HPM-MVS++ | | | 95.14 7 | 94.91 9 | 95.83 1 | 98.25 23 | 89.65 1 | 95.92 43 | 96.96 40 | 91.75 8 | 94.02 21 | 96.83 33 | 88.12 11 | 99.55 8 | 93.41 17 | 98.94 5 | 98.28 29 |
|
SMA-MVS | | | 95.20 5 | 95.07 7 | 95.59 2 | 98.14 27 | 88.48 4 | 96.26 29 | 97.28 20 | 85.90 119 | 97.67 1 | 98.10 1 | 88.41 10 | 99.56 3 | 94.66 4 | 99.19 1 | 98.71 5 |
|
3Dnovator+ | | 87.14 4 | 92.42 59 | 91.37 63 | 95.55 3 | 95.63 107 | 88.73 2 | 97.07 8 | 96.77 55 | 90.84 17 | 84.02 225 | 96.62 45 | 75.95 139 | 99.34 24 | 87.77 90 | 97.68 56 | 98.59 9 |
|
CNVR-MVS | | | 95.40 3 | 95.37 4 | 95.50 4 | 98.11 28 | 88.51 3 | 95.29 68 | 96.96 40 | 92.09 3 | 95.32 11 | 97.08 26 | 89.49 5 | 99.33 27 | 95.10 2 | 98.85 8 | 98.66 6 |
|
ACMMP_Plus | | | 94.74 11 | 94.56 12 | 95.28 5 | 98.02 33 | 87.70 5 | 95.68 52 | 97.34 12 | 88.28 66 | 95.30 12 | 97.67 5 | 85.90 33 | 99.54 11 | 93.91 11 | 98.95 4 | 98.60 8 |
|
ESAPD | | | 95.57 1 | 95.67 1 | 95.25 6 | 98.36 19 | 87.28 11 | 95.56 59 | 97.51 4 | 89.13 45 | 97.14 2 | 97.91 3 | 91.64 1 | 99.62 1 | 94.61 5 | 99.17 2 | 98.86 2 |
|
MCST-MVS | | | 94.45 14 | 94.20 21 | 95.19 7 | 98.46 12 | 87.50 9 | 95.00 92 | 97.12 29 | 87.13 93 | 92.51 54 | 96.30 56 | 89.24 7 | 99.34 24 | 93.46 14 | 98.62 32 | 98.73 4 |
|
NCCC | | | 94.81 10 | 94.69 11 | 95.17 8 | 97.83 35 | 87.46 10 | 95.66 54 | 96.93 43 | 92.34 2 | 93.94 22 | 96.58 47 | 87.74 14 | 99.44 21 | 92.83 22 | 98.40 39 | 98.62 7 |
|
MVS_0304 | | | 93.25 48 | 92.62 52 | 95.14 9 | 95.72 102 | 87.58 8 | 94.71 115 | 96.59 70 | 91.78 7 | 91.46 75 | 96.18 65 | 75.45 150 | 99.55 8 | 93.53 12 | 98.19 45 | 98.28 29 |
|
zzz-MVS | | | 94.47 13 | 94.30 15 | 95.00 10 | 98.42 14 | 86.95 13 | 95.06 88 | 96.97 37 | 91.07 14 | 93.14 38 | 97.56 7 | 84.30 50 | 99.56 3 | 93.43 15 | 98.75 16 | 98.47 14 |
|
MTAPA | | | 94.42 18 | 94.22 18 | 95.00 10 | 98.42 14 | 86.95 13 | 94.36 146 | 96.97 37 | 91.07 14 | 93.14 38 | 97.56 7 | 84.30 50 | 99.56 3 | 93.43 15 | 98.75 16 | 98.47 14 |
|
region2R | | | 94.43 16 | 94.27 17 | 94.92 12 | 98.65 1 | 86.67 25 | 96.92 14 | 97.23 23 | 88.60 59 | 93.58 29 | 97.27 14 | 85.22 40 | 99.54 11 | 92.21 31 | 98.74 18 | 98.56 10 |
|
APDe-MVS | | | 95.46 2 | 95.64 2 | 94.91 13 | 98.26 22 | 86.29 40 | 97.46 2 | 97.40 10 | 89.03 48 | 96.20 6 | 98.10 1 | 89.39 6 | 99.34 24 | 95.88 1 | 99.03 3 | 99.10 1 |
|
ACMMPR | | | 94.43 16 | 94.28 16 | 94.91 13 | 98.63 2 | 86.69 23 | 96.94 10 | 97.32 17 | 88.63 57 | 93.53 32 | 97.26 16 | 85.04 43 | 99.54 11 | 92.35 29 | 98.78 13 | 98.50 11 |
|
GST-MVS | | | 94.21 25 | 93.97 28 | 94.90 15 | 98.41 16 | 86.82 17 | 96.54 23 | 97.19 24 | 88.24 68 | 93.26 33 | 96.83 33 | 85.48 37 | 99.59 2 | 91.43 54 | 98.40 39 | 98.30 26 |
|
HFP-MVS | | | 94.52 12 | 94.40 13 | 94.86 16 | 98.61 3 | 86.81 18 | 96.94 10 | 97.34 12 | 88.63 57 | 93.65 25 | 97.21 19 | 86.10 29 | 99.49 17 | 92.35 29 | 98.77 14 | 98.30 26 |
|
#test# | | | 94.32 21 | 94.14 22 | 94.86 16 | 98.61 3 | 86.81 18 | 96.43 24 | 97.34 12 | 87.51 86 | 93.65 25 | 97.21 19 | 86.10 29 | 99.49 17 | 91.68 48 | 98.77 14 | 98.30 26 |
|
MP-MVS-pluss | | | 94.21 25 | 94.00 27 | 94.85 18 | 98.17 26 | 86.65 26 | 94.82 104 | 97.17 27 | 86.26 114 | 92.83 42 | 97.87 4 | 85.57 36 | 99.56 3 | 94.37 8 | 98.92 6 | 98.34 23 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
canonicalmvs | | | 93.27 46 | 92.75 51 | 94.85 18 | 95.70 105 | 87.66 6 | 96.33 26 | 96.41 78 | 90.00 28 | 94.09 19 | 94.60 112 | 82.33 64 | 98.62 86 | 92.40 28 | 92.86 139 | 98.27 32 |
|
XVS | | | 94.45 14 | 94.32 14 | 94.85 18 | 98.54 7 | 86.60 28 | 96.93 12 | 97.19 24 | 90.66 22 | 92.85 40 | 97.16 24 | 85.02 44 | 99.49 17 | 91.99 39 | 98.56 35 | 98.47 14 |
|
X-MVStestdata | | | 88.31 145 | 86.13 193 | 94.85 18 | 98.54 7 | 86.60 28 | 96.93 12 | 97.19 24 | 90.66 22 | 92.85 40 | 23.41 365 | 85.02 44 | 99.49 17 | 91.99 39 | 98.56 35 | 98.47 14 |
|
SteuartSystems-ACMMP | | | 95.20 5 | 95.32 6 | 94.85 18 | 96.99 58 | 86.33 36 | 97.33 3 | 97.30 18 | 91.38 12 | 95.39 10 | 97.46 10 | 88.98 9 | 99.40 22 | 94.12 9 | 98.89 7 | 98.82 3 |
Skip Steuart: Steuart Systems R&D Blog. |
alignmvs | | | 93.08 52 | 92.50 55 | 94.81 23 | 95.62 108 | 87.61 7 | 95.99 39 | 96.07 101 | 89.77 32 | 94.12 18 | 94.87 100 | 80.56 84 | 98.66 82 | 92.42 27 | 93.10 134 | 98.15 41 |
|
DeepC-MVS_fast | | 89.43 2 | 94.04 28 | 93.79 31 | 94.80 24 | 97.48 44 | 86.78 20 | 95.65 56 | 96.89 45 | 89.40 38 | 92.81 43 | 96.97 28 | 85.37 39 | 99.24 32 | 90.87 61 | 98.69 21 | 98.38 22 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
MP-MVS | | | 94.25 22 | 94.07 25 | 94.77 25 | 98.47 11 | 86.31 38 | 96.71 20 | 96.98 36 | 89.04 47 | 91.98 64 | 97.19 21 | 85.43 38 | 99.56 3 | 92.06 38 | 98.79 11 | 98.44 19 |
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
HSP-MVS | | | 95.30 4 | 95.48 3 | 94.76 26 | 98.49 10 | 86.52 30 | 96.91 15 | 96.73 57 | 91.73 9 | 96.10 7 | 96.69 40 | 89.90 2 | 99.30 30 | 94.70 3 | 98.04 50 | 98.45 18 |
|
APD-MVS | | | 94.24 23 | 94.07 25 | 94.75 27 | 98.06 31 | 86.90 16 | 95.88 44 | 96.94 42 | 85.68 125 | 95.05 13 | 97.18 22 | 87.31 19 | 99.07 45 | 91.90 46 | 98.61 33 | 98.28 29 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
CP-MVS | | | 94.34 19 | 94.21 20 | 94.74 28 | 98.39 17 | 86.64 27 | 97.60 1 | 97.24 21 | 88.53 61 | 92.73 47 | 97.23 17 | 85.20 41 | 99.32 28 | 92.15 35 | 98.83 10 | 98.25 35 |
|
Regformer-2 | | | 94.33 20 | 94.22 18 | 94.68 29 | 95.54 109 | 86.75 22 | 94.57 125 | 96.70 61 | 91.84 6 | 94.41 14 | 96.56 49 | 87.19 20 | 99.13 41 | 93.50 13 | 97.65 58 | 98.16 40 |
|
PGM-MVS | | | 93.96 31 | 93.72 34 | 94.68 29 | 98.43 13 | 86.22 41 | 95.30 66 | 97.78 1 | 87.45 87 | 93.26 33 | 97.33 12 | 84.62 48 | 99.51 15 | 90.75 63 | 98.57 34 | 98.32 25 |
|
mPP-MVS | | | 93.99 30 | 93.78 32 | 94.63 31 | 98.50 9 | 85.90 49 | 96.87 16 | 96.91 44 | 88.70 55 | 91.83 68 | 97.17 23 | 83.96 53 | 99.55 8 | 91.44 53 | 98.64 31 | 98.43 20 |
|
PHI-MVS | | | 93.89 33 | 93.65 35 | 94.62 32 | 96.84 61 | 86.43 33 | 96.69 21 | 97.49 5 | 85.15 138 | 93.56 31 | 96.28 57 | 85.60 35 | 99.31 29 | 92.45 25 | 98.79 11 | 98.12 44 |
|
TSAR-MVS + MP. | | | 94.85 9 | 94.94 8 | 94.58 33 | 98.25 23 | 86.33 36 | 96.11 35 | 96.62 68 | 88.14 71 | 96.10 7 | 96.96 29 | 89.09 8 | 98.94 66 | 94.48 6 | 98.68 24 | 98.48 13 |
|
CANet | | | 93.54 39 | 93.20 42 | 94.55 34 | 95.65 106 | 85.73 52 | 94.94 95 | 96.69 63 | 91.89 5 | 90.69 84 | 95.88 74 | 81.99 74 | 99.54 11 | 93.14 20 | 97.95 52 | 98.39 21 |
|
train_agg | | | 93.44 41 | 93.08 43 | 94.52 35 | 97.53 39 | 86.49 31 | 94.07 170 | 96.78 53 | 81.86 231 | 92.77 44 | 96.20 61 | 87.63 16 | 99.12 42 | 92.14 36 | 98.69 21 | 97.94 56 |
|
Regformer-1 | | | 94.22 24 | 94.13 23 | 94.51 36 | 95.54 109 | 86.36 35 | 94.57 125 | 96.44 75 | 91.69 10 | 94.32 16 | 96.56 49 | 87.05 22 | 99.03 51 | 93.35 18 | 97.65 58 | 98.15 41 |
|
CDPH-MVS | | | 92.83 54 | 92.30 56 | 94.44 37 | 97.79 36 | 86.11 44 | 94.06 173 | 96.66 65 | 80.09 251 | 92.77 44 | 96.63 44 | 86.62 25 | 99.04 50 | 87.40 95 | 98.66 28 | 98.17 39 |
|
3Dnovator | | 86.66 5 | 91.73 66 | 90.82 76 | 94.44 37 | 94.59 153 | 86.37 34 | 97.18 6 | 97.02 34 | 89.20 42 | 84.31 221 | 96.66 43 | 73.74 175 | 99.17 36 | 86.74 105 | 97.96 51 | 97.79 66 |
|
HPM-MVS | | | 94.02 29 | 93.88 29 | 94.43 39 | 98.39 17 | 85.78 51 | 97.25 5 | 97.07 33 | 86.90 104 | 92.62 51 | 96.80 37 | 84.85 47 | 99.17 36 | 92.43 26 | 98.65 30 | 98.33 24 |
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
TSAR-MVS + GP. | | | 93.66 37 | 93.41 38 | 94.41 40 | 96.59 67 | 86.78 20 | 94.40 136 | 93.93 227 | 89.77 32 | 94.21 17 | 95.59 83 | 87.35 18 | 98.61 87 | 92.72 23 | 96.15 81 | 97.83 64 |
|
agg_prior3 | | | 93.27 46 | 92.89 49 | 94.40 41 | 97.49 42 | 86.12 43 | 94.07 170 | 96.73 57 | 81.46 239 | 92.46 56 | 96.05 69 | 86.90 23 | 99.15 39 | 92.14 36 | 98.69 21 | 97.94 56 |
|
test12 | | | | | 94.34 42 | 97.13 56 | 86.15 42 | | 96.29 85 | | 91.04 81 | | 85.08 42 | 99.01 56 | | 98.13 47 | 97.86 62 |
|
ACMMP | | | 93.24 49 | 92.88 50 | 94.30 43 | 98.09 30 | 85.33 55 | 96.86 17 | 97.45 7 | 88.33 64 | 90.15 91 | 97.03 27 | 81.44 78 | 99.51 15 | 90.85 62 | 95.74 85 | 98.04 50 |
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 |
agg_prior1 | | | 93.29 45 | 92.97 47 | 94.26 44 | 97.38 46 | 85.92 46 | 93.92 181 | 96.72 59 | 81.96 218 | 92.16 60 | 96.23 59 | 87.85 12 | 98.97 62 | 91.95 42 | 98.55 37 | 97.90 61 |
|
DeepC-MVS | | 88.79 3 | 93.31 44 | 92.99 46 | 94.26 44 | 96.07 91 | 85.83 50 | 94.89 98 | 96.99 35 | 89.02 49 | 89.56 95 | 97.37 11 | 82.51 62 | 99.38 23 | 92.20 32 | 98.30 42 | 97.57 73 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
Regformer-4 | | | 93.91 32 | 93.81 30 | 94.19 46 | 95.36 115 | 85.47 53 | 94.68 116 | 96.41 78 | 91.60 11 | 93.75 24 | 96.71 38 | 85.95 32 | 99.10 44 | 93.21 19 | 96.65 73 | 98.01 53 |
|
EPNet | | | 91.79 63 | 91.02 72 | 94.10 47 | 90.10 303 | 85.25 56 | 96.03 38 | 92.05 261 | 92.83 1 | 87.39 136 | 95.78 77 | 79.39 100 | 99.01 56 | 88.13 86 | 97.48 60 | 98.05 49 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
DELS-MVS | | | 93.43 42 | 93.25 40 | 93.97 48 | 95.42 114 | 85.04 57 | 93.06 225 | 97.13 28 | 90.74 20 | 91.84 66 | 95.09 96 | 86.32 28 | 99.21 33 | 91.22 55 | 98.45 38 | 97.65 69 |
Christian Sormann, Emanuele Santellani, Mattia Rossi, Andreas Kuhn, Friedrich Fraundorfer: DELS-MVS: Deep Epipolar Line Search for Multi-View Stereo. Winter Conference on Applications of Computer Vision (WACV), 2023 |
DP-MVS Recon | | | 91.95 62 | 91.28 65 | 93.96 49 | 98.33 21 | 85.92 46 | 94.66 119 | 96.66 65 | 82.69 207 | 90.03 93 | 95.82 76 | 82.30 65 | 99.03 51 | 84.57 127 | 96.48 78 | 96.91 101 |
|
