LCM-MVSNet | | | 95.70 1 | 96.40 1 | 93.61 2 | 98.67 1 | 85.39 29 | 95.54 3 | 97.36 1 | 96.97 1 | 99.04 1 | 99.05 1 | 96.61 1 | 95.92 11 | 85.07 41 | 99.27 1 | 99.54 1 |
|
WR-MVS_H | | | 89.91 45 | 91.31 27 | 85.71 110 | 96.32 10 | 62.39 215 | 89.54 60 | 93.31 54 | 90.21 9 | 95.57 9 | 95.66 28 | 81.42 100 | 95.90 12 | 80.94 81 | 98.80 2 | 98.84 5 |
|
ACMP | | 79.16 10 | 90.54 31 | 90.60 42 | 90.35 43 | 94.36 43 | 80.98 58 | 89.16 66 | 94.05 26 | 79.03 90 | 92.87 37 | 93.74 90 | 90.60 11 | 95.21 47 | 82.87 64 | 98.76 3 | 94.87 62 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
ACMH+ | | 77.89 11 | 90.73 27 | 91.50 19 | 88.44 67 | 93.00 71 | 76.26 102 | 89.65 56 | 95.55 3 | 87.72 19 | 93.89 25 | 94.94 44 | 91.62 4 | 93.44 108 | 78.35 107 | 98.76 3 | 95.61 47 |
|
PS-CasMVS | | | 90.06 38 | 91.92 10 | 84.47 131 | 96.56 7 | 58.83 251 | 89.04 68 | 92.74 79 | 91.40 4 | 96.12 4 | 96.06 23 | 87.23 39 | 95.57 28 | 79.42 99 | 98.74 5 | 99.00 2 |
|
LPG-MVS_test | | | 91.47 17 | 91.68 15 | 90.82 35 | 94.75 39 | 81.69 52 | 90.00 45 | 94.27 15 | 82.35 53 | 93.67 30 | 94.82 48 | 91.18 5 | 95.52 32 | 85.36 39 | 98.73 6 | 95.23 57 |
|
LGP-MVS_train | | | | | 90.82 35 | 94.75 39 | 81.69 52 | | 94.27 15 | 82.35 53 | 93.67 30 | 94.82 48 | 91.18 5 | 95.52 32 | 85.36 39 | 98.73 6 | 95.23 57 |
|
PEN-MVS | | | 90.03 40 | 91.88 13 | 84.48 130 | 96.57 6 | 58.88 248 | 88.95 69 | 93.19 60 | 91.62 3 | 96.01 6 | 96.16 21 | 87.02 41 | 95.60 27 | 78.69 104 | 98.72 8 | 98.97 3 |
|
CP-MVSNet | | | 89.27 56 | 90.91 38 | 84.37 132 | 96.34 9 | 58.61 253 | 88.66 77 | 92.06 93 | 90.78 5 | 95.67 7 | 95.17 39 | 81.80 96 | 95.54 31 | 79.00 102 | 98.69 9 | 98.95 4 |
|
TranMVSNet+NR-MVSNet | | | 87.86 71 | 88.76 65 | 85.18 118 | 94.02 49 | 64.13 194 | 84.38 136 | 91.29 113 | 84.88 31 | 92.06 51 | 93.84 88 | 86.45 48 | 93.73 92 | 73.22 150 | 98.66 10 | 97.69 10 |
|
NR-MVSNet | | | 86.00 94 | 86.22 92 | 85.34 116 | 93.24 66 | 64.56 190 | 82.21 192 | 90.46 131 | 80.99 67 | 88.42 117 | 91.97 129 | 77.56 132 | 93.85 87 | 72.46 160 | 98.65 11 | 97.61 11 |
|
UA-Net | | | 91.49 15 | 91.53 18 | 91.39 24 | 94.98 34 | 82.95 50 | 93.52 6 | 92.79 77 | 88.22 16 | 88.53 114 | 97.64 3 | 83.45 69 | 94.55 66 | 86.02 37 | 98.60 12 | 96.67 26 |
|
FC-MVSNet-test | | | 85.93 97 | 87.05 80 | 82.58 173 | 92.25 91 | 56.44 266 | 85.75 113 | 93.09 63 | 77.33 108 | 91.94 55 | 94.65 53 | 74.78 162 | 93.41 110 | 75.11 135 | 98.58 13 | 97.88 7 |
|
DTE-MVSNet | | | 89.98 42 | 91.91 12 | 84.21 137 | 96.51 8 | 57.84 255 | 88.93 71 | 92.84 76 | 91.92 2 | 96.16 3 | 96.23 19 | 86.95 42 | 95.99 7 | 79.05 101 | 98.57 14 | 98.80 6 |
|
UniMVSNet (Re) | | | 86.87 78 | 86.98 82 | 86.55 89 | 93.11 69 | 68.48 163 | 83.80 149 | 92.87 73 | 80.37 72 | 89.61 96 | 91.81 136 | 77.72 130 | 94.18 74 | 75.00 136 | 98.53 15 | 96.99 23 |
|
Baseline_NR-MVSNet | | | 84.00 135 | 85.90 98 | 78.29 232 | 91.47 115 | 53.44 285 | 82.29 188 | 87.00 196 | 79.06 89 | 89.55 98 | 95.72 27 | 77.20 136 | 86.14 252 | 72.30 161 | 98.51 16 | 95.28 54 |
|
TDRefinement | | | 93.52 2 | 93.39 3 | 93.88 1 | 95.94 14 | 90.26 3 | 95.70 2 | 96.46 2 | 90.58 7 | 92.86 38 | 96.29 17 | 88.16 28 | 94.17 76 | 86.07 36 | 98.48 17 | 97.22 18 |
|
ACMM | | 79.39 9 | 90.65 28 | 90.99 35 | 89.63 52 | 95.03 33 | 83.53 44 | 89.62 57 | 93.35 50 | 79.20 87 | 93.83 26 | 93.60 92 | 90.81 8 | 92.96 124 | 85.02 43 | 98.45 18 | 92.41 135 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
MP-MVS-pluss | | | 90.81 26 | 91.08 31 | 89.99 48 | 95.97 13 | 79.88 64 | 88.13 82 | 94.51 13 | 75.79 127 | 92.94 35 | 94.96 43 | 88.36 22 | 95.01 53 | 90.70 2 | 98.40 19 | 95.09 60 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
CP-MVS | | | 91.67 12 | 91.58 17 | 91.96 12 | 95.29 30 | 87.62 9 | 93.38 8 | 93.36 49 | 83.16 44 | 91.06 68 | 94.00 79 | 88.26 25 | 95.71 24 | 87.28 22 | 98.39 20 | 92.55 132 |
|
UniMVSNet_NR-MVSNet | | | 86.84 80 | 87.06 79 | 86.17 102 | 92.86 76 | 67.02 172 | 82.55 182 | 91.56 105 | 83.08 46 | 90.92 70 | 91.82 135 | 78.25 126 | 93.99 82 | 74.16 139 | 98.35 21 | 97.49 14 |
|
DU-MVS | | | 86.80 81 | 86.99 81 | 86.21 100 | 93.24 66 | 67.02 172 | 83.16 169 | 92.21 89 | 81.73 60 | 90.92 70 | 91.97 129 | 77.20 136 | 93.99 82 | 74.16 139 | 98.35 21 | 97.61 11 |
|
zzz-MVS | | | 91.27 20 | 91.26 29 | 91.29 27 | 96.59 4 | 86.29 14 | 88.94 70 | 91.81 101 | 84.07 34 | 92.00 52 | 94.40 64 | 86.63 44 | 95.28 43 | 88.59 4 | 98.31 23 | 92.30 138 |
|
MTAPA | | | 91.52 14 | 91.60 16 | 91.29 27 | 96.59 4 | 86.29 14 | 92.02 26 | 91.81 101 | 84.07 34 | 92.00 52 | 94.40 64 | 86.63 44 | 95.28 43 | 88.59 4 | 98.31 23 | 92.30 138 |
|
ACMH | | 76.49 14 | 89.34 55 | 91.14 30 | 83.96 143 | 92.50 83 | 70.36 147 | 89.55 58 | 93.84 37 | 81.89 59 | 94.70 13 | 95.44 33 | 90.69 9 | 88.31 226 | 83.33 58 | 98.30 25 | 93.20 112 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
COLMAP_ROB | | 83.01 3 | 91.97 9 | 91.95 9 | 92.04 10 | 93.68 56 | 86.15 18 | 93.37 9 | 95.10 8 | 90.28 8 | 92.11 49 | 95.03 42 | 89.75 18 | 94.93 55 | 79.95 91 | 98.27 26 | 95.04 61 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
ACMMP | | | 91.91 10 | 91.87 14 | 92.03 11 | 95.53 25 | 85.91 22 | 93.35 10 | 94.16 22 | 82.52 52 | 92.39 48 | 94.14 73 | 89.15 19 | 95.62 26 | 87.35 19 | 98.24 27 | 94.56 68 |
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 |
HPM-MVS | | | 92.13 7 | 92.20 8 | 91.91 15 | 95.58 24 | 84.67 38 | 93.51 7 | 94.85 11 | 82.88 48 | 91.77 57 | 93.94 86 | 90.55 12 | 95.73 23 | 88.50 6 | 98.23 28 | 95.33 52 |
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
test_0728_THIRD | | | | | | | | | | 85.33 27 | 93.75 27 | 94.65 53 | 87.44 37 | 95.78 20 | 87.41 18 | 98.21 29 | 92.98 118 |
|
MP-MVS | | | 91.14 24 | 90.91 38 | 91.83 19 | 96.18 11 | 86.88 11 | 92.20 24 | 93.03 68 | 82.59 51 | 88.52 115 | 94.37 67 | 86.74 43 | 95.41 38 | 86.32 30 | 98.21 29 | 93.19 113 |
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
SteuartSystems-ACMMP | | | 91.16 23 | 91.36 22 | 90.55 39 | 93.91 52 | 80.97 59 | 91.49 32 | 93.48 47 | 82.82 49 | 92.60 44 | 93.97 80 | 88.19 26 | 96.29 4 | 87.61 14 | 98.20 31 | 94.39 77 |
Skip Steuart: Steuart Systems R&D Blog. |
HPM-MVS_fast | | | 92.50 5 | 92.54 5 | 92.37 5 | 95.93 15 | 85.81 27 | 92.99 12 | 94.23 18 | 85.21 28 | 92.51 45 | 95.13 40 | 90.65 10 | 95.34 40 | 88.06 8 | 98.15 32 | 95.95 40 |
|
mPP-MVS | | | 91.69 11 | 91.47 20 | 92.37 5 | 96.04 12 | 88.48 7 | 92.72 15 | 92.60 82 | 83.09 45 | 91.54 60 | 94.25 70 | 87.67 35 | 95.51 35 | 87.21 23 | 98.11 33 | 93.12 115 |
|
test_normal | | | 90.27 35 | 91.34 25 | 87.07 82 | 91.28 119 | 69.70 151 | 93.91 4 | 93.67 41 | 78.72 96 | 96.99 2 | 98.27 2 | 85.59 55 | 93.79 90 | 85.51 38 | 98.07 34 | 97.72 9 |
|
WR-MVS | | | 83.56 143 | 84.40 129 | 81.06 195 | 93.43 61 | 54.88 277 | 78.67 242 | 85.02 219 | 81.24 64 | 90.74 74 | 91.56 142 | 72.85 186 | 91.08 171 | 68.00 198 | 98.04 35 | 97.23 17 |
|
XVG-ACMP-BASELINE | | | 89.98 42 | 89.84 48 | 90.41 41 | 94.91 36 | 84.50 41 | 89.49 62 | 93.98 28 | 79.68 80 | 92.09 50 | 93.89 87 | 83.80 65 | 93.10 122 | 82.67 66 | 98.04 35 | 93.64 101 |
|
DeepC-MVS | | 82.31 4 | 89.15 58 | 89.08 58 | 89.37 57 | 93.64 57 | 79.07 72 | 88.54 78 | 94.20 19 | 73.53 152 | 89.71 91 | 94.82 48 | 85.09 57 | 95.77 22 | 84.17 51 | 98.03 37 | 93.26 110 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
FIs | | | 85.35 103 | 86.27 91 | 82.60 172 | 91.86 102 | 57.31 259 | 85.10 122 | 93.05 65 | 75.83 126 | 91.02 69 | 93.97 80 | 73.57 175 | 92.91 128 | 73.97 142 | 98.02 38 | 97.58 13 |
|
abl_6 | | | 93.02 4 | 93.16 4 | 92.60 4 | 94.73 41 | 88.99 6 | 93.26 11 | 94.19 21 | 89.11 10 | 94.43 16 | 95.27 36 | 91.86 3 | 95.09 50 | 87.54 17 | 98.02 38 | 93.71 99 |
|
Anonymous20231211 | | | 88.40 65 | 89.62 52 | 84.73 125 | 90.46 138 | 65.27 184 | 88.86 72 | 93.02 69 | 87.15 21 | 93.05 34 | 97.10 7 | 82.28 84 | 92.02 145 | 76.70 125 | 97.99 40 | 96.88 24 |
|
PGM-MVS | | | 91.20 22 | 90.95 37 | 91.93 13 | 95.67 21 | 85.85 25 | 90.00 45 | 93.90 33 | 80.32 74 | 91.74 58 | 94.41 63 | 88.17 27 | 95.98 8 | 86.37 29 | 97.99 40 | 93.96 88 |
|
APDe-MVS | | | 91.22 21 | 91.92 10 | 89.14 60 | 92.97 72 | 78.04 80 | 92.84 13 | 94.14 23 | 83.33 42 | 93.90 23 | 95.73 26 | 88.77 20 | 96.41 1 | 87.60 15 | 97.98 42 | 92.98 118 |
|
DVP-MVS | | | 90.06 38 | 91.32 26 | 86.29 95 | 94.16 46 | 72.56 122 | 90.54 39 | 91.01 121 | 83.61 38 | 93.75 27 | 94.65 53 | 89.76 16 | 95.78 20 | 86.42 27 | 97.97 43 | 90.55 183 |
|
test_0728_SECOND | | | | | 86.79 85 | 94.25 45 | 72.45 126 | 90.54 39 | 94.10 25 | | | | | 95.88 13 | 86.42 27 | 97.97 43 | 92.02 147 |
|
CLD-MVS | | | 83.18 150 | 82.64 153 | 84.79 123 | 89.05 157 | 67.82 169 | 77.93 249 | 92.52 83 | 68.33 205 | 85.07 166 | 81.54 286 | 82.06 88 | 92.96 124 | 69.35 184 | 97.91 45 | 93.57 104 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
