ETH3 D test6400 | | | 83.28 1 | 83.47 1 | 82.72 3 | 91.48 7 | 59.33 6 | 92.10 9 | 90.95 9 | 65.68 63 | 80.67 18 | 94.42 3 | 59.41 10 | 95.89 12 | 86.74 3 | 89.75 7 | 92.94 18 |
|
MCST-MVS | | | 83.01 2 | 83.30 3 | 82.15 11 | 92.84 2 | 57.58 16 | 93.77 1 | 91.10 6 | 75.95 3 | 77.10 28 | 93.09 20 | 54.15 28 | 95.57 13 | 85.80 4 | 85.87 38 | 93.31 11 |
|
DVP-MVS++ | | | 82.44 3 | 82.38 5 | 82.62 5 | 91.77 4 | 57.49 17 | 84.98 137 | 88.88 30 | 58.00 198 | 83.60 6 | 93.39 13 | 67.21 2 | 96.39 4 | 81.64 19 | 91.98 4 | 93.98 5 |
|
DPM-MVS | | | 82.39 4 | 82.36 6 | 82.49 6 | 80.12 187 | 59.50 5 | 92.24 8 | 90.72 10 | 69.37 22 | 83.22 8 | 94.47 2 | 63.81 5 | 93.18 34 | 74.02 71 | 93.25 2 | 94.80 1 |
|
DELS-MVS | | | 82.32 5 | 82.50 4 | 81.79 12 | 86.80 46 | 56.89 27 | 92.77 2 | 86.30 82 | 77.83 1 | 77.88 25 | 92.13 35 | 60.24 6 | 94.78 22 | 78.97 31 | 89.61 8 | 93.69 8 |
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 |
MSP-MVS | | | 82.30 6 | 83.47 1 | 78.80 51 | 82.99 123 | 52.71 131 | 85.04 134 | 88.63 39 | 66.08 58 | 86.77 3 | 92.75 24 | 72.05 1 | 91.46 68 | 83.35 9 | 93.53 1 | 92.23 33 |
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 |
SED-MVS | | | 81.92 7 | 81.75 8 | 82.44 8 | 89.48 19 | 56.89 27 | 92.48 3 | 88.94 28 | 57.50 213 | 84.61 4 | 94.09 4 | 58.81 12 | 96.37 6 | 82.28 14 | 87.60 18 | 94.06 3 |
|
CNVR-MVS | | | 81.76 8 | 81.90 7 | 81.33 18 | 90.04 11 | 57.70 14 | 91.71 10 | 88.87 32 | 70.31 16 | 77.64 27 | 93.87 8 | 52.58 35 | 93.91 28 | 84.17 6 | 87.92 16 | 92.39 29 |
|
DVP-MVS |  | | 81.30 9 | 81.00 12 | 82.20 9 | 89.40 22 | 57.45 19 | 92.34 5 | 89.99 16 | 57.71 207 | 81.91 12 | 93.64 11 | 55.17 21 | 96.44 2 | 81.68 16 | 87.13 21 | 92.72 24 |
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 |
CANet | | | 80.90 10 | 81.17 11 | 80.09 31 | 87.62 41 | 54.21 90 | 91.60 13 | 86.47 78 | 73.13 6 | 79.89 21 | 93.10 18 | 49.88 55 | 92.98 35 | 84.09 8 | 84.75 51 | 93.08 16 |
|
patch_mono-2 | | | 80.84 11 | 81.59 9 | 78.62 60 | 90.34 10 | 53.77 97 | 88.08 56 | 88.36 47 | 76.17 2 | 79.40 23 | 91.09 57 | 55.43 20 | 90.09 108 | 85.01 5 | 80.40 87 | 91.99 42 |
|
DeepPCF-MVS | | 69.37 1 | 80.65 12 | 81.56 10 | 77.94 83 | 85.46 67 | 49.56 203 | 90.99 20 | 86.66 76 | 70.58 14 | 80.07 20 | 95.30 1 | 56.18 18 | 90.97 83 | 82.57 13 | 86.22 36 | 93.28 12 |
|
HPM-MVS++ |  | | 80.50 13 | 80.71 13 | 79.88 33 | 87.34 43 | 55.20 63 | 89.93 29 | 87.55 62 | 66.04 61 | 79.46 22 | 93.00 22 | 53.10 32 | 91.76 62 | 80.40 26 | 89.56 9 | 92.68 25 |
|
CSCG | | | 80.41 14 | 79.72 14 | 82.49 6 | 89.12 27 | 57.67 15 | 89.29 41 | 91.54 3 | 59.19 173 | 71.82 75 | 90.05 91 | 59.72 9 | 96.04 10 | 78.37 36 | 88.40 14 | 93.75 7 |
|
PS-MVSNAJ | | | 80.06 15 | 79.52 16 | 81.68 14 | 85.58 61 | 60.97 3 | 91.69 11 | 87.02 67 | 70.62 13 | 80.75 17 | 93.22 17 | 37.77 185 | 92.50 46 | 82.75 11 | 86.25 35 | 91.57 51 |
|
xiu_mvs_v2_base | | | 79.86 16 | 79.31 17 | 81.53 15 | 85.03 77 | 60.73 4 | 91.65 12 | 86.86 70 | 70.30 17 | 80.77 16 | 93.07 21 | 37.63 190 | 92.28 51 | 82.73 12 | 85.71 39 | 91.57 51 |
|
DPE-MVS |  | | 79.82 17 | 79.66 15 | 80.29 25 | 89.27 26 | 55.08 68 | 88.70 49 | 87.92 53 | 55.55 242 | 81.21 15 | 93.69 10 | 56.51 17 | 94.27 25 | 78.36 37 | 85.70 40 | 91.51 54 |
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025 |
NCCC | | | 79.57 18 | 79.23 18 | 80.59 21 | 89.50 17 | 56.99 25 | 91.38 15 | 88.17 49 | 67.71 39 | 73.81 48 | 92.75 24 | 46.88 78 | 93.28 32 | 78.79 34 | 84.07 57 | 91.50 55 |
|
dcpmvs_2 | | | 79.33 19 | 78.94 19 | 80.49 22 | 89.75 14 | 56.54 33 | 84.83 143 | 83.68 148 | 67.85 36 | 69.36 91 | 90.24 82 | 60.20 7 | 92.10 57 | 84.14 7 | 80.40 87 | 92.82 21 |
|
SMA-MVS |  | | 79.10 20 | 78.76 20 | 80.12 29 | 84.42 85 | 55.87 48 | 87.58 69 | 86.76 73 | 61.48 131 | 80.26 19 | 93.10 18 | 46.53 83 | 92.41 48 | 79.97 27 | 88.77 11 | 92.08 37 |
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 |
ETH3D-3000-0.1 | | | 78.73 21 | 78.71 21 | 78.78 54 | 85.58 61 | 52.40 139 | 88.42 53 | 89.03 25 | 60.01 153 | 76.06 33 | 92.80 23 | 48.34 61 | 92.88 37 | 81.66 18 | 86.48 33 | 91.04 67 |
|
LFMVS | | | 78.52 22 | 77.14 38 | 82.67 4 | 89.58 15 | 58.90 8 | 91.27 18 | 88.05 51 | 63.22 101 | 74.63 40 | 90.83 68 | 41.38 154 | 94.40 23 | 75.42 58 | 79.90 97 | 94.72 2 |
|
APDe-MVS | | | 78.44 23 | 78.20 24 | 79.19 40 | 88.56 28 | 54.55 85 | 89.76 33 | 87.77 57 | 55.91 237 | 78.56 24 | 92.49 28 | 48.20 63 | 92.65 44 | 79.49 28 | 83.04 61 | 90.39 83 |
|
MG-MVS | | | 78.42 24 | 76.99 40 | 82.73 2 | 93.17 1 | 64.46 1 | 89.93 29 | 88.51 45 | 64.83 75 | 73.52 52 | 88.09 127 | 48.07 64 | 92.19 53 | 62.24 147 | 84.53 54 | 91.53 53 |
|
lupinMVS | | | 78.38 25 | 78.11 27 | 79.19 40 | 83.02 121 | 55.24 60 | 91.57 14 | 84.82 120 | 69.12 23 | 76.67 30 | 92.02 39 | 44.82 108 | 90.23 105 | 80.83 24 | 80.09 92 | 92.08 37 |
|
ETH3D cwj APD-0.16 | | | 78.36 26 | 78.19 25 | 78.86 49 | 84.21 91 | 52.68 132 | 86.70 91 | 89.02 26 | 59.13 178 | 75.37 35 | 92.49 28 | 49.06 60 | 93.20 33 | 80.67 25 | 87.08 23 | 90.71 76 |
|
EPNet | | | 78.36 26 | 78.49 22 | 77.97 81 | 85.49 64 | 52.04 146 | 89.36 38 | 84.07 141 | 73.22 5 | 77.03 29 | 91.72 47 | 49.32 59 | 90.17 107 | 73.46 77 | 82.77 62 | 91.69 46 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
TSAR-MVS + MP. | | | 78.31 28 | 78.26 23 | 78.48 64 | 81.33 164 | 56.31 40 | 81.59 228 | 86.41 79 | 69.61 21 | 81.72 14 | 88.16 126 | 55.09 23 | 88.04 173 | 74.12 70 | 86.31 34 | 91.09 66 |
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition |
canonicalmvs | | | 78.17 29 | 77.86 30 | 79.12 43 | 84.30 87 | 54.22 89 | 87.71 62 | 84.57 129 | 67.70 40 | 77.70 26 | 92.11 38 | 50.90 46 | 89.95 111 | 78.18 40 | 77.54 114 | 93.20 14 |
|
alignmvs | | | 78.08 30 | 77.98 28 | 78.39 69 | 83.53 104 | 53.22 119 | 89.77 32 | 85.45 95 | 66.11 56 | 76.59 32 | 91.99 41 | 54.07 29 | 89.05 132 | 77.34 46 | 77.00 119 | 92.89 20 |
|
DeepC-MVS_fast | | 67.50 3 | 78.00 31 | 77.63 31 | 79.13 42 | 88.52 29 | 55.12 65 | 89.95 28 | 85.98 88 | 68.31 28 | 71.33 81 | 92.75 24 | 45.52 97 | 90.37 98 | 71.15 88 | 85.14 47 | 91.91 43 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
VNet | | | 77.99 32 | 77.92 29 | 78.19 74 | 87.43 42 | 50.12 192 | 90.93 21 | 91.41 4 | 67.48 42 | 75.12 36 | 90.15 88 | 46.77 80 | 91.00 80 | 73.52 76 | 78.46 108 | 93.44 9 |
|
TSAR-MVS + GP. | | | 77.82 33 | 77.59 32 | 78.49 63 | 85.25 73 | 50.27 191 | 90.02 26 | 90.57 11 | 56.58 231 | 74.26 45 | 91.60 51 | 54.26 26 | 92.16 54 | 75.87 52 | 79.91 96 | 93.05 17 |
|
Regformer-1 | | | 77.80 34 | 77.44 34 | 78.88 47 | 87.78 39 | 52.44 138 | 87.60 64 | 90.08 14 | 68.86 24 | 72.49 67 | 91.79 44 | 47.69 70 | 94.90 20 | 73.57 75 | 77.05 116 | 89.31 108 |
|
SF-MVS | | | 77.64 35 | 77.42 35 | 78.32 72 | 83.75 101 | 52.47 137 | 86.63 93 | 87.80 54 | 58.78 186 | 74.63 40 | 92.38 30 | 47.75 68 | 91.35 70 | 78.18 40 | 86.85 26 | 91.15 64 |
|
test_prior3 | | | 77.59 36 | 77.33 36 | 78.39 69 | 86.35 49 | 54.91 74 | 89.04 43 | 85.45 95 | 61.88 122 | 73.55 50 | 91.46 55 | 48.01 66 | 89.70 117 | 74.73 63 | 85.46 42 | 90.55 78 |
|
PHI-MVS | | | 77.49 37 | 77.00 39 | 78.95 44 | 85.33 71 | 50.69 174 | 88.57 51 | 88.59 43 | 58.14 195 | 73.60 49 | 93.31 15 | 43.14 131 | 93.79 29 | 73.81 72 | 88.53 13 | 92.37 30 |
|
WTY-MVS | | | 77.47 38 | 77.52 33 | 77.30 96 | 88.33 32 | 46.25 270 | 88.46 52 | 90.32 12 | 71.40 10 | 72.32 70 | 91.72 47 | 53.44 30 | 92.37 49 | 66.28 117 | 75.42 133 | 93.28 12 |
|
casdiffmvs | | | 77.36 39 | 76.85 41 | 78.88 47 | 80.40 184 | 54.66 83 | 87.06 82 | 85.88 89 | 72.11 8 | 71.57 78 | 88.63 120 | 50.89 48 | 90.35 99 | 76.00 51 | 79.11 103 | 91.63 48 |
|
xxxxxxxxxxxxxcwj | | | 77.31 40 | 76.54 45 | 79.61 34 | 85.35 69 | 56.34 38 | 89.31 39 | 72.84 313 | 61.55 127 | 74.63 40 | 92.38 30 | 47.75 68 | 91.35 70 | 78.18 40 | 86.85 26 | 91.15 64 |
|
CS-MVS-test | | | 77.20 41 | 77.25 37 | 77.05 103 | 84.60 82 | 49.04 214 | 89.42 36 | 85.83 91 | 65.90 62 | 72.85 60 | 91.98 42 | 45.10 101 | 91.27 72 | 75.02 62 | 84.56 53 | 90.84 73 |
|
ETV-MVS | | | 77.17 42 | 76.74 43 | 78.48 64 | 81.80 147 | 54.55 85 | 86.13 102 | 85.33 101 | 68.20 30 | 73.10 56 | 90.52 76 | 45.23 100 | 90.66 91 | 79.37 29 | 80.95 78 | 90.22 87 |
|
Regformer-2 | | | 77.15 43 | 76.82 42 | 78.14 75 | 87.78 39 | 51.84 152 | 87.60 64 | 89.12 22 | 67.23 43 | 71.93 74 | 91.79 44 | 46.03 89 | 93.53 31 | 72.85 81 | 77.05 116 | 89.05 117 |
|
SteuartSystems-ACMMP | | | 77.08 44 | 76.33 50 | 79.34 38 | 80.98 168 | 55.31 58 | 89.76 33 | 86.91 69 | 62.94 105 | 71.65 76 | 91.56 52 | 42.33 138 | 92.56 45 | 77.14 47 | 83.69 59 | 90.15 90 |
Skip Steuart: Steuart Systems R&D Blog. |
jason | | | 77.01 45 | 76.45 48 | 78.69 57 | 79.69 192 | 54.74 77 | 90.56 24 | 83.99 144 | 68.26 29 | 74.10 46 | 90.91 65 | 42.14 142 | 89.99 110 | 79.30 30 | 79.12 102 | 91.36 59 |
jason: jason. |
testtj | | | 76.96 46 | 76.48 47 | 78.40 68 | 89.89 13 | 53.67 101 | 88.72 48 | 86.15 85 | 54.56 254 | 74.86 38 | 92.31 33 | 44.38 113 | 91.97 60 | 75.19 60 | 82.24 68 | 89.54 104 |
|
train_agg | | | 76.91 47 | 76.40 49 | 78.45 66 | 85.68 56 | 55.42 54 | 87.59 67 | 84.00 142 | 57.84 204 | 72.99 57 | 90.98 61 | 44.99 103 | 88.58 150 | 78.19 38 | 85.32 45 | 91.34 61 |
|
MVS | | | 76.91 47 | 75.48 58 | 81.23 19 | 84.56 83 | 55.21 62 | 80.23 251 | 91.64 2 | 58.65 188 | 65.37 129 | 91.48 54 | 45.72 94 | 95.05 17 | 72.11 85 | 89.52 10 | 93.44 9 |
|
DeepC-MVS | | 67.15 4 | 76.90 49 | 76.27 51 | 78.80 51 | 80.70 177 | 55.02 69 | 86.39 96 | 86.71 74 | 66.96 46 | 67.91 103 | 89.97 93 | 48.03 65 | 91.41 69 | 75.60 55 | 84.14 56 | 89.96 95 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
baseline | | | 76.86 50 | 76.24 52 | 78.71 56 | 80.47 183 | 54.20 92 | 83.90 168 | 84.88 119 | 71.38 11 | 71.51 79 | 89.15 109 | 50.51 49 | 90.55 95 | 75.71 53 | 78.65 106 | 91.39 57 |
|
CS-MVS | | | 76.77 51 | 76.70 44 | 76.99 108 | 83.55 103 | 48.75 223 | 88.60 50 | 85.18 109 | 66.38 51 | 72.47 68 | 91.62 50 | 45.53 96 | 90.99 82 | 74.48 66 | 82.51 64 | 91.23 62 |
|