HPM-MVS_fast | | | 93.40 43 | 93.22 41 | 93.94 50 | 98.36 19 | 84.83 59 | 97.15 7 | 96.80 52 | 85.77 122 | 92.47 55 | 97.13 25 | 82.38 63 | 99.07 45 | 90.51 65 | 98.40 39 | 97.92 60 |
|
SD-MVS | | | 94.96 8 | 95.33 5 | 93.88 51 | 97.25 55 | 86.69 23 | 96.19 31 | 97.11 31 | 90.42 24 | 96.95 3 | 97.27 14 | 89.53 4 | 96.91 228 | 94.38 7 | 98.85 8 | 98.03 51 |
|
MVS_111021_HR | | | 93.45 40 | 93.31 39 | 93.84 52 | 96.99 58 | 84.84 58 | 93.24 218 | 97.24 21 | 88.76 54 | 91.60 72 | 95.85 75 | 86.07 31 | 98.66 82 | 91.91 43 | 98.16 46 | 98.03 51 |
|
test_prior3 | | | 93.60 38 | 93.53 37 | 93.82 53 | 97.29 51 | 84.49 66 | 94.12 160 | 96.88 46 | 87.67 83 | 92.63 49 | 96.39 54 | 86.62 25 | 98.87 68 | 91.50 50 | 98.67 26 | 98.11 45 |
|
test_prior | | | | | 93.82 53 | 97.29 51 | 84.49 66 | | 96.88 46 | | | | | 98.87 68 | | | 98.11 45 |
|
Regformer-3 | | | 93.68 36 | 93.64 36 | 93.81 55 | 95.36 115 | 84.61 62 | 94.68 116 | 95.83 120 | 91.27 13 | 93.60 28 | 96.71 38 | 85.75 34 | 98.86 71 | 92.87 21 | 96.65 73 | 97.96 55 |
|
APD-MVS_3200maxsize | | | 93.78 34 | 93.77 33 | 93.80 56 | 97.92 34 | 84.19 77 | 96.30 27 | 96.87 48 | 86.96 100 | 93.92 23 | 97.47 9 | 83.88 54 | 98.96 65 | 92.71 24 | 97.87 53 | 98.26 34 |
|
CSCG | | | 93.23 50 | 93.05 44 | 93.76 57 | 98.04 32 | 84.07 79 | 96.22 30 | 97.37 11 | 84.15 159 | 90.05 92 | 95.66 81 | 87.77 13 | 99.15 39 | 89.91 68 | 98.27 43 | 98.07 47 |
|
UA-Net | | | 92.83 54 | 92.54 54 | 93.68 58 | 96.10 89 | 84.71 61 | 95.66 54 | 96.39 81 | 91.92 4 | 93.22 35 | 96.49 51 | 83.16 57 | 98.87 68 | 84.47 128 | 95.47 90 | 97.45 77 |
|
QAPM | | | 89.51 112 | 88.15 131 | 93.59 59 | 94.92 138 | 84.58 63 | 96.82 18 | 96.70 61 | 78.43 269 | 83.41 240 | 96.19 64 | 73.18 182 | 99.30 30 | 77.11 237 | 96.54 76 | 96.89 102 |
|
abl_6 | | | 93.18 51 | 93.05 44 | 93.57 60 | 97.52 41 | 84.27 76 | 95.53 60 | 96.67 64 | 87.85 77 | 93.20 36 | 97.22 18 | 80.35 86 | 99.18 35 | 91.91 43 | 97.21 63 | 97.26 82 |
|
EI-MVSNet-Vis-set | | | 93.01 53 | 92.92 48 | 93.29 61 | 95.01 132 | 83.51 93 | 94.48 128 | 95.77 124 | 90.87 16 | 92.52 53 | 96.67 42 | 84.50 49 | 99.00 59 | 91.99 39 | 94.44 110 | 97.36 78 |
|
Vis-MVSNet | | | 91.75 65 | 91.23 67 | 93.29 61 | 95.32 119 | 83.78 84 | 96.14 33 | 95.98 107 | 89.89 29 | 90.45 87 | 96.58 47 | 75.09 154 | 98.31 107 | 84.75 125 | 96.90 67 | 97.78 67 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
VNet | | | 92.24 60 | 91.91 59 | 93.24 63 | 96.59 67 | 83.43 94 | 94.84 103 | 96.44 75 | 89.19 43 | 94.08 20 | 95.90 73 | 77.85 116 | 98.17 115 | 88.90 76 | 93.38 128 | 98.13 43 |
|
1121 | | | 90.42 93 | 89.49 97 | 93.20 64 | 97.27 53 | 84.46 69 | 92.63 238 | 95.51 145 | 71.01 332 | 91.20 79 | 96.21 60 | 82.92 59 | 99.05 47 | 80.56 189 | 98.07 49 | 96.10 123 |
|
VDD-MVS | | | 90.74 82 | 89.92 93 | 93.20 64 | 96.27 77 | 83.02 106 | 95.73 49 | 93.86 228 | 88.42 63 | 92.53 52 | 96.84 32 | 62.09 297 | 98.64 84 | 90.95 60 | 92.62 142 | 97.93 59 |
|
nrg030 | | | 91.08 79 | 90.39 79 | 93.17 66 | 93.07 203 | 86.91 15 | 96.41 25 | 96.26 86 | 88.30 65 | 88.37 111 | 94.85 103 | 82.19 68 | 97.64 156 | 91.09 56 | 82.95 257 | 94.96 161 |
|
casdiffmvs1 | | | 92.43 58 | 92.18 58 | 93.17 66 | 95.33 118 | 83.03 104 | 95.08 85 | 96.41 78 | 83.18 186 | 93.20 36 | 94.49 115 | 83.84 55 | 98.29 108 | 92.16 34 | 95.96 82 | 98.20 37 |
|
EI-MVSNet-UG-set | | | 92.74 56 | 92.62 52 | 93.12 68 | 94.86 142 | 83.20 99 | 94.40 136 | 95.74 127 | 90.71 21 | 92.05 63 | 96.60 46 | 84.00 52 | 98.99 60 | 91.55 49 | 93.63 121 | 97.17 88 |
|
æ–°å‡ ä½•1 | | | | | 93.10 69 | 97.30 50 | 84.35 75 | | 95.56 138 | 71.09 331 | 91.26 78 | 96.24 58 | 82.87 60 | 98.86 71 | 79.19 217 | 98.10 48 | 96.07 125 |
|
casdiffmvs | | | 91.72 67 | 91.26 66 | 93.10 69 | 94.66 150 | 83.75 85 | 94.77 108 | 96.00 106 | 83.98 162 | 90.74 83 | 93.96 134 | 82.08 70 | 98.19 114 | 91.47 52 | 93.68 119 | 97.36 78 |
|
OMC-MVS | | | 91.23 75 | 90.62 78 | 93.08 71 | 96.27 77 | 84.07 79 | 93.52 204 | 95.93 110 | 86.95 101 | 89.51 96 | 96.13 67 | 78.50 108 | 98.35 103 | 85.84 114 | 92.90 138 | 96.83 103 |
|
OpenMVS | | 83.78 11 | 88.74 135 | 87.29 148 | 93.08 71 | 92.70 214 | 85.39 54 | 96.57 22 | 96.43 77 | 78.74 266 | 80.85 270 | 96.07 68 | 69.64 226 | 99.01 56 | 78.01 228 | 96.65 73 | 94.83 172 |
|
MAR-MVS | | | 90.30 94 | 89.37 101 | 93.07 73 | 96.61 66 | 84.48 68 | 95.68 52 | 95.67 130 | 82.36 211 | 87.85 122 | 92.85 174 | 76.63 124 | 98.80 78 | 80.01 199 | 96.68 72 | 95.91 130 |
Zhenyu Xu, Yiguang Liu, Xuelei Shi, Ying Wang, Yunan Zheng: MARMVS: Matching Ambiguity Reduced Multiple View Stereo for Efficient Large Scale Scene Reconstruction. CVPR 2020 |
lupinMVS | | | 90.92 80 | 90.21 83 | 93.03 74 | 93.86 180 | 83.88 82 | 92.81 234 | 93.86 228 | 79.84 253 | 91.76 69 | 94.29 121 | 77.92 113 | 98.04 136 | 90.48 66 | 97.11 64 | 97.17 88 |
|
Effi-MVS+ | | | 91.59 70 | 91.11 69 | 93.01 75 | 94.35 164 | 83.39 96 | 94.60 122 | 95.10 179 | 87.10 94 | 90.57 85 | 93.10 165 | 81.43 79 | 98.07 134 | 89.29 73 | 94.48 107 | 97.59 72 |
|
MVS_111021_LR | | | 92.47 57 | 92.29 57 | 92.98 76 | 95.99 94 | 84.43 73 | 93.08 223 | 96.09 99 | 88.20 70 | 91.12 80 | 95.72 80 | 81.33 80 | 97.76 149 | 91.74 47 | 97.37 62 | 96.75 105 |
|
LFMVS | | | 90.08 98 | 89.13 107 | 92.95 77 | 96.71 63 | 82.32 127 | 96.08 36 | 89.91 317 | 86.79 105 | 92.15 62 | 96.81 35 | 62.60 294 | 98.34 104 | 87.18 99 | 93.90 116 | 98.19 38 |
|
UGNet | | | 89.95 102 | 88.95 111 | 92.95 77 | 94.51 156 | 83.31 97 | 95.70 51 | 95.23 172 | 89.37 39 | 87.58 132 | 93.94 135 | 64.00 289 | 98.78 79 | 83.92 138 | 96.31 80 | 96.74 106 |
Wanjuan Su, Qingshan Xu, Wenbing Tao: Uncertainty-guided Multi-view Stereo Network for Depth Estimation. IEEE Transactions on Circuits and Systems for Video Technology, 2022 |
jason | | | 90.80 81 | 90.10 86 | 92.90 79 | 93.04 205 | 83.53 92 | 93.08 223 | 94.15 214 | 80.22 248 | 91.41 76 | 94.91 98 | 76.87 119 | 97.93 143 | 90.28 67 | 96.90 67 | 97.24 83 |
jason: jason. |
DP-MVS | | | 87.25 194 | 85.36 214 | 92.90 79 | 97.65 37 | 83.24 98 | 94.81 105 | 92.00 263 | 74.99 299 | 81.92 259 | 95.00 97 | 72.66 188 | 99.05 47 | 66.92 309 | 92.33 146 | 96.40 111 |
|
CANet_DTU | | | 90.26 96 | 89.41 100 | 92.81 81 | 93.46 193 | 83.01 107 | 93.48 205 | 94.47 204 | 89.43 37 | 87.76 130 | 94.23 125 | 70.54 217 | 99.03 51 | 84.97 120 | 96.39 79 | 96.38 112 |
|
MVSFormer | | | 91.68 69 | 91.30 64 | 92.80 82 | 93.86 180 | 83.88 82 | 95.96 41 | 95.90 114 | 84.66 148 | 91.76 69 | 94.91 98 | 77.92 113 | 97.30 195 | 89.64 71 | 97.11 64 | 97.24 83 |
|
PVSNet_Blended_VisFu | | | 91.38 72 | 90.91 74 | 92.80 82 | 96.39 74 | 83.17 100 | 94.87 101 | 96.66 65 | 83.29 183 | 89.27 99 | 94.46 116 | 80.29 88 | 99.17 36 | 87.57 93 | 95.37 92 | 96.05 127 |
|
VDDNet | | | 89.56 111 | 88.49 122 | 92.76 84 | 95.07 131 | 82.09 129 | 96.30 27 | 93.19 238 | 81.05 244 | 91.88 65 | 96.86 31 | 61.16 307 | 98.33 105 | 88.43 82 | 92.49 145 | 97.84 63 |
|
0601test | | | 90.69 84 | 90.02 91 | 92.71 85 | 95.72 102 | 82.41 125 | 94.11 162 | 95.12 177 | 85.63 126 | 91.49 73 | 94.70 106 | 74.75 157 | 98.42 99 | 86.13 112 | 92.53 143 | 97.31 80 |
|
Anonymous20240521 | | | 90.69 84 | 90.02 91 | 92.71 85 | 95.72 102 | 82.41 125 | 94.11 162 | 95.12 177 | 85.63 126 | 91.49 73 | 94.70 106 | 74.75 157 | 98.42 99 | 86.13 112 | 92.53 143 | 97.31 80 |
|
PCF-MVS | | 84.11 10 | 87.74 167 | 86.08 197 | 92.70 87 | 94.02 171 | 84.43 73 | 89.27 295 | 95.87 117 | 73.62 311 | 84.43 215 | 94.33 118 | 78.48 109 | 98.86 71 | 70.27 279 | 94.45 109 | 94.81 173 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
MSLP-MVS++ | | | 93.72 35 | 94.08 24 | 92.65 88 | 97.31 49 | 83.43 94 | 95.79 47 | 97.33 15 | 90.03 27 | 93.58 29 | 96.96 29 | 84.87 46 | 97.76 149 | 92.19 33 | 98.66 28 | 96.76 104 |
|
ab-mvs | | | 89.41 118 | 88.35 124 | 92.60 89 | 95.15 130 | 82.65 120 | 92.20 252 | 95.60 136 | 83.97 163 | 88.55 107 | 93.70 149 | 74.16 168 | 98.21 113 | 82.46 159 | 89.37 185 | 96.94 100 |
|
LS3D | | | 87.89 159 | 86.32 189 | 92.59 90 | 96.07 91 | 82.92 110 | 95.23 76 | 94.92 190 | 75.66 292 | 82.89 245 | 95.98 70 | 72.48 192 | 99.21 33 | 68.43 300 | 95.23 97 | 95.64 142 |
|
Anonymous20240529 | | | 88.09 152 | 86.59 183 | 92.58 91 | 96.53 70 | 81.92 133 | 95.99 39 | 95.84 119 | 74.11 307 | 89.06 103 | 95.21 92 | 61.44 302 | 98.81 77 | 83.67 141 | 87.47 217 | 97.01 97 |
|
CPTT-MVS | | | 91.99 61 | 91.80 60 | 92.55 92 | 98.24 25 | 81.98 132 | 96.76 19 | 96.49 74 | 81.89 223 | 90.24 89 | 96.44 53 | 78.59 106 | 98.61 87 | 89.68 70 | 97.85 54 | 97.06 94 |
|
114514_t | | | 89.51 112 | 88.50 120 | 92.54 93 | 98.11 28 | 81.99 131 | 95.16 81 | 96.36 83 | 70.19 334 | 85.81 161 | 95.25 90 | 76.70 122 | 98.63 85 | 82.07 165 | 96.86 69 | 97.00 98 |
|
PAPM_NR | | | 91.22 76 | 90.78 77 | 92.52 94 | 97.60 38 | 81.46 142 | 94.37 142 | 96.24 89 | 86.39 112 | 87.41 134 | 94.80 105 | 82.06 72 | 98.48 93 | 82.80 153 | 95.37 92 | 97.61 71 |
|
DeepPCF-MVS | | 89.96 1 | 94.20 27 | 94.77 10 | 92.49 95 | 96.52 71 | 80.00 182 | 94.00 178 | 97.08 32 | 90.05 26 | 95.65 9 | 97.29 13 | 89.66 3 | 98.97 62 | 93.95 10 | 98.71 19 | 98.50 11 |
|
IS-MVSNet | | | 91.43 71 | 91.09 71 | 92.46 96 | 95.87 99 | 81.38 145 | 96.95 9 | 93.69 232 | 89.72 34 | 89.50 97 | 95.98 70 | 78.57 107 | 97.77 148 | 83.02 148 | 96.50 77 | 98.22 36 |
|
API-MVS | | | 90.66 86 | 90.07 87 | 92.45 97 | 96.36 75 | 84.57 64 | 96.06 37 | 95.22 174 | 82.39 209 | 89.13 100 | 94.27 124 | 80.32 87 | 98.46 95 | 80.16 198 | 96.71 71 | 94.33 199 |
|
xiu_mvs_v1_base_debu | | | 90.64 87 | 90.05 88 | 92.40 98 | 93.97 177 | 84.46 69 | 93.32 209 | 95.46 149 | 85.17 135 | 92.25 57 | 94.03 127 | 70.59 213 | 98.57 89 | 90.97 57 | 94.67 100 | 94.18 202 |
|
