 | 80.91 391 | 84.81 43 | 59.12 463 | 76.45 384 | 55.06 412 | 75.31 401 | 82.36 398 | 55.74 374 | 54.82 472 | 47.02 443 | 87.24 375 | 83.52 400 |
|
| tpmvs | | | 70.16 381 | 69.56 386 | 71.96 392 | 74.71 449 | 48.13 434 | 79.63 307 | 75.45 391 | 65.02 335 | 70.26 431 | 81.88 403 | 45.34 426 | 85.68 355 | 58.34 379 | 75.39 458 | 82.08 423 |
|
| new-patchmatchnet | | | 70.10 382 | 73.37 346 | 60.29 449 | 81.23 388 | 16.95 484 | 59.54 461 | 74.62 393 | 62.93 346 | 80.97 336 | 87.93 309 | 62.83 332 | 71.90 431 | 55.24 400 | 95.01 178 | 92.00 241 |
|
| YYNet1 | | | 70.06 383 | 70.44 376 | 68.90 412 | 73.76 452 | 53.42 406 | 58.99 464 | 67.20 442 | 58.42 390 | 87.10 189 | 85.39 361 | 59.82 347 | 67.32 452 | 59.79 372 | 83.50 421 | 85.96 366 |
|
| MVStest1 | | | 70.05 384 | 69.26 387 | 72.41 390 | 58.62 481 | 55.59 388 | 76.61 365 | 65.58 449 | 53.44 421 | 89.28 133 | 93.32 128 | 22.91 480 | 71.44 435 | 74.08 223 | 89.52 340 | 90.21 299 |
|
| MDA-MVSNet_test_wron | | | 70.05 384 | 70.44 376 | 68.88 413 | 73.84 451 | 53.47 404 | 58.93 465 | 67.28 441 | 58.43 389 | 87.09 190 | 85.40 360 | 59.80 348 | 67.25 453 | 59.66 373 | 83.54 420 | 85.92 368 |
|
| CostFormer | | | 69.98 386 | 68.68 396 | 73.87 374 | 77.14 426 | 50.72 426 | 79.26 318 | 74.51 395 | 51.94 434 | 70.97 426 | 84.75 371 | 45.16 429 | 87.49 314 | 55.16 401 | 79.23 445 | 83.40 403 |
|
| testing91 | | | 69.94 387 | 68.99 392 | 72.80 383 | 83.81 351 | 45.89 445 | 71.57 414 | 73.64 405 | 68.24 284 | 70.77 429 | 77.82 436 | 34.37 456 | 84.44 368 | 53.64 409 | 87.00 382 | 88.07 337 |
|
| baseline2 | | | 69.77 388 | 66.89 405 | 78.41 320 | 79.51 409 | 58.09 366 | 76.23 371 | 69.57 431 | 57.50 399 | 64.82 459 | 77.45 442 | 46.02 414 | 88.44 294 | 53.08 412 | 77.83 450 | 88.70 330 |
|
| PatchmatchNet |  | | 69.71 389 | 68.83 394 | 72.33 391 | 77.66 422 | 53.60 403 | 79.29 317 | 69.99 429 | 57.66 397 | 72.53 417 | 82.93 391 | 46.45 411 | 80.08 400 | 60.91 366 | 72.09 462 | 83.31 406 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
| test_fmvs1 | | | 69.57 390 | 69.05 390 | 71.14 398 | 69.15 470 | 65.77 259 | 73.98 394 | 83.32 331 | 42.83 465 | 77.77 376 | 78.27 435 | 43.39 439 | 68.50 447 | 68.39 302 | 84.38 415 | 79.15 445 |
|
| JIA-IIPM | | | 69.41 391 | 66.64 409 | 77.70 334 | 73.19 456 | 71.24 187 | 75.67 377 | 65.56 450 | 70.42 251 | 65.18 455 | 92.97 147 | 33.64 459 | 83.06 378 | 53.52 411 | 69.61 468 | 78.79 446 |
|
| Syy-MVS | | | 69.40 392 | 70.03 382 | 67.49 423 | 81.72 380 | 38.94 465 | 71.00 417 | 61.99 457 | 61.38 365 | 70.81 427 | 72.36 461 | 61.37 336 | 79.30 403 | 64.50 339 | 85.18 401 | 84.22 389 |
|
| testing99 | | | 69.27 393 | 68.15 400 | 72.63 385 | 83.29 364 | 45.45 447 | 71.15 416 | 71.08 424 | 67.34 301 | 70.43 430 | 77.77 438 | 32.24 462 | 84.35 370 | 53.72 408 | 86.33 390 | 88.10 336 |
|
| UnsupCasMVSNet_bld | | | 69.21 394 | 69.68 385 | 67.82 421 | 79.42 410 | 51.15 423 | 67.82 439 | 75.79 386 | 54.15 418 | 77.47 380 | 85.36 363 | 59.26 351 | 70.64 436 | 48.46 438 | 79.35 444 | 81.66 426 |
|