PAPM | | | 76.76 52 | 76.07 54 | 78.81 50 | 80.20 185 | 59.11 7 | 86.86 89 | 86.23 83 | 68.60 26 | 70.18 90 | 88.84 114 | 51.57 40 | 87.16 196 | 65.48 123 | 86.68 30 | 90.15 90 |
|
MAR-MVS | | | 76.76 52 | 75.60 57 | 80.21 26 | 90.87 8 | 54.68 81 | 89.14 42 | 89.11 23 | 62.95 104 | 70.54 88 | 92.33 32 | 41.05 155 | 94.95 18 | 57.90 192 | 86.55 32 | 91.00 69 |
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 |
agg_prior1 | | | 76.68 54 | 76.24 52 | 78.00 79 | 85.64 59 | 54.92 72 | 87.55 70 | 83.61 152 | 57.99 200 | 72.53 65 | 91.05 58 | 45.36 98 | 88.10 170 | 77.76 44 | 84.68 52 | 90.99 70 |
|
PVSNet_Blended | | | 76.53 55 | 76.54 45 | 76.50 117 | 85.91 53 | 51.83 153 | 88.89 46 | 84.24 138 | 67.82 37 | 69.09 94 | 89.33 106 | 46.70 81 | 88.13 168 | 75.43 56 | 81.48 77 | 89.55 103 |
|
ACMMP_NAP | | | 76.43 56 | 75.66 56 | 78.73 55 | 81.92 145 | 54.67 82 | 84.06 163 | 85.35 100 | 61.10 136 | 72.99 57 | 91.50 53 | 40.25 163 | 91.00 80 | 76.84 48 | 86.98 24 | 90.51 82 |
|
MVS_111021_HR | | | 76.39 57 | 75.38 61 | 79.42 37 | 85.33 71 | 56.47 35 | 88.15 55 | 84.97 116 | 65.15 73 | 66.06 120 | 89.88 94 | 43.79 119 | 92.16 54 | 75.03 61 | 80.03 95 | 89.64 102 |
|
CHOSEN 1792x2688 | | | 76.24 58 | 74.03 78 | 82.88 1 | 83.09 117 | 62.84 2 | 85.73 113 | 85.39 98 | 69.79 19 | 64.87 137 | 83.49 186 | 41.52 153 | 93.69 30 | 70.55 91 | 81.82 73 | 92.12 36 |
|
SD-MVS | | | 76.18 59 | 74.85 69 | 80.18 27 | 85.39 68 | 56.90 26 | 85.75 111 | 82.45 173 | 56.79 226 | 74.48 44 | 91.81 43 | 43.72 122 | 90.75 89 | 74.61 65 | 78.65 106 | 92.91 19 |
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 |
APD-MVS |  | | 76.15 60 | 75.68 55 | 77.54 90 | 88.52 29 | 53.44 110 | 87.26 79 | 85.03 115 | 53.79 259 | 74.91 37 | 91.68 49 | 43.80 118 | 90.31 101 | 74.36 67 | 81.82 73 | 88.87 121 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
VDD-MVS | | | 76.08 61 | 74.97 67 | 79.44 36 | 84.27 90 | 53.33 116 | 91.13 19 | 85.88 89 | 65.33 70 | 72.37 69 | 89.34 104 | 32.52 251 | 92.76 41 | 77.90 43 | 75.96 127 | 92.22 35 |
|
CDPH-MVS | | | 76.05 62 | 75.19 63 | 78.62 60 | 86.51 48 | 54.98 71 | 87.32 74 | 84.59 128 | 58.62 189 | 70.75 86 | 90.85 67 | 43.10 133 | 90.63 93 | 70.50 92 | 84.51 55 | 90.24 86 |
|
Regformer-3 | | | 76.02 63 | 75.47 59 | 77.70 86 | 85.49 64 | 51.47 162 | 85.12 130 | 90.19 13 | 68.52 27 | 69.36 91 | 90.66 70 | 46.45 84 | 94.81 21 | 70.25 94 | 73.16 150 | 86.81 164 |
|
EIA-MVS | | | 75.92 64 | 75.18 64 | 78.13 76 | 85.14 74 | 51.60 158 | 87.17 80 | 85.32 102 | 64.69 76 | 68.56 97 | 90.53 75 | 45.79 93 | 91.58 65 | 67.21 110 | 82.18 70 | 91.20 63 |
|
test_yl | | | 75.85 65 | 74.83 70 | 78.91 45 | 88.08 36 | 51.94 148 | 91.30 16 | 89.28 19 | 57.91 201 | 71.19 83 | 89.20 107 | 42.03 145 | 92.77 39 | 69.41 96 | 75.07 138 | 92.01 40 |
|
DCV-MVSNet | | | 75.85 65 | 74.83 70 | 78.91 45 | 88.08 36 | 51.94 148 | 91.30 16 | 89.28 19 | 57.91 201 | 71.19 83 | 89.20 107 | 42.03 145 | 92.77 39 | 69.41 96 | 75.07 138 | 92.01 40 |
|
MVS_Test | | | 75.85 65 | 74.93 68 | 78.62 60 | 84.08 93 | 55.20 63 | 83.99 166 | 85.17 110 | 68.07 33 | 73.38 54 | 82.76 196 | 50.44 50 | 89.00 136 | 65.90 119 | 80.61 83 | 91.64 47 |
|
ZNCC-MVS | | | 75.82 68 | 75.02 66 | 78.23 73 | 83.88 99 | 53.80 96 | 86.91 88 | 86.05 87 | 59.71 158 | 67.85 104 | 90.55 74 | 42.23 140 | 91.02 79 | 72.66 83 | 85.29 46 | 89.87 98 |
|
CLD-MVS | | | 75.60 69 | 75.39 60 | 76.24 122 | 80.69 178 | 52.40 139 | 90.69 22 | 86.20 84 | 74.40 4 | 65.01 135 | 88.93 111 | 42.05 144 | 90.58 94 | 76.57 49 | 73.96 144 | 85.73 182 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
MP-MVS-pluss | | | 75.54 70 | 75.03 65 | 77.04 104 | 81.37 163 | 52.65 134 | 84.34 154 | 84.46 130 | 61.16 134 | 69.14 93 | 91.76 46 | 39.98 169 | 88.99 138 | 78.19 38 | 84.89 50 | 89.48 106 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
DROMVSNet | | | 75.30 71 | 75.20 62 | 75.62 136 | 80.98 168 | 49.00 215 | 87.43 71 | 84.68 126 | 63.49 98 | 70.97 85 | 90.15 88 | 42.86 135 | 91.14 77 | 74.33 68 | 81.90 72 | 86.71 166 |
|
Effi-MVS+ | | | 75.24 72 | 73.61 81 | 80.16 28 | 81.92 145 | 57.42 21 | 85.21 124 | 76.71 278 | 60.68 146 | 73.32 55 | 89.34 104 | 47.30 74 | 91.63 64 | 68.28 104 | 79.72 98 | 91.42 56 |
|
ET-MVSNet_ETH3D | | | 75.23 73 | 74.08 77 | 78.67 58 | 84.52 84 | 55.59 50 | 88.92 45 | 89.21 21 | 68.06 34 | 53.13 277 | 90.22 84 | 49.71 56 | 87.62 187 | 72.12 84 | 70.82 172 | 92.82 21 |
|
PAPR | | | 75.20 74 | 74.13 76 | 78.41 67 | 88.31 33 | 55.10 67 | 84.31 155 | 85.66 93 | 63.76 91 | 67.55 105 | 90.73 69 | 43.48 127 | 89.40 123 | 66.36 116 | 77.03 118 | 90.73 75 |
|
baseline2 | | | 75.15 75 | 74.54 74 | 76.98 109 | 81.67 150 | 51.74 155 | 83.84 169 | 91.94 1 | 69.97 18 | 58.98 206 | 86.02 156 | 59.73 8 | 91.73 63 | 68.37 103 | 70.40 176 | 87.48 148 |
|
diffmvs | | | 75.11 76 | 74.65 72 | 76.46 119 | 78.52 217 | 53.35 114 | 83.28 189 | 79.94 210 | 70.51 15 | 71.64 77 | 88.72 115 | 46.02 90 | 86.08 231 | 77.52 45 | 75.75 131 | 89.96 95 |
|
Regformer-4 | | | 75.06 77 | 74.59 73 | 76.47 118 | 85.49 64 | 50.33 187 | 85.12 130 | 88.61 41 | 66.42 49 | 68.48 98 | 90.66 70 | 44.15 114 | 92.68 42 | 69.24 98 | 73.16 150 | 86.39 172 |
|
MP-MVS |  | | 74.99 78 | 74.33 75 | 76.95 110 | 82.89 127 | 53.05 125 | 85.63 115 | 83.50 154 | 57.86 203 | 67.25 107 | 90.24 82 | 43.38 128 | 88.85 144 | 76.03 50 | 82.23 69 | 88.96 119 |
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
GST-MVS | | | 74.87 79 | 73.90 79 | 77.77 84 | 83.30 110 | 53.45 109 | 85.75 111 | 85.29 104 | 59.22 172 | 66.50 115 | 89.85 95 | 40.94 156 | 90.76 88 | 70.94 90 | 83.35 60 | 89.10 116 |
|
#test# | | | 74.86 80 | 73.78 80 | 78.10 77 | 84.30 87 | 53.68 99 | 86.95 85 | 84.36 132 | 59.00 182 | 65.78 124 | 90.56 72 | 40.70 160 | 90.90 84 | 71.48 86 | 80.88 79 | 89.71 99 |
|
3Dnovator | | 64.70 6 | 74.46 81 | 72.48 91 | 80.41 24 | 82.84 129 | 55.40 57 | 83.08 193 | 88.61 41 | 67.61 41 | 59.85 191 | 88.66 116 | 34.57 232 | 93.97 26 | 58.42 183 | 88.70 12 | 91.85 45 |
|
HFP-MVS | | | 74.37 82 | 73.13 85 | 78.10 77 | 84.30 87 | 53.68 99 | 85.58 116 | 84.36 132 | 56.82 224 | 65.78 124 | 90.56 72 | 40.70 160 | 90.90 84 | 69.18 99 | 80.88 79 | 89.71 99 |
|
VDDNet | | | 74.37 82 | 72.13 101 | 81.09 20 | 79.58 193 | 56.52 34 | 90.02 26 | 86.70 75 | 52.61 268 | 71.23 82 | 87.20 141 | 31.75 261 | 93.96 27 | 74.30 69 | 75.77 130 | 92.79 23 |
|
MSLP-MVS++ | | | 74.21 84 | 72.25 97 | 80.11 30 | 81.45 161 | 56.47 35 | 86.32 98 | 79.65 218 | 58.19 194 | 66.36 116 | 92.29 34 | 36.11 216 | 90.66 91 | 67.39 108 | 82.49 65 | 93.18 15 |
|
API-MVS | | | 74.17 85 | 72.07 104 | 80.49 22 | 90.02 12 | 58.55 9 | 87.30 76 | 84.27 135 | 57.51 212 | 65.77 126 | 87.77 133 | 41.61 151 | 95.97 11 | 51.71 235 | 82.63 63 | 86.94 156 |
|
zzz-MVS | | | 74.15 86 | 73.11 86 | 77.27 98 | 81.54 157 | 53.57 103 | 84.02 165 | 81.31 190 | 59.41 165 | 68.39 99 | 90.96 63 | 36.07 217 | 89.01 134 | 73.80 73 | 82.45 66 | 89.23 110 |
|
IB-MVS | | 68.87 2 | 74.01 87 | 72.03 106 | 79.94 32 | 83.04 120 | 55.50 52 | 90.24 25 | 88.65 37 | 67.14 44 | 61.38 180 | 81.74 212 | 53.21 31 | 94.28 24 | 60.45 167 | 62.41 236 | 90.03 94 |
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 |
h-mvs33 | | | 73.95 88 | 72.89 87 | 77.15 102 | 80.17 186 | 50.37 184 | 84.68 147 | 83.33 155 | 68.08 31 | 71.97 72 | 88.65 119 | 42.50 136 | 91.15 76 | 78.82 32 | 57.78 275 | 89.91 97 |
|
HY-MVS | | 67.03 5 | 73.90 89 | 73.14 83 | 76.18 126 | 84.70 81 | 47.36 252 | 75.56 283 | 86.36 81 | 66.27 53 | 70.66 87 | 83.91 179 | 51.05 44 | 89.31 124 | 67.10 111 | 72.61 158 | 91.88 44 |
|
CostFormer | | | 73.89 90 | 72.30 96 | 78.66 59 | 82.36 141 | 56.58 30 | 75.56 283 | 85.30 103 | 66.06 59 | 70.50 89 | 76.88 263 | 57.02 15 | 89.06 130 | 68.27 105 | 68.74 186 | 90.33 85 |
|
test_part1 | | | 73.80 91 | 72.13 101 | 78.79 53 | 85.92 52 | 58.26 10 | 90.60 23 | 86.85 71 | 63.98 86 | 63.95 153 | 81.54 215 | 52.08 39 | 92.24 52 | 64.93 132 | 59.32 254 | 85.87 180 |
|
ACMMPR | | | 73.76 92 | 72.61 88 | 77.24 101 | 83.92 97 | 52.96 128 | 85.58 116 | 84.29 134 | 56.82 224 | 65.12 131 | 90.45 77 | 37.24 200 | 90.18 106 | 69.18 99 | 80.84 81 | 88.58 129 |
|
region2R | | | 73.75 93 | 72.55 90 | 77.33 94 | 83.90 98 | 52.98 127 | 85.54 119 | 84.09 140 | 56.83 223 | 65.10 132 | 90.45 77 | 37.34 198 | 90.24 104 | 68.89 101 | 80.83 82 | 88.77 125 |
|
CANet_DTU | | | 73.71 94 | 73.14 83 | 75.40 141 | 82.61 137 | 50.05 193 | 84.67 149 | 79.36 226 | 69.72 20 | 75.39 34 | 90.03 92 | 29.41 276 | 85.93 237 | 67.99 106 | 79.11 103 | 90.22 87 |
|
thisisatest0515 | | | 73.64 95 | 72.20 99 | 77.97 81 | 81.63 151 | 53.01 126 | 86.69 92 | 88.81 34 | 62.53 111 | 64.06 149 | 85.65 161 | 52.15 38 | 92.50 46 | 58.43 181 | 69.84 179 | 88.39 133 |
|
MVSFormer | | | 73.53 96 | 72.19 100 | 77.57 89 | 83.02 121 | 55.24 60 | 81.63 225 | 81.44 188 | 50.28 283 | 76.67 30 | 90.91 65 | 44.82 108 | 86.11 225 | 60.83 159 | 80.09 92 | 91.36 59 |
|
iter_conf05 | | | 73.51 97 | 72.24 98 | 77.33 94 | 87.93 38 | 55.97 46 | 87.90 61 | 70.81 327 | 68.72 25 | 64.04 150 | 84.36 174 | 47.54 72 | 90.87 86 | 71.11 89 | 67.75 194 | 85.13 193 |
|
PVSNet_BlendedMVS | | | 73.42 98 | 73.30 82 | 73.76 179 | 85.91 53 | 51.83 153 | 86.18 101 | 84.24 138 | 65.40 67 | 69.09 94 | 80.86 221 | 46.70 81 | 88.13 168 | 75.43 56 | 65.92 207 | 81.33 259 |
|
PVSNet_Blended_VisFu | | | 73.40 99 | 72.44 92 | 76.30 120 | 81.32 165 | 54.70 80 | 85.81 107 | 78.82 236 | 63.70 92 | 64.53 142 | 85.38 165 | 47.11 77 | 87.38 193 | 67.75 107 | 77.55 113 | 86.81 164 |
|
MVSTER | | | 73.25 100 | 72.33 94 | 76.01 131 | 85.54 63 | 53.76 98 | 83.52 174 | 87.16 65 | 67.06 45 | 63.88 156 | 81.66 213 | 52.77 33 | 90.44 96 | 64.66 133 | 64.69 212 | 83.84 216 |
|
EI-MVSNet-Vis-set | | | 73.19 101 | 72.60 89 | 74.99 150 | 82.56 138 | 49.80 199 | 82.55 206 | 89.00 27 | 66.17 55 | 65.89 123 | 88.98 110 | 43.83 117 | 92.29 50 | 65.38 130 | 69.01 184 | 82.87 234 |
|
