MCST-MVS | | | 91.08 1 | 91.46 2 | 89.94 4 | 97.66 2 | 73.37 9 | 97.13 2 | 95.58 8 | 89.33 1 | 85.77 44 | 96.26 27 | 72.84 27 | 99.38 1 | 92.64 6 | 95.93 10 | 97.08 9 |
|
DPM-MVS | | | 90.70 2 | 90.52 7 | 91.24 1 | 89.68 159 | 76.68 2 | 97.29 1 | 95.35 10 | 82.87 15 | 91.58 10 | 97.22 4 | 79.93 5 | 99.10 9 | 83.12 82 | 97.64 2 | 97.94 1 |
|
DVP-MVS++ | | | 90.53 3 | 91.09 4 | 88.87 14 | 97.31 4 | 69.91 37 | 93.96 68 | 94.37 50 | 72.48 165 | 92.07 6 | 96.85 12 | 83.82 2 | 99.15 2 | 91.53 16 | 97.42 4 | 97.55 4 |
|
MSP-MVS | | | 90.38 4 | 91.87 1 | 85.88 86 | 92.83 83 | 64.03 191 | 93.06 105 | 94.33 52 | 82.19 20 | 93.65 3 | 96.15 30 | 85.89 1 | 97.19 84 | 91.02 20 | 97.75 1 | 96.43 26 |
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 |
CNVR-MVS | | | 90.32 5 | 90.89 6 | 88.61 19 | 96.76 10 | 70.65 25 | 96.47 12 | 94.83 26 | 84.83 9 | 89.07 23 | 96.80 15 | 70.86 34 | 99.06 15 | 92.64 6 | 95.71 11 | 96.12 35 |
|
ETH3 D test6400 | | | 90.27 6 | 90.44 8 | 89.75 6 | 96.82 9 | 74.33 7 | 95.89 16 | 94.80 29 | 77.13 88 | 89.13 22 | 97.38 2 | 74.49 18 | 98.48 28 | 92.32 11 | 95.98 8 | 96.46 25 |
|
DELS-MVS | | | 90.05 7 | 90.09 10 | 89.94 4 | 93.14 77 | 73.88 8 | 97.01 3 | 94.40 48 | 88.32 2 | 85.71 46 | 94.91 68 | 74.11 20 | 98.91 17 | 87.26 51 | 95.94 9 | 97.03 10 |
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 |
SED-MVS | | | 89.94 8 | 90.36 9 | 88.70 16 | 96.45 14 | 69.38 47 | 96.89 4 | 94.44 43 | 71.65 196 | 92.11 4 | 97.21 5 | 76.79 9 | 99.11 6 | 92.34 8 | 95.36 14 | 97.62 2 |
|
DeepPCF-MVS | | 81.17 1 | 89.72 9 | 91.38 3 | 84.72 127 | 93.00 80 | 58.16 291 | 96.72 7 | 94.41 46 | 86.50 6 | 90.25 18 | 97.83 1 | 75.46 14 | 98.67 23 | 92.78 5 | 95.49 13 | 97.32 6 |
|
patch_mono-2 | | | 89.71 10 | 90.99 5 | 85.85 89 | 96.04 26 | 63.70 199 | 95.04 41 | 95.19 13 | 86.74 5 | 91.53 11 | 95.15 58 | 73.86 21 | 97.58 63 | 93.38 3 | 92.00 75 | 96.28 32 |
|
CANet | | | 89.61 11 | 89.99 11 | 88.46 20 | 94.39 44 | 69.71 43 | 96.53 11 | 93.78 65 | 86.89 4 | 89.68 19 | 95.78 34 | 65.94 65 | 99.10 9 | 92.99 4 | 93.91 44 | 96.58 17 |
|
DVP-MVS |  | | 89.41 12 | 89.73 13 | 88.45 21 | 96.40 17 | 69.99 33 | 96.64 8 | 94.52 39 | 71.92 182 | 90.55 16 | 96.93 10 | 73.77 22 | 99.08 11 | 91.91 14 | 94.90 21 | 96.29 30 |
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 |
HPM-MVS++ |  | | 89.37 13 | 89.95 12 | 87.64 29 | 95.10 34 | 68.23 75 | 95.24 32 | 94.49 41 | 82.43 18 | 88.90 24 | 96.35 24 | 71.89 33 | 98.63 24 | 88.76 36 | 96.40 6 | 96.06 36 |
|
NCCC | | | 89.07 14 | 89.46 14 | 87.91 24 | 96.60 12 | 69.05 54 | 96.38 13 | 94.64 36 | 84.42 10 | 86.74 34 | 96.20 28 | 66.56 61 | 98.76 22 | 89.03 34 | 94.56 33 | 95.92 42 |
|
DPE-MVS |  | | 88.77 15 | 89.21 15 | 87.45 36 | 96.26 22 | 67.56 91 | 94.17 55 | 94.15 58 | 68.77 245 | 90.74 14 | 97.27 3 | 76.09 12 | 98.49 27 | 90.58 23 | 94.91 20 | 96.30 29 |
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025 |
SMA-MVS |  | | 88.14 16 | 88.29 19 | 87.67 28 | 93.21 74 | 68.72 62 | 93.85 78 | 94.03 61 | 74.18 127 | 91.74 9 | 96.67 16 | 65.61 70 | 98.42 32 | 89.24 30 | 96.08 7 | 95.88 44 |
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 |
PS-MVSNAJ | | | 88.14 16 | 87.61 26 | 89.71 7 | 92.06 102 | 76.72 1 | 95.75 19 | 93.26 92 | 83.86 11 | 89.55 20 | 96.06 31 | 53.55 205 | 97.89 48 | 91.10 18 | 93.31 54 | 94.54 97 |
|
TSAR-MVS + MP. | | | 88.11 18 | 88.64 16 | 86.54 65 | 91.73 118 | 68.04 79 | 90.36 215 | 93.55 79 | 82.89 14 | 91.29 12 | 92.89 120 | 72.27 30 | 96.03 134 | 87.99 40 | 94.77 25 | 95.54 52 |
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition |
TSAR-MVS + GP. | | | 87.96 19 | 88.37 18 | 86.70 59 | 93.51 67 | 65.32 152 | 95.15 35 | 93.84 64 | 78.17 72 | 85.93 43 | 94.80 71 | 75.80 13 | 98.21 35 | 89.38 27 | 88.78 108 | 96.59 15 |
|
DeepC-MVS_fast | | 79.48 2 | 87.95 20 | 88.00 20 | 87.79 27 | 95.86 29 | 68.32 70 | 95.74 20 | 94.11 60 | 83.82 12 | 83.49 69 | 96.19 29 | 64.53 82 | 98.44 30 | 83.42 81 | 94.88 24 | 96.61 14 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
xiu_mvs_v2_base | | | 87.92 21 | 87.38 32 | 89.55 12 | 91.41 129 | 76.43 3 | 95.74 20 | 93.12 101 | 83.53 13 | 89.55 20 | 95.95 32 | 53.45 209 | 97.68 54 | 91.07 19 | 92.62 63 | 94.54 97 |
|
EPNet | | | 87.84 22 | 88.38 17 | 86.23 78 | 93.30 70 | 66.05 133 | 95.26 31 | 94.84 25 | 87.09 3 | 88.06 26 | 94.53 76 | 66.79 58 | 97.34 75 | 83.89 78 | 91.68 80 | 95.29 63 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
lupinMVS | | | 87.74 23 | 87.77 23 | 87.63 33 | 89.24 171 | 71.18 20 | 96.57 10 | 92.90 109 | 82.70 17 | 87.13 30 | 95.27 51 | 64.99 75 | 95.80 139 | 89.34 28 | 91.80 78 | 95.93 41 |
|
ETH3D-3000-0.1 | | | 87.61 24 | 87.89 21 | 86.75 56 | 93.58 64 | 67.21 102 | 94.31 53 | 94.14 59 | 72.92 156 | 87.13 30 | 96.62 17 | 67.81 49 | 97.94 43 | 90.13 24 | 94.42 36 | 95.09 75 |
|
APDe-MVS | | | 87.54 25 | 87.84 22 | 86.65 60 | 96.07 25 | 66.30 129 | 94.84 46 | 93.78 65 | 69.35 236 | 88.39 25 | 96.34 25 | 67.74 50 | 97.66 58 | 90.62 22 | 93.44 53 | 96.01 39 |
|
SD-MVS | | | 87.49 26 | 87.49 29 | 87.50 35 | 93.60 63 | 68.82 60 | 93.90 75 | 92.63 120 | 76.86 92 | 87.90 27 | 95.76 35 | 66.17 62 | 97.63 60 | 89.06 32 | 91.48 84 | 96.05 37 |
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 |
test_prior3 | | | 87.38 27 | 87.70 24 | 86.42 70 | 94.71 39 | 67.35 98 | 95.10 37 | 93.10 102 | 75.40 109 | 85.25 53 | 95.61 40 | 67.94 45 | 96.84 107 | 87.47 46 | 94.77 25 | 95.05 77 |
|
dcpmvs_2 | | | 87.37 28 | 87.55 28 | 86.85 50 | 95.04 36 | 68.20 76 | 90.36 215 | 90.66 198 | 79.37 52 | 81.20 86 | 93.67 102 | 74.73 15 | 96.55 118 | 90.88 21 | 92.00 75 | 95.82 45 |
|
alignmvs | | | 87.28 29 | 86.97 37 | 88.24 23 | 91.30 130 | 71.14 22 | 95.61 24 | 93.56 78 | 79.30 53 | 87.07 33 | 95.25 53 | 68.43 39 | 96.93 105 | 87.87 41 | 84.33 148 | 96.65 13 |
|
Regformer-1 | | | 87.24 30 | 87.60 27 | 86.15 80 | 95.14 32 | 65.83 141 | 93.95 71 | 95.12 16 | 82.11 22 | 84.25 61 | 95.73 36 | 67.88 48 | 98.35 33 | 85.60 63 | 88.64 111 | 94.26 106 |
|
train_agg | | | 87.21 31 | 87.42 31 | 86.60 61 | 94.18 46 | 67.28 100 | 94.16 56 | 93.51 80 | 71.87 187 | 85.52 48 | 95.33 46 | 68.19 41 | 97.27 82 | 89.09 31 | 94.90 21 | 95.25 70 |
|
xxxxxxxxxxxxxcwj | | | 87.14 32 | 87.19 34 | 86.99 48 | 93.84 56 | 67.89 83 | 95.05 39 | 84.72 318 | 78.19 70 | 86.25 36 | 96.44 21 | 66.98 54 | 97.79 51 | 88.68 37 | 94.56 33 | 95.28 65 |
|
MG-MVS | | | 87.11 33 | 86.27 44 | 89.62 8 | 97.79 1 | 76.27 4 | 94.96 44 | 94.49 41 | 78.74 66 | 83.87 68 | 92.94 117 | 64.34 84 | 96.94 103 | 75.19 140 | 94.09 40 | 95.66 48 |
|
ETH3D cwj APD-0.16 | | | 87.06 34 | 87.18 35 | 86.71 57 | 91.99 108 | 67.48 96 | 92.97 110 | 94.21 55 | 71.48 207 | 85.72 45 | 96.32 26 | 68.13 43 | 98.00 42 | 89.06 32 | 94.70 31 | 94.65 93 |
|
SF-MVS | | | 87.03 35 | 87.09 36 | 86.84 51 | 92.70 89 | 67.45 97 | 93.64 86 | 93.76 68 | 70.78 220 | 86.25 36 | 96.44 21 | 66.98 54 | 97.79 51 | 88.68 37 | 94.56 33 | 95.28 65 |
|
agg_prior1 | | | 87.02 36 | 87.26 33 | 86.28 77 | 94.16 50 | 66.97 111 | 94.08 62 | 93.31 90 | 71.85 189 | 84.49 59 | 95.39 43 | 68.91 38 | 96.75 111 | 88.84 35 | 94.32 38 | 95.13 73 |
|
Regformer-2 | | | 87.00 37 | 87.43 30 | 85.71 96 | 95.14 32 | 64.73 170 | 93.95 71 | 94.95 23 | 81.69 27 | 84.03 66 | 95.73 36 | 67.35 52 | 98.19 37 | 85.40 65 | 88.64 111 | 94.20 108 |
|
CSCG | | | 86.87 38 | 86.26 45 | 88.72 15 | 95.05 35 | 70.79 24 | 93.83 82 | 95.33 11 | 68.48 249 | 77.63 129 | 94.35 85 | 73.04 25 | 98.45 29 | 84.92 70 | 93.71 49 | 96.92 11 |
|
canonicalmvs | | | 86.85 39 | 86.25 46 | 88.66 18 | 91.80 117 | 71.92 15 | 93.54 91 | 91.71 155 | 80.26 41 | 87.55 28 | 95.25 53 | 63.59 96 | 96.93 105 | 88.18 39 | 84.34 147 | 97.11 8 |
|
PHI-MVS | | | 86.83 40 | 86.85 40 | 86.78 55 | 93.47 68 | 65.55 148 | 95.39 28 | 95.10 18 | 71.77 193 | 85.69 47 | 96.52 18 | 62.07 111 | 98.77 21 | 86.06 61 | 95.60 12 | 96.03 38 |
|
SteuartSystems-ACMMP | | | 86.82 41 | 86.90 38 | 86.58 63 | 90.42 145 | 66.38 126 | 96.09 15 | 93.87 63 | 77.73 79 | 84.01 67 | 95.66 38 | 63.39 98 | 97.94 43 | 87.40 48 | 93.55 52 | 95.42 53 |
Skip Steuart: Steuart Systems R&D Blog. |
PVSNet_Blended | | | 86.73 42 | 86.86 39 | 86.31 76 | 93.76 58 | 67.53 93 | 96.33 14 | 93.61 76 | 82.34 19 | 81.00 91 | 93.08 112 | 63.19 101 | 97.29 78 | 87.08 52 | 91.38 86 | 94.13 114 |
|
testtj | | | 86.62 43 | 86.66 41 | 86.50 67 | 96.95 8 | 65.70 143 | 94.41 51 | 93.45 84 | 67.74 251 | 86.19 39 | 96.39 23 | 64.38 83 | 97.91 46 | 87.33 49 | 93.14 57 | 95.90 43 |
|
jason | | | 86.40 44 | 86.17 47 | 87.11 44 | 86.16 234 | 70.54 27 | 95.71 23 | 92.19 136 | 82.00 24 | 84.58 58 | 94.34 86 | 61.86 113 | 95.53 159 | 87.76 42 | 90.89 92 | 95.27 67 |
jason: jason. |
WTY-MVS | | | 86.32 45 | 85.81 52 | 87.85 25 | 92.82 85 | 69.37 49 | 95.20 33 | 95.25 12 | 82.71 16 | 81.91 79 | 94.73 72 | 67.93 47 | 97.63 60 | 79.55 110 | 82.25 159 | 96.54 18 |
|
MSLP-MVS++ | | | 86.27 46 | 85.91 51 | 87.35 39 | 92.01 105 | 68.97 57 | 95.04 41 | 92.70 114 | 79.04 61 | 81.50 83 | 96.50 20 | 58.98 144 | 96.78 109 | 83.49 80 | 93.93 43 | 96.29 30 |
|
VNet | | | 86.20 47 | 85.65 56 | 87.84 26 | 93.92 54 | 69.99 33 | 95.73 22 | 95.94 6 | 78.43 68 | 86.00 42 | 93.07 114 | 58.22 148 | 97.00 95 | 85.22 67 | 84.33 148 | 96.52 19 |
|
MVS_111021_HR | | | 86.19 48 | 85.80 53 | 87.37 38 | 93.17 76 | 69.79 40 | 93.99 67 | 93.76 68 | 79.08 60 | 78.88 117 | 93.99 97 | 62.25 110 | 98.15 38 | 85.93 62 | 91.15 90 | 94.15 113 |
|
ACMMP_NAP | | | 86.05 49 | 85.80 53 | 86.80 54 | 91.58 122 | 67.53 93 | 91.79 160 | 93.49 83 | 74.93 117 | 84.61 57 | 95.30 48 | 59.42 137 | 97.92 45 | 86.13 58 | 94.92 19 | 94.94 82 |
|
ETV-MVS | | | 86.01 50 | 86.11 48 | 85.70 97 | 90.21 150 | 67.02 110 | 93.43 96 | 91.92 144 | 81.21 32 | 84.13 65 | 94.07 96 | 60.93 120 | 95.63 149 | 89.28 29 | 89.81 100 | 94.46 104 |
|
APD-MVS |  | | 85.93 51 | 85.99 49 | 85.76 93 | 95.98 28 | 65.21 155 | 93.59 89 | 92.58 122 | 66.54 262 | 86.17 40 | 95.88 33 | 63.83 90 | 97.00 95 | 86.39 57 | 92.94 59 | 95.06 76 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
