| MSC_two_6792asdad | | | | | 89.16 1 | 94.34 31 | 75.53 2 | | 92.99 54 | | | | | 97.53 2 | 89.67 15 | 96.44 9 | 94.41 58 |
|
| No_MVS | | | | | 89.16 1 | 94.34 31 | 75.53 2 | | 92.99 54 | | | | | 97.53 2 | 89.67 15 | 96.44 9 | 94.41 58 |
|
| OPU-MVS | | | | | 89.06 3 | 94.62 15 | 75.42 4 | 93.57 8 | | | | 94.02 61 | 82.45 3 | 96.87 24 | 83.77 82 | 96.48 8 | 94.88 16 |
|
| MM | | | 89.16 8 | 89.23 10 | 88.97 4 | 90.79 102 | 73.65 10 | 92.66 28 | 91.17 149 | 86.57 1 | 87.39 57 | 94.97 25 | 71.70 62 | 97.68 1 | 92.19 1 | 95.63 32 | 95.57 1 |
|
| HPM-MVS++ |  | | 89.02 11 | 89.15 12 | 88.63 5 | 95.01 9 | 76.03 1 | 92.38 32 | 92.85 64 | 80.26 11 | 87.78 48 | 94.27 47 | 75.89 22 | 96.81 27 | 87.45 47 | 96.44 9 | 93.05 142 |
|
| SMA-MVS |  | | 89.08 10 | 89.23 10 | 88.61 6 | 94.25 35 | 73.73 9 | 92.40 29 | 93.63 26 | 74.77 147 | 92.29 7 | 95.97 2 | 74.28 33 | 97.24 16 | 88.58 33 | 96.91 1 | 94.87 18 |
| 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+ | | 77.84 4 | 85.48 73 | 84.47 92 | 88.51 7 | 91.08 93 | 73.49 16 | 93.18 16 | 93.78 23 | 80.79 8 | 76.66 254 | 93.37 83 | 60.40 236 | 96.75 30 | 77.20 162 | 93.73 70 | 95.29 6 |
|
| CNVR-MVS | | | 88.93 13 | 89.13 13 | 88.33 8 | 94.77 12 | 73.82 8 | 90.51 70 | 93.00 51 | 80.90 7 | 88.06 43 | 94.06 59 | 76.43 19 | 96.84 25 | 88.48 36 | 95.99 18 | 94.34 64 |
|
| SteuartSystems-ACMMP | | | 88.72 14 | 88.86 14 | 88.32 9 | 92.14 78 | 72.96 25 | 93.73 5 | 93.67 25 | 80.19 12 | 88.10 42 | 94.80 27 | 73.76 37 | 97.11 18 | 87.51 46 | 95.82 25 | 94.90 15 |
| Skip Steuart: Steuart Systems R&D Blog. |
| MSP-MVS | | | 89.51 5 | 89.91 6 | 88.30 10 | 94.28 34 | 73.46 17 | 92.90 21 | 94.11 11 | 80.27 10 | 91.35 17 | 94.16 54 | 78.35 15 | 96.77 28 | 89.59 17 | 94.22 66 | 94.67 38 |
| 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 |
| NCCC | | | 88.06 18 | 88.01 22 | 88.24 11 | 94.41 26 | 73.62 11 | 91.22 62 | 92.83 65 | 81.50 5 | 85.79 72 | 93.47 80 | 73.02 45 | 97.00 22 | 84.90 64 | 94.94 44 | 94.10 76 |
|
| ZNCC-MVS | | | 87.94 22 | 87.85 24 | 88.20 12 | 94.39 28 | 73.33 19 | 93.03 19 | 93.81 22 | 76.81 75 | 85.24 77 | 94.32 44 | 71.76 60 | 96.93 23 | 85.53 61 | 95.79 26 | 94.32 66 |
|
| MGCNet | | | 87.69 24 | 87.55 29 | 88.12 13 | 89.45 138 | 71.76 53 | 91.47 57 | 89.54 206 | 82.14 3 | 86.65 66 | 94.28 46 | 68.28 120 | 97.46 6 | 90.81 6 | 95.31 38 | 95.15 8 |
|
| region2R | | | 87.42 31 | 87.20 37 | 88.09 14 | 94.63 14 | 73.55 13 | 93.03 19 | 93.12 45 | 76.73 80 | 84.45 94 | 94.52 32 | 69.09 105 | 96.70 31 | 84.37 74 | 94.83 49 | 94.03 80 |
|
| ACMMPR | | | 87.44 29 | 87.23 36 | 88.08 15 | 94.64 13 | 73.59 12 | 93.04 17 | 93.20 39 | 76.78 77 | 84.66 89 | 94.52 32 | 68.81 111 | 96.65 34 | 84.53 72 | 94.90 45 | 94.00 82 |
|
| DPE-MVS |  | | 89.48 6 | 89.98 5 | 88.01 16 | 94.80 11 | 72.69 31 | 91.59 51 | 94.10 13 | 75.90 107 | 92.29 7 | 95.66 10 | 81.67 6 | 97.38 14 | 87.44 48 | 96.34 15 | 93.95 85 |
| Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025 |
| XVS | | | 87.18 37 | 86.91 44 | 88.00 17 | 94.42 24 | 73.33 19 | 92.78 23 | 92.99 54 | 79.14 26 | 83.67 113 | 94.17 53 | 67.45 129 | 96.60 37 | 83.06 87 | 94.50 57 | 94.07 78 |
|
| X-MVStestdata | | | 80.37 199 | 77.83 239 | 88.00 17 | 94.42 24 | 73.33 19 | 92.78 23 | 92.99 54 | 79.14 26 | 83.67 113 | 12.47 489 | 67.45 129 | 96.60 37 | 83.06 87 | 94.50 57 | 94.07 78 |
|
| ACMMP_NAP | | | 88.05 20 | 88.08 21 | 87.94 19 | 93.70 45 | 73.05 22 | 90.86 65 | 93.59 28 | 76.27 100 | 88.14 41 | 95.09 19 | 71.06 72 | 96.67 33 | 87.67 44 | 96.37 14 | 94.09 77 |
|
| HFP-MVS | | | 87.58 26 | 87.47 31 | 87.94 19 | 94.58 16 | 73.54 15 | 93.04 17 | 93.24 38 | 76.78 77 | 84.91 82 | 94.44 39 | 70.78 75 | 96.61 36 | 84.53 72 | 94.89 46 | 93.66 102 |
|
| MP-MVS |  | | 87.71 23 | 87.64 26 | 87.93 21 | 94.36 30 | 73.88 6 | 92.71 27 | 92.65 75 | 77.57 49 | 83.84 109 | 94.40 41 | 72.24 54 | 96.28 47 | 85.65 59 | 95.30 39 | 93.62 109 |
| Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
| MTAPA | | | 87.23 36 | 87.00 39 | 87.90 22 | 94.18 39 | 74.25 5 | 86.58 228 | 92.02 111 | 79.45 22 | 85.88 70 | 94.80 27 | 68.07 122 | 96.21 50 | 86.69 52 | 95.34 36 | 93.23 126 |
|
| PGM-MVS | | | 86.68 45 | 86.27 55 | 87.90 22 | 94.22 37 | 73.38 18 | 90.22 81 | 93.04 46 | 75.53 117 | 83.86 108 | 94.42 40 | 67.87 126 | 96.64 35 | 82.70 98 | 94.57 56 | 93.66 102 |
|
| DVP-MVS++ | | | 90.23 1 | 91.01 1 | 87.89 24 | 94.34 31 | 71.25 64 | 95.06 1 | 94.23 7 | 78.38 38 | 92.78 4 | 95.74 6 | 82.45 3 | 97.49 4 | 89.42 19 | 96.68 2 | 94.95 12 |
|
| GST-MVS | | | 87.42 31 | 87.26 34 | 87.89 24 | 94.12 40 | 72.97 24 | 92.39 31 | 93.43 33 | 76.89 73 | 84.68 86 | 93.99 65 | 70.67 77 | 96.82 26 | 84.18 79 | 95.01 41 | 93.90 88 |
|
| MED-MVS test | | | | | 87.86 26 | 94.57 17 | 71.43 60 | 93.28 12 | 94.36 3 | 75.24 126 | 92.25 9 | 95.03 20 | | 97.39 11 | 88.15 39 | 95.96 19 | 94.75 30 |
|
| MED-MVS | | | 89.59 4 | 90.16 4 | 87.86 26 | 94.57 17 | 71.43 60 | 93.28 12 | 94.36 3 | 76.30 98 | 92.25 9 | 95.03 20 | 81.59 7 | 97.39 11 | 88.15 39 | 95.96 19 | 94.75 30 |
|
| SED-MVS | | | 90.08 2 | 90.85 2 | 87.77 28 | 95.30 2 | 70.98 71 | 93.57 8 | 94.06 15 | 77.24 61 | 93.10 1 | 95.72 8 | 82.99 1 | 97.44 7 | 89.07 25 | 96.63 4 | 94.88 16 |
|
| DeepC-MVS_fast | | 79.65 3 | 86.91 41 | 86.62 50 | 87.76 29 | 93.52 50 | 72.37 43 | 91.26 59 | 93.04 46 | 76.62 83 | 84.22 100 | 93.36 84 | 71.44 66 | 96.76 29 | 80.82 113 | 95.33 37 | 94.16 72 |
| Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
| ME-MVS | | | 88.98 12 | 89.39 9 | 87.75 30 | 94.54 20 | 71.43 60 | 91.61 49 | 94.25 6 | 76.30 98 | 90.62 21 | 95.03 20 | 78.06 16 | 97.07 20 | 88.15 39 | 95.96 19 | 94.75 30 |
|
| APDe-MVS |  | | 89.15 9 | 89.63 8 | 87.73 31 | 94.49 22 | 71.69 54 | 93.83 4 | 93.96 18 | 75.70 114 | 91.06 19 | 96.03 1 | 76.84 17 | 97.03 21 | 89.09 21 | 95.65 31 | 94.47 57 |
| Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition |
| MCST-MVS | | | 87.37 34 | 87.25 35 | 87.73 31 | 94.53 21 | 72.46 40 | 89.82 88 | 93.82 21 | 73.07 196 | 84.86 85 | 92.89 95 | 76.22 20 | 96.33 45 | 84.89 66 | 95.13 40 | 94.40 60 |
|
| TSAR-MVS + MP. | | | 88.02 21 | 88.11 20 | 87.72 33 | 93.68 47 | 72.13 48 | 91.41 58 | 92.35 87 | 74.62 151 | 88.90 32 | 93.85 71 | 75.75 23 | 96.00 59 | 87.80 43 | 94.63 54 | 95.04 10 |
| Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition |
| mPP-MVS | | | 86.67 46 | 86.32 53 | 87.72 33 | 94.41 26 | 73.55 13 | 92.74 25 | 92.22 100 | 76.87 74 | 82.81 136 | 94.25 49 | 66.44 142 | 96.24 49 | 82.88 92 | 94.28 64 | 93.38 119 |
|
| test_0728_SECOND | | | | | 87.71 35 | 95.34 1 | 71.43 60 | 93.49 10 | 94.23 7 | | | | | 97.49 4 | 89.08 22 | 96.41 12 | 94.21 70 |
|
| DeepC-MVS | | 79.81 2 | 87.08 40 | 86.88 45 | 87.69 36 | 91.16 91 | 72.32 45 | 90.31 79 | 93.94 19 | 77.12 67 | 82.82 135 | 94.23 50 | 72.13 56 | 97.09 19 | 84.83 67 | 95.37 35 | 93.65 106 |
| Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
| CP-MVS | | | 87.11 38 | 86.92 43 | 87.68 37 | 94.20 38 | 73.86 7 | 93.98 3 | 92.82 68 | 76.62 83 | 83.68 112 | 94.46 36 | 67.93 124 | 95.95 62 | 84.20 78 | 94.39 61 | 93.23 126 |
|
| SF-MVS | | | 88.46 15 | 88.74 15 | 87.64 38 | 92.78 70 | 71.95 51 | 92.40 29 | 94.74 2 | 75.71 112 | 89.16 29 | 95.10 18 | 75.65 24 | 96.19 51 | 87.07 49 | 96.01 17 | 94.79 23 |
|
| TestfortrainingZip a | | | 89.27 7 | 89.82 7 | 87.60 39 | 94.57 17 | 70.90 77 | 93.28 12 | 94.36 3 | 75.24 126 | 92.25 9 | 95.03 20 | 81.59 7 | 97.39 11 | 86.12 57 | 95.96 19 | 94.52 54 |
|
| MP-MVS-pluss | | | 87.67 25 | 87.72 25 | 87.54 40 | 93.64 48 | 72.04 50 | 89.80 90 | 93.50 30 | 75.17 134 | 86.34 68 | 95.29 17 | 70.86 74 | 96.00 59 | 88.78 31 | 96.04 16 | 94.58 47 |
| MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
| NormalMVS | | | 86.29 54 | 85.88 65 | 87.52 41 | 93.26 56 | 72.47 38 | 91.65 47 | 92.19 105 | 79.31 24 | 84.39 96 | 92.18 113 | 64.64 164 | 95.53 71 | 80.70 116 | 94.65 52 | 94.56 51 |
|
| CANet | | | 86.45 48 | 86.10 61 | 87.51 42 | 90.09 115 | 70.94 75 | 89.70 94 | 92.59 79 | 81.78 4 | 81.32 158 | 91.43 145 | 70.34 79 | 97.23 17 | 84.26 75 | 93.36 74 | 94.37 62 |
|
| HPM-MVS |  | | 87.11 38 | 86.98 41 | 87.50 43 | 93.88 43 | 72.16 47 | 92.19 38 | 93.33 36 | 76.07 104 | 83.81 110 | 93.95 68 | 69.77 92 | 96.01 58 | 85.15 62 | 94.66 51 | 94.32 66 |
| Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
| ACMMP |  | | 85.89 65 | 85.39 76 | 87.38 44 | 93.59 49 | 72.63 33 | 92.74 25 | 93.18 44 | 76.78 77 | 80.73 172 | 93.82 72 | 64.33 166 | 96.29 46 | 82.67 99 | 90.69 116 | 93.23 126 |
| 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 |
| DVP-MVS |  | | 89.60 3 | 90.35 3 | 87.33 45 | 95.27 5 | 71.25 64 | 93.49 10 | 92.73 69 | 77.33 58 | 92.12 12 | 95.78 4 | 80.98 11 | 97.40 9 | 89.08 22 | 96.41 12 | 93.33 123 |
| 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 |
| PHI-MVS | | | 86.43 49 | 86.17 59 | 87.24 46 | 90.88 99 | 70.96 73 | 92.27 37 | 94.07 14 | 72.45 204 | 85.22 78 | 91.90 122 | 69.47 95 | 96.42 44 | 83.28 86 | 95.94 23 | 94.35 63 |
|
| APD-MVS |  | | 87.44 29 | 87.52 30 | 87.19 47 | 94.24 36 | 72.39 41 | 91.86 45 | 92.83 65 | 73.01 198 | 88.58 34 | 94.52 32 | 73.36 38 | 96.49 42 | 84.26 75 | 95.01 41 | 92.70 156 |
| Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
| CDPH-MVS | | | 85.76 68 | 85.29 81 | 87.17 48 | 93.49 51 | 71.08 69 | 88.58 147 | 92.42 85 | 68.32 311 | 84.61 91 | 93.48 78 | 72.32 52 | 96.15 53 | 79.00 140 | 95.43 34 | 94.28 68 |
|
| train_agg | | | 86.43 49 | 86.20 56 | 87.13 49 | 93.26 56 | 72.96 25 | 88.75 138 | 91.89 119 | 68.69 304 | 85.00 80 | 93.10 88 | 74.43 30 | 95.41 80 | 84.97 63 | 95.71 29 | 93.02 144 |
|
| SymmetryMVS | | | 85.38 78 | 84.81 86 | 87.07 50 | 91.47 87 | 72.47 38 | 91.65 47 | 88.06 267 | 79.31 24 | 84.39 96 | 92.18 113 | 64.64 164 | 95.53 71 | 80.70 116 | 90.91 113 | 93.21 129 |
|
| reproduce-ours | | | 87.47 27 | 87.61 27 | 87.07 50 | 93.27 54 | 71.60 55 | 91.56 54 | 93.19 40 | 74.98 138 | 88.96 30 | 95.54 12 | 71.20 70 | 96.54 40 | 86.28 54 | 93.49 71 | 93.06 140 |
|
| our_new_method | | | 87.47 27 | 87.61 27 | 87.07 50 | 93.27 54 | 71.60 55 | 91.56 54 | 93.19 40 | 74.98 138 | 88.96 30 | 95.54 12 | 71.20 70 | 96.54 40 | 86.28 54 | 93.49 71 | 93.06 140 |
|
| CSCG | | | 86.41 51 | 86.19 58 | 87.07 50 | 92.91 67 | 72.48 37 | 90.81 66 | 93.56 29 | 73.95 167 | 83.16 127 | 91.07 158 | 75.94 21 | 95.19 89 | 79.94 124 | 94.38 62 | 93.55 114 |
|
| reproduce_model | | | 87.28 35 | 87.39 33 | 86.95 54 | 93.10 62 | 71.24 68 | 91.60 50 | 93.19 40 | 74.69 148 | 88.80 33 | 95.61 11 | 70.29 81 | 96.44 43 | 86.20 56 | 93.08 75 | 93.16 133 |
|
| SR-MVS | | | 86.73 43 | 86.67 48 | 86.91 55 | 94.11 41 | 72.11 49 | 92.37 33 | 92.56 80 | 74.50 152 | 86.84 64 | 94.65 31 | 67.31 131 | 95.77 64 | 84.80 68 | 92.85 78 | 92.84 154 |
|
| DPM-MVS | | | 84.93 86 | 84.29 93 | 86.84 56 | 90.20 113 | 73.04 23 | 87.12 204 | 93.04 46 | 69.80 273 | 82.85 134 | 91.22 152 | 73.06 44 | 96.02 57 | 76.72 174 | 94.63 54 | 91.46 210 |
|
| TSAR-MVS + GP. | | | 85.71 69 | 85.33 78 | 86.84 56 | 91.34 88 | 72.50 36 | 89.07 124 | 87.28 288 | 76.41 90 | 85.80 71 | 90.22 186 | 74.15 35 | 95.37 85 | 81.82 103 | 91.88 94 | 92.65 160 |
|
| test12 | | | | | 86.80 58 | 92.63 73 | 70.70 81 | | 91.79 126 | | 82.71 137 | | 71.67 63 | 96.16 52 | | 94.50 57 | 93.54 115 |
|
| DeepPCF-MVS | | 80.84 1 | 88.10 16 | 88.56 17 | 86.73 59 | 92.24 77 | 69.03 110 | 89.57 99 | 93.39 35 | 77.53 53 | 89.79 25 | 94.12 56 | 78.98 14 | 96.58 39 | 85.66 58 | 95.72 28 | 94.58 47 |
|
| SD-MVS | | | 88.06 18 | 88.50 18 | 86.71 60 | 92.60 75 | 72.71 29 | 91.81 46 | 93.19 40 | 77.87 42 | 90.32 23 | 94.00 63 | 74.83 26 | 93.78 158 | 87.63 45 | 94.27 65 | 93.65 106 |
| 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 |
| 3Dnovator | | 76.31 5 | 83.38 123 | 82.31 137 | 86.59 61 | 87.94 208 | 72.94 28 | 90.64 68 | 92.14 110 | 77.21 63 | 75.47 280 | 92.83 97 | 58.56 248 | 94.72 115 | 73.24 213 | 92.71 81 | 92.13 188 |
|
| lecture | | | 88.09 17 | 88.59 16 | 86.58 62 | 93.26 56 | 69.77 96 | 93.70 6 | 94.16 9 | 77.13 66 | 89.76 26 | 95.52 14 | 72.26 53 | 96.27 48 | 86.87 50 | 94.65 52 | 93.70 101 |
|
| HPM-MVS_fast | | | 85.35 79 | 84.95 85 | 86.57 63 | 93.69 46 | 70.58 84 | 92.15 40 | 91.62 134 | 73.89 170 | 82.67 138 | 94.09 57 | 62.60 188 | 95.54 70 | 80.93 111 | 92.93 77 | 93.57 112 |
|
| test_prior | | | | | 86.33 64 | 92.61 74 | 69.59 98 | | 92.97 59 | | | | | 95.48 74 | | | 93.91 86 |
|
| MVS_111021_HR | | | 85.14 82 | 84.75 87 | 86.32 65 | 91.65 85 | 72.70 30 | 85.98 250 | 90.33 178 | 76.11 103 | 82.08 145 | 91.61 138 | 71.36 68 | 94.17 139 | 81.02 110 | 92.58 82 | 92.08 189 |
|
| SR-MVS-dyc-post | | | 85.77 67 | 85.61 72 | 86.23 66 | 93.06 64 | 70.63 82 | 91.88 43 | 92.27 93 | 73.53 181 | 85.69 73 | 94.45 37 | 65.00 162 | 95.56 68 | 82.75 94 | 91.87 95 | 92.50 166 |
|
| APD-MVS_3200maxsize | | | 85.97 61 | 85.88 65 | 86.22 67 | 92.69 72 | 69.53 99 | 91.93 42 | 92.99 54 | 73.54 180 | 85.94 69 | 94.51 35 | 65.80 154 | 95.61 67 | 83.04 89 | 92.51 83 | 93.53 116 |
|
| BP-MVS1 | | | 84.32 91 | 83.71 108 | 86.17 68 | 87.84 213 | 67.85 154 | 89.38 109 | 89.64 203 | 77.73 45 | 83.98 106 | 92.12 118 | 56.89 266 | 95.43 77 | 84.03 80 | 91.75 98 | 95.24 7 |