PMMVS | | | 72.98 102 | 72.05 105 | 75.78 135 | 83.57 102 | 48.60 226 | 84.08 161 | 82.85 168 | 61.62 126 | 68.24 101 | 90.33 81 | 28.35 280 | 87.78 182 | 72.71 82 | 76.69 121 | 90.95 71 |
|
XVS | | | 72.92 103 | 71.62 108 | 76.81 112 | 83.41 105 | 52.48 135 | 84.88 141 | 83.20 161 | 58.03 196 | 63.91 154 | 89.63 99 | 35.50 223 | 89.78 114 | 65.50 121 | 80.50 85 | 88.16 134 |
|
test2506 | | | 72.91 104 | 72.43 93 | 74.32 163 | 80.12 187 | 44.18 294 | 83.19 190 | 84.77 123 | 64.02 83 | 65.97 121 | 87.43 138 | 47.67 71 | 88.72 145 | 59.08 174 | 79.66 99 | 90.08 92 |
|
TESTMET0.1,1 | | | 72.86 105 | 72.33 94 | 74.46 157 | 81.98 144 | 50.77 172 | 85.13 127 | 85.47 94 | 66.09 57 | 67.30 106 | 83.69 184 | 37.27 199 | 83.57 267 | 65.06 131 | 78.97 105 | 89.05 117 |
|
Fast-Effi-MVS+ | | | 72.73 106 | 71.15 117 | 77.48 91 | 82.75 132 | 54.76 76 | 86.77 90 | 80.64 200 | 63.05 103 | 65.93 122 | 84.01 177 | 44.42 112 | 89.03 133 | 56.45 206 | 76.36 126 | 88.64 127 |
|
MTAPA | | | 72.73 106 | 71.22 115 | 77.27 98 | 81.54 157 | 53.57 103 | 67.06 328 | 81.31 190 | 59.41 165 | 68.39 99 | 90.96 63 | 36.07 217 | 89.01 134 | 73.80 73 | 82.45 66 | 89.23 110 |
|
PGM-MVS | | | 72.60 108 | 71.20 116 | 76.80 114 | 82.95 124 | 52.82 130 | 83.07 194 | 82.14 175 | 56.51 232 | 63.18 163 | 89.81 96 | 35.68 222 | 89.76 116 | 67.30 109 | 80.19 91 | 87.83 142 |
|
HPM-MVS |  | | 72.60 108 | 71.50 110 | 75.89 133 | 82.02 143 | 51.42 164 | 80.70 245 | 83.05 163 | 56.12 236 | 64.03 151 | 89.53 100 | 37.55 192 | 88.37 158 | 70.48 93 | 80.04 94 | 87.88 141 |
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
CP-MVS | | | 72.59 110 | 71.46 111 | 76.00 132 | 82.93 126 | 52.32 143 | 86.93 87 | 82.48 172 | 55.15 245 | 63.65 159 | 90.44 80 | 35.03 229 | 88.53 154 | 68.69 102 | 77.83 112 | 87.15 154 |
|
baseline1 | | | 72.51 111 | 72.12 103 | 73.69 182 | 85.05 75 | 44.46 288 | 83.51 178 | 86.13 86 | 71.61 9 | 64.64 139 | 87.97 130 | 55.00 24 | 89.48 122 | 59.07 175 | 56.05 288 | 87.13 155 |
|
EI-MVSNet-UG-set | | | 72.37 112 | 71.73 107 | 74.29 164 | 81.60 153 | 49.29 209 | 81.85 220 | 88.64 38 | 65.29 72 | 65.05 133 | 88.29 123 | 43.18 129 | 91.83 61 | 63.74 137 | 67.97 191 | 81.75 245 |
|
MS-PatchMatch | | | 72.34 113 | 71.26 114 | 75.61 137 | 82.38 140 | 55.55 51 | 88.00 57 | 89.95 17 | 65.38 68 | 56.51 251 | 80.74 223 | 32.28 254 | 92.89 36 | 57.95 191 | 88.10 15 | 78.39 291 |
|
HQP-MVS | | | 72.34 113 | 71.44 112 | 75.03 148 | 79.02 203 | 51.56 159 | 88.00 57 | 83.68 148 | 65.45 64 | 64.48 143 | 85.13 166 | 37.35 196 | 88.62 148 | 66.70 112 | 73.12 152 | 84.91 197 |
|
mvs_anonymous | | | 72.29 115 | 70.74 119 | 76.94 111 | 82.85 128 | 54.72 79 | 78.43 270 | 81.54 186 | 63.77 90 | 61.69 179 | 79.32 233 | 51.11 43 | 85.31 244 | 62.15 149 | 75.79 129 | 90.79 74 |
|
3Dnovator+ | | 62.71 7 | 72.29 115 | 70.50 122 | 77.65 88 | 83.40 108 | 51.29 168 | 87.32 74 | 86.40 80 | 59.01 181 | 58.49 219 | 88.32 122 | 32.40 252 | 91.27 72 | 57.04 201 | 82.15 71 | 90.38 84 |
|
nrg030 | | | 72.27 117 | 71.56 109 | 74.42 159 | 75.93 255 | 50.60 176 | 86.97 84 | 83.21 160 | 62.75 107 | 67.15 108 | 84.38 172 | 50.07 52 | 86.66 211 | 71.19 87 | 62.37 237 | 85.99 175 |
|
VPNet | | | 72.07 118 | 71.42 113 | 74.04 170 | 78.64 214 | 47.17 257 | 89.91 31 | 87.97 52 | 72.56 7 | 64.66 138 | 85.04 168 | 41.83 149 | 88.33 161 | 61.17 157 | 60.97 243 | 86.62 167 |
|
DP-MVS Recon | | | 71.99 119 | 70.31 126 | 77.01 106 | 90.65 9 | 53.44 110 | 89.37 37 | 82.97 166 | 56.33 234 | 63.56 161 | 89.47 101 | 34.02 236 | 92.15 56 | 54.05 218 | 72.41 159 | 85.43 189 |
|
QAPM | | | 71.88 120 | 69.33 142 | 79.52 35 | 82.20 142 | 54.30 88 | 86.30 99 | 88.77 35 | 56.61 230 | 59.72 193 | 87.48 136 | 33.90 239 | 95.36 14 | 47.48 260 | 81.49 76 | 88.90 120 |
|
ECVR-MVS |  | | 71.81 121 | 71.00 118 | 74.26 165 | 80.12 187 | 43.49 300 | 84.69 146 | 82.16 174 | 64.02 83 | 64.64 139 | 87.43 138 | 35.04 228 | 89.21 126 | 61.24 156 | 79.66 99 | 90.08 92 |
|
PAPM_NR | | | 71.80 122 | 69.98 133 | 77.26 100 | 81.54 157 | 53.34 115 | 78.60 269 | 85.25 107 | 53.46 261 | 60.53 188 | 88.66 116 | 45.69 95 | 89.24 125 | 56.49 203 | 79.62 101 | 89.19 113 |
|
mPP-MVS | | | 71.79 123 | 70.38 125 | 76.04 130 | 82.65 136 | 52.06 145 | 84.45 151 | 81.78 183 | 55.59 241 | 62.05 177 | 89.68 98 | 33.48 243 | 88.28 165 | 65.45 126 | 78.24 111 | 87.77 144 |
|
xiu_mvs_v1_base_debu | | | 71.60 124 | 70.29 127 | 75.55 138 | 77.26 236 | 53.15 120 | 85.34 120 | 79.37 223 | 55.83 238 | 72.54 62 | 90.19 85 | 22.38 320 | 86.66 211 | 73.28 78 | 76.39 123 | 86.85 160 |
|
xiu_mvs_v1_base | | | 71.60 124 | 70.29 127 | 75.55 138 | 77.26 236 | 53.15 120 | 85.34 120 | 79.37 223 | 55.83 238 | 72.54 62 | 90.19 85 | 22.38 320 | 86.66 211 | 73.28 78 | 76.39 123 | 86.85 160 |
|
xiu_mvs_v1_base_debi | | | 71.60 124 | 70.29 127 | 75.55 138 | 77.26 236 | 53.15 120 | 85.34 120 | 79.37 223 | 55.83 238 | 72.54 62 | 90.19 85 | 22.38 320 | 86.66 211 | 73.28 78 | 76.39 123 | 86.85 160 |
|
hse-mvs2 | | | 71.44 127 | 70.68 120 | 73.73 181 | 76.34 246 | 47.44 251 | 79.45 263 | 79.47 222 | 68.08 31 | 71.97 72 | 86.01 158 | 42.50 136 | 86.93 204 | 78.82 32 | 53.46 310 | 86.83 163 |
|
EPP-MVSNet | | | 71.14 128 | 70.07 132 | 74.33 162 | 79.18 200 | 46.52 264 | 83.81 170 | 86.49 77 | 56.32 235 | 57.95 225 | 84.90 170 | 54.23 27 | 89.14 129 | 58.14 187 | 69.65 181 | 87.33 151 |
|
VPA-MVSNet | | | 71.12 129 | 70.66 121 | 72.49 208 | 78.75 209 | 44.43 290 | 87.64 63 | 90.02 15 | 63.97 87 | 65.02 134 | 81.58 214 | 42.14 142 | 87.42 192 | 63.42 139 | 63.38 224 | 85.63 186 |
|
1314 | | | 71.11 130 | 69.41 139 | 76.22 123 | 79.32 197 | 50.49 179 | 80.23 251 | 85.14 113 | 59.44 164 | 58.93 208 | 88.89 113 | 33.83 241 | 89.60 121 | 61.49 154 | 77.42 115 | 88.57 130 |
|
test1111 | | | 71.06 131 | 70.42 124 | 72.97 197 | 79.48 194 | 41.49 318 | 84.82 144 | 82.74 169 | 64.20 81 | 62.98 166 | 87.43 138 | 35.20 226 | 87.92 175 | 58.54 180 | 78.42 109 | 89.49 105 |
|
tpmrst | | | 71.04 132 | 69.77 135 | 74.86 151 | 83.19 114 | 55.86 49 | 75.64 282 | 78.73 240 | 67.88 35 | 64.99 136 | 73.73 289 | 49.96 54 | 79.56 301 | 65.92 118 | 67.85 193 | 89.14 115 |
|
MVP-Stereo | | | 70.97 133 | 70.44 123 | 72.59 205 | 76.03 254 | 51.36 165 | 85.02 136 | 86.99 68 | 60.31 150 | 56.53 250 | 78.92 239 | 40.11 167 | 90.00 109 | 60.00 172 | 90.01 6 | 76.41 313 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
HQP_MVS | | | 70.96 134 | 69.91 134 | 74.12 168 | 77.95 225 | 49.57 201 | 85.76 109 | 82.59 170 | 63.60 95 | 62.15 174 | 83.28 190 | 36.04 219 | 88.30 163 | 65.46 124 | 72.34 160 | 84.49 200 |
|
SR-MVS | | | 70.92 135 | 69.73 136 | 74.50 156 | 83.38 109 | 50.48 180 | 84.27 156 | 79.35 227 | 48.96 292 | 66.57 114 | 90.45 77 | 33.65 242 | 87.11 197 | 66.42 114 | 74.56 141 | 85.91 178 |
|
tpm2 | | | 70.82 136 | 68.44 151 | 77.98 80 | 80.78 175 | 56.11 42 | 74.21 293 | 81.28 193 | 60.24 151 | 68.04 102 | 75.27 281 | 52.26 37 | 88.50 155 | 55.82 209 | 68.03 190 | 89.33 107 |
|
ACMMP |  | | 70.81 137 | 69.29 143 | 75.39 142 | 81.52 160 | 51.92 150 | 83.43 181 | 83.03 164 | 56.67 229 | 58.80 213 | 88.91 112 | 31.92 259 | 88.58 150 | 65.89 120 | 73.39 149 | 85.67 183 |
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 |
OPM-MVS | | | 70.75 138 | 69.58 137 | 74.26 165 | 75.55 260 | 51.34 166 | 86.05 104 | 83.29 159 | 61.94 121 | 62.95 167 | 85.77 160 | 34.15 235 | 88.44 156 | 65.44 127 | 71.07 169 | 82.99 231 |
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS). |
ab-mvs | | | 70.65 139 | 69.11 145 | 75.29 144 | 80.87 174 | 46.23 271 | 73.48 297 | 85.24 108 | 59.99 154 | 66.65 110 | 80.94 220 | 43.13 132 | 88.69 146 | 63.58 138 | 68.07 189 | 90.95 71 |
|
Vis-MVSNet |  | | 70.61 140 | 69.34 141 | 74.42 159 | 80.95 173 | 48.49 231 | 86.03 105 | 77.51 263 | 58.74 187 | 65.55 128 | 87.78 132 | 34.37 233 | 85.95 236 | 52.53 233 | 80.61 83 | 88.80 123 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
sss | | | 70.49 141 | 70.13 131 | 71.58 232 | 81.59 154 | 39.02 329 | 80.78 244 | 84.71 125 | 59.34 168 | 66.61 112 | 88.09 127 | 37.17 201 | 85.52 240 | 61.82 153 | 71.02 170 | 90.20 89 |
|
CDS-MVSNet | | | 70.48 142 | 69.43 138 | 73.64 184 | 77.56 231 | 48.83 222 | 83.51 178 | 77.45 264 | 63.27 100 | 62.33 173 | 85.54 164 | 43.85 116 | 83.29 271 | 57.38 200 | 74.00 143 | 88.79 124 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
thisisatest0530 | | | 70.47 143 | 68.56 149 | 76.20 125 | 79.78 191 | 51.52 161 | 83.49 180 | 88.58 44 | 57.62 210 | 58.60 215 | 82.79 195 | 51.03 45 | 91.48 67 | 52.84 226 | 62.36 238 | 85.59 187 |
|
XXY-MVS | | | 70.18 144 | 69.28 144 | 72.89 200 | 77.64 229 | 42.88 306 | 85.06 133 | 87.50 63 | 62.58 110 | 62.66 171 | 82.34 206 | 43.64 124 | 89.83 113 | 58.42 183 | 63.70 219 | 85.96 177 |
|
Anonymous202405211 | | | 70.11 145 | 67.88 160 | 76.79 115 | 87.20 44 | 47.24 256 | 89.49 35 | 77.38 266 | 54.88 250 | 66.14 118 | 86.84 147 | 20.93 330 | 91.54 66 | 56.45 206 | 71.62 165 | 91.59 49 |
|
PCF-MVS | | 61.03 10 | 70.10 146 | 68.40 152 | 75.22 147 | 77.15 240 | 51.99 147 | 79.30 265 | 82.12 176 | 56.47 233 | 61.88 178 | 86.48 154 | 43.98 115 | 87.24 195 | 55.37 210 | 72.79 157 | 86.43 171 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
BH-RMVSNet | | | 70.08 147 | 68.01 157 | 76.27 121 | 84.21 91 | 51.22 170 | 87.29 77 | 79.33 229 | 58.96 184 | 63.63 160 | 86.77 148 | 33.29 245 | 90.30 103 | 44.63 275 | 73.96 144 | 87.30 153 |
|
1112_ss | | | 70.05 148 | 69.37 140 | 72.10 214 | 80.77 176 | 42.78 307 | 85.12 130 | 76.75 276 | 59.69 159 | 61.19 182 | 92.12 36 | 47.48 73 | 83.84 262 | 53.04 224 | 68.21 188 | 89.66 101 |
|
BH-w/o | | | 70.02 149 | 68.51 150 | 74.56 155 | 82.77 130 | 50.39 183 | 86.60 94 | 78.14 251 | 59.77 157 | 59.65 194 | 85.57 163 | 39.27 174 | 87.30 194 | 49.86 245 | 74.94 140 | 85.99 175 |
|
FIs | | | 70.00 150 | 70.24 130 | 69.30 263 | 77.93 227 | 38.55 331 | 83.99 166 | 87.72 59 | 66.86 47 | 57.66 232 | 84.17 176 | 52.28 36 | 85.31 244 | 52.72 232 | 68.80 185 | 84.02 207 |
|
