| MSC_two_6792asdad | | | | | 96.52 1 | 97.78 60 | 90.86 1 | | 96.85 80 | | | | | 99.61 6 | 96.03 27 | 99.06 9 | 99.07 7 |
|
| No_MVS | | | | | 96.52 1 | 97.78 60 | 90.86 1 | | 96.85 80 | | | | | 99.61 6 | 96.03 27 | 99.06 9 | 99.07 7 |
|
| OPU-MVS | | | | | 96.21 3 | 98.00 48 | 90.85 3 | 97.13 19 | | | | 97.08 70 | 92.59 2 | 98.94 92 | 92.25 92 | 98.99 14 | 98.84 19 |
|
| HPM-MVS++ |  | | 95.14 13 | 94.91 26 | 95.83 4 | 98.25 35 | 89.65 4 | 95.92 87 | 96.96 68 | 91.75 13 | 94.02 72 | 96.83 82 | 88.12 28 | 99.55 20 | 93.41 66 | 98.94 16 | 98.28 61 |
|
| MM | | | 95.10 14 | 94.91 26 | 95.68 5 | 96.09 116 | 88.34 10 | 96.68 38 | 94.37 302 | 95.08 1 | 94.68 58 | 97.72 41 | 82.94 100 | 99.64 3 | 97.85 5 | 98.76 32 | 99.06 9 |
|
| SMA-MVS |  | | 95.20 10 | 95.07 20 | 95.59 6 | 98.14 41 | 88.48 9 | 96.26 54 | 97.28 40 | 85.90 208 | 97.67 4 | 98.10 14 | 88.41 24 | 99.56 16 | 94.66 48 | 99.19 1 | 98.71 25 |
| 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 |
| 3Dnovator+ | | 87.14 4 | 92.42 104 | 91.37 126 | 95.55 7 | 95.63 143 | 88.73 7 | 97.07 23 | 96.77 92 | 90.84 26 | 84.02 335 | 96.62 95 | 75.95 217 | 99.34 42 | 87.77 183 | 97.68 96 | 98.59 29 |
|
| CNVR-MVS | | | 95.40 8 | 95.37 11 | 95.50 8 | 98.11 42 | 88.51 8 | 95.29 131 | 96.96 68 | 92.09 10 | 95.32 50 | 97.08 70 | 89.49 16 | 99.33 45 | 95.10 43 | 98.85 20 | 98.66 26 |
|
| TestfortrainingZip | | | | | 95.40 9 | 97.32 74 | 88.97 6 | 97.32 10 | 96.82 85 | 89.07 91 | 95.69 45 | 96.49 100 | 89.27 18 | 99.29 50 | | 95.80 142 | 97.95 97 |
|
| MGCNet | | | 94.18 50 | 93.80 64 | 95.34 10 | 94.91 183 | 87.62 15 | 95.97 82 | 93.01 353 | 92.58 6 | 94.22 63 | 97.20 64 | 80.56 140 | 99.59 10 | 97.04 20 | 98.68 40 | 98.81 22 |
|
| ACMMP_NAP | | | 94.74 25 | 94.56 33 | 95.28 11 | 98.02 47 | 87.70 12 | 95.68 107 | 97.34 30 | 88.28 123 | 95.30 51 | 97.67 43 | 85.90 55 | 99.54 24 | 93.91 56 | 98.95 15 | 98.60 28 |
|
| DPE-MVS |  | | 95.57 5 | 95.67 5 | 95.25 12 | 98.36 31 | 87.28 19 | 95.56 119 | 97.51 10 | 89.13 90 | 97.14 17 | 97.91 34 | 91.64 8 | 99.62 4 | 94.61 49 | 99.17 2 | 98.86 16 |
| Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025 |
| SF-MVS | | | 94.97 17 | 94.90 28 | 95.20 13 | 97.84 56 | 87.76 11 | 96.65 39 | 97.48 15 | 87.76 153 | 95.71 44 | 97.70 42 | 88.28 27 | 99.35 41 | 93.89 57 | 98.78 29 | 98.48 35 |
|
| MCST-MVS | | | 94.45 34 | 94.20 51 | 95.19 14 | 98.46 22 | 87.50 17 | 95.00 155 | 97.12 55 | 87.13 174 | 92.51 113 | 96.30 105 | 89.24 19 | 99.34 42 | 93.46 63 | 98.62 49 | 98.73 23 |
|
| NCCC | | | 94.81 22 | 94.69 32 | 95.17 15 | 97.83 57 | 87.46 18 | 95.66 110 | 96.93 72 | 92.34 7 | 93.94 73 | 96.58 97 | 87.74 31 | 99.44 33 | 92.83 75 | 98.40 57 | 98.62 27 |
|
| DPM-MVS | | | 92.58 99 | 91.74 110 | 95.08 16 | 96.19 107 | 89.31 5 | 92.66 313 | 96.56 113 | 83.44 283 | 91.68 139 | 95.04 189 | 86.60 47 | 98.99 82 | 85.60 217 | 97.92 84 | 96.93 189 |
|
| ZNCC-MVS | | | 94.47 33 | 94.28 45 | 95.03 17 | 98.52 18 | 86.96 21 | 96.85 33 | 97.32 34 | 88.24 124 | 93.15 88 | 97.04 73 | 86.17 52 | 99.62 4 | 92.40 86 | 98.81 26 | 98.52 31 |
|
| test_0728_SECOND | | | | | 95.01 18 | 98.79 5 | 86.43 40 | 97.09 21 | 97.49 11 | | | | | 99.61 6 | 95.62 34 | 99.08 7 | 98.99 11 |
|
| MTAPA | | | 94.42 39 | 94.22 48 | 95.00 19 | 98.42 24 | 86.95 22 | 94.36 210 | 96.97 65 | 91.07 22 | 93.14 89 | 97.56 45 | 84.30 81 | 99.56 16 | 93.43 64 | 98.75 33 | 98.47 38 |
|
| TestfortrainingZip a | | | 95.33 9 | 95.44 10 | 94.99 20 | 98.88 1 | 86.26 48 | 97.32 10 | 97.43 25 | 90.76 29 | 96.80 26 | 98.09 18 | 89.00 22 | 99.58 13 | 93.66 60 | 96.99 111 | 99.14 2 |
|
| MSP-MVS | | | 95.42 7 | 95.56 7 | 94.98 21 | 98.49 20 | 86.52 37 | 96.91 30 | 97.47 16 | 91.73 14 | 96.10 36 | 96.69 87 | 89.90 13 | 99.30 48 | 94.70 47 | 98.04 79 | 99.13 4 |
| 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 |
| region2R | | | 94.43 36 | 94.27 47 | 94.92 22 | 98.65 11 | 86.67 31 | 96.92 29 | 97.23 43 | 88.60 114 | 93.58 80 | 97.27 58 | 85.22 64 | 99.54 24 | 92.21 94 | 98.74 34 | 98.56 30 |
|
| APDe-MVS |  | | 95.46 6 | 95.64 6 | 94.91 23 | 98.26 34 | 86.29 47 | 97.46 7 | 97.40 26 | 89.03 96 | 96.20 35 | 98.10 14 | 89.39 17 | 99.34 42 | 95.88 29 | 99.03 11 | 99.10 6 |
| Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition |
| ACMMPR | | | 94.43 36 | 94.28 45 | 94.91 23 | 98.63 12 | 86.69 29 | 96.94 25 | 97.32 34 | 88.63 111 | 93.53 83 | 97.26 60 | 85.04 68 | 99.54 24 | 92.35 89 | 98.78 29 | 98.50 32 |
|
| MED-MVS | | | 95.95 2 | 96.29 2 | 94.90 25 | 98.88 1 | 85.89 65 | 97.32 10 | 97.86 1 | 90.76 29 | 97.21 14 | 98.09 18 | 92.42 4 | 99.67 1 | 95.27 40 | 98.85 20 | 99.14 2 |
|
| GST-MVS | | | 94.21 45 | 93.97 60 | 94.90 25 | 98.41 25 | 86.82 25 | 96.54 41 | 97.19 44 | 88.24 124 | 93.26 85 | 96.83 82 | 85.48 60 | 99.59 10 | 91.43 120 | 98.40 57 | 98.30 55 |
|
| HFP-MVS | | | 94.52 31 | 94.40 38 | 94.86 27 | 98.61 13 | 86.81 26 | 96.94 25 | 97.34 30 | 88.63 111 | 93.65 78 | 97.21 62 | 86.10 53 | 99.49 30 | 92.35 89 | 98.77 31 | 98.30 55 |
|
| sasdasda | | | 93.27 82 | 92.75 92 | 94.85 28 | 95.70 139 | 87.66 13 | 96.33 44 | 96.41 123 | 90.00 53 | 94.09 68 | 94.60 214 | 82.33 109 | 98.62 133 | 92.40 86 | 92.86 234 | 98.27 64 |
|
| MP-MVS-pluss | | | 94.21 45 | 94.00 59 | 94.85 28 | 98.17 39 | 86.65 32 | 94.82 168 | 97.17 49 | 86.26 200 | 92.83 98 | 97.87 36 | 85.57 59 | 99.56 16 | 94.37 52 | 98.92 17 | 98.34 48 |
| MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
| canonicalmvs | | | 93.27 82 | 92.75 92 | 94.85 28 | 95.70 139 | 87.66 13 | 96.33 44 | 96.41 123 | 90.00 53 | 94.09 68 | 94.60 214 | 82.33 109 | 98.62 133 | 92.40 86 | 92.86 234 | 98.27 64 |
|
| XVS | | | 94.45 34 | 94.32 41 | 94.85 28 | 98.54 16 | 86.60 35 | 96.93 27 | 97.19 44 | 90.66 36 | 92.85 96 | 97.16 68 | 85.02 69 | 99.49 30 | 91.99 105 | 98.56 53 | 98.47 38 |
|
| X-MVStestdata | | | 88.31 237 | 86.13 286 | 94.85 28 | 98.54 16 | 86.60 35 | 96.93 27 | 97.19 44 | 90.66 36 | 92.85 96 | 23.41 519 | 85.02 69 | 99.49 30 | 91.99 105 | 98.56 53 | 98.47 38 |
|
| SteuartSystems-ACMMP | | | 95.20 10 | 95.32 13 | 94.85 28 | 96.99 82 | 86.33 43 | 97.33 8 | 97.30 37 | 91.38 19 | 95.39 49 | 97.46 50 | 88.98 23 | 99.40 34 | 94.12 53 | 98.89 18 | 98.82 21 |
| Skip Steuart: Steuart Systems R&D Blog. |
| MED-MVS test | | | | | 94.84 34 | 98.88 1 | 85.89 65 | 97.32 10 | 97.86 1 | 88.11 132 | 97.21 14 | 97.54 46 | | 99.67 1 | 95.27 40 | 98.85 20 | 98.95 13 |
|
| DVP-MVS++ | | | 95.98 1 | 96.36 1 | 94.82 35 | 97.78 60 | 86.00 54 | 98.29 1 | 97.49 11 | 90.75 31 | 97.62 8 | 98.06 24 | 92.59 2 | 99.61 6 | 95.64 32 | 99.02 12 | 98.86 16 |
|
| ME-MVS | | | 95.17 12 | 95.29 14 | 94.81 36 | 98.39 28 | 85.89 65 | 95.91 88 | 97.55 8 | 89.01 98 | 95.86 42 | 97.54 46 | 89.24 19 | 99.59 10 | 95.27 40 | 98.85 20 | 98.95 13 |
|
| alignmvs | | | 93.08 90 | 92.50 98 | 94.81 36 | 95.62 144 | 87.61 16 | 95.99 79 | 96.07 169 | 89.77 66 | 94.12 67 | 94.87 198 | 80.56 140 | 98.66 125 | 92.42 85 | 93.10 229 | 98.15 76 |
|
| SED-MVS | | | 95.91 3 | 96.28 3 | 94.80 38 | 98.77 8 | 85.99 56 | 97.13 19 | 97.44 20 | 90.31 43 | 97.71 2 | 98.07 22 | 92.31 5 | 99.58 13 | 95.66 30 | 99.13 3 | 98.84 19 |
|
| DeepC-MVS_fast | | 89.43 2 | 94.04 53 | 93.79 65 | 94.80 38 | 97.48 70 | 86.78 27 | 95.65 112 | 96.89 77 | 89.40 78 | 92.81 99 | 96.97 75 | 85.37 62 | 99.24 52 | 90.87 129 | 98.69 38 | 98.38 47 |
| Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
| MP-MVS |  | | 94.25 42 | 94.07 56 | 94.77 40 | 98.47 21 | 86.31 45 | 96.71 36 | 96.98 64 | 89.04 94 | 91.98 124 | 97.19 65 | 85.43 61 | 99.56 16 | 92.06 103 | 98.79 27 | 98.44 42 |
| Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
| APD-MVS |  | | 94.24 43 | 94.07 56 | 94.75 41 | 98.06 45 | 86.90 24 | 95.88 90 | 96.94 71 | 85.68 215 | 95.05 56 | 97.18 66 | 87.31 39 | 99.07 65 | 91.90 111 | 98.61 51 | 98.28 61 |
| Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
| CP-MVS | | | 94.34 40 | 94.21 50 | 94.74 42 | 98.39 28 | 86.64 33 | 97.60 5 | 97.24 41 | 88.53 116 | 92.73 104 | 97.23 61 | 85.20 65 | 99.32 46 | 92.15 97 | 98.83 25 | 98.25 69 |
|
| PGM-MVS | | | 93.96 58 | 93.72 70 | 94.68 43 | 98.43 23 | 86.22 49 | 95.30 129 | 97.78 3 | 87.45 164 | 93.26 85 | 97.33 56 | 84.62 78 | 99.51 28 | 90.75 131 | 98.57 52 | 98.32 54 |
|
| DVP-MVS |  | | 95.67 4 | 96.02 4 | 94.64 44 | 98.78 6 | 85.93 59 | 97.09 21 | 96.73 98 | 90.27 47 | 97.04 21 | 98.05 27 | 91.47 9 | 99.55 20 | 95.62 34 | 99.08 7 | 98.45 41 |
| 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 |
| mPP-MVS | | | 93.99 56 | 93.78 66 | 94.63 45 | 98.50 19 | 85.90 64 | 96.87 31 | 96.91 75 | 88.70 109 | 91.83 134 | 97.17 67 | 83.96 85 | 99.55 20 | 91.44 119 | 98.64 48 | 98.43 43 |
|
| PHI-MVS | | | 93.89 60 | 93.65 74 | 94.62 46 | 96.84 85 | 86.43 40 | 96.69 37 | 97.49 11 | 85.15 239 | 93.56 82 | 96.28 106 | 85.60 58 | 99.31 47 | 92.45 83 | 98.79 27 | 98.12 81 |
|
| TSAR-MVS + MP. | | | 94.85 19 | 94.94 24 | 94.58 47 | 98.25 35 | 86.33 43 | 96.11 67 | 96.62 108 | 88.14 129 | 96.10 36 | 96.96 76 | 89.09 21 | 98.94 92 | 94.48 50 | 98.68 40 | 98.48 35 |
| Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition |
| CANet | | | 93.54 69 | 93.20 83 | 94.55 48 | 95.65 141 | 85.73 72 | 94.94 158 | 96.69 104 | 91.89 12 | 90.69 166 | 95.88 138 | 81.99 122 | 99.54 24 | 93.14 70 | 97.95 83 | 98.39 45 |
|
| train_agg | | | 93.44 75 | 93.08 85 | 94.52 49 | 97.53 67 | 86.49 38 | 94.07 230 | 96.78 90 | 81.86 328 | 92.77 101 | 96.20 109 | 87.63 33 | 99.12 63 | 92.14 98 | 98.69 38 | 97.94 98 |
|
| CDPH-MVS | | | 92.83 94 | 92.30 102 | 94.44 50 | 97.79 58 | 86.11 53 | 94.06 232 | 96.66 105 | 80.09 359 | 92.77 101 | 96.63 94 | 86.62 45 | 99.04 69 | 87.40 190 | 98.66 44 | 98.17 74 |
|
| 3Dnovator | | 86.66 5 | 91.73 122 | 90.82 141 | 94.44 50 | 94.59 209 | 86.37 42 | 97.18 17 | 97.02 62 | 89.20 87 | 84.31 330 | 96.66 90 | 73.74 258 | 99.17 57 | 86.74 200 | 97.96 82 | 97.79 122 |
|
| SR-MVS | | | 94.23 44 | 94.17 54 | 94.43 52 | 98.21 38 | 85.78 70 | 96.40 43 | 96.90 76 | 88.20 127 | 94.33 62 | 97.40 53 | 84.75 77 | 99.03 70 | 93.35 67 | 97.99 81 | 98.48 35 |
|
| HPM-MVS |  | | 94.02 54 | 93.88 61 | 94.43 52 | 98.39 28 | 85.78 70 | 97.25 15 | 97.07 60 | 86.90 184 | 92.62 110 | 96.80 86 | 84.85 75 | 99.17 57 | 92.43 84 | 98.65 47 | 98.33 50 |
| Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
| TSAR-MVS + GP. | | | 93.66 67 | 93.41 78 | 94.41 54 | 96.59 92 | 86.78 27 | 94.40 202 | 93.93 320 | 89.77 66 | 94.21 64 | 95.59 159 | 87.35 38 | 98.61 135 | 92.72 78 | 96.15 136 | 97.83 118 |
|
| reproduce-ours | | | 94.82 20 | 94.97 22 | 94.38 55 | 97.91 53 | 85.46 75 | 95.86 91 | 97.15 51 | 89.82 59 | 95.23 53 | 98.10 14 | 87.09 41 | 99.37 37 | 95.30 38 | 98.25 66 | 98.30 55 |
|
| our_new_method | | | 94.82 20 | 94.97 22 | 94.38 55 | 97.91 53 | 85.46 75 | 95.86 91 | 97.15 51 | 89.82 59 | 95.23 53 | 98.10 14 | 87.09 41 | 99.37 37 | 95.30 38 | 98.25 66 | 98.30 55 |
|
| NormalMVS | | | 93.46 72 | 93.16 84 | 94.37 57 | 98.40 26 | 86.20 50 | 96.30 47 | 96.27 136 | 91.65 17 | 92.68 106 | 96.13 120 | 77.97 187 | 98.84 106 | 90.75 131 | 98.26 62 | 98.07 83 |
|
| test12 | | | | | 94.34 58 | 97.13 80 | 86.15 52 | | 96.29 132 | | 91.04 162 | | 85.08 67 | 99.01 75 | | 98.13 74 | 97.86 113 |
|
| SymmetryMVS | | | 92.81 96 | 92.31 101 | 94.32 59 | 96.15 108 | 86.20 50 | 96.30 47 | 94.43 298 | 91.65 17 | 92.68 106 | 96.13 120 | 77.97 187 | 98.84 106 | 90.75 131 | 94.72 169 | 97.92 107 |
|
| ACMMP |  | | 93.24 84 | 92.88 90 | 94.30 60 | 98.09 44 | 85.33 79 | 96.86 32 | 97.45 19 | 88.33 120 | 90.15 184 | 97.03 74 | 81.44 130 | 99.51 28 | 90.85 130 | 95.74 145 | 98.04 90 |
| 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 |
| reproduce_model | | | 94.76 24 | 94.92 25 | 94.29 61 | 97.92 49 | 85.18 81 | 95.95 85 | 97.19 44 | 89.67 69 | 95.27 52 | 98.16 6 | 86.53 48 | 99.36 40 | 95.42 37 | 98.15 72 | 98.33 50 |
|
| DeepC-MVS | | 88.79 3 | 93.31 81 | 92.99 88 | 94.26 62 | 96.07 118 | 85.83 68 | 94.89 161 | 96.99 63 | 89.02 97 | 89.56 193 | 97.37 55 | 82.51 106 | 99.38 35 | 92.20 95 | 98.30 60 | 97.57 137 |
| Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
| MGCFI-Net | | | 93.03 91 | 92.63 95 | 94.23 63 | 95.62 144 | 85.92 61 | 96.08 69 | 96.33 130 | 89.86 57 | 93.89 75 | 94.66 211 | 82.11 117 | 98.50 141 | 92.33 91 | 92.82 237 | 98.27 64 |
|
| fmvsm_l_conf0.5_n_3 | | | 94.80 23 | 95.01 21 | 94.15 64 | 95.64 142 | 85.08 82 | 96.09 68 | 97.36 28 | 90.98 24 | 97.09 19 | 98.12 10 | 84.98 73 | 98.94 92 | 97.07 17 | 97.80 91 | 98.43 43 |
|
| EPNet | | | 91.79 113 | 91.02 135 | 94.10 65 | 90.10 414 | 85.25 80 | 96.03 76 | 92.05 380 | 92.83 5 | 87.39 241 | 95.78 149 | 79.39 166 | 99.01 75 | 88.13 177 | 97.48 99 | 98.05 89 |
| Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
| lecture | | | 95.10 14 | 95.46 9 | 94.01 66 | 98.40 26 | 84.36 107 | 97.70 3 | 97.78 3 | 91.19 20 | 96.22 34 | 98.08 21 | 86.64 44 | 99.37 37 | 94.91 45 | 98.26 62 | 98.29 60 |
|
| test_fmvsmconf_n | | | 94.60 28 | 94.81 30 | 93.98 67 | 94.62 205 | 84.96 85 | 96.15 62 | 97.35 29 | 89.37 79 | 96.03 39 | 98.11 11 | 86.36 49 | 99.01 75 | 97.45 10 | 97.83 89 | 97.96 96 |
|
| DELS-MVS | | | 93.43 79 | 93.25 81 | 93.97 68 | 95.42 152 | 85.04 83 | 93.06 296 | 97.13 54 | 90.74 33 | 91.84 132 | 95.09 188 | 86.32 50 | 99.21 55 | 91.22 121 | 98.45 55 | 97.65 131 |
| 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 |
| DP-MVS Recon | | | 91.95 110 | 91.28 129 | 93.96 69 | 98.33 33 | 85.92 61 | 94.66 181 | 96.66 105 | 82.69 305 | 90.03 186 | 95.82 145 | 82.30 111 | 99.03 70 | 84.57 236 | 96.48 129 | 96.91 191 |
|
| HPM-MVS_fast | | | 93.40 80 | 93.22 82 | 93.94 70 | 98.36 31 | 84.83 87 | 97.15 18 | 96.80 89 | 85.77 212 | 92.47 114 | 97.13 69 | 82.38 107 | 99.07 65 | 90.51 136 | 98.40 57 | 97.92 107 |
|
| test_fmvsmconf0.1_n | | | 94.20 47 | 94.31 43 | 93.88 71 | 92.46 328 | 84.80 88 | 96.18 59 | 96.82 85 | 89.29 84 | 95.68 46 | 98.11 11 | 85.10 66 | 98.99 82 | 97.38 11 | 97.75 95 | 97.86 113 |
|
| SD-MVS | | | 94.96 18 | 95.33 12 | 93.88 71 | 97.25 79 | 86.69 29 | 96.19 57 | 97.11 58 | 90.42 39 | 96.95 23 | 97.27 58 | 89.53 15 | 96.91 319 | 94.38 51 | 98.85 20 | 98.03 91 |
| 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 |