IS-MVSNet | | | 86.66 83 | 86.82 86 | 86.17 102 | 92.05 97 | 66.87 174 | 91.21 34 | 88.64 166 | 86.30 25 | 89.60 97 | 92.59 113 | 69.22 207 | 94.91 56 | 73.89 143 | 97.89 46 | 96.72 25 |
|
ACMMP_NAP | | | 90.65 28 | 91.07 33 | 89.42 56 | 95.93 15 | 79.54 69 | 89.95 48 | 93.68 40 | 77.65 105 | 91.97 54 | 94.89 45 | 88.38 21 | 95.45 36 | 89.27 3 | 97.87 47 | 93.27 109 |
|
DPE-MVS | | | 90.53 32 | 91.08 31 | 88.88 62 | 93.38 62 | 78.65 77 | 89.15 67 | 94.05 26 | 84.68 32 | 93.90 23 | 94.11 75 | 88.13 29 | 96.30 3 | 84.51 49 | 97.81 48 | 91.70 158 |
|
OurMVSNet-221017-0 | | | 90.01 41 | 89.74 49 | 90.83 34 | 93.16 68 | 80.37 61 | 91.91 29 | 93.11 62 | 81.10 66 | 95.32 10 | 97.24 6 | 72.94 185 | 94.85 57 | 85.07 41 | 97.78 49 | 97.26 16 |
|
SMA-MVS | | | 90.31 34 | 90.48 43 | 89.83 49 | 95.31 29 | 79.52 70 | 90.98 35 | 93.24 59 | 75.37 134 | 92.84 39 | 95.28 35 | 85.58 56 | 96.09 6 | 87.92 9 | 97.76 50 | 93.88 91 |
|
ACMMPR | | | 91.49 15 | 91.35 24 | 91.92 14 | 95.74 19 | 85.88 24 | 92.58 19 | 93.25 58 | 81.99 56 | 91.40 63 | 94.17 72 | 87.51 36 | 95.87 14 | 87.74 10 | 97.76 50 | 93.99 86 |
|
HFP-MVS | | | 91.30 19 | 91.39 21 | 91.02 31 | 95.43 27 | 84.66 39 | 92.58 19 | 93.29 56 | 81.99 56 | 91.47 61 | 93.96 82 | 88.35 23 | 95.56 29 | 87.74 10 | 97.74 52 | 92.85 121 |
|
#test# | | | 90.49 33 | 90.31 45 | 91.02 31 | 95.43 27 | 84.66 39 | 90.65 37 | 93.29 56 | 77.00 112 | 91.47 61 | 93.96 82 | 88.35 23 | 95.56 29 | 84.88 44 | 97.74 52 | 92.85 121 |
|
region2R | | | 91.44 18 | 91.30 28 | 91.87 17 | 95.75 18 | 85.90 23 | 92.63 18 | 93.30 55 | 81.91 58 | 90.88 73 | 94.21 71 | 87.75 33 | 95.87 14 | 87.60 15 | 97.71 54 | 93.83 92 |
|
GST-MVS | | | 90.96 25 | 91.01 34 | 90.82 35 | 95.45 26 | 82.73 51 | 91.75 30 | 93.74 39 | 80.98 68 | 91.38 64 | 93.80 89 | 87.20 40 | 95.80 17 | 87.10 24 | 97.69 55 | 93.93 89 |
|
UniMVSNet_ETH3D | | | 89.12 59 | 90.72 40 | 84.31 135 | 97.00 2 | 64.33 193 | 89.67 55 | 88.38 170 | 88.84 13 | 94.29 19 | 97.57 4 | 90.48 13 | 91.26 166 | 72.57 159 | 97.65 56 | 97.34 15 |
|
v7n | | | 90.13 36 | 90.96 36 | 87.65 77 | 91.95 99 | 71.06 142 | 89.99 47 | 93.05 65 | 86.53 23 | 94.29 19 | 96.27 18 | 82.69 76 | 94.08 80 | 86.25 33 | 97.63 57 | 97.82 8 |
|
XVS | | | 91.54 13 | 91.36 22 | 92.08 8 | 95.64 22 | 86.25 16 | 92.64 16 | 93.33 51 | 85.07 29 | 89.99 82 | 94.03 77 | 86.57 46 | 95.80 17 | 87.35 19 | 97.62 58 | 94.20 79 |
|
X-MVStestdata | | | 85.04 109 | 82.70 151 | 92.08 8 | 95.64 22 | 86.25 16 | 92.64 16 | 93.33 51 | 85.07 29 | 89.99 82 | 16.05 333 | 86.57 46 | 95.80 17 | 87.35 19 | 97.62 58 | 94.20 79 |
|
APD-MVS_3200maxsize | | | 92.05 8 | 92.24 7 | 91.48 22 | 93.02 70 | 85.17 31 | 92.47 23 | 95.05 9 | 87.65 20 | 93.21 33 | 94.39 66 | 90.09 15 | 95.08 51 | 86.67 26 | 97.60 60 | 94.18 81 |
|
9.14 | | | | 89.29 56 | | 91.84 103 | | 88.80 74 | 95.32 7 | 75.14 136 | 91.07 67 | 92.89 105 | 87.27 38 | 93.78 91 | 83.69 56 | 97.55 61 | |
|
OPM-MVS | | | 89.80 46 | 89.97 46 | 89.27 58 | 94.76 38 | 79.86 65 | 86.76 102 | 92.78 78 | 78.78 93 | 92.51 45 | 93.64 91 | 88.13 29 | 93.84 89 | 84.83 46 | 97.55 61 | 94.10 84 |
|
LTVRE_ROB | | 86.10 1 | 93.04 3 | 93.44 2 | 91.82 21 | 93.73 55 | 85.72 28 | 96.79 1 | 95.51 4 | 88.86 12 | 95.63 8 | 96.99 9 | 84.81 59 | 93.16 118 | 91.10 1 | 97.53 63 | 96.58 29 |
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 |
MIMVSNet1 | | | 83.63 142 | 84.59 123 | 80.74 198 | 94.06 48 | 62.77 209 | 82.72 178 | 84.53 224 | 77.57 107 | 90.34 77 | 95.92 24 | 76.88 148 | 85.83 256 | 61.88 238 | 97.42 64 | 93.62 102 |
|
ACMMP++ | | | | | | | | | | | | | | | | 97.35 65 | |
|
SR-MVS | | | 92.23 6 | 92.34 6 | 91.91 15 | 94.89 37 | 87.85 8 | 92.51 21 | 93.87 36 | 88.20 17 | 93.24 32 | 94.02 78 | 90.15 14 | 95.67 25 | 86.82 25 | 97.34 66 | 92.19 144 |
|
nrg030 | | | 87.85 72 | 88.49 66 | 85.91 105 | 90.07 145 | 69.73 150 | 87.86 85 | 94.20 19 | 74.04 146 | 92.70 43 | 94.66 52 | 85.88 54 | 91.50 158 | 79.72 93 | 97.32 67 | 96.50 30 |
|
pmmvs6 | | | 86.52 85 | 88.06 69 | 81.90 182 | 92.22 93 | 62.28 218 | 84.66 128 | 89.15 161 | 83.54 40 | 89.85 87 | 97.32 5 | 88.08 31 | 86.80 242 | 70.43 177 | 97.30 68 | 96.62 27 |
|
SD-MVS | | | 88.96 61 | 89.88 47 | 86.22 98 | 91.63 106 | 77.07 92 | 89.82 51 | 93.77 38 | 78.90 91 | 92.88 36 | 92.29 123 | 86.11 52 | 90.22 196 | 86.24 34 | 97.24 69 | 91.36 167 |
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 |
CPTT-MVS | | | 89.39 54 | 88.98 61 | 90.63 38 | 95.09 32 | 86.95 10 | 92.09 25 | 92.30 88 | 79.74 79 | 87.50 131 | 92.38 119 | 81.42 100 | 93.28 113 | 83.07 61 | 97.24 69 | 91.67 159 |
|
APD-MVS | | | 89.54 51 | 89.63 51 | 89.26 59 | 92.57 80 | 81.34 57 | 90.19 43 | 93.08 64 | 80.87 69 | 91.13 66 | 93.19 95 | 86.22 51 | 95.97 9 | 82.23 70 | 97.18 71 | 90.45 185 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
wuyk23d | | | 75.13 231 | 79.30 192 | 62.63 305 | 75.56 309 | 75.18 107 | 80.89 212 | 73.10 289 | 75.06 137 | 94.76 12 | 95.32 34 | 87.73 34 | 52.85 331 | 34.16 329 | 97.11 72 | 59.85 327 |
|
PMVS | | 80.48 6 | 90.08 37 | 90.66 41 | 88.34 69 | 96.71 3 | 92.97 1 | 90.31 42 | 89.57 156 | 88.51 15 | 90.11 79 | 95.12 41 | 90.98 7 | 88.92 216 | 77.55 116 | 97.07 73 | 83.13 279 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
OMC-MVS | | | 88.19 67 | 87.52 73 | 90.19 46 | 91.94 101 | 81.68 54 | 87.49 90 | 93.17 61 | 76.02 121 | 88.64 112 | 91.22 147 | 84.24 63 | 93.37 111 | 77.97 113 | 97.03 74 | 95.52 48 |
|
test_prior3 | | | 86.31 88 | 86.31 90 | 86.32 93 | 90.59 135 | 71.99 132 | 83.37 161 | 92.85 74 | 75.43 131 | 84.58 174 | 91.57 140 | 81.92 94 | 94.17 76 | 79.54 96 | 96.97 75 | 92.80 123 |
|
test_prior2 | | | | | | | | 83.37 161 | | 75.43 131 | 84.58 174 | 91.57 140 | 81.92 94 | | 79.54 96 | 96.97 75 | |
|
save filter2 | | | | | | | | | | | 89.01 106 | 92.98 100 | 79.84 116 | 92.00 146 | 83.25 59 | 96.93 77 | 88.98 212 |
|
EPP-MVSNet | | | 85.47 102 | 85.04 112 | 86.77 86 | 91.52 113 | 69.37 154 | 91.63 31 | 87.98 179 | 81.51 63 | 87.05 139 | 91.83 134 | 66.18 220 | 95.29 41 | 70.75 172 | 96.89 78 | 95.64 45 |
|
VDDNet | | | 84.35 124 | 85.39 108 | 81.25 192 | 95.13 31 | 59.32 246 | 85.42 119 | 81.11 241 | 86.41 24 | 87.41 132 | 96.21 20 | 73.61 174 | 90.61 187 | 66.33 208 | 96.85 79 | 93.81 97 |
|
VPNet | | | 80.25 187 | 81.68 165 | 75.94 258 | 92.46 84 | 47.98 314 | 76.70 261 | 81.67 239 | 73.45 153 | 84.87 170 | 92.82 107 | 74.66 165 | 86.51 246 | 61.66 241 | 96.85 79 | 93.33 108 |
|
SixPastTwentyTwo | | | 87.20 77 | 87.45 74 | 86.45 91 | 92.52 82 | 69.19 159 | 87.84 86 | 88.05 176 | 81.66 61 | 94.64 14 | 96.53 15 | 65.94 221 | 94.75 59 | 83.02 63 | 96.83 81 | 95.41 50 |
|
VPA-MVSNet | | | 83.47 146 | 84.73 116 | 79.69 212 | 90.29 140 | 57.52 258 | 81.30 207 | 88.69 165 | 76.29 116 | 87.58 129 | 94.44 61 | 80.60 106 | 87.20 235 | 66.60 207 | 96.82 82 | 94.34 78 |
|
Gipuma | | | 84.44 121 | 86.33 89 | 78.78 222 | 84.20 243 | 73.57 114 | 89.55 58 | 90.44 132 | 84.24 33 | 84.38 178 | 94.89 45 | 76.35 151 | 80.40 288 | 76.14 128 | 96.80 83 | 82.36 287 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
CDPH-MVS | | | 86.17 93 | 85.54 105 | 88.05 73 | 92.25 91 | 75.45 105 | 83.85 146 | 92.01 94 | 65.91 223 | 86.19 152 | 91.75 138 | 83.77 66 | 94.98 54 | 77.43 119 | 96.71 84 | 93.73 98 |
|
DP-MVS | | | 88.60 64 | 89.01 59 | 87.36 80 | 91.30 117 | 77.50 86 | 87.55 88 | 92.97 71 | 87.95 18 | 89.62 94 | 92.87 106 | 84.56 60 | 93.89 86 | 77.65 115 | 96.62 85 | 90.70 178 |
|
testtj | | | 89.51 52 | 89.48 54 | 89.59 54 | 92.26 90 | 80.80 60 | 90.14 44 | 93.54 45 | 83.37 41 | 90.57 76 | 92.55 116 | 84.99 58 | 96.15 5 | 81.26 76 | 96.61 86 | 91.83 154 |
|
TransMVSNet (Re) | | | 84.02 134 | 85.74 101 | 78.85 221 | 91.00 127 | 55.20 276 | 82.29 188 | 87.26 186 | 79.65 81 | 88.38 119 | 95.52 32 | 83.00 73 | 86.88 240 | 67.97 199 | 96.60 87 | 94.45 75 |
|
ambc | | | | | 82.98 164 | 90.55 137 | 64.86 187 | 88.20 80 | 89.15 161 | | 89.40 101 | 93.96 82 | 71.67 200 | 91.38 165 | 78.83 103 | 96.55 88 | 92.71 127 |
|
train_agg | | | 85.98 96 | 85.28 109 | 88.07 72 | 92.34 87 | 79.70 67 | 83.94 142 | 90.32 136 | 65.79 224 | 84.49 176 | 90.97 155 | 81.93 92 | 93.63 96 | 81.21 77 | 96.54 89 | 90.88 174 |
|
VDD-MVS | | | 84.23 129 | 84.58 124 | 83.20 160 | 91.17 124 | 65.16 186 | 83.25 165 | 84.97 221 | 79.79 78 | 87.18 133 | 94.27 68 | 74.77 163 | 90.89 178 | 69.24 185 | 96.54 89 | 93.55 107 |
|
HPM-MVS++ | | | 88.93 62 | 88.45 67 | 90.38 42 | 94.92 35 | 85.85 25 | 89.70 52 | 91.27 114 | 78.20 101 | 86.69 143 | 92.28 124 | 80.36 109 | 95.06 52 | 86.17 35 | 96.49 91 | 90.22 189 |
|
test_djsdf | | | 89.62 49 | 89.01 59 | 91.45 23 | 92.36 86 | 82.98 49 | 91.98 27 | 90.08 147 | 71.54 179 | 94.28 21 | 96.54 14 | 81.57 98 | 94.27 68 | 86.26 31 | 96.49 91 | 97.09 20 |
|
test9_res | | | | | | | | | | | | | | | 80.83 83 | 96.45 93 | 90.57 181 |