| test_cas_vis1_n_1920 | | | 69.20 395 | 69.12 388 | 69.43 409 | 73.68 453 | 62.82 289 | 70.38 425 | 77.21 376 | 46.18 453 | 80.46 347 | 78.95 429 | 52.03 389 | 65.53 460 | 65.77 325 | 77.45 455 | 79.95 443 |
|
| gg-mvs-nofinetune | | | 68.96 396 | 69.11 389 | 68.52 419 | 76.12 438 | 45.32 448 | 83.59 219 | 55.88 471 | 86.68 33 | 64.62 460 | 97.01 12 | 30.36 467 | 83.97 375 | 44.78 452 | 82.94 424 | 76.26 450 |
|
| WBMVS | | | 68.76 397 | 68.43 397 | 69.75 406 | 83.29 364 | 40.30 463 | 67.36 441 | 72.21 416 | 57.09 403 | 77.05 381 | 85.53 356 | 33.68 458 | 80.51 396 | 48.79 436 | 90.90 310 | 88.45 333 |
|
| WB-MVSnew | | | 68.72 398 | 69.01 391 | 67.85 420 | 83.22 368 | 43.98 453 | 74.93 386 | 65.98 448 | 55.09 411 | 73.83 410 | 79.11 426 | 65.63 309 | 71.89 432 | 38.21 466 | 85.04 404 | 87.69 348 |
|
| tpm2 | | | 68.45 399 | 66.83 406 | 73.30 379 | 78.93 417 | 48.50 433 | 79.76 306 | 71.76 420 | 47.50 448 | 69.92 433 | 83.60 382 | 42.07 442 | 88.40 296 | 48.44 439 | 79.51 442 | 83.01 410 |
|
| tpm | | | 67.95 400 | 68.08 401 | 67.55 422 | 78.74 418 | 43.53 455 | 75.60 378 | 67.10 445 | 54.92 413 | 72.23 418 | 88.10 304 | 42.87 441 | 75.97 417 | 52.21 418 | 80.95 440 | 83.15 408 |
|
| WTY-MVS | | | 67.91 401 | 68.35 398 | 66.58 428 | 80.82 394 | 48.12 435 | 65.96 447 | 72.60 411 | 53.67 420 | 71.20 424 | 81.68 406 | 58.97 353 | 69.06 443 | 48.57 437 | 81.67 432 | 82.55 415 |
|
| testing11 | | | 67.38 402 | 65.93 410 | 71.73 394 | 83.37 361 | 46.60 442 | 70.95 419 | 69.40 432 | 62.47 351 | 66.14 448 | 76.66 448 | 31.22 464 | 84.10 372 | 49.10 434 | 84.10 417 | 84.49 383 |
|
| test-LLR | | | 67.21 403 | 66.74 407 | 68.63 416 | 76.45 435 | 55.21 391 | 67.89 436 | 67.14 443 | 62.43 354 | 65.08 456 | 72.39 459 | 43.41 437 | 69.37 439 | 61.00 364 | 84.89 409 | 81.31 430 |
|
| testing222 | | | 66.93 404 | 65.30 417 | 71.81 393 | 83.38 360 | 45.83 446 | 72.06 410 | 67.50 439 | 64.12 340 | 69.68 435 | 76.37 451 | 27.34 475 | 83.00 379 | 38.88 462 | 88.38 357 | 86.62 361 |
|
| sss | | | 66.92 405 | 67.26 403 | 65.90 430 | 77.23 425 | 51.10 425 | 64.79 449 | 71.72 421 | 52.12 433 | 70.13 432 | 80.18 418 | 57.96 360 | 65.36 461 | 50.21 426 | 81.01 438 | 81.25 432 |
|
| KD-MVS_2432*1600 | | | 66.87 406 | 65.81 413 | 70.04 401 | 67.50 471 | 47.49 438 | 62.56 455 | 79.16 363 | 61.21 370 | 77.98 371 | 80.61 412 | 25.29 478 | 82.48 382 | 53.02 413 | 84.92 406 | 80.16 441 |
|
| miper_refine_blended | | | 66.87 406 | 65.81 413 | 70.04 401 | 67.50 471 | 47.49 438 | 62.56 455 | 79.16 363 | 61.21 370 | 77.98 371 | 80.61 412 | 25.29 478 | 82.48 382 | 53.02 413 | 84.92 406 | 80.16 441 |
|
| dmvs_re | | | 66.81 408 | 66.98 404 | 66.28 429 | 76.87 429 | 58.68 364 | 71.66 413 | 72.24 414 | 60.29 380 | 69.52 437 | 73.53 458 | 52.38 388 | 64.40 463 | 44.90 451 | 81.44 435 | 75.76 451 |
|
| tpm cat1 | | | 66.76 409 | 65.21 418 | 71.42 395 | 77.09 427 | 50.62 427 | 78.01 337 | 73.68 404 | 44.89 457 | 68.64 439 | 79.00 428 | 45.51 423 | 82.42 384 | 49.91 429 | 70.15 465 | 81.23 434 |
|
| UWE-MVS | | | 66.43 410 | 65.56 416 | 69.05 411 | 84.15 344 | 40.98 461 | 73.06 404 | 64.71 453 | 54.84 414 | 76.18 389 | 79.62 424 | 29.21 469 | 80.50 397 | 38.54 465 | 89.75 337 | 85.66 371 |