PAPM | | | 85.89 52 | 85.46 57 | 87.18 42 | 88.20 198 | 72.42 14 | 92.41 134 | 92.77 112 | 82.11 22 | 80.34 97 | 93.07 114 | 68.27 40 | 95.02 174 | 78.39 122 | 93.59 51 | 94.09 116 |
|
Regformer-3 | | | 85.80 53 | 85.92 50 | 85.46 103 | 94.17 48 | 65.09 163 | 92.95 112 | 95.11 17 | 81.13 33 | 81.68 81 | 95.04 59 | 65.82 67 | 98.32 34 | 83.02 83 | 84.36 145 | 92.97 153 |
|
CS-MVS | | | 85.74 54 | 86.65 42 | 82.98 171 | 92.00 106 | 58.07 293 | 95.32 30 | 91.87 147 | 79.98 43 | 84.86 55 | 95.38 44 | 62.27 109 | 95.52 160 | 86.12 60 | 92.08 73 | 95.36 57 |
|
CDPH-MVS | | | 85.71 55 | 85.46 57 | 86.46 68 | 94.75 38 | 67.19 103 | 93.89 76 | 92.83 111 | 70.90 216 | 83.09 72 | 95.28 49 | 63.62 94 | 97.36 73 | 80.63 104 | 94.18 39 | 94.84 86 |
|
CS-MVS-test | | | 85.64 56 | 86.53 43 | 82.99 170 | 92.00 106 | 58.08 292 | 95.38 29 | 91.54 161 | 79.99 42 | 84.86 55 | 94.32 88 | 62.47 107 | 95.52 160 | 86.13 58 | 92.08 73 | 95.37 56 |
|
DeepC-MVS | | 77.85 3 | 85.52 57 | 85.24 59 | 86.37 73 | 88.80 181 | 66.64 120 | 92.15 140 | 93.68 73 | 81.07 34 | 76.91 139 | 93.64 103 | 62.59 106 | 98.44 30 | 85.50 64 | 92.84 61 | 94.03 120 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
Regformer-4 | | | 85.45 58 | 85.69 55 | 84.73 125 | 94.17 48 | 63.23 209 | 92.95 112 | 94.83 26 | 80.66 38 | 81.29 84 | 95.04 59 | 65.12 73 | 98.08 40 | 82.74 85 | 84.36 145 | 92.88 157 |
|
casdiffmvs | | | 85.37 59 | 84.87 65 | 86.84 51 | 88.25 196 | 69.07 53 | 93.04 107 | 91.76 152 | 81.27 31 | 80.84 93 | 92.07 138 | 64.23 85 | 96.06 132 | 84.98 69 | 87.43 121 | 95.39 54 |
|
ZNCC-MVS | | | 85.33 60 | 85.08 61 | 86.06 81 | 93.09 79 | 65.65 145 | 93.89 76 | 93.41 88 | 73.75 138 | 79.94 101 | 94.68 74 | 60.61 123 | 98.03 41 | 82.63 88 | 93.72 48 | 94.52 99 |
|
MP-MVS-pluss | | | 85.24 61 | 85.13 60 | 85.56 100 | 91.42 127 | 65.59 147 | 91.54 172 | 92.51 124 | 74.56 120 | 80.62 94 | 95.64 39 | 59.15 141 | 97.00 95 | 86.94 54 | 93.80 45 | 94.07 118 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
PAPR | | | 85.15 62 | 84.47 67 | 87.18 42 | 96.02 27 | 68.29 71 | 91.85 158 | 93.00 106 | 76.59 96 | 79.03 113 | 95.00 61 | 61.59 114 | 97.61 62 | 78.16 124 | 89.00 107 | 95.63 49 |
|
MP-MVS |  | | 85.02 63 | 84.97 63 | 85.17 114 | 92.60 91 | 64.27 187 | 93.24 100 | 92.27 129 | 73.13 150 | 79.63 106 | 94.43 79 | 61.90 112 | 97.17 85 | 85.00 68 | 92.56 64 | 94.06 119 |
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
baseline | | | 85.01 64 | 84.44 69 | 86.71 57 | 88.33 193 | 68.73 61 | 90.24 220 | 91.82 151 | 81.05 35 | 81.18 87 | 92.50 127 | 63.69 93 | 96.08 131 | 84.45 73 | 86.71 129 | 95.32 61 |
|
#test# | | | 84.98 65 | 84.74 66 | 85.72 94 | 93.75 60 | 65.01 164 | 94.09 61 | 93.19 96 | 73.55 144 | 79.22 110 | 94.93 65 | 59.04 142 | 97.67 55 | 82.66 86 | 92.21 68 | 94.49 102 |
|
CHOSEN 1792x2688 | | | 84.98 65 | 83.45 79 | 89.57 11 | 89.94 154 | 75.14 5 | 92.07 146 | 92.32 127 | 81.87 25 | 75.68 148 | 88.27 189 | 60.18 126 | 98.60 25 | 80.46 106 | 90.27 99 | 94.96 81 |
|
EIA-MVS | | | 84.84 67 | 84.88 64 | 84.69 128 | 91.30 130 | 62.36 228 | 93.85 78 | 92.04 139 | 79.45 50 | 79.33 109 | 94.28 90 | 62.42 108 | 96.35 121 | 80.05 107 | 91.25 89 | 95.38 55 |
|
zzz-MVS | | | 84.73 68 | 84.47 67 | 85.50 101 | 91.89 113 | 65.16 157 | 91.55 171 | 92.23 130 | 75.32 111 | 80.53 95 | 95.21 55 | 56.06 177 | 97.16 86 | 84.86 71 | 92.55 65 | 94.18 109 |
|
HFP-MVS | | | 84.73 68 | 84.40 70 | 85.72 94 | 93.75 60 | 65.01 164 | 93.50 93 | 93.19 96 | 72.19 176 | 79.22 110 | 94.93 65 | 59.04 142 | 97.67 55 | 81.55 95 | 92.21 68 | 94.49 102 |
|
MVS | | | 84.66 70 | 82.86 94 | 90.06 2 | 90.93 136 | 74.56 6 | 87.91 265 | 95.54 9 | 68.55 247 | 72.35 185 | 94.71 73 | 59.78 133 | 98.90 18 | 81.29 101 | 94.69 32 | 96.74 12 |
|
GST-MVS | | | 84.63 71 | 84.29 71 | 85.66 98 | 92.82 85 | 65.27 153 | 93.04 107 | 93.13 100 | 73.20 148 | 78.89 114 | 94.18 93 | 59.41 138 | 97.85 50 | 81.45 97 | 92.48 67 | 93.86 128 |
|
DROMVSNet | | | 84.53 72 | 85.04 62 | 83.01 169 | 89.34 166 | 61.37 246 | 94.42 50 | 91.09 183 | 77.91 76 | 83.24 70 | 94.20 92 | 58.37 147 | 95.40 163 | 85.35 66 | 91.41 85 | 92.27 173 |
|
ACMMPR | | | 84.37 73 | 84.06 72 | 85.28 110 | 93.56 65 | 64.37 182 | 93.50 93 | 93.15 99 | 72.19 176 | 78.85 119 | 94.86 69 | 56.69 169 | 97.45 67 | 81.55 95 | 92.20 70 | 94.02 121 |
|
region2R | | | 84.36 74 | 84.03 73 | 85.36 108 | 93.54 66 | 64.31 184 | 93.43 96 | 92.95 107 | 72.16 179 | 78.86 118 | 94.84 70 | 56.97 164 | 97.53 65 | 81.38 99 | 92.11 72 | 94.24 107 |
|
LFMVS | | | 84.34 75 | 82.73 97 | 89.18 13 | 94.76 37 | 73.25 10 | 94.99 43 | 91.89 146 | 71.90 184 | 82.16 78 | 93.49 107 | 47.98 255 | 97.05 90 | 82.55 89 | 84.82 141 | 97.25 7 |
|
test_yl | | | 84.28 76 | 83.16 87 | 87.64 29 | 94.52 42 | 69.24 50 | 95.78 17 | 95.09 19 | 69.19 239 | 81.09 88 | 92.88 121 | 57.00 162 | 97.44 68 | 81.11 102 | 81.76 163 | 96.23 33 |
|
DCV-MVSNet | | | 84.28 76 | 83.16 87 | 87.64 29 | 94.52 42 | 69.24 50 | 95.78 17 | 95.09 19 | 69.19 239 | 81.09 88 | 92.88 121 | 57.00 162 | 97.44 68 | 81.11 102 | 81.76 163 | 96.23 33 |
|
diffmvs | | | 84.28 76 | 83.83 74 | 85.61 99 | 87.40 214 | 68.02 80 | 90.88 200 | 89.24 248 | 80.54 39 | 81.64 82 | 92.52 126 | 59.83 132 | 94.52 195 | 87.32 50 | 85.11 139 | 94.29 105 |
|
HY-MVS | | 76.49 5 | 84.28 76 | 83.36 85 | 87.02 47 | 92.22 99 | 67.74 87 | 84.65 288 | 94.50 40 | 79.15 57 | 82.23 77 | 87.93 196 | 66.88 56 | 96.94 103 | 80.53 105 | 82.20 160 | 96.39 28 |
|
MAR-MVS | | | 84.18 80 | 83.43 80 | 86.44 69 | 96.25 23 | 65.93 138 | 94.28 54 | 94.27 54 | 74.41 121 | 79.16 112 | 95.61 40 | 53.99 200 | 98.88 20 | 69.62 188 | 93.26 55 | 94.50 101 |
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 |
MVS_Test | | | 84.16 81 | 83.20 86 | 87.05 46 | 91.56 123 | 69.82 39 | 89.99 229 | 92.05 138 | 77.77 78 | 82.84 73 | 86.57 211 | 63.93 89 | 96.09 129 | 74.91 146 | 89.18 106 | 95.25 70 |
|
CANet_DTU | | | 84.09 82 | 83.52 76 | 85.81 90 | 90.30 148 | 66.82 115 | 91.87 156 | 89.01 261 | 85.27 7 | 86.09 41 | 93.74 101 | 47.71 258 | 96.98 99 | 77.90 127 | 89.78 102 | 93.65 133 |
|
ET-MVSNet_ETH3D | | | 84.01 83 | 83.15 89 | 86.58 63 | 90.78 142 | 70.89 23 | 94.74 47 | 94.62 37 | 81.44 30 | 58.19 308 | 93.64 103 | 73.64 24 | 92.35 269 | 82.66 86 | 78.66 186 | 96.50 23 |
|
PVSNet_Blended_VisFu | | | 83.97 84 | 83.50 77 | 85.39 107 | 90.02 152 | 66.59 123 | 93.77 83 | 91.73 153 | 77.43 87 | 77.08 138 | 89.81 174 | 63.77 92 | 96.97 100 | 79.67 109 | 88.21 114 | 92.60 161 |
|
DWT-MVSNet_test | | | 83.95 85 | 82.80 95 | 87.41 37 | 92.90 82 | 70.07 32 | 89.12 247 | 94.42 45 | 82.15 21 | 77.64 128 | 91.77 142 | 70.81 35 | 96.22 124 | 65.03 234 | 81.36 167 | 95.94 40 |
|
MTAPA | | | 83.91 86 | 83.38 84 | 85.50 101 | 91.89 113 | 65.16 157 | 81.75 308 | 92.23 130 | 75.32 111 | 80.53 95 | 95.21 55 | 56.06 177 | 97.16 86 | 84.86 71 | 92.55 65 | 94.18 109 |
|
XVS | | | 83.87 87 | 83.47 78 | 85.05 115 | 93.22 72 | 63.78 194 | 92.92 114 | 92.66 117 | 73.99 130 | 78.18 123 | 94.31 89 | 55.25 183 | 97.41 70 | 79.16 113 | 91.58 82 | 93.95 123 |
|
Effi-MVS+ | | | 83.82 88 | 82.76 96 | 86.99 48 | 89.56 162 | 69.40 46 | 91.35 182 | 86.12 307 | 72.59 161 | 83.22 71 | 92.81 124 | 59.60 135 | 96.01 136 | 81.76 93 | 87.80 118 | 95.56 51 |
|
EI-MVSNet-Vis-set | | | 83.77 89 | 83.67 75 | 84.06 145 | 92.79 88 | 63.56 205 | 91.76 163 | 94.81 28 | 79.65 49 | 77.87 125 | 94.09 94 | 63.35 99 | 97.90 47 | 79.35 111 | 79.36 178 | 90.74 196 |
|
MVSFormer | | | 83.75 90 | 82.88 93 | 86.37 73 | 89.24 171 | 71.18 20 | 89.07 248 | 90.69 195 | 65.80 267 | 87.13 30 | 94.34 86 | 64.99 75 | 92.67 255 | 72.83 157 | 91.80 78 | 95.27 67 |
|
CP-MVS | | | 83.71 91 | 83.40 83 | 84.65 129 | 93.14 77 | 63.84 192 | 94.59 48 | 92.28 128 | 71.03 214 | 77.41 132 | 94.92 67 | 55.21 186 | 96.19 125 | 81.32 100 | 90.70 94 | 93.91 125 |
|
baseline2 | | | 83.68 92 | 83.42 82 | 84.48 135 | 87.37 215 | 66.00 135 | 90.06 224 | 95.93 7 | 79.71 48 | 69.08 221 | 90.39 164 | 77.92 6 | 96.28 122 | 78.91 117 | 81.38 166 | 91.16 192 |
|
thisisatest0515 | | | 83.41 93 | 82.49 101 | 86.16 79 | 89.46 165 | 68.26 73 | 93.54 91 | 94.70 33 | 74.31 124 | 75.75 146 | 90.92 153 | 72.62 28 | 96.52 119 | 69.64 186 | 81.50 165 | 93.71 131 |
|
PVSNet_BlendedMVS | | | 83.38 94 | 83.43 80 | 83.22 166 | 93.76 58 | 67.53 93 | 94.06 63 | 93.61 76 | 79.13 58 | 81.00 91 | 85.14 225 | 63.19 101 | 97.29 78 | 87.08 52 | 73.91 217 | 84.83 286 |
|
test2506 | | | 83.29 95 | 82.92 92 | 84.37 138 | 88.39 191 | 63.18 212 | 92.01 149 | 91.35 171 | 77.66 81 | 78.49 122 | 91.42 147 | 64.58 81 | 95.09 172 | 73.19 153 | 89.23 104 | 94.85 83 |
|
PGM-MVS | | | 83.25 96 | 82.70 98 | 84.92 119 | 92.81 87 | 64.07 190 | 90.44 211 | 92.20 135 | 71.28 209 | 77.23 135 | 94.43 79 | 55.17 187 | 97.31 77 | 79.33 112 | 91.38 86 | 93.37 138 |
|
HPM-MVS |  | | 83.25 96 | 82.95 91 | 84.17 143 | 92.25 98 | 62.88 221 | 90.91 197 | 91.86 148 | 70.30 225 | 77.12 136 | 93.96 98 | 56.75 167 | 96.28 122 | 82.04 91 | 91.34 88 | 93.34 139 |
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
EI-MVSNet-UG-set | | | 83.14 98 | 82.96 90 | 83.67 156 | 92.28 97 | 63.19 211 | 91.38 180 | 94.68 34 | 79.22 55 | 76.60 141 | 93.75 100 | 62.64 105 | 97.76 53 | 78.07 125 | 78.01 189 | 90.05 204 |
|
VDD-MVS | | | 83.06 99 | 81.81 110 | 86.81 53 | 90.86 140 | 67.70 88 | 95.40 27 | 91.50 165 | 75.46 106 | 81.78 80 | 92.34 134 | 40.09 293 | 97.13 88 | 86.85 55 | 82.04 161 | 95.60 50 |
|
h-mvs33 | | | 83.01 100 | 82.56 100 | 84.35 139 | 89.34 166 | 62.02 233 | 92.72 119 | 93.76 68 | 81.45 28 | 82.73 74 | 92.25 136 | 60.11 127 | 97.13 88 | 87.69 43 | 62.96 290 | 93.91 125 |
|
PAPM_NR | | | 82.97 101 | 81.84 108 | 86.37 73 | 94.10 52 | 66.76 118 | 87.66 269 | 92.84 110 | 69.96 229 | 74.07 164 | 93.57 105 | 63.10 103 | 97.50 66 | 70.66 181 | 90.58 96 | 94.85 83 |
|