xiu_mvs_v1_base | | | 90.64 87 | 90.05 88 | 92.40 98 | 93.97 177 | 84.46 69 | 93.32 209 | 95.46 149 | 85.17 135 | 92.25 57 | 94.03 127 | 70.59 213 | 98.57 89 | 90.97 57 | 94.67 100 | 94.18 202 |
|
xiu_mvs_v1_base_debi | | | 90.64 87 | 90.05 88 | 92.40 98 | 93.97 177 | 84.46 69 | 93.32 209 | 95.46 149 | 85.17 135 | 92.25 57 | 94.03 127 | 70.59 213 | 98.57 89 | 90.97 57 | 94.67 100 | 94.18 202 |
|
AdaColmap | | | 89.89 105 | 89.07 108 | 92.37 101 | 97.41 45 | 83.03 104 | 94.42 135 | 95.92 111 | 82.81 203 | 86.34 154 | 94.65 110 | 73.89 171 | 99.02 54 | 80.69 186 | 95.51 88 | 95.05 155 |
|
CNLPA | | | 89.07 126 | 87.98 134 | 92.34 102 | 96.87 60 | 84.78 60 | 94.08 168 | 93.24 237 | 81.41 240 | 84.46 213 | 95.13 95 | 75.57 147 | 96.62 244 | 77.21 235 | 93.84 118 | 95.61 143 |
|
Anonymous202405211 | | | 87.68 168 | 86.13 193 | 92.31 103 | 96.66 64 | 80.74 164 | 94.87 101 | 91.49 281 | 80.47 247 | 89.46 98 | 95.44 84 | 54.72 330 | 98.23 110 | 82.19 163 | 89.89 177 | 97.97 54 |
|
CHOSEN 1792x2688 | | | 88.84 132 | 87.69 139 | 92.30 104 | 96.14 83 | 81.42 144 | 90.01 284 | 95.86 118 | 74.52 304 | 87.41 134 | 93.94 135 | 75.46 149 | 98.36 101 | 80.36 193 | 95.53 87 | 97.12 91 |
|
HY-MVS | | 83.01 12 | 89.03 128 | 87.94 136 | 92.29 105 | 94.86 142 | 82.77 112 | 92.08 257 | 94.49 203 | 81.52 238 | 86.93 141 | 92.79 180 | 78.32 111 | 98.23 110 | 79.93 202 | 90.55 166 | 95.88 132 |
|
CDS-MVSNet | | | 89.45 115 | 88.51 119 | 92.29 105 | 93.62 188 | 83.61 91 | 93.01 227 | 94.68 199 | 81.95 219 | 87.82 128 | 93.24 159 | 78.69 104 | 96.99 221 | 80.34 194 | 93.23 132 | 96.28 115 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
PAPR | | | 90.02 99 | 89.27 105 | 92.29 105 | 95.78 100 | 80.95 158 | 92.68 237 | 96.22 90 | 81.91 221 | 86.66 147 | 93.75 148 | 82.23 66 | 98.44 98 | 79.40 216 | 94.79 99 | 97.48 76 |
|
test_normal | | | 88.13 151 | 86.78 169 | 92.18 108 | 90.55 295 | 81.19 151 | 92.74 236 | 94.64 200 | 83.84 165 | 77.49 299 | 90.51 263 | 68.49 250 | 98.16 116 | 88.22 83 | 94.55 105 | 97.21 86 |
|
PLC | | 84.53 7 | 89.06 127 | 88.03 133 | 92.15 109 | 97.27 53 | 82.69 119 | 94.29 147 | 95.44 155 | 79.71 255 | 84.01 226 | 94.18 126 | 76.68 123 | 98.75 80 | 77.28 234 | 93.41 127 | 95.02 156 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
DI_MVS_plusplus_test | | | 88.15 150 | 86.82 165 | 92.14 110 | 90.67 290 | 81.07 153 | 93.01 227 | 94.59 201 | 83.83 167 | 77.78 295 | 90.63 257 | 68.51 249 | 98.16 116 | 88.02 88 | 94.37 111 | 97.17 88 |
|
EPP-MVSNet | | | 91.70 68 | 91.56 62 | 92.13 111 | 95.88 97 | 80.50 171 | 97.33 3 | 95.25 168 | 86.15 116 | 89.76 94 | 95.60 82 | 83.42 56 | 98.32 106 | 87.37 97 | 93.25 131 | 97.56 74 |
|
原ACMM1 | | | | | 92.01 112 | 97.34 48 | 81.05 154 | | 96.81 51 | 78.89 261 | 90.45 87 | 95.92 72 | 82.65 61 | 98.84 76 | 80.68 187 | 98.26 44 | 96.14 119 |
|
UniMVSNet (Re) | | | 89.80 106 | 89.07 108 | 92.01 112 | 93.60 189 | 84.52 65 | 94.78 107 | 97.47 6 | 89.26 41 | 86.44 152 | 92.32 190 | 82.10 69 | 97.39 191 | 84.81 124 | 80.84 290 | 94.12 206 |
|
MG-MVS | | | 91.77 64 | 91.70 61 | 92.00 114 | 97.08 57 | 80.03 181 | 93.60 202 | 95.18 175 | 87.85 77 | 90.89 82 | 96.47 52 | 82.06 72 | 98.36 101 | 85.07 119 | 97.04 66 | 97.62 70 |
|
PVSNet_Blended | | | 90.73 83 | 90.32 82 | 91.98 115 | 96.12 84 | 81.25 147 | 92.55 242 | 96.83 49 | 82.04 217 | 89.10 101 | 92.56 184 | 81.04 82 | 98.85 74 | 86.72 108 | 95.91 83 | 95.84 134 |
|
PS-MVSNAJ | | | 91.18 77 | 90.92 73 | 91.96 116 | 95.26 122 | 82.60 122 | 92.09 256 | 95.70 129 | 86.27 113 | 91.84 66 | 92.46 185 | 79.70 95 | 98.99 60 | 89.08 74 | 95.86 84 | 94.29 200 |
|
TAMVS | | | 89.21 123 | 88.29 128 | 91.96 116 | 93.71 186 | 82.62 121 | 93.30 213 | 94.19 212 | 82.22 212 | 87.78 129 | 93.94 135 | 78.83 102 | 96.95 225 | 77.70 230 | 92.98 137 | 96.32 113 |
|
MVS_Test | | | 91.31 74 | 91.11 69 | 91.93 118 | 94.37 161 | 80.14 175 | 93.46 207 | 95.80 122 | 86.46 110 | 91.35 77 | 93.77 146 | 82.21 67 | 98.09 132 | 87.57 93 | 94.95 98 | 97.55 75 |
|
NR-MVSNet | | | 88.58 140 | 87.47 144 | 91.93 118 | 93.04 205 | 84.16 78 | 94.77 108 | 96.25 88 | 89.05 46 | 80.04 282 | 93.29 157 | 79.02 101 | 97.05 218 | 81.71 173 | 80.05 300 | 94.59 185 |
|
HyFIR lowres test | | | 88.09 152 | 86.81 166 | 91.93 118 | 96.00 93 | 80.63 166 | 90.01 284 | 95.79 123 | 73.42 312 | 87.68 131 | 92.10 202 | 73.86 172 | 97.96 140 | 80.75 185 | 91.70 149 | 97.19 87 |
|
thisisatest0530 | | | 88.67 136 | 87.61 141 | 91.86 121 | 94.87 141 | 80.07 178 | 94.63 120 | 89.90 318 | 84.00 161 | 88.46 109 | 93.78 145 | 66.88 269 | 98.46 95 | 83.30 144 | 92.65 141 | 97.06 94 |
|
xiu_mvs_v2_base | | | 91.13 78 | 90.89 75 | 91.86 121 | 94.97 135 | 82.42 123 | 92.24 250 | 95.64 135 | 86.11 118 | 91.74 71 | 93.14 163 | 79.67 98 | 98.89 67 | 89.06 75 | 95.46 91 | 94.28 201 |
|
DU-MVS | | | 89.34 122 | 88.50 120 | 91.85 123 | 93.04 205 | 83.72 86 | 94.47 131 | 96.59 70 | 89.50 36 | 86.46 149 | 93.29 157 | 77.25 117 | 97.23 205 | 84.92 121 | 81.02 286 | 94.59 185 |
|
Test4 | | | 85.75 231 | 83.72 249 | 91.83 124 | 88.08 328 | 81.03 155 | 92.48 243 | 95.54 141 | 83.38 181 | 73.40 328 | 88.57 290 | 50.99 338 | 97.37 192 | 86.61 110 | 94.47 108 | 97.09 92 |
|
OPM-MVS | | | 90.12 97 | 89.56 96 | 91.82 125 | 93.14 201 | 83.90 81 | 94.16 159 | 95.74 127 | 88.96 50 | 87.86 121 | 95.43 86 | 72.48 192 | 97.91 144 | 88.10 87 | 90.18 173 | 93.65 240 |
|
HQP_MVS | | | 90.60 90 | 90.19 84 | 91.82 125 | 94.70 148 | 82.73 116 | 95.85 45 | 96.22 90 | 90.81 18 | 86.91 142 | 94.86 101 | 74.23 164 | 98.12 119 | 88.15 84 | 89.99 174 | 94.63 181 |
|
UniMVSNet_NR-MVSNet | | | 89.92 104 | 89.29 103 | 91.81 127 | 93.39 195 | 83.72 86 | 94.43 134 | 97.12 29 | 89.80 31 | 86.46 149 | 93.32 154 | 83.16 57 | 97.23 205 | 84.92 121 | 81.02 286 | 94.49 194 |
|
1112_ss | | | 88.42 141 | 87.33 147 | 91.72 128 | 94.92 138 | 80.98 156 | 92.97 230 | 94.54 202 | 78.16 274 | 83.82 229 | 93.88 140 | 78.78 103 | 97.91 144 | 79.45 212 | 89.41 184 | 96.26 116 |
|
Fast-Effi-MVS+ | | | 89.41 118 | 88.64 117 | 91.71 129 | 94.74 144 | 80.81 162 | 93.54 203 | 95.10 179 | 83.11 187 | 86.82 145 | 90.67 256 | 79.74 94 | 97.75 152 | 80.51 191 | 93.55 122 | 96.57 109 |
|
diffmvs1 | | | 91.33 73 | 91.22 68 | 91.68 130 | 93.43 194 | 79.77 187 | 93.02 226 | 95.50 146 | 87.72 80 | 90.47 86 | 93.87 142 | 81.76 77 | 97.52 162 | 89.84 69 | 95.36 94 | 97.74 68 |
|
WTY-MVS | | | 89.60 109 | 88.92 112 | 91.67 131 | 95.47 113 | 81.15 152 | 92.38 247 | 94.78 197 | 83.11 187 | 89.06 103 | 94.32 119 | 78.67 105 | 96.61 246 | 81.57 174 | 90.89 165 | 97.24 83 |
|
TAPA-MVS | | 84.62 6 | 88.16 149 | 87.01 160 | 91.62 132 | 96.64 65 | 80.65 165 | 94.39 138 | 96.21 93 | 76.38 285 | 86.19 157 | 95.44 84 | 79.75 93 | 98.08 133 | 62.75 330 | 95.29 95 | 96.13 120 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
VPA-MVSNet | | | 89.62 108 | 88.96 110 | 91.60 133 | 93.86 180 | 82.89 111 | 95.46 61 | 97.33 15 | 87.91 74 | 88.43 110 | 93.31 155 | 74.17 167 | 97.40 187 | 87.32 98 | 82.86 259 | 94.52 190 |
|
XVG-OURS | | | 89.40 120 | 88.70 116 | 91.52 134 | 94.06 169 | 81.46 142 | 91.27 271 | 96.07 101 | 86.14 117 | 88.89 105 | 95.77 78 | 68.73 246 | 97.26 201 | 87.39 96 | 89.96 176 | 95.83 135 |
|
TranMVSNet+NR-MVSNet | | | 88.84 132 | 87.95 135 | 91.49 135 | 92.68 215 | 83.01 107 | 94.92 97 | 96.31 84 | 89.88 30 | 85.53 176 | 93.85 143 | 76.63 124 | 96.96 224 | 81.91 169 | 79.87 305 | 94.50 192 |
|
XVG-OURS-SEG-HR | | | 89.95 102 | 89.45 98 | 91.47 136 | 94.00 175 | 81.21 150 | 91.87 258 | 96.06 103 | 85.78 121 | 88.55 107 | 95.73 79 | 74.67 160 | 97.27 199 | 88.71 78 | 89.64 182 | 95.91 130 |
|
MVS | | | 87.44 187 | 86.10 196 | 91.44 137 | 92.61 216 | 83.62 90 | 92.63 238 | 95.66 132 | 67.26 342 | 81.47 262 | 92.15 197 | 77.95 112 | 98.22 112 | 79.71 208 | 95.48 89 | 92.47 281 |
|
F-COLMAP | | | 87.95 158 | 86.80 167 | 91.40 138 | 96.35 76 | 80.88 160 | 94.73 110 | 95.45 153 | 79.65 256 | 82.04 257 | 94.61 111 | 71.13 204 | 98.50 92 | 76.24 244 | 91.05 159 | 94.80 174 |
|
thisisatest0515 | | | 87.33 190 | 85.99 199 | 91.37 139 | 93.49 191 | 79.55 190 | 90.63 276 | 89.56 326 | 80.17 249 | 87.56 133 | 90.86 252 | 67.07 266 | 98.28 109 | 81.50 175 | 93.02 136 | 96.29 114 |
|
HQP-MVS | | | 89.80 106 | 89.28 104 | 91.34 140 | 94.17 166 | 81.56 136 | 94.39 138 | 96.04 104 | 88.81 51 | 85.43 185 | 93.97 133 | 73.83 173 | 97.96 140 | 87.11 102 | 89.77 180 | 94.50 192 |
|
FMVSNet3 | | | 87.40 189 | 86.11 195 | 91.30 141 | 93.79 185 | 83.64 89 | 94.20 158 | 94.81 196 | 83.89 164 | 84.37 216 | 91.87 212 | 68.45 252 | 96.56 247 | 78.23 225 | 85.36 234 | 93.70 235 |
|
FMVSNet2 | | | 87.19 198 | 85.82 204 | 91.30 141 | 94.01 172 | 83.67 88 | 94.79 106 | 94.94 186 | 83.57 173 | 83.88 227 | 92.05 206 | 66.59 272 | 96.51 250 | 77.56 232 | 85.01 238 | 93.73 233 |
|
IB-MVS | | 80.51 15 | 85.24 243 | 83.26 262 | 91.19 143 | 92.13 223 | 79.86 185 | 91.75 260 | 91.29 286 | 83.28 184 | 80.66 273 | 88.49 292 | 61.28 303 | 98.46 95 | 80.99 182 | 79.46 307 | 95.25 152 |
Christian Sormann, Mattia Rossi, Andreas Kuhn and Friedrich Fraundorfer: IB-MVS: An Iterative Algorithm for Deep Multi-View Stereo based on Binary Decisions. BMVC 2021 |
CLD-MVS | | | 89.47 114 | 88.90 113 | 91.18 144 | 94.22 165 | 82.07 130 | 92.13 254 | 96.09 99 | 87.90 75 | 85.37 192 | 92.45 186 | 74.38 162 | 97.56 159 | 87.15 100 | 90.43 167 | 93.93 216 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
LPG-MVS_test | | | 89.45 115 | 88.90 113 | 91.12 145 | 94.47 157 | 81.49 140 | 95.30 66 | 96.14 95 | 86.73 106 | 85.45 182 | 95.16 93 | 69.89 222 | 98.10 125 | 87.70 91 | 89.23 189 | 93.77 230 |
|
LGP-MVS_train | | | | | 91.12 145 | 94.47 157 | 81.49 140 | | 96.14 95 | 86.73 106 | 85.45 182 | 95.16 93 | 69.89 222 | 98.10 125 | 87.70 91 | 89.23 189 | 93.77 230 |