|
| PVSNet | | 58.17 21 | 66.41 411 | 65.63 415 | 68.75 414 | 81.96 377 | 49.88 430 | 62.19 457 | 72.51 413 | 51.03 439 | 68.04 442 | 75.34 455 | 50.84 395 | 74.77 422 | 45.82 450 | 82.96 423 | 81.60 427 |
|
| tpmrst | | | 66.28 412 | 66.69 408 | 65.05 436 | 72.82 461 | 39.33 464 | 78.20 335 | 70.69 427 | 53.16 424 | 67.88 443 | 80.36 417 | 48.18 405 | 74.75 423 | 58.13 381 | 70.79 464 | 81.08 435 |
|
| Patchmatch-test | | | 65.91 413 | 67.38 402 | 61.48 446 | 75.51 442 | 43.21 456 | 68.84 432 | 63.79 455 | 62.48 350 | 72.80 416 | 83.42 386 | 44.89 432 | 59.52 469 | 48.27 440 | 86.45 387 | 81.70 425 |
|
| ADS-MVSNet2 | | | 65.87 414 | 63.64 423 | 72.55 387 | 73.16 457 | 56.92 378 | 67.10 443 | 74.81 392 | 49.74 446 | 66.04 450 | 82.97 389 | 46.71 409 | 77.26 413 | 42.29 455 | 69.96 466 | 83.46 401 |
|
| myMVS_eth3d28 | | | 65.83 415 | 65.85 411 | 65.78 431 | 83.42 359 | 35.71 471 | 67.29 442 | 68.01 438 | 67.58 298 | 69.80 434 | 77.72 439 | 32.29 461 | 74.30 425 | 37.49 467 | 89.06 347 | 87.32 352 |
|
| test_vis1_rt | | | 65.64 416 | 64.09 420 | 70.31 400 | 66.09 475 | 70.20 200 | 61.16 458 | 81.60 350 | 38.65 471 | 72.87 415 | 69.66 464 | 52.84 385 | 60.04 468 | 56.16 390 | 77.77 451 | 80.68 439 |
|
| mvsany_test3 | | | 65.48 417 | 62.97 426 | 73.03 382 | 69.99 468 | 76.17 124 | 64.83 448 | 43.71 479 | 43.68 461 | 80.25 351 | 87.05 335 | 52.83 386 | 63.09 466 | 51.92 423 | 72.44 461 | 79.84 444 |
|
| test-mter | | | 65.00 418 | 63.79 422 | 68.63 416 | 76.45 435 | 55.21 391 | 67.89 436 | 67.14 443 | 50.98 440 | 65.08 456 | 72.39 459 | 28.27 472 | 69.37 439 | 61.00 364 | 84.89 409 | 81.31 430 |
|
| ETVMVS | | | 64.67 419 | 63.34 425 | 68.64 415 | 83.44 358 | 41.89 458 | 69.56 431 | 61.70 462 | 61.33 367 | 68.74 438 | 75.76 453 | 28.76 470 | 79.35 402 | 34.65 470 | 86.16 393 | 84.67 382 |
|
| myMVS_eth3d | | | 64.66 420 | 63.89 421 | 66.97 426 | 81.72 380 | 37.39 468 | 71.00 417 | 61.99 457 | 61.38 365 | 70.81 427 | 72.36 461 | 20.96 481 | 79.30 403 | 49.59 431 | 85.18 401 | 84.22 389 |
|
| test0.0.03 1 | | | 64.66 420 | 64.36 419 | 65.57 433 | 75.03 447 | 46.89 441 | 64.69 450 | 61.58 463 | 62.43 354 | 71.18 425 | 77.54 440 | 43.41 437 | 68.47 448 | 40.75 460 | 82.65 428 | 81.35 429 |
|
| UBG | | | 64.34 422 | 63.35 424 | 67.30 424 | 83.50 355 | 40.53 462 | 67.46 440 | 65.02 452 | 54.77 415 | 67.54 446 | 74.47 457 | 32.99 460 | 78.50 409 | 40.82 459 | 83.58 419 | 82.88 411 |
|
| test_f | | | 64.31 423 | 65.85 411 | 59.67 450 | 66.54 474 | 62.24 307 | 57.76 467 | 70.96 425 | 40.13 468 | 84.36 267 | 82.09 400 | 46.93 408 | 51.67 474 | 61.99 357 | 81.89 431 | 65.12 465 |
|
| pmmvs3 | | | 62.47 424 | 60.02 437 | 69.80 405 | 71.58 465 | 64.00 275 | 70.52 423 | 58.44 469 | 39.77 469 | 66.05 449 | 75.84 452 | 27.10 477 | 72.28 429 | 46.15 448 | 84.77 413 | 73.11 455 |
|
| EPMVS | | | 62.47 424 | 62.63 428 | 62.01 442 | 70.63 467 | 38.74 466 | 74.76 387 | 52.86 473 | 53.91 419 | 67.71 445 | 80.01 419 | 39.40 446 | 66.60 456 | 55.54 397 | 68.81 470 | 80.68 439 |
|