mPP-MVS | | | 82.96 102 | 82.44 102 | 84.52 133 | 92.83 83 | 62.92 219 | 92.76 117 | 91.85 149 | 71.52 204 | 75.61 151 | 94.24 91 | 53.48 208 | 96.99 98 | 78.97 116 | 90.73 93 | 93.64 134 |
|
SR-MVS | | | 82.81 103 | 82.58 99 | 83.50 161 | 93.35 69 | 61.16 249 | 92.23 139 | 91.28 175 | 64.48 275 | 81.27 85 | 95.28 49 | 53.71 204 | 95.86 138 | 82.87 84 | 88.77 109 | 93.49 137 |
|
DP-MVS Recon | | | 82.73 104 | 81.65 111 | 85.98 83 | 97.31 4 | 67.06 107 | 95.15 35 | 91.99 141 | 69.08 242 | 76.50 143 | 93.89 99 | 54.48 195 | 98.20 36 | 70.76 179 | 85.66 136 | 92.69 158 |
|
CLD-MVS | | | 82.73 104 | 82.35 104 | 83.86 149 | 87.90 205 | 67.65 90 | 95.45 26 | 92.18 137 | 85.06 8 | 72.58 178 | 92.27 135 | 52.46 215 | 95.78 140 | 84.18 74 | 79.06 181 | 88.16 228 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
sss | | | 82.71 106 | 82.38 103 | 83.73 153 | 89.25 170 | 59.58 276 | 92.24 138 | 94.89 24 | 77.96 74 | 79.86 103 | 92.38 132 | 56.70 168 | 97.05 90 | 77.26 130 | 80.86 171 | 94.55 95 |
|
3Dnovator | | 73.91 6 | 82.69 107 | 80.82 121 | 88.31 22 | 89.57 161 | 71.26 19 | 92.60 127 | 94.39 49 | 78.84 63 | 67.89 240 | 92.48 130 | 48.42 250 | 98.52 26 | 68.80 198 | 94.40 37 | 95.15 72 |
|
MVSTER | | | 82.47 108 | 82.05 105 | 83.74 151 | 92.68 90 | 69.01 55 | 91.90 155 | 93.21 93 | 79.83 44 | 72.14 186 | 85.71 221 | 74.72 16 | 94.72 184 | 75.72 137 | 72.49 227 | 87.50 233 |
|
TESTMET0.1,1 | | | 82.41 109 | 81.98 107 | 83.72 154 | 88.08 199 | 63.74 196 | 92.70 121 | 93.77 67 | 79.30 53 | 77.61 130 | 87.57 201 | 58.19 149 | 94.08 209 | 73.91 151 | 86.68 130 | 93.33 141 |
|
CostFormer | | | 82.33 110 | 81.15 115 | 85.86 88 | 89.01 176 | 68.46 67 | 82.39 306 | 93.01 104 | 75.59 104 | 80.25 98 | 81.57 266 | 72.03 32 | 94.96 176 | 79.06 115 | 77.48 198 | 94.16 112 |
|
API-MVS | | | 82.28 111 | 80.53 127 | 87.54 34 | 96.13 24 | 70.59 26 | 93.63 87 | 91.04 188 | 65.72 269 | 75.45 153 | 92.83 123 | 56.11 176 | 98.89 19 | 64.10 239 | 89.75 103 | 93.15 147 |
|
IB-MVS | | 77.80 4 | 82.18 112 | 80.46 129 | 87.35 39 | 89.14 173 | 70.28 30 | 95.59 25 | 95.17 15 | 78.85 62 | 70.19 208 | 85.82 219 | 70.66 36 | 97.67 55 | 72.19 168 | 66.52 266 | 94.09 116 |
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 |
xiu_mvs_v1_base_debu | | | 82.16 113 | 81.12 116 | 85.26 111 | 86.42 228 | 68.72 62 | 92.59 129 | 90.44 204 | 73.12 151 | 84.20 62 | 94.36 81 | 38.04 304 | 95.73 143 | 84.12 75 | 86.81 124 | 91.33 186 |
|
xiu_mvs_v1_base | | | 82.16 113 | 81.12 116 | 85.26 111 | 86.42 228 | 68.72 62 | 92.59 129 | 90.44 204 | 73.12 151 | 84.20 62 | 94.36 81 | 38.04 304 | 95.73 143 | 84.12 75 | 86.81 124 | 91.33 186 |
|
xiu_mvs_v1_base_debi | | | 82.16 113 | 81.12 116 | 85.26 111 | 86.42 228 | 68.72 62 | 92.59 129 | 90.44 204 | 73.12 151 | 84.20 62 | 94.36 81 | 38.04 304 | 95.73 143 | 84.12 75 | 86.81 124 | 91.33 186 |
|
3Dnovator+ | | 73.60 7 | 82.10 116 | 80.60 126 | 86.60 61 | 90.89 139 | 66.80 117 | 95.20 33 | 93.44 86 | 74.05 129 | 67.42 246 | 92.49 129 | 49.46 240 | 97.65 59 | 70.80 178 | 91.68 80 | 95.33 59 |
|
MVS_111021_LR | | | 82.02 117 | 81.52 112 | 83.51 160 | 88.42 189 | 62.88 221 | 89.77 232 | 88.93 263 | 76.78 94 | 75.55 152 | 93.10 110 | 50.31 232 | 95.38 165 | 83.82 79 | 87.02 123 | 92.26 174 |
|
PMMVS | | | 81.98 118 | 82.04 106 | 81.78 204 | 89.76 158 | 56.17 311 | 91.13 193 | 90.69 195 | 77.96 74 | 80.09 100 | 93.57 105 | 46.33 268 | 94.99 175 | 81.41 98 | 87.46 120 | 94.17 111 |
|
test1172 | | | 81.90 119 | 81.83 109 | 82.13 196 | 93.23 71 | 57.52 301 | 91.61 170 | 90.98 190 | 64.32 277 | 80.20 99 | 95.00 61 | 51.26 225 | 95.61 151 | 81.73 94 | 88.13 115 | 93.26 143 |
|
baseline1 | | | 81.84 120 | 81.03 120 | 84.28 142 | 91.60 121 | 66.62 121 | 91.08 194 | 91.66 158 | 81.87 25 | 74.86 156 | 91.67 146 | 69.98 37 | 94.92 179 | 71.76 172 | 64.75 279 | 91.29 191 |
|
EPP-MVSNet | | | 81.79 121 | 81.52 112 | 82.61 180 | 88.77 182 | 60.21 268 | 93.02 109 | 93.66 75 | 68.52 248 | 72.90 173 | 90.39 164 | 72.19 31 | 94.96 176 | 74.93 145 | 79.29 180 | 92.67 159 |
|
APD-MVS_3200maxsize | | | 81.64 122 | 81.32 114 | 82.59 181 | 92.36 94 | 58.74 285 | 91.39 178 | 91.01 189 | 63.35 283 | 79.72 105 | 94.62 75 | 51.82 218 | 96.14 127 | 79.71 108 | 87.93 117 | 92.89 156 |
|
ACMMP |  | | 81.49 123 | 80.67 124 | 83.93 148 | 91.71 119 | 62.90 220 | 92.13 141 | 92.22 134 | 71.79 192 | 71.68 194 | 93.49 107 | 50.32 231 | 96.96 101 | 78.47 121 | 84.22 152 | 91.93 177 |
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 |
CDS-MVSNet | | | 81.43 124 | 80.74 122 | 83.52 159 | 86.26 232 | 64.45 176 | 92.09 144 | 90.65 199 | 75.83 103 | 73.95 166 | 89.81 174 | 63.97 88 | 92.91 245 | 71.27 175 | 82.82 156 | 93.20 146 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
mvs_anonymous | | | 81.36 125 | 79.99 135 | 85.46 103 | 90.39 147 | 68.40 68 | 86.88 279 | 90.61 200 | 74.41 121 | 70.31 207 | 84.67 231 | 63.79 91 | 92.32 270 | 73.13 154 | 85.70 135 | 95.67 47 |
|
ECVR-MVS |  | | 81.29 126 | 80.38 130 | 84.01 147 | 88.39 191 | 61.96 235 | 92.56 132 | 86.79 299 | 77.66 81 | 76.63 140 | 91.42 147 | 46.34 267 | 95.24 170 | 74.36 150 | 89.23 104 | 94.85 83 |
|
1121 | | | 81.25 127 | 80.05 132 | 84.87 122 | 92.30 96 | 64.31 184 | 87.91 265 | 91.39 169 | 59.44 315 | 79.94 101 | 92.91 118 | 57.09 158 | 97.01 93 | 66.63 213 | 92.81 62 | 93.29 142 |
|
thisisatest0530 | | | 81.15 128 | 80.07 131 | 84.39 137 | 88.26 195 | 65.63 146 | 91.40 176 | 94.62 37 | 71.27 210 | 70.93 199 | 89.18 178 | 72.47 29 | 96.04 133 | 65.62 228 | 76.89 204 | 91.49 182 |
|
Fast-Effi-MVS+ | | | 81.14 129 | 80.01 134 | 84.51 134 | 90.24 149 | 65.86 139 | 94.12 60 | 89.15 254 | 73.81 137 | 75.37 154 | 88.26 190 | 57.26 156 | 94.53 194 | 66.97 212 | 84.92 140 | 93.15 147 |
|
HQP-MVS | | | 81.14 129 | 80.64 125 | 82.64 179 | 87.54 210 | 63.66 202 | 94.06 63 | 91.70 156 | 79.80 45 | 74.18 160 | 90.30 166 | 51.63 222 | 95.61 151 | 77.63 128 | 78.90 182 | 88.63 218 |
|
hse-mvs2 | | | 81.12 131 | 81.11 119 | 81.16 219 | 86.52 227 | 57.48 302 | 89.40 240 | 91.16 178 | 81.45 28 | 82.73 74 | 90.49 162 | 60.11 127 | 94.58 188 | 87.69 43 | 60.41 317 | 91.41 185 |
|
SR-MVS-dyc-post | | | 81.06 132 | 80.70 123 | 82.15 194 | 92.02 103 | 58.56 287 | 90.90 198 | 90.45 201 | 62.76 289 | 78.89 114 | 94.46 77 | 51.26 225 | 95.61 151 | 78.77 119 | 86.77 127 | 92.28 170 |
|
HyFIR lowres test | | | 81.03 133 | 79.56 143 | 85.43 105 | 87.81 207 | 68.11 78 | 90.18 221 | 90.01 225 | 70.65 222 | 72.95 172 | 86.06 217 | 63.61 95 | 94.50 196 | 75.01 144 | 79.75 176 | 93.67 132 |
|
nrg030 | | | 80.93 134 | 79.86 137 | 84.13 144 | 83.69 272 | 68.83 59 | 93.23 101 | 91.20 176 | 75.55 105 | 75.06 155 | 88.22 193 | 63.04 104 | 94.74 183 | 81.88 92 | 66.88 263 | 88.82 216 |
|
Vis-MVSNet |  | | 80.92 135 | 79.98 136 | 83.74 151 | 88.48 186 | 61.80 237 | 93.44 95 | 88.26 283 | 73.96 133 | 77.73 126 | 91.76 143 | 49.94 236 | 94.76 181 | 65.84 225 | 90.37 98 | 94.65 93 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
test1111 | | | 80.84 136 | 80.02 133 | 83.33 164 | 87.87 206 | 60.76 257 | 92.62 126 | 86.86 298 | 77.86 77 | 75.73 147 | 91.39 149 | 46.35 266 | 94.70 187 | 72.79 159 | 88.68 110 | 94.52 99 |
|
1314 | | | 80.70 137 | 78.95 155 | 85.94 85 | 87.77 208 | 67.56 91 | 87.91 265 | 92.55 123 | 72.17 178 | 67.44 245 | 93.09 111 | 50.27 233 | 97.04 92 | 71.68 174 | 87.64 119 | 93.23 145 |
|
RRT_test8_iter05 | | | 80.61 138 | 79.62 141 | 83.60 158 | 91.87 116 | 66.90 113 | 93.42 98 | 93.68 73 | 77.09 90 | 68.83 227 | 85.63 222 | 66.82 57 | 95.42 162 | 76.46 135 | 62.74 293 | 88.48 221 |
|
tpmrst | | | 80.57 139 | 79.14 154 | 84.84 123 | 90.10 151 | 68.28 72 | 81.70 309 | 89.72 236 | 77.63 83 | 75.96 145 | 79.54 297 | 64.94 77 | 92.71 252 | 75.43 138 | 77.28 201 | 93.55 135 |
|
1112_ss | | | 80.56 140 | 79.83 138 | 82.77 175 | 88.65 183 | 60.78 255 | 92.29 136 | 88.36 278 | 72.58 162 | 72.46 182 | 94.95 63 | 65.09 74 | 93.42 233 | 66.38 219 | 77.71 191 | 94.10 115 |
|
VDDNet | | | 80.50 141 | 78.26 162 | 87.21 41 | 86.19 233 | 69.79 40 | 94.48 49 | 91.31 172 | 60.42 307 | 79.34 108 | 90.91 154 | 38.48 300 | 96.56 117 | 82.16 90 | 81.05 169 | 95.27 67 |
|
BH-w/o | | | 80.49 142 | 79.30 150 | 84.05 146 | 90.83 141 | 64.36 183 | 93.60 88 | 89.42 243 | 74.35 123 | 69.09 220 | 90.15 169 | 55.23 185 | 95.61 151 | 64.61 236 | 86.43 133 | 92.17 175 |
|
TAMVS | | | 80.37 143 | 79.45 146 | 83.13 168 | 85.14 249 | 63.37 206 | 91.23 187 | 90.76 194 | 74.81 119 | 72.65 176 | 88.49 184 | 60.63 122 | 92.95 240 | 69.41 190 | 81.95 162 | 93.08 150 |
|
HQP_MVS | | | 80.34 144 | 79.75 139 | 82.12 197 | 86.94 221 | 62.42 226 | 93.13 103 | 91.31 172 | 78.81 64 | 72.53 179 | 89.14 180 | 50.66 229 | 95.55 157 | 76.74 131 | 78.53 187 | 88.39 224 |
|
HPM-MVS_fast | | | 80.25 145 | 79.55 145 | 82.33 187 | 91.55 124 | 59.95 271 | 91.32 184 | 89.16 253 | 65.23 273 | 74.71 157 | 93.07 114 | 47.81 257 | 95.74 142 | 74.87 148 | 88.23 113 | 91.31 190 |
|
ab-mvs | | | 80.18 146 | 78.31 161 | 85.80 91 | 88.44 188 | 65.49 151 | 83.00 303 | 92.67 116 | 71.82 191 | 77.36 133 | 85.01 226 | 54.50 192 | 96.59 114 | 76.35 136 | 75.63 210 | 95.32 61 |
|
IS-MVSNet | | | 80.14 147 | 79.41 147 | 82.33 187 | 87.91 204 | 60.08 270 | 91.97 153 | 88.27 281 | 72.90 157 | 71.44 196 | 91.73 145 | 61.44 115 | 93.66 228 | 62.47 252 | 86.53 131 | 93.24 144 |
|
test-LLR | | | 80.10 148 | 79.56 143 | 81.72 206 | 86.93 223 | 61.17 247 | 92.70 121 | 91.54 161 | 71.51 205 | 75.62 149 | 86.94 208 | 53.83 201 | 92.38 266 | 72.21 166 | 84.76 143 | 91.60 180 |
|
PVSNet | | 73.49 8 | 80.05 149 | 78.63 157 | 84.31 140 | 90.92 137 | 64.97 166 | 92.47 133 | 91.05 187 | 79.18 56 | 72.43 183 | 90.51 161 | 37.05 316 | 94.06 211 | 68.06 201 | 86.00 134 | 93.90 127 |
|
UA-Net | | | 80.02 150 | 79.65 140 | 81.11 222 | 89.33 168 | 57.72 297 | 86.33 282 | 89.00 262 | 77.44 86 | 81.01 90 | 89.15 179 | 59.33 139 | 95.90 137 | 61.01 259 | 84.28 150 | 89.73 208 |
|