|
Anonymous20240529 | | | 86.20 92 | 87.13 77 | 83.42 156 | 90.19 142 | 64.55 191 | 84.55 131 | 90.71 125 | 85.85 26 | 89.94 85 | 95.24 38 | 82.13 86 | 90.40 191 | 69.19 188 | 96.40 94 | 95.31 53 |
|
agg_prior1 | | | 85.72 99 | 85.20 110 | 87.28 81 | 91.58 110 | 77.69 83 | 83.69 152 | 90.30 140 | 66.29 220 | 84.32 180 | 91.07 152 | 82.13 86 | 93.18 116 | 81.02 79 | 96.36 95 | 90.98 170 |
|
anonymousdsp | | | 89.73 48 | 88.88 62 | 92.27 7 | 89.82 149 | 86.67 12 | 90.51 41 | 90.20 146 | 69.87 194 | 95.06 11 | 96.14 22 | 84.28 62 | 93.07 123 | 87.68 12 | 96.34 96 | 97.09 20 |
|
PHI-MVS | | | 86.38 87 | 85.81 100 | 88.08 71 | 88.44 169 | 77.34 89 | 89.35 65 | 93.05 65 | 73.15 163 | 84.76 172 | 87.70 209 | 78.87 121 | 94.18 74 | 80.67 86 | 96.29 97 | 92.73 126 |
|
PS-MVSNAJss | | | 88.31 66 | 87.90 70 | 89.56 55 | 93.31 64 | 77.96 81 | 87.94 84 | 91.97 96 | 70.73 185 | 94.19 22 | 96.67 12 | 76.94 142 | 94.57 64 | 83.07 61 | 96.28 98 | 96.15 32 |
|
v10 | | | 86.54 84 | 87.10 78 | 84.84 122 | 88.16 175 | 63.28 203 | 86.64 105 | 92.20 90 | 75.42 133 | 92.81 41 | 94.50 58 | 74.05 169 | 94.06 81 | 83.88 53 | 96.28 98 | 97.17 19 |
|
CNVR-MVS | | | 87.81 73 | 87.68 72 | 88.21 70 | 92.87 74 | 77.30 91 | 85.25 120 | 91.23 115 | 77.31 109 | 87.07 138 | 91.47 144 | 82.94 74 | 94.71 60 | 84.67 47 | 96.27 100 | 92.62 131 |
|
114514_t | | | 83.10 152 | 82.54 156 | 84.77 124 | 92.90 73 | 69.10 161 | 86.65 104 | 90.62 129 | 54.66 285 | 81.46 219 | 90.81 162 | 76.98 141 | 94.38 67 | 72.62 158 | 96.18 101 | 90.82 176 |
|
agg_prior2 | | | | | | | | | | | | | | | 79.68 94 | 96.16 102 | 90.22 189 |
|
AllTest | | | 87.97 70 | 87.40 76 | 89.68 50 | 91.59 107 | 83.40 45 | 89.50 61 | 95.44 5 | 79.47 82 | 88.00 124 | 93.03 98 | 82.66 77 | 91.47 159 | 70.81 169 | 96.14 103 | 94.16 82 |
|
TestCases | | | | | 89.68 50 | 91.59 107 | 83.40 45 | | 95.44 5 | 79.47 82 | 88.00 124 | 93.03 98 | 82.66 77 | 91.47 159 | 70.81 169 | 96.14 103 | 94.16 82 |
|
EPNet | | | 80.37 185 | 78.41 200 | 86.23 97 | 76.75 301 | 73.28 116 | 87.18 93 | 77.45 258 | 76.24 118 | 68.14 302 | 88.93 193 | 65.41 223 | 93.85 87 | 69.47 183 | 96.12 105 | 91.55 164 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
pm-mvs1 | | | 83.69 140 | 84.95 114 | 79.91 208 | 90.04 147 | 59.66 243 | 82.43 184 | 87.44 183 | 75.52 130 | 87.85 126 | 95.26 37 | 81.25 102 | 85.65 258 | 68.74 193 | 96.04 106 | 94.42 76 |
|
mvs_tets | | | 89.78 47 | 89.27 57 | 91.30 26 | 93.51 58 | 84.79 36 | 89.89 50 | 90.63 128 | 70.00 193 | 94.55 15 | 96.67 12 | 87.94 32 | 93.59 100 | 84.27 50 | 95.97 107 | 95.52 48 |
|
DeepPCF-MVS | | 81.24 5 | 87.28 76 | 86.21 93 | 90.49 40 | 91.48 114 | 84.90 34 | 83.41 160 | 92.38 87 | 70.25 191 | 89.35 102 | 90.68 166 | 82.85 75 | 94.57 64 | 79.55 95 | 95.95 108 | 92.00 148 |
|
jajsoiax | | | 89.41 53 | 88.81 64 | 91.19 30 | 93.38 62 | 84.72 37 | 89.70 52 | 90.29 143 | 69.27 197 | 94.39 17 | 96.38 16 | 86.02 53 | 93.52 104 | 83.96 52 | 95.92 109 | 95.34 51 |
|
ANet_high | | | 83.17 151 | 85.68 103 | 75.65 259 | 81.24 269 | 45.26 320 | 79.94 221 | 92.91 72 | 83.83 37 | 91.33 65 | 96.88 11 | 80.25 110 | 85.92 254 | 68.89 191 | 95.89 110 | 95.76 42 |
|
3Dnovator+ | | 83.92 2 | 89.97 44 | 89.66 50 | 90.92 33 | 91.27 120 | 81.66 55 | 91.25 33 | 94.13 24 | 88.89 11 | 88.83 109 | 94.26 69 | 77.55 133 | 95.86 16 | 84.88 44 | 95.87 111 | 95.24 56 |
|
HQP_MVS | | | 87.75 74 | 87.43 75 | 88.70 65 | 93.45 59 | 76.42 100 | 89.45 63 | 93.61 42 | 79.44 84 | 86.55 145 | 92.95 103 | 74.84 160 | 95.22 45 | 80.78 84 | 95.83 112 | 94.46 73 |
|
plane_prior5 | | | | | | | | | 93.61 42 | | | | | 95.22 45 | 80.78 84 | 95.83 112 | 94.46 73 |
|
DeepC-MVS_fast | | 80.27 8 | 86.23 90 | 85.65 104 | 87.96 74 | 91.30 117 | 76.92 93 | 87.19 92 | 91.99 95 | 70.56 186 | 84.96 167 | 90.69 165 | 80.01 112 | 95.14 48 | 78.37 106 | 95.78 114 | 91.82 155 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
LFMVS | | | 80.15 190 | 80.56 178 | 78.89 220 | 89.19 156 | 55.93 268 | 85.22 121 | 73.78 282 | 82.96 47 | 84.28 183 | 92.72 111 | 57.38 262 | 90.07 203 | 63.80 225 | 95.75 115 | 90.68 179 |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 95.74 116 | |
|
原ACMM1 | | | | | 84.60 128 | 92.81 78 | 74.01 112 | | 91.50 107 | 62.59 242 | 82.73 201 | 90.67 167 | 76.53 149 | 94.25 70 | 69.24 185 | 95.69 117 | 85.55 247 |
|
tfpnnormal | | | 81.79 168 | 82.95 149 | 78.31 231 | 88.93 161 | 55.40 272 | 80.83 214 | 82.85 230 | 76.81 113 | 85.90 157 | 94.14 73 | 74.58 166 | 86.51 246 | 66.82 206 | 95.68 118 | 93.01 117 |
|
TAPA-MVS | | 77.73 12 | 85.71 100 | 84.83 115 | 88.37 68 | 88.78 163 | 79.72 66 | 87.15 94 | 93.50 46 | 69.17 198 | 85.80 158 | 89.56 185 | 80.76 104 | 92.13 141 | 73.21 155 | 95.51 119 | 93.25 111 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
LS3D | | | 90.60 30 | 90.34 44 | 91.38 25 | 89.03 158 | 84.23 42 | 93.58 5 | 94.68 12 | 90.65 6 | 90.33 78 | 93.95 85 | 84.50 61 | 95.37 39 | 80.87 82 | 95.50 120 | 94.53 72 |
|
v8 | | | 86.22 91 | 86.83 85 | 84.36 133 | 87.82 180 | 62.35 217 | 86.42 108 | 91.33 112 | 76.78 114 | 92.73 42 | 94.48 60 | 73.41 179 | 93.72 93 | 83.10 60 | 95.41 121 | 97.01 22 |
|
Vis-MVSNet (Re-imp) | | | 77.82 205 | 77.79 203 | 77.92 238 | 88.82 162 | 51.29 301 | 83.28 163 | 71.97 296 | 74.04 146 | 82.23 207 | 89.78 182 | 57.38 262 | 89.41 211 | 57.22 265 | 95.41 121 | 93.05 116 |
|
FMVSNet1 | | | 84.55 118 | 85.45 107 | 81.85 184 | 90.27 141 | 61.05 230 | 86.83 99 | 88.27 173 | 78.57 98 | 89.66 93 | 95.64 29 | 75.43 154 | 90.68 184 | 69.09 189 | 95.33 123 | 93.82 94 |
|
test12 | | | | | 86.57 88 | 90.74 131 | 72.63 120 | | 90.69 126 | | 82.76 200 | | 79.20 118 | 94.80 58 | | 95.32 124 | 92.27 140 |
|
NCCC | | | 87.36 75 | 86.87 84 | 88.83 63 | 92.32 89 | 78.84 75 | 86.58 106 | 91.09 119 | 78.77 94 | 84.85 171 | 90.89 159 | 80.85 103 | 95.29 41 | 81.14 78 | 95.32 124 | 92.34 137 |
|
Patchmtry | | | 76.56 219 | 77.46 204 | 73.83 267 | 79.37 287 | 46.60 317 | 82.41 185 | 76.90 260 | 73.81 149 | 85.56 162 | 92.38 119 | 48.07 289 | 83.98 273 | 63.36 228 | 95.31 126 | 90.92 173 |
|
XVG-OURS | | | 89.18 57 | 88.83 63 | 90.23 45 | 94.28 44 | 86.11 20 | 85.91 111 | 93.60 44 | 80.16 76 | 89.13 105 | 93.44 93 | 83.82 64 | 90.98 173 | 83.86 54 | 95.30 127 | 93.60 103 |
|
TSAR-MVS + GP. | | | 83.95 136 | 82.69 152 | 87.72 75 | 89.27 154 | 81.45 56 | 83.72 151 | 81.58 240 | 74.73 139 | 85.66 159 | 86.06 232 | 72.56 191 | 92.69 132 | 75.44 133 | 95.21 128 | 89.01 211 |
|
test_0402 | | | 88.65 63 | 89.58 53 | 85.88 107 | 92.55 81 | 72.22 130 | 84.01 141 | 89.44 158 | 88.63 14 | 94.38 18 | 95.77 25 | 86.38 50 | 93.59 100 | 79.84 92 | 95.21 128 | 91.82 155 |
|
TinyColmap | | | 81.25 173 | 82.34 159 | 77.99 237 | 85.33 226 | 60.68 235 | 82.32 187 | 88.33 171 | 71.26 181 | 86.97 140 | 92.22 127 | 77.10 139 | 86.98 239 | 62.37 233 | 95.17 130 | 86.31 240 |
|
Anonymous202405211 | | | 80.51 183 | 81.19 173 | 78.49 228 | 88.48 167 | 57.26 260 | 76.63 262 | 82.49 232 | 81.21 65 | 84.30 182 | 92.24 126 | 67.99 212 | 86.24 250 | 62.22 234 | 95.13 131 | 91.98 151 |
|
tttt0517 | | | 81.07 174 | 79.58 190 | 85.52 113 | 88.99 160 | 66.45 178 | 87.03 96 | 75.51 271 | 73.76 150 | 88.32 121 | 90.20 175 | 37.96 327 | 94.16 79 | 79.36 100 | 95.13 131 | 95.93 41 |
|
DP-MVS Recon | | | 84.05 133 | 83.22 144 | 86.52 90 | 91.73 105 | 75.27 106 | 83.23 167 | 92.40 85 | 72.04 176 | 82.04 210 | 88.33 199 | 77.91 129 | 93.95 85 | 66.17 209 | 95.12 133 | 90.34 188 |
|
PCF-MVS | | 74.62 15 | 82.15 163 | 80.92 176 | 85.84 108 | 89.43 151 | 72.30 128 | 80.53 215 | 91.82 100 | 57.36 274 | 87.81 127 | 89.92 181 | 77.67 131 | 93.63 96 | 58.69 257 | 95.08 134 | 91.58 163 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
CSCG | | | 86.26 89 | 86.47 88 | 85.60 112 | 90.87 129 | 74.26 111 | 87.98 83 | 91.85 99 | 80.35 73 | 89.54 100 | 88.01 203 | 79.09 119 | 92.13 141 | 75.51 131 | 95.06 135 | 90.41 186 |
|
plane_prior | | | | | | | 76.42 100 | 87.15 94 | | 75.94 125 | | | | | | 95.03 136 | |
|
new-patchmatchnet | | | 70.10 269 | 73.37 242 | 60.29 312 | 81.23 270 | 16.95 336 | 59.54 322 | 74.62 274 | 62.93 240 | 80.97 224 | 87.93 206 | 62.83 233 | 71.90 307 | 55.24 277 | 95.01 137 | 92.00 148 |
|
v1192 | | | 84.57 117 | 84.69 120 | 84.21 137 | 87.75 182 | 62.88 207 | 83.02 172 | 91.43 109 | 69.08 200 | 89.98 84 | 90.89 159 | 72.70 189 | 93.62 99 | 82.41 67 | 94.97 138 | 96.13 33 |
|
v1921920 | | | 84.23 129 | 84.37 130 | 83.79 146 | 87.64 186 | 61.71 221 | 82.91 175 | 91.20 116 | 67.94 210 | 90.06 80 | 90.34 172 | 72.04 196 | 93.59 100 | 82.32 69 | 94.91 139 | 96.07 35 |
|
v144192 | | | 84.24 128 | 84.41 128 | 83.71 149 | 87.59 187 | 61.57 223 | 82.95 174 | 91.03 120 | 67.82 213 | 89.80 89 | 90.49 170 | 73.28 182 | 93.51 105 | 81.88 74 | 94.89 140 | 96.04 37 |
|