| ADS-MVSNet | | | 61.90 426 | 62.19 430 | 61.03 447 | 73.16 457 | 36.42 470 | 67.10 443 | 61.75 460 | 49.74 446 | 66.04 450 | 82.97 389 | 46.71 409 | 63.21 464 | 42.29 455 | 69.96 466 | 83.46 401 |
|
| PMMVS | | | 61.65 427 | 60.38 434 | 65.47 434 | 65.40 478 | 69.26 214 | 63.97 453 | 61.73 461 | 36.80 475 | 60.11 467 | 68.43 466 | 59.42 349 | 66.35 457 | 48.97 435 | 78.57 449 | 60.81 468 |
|
| E-PMN | | | 61.59 428 | 61.62 431 | 61.49 445 | 66.81 473 | 55.40 389 | 53.77 470 | 60.34 465 | 66.80 309 | 58.90 470 | 65.50 469 | 40.48 445 | 66.12 458 | 55.72 394 | 86.25 391 | 62.95 467 |
|
| TESTMET0.1,1 | | | 61.29 429 | 60.32 435 | 64.19 438 | 72.06 463 | 51.30 421 | 67.89 436 | 62.09 456 | 45.27 455 | 60.65 466 | 69.01 465 | 27.93 473 | 64.74 462 | 56.31 389 | 81.65 434 | 76.53 449 |
|
| MVS-HIRNet | | | 61.16 430 | 62.92 427 | 55.87 453 | 79.09 414 | 35.34 472 | 71.83 411 | 57.98 470 | 46.56 451 | 59.05 469 | 91.14 221 | 49.95 401 | 76.43 415 | 38.74 463 | 71.92 463 | 55.84 472 |
|
| EMVS | | | 61.10 431 | 60.81 433 | 61.99 443 | 65.96 476 | 55.86 385 | 53.10 471 | 58.97 468 | 67.06 306 | 56.89 474 | 63.33 470 | 40.98 443 | 67.03 454 | 54.79 403 | 86.18 392 | 63.08 466 |
|
| DSMNet-mixed | | | 60.98 432 | 61.61 432 | 59.09 452 | 72.88 460 | 45.05 450 | 74.70 388 | 46.61 478 | 26.20 476 | 65.34 454 | 90.32 260 | 55.46 376 | 63.12 465 | 41.72 457 | 81.30 437 | 69.09 461 |
|
| dp | | | 60.70 433 | 60.29 436 | 61.92 444 | 72.04 464 | 38.67 467 | 70.83 421 | 64.08 454 | 51.28 437 | 60.75 465 | 77.28 443 | 36.59 454 | 71.58 434 | 47.41 442 | 62.34 472 | 75.52 452 |
|
| dmvs_testset | | | 60.59 434 | 62.54 429 | 54.72 455 | 77.26 424 | 27.74 478 | 74.05 393 | 61.00 464 | 60.48 377 | 65.62 453 | 67.03 468 | 55.93 373 | 68.23 450 | 32.07 474 | 69.46 469 | 68.17 462 |
|
| CHOSEN 280x420 | | | 59.08 435 | 56.52 441 | 66.76 427 | 76.51 433 | 64.39 271 | 49.62 472 | 59.00 467 | 43.86 460 | 55.66 475 | 68.41 467 | 35.55 455 | 68.21 451 | 43.25 454 | 76.78 457 | 67.69 463 |
|
| mvsany_test1 | | | 58.48 436 | 56.47 442 | 64.50 437 | 65.90 477 | 68.21 230 | 56.95 468 | 42.11 480 | 38.30 472 | 65.69 452 | 77.19 446 | 56.96 367 | 59.35 470 | 46.16 447 | 58.96 473 | 65.93 464 |
|
| UWE-MVS-28 | | | 58.44 437 | 57.71 439 | 60.65 448 | 73.58 454 | 31.23 475 | 69.68 430 | 48.80 476 | 53.12 425 | 61.79 463 | 78.83 430 | 30.98 465 | 68.40 449 | 21.58 477 | 80.99 439 | 82.33 420 |
|
| PVSNet_0 | | 51.08 22 | 56.10 438 | 54.97 443 | 59.48 451 | 75.12 446 | 53.28 407 | 55.16 469 | 61.89 459 | 44.30 458 | 59.16 468 | 62.48 471 | 54.22 381 | 65.91 459 | 35.40 469 | 47.01 474 | 59.25 470 |
|
| new_pmnet | | | 55.69 439 | 57.66 440 | 49.76 456 | 75.47 443 | 30.59 476 | 59.56 460 | 51.45 474 | 43.62 462 | 62.49 462 | 75.48 454 | 40.96 444 | 49.15 476 | 37.39 468 | 72.52 460 | 69.55 460 |
|
| PMMVS2 | | | 55.64 440 | 59.27 438 | 44.74 457 | 64.30 479 | 12.32 485 | 40.60 473 | 49.79 475 | 53.19 423 | 65.06 458 | 84.81 370 | 53.60 384 | 49.76 475 | 32.68 473 | 89.41 342 | 72.15 456 |
|
| MVE |  | 40.22 23 | 51.82 441 | 50.47 444 | 55.87 453 | 62.66 480 | 51.91 416 | 31.61 475 | 39.28 481 | 40.65 467 | 50.76 476 | 74.98 456 | 56.24 372 | 44.67 477 | 33.94 472 | 64.11 471 | 71.04 459 |
| Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
| dongtai | | | 41.90 442 | 42.65 445 | 39.67 458 | 70.86 466 | 21.11 480 | 61.01 459 | 21.42 485 | 57.36 400 | 57.97 473 | 50.06 474 | 16.40 483 | 58.73 471 | 21.03 478 | 27.69 478 | 39.17 474 |
|
| kuosan | | | 30.83 443 | 32.17 446 | 26.83 460 | 53.36 482 | 19.02 483 | 57.90 466 | 20.44 486 | 38.29 473 | 38.01 477 | 37.82 476 | 15.18 484 | 33.45 479 | 7.74 480 | 20.76 479 | 28.03 475 |
|
| test_method | | | 30.46 444 | 29.60 447 | 33.06 459 | 17.99 484 | 3.84 487 | 13.62 476 | 73.92 399 | 2.79 478 | 18.29 480 | 53.41 473 | 28.53 471 | 43.25 478 | 22.56 475 | 35.27 476 | 52.11 473 |
|
| cdsmvs_eth3d_5k | | | 20.81 445 | 27.75 448 | 0.00 465 | 0.00 488 | 0.00 490 | 0.00 477 | 85.44 301 | 0.00 483 | 0.00 484 | 82.82 393 | 81.46 135 | 0.00 484 | 0.00 483 | 0.00 482 | 0.00 480 |
|
| tmp_tt | | | 20.25 446 | 24.50 449 | 7.49 462 | 4.47 485 | 8.70 486 | 34.17 474 | 25.16 483 | 1.00 480 | 32.43 479 | 18.49 477 | 39.37 447 | 9.21 481 | 21.64 476 | 43.75 475 | 4.57 477 |
|
| ab-mvs-re | | | 6.65 447 | 8.87 450 | 0.00 465 | 0.00 488 | 0.00 490 | 0.00 477 | 0.00 489 | 0.00 483 | 0.00 484 | 79.80 421 | 0.00 487 | 0.00 484 | 0.00 483 | 0.00 482 | 0.00 480 |
|
| pcd_1.5k_mvsjas | | | 6.41 448 | 8.55 451 | 0.00 465 | 0.00 488 | 0.00 490 | 0.00 477 | 0.00 489 | 0.00 483 | 0.00 484 | 0.00 483 | 76.94 194 | 0.00 484 | 0.00 483 | 0.00 482 | 0.00 480 |
|
| test123 | | | 6.27 449 | 8.08 452 | 0.84 463 | 1.11 487 | 0.57 488 | 62.90 454 | 0.82 487 | 0.54 481 | 1.07 483 | 2.75 482 | 1.26 485 | 0.30 482 | 1.04 481 | 1.26 481 | 1.66 478 |
|
| testmvs | | | 5.91 450 | 7.65 453 | 0.72 464 | 1.20 486 | 0.37 489 | 59.14 462 | 0.67 488 | 0.49 482 | 1.11 482 | 2.76 481 | 0.94 486 | 0.24 483 | 1.02 482 | 1.47 480 | 1.55 479 |
|
| mmdepth | | | 0.00 451 | 0.00 454 | 0.00 465 | 0.00 488 | 0.00 490 | 0.00 477 | 0.00 489 | 0.00 483 | 0.00 484 | 0.00 483 | 0.00 487 | 0.00 484 | 0.00 483 | 0.00 482 | 0.00 480 |
|
| monomultidepth | | | 0.00 451 | 0.00 454 | 0.00 465 | 0.00 488 | 0.00 490 | 0.00 477 | 0.00 489 | 0.00 483 | 0.00 484 | 0.00 483 | 0.00 487 | 0.00 484 | 0.00 483 | 0.00 482 | 0.00 480 |
|
| test_blank | | | 0.00 451 | 0.00 454 | 0.00 465 | 0.00 488 | 0.00 490 | 0.00 477 | 0.00 489 | 0.00 483 | 0.00 484 | 0.00 483 | 0.00 487 | 0.00 484 | 0.00 483 | 0.00 482 | 0.00 480 |
|
| uanet_test | | | 0.00 451 | 0.00 454 | 0.00 465 | 0.00 488 | 0.00 490 | 0.00 477 | 0.00 489 | 0.00 483 | 0.00 484 | 0.00 483 | 0.00 487 | 0.00 484 | 0.00 483 | 0.00 482 | 0.00 480 |
|
| DCPMVS | | | 0.00 451 | 0.00 454 | 0.00 465 | 0.00 488 | 0.00 490 | 0.00 477 | 0.00 489 | 0.00 483 | 0.00 484 | 0.00 483 | 0.00 487 | 0.00 484 | 0.00 483 | 0.00 482 | 0.00 480 |
|
| sosnet-low-res | | | 0.00 451 | 0.00 454 | 0.00 465 | 0.00 488 | 0.00 490 | 0.00 477 | 0.00 489 | 0.00 483 | 0.00 484 | 0.00 483 | 0.00 487 | 0.00 484 | 0.00 483 | 0.00 482 | 0.00 480 |
|
| sosnet | | | 0.00 451 | 0.00 454 | 0.00 465 | 0.00 488 | 0.00 490 | 0.00 477 | 0.00 489 | 0.00 483 | 0.00 484 | 0.00 483 | 0.00 487 | 0.00 484 | 0.00 483 | 0.00 482 | 0.00 480 |