|
ACMM | | 84.12 9 | 89.14 124 | 88.48 123 | 91.12 145 | 94.65 152 | 81.22 149 | 95.31 64 | 96.12 98 | 85.31 134 | 85.92 160 | 94.34 117 | 70.19 221 | 98.06 135 | 85.65 115 | 88.86 200 | 94.08 210 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
tttt0517 | | | 88.61 138 | 87.78 138 | 91.11 148 | 94.96 136 | 77.81 257 | 95.35 62 | 89.69 322 | 85.09 140 | 88.05 119 | 94.59 113 | 66.93 267 | 98.48 93 | 83.27 145 | 92.13 148 | 97.03 96 |
|
GBi-Net | | | 87.26 192 | 85.98 200 | 91.08 149 | 94.01 172 | 83.10 101 | 95.14 82 | 94.94 186 | 83.57 173 | 84.37 216 | 91.64 216 | 66.59 272 | 96.34 260 | 78.23 225 | 85.36 234 | 93.79 226 |
|
test1 | | | 87.26 192 | 85.98 200 | 91.08 149 | 94.01 172 | 83.10 101 | 95.14 82 | 94.94 186 | 83.57 173 | 84.37 216 | 91.64 216 | 66.59 272 | 96.34 260 | 78.23 225 | 85.36 234 | 93.79 226 |
|
FMVSNet1 | | | 85.85 225 | 84.11 241 | 91.08 149 | 92.81 212 | 83.10 101 | 95.14 82 | 94.94 186 | 81.64 234 | 82.68 247 | 91.64 216 | 59.01 317 | 96.34 260 | 75.37 250 | 83.78 247 | 93.79 226 |
|
Test_1112_low_res | | | 87.65 170 | 86.51 185 | 91.08 149 | 94.94 137 | 79.28 213 | 91.77 259 | 94.30 210 | 76.04 290 | 83.51 238 | 92.37 188 | 77.86 115 | 97.73 153 | 78.69 221 | 89.13 197 | 96.22 117 |
|
PS-MVSNAJss | | | 89.97 101 | 89.62 95 | 91.02 153 | 91.90 226 | 80.85 161 | 95.26 75 | 95.98 107 | 86.26 114 | 86.21 156 | 94.29 121 | 79.70 95 | 97.65 154 | 88.87 77 | 88.10 211 | 94.57 187 |
|
diffmvs | | | 90.50 92 | 90.33 81 | 91.02 153 | 93.04 205 | 78.59 228 | 92.85 233 | 95.07 182 | 87.32 89 | 88.32 112 | 93.34 151 | 80.46 85 | 97.40 187 | 88.50 80 | 94.06 114 | 97.07 93 |
|
BH-RMVSNet | | | 88.37 143 | 87.48 143 | 91.02 153 | 95.28 120 | 79.45 199 | 92.89 232 | 93.07 240 | 85.45 131 | 86.91 142 | 94.84 104 | 70.35 218 | 97.76 149 | 73.97 262 | 94.59 104 | 95.85 133 |
|
FIs | | | 90.51 91 | 90.35 80 | 90.99 156 | 93.99 176 | 80.98 156 | 95.73 49 | 97.54 3 | 89.15 44 | 86.72 146 | 94.68 108 | 81.83 76 | 97.24 203 | 85.18 118 | 88.31 210 | 94.76 175 |
|
ACMP | | 84.23 8 | 89.01 130 | 88.35 124 | 90.99 156 | 94.73 145 | 81.27 146 | 95.07 86 | 95.89 116 | 86.48 109 | 83.67 233 | 94.30 120 | 69.33 229 | 97.99 139 | 87.10 104 | 88.55 202 | 93.72 234 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
Anonymous20231211 | | | 86.59 211 | 85.13 217 | 90.98 158 | 96.52 71 | 81.50 138 | 96.14 33 | 96.16 94 | 73.78 309 | 83.65 234 | 92.15 197 | 63.26 292 | 97.37 192 | 82.82 152 | 81.74 276 | 94.06 211 |
|
sss | | | 88.93 131 | 88.26 130 | 90.94 159 | 94.05 170 | 80.78 163 | 91.71 262 | 95.38 159 | 81.55 237 | 88.63 106 | 93.91 139 | 75.04 155 | 95.47 293 | 82.47 158 | 91.61 150 | 96.57 109 |
|
PVSNet_BlendedMVS | | | 89.98 100 | 89.70 94 | 90.82 160 | 96.12 84 | 81.25 147 | 93.92 181 | 96.83 49 | 83.49 177 | 89.10 101 | 92.26 195 | 81.04 82 | 98.85 74 | 86.72 108 | 87.86 215 | 92.35 286 |
|
cascas | | | 86.43 215 | 84.98 220 | 90.80 161 | 92.10 224 | 80.92 159 | 90.24 280 | 95.91 113 | 73.10 315 | 83.57 237 | 88.39 293 | 65.15 284 | 97.46 167 | 84.90 123 | 91.43 151 | 94.03 213 |
|
GA-MVS | | | 86.61 209 | 85.27 216 | 90.66 162 | 91.33 255 | 78.71 225 | 90.40 278 | 93.81 231 | 85.34 133 | 85.12 196 | 89.57 277 | 61.25 304 | 97.11 213 | 80.99 182 | 89.59 183 | 96.15 118 |
|
thres600view7 | | | 87.65 170 | 86.67 175 | 90.59 163 | 96.08 90 | 78.72 224 | 94.88 100 | 91.58 274 | 87.06 99 | 88.08 115 | 92.30 191 | 68.91 237 | 98.10 125 | 70.05 287 | 91.10 153 | 94.96 161 |
|
thres400 | | | 87.62 177 | 86.64 180 | 90.57 164 | 95.99 94 | 78.64 226 | 94.58 123 | 91.98 265 | 86.94 102 | 88.09 113 | 91.77 213 | 69.18 234 | 98.10 125 | 70.13 283 | 91.10 153 | 94.96 161 |
|
testing_2 | | | 83.40 274 | 81.02 279 | 90.56 165 | 85.06 339 | 80.51 170 | 91.37 269 | 95.57 137 | 82.92 200 | 67.06 343 | 85.54 326 | 49.47 341 | 97.24 203 | 86.74 105 | 85.44 233 | 93.93 216 |
|
view600 | | | 87.62 177 | 86.65 176 | 90.53 166 | 96.19 79 | 78.52 233 | 95.29 68 | 91.09 288 | 87.08 95 | 87.84 123 | 93.03 168 | 68.86 241 | 98.11 121 | 69.44 290 | 91.02 161 | 94.96 161 |
|
view800 | | | 87.62 177 | 86.65 176 | 90.53 166 | 96.19 79 | 78.52 233 | 95.29 68 | 91.09 288 | 87.08 95 | 87.84 123 | 93.03 168 | 68.86 241 | 98.11 121 | 69.44 290 | 91.02 161 | 94.96 161 |
|
conf0.05thres1000 | | | 87.62 177 | 86.65 176 | 90.53 166 | 96.19 79 | 78.52 233 | 95.29 68 | 91.09 288 | 87.08 95 | 87.84 123 | 93.03 168 | 68.86 241 | 98.11 121 | 69.44 290 | 91.02 161 | 94.96 161 |
|
tfpn | | | 87.62 177 | 86.65 176 | 90.53 166 | 96.19 79 | 78.52 233 | 95.29 68 | 91.09 288 | 87.08 95 | 87.84 123 | 93.03 168 | 68.86 241 | 98.11 121 | 69.44 290 | 91.02 161 | 94.96 161 |
|
FC-MVSNet-test | | | 90.27 95 | 90.18 85 | 90.53 166 | 93.71 186 | 79.85 186 | 95.77 48 | 97.59 2 | 89.31 40 | 86.27 155 | 94.67 109 | 81.93 75 | 97.01 220 | 84.26 133 | 88.09 213 | 94.71 176 |
|
PAPM | | | 86.68 208 | 85.39 213 | 90.53 166 | 93.05 204 | 79.33 212 | 89.79 288 | 94.77 198 | 78.82 263 | 81.95 258 | 93.24 159 | 76.81 120 | 97.30 195 | 66.94 307 | 93.16 133 | 94.95 168 |
|
WR-MVS | | | 88.38 142 | 87.67 140 | 90.52 172 | 93.30 198 | 80.18 173 | 93.26 216 | 95.96 109 | 88.57 60 | 85.47 181 | 92.81 178 | 76.12 128 | 96.91 228 | 81.24 177 | 82.29 263 | 94.47 197 |
|
MVSTER | | | 88.84 132 | 88.29 128 | 90.51 173 | 92.95 210 | 80.44 172 | 93.73 193 | 95.01 183 | 84.66 148 | 87.15 137 | 93.12 164 | 72.79 186 | 97.21 207 | 87.86 89 | 87.36 220 | 93.87 221 |
|
testdata | | | | | 90.49 174 | 96.40 73 | 77.89 254 | | 95.37 161 | 72.51 321 | 93.63 27 | 96.69 40 | 82.08 70 | 97.65 154 | 83.08 146 | 97.39 61 | 95.94 129 |
|
jajsoiax | | | 88.24 147 | 87.50 142 | 90.48 175 | 90.89 282 | 80.14 175 | 95.31 64 | 95.65 134 | 84.97 142 | 84.24 223 | 94.02 130 | 65.31 283 | 97.42 180 | 88.56 79 | 88.52 204 | 93.89 218 |
|
tfpn111 | | | 87.63 174 | 86.68 174 | 90.47 176 | 96.12 84 | 78.55 229 | 95.03 89 | 91.58 274 | 87.15 90 | 88.06 116 | 92.29 192 | 68.91 237 | 98.15 118 | 69.88 288 | 91.10 153 | 94.71 176 |
|
PatchMatch-RL | | | 86.77 207 | 85.54 207 | 90.47 176 | 95.88 97 | 82.71 118 | 90.54 277 | 92.31 253 | 79.82 254 | 84.32 220 | 91.57 223 | 68.77 245 | 96.39 257 | 73.16 267 | 93.48 126 | 92.32 287 |
|
conf200view11 | | | 87.65 170 | 86.71 171 | 90.46 178 | 96.12 84 | 78.55 229 | 95.03 89 | 91.58 274 | 87.15 90 | 88.06 116 | 92.29 192 | 68.91 237 | 98.10 125 | 70.13 283 | 91.10 153 | 94.71 176 |
|
tfpn200view9 | | | 87.58 183 | 86.64 180 | 90.41 179 | 95.99 94 | 78.64 226 | 94.58 123 | 91.98 265 | 86.94 102 | 88.09 113 | 91.77 213 | 69.18 234 | 98.10 125 | 70.13 283 | 91.10 153 | 94.48 195 |
|
VPNet | | | 88.20 148 | 87.47 144 | 90.39 180 | 93.56 190 | 79.46 197 | 94.04 174 | 95.54 141 | 88.67 56 | 86.96 140 | 94.58 114 | 69.33 229 | 97.15 209 | 84.05 137 | 80.53 295 | 94.56 188 |
|
ACMH | | 80.38 17 | 85.36 239 | 83.68 251 | 90.39 180 | 94.45 159 | 80.63 166 | 94.73 110 | 94.85 193 | 82.09 214 | 77.24 300 | 92.65 182 | 60.01 313 | 97.58 157 | 72.25 271 | 84.87 239 | 92.96 267 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
thres100view900 | | | 87.63 174 | 86.71 171 | 90.38 182 | 96.12 84 | 78.55 229 | 95.03 89 | 91.58 274 | 87.15 90 | 88.06 116 | 92.29 192 | 68.91 237 | 98.10 125 | 70.13 283 | 91.10 153 | 94.48 195 |
|
mvs-test1 | | | 89.45 115 | 89.14 106 | 90.38 182 | 93.33 196 | 77.63 264 | 94.95 94 | 94.36 207 | 87.70 81 | 87.10 139 | 92.81 178 | 73.45 178 | 98.03 137 | 85.57 116 | 93.04 135 | 95.48 145 |
|
mvs_tets | | | 88.06 154 | 87.28 149 | 90.38 182 | 90.94 278 | 79.88 184 | 95.22 77 | 95.66 132 | 85.10 139 | 84.21 224 | 93.94 135 | 63.53 291 | 97.40 187 | 88.50 80 | 88.40 209 | 93.87 221 |
|
1314 | | | 87.51 185 | 86.57 184 | 90.34 185 | 92.42 218 | 79.74 189 | 92.63 238 | 95.35 163 | 78.35 270 | 80.14 280 | 91.62 220 | 74.05 169 | 97.15 209 | 81.05 178 | 93.53 123 | 94.12 206 |
|
LTVRE_ROB | | 82.13 13 | 86.26 217 | 84.90 225 | 90.34 185 | 94.44 160 | 81.50 138 | 92.31 249 | 94.89 191 | 83.03 194 | 79.63 285 | 92.67 181 | 69.69 225 | 97.79 147 | 71.20 275 | 86.26 228 | 91.72 297 |
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 |
test_djsdf | | | 89.03 128 | 88.64 117 | 90.21 187 | 90.74 287 | 79.28 213 | 95.96 41 | 95.90 114 | 84.66 148 | 85.33 194 | 92.94 173 | 74.02 170 | 97.30 195 | 89.64 71 | 88.53 203 | 94.05 212 |
|
v2v482 | | | 87.84 161 | 87.06 158 | 90.17 188 | 90.99 274 | 79.23 219 | 94.00 178 | 95.13 176 | 84.87 143 | 85.53 176 | 92.07 205 | 74.45 161 | 97.45 169 | 84.71 126 | 81.75 275 | 93.85 224 |
|
v1neww | | | 87.98 155 | 87.25 151 | 90.16 189 | 91.38 247 | 79.41 201 | 94.37 142 | 95.28 164 | 84.48 151 | 85.77 163 | 91.53 225 | 76.12 128 | 97.45 169 | 84.45 130 | 81.89 270 | 93.61 245 |
|
v7new | | | 87.98 155 | 87.25 151 | 90.16 189 | 91.38 247 | 79.41 201 | 94.37 142 | 95.28 164 | 84.48 151 | 85.77 163 | 91.53 225 | 76.12 128 | 97.45 169 | 84.45 130 | 81.89 270 | 93.61 245 |
|
v6 | | | 87.98 155 | 87.25 151 | 90.16 189 | 91.36 250 | 79.39 206 | 94.37 142 | 95.27 167 | 84.48 151 | 85.78 162 | 91.51 227 | 76.15 127 | 97.46 167 | 84.46 129 | 81.88 272 | 93.62 244 |
|
pmmvs4 | | | 85.43 238 | 83.86 245 | 90.16 189 | 90.02 306 | 82.97 109 | 90.27 279 | 92.67 248 | 75.93 291 | 80.73 271 | 91.74 215 | 71.05 205 | 95.73 283 | 78.85 219 | 83.46 254 | 91.78 294 |
|
V42 | | | 87.68 168 | 86.86 163 | 90.15 193 | 90.58 292 | 80.14 175 | 94.24 150 | 95.28 164 | 83.66 170 | 85.67 171 | 91.33 235 | 74.73 159 | 97.41 185 | 84.43 132 | 81.83 273 | 92.89 269 |
|
MSDG | | | 84.86 253 | 83.09 264 | 90.14 194 | 93.80 183 | 80.05 179 | 89.18 298 | 93.09 239 | 78.89 261 | 78.19 291 | 91.91 210 | 65.86 282 | 97.27 199 | 68.47 298 | 88.45 206 | 93.11 264 |