test-mter | | | 79.96 151 | 79.38 149 | 81.72 206 | 86.93 223 | 61.17 247 | 92.70 121 | 91.54 161 | 73.85 135 | 75.62 149 | 86.94 208 | 49.84 238 | 92.38 266 | 72.21 166 | 84.76 143 | 91.60 180 |
|
QAPM | | | 79.95 152 | 77.39 181 | 87.64 29 | 89.63 160 | 71.41 18 | 93.30 99 | 93.70 72 | 65.34 272 | 67.39 248 | 91.75 144 | 47.83 256 | 98.96 16 | 57.71 274 | 89.81 100 | 92.54 163 |
|
UGNet | | | 79.87 153 | 78.68 156 | 83.45 163 | 89.96 153 | 61.51 243 | 92.13 141 | 90.79 193 | 76.83 93 | 78.85 119 | 86.33 214 | 38.16 302 | 96.17 126 | 67.93 203 | 87.17 122 | 92.67 159 |
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 |
abl_6 | | | 79.82 154 | 79.20 152 | 81.70 208 | 89.85 155 | 58.34 289 | 88.47 258 | 90.07 220 | 62.56 292 | 77.71 127 | 93.08 112 | 47.65 259 | 96.78 109 | 77.94 126 | 85.45 138 | 89.99 205 |
|
tpm2 | | | 79.80 155 | 77.95 168 | 85.34 109 | 88.28 194 | 68.26 73 | 81.56 311 | 91.42 168 | 70.11 227 | 77.59 131 | 80.50 284 | 67.40 51 | 94.26 204 | 67.34 208 | 77.35 199 | 93.51 136 |
|
thres200 | | | 79.66 156 | 78.33 160 | 83.66 157 | 92.54 92 | 65.82 142 | 93.06 105 | 96.31 3 | 74.90 118 | 73.30 169 | 88.66 182 | 59.67 134 | 95.61 151 | 47.84 310 | 78.67 185 | 89.56 211 |
|
test_part1 | | | 79.63 157 | 77.86 171 | 84.93 118 | 92.50 93 | 71.43 17 | 94.15 58 | 91.08 185 | 72.51 164 | 70.66 200 | 84.98 227 | 59.84 131 | 95.07 173 | 72.07 169 | 62.94 291 | 88.30 227 |
|
CPTT-MVS | | | 79.59 158 | 79.16 153 | 80.89 231 | 91.54 125 | 59.80 273 | 92.10 143 | 88.54 276 | 60.42 307 | 72.96 171 | 93.28 109 | 48.27 251 | 92.80 249 | 78.89 118 | 86.50 132 | 90.06 203 |
|
Test_1112_low_res | | | 79.56 159 | 78.60 158 | 82.43 183 | 88.24 197 | 60.39 265 | 92.09 144 | 87.99 287 | 72.10 180 | 71.84 190 | 87.42 203 | 64.62 80 | 93.04 237 | 65.80 226 | 77.30 200 | 93.85 129 |
|
tttt0517 | | | 79.50 160 | 78.53 159 | 82.41 186 | 87.22 217 | 61.43 245 | 89.75 233 | 94.76 30 | 69.29 237 | 67.91 239 | 88.06 195 | 72.92 26 | 95.63 149 | 62.91 248 | 73.90 218 | 90.16 202 |
|
FIs | | | 79.47 161 | 79.41 147 | 79.67 254 | 85.95 237 | 59.40 278 | 91.68 167 | 93.94 62 | 78.06 73 | 68.96 224 | 88.28 188 | 66.61 60 | 91.77 281 | 66.20 222 | 74.99 211 | 87.82 230 |
|
BH-RMVSNet | | | 79.46 162 | 77.65 173 | 84.89 120 | 91.68 120 | 65.66 144 | 93.55 90 | 88.09 285 | 72.93 155 | 73.37 168 | 91.12 152 | 46.20 270 | 96.12 128 | 56.28 279 | 85.61 137 | 92.91 155 |
|
PCF-MVS | | 73.15 9 | 79.29 163 | 77.63 174 | 84.29 141 | 86.06 235 | 65.96 137 | 87.03 275 | 91.10 182 | 69.86 231 | 69.79 216 | 90.64 157 | 57.54 155 | 96.59 114 | 64.37 238 | 82.29 158 | 90.32 200 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
Vis-MVSNet (Re-imp) | | | 79.24 164 | 79.57 142 | 78.24 274 | 88.46 187 | 52.29 330 | 90.41 213 | 89.12 256 | 74.24 126 | 69.13 219 | 91.91 140 | 65.77 68 | 90.09 305 | 59.00 271 | 88.09 116 | 92.33 167 |
|
114514_t | | | 79.17 165 | 77.67 172 | 83.68 155 | 95.32 31 | 65.53 149 | 92.85 116 | 91.60 160 | 63.49 282 | 67.92 238 | 90.63 159 | 46.65 263 | 95.72 147 | 67.01 211 | 83.54 153 | 89.79 206 |
|
VPA-MVSNet | | | 79.03 166 | 78.00 166 | 82.11 200 | 85.95 237 | 64.48 175 | 93.22 102 | 94.66 35 | 75.05 116 | 74.04 165 | 84.95 228 | 52.17 217 | 93.52 230 | 74.90 147 | 67.04 262 | 88.32 226 |
|
OPM-MVS | | | 79.00 167 | 78.09 164 | 81.73 205 | 83.52 275 | 63.83 193 | 91.64 169 | 90.30 211 | 76.36 99 | 71.97 189 | 89.93 173 | 46.30 269 | 95.17 171 | 75.10 141 | 77.70 192 | 86.19 260 |
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS). |
EI-MVSNet | | | 78.97 168 | 78.22 163 | 81.25 216 | 85.33 245 | 62.73 224 | 89.53 237 | 93.21 93 | 72.39 170 | 72.14 186 | 90.13 170 | 60.99 118 | 94.72 184 | 67.73 205 | 72.49 227 | 86.29 257 |
|
AdaColmap |  | | 78.94 169 | 77.00 186 | 84.76 124 | 96.34 19 | 65.86 139 | 92.66 125 | 87.97 288 | 62.18 295 | 70.56 201 | 92.37 133 | 43.53 282 | 97.35 74 | 64.50 237 | 82.86 155 | 91.05 194 |
|
GeoE | | | 78.90 170 | 77.43 177 | 83.29 165 | 88.95 177 | 62.02 233 | 92.31 135 | 86.23 305 | 70.24 226 | 71.34 197 | 89.27 177 | 54.43 196 | 94.04 214 | 63.31 244 | 80.81 172 | 93.81 130 |
|
miper_enhance_ethall | | | 78.86 171 | 77.97 167 | 81.54 210 | 88.00 203 | 65.17 156 | 91.41 174 | 89.15 254 | 75.19 114 | 68.79 228 | 83.98 238 | 67.17 53 | 92.82 247 | 72.73 160 | 65.30 270 | 86.62 253 |
|
VPNet | | | 78.82 172 | 77.53 176 | 82.70 177 | 84.52 259 | 66.44 125 | 93.93 73 | 92.23 130 | 80.46 40 | 72.60 177 | 88.38 187 | 49.18 244 | 93.13 236 | 72.47 164 | 63.97 287 | 88.55 220 |
|
EPNet_dtu | | | 78.80 173 | 79.26 151 | 77.43 282 | 88.06 200 | 49.71 343 | 91.96 154 | 91.95 143 | 77.67 80 | 76.56 142 | 91.28 151 | 58.51 146 | 90.20 303 | 56.37 278 | 80.95 170 | 92.39 165 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
tfpn200view9 | | | 78.79 174 | 77.43 177 | 82.88 173 | 92.21 100 | 64.49 173 | 92.05 147 | 96.28 4 | 73.48 145 | 71.75 192 | 88.26 190 | 60.07 129 | 95.32 166 | 45.16 320 | 77.58 194 | 88.83 214 |
|
TR-MVS | | | 78.77 175 | 77.37 182 | 82.95 172 | 90.49 144 | 60.88 253 | 93.67 85 | 90.07 220 | 70.08 228 | 74.51 158 | 91.37 150 | 45.69 271 | 95.70 148 | 60.12 265 | 80.32 173 | 92.29 169 |
|
mvs-test1 | | | 78.74 176 | 77.95 168 | 81.14 220 | 83.22 277 | 57.13 306 | 93.96 68 | 87.78 289 | 75.42 107 | 72.68 175 | 90.80 156 | 45.08 275 | 94.54 193 | 75.08 142 | 77.49 197 | 91.74 179 |
|
thres400 | | | 78.68 177 | 77.43 177 | 82.43 183 | 92.21 100 | 64.49 173 | 92.05 147 | 96.28 4 | 73.48 145 | 71.75 192 | 88.26 190 | 60.07 129 | 95.32 166 | 45.16 320 | 77.58 194 | 87.48 234 |
|
BH-untuned | | | 78.68 177 | 77.08 183 | 83.48 162 | 89.84 156 | 63.74 196 | 92.70 121 | 88.59 274 | 71.57 202 | 66.83 254 | 88.65 183 | 51.75 220 | 95.39 164 | 59.03 270 | 84.77 142 | 91.32 189 |
|
OMC-MVS | | | 78.67 179 | 77.91 170 | 80.95 229 | 85.76 241 | 57.40 304 | 88.49 257 | 88.67 271 | 73.85 135 | 72.43 183 | 92.10 137 | 49.29 243 | 94.55 192 | 72.73 160 | 77.89 190 | 90.91 195 |
|
tpm | | | 78.58 180 | 77.03 184 | 83.22 166 | 85.94 239 | 64.56 171 | 83.21 301 | 91.14 181 | 78.31 69 | 73.67 167 | 79.68 295 | 64.01 87 | 92.09 275 | 66.07 223 | 71.26 237 | 93.03 151 |
|
OpenMVS |  | 70.45 11 | 78.54 181 | 75.92 200 | 86.41 72 | 85.93 240 | 71.68 16 | 92.74 118 | 92.51 124 | 66.49 263 | 64.56 269 | 91.96 139 | 43.88 281 | 98.10 39 | 54.61 283 | 90.65 95 | 89.44 212 |
|
EPMVS | | | 78.49 182 | 75.98 199 | 86.02 82 | 91.21 132 | 69.68 44 | 80.23 321 | 91.20 176 | 75.25 113 | 72.48 181 | 78.11 305 | 54.65 191 | 93.69 227 | 57.66 275 | 83.04 154 | 94.69 89 |
|
AUN-MVS | | | 78.37 183 | 77.43 177 | 81.17 218 | 86.60 226 | 57.45 303 | 89.46 239 | 91.16 178 | 74.11 128 | 74.40 159 | 90.49 162 | 55.52 182 | 94.57 189 | 74.73 149 | 60.43 316 | 91.48 183 |
|
thres100view900 | | | 78.37 183 | 77.01 185 | 82.46 182 | 91.89 113 | 63.21 210 | 91.19 191 | 96.33 1 | 72.28 173 | 70.45 204 | 87.89 197 | 60.31 124 | 95.32 166 | 45.16 320 | 77.58 194 | 88.83 214 |
|
GA-MVS | | | 78.33 185 | 76.23 196 | 84.65 129 | 83.65 273 | 66.30 129 | 91.44 173 | 90.14 218 | 76.01 101 | 70.32 206 | 84.02 237 | 42.50 285 | 94.72 184 | 70.98 176 | 77.00 203 | 92.94 154 |
|
cascas | | | 78.18 186 | 75.77 202 | 85.41 106 | 87.14 219 | 69.11 52 | 92.96 111 | 91.15 180 | 66.71 261 | 70.47 202 | 86.07 216 | 37.49 310 | 96.48 120 | 70.15 184 | 79.80 175 | 90.65 197 |
|
UniMVSNet_NR-MVSNet | | | 78.15 187 | 77.55 175 | 79.98 245 | 84.46 261 | 60.26 266 | 92.25 137 | 93.20 95 | 77.50 85 | 68.88 225 | 86.61 210 | 66.10 63 | 92.13 273 | 66.38 219 | 62.55 294 | 87.54 232 |
|
thres600view7 | | | 78.00 188 | 76.66 190 | 82.03 202 | 91.93 110 | 63.69 200 | 91.30 185 | 96.33 1 | 72.43 168 | 70.46 203 | 87.89 197 | 60.31 124 | 94.92 179 | 42.64 332 | 76.64 205 | 87.48 234 |
|
FC-MVSNet-test | | | 77.99 189 | 78.08 165 | 77.70 277 | 84.89 254 | 55.51 316 | 90.27 218 | 93.75 71 | 76.87 91 | 66.80 255 | 87.59 200 | 65.71 69 | 90.23 302 | 62.89 249 | 73.94 216 | 87.37 237 |
|
Anonymous202405211 | | | 77.96 190 | 75.33 206 | 85.87 87 | 93.73 62 | 64.52 172 | 94.85 45 | 85.36 313 | 62.52 293 | 76.11 144 | 90.18 168 | 29.43 341 | 97.29 78 | 68.51 199 | 77.24 202 | 95.81 46 |
|
cl22 | | | 77.94 191 | 76.78 188 | 81.42 212 | 87.57 209 | 64.93 168 | 90.67 206 | 88.86 266 | 72.45 167 | 67.63 244 | 82.68 251 | 64.07 86 | 92.91 245 | 71.79 170 | 65.30 270 | 86.44 254 |
|
XXY-MVS | | | 77.94 191 | 76.44 193 | 82.43 183 | 82.60 283 | 64.44 177 | 92.01 149 | 91.83 150 | 73.59 143 | 70.00 211 | 85.82 219 | 54.43 196 | 94.76 181 | 69.63 187 | 68.02 256 | 88.10 229 |
|
MS-PatchMatch | | | 77.90 193 | 76.50 192 | 82.12 197 | 85.99 236 | 69.95 36 | 91.75 165 | 92.70 114 | 73.97 132 | 62.58 288 | 84.44 234 | 41.11 290 | 95.78 140 | 63.76 242 | 92.17 71 | 80.62 330 |
|
FMVSNet3 | | | 77.73 194 | 76.04 198 | 82.80 174 | 91.20 133 | 68.99 56 | 91.87 156 | 91.99 141 | 73.35 147 | 67.04 251 | 83.19 247 | 56.62 170 | 92.14 272 | 59.80 267 | 69.34 245 | 87.28 240 |
|
miper_ehance_all_eth | | | 77.60 195 | 76.44 193 | 81.09 226 | 85.70 242 | 64.41 180 | 90.65 207 | 88.64 273 | 72.31 171 | 67.37 249 | 82.52 252 | 64.77 79 | 92.64 258 | 70.67 180 | 65.30 270 | 86.24 259 |
|
UniMVSNet (Re) | | | 77.58 196 | 76.78 188 | 79.98 245 | 84.11 267 | 60.80 254 | 91.76 163 | 93.17 98 | 76.56 97 | 69.93 214 | 84.78 230 | 63.32 100 | 92.36 268 | 64.89 235 | 62.51 296 | 86.78 247 |
|
PatchmatchNet |  | | 77.46 197 | 74.63 212 | 85.96 84 | 89.55 163 | 70.35 29 | 79.97 325 | 89.55 239 | 72.23 175 | 70.94 198 | 76.91 316 | 57.03 160 | 92.79 250 | 54.27 285 | 81.17 168 | 94.74 88 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
v2v482 | | | 77.42 198 | 75.65 204 | 82.73 176 | 80.38 300 | 67.13 106 | 91.85 158 | 90.23 215 | 75.09 115 | 69.37 217 | 83.39 245 | 53.79 203 | 94.44 197 | 71.77 171 | 65.00 276 | 86.63 252 |
|
RRT_MVS | | | 77.38 199 | 76.59 191 | 79.77 252 | 90.91 138 | 63.61 204 | 91.15 192 | 90.91 191 | 72.28 173 | 72.06 188 | 87.28 206 | 43.92 280 | 89.04 312 | 73.32 152 | 67.47 260 | 86.67 248 |
|