| MVS_111021_HR | | | 93.45 74 | 93.31 79 | 93.84 73 | 96.99 82 | 84.84 86 | 93.24 287 | 97.24 41 | 88.76 106 | 91.60 140 | 95.85 142 | 86.07 54 | 98.66 125 | 91.91 109 | 98.16 70 | 98.03 91 |
|
| SR-MVS-dyc-post | | | 93.82 62 | 93.82 63 | 93.82 74 | 97.92 49 | 84.57 94 | 96.28 51 | 96.76 93 | 87.46 162 | 93.75 76 | 97.43 51 | 84.24 82 | 99.01 75 | 92.73 76 | 97.80 91 | 97.88 111 |
|
| test_prior | | | | | 93.82 74 | 97.29 77 | 84.49 98 | | 96.88 78 | | | | | 98.87 100 | | | 98.11 82 |
|
| APD-MVS_3200maxsize | | | 93.78 63 | 93.77 67 | 93.80 76 | 97.92 49 | 84.19 111 | 96.30 47 | 96.87 79 | 86.96 180 | 93.92 74 | 97.47 49 | 83.88 86 | 98.96 89 | 92.71 79 | 97.87 87 | 98.26 68 |
|
| fmvsm_l_conf0.5_n | | | 94.29 41 | 94.46 36 | 93.79 77 | 95.28 158 | 85.43 77 | 95.68 107 | 96.43 121 | 86.56 192 | 96.84 25 | 97.81 39 | 87.56 36 | 98.77 115 | 97.14 15 | 96.82 119 | 97.16 170 |
|
| CSCG | | | 93.23 85 | 93.05 86 | 93.76 78 | 98.04 46 | 84.07 113 | 96.22 56 | 97.37 27 | 84.15 264 | 90.05 185 | 95.66 155 | 87.77 30 | 99.15 61 | 89.91 147 | 98.27 61 | 98.07 83 |
|
| GDP-MVS | | | 92.04 108 | 91.46 123 | 93.75 79 | 94.55 215 | 84.69 91 | 95.60 118 | 96.56 113 | 87.83 150 | 93.07 92 | 95.89 137 | 73.44 262 | 98.65 127 | 90.22 140 | 96.03 138 | 97.91 109 |
|
| BP-MVS1 | | | 92.48 101 | 92.07 105 | 93.72 80 | 94.50 219 | 84.39 106 | 95.90 89 | 94.30 305 | 90.39 40 | 92.67 108 | 95.94 133 | 74.46 241 | 98.65 127 | 93.14 70 | 97.35 103 | 98.13 78 |
|
| test_fmvsmconf0.01_n | | | 93.19 86 | 93.02 87 | 93.71 81 | 89.25 427 | 84.42 105 | 96.06 73 | 96.29 132 | 89.06 92 | 94.68 58 | 98.13 7 | 79.22 168 | 98.98 86 | 97.22 13 | 97.24 105 | 97.74 125 |
|
| UA-Net | | | 92.83 94 | 92.54 97 | 93.68 82 | 96.10 115 | 84.71 90 | 95.66 110 | 96.39 125 | 91.92 11 | 93.22 87 | 96.49 100 | 83.16 95 | 98.87 100 | 84.47 238 | 95.47 152 | 97.45 144 |
|
| fmvsm_l_conf0.5_n_a | | | 94.20 47 | 94.40 38 | 93.60 83 | 95.29 157 | 84.98 84 | 95.61 115 | 96.28 135 | 86.31 198 | 96.75 28 | 97.86 37 | 87.40 37 | 98.74 119 | 97.07 17 | 97.02 110 | 97.07 175 |
|
| QAPM | | | 89.51 194 | 88.15 221 | 93.59 84 | 94.92 181 | 84.58 93 | 96.82 34 | 96.70 103 | 78.43 386 | 83.41 353 | 96.19 113 | 73.18 267 | 99.30 48 | 77.11 363 | 96.54 126 | 96.89 192 |
|
| test_fmvsm_n_1920 | | | 94.71 26 | 95.11 19 | 93.50 85 | 95.79 133 | 84.62 92 | 96.15 62 | 97.64 5 | 89.85 58 | 97.19 16 | 97.89 35 | 86.28 51 | 98.71 122 | 97.11 16 | 98.08 78 | 97.17 163 |
|
| fmvsm_s_conf0.5_n_9 | | | 94.99 16 | 95.50 8 | 93.44 86 | 96.51 100 | 82.25 185 | 95.76 102 | 96.92 73 | 93.37 3 | 97.63 7 | 98.43 1 | 84.82 76 | 99.16 60 | 98.15 1 | 97.92 84 | 98.90 15 |
|
| KinetiMVS | | | 91.82 112 | 91.30 127 | 93.39 87 | 94.72 197 | 83.36 138 | 95.45 122 | 96.37 127 | 90.33 42 | 92.17 119 | 96.03 127 | 72.32 279 | 98.75 116 | 87.94 180 | 96.34 131 | 98.07 83 |
|
| casdiffmvs_mvg |  | | 92.96 93 | 92.83 91 | 93.35 88 | 94.59 209 | 83.40 136 | 95.00 155 | 96.34 129 | 90.30 45 | 92.05 122 | 96.05 124 | 83.43 89 | 98.15 177 | 92.07 100 | 95.67 146 | 98.49 34 |
| 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_5 | | | 93.96 58 | 94.18 53 | 93.30 89 | 94.79 190 | 83.81 122 | 95.77 100 | 96.74 97 | 88.02 137 | 96.23 33 | 97.84 38 | 83.36 93 | 98.83 109 | 97.49 8 | 97.34 104 | 97.25 155 |
|
| EI-MVSNet-Vis-set | | | 93.01 92 | 92.92 89 | 93.29 90 | 95.01 172 | 83.51 133 | 94.48 190 | 95.77 197 | 90.87 25 | 92.52 112 | 96.67 89 | 84.50 79 | 99.00 80 | 91.99 105 | 94.44 182 | 97.36 147 |
|
| Vis-MVSNet |  | | 91.75 120 | 91.23 130 | 93.29 90 | 95.32 156 | 83.78 123 | 96.14 64 | 95.98 176 | 89.89 55 | 90.45 170 | 96.58 97 | 75.09 230 | 98.31 168 | 84.75 230 | 96.90 115 | 97.78 123 |
| Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
| BridgeMVS | | | 93.98 57 | 94.22 48 | 93.26 92 | 96.13 110 | 83.29 140 | 96.27 53 | 96.52 116 | 89.82 59 | 95.56 48 | 95.51 163 | 84.50 79 | 98.79 113 | 94.83 46 | 98.86 19 | 97.72 127 |
|
| SPE-MVS-test | | | 94.02 54 | 94.29 44 | 93.24 93 | 96.69 88 | 83.24 141 | 97.49 6 | 96.92 73 | 92.14 9 | 92.90 94 | 95.77 150 | 85.02 69 | 98.33 165 | 93.03 72 | 98.62 49 | 98.13 78 |
|
| VNet | | | 92.24 106 | 91.91 108 | 93.24 93 | 96.59 92 | 83.43 134 | 94.84 167 | 96.44 120 | 89.19 88 | 94.08 71 | 95.90 136 | 77.85 193 | 98.17 175 | 88.90 167 | 93.38 218 | 98.13 78 |
|
| fmvsm_s_conf0.5_n_10 | | | 94.43 36 | 94.84 29 | 93.20 95 | 95.73 136 | 83.19 144 | 95.99 79 | 97.31 36 | 91.08 21 | 97.67 4 | 98.11 11 | 81.87 124 | 99.22 53 | 97.86 4 | 97.91 86 | 97.20 161 |
|
| VDD-MVS | | | 90.74 150 | 89.92 165 | 93.20 95 | 96.27 105 | 83.02 156 | 95.73 104 | 93.86 324 | 88.42 119 | 92.53 111 | 96.84 81 | 62.09 394 | 98.64 130 | 90.95 127 | 92.62 244 | 97.93 106 |
|
| Elysia | | | 90.12 170 | 89.10 189 | 93.18 97 | 93.16 296 | 84.05 115 | 95.22 138 | 96.27 136 | 85.16 237 | 90.59 167 | 94.68 207 | 64.64 373 | 98.37 158 | 86.38 206 | 95.77 143 | 97.12 172 |
|
| StellarMVS | | | 90.12 170 | 89.10 189 | 93.18 97 | 93.16 296 | 84.05 115 | 95.22 138 | 96.27 136 | 85.16 237 | 90.59 167 | 94.68 207 | 64.64 373 | 98.37 158 | 86.38 206 | 95.77 143 | 97.12 172 |
|
| CS-MVS | | | 94.12 51 | 94.44 37 | 93.17 99 | 96.55 95 | 83.08 153 | 97.63 4 | 96.95 70 | 91.71 15 | 93.50 84 | 96.21 108 | 85.61 57 | 98.24 170 | 93.64 61 | 98.17 69 | 98.19 72 |
|
| nrg030 | | | 91.08 145 | 90.39 149 | 93.17 99 | 93.07 303 | 86.91 23 | 96.41 42 | 96.26 140 | 88.30 122 | 88.37 218 | 94.85 201 | 82.19 116 | 97.64 241 | 91.09 122 | 82.95 371 | 94.96 277 |
|
| MVSMamba_PlusPlus | | | 93.44 75 | 93.54 76 | 93.14 101 | 96.58 94 | 83.05 154 | 96.06 73 | 96.50 118 | 84.42 261 | 94.09 68 | 95.56 161 | 85.01 72 | 98.69 124 | 94.96 44 | 98.66 44 | 97.67 130 |
|
| EI-MVSNet-UG-set | | | 92.74 97 | 92.62 96 | 93.12 102 | 94.86 186 | 83.20 143 | 94.40 202 | 95.74 200 | 90.71 35 | 92.05 122 | 96.60 96 | 84.00 84 | 98.99 82 | 91.55 117 | 93.63 207 | 97.17 163 |
|
| test_fmvsmvis_n_1920 | | | 93.44 75 | 93.55 75 | 93.10 103 | 93.67 282 | 84.26 109 | 95.83 95 | 96.14 160 | 89.00 99 | 92.43 115 | 97.50 48 | 83.37 92 | 98.72 120 | 96.61 24 | 97.44 100 | 96.32 217 |
|
| æ–°å‡ ä½•1 | | | | | 93.10 103 | 97.30 76 | 84.35 108 | | 95.56 218 | 71.09 464 | 91.26 150 | 96.24 107 | 82.87 102 | 98.86 102 | 79.19 340 | 98.10 75 | 96.07 233 |
|
| OMC-MVS | | | 91.23 136 | 90.62 146 | 93.08 105 | 96.27 105 | 84.07 113 | 93.52 269 | 95.93 182 | 86.95 181 | 89.51 194 | 96.13 120 | 78.50 181 | 98.35 162 | 85.84 215 | 92.90 233 | 96.83 199 |
|
| OpenMVS |  | 83.78 11 | 88.74 224 | 87.29 243 | 93.08 105 | 92.70 322 | 85.39 78 | 96.57 40 | 96.43 121 | 78.74 381 | 80.85 386 | 96.07 123 | 69.64 316 | 99.01 75 | 78.01 354 | 96.65 124 | 94.83 285 |
|
| MAR-MVS | | | 90.30 166 | 89.37 182 | 93.07 107 | 96.61 91 | 84.48 99 | 95.68 107 | 95.67 209 | 82.36 310 | 87.85 228 | 92.85 282 | 76.63 206 | 98.80 111 | 80.01 320 | 96.68 123 | 95.91 239 |
| 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 |
| lupinMVS | | | 90.92 146 | 90.21 153 | 93.03 108 | 93.86 267 | 83.88 120 | 92.81 307 | 93.86 324 | 79.84 362 | 91.76 136 | 94.29 228 | 77.92 190 | 98.04 199 | 90.48 137 | 97.11 106 | 97.17 163 |
|
| Effi-MVS+ | | | 91.59 130 | 91.11 132 | 93.01 109 | 94.35 234 | 83.39 137 | 94.60 183 | 95.10 254 | 87.10 175 | 90.57 169 | 93.10 277 | 81.43 131 | 98.07 193 | 89.29 159 | 94.48 180 | 97.59 136 |
|
| fmvsm_s_conf0.5_n_a | | | 93.57 68 | 93.76 68 | 93.00 110 | 95.02 171 | 83.67 126 | 96.19 57 | 96.10 166 | 87.27 168 | 95.98 40 | 98.05 27 | 83.07 99 | 98.45 151 | 96.68 23 | 95.51 149 | 96.88 193 |
|
| MVS_111021_LR | | | 92.47 102 | 92.29 103 | 92.98 111 | 95.99 125 | 84.43 103 | 93.08 293 | 96.09 167 | 88.20 127 | 91.12 155 | 95.72 153 | 81.33 132 | 97.76 230 | 91.74 113 | 97.37 102 | 96.75 201 |
|
| fmvsm_s_conf0.1_n_a | | | 93.19 86 | 93.26 80 | 92.97 112 | 92.49 326 | 83.62 129 | 96.02 77 | 95.72 204 | 86.78 186 | 96.04 38 | 98.19 4 | 82.30 111 | 98.43 155 | 96.38 25 | 95.42 155 | 96.86 194 |
|
| ETV-MVS | | | 92.74 97 | 92.66 94 | 92.97 112 | 95.20 164 | 84.04 117 | 95.07 150 | 96.51 117 | 90.73 34 | 92.96 93 | 91.19 343 | 84.06 83 | 98.34 163 | 91.72 114 | 96.54 126 | 96.54 212 |
|
| LFMVS | | | 90.08 173 | 89.13 188 | 92.95 114 | 96.71 87 | 82.32 184 | 96.08 69 | 89.91 439 | 86.79 185 | 92.15 121 | 96.81 84 | 62.60 392 | 98.34 163 | 87.18 194 | 93.90 196 | 98.19 72 |
|
| UGNet | | | 89.95 180 | 88.95 197 | 92.95 114 | 94.51 217 | 83.31 139 | 95.70 106 | 95.23 246 | 89.37 79 | 87.58 235 | 93.94 244 | 64.00 381 | 98.78 114 | 83.92 246 | 96.31 132 | 96.74 202 |
| 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 |
| jason | | | 90.80 148 | 90.10 157 | 92.90 116 | 93.04 306 | 83.53 132 | 93.08 293 | 94.15 313 | 80.22 356 | 91.41 146 | 94.91 195 | 76.87 200 | 97.93 219 | 90.28 138 | 96.90 115 | 97.24 156 |
| jason: jason. |
| DP-MVS | | | 87.25 278 | 85.36 317 | 92.90 116 | 97.65 64 | 83.24 141 | 94.81 169 | 92.00 382 | 74.99 431 | 81.92 375 | 95.00 191 | 72.66 272 | 99.05 67 | 66.92 444 | 92.33 249 | 96.40 214 |
|
| fmvsm_s_conf0.5_n_8 | | | 94.56 30 | 95.12 18 | 92.87 118 | 95.96 128 | 81.32 215 | 95.76 102 | 97.57 7 | 93.48 2 | 97.53 10 | 98.32 3 | 81.78 127 | 99.13 62 | 97.91 2 | 97.81 90 | 98.16 75 |
|
| fmvsm_s_conf0.5_n | | | 93.76 64 | 94.06 58 | 92.86 119 | 95.62 144 | 83.17 145 | 96.14 64 | 96.12 164 | 88.13 130 | 95.82 43 | 98.04 30 | 83.43 89 | 98.48 143 | 96.97 21 | 96.23 133 | 96.92 190 |
|
| fmvsm_s_conf0.1_n | | | 93.46 72 | 93.66 73 | 92.85 120 | 93.75 274 | 83.13 147 | 96.02 77 | 95.74 200 | 87.68 156 | 95.89 41 | 98.17 5 | 82.78 103 | 98.46 147 | 96.71 22 | 96.17 135 | 96.98 184 |
|
| casdiffseed414692147 | | | 91.11 143 | 90.55 147 | 92.81 121 | 94.27 242 | 82.58 177 | 94.81 169 | 96.03 174 | 87.93 143 | 90.17 182 | 95.62 157 | 78.51 180 | 97.90 223 | 84.18 242 | 93.45 216 | 97.94 98 |
|
| CANet_DTU | | | 90.26 168 | 89.41 181 | 92.81 121 | 93.46 289 | 83.01 157 | 93.48 270 | 94.47 297 | 89.43 77 | 87.76 233 | 94.23 233 | 70.54 304 | 99.03 70 | 84.97 225 | 96.39 130 | 96.38 215 |
|
| MVSFormer | | | 91.68 128 | 91.30 127 | 92.80 123 | 93.86 267 | 83.88 120 | 95.96 83 | 95.90 186 | 84.66 257 | 91.76 136 | 94.91 195 | 77.92 190 | 97.30 284 | 89.64 155 | 97.11 106 | 97.24 156 |
|
| PVSNet_Blended_VisFu | | | 91.38 133 | 90.91 138 | 92.80 123 | 96.39 102 | 83.17 145 | 94.87 163 | 96.66 105 | 83.29 288 | 89.27 200 | 94.46 223 | 80.29 143 | 99.17 57 | 87.57 187 | 95.37 156 | 96.05 236 |
|
| fmvsm_l_conf0.5_n_9 | | | 94.65 27 | 95.28 15 | 92.77 125 | 95.95 129 | 81.83 197 | 95.53 120 | 97.12 55 | 91.68 16 | 97.89 1 | 98.06 24 | 85.71 56 | 98.65 127 | 97.32 12 | 98.26 62 | 97.83 118 |
|
| LuminaMVS | | | 90.55 162 | 89.81 167 | 92.77 125 | 92.78 320 | 84.21 110 | 94.09 228 | 94.17 312 | 85.82 209 | 91.54 141 | 94.14 235 | 69.93 310 | 97.92 220 | 91.62 116 | 94.21 190 | 96.18 225 |
|
| balanced_ft_v1 | | | 92.23 107 | 92.05 106 | 92.77 125 | 95.40 153 | 81.78 201 | 95.80 96 | 95.69 208 | 87.94 141 | 91.92 129 | 95.04 189 | 75.91 218 | 98.71 122 | 93.83 58 | 96.94 112 | 97.82 120 |
|
| fmvsm_s_conf0.5_n_6 | | | 94.11 52 | 94.56 33 | 92.76 128 | 94.98 176 | 81.96 194 | 95.79 98 | 97.29 39 | 89.31 82 | 97.52 11 | 97.61 44 | 83.25 94 | 98.88 99 | 97.05 19 | 98.22 68 | 97.43 146 |
|
| VDDNet | | | 89.56 193 | 88.49 212 | 92.76 128 | 95.07 170 | 82.09 188 | 96.30 47 | 93.19 348 | 81.05 350 | 91.88 130 | 96.86 80 | 61.16 410 | 98.33 165 | 88.43 174 | 92.49 248 | 97.84 117 |
|
| viewdifsd2359ckpt09 | | | 91.18 139 | 90.65 145 | 92.75 130 | 94.61 208 | 82.36 183 | 94.32 211 | 95.74 200 | 84.72 254 | 89.66 192 | 95.15 186 | 79.69 161 | 98.04 199 | 87.70 184 | 94.27 189 | 97.85 116 |
|
| h-mvs33 | | | 90.80 148 | 90.15 156 | 92.75 130 | 96.01 121 | 82.66 170 | 95.43 123 | 95.53 222 | 89.80 62 | 93.08 90 | 95.64 156 | 75.77 219 | 99.00 80 | 92.07 100 | 78.05 428 | 96.60 207 |
|
| hybridcas | | | 92.43 103 | 92.33 100 | 92.74 132 | 94.51 217 | 81.84 196 | 95.05 153 | 96.16 158 | 89.60 71 | 91.40 147 | 96.20 109 | 82.23 113 | 98.09 188 | 89.95 146 | 95.87 140 | 98.28 61 |
|
| casdiffmvs |  | | 92.51 100 | 92.43 99 | 92.74 132 | 94.41 229 | 81.98 192 | 94.54 187 | 96.23 144 | 89.57 73 | 91.96 126 | 96.17 114 | 82.58 105 | 98.01 206 | 90.95 127 | 95.45 154 | 98.23 70 |
| 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_yl | | | 90.69 153 | 90.02 163 | 92.71 134 | 95.72 137 | 82.41 181 | 94.11 224 | 95.12 252 | 85.63 216 | 91.49 143 | 94.70 205 | 74.75 234 | 98.42 156 | 86.13 210 | 92.53 246 | 97.31 148 |
|
| DCV-MVSNet | | | 90.69 153 | 90.02 163 | 92.71 134 | 95.72 137 | 82.41 181 | 94.11 224 | 95.12 252 | 85.63 216 | 91.49 143 | 94.70 205 | 74.75 234 | 98.42 156 | 86.13 210 | 92.53 246 | 97.31 148 |
|
| PCF-MVS | | 84.11 10 | 87.74 252 | 86.08 290 | 92.70 136 | 94.02 256 | 84.43 103 | 89.27 415 | 95.87 191 | 73.62 446 | 84.43 322 | 94.33 225 | 78.48 183 | 98.86 102 | 70.27 418 | 94.45 181 | 94.81 286 |
| Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
| fmvsm_s_conf0.5_n_11 | | | 94.60 28 | 95.23 16 | 92.69 137 | 96.05 120 | 82.00 190 | 96.31 46 | 96.71 101 | 92.27 8 | 96.68 30 | 98.39 2 | 85.32 63 | 98.92 95 | 97.20 14 | 98.16 70 | 97.17 163 |
|
| SSM_0404 | | | 90.73 151 | 90.08 158 | 92.69 137 | 95.00 175 | 83.13 147 | 94.32 211 | 95.00 262 | 85.41 227 | 89.84 187 | 95.35 172 | 76.13 209 | 97.98 211 | 85.46 220 | 94.18 191 | 96.95 186 |
|
| baseline | | | 92.39 105 | 92.29 103 | 92.69 137 | 94.46 224 | 81.77 202 | 94.14 221 | 96.27 136 | 89.22 86 | 91.88 130 | 96.00 128 | 82.35 108 | 97.99 208 | 91.05 123 | 95.27 160 | 98.30 55 |
|
| MSLP-MVS++ | | | 93.72 66 | 94.08 55 | 92.65 140 | 97.31 75 | 83.43 134 | 95.79 98 | 97.33 32 | 90.03 52 | 93.58 80 | 96.96 76 | 84.87 74 | 97.76 230 | 92.19 96 | 98.66 44 | 96.76 200 |
|
| EC-MVSNet | | | 93.44 75 | 93.71 71 | 92.63 141 | 95.21 163 | 82.43 178 | 97.27 14 | 96.71 101 | 90.57 38 | 92.88 95 | 95.80 146 | 83.16 95 | 98.16 176 | 93.68 59 | 98.14 73 | 97.31 148 |
|
| ab-mvs | | | 89.41 201 | 88.35 214 | 92.60 142 | 95.15 168 | 82.65 174 | 92.20 335 | 95.60 216 | 83.97 268 | 88.55 214 | 93.70 258 | 74.16 249 | 98.21 174 | 82.46 270 | 89.37 294 | 96.94 188 |
|
| LS3D | | | 87.89 247 | 86.32 279 | 92.59 143 | 96.07 118 | 82.92 160 | 95.23 136 | 94.92 272 | 75.66 423 | 82.89 361 | 95.98 130 | 72.48 276 | 99.21 55 | 68.43 432 | 95.23 161 | 95.64 253 |