|
anonymousdsp | | | 87.84 161 | 87.09 155 | 90.12 195 | 89.13 314 | 80.54 169 | 94.67 118 | 95.55 139 | 82.05 215 | 83.82 229 | 92.12 199 | 71.47 202 | 97.15 209 | 87.15 100 | 87.80 216 | 92.67 275 |
|
v7 | | | 87.75 166 | 86.96 161 | 90.12 195 | 91.20 265 | 79.50 192 | 94.28 148 | 95.46 149 | 83.45 178 | 85.75 165 | 91.56 224 | 75.13 152 | 97.43 178 | 83.60 142 | 82.18 265 | 93.42 254 |
|
thres200 | | | 87.21 197 | 86.24 192 | 90.12 195 | 95.36 115 | 78.53 232 | 93.26 216 | 92.10 258 | 86.42 111 | 88.00 120 | 91.11 248 | 69.24 233 | 98.00 138 | 69.58 289 | 91.04 160 | 93.83 225 |
|
CR-MVSNet | | | 85.35 240 | 83.76 246 | 90.12 195 | 90.58 292 | 79.34 209 | 85.24 330 | 91.96 267 | 78.27 271 | 85.55 174 | 87.87 303 | 71.03 206 | 95.61 284 | 73.96 263 | 89.36 186 | 95.40 148 |
|
RPMNet | | | 83.18 276 | 80.87 282 | 90.12 195 | 90.58 292 | 79.34 209 | 85.24 330 | 90.78 302 | 71.44 327 | 85.55 174 | 82.97 335 | 70.87 208 | 95.61 284 | 61.01 334 | 89.36 186 | 95.40 148 |
|
v1141 | | | 87.84 161 | 87.09 155 | 90.11 200 | 91.23 262 | 79.25 215 | 94.08 168 | 95.24 169 | 84.44 155 | 85.69 170 | 91.31 238 | 75.91 140 | 97.44 176 | 84.17 135 | 81.74 276 | 93.63 243 |
|
v1 | | | 87.85 160 | 87.10 154 | 90.11 200 | 91.21 264 | 79.24 217 | 94.09 166 | 95.24 169 | 84.44 155 | 85.70 168 | 91.31 238 | 75.96 138 | 97.45 169 | 84.18 134 | 81.73 278 | 93.64 241 |
|
divwei89l23v2f112 | | | 87.84 161 | 87.09 155 | 90.10 202 | 91.23 262 | 79.24 217 | 94.09 166 | 95.24 169 | 84.44 155 | 85.70 168 | 91.31 238 | 75.91 140 | 97.44 176 | 84.17 135 | 81.73 278 | 93.64 241 |
|
v1144 | | | 87.61 182 | 86.79 168 | 90.06 203 | 91.01 273 | 79.34 209 | 93.95 180 | 95.42 158 | 83.36 182 | 85.66 172 | 91.31 238 | 74.98 156 | 97.42 180 | 83.37 143 | 82.06 266 | 93.42 254 |
|
XXY-MVS | | | 87.65 170 | 86.85 164 | 90.03 204 | 92.14 222 | 80.60 168 | 93.76 190 | 95.23 172 | 82.94 199 | 84.60 209 | 94.02 130 | 74.27 163 | 95.49 292 | 81.04 179 | 83.68 250 | 94.01 215 |
|
Vis-MVSNet (Re-imp) | | | 89.59 110 | 89.44 99 | 90.03 204 | 95.74 101 | 75.85 284 | 95.61 57 | 90.80 301 | 87.66 85 | 87.83 127 | 95.40 87 | 76.79 121 | 96.46 254 | 78.37 222 | 96.73 70 | 97.80 65 |
|
BH-untuned | | | 88.60 139 | 88.13 132 | 90.01 206 | 95.24 129 | 78.50 238 | 93.29 214 | 94.15 214 | 84.75 146 | 84.46 213 | 93.40 150 | 75.76 144 | 97.40 187 | 77.59 231 | 94.52 106 | 94.12 206 |
|
v1192 | | | 87.25 194 | 86.33 188 | 90.00 207 | 90.76 286 | 79.04 221 | 93.80 187 | 95.48 148 | 82.57 208 | 85.48 180 | 91.18 244 | 73.38 181 | 97.42 180 | 82.30 161 | 82.06 266 | 93.53 249 |
|
v7n | | | 86.81 203 | 85.76 205 | 89.95 208 | 90.72 288 | 79.25 215 | 95.07 86 | 95.92 111 | 84.45 154 | 82.29 250 | 90.86 252 | 72.60 190 | 97.53 161 | 79.42 215 | 80.52 296 | 93.08 266 |
|
v8 | | | 87.50 186 | 86.71 171 | 89.89 209 | 91.37 249 | 79.40 205 | 94.50 127 | 95.38 159 | 84.81 145 | 83.60 236 | 91.33 235 | 76.05 132 | 97.42 180 | 82.84 151 | 80.51 297 | 92.84 271 |
|
v10 | | | 87.25 194 | 86.38 186 | 89.85 210 | 91.19 267 | 79.50 192 | 94.48 128 | 95.45 153 | 83.79 168 | 83.62 235 | 91.19 243 | 75.13 152 | 97.42 180 | 81.94 168 | 80.60 292 | 92.63 277 |
|
pm-mvs1 | | | 86.61 209 | 85.54 207 | 89.82 211 | 91.44 240 | 80.18 173 | 95.28 74 | 94.85 193 | 83.84 165 | 81.66 261 | 92.62 183 | 72.45 194 | 96.48 252 | 79.67 209 | 78.06 311 | 92.82 273 |
|
TR-MVS | | | 86.78 205 | 85.76 205 | 89.82 211 | 94.37 161 | 78.41 240 | 92.47 244 | 92.83 243 | 81.11 243 | 86.36 153 | 92.40 187 | 68.73 246 | 97.48 165 | 73.75 265 | 89.85 179 | 93.57 248 |
|
ACMH+ | | 81.04 14 | 85.05 246 | 83.46 258 | 89.82 211 | 94.66 150 | 79.37 207 | 94.44 133 | 94.12 216 | 82.19 213 | 78.04 293 | 92.82 177 | 58.23 319 | 97.54 160 | 73.77 264 | 82.90 258 | 92.54 278 |
|
EI-MVSNet | | | 89.10 125 | 88.86 115 | 89.80 214 | 91.84 228 | 78.30 243 | 93.70 197 | 95.01 183 | 85.73 123 | 87.15 137 | 95.28 88 | 79.87 92 | 97.21 207 | 83.81 140 | 87.36 220 | 93.88 220 |
|
v144192 | | | 87.19 198 | 86.35 187 | 89.74 215 | 90.64 291 | 78.24 246 | 93.92 181 | 95.43 156 | 81.93 220 | 85.51 178 | 91.05 250 | 74.21 166 | 97.45 169 | 82.86 150 | 81.56 280 | 93.53 249 |
|
COLMAP_ROB | | 80.39 16 | 83.96 267 | 82.04 273 | 89.74 215 | 95.28 120 | 79.75 188 | 94.25 149 | 92.28 254 | 75.17 297 | 78.02 294 | 93.77 146 | 58.60 318 | 97.84 146 | 65.06 323 | 85.92 229 | 91.63 299 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
conf0.01 | | | 85.83 227 | 84.54 233 | 89.71 217 | 95.26 122 | 77.63 264 | 94.21 152 | 89.33 327 | 81.89 223 | 84.94 200 | 91.51 227 | 68.43 253 | 96.80 233 | 66.05 312 | 89.23 189 | 94.71 176 |
|
conf0.002 | | | 85.83 227 | 84.54 233 | 89.71 217 | 95.26 122 | 77.63 264 | 94.21 152 | 89.33 327 | 81.89 223 | 84.94 200 | 91.51 227 | 68.43 253 | 96.80 233 | 66.05 312 | 89.23 189 | 94.71 176 |
|
IterMVS-LS | | | 88.36 144 | 87.91 137 | 89.70 219 | 93.80 183 | 78.29 244 | 93.73 193 | 95.08 181 | 85.73 123 | 84.75 207 | 91.90 211 | 79.88 91 | 96.92 227 | 83.83 139 | 82.51 261 | 93.89 218 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
v1921920 | | | 86.97 202 | 86.06 198 | 89.69 220 | 90.53 296 | 78.11 249 | 93.80 187 | 95.43 156 | 81.90 222 | 85.33 194 | 91.05 250 | 72.66 188 | 97.41 185 | 82.05 166 | 81.80 274 | 93.53 249 |
|
Fast-Effi-MVS+-dtu | | | 87.44 187 | 86.72 170 | 89.63 221 | 92.04 225 | 77.68 263 | 94.03 175 | 93.94 226 | 85.81 120 | 82.42 249 | 91.32 237 | 70.33 219 | 97.06 217 | 80.33 195 | 90.23 172 | 94.14 205 |
|
v1240 | | | 86.78 205 | 85.85 203 | 89.56 222 | 90.45 297 | 77.79 258 | 93.61 201 | 95.37 161 | 81.65 233 | 85.43 185 | 91.15 246 | 71.50 201 | 97.43 178 | 81.47 176 | 82.05 268 | 93.47 253 |
|
Effi-MVS+-dtu | | | 88.65 137 | 88.35 124 | 89.54 223 | 93.33 196 | 76.39 279 | 94.47 131 | 94.36 207 | 87.70 81 | 85.43 185 | 89.56 278 | 73.45 178 | 97.26 201 | 85.57 116 | 91.28 152 | 94.97 158 |
|
AllTest | | | 83.42 272 | 81.39 276 | 89.52 224 | 95.01 132 | 77.79 258 | 93.12 220 | 90.89 299 | 77.41 277 | 76.12 311 | 93.34 151 | 54.08 333 | 97.51 163 | 68.31 301 | 84.27 244 | 93.26 257 |
|
TestCases | | | | | 89.52 224 | 95.01 132 | 77.79 258 | | 90.89 299 | 77.41 277 | 76.12 311 | 93.34 151 | 54.08 333 | 97.51 163 | 68.31 301 | 84.27 244 | 93.26 257 |
|
mvs_anonymous | | | 89.37 121 | 89.32 102 | 89.51 226 | 93.47 192 | 74.22 291 | 91.65 265 | 94.83 195 | 82.91 201 | 85.45 182 | 93.79 144 | 81.23 81 | 96.36 259 | 86.47 111 | 94.09 113 | 97.94 56 |
|
tfpn1000 | | | 86.06 220 | 84.92 224 | 89.49 227 | 95.54 109 | 77.79 258 | 94.72 113 | 89.07 334 | 82.05 215 | 85.36 193 | 91.94 209 | 68.32 260 | 96.65 242 | 67.04 306 | 90.24 171 | 94.02 214 |
|
XVG-ACMP-BASELINE | | | 86.00 222 | 84.84 227 | 89.45 228 | 91.20 265 | 78.00 250 | 91.70 263 | 95.55 139 | 85.05 141 | 82.97 244 | 92.25 196 | 54.49 331 | 97.48 165 | 82.93 149 | 87.45 219 | 92.89 269 |
|
tfpn_ndepth | | | 86.10 219 | 84.98 220 | 89.43 229 | 95.52 112 | 78.29 244 | 94.62 121 | 89.60 325 | 81.88 230 | 85.43 185 | 90.54 260 | 68.47 251 | 96.85 232 | 68.46 299 | 90.34 170 | 93.15 263 |
|
v52 | | | 86.50 212 | 85.53 210 | 89.39 230 | 89.17 313 | 78.99 222 | 94.72 113 | 95.54 141 | 83.59 171 | 82.10 254 | 90.60 259 | 71.59 199 | 97.45 169 | 82.52 155 | 79.99 302 | 91.73 296 |
|
V4 | | | 86.50 212 | 85.54 207 | 89.39 230 | 89.13 314 | 78.99 222 | 94.73 110 | 95.54 141 | 83.59 171 | 82.10 254 | 90.61 258 | 71.60 198 | 97.45 169 | 82.52 155 | 80.01 301 | 91.74 295 |
|
thresconf0.02 | | | 85.75 231 | 84.54 233 | 89.38 232 | 95.26 122 | 77.63 264 | 94.21 152 | 89.33 327 | 81.89 223 | 84.94 200 | 91.51 227 | 68.43 253 | 96.80 233 | 66.05 312 | 89.23 189 | 93.70 235 |
|
tfpn_n400 | | | 85.75 231 | 84.54 233 | 89.38 232 | 95.26 122 | 77.63 264 | 94.21 152 | 89.33 327 | 81.89 223 | 84.94 200 | 91.51 227 | 68.43 253 | 96.80 233 | 66.05 312 | 89.23 189 | 93.70 235 |
|
tfpnconf | | | 85.75 231 | 84.54 233 | 89.38 232 | 95.26 122 | 77.63 264 | 94.21 152 | 89.33 327 | 81.89 223 | 84.94 200 | 91.51 227 | 68.43 253 | 96.80 233 | 66.05 312 | 89.23 189 | 93.70 235 |
|
tfpnview11 | | | 85.75 231 | 84.54 233 | 89.38 232 | 95.26 122 | 77.63 264 | 94.21 152 | 89.33 327 | 81.89 223 | 84.94 200 | 91.51 227 | 68.43 253 | 96.80 233 | 66.05 312 | 89.23 189 | 93.70 235 |
|
MVP-Stereo | | | 85.97 223 | 84.86 226 | 89.32 236 | 90.92 280 | 82.19 128 | 92.11 255 | 94.19 212 | 78.76 265 | 78.77 290 | 91.63 219 | 68.38 259 | 96.56 247 | 75.01 255 | 93.95 115 | 89.20 331 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
PatchmatchNet | | | 85.85 225 | 84.70 230 | 89.29 237 | 91.76 231 | 75.54 286 | 88.49 306 | 91.30 285 | 81.63 235 | 85.05 197 | 88.70 288 | 71.71 196 | 96.24 263 | 74.61 258 | 89.05 198 | 96.08 124 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
v748 | | | 86.27 216 | 85.28 215 | 89.25 238 | 90.26 300 | 77.58 271 | 94.89 98 | 95.50 146 | 84.28 158 | 81.41 264 | 90.46 264 | 72.57 191 | 97.32 194 | 79.81 207 | 78.36 310 | 92.84 271 |
|
v148 | | | 87.04 201 | 86.32 189 | 89.21 239 | 90.94 278 | 77.26 272 | 93.71 196 | 94.43 205 | 84.84 144 | 84.36 219 | 90.80 254 | 76.04 134 | 97.05 218 | 82.12 164 | 79.60 306 | 93.31 256 |
|
tfpnnormal | | | 84.72 259 | 83.23 263 | 89.20 240 | 92.79 213 | 80.05 179 | 94.48 128 | 95.81 121 | 82.38 210 | 81.08 268 | 91.21 242 | 69.01 236 | 96.95 225 | 61.69 332 | 80.59 293 | 90.58 324 |
|
Patchmatch-test1 | | | 85.81 229 | 84.71 229 | 89.12 241 | 92.15 221 | 76.60 277 | 91.12 274 | 91.69 272 | 83.53 176 | 85.50 179 | 88.56 291 | 66.79 270 | 95.00 310 | 72.69 269 | 90.35 169 | 95.76 138 |
|
BH-w/o | | | 87.57 184 | 87.05 159 | 89.12 241 | 94.90 140 | 77.90 253 | 92.41 245 | 93.51 234 | 82.89 202 | 83.70 232 | 91.34 234 | 75.75 145 | 97.07 216 | 75.49 248 | 93.49 124 | 92.39 284 |