OpenMVS |  | 61.00 11 | 69.99 151 | 67.55 170 | 77.30 96 | 78.37 221 | 54.07 94 | 84.36 153 | 85.76 92 | 57.22 217 | 56.71 247 | 87.67 134 | 30.79 268 | 92.83 38 | 43.04 281 | 84.06 58 | 85.01 195 |
|
GeoE | | | 69.96 152 | 67.88 160 | 76.22 123 | 81.11 167 | 51.71 156 | 84.15 159 | 76.74 277 | 59.83 156 | 60.91 183 | 84.38 172 | 41.56 152 | 88.10 170 | 51.67 236 | 70.57 174 | 88.84 122 |
|
HyFIR lowres test | | | 69.94 153 | 67.58 167 | 77.04 104 | 77.11 241 | 57.29 22 | 81.49 233 | 79.11 232 | 58.27 193 | 58.86 211 | 80.41 225 | 42.33 138 | 86.96 202 | 61.91 151 | 68.68 187 | 86.87 158 |
|
114514_t | | | 69.87 154 | 67.88 160 | 75.85 134 | 88.38 31 | 52.35 142 | 86.94 86 | 83.68 148 | 53.70 260 | 55.68 257 | 85.60 162 | 30.07 273 | 91.20 74 | 55.84 208 | 71.02 170 | 83.99 209 |
|
miper_enhance_ethall | | | 69.77 155 | 68.90 147 | 72.38 210 | 78.93 206 | 49.91 196 | 83.29 188 | 78.85 234 | 64.90 74 | 59.37 200 | 79.46 231 | 52.77 33 | 85.16 249 | 63.78 136 | 58.72 258 | 82.08 241 |
|
Anonymous20240529 | | | 69.71 156 | 67.28 175 | 77.00 107 | 83.78 100 | 50.36 185 | 88.87 47 | 85.10 114 | 47.22 300 | 64.03 151 | 83.37 188 | 27.93 285 | 92.10 57 | 57.78 195 | 67.44 195 | 88.53 131 |
|
TR-MVS | | | 69.71 156 | 67.85 163 | 75.27 145 | 82.94 125 | 48.48 232 | 87.40 73 | 80.86 197 | 57.15 219 | 64.61 141 | 87.08 144 | 32.67 250 | 89.64 120 | 46.38 267 | 71.55 167 | 87.68 146 |
|
EI-MVSNet | | | 69.70 158 | 68.70 148 | 72.68 203 | 75.00 267 | 48.90 219 | 79.54 260 | 87.16 65 | 61.05 137 | 63.88 156 | 83.74 182 | 45.87 91 | 90.44 96 | 57.42 199 | 64.68 213 | 78.70 284 |
|
test-LLR | | | 69.65 159 | 69.01 146 | 71.60 230 | 78.67 211 | 48.17 239 | 85.13 127 | 79.72 215 | 59.18 175 | 63.13 164 | 82.58 201 | 36.91 205 | 80.24 292 | 60.56 163 | 75.17 135 | 86.39 172 |
|
test1172 | | | 69.64 160 | 68.38 153 | 73.41 190 | 82.77 130 | 48.84 221 | 82.79 200 | 78.34 249 | 47.02 303 | 65.27 130 | 90.07 90 | 31.17 265 | 86.09 229 | 64.51 134 | 73.49 148 | 85.31 190 |
|
APD-MVS_3200maxsize | | | 69.62 161 | 68.23 155 | 73.80 178 | 81.58 155 | 48.22 238 | 81.91 218 | 79.50 221 | 48.21 294 | 64.24 148 | 89.75 97 | 31.91 260 | 87.55 189 | 63.08 141 | 73.85 146 | 85.64 185 |
|
v2v482 | | | 69.55 162 | 67.64 166 | 75.26 146 | 72.32 298 | 53.83 95 | 84.93 140 | 81.94 178 | 65.37 69 | 60.80 185 | 79.25 235 | 41.62 150 | 88.98 139 | 63.03 142 | 59.51 251 | 82.98 232 |
|
TAMVS | | | 69.51 163 | 68.16 156 | 73.56 187 | 76.30 249 | 48.71 225 | 82.57 204 | 77.17 269 | 62.10 117 | 61.32 181 | 84.23 175 | 41.90 147 | 83.46 269 | 54.80 214 | 73.09 154 | 88.50 132 |
|
PVSNet | | 62.49 8 | 69.27 164 | 67.81 164 | 73.64 184 | 84.41 86 | 51.85 151 | 84.63 150 | 77.80 256 | 66.42 49 | 59.80 192 | 84.95 169 | 22.14 325 | 80.44 290 | 55.03 211 | 75.11 137 | 88.62 128 |
|
MVS_111021_LR | | | 69.07 165 | 67.91 158 | 72.54 206 | 77.27 235 | 49.56 203 | 79.77 256 | 73.96 303 | 59.33 170 | 60.73 186 | 87.82 131 | 30.19 272 | 81.53 279 | 69.94 95 | 72.19 162 | 86.53 168 |
|
mvs-test1 | | | 69.04 166 | 67.57 169 | 73.44 189 | 75.17 261 | 51.68 157 | 86.57 95 | 74.48 297 | 62.15 115 | 62.07 176 | 85.79 159 | 30.59 269 | 87.48 190 | 65.40 128 | 65.94 206 | 81.18 263 |
|
GA-MVS | | | 69.04 166 | 66.70 185 | 76.06 129 | 75.11 263 | 52.36 141 | 83.12 192 | 80.23 206 | 63.32 99 | 60.65 187 | 79.22 236 | 30.98 267 | 88.37 158 | 61.25 155 | 66.41 201 | 87.46 149 |
|
cascas | | | 69.01 168 | 66.13 196 | 77.66 87 | 79.36 195 | 55.41 56 | 86.99 83 | 83.75 147 | 56.69 228 | 58.92 209 | 81.35 217 | 24.31 308 | 92.10 57 | 53.23 221 | 70.61 173 | 85.46 188 |
|
cl22 | | | 68.85 169 | 67.69 165 | 72.35 211 | 78.07 224 | 49.98 195 | 82.45 209 | 78.48 246 | 62.50 112 | 58.46 220 | 77.95 244 | 49.99 53 | 85.17 248 | 62.55 144 | 58.72 258 | 81.90 243 |
|
FMVSNet3 | | | 68.84 170 | 67.40 173 | 73.19 193 | 85.05 75 | 48.53 229 | 85.71 114 | 85.36 99 | 60.90 141 | 57.58 234 | 79.15 237 | 42.16 141 | 86.77 207 | 47.25 262 | 63.40 221 | 84.27 204 |
|
UniMVSNet_NR-MVSNet | | | 68.82 171 | 68.29 154 | 70.40 251 | 75.71 258 | 42.59 309 | 84.23 157 | 86.78 72 | 66.31 52 | 58.51 216 | 82.45 203 | 51.57 40 | 84.64 258 | 53.11 222 | 55.96 289 | 83.96 213 |
|
v1144 | | | 68.81 172 | 66.82 180 | 74.80 153 | 72.34 297 | 53.46 106 | 84.68 147 | 81.77 184 | 64.25 80 | 60.28 189 | 77.91 245 | 40.23 164 | 88.95 140 | 60.37 168 | 59.52 250 | 81.97 242 |
|
IS-MVSNet | | | 68.80 173 | 67.55 170 | 72.54 206 | 78.50 218 | 43.43 301 | 81.03 239 | 79.35 227 | 59.12 179 | 57.27 242 | 86.71 149 | 46.05 88 | 87.70 184 | 44.32 276 | 75.60 132 | 86.49 169 |
|
1121 | | | 68.79 174 | 66.77 182 | 74.82 152 | 83.08 118 | 53.46 106 | 80.23 251 | 71.53 322 | 45.47 315 | 66.31 117 | 87.19 142 | 34.02 236 | 85.13 250 | 52.78 228 | 80.36 89 | 85.87 180 |
|
PS-MVSNAJss | | | 68.78 175 | 67.17 177 | 73.62 186 | 73.01 288 | 48.33 237 | 84.95 139 | 84.81 121 | 59.30 171 | 58.91 210 | 79.84 228 | 37.77 185 | 88.86 143 | 62.83 143 | 63.12 231 | 83.67 218 |
|
thres200 | | | 68.71 176 | 67.27 176 | 73.02 195 | 84.73 80 | 46.76 260 | 85.03 135 | 87.73 58 | 62.34 114 | 59.87 190 | 83.45 187 | 43.15 130 | 88.32 162 | 31.25 328 | 67.91 192 | 83.98 211 |
|
UGNet | | | 68.71 176 | 67.11 178 | 73.50 188 | 80.55 182 | 47.61 248 | 84.08 161 | 78.51 245 | 59.45 163 | 65.68 127 | 82.73 199 | 23.78 311 | 85.08 252 | 52.80 227 | 76.40 122 | 87.80 143 |
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 |
miper_ehance_all_eth | | | 68.70 178 | 67.58 167 | 72.08 215 | 76.91 242 | 49.48 206 | 82.47 208 | 78.45 247 | 62.68 108 | 58.28 224 | 77.88 246 | 50.90 46 | 85.01 253 | 61.91 151 | 58.72 258 | 81.75 245 |
|
EPMVS | | | 68.45 179 | 65.44 213 | 77.47 92 | 84.91 78 | 56.17 41 | 71.89 313 | 81.91 181 | 61.72 125 | 60.85 184 | 72.49 303 | 36.21 215 | 87.06 199 | 47.32 261 | 71.62 165 | 89.17 114 |
|
test-mter | | | 68.36 180 | 67.29 174 | 71.60 230 | 78.67 211 | 48.17 239 | 85.13 127 | 79.72 215 | 53.38 262 | 63.13 164 | 82.58 201 | 27.23 291 | 80.24 292 | 60.56 163 | 75.17 135 | 86.39 172 |
|
tpm | | | 68.36 180 | 67.48 172 | 70.97 242 | 79.93 190 | 51.34 166 | 76.58 279 | 78.75 239 | 67.73 38 | 63.54 162 | 74.86 283 | 48.33 62 | 72.36 343 | 53.93 219 | 63.71 218 | 89.21 112 |
|
tttt0517 | | | 68.33 182 | 66.29 191 | 74.46 157 | 78.08 223 | 49.06 211 | 80.88 242 | 89.08 24 | 54.40 256 | 54.75 262 | 80.77 222 | 51.31 42 | 90.33 100 | 49.35 249 | 58.01 269 | 83.99 209 |
|
BH-untuned | | | 68.28 183 | 66.40 188 | 73.91 173 | 81.62 152 | 50.01 194 | 85.56 118 | 77.39 265 | 57.63 209 | 57.47 239 | 83.69 184 | 36.36 214 | 87.08 198 | 44.81 274 | 73.08 155 | 84.65 199 |
|
SR-MVS-dyc-post | | | 68.27 184 | 66.87 179 | 72.48 209 | 80.96 170 | 48.14 241 | 81.54 229 | 76.98 272 | 46.42 308 | 62.75 169 | 89.42 102 | 31.17 265 | 86.09 229 | 60.52 165 | 72.06 163 | 83.19 227 |
|
v148 | | | 68.24 185 | 66.35 189 | 73.88 174 | 71.76 301 | 51.47 162 | 84.23 157 | 81.90 182 | 63.69 93 | 58.94 207 | 76.44 268 | 43.72 122 | 87.78 182 | 60.63 161 | 55.86 291 | 82.39 239 |
|
AUN-MVS | | | 68.20 186 | 66.35 189 | 73.76 179 | 76.37 245 | 47.45 250 | 79.52 262 | 79.52 220 | 60.98 139 | 62.34 172 | 86.02 156 | 36.59 213 | 86.94 203 | 62.32 146 | 53.47 309 | 86.89 157 |
|
abl_6 | | | 68.03 187 | 66.15 195 | 73.66 183 | 78.54 216 | 48.48 232 | 79.77 256 | 78.04 252 | 47.39 299 | 63.70 158 | 88.25 124 | 28.21 281 | 89.06 130 | 60.17 171 | 71.25 168 | 83.45 220 |
|
c3_l | | | 67.97 188 | 66.66 186 | 71.91 226 | 76.20 251 | 49.31 208 | 82.13 214 | 78.00 254 | 61.99 119 | 57.64 233 | 76.94 260 | 49.41 57 | 84.93 254 | 60.62 162 | 57.01 279 | 81.49 250 |
|
v1192 | | | 67.96 189 | 65.74 205 | 74.63 154 | 71.79 300 | 53.43 112 | 84.06 163 | 80.99 196 | 63.19 102 | 59.56 197 | 77.46 252 | 37.50 195 | 88.65 147 | 58.20 186 | 58.93 257 | 81.79 244 |
|
v144192 | | | 67.86 190 | 65.76 204 | 74.16 167 | 71.68 302 | 53.09 123 | 84.14 160 | 80.83 198 | 62.85 106 | 59.21 204 | 77.28 255 | 39.30 173 | 88.00 174 | 58.67 179 | 57.88 273 | 81.40 256 |
|
HPM-MVS_fast | | | 67.86 190 | 66.28 192 | 72.61 204 | 80.67 179 | 48.34 236 | 81.18 237 | 75.95 287 | 50.81 282 | 59.55 198 | 88.05 129 | 27.86 286 | 85.98 233 | 58.83 177 | 73.58 147 | 83.51 219 |
|
AdaColmap |  | | 67.86 190 | 65.48 210 | 75.00 149 | 88.15 35 | 54.99 70 | 86.10 103 | 76.63 280 | 49.30 289 | 57.80 228 | 86.65 151 | 29.39 277 | 88.94 142 | 45.10 273 | 70.21 177 | 81.06 264 |
|
UniMVSNet (Re) | | | 67.71 193 | 66.80 181 | 70.45 249 | 74.44 272 | 42.93 305 | 82.42 210 | 84.90 118 | 63.69 93 | 59.63 195 | 80.99 219 | 47.18 75 | 85.23 247 | 51.17 239 | 56.75 280 | 83.19 227 |
|
V42 | | | 67.66 194 | 65.60 209 | 73.86 175 | 70.69 314 | 53.63 102 | 81.50 231 | 78.61 243 | 63.85 89 | 59.49 199 | 77.49 251 | 37.98 182 | 87.65 185 | 62.33 145 | 58.43 262 | 80.29 274 |
|
WR-MVS | | | 67.58 195 | 66.76 183 | 70.04 258 | 75.92 256 | 45.06 286 | 86.23 100 | 85.28 105 | 64.31 79 | 58.50 218 | 81.00 218 | 44.80 110 | 82.00 278 | 49.21 250 | 55.57 294 | 83.06 230 |
|
tfpn200view9 | | | 67.57 196 | 66.13 196 | 71.89 227 | 84.05 94 | 45.07 283 | 83.40 183 | 87.71 60 | 60.79 142 | 57.79 229 | 82.76 196 | 43.53 125 | 87.80 179 | 28.80 334 | 66.36 202 | 82.78 236 |
|
FMVSNet2 | | | 67.57 196 | 65.79 203 | 72.90 198 | 82.71 133 | 47.97 246 | 85.15 126 | 84.93 117 | 58.55 190 | 56.71 247 | 78.26 243 | 36.72 210 | 86.67 210 | 46.15 269 | 62.94 233 | 84.07 206 |
|
FC-MVSNet-test | | | 67.49 198 | 67.91 158 | 66.21 293 | 76.06 252 | 33.06 349 | 80.82 243 | 87.18 64 | 64.44 78 | 54.81 260 | 82.87 193 | 50.40 51 | 82.60 273 | 48.05 257 | 66.55 200 | 82.98 232 |
|
v1921920 | | | 67.45 199 | 65.23 217 | 74.10 169 | 71.51 305 | 52.90 129 | 83.75 172 | 80.44 203 | 62.48 113 | 59.12 205 | 77.13 256 | 36.98 203 | 87.90 176 | 57.53 197 | 58.14 267 | 81.49 250 |
|
cl____ | | | 67.43 200 | 65.93 200 | 71.95 223 | 76.33 247 | 48.02 244 | 82.58 203 | 79.12 231 | 61.30 133 | 56.72 246 | 76.92 261 | 46.12 86 | 86.44 219 | 57.98 189 | 56.31 283 | 81.38 258 |
|