testing_2 | | | 84.36 122 | 84.64 122 | 83.50 155 | 86.74 205 | 63.97 197 | 84.56 130 | 90.31 138 | 66.22 221 | 91.62 59 | 94.55 56 | 75.88 152 | 91.95 147 | 77.02 124 | 94.89 140 | 94.56 68 |
|
LCM-MVSNet-Re | | | 83.48 145 | 85.06 111 | 78.75 223 | 85.94 221 | 55.75 271 | 80.05 219 | 94.27 15 | 76.47 115 | 96.09 5 | 94.54 57 | 83.31 71 | 89.75 207 | 59.95 252 | 94.89 140 | 90.75 177 |
|
v1240 | | | 84.30 126 | 84.51 126 | 83.65 150 | 87.65 185 | 61.26 227 | 82.85 176 | 91.54 106 | 67.94 210 | 90.68 75 | 90.65 168 | 71.71 199 | 93.64 95 | 82.84 65 | 94.78 143 | 96.07 35 |
|
MSLP-MVS++ | | | 85.00 111 | 86.03 96 | 81.90 182 | 91.84 103 | 71.56 140 | 86.75 103 | 93.02 69 | 75.95 124 | 87.12 134 | 89.39 186 | 77.98 127 | 89.40 212 | 77.46 117 | 94.78 143 | 84.75 256 |
|
IterMVS-LS | | | 84.73 114 | 84.98 113 | 83.96 143 | 87.35 190 | 63.66 198 | 83.25 165 | 89.88 151 | 76.06 119 | 89.62 94 | 92.37 122 | 73.40 181 | 92.52 135 | 78.16 110 | 94.77 145 | 95.69 43 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
AdaColmap | | | 83.66 141 | 83.69 140 | 83.57 153 | 90.05 146 | 72.26 129 | 86.29 110 | 90.00 149 | 78.19 102 | 81.65 217 | 87.16 218 | 83.40 70 | 94.24 71 | 61.69 240 | 94.76 146 | 84.21 261 |
|
ITE_SJBPF | | | | | 90.11 47 | 90.72 132 | 84.97 33 | | 90.30 140 | 81.56 62 | 90.02 81 | 91.20 148 | 82.40 80 | 90.81 180 | 73.58 147 | 94.66 147 | 94.56 68 |
|
v1144 | | | 84.54 120 | 84.72 118 | 84.00 141 | 87.67 184 | 62.55 213 | 82.97 173 | 90.93 122 | 70.32 190 | 89.80 89 | 90.99 154 | 73.50 176 | 93.48 106 | 81.69 75 | 94.65 148 | 95.97 38 |
|
test20.03 | | | 73.75 244 | 74.59 231 | 71.22 281 | 81.11 271 | 51.12 303 | 70.15 301 | 72.10 295 | 70.42 187 | 80.28 236 | 91.50 143 | 64.21 225 | 74.72 304 | 46.96 312 | 94.58 149 | 87.82 226 |
|
TSAR-MVS + MP. | | | 88.14 68 | 87.82 71 | 89.09 61 | 95.72 20 | 76.74 96 | 92.49 22 | 91.19 117 | 67.85 212 | 86.63 144 | 94.84 47 | 79.58 117 | 95.96 10 | 87.62 13 | 94.50 150 | 94.56 68 |
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition |
HQP3-MVS | | | | | | | | | 92.68 80 | | | | | | | 94.47 151 | |
|
HQP-MVS | | | 84.61 116 | 84.06 134 | 86.27 96 | 91.19 121 | 70.66 144 | 84.77 124 | 92.68 80 | 73.30 158 | 80.55 232 | 90.17 178 | 72.10 193 | 94.61 62 | 77.30 120 | 94.47 151 | 93.56 105 |
|
MCST-MVS | | | 84.36 122 | 83.93 137 | 85.63 111 | 91.59 107 | 71.58 139 | 83.52 155 | 92.13 91 | 61.82 248 | 83.96 186 | 89.75 183 | 79.93 115 | 93.46 107 | 78.33 108 | 94.34 153 | 91.87 153 |
|
thisisatest0530 | | | 79.07 195 | 77.33 206 | 84.26 136 | 87.13 195 | 64.58 189 | 83.66 153 | 75.95 266 | 68.86 203 | 85.22 165 | 87.36 216 | 38.10 325 | 93.57 103 | 75.47 132 | 94.28 154 | 94.62 67 |
|
baseline | | | 85.20 105 | 85.93 97 | 83.02 163 | 86.30 213 | 62.37 216 | 84.55 131 | 93.96 29 | 74.48 143 | 87.12 134 | 92.03 128 | 82.30 82 | 91.94 148 | 78.39 105 | 94.21 155 | 94.74 66 |
|
alignmvs | | | 83.94 137 | 83.98 136 | 83.80 145 | 87.80 181 | 67.88 168 | 84.54 133 | 91.42 111 | 73.27 161 | 88.41 118 | 87.96 204 | 72.33 192 | 90.83 179 | 76.02 129 | 94.11 156 | 92.69 128 |
|
USDC | | | 76.63 217 | 76.73 212 | 76.34 255 | 83.46 252 | 57.20 261 | 80.02 220 | 88.04 177 | 52.14 300 | 83.65 190 | 91.25 146 | 63.24 231 | 86.65 245 | 54.66 281 | 94.11 156 | 85.17 251 |
|
MVS_111021_HR | | | 84.63 115 | 84.34 131 | 85.49 115 | 90.18 143 | 75.86 104 | 79.23 235 | 87.13 191 | 73.35 155 | 85.56 162 | 89.34 187 | 83.60 68 | 90.50 189 | 76.64 126 | 94.05 158 | 90.09 194 |
|
VNet | | | 79.31 194 | 80.27 183 | 76.44 253 | 87.92 178 | 53.95 281 | 75.58 275 | 84.35 225 | 74.39 144 | 82.23 207 | 90.72 164 | 72.84 187 | 84.39 269 | 60.38 251 | 93.98 159 | 90.97 171 |
|
FMVSNet2 | | | 81.31 171 | 81.61 167 | 80.41 202 | 86.38 208 | 58.75 252 | 83.93 144 | 86.58 198 | 72.43 171 | 87.65 128 | 92.98 100 | 63.78 228 | 90.22 196 | 66.86 203 | 93.92 160 | 92.27 140 |
|
LF4IMVS | | | 82.75 154 | 81.93 164 | 85.19 117 | 82.08 261 | 80.15 63 | 85.53 117 | 88.76 164 | 68.01 207 | 85.58 161 | 87.75 208 | 71.80 198 | 86.85 241 | 74.02 141 | 93.87 161 | 88.58 215 |
|
canonicalmvs | | | 85.50 101 | 86.14 94 | 83.58 152 | 87.97 176 | 67.13 171 | 87.55 88 | 94.32 14 | 73.44 154 | 88.47 116 | 87.54 212 | 86.45 48 | 91.06 172 | 75.76 130 | 93.76 162 | 92.54 133 |
|
v2v482 | | | 84.09 131 | 84.24 132 | 83.62 151 | 87.13 195 | 61.40 224 | 82.71 179 | 89.71 153 | 72.19 175 | 89.55 98 | 91.41 145 | 70.70 204 | 93.20 115 | 81.02 79 | 93.76 162 | 96.25 31 |
|
casdiffmvs | | | 85.21 104 | 85.85 99 | 83.31 158 | 86.17 218 | 62.77 209 | 83.03 171 | 93.93 30 | 74.69 140 | 88.21 122 | 92.68 112 | 82.29 83 | 91.89 151 | 77.87 114 | 93.75 164 | 95.27 55 |
|
UGNet | | | 82.78 153 | 81.64 166 | 86.21 100 | 86.20 217 | 76.24 103 | 86.86 97 | 85.68 206 | 77.07 111 | 73.76 281 | 92.82 107 | 69.64 205 | 91.82 155 | 69.04 190 | 93.69 165 | 90.56 182 |
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 |
旧先验1 | | | | | | 91.97 98 | 71.77 134 | | 81.78 238 | | | 91.84 133 | 73.92 170 | | | 93.65 166 | 83.61 269 |
|
MVS_111021_LR | | | 84.28 127 | 83.76 139 | 85.83 109 | 89.23 155 | 83.07 48 | 80.99 211 | 83.56 226 | 72.71 169 | 86.07 153 | 89.07 191 | 81.75 97 | 86.19 251 | 77.11 122 | 93.36 167 | 88.24 216 |
|
GBi-Net | | | 82.02 165 | 82.07 161 | 81.85 184 | 86.38 208 | 61.05 230 | 86.83 99 | 88.27 173 | 72.43 171 | 86.00 154 | 95.64 29 | 63.78 228 | 90.68 184 | 65.95 210 | 93.34 168 | 93.82 94 |
|
test1 | | | 82.02 165 | 82.07 161 | 81.85 184 | 86.38 208 | 61.05 230 | 86.83 99 | 88.27 173 | 72.43 171 | 86.00 154 | 95.64 29 | 63.78 228 | 90.68 184 | 65.95 210 | 93.34 168 | 93.82 94 |
|
FMVSNet3 | | | 78.80 197 | 78.55 197 | 79.57 214 | 82.89 259 | 56.89 264 | 81.76 197 | 85.77 205 | 69.04 201 | 86.00 154 | 90.44 171 | 51.75 280 | 90.09 202 | 65.95 210 | 93.34 168 | 91.72 157 |
|
CS-MVS | | | 83.43 148 | 83.04 148 | 84.59 129 | 87.87 179 | 66.61 176 | 85.57 116 | 94.90 10 | 73.02 165 | 81.12 223 | 78.56 303 | 80.00 113 | 95.52 32 | 73.04 156 | 93.29 171 | 91.62 161 |
|
K. test v3 | | | 85.14 106 | 84.73 116 | 86.37 92 | 91.13 125 | 69.63 153 | 85.45 118 | 76.68 263 | 84.06 36 | 92.44 47 | 96.99 9 | 62.03 234 | 94.65 61 | 80.58 87 | 93.24 172 | 94.83 65 |
|
Anonymous20231206 | | | 71.38 262 | 71.88 256 | 69.88 282 | 86.31 212 | 54.37 278 | 70.39 300 | 74.62 274 | 52.57 296 | 76.73 257 | 88.76 194 | 59.94 245 | 72.06 306 | 44.35 317 | 93.23 173 | 83.23 277 |
|
D2MVS | | | 76.84 215 | 75.67 223 | 80.34 203 | 80.48 280 | 62.16 220 | 73.50 288 | 84.80 223 | 57.61 272 | 82.24 206 | 87.54 212 | 51.31 281 | 87.65 231 | 70.40 178 | 93.19 174 | 91.23 168 |
|
miper_lstm_enhance | | | 76.45 221 | 76.10 217 | 77.51 242 | 76.72 302 | 60.97 233 | 64.69 316 | 85.04 218 | 63.98 236 | 83.20 195 | 88.22 200 | 56.67 265 | 78.79 293 | 73.22 150 | 93.12 175 | 92.78 125 |
|
新几何1 | | | | | 82.95 165 | 93.96 50 | 78.56 78 | | 80.24 246 | 55.45 281 | 83.93 187 | 91.08 151 | 71.19 202 | 88.33 225 | 65.84 213 | 93.07 176 | 81.95 292 |
|
1121 | | | 80.86 177 | 79.81 189 | 84.02 140 | 93.93 51 | 78.70 76 | 81.64 200 | 80.18 247 | 55.43 282 | 83.67 189 | 91.15 149 | 71.29 201 | 91.41 163 | 67.95 200 | 93.06 177 | 81.96 291 |
|
lessismore_v0 | | | | | 85.95 104 | 91.10 126 | 70.99 143 | | 70.91 303 | | 91.79 56 | 94.42 62 | 61.76 235 | 92.93 126 | 79.52 98 | 93.03 178 | 93.93 89 |
|
TAMVS | | | 78.08 204 | 76.36 214 | 83.23 159 | 90.62 134 | 72.87 118 | 79.08 236 | 80.01 249 | 61.72 250 | 81.35 221 | 86.92 221 | 63.96 227 | 88.78 220 | 50.61 296 | 93.01 179 | 88.04 220 |
|
EIA-MVS | | | 84.31 125 | 83.91 138 | 85.52 113 | 88.58 165 | 70.40 146 | 84.50 135 | 93.37 48 | 78.76 95 | 84.07 185 | 78.72 302 | 80.39 108 | 95.13 49 | 73.82 145 | 92.98 180 | 91.04 169 |
|
EPNet_dtu | | | 72.87 251 | 71.33 262 | 77.49 243 | 77.72 295 | 60.55 236 | 82.35 186 | 75.79 267 | 66.49 219 | 58.39 330 | 81.06 289 | 53.68 277 | 85.98 253 | 53.55 285 | 92.97 181 | 85.95 243 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
Effi-MVS+-dtu | | | 85.82 98 | 83.38 142 | 93.14 3 | 87.13 195 | 91.15 2 | 87.70 87 | 88.42 168 | 74.57 141 | 83.56 191 | 85.65 235 | 78.49 123 | 94.21 72 | 72.04 163 | 92.88 182 | 94.05 85 |
|
CANet | | | 83.79 139 | 82.85 150 | 86.63 87 | 86.17 218 | 72.21 131 | 83.76 150 | 91.43 109 | 77.24 110 | 74.39 278 | 87.45 214 | 75.36 155 | 95.42 37 | 77.03 123 | 92.83 183 | 92.25 142 |
|
API-MVS | | | 82.28 160 | 82.61 154 | 81.30 190 | 86.29 214 | 69.79 148 | 88.71 76 | 87.67 182 | 78.42 100 | 82.15 209 | 84.15 260 | 77.98 127 | 91.59 157 | 65.39 216 | 92.75 184 | 82.51 286 |
|
test_yl | | | 78.71 199 | 78.51 198 | 79.32 217 | 84.32 238 | 58.84 249 | 78.38 243 | 85.33 210 | 75.99 122 | 82.49 202 | 86.57 223 | 58.01 256 | 90.02 204 | 62.74 231 | 92.73 185 | 89.10 206 |
|