|
| Anonymous20240529 | | | 88.09 243 | 86.59 268 | 92.58 144 | 96.53 97 | 81.92 195 | 95.99 79 | 95.84 193 | 74.11 441 | 89.06 204 | 95.21 181 | 61.44 402 | 98.81 110 | 83.67 253 | 87.47 325 | 97.01 182 |
|
| fmvsm_s_conf0.5_n_3 | | | 94.49 32 | 95.13 17 | 92.56 145 | 95.49 150 | 81.10 225 | 95.93 86 | 97.16 50 | 92.96 4 | 97.39 12 | 98.13 7 | 83.63 88 | 98.80 111 | 97.89 3 | 97.61 98 | 97.78 123 |
|
| CPTT-MVS | | | 91.99 109 | 91.80 109 | 92.55 146 | 98.24 37 | 81.98 192 | 96.76 35 | 96.49 119 | 81.89 327 | 90.24 175 | 96.44 103 | 78.59 177 | 98.61 135 | 89.68 153 | 97.85 88 | 97.06 176 |
|
| viewdifsd2359ckpt13 | | | 91.20 138 | 90.75 143 | 92.54 147 | 94.30 240 | 82.13 187 | 94.03 234 | 95.89 188 | 85.60 218 | 90.20 177 | 95.36 171 | 79.69 161 | 97.90 223 | 87.85 182 | 93.86 197 | 97.61 133 |
|
| 114514_t | | | 89.51 194 | 88.50 210 | 92.54 147 | 98.11 42 | 81.99 191 | 95.16 146 | 96.36 128 | 70.19 468 | 85.81 275 | 95.25 177 | 76.70 204 | 98.63 132 | 82.07 280 | 96.86 118 | 97.00 183 |
|
| PAPM_NR | | | 91.22 137 | 90.78 142 | 92.52 149 | 97.60 65 | 81.46 211 | 94.37 208 | 96.24 143 | 86.39 197 | 87.41 238 | 94.80 203 | 82.06 120 | 98.48 143 | 82.80 265 | 95.37 156 | 97.61 133 |
|
| mamba_0408 | | | 89.06 214 | 87.92 228 | 92.50 150 | 94.76 191 | 82.66 170 | 79.84 488 | 94.64 290 | 85.18 232 | 88.96 206 | 95.00 191 | 76.00 214 | 97.98 211 | 83.74 250 | 93.15 226 | 96.85 195 |
|
| DeepPCF-MVS | | 89.96 1 | 94.20 47 | 94.77 31 | 92.49 151 | 96.52 98 | 80.00 276 | 94.00 239 | 97.08 59 | 90.05 51 | 95.65 47 | 97.29 57 | 89.66 14 | 98.97 87 | 93.95 55 | 98.71 35 | 98.50 32 |
|
| SSM_0407 | | | 90.47 164 | 89.80 168 | 92.46 152 | 94.76 191 | 82.66 170 | 93.98 241 | 95.00 262 | 85.41 227 | 88.96 206 | 95.35 172 | 76.13 209 | 97.88 225 | 85.46 220 | 93.15 226 | 96.85 195 |
|
| IS-MVSNet | | | 91.43 132 | 91.09 134 | 92.46 152 | 95.87 132 | 81.38 214 | 96.95 24 | 93.69 337 | 89.72 68 | 89.50 196 | 95.98 130 | 78.57 178 | 97.77 229 | 83.02 259 | 96.50 128 | 98.22 71 |
|
| API-MVS | | | 90.66 157 | 90.07 159 | 92.45 154 | 96.36 103 | 84.57 94 | 96.06 73 | 95.22 248 | 82.39 308 | 89.13 201 | 94.27 231 | 80.32 142 | 98.46 147 | 80.16 318 | 96.71 122 | 94.33 309 |
|
| xiu_mvs_v1_base_debu | | | 90.64 158 | 90.05 160 | 92.40 155 | 93.97 262 | 84.46 100 | 93.32 278 | 95.46 226 | 85.17 234 | 92.25 116 | 94.03 236 | 70.59 300 | 98.57 138 | 90.97 124 | 94.67 171 | 94.18 313 |
|
| xiu_mvs_v1_base | | | 90.64 158 | 90.05 160 | 92.40 155 | 93.97 262 | 84.46 100 | 93.32 278 | 95.46 226 | 85.17 234 | 92.25 116 | 94.03 236 | 70.59 300 | 98.57 138 | 90.97 124 | 94.67 171 | 94.18 313 |
|
| xiu_mvs_v1_base_debi | | | 90.64 158 | 90.05 160 | 92.40 155 | 93.97 262 | 84.46 100 | 93.32 278 | 95.46 226 | 85.17 234 | 92.25 116 | 94.03 236 | 70.59 300 | 98.57 138 | 90.97 124 | 94.67 171 | 94.18 313 |
|
| fmvsm_s_conf0.5_n_2 | | | 93.47 71 | 93.83 62 | 92.39 158 | 95.36 154 | 81.19 221 | 95.20 143 | 96.56 113 | 90.37 41 | 97.13 18 | 98.03 31 | 77.47 196 | 98.96 89 | 97.79 6 | 96.58 125 | 97.03 179 |
|
| viewmacassd2359aftdt | | | 91.67 129 | 91.43 125 | 92.37 159 | 93.95 265 | 81.00 229 | 93.90 249 | 95.97 179 | 87.75 154 | 91.45 145 | 96.04 126 | 79.92 149 | 97.97 213 | 89.26 160 | 94.67 171 | 98.14 77 |
|
| viewmanbaseed2359cas | | | 91.78 116 | 91.58 115 | 92.37 159 | 94.32 237 | 81.07 226 | 93.76 255 | 95.96 180 | 87.26 169 | 91.50 142 | 95.88 138 | 80.92 138 | 97.97 213 | 89.70 152 | 94.92 165 | 98.07 83 |
|
| fmvsm_s_conf0.1_n_2 | | | 93.16 88 | 93.42 77 | 92.37 159 | 94.62 205 | 81.13 223 | 95.23 136 | 95.89 188 | 90.30 45 | 96.74 29 | 98.02 32 | 76.14 208 | 98.95 91 | 97.64 7 | 96.21 134 | 97.03 179 |
|
| AdaColmap |  | | 89.89 183 | 89.07 191 | 92.37 159 | 97.41 71 | 83.03 155 | 94.42 197 | 95.92 183 | 82.81 302 | 86.34 264 | 94.65 212 | 73.89 254 | 99.02 73 | 80.69 307 | 95.51 149 | 95.05 272 |
|
| CNLPA | | | 89.07 213 | 87.98 225 | 92.34 163 | 96.87 84 | 84.78 89 | 94.08 229 | 93.24 345 | 81.41 341 | 84.46 320 | 95.13 187 | 75.57 226 | 96.62 336 | 77.21 361 | 93.84 199 | 95.61 256 |
|
| fmvsm_s_conf0.5_n_4 | | | 93.86 61 | 94.37 40 | 92.33 164 | 95.13 169 | 80.95 232 | 95.64 113 | 96.97 65 | 89.60 71 | 96.85 24 | 97.77 40 | 83.08 98 | 98.92 95 | 97.49 8 | 96.78 120 | 97.13 171 |
|
| ET-MVSNet_ETH3D | | | 87.51 266 | 85.91 298 | 92.32 165 | 93.70 281 | 83.93 118 | 92.33 327 | 90.94 415 | 84.16 263 | 72.09 466 | 92.52 295 | 69.90 311 | 95.85 388 | 89.20 161 | 88.36 312 | 97.17 163 |
|
| E4 | | | 91.74 121 | 91.55 118 | 92.31 166 | 94.27 242 | 80.80 242 | 93.81 252 | 96.17 156 | 87.97 139 | 91.11 156 | 96.05 124 | 80.75 139 | 98.08 191 | 89.78 148 | 94.02 193 | 98.06 88 |
|
| E2 | | | 91.79 113 | 91.61 113 | 92.31 166 | 94.49 220 | 80.86 238 | 93.74 257 | 96.19 149 | 87.63 159 | 91.16 151 | 95.94 133 | 81.31 133 | 98.06 194 | 89.76 149 | 94.29 187 | 97.99 93 |
|
| Anonymous202405211 | | | 87.68 253 | 86.13 286 | 92.31 166 | 96.66 89 | 80.74 244 | 94.87 163 | 91.49 399 | 80.47 355 | 89.46 197 | 95.44 166 | 54.72 451 | 98.23 171 | 82.19 276 | 89.89 284 | 97.97 95 |
|
| E3 | | | 91.78 116 | 91.61 113 | 92.30 169 | 94.48 221 | 80.86 238 | 93.73 258 | 96.19 149 | 87.63 159 | 91.16 151 | 95.95 132 | 81.30 134 | 98.06 194 | 89.76 149 | 94.29 187 | 97.99 93 |
|
| CHOSEN 1792x2688 | | | 88.84 220 | 87.69 233 | 92.30 169 | 96.14 109 | 81.42 213 | 90.01 402 | 95.86 192 | 74.52 436 | 87.41 238 | 93.94 244 | 75.46 227 | 98.36 160 | 80.36 313 | 95.53 148 | 97.12 172 |
|
| viewcassd2359sk11 | | | 91.79 113 | 91.62 112 | 92.29 171 | 94.62 205 | 80.88 236 | 93.70 262 | 96.18 155 | 87.38 166 | 91.13 154 | 95.85 142 | 81.62 129 | 98.06 194 | 89.71 151 | 94.40 183 | 97.94 98 |
|
| HY-MVS | | 83.01 12 | 89.03 216 | 87.94 227 | 92.29 171 | 94.86 186 | 82.77 162 | 92.08 340 | 94.49 296 | 81.52 340 | 86.93 245 | 92.79 288 | 78.32 185 | 98.23 171 | 79.93 321 | 90.55 271 | 95.88 242 |
|
| CDS-MVSNet | | | 89.45 197 | 88.51 209 | 92.29 171 | 93.62 284 | 83.61 131 | 93.01 297 | 94.68 288 | 81.95 322 | 87.82 231 | 93.24 271 | 78.69 175 | 96.99 313 | 80.34 314 | 93.23 223 | 96.28 220 |
| Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
| PAPR | | | 90.02 176 | 89.27 187 | 92.29 171 | 95.78 134 | 80.95 232 | 92.68 312 | 96.22 145 | 81.91 324 | 86.66 255 | 93.75 256 | 82.23 113 | 98.44 153 | 79.40 339 | 94.79 168 | 97.48 142 |
|
| E3new | | | 91.76 119 | 91.58 115 | 92.28 175 | 94.69 202 | 80.90 235 | 93.68 265 | 96.17 156 | 87.15 172 | 91.09 161 | 95.70 154 | 81.75 128 | 98.05 198 | 89.67 154 | 94.35 184 | 97.90 110 |
|
| mvsmamba | | | 90.33 165 | 89.69 171 | 92.25 176 | 95.17 165 | 81.64 204 | 95.27 134 | 93.36 343 | 84.88 247 | 89.51 194 | 94.27 231 | 69.29 326 | 97.42 267 | 89.34 158 | 96.12 137 | 97.68 129 |
|
| E5new | | | 91.71 123 | 91.55 118 | 92.20 177 | 94.33 235 | 80.62 248 | 94.41 198 | 96.19 149 | 88.06 133 | 91.11 156 | 96.16 115 | 79.92 149 | 98.03 202 | 90.00 141 | 93.80 201 | 97.94 98 |
|
| E6new | | | 91.71 123 | 91.55 118 | 92.20 177 | 94.32 237 | 80.62 248 | 94.41 198 | 96.19 149 | 88.06 133 | 91.11 156 | 96.16 115 | 79.92 149 | 98.03 202 | 90.00 141 | 93.80 201 | 97.94 98 |
|
| E6 | | | 91.71 123 | 91.55 118 | 92.20 177 | 94.32 237 | 80.62 248 | 94.41 198 | 96.19 149 | 88.06 133 | 91.11 156 | 96.16 115 | 79.92 149 | 98.03 202 | 90.00 141 | 93.80 201 | 97.94 98 |
|
| E5 | | | 91.71 123 | 91.55 118 | 92.20 177 | 94.33 235 | 80.62 248 | 94.41 198 | 96.19 149 | 88.06 133 | 91.11 156 | 96.16 115 | 79.92 149 | 98.03 202 | 90.00 141 | 93.80 201 | 97.94 98 |
|
| PLC |  | 84.53 7 | 89.06 214 | 88.03 223 | 92.15 181 | 97.27 78 | 82.69 169 | 94.29 213 | 95.44 231 | 79.71 364 | 84.01 336 | 94.18 234 | 76.68 205 | 98.75 116 | 77.28 360 | 93.41 217 | 95.02 273 |
| Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
| EPP-MVSNet | | | 91.70 127 | 91.56 117 | 92.13 182 | 95.88 130 | 80.50 255 | 97.33 8 | 95.25 245 | 86.15 203 | 89.76 191 | 95.60 158 | 83.42 91 | 98.32 167 | 87.37 192 | 93.25 222 | 97.56 138 |
|
| patch_mono-2 | | | 93.74 65 | 94.32 41 | 92.01 183 | 97.54 66 | 78.37 326 | 93.40 274 | 97.19 44 | 88.02 137 | 94.99 57 | 97.21 62 | 88.35 25 | 98.44 153 | 94.07 54 | 98.09 76 | 99.23 1 |
|
| 原ACMM1 | | | | | 92.01 183 | 97.34 73 | 81.05 227 | | 96.81 88 | 78.89 375 | 90.45 170 | 95.92 135 | 82.65 104 | 98.84 106 | 80.68 308 | 98.26 62 | 96.14 227 |
|
| UniMVSNet (Re) | | | 89.80 186 | 89.07 191 | 92.01 183 | 93.60 285 | 84.52 97 | 94.78 172 | 97.47 16 | 89.26 85 | 86.44 261 | 92.32 301 | 82.10 118 | 97.39 278 | 84.81 229 | 80.84 405 | 94.12 317 |
|
| MG-MVS | | | 91.77 118 | 91.70 111 | 92.00 186 | 97.08 81 | 80.03 274 | 93.60 267 | 95.18 250 | 87.85 149 | 90.89 164 | 96.47 102 | 82.06 120 | 98.36 160 | 85.07 224 | 97.04 109 | 97.62 132 |
|
| EIA-MVS | | | 91.95 110 | 91.94 107 | 91.98 187 | 95.16 166 | 80.01 275 | 95.36 124 | 96.73 98 | 88.44 117 | 89.34 198 | 92.16 306 | 83.82 87 | 98.45 151 | 89.35 157 | 97.06 108 | 97.48 142 |
|
| PVSNet_Blended | | | 90.73 151 | 90.32 151 | 91.98 187 | 96.12 111 | 81.25 217 | 92.55 317 | 96.83 83 | 82.04 320 | 89.10 202 | 92.56 294 | 81.04 136 | 98.85 104 | 86.72 202 | 95.91 139 | 95.84 244 |
|
| guyue | | | 91.12 142 | 90.84 140 | 91.96 189 | 94.59 209 | 80.57 253 | 94.87 163 | 93.71 336 | 88.96 100 | 91.14 153 | 95.22 178 | 73.22 266 | 97.76 230 | 92.01 104 | 93.81 200 | 97.54 141 |
|
| PS-MVSNAJ | | | 91.18 139 | 90.92 137 | 91.96 189 | 95.26 161 | 82.60 176 | 92.09 339 | 95.70 206 | 86.27 199 | 91.84 132 | 92.46 296 | 79.70 158 | 98.99 82 | 89.08 162 | 95.86 141 | 94.29 310 |
|
| TAMVS | | | 89.21 207 | 88.29 218 | 91.96 189 | 93.71 279 | 82.62 175 | 93.30 282 | 94.19 310 | 82.22 314 | 87.78 232 | 93.94 244 | 78.83 172 | 96.95 316 | 77.70 356 | 92.98 231 | 96.32 217 |
|
| SDMVSNet | | | 90.19 169 | 89.61 174 | 91.93 192 | 96.00 122 | 83.09 152 | 92.89 304 | 95.98 176 | 88.73 107 | 86.85 251 | 95.20 182 | 72.09 283 | 97.08 304 | 88.90 167 | 89.85 286 | 95.63 254 |
|
| FA-MVS(test-final) | | | 89.66 189 | 88.91 199 | 91.93 192 | 94.57 213 | 80.27 259 | 91.36 360 | 94.74 285 | 84.87 248 | 89.82 188 | 92.61 293 | 74.72 237 | 98.47 146 | 83.97 245 | 93.53 211 | 97.04 178 |
|
| MVS_Test | | | 91.31 135 | 91.11 132 | 91.93 192 | 94.37 230 | 80.14 264 | 93.46 272 | 95.80 195 | 86.46 195 | 91.35 149 | 93.77 254 | 82.21 115 | 98.09 188 | 87.57 187 | 94.95 164 | 97.55 139 |
|
| NR-MVSNet | | | 88.58 230 | 87.47 239 | 91.93 192 | 93.04 306 | 84.16 112 | 94.77 173 | 96.25 142 | 89.05 93 | 80.04 400 | 93.29 269 | 79.02 170 | 97.05 309 | 81.71 291 | 80.05 415 | 94.59 293 |
|
| HyFIR lowres test | | | 88.09 243 | 86.81 256 | 91.93 192 | 96.00 122 | 80.63 246 | 90.01 402 | 95.79 196 | 73.42 448 | 87.68 234 | 92.10 312 | 73.86 255 | 97.96 215 | 80.75 306 | 91.70 254 | 97.19 162 |
|
| GeoE | | | 90.05 174 | 89.43 179 | 91.90 197 | 95.16 166 | 80.37 258 | 95.80 96 | 94.65 289 | 83.90 269 | 87.55 237 | 94.75 204 | 78.18 186 | 97.62 243 | 81.28 296 | 93.63 207 | 97.71 128 |
|
| thisisatest0530 | | | 88.67 225 | 87.61 235 | 91.86 198 | 94.87 185 | 80.07 269 | 94.63 182 | 89.90 440 | 84.00 267 | 88.46 216 | 93.78 253 | 66.88 350 | 98.46 147 | 83.30 255 | 92.65 239 | 97.06 176 |
|
| xiu_mvs_v2_base | | | 91.13 141 | 90.89 139 | 91.86 198 | 94.97 177 | 82.42 179 | 92.24 332 | 95.64 214 | 86.11 207 | 91.74 138 | 93.14 275 | 79.67 163 | 98.89 98 | 89.06 163 | 95.46 153 | 94.28 311 |
|
| DU-MVS | | | 89.34 206 | 88.50 210 | 91.85 200 | 93.04 306 | 83.72 124 | 94.47 193 | 96.59 110 | 89.50 74 | 86.46 258 | 93.29 269 | 77.25 198 | 97.23 293 | 84.92 226 | 81.02 401 | 94.59 293 |
|
| AstraMVS | | | 90.69 153 | 90.30 152 | 91.84 201 | 93.81 270 | 79.85 282 | 94.76 174 | 92.39 368 | 88.96 100 | 91.01 163 | 95.87 141 | 70.69 298 | 97.94 218 | 92.49 82 | 92.70 238 | 97.73 126 |
|
| OPM-MVS | | | 90.12 170 | 89.56 175 | 91.82 202 | 93.14 298 | 83.90 119 | 94.16 220 | 95.74 200 | 88.96 100 | 87.86 227 | 95.43 168 | 72.48 276 | 97.91 221 | 88.10 179 | 90.18 278 | 93.65 351 |
| Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS). |
| HQP_MVS | | | 90.60 161 | 90.19 154 | 91.82 202 | 94.70 200 | 82.73 166 | 95.85 93 | 96.22 145 | 90.81 27 | 86.91 247 | 94.86 199 | 74.23 245 | 98.12 178 | 88.15 175 | 89.99 280 | 94.63 290 |
|
| UniMVSNet_NR-MVSNet | | | 89.92 182 | 89.29 185 | 91.81 204 | 93.39 291 | 83.72 124 | 94.43 196 | 97.12 55 | 89.80 62 | 86.46 258 | 93.32 266 | 83.16 95 | 97.23 293 | 84.92 226 | 81.02 401 | 94.49 303 |
|
| diffmvs |  | | 91.37 134 | 91.23 130 | 91.77 205 | 93.09 301 | 80.27 259 | 92.36 323 | 95.52 223 | 87.03 177 | 91.40 147 | 94.93 194 | 80.08 146 | 97.44 265 | 92.13 99 | 94.56 177 | 97.61 133 |
| Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025 |
| diffmvs_AUTHOR | | | 91.51 131 | 91.44 124 | 91.73 206 | 93.09 301 | 80.27 259 | 92.51 318 | 95.58 217 | 87.22 170 | 91.80 135 | 95.57 160 | 79.96 148 | 97.48 257 | 92.23 93 | 94.97 163 | 97.45 144 |
|
| 1112_ss | | | 88.42 232 | 87.33 242 | 91.72 207 | 94.92 181 | 80.98 230 | 92.97 301 | 94.54 293 | 78.16 392 | 83.82 339 | 93.88 249 | 78.78 174 | 97.91 221 | 79.45 335 | 89.41 293 | 96.26 221 |
|
| Fast-Effi-MVS+ | | | 89.41 201 | 88.64 205 | 91.71 208 | 94.74 194 | 80.81 241 | 93.54 268 | 95.10 254 | 83.11 292 | 86.82 253 | 90.67 366 | 79.74 157 | 97.75 234 | 80.51 311 | 93.55 209 | 96.57 210 |
|
| WTY-MVS | | | 89.60 191 | 88.92 198 | 91.67 209 | 95.47 151 | 81.15 222 | 92.38 322 | 94.78 283 | 83.11 292 | 89.06 204 | 94.32 226 | 78.67 176 | 96.61 339 | 81.57 292 | 90.89 267 | 97.24 156 |
|
| TAPA-MVS | | 84.62 6 | 88.16 241 | 87.01 251 | 91.62 210 | 96.64 90 | 80.65 245 | 94.39 204 | 96.21 148 | 76.38 415 | 86.19 268 | 95.44 166 | 79.75 156 | 98.08 191 | 62.75 462 | 95.29 158 | 96.13 228 |
| Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
| VPA-MVSNet | | | 89.62 190 | 88.96 196 | 91.60 211 | 93.86 267 | 82.89 161 | 95.46 121 | 97.33 32 | 87.91 144 | 88.43 217 | 93.31 267 | 74.17 248 | 97.40 275 | 87.32 193 | 82.86 376 | 94.52 298 |
|
| FE-MVS | | | 87.40 271 | 86.02 292 | 91.57 212 | 94.56 214 | 79.69 289 | 90.27 389 | 93.72 335 | 80.57 353 | 88.80 210 | 91.62 332 | 65.32 366 | 98.59 137 | 74.97 386 | 94.33 186 | 96.44 213 |
|