|
| GDP-MVS | | | 83.52 118 | 82.64 130 | 86.16 69 | 88.14 197 | 68.45 132 | 89.13 121 | 92.69 70 | 72.82 202 | 83.71 111 | 91.86 125 | 55.69 274 | 95.35 86 | 80.03 122 | 89.74 134 | 94.69 33 |
|
| balanced_conf03 | | | 86.78 42 | 86.99 40 | 86.15 70 | 91.24 90 | 67.61 162 | 90.51 70 | 92.90 61 | 77.26 60 | 87.44 56 | 91.63 135 | 71.27 69 | 96.06 54 | 85.62 60 | 95.01 41 | 94.78 24 |
|
| DP-MVS Recon | | | 83.11 132 | 82.09 143 | 86.15 70 | 94.44 23 | 70.92 76 | 88.79 135 | 92.20 103 | 70.53 251 | 79.17 195 | 91.03 161 | 64.12 168 | 96.03 55 | 68.39 269 | 90.14 125 | 91.50 206 |
|
| EPNet | | | 83.72 111 | 82.92 125 | 86.14 72 | 84.22 332 | 69.48 101 | 91.05 64 | 85.27 328 | 81.30 6 | 76.83 249 | 91.65 133 | 66.09 149 | 95.56 68 | 76.00 181 | 93.85 68 | 93.38 119 |
| Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
| MVSMamba_PlusPlus | | | 85.99 59 | 85.96 64 | 86.05 73 | 91.09 92 | 67.64 161 | 89.63 97 | 92.65 75 | 72.89 201 | 84.64 90 | 91.71 130 | 71.85 58 | 96.03 55 | 84.77 69 | 94.45 60 | 94.49 56 |
|
| sasdasda | | | 85.91 63 | 85.87 67 | 86.04 74 | 89.84 125 | 69.44 105 | 90.45 76 | 93.00 51 | 76.70 81 | 88.01 45 | 91.23 149 | 73.28 40 | 93.91 152 | 81.50 105 | 88.80 150 | 94.77 25 |
|
| canonicalmvs | | | 85.91 63 | 85.87 67 | 86.04 74 | 89.84 125 | 69.44 105 | 90.45 76 | 93.00 51 | 76.70 81 | 88.01 45 | 91.23 149 | 73.28 40 | 93.91 152 | 81.50 105 | 88.80 150 | 94.77 25 |
|
| h-mvs33 | | | 83.15 129 | 82.19 140 | 86.02 76 | 90.56 105 | 70.85 79 | 88.15 166 | 89.16 229 | 76.02 105 | 84.67 87 | 91.39 146 | 61.54 209 | 95.50 73 | 82.71 96 | 75.48 366 | 91.72 200 |
|
| alignmvs | | | 85.48 73 | 85.32 79 | 85.96 77 | 89.51 134 | 69.47 102 | 89.74 92 | 92.47 81 | 76.17 102 | 87.73 52 | 91.46 144 | 70.32 80 | 93.78 158 | 81.51 104 | 88.95 147 | 94.63 44 |
|
| CS-MVS | | | 86.69 44 | 86.95 42 | 85.90 78 | 90.76 103 | 67.57 164 | 92.83 22 | 93.30 37 | 79.67 19 | 84.57 93 | 92.27 107 | 71.47 65 | 95.02 100 | 84.24 77 | 93.46 73 | 95.13 9 |
|
| DELS-MVS | | | 85.41 76 | 85.30 80 | 85.77 79 | 88.49 182 | 67.93 152 | 85.52 268 | 93.44 32 | 78.70 34 | 83.63 115 | 89.03 219 | 74.57 27 | 95.71 66 | 80.26 121 | 94.04 67 | 93.66 102 |
| 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 |
| SPE-MVS-test | | | 86.29 54 | 86.48 51 | 85.71 80 | 91.02 95 | 67.21 180 | 92.36 34 | 93.78 23 | 78.97 33 | 83.51 120 | 91.20 153 | 70.65 78 | 95.15 91 | 81.96 102 | 94.89 46 | 94.77 25 |
|
| viewdifsd2359ckpt09 | | | 83.34 124 | 82.55 132 | 85.70 81 | 87.64 230 | 67.72 159 | 88.43 151 | 91.68 131 | 71.91 216 | 81.65 154 | 90.68 170 | 67.10 134 | 94.75 113 | 76.17 177 | 87.70 178 | 94.62 46 |
|
| fmvsm_s_conf0.5_n_9 | | | 87.39 33 | 87.95 23 | 85.70 81 | 89.48 137 | 67.88 153 | 88.59 146 | 89.05 234 | 80.19 12 | 90.70 20 | 95.40 15 | 74.56 28 | 93.92 151 | 91.54 2 | 92.07 92 | 95.31 5 |
|
| casdiffmvs_mvg |  | | 85.99 59 | 86.09 62 | 85.70 81 | 87.65 229 | 67.22 179 | 88.69 142 | 93.04 46 | 79.64 21 | 85.33 76 | 92.54 104 | 73.30 39 | 94.50 124 | 83.49 83 | 91.14 108 | 95.37 2 |
| Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025 |
| Elysia | | | 81.53 162 | 80.16 177 | 85.62 84 | 85.51 300 | 68.25 139 | 88.84 133 | 92.19 105 | 71.31 227 | 80.50 175 | 89.83 192 | 46.89 372 | 94.82 108 | 76.85 167 | 89.57 136 | 93.80 96 |
|
| StellarMVS | | | 81.53 162 | 80.16 177 | 85.62 84 | 85.51 300 | 68.25 139 | 88.84 133 | 92.19 105 | 71.31 227 | 80.50 175 | 89.83 192 | 46.89 372 | 94.82 108 | 76.85 167 | 89.57 136 | 93.80 96 |
|
| ETV-MVS | | | 84.90 88 | 84.67 88 | 85.59 86 | 89.39 142 | 68.66 127 | 88.74 140 | 92.64 77 | 79.97 16 | 84.10 103 | 85.71 315 | 69.32 98 | 95.38 82 | 80.82 113 | 91.37 105 | 92.72 155 |
|
| test_fmvsmconf_n | | | 85.92 62 | 86.04 63 | 85.57 87 | 85.03 316 | 69.51 100 | 89.62 98 | 90.58 167 | 73.42 184 | 87.75 50 | 94.02 61 | 72.85 48 | 93.24 194 | 90.37 8 | 90.75 115 | 93.96 83 |
|
| test_fmvsmconf0.1_n | | | 85.61 71 | 85.65 71 | 85.50 88 | 82.99 369 | 69.39 107 | 89.65 95 | 90.29 181 | 73.31 188 | 87.77 49 | 94.15 55 | 71.72 61 | 93.23 195 | 90.31 9 | 90.67 117 | 93.89 89 |
|
| UA-Net | | | 85.08 84 | 84.96 84 | 85.45 89 | 92.07 79 | 68.07 145 | 89.78 91 | 90.86 160 | 82.48 2 | 84.60 92 | 93.20 87 | 69.35 97 | 95.22 88 | 71.39 234 | 90.88 114 | 93.07 139 |
|
| Vis-MVSNet |  | | 83.46 120 | 82.80 127 | 85.43 90 | 90.25 112 | 68.74 121 | 90.30 80 | 90.13 186 | 76.33 97 | 80.87 169 | 92.89 95 | 61.00 223 | 94.20 136 | 72.45 226 | 90.97 111 | 93.35 122 |
| Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
| KinetiMVS | | | 83.31 127 | 82.61 131 | 85.39 91 | 87.08 260 | 67.56 165 | 88.06 168 | 91.65 132 | 77.80 44 | 82.21 143 | 91.79 126 | 57.27 261 | 94.07 142 | 77.77 155 | 89.89 132 | 94.56 51 |
|
| test_fmvsmconf0.01_n | | | 84.73 89 | 84.52 91 | 85.34 92 | 80.25 411 | 69.03 110 | 89.47 102 | 89.65 202 | 73.24 192 | 86.98 62 | 94.27 47 | 66.62 138 | 93.23 195 | 90.26 10 | 89.95 130 | 93.78 98 |
|
| EI-MVSNet-Vis-set | | | 84.19 96 | 83.81 105 | 85.31 93 | 88.18 194 | 67.85 154 | 87.66 182 | 89.73 200 | 80.05 15 | 82.95 130 | 89.59 204 | 70.74 76 | 94.82 108 | 80.66 118 | 84.72 231 | 93.28 125 |
|
| MAR-MVS | | | 81.84 153 | 80.70 163 | 85.27 94 | 91.32 89 | 71.53 58 | 89.82 88 | 90.92 156 | 69.77 275 | 78.50 208 | 86.21 306 | 62.36 194 | 94.52 123 | 65.36 293 | 92.05 93 | 89.77 282 |
| 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 |
| fmvsm_s_conf0.5_n_10 | | | 86.38 52 | 86.76 46 | 85.24 95 | 87.33 246 | 67.30 174 | 89.50 101 | 90.98 154 | 76.25 101 | 90.56 22 | 94.75 29 | 68.38 117 | 94.24 135 | 90.80 7 | 92.32 89 | 94.19 71 |
|
| Effi-MVS+ | | | 83.62 116 | 83.08 120 | 85.24 95 | 88.38 188 | 67.45 167 | 88.89 129 | 89.15 230 | 75.50 118 | 82.27 141 | 88.28 244 | 69.61 94 | 94.45 127 | 77.81 154 | 87.84 174 | 93.84 92 |
|
| MVSFormer | | | 82.85 136 | 82.05 144 | 85.24 95 | 87.35 241 | 70.21 86 | 90.50 72 | 90.38 174 | 68.55 306 | 81.32 158 | 89.47 207 | 61.68 206 | 93.46 184 | 78.98 141 | 90.26 123 | 92.05 190 |
|
| fmvsm_l_conf0.5_n_3 | | | 86.02 57 | 86.32 53 | 85.14 98 | 87.20 251 | 68.54 130 | 89.57 99 | 90.44 172 | 75.31 125 | 87.49 54 | 94.39 42 | 72.86 47 | 92.72 225 | 89.04 27 | 90.56 118 | 94.16 72 |
|
| OPM-MVS | | | 83.50 119 | 82.95 124 | 85.14 98 | 88.79 172 | 70.95 74 | 89.13 121 | 91.52 138 | 77.55 52 | 80.96 166 | 91.75 129 | 60.71 226 | 94.50 124 | 79.67 132 | 86.51 200 | 89.97 274 |
| Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS). |
| HQP_MVS | | | 83.64 114 | 83.14 119 | 85.14 98 | 90.08 116 | 68.71 123 | 91.25 60 | 92.44 82 | 79.12 28 | 78.92 199 | 91.00 163 | 60.42 234 | 95.38 82 | 78.71 144 | 86.32 202 | 91.33 211 |
|
| SSM_0404 | | | 81.91 151 | 80.84 162 | 85.13 101 | 89.24 151 | 68.26 137 | 87.84 179 | 89.25 224 | 71.06 236 | 80.62 173 | 90.39 179 | 59.57 239 | 94.65 119 | 72.45 226 | 87.19 187 | 92.47 169 |
|
| test_fmvsm_n_1920 | | | 85.29 80 | 85.34 77 | 85.13 101 | 86.12 286 | 69.93 92 | 88.65 144 | 90.78 163 | 69.97 269 | 88.27 38 | 93.98 66 | 71.39 67 | 91.54 279 | 88.49 35 | 90.45 120 | 93.91 86 |
|
| EI-MVSNet-UG-set | | | 83.81 105 | 83.38 116 | 85.09 103 | 87.87 211 | 67.53 166 | 87.44 195 | 89.66 201 | 79.74 18 | 82.23 142 | 89.41 213 | 70.24 82 | 94.74 114 | 79.95 123 | 83.92 246 | 92.99 147 |
|
| QAPM | | | 80.88 175 | 79.50 198 | 85.03 104 | 88.01 206 | 68.97 114 | 91.59 51 | 92.00 113 | 66.63 333 | 75.15 298 | 92.16 115 | 57.70 255 | 95.45 75 | 63.52 305 | 88.76 152 | 90.66 237 |
|
| casdiffmvs |  | | 85.11 83 | 85.14 82 | 85.01 105 | 87.20 251 | 65.77 209 | 87.75 180 | 92.83 65 | 77.84 43 | 84.36 99 | 92.38 106 | 72.15 55 | 93.93 150 | 81.27 109 | 90.48 119 | 95.33 4 |
| Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025 |
| PCF-MVS | | 73.52 7 | 80.38 197 | 78.84 215 | 85.01 105 | 87.71 224 | 68.99 113 | 83.65 317 | 91.46 143 | 63.00 382 | 77.77 229 | 90.28 182 | 66.10 148 | 95.09 98 | 61.40 335 | 88.22 166 | 90.94 226 |
| Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
| nrg030 | | | 83.88 104 | 83.53 113 | 84.96 107 | 86.77 269 | 69.28 109 | 90.46 75 | 92.67 72 | 74.79 146 | 82.95 130 | 91.33 148 | 72.70 50 | 93.09 208 | 80.79 115 | 79.28 314 | 92.50 166 |
|
| VDD-MVS | | | 83.01 134 | 82.36 136 | 84.96 107 | 91.02 95 | 66.40 191 | 88.91 128 | 88.11 263 | 77.57 49 | 84.39 96 | 93.29 85 | 52.19 308 | 93.91 152 | 77.05 165 | 88.70 154 | 94.57 49 |
|
| PVSNet_Blended_VisFu | | | 82.62 139 | 81.83 149 | 84.96 107 | 90.80 101 | 69.76 97 | 88.74 140 | 91.70 130 | 69.39 282 | 78.96 197 | 88.46 239 | 65.47 156 | 94.87 107 | 74.42 199 | 88.57 155 | 90.24 256 |
|
| mamba_0408 | | | 79.37 224 | 77.52 251 | 84.93 110 | 88.81 167 | 67.96 149 | 65.03 473 | 88.66 254 | 70.96 240 | 79.48 189 | 89.80 194 | 58.69 245 | 94.65 119 | 70.35 245 | 85.93 213 | 92.18 183 |
|
| CPTT-MVS | | | 83.73 110 | 83.33 118 | 84.92 111 | 93.28 53 | 70.86 78 | 92.09 41 | 90.38 174 | 68.75 303 | 79.57 187 | 92.83 97 | 60.60 232 | 93.04 213 | 80.92 112 | 91.56 102 | 90.86 228 |
|
| EC-MVSNet | | | 86.01 58 | 86.38 52 | 84.91 112 | 89.31 147 | 66.27 194 | 92.32 35 | 93.63 26 | 79.37 23 | 84.17 102 | 91.88 123 | 69.04 109 | 95.43 77 | 83.93 81 | 93.77 69 | 93.01 145 |
|
| SSM_0407 | | | 81.58 161 | 80.48 169 | 84.87 113 | 88.81 167 | 67.96 149 | 87.37 196 | 89.25 224 | 71.06 236 | 79.48 189 | 90.39 179 | 59.57 239 | 94.48 126 | 72.45 226 | 85.93 213 | 92.18 183 |
|
| OMC-MVS | | | 82.69 138 | 81.97 147 | 84.85 114 | 88.75 174 | 67.42 168 | 87.98 170 | 90.87 159 | 74.92 141 | 79.72 185 | 91.65 133 | 62.19 198 | 93.96 144 | 75.26 192 | 86.42 201 | 93.16 133 |
|
| EIA-MVS | | | 83.31 127 | 82.80 127 | 84.82 115 | 89.59 130 | 65.59 213 | 88.21 162 | 92.68 71 | 74.66 150 | 78.96 197 | 86.42 302 | 69.06 107 | 95.26 87 | 75.54 188 | 90.09 126 | 93.62 109 |
|
| PAPM_NR | | | 83.02 133 | 82.41 134 | 84.82 115 | 92.47 76 | 66.37 192 | 87.93 174 | 91.80 125 | 73.82 171 | 77.32 237 | 90.66 171 | 67.90 125 | 94.90 104 | 70.37 244 | 89.48 139 | 93.19 132 |
|
| baseline | | | 84.93 86 | 84.98 83 | 84.80 117 | 87.30 249 | 65.39 218 | 87.30 200 | 92.88 62 | 77.62 47 | 84.04 105 | 92.26 108 | 71.81 59 | 93.96 144 | 81.31 107 | 90.30 122 | 95.03 11 |
|
| viewdifsd2359ckpt13 | | | 82.91 135 | 82.29 138 | 84.77 118 | 86.96 263 | 66.90 187 | 87.47 187 | 91.62 134 | 72.19 209 | 81.68 153 | 90.71 169 | 66.92 135 | 93.28 190 | 75.90 182 | 87.15 188 | 94.12 75 |
|
| lupinMVS | | | 81.39 167 | 80.27 175 | 84.76 119 | 87.35 241 | 70.21 86 | 85.55 264 | 86.41 312 | 62.85 385 | 81.32 158 | 88.61 234 | 61.68 206 | 92.24 248 | 78.41 148 | 90.26 123 | 91.83 193 |
|
| fmvsm_s_conf0.5_n_8 | | | 86.56 47 | 87.17 38 | 84.73 120 | 87.76 221 | 65.62 212 | 89.20 114 | 92.21 102 | 79.94 17 | 89.74 27 | 94.86 26 | 68.63 114 | 94.20 136 | 90.83 5 | 91.39 104 | 94.38 61 |
|
| jason | | | 81.39 167 | 80.29 174 | 84.70 121 | 86.63 274 | 69.90 94 | 85.95 251 | 86.77 305 | 63.24 378 | 81.07 164 | 89.47 207 | 61.08 222 | 92.15 250 | 78.33 149 | 90.07 128 | 92.05 190 |
| jason: jason. |
| ET-MVSNet_ETH3D | | | 78.63 242 | 76.63 274 | 84.64 122 | 86.73 270 | 69.47 102 | 85.01 279 | 84.61 337 | 69.54 280 | 66.51 415 | 86.59 295 | 50.16 342 | 91.75 266 | 76.26 176 | 84.24 242 | 92.69 158 |
|
| EPP-MVSNet | | | 83.40 122 | 83.02 122 | 84.57 123 | 90.13 114 | 64.47 253 | 92.32 35 | 90.73 164 | 74.45 155 | 79.35 193 | 91.10 156 | 69.05 108 | 95.12 92 | 72.78 217 | 87.22 186 | 94.13 74 |
|
| UGNet | | | 80.83 177 | 79.59 196 | 84.54 124 | 88.04 203 | 68.09 144 | 89.42 106 | 88.16 262 | 76.95 71 | 76.22 266 | 89.46 209 | 49.30 355 | 93.94 147 | 68.48 267 | 90.31 121 | 91.60 201 |
| 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 |
| E6new | | | 84.22 92 | 84.12 95 | 84.52 125 | 87.60 231 | 65.36 220 | 87.45 190 | 92.30 91 | 76.51 85 | 83.53 116 | 92.26 108 | 69.26 100 | 93.49 179 | 79.88 125 | 88.26 161 | 94.69 33 |
|
| E6 | | | 84.22 92 | 84.12 95 | 84.52 125 | 87.60 231 | 65.36 220 | 87.45 190 | 92.30 91 | 76.51 85 | 83.53 116 | 92.26 108 | 69.26 100 | 93.49 179 | 79.88 125 | 88.26 161 | 94.69 33 |
|
| E5new | | | 84.22 92 | 84.12 95 | 84.51 127 | 87.60 231 | 65.36 220 | 87.45 190 | 92.31 89 | 76.51 85 | 83.53 116 | 92.26 108 | 69.25 102 | 93.50 177 | 79.88 125 | 88.26 161 | 94.69 33 |
|
| E5 | | | 84.22 92 | 84.12 95 | 84.51 127 | 87.60 231 | 65.36 220 | 87.45 190 | 92.31 89 | 76.51 85 | 83.53 116 | 92.26 108 | 69.25 102 | 93.50 177 | 79.88 125 | 88.26 161 | 94.69 33 |
|
| LPG-MVS_test | | | 82.08 147 | 81.27 153 | 84.50 129 | 89.23 152 | 68.76 119 | 90.22 81 | 91.94 117 | 75.37 123 | 76.64 255 | 91.51 141 | 54.29 287 | 94.91 102 | 78.44 146 | 83.78 247 | 89.83 279 |
|
| LGP-MVS_train | | | | | 84.50 129 | 89.23 152 | 68.76 119 | | 91.94 117 | 75.37 123 | 76.64 255 | 91.51 141 | 54.29 287 | 94.91 102 | 78.44 146 | 83.78 247 | 89.83 279 |
|
| test_fmvsmvis_n_1920 | | | 84.02 100 | 83.87 102 | 84.49 131 | 84.12 334 | 69.37 108 | 88.15 166 | 87.96 270 | 70.01 267 | 83.95 107 | 93.23 86 | 68.80 112 | 91.51 282 | 88.61 32 | 89.96 129 | 92.57 161 |
|
| E4 | | | 84.10 98 | 83.99 101 | 84.45 132 | 87.58 239 | 64.99 234 | 86.54 230 | 92.25 96 | 76.38 94 | 83.37 121 | 92.09 119 | 69.88 90 | 93.58 166 | 79.78 130 | 88.03 171 | 94.77 25 |