DCV-MVSNet | | | 78.71 199 | 78.51 198 | 79.32 217 | 84.32 238 | 58.84 249 | 78.38 243 | 85.33 210 | 75.99 122 | 82.49 202 | 86.57 223 | 58.01 256 | 90.02 204 | 62.74 231 | 92.73 185 | 89.10 206 |
|
Regformer-1 | | | 86.00 94 | 85.50 106 | 87.49 78 | 84.18 244 | 76.90 94 | 83.52 155 | 87.94 180 | 82.18 55 | 89.19 103 | 85.07 248 | 82.28 84 | 91.89 151 | 82.40 68 | 92.72 187 | 93.69 100 |
|
Regformer-2 | | | 86.74 82 | 86.08 95 | 88.73 64 | 84.18 244 | 79.20 71 | 83.52 155 | 89.33 159 | 83.33 42 | 89.92 86 | 85.07 248 | 83.23 72 | 93.16 118 | 83.39 57 | 92.72 187 | 93.83 92 |
|
testgi | | | 72.36 254 | 74.61 229 | 65.59 299 | 80.56 279 | 42.82 326 | 68.29 306 | 73.35 286 | 66.87 216 | 81.84 213 | 89.93 180 | 72.08 195 | 66.92 320 | 46.05 314 | 92.54 189 | 87.01 234 |
|
FMVSNet5 | | | 72.10 257 | 71.69 257 | 73.32 268 | 81.57 266 | 53.02 288 | 76.77 260 | 78.37 254 | 63.31 238 | 76.37 259 | 91.85 132 | 36.68 329 | 78.98 291 | 47.87 308 | 92.45 190 | 87.95 222 |
|
CDS-MVSNet | | | 77.32 210 | 75.40 224 | 83.06 162 | 89.00 159 | 72.48 125 | 77.90 250 | 82.17 235 | 60.81 255 | 78.94 246 | 83.49 265 | 59.30 250 | 88.76 221 | 54.64 282 | 92.37 191 | 87.93 223 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
CNLPA | | | 83.55 144 | 83.10 147 | 84.90 121 | 89.34 153 | 83.87 43 | 84.54 133 | 88.77 163 | 79.09 88 | 83.54 192 | 88.66 197 | 74.87 159 | 81.73 283 | 66.84 205 | 92.29 192 | 89.11 205 |
|
F-COLMAP | | | 84.97 112 | 83.42 141 | 89.63 52 | 92.39 85 | 83.40 45 | 88.83 73 | 91.92 98 | 73.19 162 | 80.18 237 | 89.15 189 | 77.04 140 | 93.28 113 | 65.82 214 | 92.28 193 | 92.21 143 |
|
thres600view7 | | | 75.97 225 | 75.35 226 | 77.85 240 | 87.01 201 | 51.84 298 | 80.45 216 | 73.26 287 | 75.20 135 | 83.10 197 | 86.31 229 | 45.54 302 | 89.05 213 | 55.03 279 | 92.24 194 | 92.66 129 |
|
PVSNet_BlendedMVS | | | 78.80 197 | 77.84 202 | 81.65 188 | 84.43 234 | 63.41 200 | 79.49 229 | 90.44 132 | 61.70 251 | 75.43 271 | 87.07 220 | 69.11 208 | 91.44 161 | 60.68 249 | 92.24 194 | 90.11 193 |
|
DELS-MVS | | | 81.44 170 | 81.25 171 | 82.03 180 | 84.27 240 | 62.87 208 | 76.47 266 | 92.49 84 | 70.97 183 | 81.64 218 | 83.83 261 | 75.03 157 | 92.70 131 | 74.29 137 | 92.22 196 | 90.51 184 |
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 |
testdata | | | | | 79.54 215 | 92.87 74 | 72.34 127 | | 80.14 248 | 59.91 262 | 85.47 164 | 91.75 138 | 67.96 213 | 85.24 260 | 68.57 196 | 92.18 197 | 81.06 306 |
|
MVS_0304 | | | 78.17 202 | 77.23 207 | 80.99 196 | 84.13 246 | 69.07 162 | 81.39 204 | 80.81 244 | 76.28 117 | 67.53 307 | 89.11 190 | 62.87 232 | 86.77 243 | 60.90 248 | 92.01 198 | 87.13 232 |
|
DPM-MVS | | | 80.10 191 | 79.18 193 | 82.88 169 | 90.71 133 | 69.74 149 | 78.87 239 | 90.84 123 | 60.29 260 | 75.64 270 | 85.92 234 | 67.28 214 | 93.11 121 | 71.24 167 | 91.79 199 | 85.77 246 |
|
v148 | | | 82.31 159 | 82.48 157 | 81.81 187 | 85.59 223 | 59.66 243 | 81.47 203 | 86.02 203 | 72.85 167 | 88.05 123 | 90.65 168 | 70.73 203 | 90.91 177 | 75.15 134 | 91.79 199 | 94.87 62 |
|
test222 | | | | | | 93.31 64 | 76.54 97 | 79.38 230 | 77.79 256 | 52.59 295 | 82.36 205 | 90.84 161 | 66.83 217 | | | 91.69 201 | 81.25 301 |
|
pmmvs-eth3d | | | 78.42 201 | 77.04 209 | 82.57 175 | 87.44 189 | 74.41 110 | 80.86 213 | 79.67 250 | 55.68 280 | 84.69 173 | 90.31 174 | 60.91 238 | 85.42 259 | 62.20 235 | 91.59 202 | 87.88 224 |
|
Vis-MVSNet | | | 86.86 79 | 86.58 87 | 87.72 75 | 92.09 95 | 77.43 88 | 87.35 91 | 92.09 92 | 78.87 92 | 84.27 184 | 94.05 76 | 78.35 125 | 93.65 94 | 80.54 88 | 91.58 203 | 92.08 146 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
thisisatest0515 | | | 73.00 250 | 70.52 264 | 80.46 201 | 81.45 267 | 59.90 241 | 73.16 291 | 74.31 278 | 57.86 269 | 76.08 265 | 77.78 306 | 37.60 328 | 92.12 143 | 65.00 217 | 91.45 204 | 89.35 200 |
|
ppachtmachnet_test | | | 74.73 238 | 74.00 236 | 76.90 247 | 80.71 277 | 56.89 264 | 71.53 296 | 78.42 253 | 58.24 267 | 79.32 243 | 82.92 273 | 57.91 259 | 84.26 270 | 65.60 215 | 91.36 205 | 89.56 196 |
|
OpenMVS | | 76.72 13 | 81.98 167 | 82.00 163 | 81.93 181 | 84.42 236 | 68.22 165 | 88.50 79 | 89.48 157 | 66.92 215 | 81.80 216 | 91.86 131 | 72.59 190 | 90.16 198 | 71.19 168 | 91.25 206 | 87.40 229 |
|
EG-PatchMatch MVS | | | 84.08 132 | 84.11 133 | 83.98 142 | 92.22 93 | 72.61 121 | 82.20 194 | 87.02 195 | 72.63 170 | 88.86 107 | 91.02 153 | 78.52 122 | 91.11 170 | 73.41 149 | 91.09 207 | 88.21 217 |
|
3Dnovator | | 80.37 7 | 84.80 113 | 84.71 119 | 85.06 120 | 86.36 211 | 74.71 108 | 88.77 75 | 90.00 149 | 75.65 129 | 84.96 167 | 93.17 96 | 74.06 168 | 91.19 167 | 78.28 109 | 91.09 207 | 89.29 203 |
|
Regformer-3 | | | 85.06 108 | 84.67 121 | 86.22 98 | 84.27 240 | 73.43 115 | 84.07 139 | 85.26 212 | 80.77 70 | 88.62 113 | 85.48 238 | 80.56 107 | 90.39 192 | 81.99 72 | 91.04 209 | 94.85 64 |
|
Regformer-4 | | | 86.41 86 | 85.71 102 | 88.52 66 | 84.27 240 | 77.57 85 | 84.07 139 | 88.00 178 | 82.82 49 | 89.84 88 | 85.48 238 | 82.06 88 | 92.77 130 | 83.83 55 | 91.04 209 | 95.22 59 |
|
thres100view900 | | | 75.45 228 | 75.05 227 | 76.66 252 | 87.27 191 | 51.88 296 | 81.07 210 | 73.26 287 | 75.68 128 | 83.25 194 | 86.37 226 | 45.54 302 | 88.80 217 | 51.98 292 | 90.99 211 | 89.31 201 |
|
tfpn200view9 | | | 74.86 236 | 74.23 234 | 76.74 251 | 86.24 215 | 52.12 293 | 79.24 233 | 73.87 280 | 73.34 156 | 81.82 214 | 84.60 256 | 46.02 296 | 88.80 217 | 51.98 292 | 90.99 211 | 89.31 201 |
|
thres400 | | | 75.14 230 | 74.23 234 | 77.86 239 | 86.24 215 | 52.12 293 | 79.24 233 | 73.87 280 | 73.34 156 | 81.82 214 | 84.60 256 | 46.02 296 | 88.80 217 | 51.98 292 | 90.99 211 | 92.66 129 |
|
cascas | | | 76.29 223 | 74.81 228 | 80.72 200 | 84.47 233 | 62.94 206 | 73.89 286 | 87.34 184 | 55.94 279 | 75.16 275 | 76.53 314 | 63.97 226 | 91.16 168 | 65.00 217 | 90.97 214 | 88.06 219 |
|
MSP-MVS | | | 89.08 60 | 88.16 68 | 91.83 19 | 95.76 17 | 86.14 19 | 92.75 14 | 93.90 33 | 78.43 99 | 89.16 104 | 92.25 125 | 72.03 197 | 96.36 2 | 88.21 7 | 90.93 215 | 92.98 118 |
|
ab-mvs | | | 79.67 193 | 80.56 178 | 76.99 245 | 88.48 167 | 56.93 262 | 84.70 127 | 86.06 202 | 68.95 202 | 80.78 228 | 93.08 97 | 75.30 156 | 84.62 267 | 56.78 266 | 90.90 216 | 89.43 199 |
|
MAR-MVS | | | 80.24 188 | 78.74 196 | 84.73 125 | 86.87 204 | 78.18 79 | 85.75 113 | 87.81 181 | 65.67 227 | 77.84 251 | 78.50 304 | 73.79 172 | 90.53 188 | 61.59 243 | 90.87 217 | 85.49 249 |
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 |
EI-MVSNet-Vis-set | | | 85.12 107 | 84.53 125 | 86.88 83 | 84.01 247 | 72.76 119 | 83.91 145 | 85.18 214 | 80.44 71 | 88.75 110 | 85.49 237 | 80.08 111 | 91.92 149 | 82.02 71 | 90.85 218 | 95.97 38 |
|
EI-MVSNet-UG-set | | | 85.04 109 | 84.44 127 | 86.85 84 | 83.87 250 | 72.52 124 | 83.82 147 | 85.15 215 | 80.27 75 | 88.75 110 | 85.45 241 | 79.95 114 | 91.90 150 | 81.92 73 | 90.80 219 | 96.13 33 |
|
XVG-OURS-SEG-HR | | | 89.59 50 | 89.37 55 | 90.28 44 | 94.47 42 | 85.95 21 | 86.84 98 | 93.91 32 | 80.07 77 | 86.75 142 | 93.26 94 | 93.64 2 | 90.93 175 | 84.60 48 | 90.75 220 | 93.97 87 |
|
ET-MVSNet_ETH3D | | | 75.28 229 | 72.77 247 | 82.81 170 | 83.03 258 | 68.11 166 | 77.09 258 | 76.51 264 | 60.67 258 | 77.60 255 | 80.52 291 | 38.04 326 | 91.15 169 | 70.78 171 | 90.68 221 | 89.17 204 |
|
EI-MVSNet | | | 82.61 155 | 82.42 158 | 83.20 160 | 83.25 254 | 63.66 198 | 83.50 158 | 85.07 216 | 76.06 119 | 86.55 145 | 85.10 246 | 73.41 179 | 90.25 193 | 78.15 111 | 90.67 222 | 95.68 44 |
|
MVSTER | | | 77.09 212 | 75.70 222 | 81.25 192 | 75.27 314 | 61.08 229 | 77.49 256 | 85.07 216 | 60.78 256 | 86.55 145 | 88.68 196 | 43.14 316 | 90.25 193 | 73.69 146 | 90.67 222 | 92.42 134 |
|
Patchmatch-RL test | | | 74.48 239 | 73.68 238 | 76.89 248 | 84.83 231 | 66.54 177 | 72.29 293 | 69.16 308 | 57.70 270 | 86.76 141 | 86.33 227 | 45.79 301 | 82.59 280 | 69.63 182 | 90.65 224 | 81.54 297 |
|
CMPMVS | | 59.41 20 | 75.12 232 | 73.57 239 | 79.77 209 | 75.84 308 | 67.22 170 | 81.21 208 | 82.18 234 | 50.78 308 | 76.50 258 | 87.66 210 | 55.20 274 | 82.99 278 | 62.17 237 | 90.64 225 | 89.09 208 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
DI_MVS_plusplus_test | | | 81.27 172 | 81.26 170 | 81.29 191 | 84.98 228 | 61.65 222 | 81.98 196 | 87.25 187 | 63.56 237 | 87.56 130 | 89.60 184 | 73.62 173 | 91.83 154 | 72.20 162 | 90.59 226 | 90.38 187 |
|
V42 | | | 83.47 146 | 83.37 143 | 83.75 148 | 83.16 256 | 63.33 202 | 81.31 205 | 90.23 145 | 69.51 196 | 90.91 72 | 90.81 162 | 74.16 167 | 92.29 139 | 80.06 89 | 90.22 227 | 95.62 46 |
|
PM-MVS | | | 80.20 189 | 79.00 194 | 83.78 147 | 88.17 174 | 86.66 13 | 81.31 205 | 66.81 315 | 69.64 195 | 88.33 120 | 90.19 176 | 64.58 224 | 83.63 276 | 71.99 165 | 90.03 228 | 81.06 306 |
|
PLC | | 73.85 16 | 82.09 164 | 80.31 182 | 87.45 79 | 90.86 130 | 80.29 62 | 85.88 112 | 90.65 127 | 68.17 206 | 76.32 261 | 86.33 227 | 73.12 184 | 92.61 134 | 61.40 244 | 90.02 229 | 89.44 198 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