| XVG-OURS | | | 89.40 203 | 88.70 204 | 91.52 213 | 94.06 254 | 81.46 211 | 91.27 365 | 96.07 169 | 86.14 204 | 88.89 209 | 95.77 150 | 68.73 335 | 97.26 290 | 87.39 191 | 89.96 282 | 95.83 245 |
|
| hse-mvs2 | | | 89.88 184 | 89.34 183 | 91.51 214 | 94.83 188 | 81.12 224 | 93.94 243 | 93.91 323 | 89.80 62 | 93.08 90 | 93.60 259 | 75.77 219 | 97.66 238 | 92.07 100 | 77.07 435 | 95.74 249 |
|
| TranMVSNet+NR-MVSNet | | | 88.84 220 | 87.95 226 | 91.49 215 | 92.68 323 | 83.01 157 | 94.92 160 | 96.31 131 | 89.88 56 | 85.53 284 | 93.85 251 | 76.63 206 | 96.96 315 | 81.91 284 | 79.87 418 | 94.50 301 |
|
| AUN-MVS | | | 87.78 251 | 86.54 271 | 91.48 216 | 94.82 189 | 81.05 227 | 93.91 247 | 93.93 320 | 83.00 297 | 86.93 245 | 93.53 261 | 69.50 320 | 97.67 236 | 86.14 208 | 77.12 434 | 95.73 251 |
|
| XVG-OURS-SEG-HR | | | 89.95 180 | 89.45 177 | 91.47 217 | 94.00 260 | 81.21 220 | 91.87 344 | 96.06 171 | 85.78 211 | 88.55 214 | 95.73 152 | 74.67 238 | 97.27 288 | 88.71 171 | 89.64 291 | 95.91 239 |
|
| MVS | | | 87.44 269 | 86.10 289 | 91.44 218 | 92.61 325 | 83.62 129 | 92.63 314 | 95.66 211 | 67.26 474 | 81.47 378 | 92.15 307 | 77.95 189 | 98.22 173 | 79.71 324 | 95.48 151 | 92.47 402 |
|
| hybrid | | | 90.69 153 | 90.45 148 | 91.43 219 | 92.67 324 | 79.42 297 | 92.28 331 | 95.21 249 | 85.15 239 | 90.39 173 | 95.37 170 | 78.93 171 | 97.32 283 | 90.27 139 | 93.74 205 | 97.55 139 |
|
| viewdifsd2359ckpt07 | | | 91.11 143 | 91.02 135 | 91.41 220 | 94.21 247 | 78.37 326 | 92.91 303 | 95.71 205 | 87.50 161 | 90.32 174 | 95.88 138 | 80.27 144 | 97.99 208 | 88.78 170 | 93.55 209 | 97.86 113 |
|
| F-COLMAP | | | 87.95 246 | 86.80 257 | 91.40 221 | 96.35 104 | 80.88 236 | 94.73 176 | 95.45 229 | 79.65 365 | 82.04 373 | 94.61 213 | 71.13 290 | 98.50 141 | 76.24 373 | 91.05 265 | 94.80 287 |
|
| dcpmvs_2 | | | 93.49 70 | 94.19 52 | 91.38 222 | 97.69 63 | 76.78 370 | 94.25 215 | 96.29 132 | 88.33 120 | 94.46 60 | 96.88 79 | 88.07 29 | 98.64 130 | 93.62 62 | 98.09 76 | 98.73 23 |
|
| thisisatest0515 | | | 87.33 274 | 85.99 293 | 91.37 223 | 93.49 287 | 79.55 290 | 90.63 381 | 89.56 448 | 80.17 357 | 87.56 236 | 90.86 356 | 67.07 347 | 98.28 169 | 81.50 293 | 93.02 230 | 96.29 219 |
|
| HQP-MVS | | | 89.80 186 | 89.28 186 | 91.34 224 | 94.17 249 | 81.56 205 | 94.39 204 | 96.04 172 | 88.81 103 | 85.43 293 | 93.97 243 | 73.83 256 | 97.96 215 | 87.11 197 | 89.77 289 | 94.50 301 |
|
| fmvsm_s_conf0.5_n_7 | | | 93.15 89 | 93.76 68 | 91.31 225 | 94.42 228 | 79.48 292 | 94.52 188 | 97.14 53 | 89.33 81 | 94.17 66 | 98.09 18 | 81.83 125 | 97.49 256 | 96.33 26 | 98.02 80 | 96.95 186 |
|
| RRT-MVS | | | 90.85 147 | 90.70 144 | 91.30 226 | 94.25 244 | 76.83 369 | 94.85 166 | 96.13 163 | 89.04 94 | 90.23 176 | 94.88 197 | 70.15 309 | 98.72 120 | 91.86 112 | 94.88 166 | 98.34 48 |
|
| FMVSNet3 | | | 87.40 271 | 86.11 288 | 91.30 226 | 93.79 273 | 83.64 128 | 94.20 219 | 94.81 281 | 83.89 270 | 84.37 323 | 91.87 323 | 68.45 338 | 96.56 348 | 78.23 351 | 85.36 344 | 93.70 350 |
|
| FMVSNet2 | | | 87.19 284 | 85.82 301 | 91.30 226 | 94.01 257 | 83.67 126 | 94.79 171 | 94.94 267 | 83.57 278 | 83.88 338 | 92.05 316 | 66.59 355 | 96.51 352 | 77.56 358 | 85.01 347 | 93.73 348 |
|
| RPMNet | | | 83.95 364 | 81.53 375 | 91.21 229 | 90.58 402 | 79.34 302 | 85.24 466 | 96.76 93 | 71.44 462 | 85.55 282 | 82.97 466 | 70.87 295 | 98.91 97 | 61.01 466 | 89.36 295 | 95.40 260 |
|
| IB-MVS | | 80.51 15 | 85.24 340 | 83.26 359 | 91.19 230 | 92.13 337 | 79.86 281 | 91.75 348 | 91.29 405 | 83.28 289 | 80.66 390 | 88.49 415 | 61.28 404 | 98.46 147 | 80.99 302 | 79.46 422 | 95.25 266 |
| 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 |
| CLD-MVS | | | 89.47 196 | 88.90 200 | 91.18 231 | 94.22 246 | 82.07 189 | 92.13 337 | 96.09 167 | 87.90 145 | 85.37 299 | 92.45 297 | 74.38 243 | 97.56 248 | 87.15 195 | 90.43 273 | 93.93 328 |
| Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
| LPG-MVS_test | | | 89.45 197 | 88.90 200 | 91.12 232 | 94.47 222 | 81.49 209 | 95.30 129 | 96.14 160 | 86.73 188 | 85.45 290 | 95.16 184 | 69.89 312 | 98.10 180 | 87.70 184 | 89.23 298 | 93.77 344 |
|
| LGP-MVS_train | | | | | 91.12 232 | 94.47 222 | 81.49 209 | | 96.14 160 | 86.73 188 | 85.45 290 | 95.16 184 | 69.89 312 | 98.10 180 | 87.70 184 | 89.23 298 | 93.77 344 |
|
| ACMM | | 84.12 9 | 89.14 209 | 88.48 213 | 91.12 232 | 94.65 204 | 81.22 219 | 95.31 127 | 96.12 164 | 85.31 231 | 85.92 273 | 94.34 224 | 70.19 308 | 98.06 194 | 85.65 216 | 88.86 303 | 94.08 321 |
| Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
| tttt0517 | | | 88.61 227 | 87.78 232 | 91.11 235 | 94.96 178 | 77.81 345 | 95.35 125 | 89.69 443 | 85.09 242 | 88.05 225 | 94.59 216 | 66.93 348 | 98.48 143 | 83.27 256 | 92.13 251 | 97.03 179 |
|
| GBi-Net | | | 87.26 276 | 85.98 294 | 91.08 236 | 94.01 257 | 83.10 149 | 95.14 147 | 94.94 267 | 83.57 278 | 84.37 323 | 91.64 328 | 66.59 355 | 96.34 366 | 78.23 351 | 85.36 344 | 93.79 339 |
|
| test1 | | | 87.26 276 | 85.98 294 | 91.08 236 | 94.01 257 | 83.10 149 | 95.14 147 | 94.94 267 | 83.57 278 | 84.37 323 | 91.64 328 | 66.59 355 | 96.34 366 | 78.23 351 | 85.36 344 | 93.79 339 |
|
| FMVSNet1 | | | 85.85 325 | 84.11 346 | 91.08 236 | 92.81 318 | 83.10 149 | 95.14 147 | 94.94 267 | 81.64 335 | 82.68 363 | 91.64 328 | 59.01 426 | 96.34 366 | 75.37 380 | 83.78 360 | 93.79 339 |
|
| Test_1112_low_res | | | 87.65 255 | 86.51 272 | 91.08 236 | 94.94 180 | 79.28 306 | 91.77 347 | 94.30 305 | 76.04 421 | 83.51 349 | 92.37 299 | 77.86 192 | 97.73 235 | 78.69 346 | 89.13 300 | 96.22 222 |
|
| PS-MVSNAJss | | | 89.97 178 | 89.62 173 | 91.02 240 | 91.90 346 | 80.85 240 | 95.26 135 | 95.98 176 | 86.26 200 | 86.21 267 | 94.29 228 | 79.70 158 | 97.65 239 | 88.87 169 | 88.10 314 | 94.57 295 |
|
| BH-RMVSNet | | | 88.37 235 | 87.48 238 | 91.02 240 | 95.28 158 | 79.45 294 | 92.89 304 | 93.07 351 | 85.45 226 | 86.91 247 | 94.84 202 | 70.35 305 | 97.76 230 | 73.97 395 | 94.59 176 | 95.85 243 |
|
| UniMVSNet_ETH3D | | | 87.53 265 | 86.37 276 | 91.00 242 | 92.44 329 | 78.96 311 | 94.74 175 | 95.61 215 | 84.07 266 | 85.36 300 | 94.52 218 | 59.78 418 | 97.34 281 | 82.93 260 | 87.88 319 | 96.71 203 |
|
| FIs | | | 90.51 163 | 90.35 150 | 90.99 243 | 93.99 261 | 80.98 230 | 95.73 104 | 97.54 9 | 89.15 89 | 86.72 254 | 94.68 207 | 81.83 125 | 97.24 292 | 85.18 222 | 88.31 313 | 94.76 288 |
|
| ACMP | | 84.23 8 | 89.01 218 | 88.35 214 | 90.99 243 | 94.73 195 | 81.27 216 | 95.07 150 | 95.89 188 | 86.48 193 | 83.67 344 | 94.30 227 | 69.33 322 | 97.99 208 | 87.10 199 | 88.55 305 | 93.72 349 |
| Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
| Anonymous20231211 | | | 86.59 308 | 85.13 323 | 90.98 245 | 96.52 98 | 81.50 207 | 96.14 64 | 96.16 158 | 73.78 444 | 83.65 345 | 92.15 307 | 63.26 387 | 97.37 280 | 82.82 264 | 81.74 390 | 94.06 322 |
|
| IMVS_0403 | | | 89.97 178 | 89.64 172 | 90.96 246 | 93.72 275 | 77.75 350 | 93.00 298 | 95.34 240 | 85.53 222 | 88.77 211 | 94.49 219 | 78.49 182 | 97.84 226 | 84.75 230 | 92.65 239 | 97.28 151 |
|
| sss | | | 88.93 219 | 88.26 220 | 90.94 247 | 94.05 255 | 80.78 243 | 91.71 349 | 95.38 235 | 81.55 339 | 88.63 213 | 93.91 248 | 75.04 231 | 95.47 407 | 82.47 269 | 91.61 255 | 96.57 210 |
|
| IMVS_0407 | | | 89.85 185 | 89.51 176 | 90.88 248 | 93.72 275 | 77.75 350 | 93.07 295 | 95.34 240 | 85.53 222 | 88.34 219 | 94.49 219 | 77.69 194 | 97.60 244 | 84.75 230 | 92.65 239 | 97.28 151 |
|
| dtuplus | | | 89.78 188 | 89.43 179 | 90.85 249 | 92.83 317 | 77.91 339 | 92.32 329 | 94.97 264 | 82.33 312 | 90.20 177 | 95.53 162 | 78.56 179 | 97.38 279 | 85.15 223 | 92.95 232 | 97.24 156 |
|
| viewmambaseed2359dif | | | 90.04 175 | 89.78 169 | 90.83 250 | 92.85 316 | 77.92 338 | 92.23 333 | 95.01 258 | 81.90 325 | 90.20 177 | 95.45 165 | 79.64 165 | 97.34 281 | 87.52 189 | 93.17 224 | 97.23 160 |
|
| sd_testset | | | 88.59 229 | 87.85 231 | 90.83 250 | 96.00 122 | 80.42 257 | 92.35 325 | 94.71 286 | 88.73 107 | 86.85 251 | 95.20 182 | 67.31 342 | 96.43 360 | 79.64 327 | 89.85 286 | 95.63 254 |
|
| PVSNet_BlendedMVS | | | 89.98 177 | 89.70 170 | 90.82 252 | 96.12 111 | 81.25 217 | 93.92 245 | 96.83 83 | 83.49 282 | 89.10 202 | 92.26 304 | 81.04 136 | 98.85 104 | 86.72 202 | 87.86 320 | 92.35 409 |
|
| cascas | | | 86.43 316 | 84.98 326 | 90.80 253 | 92.10 339 | 80.92 234 | 90.24 393 | 95.91 185 | 73.10 451 | 83.57 348 | 88.39 416 | 65.15 368 | 97.46 261 | 84.90 228 | 91.43 257 | 94.03 324 |
|
| ECVR-MVS |  | | 89.09 212 | 88.53 208 | 90.77 254 | 95.62 144 | 75.89 383 | 96.16 60 | 84.22 477 | 87.89 147 | 90.20 177 | 96.65 91 | 63.19 389 | 98.10 180 | 85.90 213 | 96.94 112 | 98.33 50 |
|
| GA-MVS | | | 86.61 306 | 85.27 320 | 90.66 255 | 91.33 369 | 78.71 315 | 90.40 388 | 93.81 330 | 85.34 230 | 85.12 303 | 89.57 397 | 61.25 405 | 97.11 302 | 80.99 302 | 89.59 292 | 96.15 226 |
|
| thres600view7 | | | 87.65 255 | 86.67 263 | 90.59 256 | 96.08 117 | 78.72 313 | 94.88 162 | 91.58 395 | 87.06 176 | 88.08 223 | 92.30 302 | 68.91 332 | 98.10 180 | 70.05 425 | 91.10 260 | 94.96 277 |
|
| thres400 | | | 87.62 260 | 86.64 264 | 90.57 257 | 95.99 125 | 78.64 316 | 94.58 184 | 91.98 384 | 86.94 182 | 88.09 221 | 91.77 324 | 69.18 328 | 98.10 180 | 70.13 422 | 91.10 260 | 94.96 277 |
|
| baseline1 | | | 88.10 242 | 87.28 244 | 90.57 257 | 94.96 178 | 80.07 269 | 94.27 214 | 91.29 405 | 86.74 187 | 87.41 238 | 94.00 241 | 76.77 203 | 96.20 371 | 80.77 305 | 79.31 424 | 95.44 258 |
|
| viewdifsd2359ckpt11 | | | 89.43 199 | 89.05 193 | 90.56 259 | 92.89 314 | 77.00 365 | 92.81 307 | 94.52 294 | 87.03 177 | 89.77 189 | 95.79 147 | 74.67 238 | 97.51 252 | 88.97 165 | 84.98 348 | 97.17 163 |
|
| viewmsd2359difaftdt | | | 89.43 199 | 89.05 193 | 90.56 259 | 92.89 314 | 77.00 365 | 92.81 307 | 94.52 294 | 87.03 177 | 89.77 189 | 95.79 147 | 74.67 238 | 97.51 252 | 88.97 165 | 84.98 348 | 97.17 163 |
|
| usedtu_dtu_shiyan1 | | | 86.84 295 | 85.61 309 | 90.53 261 | 90.50 406 | 81.80 199 | 90.97 373 | 94.96 265 | 83.05 294 | 83.50 350 | 90.32 373 | 72.15 280 | 96.65 330 | 79.49 332 | 85.55 342 | 93.15 374 |
|
| FE-MVSNET3 | | | 86.84 295 | 85.61 309 | 90.53 261 | 90.50 406 | 81.80 199 | 90.97 373 | 94.96 265 | 83.05 294 | 83.50 350 | 90.32 373 | 72.15 280 | 96.65 330 | 79.49 332 | 85.55 342 | 93.15 374 |
|
| FC-MVSNet-test | | | 90.27 167 | 90.18 155 | 90.53 261 | 93.71 279 | 79.85 282 | 95.77 100 | 97.59 6 | 89.31 82 | 86.27 265 | 94.67 210 | 81.93 123 | 97.01 312 | 84.26 240 | 88.09 316 | 94.71 289 |
|
| PAPM | | | 86.68 305 | 85.39 315 | 90.53 261 | 93.05 305 | 79.33 305 | 89.79 405 | 94.77 284 | 78.82 378 | 81.95 374 | 93.24 271 | 76.81 201 | 97.30 284 | 66.94 442 | 93.16 225 | 94.95 281 |
|
| WR-MVS | | | 88.38 234 | 87.67 234 | 90.52 265 | 93.30 293 | 80.18 262 | 93.26 285 | 95.96 180 | 88.57 115 | 85.47 289 | 92.81 286 | 76.12 211 | 96.91 319 | 81.24 297 | 82.29 381 | 94.47 306 |
|
| SSM_04072 | | | 88.57 231 | 87.92 228 | 90.51 266 | 94.76 191 | 82.66 170 | 79.84 488 | 94.64 290 | 85.18 232 | 88.96 206 | 95.00 191 | 76.00 214 | 92.03 458 | 83.74 250 | 93.15 226 | 96.85 195 |
|
| MVSTER | | | 88.84 220 | 88.29 218 | 90.51 266 | 92.95 311 | 80.44 256 | 93.73 258 | 95.01 258 | 84.66 257 | 87.15 242 | 93.12 276 | 72.79 271 | 97.21 295 | 87.86 181 | 87.36 328 | 93.87 333 |
|
| testdata | | | | | 90.49 268 | 96.40 101 | 77.89 342 | | 95.37 237 | 72.51 456 | 93.63 79 | 96.69 87 | 82.08 119 | 97.65 239 | 83.08 257 | 97.39 101 | 95.94 238 |
|
| test1111 | | | 89.10 210 | 88.64 205 | 90.48 269 | 95.53 149 | 74.97 393 | 96.08 69 | 84.89 475 | 88.13 130 | 90.16 183 | 96.65 91 | 63.29 386 | 98.10 180 | 86.14 208 | 96.90 115 | 98.39 45 |
|
| tt0805 | | | 86.92 292 | 85.74 307 | 90.48 269 | 92.22 333 | 79.98 277 | 95.63 114 | 94.88 275 | 83.83 272 | 84.74 312 | 92.80 287 | 57.61 433 | 97.67 236 | 85.48 219 | 84.42 353 | 93.79 339 |
|
| jajsoiax | | | 88.24 239 | 87.50 237 | 90.48 269 | 90.89 390 | 80.14 264 | 95.31 127 | 95.65 213 | 84.97 245 | 84.24 331 | 94.02 239 | 65.31 367 | 97.42 267 | 88.56 172 | 88.52 307 | 93.89 329 |
|
| PatchMatch-RL | | | 86.77 302 | 85.54 311 | 90.47 272 | 95.88 130 | 82.71 168 | 90.54 384 | 92.31 372 | 79.82 363 | 84.32 328 | 91.57 336 | 68.77 334 | 96.39 362 | 73.16 401 | 93.48 215 | 92.32 410 |
|
| 0.4-1-1-0.1 | | | 81.55 396 | 78.59 418 | 90.42 273 | 87.55 448 | 79.90 279 | 88.56 427 | 89.19 453 | 77.01 407 | 79.72 407 | 77.71 481 | 54.84 448 | 97.11 302 | 80.50 312 | 72.20 448 | 94.26 312 |
|
| tfpn200view9 | | | 87.58 263 | 86.64 264 | 90.41 274 | 95.99 125 | 78.64 316 | 94.58 184 | 91.98 384 | 86.94 182 | 88.09 221 | 91.77 324 | 69.18 328 | 98.10 180 | 70.13 422 | 91.10 260 | 94.48 304 |
|
| VPNet | | | 88.20 240 | 87.47 239 | 90.39 275 | 93.56 286 | 79.46 293 | 94.04 233 | 95.54 221 | 88.67 110 | 86.96 244 | 94.58 217 | 69.33 322 | 97.15 297 | 84.05 244 | 80.53 410 | 94.56 296 |
|
| ACMH | | 80.38 17 | 85.36 335 | 83.68 353 | 90.39 275 | 94.45 225 | 80.63 246 | 94.73 176 | 94.85 277 | 82.09 316 | 77.24 435 | 92.65 291 | 60.01 416 | 97.58 246 | 72.25 406 | 84.87 350 | 92.96 381 |
| Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
| thres100view900 | | | 87.63 258 | 86.71 260 | 90.38 277 | 96.12 111 | 78.55 319 | 95.03 154 | 91.58 395 | 87.15 172 | 88.06 224 | 92.29 303 | 68.91 332 | 98.10 180 | 70.13 422 | 91.10 260 | 94.48 304 |
|
| mvs_tets | | | 88.06 245 | 87.28 244 | 90.38 277 | 90.94 386 | 79.88 280 | 95.22 138 | 95.66 211 | 85.10 241 | 84.21 332 | 93.94 244 | 63.53 384 | 97.40 275 | 88.50 173 | 88.40 311 | 93.87 333 |
|
| 1314 | | | 87.51 266 | 86.57 269 | 90.34 279 | 92.42 330 | 79.74 287 | 92.63 314 | 95.35 239 | 78.35 387 | 80.14 397 | 91.62 332 | 74.05 250 | 97.15 297 | 81.05 298 | 93.53 211 | 94.12 317 |
|
| LTVRE_ROB | | 82.13 13 | 86.26 319 | 84.90 329 | 90.34 279 | 94.44 226 | 81.50 207 | 92.31 330 | 94.89 273 | 83.03 296 | 79.63 409 | 92.67 290 | 69.69 315 | 97.79 228 | 71.20 411 | 86.26 337 | 91.72 420 |
| 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 |
| 0.3-1-1-0.015 | | | 80.75 409 | 77.58 423 | 90.25 281 | 86.55 453 | 79.72 288 | 87.46 448 | 89.48 451 | 76.43 414 | 77.93 430 | 75.94 483 | 52.31 460 | 97.05 309 | 80.25 317 | 71.85 452 | 93.99 326 |
|