|
| MSLP-MVS++ | | | 85.43 75 | 85.76 69 | 84.45 132 | 91.93 81 | 70.24 85 | 90.71 67 | 92.86 63 | 77.46 55 | 84.22 100 | 92.81 99 | 67.16 133 | 92.94 215 | 80.36 119 | 94.35 63 | 90.16 258 |
|
| Effi-MVS+-dtu | | | 80.03 207 | 78.57 219 | 84.42 134 | 85.13 313 | 68.74 121 | 88.77 136 | 88.10 264 | 74.99 137 | 74.97 304 | 83.49 372 | 57.27 261 | 93.36 188 | 73.53 207 | 80.88 291 | 91.18 215 |
|
| E2 | | | 84.00 101 | 83.87 102 | 84.39 135 | 87.70 226 | 64.95 235 | 86.40 237 | 92.23 97 | 75.85 108 | 83.21 123 | 91.78 127 | 70.09 85 | 93.55 171 | 79.52 133 | 88.05 169 | 94.66 41 |
|
| E3 | | | 84.00 101 | 83.87 102 | 84.39 135 | 87.70 226 | 64.95 235 | 86.40 237 | 92.23 97 | 75.85 108 | 83.21 123 | 91.78 127 | 70.09 85 | 93.55 171 | 79.52 133 | 88.05 169 | 94.66 41 |
|
| HQP-MVS | | | 82.61 140 | 82.02 145 | 84.37 137 | 89.33 144 | 66.98 183 | 89.17 116 | 92.19 105 | 76.41 90 | 77.23 240 | 90.23 185 | 60.17 237 | 95.11 94 | 77.47 159 | 85.99 211 | 91.03 221 |
|
| ACMP | | 74.13 6 | 81.51 166 | 80.57 166 | 84.36 138 | 89.42 139 | 68.69 126 | 89.97 85 | 91.50 142 | 74.46 154 | 75.04 302 | 90.41 178 | 53.82 293 | 94.54 121 | 77.56 158 | 82.91 267 | 89.86 278 |
| Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
| 原ACMM1 | | | | | 84.35 139 | 93.01 66 | 68.79 117 | | 92.44 82 | 63.96 374 | 81.09 163 | 91.57 139 | 66.06 150 | 95.45 75 | 67.19 279 | 94.82 50 | 88.81 314 |
|
| viewcassd2359sk11 | | | 83.89 103 | 83.74 107 | 84.34 140 | 87.76 221 | 64.91 241 | 86.30 241 | 92.22 100 | 75.47 119 | 83.04 129 | 91.52 140 | 70.15 83 | 93.53 174 | 79.26 135 | 87.96 172 | 94.57 49 |
|
| PS-MVSNAJss | | | 82.07 148 | 81.31 152 | 84.34 140 | 86.51 277 | 67.27 176 | 89.27 112 | 91.51 139 | 71.75 217 | 79.37 192 | 90.22 186 | 63.15 180 | 94.27 131 | 77.69 157 | 82.36 275 | 91.49 207 |
|
| E3new | | | 83.78 108 | 83.60 111 | 84.31 142 | 87.76 221 | 64.89 242 | 86.24 244 | 92.20 103 | 75.15 135 | 82.87 132 | 91.23 149 | 70.11 84 | 93.52 176 | 79.05 136 | 87.79 175 | 94.51 55 |
|
| thisisatest0530 | | | 79.40 221 | 77.76 244 | 84.31 142 | 87.69 228 | 65.10 231 | 87.36 197 | 84.26 344 | 70.04 265 | 77.42 234 | 88.26 246 | 49.94 346 | 94.79 112 | 70.20 247 | 84.70 232 | 93.03 143 |
|
| fmvsm_s_conf0.5_n_4 | | | 85.39 77 | 85.75 70 | 84.30 144 | 86.70 271 | 65.83 205 | 88.77 136 | 89.78 195 | 75.46 120 | 88.35 36 | 93.73 74 | 69.19 104 | 93.06 210 | 91.30 3 | 88.44 159 | 94.02 81 |
|
| CLD-MVS | | | 82.31 144 | 81.65 150 | 84.29 145 | 88.47 183 | 67.73 158 | 85.81 258 | 92.35 87 | 75.78 110 | 78.33 214 | 86.58 297 | 64.01 169 | 94.35 128 | 76.05 180 | 87.48 182 | 90.79 230 |
| Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
| fmvsm_s_conf0.1_n_a | | | 83.32 126 | 82.99 123 | 84.28 146 | 83.79 342 | 68.07 145 | 89.34 111 | 82.85 370 | 69.80 273 | 87.36 58 | 94.06 59 | 68.34 119 | 91.56 275 | 87.95 42 | 83.46 260 | 93.21 129 |
|
| fmvsm_s_conf0.5_n_a | | | 83.63 115 | 83.41 115 | 84.28 146 | 86.14 285 | 68.12 143 | 89.43 104 | 82.87 369 | 70.27 262 | 87.27 59 | 93.80 73 | 69.09 105 | 91.58 272 | 88.21 38 | 83.65 254 | 93.14 136 |
|
| fmvsm_l_conf0.5_n | | | 84.47 90 | 84.54 89 | 84.27 148 | 85.42 303 | 68.81 116 | 88.49 150 | 87.26 293 | 68.08 313 | 88.03 44 | 93.49 77 | 72.04 57 | 91.77 265 | 88.90 29 | 89.14 146 | 92.24 180 |
|
| mvsmamba | | | 80.60 190 | 79.38 200 | 84.27 148 | 89.74 128 | 67.24 178 | 87.47 187 | 86.95 300 | 70.02 266 | 75.38 286 | 88.93 224 | 51.24 329 | 92.56 231 | 75.47 190 | 89.22 143 | 93.00 146 |
|
| API-MVS | | | 81.99 150 | 81.23 154 | 84.26 150 | 90.94 97 | 70.18 91 | 91.10 63 | 89.32 218 | 71.51 224 | 78.66 204 | 88.28 244 | 65.26 157 | 95.10 97 | 64.74 299 | 91.23 107 | 87.51 349 |
|
| fmvsm_s_conf0.5_n_5 | | | 85.22 81 | 85.55 73 | 84.25 151 | 86.26 280 | 67.40 170 | 89.18 115 | 89.31 219 | 72.50 203 | 88.31 37 | 93.86 70 | 69.66 93 | 91.96 257 | 89.81 13 | 91.05 109 | 93.38 119 |
|
| 114514_t | | | 80.68 186 | 79.51 197 | 84.20 152 | 94.09 42 | 67.27 176 | 89.64 96 | 91.11 152 | 58.75 425 | 74.08 317 | 90.72 168 | 58.10 251 | 95.04 99 | 69.70 254 | 89.42 140 | 90.30 254 |
|
| IS-MVSNet | | | 83.15 129 | 82.81 126 | 84.18 153 | 89.94 123 | 63.30 285 | 91.59 51 | 88.46 260 | 79.04 30 | 79.49 188 | 92.16 115 | 65.10 159 | 94.28 130 | 67.71 272 | 91.86 97 | 94.95 12 |
|
| MVS_111021_LR | | | 82.61 140 | 82.11 141 | 84.11 154 | 88.82 166 | 71.58 57 | 85.15 274 | 86.16 318 | 74.69 148 | 80.47 177 | 91.04 159 | 62.29 195 | 90.55 317 | 80.33 120 | 90.08 127 | 90.20 257 |
|
| fmvsm_s_conf0.1_n | | | 83.56 117 | 83.38 116 | 84.10 155 | 84.86 318 | 67.28 175 | 89.40 108 | 83.01 365 | 70.67 246 | 87.08 60 | 93.96 67 | 68.38 117 | 91.45 285 | 88.56 34 | 84.50 234 | 93.56 113 |
|
| FA-MVS(test-final) | | | 80.96 174 | 79.91 184 | 84.10 155 | 88.30 191 | 65.01 232 | 84.55 292 | 90.01 189 | 73.25 191 | 79.61 186 | 87.57 264 | 58.35 250 | 94.72 115 | 71.29 235 | 86.25 205 | 92.56 162 |
|
| Anonymous20240529 | | | 80.19 205 | 78.89 214 | 84.10 155 | 90.60 104 | 64.75 245 | 88.95 127 | 90.90 157 | 65.97 341 | 80.59 174 | 91.17 155 | 49.97 345 | 93.73 164 | 69.16 260 | 82.70 272 | 93.81 94 |
|
| RRT-MVS | | | 82.60 142 | 82.10 142 | 84.10 155 | 87.98 207 | 62.94 296 | 87.45 190 | 91.27 145 | 77.42 56 | 79.85 183 | 90.28 182 | 56.62 269 | 94.70 117 | 79.87 129 | 88.15 167 | 94.67 38 |
|
| OpenMVS |  | 72.83 10 | 79.77 210 | 78.33 226 | 84.09 159 | 85.17 309 | 69.91 93 | 90.57 69 | 90.97 155 | 66.70 327 | 72.17 344 | 91.91 121 | 54.70 284 | 93.96 144 | 61.81 332 | 90.95 112 | 88.41 328 |
|
| FE-MVS | | | 77.78 265 | 75.68 286 | 84.08 160 | 88.09 201 | 66.00 200 | 83.13 331 | 87.79 276 | 68.42 310 | 78.01 222 | 85.23 330 | 45.50 392 | 95.12 92 | 59.11 356 | 85.83 217 | 91.11 217 |
|
| viewmacassd2359aftdt | | | 83.76 109 | 83.66 110 | 84.07 161 | 86.59 275 | 64.56 247 | 86.88 215 | 91.82 124 | 75.72 111 | 83.34 122 | 92.15 117 | 68.24 121 | 92.88 218 | 79.05 136 | 89.15 145 | 94.77 25 |
|
| fmvsm_s_conf0.5_n | | | 83.80 106 | 83.71 108 | 84.07 161 | 86.69 272 | 67.31 173 | 89.46 103 | 83.07 364 | 71.09 234 | 86.96 63 | 93.70 75 | 69.02 110 | 91.47 284 | 88.79 30 | 84.62 233 | 93.44 118 |
|
| hse-mvs2 | | | 81.72 155 | 80.94 160 | 84.07 161 | 88.72 175 | 67.68 160 | 85.87 254 | 87.26 293 | 76.02 105 | 84.67 87 | 88.22 247 | 61.54 209 | 93.48 182 | 82.71 96 | 73.44 394 | 91.06 219 |
|
| fmvsm_l_conf0.5_n_a | | | 84.13 97 | 84.16 94 | 84.06 164 | 85.38 304 | 68.40 133 | 88.34 158 | 86.85 304 | 67.48 320 | 87.48 55 | 93.40 82 | 70.89 73 | 91.61 270 | 88.38 37 | 89.22 143 | 92.16 187 |
|
| dcpmvs_2 | | | 85.63 70 | 86.15 60 | 84.06 164 | 91.71 84 | 64.94 238 | 86.47 232 | 91.87 121 | 73.63 176 | 86.60 67 | 93.02 93 | 76.57 18 | 91.87 263 | 83.36 84 | 92.15 90 | 95.35 3 |
|
| AdaColmap |  | | 80.58 193 | 79.42 199 | 84.06 164 | 93.09 63 | 68.91 115 | 89.36 110 | 88.97 240 | 69.27 286 | 75.70 276 | 89.69 198 | 57.20 263 | 95.77 64 | 63.06 314 | 88.41 160 | 87.50 350 |
|
| AUN-MVS | | | 79.21 227 | 77.60 249 | 84.05 167 | 88.71 176 | 67.61 162 | 85.84 256 | 87.26 293 | 69.08 294 | 77.23 240 | 88.14 252 | 53.20 300 | 93.47 183 | 75.50 189 | 73.45 393 | 91.06 219 |
|
| VDDNet | | | 81.52 164 | 80.67 164 | 84.05 167 | 90.44 108 | 64.13 260 | 89.73 93 | 85.91 321 | 71.11 233 | 83.18 126 | 93.48 78 | 50.54 338 | 93.49 179 | 73.40 210 | 88.25 165 | 94.54 53 |
|
| xiu_mvs_v1_base_debu | | | 80.80 181 | 79.72 192 | 84.03 169 | 87.35 241 | 70.19 88 | 85.56 261 | 88.77 247 | 69.06 295 | 81.83 147 | 88.16 248 | 50.91 332 | 92.85 219 | 78.29 150 | 87.56 179 | 89.06 299 |
|
| xiu_mvs_v1_base | | | 80.80 181 | 79.72 192 | 84.03 169 | 87.35 241 | 70.19 88 | 85.56 261 | 88.77 247 | 69.06 295 | 81.83 147 | 88.16 248 | 50.91 332 | 92.85 219 | 78.29 150 | 87.56 179 | 89.06 299 |
|
| xiu_mvs_v1_base_debi | | | 80.80 181 | 79.72 192 | 84.03 169 | 87.35 241 | 70.19 88 | 85.56 261 | 88.77 247 | 69.06 295 | 81.83 147 | 88.16 248 | 50.91 332 | 92.85 219 | 78.29 150 | 87.56 179 | 89.06 299 |
|
| fmvsm_s_conf0.5_n_11 | | | 86.06 56 | 86.75 47 | 84.00 172 | 87.78 218 | 66.09 196 | 89.96 86 | 90.80 162 | 77.37 57 | 86.72 65 | 94.20 52 | 72.51 51 | 92.78 224 | 89.08 22 | 92.33 87 | 93.13 137 |
|
| viewmanbaseed2359cas | | | 83.66 112 | 83.55 112 | 84.00 172 | 86.81 267 | 64.53 248 | 86.65 225 | 91.75 129 | 74.89 142 | 83.15 128 | 91.68 131 | 68.74 113 | 92.83 222 | 79.02 138 | 89.24 142 | 94.63 44 |
|
| PAPR | | | 81.66 159 | 80.89 161 | 83.99 174 | 90.27 111 | 64.00 261 | 86.76 222 | 91.77 128 | 68.84 302 | 77.13 247 | 89.50 205 | 67.63 127 | 94.88 106 | 67.55 274 | 88.52 157 | 93.09 138 |
|
| XVG-OURS | | | 80.41 195 | 79.23 206 | 83.97 175 | 85.64 296 | 69.02 112 | 83.03 336 | 90.39 173 | 71.09 234 | 77.63 231 | 91.49 143 | 54.62 286 | 91.35 288 | 75.71 184 | 83.47 259 | 91.54 204 |
|
| XVG-OURS-SEG-HR | | | 80.81 178 | 79.76 189 | 83.96 176 | 85.60 298 | 68.78 118 | 83.54 323 | 90.50 170 | 70.66 249 | 76.71 253 | 91.66 132 | 60.69 227 | 91.26 291 | 76.94 166 | 81.58 283 | 91.83 193 |
|
| HyFIR lowres test | | | 77.53 273 | 75.40 293 | 83.94 177 | 89.59 130 | 66.62 188 | 80.36 374 | 88.64 257 | 56.29 442 | 76.45 260 | 85.17 332 | 57.64 256 | 93.28 190 | 61.34 337 | 83.10 266 | 91.91 192 |
|
| tttt0517 | | | 79.40 221 | 77.91 235 | 83.90 178 | 88.10 200 | 63.84 266 | 88.37 157 | 84.05 346 | 71.45 225 | 76.78 251 | 89.12 216 | 49.93 348 | 94.89 105 | 70.18 248 | 83.18 265 | 92.96 148 |
|
| LuminaMVS | | | 80.68 186 | 79.62 195 | 83.83 179 | 85.07 315 | 68.01 148 | 86.99 209 | 88.83 244 | 70.36 257 | 81.38 157 | 87.99 255 | 50.11 343 | 92.51 235 | 79.02 138 | 86.89 194 | 90.97 224 |
|
| fmvsm_s_conf0.1_n_2 | | | 83.80 106 | 83.79 106 | 83.83 179 | 85.62 297 | 64.94 238 | 87.03 207 | 86.62 310 | 74.32 157 | 87.97 47 | 94.33 43 | 60.67 228 | 92.60 228 | 89.72 14 | 87.79 175 | 93.96 83 |
|
| fmvsm_s_conf0.5_n_2 | | | 84.04 99 | 84.11 99 | 83.81 181 | 86.17 284 | 65.00 233 | 86.96 210 | 87.28 288 | 74.35 156 | 88.25 39 | 94.23 50 | 61.82 204 | 92.60 228 | 89.85 12 | 88.09 168 | 93.84 92 |
|
| GeoE | | | 81.71 156 | 81.01 159 | 83.80 182 | 89.51 134 | 64.45 254 | 88.97 126 | 88.73 253 | 71.27 230 | 78.63 205 | 89.76 197 | 66.32 144 | 93.20 200 | 69.89 252 | 86.02 210 | 93.74 99 |
|
| MGCFI-Net | | | 85.06 85 | 85.51 74 | 83.70 183 | 89.42 139 | 63.01 291 | 89.43 104 | 92.62 78 | 76.43 89 | 87.53 53 | 91.34 147 | 72.82 49 | 93.42 187 | 81.28 108 | 88.74 153 | 94.66 41 |
|
| PS-MVSNAJ | | | 81.69 157 | 81.02 158 | 83.70 183 | 89.51 134 | 68.21 142 | 84.28 303 | 90.09 187 | 70.79 243 | 81.26 162 | 85.62 320 | 63.15 180 | 94.29 129 | 75.62 186 | 88.87 149 | 88.59 323 |
|
| fmvsm_s_conf0.5_n_6 | | | 85.55 72 | 86.20 56 | 83.60 185 | 87.32 248 | 65.13 228 | 88.86 130 | 91.63 133 | 75.41 121 | 88.23 40 | 93.45 81 | 68.56 115 | 92.47 236 | 89.52 18 | 92.78 79 | 93.20 131 |
|
| xiu_mvs_v2_base | | | 81.69 157 | 81.05 157 | 83.60 185 | 89.15 155 | 68.03 147 | 84.46 295 | 90.02 188 | 70.67 246 | 81.30 161 | 86.53 300 | 63.17 179 | 94.19 138 | 75.60 187 | 88.54 156 | 88.57 324 |
|
| ACMM | | 73.20 8 | 80.78 185 | 79.84 187 | 83.58 187 | 89.31 147 | 68.37 134 | 89.99 84 | 91.60 136 | 70.28 261 | 77.25 238 | 89.66 200 | 53.37 298 | 93.53 174 | 74.24 202 | 82.85 268 | 88.85 312 |
| Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
| LFMVS | | | 81.82 154 | 81.23 154 | 83.57 188 | 91.89 82 | 63.43 283 | 89.84 87 | 81.85 381 | 77.04 70 | 83.21 123 | 93.10 88 | 52.26 307 | 93.43 186 | 71.98 229 | 89.95 130 | 93.85 90 |
|
| Fast-Effi-MVS+ | | | 80.81 178 | 79.92 183 | 83.47 189 | 88.85 163 | 64.51 250 | 85.53 266 | 89.39 212 | 70.79 243 | 78.49 209 | 85.06 335 | 67.54 128 | 93.58 166 | 67.03 282 | 86.58 198 | 92.32 175 |
|
| fmvsm_l_conf0.5_n_9 | | | 85.84 66 | 86.63 49 | 83.46 190 | 87.12 259 | 66.01 199 | 88.56 148 | 89.43 210 | 75.59 116 | 89.32 28 | 94.32 44 | 72.89 46 | 91.21 296 | 90.11 11 | 92.33 87 | 93.16 133 |
|
| CHOSEN 1792x2688 | | | 77.63 272 | 75.69 285 | 83.44 191 | 89.98 122 | 68.58 129 | 78.70 399 | 87.50 283 | 56.38 441 | 75.80 275 | 86.84 283 | 58.67 247 | 91.40 287 | 61.58 334 | 85.75 218 | 90.34 251 |
|
| æ–°å‡ ä½•1 | | | | | 83.42 192 | 93.13 60 | 70.71 80 | | 85.48 327 | 57.43 436 | 81.80 150 | 91.98 120 | 63.28 174 | 92.27 246 | 64.60 300 | 92.99 76 | 87.27 358 |
|
| DP-MVS | | | 76.78 287 | 74.57 306 | 83.42 192 | 93.29 52 | 69.46 104 | 88.55 149 | 83.70 350 | 63.98 373 | 70.20 362 | 88.89 226 | 54.01 292 | 94.80 111 | 46.66 439 | 81.88 281 | 86.01 388 |
|
| MVS_Test | | | 83.15 129 | 83.06 121 | 83.41 194 | 86.86 264 | 63.21 287 | 86.11 248 | 92.00 113 | 74.31 158 | 82.87 132 | 89.44 212 | 70.03 87 | 93.21 197 | 77.39 161 | 88.50 158 | 93.81 94 |
|
| LS3D | | | 76.95 284 | 74.82 303 | 83.37 195 | 90.45 107 | 67.36 172 | 89.15 120 | 86.94 301 | 61.87 398 | 69.52 374 | 90.61 174 | 51.71 323 | 94.53 122 | 46.38 442 | 86.71 197 | 88.21 333 |
|
| IB-MVS | | 68.01 15 | 75.85 305 | 73.36 325 | 83.31 196 | 84.76 321 | 66.03 197 | 83.38 325 | 85.06 332 | 70.21 264 | 69.40 375 | 81.05 403 | 45.76 388 | 94.66 118 | 65.10 296 | 75.49 365 | 89.25 296 |
| 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 |