mvs-test1 | | | 84.55 118 | 82.12 160 | 91.84 18 | 87.13 195 | 89.54 4 | 85.05 123 | 88.42 168 | 74.57 141 | 80.60 229 | 82.98 269 | 78.49 123 | 93.98 84 | 72.04 163 | 89.77 230 | 92.00 148 |
|
CANet_DTU | | | 77.81 206 | 77.05 208 | 80.09 207 | 81.37 268 | 59.90 241 | 83.26 164 | 88.29 172 | 69.16 199 | 67.83 305 | 83.72 262 | 60.93 237 | 89.47 208 | 69.22 187 | 89.70 231 | 90.88 174 |
|
diffmvs | | | 80.40 184 | 80.48 181 | 80.17 206 | 79.02 291 | 60.04 239 | 77.54 254 | 90.28 144 | 66.65 218 | 82.40 204 | 87.33 217 | 73.50 176 | 87.35 234 | 77.98 112 | 89.62 232 | 93.13 114 |
|
PMMVS2 | | | 55.64 305 | 59.27 304 | 44.74 318 | 64.30 334 | 12.32 337 | 40.60 331 | 49.79 334 | 53.19 292 | 65.06 317 | 84.81 252 | 53.60 278 | 49.76 332 | 32.68 331 | 89.41 233 | 72.15 317 |
|
Fast-Effi-MVS+-dtu | | | 82.54 157 | 81.41 169 | 85.90 106 | 85.60 222 | 76.53 99 | 83.07 170 | 89.62 155 | 73.02 165 | 79.11 245 | 83.51 264 | 80.74 105 | 90.24 195 | 68.76 192 | 89.29 234 | 90.94 172 |
|
thres200 | | | 72.34 255 | 71.55 260 | 74.70 264 | 83.48 251 | 51.60 299 | 75.02 279 | 73.71 283 | 70.14 192 | 78.56 249 | 80.57 290 | 46.20 294 | 88.20 227 | 46.99 311 | 89.29 234 | 84.32 260 |
|
jason | | | 77.42 209 | 75.75 221 | 82.43 178 | 87.10 199 | 69.27 155 | 77.99 248 | 81.94 237 | 51.47 304 | 77.84 251 | 85.07 248 | 60.32 242 | 89.00 214 | 70.74 173 | 89.27 236 | 89.03 209 |
jason: jason. |
MG-MVS | | | 80.32 186 | 80.94 175 | 78.47 229 | 88.18 173 | 52.62 291 | 82.29 188 | 85.01 220 | 72.01 177 | 79.24 244 | 92.54 117 | 69.36 206 | 93.36 112 | 70.65 174 | 89.19 237 | 89.45 197 |
|
BH-untuned | | | 80.96 176 | 80.99 174 | 80.84 197 | 88.55 166 | 68.23 164 | 80.33 217 | 88.46 167 | 72.79 168 | 86.55 145 | 86.76 222 | 74.72 164 | 91.77 156 | 61.79 239 | 88.99 238 | 82.52 285 |
|
ETV-MVS | | | 82.19 162 | 81.23 172 | 85.10 119 | 87.95 177 | 69.17 160 | 83.22 168 | 93.33 51 | 70.42 187 | 78.58 248 | 79.77 299 | 77.29 135 | 94.20 73 | 71.51 166 | 88.96 239 | 91.93 152 |
|
PVSNet_Blended_VisFu | | | 81.55 169 | 80.49 180 | 84.70 127 | 91.58 110 | 73.24 117 | 84.21 137 | 91.67 104 | 62.86 241 | 80.94 225 | 87.16 218 | 67.27 215 | 92.87 129 | 69.82 181 | 88.94 240 | 87.99 221 |
|
MVSFormer | | | 82.23 161 | 81.57 168 | 84.19 139 | 85.54 224 | 69.26 156 | 91.98 27 | 90.08 147 | 71.54 179 | 76.23 262 | 85.07 248 | 58.69 253 | 94.27 68 | 86.26 31 | 88.77 241 | 89.03 209 |
|
lupinMVS | | | 76.37 222 | 74.46 232 | 82.09 179 | 85.54 224 | 69.26 156 | 76.79 259 | 80.77 245 | 50.68 310 | 76.23 262 | 82.82 274 | 58.69 253 | 88.94 215 | 69.85 180 | 88.77 241 | 88.07 218 |
|
RPSCF | | | 88.00 69 | 86.93 83 | 91.22 29 | 90.08 144 | 89.30 5 | 89.68 54 | 91.11 118 | 79.26 86 | 89.68 92 | 94.81 51 | 82.44 79 | 87.74 230 | 76.54 127 | 88.74 243 | 96.61 28 |
|
PAPM_NR | | | 83.23 149 | 83.19 146 | 83.33 157 | 90.90 128 | 65.98 180 | 88.19 81 | 90.78 124 | 78.13 103 | 80.87 227 | 87.92 207 | 73.49 178 | 92.42 136 | 70.07 179 | 88.40 244 | 91.60 162 |
|
xiu_mvs_v1_base_debu | | | 80.84 178 | 80.14 185 | 82.93 166 | 88.31 170 | 71.73 135 | 79.53 226 | 87.17 188 | 65.43 228 | 79.59 239 | 82.73 276 | 76.94 142 | 90.14 199 | 73.22 150 | 88.33 245 | 86.90 235 |
|
xiu_mvs_v1_base | | | 80.84 178 | 80.14 185 | 82.93 166 | 88.31 170 | 71.73 135 | 79.53 226 | 87.17 188 | 65.43 228 | 79.59 239 | 82.73 276 | 76.94 142 | 90.14 199 | 73.22 150 | 88.33 245 | 86.90 235 |
|
xiu_mvs_v1_base_debi | | | 80.84 178 | 80.14 185 | 82.93 166 | 88.31 170 | 71.73 135 | 79.53 226 | 87.17 188 | 65.43 228 | 79.59 239 | 82.73 276 | 76.94 142 | 90.14 199 | 73.22 150 | 88.33 245 | 86.90 235 |
|
XXY-MVS | | | 74.44 241 | 76.19 216 | 69.21 286 | 84.61 232 | 52.43 292 | 71.70 295 | 77.18 259 | 60.73 257 | 80.60 229 | 90.96 157 | 75.44 153 | 69.35 312 | 56.13 270 | 88.33 245 | 85.86 245 |
|
Fast-Effi-MVS+ | | | 81.04 175 | 80.57 177 | 82.46 177 | 87.50 188 | 63.22 204 | 78.37 245 | 89.63 154 | 68.01 207 | 81.87 212 | 82.08 281 | 82.31 81 | 92.65 133 | 67.10 202 | 88.30 249 | 91.51 165 |
|
MDA-MVSNet-bldmvs | | | 77.47 208 | 76.90 210 | 79.16 219 | 79.03 290 | 64.59 188 | 66.58 313 | 75.67 269 | 73.15 163 | 88.86 107 | 88.99 192 | 66.94 216 | 81.23 285 | 64.71 219 | 88.22 250 | 91.64 160 |
|
PAPR | | | 78.84 196 | 78.10 201 | 81.07 194 | 85.17 227 | 60.22 238 | 82.21 192 | 90.57 130 | 62.51 243 | 75.32 273 | 84.61 255 | 74.99 158 | 92.30 138 | 59.48 255 | 88.04 251 | 90.68 179 |
|
BH-RMVSNet | | | 80.53 182 | 80.22 184 | 81.49 189 | 87.19 194 | 66.21 179 | 77.79 251 | 86.23 200 | 74.21 145 | 83.69 188 | 88.50 198 | 73.25 183 | 90.75 181 | 63.18 230 | 87.90 252 | 87.52 227 |
|
Effi-MVS+ | | | 83.90 138 | 84.01 135 | 83.57 153 | 87.22 193 | 65.61 183 | 86.55 107 | 92.40 85 | 78.64 97 | 81.34 222 | 84.18 259 | 83.65 67 | 92.93 126 | 74.22 138 | 87.87 253 | 92.17 145 |
|
MVS_Test | | | 82.47 158 | 83.22 144 | 80.22 205 | 82.62 260 | 57.75 257 | 82.54 183 | 91.96 97 | 71.16 182 | 82.89 199 | 92.52 118 | 77.41 134 | 90.50 189 | 80.04 90 | 87.84 254 | 92.40 136 |
|
QAPM | | | 82.59 156 | 82.59 155 | 82.58 173 | 86.44 206 | 66.69 175 | 89.94 49 | 90.36 135 | 67.97 209 | 84.94 169 | 92.58 115 | 72.71 188 | 92.18 140 | 70.63 175 | 87.73 255 | 88.85 213 |
|
PVSNet_Blended | | | 76.49 220 | 75.40 224 | 79.76 210 | 84.43 234 | 63.41 200 | 75.14 278 | 90.44 132 | 57.36 274 | 75.43 271 | 78.30 305 | 69.11 208 | 91.44 161 | 60.68 249 | 87.70 256 | 84.42 259 |
|
pmmvs5 | | | 70.73 265 | 70.07 268 | 72.72 272 | 77.03 300 | 52.73 289 | 74.14 283 | 75.65 270 | 50.36 312 | 72.17 288 | 85.37 244 | 55.42 273 | 80.67 287 | 52.86 289 | 87.59 257 | 84.77 255 |
|
IB-MVS | | 62.13 19 | 71.64 260 | 68.97 273 | 79.66 213 | 80.80 276 | 62.26 219 | 73.94 285 | 76.90 260 | 63.27 239 | 68.63 301 | 76.79 312 | 33.83 332 | 91.84 153 | 59.28 256 | 87.26 258 | 84.88 254 |
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 |
N_pmnet | | | 70.20 267 | 68.80 275 | 74.38 265 | 80.91 273 | 84.81 35 | 59.12 324 | 76.45 265 | 55.06 283 | 75.31 274 | 82.36 279 | 55.74 270 | 54.82 330 | 47.02 310 | 87.24 259 | 83.52 270 |
|
pmmvs4 | | | 74.92 235 | 72.98 246 | 80.73 199 | 84.95 229 | 71.71 138 | 76.23 269 | 77.59 257 | 52.83 294 | 77.73 254 | 86.38 225 | 56.35 268 | 84.97 263 | 57.72 264 | 87.05 260 | 85.51 248 |
|
MIMVSNet | | | 71.09 263 | 71.59 258 | 69.57 285 | 87.23 192 | 50.07 309 | 78.91 237 | 71.83 297 | 60.20 261 | 71.26 291 | 91.76 137 | 55.08 275 | 76.09 298 | 41.06 322 | 87.02 261 | 82.54 284 |
|
HyFIR lowres test | | | 75.12 232 | 72.66 249 | 82.50 176 | 91.44 116 | 65.19 185 | 72.47 292 | 87.31 185 | 46.79 316 | 80.29 235 | 84.30 258 | 52.70 279 | 92.10 144 | 51.88 295 | 86.73 262 | 90.22 189 |
|
MSDG | | | 80.06 192 | 79.99 188 | 80.25 204 | 83.91 249 | 68.04 167 | 77.51 255 | 89.19 160 | 77.65 105 | 81.94 211 | 83.45 266 | 76.37 150 | 86.31 249 | 63.31 229 | 86.59 263 | 86.41 238 |
|
Patchmatch-test | | | 65.91 288 | 67.38 280 | 61.48 310 | 75.51 310 | 43.21 325 | 68.84 304 | 63.79 319 | 62.48 244 | 72.80 285 | 83.42 267 | 44.89 311 | 59.52 329 | 48.27 307 | 86.45 264 | 81.70 294 |
|
mvs_anonymous | | | 78.13 203 | 78.76 195 | 76.23 257 | 79.24 288 | 50.31 308 | 78.69 241 | 84.82 222 | 61.60 252 | 83.09 198 | 92.82 107 | 73.89 171 | 87.01 236 | 68.33 197 | 86.41 265 | 91.37 166 |
|
IterMVS-SCA-FT | | | 80.64 181 | 79.41 191 | 84.34 134 | 83.93 248 | 69.66 152 | 76.28 268 | 81.09 242 | 72.43 171 | 86.47 151 | 90.19 176 | 60.46 240 | 93.15 120 | 77.45 118 | 86.39 266 | 90.22 189 |
|
E-PMN | | | 61.59 296 | 61.62 297 | 61.49 309 | 66.81 331 | 55.40 272 | 53.77 328 | 60.34 325 | 66.80 217 | 58.90 328 | 65.50 327 | 40.48 322 | 66.12 323 | 55.72 272 | 86.25 267 | 62.95 325 |
|
EMVS | | | 61.10 299 | 60.81 299 | 61.99 307 | 65.96 332 | 55.86 269 | 53.10 329 | 58.97 327 | 67.06 214 | 56.89 331 | 63.33 328 | 40.98 320 | 67.03 319 | 54.79 280 | 86.18 268 | 63.08 324 |
|
our_test_3 | | | 71.85 258 | 71.59 258 | 72.62 274 | 80.71 277 | 53.78 282 | 69.72 303 | 71.71 301 | 58.80 264 | 78.03 250 | 80.51 292 | 56.61 266 | 78.84 292 | 62.20 235 | 86.04 269 | 85.23 250 |
|
EU-MVSNet | | | 75.12 232 | 74.43 233 | 77.18 244 | 83.11 257 | 59.48 245 | 85.71 115 | 82.43 233 | 39.76 328 | 85.64 160 | 88.76 194 | 44.71 312 | 87.88 229 | 73.86 144 | 85.88 270 | 84.16 262 |
|
GA-MVS | | | 75.83 226 | 74.61 229 | 79.48 216 | 81.87 263 | 59.25 247 | 73.42 289 | 82.88 229 | 68.68 204 | 79.75 238 | 81.80 283 | 50.62 283 | 89.46 209 | 66.85 204 | 85.64 271 | 89.72 195 |
|
MVS | | | 73.21 248 | 72.59 250 | 75.06 262 | 80.97 272 | 60.81 234 | 81.64 200 | 85.92 204 | 46.03 319 | 71.68 290 | 77.54 307 | 68.47 211 | 89.77 206 | 55.70 273 | 85.39 272 | 74.60 315 |
|