CHOSEN 280x420 | | | 77.35 200 | 76.95 187 | 78.55 269 | 87.07 220 | 62.68 225 | 69.71 348 | 82.95 334 | 68.80 244 | 71.48 195 | 87.27 207 | 66.03 64 | 84.00 342 | 76.47 134 | 82.81 157 | 88.95 213 |
|
PS-MVSNAJss | | | 77.26 201 | 76.31 195 | 80.13 242 | 80.64 298 | 59.16 282 | 90.63 210 | 91.06 186 | 72.80 158 | 68.58 232 | 84.57 233 | 53.55 205 | 93.96 219 | 72.97 155 | 71.96 231 | 87.27 241 |
|
gg-mvs-nofinetune | | | 77.18 202 | 74.31 219 | 85.80 91 | 91.42 127 | 68.36 69 | 71.78 342 | 94.72 32 | 49.61 346 | 77.12 136 | 45.92 363 | 77.41 8 | 93.98 218 | 67.62 206 | 93.16 56 | 95.05 77 |
|
MVP-Stereo | | | 77.12 203 | 76.23 196 | 79.79 251 | 81.72 289 | 66.34 128 | 89.29 241 | 90.88 192 | 70.56 223 | 62.01 291 | 82.88 248 | 49.34 241 | 94.13 206 | 65.55 230 | 93.80 45 | 78.88 343 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
X-MVStestdata | | | 76.86 204 | 74.13 224 | 85.05 115 | 93.22 72 | 63.78 194 | 92.92 114 | 92.66 117 | 73.99 130 | 78.18 123 | 10.19 375 | 55.25 183 | 97.41 70 | 79.16 113 | 91.58 82 | 93.95 123 |
|
DU-MVS | | | 76.86 204 | 75.84 201 | 79.91 247 | 82.96 281 | 60.26 266 | 91.26 186 | 91.54 161 | 76.46 98 | 68.88 225 | 86.35 212 | 56.16 174 | 92.13 273 | 66.38 219 | 62.55 294 | 87.35 238 |
|
Anonymous20240529 | | | 76.84 206 | 74.15 223 | 84.88 121 | 91.02 134 | 64.95 167 | 93.84 81 | 91.09 183 | 53.57 336 | 73.00 170 | 87.42 203 | 35.91 320 | 97.32 76 | 69.14 194 | 72.41 229 | 92.36 166 |
|
c3_l | | | 76.83 207 | 75.47 205 | 80.93 230 | 85.02 252 | 64.18 189 | 90.39 214 | 88.11 284 | 71.66 195 | 66.65 256 | 81.64 264 | 63.58 97 | 92.56 259 | 69.31 192 | 62.86 292 | 86.04 265 |
|
WR-MVS | | | 76.76 208 | 75.74 203 | 79.82 250 | 84.60 257 | 62.27 231 | 92.60 127 | 92.51 124 | 76.06 100 | 67.87 241 | 85.34 223 | 56.76 166 | 90.24 301 | 62.20 253 | 63.69 289 | 86.94 245 |
|
v1144 | | | 76.73 209 | 74.88 209 | 82.27 189 | 80.23 305 | 66.60 122 | 91.68 167 | 90.21 217 | 73.69 140 | 69.06 222 | 81.89 259 | 52.73 213 | 94.40 198 | 69.21 193 | 65.23 273 | 85.80 271 |
|
IterMVS-LS | | | 76.49 210 | 75.18 208 | 80.43 235 | 84.49 260 | 62.74 223 | 90.64 208 | 88.80 267 | 72.40 169 | 65.16 264 | 81.72 262 | 60.98 119 | 92.27 271 | 67.74 204 | 64.65 281 | 86.29 257 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
V42 | | | 76.46 211 | 74.55 215 | 82.19 193 | 79.14 317 | 67.82 85 | 90.26 219 | 89.42 243 | 73.75 138 | 68.63 231 | 81.89 259 | 51.31 224 | 94.09 208 | 71.69 173 | 64.84 277 | 84.66 287 |
|
v148 | | | 76.19 212 | 74.47 217 | 81.36 213 | 80.05 306 | 64.44 177 | 91.75 165 | 90.23 215 | 73.68 141 | 67.13 250 | 80.84 279 | 55.92 180 | 93.86 225 | 68.95 196 | 61.73 305 | 85.76 274 |
|
Effi-MVS+-dtu | | | 76.14 213 | 75.28 207 | 78.72 268 | 83.22 277 | 55.17 318 | 89.87 230 | 87.78 289 | 75.42 107 | 67.98 237 | 81.43 268 | 45.08 275 | 92.52 261 | 75.08 142 | 71.63 232 | 88.48 221 |
|
cl____ | | | 76.07 214 | 74.67 210 | 80.28 238 | 85.15 248 | 61.76 239 | 90.12 222 | 88.73 269 | 71.16 211 | 65.43 261 | 81.57 266 | 61.15 116 | 92.95 240 | 66.54 216 | 62.17 298 | 86.13 263 |
|
DIV-MVS_self_test | | | 76.07 214 | 74.67 210 | 80.28 238 | 85.14 249 | 61.75 240 | 90.12 222 | 88.73 269 | 71.16 211 | 65.42 262 | 81.60 265 | 61.15 116 | 92.94 244 | 66.54 216 | 62.16 300 | 86.14 261 |
|
FMVSNet2 | | | 76.07 214 | 74.01 226 | 82.26 191 | 88.85 178 | 67.66 89 | 91.33 183 | 91.61 159 | 70.84 217 | 65.98 258 | 82.25 255 | 48.03 252 | 92.00 277 | 58.46 272 | 68.73 251 | 87.10 242 |
|
v144192 | | | 76.05 217 | 74.03 225 | 82.12 197 | 79.50 311 | 66.55 124 | 91.39 178 | 89.71 237 | 72.30 172 | 68.17 235 | 81.33 271 | 51.75 220 | 94.03 216 | 67.94 202 | 64.19 283 | 85.77 272 |
|
NR-MVSNet | | | 76.05 217 | 74.59 213 | 80.44 234 | 82.96 281 | 62.18 232 | 90.83 202 | 91.73 153 | 77.12 89 | 60.96 294 | 86.35 212 | 59.28 140 | 91.80 280 | 60.74 260 | 61.34 309 | 87.35 238 |
|
v1192 | | | 75.98 219 | 73.92 227 | 82.15 194 | 79.73 307 | 66.24 131 | 91.22 188 | 89.75 231 | 72.67 160 | 68.49 233 | 81.42 269 | 49.86 237 | 94.27 202 | 67.08 210 | 65.02 275 | 85.95 268 |
|
eth_miper_zixun_eth | | | 75.96 220 | 74.40 218 | 80.66 232 | 84.66 256 | 63.02 214 | 89.28 242 | 88.27 281 | 71.88 186 | 65.73 259 | 81.65 263 | 59.45 136 | 92.81 248 | 68.13 200 | 60.53 314 | 86.14 261 |
|
bset_n11_16_dypcd | | | 75.95 221 | 74.16 222 | 81.30 215 | 76.91 336 | 65.14 159 | 88.89 250 | 87.48 292 | 74.30 125 | 69.90 215 | 83.40 244 | 42.16 288 | 92.42 264 | 78.39 122 | 66.03 267 | 86.32 256 |
|
TranMVSNet+NR-MVSNet | | | 75.86 222 | 74.52 216 | 79.89 248 | 82.44 284 | 60.64 262 | 91.37 181 | 91.37 170 | 76.63 95 | 67.65 243 | 86.21 215 | 52.37 216 | 91.55 285 | 61.84 255 | 60.81 312 | 87.48 234 |
|
SCA | | | 75.82 223 | 72.76 238 | 85.01 117 | 86.63 225 | 70.08 31 | 81.06 315 | 89.19 251 | 71.60 201 | 70.01 210 | 77.09 314 | 45.53 272 | 90.25 298 | 60.43 262 | 73.27 220 | 94.68 90 |
|
LPG-MVS_test | | | 75.82 223 | 74.58 214 | 79.56 258 | 84.31 264 | 59.37 279 | 90.44 211 | 89.73 234 | 69.49 234 | 64.86 265 | 88.42 185 | 38.65 298 | 94.30 200 | 72.56 162 | 72.76 224 | 85.01 284 |
|
GBi-Net | | | 75.65 225 | 73.83 228 | 81.10 223 | 88.85 178 | 65.11 160 | 90.01 226 | 90.32 207 | 70.84 217 | 67.04 251 | 80.25 289 | 48.03 252 | 91.54 286 | 59.80 267 | 69.34 245 | 86.64 249 |
|
test1 | | | 75.65 225 | 73.83 228 | 81.10 223 | 88.85 178 | 65.11 160 | 90.01 226 | 90.32 207 | 70.84 217 | 67.04 251 | 80.25 289 | 48.03 252 | 91.54 286 | 59.80 267 | 69.34 245 | 86.64 249 |
|
v1921920 | | | 75.63 227 | 73.49 232 | 82.06 201 | 79.38 312 | 66.35 127 | 91.07 196 | 89.48 240 | 71.98 181 | 67.99 236 | 81.22 274 | 49.16 246 | 93.90 222 | 66.56 215 | 64.56 282 | 85.92 270 |
|
ACMP | | 71.68 10 | 75.58 228 | 74.23 221 | 79.62 256 | 84.97 253 | 59.64 274 | 90.80 203 | 89.07 259 | 70.39 224 | 62.95 284 | 87.30 205 | 38.28 301 | 93.87 223 | 72.89 156 | 71.45 235 | 85.36 280 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
v8 | | | 75.35 229 | 73.26 234 | 81.61 209 | 80.67 297 | 66.82 115 | 89.54 236 | 89.27 247 | 71.65 196 | 63.30 282 | 80.30 288 | 54.99 189 | 94.06 211 | 67.33 209 | 62.33 297 | 83.94 292 |
|
tpm cat1 | | | 75.30 230 | 72.21 246 | 84.58 132 | 88.52 184 | 67.77 86 | 78.16 334 | 88.02 286 | 61.88 300 | 68.45 234 | 76.37 320 | 60.65 121 | 94.03 216 | 53.77 288 | 74.11 214 | 91.93 177 |
|
PLC |  | 68.80 14 | 75.23 231 | 73.68 230 | 79.86 249 | 92.93 81 | 58.68 286 | 90.64 208 | 88.30 279 | 60.90 304 | 64.43 273 | 90.53 160 | 42.38 286 | 94.57 189 | 56.52 277 | 76.54 206 | 86.33 255 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
v1240 | | | 75.21 232 | 72.98 236 | 81.88 203 | 79.20 314 | 66.00 135 | 90.75 205 | 89.11 257 | 71.63 200 | 67.41 247 | 81.22 274 | 47.36 260 | 93.87 223 | 65.46 231 | 64.72 280 | 85.77 272 |
|
Fast-Effi-MVS+-dtu | | | 75.04 233 | 73.37 233 | 80.07 243 | 80.86 294 | 59.52 277 | 91.20 190 | 85.38 312 | 71.90 184 | 65.20 263 | 84.84 229 | 41.46 289 | 92.97 239 | 66.50 218 | 72.96 223 | 87.73 231 |
|
dp | | | 75.01 234 | 72.09 247 | 83.76 150 | 89.28 169 | 66.22 132 | 79.96 326 | 89.75 231 | 71.16 211 | 67.80 242 | 77.19 313 | 51.81 219 | 92.54 260 | 50.39 296 | 71.44 236 | 92.51 164 |
|
TAPA-MVS | | 70.22 12 | 74.94 235 | 73.53 231 | 79.17 263 | 90.40 146 | 52.07 331 | 89.19 245 | 89.61 238 | 62.69 291 | 70.07 209 | 92.67 125 | 48.89 249 | 94.32 199 | 38.26 346 | 79.97 174 | 91.12 193 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
v10 | | | 74.77 236 | 72.54 243 | 81.46 211 | 80.33 303 | 66.71 119 | 89.15 246 | 89.08 258 | 70.94 215 | 63.08 283 | 79.86 293 | 52.52 214 | 94.04 214 | 65.70 227 | 62.17 298 | 83.64 294 |
|
XVG-OURS-SEG-HR | | | 74.70 237 | 73.08 235 | 79.57 257 | 78.25 327 | 57.33 305 | 80.49 317 | 87.32 294 | 63.22 285 | 68.76 229 | 90.12 172 | 44.89 277 | 91.59 284 | 70.55 182 | 74.09 215 | 89.79 206 |
|
ACMM | | 69.62 13 | 74.34 238 | 72.73 239 | 79.17 263 | 84.25 266 | 57.87 295 | 90.36 215 | 89.93 226 | 63.17 286 | 65.64 260 | 86.04 218 | 37.79 308 | 94.10 207 | 65.89 224 | 71.52 234 | 85.55 277 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
CNLPA | | | 74.31 239 | 72.30 245 | 80.32 236 | 91.49 126 | 61.66 241 | 90.85 201 | 80.72 340 | 56.67 329 | 63.85 277 | 90.64 157 | 46.75 262 | 90.84 293 | 53.79 287 | 75.99 209 | 88.47 223 |
|
XVG-OURS | | | 74.25 240 | 72.46 244 | 79.63 255 | 78.45 326 | 57.59 300 | 80.33 319 | 87.39 293 | 63.86 280 | 68.76 229 | 89.62 176 | 40.50 292 | 91.72 282 | 69.00 195 | 74.25 213 | 89.58 209 |
|
CVMVSNet | | | 74.04 241 | 74.27 220 | 73.33 313 | 85.33 245 | 43.94 359 | 89.53 237 | 88.39 277 | 54.33 335 | 70.37 205 | 90.13 170 | 49.17 245 | 84.05 340 | 61.83 256 | 79.36 178 | 91.99 176 |
|
Baseline_NR-MVSNet | | | 73.99 242 | 72.83 237 | 77.48 281 | 80.78 295 | 59.29 281 | 91.79 160 | 84.55 321 | 68.85 243 | 68.99 223 | 80.70 280 | 56.16 174 | 92.04 276 | 62.67 250 | 60.98 311 | 81.11 324 |
|
pmmvs4 | | | 73.92 243 | 71.81 250 | 80.25 240 | 79.17 315 | 65.24 154 | 87.43 272 | 87.26 296 | 67.64 255 | 63.46 280 | 83.91 239 | 48.96 248 | 91.53 289 | 62.94 247 | 65.49 269 | 83.96 291 |
|
D2MVS | | | 73.80 244 | 72.02 248 | 79.15 265 | 79.15 316 | 62.97 215 | 88.58 256 | 90.07 220 | 72.94 154 | 59.22 302 | 78.30 302 | 42.31 287 | 92.70 254 | 65.59 229 | 72.00 230 | 81.79 321 |
|
CR-MVSNet | | | 73.79 245 | 70.82 257 | 82.70 177 | 83.15 279 | 67.96 81 | 70.25 345 | 84.00 326 | 73.67 142 | 69.97 212 | 72.41 335 | 57.82 152 | 89.48 309 | 52.99 291 | 73.13 221 | 90.64 198 |
|
test_djsdf | | | 73.76 246 | 72.56 242 | 77.39 283 | 77.00 335 | 53.93 323 | 89.07 248 | 90.69 195 | 65.80 267 | 63.92 275 | 82.03 258 | 43.14 284 | 92.67 255 | 72.83 157 | 68.53 252 | 85.57 276 |
|
pmmvs5 | | | 73.35 247 | 71.52 252 | 78.86 267 | 78.64 324 | 60.61 263 | 91.08 194 | 86.90 297 | 67.69 252 | 63.32 281 | 83.64 240 | 44.33 279 | 90.53 295 | 62.04 254 | 66.02 268 | 85.46 278 |
|
Anonymous20231211 | | | 73.08 248 | 70.39 259 | 81.13 221 | 90.62 143 | 63.33 207 | 91.40 176 | 90.06 223 | 51.84 340 | 64.46 272 | 80.67 282 | 36.49 318 | 94.07 210 | 63.83 241 | 64.17 284 | 85.98 267 |