|
WR-MVS_H | | | 87.80 165 | 87.37 146 | 89.10 243 | 93.23 199 | 78.12 248 | 95.61 57 | 97.30 18 | 87.90 75 | 83.72 231 | 92.01 207 | 79.65 99 | 96.01 271 | 76.36 241 | 80.54 294 | 93.16 261 |
|
gg-mvs-nofinetune | | | 81.77 286 | 79.37 296 | 88.99 244 | 90.85 284 | 77.73 262 | 86.29 322 | 79.63 361 | 74.88 302 | 83.19 243 | 69.05 353 | 60.34 310 | 96.11 267 | 75.46 249 | 94.64 103 | 93.11 264 |
|
pmmvs6 | | | 83.42 272 | 81.60 275 | 88.87 245 | 88.01 329 | 77.87 255 | 94.96 93 | 94.24 211 | 74.67 303 | 78.80 289 | 91.09 249 | 60.17 312 | 96.49 251 | 77.06 239 | 75.40 320 | 92.23 289 |
|
DWT-MVSNet_test | | | 84.95 250 | 83.68 251 | 88.77 246 | 91.43 243 | 73.75 297 | 91.74 261 | 90.98 296 | 80.66 246 | 83.84 228 | 87.36 307 | 62.44 295 | 97.11 213 | 78.84 220 | 85.81 230 | 95.46 146 |
|
MIMVSNet | | | 82.59 280 | 80.53 283 | 88.76 247 | 91.51 238 | 78.32 242 | 86.57 321 | 90.13 311 | 79.32 257 | 80.70 272 | 88.69 289 | 52.98 335 | 93.07 330 | 66.03 318 | 88.86 200 | 94.90 169 |
|
CP-MVSNet | | | 87.63 174 | 87.26 150 | 88.74 248 | 93.12 202 | 76.59 278 | 95.29 68 | 96.58 72 | 88.43 62 | 83.49 239 | 92.98 172 | 75.28 151 | 95.83 278 | 78.97 218 | 81.15 283 | 93.79 226 |
|
PatchFormer-LS_test | | | 86.02 221 | 85.13 217 | 88.70 249 | 91.52 237 | 74.12 294 | 91.19 273 | 92.09 259 | 82.71 206 | 84.30 222 | 87.24 309 | 70.87 208 | 96.98 222 | 81.04 179 | 85.17 237 | 95.00 157 |
|
CHOSEN 280x420 | | | 85.15 244 | 83.99 243 | 88.65 250 | 92.47 217 | 78.40 241 | 79.68 350 | 92.76 245 | 74.90 301 | 81.41 264 | 89.59 276 | 69.85 224 | 95.51 289 | 79.92 203 | 95.29 95 | 92.03 291 |
|
PS-CasMVS | | | 87.32 191 | 86.88 162 | 88.63 251 | 92.99 209 | 76.33 281 | 95.33 63 | 96.61 69 | 88.22 69 | 83.30 242 | 93.07 166 | 73.03 184 | 95.79 281 | 78.36 223 | 81.00 288 | 93.75 232 |
|
v17 | | | 84.93 251 | 83.70 250 | 88.62 252 | 91.36 250 | 79.48 195 | 93.83 184 | 94.03 219 | 83.04 193 | 76.51 306 | 86.57 314 | 76.05 132 | 95.42 295 | 80.31 197 | 71.65 330 | 90.96 311 |
|
v16 | | | 84.96 249 | 83.74 248 | 88.62 252 | 91.40 245 | 79.48 195 | 93.83 184 | 94.04 217 | 83.03 194 | 76.54 305 | 86.59 313 | 76.11 131 | 95.42 295 | 80.33 195 | 71.80 328 | 90.95 313 |
|
v18 | | | 84.97 248 | 83.76 246 | 88.60 254 | 91.36 250 | 79.41 201 | 93.82 186 | 94.04 217 | 83.00 197 | 76.61 304 | 86.60 312 | 76.19 126 | 95.43 294 | 80.39 192 | 71.79 329 | 90.96 311 |
|
v13 | | | 84.72 259 | 83.44 260 | 88.58 255 | 91.31 260 | 79.52 191 | 93.77 189 | 94.00 223 | 83.03 194 | 75.85 316 | 86.38 320 | 75.84 142 | 95.35 302 | 79.83 206 | 70.95 335 | 90.87 318 |
|
v12 | | | 84.74 257 | 83.46 258 | 88.58 255 | 91.32 257 | 79.50 192 | 93.75 191 | 94.01 220 | 83.06 190 | 75.98 315 | 86.41 319 | 75.82 143 | 95.36 301 | 79.87 205 | 70.89 337 | 90.89 317 |
|
V9 | | | 84.77 256 | 83.50 257 | 88.58 255 | 91.33 255 | 79.46 197 | 93.75 191 | 94.00 223 | 83.07 189 | 76.07 313 | 86.43 315 | 75.97 137 | 95.37 298 | 79.91 204 | 70.93 336 | 90.91 315 |
|
v15 | | | 84.79 254 | 83.53 255 | 88.57 258 | 91.30 261 | 79.41 201 | 93.70 197 | 94.01 220 | 83.06 190 | 76.27 307 | 86.42 318 | 76.03 135 | 95.38 297 | 80.01 199 | 71.00 333 | 90.92 314 |
|
V14 | | | 84.79 254 | 83.52 256 | 88.57 258 | 91.32 257 | 79.43 200 | 93.72 195 | 94.01 220 | 83.06 190 | 76.22 308 | 86.43 315 | 76.01 136 | 95.37 298 | 79.96 201 | 70.99 334 | 90.91 315 |
|
TransMVSNet (Re) | | | 84.43 264 | 83.06 265 | 88.54 260 | 91.72 232 | 78.44 239 | 95.18 79 | 92.82 244 | 82.73 205 | 79.67 284 | 92.12 199 | 73.49 177 | 95.96 273 | 71.10 278 | 68.73 344 | 91.21 306 |
|
tpmp4_e23 | | | 83.87 270 | 82.33 271 | 88.48 261 | 91.46 239 | 72.82 304 | 89.82 287 | 91.57 278 | 73.02 317 | 81.86 260 | 89.05 281 | 66.20 277 | 96.97 223 | 71.57 273 | 86.39 227 | 95.66 141 |
|
EG-PatchMatch MVS | | | 82.37 282 | 80.34 285 | 88.46 262 | 90.27 299 | 79.35 208 | 92.80 235 | 94.33 209 | 77.14 281 | 73.26 329 | 90.18 268 | 47.47 345 | 96.72 239 | 70.25 280 | 87.32 222 | 89.30 329 |
|
v11 | | | 84.67 262 | 83.41 261 | 88.44 263 | 91.32 257 | 79.13 220 | 93.69 200 | 93.99 225 | 82.81 203 | 76.20 309 | 86.24 322 | 75.48 148 | 95.35 302 | 79.53 210 | 71.48 332 | 90.85 319 |
|
PEN-MVS | | | 86.80 204 | 86.27 191 | 88.40 264 | 92.32 220 | 75.71 285 | 95.18 79 | 96.38 82 | 87.97 72 | 82.82 246 | 93.15 162 | 73.39 180 | 95.92 274 | 76.15 245 | 79.03 309 | 93.59 247 |
|
Baseline_NR-MVSNet | | | 87.07 200 | 86.63 182 | 88.40 264 | 91.44 240 | 77.87 255 | 94.23 151 | 92.57 250 | 84.12 160 | 85.74 167 | 92.08 203 | 77.25 117 | 96.04 268 | 82.29 162 | 79.94 303 | 91.30 305 |
|
pmmvs5 | | | 84.21 265 | 82.84 269 | 88.34 266 | 88.95 317 | 76.94 275 | 92.41 245 | 91.91 269 | 75.63 293 | 80.28 277 | 91.18 244 | 64.59 287 | 95.57 286 | 77.09 238 | 83.47 253 | 92.53 279 |
|
LCM-MVSNet-Re | | | 88.30 146 | 88.32 127 | 88.27 267 | 94.71 147 | 72.41 312 | 93.15 219 | 90.98 296 | 87.77 79 | 79.25 288 | 91.96 208 | 78.35 110 | 95.75 282 | 83.04 147 | 95.62 86 | 96.65 107 |
|
CostFormer | | | 85.77 230 | 84.94 223 | 88.26 268 | 91.16 270 | 72.58 311 | 89.47 293 | 91.04 295 | 76.26 288 | 86.45 151 | 89.97 271 | 70.74 211 | 96.86 231 | 82.35 160 | 87.07 225 | 95.34 151 |
|
ITE_SJBPF | | | | | 88.24 269 | 91.88 227 | 77.05 274 | | 92.92 241 | 85.54 129 | 80.13 281 | 93.30 156 | 57.29 322 | 96.20 264 | 72.46 270 | 84.71 240 | 91.49 301 |
|
PVSNet | | 78.82 18 | 85.55 237 | 84.65 231 | 88.23 270 | 94.72 146 | 71.93 313 | 87.12 318 | 92.75 246 | 78.80 264 | 84.95 199 | 90.53 262 | 64.43 288 | 96.71 241 | 74.74 256 | 93.86 117 | 96.06 126 |
|
semantic-postprocess | | | | | 88.18 271 | 91.71 233 | 76.87 276 | | 92.65 249 | 85.40 132 | 81.44 263 | 90.54 260 | 66.21 276 | 95.00 310 | 81.04 179 | 81.05 284 | 92.66 276 |
|
EPNet_dtu | | | 86.49 214 | 85.94 202 | 88.14 272 | 90.24 301 | 72.82 304 | 94.11 162 | 92.20 256 | 86.66 108 | 79.42 287 | 92.36 189 | 73.52 176 | 95.81 280 | 71.26 274 | 93.66 120 | 95.80 137 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
Patchmtry | | | 82.71 278 | 80.93 281 | 88.06 273 | 90.05 305 | 76.37 280 | 84.74 332 | 91.96 267 | 72.28 323 | 81.32 266 | 87.87 303 | 71.03 206 | 95.50 291 | 68.97 295 | 80.15 299 | 92.32 287 |
|
DTE-MVSNet | | | 86.11 218 | 85.48 211 | 87.98 274 | 91.65 236 | 74.92 288 | 94.93 96 | 95.75 126 | 87.36 88 | 82.26 251 | 93.04 167 | 72.85 185 | 95.82 279 | 74.04 261 | 77.46 315 | 93.20 259 |
|
PMMVS | | | 85.71 236 | 84.96 222 | 87.95 275 | 88.90 318 | 77.09 273 | 88.68 304 | 90.06 313 | 72.32 322 | 86.47 148 | 90.76 255 | 72.15 195 | 94.40 314 | 81.78 172 | 93.49 124 | 92.36 285 |
|
GG-mvs-BLEND | | | | | 87.94 276 | 89.73 311 | 77.91 252 | 87.80 312 | 78.23 363 | | 80.58 274 | 83.86 330 | 59.88 314 | 95.33 304 | 71.20 275 | 92.22 147 | 90.60 323 |
|
pmmvs-eth3d | | | 80.97 298 | 78.72 303 | 87.74 277 | 84.99 340 | 79.97 183 | 90.11 283 | 91.65 273 | 75.36 294 | 73.51 326 | 86.03 323 | 59.45 315 | 93.96 319 | 75.17 252 | 72.21 326 | 89.29 330 |
|
MS-PatchMatch | | | 85.05 246 | 84.16 240 | 87.73 278 | 91.42 244 | 78.51 237 | 91.25 272 | 93.53 233 | 77.50 276 | 80.15 279 | 91.58 221 | 61.99 298 | 95.51 289 | 75.69 247 | 94.35 112 | 89.16 332 |
|
test_0402 | | | 81.30 295 | 79.17 299 | 87.67 279 | 93.19 200 | 78.17 247 | 92.98 229 | 91.71 270 | 75.25 296 | 76.02 314 | 90.31 266 | 59.23 316 | 96.37 258 | 50.22 347 | 83.63 251 | 88.47 341 |
|
IterMVS | | | 84.88 252 | 83.98 244 | 87.60 280 | 91.44 240 | 76.03 283 | 90.18 282 | 92.41 252 | 83.24 185 | 81.06 269 | 90.42 265 | 66.60 271 | 94.28 316 | 79.46 211 | 80.98 289 | 92.48 280 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
Patchmatch-test | | | 81.37 293 | 79.30 297 | 87.58 281 | 90.92 280 | 74.16 293 | 80.99 347 | 87.68 344 | 70.52 333 | 76.63 303 | 88.81 285 | 71.21 203 | 92.76 331 | 60.01 338 | 86.93 226 | 95.83 135 |
|
EPMVS | | | 83.90 269 | 82.70 270 | 87.51 282 | 90.23 302 | 72.67 307 | 88.62 305 | 81.96 357 | 81.37 241 | 85.01 198 | 88.34 294 | 66.31 275 | 94.45 313 | 75.30 251 | 87.12 223 | 95.43 147 |
|
ADS-MVSNet2 | | | 81.66 288 | 79.71 294 | 87.50 283 | 91.35 253 | 74.19 292 | 83.33 341 | 88.48 338 | 72.90 318 | 82.24 252 | 85.77 324 | 64.98 285 | 93.20 327 | 64.57 324 | 83.74 248 | 95.12 153 |
|
OurMVSNet-221017-0 | | | 85.35 240 | 84.64 232 | 87.49 284 | 90.77 285 | 72.59 310 | 94.01 177 | 94.40 206 | 84.72 147 | 79.62 286 | 93.17 161 | 61.91 299 | 96.72 239 | 81.99 167 | 81.16 281 | 93.16 261 |
|
tpm2 | | | 84.08 266 | 82.94 266 | 87.48 285 | 91.39 246 | 71.27 317 | 89.23 297 | 90.37 306 | 71.95 325 | 84.64 208 | 89.33 279 | 67.30 262 | 96.55 249 | 75.17 252 | 87.09 224 | 94.63 181 |
|
RPSCF | | | 85.07 245 | 84.27 239 | 87.48 285 | 92.91 211 | 70.62 325 | 91.69 264 | 92.46 251 | 76.20 289 | 82.67 248 | 95.22 91 | 63.94 290 | 97.29 198 | 77.51 233 | 85.80 231 | 94.53 189 |
|
FMVSNet5 | | | 81.52 291 | 79.60 295 | 87.27 287 | 91.17 268 | 77.95 251 | 91.49 267 | 92.26 255 | 76.87 282 | 76.16 310 | 87.91 302 | 51.67 336 | 92.34 332 | 67.74 305 | 81.16 281 | 91.52 300 |
|
USDC | | | 82.76 277 | 81.26 278 | 87.26 288 | 91.17 268 | 74.55 289 | 89.27 295 | 93.39 236 | 78.26 272 | 75.30 318 | 92.08 203 | 54.43 332 | 96.63 243 | 71.64 272 | 85.79 232 | 90.61 321 |
|
test-LLR | | | 85.87 224 | 85.41 212 | 87.25 289 | 90.95 276 | 71.67 315 | 89.55 289 | 89.88 319 | 83.41 179 | 84.54 211 | 87.95 300 | 67.25 263 | 95.11 307 | 81.82 170 | 93.37 129 | 94.97 158 |
|
test-mter | | | 84.54 263 | 83.64 253 | 87.25 289 | 90.95 276 | 71.67 315 | 89.55 289 | 89.88 319 | 79.17 258 | 84.54 211 | 87.95 300 | 55.56 326 | 95.11 307 | 81.82 170 | 93.37 129 | 94.97 158 |
|