|
| uncertanet | | | 0.00 451 | 0.00 454 | 0.00 465 | 0.00 488 | 0.00 490 | 0.00 477 | 0.00 489 | 0.00 483 | 0.00 484 | 0.00 483 | 0.00 487 | 0.00 484 | 0.00 483 | 0.00 482 | 0.00 480 |
|
| Regformer | | | 0.00 451 | 0.00 454 | 0.00 465 | 0.00 488 | 0.00 490 | 0.00 477 | 0.00 489 | 0.00 483 | 0.00 484 | 0.00 483 | 0.00 487 | 0.00 484 | 0.00 483 | 0.00 482 | 0.00 480 |
|
| uanet | | | 0.00 451 | 0.00 454 | 0.00 465 | 0.00 488 | 0.00 490 | 0.00 477 | 0.00 489 | 0.00 483 | 0.00 484 | 0.00 483 | 0.00 487 | 0.00 484 | 0.00 483 | 0.00 482 | 0.00 480 |
|
| MED-MVS test | | | | | 88.50 80 | 94.38 48 | 76.12 126 | 92.12 33 | 93.85 53 | 77.53 141 | 93.24 43 | 93.18 132 | | 95.85 24 | 84.99 75 | 97.69 65 | 93.54 157 |
|
| TestfortrainingZip | | | | | | | | 92.12 33 | | | | | | | | | |
|
| WAC-MVS | | | | | | | 37.39 468 | | | | | | | | 52.61 417 | | |
|
| FOURS1 | | | | | | 96.08 12 | 87.41 14 | 96.19 2 | 95.83 5 | 92.95 3 | 96.57 3 | | | | | | |
|
| MSC_two_6792asdad | | | | | 88.81 73 | 91.55 140 | 77.99 97 | | 91.01 172 | | | | | 96.05 9 | 87.45 29 | 98.17 37 | 92.40 216 |
|
| PC_three_1452 | | | | | | | | | | 58.96 387 | 90.06 108 | 91.33 211 | 80.66 145 | 93.03 156 | 75.78 197 | 95.94 138 | 92.48 210 |
|
| No_MVS | | | | | 88.81 73 | 91.55 140 | 77.99 97 | | 91.01 172 | | | | | 96.05 9 | 87.45 29 | 98.17 37 | 92.40 216 |
|
| test_one_0601 | | | | | | 93.85 67 | 73.27 148 | | 94.11 39 | 86.57 34 | 93.47 42 | 94.64 69 | 88.42 29 | | | | |
|
| eth-test2 | | | | | | 0.00 488 | | | | | | | | | | | |
|
| eth-test | | | | | | 0.00 488 | | | | | | | | | | | |
|
| ZD-MVS | | | | | | 92.22 113 | 80.48 71 | | 91.85 140 | 71.22 242 | 90.38 103 | 92.98 144 | 86.06 68 | 96.11 7 | 81.99 115 | 96.75 101 | |
|
| RE-MVS-def | | | | 92.61 9 | | 94.13 60 | 88.95 6 | 92.87 13 | 94.16 33 | 88.75 18 | 93.79 33 | 94.43 77 | 90.64 11 | | 87.16 38 | 97.60 75 | 92.73 193 |
|
| IU-MVS | | | | | | 94.18 55 | 72.64 158 | | 90.82 177 | 56.98 404 | 89.67 121 | | | | 85.78 64 | 97.92 52 | 93.28 165 |
|
| OPU-MVS | | | | | 88.27 88 | 91.89 125 | 77.83 100 | 90.47 60 | | | | 91.22 217 | 81.12 139 | 94.68 82 | 74.48 212 | 95.35 161 | 92.29 226 |
|
| test_241102_TWO | | | | | | | | | 93.71 60 | 83.77 58 | 93.49 40 | 94.27 84 | 89.27 24 | 95.84 27 | 86.03 57 | 97.82 57 | 92.04 239 |
|
| test_241102_ONE | | | | | | 94.18 55 | 72.65 156 | | 93.69 62 | 83.62 62 | 94.11 27 | 93.78 115 | 90.28 15 | 95.50 52 | | | |
|
| 9.14 | | | | 89.29 66 | | 91.84 129 | | 88.80 99 | 95.32 13 | 75.14 171 | 91.07 87 | 92.89 150 | 87.27 49 | 93.78 121 | 83.69 93 | 97.55 78 | |
|
| save fliter | | | | | | 93.75 68 | 77.44 106 | 86.31 145 | 89.72 216 | 70.80 247 | | | | | | | |
|
| test_0728_THIRD | | | | | | | | | | 85.33 42 | 93.75 35 | 94.65 66 | 87.44 48 | 95.78 35 | 87.41 31 | 98.21 34 | 92.98 186 |
|
| test_0728_SECOND | | | | | 86.79 112 | 94.25 53 | 72.45 166 | 90.54 57 | 94.10 40 | | | | | 95.88 18 | 86.42 47 | 97.97 49 | 92.02 240 |
|
| test0726 | | | | | | 94.16 58 | 72.56 162 | 90.63 54 | 93.90 49 | 83.61 63 | 93.75 35 | 94.49 74 | 89.76 19 | | | | |