| MG-MVS | | | 83.41 121 | 83.45 114 | 83.28 197 | 92.74 71 | 62.28 308 | 88.17 164 | 89.50 208 | 75.22 128 | 81.49 156 | 92.74 103 | 66.75 136 | 95.11 94 | 72.85 216 | 91.58 101 | 92.45 170 |
|
| jajsoiax | | | 79.29 225 | 77.96 233 | 83.27 198 | 84.68 323 | 66.57 190 | 89.25 113 | 90.16 185 | 69.20 291 | 75.46 282 | 89.49 206 | 45.75 389 | 93.13 206 | 76.84 169 | 80.80 293 | 90.11 262 |
|
| test_djsdf | | | 80.30 202 | 79.32 203 | 83.27 198 | 83.98 338 | 65.37 219 | 90.50 72 | 90.38 174 | 68.55 306 | 76.19 267 | 88.70 230 | 56.44 270 | 93.46 184 | 78.98 141 | 80.14 303 | 90.97 224 |
|
| test_yl | | | 81.17 169 | 80.47 170 | 83.24 200 | 89.13 156 | 63.62 270 | 86.21 245 | 89.95 191 | 72.43 207 | 81.78 151 | 89.61 202 | 57.50 258 | 93.58 166 | 70.75 239 | 86.90 192 | 92.52 164 |
|
| DCV-MVSNet | | | 81.17 169 | 80.47 170 | 83.24 200 | 89.13 156 | 63.62 270 | 86.21 245 | 89.95 191 | 72.43 207 | 81.78 151 | 89.61 202 | 57.50 258 | 93.58 166 | 70.75 239 | 86.90 192 | 92.52 164 |
|
| mvs_tets | | | 79.13 229 | 77.77 243 | 83.22 202 | 84.70 322 | 66.37 192 | 89.17 116 | 90.19 184 | 69.38 283 | 75.40 285 | 89.46 209 | 44.17 401 | 93.15 204 | 76.78 173 | 80.70 295 | 90.14 259 |
|
| thisisatest0515 | | | 77.33 277 | 75.38 294 | 83.18 203 | 85.27 308 | 63.80 267 | 82.11 346 | 83.27 358 | 65.06 355 | 75.91 272 | 83.84 361 | 49.54 350 | 94.27 131 | 67.24 278 | 86.19 206 | 91.48 208 |
|
| CDS-MVSNet | | | 79.07 231 | 77.70 246 | 83.17 204 | 87.60 231 | 68.23 141 | 84.40 301 | 86.20 317 | 67.49 319 | 76.36 263 | 86.54 299 | 61.54 209 | 90.79 311 | 61.86 331 | 87.33 184 | 90.49 245 |
| Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
| v7n | | | 78.97 234 | 77.58 250 | 83.14 205 | 83.45 352 | 65.51 214 | 88.32 159 | 91.21 147 | 73.69 175 | 72.41 340 | 86.32 305 | 57.93 252 | 93.81 157 | 69.18 259 | 75.65 362 | 90.11 262 |
|
| BH-RMVSNet | | | 79.61 212 | 78.44 222 | 83.14 205 | 89.38 143 | 65.93 202 | 84.95 281 | 87.15 296 | 73.56 179 | 78.19 217 | 89.79 196 | 56.67 268 | 93.36 188 | 59.53 351 | 86.74 196 | 90.13 260 |
|
| fmvsm_s_conf0.5_n_3 | | | 86.36 53 | 87.46 32 | 83.09 207 | 87.08 260 | 65.21 225 | 89.09 123 | 90.21 183 | 79.67 19 | 89.98 24 | 95.02 24 | 73.17 42 | 91.71 269 | 91.30 3 | 91.60 99 | 92.34 173 |
|
| UniMVSNet (Re) | | | 81.60 160 | 81.11 156 | 83.09 207 | 88.38 188 | 64.41 255 | 87.60 183 | 93.02 50 | 78.42 37 | 78.56 207 | 88.16 248 | 69.78 91 | 93.26 193 | 69.58 256 | 76.49 348 | 91.60 201 |
|
| PLC |  | 70.83 11 | 78.05 258 | 76.37 280 | 83.08 209 | 91.88 83 | 67.80 156 | 88.19 163 | 89.46 209 | 64.33 366 | 69.87 371 | 88.38 241 | 53.66 294 | 93.58 166 | 58.86 359 | 82.73 270 | 87.86 339 |
| Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
| v1192 | | | 79.59 214 | 78.43 223 | 83.07 210 | 83.55 350 | 64.52 249 | 86.93 213 | 90.58 167 | 70.83 242 | 77.78 228 | 85.90 311 | 59.15 243 | 93.94 147 | 73.96 204 | 77.19 338 | 90.76 232 |
|
| v2v482 | | | 80.23 203 | 79.29 204 | 83.05 211 | 83.62 348 | 64.14 259 | 87.04 206 | 89.97 190 | 73.61 177 | 78.18 218 | 87.22 275 | 61.10 221 | 93.82 156 | 76.11 178 | 76.78 345 | 91.18 215 |
|
| TAMVS | | | 78.89 237 | 77.51 253 | 83.03 212 | 87.80 215 | 67.79 157 | 84.72 285 | 85.05 333 | 67.63 316 | 76.75 252 | 87.70 260 | 62.25 196 | 90.82 310 | 58.53 363 | 87.13 189 | 90.49 245 |
|
| v1144 | | | 80.03 207 | 79.03 210 | 83.01 213 | 83.78 343 | 64.51 250 | 87.11 205 | 90.57 169 | 71.96 215 | 78.08 221 | 86.20 307 | 61.41 213 | 93.94 147 | 74.93 194 | 77.23 336 | 90.60 240 |
|
| viewdifsd2359ckpt07 | | | 82.83 137 | 82.78 129 | 82.99 214 | 86.51 277 | 62.58 299 | 85.09 277 | 90.83 161 | 75.22 128 | 82.28 140 | 91.63 135 | 69.43 96 | 92.03 253 | 77.71 156 | 86.32 202 | 94.34 64 |
|
| cascas | | | 76.72 288 | 74.64 305 | 82.99 214 | 85.78 293 | 65.88 204 | 82.33 342 | 89.21 227 | 60.85 404 | 72.74 334 | 81.02 404 | 47.28 368 | 93.75 162 | 67.48 275 | 85.02 226 | 89.34 294 |
|
| anonymousdsp | | | 78.60 243 | 77.15 259 | 82.98 216 | 80.51 409 | 67.08 181 | 87.24 202 | 89.53 207 | 65.66 344 | 75.16 297 | 87.19 277 | 52.52 302 | 92.25 247 | 77.17 163 | 79.34 313 | 89.61 286 |
|
| v10 | | | 79.74 211 | 78.67 216 | 82.97 217 | 84.06 336 | 64.95 235 | 87.88 177 | 90.62 166 | 73.11 195 | 75.11 299 | 86.56 298 | 61.46 212 | 94.05 143 | 73.68 205 | 75.55 364 | 89.90 276 |
|
| UniMVSNet_NR-MVSNet | | | 81.88 152 | 81.54 151 | 82.92 218 | 88.46 184 | 63.46 281 | 87.13 203 | 92.37 86 | 80.19 12 | 78.38 212 | 89.14 215 | 71.66 64 | 93.05 211 | 70.05 249 | 76.46 349 | 92.25 178 |
|
| DU-MVS | | | 81.12 172 | 80.52 168 | 82.90 219 | 87.80 215 | 63.46 281 | 87.02 208 | 91.87 121 | 79.01 31 | 78.38 212 | 89.07 217 | 65.02 160 | 93.05 211 | 70.05 249 | 76.46 349 | 92.20 181 |
|
| PVSNet_Blended | | | 80.98 173 | 80.34 172 | 82.90 219 | 88.85 163 | 65.40 216 | 84.43 298 | 92.00 113 | 67.62 317 | 78.11 219 | 85.05 336 | 66.02 151 | 94.27 131 | 71.52 231 | 89.50 138 | 89.01 304 |
|
| IMVS_0403 | | | 80.80 181 | 80.12 180 | 82.87 221 | 87.13 254 | 63.59 274 | 85.19 271 | 89.33 214 | 70.51 252 | 78.49 209 | 89.03 219 | 63.26 176 | 93.27 192 | 72.56 222 | 85.56 220 | 91.74 196 |
|
| CANet_DTU | | | 80.61 188 | 79.87 186 | 82.83 222 | 85.60 298 | 63.17 290 | 87.36 197 | 88.65 256 | 76.37 95 | 75.88 273 | 88.44 240 | 53.51 296 | 93.07 209 | 73.30 211 | 89.74 134 | 92.25 178 |
|
| V42 | | | 79.38 223 | 78.24 228 | 82.83 222 | 81.10 403 | 65.50 215 | 85.55 264 | 89.82 194 | 71.57 223 | 78.21 216 | 86.12 309 | 60.66 229 | 93.18 203 | 75.64 185 | 75.46 368 | 89.81 281 |
|
| Anonymous20231211 | | | 78.97 234 | 77.69 247 | 82.81 224 | 90.54 106 | 64.29 257 | 90.11 83 | 91.51 139 | 65.01 357 | 76.16 271 | 88.13 253 | 50.56 337 | 93.03 214 | 69.68 255 | 77.56 335 | 91.11 217 |
|
| AstraMVS | | | 80.81 178 | 80.14 179 | 82.80 225 | 86.05 289 | 63.96 262 | 86.46 233 | 85.90 322 | 73.71 174 | 80.85 170 | 90.56 175 | 54.06 291 | 91.57 274 | 79.72 131 | 83.97 245 | 92.86 152 |
|
| v1921920 | | | 79.22 226 | 78.03 232 | 82.80 225 | 83.30 355 | 63.94 264 | 86.80 218 | 90.33 178 | 69.91 271 | 77.48 233 | 85.53 322 | 58.44 249 | 93.75 162 | 73.60 206 | 76.85 343 | 90.71 236 |
|
| v8 | | | 79.97 209 | 79.02 211 | 82.80 225 | 84.09 335 | 64.50 252 | 87.96 171 | 90.29 181 | 74.13 165 | 75.24 295 | 86.81 284 | 62.88 187 | 93.89 155 | 74.39 200 | 75.40 371 | 90.00 270 |
|
| TAPA-MVS | | 73.13 9 | 79.15 228 | 77.94 234 | 82.79 228 | 89.59 130 | 62.99 295 | 88.16 165 | 91.51 139 | 65.77 342 | 77.14 246 | 91.09 157 | 60.91 224 | 93.21 197 | 50.26 420 | 87.05 190 | 92.17 186 |
| Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
| v144192 | | | 79.47 217 | 78.37 224 | 82.78 229 | 83.35 353 | 63.96 262 | 86.96 210 | 90.36 177 | 69.99 268 | 77.50 232 | 85.67 318 | 60.66 229 | 93.77 160 | 74.27 201 | 76.58 346 | 90.62 238 |
|
| NR-MVSNet | | | 80.23 203 | 79.38 200 | 82.78 229 | 87.80 215 | 63.34 284 | 86.31 240 | 91.09 153 | 79.01 31 | 72.17 344 | 89.07 217 | 67.20 132 | 92.81 223 | 66.08 288 | 75.65 362 | 92.20 181 |
|
| diffmvs |  | | 82.10 146 | 81.88 148 | 82.76 231 | 83.00 366 | 63.78 269 | 83.68 316 | 89.76 197 | 72.94 199 | 82.02 146 | 89.85 191 | 65.96 153 | 90.79 311 | 82.38 100 | 87.30 185 | 93.71 100 |
| Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025 |
| IMVS_0407 | | | 80.61 188 | 79.90 185 | 82.75 232 | 87.13 254 | 63.59 274 | 85.33 270 | 89.33 214 | 70.51 252 | 77.82 225 | 89.03 219 | 61.84 202 | 92.91 216 | 72.56 222 | 85.56 220 | 91.74 196 |
|
| diffmvs_AUTHOR | | | 82.38 143 | 82.27 139 | 82.73 233 | 83.26 356 | 63.80 267 | 83.89 311 | 89.76 197 | 73.35 187 | 82.37 139 | 90.84 166 | 66.25 145 | 90.79 311 | 82.77 93 | 87.93 173 | 93.59 111 |
|
| v1240 | | | 78.99 233 | 77.78 242 | 82.64 234 | 83.21 358 | 63.54 278 | 86.62 227 | 90.30 180 | 69.74 278 | 77.33 236 | 85.68 317 | 57.04 264 | 93.76 161 | 73.13 214 | 76.92 340 | 90.62 238 |
|
| Fast-Effi-MVS+-dtu | | | 78.02 259 | 76.49 275 | 82.62 235 | 83.16 362 | 66.96 185 | 86.94 212 | 87.45 285 | 72.45 204 | 71.49 352 | 84.17 356 | 54.79 283 | 91.58 272 | 67.61 273 | 80.31 300 | 89.30 295 |
|
| guyue | | | 81.13 171 | 80.64 165 | 82.60 236 | 86.52 276 | 63.92 265 | 86.69 224 | 87.73 278 | 73.97 166 | 80.83 171 | 89.69 198 | 56.70 267 | 91.33 290 | 78.26 153 | 85.40 224 | 92.54 163 |
|
| RPMNet | | | 73.51 334 | 70.49 362 | 82.58 237 | 81.32 401 | 65.19 226 | 75.92 424 | 92.27 93 | 57.60 434 | 72.73 335 | 76.45 446 | 52.30 306 | 95.43 77 | 48.14 434 | 77.71 331 | 87.11 365 |
|
| F-COLMAP | | | 76.38 298 | 74.33 312 | 82.50 238 | 89.28 149 | 66.95 186 | 88.41 153 | 89.03 235 | 64.05 371 | 66.83 407 | 88.61 234 | 46.78 374 | 92.89 217 | 57.48 372 | 78.55 318 | 87.67 342 |
|
| TranMVSNet+NR-MVSNet | | | 80.84 176 | 80.31 173 | 82.42 239 | 87.85 212 | 62.33 306 | 87.74 181 | 91.33 144 | 80.55 9 | 77.99 223 | 89.86 190 | 65.23 158 | 92.62 226 | 67.05 281 | 75.24 376 | 92.30 176 |
|
| MVSTER | | | 79.01 232 | 77.88 238 | 82.38 240 | 83.07 363 | 64.80 244 | 84.08 310 | 88.95 241 | 69.01 298 | 78.69 202 | 87.17 278 | 54.70 284 | 92.43 238 | 74.69 195 | 80.57 297 | 89.89 277 |
|
| PVSNet_BlendedMVS | | | 80.60 190 | 80.02 181 | 82.36 241 | 88.85 163 | 65.40 216 | 86.16 247 | 92.00 113 | 69.34 284 | 78.11 219 | 86.09 310 | 66.02 151 | 94.27 131 | 71.52 231 | 82.06 278 | 87.39 351 |
|
| viewdifsd2359ckpt11 | | | 80.37 199 | 79.73 190 | 82.30 242 | 83.70 346 | 62.39 303 | 84.20 305 | 86.67 306 | 73.22 193 | 80.90 167 | 90.62 172 | 63.00 185 | 91.56 275 | 76.81 171 | 78.44 321 | 92.95 149 |
|
| viewmsd2359difaftdt | | | 80.37 199 | 79.73 190 | 82.30 242 | 83.70 346 | 62.39 303 | 84.20 305 | 86.67 306 | 73.22 193 | 80.90 167 | 90.62 172 | 63.00 185 | 91.56 275 | 76.81 171 | 78.44 321 | 92.95 149 |
|
| viewmambaseed2359dif | | | 80.41 195 | 79.84 187 | 82.12 244 | 82.95 371 | 62.50 302 | 83.39 324 | 88.06 267 | 67.11 322 | 80.98 165 | 90.31 181 | 66.20 147 | 91.01 304 | 74.62 196 | 84.90 228 | 92.86 152 |
|
| EI-MVSNet | | | 80.52 194 | 79.98 182 | 82.12 244 | 84.28 330 | 63.19 289 | 86.41 234 | 88.95 241 | 74.18 163 | 78.69 202 | 87.54 267 | 66.62 138 | 92.43 238 | 72.57 220 | 80.57 297 | 90.74 234 |
|
| IterMVS-LS | | | 80.06 206 | 79.38 200 | 82.11 246 | 85.89 290 | 63.20 288 | 86.79 219 | 89.34 213 | 74.19 162 | 75.45 283 | 86.72 287 | 66.62 138 | 92.39 240 | 72.58 219 | 76.86 342 | 90.75 233 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
| BH-untuned | | | 79.47 217 | 78.60 218 | 82.05 247 | 89.19 154 | 65.91 203 | 86.07 249 | 88.52 259 | 72.18 210 | 75.42 284 | 87.69 261 | 61.15 220 | 93.54 173 | 60.38 343 | 86.83 195 | 86.70 375 |
|
| ACMH+ | | 68.96 14 | 76.01 303 | 74.01 314 | 82.03 248 | 88.60 179 | 65.31 224 | 88.86 130 | 87.55 281 | 70.25 263 | 67.75 394 | 87.47 269 | 41.27 420 | 93.19 202 | 58.37 365 | 75.94 359 | 87.60 344 |
|
| Anonymous202405211 | | | 78.25 250 | 77.01 261 | 81.99 249 | 91.03 94 | 60.67 335 | 84.77 284 | 83.90 348 | 70.65 250 | 80.00 182 | 91.20 153 | 41.08 422 | 91.43 286 | 65.21 294 | 85.26 225 | 93.85 90 |
|
| GA-MVS | | | 76.87 285 | 75.17 300 | 81.97 250 | 82.75 374 | 62.58 299 | 81.44 356 | 86.35 315 | 72.16 212 | 74.74 307 | 82.89 383 | 46.20 383 | 92.02 255 | 68.85 264 | 81.09 288 | 91.30 213 |
|
| CNLPA | | | 78.08 256 | 76.79 268 | 81.97 250 | 90.40 109 | 71.07 70 | 87.59 184 | 84.55 338 | 66.03 340 | 72.38 341 | 89.64 201 | 57.56 257 | 86.04 384 | 59.61 350 | 83.35 261 | 88.79 315 |
|
| MVS | | | 78.19 254 | 76.99 263 | 81.78 252 | 85.66 295 | 66.99 182 | 84.66 287 | 90.47 171 | 55.08 446 | 72.02 346 | 85.27 328 | 63.83 171 | 94.11 141 | 66.10 287 | 89.80 133 | 84.24 415 |
|
| ACMH | | 67.68 16 | 75.89 304 | 73.93 316 | 81.77 253 | 88.71 176 | 66.61 189 | 88.62 145 | 89.01 237 | 69.81 272 | 66.78 408 | 86.70 291 | 41.95 417 | 91.51 282 | 55.64 388 | 78.14 327 | 87.17 361 |
| Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
| UniMVSNet_ETH3D | | | 79.10 230 | 78.24 228 | 81.70 254 | 86.85 265 | 60.24 342 | 87.28 201 | 88.79 246 | 74.25 161 | 76.84 248 | 90.53 177 | 49.48 351 | 91.56 275 | 67.98 270 | 82.15 276 | 93.29 124 |
|
| VNet | | | 82.21 145 | 82.41 134 | 81.62 255 | 90.82 100 | 60.93 329 | 84.47 293 | 89.78 195 | 76.36 96 | 84.07 104 | 91.88 123 | 64.71 163 | 90.26 320 | 70.68 241 | 88.89 148 | 93.66 102 |
|
| XVG-ACMP-BASELINE | | | 76.11 301 | 74.27 313 | 81.62 255 | 83.20 359 | 64.67 246 | 83.60 320 | 89.75 199 | 69.75 276 | 71.85 347 | 87.09 280 | 32.78 453 | 92.11 251 | 69.99 251 | 80.43 299 | 88.09 335 |
|
| eth_miper_zixun_eth | | | 77.92 262 | 76.69 272 | 81.61 257 | 83.00 366 | 61.98 313 | 83.15 330 | 89.20 228 | 69.52 281 | 74.86 306 | 84.35 349 | 61.76 205 | 92.56 231 | 71.50 233 | 72.89 398 | 90.28 255 |
|
| PAPM | | | 77.68 270 | 76.40 279 | 81.51 258 | 87.29 250 | 61.85 315 | 83.78 313 | 89.59 205 | 64.74 359 | 71.23 354 | 88.70 230 | 62.59 189 | 93.66 165 | 52.66 404 | 87.03 191 | 89.01 304 |
|
| v148 | | | 78.72 240 | 77.80 241 | 81.47 259 | 82.73 375 | 61.96 314 | 86.30 241 | 88.08 265 | 73.26 190 | 76.18 268 | 85.47 324 | 62.46 192 | 92.36 242 | 71.92 230 | 73.82 390 | 90.09 264 |
|