JIA-IIPM | | | 81.04 296 | 78.98 302 | 87.25 289 | 88.64 319 | 73.48 299 | 81.75 346 | 89.61 324 | 73.19 314 | 82.05 256 | 73.71 350 | 66.07 281 | 95.87 277 | 71.18 277 | 84.60 241 | 92.41 283 |
|
TDRefinement | | | 79.81 304 | 77.34 306 | 87.22 292 | 79.24 353 | 75.48 287 | 93.12 220 | 92.03 262 | 76.45 284 | 75.01 319 | 91.58 221 | 49.19 342 | 96.44 255 | 70.22 282 | 69.18 341 | 89.75 327 |
|
tpmvs | | | 83.35 275 | 82.07 272 | 87.20 293 | 91.07 272 | 71.00 322 | 88.31 309 | 91.70 271 | 78.91 260 | 80.49 276 | 87.18 310 | 69.30 232 | 97.08 215 | 68.12 304 | 83.56 252 | 93.51 252 |
|
ppachtmachnet_test | | | 81.84 285 | 80.07 290 | 87.15 294 | 88.46 322 | 74.43 290 | 89.04 300 | 92.16 257 | 75.33 295 | 77.75 296 | 88.99 282 | 66.20 277 | 95.37 298 | 65.12 322 | 77.60 313 | 91.65 298 |
|
tpm cat1 | | | 81.96 283 | 80.27 286 | 87.01 295 | 91.09 271 | 71.02 321 | 87.38 317 | 91.53 280 | 66.25 343 | 80.17 278 | 86.35 321 | 68.22 261 | 96.15 266 | 69.16 294 | 82.29 263 | 93.86 223 |
|
OpenMVS_ROB | | 74.94 19 | 79.51 306 | 77.03 310 | 86.93 296 | 87.00 333 | 76.23 282 | 92.33 248 | 90.74 303 | 68.93 337 | 74.52 322 | 88.23 297 | 49.58 340 | 96.62 244 | 57.64 340 | 84.29 243 | 87.94 343 |
|
SixPastTwentyTwo | | | 83.91 268 | 82.90 267 | 86.92 297 | 90.99 274 | 70.67 324 | 93.48 205 | 91.99 264 | 85.54 129 | 77.62 298 | 92.11 201 | 60.59 309 | 96.87 230 | 76.05 246 | 77.75 312 | 93.20 259 |
|
ADS-MVSNet | | | 81.56 290 | 79.78 292 | 86.90 298 | 91.35 253 | 71.82 314 | 83.33 341 | 89.16 333 | 72.90 318 | 82.24 252 | 85.77 324 | 64.98 285 | 93.76 320 | 64.57 324 | 83.74 248 | 95.12 153 |
|
PatchT | | | 82.68 279 | 81.27 277 | 86.89 299 | 90.09 304 | 70.94 323 | 84.06 337 | 90.15 310 | 74.91 300 | 85.63 173 | 83.57 332 | 69.37 228 | 94.87 312 | 65.19 320 | 88.50 205 | 94.84 171 |
|
tpm | | | 84.73 258 | 84.02 242 | 86.87 300 | 90.33 298 | 68.90 332 | 89.06 299 | 89.94 316 | 80.85 245 | 85.75 165 | 89.86 273 | 68.54 248 | 95.97 272 | 77.76 229 | 84.05 246 | 95.75 139 |
|
Patchmatch-RL test | | | 81.67 287 | 79.96 291 | 86.81 301 | 85.42 337 | 71.23 318 | 82.17 345 | 87.50 346 | 78.47 268 | 77.19 301 | 82.50 336 | 70.81 210 | 93.48 323 | 82.66 154 | 72.89 325 | 95.71 140 |
|
MDA-MVSNet-bldmvs | | | 78.85 310 | 76.31 311 | 86.46 302 | 89.76 310 | 73.88 296 | 88.79 302 | 90.42 305 | 79.16 259 | 59.18 351 | 88.33 295 | 60.20 311 | 94.04 318 | 62.00 331 | 68.96 342 | 91.48 302 |
|
tpmrst | | | 85.35 240 | 84.99 219 | 86.43 303 | 90.88 283 | 67.88 335 | 88.71 303 | 91.43 283 | 80.13 250 | 86.08 159 | 88.80 286 | 73.05 183 | 96.02 270 | 82.48 157 | 83.40 256 | 95.40 148 |
|
TESTMET0.1,1 | | | 83.74 271 | 82.85 268 | 86.42 304 | 89.96 307 | 71.21 319 | 89.55 289 | 87.88 341 | 77.41 277 | 83.37 241 | 87.31 308 | 56.71 323 | 93.65 322 | 80.62 188 | 92.85 140 | 94.40 198 |
|
our_test_3 | | | 81.93 284 | 80.46 284 | 86.33 305 | 88.46 322 | 73.48 299 | 88.46 307 | 91.11 287 | 76.46 283 | 76.69 302 | 88.25 296 | 66.89 268 | 94.36 315 | 68.75 296 | 79.08 308 | 91.14 308 |
|
lessismore_v0 | | | | | 86.04 306 | 88.46 322 | 68.78 333 | | 80.59 359 | | 73.01 330 | 90.11 269 | 55.39 327 | 96.43 256 | 75.06 254 | 65.06 346 | 92.90 268 |
|
TinyColmap | | | 79.76 305 | 77.69 305 | 85.97 307 | 91.71 233 | 73.12 301 | 89.55 289 | 90.36 307 | 75.03 298 | 72.03 334 | 90.19 267 | 46.22 347 | 96.19 265 | 63.11 328 | 81.03 285 | 88.59 338 |
|
K. test v3 | | | 81.59 289 | 80.15 289 | 85.91 308 | 89.89 309 | 69.42 331 | 92.57 241 | 87.71 343 | 85.56 128 | 73.44 327 | 89.71 275 | 55.58 325 | 95.52 288 | 77.17 236 | 69.76 340 | 92.78 274 |
|
MIMVSNet1 | | | 79.38 307 | 77.28 307 | 85.69 309 | 86.35 335 | 73.67 298 | 91.61 266 | 92.75 246 | 78.11 275 | 72.64 332 | 88.12 298 | 48.16 343 | 91.97 336 | 60.32 335 | 77.49 314 | 91.43 303 |
|
LP | | | 75.51 316 | 72.15 320 | 85.61 310 | 87.86 331 | 73.93 295 | 80.20 349 | 88.43 339 | 67.39 339 | 70.05 337 | 80.56 343 | 58.18 320 | 93.18 328 | 46.28 353 | 70.36 339 | 89.71 328 |
|
UnsupCasMVSNet_eth | | | 80.07 302 | 78.27 304 | 85.46 311 | 85.24 338 | 72.63 309 | 88.45 308 | 94.87 192 | 82.99 198 | 71.64 336 | 88.07 299 | 56.34 324 | 91.75 337 | 73.48 266 | 63.36 350 | 92.01 292 |
|
MDA-MVSNet_test_wron | | | 79.21 309 | 77.19 309 | 85.29 312 | 88.22 326 | 72.77 306 | 85.87 325 | 90.06 313 | 74.34 305 | 62.62 350 | 87.56 306 | 66.14 279 | 91.99 335 | 66.90 310 | 73.01 323 | 91.10 310 |
|
YYNet1 | | | 79.22 308 | 77.20 308 | 85.28 313 | 88.20 327 | 72.66 308 | 85.87 325 | 90.05 315 | 74.33 306 | 62.70 349 | 87.61 305 | 66.09 280 | 92.03 334 | 66.94 307 | 72.97 324 | 91.15 307 |
|
dp | | | 81.47 292 | 80.23 287 | 85.17 314 | 89.92 308 | 65.49 341 | 86.74 319 | 90.10 312 | 76.30 287 | 81.10 267 | 87.12 311 | 62.81 293 | 95.92 274 | 68.13 303 | 79.88 304 | 94.09 209 |
|
UnsupCasMVSNet_bld | | | 76.23 315 | 73.27 317 | 85.09 315 | 83.79 343 | 72.92 302 | 85.65 329 | 93.47 235 | 71.52 326 | 68.84 340 | 79.08 346 | 49.77 339 | 93.21 326 | 66.81 311 | 60.52 352 | 89.13 334 |
|
Anonymous20231206 | | | 81.03 297 | 79.77 293 | 84.82 316 | 87.85 332 | 70.26 327 | 91.42 268 | 92.08 260 | 73.67 310 | 77.75 296 | 89.25 280 | 62.43 296 | 93.08 329 | 61.50 333 | 82.00 269 | 91.12 309 |
|
test0.0.03 1 | | | 82.41 281 | 81.69 274 | 84.59 317 | 88.23 325 | 72.89 303 | 90.24 280 | 87.83 342 | 83.41 179 | 79.86 283 | 89.78 274 | 67.25 263 | 88.99 343 | 65.18 321 | 83.42 255 | 91.90 293 |
|
CMPMVS | | 59.16 21 | 80.52 300 | 79.20 298 | 84.48 318 | 83.98 342 | 67.63 337 | 89.95 286 | 93.84 230 | 64.79 347 | 66.81 344 | 91.14 247 | 57.93 321 | 95.17 305 | 76.25 243 | 88.10 211 | 90.65 320 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
CVMVSNet | | | 84.69 261 | 84.79 228 | 84.37 319 | 91.84 228 | 64.92 342 | 93.70 197 | 91.47 282 | 66.19 344 | 86.16 158 | 95.28 88 | 67.18 265 | 93.33 325 | 80.89 184 | 90.42 168 | 94.88 170 |
|
PVSNet_0 | | 73.20 20 | 77.22 312 | 74.83 315 | 84.37 319 | 90.70 289 | 71.10 320 | 83.09 343 | 89.67 323 | 72.81 320 | 73.93 325 | 83.13 334 | 60.79 308 | 93.70 321 | 68.54 297 | 50.84 355 | 88.30 342 |
|
LF4IMVS | | | 80.37 301 | 79.07 301 | 84.27 321 | 86.64 334 | 69.87 330 | 89.39 294 | 91.05 294 | 76.38 285 | 74.97 320 | 90.00 270 | 47.85 344 | 94.25 317 | 74.55 259 | 80.82 291 | 88.69 337 |
|
PM-MVS | | | 78.11 311 | 76.12 313 | 84.09 322 | 83.54 344 | 70.08 328 | 88.97 301 | 85.27 351 | 79.93 252 | 74.73 321 | 86.43 315 | 34.70 356 | 93.48 323 | 79.43 214 | 72.06 327 | 88.72 336 |
|
testgi | | | 80.94 299 | 80.20 288 | 83.18 323 | 87.96 330 | 66.29 338 | 91.28 270 | 90.70 304 | 83.70 169 | 78.12 292 | 92.84 175 | 51.37 337 | 90.82 340 | 63.34 327 | 82.46 262 | 92.43 282 |
|
ambc | | | | | 83.06 324 | 79.99 350 | 63.51 344 | 77.47 353 | 92.86 242 | | 74.34 324 | 84.45 328 | 28.74 357 | 95.06 309 | 73.06 268 | 68.89 343 | 90.61 321 |
|
test20.03 | | | 79.95 303 | 79.08 300 | 82.55 325 | 85.79 336 | 67.74 336 | 91.09 275 | 91.08 292 | 81.23 242 | 74.48 323 | 89.96 272 | 61.63 300 | 90.15 341 | 60.08 336 | 76.38 317 | 89.76 326 |
|
EU-MVSNet | | | 81.32 294 | 80.95 280 | 82.42 326 | 88.50 321 | 63.67 343 | 93.32 209 | 91.33 284 | 64.02 348 | 80.57 275 | 92.83 176 | 61.21 306 | 92.27 333 | 76.34 242 | 80.38 298 | 91.32 304 |
|
pmmvs3 | | | 71.81 322 | 68.71 325 | 81.11 327 | 75.86 355 | 70.42 326 | 86.74 319 | 83.66 353 | 58.95 352 | 68.64 342 | 80.89 342 | 36.93 355 | 89.52 342 | 63.10 329 | 63.59 349 | 83.39 347 |
|
new-patchmatchnet | | | 76.41 314 | 75.17 314 | 80.13 328 | 82.65 347 | 59.61 348 | 87.66 315 | 91.08 292 | 78.23 273 | 69.85 338 | 83.22 333 | 54.76 329 | 91.63 339 | 64.14 326 | 64.89 347 | 89.16 332 |
|
DSMNet-mixed | | | 76.94 313 | 76.29 312 | 78.89 329 | 83.10 345 | 56.11 355 | 87.78 313 | 79.77 360 | 60.65 351 | 75.64 317 | 88.71 287 | 61.56 301 | 88.34 345 | 60.07 337 | 89.29 188 | 92.21 290 |
|
test2356 | | | 74.50 317 | 73.27 317 | 78.20 330 | 80.81 349 | 59.84 346 | 83.76 340 | 88.33 340 | 71.43 328 | 72.37 333 | 81.84 339 | 45.60 348 | 86.26 351 | 50.97 345 | 84.32 242 | 88.50 339 |
|
new_pmnet | | | 72.15 321 | 70.13 323 | 78.20 330 | 82.95 346 | 65.68 339 | 83.91 338 | 82.40 356 | 62.94 350 | 64.47 347 | 79.82 345 | 42.85 350 | 86.26 351 | 57.41 341 | 74.44 322 | 82.65 349 |
|
MVS-HIRNet | | | 73.70 319 | 72.20 319 | 78.18 332 | 91.81 230 | 56.42 354 | 82.94 344 | 82.58 355 | 55.24 353 | 68.88 339 | 66.48 354 | 55.32 328 | 95.13 306 | 58.12 339 | 88.42 208 | 83.01 348 |
|
test1235678 | | | 72.22 320 | 70.31 322 | 77.93 333 | 78.04 354 | 58.04 350 | 85.76 327 | 89.80 321 | 70.15 335 | 63.43 348 | 80.20 344 | 42.24 351 | 87.24 348 | 48.68 349 | 74.50 321 | 88.50 339 |
|
testus | | | 74.41 318 | 73.35 316 | 77.59 334 | 82.49 348 | 57.08 351 | 86.02 323 | 90.21 309 | 72.28 323 | 72.89 331 | 84.32 329 | 37.08 354 | 86.96 349 | 52.24 344 | 82.65 260 | 88.73 335 |
|
LCM-MVSNet | | | 66.00 326 | 62.16 330 | 77.51 335 | 64.51 365 | 58.29 349 | 83.87 339 | 90.90 298 | 48.17 356 | 54.69 353 | 73.31 351 | 16.83 368 | 86.75 350 | 65.47 319 | 61.67 351 | 87.48 344 |
|
no-one | | | 61.56 330 | 56.58 332 | 76.49 336 | 67.80 363 | 62.76 345 | 78.13 352 | 86.11 347 | 63.16 349 | 43.24 358 | 64.70 356 | 26.12 360 | 88.95 344 | 50.84 346 | 29.15 358 | 77.77 353 |
|
testmv | | | 65.49 327 | 62.66 328 | 73.96 337 | 68.78 360 | 53.14 358 | 84.70 333 | 88.56 337 | 65.94 345 | 52.35 354 | 74.65 349 | 25.02 361 | 85.14 354 | 43.54 355 | 60.40 353 | 83.60 346 |
|
1111 | | | 70.54 324 | 69.71 324 | 73.04 338 | 79.30 351 | 44.83 363 | 84.23 335 | 88.96 335 | 67.33 340 | 65.42 345 | 82.28 337 | 41.11 352 | 88.11 346 | 47.12 351 | 71.60 331 | 86.19 345 |
|
ANet_high | | | 58.88 332 | 54.22 335 | 72.86 339 | 56.50 369 | 56.67 353 | 80.75 348 | 86.00 348 | 73.09 316 | 37.39 360 | 64.63 357 | 22.17 363 | 79.49 361 | 43.51 356 | 23.96 362 | 82.43 350 |