|
miper_lstm_enhance | | | 73.05 249 | 71.73 251 | 77.03 287 | 83.80 270 | 58.32 290 | 81.76 307 | 88.88 264 | 69.80 232 | 61.01 293 | 78.23 304 | 57.19 157 | 87.51 327 | 65.34 232 | 59.53 319 | 85.27 283 |
|
jajsoiax | | | 73.05 249 | 71.51 253 | 77.67 278 | 77.46 332 | 54.83 319 | 88.81 252 | 90.04 224 | 69.13 241 | 62.85 286 | 83.51 242 | 31.16 336 | 92.75 251 | 70.83 177 | 69.80 241 | 85.43 279 |
|
LCM-MVSNet-Re | | | 72.93 251 | 71.84 249 | 76.18 296 | 88.49 185 | 48.02 348 | 80.07 324 | 70.17 360 | 73.96 133 | 52.25 330 | 80.09 292 | 49.98 235 | 88.24 318 | 67.35 207 | 84.23 151 | 92.28 170 |
|
pm-mvs1 | | | 72.89 252 | 71.09 255 | 78.26 273 | 79.10 318 | 57.62 299 | 90.80 203 | 89.30 246 | 67.66 253 | 62.91 285 | 81.78 261 | 49.11 247 | 92.95 240 | 60.29 264 | 58.89 322 | 84.22 290 |
|
tpmvs | | | 72.88 253 | 69.76 265 | 82.22 192 | 90.98 135 | 67.05 108 | 78.22 333 | 88.30 279 | 63.10 287 | 64.35 274 | 74.98 327 | 55.09 188 | 94.27 202 | 43.25 326 | 69.57 244 | 85.34 281 |
|
test0.0.03 1 | | | 72.76 254 | 72.71 240 | 72.88 317 | 80.25 304 | 47.99 349 | 91.22 188 | 89.45 241 | 71.51 205 | 62.51 289 | 87.66 199 | 53.83 201 | 85.06 337 | 50.16 297 | 67.84 259 | 85.58 275 |
|
UniMVSNet_ETH3D | | | 72.74 255 | 70.53 258 | 79.36 260 | 78.62 325 | 56.64 309 | 85.01 286 | 89.20 250 | 63.77 281 | 64.84 267 | 84.44 234 | 34.05 325 | 91.86 279 | 63.94 240 | 70.89 239 | 89.57 210 |
|
mvs_tets | | | 72.71 256 | 71.11 254 | 77.52 279 | 77.41 333 | 54.52 321 | 88.45 259 | 89.76 230 | 68.76 246 | 62.70 287 | 83.26 246 | 29.49 340 | 92.71 252 | 70.51 183 | 69.62 243 | 85.34 281 |
|
FMVSNet1 | | | 72.71 256 | 69.91 263 | 81.10 223 | 83.60 274 | 65.11 160 | 90.01 226 | 90.32 207 | 63.92 279 | 63.56 279 | 80.25 289 | 36.35 319 | 91.54 286 | 54.46 284 | 66.75 264 | 86.64 249 |
|
IterMVS | | | 72.65 258 | 70.83 256 | 78.09 275 | 82.17 285 | 62.96 216 | 87.64 270 | 86.28 303 | 71.56 203 | 60.44 296 | 78.85 300 | 45.42 274 | 86.66 331 | 63.30 245 | 61.83 302 | 84.65 288 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
PatchMatch-RL | | | 72.06 259 | 69.98 260 | 78.28 272 | 89.51 164 | 55.70 315 | 83.49 295 | 83.39 332 | 61.24 303 | 63.72 278 | 82.76 249 | 34.77 323 | 93.03 238 | 53.37 290 | 77.59 193 | 86.12 264 |
|
PVSNet_0 | | 68.08 15 | 71.81 260 | 68.32 272 | 82.27 189 | 84.68 255 | 62.31 230 | 88.68 254 | 90.31 210 | 75.84 102 | 57.93 313 | 80.65 283 | 37.85 307 | 94.19 205 | 69.94 185 | 29.05 367 | 90.31 201 |
|
MIMVSNet | | | 71.64 261 | 68.44 270 | 81.23 217 | 81.97 288 | 64.44 177 | 73.05 341 | 88.80 267 | 69.67 233 | 64.59 268 | 74.79 328 | 32.79 328 | 87.82 322 | 53.99 286 | 76.35 207 | 91.42 184 |
|
IterMVS-SCA-FT | | | 71.55 262 | 69.97 261 | 76.32 294 | 81.48 290 | 60.67 261 | 87.64 270 | 85.99 308 | 66.17 265 | 59.50 300 | 78.88 299 | 45.53 272 | 83.65 344 | 62.58 251 | 61.93 301 | 84.63 289 |
|
v7n | | | 71.31 263 | 68.65 268 | 79.28 261 | 76.40 338 | 60.77 256 | 86.71 280 | 89.45 241 | 64.17 278 | 58.77 307 | 78.24 303 | 44.59 278 | 93.54 229 | 57.76 273 | 61.75 304 | 83.52 297 |
|
anonymousdsp | | | 71.14 264 | 69.37 266 | 76.45 293 | 72.95 348 | 54.71 320 | 84.19 290 | 88.88 264 | 61.92 299 | 62.15 290 | 79.77 294 | 38.14 303 | 91.44 291 | 68.90 197 | 67.45 261 | 83.21 303 |
|
F-COLMAP | | | 70.66 265 | 68.44 270 | 77.32 284 | 86.37 231 | 55.91 313 | 88.00 263 | 86.32 302 | 56.94 327 | 57.28 316 | 88.07 194 | 33.58 326 | 92.49 262 | 51.02 294 | 68.37 253 | 83.55 295 |
|
WR-MVS_H | | | 70.59 266 | 69.94 262 | 72.53 319 | 81.03 293 | 51.43 334 | 87.35 273 | 92.03 140 | 67.38 256 | 60.23 297 | 80.70 280 | 55.84 181 | 83.45 346 | 46.33 316 | 58.58 324 | 82.72 309 |
|
CP-MVSNet | | | 70.50 267 | 69.91 263 | 72.26 322 | 80.71 296 | 51.00 337 | 87.23 274 | 90.30 211 | 67.84 250 | 59.64 299 | 82.69 250 | 50.23 234 | 82.30 354 | 51.28 293 | 59.28 320 | 83.46 299 |
|
RPMNet | | | 70.42 268 | 65.68 284 | 84.63 131 | 83.15 279 | 67.96 81 | 70.25 345 | 90.45 201 | 46.83 354 | 69.97 212 | 65.10 352 | 56.48 173 | 95.30 169 | 35.79 351 | 73.13 221 | 90.64 198 |
|
tfpnnormal | | | 70.10 269 | 67.36 275 | 78.32 271 | 83.45 276 | 60.97 252 | 88.85 251 | 92.77 112 | 64.85 274 | 60.83 295 | 78.53 301 | 43.52 283 | 93.48 231 | 31.73 362 | 61.70 306 | 80.52 331 |
|
TransMVSNet (Re) | | | 70.07 270 | 67.66 274 | 77.31 285 | 80.62 299 | 59.13 283 | 91.78 162 | 84.94 317 | 65.97 266 | 60.08 298 | 80.44 285 | 50.78 228 | 91.87 278 | 48.84 303 | 45.46 351 | 80.94 326 |
|
CL-MVSNet_self_test | | | 69.92 271 | 68.09 273 | 75.41 299 | 73.25 347 | 55.90 314 | 90.05 225 | 89.90 227 | 69.96 229 | 61.96 292 | 76.54 317 | 51.05 227 | 87.64 324 | 49.51 301 | 50.59 343 | 82.70 311 |
|
DP-MVS | | | 69.90 272 | 66.48 278 | 80.14 241 | 95.36 30 | 62.93 217 | 89.56 234 | 76.11 347 | 50.27 345 | 57.69 314 | 85.23 224 | 39.68 294 | 95.73 143 | 33.35 356 | 71.05 238 | 81.78 322 |
|
PS-CasMVS | | | 69.86 273 | 69.13 267 | 72.07 325 | 80.35 302 | 50.57 339 | 87.02 276 | 89.75 231 | 67.27 257 | 59.19 303 | 82.28 254 | 46.58 264 | 82.24 355 | 50.69 295 | 59.02 321 | 83.39 301 |
|
MSDG | | | 69.54 274 | 65.73 283 | 80.96 228 | 85.11 251 | 63.71 198 | 84.19 290 | 83.28 333 | 56.95 326 | 54.50 321 | 84.03 236 | 31.50 334 | 96.03 134 | 42.87 330 | 69.13 248 | 83.14 305 |
|
PEN-MVS | | | 69.46 275 | 68.56 269 | 72.17 324 | 79.27 313 | 49.71 343 | 86.90 278 | 89.24 248 | 67.24 260 | 59.08 304 | 82.51 253 | 47.23 261 | 83.54 345 | 48.42 305 | 57.12 325 | 83.25 302 |
|
LS3D | | | 69.17 276 | 66.40 279 | 77.50 280 | 91.92 111 | 56.12 312 | 85.12 285 | 80.37 341 | 46.96 352 | 56.50 318 | 87.51 202 | 37.25 311 | 93.71 226 | 32.52 361 | 79.40 177 | 82.68 312 |
|
PatchT | | | 69.11 277 | 65.37 288 | 80.32 236 | 82.07 287 | 63.68 201 | 67.96 354 | 87.62 291 | 50.86 343 | 69.37 217 | 65.18 351 | 57.09 158 | 88.53 316 | 41.59 335 | 66.60 265 | 88.74 217 |
|
KD-MVS_2432*1600 | | | 69.03 278 | 66.37 280 | 77.01 288 | 85.56 243 | 61.06 250 | 81.44 312 | 90.25 213 | 67.27 257 | 58.00 311 | 76.53 318 | 54.49 193 | 87.63 325 | 48.04 307 | 35.77 362 | 82.34 315 |
|
miper_refine_blended | | | 69.03 278 | 66.37 280 | 77.01 288 | 85.56 243 | 61.06 250 | 81.44 312 | 90.25 213 | 67.27 257 | 58.00 311 | 76.53 318 | 54.49 193 | 87.63 325 | 48.04 307 | 35.77 362 | 82.34 315 |
|
MVS_0304 | | | 68.99 280 | 67.23 277 | 74.28 308 | 80.36 301 | 52.54 328 | 87.01 277 | 86.36 301 | 59.89 313 | 66.22 257 | 73.56 331 | 24.25 350 | 88.03 320 | 57.34 276 | 70.11 240 | 82.27 317 |
|
ACMH | | 63.93 17 | 68.62 281 | 64.81 289 | 80.03 244 | 85.22 247 | 63.25 208 | 87.72 268 | 84.66 320 | 60.83 305 | 51.57 333 | 79.43 298 | 27.29 346 | 94.96 176 | 41.76 333 | 64.84 277 | 81.88 320 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
EG-PatchMatch MVS | | | 68.55 282 | 65.41 287 | 77.96 276 | 78.69 323 | 62.93 217 | 89.86 231 | 89.17 252 | 60.55 306 | 50.27 338 | 77.73 308 | 22.60 355 | 94.06 211 | 47.18 313 | 72.65 226 | 76.88 350 |
|
ADS-MVSNet | | | 68.54 283 | 64.38 296 | 81.03 227 | 88.06 200 | 66.90 113 | 68.01 352 | 84.02 325 | 57.57 321 | 64.48 270 | 69.87 344 | 38.68 296 | 89.21 311 | 40.87 337 | 67.89 257 | 86.97 243 |
|
DTE-MVSNet | | | 68.46 284 | 67.33 276 | 71.87 327 | 77.94 330 | 49.00 346 | 86.16 283 | 88.58 275 | 66.36 264 | 58.19 308 | 82.21 256 | 46.36 265 | 83.87 343 | 44.97 323 | 55.17 332 | 82.73 308 |
|
our_test_3 | | | 68.29 285 | 64.69 291 | 79.11 266 | 78.92 319 | 64.85 169 | 88.40 260 | 85.06 315 | 60.32 309 | 52.68 328 | 76.12 322 | 40.81 291 | 89.80 308 | 44.25 325 | 55.65 330 | 82.67 313 |
|
Patchmatch-RL test | | | 68.17 286 | 64.49 294 | 79.19 262 | 71.22 352 | 53.93 323 | 70.07 347 | 71.54 359 | 69.22 238 | 56.79 317 | 62.89 354 | 56.58 171 | 88.61 313 | 69.53 189 | 52.61 338 | 95.03 80 |
|
XVG-ACMP-BASELINE | | | 68.04 287 | 65.53 286 | 75.56 298 | 74.06 346 | 52.37 329 | 78.43 330 | 85.88 309 | 62.03 297 | 58.91 306 | 81.21 276 | 20.38 359 | 91.15 292 | 60.69 261 | 68.18 254 | 83.16 304 |
|
FMVSNet5 | | | 68.04 287 | 65.66 285 | 75.18 301 | 84.43 262 | 57.89 294 | 83.54 294 | 86.26 304 | 61.83 301 | 53.64 326 | 73.30 332 | 37.15 314 | 85.08 336 | 48.99 302 | 61.77 303 | 82.56 314 |
|
ppachtmachnet_test | | | 67.72 289 | 63.70 298 | 79.77 252 | 78.92 319 | 66.04 134 | 88.68 254 | 82.90 335 | 60.11 311 | 55.45 319 | 75.96 323 | 39.19 295 | 90.55 294 | 39.53 341 | 52.55 339 | 82.71 310 |
|
ACMH+ | | 65.35 16 | 67.65 290 | 64.55 292 | 76.96 290 | 84.59 258 | 57.10 307 | 88.08 262 | 80.79 339 | 58.59 320 | 53.00 327 | 81.09 278 | 26.63 348 | 92.95 240 | 46.51 314 | 61.69 307 | 80.82 327 |
|
pmmvs6 | | | 67.57 291 | 64.76 290 | 76.00 297 | 72.82 350 | 53.37 325 | 88.71 253 | 86.78 300 | 53.19 337 | 57.58 315 | 78.03 306 | 35.33 322 | 92.41 265 | 55.56 281 | 54.88 334 | 82.21 318 |
|
Anonymous20231206 | | | 67.53 292 | 65.78 282 | 72.79 318 | 74.95 342 | 47.59 351 | 88.23 261 | 87.32 294 | 61.75 302 | 58.07 310 | 77.29 311 | 37.79 308 | 87.29 329 | 42.91 328 | 63.71 288 | 83.48 298 |
|
Patchmtry | | | 67.53 292 | 63.93 297 | 78.34 270 | 82.12 286 | 64.38 181 | 68.72 349 | 84.00 326 | 48.23 351 | 59.24 301 | 72.41 335 | 57.82 152 | 89.27 310 | 46.10 317 | 56.68 329 | 81.36 323 |
|
USDC | | | 67.43 294 | 64.51 293 | 76.19 295 | 77.94 330 | 55.29 317 | 78.38 331 | 85.00 316 | 73.17 149 | 48.36 344 | 80.37 286 | 21.23 357 | 92.48 263 | 52.15 292 | 64.02 286 | 80.81 328 |
|
ADS-MVSNet2 | | | 66.90 295 | 63.44 300 | 77.26 286 | 88.06 200 | 60.70 260 | 68.01 352 | 75.56 350 | 57.57 321 | 64.48 270 | 69.87 344 | 38.68 296 | 84.10 339 | 40.87 337 | 67.89 257 | 86.97 243 |
|
CMPMVS |  | 48.56 21 | 66.77 296 | 64.41 295 | 73.84 310 | 70.65 355 | 50.31 340 | 77.79 335 | 85.73 311 | 45.54 355 | 44.76 353 | 82.14 257 | 35.40 321 | 90.14 304 | 63.18 246 | 74.54 212 | 81.07 325 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
OpenMVS_ROB |  | 61.12 18 | 66.39 297 | 62.92 303 | 76.80 292 | 76.51 337 | 57.77 296 | 89.22 243 | 83.41 331 | 55.48 333 | 53.86 325 | 77.84 307 | 26.28 349 | 93.95 220 | 34.90 353 | 68.76 250 | 78.68 345 |