PatchT | | | 70.52 266 | 72.76 248 | 63.79 304 | 79.38 286 | 33.53 332 | 77.63 252 | 65.37 317 | 73.61 151 | 71.77 289 | 92.79 110 | 44.38 313 | 75.65 301 | 64.53 223 | 85.37 273 | 82.18 289 |
|
TR-MVS | | | 76.77 216 | 75.79 219 | 79.72 211 | 86.10 220 | 65.79 182 | 77.14 257 | 83.02 228 | 65.20 232 | 81.40 220 | 82.10 280 | 66.30 218 | 90.73 183 | 55.57 274 | 85.27 274 | 82.65 281 |
|
BH-w/o | | | 76.57 218 | 76.07 218 | 78.10 235 | 86.88 203 | 65.92 181 | 77.63 252 | 86.33 199 | 65.69 226 | 80.89 226 | 79.95 296 | 68.97 210 | 90.74 182 | 53.01 288 | 85.25 275 | 77.62 310 |
|
IterMVS | | | 76.91 214 | 76.34 215 | 78.64 225 | 80.91 273 | 64.03 195 | 76.30 267 | 79.03 251 | 64.88 234 | 83.11 196 | 89.16 188 | 59.90 246 | 84.46 268 | 68.61 195 | 85.15 276 | 87.42 228 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
OpenMVS_ROB | | 70.19 17 | 77.77 207 | 77.46 204 | 78.71 224 | 84.39 237 | 61.15 228 | 81.18 209 | 82.52 231 | 62.45 245 | 83.34 193 | 87.37 215 | 66.20 219 | 88.66 222 | 64.69 220 | 85.02 277 | 86.32 239 |
|
test-LLR | | | 67.21 282 | 66.74 284 | 68.63 290 | 76.45 305 | 55.21 274 | 67.89 307 | 67.14 312 | 62.43 246 | 65.08 315 | 72.39 319 | 43.41 314 | 69.37 310 | 61.00 245 | 84.89 278 | 81.31 299 |
|
test-mter | | | 65.00 290 | 63.79 292 | 68.63 290 | 76.45 305 | 55.21 274 | 67.89 307 | 67.14 312 | 50.98 307 | 65.08 315 | 72.39 319 | 28.27 338 | 69.37 310 | 61.00 245 | 84.89 278 | 81.31 299 |
|
PS-MVSNAJ | | | 77.04 213 | 76.53 213 | 78.56 226 | 87.09 200 | 61.40 224 | 75.26 277 | 87.13 191 | 61.25 253 | 74.38 279 | 77.22 311 | 76.94 142 | 90.94 174 | 64.63 221 | 84.83 280 | 83.35 274 |
|
xiu_mvs_v2_base | | | 77.19 211 | 76.75 211 | 78.52 227 | 87.01 201 | 61.30 226 | 75.55 276 | 87.12 193 | 61.24 254 | 74.45 277 | 78.79 301 | 77.20 136 | 90.93 175 | 64.62 222 | 84.80 281 | 83.32 275 |
|
pmmvs3 | | | 62.47 292 | 60.02 303 | 69.80 283 | 71.58 329 | 64.00 196 | 70.52 299 | 58.44 328 | 39.77 327 | 66.05 309 | 75.84 315 | 27.10 340 | 72.28 305 | 46.15 313 | 84.77 282 | 73.11 316 |
|
MDTV_nov1_ep13 | | | | 68.29 278 | | 78.03 294 | 43.87 323 | 74.12 284 | 72.22 294 | 52.17 298 | 67.02 308 | 85.54 236 | 45.36 306 | 80.85 286 | 55.73 271 | 84.42 283 | |
|
1112_ss | | | 74.82 237 | 73.74 237 | 78.04 236 | 89.57 150 | 60.04 239 | 76.49 265 | 87.09 194 | 54.31 286 | 73.66 282 | 79.80 297 | 60.25 243 | 86.76 244 | 58.37 258 | 84.15 284 | 87.32 230 |
|
PatchMatch-RL | | | 74.48 239 | 73.22 243 | 78.27 233 | 87.70 183 | 85.26 30 | 75.92 271 | 70.09 305 | 64.34 235 | 76.09 264 | 81.25 288 | 65.87 222 | 78.07 294 | 53.86 284 | 83.82 285 | 71.48 318 |
|
MDA-MVSNet_test_wron | | | 70.05 271 | 70.44 265 | 68.88 288 | 73.84 319 | 53.47 284 | 58.93 326 | 67.28 310 | 58.43 265 | 87.09 137 | 85.40 242 | 59.80 248 | 67.25 318 | 59.66 254 | 83.54 286 | 85.92 244 |
|
YYNet1 | | | 70.06 270 | 70.44 265 | 68.90 287 | 73.76 320 | 53.42 286 | 58.99 325 | 67.20 311 | 58.42 266 | 87.10 136 | 85.39 243 | 59.82 247 | 67.32 317 | 59.79 253 | 83.50 287 | 85.96 242 |
|
Test_1112_low_res | | | 73.90 243 | 73.08 244 | 76.35 254 | 90.35 139 | 55.95 267 | 73.40 290 | 86.17 201 | 50.70 309 | 73.14 283 | 85.94 233 | 58.31 255 | 85.90 255 | 56.51 268 | 83.22 288 | 87.20 231 |
|
PVSNet | | 58.17 21 | 66.41 286 | 65.63 288 | 68.75 289 | 81.96 262 | 49.88 310 | 62.19 320 | 72.51 293 | 51.03 306 | 68.04 303 | 75.34 317 | 50.84 282 | 74.77 302 | 45.82 315 | 82.96 289 | 81.60 296 |
|
gg-mvs-nofinetune | | | 68.96 277 | 69.11 272 | 68.52 292 | 76.12 307 | 45.32 319 | 83.59 154 | 55.88 330 | 86.68 22 | 64.62 319 | 97.01 8 | 30.36 336 | 83.97 274 | 44.78 316 | 82.94 290 | 76.26 312 |
|
CR-MVSNet | | | 74.00 242 | 73.04 245 | 76.85 249 | 79.58 282 | 62.64 211 | 82.58 180 | 76.90 260 | 50.50 311 | 75.72 268 | 92.38 119 | 48.07 289 | 84.07 271 | 68.72 194 | 82.91 291 | 83.85 266 |
|
RPMNet | | | 76.06 224 | 75.79 219 | 76.85 249 | 79.58 282 | 62.64 211 | 82.58 180 | 71.75 299 | 74.80 138 | 75.72 268 | 92.59 113 | 48.69 287 | 84.07 271 | 73.48 148 | 82.91 291 | 83.85 266 |
|
test0.0.03 1 | | | 64.66 291 | 64.36 291 | 65.57 300 | 75.03 316 | 46.89 316 | 64.69 316 | 61.58 324 | 62.43 246 | 71.18 293 | 77.54 307 | 43.41 314 | 68.47 315 | 40.75 323 | 82.65 293 | 81.35 298 |
|
HY-MVS | | 64.64 18 | 73.03 249 | 72.47 253 | 74.71 263 | 83.36 253 | 54.19 279 | 82.14 195 | 81.96 236 | 56.76 278 | 69.57 298 | 86.21 231 | 60.03 244 | 84.83 266 | 49.58 301 | 82.65 293 | 85.11 252 |
|
SCA | | | 73.32 245 | 72.57 251 | 75.58 260 | 81.62 265 | 55.86 269 | 78.89 238 | 71.37 302 | 61.73 249 | 74.93 276 | 83.42 267 | 60.46 240 | 87.01 236 | 58.11 262 | 82.63 295 | 83.88 263 |
|
CHOSEN 1792x2688 | | | 72.45 253 | 70.56 263 | 78.13 234 | 90.02 148 | 63.08 205 | 68.72 305 | 83.16 227 | 42.99 325 | 75.92 266 | 85.46 240 | 57.22 264 | 85.18 262 | 49.87 300 | 81.67 296 | 86.14 241 |
|
WTY-MVS | | | 67.91 280 | 68.35 277 | 66.58 297 | 80.82 275 | 48.12 313 | 65.96 314 | 72.60 291 | 53.67 290 | 71.20 292 | 81.68 285 | 58.97 252 | 69.06 314 | 48.57 304 | 81.67 296 | 82.55 283 |
|
TESTMET0.1,1 | | | 61.29 297 | 60.32 301 | 64.19 303 | 72.06 327 | 51.30 300 | 67.89 307 | 62.09 320 | 45.27 320 | 60.65 324 | 69.01 322 | 27.93 339 | 64.74 326 | 56.31 269 | 81.65 298 | 76.53 311 |
|
PAPM | | | 71.77 259 | 70.06 269 | 76.92 246 | 86.39 207 | 53.97 280 | 76.62 263 | 86.62 197 | 53.44 291 | 63.97 320 | 84.73 254 | 57.79 261 | 92.34 137 | 39.65 324 | 81.33 299 | 84.45 258 |
|
DSMNet-mixed | | | 60.98 300 | 61.61 298 | 59.09 314 | 72.88 325 | 45.05 321 | 74.70 281 | 46.61 335 | 26.20 331 | 65.34 313 | 90.32 173 | 55.46 272 | 63.12 328 | 41.72 321 | 81.30 300 | 69.09 322 |
|
sss | | | 66.92 283 | 67.26 281 | 65.90 298 | 77.23 297 | 51.10 304 | 64.79 315 | 71.72 300 | 52.12 301 | 70.13 296 | 80.18 294 | 57.96 258 | 65.36 325 | 50.21 297 | 81.01 301 | 81.25 301 |
|
tpm | | | 67.95 279 | 68.08 279 | 67.55 294 | 78.74 293 | 43.53 324 | 75.60 274 | 67.10 314 | 54.92 284 | 72.23 287 | 88.10 202 | 42.87 317 | 75.97 299 | 52.21 290 | 80.95 302 | 83.15 278 |
|
tpm2 | | | 68.45 278 | 66.83 283 | 73.30 269 | 78.93 292 | 48.50 311 | 79.76 223 | 71.76 298 | 47.50 315 | 69.92 297 | 83.60 263 | 42.07 319 | 88.40 224 | 48.44 306 | 79.51 303 | 83.01 280 |
|
FPMVS | | | 72.29 256 | 72.00 255 | 73.14 270 | 88.63 164 | 85.00 32 | 74.65 282 | 67.39 309 | 71.94 178 | 77.80 253 | 87.66 210 | 50.48 284 | 75.83 300 | 49.95 298 | 79.51 303 | 58.58 329 |
|
UnsupCasMVSNet_bld | | | 69.21 276 | 69.68 270 | 67.82 293 | 79.42 285 | 51.15 302 | 67.82 310 | 75.79 267 | 54.15 287 | 77.47 256 | 85.36 245 | 59.26 251 | 70.64 309 | 48.46 305 | 79.35 305 | 81.66 295 |
|
CostFormer | | | 69.98 272 | 68.68 276 | 73.87 266 | 77.14 298 | 50.72 306 | 79.26 232 | 74.51 276 | 51.94 302 | 70.97 294 | 84.75 253 | 45.16 310 | 87.49 232 | 55.16 278 | 79.23 306 | 83.40 273 |
|
1314 | | | 73.22 247 | 72.56 252 | 75.20 261 | 80.41 281 | 57.84 255 | 81.64 200 | 85.36 209 | 51.68 303 | 73.10 284 | 76.65 313 | 61.45 236 | 85.19 261 | 63.54 226 | 79.21 307 | 82.59 282 |
|
baseline1 | | | 73.26 246 | 73.54 240 | 72.43 276 | 84.92 230 | 47.79 315 | 79.89 222 | 74.00 279 | 65.93 222 | 78.81 247 | 86.28 230 | 56.36 267 | 81.63 284 | 56.63 267 | 79.04 308 | 87.87 225 |
|
PMMVS | | | 61.65 295 | 60.38 300 | 65.47 301 | 65.40 333 | 69.26 156 | 63.97 318 | 61.73 323 | 36.80 330 | 60.11 325 | 68.43 323 | 59.42 249 | 66.35 322 | 48.97 303 | 78.57 309 | 60.81 326 |
|
baseline2 | | | 69.77 273 | 66.89 282 | 78.41 230 | 79.51 284 | 58.09 254 | 76.23 269 | 69.57 307 | 57.50 273 | 64.82 318 | 77.45 309 | 46.02 296 | 88.44 223 | 53.08 287 | 77.83 310 | 88.70 214 |
|
MS-PatchMatch | | | 70.93 264 | 70.22 267 | 73.06 271 | 81.85 264 | 62.50 214 | 73.82 287 | 77.90 255 | 52.44 297 | 75.92 266 | 81.27 287 | 55.67 271 | 81.75 282 | 55.37 276 | 77.70 311 | 74.94 314 |
|
UnsupCasMVSNet_eth | | | 71.63 261 | 72.30 254 | 69.62 284 | 76.47 304 | 52.70 290 | 70.03 302 | 80.97 243 | 59.18 263 | 79.36 242 | 88.21 201 | 60.50 239 | 69.12 313 | 58.33 260 | 77.62 312 | 87.04 233 |
|
CVMVSNet | | | 72.62 252 | 71.41 261 | 76.28 256 | 83.25 254 | 60.34 237 | 83.50 158 | 79.02 252 | 37.77 329 | 76.33 260 | 85.10 246 | 49.60 286 | 87.41 233 | 70.54 176 | 77.54 313 | 81.08 304 |
|
GG-mvs-BLEND | | | | | 67.16 295 | 73.36 321 | 46.54 318 | 84.15 138 | 55.04 331 | | 58.64 329 | 61.95 330 | 29.93 337 | 83.87 275 | 38.71 326 | 76.92 314 | 71.07 319 |
|
CHOSEN 280x420 | | | 59.08 302 | 56.52 306 | 66.76 296 | 76.51 303 | 64.39 192 | 49.62 330 | 59.00 326 | 43.86 323 | 55.66 332 | 68.41 324 | 35.55 331 | 68.21 316 | 43.25 318 | 76.78 315 | 67.69 323 |
|
tpmvs | | | 70.16 268 | 69.56 271 | 71.96 279 | 74.71 318 | 48.13 312 | 79.63 224 | 75.45 272 | 65.02 233 | 70.26 295 | 81.88 282 | 45.34 307 | 85.68 257 | 58.34 259 | 75.39 316 | 82.08 290 |
|