|
FPMVS | | | 64.63 329 | 62.55 329 | 70.88 340 | 70.80 358 | 56.71 352 | 84.42 334 | 84.42 352 | 51.78 355 | 49.57 355 | 81.61 340 | 23.49 362 | 81.48 358 | 40.61 358 | 76.25 318 | 74.46 355 |
|
N_pmnet | | | 68.89 325 | 68.44 326 | 70.23 341 | 89.07 316 | 28.79 370 | 88.06 310 | 19.50 372 | 69.47 336 | 71.86 335 | 84.93 327 | 61.24 305 | 91.75 337 | 54.70 342 | 77.15 316 | 90.15 325 |
|
wuykxyi23d | | | 50.55 336 | 44.13 339 | 69.81 342 | 56.77 367 | 54.58 357 | 73.22 357 | 80.78 358 | 39.79 361 | 22.08 367 | 46.69 363 | 4.03 372 | 79.71 360 | 47.65 350 | 26.13 360 | 75.14 354 |
|
testpf | | | 71.41 323 | 72.11 321 | 69.30 343 | 84.53 341 | 59.79 347 | 62.74 360 | 83.14 354 | 71.11 330 | 68.83 341 | 81.57 341 | 46.70 346 | 84.83 356 | 74.51 260 | 75.86 319 | 63.30 356 |
|
PMMVS2 | | | 59.60 331 | 56.40 333 | 69.21 344 | 68.83 359 | 46.58 361 | 73.02 358 | 77.48 364 | 55.07 354 | 49.21 356 | 72.95 352 | 17.43 367 | 80.04 359 | 49.32 348 | 44.33 356 | 80.99 352 |
|
test12356 | | | 64.99 328 | 63.78 327 | 68.61 345 | 72.69 357 | 39.14 366 | 78.46 351 | 87.61 345 | 64.91 346 | 55.77 352 | 77.48 347 | 28.10 358 | 85.59 353 | 44.69 354 | 64.35 348 | 81.12 351 |
|
Gipuma | | | 57.99 333 | 54.91 334 | 67.24 346 | 88.51 320 | 65.59 340 | 52.21 363 | 90.33 308 | 43.58 359 | 42.84 359 | 51.18 361 | 20.29 365 | 85.07 355 | 34.77 360 | 70.45 338 | 51.05 361 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
PMVS | | 47.18 22 | 52.22 335 | 48.46 337 | 63.48 347 | 45.72 370 | 46.20 362 | 73.41 356 | 78.31 362 | 41.03 360 | 30.06 363 | 65.68 355 | 6.05 370 | 83.43 357 | 30.04 361 | 65.86 345 | 60.80 358 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
PNet_i23d | | | 50.48 337 | 47.18 338 | 60.36 348 | 68.59 361 | 44.56 365 | 72.75 359 | 72.61 365 | 43.92 358 | 33.91 362 | 60.19 359 | 6.16 369 | 73.52 362 | 38.50 359 | 28.04 359 | 63.01 357 |
|
MVE | | 39.65 23 | 43.39 338 | 38.59 344 | 57.77 349 | 56.52 368 | 48.77 360 | 55.38 362 | 58.64 369 | 29.33 364 | 28.96 364 | 52.65 360 | 4.68 371 | 64.62 365 | 28.11 362 | 33.07 357 | 59.93 359 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
DeepMVS_CX | | | | | 56.31 350 | 74.23 356 | 51.81 359 | | 56.67 370 | 44.85 357 | 48.54 357 | 75.16 348 | 27.87 359 | 58.74 366 | 40.92 357 | 52.22 354 | 58.39 360 |
|
E-PMN | | | 43.23 339 | 42.29 340 | 46.03 351 | 65.58 364 | 37.41 367 | 73.51 355 | 64.62 366 | 33.99 362 | 28.47 365 | 47.87 362 | 19.90 366 | 67.91 363 | 22.23 363 | 24.45 361 | 32.77 362 |
|
.test1245 | | | 57.63 334 | 61.79 331 | 45.14 352 | 79.30 351 | 44.83 363 | 84.23 335 | 88.96 335 | 67.33 340 | 65.42 345 | 82.28 337 | 41.11 352 | 88.11 346 | 47.12 351 | 0.39 366 | 2.46 367 |
|
EMVS | | | 42.07 340 | 41.12 341 | 44.92 353 | 63.45 366 | 35.56 369 | 73.65 354 | 63.48 367 | 33.05 363 | 26.88 366 | 45.45 364 | 21.27 364 | 67.14 364 | 19.80 364 | 23.02 363 | 32.06 363 |
|
pcd1.5k->3k | | | 37.02 342 | 38.84 343 | 31.53 354 | 92.33 219 | 0.00 374 | 0.00 365 | 96.13 97 | 0.00 369 | 0.00 371 | 0.00 371 | 72.70 187 | 0.00 371 | 0.00 368 | 88.43 207 | 94.60 184 |
|
tmp_tt | | | 35.64 343 | 39.24 342 | 24.84 355 | 14.87 371 | 23.90 371 | 62.71 361 | 51.51 371 | 6.58 366 | 36.66 361 | 62.08 358 | 44.37 349 | 30.34 368 | 52.40 343 | 22.00 364 | 20.27 364 |
|
wuyk23d | | | 21.27 345 | 20.48 346 | 23.63 356 | 68.59 361 | 36.41 368 | 49.57 364 | 6.85 373 | 9.37 365 | 7.89 368 | 4.46 370 | 4.03 372 | 31.37 367 | 17.47 365 | 16.07 365 | 3.12 365 |
|
test123 | | | 8.76 347 | 11.22 348 | 1.39 357 | 0.85 373 | 0.97 372 | 85.76 327 | 0.35 375 | 0.54 368 | 2.45 370 | 8.14 369 | 0.60 374 | 0.48 369 | 2.16 367 | 0.17 368 | 2.71 366 |
|
testmvs | | | 8.92 346 | 11.52 347 | 1.12 358 | 1.06 372 | 0.46 373 | 86.02 323 | 0.65 374 | 0.62 367 | 2.74 369 | 9.52 368 | 0.31 375 | 0.45 370 | 2.38 366 | 0.39 366 | 2.46 367 |
|
test_part1 | | | | | 0.00 359 | | 0.00 374 | 0.00 365 | 97.45 7 | | | | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
v1.0 | | | 39.85 341 | 53.14 336 | 0.00 359 | 98.55 5 | 0.00 374 | 0.00 365 | 97.45 7 | 88.25 67 | 96.40 4 | 97.60 6 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
cdsmvs_eth3d_5k | | | 22.14 344 | 29.52 345 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 95.76 125 | 0.00 369 | 0.00 371 | 94.29 121 | 75.66 146 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
pcd_1.5k_mvsjas | | | 6.64 349 | 8.86 350 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 0.00 371 | 79.70 95 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
sosnet-low-res | | | 0.00 350 | 0.00 351 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 0.00 371 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
sosnet | | | 0.00 350 | 0.00 351 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 0.00 371 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
uncertanet | | | 0.00 350 | 0.00 351 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 0.00 371 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
Regformer | | | 0.00 350 | 0.00 351 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 0.00 371 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
ab-mvs-re | | | 7.82 348 | 10.43 349 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 93.88 140 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
uanet | | | 0.00 350 | 0.00 351 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 0.00 371 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
GSMVS | | | | | | | | | | | | | | | | | 96.12 121 |
|
test_part2 | | | | | | 98.55 5 | 87.22 12 | | | | 96.40 4 | | | | | | |
|
sam_mvs1 | | | | | | | | | | | | | 71.70 197 | | | | 96.12 121 |
|
sam_mvs | | | | | | | | | | | | | 70.60 212 | | | | |
|
MTGPA | | | | | | | | | 96.97 37 | | | | | | | | |
|
test_post1 | | | | | | | | 88.00 311 | | | | 9.81 367 | 69.31 231 | 95.53 287 | 76.65 240 | | |
|
test_post | | | | | | | | | | | | 10.29 366 | 70.57 216 | 95.91 276 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 83.76 331 | 71.53 200 | 96.48 252 | | | |
|
MTMP | | | | | | | | 96.16 32 | 60.64 368 | | | | | | | | |
|
gm-plane-assit | | | | | | 89.60 312 | 68.00 334 | | | 77.28 280 | | 88.99 282 | | 97.57 158 | 79.44 213 | | |
|
test9_res | | | | | | | | | | | | | | | 91.91 43 | 98.71 19 | 98.07 47 |
|
TEST9 | | | | | | 97.53 39 | 86.49 31 | 94.07 170 | 96.78 53 | 81.61 236 | 92.77 44 | 96.20 61 | 87.71 15 | 99.12 42 | | | |
|
test_8 | | | | | | 97.49 42 | 86.30 39 | 94.02 176 | 96.76 56 | 81.86 231 | 92.70 48 | 96.20 61 | 87.63 16 | 99.02 54 | | | |
|
agg_prior2 | | | | | | | | | | | | | | | 90.54 64 | 98.68 24 | 98.27 32 |
|
agg_prior | | | | | | 97.38 46 | 85.92 46 | | 96.72 59 | | 92.16 60 | | | 98.97 62 | | | |
|
test_prior4 | | | | | | | 85.96 45 | 94.11 162 | | | | | | | | | |
|
test_prior2 | | | | | | | | 94.12 160 | | 87.67 83 | 92.63 49 | 96.39 54 | 86.62 25 | | 91.50 50 | 98.67 26 | |
|
旧先验2 | | | | | | | | 93.36 208 | | 71.25 329 | 94.37 15 | | | 97.13 212 | 86.74 105 | | |
|
æ–°å‡ ä½•2 | | | | | | | | 93.11 222 | | | | | | | | | |
|
旧先验1 | | | | | | 96.79 62 | 81.81 134 | | 95.67 130 | | | 96.81 35 | 86.69 24 | | | 97.66 57 | 96.97 99 |
|
æ— å…ˆéªŒ | | | | | | | | 93.28 215 | 96.26 86 | 73.95 308 | | | | 99.05 47 | 80.56 189 | | 96.59 108 |
|
原ACMM2 | | | | | | | | 92.94 231 | | | | | | | | | |
|
test222 | | | | | | 96.55 69 | 81.70 135 | 92.22 251 | 95.01 183 | 68.36 338 | 90.20 90 | 96.14 66 | 80.26 89 | | | 97.80 55 | 96.05 127 |
|
testdata2 | | | | | | | | | | | | | | 98.75 80 | 78.30 224 | | |
|
segment_acmp | | | | | | | | | | | | | 87.16 21 | | | | |
|
testdata1 | | | | | | | | 92.15 253 | | 87.94 73 | | | | | | | |
|
plane_prior7 | | | | | | 94.70 148 | 82.74 115 | | | | | | | | | | |
|
plane_prior6 | | | | | | 94.52 155 | 82.75 113 | | | | | | 74.23 164 | | | | |
|
plane_prior5 | | | | | | | | | 96.22 90 | | | | | 98.12 119 | 88.15 84 | 89.99 174 | 94.63 181 |
|
plane_prior4 | | | | | | | | | | | | 94.86 101 | | | | | |
|
plane_prior3 | | | | | | | 82.75 113 | | | 90.26 25 | 86.91 142 | | | | | | |
|
plane_prior2 | | | | | | | | 95.85 45 | | 90.81 18 | | | | | | | |
|
plane_prior1 | | | | | | 94.59 153 | | | | | | | | | | | |
|
plane_prior | | | | | | | 82.73 116 | 95.21 78 | | 89.66 35 | | | | | | 89.88 178 | |
|
n2 | | | | | | | | | 0.00 376 | | | | | | | | |
|
nn | | | | | | | | | 0.00 376 | | | | | | | | |
|
door-mid | | | | | | | | | 85.49 349 | | | | | | | | |
|
test11 | | | | | | | | | 96.57 73 | | | | | | | | |
|
door | | | | | | | | | 85.33 350 | | | | | | | | |
|
HQP5-MVS | | | | | | | 81.56 136 | | | | | | | | | | |
|
HQP-NCC | | | | | | 94.17 166 | | 94.39 138 | | 88.81 51 | 85.43 185 | | | | | | |
|
ACMP_Plane | | | | | | 94.17 166 | | 94.39 138 | | 88.81 51 | 85.43 185 | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 87.11 102 | | |
|
HQP4-MVS | | | | | | | | | | | 85.43 185 | | | 97.96 140 | | | 94.51 191 |
|
HQP3-MVS | | | | | | | | | 96.04 104 | | | | | | | 89.77 180 | |
|
HQP2-MVS | | | | | | | | | | | | | 73.83 173 | | | | |
|
NP-MVS | | | | | | 94.37 161 | 82.42 123 | | | | | 93.98 132 | | | | | |
|
MDTV_nov1_ep13_2view | | | | | | | 55.91 356 | 87.62 316 | | 73.32 313 | 84.59 210 | | 70.33 219 | | 74.65 257 | | 95.50 144 |
|
MDTV_nov1_ep13 | | | | 83.56 254 | | 91.69 235 | 69.93 329 | 87.75 314 | 91.54 279 | 78.60 267 | 84.86 206 | 88.90 284 | 69.54 227 | 96.03 269 | 70.25 280 | 88.93 199 | |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 87.47 217 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 88.01 214 | |
|
Test By Simon | | | | | | | | | | | | | 80.02 90 | | | | |
|