|
LTVRE_ROB | | 59.60 19 | 66.27 298 | 63.54 299 | 74.45 305 | 84.00 269 | 51.55 333 | 67.08 355 | 83.53 329 | 58.78 318 | 54.94 320 | 80.31 287 | 34.54 324 | 93.23 235 | 40.64 339 | 68.03 255 | 78.58 346 |
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 |
JIA-IIPM | | | 66.06 299 | 62.45 306 | 76.88 291 | 81.42 292 | 54.45 322 | 57.49 363 | 88.67 271 | 49.36 347 | 63.86 276 | 46.86 362 | 56.06 177 | 90.25 298 | 49.53 300 | 68.83 249 | 85.95 268 |
|
Patchmatch-test | | | 65.86 300 | 60.94 312 | 80.62 233 | 83.75 271 | 58.83 284 | 58.91 362 | 75.26 352 | 44.50 358 | 50.95 337 | 77.09 314 | 58.81 145 | 87.90 321 | 35.13 352 | 64.03 285 | 95.12 74 |
|
UnsupCasMVSNet_eth | | | 65.79 301 | 63.10 301 | 73.88 309 | 70.71 354 | 50.29 341 | 81.09 314 | 89.88 228 | 72.58 162 | 49.25 342 | 74.77 329 | 32.57 330 | 87.43 328 | 55.96 280 | 41.04 357 | 83.90 293 |
|
pmmvs-eth3d | | | 65.53 302 | 62.32 307 | 75.19 300 | 69.39 358 | 59.59 275 | 82.80 304 | 83.43 330 | 62.52 293 | 51.30 335 | 72.49 333 | 32.86 327 | 87.16 330 | 55.32 282 | 50.73 342 | 78.83 344 |
|
SixPastTwentyTwo | | | 64.92 303 | 61.78 310 | 74.34 307 | 78.74 322 | 49.76 342 | 83.42 298 | 79.51 344 | 62.86 288 | 50.27 338 | 77.35 309 | 30.92 338 | 90.49 296 | 45.89 318 | 47.06 348 | 82.78 306 |
|
OurMVSNet-221017-0 | | | 64.68 304 | 62.17 308 | 72.21 323 | 76.08 341 | 47.35 352 | 80.67 316 | 81.02 338 | 56.19 330 | 51.60 332 | 79.66 296 | 27.05 347 | 88.56 315 | 53.60 289 | 53.63 337 | 80.71 329 |
|
test_0402 | | | 64.54 305 | 61.09 311 | 74.92 302 | 84.10 268 | 60.75 258 | 87.95 264 | 79.71 343 | 52.03 339 | 52.41 329 | 77.20 312 | 32.21 332 | 91.64 283 | 23.14 365 | 61.03 310 | 72.36 357 |
|
testgi | | | 64.48 306 | 62.87 304 | 69.31 332 | 71.24 351 | 40.62 363 | 85.49 284 | 79.92 342 | 65.36 271 | 54.18 323 | 83.49 243 | 23.74 353 | 84.55 338 | 41.60 334 | 60.79 313 | 82.77 307 |
|
RPSCF | | | 64.24 307 | 61.98 309 | 71.01 329 | 76.10 340 | 45.00 356 | 75.83 338 | 75.94 348 | 46.94 353 | 58.96 305 | 84.59 232 | 31.40 335 | 82.00 356 | 47.76 311 | 60.33 318 | 86.04 265 |
|
EU-MVSNet | | | 64.01 308 | 63.01 302 | 67.02 339 | 74.40 345 | 38.86 368 | 83.27 299 | 86.19 306 | 45.11 356 | 54.27 322 | 81.15 277 | 36.91 317 | 80.01 359 | 48.79 304 | 57.02 326 | 82.19 319 |
|
test20.03 | | | 63.83 309 | 62.65 305 | 67.38 338 | 70.58 356 | 39.94 364 | 86.57 281 | 84.17 323 | 63.29 284 | 51.86 331 | 77.30 310 | 37.09 315 | 82.47 352 | 38.87 345 | 54.13 336 | 79.73 337 |
|
MDA-MVSNet_test_wron | | | 63.78 310 | 60.16 313 | 74.64 303 | 78.15 328 | 60.41 264 | 83.49 295 | 84.03 324 | 56.17 332 | 39.17 361 | 71.59 341 | 37.22 312 | 83.24 349 | 42.87 330 | 48.73 345 | 80.26 334 |
|
YYNet1 | | | 63.76 311 | 60.14 314 | 74.62 304 | 78.06 329 | 60.19 269 | 83.46 297 | 83.99 328 | 56.18 331 | 39.25 360 | 71.56 342 | 37.18 313 | 83.34 347 | 42.90 329 | 48.70 346 | 80.32 333 |
|
K. test v3 | | | 63.09 312 | 59.61 316 | 73.53 312 | 76.26 339 | 49.38 345 | 83.27 299 | 77.15 346 | 64.35 276 | 47.77 346 | 72.32 337 | 28.73 342 | 87.79 323 | 49.93 299 | 36.69 361 | 83.41 300 |
|
COLMAP_ROB |  | 57.96 20 | 62.98 313 | 59.65 315 | 72.98 316 | 81.44 291 | 53.00 327 | 83.75 293 | 75.53 351 | 48.34 350 | 48.81 343 | 81.40 270 | 24.14 351 | 90.30 297 | 32.95 358 | 60.52 315 | 75.65 353 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
Anonymous20240521 | | | 62.09 314 | 59.08 317 | 71.10 328 | 67.19 360 | 48.72 347 | 83.91 292 | 85.23 314 | 50.38 344 | 47.84 345 | 71.22 343 | 20.74 358 | 85.51 335 | 46.47 315 | 58.75 323 | 79.06 342 |
|
AllTest | | | 61.66 315 | 58.06 319 | 72.46 320 | 79.57 308 | 51.42 335 | 80.17 322 | 68.61 362 | 51.25 341 | 45.88 348 | 81.23 272 | 19.86 360 | 86.58 332 | 38.98 343 | 57.01 327 | 79.39 339 |
|
UnsupCasMVSNet_bld | | | 61.60 316 | 57.71 320 | 73.29 314 | 68.73 359 | 51.64 332 | 78.61 329 | 89.05 260 | 57.20 325 | 46.11 347 | 61.96 356 | 28.70 343 | 88.60 314 | 50.08 298 | 38.90 359 | 79.63 338 |
|
MDA-MVSNet-bldmvs | | | 61.54 317 | 57.70 321 | 73.05 315 | 79.53 310 | 57.00 308 | 83.08 302 | 81.23 337 | 57.57 321 | 34.91 363 | 72.45 334 | 32.79 328 | 86.26 334 | 35.81 350 | 41.95 355 | 75.89 352 |
|
KD-MVS_self_test | | | 60.87 318 | 58.60 318 | 67.68 336 | 66.13 361 | 39.93 365 | 75.63 339 | 84.70 319 | 57.32 324 | 49.57 341 | 68.45 347 | 29.55 339 | 82.87 350 | 48.09 306 | 47.94 347 | 80.25 335 |
|
TinyColmap | | | 60.32 319 | 56.42 325 | 72.00 326 | 78.78 321 | 53.18 326 | 78.36 332 | 75.64 349 | 52.30 338 | 41.59 359 | 75.82 325 | 14.76 365 | 88.35 317 | 35.84 349 | 54.71 335 | 74.46 354 |
|
MVS-HIRNet | | | 60.25 320 | 55.55 326 | 74.35 306 | 84.37 263 | 56.57 310 | 71.64 343 | 74.11 353 | 34.44 363 | 45.54 352 | 42.24 366 | 31.11 337 | 89.81 306 | 40.36 340 | 76.10 208 | 76.67 351 |
|
MIMVSNet1 | | | 60.16 321 | 57.33 322 | 68.67 333 | 69.71 357 | 44.13 358 | 78.92 328 | 84.21 322 | 55.05 334 | 44.63 354 | 71.85 339 | 23.91 352 | 81.54 358 | 32.63 360 | 55.03 333 | 80.35 332 |
|
PM-MVS | | | 59.40 322 | 56.59 323 | 67.84 334 | 63.63 363 | 41.86 360 | 76.76 336 | 63.22 368 | 59.01 317 | 51.07 336 | 72.27 338 | 11.72 368 | 83.25 348 | 61.34 257 | 50.28 344 | 78.39 347 |
|
new-patchmatchnet | | | 59.30 323 | 56.48 324 | 67.79 335 | 65.86 362 | 44.19 357 | 82.47 305 | 81.77 336 | 59.94 312 | 43.65 357 | 66.20 350 | 27.67 345 | 81.68 357 | 39.34 342 | 41.40 356 | 77.50 349 |
|
DSMNet-mixed | | | 56.78 324 | 54.44 327 | 63.79 341 | 63.21 364 | 29.44 372 | 64.43 357 | 64.10 367 | 42.12 360 | 51.32 334 | 71.60 340 | 31.76 333 | 75.04 361 | 36.23 348 | 65.20 274 | 86.87 246 |
|
pmmvs3 | | | 55.51 325 | 51.50 330 | 67.53 337 | 57.90 369 | 50.93 338 | 80.37 318 | 73.66 354 | 40.63 361 | 44.15 356 | 64.75 353 | 16.30 362 | 78.97 360 | 44.77 324 | 40.98 358 | 72.69 355 |
|
TDRefinement | | | 55.28 326 | 51.58 329 | 66.39 340 | 59.53 368 | 46.15 355 | 76.23 337 | 72.80 355 | 44.60 357 | 42.49 358 | 76.28 321 | 15.29 363 | 82.39 353 | 33.20 357 | 43.75 353 | 70.62 359 |
|
LF4IMVS | | | 54.01 327 | 52.12 328 | 59.69 342 | 62.41 366 | 39.91 366 | 68.59 350 | 68.28 364 | 42.96 359 | 44.55 355 | 75.18 326 | 14.09 367 | 68.39 365 | 41.36 336 | 51.68 340 | 70.78 358 |
|
N_pmnet | | | 50.55 328 | 49.11 331 | 54.88 346 | 77.17 334 | 4.02 382 | 84.36 289 | 2.00 381 | 48.59 348 | 45.86 350 | 68.82 346 | 32.22 331 | 82.80 351 | 31.58 363 | 51.38 341 | 77.81 348 |
|
new_pmnet | | | 49.31 329 | 46.44 332 | 57.93 343 | 62.84 365 | 40.74 362 | 68.47 351 | 62.96 369 | 36.48 362 | 35.09 362 | 57.81 358 | 14.97 364 | 72.18 363 | 32.86 359 | 46.44 349 | 60.88 363 |
|
FPMVS | | | 45.64 330 | 43.10 333 | 53.23 348 | 51.42 372 | 36.46 369 | 64.97 356 | 71.91 357 | 29.13 365 | 27.53 365 | 61.55 357 | 9.83 370 | 65.01 369 | 16.00 369 | 55.58 331 | 58.22 364 |
|
EGC-MVSNET | | | 42.35 331 | 38.09 334 | 55.11 345 | 74.57 343 | 46.62 354 | 71.63 344 | 55.77 371 | 0.04 376 | 0.24 377 | 62.70 355 | 14.24 366 | 74.91 362 | 17.59 368 | 46.06 350 | 43.80 365 |
|
LCM-MVSNet | | | 40.54 332 | 35.79 335 | 54.76 347 | 36.92 377 | 30.81 371 | 51.41 364 | 69.02 361 | 22.07 367 | 24.63 366 | 45.37 364 | 4.56 377 | 65.81 367 | 33.67 355 | 34.50 364 | 67.67 360 |
|
ANet_high | | | 40.27 333 | 35.20 336 | 55.47 344 | 34.74 378 | 34.47 370 | 63.84 358 | 71.56 358 | 48.42 349 | 18.80 369 | 41.08 367 | 9.52 371 | 64.45 370 | 20.18 366 | 8.66 374 | 67.49 361 |
|
test_method | | | 38.59 334 | 35.16 337 | 48.89 350 | 54.33 370 | 21.35 377 | 45.32 367 | 53.71 372 | 7.41 373 | 28.74 364 | 51.62 360 | 8.70 372 | 52.87 371 | 33.73 354 | 32.89 365 | 72.47 356 |
|
PMMVS2 | | | 37.93 335 | 33.61 338 | 50.92 349 | 46.31 374 | 24.76 375 | 60.55 361 | 50.05 373 | 28.94 366 | 20.93 367 | 47.59 361 | 4.41 378 | 65.13 368 | 25.14 364 | 18.55 369 | 62.87 362 |
|
Gipuma |  | | 34.91 336 | 31.44 339 | 45.30 351 | 70.99 353 | 39.64 367 | 19.85 371 | 72.56 356 | 20.10 369 | 16.16 371 | 21.47 372 | 5.08 376 | 71.16 364 | 13.07 370 | 43.70 354 | 25.08 369 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
PMVS |  | 26.43 22 | 31.84 337 | 28.16 340 | 42.89 352 | 25.87 380 | 27.58 373 | 50.92 365 | 49.78 374 | 21.37 368 | 14.17 372 | 40.81 368 | 2.01 379 | 66.62 366 | 9.61 372 | 38.88 360 | 34.49 368 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
E-PMN | | | 24.61 338 | 24.00 342 | 26.45 355 | 43.74 375 | 18.44 379 | 60.86 359 | 39.66 375 | 15.11 370 | 9.53 374 | 22.10 371 | 6.52 374 | 46.94 373 | 8.31 373 | 10.14 371 | 13.98 371 |
|
MVE |  | 24.84 23 | 24.35 339 | 19.77 345 | 38.09 353 | 34.56 379 | 26.92 374 | 26.57 369 | 38.87 377 | 11.73 372 | 11.37 373 | 27.44 369 | 1.37 380 | 50.42 372 | 11.41 371 | 14.60 370 | 36.93 366 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
EMVS | | | 23.76 340 | 23.20 344 | 25.46 356 | 41.52 376 | 16.90 380 | 60.56 360 | 38.79 378 | 14.62 371 | 8.99 375 | 20.24 374 | 7.35 373 | 45.82 374 | 7.25 374 | 9.46 372 | 13.64 372 |
|
tmp_tt | | | 22.26 341 | 23.75 343 | 17.80 357 | 5.23 381 | 12.06 381 | 35.26 368 | 39.48 376 | 2.82 375 | 18.94 368 | 44.20 365 | 22.23 356 | 24.64 376 | 36.30 347 | 9.31 373 | 16.69 370 |
|
cdsmvs_eth3d_5k | | | 19.86 342 | 26.47 341 | 0.00 361 | 0.00 384 | 0.00 385 | 0.00 372 | 93.45 84 | 0.00 379 | 0.00 380 | 95.27 51 | 49.56 239 | 0.00 380 | 0.00 378 | 0.00 377 | 0.00 376 |
|
wuyk23d | | | 11.30 343 | 10.95 346 | 12.33 358 | 48.05 373 | 19.89 378 | 25.89 370 | 1.92 382 | 3.58 374 | 3.12 376 | 1.37 376 | 0.64 381 | 15.77 377 | 6.23 375 | 7.77 375 | 1.35 373 |
|
ab-mvs-re | | | 7.91 344 | 10.55 347 | 0.00 361 | 0.00 384 | 0.00 385 | 0.00 372 | 0.00 385 | 0.00 379 | 0.00 380 | 94.95 63 | 0.00 384 | 0.00 380 | 0.00 378 | 0.00 377 | 0.00 376 |
|
testmvs | | | 7.23 345 | 9.62 348 | 0.06 360 | 0.04 382 | 0.02 384 | 84.98 287 | 0.02 383 | 0.03 377 | 0.18 378 | 1.21 377 | 0.01 383 | 0.02 378 | 0.14 376 | 0.01 376 | 0.13 375 |
|