MVP-Stereo | | | 75.81 227 | 73.51 241 | 82.71 171 | 89.35 152 | 73.62 113 | 80.06 218 | 85.20 213 | 60.30 259 | 73.96 280 | 87.94 205 | 57.89 260 | 89.45 210 | 52.02 291 | 74.87 317 | 85.06 253 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
DWT-MVSNet_test | | | 66.43 285 | 64.37 290 | 72.63 273 | 74.86 317 | 50.86 305 | 76.52 264 | 72.74 290 | 54.06 288 | 65.50 312 | 68.30 325 | 32.13 334 | 84.84 265 | 61.63 242 | 73.59 318 | 82.19 288 |
|
PatchFormer-LS_test | | | 67.91 280 | 66.49 287 | 72.17 278 | 75.29 313 | 51.85 297 | 75.68 272 | 73.62 285 | 57.23 276 | 68.64 299 | 68.13 326 | 42.19 318 | 82.76 279 | 64.06 224 | 73.51 319 | 81.89 293 |
|
new_pmnet | | | 55.69 304 | 57.66 305 | 49.76 317 | 75.47 311 | 30.59 333 | 59.56 321 | 51.45 333 | 43.62 324 | 62.49 321 | 75.48 316 | 40.96 321 | 49.15 333 | 37.39 327 | 72.52 320 | 69.55 321 |
|
PatchmatchNet | | | 69.71 274 | 68.83 274 | 72.33 277 | 77.66 296 | 53.60 283 | 79.29 231 | 69.99 306 | 57.66 271 | 72.53 286 | 82.93 272 | 46.45 293 | 80.08 290 | 60.91 247 | 72.09 321 | 83.31 276 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
MVS-HIRNet | | | 61.16 298 | 62.92 294 | 55.87 315 | 79.09 289 | 35.34 331 | 71.83 294 | 57.98 329 | 46.56 317 | 59.05 327 | 91.14 150 | 49.95 285 | 76.43 297 | 38.74 325 | 71.92 322 | 55.84 330 |
|
tpmrst | | | 66.28 287 | 66.69 285 | 65.05 302 | 72.82 326 | 39.33 327 | 78.20 246 | 70.69 304 | 53.16 293 | 67.88 304 | 80.36 293 | 48.18 288 | 74.75 303 | 58.13 261 | 70.79 323 | 81.08 304 |
|
tpm cat1 | | | 66.76 284 | 65.21 289 | 71.42 280 | 77.09 299 | 50.62 307 | 78.01 247 | 73.68 284 | 44.89 321 | 68.64 299 | 79.00 300 | 45.51 304 | 82.42 281 | 49.91 299 | 70.15 324 | 81.23 303 |
|
ADS-MVSNet2 | | | 65.87 289 | 63.64 293 | 72.55 275 | 73.16 323 | 56.92 263 | 67.10 311 | 74.81 273 | 49.74 313 | 66.04 310 | 82.97 270 | 46.71 291 | 77.26 295 | 42.29 319 | 69.96 325 | 83.46 271 |
|
ADS-MVSNet | | | 61.90 294 | 62.19 296 | 61.03 311 | 73.16 323 | 36.42 330 | 67.10 311 | 61.75 322 | 49.74 313 | 66.04 310 | 82.97 270 | 46.71 291 | 63.21 327 | 42.29 319 | 69.96 325 | 83.46 271 |
|
JIA-IIPM | | | 69.41 275 | 66.64 286 | 77.70 241 | 73.19 322 | 71.24 141 | 75.67 273 | 65.56 316 | 70.42 187 | 65.18 314 | 92.97 102 | 33.64 333 | 83.06 277 | 53.52 286 | 69.61 327 | 78.79 309 |
|
EPMVS | | | 62.47 292 | 62.63 295 | 62.01 306 | 70.63 330 | 38.74 328 | 74.76 280 | 52.86 332 | 53.91 289 | 67.71 306 | 80.01 295 | 39.40 323 | 66.60 321 | 55.54 275 | 68.81 328 | 80.68 308 |
|
MVE | | 40.22 23 | 51.82 306 | 50.47 308 | 55.87 315 | 62.66 335 | 51.91 295 | 31.61 333 | 39.28 336 | 40.65 326 | 50.76 333 | 74.98 318 | 56.24 269 | 44.67 334 | 33.94 330 | 64.11 329 | 71.04 320 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
dp | | | 60.70 301 | 60.29 302 | 61.92 308 | 72.04 328 | 38.67 329 | 70.83 297 | 64.08 318 | 51.28 305 | 60.75 323 | 77.28 310 | 36.59 330 | 71.58 308 | 47.41 309 | 62.34 330 | 75.52 313 |
|
PVSNet_0 | | 51.08 22 | 56.10 303 | 54.97 307 | 59.48 313 | 75.12 315 | 53.28 287 | 55.16 327 | 61.89 321 | 44.30 322 | 59.16 326 | 62.48 329 | 54.22 276 | 65.91 324 | 35.40 328 | 47.01 331 | 59.25 328 |
|
tmp_tt | | | 20.25 308 | 24.50 310 | 7.49 320 | 4.47 337 | 8.70 338 | 34.17 332 | 25.16 338 | 1.00 333 | 32.43 335 | 18.49 332 | 39.37 324 | 9.21 336 | 21.64 332 | 43.75 332 | 4.57 332 |
|
DeepMVS_CX | | | | | 24.13 319 | 32.95 336 | 29.49 334 | | 21.63 339 | 12.07 332 | 37.95 334 | 45.07 331 | 30.84 335 | 19.21 335 | 17.94 333 | 33.06 333 | 23.69 331 |
|
testmvs | | | 5.91 312 | 7.65 314 | 0.72 322 | 1.20 338 | 0.37 340 | 59.14 323 | 0.67 341 | 0.49 335 | 1.11 336 | 2.76 336 | 0.94 342 | 0.24 338 | 1.02 335 | 1.47 334 | 1.55 334 |
|
test123 | | | 6.27 311 | 8.08 313 | 0.84 321 | 1.11 339 | 0.57 339 | 62.90 319 | 0.82 340 | 0.54 334 | 1.07 337 | 2.75 337 | 1.26 341 | 0.30 337 | 1.04 334 | 1.26 335 | 1.66 333 |
|
test_part1 | | | | | 0.00 323 | | 0.00 341 | 0.00 334 | 93.93 30 | | | | 0.00 343 | 0.00 339 | 0.00 336 | 0.00 336 | 0.00 335 |
|
cdsmvs_eth3d_5k | | | 20.81 307 | 27.75 309 | 0.00 323 | 0.00 340 | 0.00 341 | 0.00 334 | 85.44 208 | 0.00 336 | 0.00 338 | 82.82 274 | 81.46 99 | 0.00 339 | 0.00 336 | 0.00 336 | 0.00 335 |
|
pcd_1.5k_mvsjas | | | 6.41 310 | 8.55 312 | 0.00 323 | 0.00 340 | 0.00 341 | 0.00 334 | 0.00 342 | 0.00 336 | 0.00 338 | 0.00 338 | 76.94 142 | 0.00 339 | 0.00 336 | 0.00 336 | 0.00 335 |
|
sosnet-low-res | | | 0.00 313 | 0.00 315 | 0.00 323 | 0.00 340 | 0.00 341 | 0.00 334 | 0.00 342 | 0.00 336 | 0.00 338 | 0.00 338 | 0.00 343 | 0.00 339 | 0.00 336 | 0.00 336 | 0.00 335 |
|
sosnet | | | 0.00 313 | 0.00 315 | 0.00 323 | 0.00 340 | 0.00 341 | 0.00 334 | 0.00 342 | 0.00 336 | 0.00 338 | 0.00 338 | 0.00 343 | 0.00 339 | 0.00 336 | 0.00 336 | 0.00 335 |
|
uncertanet | | | 0.00 313 | 0.00 315 | 0.00 323 | 0.00 340 | 0.00 341 | 0.00 334 | 0.00 342 | 0.00 336 | 0.00 338 | 0.00 338 | 0.00 343 | 0.00 339 | 0.00 336 | 0.00 336 | 0.00 335 |
|
Regformer | | | 0.00 313 | 0.00 315 | 0.00 323 | 0.00 340 | 0.00 341 | 0.00 334 | 0.00 342 | 0.00 336 | 0.00 338 | 0.00 338 | 0.00 343 | 0.00 339 | 0.00 336 | 0.00 336 | 0.00 335 |
|
ab-mvs-re | | | 6.65 309 | 8.87 311 | 0.00 323 | 0.00 340 | 0.00 341 | 0.00 334 | 0.00 342 | 0.00 336 | 0.00 338 | 79.80 297 | 0.00 343 | 0.00 339 | 0.00 336 | 0.00 336 | 0.00 335 |
|
uanet | | | 0.00 313 | 0.00 315 | 0.00 323 | 0.00 340 | 0.00 341 | 0.00 334 | 0.00 342 | 0.00 336 | 0.00 338 | 0.00 338 | 0.00 343 | 0.00 339 | 0.00 336 | 0.00 336 | 0.00 335 |
|
save fliter | | | | | | 93.75 54 | 77.44 87 | 86.31 109 | 89.72 152 | 70.80 184 | | | | | | | |
|
test0726 | | | | | | 94.16 46 | 72.56 122 | 90.63 38 | 93.90 33 | 83.61 38 | 93.75 27 | 94.49 59 | 89.76 16 | | | | |
|
GSMVS | | | | | | | | | | | | | | | | | 83.88 263 |
|
test_part2 | | | | | | 93.86 53 | 77.77 82 | | | | 92.84 39 | | | | | | |
|
sam_mvs1 | | | | | | | | | | | | | 46.11 295 | | | | 83.88 263 |
|
sam_mvs | | | | | | | | | | | | | 45.92 300 | | | | |
|
MTGPA | | | | | | | | | 91.81 101 | | | | | | | | |
|
test_post1 | | | | | | | | 78.85 240 | | | | 3.13 334 | 45.19 309 | 80.13 289 | 58.11 262 | | |
|
test_post | | | | | | | | | | | | 3.10 335 | 45.43 305 | 77.22 296 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 81.71 284 | 45.93 299 | 87.01 236 | | | |
|
MTMP | | | | | | | | 90.66 36 | 33.14 337 | | | | | | | | |
|
gm-plane-assit | | | | | | 75.42 312 | 44.97 322 | | | 52.17 298 | | 72.36 321 | | 87.90 228 | 54.10 283 | | |
|
TEST9 | | | | | | 92.34 87 | 79.70 67 | 83.94 142 | 90.32 136 | 65.41 231 | 84.49 176 | 90.97 155 | 82.03 90 | 93.63 96 | | | |
|
test_8 | | | | | | 92.09 95 | 78.87 74 | 83.82 147 | 90.31 138 | 65.79 224 | 84.36 179 | 90.96 157 | 81.93 92 | 93.44 108 | | | |
|
agg_prior | | | | | | 91.58 110 | 77.69 83 | | 90.30 140 | | 84.32 180 | | | 93.18 116 | | | |
|
test_prior4 | | | | | | | 78.97 73 | 84.59 129 | | | | | | | | | |
|
test_prior | | | | | 86.32 93 | 90.59 135 | 71.99 132 | | 92.85 74 | | | | | 94.17 76 | | | 92.80 123 |
|
旧先验2 | | | | | | | | 81.73 198 | | 56.88 277 | 86.54 150 | | | 84.90 264 | 72.81 157 | | |
|
新几何2 | | | | | | | | 81.72 199 | | | | | | | | | |
|
无先验 | | | | | | | | 82.81 177 | 85.62 207 | 58.09 268 | | | | 91.41 163 | 67.95 200 | | 84.48 257 |
|
原ACMM2 | | | | | | | | 82.26 191 | | | | | | | | | |
|
testdata2 | | | | | | | | | | | | | | 86.43 248 | 63.52 227 | | |
|
segment_acmp | | | | | | | | | | | | | 81.94 91 | | | | |
|
testdata1 | | | | | | | | 79.62 225 | | 73.95 148 | | | | | | | |
|
plane_prior7 | | | | | | 93.45 59 | 77.31 90 | | | | | | | | | | |
|
plane_prior6 | | | | | | 92.61 79 | 76.54 97 | | | | | | 74.84 160 | | | | |
|
plane_prior4 | | | | | | | | | | | | 92.95 103 | | | | | |
|
plane_prior3 | | | | | | | 76.85 95 | | | 77.79 104 | 86.55 145 | | | | | | |
|
plane_prior2 | | | | | | | | 89.45 63 | | 79.44 84 | | | | | | | |
|
plane_prior1 | | | | | | 92.83 77 | | | | | | | | | | | |
|
n2 | | | | | | | | | 0.00 342 | | | | | | | | |
|
nn | | | | | | | | | 0.00 342 | | | | | | | | |
|
door-mid | | | | | | | | | 74.45 277 | | | | | | | | |
|
test11 | | | | | | | | | 91.46 108 | | | | | | | | |
|
door | | | | | | | | | 72.57 292 | | | | | | | | |
|
HQP5-MVS | | | | | | | 70.66 144 | | | | | | | | | | |
|
HQP-NCC | | | | | | 91.19 121 | | 84.77 124 | | 73.30 158 | 80.55 232 | | | | | | |
|
ACMP_Plane | | | | | | 91.19 121 | | 84.77 124 | | 73.30 158 | 80.55 232 | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 77.30 120 | | |
|
HQP4-MVS | | | | | | | | | | | 80.56 231 | | | 94.61 62 | | | 93.56 105 |
|
HQP2-MVS | | | | | | | | | | | | | 72.10 193 | | | | |
|
NP-MVS | | | | | | 91.95 99 | 74.55 109 | | | | | 90.17 178 | | | | | |
|
MDTV_nov1_ep13_2view | | | | | | | 27.60 335 | 70.76 298 | | 46.47 318 | 61.27 322 | | 45.20 308 | | 49.18 302 | | 83.75 268 |
|
Test By Simon | | | | | | | | | | | | | 79.09 119 | | | | |
|