DIV-MVS_self_test | | | 67.43 200 | 65.93 200 | 71.94 224 | 76.33 247 | 48.01 245 | 82.57 204 | 79.11 232 | 61.31 132 | 56.73 245 | 76.92 261 | 46.09 87 | 86.43 220 | 57.98 189 | 56.31 283 | 81.39 257 |
|
gg-mvs-nofinetune | | | 67.43 200 | 64.53 225 | 76.13 127 | 85.95 51 | 47.79 247 | 64.38 332 | 88.28 48 | 39.34 338 | 66.62 111 | 41.27 360 | 58.69 14 | 89.00 136 | 49.64 247 | 86.62 31 | 91.59 49 |
|
thres400 | | | 67.40 203 | 66.13 196 | 71.19 238 | 84.05 94 | 45.07 283 | 83.40 183 | 87.71 60 | 60.79 142 | 57.79 229 | 82.76 196 | 43.53 125 | 87.80 179 | 28.80 334 | 66.36 202 | 80.71 269 |
|
UA-Net | | | 67.32 204 | 66.23 193 | 70.59 246 | 78.85 207 | 41.23 321 | 73.60 295 | 75.45 291 | 61.54 129 | 66.61 112 | 84.53 171 | 38.73 178 | 86.57 216 | 42.48 286 | 74.24 142 | 83.98 211 |
|
v8 | | | 67.25 205 | 64.99 220 | 74.04 170 | 72.89 291 | 53.31 117 | 82.37 211 | 80.11 208 | 61.54 129 | 54.29 268 | 76.02 277 | 42.89 134 | 88.41 157 | 58.43 181 | 56.36 281 | 80.39 273 |
|
NR-MVSNet | | | 67.25 205 | 65.99 199 | 71.04 241 | 73.27 286 | 43.91 295 | 85.32 123 | 84.75 124 | 66.05 60 | 53.65 275 | 82.11 209 | 45.05 102 | 85.97 235 | 47.55 259 | 56.18 286 | 83.24 225 |
|
Test_1112_low_res | | | 67.18 207 | 66.23 193 | 70.02 259 | 78.75 209 | 41.02 322 | 83.43 181 | 73.69 305 | 57.29 216 | 58.45 221 | 82.39 205 | 45.30 99 | 80.88 285 | 50.50 241 | 66.26 205 | 88.16 134 |
|
CPTT-MVS | | | 67.15 208 | 65.84 202 | 71.07 240 | 80.96 170 | 50.32 188 | 81.94 217 | 74.10 300 | 46.18 311 | 57.91 226 | 87.64 135 | 29.57 275 | 81.31 281 | 64.10 135 | 70.18 178 | 81.56 249 |
|
GBi-Net | | | 67.09 209 | 65.47 211 | 71.96 220 | 82.71 133 | 46.36 266 | 83.52 174 | 83.31 156 | 58.55 190 | 57.58 234 | 76.23 272 | 36.72 210 | 86.20 221 | 47.25 262 | 63.40 221 | 83.32 222 |
|
test1 | | | 67.09 209 | 65.47 211 | 71.96 220 | 82.71 133 | 46.36 266 | 83.52 174 | 83.31 156 | 58.55 190 | 57.58 234 | 76.23 272 | 36.72 210 | 86.20 221 | 47.25 262 | 63.40 221 | 83.32 222 |
|
PatchmatchNet |  | | 67.07 211 | 63.63 231 | 77.40 93 | 83.10 115 | 58.03 11 | 72.11 311 | 77.77 258 | 58.85 185 | 59.37 200 | 70.83 316 | 37.84 184 | 84.93 254 | 42.96 283 | 69.83 180 | 89.26 109 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
v1240 | | | 66.99 212 | 64.68 223 | 73.93 172 | 71.38 309 | 52.66 133 | 83.39 185 | 79.98 209 | 61.97 120 | 58.44 222 | 77.11 257 | 35.25 225 | 87.81 178 | 56.46 205 | 58.15 265 | 81.33 259 |
|
eth_miper_zixun_eth | | | 66.98 213 | 65.28 216 | 72.06 216 | 75.61 259 | 50.40 182 | 81.00 240 | 76.97 275 | 62.00 118 | 56.99 244 | 76.97 259 | 44.84 107 | 85.58 239 | 58.75 178 | 54.42 301 | 80.21 275 |
|
TranMVSNet+NR-MVSNet | | | 66.94 214 | 65.61 208 | 70.93 243 | 73.45 283 | 43.38 302 | 83.02 196 | 84.25 136 | 65.31 71 | 58.33 223 | 81.90 211 | 39.92 170 | 85.52 240 | 49.43 248 | 54.89 298 | 83.89 215 |
|
bld_raw_dy_conf001 | | | 66.93 215 | 64.88 222 | 73.09 194 | 75.06 265 | 47.26 254 | 83.36 187 | 69.21 333 | 62.64 109 | 55.68 257 | 81.43 216 | 29.72 274 | 89.20 127 | 63.35 140 | 63.50 220 | 82.79 235 |
|
thres100view900 | | | 66.87 216 | 65.42 214 | 71.24 236 | 83.29 111 | 43.15 303 | 81.67 224 | 87.78 55 | 59.04 180 | 55.92 255 | 82.18 208 | 43.73 120 | 87.80 179 | 28.80 334 | 66.36 202 | 82.78 236 |
|
DU-MVS | | | 66.84 217 | 65.74 205 | 70.16 254 | 73.27 286 | 42.59 309 | 81.50 231 | 82.92 167 | 63.53 97 | 58.51 216 | 82.11 209 | 40.75 157 | 84.64 258 | 53.11 222 | 55.96 289 | 83.24 225 |
|
IterMVS-LS | | | 66.63 218 | 65.36 215 | 70.42 250 | 75.10 264 | 48.90 219 | 81.45 234 | 76.69 279 | 61.05 137 | 55.71 256 | 77.10 258 | 45.86 92 | 83.65 266 | 57.44 198 | 57.88 273 | 78.70 284 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
v10 | | | 66.61 219 | 64.20 228 | 73.83 177 | 72.59 294 | 53.37 113 | 81.88 219 | 79.91 212 | 61.11 135 | 54.09 270 | 75.60 279 | 40.06 168 | 88.26 166 | 56.47 204 | 56.10 287 | 79.86 279 |
|
Fast-Effi-MVS+-dtu | | | 66.53 220 | 64.10 229 | 73.84 176 | 72.41 296 | 52.30 144 | 84.73 145 | 75.66 288 | 59.51 162 | 56.34 252 | 79.11 238 | 28.11 283 | 85.85 238 | 57.74 196 | 63.29 225 | 83.35 221 |
|
thres600view7 | | | 66.46 221 | 65.12 218 | 70.47 248 | 83.41 105 | 43.80 297 | 82.15 213 | 87.78 55 | 59.37 167 | 56.02 254 | 82.21 207 | 43.73 120 | 86.90 205 | 26.51 345 | 64.94 209 | 80.71 269 |
|
LPG-MVS_test | | | 66.44 222 | 64.58 224 | 72.02 217 | 74.42 273 | 48.60 226 | 83.07 194 | 80.64 200 | 54.69 252 | 53.75 273 | 83.83 180 | 25.73 301 | 86.98 200 | 60.33 169 | 64.71 210 | 80.48 271 |
|
tpm cat1 | | | 66.28 223 | 62.78 233 | 76.77 116 | 81.40 162 | 57.14 24 | 70.03 320 | 77.19 268 | 53.00 265 | 58.76 214 | 70.73 319 | 46.17 85 | 86.73 209 | 43.27 280 | 64.46 214 | 86.44 170 |
|
EPNet_dtu | | | 66.25 224 | 66.71 184 | 64.87 303 | 78.66 213 | 34.12 344 | 82.80 199 | 75.51 289 | 61.75 124 | 64.47 146 | 86.90 146 | 37.06 202 | 72.46 342 | 43.65 279 | 69.63 182 | 88.02 140 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
Effi-MVS+-dtu | | | 66.24 225 | 64.96 221 | 70.08 256 | 75.17 261 | 49.64 200 | 82.01 215 | 74.48 297 | 62.15 115 | 57.83 227 | 76.08 276 | 30.59 269 | 83.79 263 | 65.40 128 | 60.93 244 | 76.81 306 |
|
ACMP | | 61.11 9 | 66.24 225 | 64.33 226 | 72.00 219 | 74.89 269 | 49.12 210 | 83.18 191 | 79.83 213 | 55.41 244 | 52.29 283 | 82.68 200 | 25.83 299 | 86.10 227 | 60.89 158 | 63.94 217 | 80.78 267 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
Anonymous20231211 | | | 66.08 227 | 63.67 230 | 73.31 191 | 83.07 119 | 48.75 223 | 86.01 106 | 84.67 127 | 45.27 316 | 56.54 249 | 76.67 266 | 28.06 284 | 88.95 140 | 52.78 228 | 59.95 247 | 82.23 240 |
|
OMC-MVS | | | 65.97 228 | 65.06 219 | 68.71 272 | 72.97 289 | 42.58 311 | 78.61 268 | 75.35 292 | 54.72 251 | 59.31 202 | 86.25 155 | 33.30 244 | 77.88 314 | 57.99 188 | 67.05 197 | 85.66 184 |
|
X-MVStestdata | | | 65.85 229 | 62.20 237 | 76.81 112 | 83.41 105 | 52.48 135 | 84.88 141 | 83.20 161 | 58.03 196 | 63.91 154 | 4.82 376 | 35.50 223 | 89.78 114 | 65.50 121 | 80.50 85 | 88.16 134 |
|
bld_raw_conf005 | | | 65.62 230 | 63.24 232 | 72.77 201 | 74.32 276 | 46.61 262 | 82.74 201 | 66.71 339 | 60.71 145 | 54.67 263 | 80.73 224 | 24.12 310 | 89.16 128 | 61.92 150 | 63.22 227 | 82.54 238 |
|
Vis-MVSNet (Re-imp) | | | 65.52 231 | 65.63 207 | 65.17 301 | 77.49 232 | 30.54 356 | 75.49 286 | 77.73 259 | 59.34 168 | 52.26 285 | 86.69 150 | 49.38 58 | 80.53 289 | 37.07 299 | 75.28 134 | 84.42 202 |
|
Baseline_NR-MVSNet | | | 65.49 232 | 64.27 227 | 69.13 264 | 74.37 275 | 41.65 316 | 83.39 185 | 78.85 234 | 59.56 161 | 59.62 196 | 76.88 263 | 40.75 157 | 87.44 191 | 49.99 243 | 55.05 296 | 78.28 293 |
|
FMVSNet1 | | | 64.57 233 | 62.11 238 | 71.96 220 | 77.32 234 | 46.36 266 | 83.52 174 | 83.31 156 | 52.43 271 | 54.42 266 | 76.23 272 | 27.80 287 | 86.20 221 | 42.59 285 | 61.34 242 | 83.32 222 |
|
dp | | | 64.41 234 | 61.58 241 | 72.90 198 | 82.40 139 | 54.09 93 | 72.53 303 | 76.59 281 | 60.39 149 | 55.68 257 | 70.39 320 | 35.18 227 | 76.90 322 | 39.34 291 | 61.71 240 | 87.73 145 |
|
ACMM | | 58.35 12 | 64.35 235 | 62.01 239 | 71.38 234 | 74.21 277 | 48.51 230 | 82.25 212 | 79.66 217 | 47.61 297 | 54.54 265 | 80.11 226 | 25.26 303 | 86.00 232 | 51.26 237 | 63.16 229 | 79.64 280 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
pm-mvs1 | | | 64.12 236 | 62.56 234 | 68.78 270 | 71.68 302 | 38.87 330 | 82.89 198 | 81.57 185 | 55.54 243 | 53.89 272 | 77.82 247 | 37.73 188 | 86.74 208 | 48.46 255 | 53.49 308 | 80.72 268 |
|
miper_lstm_enhance | | | 63.91 237 | 62.30 236 | 68.75 271 | 75.06 265 | 46.78 259 | 69.02 324 | 81.14 194 | 59.68 160 | 52.76 280 | 72.39 306 | 40.71 159 | 77.99 312 | 56.81 202 | 53.09 311 | 81.48 252 |
|
SCA | | | 63.84 238 | 60.01 257 | 75.32 143 | 78.58 215 | 57.92 12 | 61.61 340 | 77.53 262 | 56.71 227 | 57.75 231 | 70.77 317 | 31.97 257 | 79.91 298 | 48.80 251 | 56.36 281 | 88.13 137 |
|
test_djsdf | | | 63.84 238 | 61.56 242 | 70.70 245 | 68.78 323 | 44.69 287 | 81.63 225 | 81.44 188 | 50.28 283 | 52.27 284 | 76.26 271 | 26.72 294 | 86.11 225 | 60.83 159 | 55.84 292 | 81.29 262 |
|
IterMVS | | | 63.77 240 | 61.67 240 | 70.08 256 | 72.68 293 | 51.24 169 | 80.44 247 | 75.51 289 | 60.51 148 | 51.41 288 | 73.70 292 | 32.08 256 | 78.91 302 | 54.30 216 | 54.35 302 | 80.08 277 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
RRT_MVS | | | 63.68 241 | 61.01 249 | 71.70 228 | 73.48 282 | 45.98 273 | 81.19 236 | 76.08 285 | 54.33 257 | 52.84 279 | 79.27 234 | 22.21 323 | 87.65 185 | 54.13 217 | 55.54 295 | 81.46 253 |
|
test_low_dy_conf_001 | | | 63.62 242 | 61.32 245 | 70.53 247 | 71.46 306 | 43.56 299 | 79.77 256 | 77.78 257 | 52.44 270 | 50.15 296 | 79.69 229 | 22.46 319 | 86.45 218 | 57.90 192 | 60.21 246 | 81.57 248 |
|
D2MVS | | | 63.49 243 | 61.39 244 | 69.77 260 | 69.29 321 | 48.93 218 | 78.89 267 | 77.71 260 | 60.64 147 | 49.70 298 | 72.10 311 | 27.08 292 | 83.48 268 | 54.48 215 | 62.65 234 | 76.90 305 |
|
pmmvs4 | | | 63.34 244 | 61.07 248 | 70.16 254 | 70.14 316 | 50.53 178 | 79.97 255 | 71.41 324 | 55.08 246 | 54.12 269 | 78.58 241 | 32.79 249 | 82.09 277 | 50.33 242 | 57.22 278 | 77.86 297 |
|
jajsoiax | | | 63.21 245 | 60.84 250 | 70.32 252 | 68.33 328 | 44.45 289 | 81.23 235 | 81.05 195 | 53.37 263 | 50.96 293 | 77.81 248 | 17.49 343 | 85.49 242 | 59.31 173 | 58.05 268 | 81.02 265 |
|
MIMVSNet | | | 63.12 246 | 60.29 255 | 71.61 229 | 75.92 256 | 46.65 261 | 65.15 329 | 81.94 178 | 59.14 177 | 54.65 264 | 69.47 323 | 25.74 300 | 80.63 287 | 41.03 288 | 69.56 183 | 87.55 147 |
|
CL-MVSNet_self_test | | | 62.98 247 | 61.14 247 | 68.50 276 | 65.86 337 | 42.96 304 | 84.37 152 | 82.98 165 | 60.98 139 | 53.95 271 | 72.70 302 | 40.43 162 | 83.71 265 | 41.10 287 | 47.93 323 | 78.83 283 |
|
mvs_tets | | | 62.96 248 | 60.55 252 | 70.19 253 | 68.22 331 | 44.24 293 | 80.90 241 | 80.74 199 | 52.99 266 | 50.82 295 | 77.56 249 | 16.74 346 | 85.44 243 | 59.04 176 | 57.94 270 | 80.89 266 |
|
TransMVSNet (Re) | | | 62.82 249 | 60.76 251 | 69.02 265 | 73.98 279 | 41.61 317 | 86.36 97 | 79.30 230 | 56.90 221 | 52.53 281 | 76.44 268 | 41.85 148 | 87.60 188 | 38.83 292 | 40.61 345 | 77.86 297 |