test123 | | | 6.92 346 | 9.21 349 | 0.08 359 | 0.03 383 | 0.05 383 | 81.65 310 | 0.01 384 | 0.02 378 | 0.14 379 | 0.85 378 | 0.03 382 | 0.02 378 | 0.12 377 | 0.00 377 | 0.16 374 |
|
pcd_1.5k_mvsjas | | | 4.46 347 | 5.95 350 | 0.00 361 | 0.00 384 | 0.00 385 | 0.00 372 | 0.00 385 | 0.00 379 | 0.00 380 | 0.00 379 | 53.55 205 | 0.00 380 | 0.00 378 | 0.00 377 | 0.00 376 |
|
test_blank | | | 0.00 348 | 0.00 351 | 0.00 361 | 0.00 384 | 0.00 385 | 0.00 372 | 0.00 385 | 0.00 379 | 0.00 380 | 0.00 379 | 0.00 384 | 0.00 380 | 0.00 378 | 0.00 377 | 0.00 376 |
|
uanet_test | | | 0.00 348 | 0.00 351 | 0.00 361 | 0.00 384 | 0.00 385 | 0.00 372 | 0.00 385 | 0.00 379 | 0.00 380 | 0.00 379 | 0.00 384 | 0.00 380 | 0.00 378 | 0.00 377 | 0.00 376 |
|
DCPMVS | | | 0.00 348 | 0.00 351 | 0.00 361 | 0.00 384 | 0.00 385 | 0.00 372 | 0.00 385 | 0.00 379 | 0.00 380 | 0.00 379 | 0.00 384 | 0.00 380 | 0.00 378 | 0.00 377 | 0.00 376 |
|
sosnet-low-res | | | 0.00 348 | 0.00 351 | 0.00 361 | 0.00 384 | 0.00 385 | 0.00 372 | 0.00 385 | 0.00 379 | 0.00 380 | 0.00 379 | 0.00 384 | 0.00 380 | 0.00 378 | 0.00 377 | 0.00 376 |
|
sosnet | | | 0.00 348 | 0.00 351 | 0.00 361 | 0.00 384 | 0.00 385 | 0.00 372 | 0.00 385 | 0.00 379 | 0.00 380 | 0.00 379 | 0.00 384 | 0.00 380 | 0.00 378 | 0.00 377 | 0.00 376 |
|
uncertanet | | | 0.00 348 | 0.00 351 | 0.00 361 | 0.00 384 | 0.00 385 | 0.00 372 | 0.00 385 | 0.00 379 | 0.00 380 | 0.00 379 | 0.00 384 | 0.00 380 | 0.00 378 | 0.00 377 | 0.00 376 |
|
Regformer | | | 0.00 348 | 0.00 351 | 0.00 361 | 0.00 384 | 0.00 385 | 0.00 372 | 0.00 385 | 0.00 379 | 0.00 380 | 0.00 379 | 0.00 384 | 0.00 380 | 0.00 378 | 0.00 377 | 0.00 376 |
|
uanet | | | 0.00 348 | 0.00 351 | 0.00 361 | 0.00 384 | 0.00 385 | 0.00 372 | 0.00 385 | 0.00 379 | 0.00 380 | 0.00 379 | 0.00 384 | 0.00 380 | 0.00 378 | 0.00 377 | 0.00 376 |
|
FOURS1 | | | | | | 93.95 53 | 61.77 238 | 93.96 68 | 91.92 144 | 62.14 296 | 86.57 35 | | | | | | |
|
MSC_two_6792asdad | | | | | 89.60 9 | 97.31 4 | 73.22 11 | | 95.05 21 | | | | | 99.07 13 | 92.01 12 | 94.77 25 | 96.51 20 |
|
PC_three_1452 | | | | | | | | | | 80.91 36 | 94.07 2 | 96.83 14 | 83.57 4 | 99.12 5 | 95.70 2 | 97.42 4 | 97.55 4 |
|
No_MVS | | | | | 89.60 9 | 97.31 4 | 73.22 11 | | 95.05 21 | | | | | 99.07 13 | 92.01 12 | 94.77 25 | 96.51 20 |
|
test_one_0601 | | | | | | 96.32 20 | 69.74 42 | | 94.18 56 | 71.42 208 | 90.67 15 | 96.85 12 | 74.45 19 | | | | |
|
eth-test2 | | | | | | 0.00 384 | | | | | | | | | | | |
|
eth-test | | | | | | 0.00 384 | | | | | | | | | | | |
|
ZD-MVS | | | | | | 96.63 11 | 65.50 150 | | 93.50 82 | 70.74 221 | 85.26 52 | 95.19 57 | 64.92 78 | 97.29 78 | 87.51 45 | 93.01 58 | |
|
RE-MVS-def | | | | 80.48 128 | | 92.02 103 | 58.56 287 | 90.90 198 | 90.45 201 | 62.76 289 | 78.89 114 | 94.46 77 | 49.30 242 | | 78.77 119 | 86.77 127 | 92.28 170 |
|
IU-MVS | | | | | | 96.46 13 | 69.91 37 | | 95.18 14 | 80.75 37 | 95.28 1 | | | | 92.34 8 | 95.36 14 | 96.47 24 |
|
OPU-MVS | | | | | 89.97 3 | 97.52 3 | 73.15 13 | 96.89 4 | | | | 97.00 9 | 83.82 2 | 99.15 2 | 95.72 1 | 97.63 3 | 97.62 2 |
|
test_241102_TWO | | | | | | | | | 94.41 46 | 71.65 196 | 92.07 6 | 97.21 5 | 74.58 17 | 99.11 6 | 92.34 8 | 95.36 14 | 96.59 15 |
|
test_241102_ONE | | | | | | 96.45 14 | 69.38 47 | | 94.44 43 | 71.65 196 | 92.11 4 | 97.05 8 | 76.79 9 | 99.11 6 | | | |
|
9.14 | | | | 87.63 25 | | 93.86 55 | | 94.41 51 | 94.18 56 | 72.76 159 | 86.21 38 | 96.51 19 | 66.64 59 | 97.88 49 | 90.08 25 | 94.04 41 | |
|
save fliter | | | | | | 93.84 56 | 67.89 83 | 95.05 39 | 92.66 117 | 78.19 70 | | | | | | | |
|
test_0728_THIRD | | | | | | | | | | 72.48 165 | 90.55 16 | 96.93 10 | 76.24 11 | 99.08 11 | 91.53 16 | 94.99 17 | 96.43 26 |
|
test_0728_SECOND | | | | | 88.70 16 | 96.45 14 | 70.43 28 | 96.64 8 | 94.37 50 | | | | | 99.15 2 | 91.91 14 | 94.90 21 | 96.51 20 |
|
test0726 | | | | | | 96.40 17 | 69.99 33 | 96.76 6 | 94.33 52 | 71.92 182 | 91.89 8 | 97.11 7 | 73.77 22 | | | | |
|
GSMVS | | | | | | | | | | | | | | | | | 94.68 90 |
|
test_part2 | | | | | | 96.29 21 | 68.16 77 | | | | 90.78 13 | | | | | | |
|
sam_mvs1 | | | | | | | | | | | | | 57.85 151 | | | | 94.68 90 |
|
sam_mvs | | | | | | | | | | | | | 54.91 190 | | | | |
|
ambc | | | | | 69.61 331 | 61.38 367 | 41.35 361 | 49.07 366 | 85.86 310 | | 50.18 340 | 66.40 349 | 10.16 369 | 88.14 319 | 45.73 319 | 44.20 352 | 79.32 341 |
|
MTGPA |  | | | | | | | | 92.23 130 | | | | | | | | |
|
test_post1 | | | | | | | | 78.95 327 | | | | 20.70 373 | 53.05 210 | 91.50 290 | 60.43 262 | | |
|
test_post | | | | | | | | | | | | 23.01 370 | 56.49 172 | 92.67 255 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 67.62 348 | 57.62 154 | 90.25 298 | | | |
|
GG-mvs-BLEND | | | | | 86.53 66 | 91.91 112 | 69.67 45 | 75.02 340 | 94.75 31 | | 78.67 121 | 90.85 155 | 77.91 7 | 94.56 191 | 72.25 165 | 93.74 47 | 95.36 57 |
|
MTMP | | | | | | | | 93.77 83 | 32.52 379 | | | | | | | | |
|
gm-plane-assit | | | | | | 88.42 189 | 67.04 109 | | | 78.62 67 | | 91.83 141 | | 97.37 72 | 76.57 133 | | |
|
test9_res | | | | | | | | | | | | | | | 89.41 26 | 94.96 18 | 95.29 63 |
|
TEST9 | | | | | | 94.18 46 | 67.28 100 | 94.16 56 | 93.51 80 | 71.75 194 | 85.52 48 | 95.33 46 | 68.01 44 | 97.27 82 | | | |
|
test_8 | | | | | | 94.19 45 | 67.19 103 | 94.15 58 | 93.42 87 | 71.87 187 | 85.38 50 | 95.35 45 | 68.19 41 | 96.95 102 | | | |
|
agg_prior2 | | | | | | | | | | | | | | | 86.41 56 | 94.75 30 | 95.33 59 |
|
agg_prior | | | | | | 94.16 50 | 66.97 111 | | 93.31 90 | | 84.49 59 | | | 96.75 111 | | | |
|
TestCases | | | | | 72.46 320 | 79.57 308 | 51.42 335 | | 68.61 362 | 51.25 341 | 45.88 348 | 81.23 272 | 19.86 360 | 86.58 332 | 38.98 343 | 57.01 327 | 79.39 339 |
|
test_prior4 | | | | | | | 67.18 105 | 93.92 74 | | | | | | | | | |
|
test_prior2 | | | | | | | | 95.10 37 | | 75.40 109 | 85.25 53 | 95.61 40 | 67.94 45 | | 87.47 46 | 94.77 25 | |
|
test_prior | | | | | 86.42 70 | 94.71 39 | 67.35 98 | | 93.10 102 | | | | | 96.84 107 | | | 95.05 77 |
|
旧先验2 | | | | | | | | 92.00 152 | | 59.37 316 | 87.54 29 | | | 93.47 232 | 75.39 139 | | |
|
æ–°å‡ ä½•2 | | | | | | | | 91.41 174 | | | | | | | | | |
|
æ–°å‡ ä½•1 | | | | | 84.73 125 | 92.32 95 | 64.28 186 | | 91.46 167 | 59.56 314 | 79.77 104 | 92.90 119 | 56.95 165 | 96.57 116 | 63.40 243 | 92.91 60 | 93.34 139 |
|
旧先验1 | | | | | | 91.94 109 | 60.74 259 | | 91.50 165 | | | 94.36 81 | 65.23 72 | | | 91.84 77 | 94.55 95 |
|
æ— å…ˆéªŒ | | | | | | | | 92.71 120 | 92.61 121 | 62.03 297 | | | | 97.01 93 | 66.63 213 | | 93.97 122 |
|
原ACMM2 | | | | | | | | 92.01 149 | | | | | | | | | |
|
原ACMM1 | | | | | 84.42 136 | 93.21 74 | 64.27 187 | | 93.40 89 | 65.39 270 | 79.51 107 | 92.50 127 | 58.11 150 | 96.69 113 | 65.27 233 | 93.96 42 | 92.32 168 |
|
test222 | | | | | | 89.77 157 | 61.60 242 | 89.55 235 | 89.42 243 | 56.83 328 | 77.28 134 | 92.43 131 | 52.76 212 | | | 91.14 91 | 93.09 149 |
|
testdata2 | | | | | | | | | | | | | | 96.09 129 | 61.26 258 | | |
|
segment_acmp | | | | | | | | | | | | | 65.94 65 | | | | |
|
testdata | | | | | 81.34 214 | 89.02 175 | 57.72 297 | | 89.84 229 | 58.65 319 | 85.32 51 | 94.09 94 | 57.03 160 | 93.28 234 | 69.34 191 | 90.56 97 | 93.03 151 |
|
testdata1 | | | | | | | | 89.21 244 | | 77.55 84 | | | | | | | |
|
test12 | | | | | 87.09 45 | 94.60 41 | 68.86 58 | | 92.91 108 | | 82.67 76 | | 65.44 71 | 97.55 64 | | 93.69 50 | 94.84 86 |
|
plane_prior7 | | | | | | 86.94 221 | 61.51 243 | | | | | | | | | | |
|
plane_prior6 | | | | | | 87.23 216 | 62.32 229 | | | | | | 50.66 229 | | | | |
|
plane_prior5 | | | | | | | | | 91.31 172 | | | | | 95.55 157 | 76.74 131 | 78.53 187 | 88.39 224 |
|
plane_prior4 | | | | | | | | | | | | 89.14 180 | | | | | |
|
plane_prior3 | | | | | | | 61.95 236 | | | 79.09 59 | 72.53 179 | | | | | | |
|
plane_prior2 | | | | | | | | 93.13 103 | | 78.81 64 | | | | | | | |
|
plane_prior1 | | | | | | 87.15 218 | | | | | | | | | | | |
|
plane_prior | | | | | | | 62.42 226 | 93.85 78 | | 79.38 51 | | | | | | 78.80 184 | |
|
n2 | | | | | | | | | 0.00 385 | | | | | | | | |
|
nn | | | | | | | | | 0.00 385 | | | | | | | | |
|
door-mid | | | | | | | | | 66.01 366 | | | | | | | | |
|
lessismore_v0 | | | | | 73.72 311 | 72.93 349 | 47.83 350 | | 61.72 370 | | 45.86 350 | 73.76 330 | 28.63 344 | 89.81 306 | 47.75 312 | 31.37 366 | 83.53 296 |
|
LGP-MVS_train | | | | | 79.56 258 | 84.31 264 | 59.37 279 | | 89.73 234 | 69.49 234 | 64.86 265 | 88.42 185 | 38.65 298 | 94.30 200 | 72.56 162 | 72.76 224 | 85.01 284 |
|
test11 | | | | | | | | | 93.01 104 | | | | | | | | |
|
door | | | | | | | | | 66.57 365 | | | | | | | | |
|
HQP5-MVS | | | | | | | 63.66 202 | | | | | | | | | | |
|
HQP-NCC | | | | | | 87.54 210 | | 94.06 63 | | 79.80 45 | 74.18 160 | | | | | | |
|
ACMP_Plane | | | | | | 87.54 210 | | 94.06 63 | | 79.80 45 | 74.18 160 | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 77.63 128 | | |
|
HQP4-MVS | | | | | | | | | | | 74.18 160 | | | 95.61 151 | | | 88.63 218 |
|
HQP3-MVS | | | | | | | | | 91.70 156 | | | | | | | 78.90 182 | |
|
HQP2-MVS | | | | | | | | | | | | | 51.63 222 | | | | |
|
NP-MVS | | | | | | 87.41 213 | 63.04 213 | | | | | 90.30 166 | | | | | |
|
MDTV_nov1_ep13_2view | | | | | | | 59.90 272 | 80.13 323 | | 67.65 254 | 72.79 174 | | 54.33 198 | | 59.83 266 | | 92.58 162 |
|
MDTV_nov1_ep13 | | | | 72.61 241 | | 89.06 174 | 68.48 66 | 80.33 319 | 90.11 219 | 71.84 190 | 71.81 191 | 75.92 324 | 53.01 211 | 93.92 221 | 48.04 307 | 73.38 219 | |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 71.63 232 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 69.72 242 | |
|
Test By Simon | | | | | | | | | | | | | 54.21 199 | | | | |
|
ITE_SJBPF | | | | | 70.43 330 | 74.44 344 | 47.06 353 | | 77.32 345 | 60.16 310 | 54.04 324 | 83.53 241 | 23.30 354 | 84.01 341 | 43.07 327 | 61.58 308 | 80.21 336 |
|
DeepMVS_CX |  | | | | 34.71 354 | 51.45 371 | 24.73 376 | | 28.48 380 | 31.46 364 | 17.49 370 | 52.75 359 | 5.80 375 | 42.60 375 | 18.18 367 | 19.42 368 | 36.81 367 |
|