| tt0805 | | | 78.73 239 | 77.83 239 | 81.43 260 | 85.17 309 | 60.30 341 | 89.41 107 | 90.90 157 | 71.21 231 | 77.17 245 | 88.73 229 | 46.38 378 | 93.21 197 | 72.57 220 | 78.96 316 | 90.79 230 |
|
| LTVRE_ROB | | 69.57 13 | 76.25 299 | 74.54 308 | 81.41 261 | 88.60 179 | 64.38 256 | 79.24 389 | 89.12 233 | 70.76 245 | 69.79 373 | 87.86 257 | 49.09 358 | 93.20 200 | 56.21 387 | 80.16 301 | 86.65 377 |
| 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 |
| GBi-Net | | | 78.40 247 | 77.40 254 | 81.40 262 | 87.60 231 | 63.01 291 | 88.39 154 | 89.28 220 | 71.63 219 | 75.34 288 | 87.28 271 | 54.80 280 | 91.11 297 | 62.72 317 | 79.57 307 | 90.09 264 |
|
| test1 | | | 78.40 247 | 77.40 254 | 81.40 262 | 87.60 231 | 63.01 291 | 88.39 154 | 89.28 220 | 71.63 219 | 75.34 288 | 87.28 271 | 54.80 280 | 91.11 297 | 62.72 317 | 79.57 307 | 90.09 264 |
|
| FMVSNet1 | | | 77.44 274 | 76.12 282 | 81.40 262 | 86.81 267 | 63.01 291 | 88.39 154 | 89.28 220 | 70.49 256 | 74.39 314 | 87.28 271 | 49.06 359 | 91.11 297 | 60.91 339 | 78.52 319 | 90.09 264 |
|
| baseline2 | | | 75.70 306 | 73.83 319 | 81.30 265 | 83.26 356 | 61.79 317 | 82.57 339 | 80.65 393 | 66.81 324 | 66.88 406 | 83.42 373 | 57.86 254 | 92.19 249 | 63.47 306 | 79.57 307 | 89.91 275 |
|
| fmvsm_s_conf0.5_n_7 | | | 83.34 124 | 84.03 100 | 81.28 266 | 85.73 294 | 65.13 228 | 85.40 269 | 89.90 193 | 74.96 140 | 82.13 144 | 93.89 69 | 66.65 137 | 87.92 363 | 86.56 53 | 91.05 109 | 90.80 229 |
|
| c3_l | | | 78.75 238 | 77.91 235 | 81.26 267 | 82.89 372 | 61.56 319 | 84.09 309 | 89.13 232 | 69.97 269 | 75.56 278 | 84.29 350 | 66.36 143 | 92.09 252 | 73.47 209 | 75.48 366 | 90.12 261 |
|
| cl22 | | | 78.07 257 | 77.01 261 | 81.23 268 | 82.37 384 | 61.83 316 | 83.55 321 | 87.98 269 | 68.96 300 | 75.06 301 | 83.87 359 | 61.40 214 | 91.88 262 | 73.53 207 | 76.39 351 | 89.98 273 |
|
| FMVSNet2 | | | 78.20 253 | 77.21 258 | 81.20 269 | 87.60 231 | 62.89 297 | 87.47 187 | 89.02 236 | 71.63 219 | 75.29 294 | 87.28 271 | 54.80 280 | 91.10 300 | 62.38 323 | 79.38 312 | 89.61 286 |
|
| TR-MVS | | | 77.44 274 | 76.18 281 | 81.20 269 | 88.24 192 | 63.24 286 | 84.61 290 | 86.40 313 | 67.55 318 | 77.81 227 | 86.48 301 | 54.10 289 | 93.15 204 | 57.75 371 | 82.72 271 | 87.20 360 |
|
| ab-mvs | | | 79.51 215 | 78.97 212 | 81.14 271 | 88.46 184 | 60.91 330 | 83.84 312 | 89.24 226 | 70.36 257 | 79.03 196 | 88.87 227 | 63.23 178 | 90.21 322 | 65.12 295 | 82.57 273 | 92.28 177 |
|
| MVP-Stereo | | | 76.12 300 | 74.46 310 | 81.13 272 | 85.37 305 | 69.79 95 | 84.42 300 | 87.95 271 | 65.03 356 | 67.46 398 | 85.33 327 | 53.28 299 | 91.73 268 | 58.01 369 | 83.27 263 | 81.85 442 |
| Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
| miper_ehance_all_eth | | | 78.59 244 | 77.76 244 | 81.08 273 | 82.66 377 | 61.56 319 | 83.65 317 | 89.15 230 | 68.87 301 | 75.55 279 | 83.79 363 | 66.49 141 | 92.03 253 | 73.25 212 | 76.39 351 | 89.64 285 |
|
| FIs | | | 82.07 148 | 82.42 133 | 81.04 274 | 88.80 171 | 58.34 359 | 88.26 161 | 93.49 31 | 76.93 72 | 78.47 211 | 91.04 159 | 69.92 89 | 92.34 244 | 69.87 253 | 84.97 227 | 92.44 171 |
|
| SDMVSNet | | | 80.38 197 | 80.18 176 | 80.99 275 | 89.03 161 | 64.94 238 | 80.45 373 | 89.40 211 | 75.19 132 | 76.61 257 | 89.98 188 | 60.61 231 | 87.69 367 | 76.83 170 | 83.55 256 | 90.33 252 |
|
| patch_mono-2 | | | 83.65 113 | 84.54 89 | 80.99 275 | 90.06 120 | 65.83 205 | 84.21 304 | 88.74 252 | 71.60 222 | 85.01 79 | 92.44 105 | 74.51 29 | 83.50 409 | 82.15 101 | 92.15 90 | 93.64 108 |
|
| FMVSNet3 | | | 77.88 263 | 76.85 266 | 80.97 277 | 86.84 266 | 62.36 305 | 86.52 231 | 88.77 247 | 71.13 232 | 75.34 288 | 86.66 293 | 54.07 290 | 91.10 300 | 62.72 317 | 79.57 307 | 89.45 290 |
|
| miper_enhance_ethall | | | 77.87 264 | 76.86 265 | 80.92 278 | 81.65 391 | 61.38 323 | 82.68 337 | 88.98 238 | 65.52 346 | 75.47 280 | 82.30 392 | 65.76 155 | 92.00 256 | 72.95 215 | 76.39 351 | 89.39 292 |
|
| BH-w/o | | | 78.21 252 | 77.33 257 | 80.84 279 | 88.81 167 | 65.13 228 | 84.87 282 | 87.85 275 | 69.75 276 | 74.52 312 | 84.74 342 | 61.34 215 | 93.11 207 | 58.24 367 | 85.84 216 | 84.27 414 |
|
| COLMAP_ROB |  | 66.92 17 | 73.01 347 | 70.41 364 | 80.81 280 | 87.13 254 | 65.63 211 | 88.30 160 | 84.19 345 | 62.96 383 | 63.80 436 | 87.69 261 | 38.04 439 | 92.56 231 | 46.66 439 | 74.91 379 | 84.24 415 |
| Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
| VPA-MVSNet | | | 80.60 190 | 80.55 167 | 80.76 281 | 88.07 202 | 60.80 332 | 86.86 216 | 91.58 137 | 75.67 115 | 80.24 179 | 89.45 211 | 63.34 173 | 90.25 321 | 70.51 243 | 79.22 315 | 91.23 214 |
|
| EG-PatchMatch MVS | | | 74.04 327 | 71.82 341 | 80.71 282 | 84.92 317 | 67.42 168 | 85.86 255 | 88.08 265 | 66.04 339 | 64.22 431 | 83.85 360 | 35.10 449 | 92.56 231 | 57.44 373 | 80.83 292 | 82.16 440 |
|
| ECVR-MVS |  | | 79.61 212 | 79.26 205 | 80.67 283 | 90.08 116 | 54.69 414 | 87.89 176 | 77.44 428 | 74.88 143 | 80.27 178 | 92.79 100 | 48.96 361 | 92.45 237 | 68.55 266 | 92.50 84 | 94.86 19 |
|
| VortexMVS | | | 78.57 245 | 77.89 237 | 80.59 284 | 85.89 290 | 62.76 298 | 85.61 259 | 89.62 204 | 72.06 213 | 74.99 303 | 85.38 326 | 55.94 273 | 90.77 314 | 74.99 193 | 76.58 346 | 88.23 331 |
|
| cl____ | | | 77.72 267 | 76.76 269 | 80.58 285 | 82.49 381 | 60.48 338 | 83.09 332 | 87.87 273 | 69.22 289 | 74.38 315 | 85.22 331 | 62.10 199 | 91.53 280 | 71.09 236 | 75.41 370 | 89.73 284 |
|
| DIV-MVS_self_test | | | 77.72 267 | 76.76 269 | 80.58 285 | 82.48 382 | 60.48 338 | 83.09 332 | 87.86 274 | 69.22 289 | 74.38 315 | 85.24 329 | 62.10 199 | 91.53 280 | 71.09 236 | 75.40 371 | 89.74 283 |
|
| MSDG | | | 73.36 340 | 70.99 355 | 80.49 287 | 84.51 328 | 65.80 207 | 80.71 368 | 86.13 319 | 65.70 343 | 65.46 421 | 83.74 364 | 44.60 396 | 90.91 309 | 51.13 413 | 76.89 341 | 84.74 410 |
|
| pmmvs4 | | | 74.03 329 | 71.91 340 | 80.39 288 | 81.96 387 | 68.32 135 | 81.45 355 | 82.14 376 | 59.32 417 | 69.87 371 | 85.13 333 | 52.40 305 | 88.13 361 | 60.21 345 | 74.74 381 | 84.73 411 |
|
| HY-MVS | | 69.67 12 | 77.95 261 | 77.15 259 | 80.36 289 | 87.57 240 | 60.21 343 | 83.37 326 | 87.78 277 | 66.11 337 | 75.37 287 | 87.06 282 | 63.27 175 | 90.48 318 | 61.38 336 | 82.43 274 | 90.40 249 |
|
| mvs_anonymous | | | 79.42 220 | 79.11 209 | 80.34 290 | 84.45 329 | 57.97 365 | 82.59 338 | 87.62 280 | 67.40 321 | 76.17 270 | 88.56 237 | 68.47 116 | 89.59 333 | 70.65 242 | 86.05 209 | 93.47 117 |
|
| 1112_ss | | | 77.40 276 | 76.43 277 | 80.32 291 | 89.11 160 | 60.41 340 | 83.65 317 | 87.72 279 | 62.13 395 | 73.05 330 | 86.72 287 | 62.58 190 | 89.97 326 | 62.11 329 | 80.80 293 | 90.59 241 |
|
| WR-MVS | | | 79.49 216 | 79.22 207 | 80.27 292 | 88.79 172 | 58.35 358 | 85.06 278 | 88.61 258 | 78.56 35 | 77.65 230 | 88.34 242 | 63.81 172 | 90.66 316 | 64.98 297 | 77.22 337 | 91.80 195 |
|
| usedtu_blend_shiyan5 | | | 73.29 342 | 70.96 356 | 80.25 293 | 77.80 437 | 62.16 310 | 84.44 297 | 87.38 286 | 64.41 363 | 68.09 390 | 76.28 449 | 51.32 326 | 91.23 293 | 63.21 312 | 65.76 433 | 87.35 353 |
|
| sc_t1 | | | 72.19 359 | 69.51 370 | 80.23 294 | 84.81 319 | 61.09 326 | 84.68 286 | 80.22 404 | 60.70 405 | 71.27 353 | 83.58 370 | 36.59 444 | 89.24 340 | 60.41 342 | 63.31 444 | 90.37 250 |
|
| blend_shiyan4 | | | 72.29 357 | 69.65 369 | 80.21 295 | 78.24 435 | 62.16 310 | 82.29 343 | 87.27 291 | 65.41 349 | 68.43 389 | 76.42 448 | 39.91 428 | 91.23 293 | 63.21 312 | 65.66 437 | 87.22 359 |
|
| 1314 | | | 76.53 290 | 75.30 298 | 80.21 295 | 83.93 339 | 62.32 307 | 84.66 287 | 88.81 245 | 60.23 409 | 70.16 365 | 84.07 358 | 55.30 277 | 90.73 315 | 67.37 276 | 83.21 264 | 87.59 346 |
|
| test1111 | | | 79.43 219 | 79.18 208 | 80.15 297 | 89.99 121 | 53.31 427 | 87.33 199 | 77.05 432 | 75.04 136 | 80.23 180 | 92.77 102 | 48.97 360 | 92.33 245 | 68.87 263 | 92.40 86 | 94.81 22 |
|
| IterMVS-SCA-FT | | | 75.43 311 | 73.87 318 | 80.11 298 | 82.69 376 | 64.85 243 | 81.57 353 | 83.47 355 | 69.16 292 | 70.49 359 | 84.15 357 | 51.95 315 | 88.15 360 | 69.23 258 | 72.14 404 | 87.34 355 |
|
| FC-MVSNet-test | | | 81.52 164 | 82.02 145 | 80.03 299 | 88.42 187 | 55.97 399 | 87.95 172 | 93.42 34 | 77.10 68 | 77.38 235 | 90.98 165 | 69.96 88 | 91.79 264 | 68.46 268 | 84.50 234 | 92.33 174 |
|
| blended_shiyan8 | | | 73.38 336 | 71.17 352 | 80.02 300 | 78.36 432 | 61.51 321 | 82.43 340 | 87.28 288 | 65.40 350 | 68.61 383 | 77.53 441 | 51.91 318 | 91.00 307 | 63.28 310 | 65.76 433 | 87.53 348 |
|
| blended_shiyan6 | | | 73.38 336 | 71.17 352 | 80.01 301 | 78.36 432 | 61.48 322 | 82.43 340 | 87.27 291 | 65.40 350 | 68.56 385 | 77.55 440 | 51.94 317 | 91.01 304 | 63.27 311 | 65.76 433 | 87.55 347 |
|
| testdata | | | | | 79.97 302 | 90.90 98 | 64.21 258 | | 84.71 335 | 59.27 418 | 85.40 75 | 92.91 94 | 62.02 201 | 89.08 344 | 68.95 262 | 91.37 105 | 86.63 378 |
|
| SCA | | | 74.22 324 | 72.33 337 | 79.91 303 | 84.05 337 | 62.17 309 | 79.96 382 | 79.29 414 | 66.30 336 | 72.38 341 | 80.13 416 | 51.95 315 | 88.60 354 | 59.25 354 | 77.67 334 | 88.96 308 |
|
| thres400 | | | 76.50 291 | 75.37 295 | 79.86 304 | 89.13 156 | 57.65 373 | 85.17 272 | 83.60 351 | 73.41 185 | 76.45 260 | 86.39 303 | 52.12 309 | 91.95 258 | 48.33 430 | 83.75 250 | 90.00 270 |
|
| test_0402 | | | 72.79 352 | 70.44 363 | 79.84 305 | 88.13 198 | 65.99 201 | 85.93 252 | 84.29 342 | 65.57 345 | 67.40 401 | 85.49 323 | 46.92 371 | 92.61 227 | 35.88 468 | 74.38 384 | 80.94 447 |
|
| OurMVSNet-221017-0 | | | 74.26 323 | 72.42 336 | 79.80 306 | 83.76 344 | 59.59 349 | 85.92 253 | 86.64 308 | 66.39 335 | 66.96 405 | 87.58 263 | 39.46 429 | 91.60 271 | 65.76 291 | 69.27 418 | 88.22 332 |
|
| FE-blended-shiyan7 | | | 72.94 349 | 70.66 359 | 79.79 307 | 77.80 437 | 61.03 328 | 81.31 358 | 87.15 296 | 65.18 353 | 68.09 390 | 76.28 449 | 51.32 326 | 90.97 308 | 63.06 314 | 65.76 433 | 87.35 353 |
|
| FE-MVSNET3 | | | 76.43 295 | 75.32 297 | 79.76 308 | 83.00 366 | 60.72 333 | 81.74 349 | 88.76 251 | 68.99 299 | 72.98 331 | 84.19 355 | 56.41 271 | 90.27 319 | 62.39 322 | 79.40 311 | 88.31 329 |
|
| test2506 | | | 77.30 278 | 76.49 275 | 79.74 309 | 90.08 116 | 52.02 432 | 87.86 178 | 63.10 475 | 74.88 143 | 80.16 181 | 92.79 100 | 38.29 438 | 92.35 243 | 68.74 265 | 92.50 84 | 94.86 19 |
|
| SixPastTwentyTwo | | | 73.37 338 | 71.26 351 | 79.70 310 | 85.08 314 | 57.89 367 | 85.57 260 | 83.56 353 | 71.03 238 | 65.66 420 | 85.88 312 | 42.10 415 | 92.57 230 | 59.11 356 | 63.34 443 | 88.65 321 |
|
| thres600view7 | | | 76.50 291 | 75.44 291 | 79.68 311 | 89.40 141 | 57.16 379 | 85.53 266 | 83.23 359 | 73.79 172 | 76.26 265 | 87.09 280 | 51.89 319 | 91.89 261 | 48.05 435 | 83.72 253 | 90.00 270 |
|
| CR-MVSNet | | | 73.37 338 | 71.27 350 | 79.67 312 | 81.32 401 | 65.19 226 | 75.92 424 | 80.30 402 | 59.92 412 | 72.73 335 | 81.19 401 | 52.50 303 | 86.69 375 | 59.84 347 | 77.71 331 | 87.11 365 |
|
| D2MVS | | | 74.82 318 | 73.21 326 | 79.64 313 | 79.81 418 | 62.56 301 | 80.34 375 | 87.35 287 | 64.37 365 | 68.86 380 | 82.66 387 | 46.37 379 | 90.10 323 | 67.91 271 | 81.24 286 | 86.25 381 |
|
| AllTest | | | 70.96 368 | 68.09 383 | 79.58 314 | 85.15 311 | 63.62 270 | 84.58 291 | 79.83 407 | 62.31 392 | 60.32 449 | 86.73 285 | 32.02 454 | 88.96 348 | 50.28 418 | 71.57 408 | 86.15 384 |
|
| TestCases | | | | | 79.58 314 | 85.15 311 | 63.62 270 | | 79.83 407 | 62.31 392 | 60.32 449 | 86.73 285 | 32.02 454 | 88.96 348 | 50.28 418 | 71.57 408 | 86.15 384 |
|
| tfpn200view9 | | | 76.42 296 | 75.37 295 | 79.55 316 | 89.13 156 | 57.65 373 | 85.17 272 | 83.60 351 | 73.41 185 | 76.45 260 | 86.39 303 | 52.12 309 | 91.95 258 | 48.33 430 | 83.75 250 | 89.07 297 |
|
| IMVS_0404 | | | 77.16 280 | 76.42 278 | 79.37 317 | 87.13 254 | 63.59 274 | 77.12 418 | 89.33 214 | 70.51 252 | 66.22 418 | 89.03 219 | 50.36 340 | 82.78 414 | 72.56 222 | 85.56 220 | 91.74 196 |
|
| thres100view900 | | | 76.50 291 | 75.55 290 | 79.33 318 | 89.52 133 | 56.99 382 | 85.83 257 | 83.23 359 | 73.94 168 | 76.32 264 | 87.12 279 | 51.89 319 | 91.95 258 | 48.33 430 | 83.75 250 | 89.07 297 |
|
| CostFormer | | | 75.24 315 | 73.90 317 | 79.27 319 | 82.65 378 | 58.27 360 | 80.80 363 | 82.73 372 | 61.57 399 | 75.33 292 | 83.13 378 | 55.52 275 | 91.07 303 | 64.98 297 | 78.34 326 | 88.45 326 |
|
| Test_1112_low_res | | | 76.40 297 | 75.44 291 | 79.27 319 | 89.28 149 | 58.09 361 | 81.69 351 | 87.07 298 | 59.53 416 | 72.48 339 | 86.67 292 | 61.30 216 | 89.33 337 | 60.81 341 | 80.15 302 | 90.41 248 |
|
| K. test v3 | | | 71.19 365 | 68.51 377 | 79.21 321 | 83.04 365 | 57.78 371 | 84.35 302 | 76.91 433 | 72.90 200 | 62.99 439 | 82.86 384 | 39.27 430 | 91.09 302 | 61.65 333 | 52.66 466 | 88.75 317 |
|
| testing91 | | | 76.54 289 | 75.66 288 | 79.18 322 | 88.43 186 | 55.89 400 | 81.08 360 | 83.00 366 | 73.76 173 | 75.34 288 | 84.29 350 | 46.20 383 | 90.07 324 | 64.33 301 | 84.50 234 | 91.58 203 |
|
| testing99 | | | 76.09 302 | 75.12 301 | 79.00 323 | 88.16 195 | 55.50 406 | 80.79 364 | 81.40 386 | 73.30 189 | 75.17 296 | 84.27 353 | 44.48 398 | 90.02 325 | 64.28 302 | 84.22 243 | 91.48 208 |
|
| lessismore_v0 | | | | | 78.97 324 | 81.01 404 | 57.15 380 | | 65.99 468 | | 61.16 445 | 82.82 385 | 39.12 432 | 91.34 289 | 59.67 349 | 46.92 473 | 88.43 327 |