|
pmmvs5 | | | 62.80 250 | 61.18 246 | 67.66 280 | 69.53 320 | 42.37 314 | 82.65 202 | 75.19 293 | 54.30 258 | 52.03 286 | 78.51 242 | 31.64 262 | 80.67 286 | 48.60 253 | 58.15 265 | 79.95 278 |
|
test0.0.03 1 | | | 62.54 251 | 62.44 235 | 62.86 313 | 72.28 299 | 29.51 358 | 82.93 197 | 78.78 237 | 59.18 175 | 53.07 278 | 82.41 204 | 36.91 205 | 77.39 318 | 37.45 295 | 58.96 256 | 81.66 247 |
|
UniMVSNet_ETH3D | | | 62.51 252 | 60.49 253 | 68.57 275 | 68.30 329 | 40.88 324 | 73.89 294 | 79.93 211 | 51.81 277 | 54.77 261 | 79.61 230 | 24.80 306 | 81.10 282 | 49.93 244 | 61.35 241 | 83.73 217 |
|
v7n | | | 62.50 253 | 59.27 262 | 72.20 213 | 67.25 334 | 49.83 198 | 77.87 272 | 80.12 207 | 52.50 269 | 48.80 302 | 73.07 297 | 32.10 255 | 87.90 176 | 46.83 265 | 54.92 297 | 78.86 282 |
|
CR-MVSNet | | | 62.47 254 | 59.04 264 | 72.77 201 | 73.97 280 | 56.57 31 | 60.52 343 | 71.72 318 | 60.04 152 | 57.49 237 | 65.86 334 | 38.94 175 | 80.31 291 | 42.86 284 | 59.93 248 | 81.42 254 |
|
tpmvs | | | 62.45 255 | 59.42 260 | 71.53 233 | 83.93 96 | 54.32 87 | 70.03 320 | 77.61 261 | 51.91 274 | 53.48 276 | 68.29 327 | 37.91 183 | 86.66 211 | 33.36 318 | 58.27 263 | 73.62 331 |
|
EG-PatchMatch MVS | | | 62.40 256 | 59.59 258 | 70.81 244 | 73.29 285 | 49.05 212 | 85.81 107 | 84.78 122 | 51.85 276 | 44.19 320 | 73.48 295 | 15.52 351 | 89.85 112 | 40.16 289 | 67.24 196 | 73.54 332 |
|
XVG-OURS-SEG-HR | | | 62.02 257 | 59.54 259 | 69.46 262 | 65.30 340 | 45.88 274 | 65.06 330 | 73.57 307 | 46.45 307 | 57.42 240 | 83.35 189 | 26.95 293 | 78.09 308 | 53.77 220 | 64.03 215 | 84.42 202 |
|
XVG-OURS | | | 61.88 258 | 59.34 261 | 69.49 261 | 65.37 339 | 46.27 269 | 64.80 331 | 73.49 308 | 47.04 302 | 57.41 241 | 82.85 194 | 25.15 304 | 78.18 306 | 53.00 225 | 64.98 208 | 84.01 208 |
|
TAPA-MVS | | 56.12 14 | 61.82 259 | 60.18 256 | 66.71 289 | 78.48 219 | 37.97 334 | 75.19 288 | 76.41 283 | 46.82 304 | 57.04 243 | 86.52 153 | 27.67 289 | 77.03 320 | 26.50 346 | 67.02 198 | 85.14 192 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
tfpnnormal | | | 61.47 260 | 59.09 263 | 68.62 274 | 76.29 250 | 41.69 315 | 81.14 238 | 85.16 111 | 54.48 255 | 51.32 289 | 73.63 293 | 32.32 253 | 86.89 206 | 21.78 355 | 55.71 293 | 77.29 303 |
|
PVSNet_0 | | 57.04 13 | 61.19 261 | 57.24 272 | 73.02 195 | 77.45 233 | 50.31 189 | 79.43 264 | 77.36 267 | 63.96 88 | 47.51 311 | 72.45 305 | 25.03 305 | 83.78 264 | 52.76 231 | 19.22 368 | 84.96 196 |
|
PLC |  | 52.38 18 | 60.89 262 | 58.97 265 | 66.68 291 | 81.77 148 | 45.70 278 | 78.96 266 | 74.04 302 | 43.66 328 | 47.63 308 | 83.19 192 | 23.52 314 | 77.78 317 | 37.47 294 | 60.46 245 | 76.55 312 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
CVMVSNet | | | 60.85 263 | 60.44 254 | 62.07 314 | 75.00 267 | 32.73 351 | 79.54 260 | 73.49 308 | 36.98 346 | 56.28 253 | 83.74 182 | 29.28 278 | 69.53 351 | 46.48 266 | 63.23 226 | 83.94 214 |
|
CNLPA | | | 60.59 264 | 58.44 267 | 67.05 286 | 79.21 199 | 47.26 254 | 79.75 259 | 64.34 345 | 42.46 334 | 51.90 287 | 83.94 178 | 27.79 288 | 75.41 327 | 37.12 297 | 59.49 252 | 78.47 288 |
|
anonymousdsp | | | 60.46 265 | 57.65 269 | 68.88 266 | 63.63 349 | 45.09 282 | 72.93 301 | 78.63 242 | 46.52 306 | 51.12 290 | 72.80 301 | 21.46 328 | 83.07 272 | 57.79 194 | 53.97 303 | 78.47 288 |
|
ACMH | | 53.70 16 | 59.78 266 | 55.94 283 | 71.28 235 | 76.59 244 | 48.35 235 | 80.15 254 | 76.11 284 | 49.74 287 | 41.91 331 | 73.45 296 | 16.50 348 | 90.31 101 | 31.42 326 | 57.63 276 | 75.17 321 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
pmmvs6 | | | 59.64 267 | 57.15 273 | 67.09 284 | 66.01 335 | 36.86 338 | 80.50 246 | 78.64 241 | 45.05 318 | 49.05 301 | 73.94 288 | 27.28 290 | 86.10 227 | 43.96 278 | 49.94 318 | 78.31 292 |
|
MSDG | | | 59.44 268 | 55.14 288 | 72.32 212 | 74.69 270 | 50.71 173 | 74.39 292 | 73.58 306 | 44.44 322 | 43.40 325 | 77.52 250 | 19.45 334 | 90.87 86 | 31.31 327 | 57.49 277 | 75.38 319 |
|
RPMNet | | | 59.29 269 | 54.25 292 | 74.42 159 | 73.97 280 | 56.57 31 | 60.52 343 | 76.98 272 | 35.72 350 | 57.49 237 | 58.87 352 | 37.73 188 | 85.26 246 | 27.01 344 | 59.93 248 | 81.42 254 |
|
DP-MVS | | | 59.24 270 | 56.12 281 | 68.63 273 | 88.24 34 | 50.35 186 | 82.51 207 | 64.43 344 | 41.10 336 | 46.70 314 | 78.77 240 | 24.75 307 | 88.57 153 | 22.26 353 | 56.29 285 | 66.96 351 |
|
OpenMVS_ROB |  | 53.19 17 | 59.20 271 | 56.00 282 | 68.83 268 | 71.13 311 | 44.30 291 | 83.64 173 | 75.02 294 | 46.42 308 | 46.48 316 | 73.03 298 | 18.69 338 | 88.14 167 | 27.74 341 | 61.80 239 | 74.05 328 |
|
IterMVS-SCA-FT | | | 59.12 272 | 58.81 266 | 60.08 326 | 70.68 315 | 45.07 283 | 80.42 248 | 74.25 299 | 43.54 329 | 50.02 297 | 73.73 289 | 31.97 257 | 56.74 361 | 51.06 240 | 53.60 307 | 78.42 290 |
|
our_test_3 | | | 59.11 273 | 55.08 289 | 71.18 239 | 71.42 307 | 53.29 118 | 81.96 216 | 74.52 296 | 48.32 293 | 42.08 329 | 69.28 325 | 28.14 282 | 82.15 275 | 34.35 315 | 45.68 335 | 78.11 296 |
|
Anonymous20231206 | | | 59.08 274 | 57.59 270 | 63.55 308 | 68.77 324 | 32.14 354 | 80.26 250 | 79.78 214 | 50.00 286 | 49.39 299 | 72.39 306 | 26.64 295 | 78.36 305 | 33.12 321 | 57.94 270 | 80.14 276 |
|
KD-MVS_2432*1600 | | | 59.04 275 | 56.44 278 | 66.86 287 | 79.07 201 | 45.87 275 | 72.13 309 | 80.42 204 | 55.03 247 | 48.15 304 | 71.01 314 | 36.73 208 | 78.05 310 | 35.21 309 | 30.18 362 | 76.67 307 |
|
miper_refine_blended | | | 59.04 275 | 56.44 278 | 66.86 287 | 79.07 201 | 45.87 275 | 72.13 309 | 80.42 204 | 55.03 247 | 48.15 304 | 71.01 314 | 36.73 208 | 78.05 310 | 35.21 309 | 30.18 362 | 76.67 307 |
|
WR-MVS_H | | | 58.91 277 | 58.04 268 | 61.54 319 | 69.07 322 | 33.83 346 | 76.91 276 | 81.99 177 | 51.40 279 | 48.17 303 | 74.67 284 | 40.23 164 | 74.15 331 | 31.78 325 | 48.10 321 | 76.64 310 |
|
LCM-MVSNet-Re | | | 58.82 278 | 56.54 276 | 65.68 295 | 79.31 198 | 29.09 361 | 61.39 342 | 45.79 363 | 60.73 144 | 37.65 344 | 72.47 304 | 31.42 263 | 81.08 283 | 49.66 246 | 70.41 175 | 86.87 158 |
|
Patchmatch-RL test | | | 58.72 279 | 54.32 291 | 71.92 225 | 63.91 348 | 44.25 292 | 61.73 339 | 55.19 355 | 57.38 215 | 49.31 300 | 54.24 356 | 37.60 191 | 80.89 284 | 62.19 148 | 47.28 327 | 90.63 77 |
|
FMVSNet5 | | | 58.61 280 | 56.45 277 | 65.10 302 | 77.20 239 | 39.74 326 | 74.77 289 | 77.12 270 | 50.27 285 | 43.28 326 | 67.71 329 | 26.15 298 | 76.90 322 | 36.78 302 | 54.78 299 | 78.65 286 |
|
ppachtmachnet_test | | | 58.56 281 | 54.34 290 | 71.24 236 | 71.42 307 | 54.74 77 | 81.84 221 | 72.27 315 | 49.02 291 | 45.86 319 | 68.99 326 | 26.27 296 | 83.30 270 | 30.12 330 | 43.23 340 | 75.69 316 |
|
ACMH+ | | 54.58 15 | 58.55 282 | 55.24 285 | 68.50 276 | 74.68 271 | 45.80 277 | 80.27 249 | 70.21 330 | 47.15 301 | 42.77 328 | 75.48 280 | 16.73 347 | 85.98 233 | 35.10 313 | 54.78 299 | 73.72 330 |
|
CP-MVSNet | | | 58.54 283 | 57.57 271 | 61.46 320 | 68.50 326 | 33.96 345 | 76.90 277 | 78.60 244 | 51.67 278 | 47.83 306 | 76.60 267 | 34.99 230 | 72.79 340 | 35.45 306 | 47.58 324 | 77.64 301 |
|
PEN-MVS | | | 58.35 284 | 57.15 273 | 61.94 316 | 67.55 333 | 34.39 343 | 77.01 275 | 78.35 248 | 51.87 275 | 47.72 307 | 76.73 265 | 33.91 238 | 73.75 335 | 34.03 316 | 47.17 328 | 77.68 299 |
|
PS-CasMVS | | | 58.12 285 | 57.03 275 | 61.37 321 | 68.24 330 | 33.80 347 | 76.73 278 | 78.01 253 | 51.20 280 | 47.54 310 | 76.20 275 | 32.85 247 | 72.76 341 | 35.17 311 | 47.37 326 | 77.55 302 |
|
UnsupCasMVSNet_eth | | | 57.56 286 | 55.15 287 | 64.79 304 | 64.57 346 | 33.12 348 | 73.17 300 | 83.87 146 | 58.98 183 | 41.75 332 | 70.03 321 | 22.54 318 | 79.92 296 | 46.12 270 | 35.31 351 | 81.32 261 |
|
CHOSEN 280x420 | | | 57.53 287 | 56.38 280 | 60.97 324 | 74.01 278 | 48.10 243 | 46.30 357 | 54.31 357 | 48.18 295 | 50.88 294 | 77.43 253 | 38.37 181 | 59.16 360 | 54.83 212 | 63.14 230 | 75.66 317 |
|
DTE-MVSNet | | | 57.03 288 | 55.73 284 | 60.95 325 | 65.94 336 | 32.57 352 | 75.71 281 | 77.09 271 | 51.16 281 | 46.65 315 | 76.34 270 | 32.84 248 | 73.22 339 | 30.94 329 | 44.87 336 | 77.06 304 |
|
MVS_0304 | | | 56.72 289 | 55.17 286 | 61.37 321 | 70.71 312 | 36.80 339 | 75.74 280 | 68.75 335 | 44.11 326 | 52.53 281 | 68.20 328 | 15.05 352 | 74.53 330 | 42.98 282 | 58.44 261 | 72.79 337 |
|
PatchMatch-RL | | | 56.66 290 | 53.75 295 | 65.37 300 | 77.91 228 | 45.28 281 | 69.78 322 | 60.38 350 | 41.35 335 | 47.57 309 | 73.73 289 | 16.83 345 | 76.91 321 | 36.99 300 | 59.21 255 | 73.92 329 |
|
PatchT | | | 56.60 291 | 52.97 298 | 67.48 281 | 72.94 290 | 46.16 272 | 57.30 349 | 73.78 304 | 38.77 340 | 54.37 267 | 57.26 355 | 37.52 193 | 78.06 309 | 32.02 323 | 52.79 312 | 78.23 295 |
|
Patchmtry | | | 56.56 292 | 52.95 299 | 67.42 282 | 72.53 295 | 50.59 177 | 59.05 346 | 71.72 318 | 37.86 344 | 46.92 312 | 65.86 334 | 38.94 175 | 80.06 295 | 36.94 301 | 46.72 332 | 71.60 342 |
|
test_0402 | | | 56.45 293 | 53.03 297 | 66.69 290 | 76.78 243 | 50.31 189 | 81.76 222 | 69.61 332 | 42.79 332 | 43.88 321 | 72.13 309 | 22.82 317 | 86.46 217 | 16.57 364 | 50.94 316 | 63.31 357 |
|
LS3D | | | 56.40 294 | 53.82 294 | 64.12 305 | 81.12 166 | 45.69 279 | 73.42 298 | 66.14 340 | 35.30 354 | 43.24 327 | 79.88 227 | 22.18 324 | 79.62 300 | 19.10 361 | 64.00 216 | 67.05 350 |
|
ADS-MVSNet | | | 56.17 295 | 51.95 304 | 68.84 267 | 80.60 180 | 53.07 124 | 55.03 351 | 70.02 331 | 44.72 319 | 51.00 291 | 61.19 345 | 22.83 315 | 78.88 303 | 28.54 337 | 53.63 305 | 74.57 325 |
|
XVG-ACMP-BASELINE | | | 56.03 296 | 52.85 300 | 65.58 296 | 61.91 354 | 40.95 323 | 63.36 333 | 72.43 314 | 45.20 317 | 46.02 317 | 74.09 286 | 9.20 362 | 78.12 307 | 45.13 272 | 58.27 263 | 77.66 300 |
|
pmmvs-eth3d | | | 55.97 297 | 52.78 301 | 65.54 297 | 61.02 356 | 46.44 265 | 75.36 287 | 67.72 337 | 49.61 288 | 43.65 323 | 67.58 330 | 21.63 327 | 77.04 319 | 44.11 277 | 44.33 337 | 73.15 336 |
|
F-COLMAP | | | 55.96 298 | 53.65 296 | 62.87 312 | 72.76 292 | 42.77 308 | 74.70 291 | 70.37 329 | 40.03 337 | 41.11 335 | 79.36 232 | 17.77 342 | 73.70 336 | 32.80 322 | 53.96 304 | 72.15 338 |