|
| GSMVS | | | | | | | | | | | | | | | | | 83.88 393 |
|
| test_part2 | | | | | | 93.86 66 | 77.77 101 | | | | 92.84 55 | | | | | | |
|
| sam_mvs1 | | | | | | | | | | | | | 46.11 413 | | | | 83.88 393 |
|
| sam_mvs | | | | | | | | | | | | | 45.92 418 | | | | |
|
| ambc | | | | | 82.98 221 | 90.55 169 | 64.86 265 | 88.20 108 | 89.15 229 | | 89.40 130 | 93.96 106 | 71.67 274 | 91.38 202 | 78.83 150 | 96.55 106 | 92.71 196 |
|
| MTGPA |  | | | | | | | | 91.81 144 | | | | | | | | |
|
| test_post1 | | | | | | | | 78.85 327 | | | | 3.13 479 | 45.19 428 | 80.13 399 | 58.11 382 | | |
|
| test_post | | | | | | | | | | | | 3.10 480 | 45.43 424 | 77.22 414 | | | |
|
| patchmatchnet-post | | | | | | | | | | | | 81.71 405 | 45.93 417 | 87.01 320 | | | |
|
| GG-mvs-BLEND | | | | | 67.16 425 | 73.36 455 | 46.54 444 | 84.15 199 | 55.04 472 | | 58.64 471 | 61.95 472 | 29.93 468 | 83.87 376 | 38.71 464 | 76.92 456 | 71.07 458 |
|
| MTMP | | | | | | | | 90.66 53 | 33.14 482 | | | | | | | | |
|
| gm-plane-assit | | | | | | 75.42 444 | 44.97 451 | | | 52.17 430 | | 72.36 461 | | 87.90 306 | 54.10 406 | | |
|
| test9_res | | | | | | | | | | | | | | | 80.83 125 | 96.45 112 | 90.57 287 |
|
| TEST9 | | | | | | 92.34 108 | 79.70 80 | 83.94 205 | 90.32 196 | 65.41 327 | 84.49 263 | 90.97 228 | 82.03 124 | 93.63 127 | | | |
|
| test_8 | | | | | | 92.09 117 | 78.87 88 | 83.82 210 | 90.31 198 | 65.79 317 | 84.36 267 | 90.96 230 | 81.93 126 | 93.44 141 | | | |
|
| agg_prior2 | | | | | | | | | | | | | | | 79.68 138 | 96.16 125 | 90.22 295 |
|
| agg_prior | | | | | | 91.58 138 | 77.69 103 | | 90.30 199 | | 84.32 269 | | | 93.18 149 | | | |
|
| TestCases | | | | | 89.68 56 | 91.59 135 | 83.40 52 | | 95.44 11 | 79.47 108 | 88.00 164 | 93.03 142 | 82.66 104 | 91.47 196 | 70.81 266 | 96.14 126 | 94.16 116 |
|
| test_prior4 | | | | | | | 78.97 87 | 84.59 188 | | | | | | | | | |
|
| test_prior2 | | | | | | | | 83.37 226 | | 75.43 167 | 84.58 260 | 91.57 201 | 81.92 128 | | 79.54 142 | 96.97 94 | |
|
| test_prior | | | | | 86.32 120 | 90.59 168 | 71.99 174 | | 92.85 105 | | | | | 94.17 106 | | | 92.80 191 |
|
| 旧先验2 | | | | | | | | 81.73 273 | | 56.88 405 | 86.54 210 | | | 84.90 362 | 72.81 250 | | |
|
| 新几何2 | | | | | | | | 81.72 274 | | | | | | | | | |
|
| 新几何1 | | | | | 82.95 223 | 93.96 64 | 78.56 91 | | 80.24 359 | 55.45 410 | 83.93 280 | 91.08 224 | 71.19 276 | 88.33 298 | 65.84 323 | 93.07 246 | 81.95 424 |
|
| 旧先验1 | | | | | | 91.97 121 | 71.77 175 | | 81.78 347 | | | 91.84 190 | 73.92 237 | | | 93.65 227 | 83.61 399 |
|
| 无先验 | | | | | | | | 82.81 245 | 85.62 299 | 58.09 393 | | | | 91.41 201 | 67.95 306 | | 84.48 384 |
|
| 原ACMM2 | | | | | | | | 82.26 265 | | | | | | | | | |
|
| 原ACMM1 | | | | | 84.60 169 | 92.81 98 | 74.01 140 | | 91.50 152 | 62.59 348 | 82.73 306 | 90.67 247 | 76.53 203 | 94.25 98 | 69.24 287 | 95.69 153 | 85.55 372 |
|
| test222 | | | | | | 93.31 81 | 76.54 116 | 79.38 316 | 77.79 370 | 52.59 427 | 82.36 311 | 90.84 238 | 66.83 300 | | | 91.69 289 | 81.25 432 |
|
| testdata2 | | | | | | | | | | | | | | 86.43 335 | 63.52 345 | | |