| test_djsdf | | | 89.03 216 | 88.64 205 | 90.21 282 | 90.74 397 | 79.28 306 | 95.96 83 | 95.90 186 | 84.66 257 | 85.33 301 | 92.94 281 | 74.02 251 | 97.30 284 | 89.64 155 | 88.53 306 | 94.05 323 |
|
| v2v482 | | | 87.84 248 | 87.06 248 | 90.17 283 | 90.99 382 | 79.23 309 | 94.00 239 | 95.13 251 | 84.87 248 | 85.53 284 | 92.07 315 | 74.45 242 | 97.45 262 | 84.71 235 | 81.75 389 | 93.85 336 |
|
| pmmvs4 | | | 85.43 333 | 83.86 351 | 90.16 284 | 90.02 417 | 82.97 159 | 90.27 389 | 92.67 363 | 75.93 422 | 80.73 388 | 91.74 326 | 71.05 291 | 95.73 396 | 78.85 345 | 83.46 367 | 91.78 419 |
|
| V42 | | | 87.68 253 | 86.86 253 | 90.15 285 | 90.58 402 | 80.14 264 | 94.24 217 | 95.28 244 | 83.66 276 | 85.67 279 | 91.33 338 | 74.73 236 | 97.41 273 | 84.43 239 | 81.83 387 | 92.89 384 |
|
| MSDG | | | 84.86 348 | 83.09 362 | 90.14 286 | 93.80 271 | 80.05 271 | 89.18 418 | 93.09 350 | 78.89 375 | 78.19 426 | 91.91 321 | 65.86 365 | 97.27 288 | 68.47 431 | 88.45 309 | 93.11 376 |
|
| sc_t1 | | | 81.53 397 | 78.67 417 | 90.12 287 | 90.78 394 | 78.64 316 | 93.91 247 | 90.20 429 | 68.42 471 | 80.82 387 | 89.88 390 | 46.48 475 | 96.76 324 | 76.03 376 | 71.47 453 | 94.96 277 |
|
| anonymousdsp | | | 87.84 248 | 87.09 247 | 90.12 287 | 89.13 428 | 80.54 254 | 94.67 180 | 95.55 219 | 82.05 318 | 83.82 339 | 92.12 309 | 71.47 288 | 97.15 297 | 87.15 195 | 87.80 323 | 92.67 391 |
|
| thres200 | | | 87.21 282 | 86.24 283 | 90.12 287 | 95.36 154 | 78.53 320 | 93.26 285 | 92.10 378 | 86.42 196 | 88.00 226 | 91.11 349 | 69.24 327 | 98.00 207 | 69.58 426 | 91.04 266 | 93.83 338 |
|
| CR-MVSNet | | | 85.35 336 | 83.76 352 | 90.12 287 | 90.58 402 | 79.34 302 | 85.24 466 | 91.96 386 | 78.27 389 | 85.55 282 | 87.87 426 | 71.03 292 | 95.61 399 | 73.96 396 | 89.36 295 | 95.40 260 |
|
| 0.4-1-1-0.2 | | | 80.84 408 | 77.77 421 | 90.06 291 | 86.18 457 | 79.35 300 | 86.75 454 | 89.54 449 | 76.23 419 | 78.59 425 | 75.46 486 | 55.03 447 | 96.99 313 | 80.11 319 | 72.05 450 | 93.85 336 |
|
| v1144 | | | 87.61 261 | 86.79 258 | 90.06 291 | 91.01 381 | 79.34 302 | 93.95 242 | 95.42 234 | 83.36 287 | 85.66 280 | 91.31 341 | 74.98 232 | 97.42 267 | 83.37 254 | 82.06 383 | 93.42 360 |
|
| XXY-MVS | | | 87.65 255 | 86.85 254 | 90.03 293 | 92.14 336 | 80.60 252 | 93.76 255 | 95.23 246 | 82.94 299 | 84.60 314 | 94.02 239 | 74.27 244 | 95.49 406 | 81.04 299 | 83.68 363 | 94.01 325 |
|
| Vis-MVSNet (Re-imp) | | | 89.59 192 | 89.44 178 | 90.03 293 | 95.74 135 | 75.85 384 | 95.61 115 | 90.80 419 | 87.66 158 | 87.83 230 | 95.40 169 | 76.79 202 | 96.46 357 | 78.37 347 | 96.73 121 | 97.80 121 |
|
| test2506 | | | 87.21 282 | 86.28 281 | 90.02 295 | 95.62 144 | 73.64 409 | 96.25 55 | 71.38 500 | 87.89 147 | 90.45 170 | 96.65 91 | 55.29 445 | 98.09 188 | 86.03 212 | 96.94 112 | 98.33 50 |
|
| BH-untuned | | | 88.60 228 | 88.13 222 | 90.01 296 | 95.24 162 | 78.50 322 | 93.29 283 | 94.15 313 | 84.75 253 | 84.46 320 | 93.40 263 | 75.76 221 | 97.40 275 | 77.59 357 | 94.52 179 | 94.12 317 |
|
| v1192 | | | 87.25 278 | 86.33 278 | 90.00 297 | 90.76 396 | 79.04 310 | 93.80 253 | 95.48 224 | 82.57 306 | 85.48 288 | 91.18 345 | 73.38 265 | 97.42 267 | 82.30 273 | 82.06 383 | 93.53 354 |
|
| v7n | | | 86.81 297 | 85.76 305 | 89.95 298 | 90.72 398 | 79.25 308 | 95.07 150 | 95.92 183 | 84.45 260 | 82.29 367 | 90.86 356 | 72.60 275 | 97.53 250 | 79.42 338 | 80.52 411 | 93.08 378 |
|
| testing91 | | | 87.11 287 | 86.18 284 | 89.92 299 | 94.43 227 | 75.38 392 | 91.53 355 | 92.27 374 | 86.48 193 | 86.50 256 | 90.24 376 | 61.19 408 | 97.53 250 | 82.10 278 | 90.88 268 | 96.84 198 |
|
| IMVS_0404 | | | 87.60 262 | 86.84 255 | 89.89 300 | 93.72 275 | 77.75 350 | 88.56 427 | 95.34 240 | 85.53 222 | 79.98 401 | 94.49 219 | 66.54 358 | 94.64 420 | 84.75 230 | 92.65 239 | 97.28 151 |
|
| v8 | | | 87.50 268 | 86.71 260 | 89.89 300 | 91.37 366 | 79.40 298 | 94.50 189 | 95.38 235 | 84.81 251 | 83.60 347 | 91.33 338 | 76.05 212 | 97.42 267 | 82.84 263 | 80.51 412 | 92.84 386 |
|
| v10 | | | 87.25 278 | 86.38 275 | 89.85 302 | 91.19 372 | 79.50 291 | 94.48 190 | 95.45 229 | 83.79 274 | 83.62 346 | 91.19 343 | 75.13 229 | 97.42 267 | 81.94 283 | 80.60 407 | 92.63 393 |
|
| baseline2 | | | 86.50 312 | 85.39 315 | 89.84 303 | 91.12 377 | 76.70 372 | 91.88 343 | 88.58 455 | 82.35 311 | 79.95 402 | 90.95 354 | 73.42 263 | 97.63 242 | 80.27 316 | 89.95 283 | 95.19 267 |
|
| pm-mvs1 | | | 86.61 306 | 85.54 311 | 89.82 304 | 91.44 361 | 80.18 262 | 95.28 133 | 94.85 277 | 83.84 271 | 81.66 376 | 92.62 292 | 72.45 278 | 96.48 354 | 79.67 326 | 78.06 427 | 92.82 387 |
|
| TR-MVS | | | 86.78 299 | 85.76 305 | 89.82 304 | 94.37 230 | 78.41 324 | 92.47 319 | 92.83 357 | 81.11 349 | 86.36 262 | 92.40 298 | 68.73 335 | 97.48 257 | 73.75 399 | 89.85 286 | 93.57 353 |
|
| ACMH+ | | 81.04 14 | 85.05 343 | 83.46 356 | 89.82 304 | 94.66 203 | 79.37 299 | 94.44 195 | 94.12 316 | 82.19 315 | 78.04 428 | 92.82 285 | 58.23 429 | 97.54 249 | 73.77 398 | 82.90 375 | 92.54 399 |
|
| EI-MVSNet | | | 89.10 210 | 88.86 202 | 89.80 307 | 91.84 348 | 78.30 329 | 93.70 262 | 95.01 258 | 85.73 213 | 87.15 242 | 95.28 175 | 79.87 155 | 97.21 295 | 83.81 248 | 87.36 328 | 93.88 332 |
|
| gbinet_0.2-2-1-0.02 | | | 82.59 378 | 80.19 390 | 89.77 308 | 85.23 468 | 80.05 271 | 91.59 354 | 93.52 339 | 77.60 396 | 79.78 406 | 82.87 468 | 63.26 387 | 96.45 358 | 78.93 343 | 68.97 463 | 92.81 388 |
|
| usedtu_blend_shiyan5 | | | 82.39 383 | 79.93 397 | 89.75 309 | 85.12 469 | 80.08 267 | 92.36 323 | 93.26 344 | 74.29 439 | 79.00 417 | 82.72 469 | 64.29 378 | 96.60 343 | 79.60 328 | 68.75 467 | 92.55 396 |
|
| v144192 | | | 87.19 284 | 86.35 277 | 89.74 310 | 90.64 400 | 78.24 331 | 93.92 245 | 95.43 232 | 81.93 323 | 85.51 286 | 91.05 352 | 74.21 247 | 97.45 262 | 82.86 262 | 81.56 391 | 93.53 354 |
|
| COLMAP_ROB |  | 80.39 16 | 83.96 363 | 82.04 372 | 89.74 310 | 95.28 158 | 79.75 286 | 94.25 215 | 92.28 373 | 75.17 429 | 78.02 429 | 93.77 254 | 58.60 428 | 97.84 226 | 65.06 453 | 85.92 338 | 91.63 422 |
| Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
| SCA | | | 86.32 318 | 85.18 322 | 89.73 312 | 92.15 335 | 76.60 373 | 91.12 369 | 91.69 391 | 83.53 281 | 85.50 287 | 88.81 409 | 66.79 351 | 96.48 354 | 76.65 366 | 90.35 275 | 96.12 229 |
|
| blend_shiyan4 | | | 81.94 386 | 79.35 405 | 89.70 313 | 85.52 464 | 80.08 267 | 91.29 363 | 93.82 327 | 77.12 405 | 79.31 413 | 82.94 467 | 54.81 449 | 96.60 343 | 79.60 328 | 69.78 458 | 92.41 405 |
|
| IterMVS-LS | | | 88.36 236 | 87.91 230 | 89.70 313 | 93.80 271 | 78.29 330 | 93.73 258 | 95.08 256 | 85.73 213 | 84.75 311 | 91.90 322 | 79.88 154 | 96.92 318 | 83.83 247 | 82.51 377 | 93.89 329 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
| blended_shiyan8 | | | 82.79 373 | 80.49 383 | 89.69 315 | 85.50 465 | 79.83 284 | 91.38 358 | 93.82 327 | 77.14 402 | 79.39 412 | 83.73 459 | 64.95 372 | 96.63 333 | 79.75 323 | 68.77 466 | 92.62 395 |
|
| testing11 | | | 86.44 315 | 85.35 318 | 89.69 315 | 94.29 241 | 75.40 391 | 91.30 362 | 90.53 424 | 84.76 252 | 85.06 305 | 90.13 382 | 58.95 427 | 97.45 262 | 82.08 279 | 91.09 264 | 96.21 224 |
|
| testing99 | | | 86.72 303 | 85.73 308 | 89.69 315 | 94.23 245 | 74.91 395 | 91.35 361 | 90.97 413 | 86.14 204 | 86.36 262 | 90.22 377 | 59.41 421 | 97.48 257 | 82.24 275 | 90.66 270 | 96.69 205 |
|
| v1921920 | | | 86.97 291 | 86.06 291 | 89.69 315 | 90.53 405 | 78.11 334 | 93.80 253 | 95.43 232 | 81.90 325 | 85.33 301 | 91.05 352 | 72.66 272 | 97.41 273 | 82.05 281 | 81.80 388 | 93.53 354 |
|
| icg_test_0407_2 | | | 89.15 208 | 88.97 195 | 89.68 319 | 93.72 275 | 77.75 350 | 88.26 433 | 95.34 240 | 85.53 222 | 88.34 219 | 94.49 219 | 77.69 194 | 93.99 433 | 84.75 230 | 92.65 239 | 97.28 151 |
|
| blended_shiyan6 | | | 82.78 374 | 80.48 384 | 89.67 320 | 85.53 463 | 79.76 285 | 91.37 359 | 93.82 327 | 77.14 402 | 79.30 414 | 83.73 459 | 64.96 371 | 96.63 333 | 79.68 325 | 68.75 467 | 92.63 393 |
|
| VortexMVS | | | 88.42 232 | 88.01 224 | 89.63 321 | 93.89 266 | 78.82 312 | 93.82 251 | 95.47 225 | 86.67 190 | 84.53 318 | 91.99 318 | 72.62 274 | 96.65 330 | 89.02 164 | 84.09 357 | 93.41 361 |
|
| Fast-Effi-MVS+-dtu | | | 87.44 269 | 86.72 259 | 89.63 321 | 92.04 340 | 77.68 355 | 94.03 234 | 93.94 319 | 85.81 210 | 82.42 366 | 91.32 340 | 70.33 306 | 97.06 307 | 80.33 315 | 90.23 277 | 94.14 316 |
|
| v1240 | | | 86.78 299 | 85.85 300 | 89.56 323 | 90.45 409 | 77.79 347 | 93.61 266 | 95.37 237 | 81.65 334 | 85.43 293 | 91.15 347 | 71.50 287 | 97.43 266 | 81.47 294 | 82.05 385 | 93.47 358 |
|
| Effi-MVS+-dtu | | | 88.65 226 | 88.35 214 | 89.54 324 | 93.33 292 | 76.39 377 | 94.47 193 | 94.36 303 | 87.70 155 | 85.43 293 | 89.56 398 | 73.45 261 | 97.26 290 | 85.57 218 | 91.28 259 | 94.97 274 |
|
| wanda-best-256-512 | | | 82.44 380 | 80.07 392 | 89.53 325 | 85.12 469 | 79.44 295 | 90.49 385 | 93.75 333 | 76.97 408 | 79.00 417 | 82.72 469 | 64.29 378 | 96.61 339 | 79.56 330 | 68.75 467 | 92.55 396 |
|
| FE-blended-shiyan7 | | | 82.44 380 | 80.07 392 | 89.53 325 | 85.12 469 | 79.44 295 | 90.49 385 | 93.75 333 | 76.97 408 | 79.00 417 | 82.72 469 | 64.29 378 | 96.61 339 | 79.56 330 | 68.75 467 | 92.55 396 |
|
| AllTest | | | 83.42 370 | 81.39 376 | 89.52 327 | 95.01 172 | 77.79 347 | 93.12 289 | 90.89 417 | 77.41 398 | 76.12 444 | 93.34 264 | 54.08 454 | 97.51 252 | 68.31 433 | 84.27 355 | 93.26 364 |
|
| TestCases | | | | | 89.52 327 | 95.01 172 | 77.79 347 | | 90.89 417 | 77.41 398 | 76.12 444 | 93.34 264 | 54.08 454 | 97.51 252 | 68.31 433 | 84.27 355 | 93.26 364 |
|
| mvs_anonymous | | | 89.37 205 | 89.32 184 | 89.51 329 | 93.47 288 | 74.22 402 | 91.65 352 | 94.83 279 | 82.91 300 | 85.45 290 | 93.79 252 | 81.23 135 | 96.36 365 | 86.47 204 | 94.09 192 | 97.94 98 |
|
| XVG-ACMP-BASELINE | | | 86.00 321 | 84.84 331 | 89.45 330 | 91.20 371 | 78.00 336 | 91.70 350 | 95.55 219 | 85.05 243 | 82.97 360 | 92.25 305 | 54.49 452 | 97.48 257 | 82.93 260 | 87.45 327 | 92.89 384 |
|
| testing222 | | | 84.84 349 | 83.32 357 | 89.43 331 | 94.15 252 | 75.94 382 | 91.09 370 | 89.41 452 | 84.90 246 | 85.78 276 | 89.44 399 | 52.70 459 | 96.28 369 | 70.80 417 | 91.57 256 | 96.07 233 |
|
| MVP-Stereo | | | 85.97 322 | 84.86 330 | 89.32 332 | 90.92 388 | 82.19 186 | 92.11 338 | 94.19 310 | 78.76 380 | 78.77 424 | 91.63 331 | 68.38 339 | 96.56 348 | 75.01 385 | 93.95 195 | 89.20 462 |
| Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
| PatchmatchNet |  | | 85.85 325 | 84.70 333 | 89.29 333 | 91.76 352 | 75.54 388 | 88.49 429 | 91.30 404 | 81.63 336 | 85.05 306 | 88.70 413 | 71.71 284 | 96.24 370 | 74.61 391 | 89.05 301 | 96.08 232 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
| v148 | | | 87.04 289 | 86.32 279 | 89.21 334 | 90.94 386 | 77.26 361 | 93.71 261 | 94.43 298 | 84.84 250 | 84.36 326 | 90.80 360 | 76.04 213 | 97.05 309 | 82.12 277 | 79.60 421 | 93.31 363 |
|
| tfpnnormal | | | 84.72 351 | 83.23 360 | 89.20 335 | 92.79 319 | 80.05 271 | 94.48 190 | 95.81 194 | 82.38 309 | 81.08 384 | 91.21 342 | 69.01 331 | 96.95 316 | 61.69 464 | 80.59 408 | 90.58 448 |
|
| cl22 | | | 86.78 299 | 85.98 294 | 89.18 336 | 92.34 331 | 77.62 356 | 90.84 377 | 94.13 315 | 81.33 343 | 83.97 337 | 90.15 381 | 73.96 252 | 96.60 343 | 84.19 241 | 82.94 372 | 93.33 362 |
|
| BH-w/o | | | 87.57 264 | 87.05 249 | 89.12 337 | 94.90 184 | 77.90 341 | 92.41 320 | 93.51 340 | 82.89 301 | 83.70 343 | 91.34 337 | 75.75 222 | 97.07 306 | 75.49 378 | 93.49 213 | 92.39 407 |
|
| WR-MVS_H | | | 87.80 250 | 87.37 241 | 89.10 338 | 93.23 294 | 78.12 333 | 95.61 115 | 97.30 37 | 87.90 145 | 83.72 342 | 92.01 317 | 79.65 164 | 96.01 380 | 76.36 370 | 80.54 409 | 93.16 372 |
|
| miper_enhance_ethall | | | 86.90 293 | 86.18 284 | 89.06 339 | 91.66 357 | 77.58 357 | 90.22 395 | 94.82 280 | 79.16 371 | 84.48 319 | 89.10 403 | 79.19 169 | 96.66 329 | 84.06 243 | 82.94 372 | 92.94 382 |
|
| c3_l | | | 87.14 286 | 86.50 273 | 89.04 340 | 92.20 334 | 77.26 361 | 91.22 368 | 94.70 287 | 82.01 321 | 84.34 327 | 90.43 371 | 78.81 173 | 96.61 339 | 83.70 252 | 81.09 398 | 93.25 366 |
|
| miper_ehance_all_eth | | | 87.22 281 | 86.62 267 | 89.02 341 | 92.13 337 | 77.40 359 | 90.91 376 | 94.81 281 | 81.28 344 | 84.32 328 | 90.08 384 | 79.26 167 | 96.62 336 | 83.81 248 | 82.94 372 | 93.04 379 |
|
| gg-mvs-nofinetune | | | 81.77 390 | 79.37 404 | 88.99 342 | 90.85 392 | 77.73 354 | 86.29 458 | 79.63 488 | 74.88 434 | 83.19 359 | 69.05 496 | 60.34 413 | 96.11 375 | 75.46 379 | 94.64 175 | 93.11 376 |
|
| ETVMVS | | | 84.43 356 | 82.92 366 | 88.97 343 | 94.37 230 | 74.67 396 | 91.23 367 | 88.35 457 | 83.37 286 | 86.06 271 | 89.04 404 | 55.38 443 | 95.67 398 | 67.12 440 | 91.34 258 | 96.58 209 |
|
| pmmvs6 | | | 83.42 370 | 81.60 374 | 88.87 344 | 88.01 443 | 77.87 343 | 94.96 157 | 94.24 309 | 74.67 435 | 78.80 423 | 91.09 350 | 60.17 415 | 96.49 353 | 77.06 365 | 75.40 441 | 92.23 412 |
|
| test_cas_vis1_n_1920 | | | 88.83 223 | 88.85 203 | 88.78 345 | 91.15 376 | 76.72 371 | 93.85 250 | 94.93 271 | 83.23 291 | 92.81 99 | 96.00 128 | 61.17 409 | 94.45 421 | 91.67 115 | 94.84 167 | 95.17 268 |
|
| MIMVSNet | | | 82.59 378 | 80.53 381 | 88.76 346 | 91.51 359 | 78.32 328 | 86.57 457 | 90.13 432 | 79.32 367 | 80.70 389 | 88.69 414 | 52.98 458 | 93.07 449 | 66.03 448 | 88.86 303 | 94.90 282 |
|
| cl____ | | | 86.52 311 | 85.78 302 | 88.75 347 | 92.03 341 | 76.46 375 | 90.74 378 | 94.30 305 | 81.83 330 | 83.34 355 | 90.78 361 | 75.74 224 | 96.57 346 | 81.74 289 | 81.54 392 | 93.22 368 |
|
| DIV-MVS_self_test | | | 86.53 310 | 85.78 302 | 88.75 347 | 92.02 342 | 76.45 376 | 90.74 378 | 94.30 305 | 81.83 330 | 83.34 355 | 90.82 359 | 75.75 222 | 96.57 346 | 81.73 290 | 81.52 393 | 93.24 367 |
|
| CP-MVSNet | | | 87.63 258 | 87.26 246 | 88.74 349 | 93.12 299 | 76.59 374 | 95.29 131 | 96.58 111 | 88.43 118 | 83.49 352 | 92.98 280 | 75.28 228 | 95.83 389 | 78.97 342 | 81.15 397 | 93.79 339 |
|
| eth_miper_zixun_eth | | | 86.50 312 | 85.77 304 | 88.68 350 | 91.94 343 | 75.81 385 | 90.47 387 | 94.89 273 | 82.05 318 | 84.05 334 | 90.46 370 | 75.96 216 | 96.77 323 | 82.76 266 | 79.36 423 | 93.46 359 |
|
| CHOSEN 280x420 | | | 85.15 341 | 83.99 349 | 88.65 351 | 92.47 327 | 78.40 325 | 79.68 490 | 92.76 360 | 74.90 433 | 81.41 380 | 89.59 396 | 69.85 314 | 95.51 403 | 79.92 322 | 95.29 158 | 92.03 415 |