|
CMPMVS |  | 40.41 21 | 55.34 299 | 52.64 302 | 63.46 309 | 60.88 357 | 43.84 296 | 61.58 341 | 71.06 325 | 30.43 357 | 36.33 346 | 74.63 285 | 24.14 309 | 75.44 326 | 48.05 257 | 66.62 199 | 71.12 345 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
test20.03 | | | 55.22 300 | 54.07 293 | 58.68 330 | 63.14 351 | 25.00 365 | 77.69 273 | 74.78 295 | 52.64 267 | 43.43 324 | 72.39 306 | 26.21 297 | 74.76 329 | 29.31 332 | 47.05 330 | 76.28 314 |
|
ADS-MVSNet2 | | | 55.21 301 | 51.44 305 | 66.51 292 | 80.60 180 | 49.56 203 | 55.03 351 | 65.44 341 | 44.72 319 | 51.00 291 | 61.19 345 | 22.83 315 | 75.41 327 | 28.54 337 | 53.63 305 | 74.57 325 |
|
SixPastTwentyTwo | | | 54.37 302 | 50.10 309 | 67.21 283 | 70.70 313 | 41.46 319 | 74.73 290 | 64.69 343 | 47.56 298 | 39.12 340 | 69.49 322 | 18.49 340 | 84.69 257 | 31.87 324 | 34.20 357 | 75.48 318 |
|
USDC | | | 54.36 303 | 51.23 306 | 63.76 307 | 64.29 347 | 37.71 335 | 62.84 338 | 73.48 310 | 56.85 222 | 35.47 349 | 71.94 312 | 9.23 361 | 78.43 304 | 38.43 293 | 48.57 320 | 75.13 322 |
|
testgi | | | 54.25 304 | 52.57 303 | 59.29 328 | 62.76 352 | 21.65 370 | 72.21 308 | 70.47 328 | 53.25 264 | 41.94 330 | 77.33 254 | 14.28 353 | 77.95 313 | 29.18 333 | 51.72 315 | 78.28 293 |
|
K. test v3 | | | 54.04 305 | 49.42 313 | 67.92 279 | 68.55 325 | 42.57 312 | 75.51 285 | 63.07 347 | 52.07 272 | 39.21 339 | 64.59 338 | 19.34 335 | 82.21 274 | 37.11 298 | 25.31 364 | 78.97 281 |
|
UnsupCasMVSNet_bld | | | 53.86 306 | 50.53 308 | 63.84 306 | 63.52 350 | 34.75 342 | 71.38 314 | 81.92 180 | 46.53 305 | 38.95 341 | 57.93 353 | 20.55 331 | 80.20 294 | 39.91 290 | 34.09 358 | 76.57 311 |
|
YYNet1 | | | 53.82 307 | 49.96 310 | 65.41 299 | 70.09 318 | 48.95 216 | 72.30 306 | 71.66 320 | 44.25 324 | 31.89 358 | 63.07 342 | 23.73 312 | 73.95 333 | 33.26 319 | 39.40 347 | 73.34 333 |
|
MDA-MVSNet_test_wron | | | 53.82 307 | 49.95 311 | 65.43 298 | 70.13 317 | 49.05 212 | 72.30 306 | 71.65 321 | 44.23 325 | 31.85 359 | 63.13 341 | 23.68 313 | 74.01 332 | 33.25 320 | 39.35 348 | 73.23 335 |
|
Patchmatch-test | | | 53.33 309 | 48.17 316 | 68.81 269 | 73.31 284 | 42.38 313 | 42.98 360 | 58.23 352 | 32.53 355 | 38.79 342 | 70.77 317 | 39.66 171 | 73.51 337 | 25.18 348 | 52.06 314 | 90.55 78 |
|
LTVRE_ROB | | 45.45 19 | 52.73 310 | 49.74 312 | 61.69 318 | 69.78 319 | 34.99 341 | 44.52 358 | 67.60 338 | 43.11 331 | 43.79 322 | 74.03 287 | 18.54 339 | 81.45 280 | 28.39 339 | 57.94 270 | 68.62 348 |
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 |
EU-MVSNet | | | 52.63 311 | 50.72 307 | 58.37 331 | 62.69 353 | 28.13 363 | 72.60 302 | 75.97 286 | 30.94 356 | 40.76 337 | 72.11 310 | 20.16 332 | 70.80 347 | 35.11 312 | 46.11 333 | 76.19 315 |
|
OurMVSNet-221017-0 | | | 52.39 312 | 48.73 314 | 63.35 310 | 65.21 341 | 38.42 332 | 68.54 326 | 64.95 342 | 38.19 341 | 39.57 338 | 71.43 313 | 13.23 355 | 79.92 296 | 37.16 296 | 40.32 346 | 71.72 341 |
|
JIA-IIPM | | | 52.33 313 | 47.77 319 | 66.03 294 | 71.20 310 | 46.92 258 | 40.00 364 | 76.48 282 | 37.10 345 | 46.73 313 | 37.02 362 | 32.96 246 | 77.88 314 | 35.97 304 | 52.45 313 | 73.29 334 |
|
Anonymous20240521 | | | 51.65 314 | 48.42 315 | 61.34 323 | 56.43 362 | 39.65 328 | 73.57 296 | 73.47 311 | 36.64 348 | 36.59 345 | 63.98 339 | 10.75 358 | 72.25 344 | 35.35 307 | 49.01 319 | 72.11 339 |
|
MDA-MVSNet-bldmvs | | | 51.56 315 | 47.75 320 | 63.00 311 | 71.60 304 | 47.32 253 | 69.70 323 | 72.12 316 | 43.81 327 | 27.65 363 | 63.38 340 | 21.97 326 | 75.96 324 | 27.30 343 | 32.19 359 | 65.70 354 |
|
COLMAP_ROB |  | 43.60 20 | 50.90 316 | 48.05 317 | 59.47 327 | 67.81 332 | 40.57 325 | 71.25 315 | 62.72 349 | 36.49 349 | 36.19 347 | 73.51 294 | 13.48 354 | 73.92 334 | 20.71 357 | 50.26 317 | 63.92 356 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
MIMVSNet1 | | | 50.35 317 | 47.81 318 | 57.96 332 | 61.53 355 | 27.80 364 | 67.40 327 | 74.06 301 | 43.25 330 | 33.31 357 | 65.38 337 | 16.03 349 | 71.34 345 | 21.80 354 | 47.55 325 | 74.75 323 |
|
KD-MVS_self_test | | | 49.24 318 | 46.85 321 | 56.44 334 | 54.32 363 | 22.87 367 | 57.39 348 | 73.36 312 | 44.36 323 | 37.98 343 | 59.30 351 | 18.97 337 | 71.17 346 | 33.48 317 | 42.44 341 | 75.26 320 |
|
MVS-HIRNet | | | 49.01 319 | 44.71 323 | 61.92 317 | 76.06 252 | 46.61 262 | 63.23 335 | 54.90 356 | 24.77 361 | 33.56 354 | 36.60 364 | 21.28 329 | 75.88 325 | 29.49 331 | 62.54 235 | 63.26 358 |
|
new-patchmatchnet | | | 48.21 320 | 46.55 322 | 53.18 338 | 57.73 360 | 18.19 374 | 70.24 318 | 71.02 326 | 45.70 312 | 33.70 353 | 60.23 347 | 18.00 341 | 69.86 350 | 27.97 340 | 34.35 355 | 71.49 344 |
|
TinyColmap | | | 48.15 321 | 44.49 325 | 59.13 329 | 65.73 338 | 38.04 333 | 63.34 334 | 62.86 348 | 38.78 339 | 29.48 361 | 67.23 332 | 6.46 368 | 73.30 338 | 24.59 349 | 41.90 343 | 66.04 352 |
|
AllTest | | | 47.32 322 | 44.66 324 | 55.32 336 | 65.08 342 | 37.50 336 | 62.96 337 | 54.25 358 | 35.45 352 | 33.42 355 | 72.82 299 | 9.98 359 | 59.33 358 | 24.13 350 | 43.84 338 | 69.13 346 |
|
PM-MVS | | | 46.92 323 | 43.76 327 | 56.41 335 | 52.18 365 | 32.26 353 | 63.21 336 | 38.18 369 | 37.99 343 | 40.78 336 | 66.20 333 | 5.09 371 | 65.42 354 | 48.19 256 | 41.99 342 | 71.54 343 |
|
RPSCF | | | 45.77 324 | 44.13 326 | 50.68 340 | 57.67 361 | 29.66 357 | 54.92 353 | 45.25 365 | 26.69 360 | 45.92 318 | 75.92 278 | 17.43 344 | 45.70 369 | 27.44 342 | 45.95 334 | 76.67 307 |
|
pmmvs3 | | | 45.53 325 | 41.55 328 | 57.44 333 | 48.97 368 | 39.68 327 | 70.06 319 | 57.66 353 | 28.32 359 | 34.06 352 | 57.29 354 | 8.50 363 | 66.85 353 | 34.86 314 | 34.26 356 | 65.80 353 |
|
N_pmnet | | | 41.25 326 | 39.77 329 | 45.66 344 | 68.50 326 | 0.82 383 | 72.51 304 | 0.38 383 | 35.61 351 | 35.26 350 | 61.51 344 | 20.07 333 | 67.74 352 | 23.51 352 | 40.63 344 | 68.42 349 |
|
TDRefinement | | | 40.91 327 | 38.37 330 | 48.55 342 | 50.45 366 | 33.03 350 | 58.98 347 | 50.97 361 | 28.50 358 | 29.89 360 | 67.39 331 | 6.21 370 | 54.51 362 | 17.67 363 | 35.25 352 | 58.11 359 |
|
DSMNet-mixed | | | 38.35 328 | 35.36 331 | 47.33 343 | 48.11 369 | 14.91 376 | 37.87 365 | 36.60 371 | 19.18 365 | 34.37 351 | 59.56 350 | 15.53 350 | 53.01 364 | 20.14 359 | 46.89 331 | 74.07 327 |
|
FPMVS | | | 35.40 329 | 33.67 332 | 40.57 347 | 46.34 370 | 28.74 362 | 41.05 362 | 57.05 354 | 20.37 364 | 22.27 365 | 53.38 358 | 6.87 366 | 44.94 370 | 8.62 369 | 47.11 329 | 48.01 364 |
|
ANet_high | | | 34.39 330 | 29.59 336 | 48.78 341 | 30.34 376 | 22.28 368 | 55.53 350 | 63.79 346 | 38.11 342 | 15.47 367 | 36.56 365 | 6.94 365 | 59.98 357 | 13.93 366 | 5.64 376 | 64.08 355 |
|
EGC-MVSNET | | | 33.75 331 | 30.42 335 | 43.75 345 | 64.94 344 | 36.21 340 | 60.47 345 | 40.70 368 | 0.02 377 | 0.10 378 | 53.79 357 | 7.39 364 | 60.26 356 | 11.09 368 | 35.23 353 | 34.79 366 |
|
new_pmnet | | | 33.56 332 | 31.89 334 | 38.59 348 | 49.01 367 | 20.42 371 | 51.01 354 | 37.92 370 | 20.58 362 | 23.45 364 | 46.79 359 | 6.66 367 | 49.28 367 | 20.00 360 | 31.57 361 | 46.09 365 |
|
LF4IMVS | | | 33.04 333 | 32.55 333 | 34.52 351 | 40.96 371 | 22.03 369 | 44.45 359 | 35.62 372 | 20.42 363 | 28.12 362 | 62.35 343 | 5.03 372 | 31.88 375 | 21.61 356 | 34.42 354 | 49.63 363 |
|
LCM-MVSNet | | | 28.07 334 | 23.85 339 | 40.71 346 | 27.46 379 | 18.93 373 | 30.82 367 | 46.19 362 | 12.76 369 | 16.40 366 | 34.70 367 | 1.90 378 | 48.69 368 | 20.25 358 | 24.22 365 | 54.51 361 |
|
Gipuma |  | | 27.47 335 | 24.26 338 | 37.12 350 | 60.55 358 | 29.17 360 | 11.68 371 | 60.00 351 | 14.18 368 | 10.52 372 | 15.12 373 | 2.20 377 | 63.01 355 | 8.39 370 | 35.65 350 | 19.18 369 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
PMMVS2 | | | 26.71 336 | 22.98 340 | 37.87 349 | 36.89 373 | 8.51 380 | 42.51 361 | 29.32 377 | 19.09 366 | 13.01 369 | 37.54 361 | 2.23 376 | 53.11 363 | 14.54 365 | 11.71 369 | 51.99 362 |
|
PMVS |  | 19.57 22 | 25.07 337 | 22.43 341 | 32.99 353 | 23.12 380 | 22.98 366 | 40.98 363 | 35.19 373 | 15.99 367 | 11.95 371 | 35.87 366 | 1.47 380 | 49.29 366 | 5.41 374 | 31.90 360 | 26.70 368 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
test_method | | | 24.09 338 | 21.07 342 | 33.16 352 | 27.67 378 | 8.35 381 | 26.63 368 | 35.11 374 | 3.40 374 | 14.35 368 | 36.98 363 | 3.46 375 | 35.31 374 | 19.08 362 | 22.95 366 | 55.81 360 |
|
E-PMN | | | 19.16 339 | 18.40 343 | 21.44 355 | 36.19 374 | 13.63 377 | 47.59 355 | 30.89 375 | 10.73 370 | 5.91 375 | 16.59 371 | 3.66 374 | 39.77 371 | 5.95 373 | 8.14 371 | 10.92 371 |
|
EMVS | | | 18.42 340 | 17.66 344 | 20.71 356 | 34.13 375 | 12.64 378 | 46.94 356 | 29.94 376 | 10.46 372 | 5.58 376 | 14.93 374 | 4.23 373 | 38.83 372 | 5.24 375 | 7.51 373 | 10.67 372 |
|
cdsmvs_eth3d_5k | | | 18.33 341 | 24.44 337 | 0.00 362 | 0.00 384 | 0.00 385 | 0.00 373 | 89.40 18 | 0.00 378 | 0.00 381 | 92.02 39 | 38.55 179 | 0.00 379 | 0.00 379 | 0.00 377 | 0.00 377 |
|
MVE |  | 16.60 23 | 17.34 342 | 13.39 345 | 29.16 354 | 28.43 377 | 19.72 372 | 13.73 370 | 23.63 378 | 7.23 373 | 7.96 373 | 21.41 369 | 0.80 381 | 36.08 373 | 6.97 371 | 10.39 370 | 31.69 367 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
tmp_tt | | | 9.44 343 | 10.68 346 | 5.73 359 | 2.49 382 | 4.21 382 | 10.48 372 | 18.04 379 | 0.34 376 | 12.59 370 | 20.49 370 | 11.39 356 | 7.03 378 | 13.84 367 | 6.46 375 | 5.95 373 |
|
wuyk23d | | | 9.11 344 | 8.77 348 | 10.15 358 | 40.18 372 | 16.76 375 | 20.28 369 | 1.01 382 | 2.58 375 | 2.66 377 | 0.98 377 | 0.23 382 | 12.49 377 | 4.08 376 | 6.90 374 | 1.19 374 |
|
ab-mvs-re | | | 7.68 345 | 10.24 347 | 0.00 362 | 0.00 384 | 0.00 385 | 0.00 373 | 0.00 384 | 0.00 378 | 0.00 381 | 92.12 36 | 0.00 383 | 0.00 379 | 0.00 379 | 0.00 377 | 0.00 377 |
|
testmvs | | | 6.14 346 | 8.18 349 | 0.01 360 | 0.01 383 | 0.00 385 | 73.40 299 | 0.00 384 | 0.00 378 | 0.02 379 | 0.15 378 | 0.00 383 | 0.00 379 | 0.02 377 | 0.00 377 | 0.02 375 |
|