|
| segment_acmp | | | | | | | | | | | | | 81.94 125 | | | | |
|
| testdata | | | | | 79.54 305 | 92.87 92 | 72.34 167 | | 80.14 360 | 59.91 383 | 85.47 237 | 91.75 197 | 67.96 294 | 85.24 358 | 68.57 301 | 92.18 275 | 81.06 437 |
|
| testdata1 | | | | | | | | 79.62 308 | | 73.95 188 | | | | | | | |
|
| test12 | | | | | 86.57 115 | 90.74 164 | 72.63 160 | | 90.69 180 | | 82.76 304 | | 79.20 158 | 94.80 79 | | 95.32 163 | 92.27 228 |
|
| plane_prior7 | | | | | | 93.45 75 | 77.31 109 | | | | | | | | | | |
|
| plane_prior6 | | | | | | 92.61 99 | 76.54 116 | | | | | | 74.84 219 | | | | |
|
| plane_prior5 | | | | | | | | | 93.61 65 | | | | | 95.22 63 | 80.78 126 | 95.83 146 | 94.46 98 |
|
| plane_prior4 | | | | | | | | | | | | 92.95 148 | | | | | |
|
| plane_prior3 | | | | | | | 76.85 114 | | | 77.79 136 | 86.55 204 | | | | | | |
|
| plane_prior2 | | | | | | | | 89.45 87 | | 79.44 110 | | | | | | | |
|
| plane_prior1 | | | | | | 92.83 96 | | | | | | | | | | | |
|
| plane_prior | | | | | | | 76.42 119 | 87.15 127 | | 75.94 158 | | | | | | 95.03 175 | |
|
| n2 | | | | | | | | | 0.00 489 | | | | | | | | |
|
| nn | | | | | | | | | 0.00 489 | | | | | | | | |
|
| door-mid | | | | | | | | | 74.45 396 | | | | | | | | |
|
| lessismore_v0 | | | | | 85.95 131 | 91.10 157 | 70.99 191 | | 70.91 426 | | 91.79 75 | 94.42 79 | 61.76 334 | 92.93 159 | 79.52 143 | 93.03 247 | 93.93 126 |
|
| LGP-MVS_train | | | | | 90.82 37 | 94.75 41 | 81.69 63 | | 94.27 25 | 82.35 76 | 93.67 38 | 94.82 61 | 91.18 5 | 95.52 48 | 85.36 67 | 98.73 7 | 95.23 67 |
|
| test11 | | | | | | | | | 91.46 153 | | | | | | | | |
|
| door | | | | | | | | | 72.57 412 | | | | | | | | |
|
| HQP5-MVS | | | | | | | 70.66 193 | | | | | | | | | | |
|
| HQP-NCC | | | | | | 91.19 152 | | 84.77 179 | | 73.30 202 | 80.55 344 | | | | | | |
|
| ACMP_Plane | | | | | | 91.19 152 | | 84.77 179 | | 73.30 202 | 80.55 344 | | | | | | |
|
| BP-MVS | | | | | | | | | | | | | | | 77.30 175 | | |
|
| HQP4-MVS | | | | | | | | | | | 80.56 343 | | | 94.61 86 | | | 93.56 154 |
|
| HQP3-MVS | | | | | | | | | 92.68 111 | | | | | | | 94.47 197 | |
|
| HQP2-MVS | | | | | | | | | | | | | 72.10 265 | | | | |
|
| NP-MVS | | | | | | 91.95 122 | 74.55 137 | | | | | 90.17 267 | | | | | |
|
| MDTV_nov1_ep13_2view | | | | | | | 27.60 479 | 70.76 422 | | 46.47 452 | 61.27 464 | | 45.20 427 | | 49.18 433 | | 83.75 398 |
|
| MDTV_nov1_ep13 | | | | 68.29 399 | | 78.03 419 | 43.87 454 | 74.12 392 | 72.22 415 | 52.17 430 | 67.02 447 | 85.54 355 | 45.36 425 | 80.85 393 | 55.73 393 | 84.42 414 | |
|
| ACMMP++_ref | | | | | | | | | | | | | | | | 95.74 152 | |
|
| ACMMP++ | | | | | | | | | | | | | | | | 97.35 84 | |
|
| Test By Simon | | | | | | | | | | | | | 79.09 160 | | | | |
|
| ITE_SJBPF | | | | | 90.11 49 | 90.72 165 | 84.97 41 | | 90.30 199 | 81.56 84 | 90.02 110 | 91.20 219 | 82.40 109 | 90.81 225 | 73.58 236 | 94.66 192 | 94.56 91 |
|
| DeepMVS_CX |  | | | | 24.13 461 | 32.95 483 | 29.49 477 | | 21.63 484 | 12.07 477 | 37.95 478 | 45.07 475 | 30.84 466 | 19.21 480 | 17.94 479 | 33.06 477 | 23.69 476 |
|