|
| PS-CasMVS | | | 87.32 275 | 86.88 252 | 88.63 352 | 92.99 309 | 76.33 379 | 95.33 126 | 96.61 109 | 88.22 126 | 83.30 357 | 93.07 278 | 73.03 269 | 95.79 393 | 78.36 348 | 81.00 403 | 93.75 346 |
|
| TransMVSNet (Re) | | | 84.43 356 | 83.06 364 | 88.54 353 | 91.72 353 | 78.44 323 | 95.18 144 | 92.82 359 | 82.73 304 | 79.67 408 | 92.12 309 | 73.49 260 | 95.96 382 | 71.10 415 | 68.73 471 | 91.21 435 |
|
| tt0320-xc | | | 79.63 422 | 76.66 431 | 88.52 354 | 91.03 380 | 78.72 313 | 93.00 298 | 89.53 450 | 66.37 476 | 76.11 446 | 87.11 437 | 46.36 477 | 95.32 411 | 72.78 403 | 67.67 472 | 91.51 427 |
|
| EG-PatchMatch MVS | | | 82.37 384 | 80.34 386 | 88.46 355 | 90.27 411 | 79.35 300 | 92.80 310 | 94.33 304 | 77.14 402 | 73.26 463 | 90.18 380 | 47.47 472 | 96.72 325 | 70.25 419 | 87.32 330 | 89.30 459 |
|
| PEN-MVS | | | 86.80 298 | 86.27 282 | 88.40 356 | 92.32 332 | 75.71 387 | 95.18 144 | 96.38 126 | 87.97 139 | 82.82 362 | 93.15 274 | 73.39 264 | 95.92 384 | 76.15 374 | 79.03 426 | 93.59 352 |
|
| Baseline_NR-MVSNet | | | 87.07 288 | 86.63 266 | 88.40 356 | 91.44 361 | 77.87 343 | 94.23 218 | 92.57 365 | 84.12 265 | 85.74 278 | 92.08 313 | 77.25 198 | 96.04 376 | 82.29 274 | 79.94 416 | 91.30 433 |
|
| UBG | | | 85.51 331 | 84.57 338 | 88.35 358 | 94.21 247 | 71.78 434 | 90.07 400 | 89.66 445 | 82.28 313 | 85.91 274 | 89.01 405 | 61.30 403 | 97.06 307 | 76.58 369 | 92.06 252 | 96.22 222 |
|
| D2MVS | | | 85.90 323 | 85.09 324 | 88.35 358 | 90.79 393 | 77.42 358 | 91.83 346 | 95.70 206 | 80.77 352 | 80.08 399 | 90.02 386 | 66.74 353 | 96.37 363 | 81.88 285 | 87.97 318 | 91.26 434 |
|
| pmmvs5 | | | 84.21 359 | 82.84 369 | 88.34 360 | 88.95 430 | 76.94 367 | 92.41 320 | 91.91 388 | 75.63 424 | 80.28 394 | 91.18 345 | 64.59 375 | 95.57 400 | 77.09 364 | 83.47 366 | 92.53 400 |
|
| tt0320 | | | 80.13 415 | 77.41 424 | 88.29 361 | 90.50 406 | 78.02 335 | 93.10 292 | 90.71 422 | 66.06 479 | 76.75 439 | 86.97 438 | 49.56 467 | 95.40 408 | 71.65 407 | 71.41 454 | 91.46 430 |
|
| LCM-MVSNet-Re | | | 88.30 238 | 88.32 217 | 88.27 362 | 94.71 199 | 72.41 429 | 93.15 288 | 90.98 412 | 87.77 152 | 79.25 415 | 91.96 319 | 78.35 184 | 95.75 394 | 83.04 258 | 95.62 147 | 96.65 206 |
|
| CostFormer | | | 85.77 328 | 84.94 328 | 88.26 363 | 91.16 375 | 72.58 427 | 89.47 413 | 91.04 411 | 76.26 418 | 86.45 260 | 89.97 388 | 70.74 297 | 96.86 322 | 82.35 272 | 87.07 333 | 95.34 264 |
|
| ITE_SJBPF | | | | | 88.24 364 | 91.88 347 | 77.05 364 | | 92.92 354 | 85.54 220 | 80.13 398 | 93.30 268 | 57.29 434 | 96.20 371 | 72.46 405 | 84.71 351 | 91.49 428 |
|
| PVSNet | | 78.82 18 | 85.55 330 | 84.65 334 | 88.23 365 | 94.72 197 | 71.93 430 | 87.12 451 | 92.75 361 | 78.80 379 | 84.95 308 | 90.53 368 | 64.43 376 | 96.71 327 | 74.74 388 | 93.86 197 | 96.06 235 |
|
| IterMVS-SCA-FT | | | 85.45 332 | 84.53 339 | 88.18 366 | 91.71 354 | 76.87 368 | 90.19 397 | 92.65 364 | 85.40 229 | 81.44 379 | 90.54 367 | 66.79 351 | 95.00 417 | 81.04 299 | 81.05 399 | 92.66 392 |
|
| EPNet_dtu | | | 86.49 314 | 85.94 297 | 88.14 367 | 90.24 412 | 72.82 419 | 94.11 224 | 92.20 376 | 86.66 191 | 79.42 411 | 92.36 300 | 73.52 259 | 95.81 391 | 71.26 410 | 93.66 206 | 95.80 247 |
| Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
| Patchmtry | | | 82.71 376 | 80.93 380 | 88.06 368 | 90.05 416 | 76.37 378 | 84.74 471 | 91.96 386 | 72.28 459 | 81.32 382 | 87.87 426 | 71.03 292 | 95.50 405 | 68.97 428 | 80.15 414 | 92.32 410 |
|
| test_vis1_n_1920 | | | 89.39 204 | 89.84 166 | 88.04 369 | 92.97 310 | 72.64 424 | 94.71 178 | 96.03 174 | 86.18 202 | 91.94 128 | 96.56 99 | 61.63 398 | 95.74 395 | 93.42 65 | 95.11 162 | 95.74 249 |
|
| DTE-MVSNet | | | 86.11 320 | 85.48 313 | 87.98 370 | 91.65 358 | 74.92 394 | 94.93 159 | 95.75 199 | 87.36 167 | 82.26 368 | 93.04 279 | 72.85 270 | 95.82 390 | 74.04 394 | 77.46 432 | 93.20 370 |
|
| PMMVS | | | 85.71 329 | 84.96 327 | 87.95 371 | 88.90 431 | 77.09 363 | 88.68 425 | 90.06 434 | 72.32 458 | 86.47 257 | 90.76 362 | 72.15 280 | 94.40 424 | 81.78 288 | 93.49 213 | 92.36 408 |
|
| GG-mvs-BLEND | | | | | 87.94 372 | 89.73 423 | 77.91 339 | 87.80 439 | 78.23 493 | | 80.58 391 | 83.86 457 | 59.88 417 | 95.33 410 | 71.20 411 | 92.22 250 | 90.60 447 |
|
| MonoMVSNet | | | 86.89 294 | 86.55 270 | 87.92 373 | 89.46 426 | 73.75 406 | 94.12 222 | 93.10 349 | 87.82 151 | 85.10 304 | 90.76 362 | 69.59 317 | 94.94 418 | 86.47 204 | 82.50 378 | 95.07 271 |
|
| reproduce_monomvs | | | 86.37 317 | 85.87 299 | 87.87 374 | 93.66 283 | 73.71 407 | 93.44 273 | 95.02 257 | 88.61 113 | 82.64 365 | 91.94 320 | 57.88 431 | 96.68 328 | 89.96 145 | 79.71 420 | 93.22 368 |
|
| pmmvs-eth3d | | | 80.97 406 | 78.72 416 | 87.74 375 | 84.99 472 | 79.97 278 | 90.11 399 | 91.65 393 | 75.36 426 | 73.51 461 | 86.03 446 | 59.45 420 | 93.96 436 | 75.17 382 | 72.21 447 | 89.29 461 |
|
| MS-PatchMatch | | | 85.05 343 | 84.16 344 | 87.73 376 | 91.42 364 | 78.51 321 | 91.25 366 | 93.53 338 | 77.50 397 | 80.15 396 | 91.58 334 | 61.99 395 | 95.51 403 | 75.69 377 | 94.35 184 | 89.16 463 |
|
| mmtdpeth | | | 85.04 345 | 84.15 345 | 87.72 377 | 93.11 300 | 75.74 386 | 94.37 208 | 92.83 357 | 84.98 244 | 89.31 199 | 86.41 443 | 61.61 400 | 97.14 300 | 92.63 81 | 62.11 483 | 90.29 449 |
|
| test_0402 | | | 81.30 402 | 79.17 410 | 87.67 378 | 93.19 295 | 78.17 332 | 92.98 300 | 91.71 389 | 75.25 428 | 76.02 447 | 90.31 375 | 59.23 422 | 96.37 363 | 50.22 486 | 83.63 364 | 88.47 471 |
|
| IterMVS | | | 84.88 347 | 83.98 350 | 87.60 379 | 91.44 361 | 76.03 381 | 90.18 398 | 92.41 367 | 83.24 290 | 81.06 385 | 90.42 372 | 66.60 354 | 94.28 428 | 79.46 334 | 80.98 404 | 92.48 401 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
| Patchmatch-test | | | 81.37 400 | 79.30 406 | 87.58 380 | 90.92 388 | 74.16 404 | 80.99 483 | 87.68 462 | 70.52 466 | 76.63 441 | 88.81 409 | 71.21 289 | 92.76 453 | 60.01 471 | 86.93 334 | 95.83 245 |
|
| EPMVS | | | 83.90 366 | 82.70 370 | 87.51 381 | 90.23 413 | 72.67 422 | 88.62 426 | 81.96 483 | 81.37 342 | 85.01 307 | 88.34 417 | 66.31 359 | 94.45 421 | 75.30 381 | 87.12 331 | 95.43 259 |
|
| ADS-MVSNet2 | | | 81.66 393 | 79.71 401 | 87.50 382 | 91.35 367 | 74.19 403 | 83.33 476 | 88.48 456 | 72.90 453 | 82.24 369 | 85.77 449 | 64.98 369 | 93.20 447 | 64.57 455 | 83.74 361 | 95.12 269 |
|
| OurMVSNet-221017-0 | | | 85.35 336 | 84.64 336 | 87.49 383 | 90.77 395 | 72.59 426 | 94.01 237 | 94.40 301 | 84.72 254 | 79.62 410 | 93.17 273 | 61.91 396 | 96.72 325 | 81.99 282 | 81.16 395 | 93.16 372 |
|
| tpm2 | | | 84.08 361 | 82.94 365 | 87.48 384 | 91.39 365 | 71.27 439 | 89.23 417 | 90.37 426 | 71.95 460 | 84.64 313 | 89.33 400 | 67.30 343 | 96.55 350 | 75.17 382 | 87.09 332 | 94.63 290 |
|
| RPSCF | | | 85.07 342 | 84.27 341 | 87.48 384 | 92.91 313 | 70.62 448 | 91.69 351 | 92.46 366 | 76.20 420 | 82.67 364 | 95.22 178 | 63.94 382 | 97.29 287 | 77.51 359 | 85.80 339 | 94.53 297 |
|
| myMVS_eth3d28 | | | 85.80 327 | 85.26 321 | 87.42 386 | 94.73 195 | 69.92 454 | 90.60 382 | 90.95 414 | 87.21 171 | 86.06 271 | 90.04 385 | 59.47 419 | 96.02 378 | 74.89 387 | 93.35 221 | 96.33 216 |
|
| FE-MVSNET2 | | | 81.82 389 | 79.99 395 | 87.34 387 | 84.74 473 | 77.36 360 | 92.72 311 | 94.55 292 | 82.09 316 | 73.79 460 | 86.46 440 | 57.80 432 | 94.45 421 | 74.65 389 | 73.10 443 | 90.20 450 |
|
| WBMVS | | | 84.97 346 | 84.18 343 | 87.34 387 | 94.14 253 | 71.62 438 | 90.20 396 | 92.35 369 | 81.61 337 | 84.06 333 | 90.76 362 | 61.82 397 | 96.52 351 | 78.93 343 | 83.81 359 | 93.89 329 |
|
| miper_lstm_enhance | | | 85.27 339 | 84.59 337 | 87.31 389 | 91.28 370 | 74.63 397 | 87.69 444 | 94.09 317 | 81.20 348 | 81.36 381 | 89.85 392 | 74.97 233 | 94.30 427 | 81.03 301 | 79.84 419 | 93.01 380 |
|
| FMVSNet5 | | | 81.52 398 | 79.60 402 | 87.27 390 | 91.17 373 | 77.95 337 | 91.49 356 | 92.26 375 | 76.87 410 | 76.16 443 | 87.91 425 | 51.67 461 | 92.34 456 | 67.74 437 | 81.16 395 | 91.52 426 |
|
| USDC | | | 82.76 375 | 81.26 378 | 87.26 391 | 91.17 373 | 74.55 398 | 89.27 415 | 93.39 342 | 78.26 390 | 75.30 451 | 92.08 313 | 54.43 453 | 96.63 333 | 71.64 408 | 85.79 340 | 90.61 445 |
|
| test-LLR | | | 85.87 324 | 85.41 314 | 87.25 392 | 90.95 384 | 71.67 436 | 89.55 409 | 89.88 441 | 83.41 284 | 84.54 316 | 87.95 423 | 67.25 344 | 95.11 414 | 81.82 286 | 93.37 219 | 94.97 274 |
|
| test-mter | | | 84.54 355 | 83.64 354 | 87.25 392 | 90.95 384 | 71.67 436 | 89.55 409 | 89.88 441 | 79.17 370 | 84.54 316 | 87.95 423 | 55.56 440 | 95.11 414 | 81.82 286 | 93.37 219 | 94.97 274 |
|
| JIA-IIPM | | | 81.04 403 | 78.98 414 | 87.25 392 | 88.64 432 | 73.48 411 | 81.75 482 | 89.61 447 | 73.19 450 | 82.05 372 | 73.71 490 | 66.07 364 | 95.87 387 | 71.18 413 | 84.60 352 | 92.41 405 |
|
| TDRefinement | | | 79.81 419 | 77.34 425 | 87.22 395 | 79.24 489 | 75.48 389 | 93.12 289 | 92.03 381 | 76.45 413 | 75.01 452 | 91.58 334 | 49.19 468 | 96.44 359 | 70.22 421 | 69.18 462 | 89.75 455 |
|
| tpmvs | | | 83.35 372 | 82.07 371 | 87.20 396 | 91.07 379 | 71.00 445 | 88.31 432 | 91.70 390 | 78.91 373 | 80.49 393 | 87.18 435 | 69.30 325 | 97.08 304 | 68.12 436 | 83.56 365 | 93.51 357 |
|
| ppachtmachnet_test | | | 81.84 388 | 80.07 392 | 87.15 397 | 88.46 436 | 74.43 401 | 89.04 421 | 92.16 377 | 75.33 427 | 77.75 432 | 88.99 406 | 66.20 361 | 95.37 409 | 65.12 452 | 77.60 430 | 91.65 421 |
|
| dmvs_re | | | 84.20 360 | 83.22 361 | 87.14 398 | 91.83 350 | 77.81 345 | 90.04 401 | 90.19 430 | 84.70 256 | 81.49 377 | 89.17 402 | 64.37 377 | 91.13 469 | 71.58 409 | 85.65 341 | 92.46 403 |
|
| tpm cat1 | | | 81.96 385 | 80.27 387 | 87.01 399 | 91.09 378 | 71.02 444 | 87.38 449 | 91.53 398 | 66.25 477 | 80.17 395 | 86.35 445 | 68.22 340 | 96.15 374 | 69.16 427 | 82.29 381 | 93.86 335 |
|
| test_fmvs1_n | | | 87.03 290 | 87.04 250 | 86.97 400 | 89.74 422 | 71.86 431 | 94.55 186 | 94.43 298 | 78.47 384 | 91.95 127 | 95.50 164 | 51.16 463 | 93.81 437 | 93.02 73 | 94.56 177 | 95.26 265 |
|
| OpenMVS_ROB |  | 74.94 19 | 79.51 423 | 77.03 430 | 86.93 401 | 87.00 450 | 76.23 380 | 92.33 327 | 90.74 421 | 68.93 470 | 74.52 456 | 88.23 420 | 49.58 466 | 96.62 336 | 57.64 477 | 84.29 354 | 87.94 474 |
|
| SixPastTwentyTwo | | | 83.91 365 | 82.90 367 | 86.92 402 | 90.99 382 | 70.67 447 | 93.48 270 | 91.99 383 | 85.54 220 | 77.62 434 | 92.11 311 | 60.59 412 | 96.87 321 | 76.05 375 | 77.75 429 | 93.20 370 |
|
| ADS-MVSNet | | | 81.56 395 | 79.78 398 | 86.90 403 | 91.35 367 | 71.82 432 | 83.33 476 | 89.16 454 | 72.90 453 | 82.24 369 | 85.77 449 | 64.98 369 | 93.76 438 | 64.57 455 | 83.74 361 | 95.12 269 |
|
| PatchT | | | 82.68 377 | 81.27 377 | 86.89 404 | 90.09 415 | 70.94 446 | 84.06 473 | 90.15 431 | 74.91 432 | 85.63 281 | 83.57 461 | 69.37 321 | 94.87 419 | 65.19 450 | 88.50 308 | 94.84 284 |
|
| tpm | | | 84.73 350 | 84.02 348 | 86.87 405 | 90.33 410 | 68.90 457 | 89.06 420 | 89.94 438 | 80.85 351 | 85.75 277 | 89.86 391 | 68.54 337 | 95.97 381 | 77.76 355 | 84.05 358 | 95.75 248 |
|
| Patchmatch-RL test | | | 81.67 392 | 79.96 396 | 86.81 406 | 85.42 466 | 71.23 440 | 82.17 481 | 87.50 463 | 78.47 384 | 77.19 436 | 82.50 473 | 70.81 296 | 93.48 442 | 82.66 267 | 72.89 446 | 95.71 252 |
|
| test_vis1_n | | | 86.56 309 | 86.49 274 | 86.78 407 | 88.51 433 | 72.69 421 | 94.68 179 | 93.78 332 | 79.55 366 | 90.70 165 | 95.31 174 | 48.75 469 | 93.28 445 | 93.15 69 | 93.99 194 | 94.38 308 |
|
| testing3-2 | | | 86.72 303 | 86.71 260 | 86.74 408 | 96.11 114 | 65.92 469 | 93.39 275 | 89.65 446 | 89.46 75 | 87.84 229 | 92.79 288 | 59.17 424 | 97.60 244 | 81.31 295 | 90.72 269 | 96.70 204 |
|
| test_fmvs1 | | | 87.34 273 | 87.56 236 | 86.68 409 | 90.59 401 | 71.80 433 | 94.01 237 | 94.04 318 | 78.30 388 | 91.97 125 | 95.22 178 | 56.28 438 | 93.71 439 | 92.89 74 | 94.71 170 | 94.52 298 |
|
| MDA-MVSNet-bldmvs | | | 78.85 428 | 76.31 433 | 86.46 410 | 89.76 421 | 73.88 405 | 88.79 423 | 90.42 425 | 79.16 371 | 59.18 487 | 88.33 418 | 60.20 414 | 94.04 431 | 62.00 463 | 68.96 464 | 91.48 429 |
|
| mvs5depth | | | 80.98 405 | 79.15 411 | 86.45 411 | 84.57 474 | 73.29 414 | 87.79 440 | 91.67 392 | 80.52 354 | 82.20 371 | 89.72 394 | 55.14 446 | 95.93 383 | 73.93 397 | 66.83 474 | 90.12 452 |
|
| tpmrst | | | 85.35 336 | 84.99 325 | 86.43 412 | 90.88 391 | 67.88 462 | 88.71 424 | 91.43 402 | 80.13 358 | 86.08 270 | 88.80 411 | 73.05 268 | 96.02 378 | 82.48 268 | 83.40 369 | 95.40 260 |
|
| TESTMET0.1,1 | | | 83.74 368 | 82.85 368 | 86.42 413 | 89.96 418 | 71.21 441 | 89.55 409 | 87.88 459 | 77.41 398 | 83.37 354 | 87.31 431 | 56.71 436 | 93.65 441 | 80.62 309 | 92.85 236 | 94.40 307 |
|
| our_test_3 | | | 81.93 387 | 80.46 385 | 86.33 414 | 88.46 436 | 73.48 411 | 88.46 430 | 91.11 407 | 76.46 412 | 76.69 440 | 88.25 419 | 66.89 349 | 94.36 425 | 68.75 429 | 79.08 425 | 91.14 437 |
|
| lessismore_v0 | | | | | 86.04 415 | 88.46 436 | 68.78 458 | | 80.59 486 | | 73.01 464 | 90.11 383 | 55.39 442 | 96.43 360 | 75.06 384 | 65.06 478 | 92.90 383 |
|
| TinyColmap | | | 79.76 420 | 77.69 422 | 85.97 416 | 91.71 354 | 73.12 415 | 89.55 409 | 90.36 427 | 75.03 430 | 72.03 467 | 90.19 379 | 46.22 478 | 96.19 373 | 63.11 459 | 81.03 400 | 88.59 470 |
|
| KD-MVS_2432*1600 | | | 78.50 429 | 76.02 437 | 85.93 417 | 86.22 455 | 74.47 399 | 84.80 469 | 92.33 370 | 79.29 368 | 76.98 437 | 85.92 447 | 53.81 456 | 93.97 434 | 67.39 438 | 57.42 488 | 89.36 457 |
|
| miper_refine_blended | | | 78.50 429 | 76.02 437 | 85.93 417 | 86.22 455 | 74.47 399 | 84.80 469 | 92.33 370 | 79.29 368 | 76.98 437 | 85.92 447 | 53.81 456 | 93.97 434 | 67.39 438 | 57.42 488 | 89.36 457 |
|
| K. test v3 | | | 81.59 394 | 80.15 391 | 85.91 419 | 89.89 420 | 69.42 456 | 92.57 316 | 87.71 461 | 85.56 219 | 73.44 462 | 89.71 395 | 55.58 439 | 95.52 402 | 77.17 362 | 69.76 459 | 92.78 389 |
|
| SSC-MVS3.2 | | | 84.60 354 | 84.19 342 | 85.85 420 | 92.74 321 | 68.07 459 | 88.15 435 | 93.81 330 | 87.42 165 | 83.76 341 | 91.07 351 | 62.91 390 | 95.73 396 | 74.56 392 | 83.24 370 | 93.75 346 |
|
| mvsany_test1 | | | 85.42 334 | 85.30 319 | 85.77 421 | 87.95 445 | 75.41 390 | 87.61 447 | 80.97 485 | 76.82 411 | 88.68 212 | 95.83 144 | 77.44 197 | 90.82 471 | 85.90 213 | 86.51 335 | 91.08 441 |