|
| pm-mvs1 | | | 77.25 279 | 76.68 273 | 78.93 325 | 84.22 332 | 58.62 356 | 86.41 234 | 88.36 261 | 71.37 226 | 73.31 326 | 88.01 254 | 61.22 219 | 89.15 343 | 64.24 303 | 73.01 397 | 89.03 303 |
|
| icg_test_0407_2 | | | 78.92 236 | 78.93 213 | 78.90 326 | 87.13 254 | 63.59 274 | 76.58 420 | 89.33 214 | 70.51 252 | 77.82 225 | 89.03 219 | 61.84 202 | 81.38 424 | 72.56 222 | 85.56 220 | 91.74 196 |
|
| thres200 | | | 75.55 308 | 74.47 309 | 78.82 327 | 87.78 218 | 57.85 368 | 83.07 334 | 83.51 354 | 72.44 206 | 75.84 274 | 84.42 345 | 52.08 312 | 91.75 266 | 47.41 437 | 83.64 255 | 86.86 371 |
|
| VPNet | | | 78.69 241 | 78.66 217 | 78.76 328 | 88.31 190 | 55.72 403 | 84.45 296 | 86.63 309 | 76.79 76 | 78.26 215 | 90.55 176 | 59.30 242 | 89.70 332 | 66.63 283 | 77.05 339 | 90.88 227 |
|
| tpm2 | | | 73.26 343 | 71.46 345 | 78.63 329 | 83.34 354 | 56.71 387 | 80.65 369 | 80.40 401 | 56.63 440 | 73.55 324 | 82.02 397 | 51.80 321 | 91.24 292 | 56.35 386 | 78.42 324 | 87.95 336 |
|
| pmmvs6 | | | 74.69 319 | 73.39 323 | 78.61 330 | 81.38 398 | 57.48 376 | 86.64 226 | 87.95 271 | 64.99 358 | 70.18 363 | 86.61 294 | 50.43 339 | 89.52 334 | 62.12 328 | 70.18 415 | 88.83 313 |
|
| sd_testset | | | 77.70 269 | 77.40 254 | 78.60 331 | 89.03 161 | 60.02 344 | 79.00 394 | 85.83 323 | 75.19 132 | 76.61 257 | 89.98 188 | 54.81 279 | 85.46 392 | 62.63 321 | 83.55 256 | 90.33 252 |
|
| MonoMVSNet | | | 76.49 294 | 75.80 283 | 78.58 332 | 81.55 394 | 58.45 357 | 86.36 239 | 86.22 316 | 74.87 145 | 74.73 308 | 83.73 365 | 51.79 322 | 88.73 351 | 70.78 238 | 72.15 403 | 88.55 325 |
|
| WR-MVS_H | | | 78.51 246 | 78.49 220 | 78.56 333 | 88.02 204 | 56.38 393 | 88.43 151 | 92.67 72 | 77.14 65 | 73.89 319 | 87.55 266 | 66.25 145 | 89.24 340 | 58.92 358 | 73.55 392 | 90.06 268 |
|
| RPSCF | | | 73.23 344 | 71.46 345 | 78.54 334 | 82.50 380 | 59.85 345 | 82.18 345 | 82.84 371 | 58.96 421 | 71.15 356 | 89.41 213 | 45.48 393 | 84.77 399 | 58.82 360 | 71.83 406 | 91.02 223 |
|
| testing11 | | | 75.14 316 | 74.01 314 | 78.53 335 | 88.16 195 | 56.38 393 | 80.74 367 | 80.42 400 | 70.67 246 | 72.69 337 | 83.72 366 | 43.61 405 | 89.86 327 | 62.29 325 | 83.76 249 | 89.36 293 |
|
| pmmvs-eth3d | | | 70.50 375 | 67.83 389 | 78.52 336 | 77.37 441 | 66.18 195 | 81.82 347 | 81.51 384 | 58.90 422 | 63.90 435 | 80.42 411 | 42.69 410 | 86.28 381 | 58.56 362 | 65.30 439 | 83.11 429 |
|
| PatchmatchNet |  | | 73.12 345 | 71.33 348 | 78.49 337 | 83.18 360 | 60.85 331 | 79.63 384 | 78.57 419 | 64.13 367 | 71.73 348 | 79.81 421 | 51.20 330 | 85.97 385 | 57.40 374 | 76.36 356 | 88.66 320 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
| reproduce_monomvs | | | 75.40 313 | 74.38 311 | 78.46 338 | 83.92 340 | 57.80 370 | 83.78 313 | 86.94 301 | 73.47 183 | 72.25 343 | 84.47 344 | 38.74 434 | 89.27 339 | 75.32 191 | 70.53 413 | 88.31 329 |
|
| IterMVS | | | 74.29 322 | 72.94 330 | 78.35 339 | 81.53 395 | 63.49 280 | 81.58 352 | 82.49 373 | 68.06 314 | 69.99 368 | 83.69 367 | 51.66 324 | 85.54 390 | 65.85 290 | 71.64 407 | 86.01 388 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
| ITE_SJBPF | | | | | 78.22 340 | 81.77 390 | 60.57 336 | | 83.30 357 | 69.25 288 | 67.54 396 | 87.20 276 | 36.33 446 | 87.28 372 | 54.34 395 | 74.62 382 | 86.80 372 |
|
| testing222 | | | 74.04 327 | 72.66 333 | 78.19 341 | 87.89 210 | 55.36 407 | 81.06 361 | 79.20 415 | 71.30 229 | 74.65 310 | 83.57 371 | 39.11 433 | 88.67 353 | 51.43 412 | 85.75 218 | 90.53 243 |
|
| ppachtmachnet_test | | | 70.04 381 | 67.34 399 | 78.14 342 | 79.80 419 | 61.13 324 | 79.19 391 | 80.59 394 | 59.16 419 | 65.27 423 | 79.29 425 | 46.75 375 | 87.29 371 | 49.33 425 | 66.72 427 | 86.00 390 |
|
| SSM_04072 | | | 77.67 271 | 77.52 251 | 78.12 343 | 88.81 167 | 67.96 149 | 65.03 473 | 88.66 254 | 70.96 240 | 79.48 189 | 89.80 194 | 58.69 245 | 74.23 465 | 70.35 245 | 85.93 213 | 92.18 183 |
|
| tfpnnormal | | | 74.39 321 | 73.16 327 | 78.08 344 | 86.10 288 | 58.05 362 | 84.65 289 | 87.53 282 | 70.32 260 | 71.22 355 | 85.63 319 | 54.97 278 | 89.86 327 | 43.03 454 | 75.02 378 | 86.32 380 |
|
| tt0320-xc | | | 70.11 380 | 67.45 397 | 78.07 345 | 85.33 306 | 59.51 351 | 83.28 327 | 78.96 417 | 58.77 423 | 67.10 404 | 80.28 414 | 36.73 443 | 87.42 370 | 56.83 382 | 59.77 455 | 87.29 357 |
|
| Vis-MVSNet (Re-imp) | | | 78.36 249 | 78.45 221 | 78.07 345 | 88.64 178 | 51.78 438 | 86.70 223 | 79.63 410 | 74.14 164 | 75.11 299 | 90.83 167 | 61.29 217 | 89.75 330 | 58.10 368 | 91.60 99 | 92.69 158 |
|
| tt0320 | | | 70.49 376 | 68.03 384 | 77.89 347 | 84.78 320 | 59.12 353 | 83.55 321 | 80.44 399 | 58.13 429 | 67.43 400 | 80.41 412 | 39.26 431 | 87.54 369 | 55.12 390 | 63.18 445 | 86.99 368 |
|
| TransMVSNet (Re) | | | 75.39 314 | 74.56 307 | 77.86 348 | 85.50 302 | 57.10 381 | 86.78 220 | 86.09 320 | 72.17 211 | 71.53 351 | 87.34 270 | 63.01 184 | 89.31 338 | 56.84 381 | 61.83 448 | 87.17 361 |
|
| PEN-MVS | | | 77.73 266 | 77.69 247 | 77.84 349 | 87.07 262 | 53.91 421 | 87.91 175 | 91.18 148 | 77.56 51 | 73.14 329 | 88.82 228 | 61.23 218 | 89.17 342 | 59.95 346 | 72.37 400 | 90.43 247 |
|
| CP-MVSNet | | | 78.22 251 | 78.34 225 | 77.84 349 | 87.83 214 | 54.54 416 | 87.94 173 | 91.17 149 | 77.65 46 | 73.48 325 | 88.49 238 | 62.24 197 | 88.43 357 | 62.19 326 | 74.07 385 | 90.55 242 |
|
| PS-CasMVS | | | 78.01 260 | 78.09 231 | 77.77 351 | 87.71 224 | 54.39 418 | 88.02 169 | 91.22 146 | 77.50 54 | 73.26 327 | 88.64 233 | 60.73 225 | 88.41 358 | 61.88 330 | 73.88 389 | 90.53 243 |
|
| FE-MVSNET2 | | | 72.88 351 | 71.28 349 | 77.67 352 | 78.30 434 | 57.78 371 | 84.43 298 | 88.92 243 | 69.56 279 | 64.61 428 | 81.67 399 | 46.73 376 | 88.54 356 | 59.33 352 | 67.99 424 | 86.69 376 |
|
| baseline1 | | | 76.98 283 | 76.75 271 | 77.66 353 | 88.13 198 | 55.66 404 | 85.12 275 | 81.89 379 | 73.04 197 | 76.79 250 | 88.90 225 | 62.43 193 | 87.78 366 | 63.30 309 | 71.18 410 | 89.55 288 |
|
| OpenMVS_ROB |  | 64.09 19 | 70.56 374 | 68.19 380 | 77.65 354 | 80.26 410 | 59.41 352 | 85.01 279 | 82.96 368 | 58.76 424 | 65.43 422 | 82.33 391 | 37.63 441 | 91.23 293 | 45.34 449 | 76.03 358 | 82.32 437 |
|
| Patchmatch-RL test | | | 70.24 378 | 67.78 391 | 77.61 355 | 77.43 440 | 59.57 350 | 71.16 448 | 70.33 455 | 62.94 384 | 68.65 382 | 72.77 461 | 50.62 336 | 85.49 391 | 69.58 256 | 66.58 429 | 87.77 341 |
|
| Baseline_NR-MVSNet | | | 78.15 255 | 78.33 226 | 77.61 355 | 85.79 292 | 56.21 397 | 86.78 220 | 85.76 324 | 73.60 178 | 77.93 224 | 87.57 264 | 65.02 160 | 88.99 345 | 67.14 280 | 75.33 373 | 87.63 343 |
|
| mmtdpeth | | | 74.16 325 | 73.01 329 | 77.60 357 | 83.72 345 | 61.13 324 | 85.10 276 | 85.10 331 | 72.06 213 | 77.21 244 | 80.33 413 | 43.84 403 | 85.75 386 | 77.14 164 | 52.61 467 | 85.91 391 |
|
| DTE-MVSNet | | | 76.99 282 | 76.80 267 | 77.54 358 | 86.24 281 | 53.06 430 | 87.52 185 | 90.66 165 | 77.08 69 | 72.50 338 | 88.67 232 | 60.48 233 | 89.52 334 | 57.33 375 | 70.74 412 | 90.05 269 |
|
| LCM-MVSNet-Re | | | 77.05 281 | 76.94 264 | 77.36 359 | 87.20 251 | 51.60 439 | 80.06 379 | 80.46 398 | 75.20 131 | 67.69 395 | 86.72 287 | 62.48 191 | 88.98 346 | 63.44 307 | 89.25 141 | 91.51 205 |
|
| tpm cat1 | | | 70.57 373 | 68.31 379 | 77.35 360 | 82.41 383 | 57.95 366 | 78.08 408 | 80.22 404 | 52.04 453 | 68.54 386 | 77.66 439 | 52.00 314 | 87.84 365 | 51.77 407 | 72.07 405 | 86.25 381 |
|
| MS-PatchMatch | | | 73.83 330 | 72.67 332 | 77.30 361 | 83.87 341 | 66.02 198 | 81.82 347 | 84.66 336 | 61.37 402 | 68.61 383 | 82.82 385 | 47.29 367 | 88.21 359 | 59.27 353 | 84.32 241 | 77.68 457 |
|
| EPNet_dtu | | | 75.46 310 | 74.86 302 | 77.23 362 | 82.57 379 | 54.60 415 | 86.89 214 | 83.09 363 | 71.64 218 | 66.25 417 | 85.86 313 | 55.99 272 | 88.04 362 | 54.92 392 | 86.55 199 | 89.05 302 |
| Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
| miper_lstm_enhance | | | 74.11 326 | 73.11 328 | 77.13 363 | 80.11 413 | 59.62 348 | 72.23 444 | 86.92 303 | 66.76 326 | 70.40 360 | 82.92 382 | 56.93 265 | 82.92 413 | 69.06 261 | 72.63 399 | 88.87 311 |
|
| TDRefinement | | | 67.49 400 | 64.34 412 | 76.92 364 | 73.47 461 | 61.07 327 | 84.86 283 | 82.98 367 | 59.77 413 | 58.30 456 | 85.13 333 | 26.06 464 | 87.89 364 | 47.92 436 | 60.59 453 | 81.81 443 |
|
| JIA-IIPM | | | 66.32 411 | 62.82 423 | 76.82 365 | 77.09 442 | 61.72 318 | 65.34 471 | 75.38 439 | 58.04 431 | 64.51 429 | 62.32 471 | 42.05 416 | 86.51 378 | 51.45 411 | 69.22 419 | 82.21 438 |
|
| PatchMatch-RL | | | 72.38 354 | 70.90 357 | 76.80 366 | 88.60 179 | 67.38 171 | 79.53 385 | 76.17 438 | 62.75 388 | 69.36 376 | 82.00 398 | 45.51 391 | 84.89 398 | 53.62 399 | 80.58 296 | 78.12 456 |
|
| tpmvs | | | 71.09 367 | 69.29 372 | 76.49 367 | 82.04 386 | 56.04 398 | 78.92 396 | 81.37 387 | 64.05 371 | 67.18 403 | 78.28 434 | 49.74 349 | 89.77 329 | 49.67 423 | 72.37 400 | 83.67 423 |
|
| CMPMVS |  | 51.72 21 | 70.19 379 | 68.16 381 | 76.28 368 | 73.15 464 | 57.55 375 | 79.47 386 | 83.92 347 | 48.02 462 | 56.48 462 | 84.81 340 | 43.13 407 | 86.42 380 | 62.67 320 | 81.81 282 | 84.89 408 |
| M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
| USDC | | | 70.33 377 | 68.37 378 | 76.21 369 | 80.60 407 | 56.23 396 | 79.19 391 | 86.49 311 | 60.89 403 | 61.29 444 | 85.47 324 | 31.78 456 | 89.47 336 | 53.37 401 | 76.21 357 | 82.94 433 |
|
| gg-mvs-nofinetune | | | 69.95 382 | 67.96 385 | 75.94 370 | 83.07 363 | 54.51 417 | 77.23 417 | 70.29 456 | 63.11 380 | 70.32 361 | 62.33 470 | 43.62 404 | 88.69 352 | 53.88 398 | 87.76 177 | 84.62 412 |
|
| ETVMVS | | | 72.25 358 | 71.05 354 | 75.84 371 | 87.77 220 | 51.91 435 | 79.39 387 | 74.98 441 | 69.26 287 | 73.71 321 | 82.95 381 | 40.82 424 | 86.14 382 | 46.17 443 | 84.43 239 | 89.47 289 |
|
| MDA-MVSNet-bldmvs | | | 66.68 407 | 63.66 417 | 75.75 372 | 79.28 426 | 60.56 337 | 73.92 440 | 78.35 421 | 64.43 362 | 50.13 471 | 79.87 420 | 44.02 402 | 83.67 406 | 46.10 444 | 56.86 457 | 83.03 431 |
|
| PVSNet | | 64.34 18 | 72.08 361 | 70.87 358 | 75.69 373 | 86.21 282 | 56.44 391 | 74.37 438 | 80.73 392 | 62.06 396 | 70.17 364 | 82.23 394 | 42.86 409 | 83.31 411 | 54.77 393 | 84.45 238 | 87.32 356 |
|
| pmmvs5 | | | 71.55 363 | 70.20 367 | 75.61 374 | 77.83 436 | 56.39 392 | 81.74 349 | 80.89 389 | 57.76 432 | 67.46 398 | 84.49 343 | 49.26 356 | 85.32 394 | 57.08 377 | 75.29 374 | 85.11 405 |
|
| our_test_3 | | | 69.14 388 | 67.00 401 | 75.57 375 | 79.80 419 | 58.80 354 | 77.96 410 | 77.81 423 | 59.55 415 | 62.90 440 | 78.25 435 | 47.43 366 | 83.97 404 | 51.71 408 | 67.58 426 | 83.93 420 |
|
| WTY-MVS | | | 75.65 307 | 75.68 286 | 75.57 375 | 86.40 279 | 56.82 384 | 77.92 412 | 82.40 374 | 65.10 354 | 76.18 268 | 87.72 259 | 63.13 183 | 80.90 427 | 60.31 344 | 81.96 279 | 89.00 306 |
|
| UBG | | | 73.08 346 | 72.27 338 | 75.51 377 | 88.02 204 | 51.29 443 | 78.35 406 | 77.38 429 | 65.52 346 | 73.87 320 | 82.36 390 | 45.55 390 | 86.48 379 | 55.02 391 | 84.39 240 | 88.75 317 |
|
| Patchmtry | | | 70.74 371 | 69.16 374 | 75.49 378 | 80.72 405 | 54.07 420 | 74.94 435 | 80.30 402 | 58.34 426 | 70.01 366 | 81.19 401 | 52.50 303 | 86.54 377 | 53.37 401 | 71.09 411 | 85.87 393 |
|
| mvs5depth | | | 69.45 386 | 67.45 397 | 75.46 379 | 73.93 455 | 55.83 401 | 79.19 391 | 83.23 359 | 66.89 323 | 71.63 350 | 83.32 374 | 33.69 452 | 85.09 395 | 59.81 348 | 55.34 463 | 85.46 397 |
|
| GG-mvs-BLEND | | | | | 75.38 380 | 81.59 393 | 55.80 402 | 79.32 388 | 69.63 458 | | 67.19 402 | 73.67 459 | 43.24 406 | 88.90 350 | 50.41 415 | 84.50 234 | 81.45 444 |
|
| WBMVS | | | 73.43 335 | 72.81 331 | 75.28 381 | 87.91 209 | 50.99 445 | 78.59 402 | 81.31 388 | 65.51 348 | 74.47 313 | 84.83 339 | 46.39 377 | 86.68 376 | 58.41 364 | 77.86 329 | 88.17 334 |
|
| ambc | | | | | 75.24 382 | 73.16 463 | 50.51 448 | 63.05 478 | 87.47 284 | | 64.28 430 | 77.81 438 | 17.80 478 | 89.73 331 | 57.88 370 | 60.64 452 | 85.49 396 |
|
| CL-MVSNet_self_test | | | 72.37 355 | 71.46 345 | 75.09 383 | 79.49 424 | 53.53 423 | 80.76 366 | 85.01 334 | 69.12 293 | 70.51 358 | 82.05 396 | 57.92 253 | 84.13 403 | 52.27 406 | 66.00 432 | 87.60 344 |
|
| XXY-MVS | | | 75.41 312 | 75.56 289 | 74.96 384 | 83.59 349 | 57.82 369 | 80.59 370 | 83.87 349 | 66.54 334 | 74.93 305 | 88.31 243 | 63.24 177 | 80.09 430 | 62.16 327 | 76.85 343 | 86.97 369 |
|
| testing3-2 | | | 75.12 317 | 75.19 299 | 74.91 385 | 90.40 109 | 45.09 468 | 80.29 376 | 78.42 420 | 78.37 40 | 76.54 259 | 87.75 258 | 44.36 399 | 87.28 372 | 57.04 378 | 83.49 258 | 92.37 172 |
|
| MIMVSNet | | | 70.69 372 | 69.30 371 | 74.88 386 | 84.52 327 | 56.35 395 | 75.87 426 | 79.42 411 | 64.59 360 | 67.76 393 | 82.41 389 | 41.10 421 | 81.54 422 | 46.64 441 | 81.34 284 | 86.75 374 |
|
| ADS-MVSNet2 | | | 66.20 414 | 63.33 418 | 74.82 387 | 79.92 415 | 58.75 355 | 67.55 463 | 75.19 440 | 53.37 450 | 65.25 424 | 75.86 452 | 42.32 412 | 80.53 429 | 41.57 458 | 68.91 420 | 85.18 402 |
|
| TinyColmap | | | 67.30 403 | 64.81 410 | 74.76 388 | 81.92 389 | 56.68 388 | 80.29 376 | 81.49 385 | 60.33 407 | 56.27 463 | 83.22 375 | 24.77 468 | 87.66 368 | 45.52 447 | 69.47 417 | 79.95 452 |
|