test123 | | | 6.01 347 | 8.01 350 | 0.01 360 | 0.00 384 | 0.01 384 | 71.93 312 | 0.00 384 | 0.00 378 | 0.02 379 | 0.11 379 | 0.00 383 | 0.00 379 | 0.02 377 | 0.00 377 | 0.02 375 |
|
pcd_1.5k_mvsjas | | | 3.15 348 | 4.20 351 | 0.00 362 | 0.00 384 | 0.00 385 | 0.00 373 | 0.00 384 | 0.00 378 | 0.00 381 | 0.00 380 | 37.77 185 | 0.00 379 | 0.00 379 | 0.00 377 | 0.00 377 |
|
test_blank | | | 0.00 349 | 0.00 352 | 0.00 362 | 0.00 384 | 0.00 385 | 0.00 373 | 0.00 384 | 0.00 378 | 0.00 381 | 0.00 380 | 0.00 383 | 0.00 379 | 0.00 379 | 0.00 377 | 0.00 377 |
|
uanet_test | | | 0.00 349 | 0.00 352 | 0.00 362 | 0.00 384 | 0.00 385 | 0.00 373 | 0.00 384 | 0.00 378 | 0.00 381 | 0.00 380 | 0.00 383 | 0.00 379 | 0.00 379 | 0.00 377 | 0.00 377 |
|
DCPMVS | | | 0.00 349 | 0.00 352 | 0.00 362 | 0.00 384 | 0.00 385 | 0.00 373 | 0.00 384 | 0.00 378 | 0.00 381 | 0.00 380 | 0.00 383 | 0.00 379 | 0.00 379 | 0.00 377 | 0.00 377 |
|
sosnet-low-res | | | 0.00 349 | 0.00 352 | 0.00 362 | 0.00 384 | 0.00 385 | 0.00 373 | 0.00 384 | 0.00 378 | 0.00 381 | 0.00 380 | 0.00 383 | 0.00 379 | 0.00 379 | 0.00 377 | 0.00 377 |
|
sosnet | | | 0.00 349 | 0.00 352 | 0.00 362 | 0.00 384 | 0.00 385 | 0.00 373 | 0.00 384 | 0.00 378 | 0.00 381 | 0.00 380 | 0.00 383 | 0.00 379 | 0.00 379 | 0.00 377 | 0.00 377 |
|
uncertanet | | | 0.00 349 | 0.00 352 | 0.00 362 | 0.00 384 | 0.00 385 | 0.00 373 | 0.00 384 | 0.00 378 | 0.00 381 | 0.00 380 | 0.00 383 | 0.00 379 | 0.00 379 | 0.00 377 | 0.00 377 |
|
Regformer | | | 0.00 349 | 0.00 352 | 0.00 362 | 0.00 384 | 0.00 385 | 0.00 373 | 0.00 384 | 0.00 378 | 0.00 381 | 0.00 380 | 0.00 383 | 0.00 379 | 0.00 379 | 0.00 377 | 0.00 377 |
|
uanet | | | 0.00 349 | 0.00 352 | 0.00 362 | 0.00 384 | 0.00 385 | 0.00 373 | 0.00 384 | 0.00 378 | 0.00 381 | 0.00 380 | 0.00 383 | 0.00 379 | 0.00 379 | 0.00 377 | 0.00 377 |
|
FOURS1 | | | | | | 83.24 112 | 49.90 197 | 84.98 137 | 78.76 238 | 47.71 296 | 73.42 53 | | | | | | |
|
MSC_two_6792asdad | | | | | 81.53 15 | 91.77 4 | 56.03 44 | | 91.10 6 | | | | | 96.22 8 | 81.46 21 | 86.80 28 | 92.34 31 |
|
PC_three_1452 | | | | | | | | | | 66.58 48 | 87.27 2 | 93.70 9 | 66.82 4 | 94.95 18 | 89.74 2 | 91.98 4 | 93.98 5 |
|
No_MVS | | | | | 81.53 15 | 91.77 4 | 56.03 44 | | 91.10 6 | | | | | 96.22 8 | 81.46 21 | 86.80 28 | 92.34 31 |
|
test_one_0601 | | | | | | 89.39 24 | 57.29 22 | | 88.09 50 | 57.21 218 | 82.06 11 | 93.39 13 | 54.94 25 | | | | |
|
eth-test2 | | | | | | 0.00 384 | | | | | | | | | | | |
|
eth-test | | | | | | 0.00 384 | | | | | | | | | | | |
|
ZD-MVS | | | | | | 89.55 16 | 53.46 106 | | 84.38 131 | 57.02 220 | 73.97 47 | 91.03 59 | 44.57 111 | 91.17 75 | 75.41 59 | 81.78 75 | |
|
RE-MVS-def | | | | 66.66 186 | | 80.96 170 | 48.14 241 | 81.54 229 | 76.98 272 | 46.42 308 | 62.75 169 | 89.42 102 | 29.28 278 | | 60.52 165 | 72.06 163 | 83.19 227 |
|
IU-MVS | | | | | | 89.48 19 | 57.49 17 | | 91.38 5 | 66.22 54 | 88.26 1 | | | | 82.83 10 | 87.60 18 | 92.44 28 |
|
OPU-MVS | | | | | 81.71 13 | 92.05 3 | 55.97 46 | 92.48 3 | | | | 94.01 6 | 67.21 2 | 95.10 16 | 89.82 1 | 92.55 3 | 94.06 3 |
|
test_241102_TWO | | | | | | | | | 88.76 36 | 57.50 213 | 83.60 6 | 94.09 4 | 56.14 19 | 96.37 6 | 82.28 14 | 87.43 20 | 92.55 26 |
|
test_241102_ONE | | | | | | 89.48 19 | 56.89 27 | | 88.94 28 | 57.53 211 | 84.61 4 | 93.29 16 | 58.81 12 | 96.45 1 | | | |
|
9.14 | | | | 78.19 25 | | 85.67 58 | | 88.32 54 | 88.84 33 | 59.89 155 | 74.58 43 | 92.62 27 | 46.80 79 | 92.66 43 | 81.40 23 | 85.62 41 | |
|
save fliter | | | | | | 85.35 69 | 56.34 38 | 89.31 39 | 81.46 187 | 61.55 127 | | | | | | | |
|
test_0728_THIRD | | | | | | | | | | 58.00 198 | 81.91 12 | 93.64 11 | 56.54 16 | 96.44 2 | 81.64 19 | 86.86 25 | 92.23 33 |
|
test_0728_SECOND | | | | | 82.20 9 | 89.50 17 | 57.73 13 | 92.34 5 | 88.88 30 | | | | | 96.39 4 | 81.68 16 | 87.13 21 | 92.47 27 |
|
test0726 | | | | | | 89.40 22 | 57.45 19 | 92.32 7 | 88.63 39 | 57.71 207 | 83.14 9 | 93.96 7 | 55.17 21 | | | | |
|
GSMVS | | | | | | | | | | | | | | | | | 88.13 137 |
|
test_part2 | | | | | | 89.33 25 | 55.48 53 | | | | 82.27 10 | | | | | | |
|
sam_mvs1 | | | | | | | | | | | | | 38.86 177 | | | | 88.13 137 |
|
sam_mvs | | | | | | | | | | | | | 35.99 221 | | | | |
|
ambc | | | | | 62.06 315 | 53.98 364 | 29.38 359 | 35.08 366 | 79.65 218 | | 41.37 333 | 59.96 348 | 6.27 369 | 82.15 275 | 35.34 308 | 38.22 349 | 74.65 324 |
|
MTGPA |  | | | | | | | | 81.31 190 | | | | | | | | |
|
test_post1 | | | | | | | | 70.84 317 | | | | 14.72 375 | 34.33 234 | 83.86 261 | 48.80 251 | | |
|
test_post | | | | | | | | | | | | 16.22 372 | 37.52 193 | 84.72 256 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 59.74 349 | 38.41 180 | 79.91 298 | | | |
|
GG-mvs-BLEND | | | | | 77.77 84 | 86.68 47 | 50.61 175 | 68.67 325 | 88.45 46 | | 68.73 96 | 87.45 137 | 59.15 11 | 90.67 90 | 54.83 212 | 87.67 17 | 92.03 39 |
|
MTMP | | | | | | | | 87.27 78 | 15.34 380 | | | | | | | | |
|
gm-plane-assit | | | | | | 83.24 112 | 54.21 90 | | | 70.91 12 | | 88.23 125 | | 95.25 15 | 66.37 115 | | |
|
test9_res | | | | | | | | | | | | | | | 78.72 35 | 85.44 44 | 91.39 57 |
|
TEST9 | | | | | | 85.68 56 | 55.42 54 | 87.59 67 | 84.00 142 | 57.72 206 | 72.99 57 | 90.98 61 | 44.87 106 | 88.58 150 | | | |
|
test_8 | | | | | | 85.72 55 | 55.31 58 | 87.60 64 | 83.88 145 | 57.84 204 | 72.84 61 | 90.99 60 | 44.99 103 | 88.34 160 | | | |
|
agg_prior2 | | | | | | | | | | | | | | | 75.65 54 | 85.11 48 | 91.01 68 |
|
agg_prior | | | | | | 85.64 59 | 54.92 72 | | 83.61 152 | | 72.53 65 | | | 88.10 170 | | | |
|
TestCases | | | | | 55.32 336 | 65.08 342 | 37.50 336 | | 54.25 358 | 35.45 352 | 33.42 355 | 72.82 299 | 9.98 359 | 59.33 358 | 24.13 350 | 43.84 338 | 69.13 346 |
|
test_prior4 | | | | | | | 56.39 37 | 87.15 81 | | | | | | | | | |
|
test_prior2 | | | | | | | | 89.04 43 | | 61.88 122 | 73.55 50 | 91.46 55 | 48.01 66 | | 74.73 63 | 85.46 42 | |
|
test_prior | | | | | 78.39 69 | 86.35 49 | 54.91 74 | | 85.45 95 | | | | | 89.70 117 | | | 90.55 78 |
|
旧先验2 | | | | | | | | 81.73 223 | | 45.53 314 | 74.66 39 | | | 70.48 349 | 58.31 185 | | |
|
æ–°å‡ ä½•2 | | | | | | | | 81.61 227 | | | | | | | | | |
|
æ–°å‡ ä½•1 | | | | | 73.30 192 | 83.10 115 | 53.48 105 | | 71.43 323 | 45.55 313 | 66.14 118 | 87.17 143 | 33.88 240 | 80.54 288 | 48.50 254 | 80.33 90 | 85.88 179 |
|
旧先验1 | | | | | | 81.57 156 | 47.48 249 | | 71.83 317 | | | 88.66 116 | 36.94 204 | | | 78.34 110 | 88.67 126 |
|
æ— å…ˆéªŒ | | | | | | | | 85.19 125 | 78.00 254 | 49.08 290 | | | | 85.13 250 | 52.78 228 | | 87.45 150 |
|
原ACMM2 | | | | | | | | 83.77 171 | | | | | | | | | |
|
原ACMM1 | | | | | 76.13 127 | 84.89 79 | 54.59 84 | | 85.26 106 | 51.98 273 | 66.70 109 | 87.07 145 | 40.15 166 | 89.70 117 | 51.23 238 | 85.06 49 | 84.10 205 |
|
test222 | | | | | | 79.36 195 | 50.97 171 | 77.99 271 | 67.84 336 | 42.54 333 | 62.84 168 | 86.53 152 | 30.26 271 | | | 76.91 120 | 85.23 191 |
|
testdata2 | | | | | | | | | | | | | | 77.81 316 | 45.64 271 | | |
|
segment_acmp | | | | | | | | | | | | | 44.97 105 | | | | |
|
testdata | | | | | 67.08 285 | 77.59 230 | 45.46 280 | | 69.20 334 | 44.47 321 | 71.50 80 | 88.34 121 | 31.21 264 | 70.76 348 | 52.20 234 | 75.88 128 | 85.03 194 |
|
testdata1 | | | | | | | | 77.55 274 | | 64.14 82 | | | | | | | |
|
test12 | | | | | 79.24 39 | 86.89 45 | 56.08 43 | | 85.16 111 | | 72.27 71 | | 47.15 76 | 91.10 78 | | 85.93 37 | 90.54 81 |
|
plane_prior7 | | | | | | 77.95 225 | 48.46 234 | | | | | | | | | | |
|
plane_prior6 | | | | | | 78.42 220 | 49.39 207 | | | | | | 36.04 219 | | | | |
|
plane_prior5 | | | | | | | | | 82.59 170 | | | | | 88.30 163 | 65.46 124 | 72.34 160 | 84.49 200 |
|
plane_prior4 | | | | | | | | | | | | 83.28 190 | | | | | |
|
plane_prior3 | | | | | | | 48.95 216 | | | 64.01 85 | 62.15 174 | | | | | | |
|
plane_prior2 | | | | | | | | 85.76 109 | | 63.60 95 | | | | | | | |
|
plane_prior1 | | | | | | 78.31 222 | | | | | | | | | | | |
|
plane_prior | | | | | | | 49.57 201 | 87.43 71 | | 64.57 77 | | | | | | 72.84 156 | |
|
n2 | | | | | | | | | 0.00 384 | | | | | | | | |
|
nn | | | | | | | | | 0.00 384 | | | | | | | | |
|
door-mid | | | | | | | | | 41.31 367 | | | | | | | | |
|
lessismore_v0 | | | | | 67.98 278 | 64.76 345 | 41.25 320 | | 45.75 364 | | 36.03 348 | 65.63 336 | 19.29 336 | 84.11 260 | 35.67 305 | 21.24 367 | 78.59 287 |
|
LGP-MVS_train | | | | | 72.02 217 | 74.42 273 | 48.60 226 | | 80.64 200 | 54.69 252 | 53.75 273 | 83.83 180 | 25.73 301 | 86.98 200 | 60.33 169 | 64.71 210 | 80.48 271 |
|
test11 | | | | | | | | | 84.25 136 | | | | | | | | |
|
door | | | | | | | | | 43.27 366 | | | | | | | | |
|
HQP5-MVS | | | | | | | 51.56 159 | | | | | | | | | | |
|
HQP-NCC | | | | | | 79.02 203 | | 88.00 57 | | 65.45 64 | 64.48 143 | | | | | | |
|
ACMP_Plane | | | | | | 79.02 203 | | 88.00 57 | | 65.45 64 | 64.48 143 | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 66.70 112 | | |
|
HQP4-MVS | | | | | | | | | | | 64.47 146 | | | 88.61 149 | | | 84.91 197 |
|
HQP3-MVS | | | | | | | | | 83.68 148 | | | | | | | 73.12 152 | |
|
HQP2-MVS | | | | | | | | | | | | | 37.35 196 | | | | |
|
NP-MVS | | | | | | 78.76 208 | 50.43 181 | | | | | 85.12 167 | | | | | |
|
MDTV_nov1_ep13_2view | | | | | | | 43.62 298 | 71.13 316 | | 54.95 249 | 59.29 203 | | 36.76 207 | | 46.33 268 | | 87.32 152 |
|
MDTV_nov1_ep13 | | | | 61.56 242 | | 81.68 149 | 55.12 65 | 72.41 305 | 78.18 250 | 59.19 173 | 58.85 212 | 69.29 324 | 34.69 231 | 86.16 224 | 36.76 303 | 62.96 232 | |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 63.20 228 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 59.38 253 | |
|
Test By Simon | | | | | | | | | | | | | 39.38 172 | | | | |
|
ITE_SJBPF | | | | | 51.84 339 | 58.03 359 | 31.94 355 | | 53.57 360 | 36.67 347 | 41.32 334 | 75.23 282 | 11.17 357 | 51.57 365 | 25.81 347 | 48.04 322 | 72.02 340 |
|
DeepMVS_CX |  | | | | 13.10 357 | 21.34 381 | 8.99 379 | | 10.02 381 | 10.59 371 | 7.53 374 | 30.55 368 | 1.82 379 | 14.55 376 | 6.83 372 | 7.52 372 | 15.75 370 |
|