|
| MIMVSNet1 | | | 79.38 424 | 77.28 426 | 85.69 422 | 86.35 454 | 73.67 408 | 91.61 353 | 92.75 361 | 78.11 393 | 72.64 465 | 88.12 421 | 48.16 470 | 91.97 462 | 60.32 468 | 77.49 431 | 91.43 431 |
|
| UWE-MVS | | | 83.69 369 | 83.09 362 | 85.48 423 | 93.06 304 | 65.27 474 | 90.92 375 | 86.14 467 | 79.90 361 | 86.26 266 | 90.72 365 | 57.17 435 | 95.81 391 | 71.03 416 | 92.62 244 | 95.35 263 |
|
| UnsupCasMVSNet_eth | | | 80.07 416 | 78.27 420 | 85.46 424 | 85.24 467 | 72.63 425 | 88.45 431 | 94.87 276 | 82.99 298 | 71.64 470 | 88.07 422 | 56.34 437 | 91.75 464 | 73.48 400 | 63.36 481 | 92.01 416 |
|
| CL-MVSNet_self_test | | | 81.74 391 | 80.53 381 | 85.36 425 | 85.96 458 | 72.45 428 | 90.25 391 | 93.07 351 | 81.24 346 | 79.85 405 | 87.29 432 | 70.93 294 | 92.52 454 | 66.95 441 | 69.23 461 | 91.11 439 |
|
| MDA-MVSNet_test_wron | | | 79.21 426 | 77.19 428 | 85.29 426 | 88.22 440 | 72.77 420 | 85.87 460 | 90.06 434 | 74.34 437 | 62.62 484 | 87.56 429 | 66.14 362 | 91.99 461 | 66.90 445 | 73.01 444 | 91.10 440 |
|
| YYNet1 | | | 79.22 425 | 77.20 427 | 85.28 427 | 88.20 441 | 72.66 423 | 85.87 460 | 90.05 436 | 74.33 438 | 62.70 482 | 87.61 428 | 66.09 363 | 92.03 458 | 66.94 442 | 72.97 445 | 91.15 436 |
|
| WB-MVSnew | | | 83.77 367 | 83.28 358 | 85.26 428 | 91.48 360 | 71.03 443 | 91.89 342 | 87.98 458 | 78.91 373 | 84.78 310 | 90.22 377 | 69.11 330 | 94.02 432 | 64.70 454 | 90.44 272 | 90.71 443 |
|
| dp | | | 81.47 399 | 80.23 388 | 85.17 429 | 89.92 419 | 65.49 472 | 86.74 455 | 90.10 433 | 76.30 417 | 81.10 383 | 87.12 436 | 62.81 391 | 95.92 384 | 68.13 435 | 79.88 417 | 94.09 320 |
|
| UnsupCasMVSNet_bld | | | 76.23 439 | 73.27 443 | 85.09 430 | 83.79 476 | 72.92 417 | 85.65 463 | 93.47 341 | 71.52 461 | 68.84 476 | 79.08 479 | 49.77 465 | 93.21 446 | 66.81 446 | 60.52 485 | 89.13 465 |
|
| usedtu_dtu_shiyan2 | | | 74.72 441 | 71.30 446 | 84.98 431 | 77.78 491 | 70.58 449 | 91.85 345 | 90.76 420 | 67.24 475 | 68.06 478 | 82.17 474 | 37.13 487 | 92.78 452 | 60.69 467 | 66.03 475 | 91.59 425 |
|
| SD_0403 | | | 84.71 352 | 84.65 334 | 84.92 432 | 92.95 311 | 65.95 468 | 92.07 341 | 93.23 346 | 83.82 273 | 79.03 416 | 93.73 257 | 73.90 253 | 92.91 451 | 63.02 461 | 90.05 279 | 95.89 241 |
|
| Anonymous20231206 | | | 81.03 404 | 79.77 400 | 84.82 433 | 87.85 446 | 70.26 451 | 91.42 357 | 92.08 379 | 73.67 445 | 77.75 432 | 89.25 401 | 62.43 393 | 93.08 448 | 61.50 465 | 82.00 386 | 91.12 438 |
|
| FE-MVSNET | | | 78.19 431 | 76.03 436 | 84.69 434 | 83.70 477 | 73.31 413 | 90.58 383 | 90.00 437 | 77.11 406 | 71.91 468 | 85.47 451 | 55.53 441 | 91.94 463 | 59.69 472 | 70.24 456 | 88.83 467 |
|
| test0.0.03 1 | | | 82.41 382 | 81.69 373 | 84.59 435 | 88.23 439 | 72.89 418 | 90.24 393 | 87.83 460 | 83.41 284 | 79.86 404 | 89.78 393 | 67.25 344 | 88.99 481 | 65.18 451 | 83.42 368 | 91.90 418 |
|
| CMPMVS |  | 59.16 21 | 80.52 410 | 79.20 409 | 84.48 436 | 83.98 475 | 67.63 465 | 89.95 404 | 93.84 326 | 64.79 481 | 66.81 479 | 91.14 348 | 57.93 430 | 95.17 412 | 76.25 372 | 88.10 314 | 90.65 444 |
| M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
| CVMVSNet | | | 84.69 353 | 84.79 332 | 84.37 437 | 91.84 348 | 64.92 475 | 93.70 262 | 91.47 401 | 66.19 478 | 86.16 269 | 95.28 175 | 67.18 346 | 93.33 444 | 80.89 304 | 90.42 274 | 94.88 283 |
|
| PVSNet_0 | | 73.20 20 | 77.22 435 | 74.83 441 | 84.37 437 | 90.70 399 | 71.10 442 | 83.09 478 | 89.67 444 | 72.81 455 | 73.93 459 | 83.13 463 | 60.79 411 | 93.70 440 | 68.54 430 | 50.84 493 | 88.30 472 |
|
| LF4IMVS | | | 80.37 413 | 79.07 413 | 84.27 439 | 86.64 451 | 69.87 455 | 89.39 414 | 91.05 410 | 76.38 415 | 74.97 453 | 90.00 387 | 47.85 471 | 94.25 429 | 74.55 393 | 80.82 406 | 88.69 469 |
|
| Anonymous20240521 | | | 80.44 412 | 79.21 408 | 84.11 440 | 85.75 461 | 67.89 461 | 92.86 306 | 93.23 346 | 75.61 425 | 75.59 450 | 87.47 430 | 50.03 464 | 94.33 426 | 71.14 414 | 81.21 394 | 90.12 452 |
|
| PM-MVS | | | 78.11 432 | 76.12 435 | 84.09 441 | 83.54 478 | 70.08 452 | 88.97 422 | 85.27 474 | 79.93 360 | 74.73 455 | 86.43 442 | 34.70 490 | 93.48 442 | 79.43 337 | 72.06 449 | 88.72 468 |
|
| dtuonly | | | 84.33 358 | 84.48 340 | 83.87 442 | 86.63 452 | 63.54 480 | 86.79 453 | 91.48 400 | 78.02 394 | 83.20 358 | 93.56 260 | 69.53 319 | 94.11 430 | 79.08 341 | 92.02 253 | 93.97 327 |
|
| test_fmvs2 | | | 83.98 362 | 84.03 347 | 83.83 443 | 87.16 449 | 67.53 466 | 93.93 244 | 92.89 355 | 77.62 395 | 86.89 250 | 93.53 261 | 47.18 473 | 92.02 460 | 90.54 134 | 86.51 335 | 91.93 417 |
|
| testgi | | | 80.94 407 | 80.20 389 | 83.18 444 | 87.96 444 | 66.29 467 | 91.28 364 | 90.70 423 | 83.70 275 | 78.12 427 | 92.84 283 | 51.37 462 | 90.82 471 | 63.34 458 | 82.46 379 | 92.43 404 |
|
| KD-MVS_self_test | | | 80.20 414 | 79.24 407 | 83.07 445 | 85.64 462 | 65.29 473 | 91.01 372 | 93.93 320 | 78.71 382 | 76.32 442 | 86.40 444 | 59.20 423 | 92.93 450 | 72.59 404 | 69.35 460 | 91.00 442 |
|
| testing3 | | | 80.46 411 | 79.59 403 | 83.06 446 | 93.44 290 | 64.64 476 | 93.33 277 | 85.47 472 | 84.34 262 | 79.93 403 | 90.84 358 | 44.35 481 | 92.39 455 | 57.06 479 | 87.56 324 | 92.16 414 |
|
| ambc | | | | | 83.06 446 | 79.99 487 | 63.51 481 | 77.47 491 | 92.86 356 | | 74.34 458 | 84.45 456 | 28.74 491 | 95.06 416 | 73.06 402 | 68.89 465 | 90.61 445 |
|
| test20.03 | | | 79.95 418 | 79.08 412 | 82.55 448 | 85.79 460 | 67.74 464 | 91.09 370 | 91.08 408 | 81.23 347 | 74.48 457 | 89.96 389 | 61.63 398 | 90.15 473 | 60.08 469 | 76.38 437 | 89.76 454 |
|
| MVStest1 | | | 72.91 444 | 69.70 449 | 82.54 449 | 78.14 490 | 73.05 416 | 88.21 434 | 86.21 466 | 60.69 485 | 64.70 480 | 90.53 368 | 46.44 476 | 85.70 488 | 58.78 475 | 53.62 490 | 88.87 466 |
|
| test_vis1_rt | | | 77.96 433 | 76.46 432 | 82.48 450 | 85.89 459 | 71.74 435 | 90.25 391 | 78.89 489 | 71.03 465 | 71.30 471 | 81.35 476 | 42.49 483 | 91.05 470 | 84.55 237 | 82.37 380 | 84.65 477 |
|
| EU-MVSNet | | | 81.32 401 | 80.95 379 | 82.42 451 | 88.50 435 | 63.67 479 | 93.32 278 | 91.33 403 | 64.02 482 | 80.57 392 | 92.83 284 | 61.21 407 | 92.27 457 | 76.34 371 | 80.38 413 | 91.32 432 |
|
| myMVS_eth3d | | | 79.67 421 | 78.79 415 | 82.32 452 | 91.92 344 | 64.08 477 | 89.75 407 | 87.40 464 | 81.72 332 | 78.82 421 | 87.20 433 | 45.33 479 | 91.29 467 | 59.09 474 | 87.84 321 | 91.60 423 |
|
| ttmdpeth | | | 76.55 437 | 74.64 442 | 82.29 453 | 82.25 483 | 67.81 463 | 89.76 406 | 85.69 470 | 70.35 467 | 75.76 448 | 91.69 327 | 46.88 474 | 89.77 475 | 66.16 447 | 63.23 482 | 89.30 459 |
|
| pmmvs3 | | | 71.81 447 | 68.71 450 | 81.11 454 | 75.86 493 | 70.42 450 | 86.74 455 | 83.66 478 | 58.95 488 | 68.64 477 | 80.89 477 | 36.93 488 | 89.52 477 | 63.10 460 | 63.59 480 | 83.39 478 |
|
| Syy-MVS | | | 80.07 416 | 79.78 398 | 80.94 455 | 91.92 344 | 59.93 487 | 89.75 407 | 87.40 464 | 81.72 332 | 78.82 421 | 87.20 433 | 66.29 360 | 91.29 467 | 47.06 490 | 87.84 321 | 91.60 423 |
|
| UWE-MVS-28 | | | 78.98 427 | 78.38 419 | 80.80 456 | 88.18 442 | 60.66 486 | 90.65 380 | 78.51 490 | 78.84 377 | 77.93 430 | 90.93 355 | 59.08 425 | 89.02 480 | 50.96 485 | 90.33 276 | 92.72 390 |
|
| new-patchmatchnet | | | 76.41 438 | 75.17 440 | 80.13 457 | 82.65 482 | 59.61 488 | 87.66 445 | 91.08 408 | 78.23 391 | 69.85 474 | 83.22 462 | 54.76 450 | 91.63 466 | 64.14 457 | 64.89 479 | 89.16 463 |
|
| mvsany_test3 | | | 74.95 440 | 73.26 444 | 80.02 458 | 74.61 494 | 63.16 482 | 85.53 464 | 78.42 491 | 74.16 440 | 74.89 454 | 86.46 440 | 36.02 489 | 89.09 479 | 82.39 271 | 66.91 473 | 87.82 475 |
|
| test_fmvs3 | | | 77.67 434 | 77.16 429 | 79.22 459 | 79.52 488 | 61.14 484 | 92.34 326 | 91.64 394 | 73.98 442 | 78.86 420 | 86.59 439 | 27.38 494 | 87.03 483 | 88.12 178 | 75.97 439 | 89.50 456 |
|
| DSMNet-mixed | | | 76.94 436 | 76.29 434 | 78.89 460 | 83.10 480 | 56.11 496 | 87.78 441 | 79.77 487 | 60.65 486 | 75.64 449 | 88.71 412 | 61.56 401 | 88.34 482 | 60.07 470 | 89.29 297 | 92.21 413 |
|
| EGC-MVSNET | | | 61.97 455 | 56.37 460 | 78.77 461 | 89.63 424 | 73.50 410 | 89.12 419 | 82.79 480 | 0.21 538 | 1.24 539 | 84.80 454 | 39.48 484 | 90.04 474 | 44.13 492 | 75.94 440 | 72.79 492 |
|
| new_pmnet | | | 72.15 445 | 70.13 448 | 78.20 462 | 82.95 481 | 65.68 470 | 83.91 474 | 82.40 482 | 62.94 484 | 64.47 481 | 79.82 478 | 42.85 482 | 86.26 487 | 57.41 478 | 74.44 442 | 82.65 482 |
|
| MVS-HIRNet | | | 73.70 443 | 72.20 445 | 78.18 463 | 91.81 351 | 56.42 495 | 82.94 479 | 82.58 481 | 55.24 489 | 68.88 475 | 66.48 497 | 55.32 444 | 95.13 413 | 58.12 476 | 88.42 310 | 83.01 480 |
|
| LCM-MVSNet | | | 66.00 452 | 62.16 457 | 77.51 464 | 64.51 508 | 58.29 490 | 83.87 475 | 90.90 416 | 48.17 493 | 54.69 490 | 73.31 491 | 16.83 503 | 86.75 484 | 65.47 449 | 61.67 484 | 87.48 476 |
|
| APD_test1 | | | 69.04 448 | 66.26 454 | 77.36 465 | 80.51 486 | 62.79 483 | 85.46 465 | 83.51 479 | 54.11 491 | 59.14 488 | 84.79 455 | 23.40 497 | 89.61 476 | 55.22 480 | 70.24 456 | 79.68 487 |
|
| test_f | | | 71.95 446 | 70.87 447 | 75.21 466 | 74.21 496 | 59.37 489 | 85.07 468 | 85.82 469 | 65.25 480 | 70.42 473 | 83.13 463 | 23.62 495 | 82.93 494 | 78.32 349 | 71.94 451 | 83.33 479 |
|
| ANet_high | | | 58.88 459 | 54.22 464 | 72.86 467 | 56.50 513 | 56.67 492 | 80.75 484 | 86.00 468 | 73.09 452 | 37.39 503 | 64.63 501 | 22.17 498 | 79.49 498 | 43.51 493 | 23.96 506 | 82.43 483 |
|
| test_vis3_rt | | | 65.12 453 | 62.60 455 | 72.69 468 | 71.44 498 | 60.71 485 | 87.17 450 | 65.55 502 | 63.80 483 | 53.22 491 | 65.65 500 | 14.54 504 | 89.44 478 | 76.65 366 | 65.38 477 | 67.91 497 |
|
| LoFTR | | | 57.22 462 | 52.62 466 | 71.00 469 | 72.03 497 | 48.57 501 | 72.00 498 | 70.08 501 | 44.40 498 | 40.92 501 | 76.42 482 | 8.12 508 | 82.76 495 | 42.28 496 | 47.33 496 | 81.66 484 |
|
| FPMVS | | | 64.63 454 | 62.55 456 | 70.88 470 | 70.80 499 | 56.71 491 | 84.42 472 | 84.42 476 | 51.78 492 | 49.57 492 | 81.61 475 | 23.49 496 | 81.48 496 | 40.61 498 | 76.25 438 | 74.46 491 |
|
| dmvs_testset | | | 74.57 442 | 75.81 439 | 70.86 471 | 87.72 447 | 40.47 510 | 87.05 452 | 77.90 495 | 82.75 303 | 71.15 472 | 85.47 451 | 67.98 341 | 84.12 492 | 45.26 491 | 76.98 436 | 88.00 473 |
|
| N_pmnet | | | 68.89 449 | 68.44 451 | 70.23 472 | 89.07 429 | 28.79 518 | 88.06 436 | 19.50 518 | 69.47 469 | 71.86 469 | 84.93 453 | 61.24 406 | 91.75 464 | 54.70 481 | 77.15 433 | 90.15 451 |
|
| testf1 | | | 59.54 457 | 56.11 461 | 69.85 473 | 69.28 500 | 56.61 493 | 80.37 485 | 76.55 498 | 42.58 500 | 45.68 496 | 75.61 484 | 11.26 505 | 84.18 490 | 43.20 494 | 60.44 486 | 68.75 495 |
|
| APD_test2 | | | 59.54 457 | 56.11 461 | 69.85 473 | 69.28 500 | 56.61 493 | 80.37 485 | 76.55 498 | 42.58 500 | 45.68 496 | 75.61 484 | 11.26 505 | 84.18 490 | 43.20 494 | 60.44 486 | 68.75 495 |
|
| WB-MVS | | | 67.92 450 | 67.49 452 | 69.21 475 | 81.09 484 | 41.17 509 | 88.03 437 | 78.00 494 | 73.50 447 | 62.63 483 | 83.11 465 | 63.94 382 | 86.52 485 | 25.66 505 | 51.45 492 | 79.94 486 |
|
| PMMVS2 | | | 59.60 456 | 56.40 459 | 69.21 475 | 68.83 502 | 46.58 502 | 73.02 497 | 77.48 496 | 55.07 490 | 49.21 493 | 72.95 492 | 17.43 502 | 80.04 497 | 49.32 487 | 44.33 497 | 80.99 485 |
|
| SSC-MVS | | | 67.06 451 | 66.56 453 | 68.56 477 | 80.54 485 | 40.06 511 | 87.77 442 | 77.37 497 | 72.38 457 | 61.75 485 | 82.66 472 | 63.37 385 | 86.45 486 | 24.48 506 | 48.69 495 | 79.16 488 |
|
| Gipuma |  | | 57.99 461 | 54.91 463 | 67.24 478 | 88.51 433 | 65.59 471 | 52.21 503 | 90.33 428 | 43.58 499 | 42.84 499 | 51.18 506 | 20.29 500 | 85.07 489 | 34.77 499 | 70.45 455 | 51.05 505 |
| S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
| RoMa-SfM | | | 53.80 463 | 49.39 467 | 67.06 479 | 67.87 504 | 48.86 499 | 75.04 492 | 38.06 514 | 47.23 495 | 47.40 495 | 78.96 480 | 7.40 509 | 76.66 500 | 48.89 488 | 33.62 501 | 75.64 490 |
|
| DKM | | | 50.92 467 | 46.13 471 | 65.30 480 | 66.27 506 | 45.98 504 | 73.05 496 | 31.91 516 | 45.08 496 | 42.04 500 | 75.01 488 | 4.95 516 | 73.81 502 | 47.90 489 | 28.96 503 | 76.09 489 |
|
| MatchFormer | | | 51.11 466 | 46.66 470 | 64.46 481 | 67.11 505 | 43.39 507 | 70.54 499 | 63.67 504 | 33.19 504 | 37.22 504 | 70.30 494 | 6.67 511 | 78.17 499 | 30.29 502 | 40.94 499 | 71.81 493 |
|
| PMVS |  | 47.18 22 | 52.22 465 | 48.46 469 | 63.48 482 | 45.72 517 | 46.20 503 | 73.41 495 | 78.31 492 | 41.03 502 | 30.06 507 | 65.68 499 | 6.05 512 | 83.43 493 | 30.04 503 | 65.86 476 | 60.80 499 |
| Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
| dongtai | | | 58.82 460 | 58.24 458 | 60.56 483 | 83.13 479 | 45.09 506 | 82.32 480 | 48.22 511 | 67.61 473 | 61.70 486 | 69.15 495 | 38.75 485 | 76.05 501 | 32.01 501 | 41.31 498 | 60.55 500 |
|
| PDCNetPlus | | | 48.34 469 | 45.15 472 | 57.91 484 | 61.43 510 | 41.85 508 | 65.98 500 | 38.30 513 | 47.59 494 | 37.96 502 | 71.85 493 | 10.18 507 | 66.85 507 | 52.94 483 | 20.14 517 | 65.03 498 |
|
| MVE |  | 39.65 23 | 43.39 470 | 38.59 476 | 57.77 485 | 56.52 512 | 48.77 500 | 55.38 502 | 58.64 507 | 29.33 506 | 28.96 508 | 52.65 505 | 4.68 519 | 64.62 508 | 28.11 504 | 33.07 502 | 59.93 501 |
| Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
| test_method | | | 50.52 468 | 48.47 468 | 56.66 486 | 52.26 516 | 18.98 522 | 41.51 509 | 81.40 484 | 10.10 512 | 44.59 498 | 75.01 488 | 28.51 492 | 68.16 503 | 53.54 482 | 49.31 494 | 82.83 481 |
|
| DeepMVS_CX |  | | | | 56.31 487 | 74.23 495 | 51.81 498 | | 56.67 508 | 44.85 497 | 48.54 494 | 75.16 487 | 27.87 493 | 58.74 510 | 40.92 497 | 52.22 491 | 58.39 503 |
|
| ELoFTR | | | 40.15 473 | 35.08 477 | 55.36 488 | 41.27 522 | 28.17 519 | 47.70 505 | 43.76 512 | 29.15 507 | 30.35 506 | 65.97 498 | 2.17 526 | 66.90 506 | 34.51 500 | 20.83 516 | 71.00 494 |
|
| kuosan | | | 53.51 464 | 53.30 465 | 54.13 489 | 76.06 492 | 45.36 505 | 80.11 487 | 48.36 510 | 59.63 487 | 54.84 489 | 63.43 502 | 37.41 486 | 62.07 509 | 20.73 508 | 39.10 500 | 54.96 504 |
|
| GLUNet-SfM | | | 31.36 475 | 26.25 480 | 46.70 490 | 35.51 524 | 24.89 520 | 33.71 514 | 36.36 515 | 19.08 508 | 23.78 511 | 52.69 504 | 3.82 524 | 56.26 511 | 19.75 510 | 11.56 527 | 58.95 502 |
|