| test_vis1_n_1920 | | | 75.52 309 | 75.78 284 | 74.75 389 | 79.84 417 | 57.44 377 | 83.26 328 | 85.52 326 | 62.83 386 | 79.34 194 | 86.17 308 | 45.10 394 | 79.71 431 | 78.75 143 | 81.21 287 | 87.10 367 |
|
| test-LLR | | | 72.94 349 | 72.43 335 | 74.48 390 | 81.35 399 | 58.04 363 | 78.38 403 | 77.46 426 | 66.66 328 | 69.95 369 | 79.00 428 | 48.06 364 | 79.24 432 | 66.13 285 | 84.83 229 | 86.15 384 |
|
| test-mter | | | 71.41 364 | 70.39 365 | 74.48 390 | 81.35 399 | 58.04 363 | 78.38 403 | 77.46 426 | 60.32 408 | 69.95 369 | 79.00 428 | 36.08 447 | 79.24 432 | 66.13 285 | 84.83 229 | 86.15 384 |
|
| tpm | | | 72.37 355 | 71.71 342 | 74.35 392 | 82.19 385 | 52.00 433 | 79.22 390 | 77.29 430 | 64.56 361 | 72.95 333 | 83.68 368 | 51.35 325 | 83.26 412 | 58.33 366 | 75.80 360 | 87.81 340 |
|
| SD_0403 | | | 74.65 320 | 74.77 304 | 74.29 393 | 86.20 283 | 47.42 457 | 83.71 315 | 85.12 330 | 69.30 285 | 68.50 387 | 87.95 256 | 59.40 241 | 86.05 383 | 49.38 424 | 83.35 261 | 89.40 291 |
|
| CVMVSNet | | | 72.99 348 | 72.58 334 | 74.25 394 | 84.28 330 | 50.85 446 | 86.41 234 | 83.45 356 | 44.56 466 | 73.23 328 | 87.54 267 | 49.38 353 | 85.70 387 | 65.90 289 | 78.44 321 | 86.19 383 |
|
| FMVSNet5 | | | 69.50 385 | 67.96 385 | 74.15 395 | 82.97 370 | 55.35 408 | 80.01 381 | 82.12 377 | 62.56 390 | 63.02 437 | 81.53 400 | 36.92 442 | 81.92 420 | 48.42 429 | 74.06 386 | 85.17 404 |
|
| UWE-MVS | | | 72.13 360 | 71.49 344 | 74.03 396 | 86.66 273 | 47.70 455 | 81.40 357 | 76.89 434 | 63.60 377 | 75.59 277 | 84.22 354 | 39.94 427 | 85.62 389 | 48.98 427 | 86.13 208 | 88.77 316 |
|
| MIMVSNet1 | | | 68.58 393 | 66.78 403 | 73.98 397 | 80.07 414 | 51.82 437 | 80.77 365 | 84.37 339 | 64.40 364 | 59.75 452 | 82.16 395 | 36.47 445 | 83.63 407 | 42.73 455 | 70.33 414 | 86.48 379 |
|
| myMVS_eth3d28 | | | 73.62 332 | 73.53 322 | 73.90 398 | 88.20 193 | 47.41 458 | 78.06 409 | 79.37 412 | 74.29 160 | 73.98 318 | 84.29 350 | 44.67 395 | 83.54 408 | 51.47 410 | 87.39 183 | 90.74 234 |
|
| test_cas_vis1_n_1920 | | | 73.76 331 | 73.74 320 | 73.81 399 | 75.90 445 | 59.77 346 | 80.51 371 | 82.40 374 | 58.30 427 | 81.62 155 | 85.69 316 | 44.35 400 | 76.41 449 | 76.29 175 | 78.61 317 | 85.23 401 |
|
| Anonymous20240521 | | | 68.80 391 | 67.22 400 | 73.55 400 | 74.33 453 | 54.11 419 | 83.18 329 | 85.61 325 | 58.15 428 | 61.68 443 | 80.94 406 | 30.71 459 | 81.27 425 | 57.00 379 | 73.34 396 | 85.28 400 |
|
| sss | | | 73.60 333 | 73.64 321 | 73.51 401 | 82.80 373 | 55.01 412 | 76.12 422 | 81.69 382 | 62.47 391 | 74.68 309 | 85.85 314 | 57.32 260 | 78.11 438 | 60.86 340 | 80.93 289 | 87.39 351 |
|
| SSC-MVS3.2 | | | 73.35 341 | 73.39 323 | 73.23 402 | 85.30 307 | 49.01 453 | 74.58 437 | 81.57 383 | 75.21 130 | 73.68 322 | 85.58 321 | 52.53 301 | 82.05 419 | 54.33 396 | 77.69 333 | 88.63 322 |
|
| KD-MVS_2432*1600 | | | 66.22 412 | 63.89 415 | 73.21 403 | 75.47 451 | 53.42 425 | 70.76 451 | 84.35 340 | 64.10 369 | 66.52 413 | 78.52 432 | 34.55 450 | 84.98 396 | 50.40 416 | 50.33 470 | 81.23 445 |
|
| miper_refine_blended | | | 66.22 412 | 63.89 415 | 73.21 403 | 75.47 451 | 53.42 425 | 70.76 451 | 84.35 340 | 64.10 369 | 66.52 413 | 78.52 432 | 34.55 450 | 84.98 396 | 50.40 416 | 50.33 470 | 81.23 445 |
|
| PM-MVS | | | 66.41 410 | 64.14 413 | 73.20 405 | 73.92 456 | 56.45 390 | 78.97 395 | 64.96 472 | 63.88 375 | 64.72 427 | 80.24 415 | 19.84 476 | 83.44 410 | 66.24 284 | 64.52 441 | 79.71 453 |
|
| tpmrst | | | 72.39 353 | 72.13 339 | 73.18 406 | 80.54 408 | 49.91 450 | 79.91 383 | 79.08 416 | 63.11 380 | 71.69 349 | 79.95 418 | 55.32 276 | 82.77 415 | 65.66 292 | 73.89 388 | 86.87 370 |
|
| FE-MVSNET | | | 67.25 404 | 65.33 408 | 73.02 407 | 75.86 446 | 52.54 431 | 80.26 378 | 80.56 395 | 63.80 376 | 60.39 447 | 79.70 422 | 41.41 419 | 84.66 401 | 43.34 453 | 62.62 446 | 81.86 441 |
|
| WB-MVSnew | | | 71.96 362 | 71.65 343 | 72.89 408 | 84.67 326 | 51.88 436 | 82.29 343 | 77.57 425 | 62.31 392 | 73.67 323 | 83.00 380 | 53.49 297 | 81.10 426 | 45.75 446 | 82.13 277 | 85.70 394 |
|
| dmvs_re | | | 71.14 366 | 70.58 360 | 72.80 409 | 81.96 387 | 59.68 347 | 75.60 428 | 79.34 413 | 68.55 306 | 69.27 378 | 80.72 409 | 49.42 352 | 76.54 446 | 52.56 405 | 77.79 330 | 82.19 439 |
|
| test_fmvs1_n | | | 70.86 370 | 70.24 366 | 72.73 410 | 72.51 468 | 55.28 409 | 81.27 359 | 79.71 409 | 51.49 457 | 78.73 201 | 84.87 338 | 27.54 463 | 77.02 443 | 76.06 179 | 79.97 305 | 85.88 392 |
|
| TESTMET0.1,1 | | | 69.89 383 | 69.00 375 | 72.55 411 | 79.27 427 | 56.85 383 | 78.38 403 | 74.71 445 | 57.64 433 | 68.09 390 | 77.19 443 | 37.75 440 | 76.70 445 | 63.92 304 | 84.09 244 | 84.10 418 |
|
| mamv4 | | | 76.81 286 | 78.23 230 | 72.54 412 | 86.12 286 | 65.75 210 | 78.76 398 | 82.07 378 | 64.12 368 | 72.97 332 | 91.02 162 | 67.97 123 | 68.08 477 | 83.04 89 | 78.02 328 | 83.80 422 |
|
| KD-MVS_self_test | | | 68.81 390 | 67.59 395 | 72.46 413 | 74.29 454 | 45.45 463 | 77.93 411 | 87.00 299 | 63.12 379 | 63.99 434 | 78.99 430 | 42.32 412 | 84.77 399 | 56.55 385 | 64.09 442 | 87.16 363 |
|
| test_fmvs1 | | | 70.93 369 | 70.52 361 | 72.16 414 | 73.71 457 | 55.05 411 | 80.82 362 | 78.77 418 | 51.21 458 | 78.58 206 | 84.41 346 | 31.20 458 | 76.94 444 | 75.88 183 | 80.12 304 | 84.47 413 |
|
| CHOSEN 280x420 | | | 66.51 409 | 64.71 411 | 71.90 415 | 81.45 396 | 63.52 279 | 57.98 480 | 68.95 462 | 53.57 449 | 62.59 441 | 76.70 444 | 46.22 382 | 75.29 461 | 55.25 389 | 79.68 306 | 76.88 459 |
|
| test_vis1_n | | | 69.85 384 | 69.21 373 | 71.77 416 | 72.66 467 | 55.27 410 | 81.48 354 | 76.21 437 | 52.03 454 | 75.30 293 | 83.20 377 | 28.97 461 | 76.22 451 | 74.60 197 | 78.41 325 | 83.81 421 |
|
| EPMVS | | | 69.02 389 | 68.16 381 | 71.59 417 | 79.61 422 | 49.80 452 | 77.40 415 | 66.93 466 | 62.82 387 | 70.01 366 | 79.05 426 | 45.79 387 | 77.86 440 | 56.58 384 | 75.26 375 | 87.13 364 |
|
| YYNet1 | | | 65.03 416 | 62.91 421 | 71.38 418 | 75.85 447 | 56.60 389 | 69.12 459 | 74.66 446 | 57.28 437 | 54.12 465 | 77.87 437 | 45.85 386 | 74.48 463 | 49.95 421 | 61.52 450 | 83.05 430 |
|
| MDA-MVSNet_test_wron | | | 65.03 416 | 62.92 420 | 71.37 419 | 75.93 444 | 56.73 385 | 69.09 460 | 74.73 444 | 57.28 437 | 54.03 466 | 77.89 436 | 45.88 385 | 74.39 464 | 49.89 422 | 61.55 449 | 82.99 432 |
|
| UnsupCasMVSNet_eth | | | 67.33 402 | 65.99 406 | 71.37 419 | 73.48 460 | 51.47 441 | 75.16 431 | 85.19 329 | 65.20 352 | 60.78 446 | 80.93 408 | 42.35 411 | 77.20 442 | 57.12 376 | 53.69 465 | 85.44 398 |
|
| PMMVS | | | 69.34 387 | 68.67 376 | 71.35 421 | 75.67 448 | 62.03 312 | 75.17 430 | 73.46 448 | 50.00 459 | 68.68 381 | 79.05 426 | 52.07 313 | 78.13 437 | 61.16 338 | 82.77 269 | 73.90 463 |
|
| EU-MVSNet | | | 68.53 395 | 67.61 394 | 71.31 422 | 78.51 431 | 47.01 460 | 84.47 293 | 84.27 343 | 42.27 469 | 66.44 416 | 84.79 341 | 40.44 425 | 83.76 405 | 58.76 361 | 68.54 423 | 83.17 427 |
|
| testing3 | | | 68.56 394 | 67.67 393 | 71.22 423 | 87.33 246 | 42.87 473 | 83.06 335 | 71.54 453 | 70.36 257 | 69.08 379 | 84.38 347 | 30.33 460 | 85.69 388 | 37.50 466 | 75.45 369 | 85.09 406 |
|
| Anonymous20231206 | | | 68.60 392 | 67.80 390 | 71.02 424 | 80.23 412 | 50.75 447 | 78.30 407 | 80.47 397 | 56.79 439 | 66.11 419 | 82.63 388 | 46.35 380 | 78.95 434 | 43.62 452 | 75.70 361 | 83.36 426 |
|
| test_fmvs2 | | | 68.35 397 | 67.48 396 | 70.98 425 | 69.50 471 | 51.95 434 | 80.05 380 | 76.38 436 | 49.33 460 | 74.65 310 | 84.38 347 | 23.30 472 | 75.40 460 | 74.51 198 | 75.17 377 | 85.60 395 |
|
| dp | | | 66.80 406 | 65.43 407 | 70.90 426 | 79.74 421 | 48.82 454 | 75.12 433 | 74.77 443 | 59.61 414 | 64.08 433 | 77.23 442 | 42.89 408 | 80.72 428 | 48.86 428 | 66.58 429 | 83.16 428 |
|
| PatchT | | | 68.46 396 | 67.85 387 | 70.29 427 | 80.70 406 | 43.93 471 | 72.47 443 | 74.88 442 | 60.15 410 | 70.55 357 | 76.57 445 | 49.94 346 | 81.59 421 | 50.58 414 | 74.83 380 | 85.34 399 |
|
| UnsupCasMVSNet_bld | | | 63.70 421 | 61.53 427 | 70.21 428 | 73.69 458 | 51.39 442 | 72.82 442 | 81.89 379 | 55.63 444 | 57.81 458 | 71.80 463 | 38.67 435 | 78.61 435 | 49.26 426 | 52.21 468 | 80.63 449 |
|
| Patchmatch-test | | | 64.82 418 | 63.24 419 | 69.57 429 | 79.42 425 | 49.82 451 | 63.49 477 | 69.05 461 | 51.98 455 | 59.95 451 | 80.13 416 | 50.91 332 | 70.98 470 | 40.66 460 | 73.57 391 | 87.90 338 |
|
| LF4IMVS | | | 64.02 420 | 62.19 424 | 69.50 430 | 70.90 469 | 53.29 428 | 76.13 421 | 77.18 431 | 52.65 452 | 58.59 454 | 80.98 405 | 23.55 471 | 76.52 447 | 53.06 403 | 66.66 428 | 78.68 455 |
|
| myMVS_eth3d | | | 67.02 405 | 66.29 405 | 69.21 431 | 84.68 323 | 42.58 474 | 78.62 400 | 73.08 450 | 66.65 331 | 66.74 409 | 79.46 423 | 31.53 457 | 82.30 417 | 39.43 463 | 76.38 354 | 82.75 434 |
|
| test20.03 | | | 67.45 401 | 66.95 402 | 68.94 432 | 75.48 450 | 44.84 469 | 77.50 414 | 77.67 424 | 66.66 328 | 63.01 438 | 83.80 362 | 47.02 370 | 78.40 436 | 42.53 457 | 68.86 422 | 83.58 424 |
|
| test0.0.03 1 | | | 68.00 399 | 67.69 392 | 68.90 433 | 77.55 439 | 47.43 456 | 75.70 427 | 72.95 452 | 66.66 328 | 66.56 411 | 82.29 393 | 48.06 364 | 75.87 455 | 44.97 450 | 74.51 383 | 83.41 425 |
|
| PVSNet_0 | | 57.27 20 | 61.67 426 | 59.27 429 | 68.85 434 | 79.61 422 | 57.44 377 | 68.01 461 | 73.44 449 | 55.93 443 | 58.54 455 | 70.41 466 | 44.58 397 | 77.55 441 | 47.01 438 | 35.91 478 | 71.55 466 |
|
| ADS-MVSNet | | | 64.36 419 | 62.88 422 | 68.78 435 | 79.92 415 | 47.17 459 | 67.55 463 | 71.18 454 | 53.37 450 | 65.25 424 | 75.86 452 | 42.32 412 | 73.99 466 | 41.57 458 | 68.91 420 | 85.18 402 |
|
| Syy-MVS | | | 68.05 398 | 67.85 387 | 68.67 436 | 84.68 323 | 40.97 479 | 78.62 400 | 73.08 450 | 66.65 331 | 66.74 409 | 79.46 423 | 52.11 311 | 82.30 417 | 32.89 471 | 76.38 354 | 82.75 434 |
|
| pmmvs3 | | | 57.79 430 | 54.26 435 | 68.37 437 | 64.02 479 | 56.72 386 | 75.12 433 | 65.17 470 | 40.20 471 | 52.93 467 | 69.86 467 | 20.36 475 | 75.48 458 | 45.45 448 | 55.25 464 | 72.90 465 |
|
| ttmdpeth | | | 59.91 428 | 57.10 432 | 68.34 438 | 67.13 475 | 46.65 462 | 74.64 436 | 67.41 465 | 48.30 461 | 62.52 442 | 85.04 337 | 20.40 474 | 75.93 454 | 42.55 456 | 45.90 476 | 82.44 436 |
|
| MVStest1 | | | 56.63 432 | 52.76 438 | 68.25 439 | 61.67 481 | 53.25 429 | 71.67 446 | 68.90 463 | 38.59 474 | 50.59 470 | 83.05 379 | 25.08 466 | 70.66 471 | 36.76 467 | 38.56 477 | 80.83 448 |
|
| test_fmvs3 | | | 63.36 422 | 61.82 425 | 67.98 440 | 62.51 480 | 46.96 461 | 77.37 416 | 74.03 447 | 45.24 465 | 67.50 397 | 78.79 431 | 12.16 484 | 72.98 469 | 72.77 218 | 66.02 431 | 83.99 419 |
|
| LCM-MVSNet | | | 54.25 434 | 49.68 444 | 67.97 441 | 53.73 489 | 45.28 466 | 66.85 466 | 80.78 391 | 35.96 478 | 39.45 479 | 62.23 472 | 8.70 488 | 78.06 439 | 48.24 433 | 51.20 469 | 80.57 450 |
|
| EGC-MVSNET | | | 52.07 441 | 47.05 445 | 67.14 442 | 83.51 351 | 60.71 334 | 80.50 372 | 67.75 464 | 0.07 492 | 0.43 493 | 75.85 454 | 24.26 469 | 81.54 422 | 28.82 475 | 62.25 447 | 59.16 475 |
|
| testgi | | | 66.67 408 | 66.53 404 | 67.08 443 | 75.62 449 | 41.69 478 | 75.93 423 | 76.50 435 | 66.11 337 | 65.20 426 | 86.59 295 | 35.72 448 | 74.71 462 | 43.71 451 | 73.38 395 | 84.84 409 |
|
| UWE-MVS-28 | | | 65.32 415 | 64.93 409 | 66.49 444 | 78.70 429 | 38.55 481 | 77.86 413 | 64.39 473 | 62.00 397 | 64.13 432 | 83.60 369 | 41.44 418 | 76.00 453 | 31.39 473 | 80.89 290 | 84.92 407 |
|
| test_vis1_rt | | | 60.28 427 | 58.42 430 | 65.84 445 | 67.25 474 | 55.60 405 | 70.44 453 | 60.94 478 | 44.33 467 | 59.00 453 | 66.64 468 | 24.91 467 | 68.67 475 | 62.80 316 | 69.48 416 | 73.25 464 |
|
| mvsany_test1 | | | 62.30 424 | 61.26 428 | 65.41 446 | 69.52 470 | 54.86 413 | 66.86 465 | 49.78 486 | 46.65 463 | 68.50 387 | 83.21 376 | 49.15 357 | 66.28 478 | 56.93 380 | 60.77 451 | 75.11 462 |
|
| ANet_high | | | 50.57 443 | 46.10 447 | 63.99 447 | 48.67 492 | 39.13 480 | 70.99 450 | 80.85 390 | 61.39 401 | 31.18 481 | 57.70 477 | 17.02 479 | 73.65 468 | 31.22 474 | 15.89 489 | 79.18 454 |
|
| MVS-HIRNet | | | 59.14 429 | 57.67 431 | 63.57 448 | 81.65 391 | 43.50 472 | 71.73 445 | 65.06 471 | 39.59 473 | 51.43 468 | 57.73 476 | 38.34 437 | 82.58 416 | 39.53 461 | 73.95 387 | 64.62 472 |
|
| APD_test1 | | | 53.31 438 | 49.93 443 | 63.42 449 | 65.68 476 | 50.13 449 | 71.59 447 | 66.90 467 | 34.43 479 | 40.58 478 | 71.56 464 | 8.65 489 | 76.27 450 | 34.64 470 | 55.36 462 | 63.86 473 |
|
| new-patchmatchnet | | | 61.73 425 | 61.73 426 | 61.70 450 | 72.74 466 | 24.50 493 | 69.16 458 | 78.03 422 | 61.40 400 | 56.72 461 | 75.53 455 | 38.42 436 | 76.48 448 | 45.95 445 | 57.67 456 | 84.13 417 |
|
| mvsany_test3 | | | 53.99 435 | 51.45 440 | 61.61 451 | 55.51 485 | 44.74 470 | 63.52 476 | 45.41 490 | 43.69 468 | 58.11 457 | 76.45 446 | 17.99 477 | 63.76 481 | 54.77 393 | 47.59 472 | 76.34 460 |
|
| DSMNet-mixed | | | 57.77 431 | 56.90 433 | 60.38 452 | 67.70 473 | 35.61 483 | 69.18 457 | 53.97 484 | 32.30 482 | 57.49 459 | 79.88 419 | 40.39 426 | 68.57 476 | 38.78 464 | 72.37 400 | 76.97 458 |
|
| FPMVS | | | 53.68 437 | 51.64 439 | 59.81 453 | 65.08 477 | 51.03 444 | 69.48 456 | 69.58 459 | 41.46 470 | 40.67 477 | 72.32 462 | 16.46 480 | 70.00 474 | 24.24 481 | 65.42 438 | 58.40 477 |
|