| E-PMN | | | 43.23 471 | 42.29 473 | 46.03 491 | 65.58 507 | 37.41 512 | 73.51 494 | 64.62 503 | 33.99 503 | 28.47 509 | 47.87 507 | 19.90 501 | 67.91 504 | 22.23 507 | 24.45 504 | 32.77 511 |
|
| EMVS | | | 42.07 472 | 41.12 474 | 44.92 492 | 63.45 509 | 35.56 514 | 73.65 493 | 63.48 505 | 33.05 505 | 26.88 510 | 45.45 508 | 21.27 499 | 67.14 505 | 19.80 509 | 23.02 508 | 32.06 512 |
|
| ALIKED-LG | | | 28.00 476 | 26.54 479 | 32.41 493 | 58.12 511 | 31.80 515 | 47.26 506 | 21.21 517 | 14.15 509 | 19.16 513 | 41.93 510 | 6.72 510 | 35.73 512 | 5.96 519 | 24.32 505 | 29.69 513 |
|
| ALIKED-MNN | | | 26.28 477 | 24.57 482 | 31.39 494 | 56.22 514 | 31.73 516 | 45.54 507 | 19.13 520 | 11.12 510 | 17.11 515 | 39.35 512 | 5.01 515 | 34.53 513 | 5.54 521 | 22.12 510 | 27.92 514 |
|
| ALIKED-NN | | | 26.07 478 | 24.75 481 | 30.02 495 | 55.08 515 | 30.61 517 | 44.20 508 | 19.22 519 | 10.98 511 | 17.98 514 | 40.71 511 | 5.39 514 | 32.83 514 | 5.59 520 | 23.63 507 | 26.63 515 |
|
| tmp_tt | | | 35.64 474 | 39.24 475 | 24.84 496 | 14.87 541 | 23.90 521 | 62.71 501 | 51.51 509 | 6.58 520 | 36.66 505 | 62.08 503 | 44.37 480 | 30.34 516 | 52.40 484 | 22.00 511 | 20.27 517 |
|
| wuyk23d | | | 21.27 480 | 20.48 483 | 23.63 497 | 68.59 503 | 36.41 513 | 49.57 504 | 6.85 533 | 9.37 513 | 7.89 522 | 4.46 538 | 4.03 523 | 31.37 515 | 17.47 511 | 16.07 520 | 3.12 533 |
|
| SP-LightGlue | | | 20.24 481 | 20.15 485 | 20.49 498 | 43.51 518 | 12.27 530 | 38.68 511 | 14.56 524 | 7.54 517 | 12.90 519 | 30.07 516 | 4.75 517 | 14.38 520 | 7.60 515 | 21.75 512 | 34.82 506 |
|
| SP-SuperGlue | | | 20.22 482 | 20.18 484 | 20.36 499 | 43.26 519 | 12.27 530 | 38.71 510 | 14.77 523 | 7.64 516 | 13.04 518 | 30.21 515 | 4.73 518 | 14.21 522 | 7.59 516 | 21.65 513 | 34.59 507 |
|
| SP-DiffGlue | | | 20.02 483 | 19.96 486 | 20.21 500 | 19.64 538 | 13.14 529 | 30.51 515 | 15.49 522 | 8.39 514 | 19.98 512 | 43.75 509 | 5.48 513 | 13.72 523 | 13.75 512 | 22.65 509 | 33.78 509 |
|
| SP-MNN | | | 19.61 484 | 19.42 487 | 20.19 501 | 42.15 520 | 11.42 536 | 38.15 512 | 14.24 525 | 6.55 521 | 11.64 521 | 29.88 518 | 4.16 521 | 14.56 519 | 7.09 518 | 20.92 515 | 34.58 508 |
|
| SP-NN | | | 19.44 485 | 19.37 488 | 19.67 502 | 41.70 521 | 11.48 535 | 37.75 513 | 13.72 527 | 6.86 518 | 11.86 520 | 29.97 517 | 4.23 520 | 14.25 521 | 7.13 517 | 21.07 514 | 33.30 510 |
|
| XFeat-MNN | | | 17.43 486 | 16.95 489 | 18.86 503 | 16.90 539 | 11.28 537 | 27.31 516 | 17.08 521 | 8.08 515 | 15.61 517 | 35.73 513 | 4.06 522 | 22.95 517 | 10.20 513 | 17.59 519 | 22.35 516 |
|
| XFeat-NN | | | 15.96 487 | 15.86 490 | 16.25 504 | 15.78 540 | 9.87 540 | 25.17 517 | 13.83 526 | 6.76 519 | 15.68 516 | 34.83 514 | 3.61 525 | 19.28 518 | 9.22 514 | 17.90 518 | 19.58 518 |
|
| SIFT-NN | | | 12.98 488 | 13.18 491 | 12.37 505 | 36.49 523 | 16.03 523 | 22.41 518 | 7.69 529 | 4.89 522 | 7.41 523 | 20.48 520 | 1.69 527 | 11.46 525 | 1.88 524 | 15.70 521 | 9.61 520 |
|
| SIFT-MNN | | | 12.44 489 | 12.55 492 | 12.11 506 | 34.55 525 | 15.21 524 | 20.91 519 | 7.74 528 | 4.86 523 | 6.54 525 | 20.09 521 | 1.51 528 | 11.47 524 | 1.88 524 | 14.87 523 | 9.64 519 |
|
| SIFT-NN-NCMNet | | | 12.12 490 | 12.25 493 | 11.75 507 | 32.82 527 | 14.83 525 | 20.73 520 | 7.58 530 | 4.72 525 | 6.60 524 | 19.53 522 | 1.49 529 | 11.15 527 | 1.74 526 | 15.02 522 | 9.28 521 |
|
| SIFT-NCM-Cal | | | 11.58 491 | 11.64 494 | 11.40 508 | 33.45 526 | 14.10 526 | 19.75 522 | 6.89 531 | 4.68 528 | 4.55 532 | 18.60 527 | 1.34 533 | 11.28 526 | 1.53 532 | 13.95 524 | 8.82 525 |
|
| SIFT-NN-CMatch | | | 11.26 492 | 11.31 496 | 11.13 509 | 30.21 531 | 13.40 528 | 18.43 523 | 6.79 534 | 4.71 526 | 6.47 526 | 19.53 522 | 1.43 531 | 10.72 529 | 1.71 527 | 12.49 526 | 9.26 522 |
|
| SIFT-ConvMatch | | | 10.91 494 | 10.94 499 | 10.84 510 | 32.07 528 | 13.57 527 | 17.23 526 | 6.35 535 | 4.71 526 | 5.18 529 | 18.94 525 | 1.30 534 | 10.76 528 | 1.65 530 | 11.02 529 | 8.19 526 |
|
| SIFT-NN-UMatch | | | 11.06 493 | 11.19 498 | 10.66 511 | 28.66 533 | 12.16 532 | 19.79 521 | 6.86 532 | 4.73 524 | 5.21 528 | 19.47 524 | 1.46 530 | 10.70 530 | 1.71 527 | 12.79 525 | 9.13 523 |
|
| SIFT-UMatch | | | 10.58 495 | 10.73 500 | 10.15 512 | 31.05 529 | 11.65 534 | 18.01 524 | 5.92 537 | 4.65 529 | 4.72 530 | 18.93 526 | 1.25 536 | 10.62 531 | 1.66 529 | 10.39 530 | 8.16 527 |
|
| SIFT-CM-Cal | | | 10.08 497 | 10.13 503 | 9.92 513 | 30.71 530 | 11.88 533 | 15.35 528 | 5.44 538 | 4.59 530 | 4.72 530 | 18.04 530 | 1.26 535 | 10.19 532 | 1.46 534 | 9.60 531 | 7.69 528 |
|
| SIFT-NN-PointCN | | | 10.26 496 | 10.46 501 | 9.65 514 | 27.18 534 | 9.89 539 | 17.89 525 | 6.17 536 | 4.40 532 | 5.65 527 | 18.29 528 | 1.43 531 | 10.09 533 | 1.61 531 | 11.55 528 | 8.99 524 |
|
| SIFT-UM-Cal | | | 9.80 498 | 10.00 504 | 9.22 515 | 30.05 532 | 10.15 538 | 16.31 527 | 4.85 540 | 4.54 531 | 4.19 533 | 18.23 529 | 1.19 537 | 9.95 534 | 1.52 533 | 9.11 533 | 7.57 529 |
|
| SIFT-PCN-Cal | | | 8.65 502 | 8.88 506 | 7.98 516 | 26.74 535 | 7.47 542 | 13.90 530 | 4.61 541 | 4.09 534 | 3.82 534 | 15.86 531 | 1.01 538 | 8.94 535 | 1.34 535 | 8.52 534 | 7.53 530 |
|
| SIFT-PointCN | | | 8.76 500 | 9.03 505 | 7.96 517 | 26.50 536 | 7.60 541 | 14.94 529 | 5.08 539 | 4.10 533 | 3.74 535 | 15.46 532 | 0.94 539 | 8.92 536 | 1.33 536 | 9.14 532 | 7.37 531 |
|
| SIFT-NCMNet | | | 7.46 504 | 7.71 508 | 6.72 518 | 25.03 537 | 6.86 543 | 11.42 531 | 2.98 542 | 4.05 535 | 3.38 536 | 13.68 533 | 0.84 540 | 7.65 537 | 1.13 537 | 6.87 535 | 5.66 532 |
|
| test123 | | | 8.76 500 | 11.22 497 | 1.39 519 | 0.85 543 | 0.97 544 | 85.76 462 | 0.35 544 | 0.54 537 | 2.45 538 | 8.14 537 | 0.60 541 | 0.48 538 | 2.16 523 | 0.17 537 | 2.71 534 |
|
| testmvs | | | 8.92 499 | 11.52 495 | 1.12 520 | 1.06 542 | 0.46 545 | 86.02 459 | 0.65 543 | 0.62 536 | 2.74 537 | 9.52 536 | 0.31 542 | 0.45 539 | 2.38 522 | 0.39 536 | 2.46 535 |
|
| mmdepth | | | 0.00 506 | 0.00 509 | 0.00 521 | 0.00 544 | 0.00 546 | 0.00 532 | 0.00 545 | 0.00 539 | 0.00 540 | 0.00 539 | 0.00 543 | 0.00 540 | 0.00 538 | 0.00 538 | 0.00 536 |
|
| monomultidepth | | | 0.00 506 | 0.00 509 | 0.00 521 | 0.00 544 | 0.00 546 | 0.00 532 | 0.00 545 | 0.00 539 | 0.00 540 | 0.00 539 | 0.00 543 | 0.00 540 | 0.00 538 | 0.00 538 | 0.00 536 |
|
| test_blank | | | 0.00 506 | 0.00 509 | 0.00 521 | 0.00 544 | 0.00 546 | 0.00 532 | 0.00 545 | 0.00 539 | 0.00 540 | 0.00 539 | 0.00 543 | 0.00 540 | 0.00 538 | 0.00 538 | 0.00 536 |
|
| uanet_test | | | 0.00 506 | 0.00 509 | 0.00 521 | 0.00 544 | 0.00 546 | 0.00 532 | 0.00 545 | 0.00 539 | 0.00 540 | 0.00 539 | 0.00 543 | 0.00 540 | 0.00 538 | 0.00 538 | 0.00 536 |
|
| DCPMVS | | | 0.00 506 | 0.00 509 | 0.00 521 | 0.00 544 | 0.00 546 | 0.00 532 | 0.00 545 | 0.00 539 | 0.00 540 | 0.00 539 | 0.00 543 | 0.00 540 | 0.00 538 | 0.00 538 | 0.00 536 |
|
| cdsmvs_eth3d_5k | | | 22.14 479 | 29.52 478 | 0.00 521 | 0.00 544 | 0.00 546 | 0.00 532 | 95.76 198 | 0.00 539 | 0.00 540 | 94.29 228 | 75.66 225 | 0.00 540 | 0.00 538 | 0.00 538 | 0.00 536 |
|
| pcd_1.5k_mvsjas | | | 6.64 505 | 8.86 507 | 0.00 521 | 0.00 544 | 0.00 546 | 0.00 532 | 0.00 545 | 0.00 539 | 0.00 540 | 0.00 539 | 79.70 158 | 0.00 540 | 0.00 538 | 0.00 538 | 0.00 536 |
|
| sosnet-low-res | | | 0.00 506 | 0.00 509 | 0.00 521 | 0.00 544 | 0.00 546 | 0.00 532 | 0.00 545 | 0.00 539 | 0.00 540 | 0.00 539 | 0.00 543 | 0.00 540 | 0.00 538 | 0.00 538 | 0.00 536 |
|
| sosnet | | | 0.00 506 | 0.00 509 | 0.00 521 | 0.00 544 | 0.00 546 | 0.00 532 | 0.00 545 | 0.00 539 | 0.00 540 | 0.00 539 | 0.00 543 | 0.00 540 | 0.00 538 | 0.00 538 | 0.00 536 |
|
| uncertanet | | | 0.00 506 | 0.00 509 | 0.00 521 | 0.00 544 | 0.00 546 | 0.00 532 | 0.00 545 | 0.00 539 | 0.00 540 | 0.00 539 | 0.00 543 | 0.00 540 | 0.00 538 | 0.00 538 | 0.00 536 |
|
| Regformer | | | 0.00 506 | 0.00 509 | 0.00 521 | 0.00 544 | 0.00 546 | 0.00 532 | 0.00 545 | 0.00 539 | 0.00 540 | 0.00 539 | 0.00 543 | 0.00 540 | 0.00 538 | 0.00 538 | 0.00 536 |
|
| ab-mvs-re | | | 7.82 503 | 10.43 502 | 0.00 521 | 0.00 544 | 0.00 546 | 0.00 532 | 0.00 545 | 0.00 539 | 0.00 540 | 93.88 249 | 0.00 543 | 0.00 540 | 0.00 538 | 0.00 538 | 0.00 536 |
|
| uanet | | | 0.00 506 | 0.00 509 | 0.00 521 | 0.00 544 | 0.00 546 | 0.00 532 | 0.00 545 | 0.00 539 | 0.00 540 | 0.00 539 | 0.00 543 | 0.00 540 | 0.00 538 | 0.00 538 | 0.00 536 |
|
| WAC-MVS | | | | | | | 64.08 477 | | | | | | | | 59.14 473 | | |
|
| FOURS1 | | | | | | 98.86 4 | 85.54 74 | 98.29 1 | 97.49 11 | 89.79 65 | 96.29 32 | | | | | | |
|
| PC_three_1452 | | | | | | | | | | 82.47 307 | 97.09 19 | 97.07 72 | 92.72 1 | 98.04 199 | 92.70 80 | 99.02 12 | 98.86 16 |
|
| test_one_0601 | | | | | | 98.58 14 | 85.83 68 | | 97.44 20 | 91.05 23 | 96.78 27 | 98.06 24 | 91.45 12 | | | | |
|
| eth-test2 | | | | | | 0.00 544 | | | | | | | | | | | |
|
| eth-test | | | | | | 0.00 544 | | | | | | | | | | | |
|
| ZD-MVS | | | | | | 98.15 40 | 86.62 34 | | 97.07 60 | 83.63 277 | 94.19 65 | 96.91 78 | 87.57 35 | 99.26 51 | 91.99 105 | 98.44 56 | |
|
| RE-MVS-def | | | | 93.68 72 | | 97.92 49 | 84.57 94 | 96.28 51 | 96.76 93 | 87.46 162 | 93.75 76 | 97.43 51 | 82.94 100 | | 92.73 76 | 97.80 91 | 97.88 111 |
|
| IU-MVS | | | | | | 98.77 8 | 86.00 54 | | 96.84 82 | 81.26 345 | 97.26 13 | | | | 95.50 36 | 99.13 3 | 99.03 10 |
|
| test_241102_TWO | | | | | | | | | 97.44 20 | 90.31 43 | 97.62 8 | 98.07 22 | 91.46 11 | 99.58 13 | 95.66 30 | 99.12 6 | 98.98 12 |
|
| test_241102_ONE | | | | | | 98.77 8 | 85.99 56 | | 97.44 20 | 90.26 49 | 97.71 2 | 97.96 33 | 92.31 5 | 99.38 35 | | | |
|
| 9.14 | | | | 94.47 35 | | 97.79 58 | | 96.08 69 | 97.44 20 | 86.13 206 | 95.10 55 | 97.40 53 | 88.34 26 | 99.22 53 | 93.25 68 | 98.70 37 | |
|
| save fliter | | | | | | 97.85 55 | 85.63 73 | 95.21 141 | 96.82 85 | 89.44 76 | | | | | | | |
|
| test_0728_THIRD | | | | | | | | | | 90.75 31 | 97.04 21 | 98.05 27 | 92.09 7 | 99.55 20 | 95.64 32 | 99.13 3 | 99.13 4 |
|
| test0726 | | | | | | 98.78 6 | 85.93 59 | 97.19 16 | 97.47 16 | 90.27 47 | 97.64 6 | 98.13 7 | 91.47 9 | | | | |
|
| GSMVS | | | | | | | | | | | | | | | | | 96.12 229 |
|
| test_part2 | | | | | | 98.55 15 | 87.22 20 | | | | 96.40 31 | | | | | | |
|
| sam_mvs1 | | | | | | | | | | | | | 71.70 285 | | | | 96.12 229 |
|
| sam_mvs | | | | | | | | | | | | | 70.60 299 | | | | |
|
| MTGPA |  | | | | | | | | 96.97 65 | | | | | | | | |
|
| test_post1 | | | | | | | | 88.00 438 | | | | 9.81 535 | 69.31 324 | 95.53 401 | 76.65 366 | | |
|
| test_post | | | | | | | | | | | | 10.29 534 | 70.57 303 | 95.91 386 | | | |
|
| patchmatchnet-post | | | | | | | | | | | | 83.76 458 | 71.53 286 | 96.48 354 | | | |
|
| MTMP | | | | | | | | 96.16 60 | 60.64 506 | | | | | | | | |
|
| gm-plane-assit | | | | | | 89.60 425 | 68.00 460 | | | 77.28 401 | | 88.99 406 | | 97.57 247 | 79.44 336 | | |
|
| test9_res | | | | | | | | | | | | | | | 91.91 109 | 98.71 35 | 98.07 83 |
|
| TEST9 | | | | | | 97.53 67 | 86.49 38 | 94.07 230 | 96.78 90 | 81.61 337 | 92.77 101 | 96.20 109 | 87.71 32 | 99.12 63 | | | |
|
| test_8 | | | | | | 97.49 69 | 86.30 46 | 94.02 236 | 96.76 93 | 81.86 328 | 92.70 105 | 96.20 109 | 87.63 33 | 99.02 73 | | | |
|
| agg_prior2 | | | | | | | | | | | | | | | 90.54 134 | 98.68 40 | 98.27 64 |
|
| agg_prior | | | | | | 97.38 72 | 85.92 61 | | 96.72 100 | | 92.16 120 | | | 98.97 87 | | | |
|
| test_prior4 | | | | | | | 85.96 58 | 94.11 224 | | | | | | | | | |
|
| test_prior2 | | | | | | | | 94.12 222 | | 87.67 157 | 92.63 109 | 96.39 104 | 86.62 45 | | 91.50 118 | 98.67 43 | |
|
| 旧先验2 | | | | | | | | 93.36 276 | | 71.25 463 | 94.37 61 | | | 97.13 301 | 86.74 200 | | |
|
| æ–°å‡ ä½•2 | | | | | | | | 93.11 291 | | | | | | | | | |
|
| 旧先验1 | | | | | | 96.79 86 | 81.81 198 | | 95.67 209 | | | 96.81 84 | 86.69 43 | | | 97.66 97 | 96.97 185 |
|
| æ— å…ˆéªŒ | | | | | | | | 93.28 284 | 96.26 140 | 73.95 443 | | | | 99.05 67 | 80.56 310 | | 96.59 208 |
|
| 原ACMM2 | | | | | | | | 92.94 302 | | | | | | | | | |
|
| test222 | | | | | | 96.55 95 | 81.70 203 | 92.22 334 | 95.01 258 | 68.36 472 | 90.20 177 | 96.14 119 | 80.26 145 | | | 97.80 91 | 96.05 236 |
|
| testdata2 | | | | | | | | | | | | | | 98.75 116 | 78.30 350 | | |
|
| segment_acmp | | | | | | | | | | | | | 87.16 40 | | | | |
|
| testdata1 | | | | | | | | 92.15 336 | | 87.94 141 | | | | | | | |
|
| plane_prior7 | | | | | | 94.70 200 | 82.74 165 | | | | | | | | | | |
|
| plane_prior6 | | | | | | 94.52 216 | 82.75 163 | | | | | | 74.23 245 | | | | |
|
| plane_prior5 | | | | | | | | | 96.22 145 | | | | | 98.12 178 | 88.15 175 | 89.99 280 | 94.63 290 |
|
| plane_prior4 | | | | | | | | | | | | 94.86 199 | | | | | |
|
| plane_prior3 | | | | | | | 82.75 163 | | | 90.26 49 | 86.91 247 | | | | | | |
|
| plane_prior2 | | | | | | | | 95.85 93 | | 90.81 27 | | | | | | | |
|
| plane_prior1 | | | | | | 94.59 209 | | | | | | | | | | | |
|
| plane_prior | | | | | | | 82.73 166 | 95.21 141 | | 89.66 70 | | | | | | 89.88 285 | |
|
| n2 | | | | | | | | | 0.00 545 | | | | | | | | |
|
| nn | | | | | | | | | 0.00 545 | | | | | | | | |
|
| door-mid | | | | | | | | | 85.49 471 | | | | | | | | |
|
| test11 | | | | | | | | | 96.57 112 | | | | | | | | |
|
| door | | | | | | | | | 85.33 473 | | | | | | | | |
|
| HQP5-MVS | | | | | | | 81.56 205 | | | | | | | | | | |
|
| HQP-NCC | | | | | | 94.17 249 | | 94.39 204 | | 88.81 103 | 85.43 293 | | | | | | |
|
| ACMP_Plane | | | | | | 94.17 249 | | 94.39 204 | | 88.81 103 | 85.43 293 | | | | | | |
|
| BP-MVS | | | | | | | | | | | | | | | 87.11 197 | | |
|
| HQP4-MVS | | | | | | | | | | | 85.43 293 | | | 97.96 215 | | | 94.51 300 |
|
| HQP3-MVS | | | | | | | | | 96.04 172 | | | | | | | 89.77 289 | |
|
| HQP2-MVS | | | | | | | | | | | | | 73.83 256 | | | | |
|
| NP-MVS | | | | | | 94.37 230 | 82.42 179 | | | | | 93.98 242 | | | | | |
|
| MDTV_nov1_ep13_2view | | | | | | | 55.91 497 | 87.62 446 | | 73.32 449 | 84.59 315 | | 70.33 306 | | 74.65 389 | | 95.50 257 |
|
| MDTV_nov1_ep13 | | | | 83.56 355 | | 91.69 356 | 69.93 453 | 87.75 443 | 91.54 397 | 78.60 383 | 84.86 309 | 88.90 408 | 69.54 318 | 96.03 377 | 70.25 419 | 88.93 302 | |
|
| ACMMP++_ref | | | | | | | | | | | | | | | | 87.47 325 | |
|
| ACMMP++ | | | | | | | | | | | | | | | | 88.01 317 | |
|
| Test By Simon | | | | | | | | | | | | | 80.02 147 | | | | |
|