| dmvs_testset | | | 62.63 423 | 64.11 414 | 58.19 454 | 78.55 430 | 24.76 492 | 75.28 429 | 65.94 469 | 67.91 315 | 60.34 448 | 76.01 451 | 53.56 295 | 73.94 467 | 31.79 472 | 67.65 425 | 75.88 461 |
|
| testf1 | | | 45.72 445 | 41.96 449 | 57.00 455 | 56.90 483 | 45.32 464 | 66.14 468 | 59.26 480 | 26.19 483 | 30.89 482 | 60.96 474 | 4.14 492 | 70.64 472 | 26.39 479 | 46.73 474 | 55.04 478 |
|
| APD_test2 | | | 45.72 445 | 41.96 449 | 57.00 455 | 56.90 483 | 45.32 464 | 66.14 468 | 59.26 480 | 26.19 483 | 30.89 482 | 60.96 474 | 4.14 492 | 70.64 472 | 26.39 479 | 46.73 474 | 55.04 478 |
|
| test_vis3_rt | | | 49.26 444 | 47.02 446 | 56.00 457 | 54.30 486 | 45.27 467 | 66.76 467 | 48.08 487 | 36.83 476 | 44.38 475 | 53.20 480 | 7.17 491 | 64.07 480 | 56.77 383 | 55.66 460 | 58.65 476 |
|
| test_f | | | 52.09 440 | 50.82 441 | 55.90 458 | 53.82 488 | 42.31 477 | 59.42 479 | 58.31 482 | 36.45 477 | 56.12 464 | 70.96 465 | 12.18 483 | 57.79 484 | 53.51 400 | 56.57 459 | 67.60 469 |
|
| PMVS |  | 37.38 22 | 44.16 449 | 40.28 453 | 55.82 459 | 40.82 494 | 42.54 476 | 65.12 472 | 63.99 474 | 34.43 479 | 24.48 485 | 57.12 478 | 3.92 494 | 76.17 452 | 17.10 486 | 55.52 461 | 48.75 480 |
| Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
| WB-MVS | | | 54.94 433 | 54.72 434 | 55.60 460 | 73.50 459 | 20.90 494 | 74.27 439 | 61.19 477 | 59.16 419 | 50.61 469 | 74.15 457 | 47.19 369 | 75.78 456 | 17.31 485 | 35.07 479 | 70.12 467 |
|
| Gipuma |  | | 45.18 448 | 41.86 451 | 55.16 461 | 77.03 443 | 51.52 440 | 32.50 486 | 80.52 396 | 32.46 481 | 27.12 484 | 35.02 485 | 9.52 487 | 75.50 457 | 22.31 482 | 60.21 454 | 38.45 484 |
| S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
| SSC-MVS | | | 53.88 436 | 53.59 436 | 54.75 462 | 72.87 465 | 19.59 495 | 73.84 441 | 60.53 479 | 57.58 435 | 49.18 473 | 73.45 460 | 46.34 381 | 75.47 459 | 16.20 488 | 32.28 481 | 69.20 468 |
|
| new_pmnet | | | 50.91 442 | 50.29 442 | 52.78 463 | 68.58 472 | 34.94 485 | 63.71 475 | 56.63 483 | 39.73 472 | 44.95 474 | 65.47 469 | 21.93 473 | 58.48 483 | 34.98 469 | 56.62 458 | 64.92 471 |
|
| N_pmnet | | | 52.79 439 | 53.26 437 | 51.40 464 | 78.99 428 | 7.68 498 | 69.52 455 | 3.89 497 | 51.63 456 | 57.01 460 | 74.98 456 | 40.83 423 | 65.96 479 | 37.78 465 | 64.67 440 | 80.56 451 |
|
| PMMVS2 | | | 40.82 450 | 38.86 454 | 46.69 465 | 53.84 487 | 16.45 496 | 48.61 483 | 49.92 485 | 37.49 475 | 31.67 480 | 60.97 473 | 8.14 490 | 56.42 485 | 28.42 476 | 30.72 482 | 67.19 470 |
|
| dongtai | | | 45.42 447 | 45.38 448 | 45.55 466 | 73.36 462 | 26.85 490 | 67.72 462 | 34.19 492 | 54.15 448 | 49.65 472 | 56.41 479 | 25.43 465 | 62.94 482 | 19.45 483 | 28.09 483 | 46.86 482 |
|
| MVE |  | 26.22 23 | 30.37 455 | 25.89 459 | 43.81 467 | 44.55 493 | 35.46 484 | 28.87 487 | 39.07 491 | 18.20 487 | 18.58 489 | 40.18 484 | 2.68 495 | 47.37 489 | 17.07 487 | 23.78 486 | 48.60 481 |
| Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
| test_method | | | 31.52 453 | 29.28 457 | 38.23 468 | 27.03 496 | 6.50 499 | 20.94 488 | 62.21 476 | 4.05 490 | 22.35 488 | 52.50 481 | 13.33 481 | 47.58 488 | 27.04 478 | 34.04 480 | 60.62 474 |
|
| kuosan | | | 39.70 451 | 40.40 452 | 37.58 469 | 64.52 478 | 26.98 488 | 65.62 470 | 33.02 493 | 46.12 464 | 42.79 476 | 48.99 482 | 24.10 470 | 46.56 490 | 12.16 491 | 26.30 484 | 39.20 483 |
|
| E-PMN | | | 31.77 452 | 30.64 455 | 35.15 470 | 52.87 490 | 27.67 487 | 57.09 481 | 47.86 488 | 24.64 485 | 16.40 490 | 33.05 486 | 11.23 485 | 54.90 486 | 14.46 489 | 18.15 487 | 22.87 486 |
|
| EMVS | | | 30.81 454 | 29.65 456 | 34.27 471 | 50.96 491 | 25.95 491 | 56.58 482 | 46.80 489 | 24.01 486 | 15.53 491 | 30.68 487 | 12.47 482 | 54.43 487 | 12.81 490 | 17.05 488 | 22.43 487 |
|
| DeepMVS_CX |  | | | | 27.40 472 | 40.17 495 | 26.90 489 | | 24.59 496 | 17.44 488 | 23.95 486 | 48.61 483 | 9.77 486 | 26.48 491 | 18.06 484 | 24.47 485 | 28.83 485 |
|
| wuyk23d | | | 16.82 458 | 15.94 461 | 19.46 473 | 58.74 482 | 31.45 486 | 39.22 484 | 3.74 498 | 6.84 489 | 6.04 492 | 2.70 492 | 1.27 496 | 24.29 492 | 10.54 492 | 14.40 491 | 2.63 489 |
|
| tmp_tt | | | 18.61 457 | 21.40 460 | 10.23 474 | 4.82 497 | 10.11 497 | 34.70 485 | 30.74 495 | 1.48 491 | 23.91 487 | 26.07 488 | 28.42 462 | 13.41 493 | 27.12 477 | 15.35 490 | 7.17 488 |
|
| test123 | | | 6.12 460 | 8.11 463 | 0.14 475 | 0.06 499 | 0.09 500 | 71.05 449 | 0.03 500 | 0.04 494 | 0.25 495 | 1.30 494 | 0.05 497 | 0.03 495 | 0.21 494 | 0.01 493 | 0.29 490 |
|
| testmvs | | | 6.04 461 | 8.02 464 | 0.10 476 | 0.08 498 | 0.03 501 | 69.74 454 | 0.04 499 | 0.05 493 | 0.31 494 | 1.68 493 | 0.02 498 | 0.04 494 | 0.24 493 | 0.02 492 | 0.25 491 |
|
| mmdepth | | | 0.00 463 | 0.00 466 | 0.00 477 | 0.00 500 | 0.00 502 | 0.00 489 | 0.00 501 | 0.00 495 | 0.00 496 | 0.00 495 | 0.00 499 | 0.00 496 | 0.00 495 | 0.00 494 | 0.00 492 |
|
| monomultidepth | | | 0.00 463 | 0.00 466 | 0.00 477 | 0.00 500 | 0.00 502 | 0.00 489 | 0.00 501 | 0.00 495 | 0.00 496 | 0.00 495 | 0.00 499 | 0.00 496 | 0.00 495 | 0.00 494 | 0.00 492 |
|
| test_blank | | | 0.00 463 | 0.00 466 | 0.00 477 | 0.00 500 | 0.00 502 | 0.00 489 | 0.00 501 | 0.00 495 | 0.00 496 | 0.00 495 | 0.00 499 | 0.00 496 | 0.00 495 | 0.00 494 | 0.00 492 |
|
| uanet_test | | | 0.00 463 | 0.00 466 | 0.00 477 | 0.00 500 | 0.00 502 | 0.00 489 | 0.00 501 | 0.00 495 | 0.00 496 | 0.00 495 | 0.00 499 | 0.00 496 | 0.00 495 | 0.00 494 | 0.00 492 |
|
| DCPMVS | | | 0.00 463 | 0.00 466 | 0.00 477 | 0.00 500 | 0.00 502 | 0.00 489 | 0.00 501 | 0.00 495 | 0.00 496 | 0.00 495 | 0.00 499 | 0.00 496 | 0.00 495 | 0.00 494 | 0.00 492 |
|
| cdsmvs_eth3d_5k | | | 19.96 456 | 26.61 458 | 0.00 477 | 0.00 500 | 0.00 502 | 0.00 489 | 89.26 223 | 0.00 495 | 0.00 496 | 88.61 234 | 61.62 208 | 0.00 496 | 0.00 495 | 0.00 494 | 0.00 492 |
|
| pcd_1.5k_mvsjas | | | 5.26 462 | 7.02 465 | 0.00 477 | 0.00 500 | 0.00 502 | 0.00 489 | 0.00 501 | 0.00 495 | 0.00 496 | 0.00 495 | 63.15 180 | 0.00 496 | 0.00 495 | 0.00 494 | 0.00 492 |
|
| sosnet-low-res | | | 0.00 463 | 0.00 466 | 0.00 477 | 0.00 500 | 0.00 502 | 0.00 489 | 0.00 501 | 0.00 495 | 0.00 496 | 0.00 495 | 0.00 499 | 0.00 496 | 0.00 495 | 0.00 494 | 0.00 492 |
|
| sosnet | | | 0.00 463 | 0.00 466 | 0.00 477 | 0.00 500 | 0.00 502 | 0.00 489 | 0.00 501 | 0.00 495 | 0.00 496 | 0.00 495 | 0.00 499 | 0.00 496 | 0.00 495 | 0.00 494 | 0.00 492 |
|
| uncertanet | | | 0.00 463 | 0.00 466 | 0.00 477 | 0.00 500 | 0.00 502 | 0.00 489 | 0.00 501 | 0.00 495 | 0.00 496 | 0.00 495 | 0.00 499 | 0.00 496 | 0.00 495 | 0.00 494 | 0.00 492 |
|
| Regformer | | | 0.00 463 | 0.00 466 | 0.00 477 | 0.00 500 | 0.00 502 | 0.00 489 | 0.00 501 | 0.00 495 | 0.00 496 | 0.00 495 | 0.00 499 | 0.00 496 | 0.00 495 | 0.00 494 | 0.00 492 |
|
| ab-mvs-re | | | 7.23 459 | 9.64 462 | 0.00 477 | 0.00 500 | 0.00 502 | 0.00 489 | 0.00 501 | 0.00 495 | 0.00 496 | 86.72 287 | 0.00 499 | 0.00 496 | 0.00 495 | 0.00 494 | 0.00 492 |
|
| uanet | | | 0.00 463 | 0.00 466 | 0.00 477 | 0.00 500 | 0.00 502 | 0.00 489 | 0.00 501 | 0.00 495 | 0.00 496 | 0.00 495 | 0.00 499 | 0.00 496 | 0.00 495 | 0.00 494 | 0.00 492 |
|
| TestfortrainingZip | | | | | | | | 93.28 12 | | | | | | | | | |
|
| WAC-MVS | | | | | | | 42.58 474 | | | | | | | | 39.46 462 | | |
|
| FOURS1 | | | | | | 95.00 10 | 72.39 41 | 95.06 1 | 93.84 20 | 74.49 153 | 91.30 18 | | | | | | |
|
| PC_three_1452 | | | | | | | | | | 68.21 312 | 92.02 15 | 94.00 63 | 82.09 5 | 95.98 61 | 84.58 71 | 96.68 2 | 94.95 12 |
|
| test_one_0601 | | | | | | 95.07 7 | 71.46 59 | | 94.14 10 | 78.27 41 | 92.05 14 | 95.74 6 | 80.83 13 | | | | |
|
| eth-test2 | | | | | | 0.00 500 | | | | | | | | | | | |
|
| eth-test | | | | | | 0.00 500 | | | | | | | | | | | |
|
| ZD-MVS | | | | | | 94.38 29 | 72.22 46 | | 92.67 72 | 70.98 239 | 87.75 50 | 94.07 58 | 74.01 36 | 96.70 31 | 84.66 70 | 94.84 48 | |
|
| RE-MVS-def | | | | 85.48 75 | | 93.06 64 | 70.63 82 | 91.88 43 | 92.27 93 | 73.53 181 | 85.69 73 | 94.45 37 | 63.87 170 | | 82.75 94 | 91.87 95 | 92.50 166 |
|
| IU-MVS | | | | | | 95.30 2 | 71.25 64 | | 92.95 60 | 66.81 324 | 92.39 6 | | | | 88.94 28 | 96.63 4 | 94.85 21 |
|
| test_241102_TWO | | | | | | | | | 94.06 15 | 77.24 61 | 92.78 4 | 95.72 8 | 81.26 10 | 97.44 7 | 89.07 25 | 96.58 6 | 94.26 69 |
|
| test_241102_ONE | | | | | | 95.30 2 | 70.98 71 | | 94.06 15 | 77.17 64 | 93.10 1 | 95.39 16 | 82.99 1 | 97.27 15 | | | |
|
| 9.14 | | | | 88.26 19 | | 92.84 69 | | 91.52 56 | 94.75 1 | 73.93 169 | 88.57 35 | 94.67 30 | 75.57 25 | 95.79 63 | 86.77 51 | 95.76 27 | |
|
| save fliter | | | | | | 93.80 44 | 72.35 44 | 90.47 74 | 91.17 149 | 74.31 158 | | | | | | | |
|
| test_0728_THIRD | | | | | | | | | | 78.38 38 | 92.12 12 | 95.78 4 | 81.46 9 | 97.40 9 | 89.42 19 | 96.57 7 | 94.67 38 |
|
| test0726 | | | | | | 95.27 5 | 71.25 64 | 93.60 7 | 94.11 11 | 77.33 58 | 92.81 3 | 95.79 3 | 80.98 11 | | | | |
|
| GSMVS | | | | | | | | | | | | | | | | | 88.96 308 |
|
| test_part2 | | | | | | 95.06 8 | 72.65 32 | | | | 91.80 16 | | | | | | |
|
| sam_mvs1 | | | | | | | | | | | | | 51.32 326 | | | | 88.96 308 |
|
| sam_mvs | | | | | | | | | | | | | 50.01 344 | | | | |
|
| MTGPA |  | | | | | | | | 92.02 111 | | | | | | | | |
|
| test_post1 | | | | | | | | 78.90 397 | | | | 5.43 491 | 48.81 363 | 85.44 393 | 59.25 354 | | |
|
| test_post | | | | | | | | | | | | 5.46 490 | 50.36 340 | 84.24 402 | | | |
|
| patchmatchnet-post | | | | | | | | | | | | 74.00 458 | 51.12 331 | 88.60 354 | | | |
|
| MTMP | | | | | | | | 92.18 39 | 32.83 494 | | | | | | | | |
|
| gm-plane-assit | | | | | | 81.40 397 | 53.83 422 | | | 62.72 389 | | 80.94 406 | | 92.39 240 | 63.40 308 | | |
|
| test9_res | | | | | | | | | | | | | | | 84.90 64 | 95.70 30 | 92.87 151 |
|
| TEST9 | | | | | | 93.26 56 | 72.96 25 | 88.75 138 | 91.89 119 | 68.44 309 | 85.00 80 | 93.10 88 | 74.36 32 | 95.41 80 | | | |
|
| test_8 | | | | | | 93.13 60 | 72.57 35 | 88.68 143 | 91.84 123 | 68.69 304 | 84.87 84 | 93.10 88 | 74.43 30 | 95.16 90 | | | |
|
| agg_prior2 | | | | | | | | | | | | | | | 82.91 91 | 95.45 33 | 92.70 156 |
|
| agg_prior | | | | | | 92.85 68 | 71.94 52 | | 91.78 127 | | 84.41 95 | | | 94.93 101 | | | |
|
| test_prior4 | | | | | | | 72.60 34 | 89.01 125 | | | | | | | | | |
|
| test_prior2 | | | | | | | | 88.85 132 | | 75.41 121 | 84.91 82 | 93.54 76 | 74.28 33 | | 83.31 85 | 95.86 24 | |
|
| 旧先验2 | | | | | | | | 86.56 229 | | 58.10 430 | 87.04 61 | | | 88.98 346 | 74.07 203 | | |
|
| æ–°å‡ ä½•2 | | | | | | | | 86.29 243 | | | | | | | | | |
|
| 旧先验1 | | | | | | 91.96 80 | 65.79 208 | | 86.37 314 | | | 93.08 92 | 69.31 99 | | | 92.74 80 | 88.74 319 |
|
| æ— å…ˆéªŒ | | | | | | | | 87.48 186 | 88.98 238 | 60.00 411 | | | | 94.12 140 | 67.28 277 | | 88.97 307 |
|
| 原ACMM2 | | | | | | | | 86.86 216 | | | | | | | | | |
|
| test222 | | | | | | 91.50 86 | 68.26 137 | 84.16 307 | 83.20 362 | 54.63 447 | 79.74 184 | 91.63 135 | 58.97 244 | | | 91.42 103 | 86.77 373 |
|
| testdata2 | | | | | | | | | | | | | | 91.01 304 | 62.37 324 | | |
|
| segment_acmp | | | | | | | | | | | | | 73.08 43 | | | | |
|
| testdata1 | | | | | | | | 84.14 308 | | 75.71 112 | | | | | | | |
|
| plane_prior7 | | | | | | 90.08 116 | 68.51 131 | | | | | | | | | | |
|
| plane_prior6 | | | | | | 89.84 125 | 68.70 125 | | | | | | 60.42 234 | | | | |
|
| plane_prior5 | | | | | | | | | 92.44 82 | | | | | 95.38 82 | 78.71 144 | 86.32 202 | 91.33 211 |
|
| plane_prior4 | | | | | | | | | | | | 91.00 163 | | | | | |
|
| plane_prior3 | | | | | | | 68.60 128 | | | 78.44 36 | 78.92 199 | | | | | | |
|
| plane_prior2 | | | | | | | | 91.25 60 | | 79.12 28 | | | | | | | |
|
| plane_prior1 | | | | | | 89.90 124 | | | | | | | | | | | |
|
| plane_prior | | | | | | | 68.71 123 | 90.38 78 | | 77.62 47 | | | | | | 86.16 207 | |
|
| n2 | | | | | | | | | 0.00 501 | | | | | | | | |
|
| nn | | | | | | | | | 0.00 501 | | | | | | | | |
|
| door-mid | | | | | | | | | 69.98 457 | | | | | | | | |
|
| test11 | | | | | | | | | 92.23 97 | | | | | | | | |
|
| door | | | | | | | | | 69.44 460 | | | | | | | | |
|
| HQP5-MVS | | | | | | | 66.98 183 | | | | | | | | | | |
|
| HQP-NCC | | | | | | 89.33 144 | | 89.17 116 | | 76.41 90 | 77.23 240 | | | | | | |
|
| ACMP_Plane | | | | | | 89.33 144 | | 89.17 116 | | 76.41 90 | 77.23 240 | | | | | | |
|
| BP-MVS | | | | | | | | | | | | | | | 77.47 159 | | |
|
| HQP4-MVS | | | | | | | | | | | 77.24 239 | | | 95.11 94 | | | 91.03 221 |
|
| HQP3-MVS | | | | | | | | | 92.19 105 | | | | | | | 85.99 211 | |
|
| HQP2-MVS | | | | | | | | | | | | | 60.17 237 | | | | |
|
| NP-MVS | | | | | | 89.62 129 | 68.32 135 | | | | | 90.24 184 | | | | | |
|
| MDTV_nov1_ep13_2view | | | | | | | 37.79 482 | 75.16 431 | | 55.10 445 | 66.53 412 | | 49.34 354 | | 53.98 397 | | 87.94 337 |
|
| MDTV_nov1_ep13 | | | | 69.97 368 | | 83.18 360 | 53.48 424 | 77.10 419 | 80.18 406 | 60.45 406 | 69.33 377 | 80.44 410 | 48.89 362 | 86.90 374 | 51.60 409 | 78.51 320 | |
|
| ACMMP++_ref | | | | | | | | | | | | | | | | 81.95 280 | |
|
| ACMMP++ | | | | | | | | | | | | | | | | 81.25 285 | |
|
| Test By Simon | | | | | | | | | | | | | 64.33 166 | | | | |
|