AdaColmap | | | 97.23 90 | 96.80 93 | 98.51 102 | 99.99 1 | 95.60 148 | 99.09 203 | 98.84 46 | 93.32 132 | 96.74 135 | 99.72 71 | 86.04 183 | 100.00 1 | 98.01 90 | 99.43 99 | 99.94 70 |
|
CNVR-MVS | | | 99.40 1 | 99.26 1 | 99.84 3 | 99.98 2 | 99.51 3 | 99.98 8 | 98.69 54 | 98.20 3 | 99.93 1 | 99.98 2 | 96.82 17 | 100.00 1 | 99.75 15 | 100.00 1 | 99.99 15 |
|
MCST-MVS | | | 99.32 3 | 99.14 4 | 99.86 2 | 99.97 3 | 99.59 2 | 99.97 16 | 98.64 62 | 98.47 2 | 99.13 64 | 99.92 9 | 96.38 21 | 100.00 1 | 99.74 17 | 100.00 1 | 100.00 1 |
|
mPP-MVS | | | 98.39 46 | 98.20 44 | 98.97 73 | 99.97 3 | 96.92 104 | 99.95 37 | 98.38 130 | 95.04 73 | 98.61 87 | 99.80 49 | 93.39 93 | 100.00 1 | 98.64 69 | 100.00 1 | 99.98 47 |
|
CPTT-MVS | | | 97.64 77 | 97.32 78 | 98.58 95 | 99.97 3 | 95.77 141 | 99.96 23 | 98.35 135 | 89.90 220 | 98.36 96 | 99.79 51 | 91.18 136 | 99.99 33 | 98.37 77 | 99.99 17 | 99.99 15 |
|
DP-MVS Recon | | | 98.41 44 | 98.02 51 | 99.56 18 | 99.97 3 | 98.70 37 | 99.92 60 | 98.44 103 | 92.06 176 | 98.40 95 | 99.84 39 | 95.68 34 | 100.00 1 | 98.19 80 | 99.71 80 | 99.97 58 |
|
PAPR | | | 98.52 36 | 98.16 46 | 99.58 17 | 99.97 3 | 98.77 30 | 99.95 37 | 98.43 110 | 95.35 66 | 98.03 107 | 99.75 66 | 94.03 80 | 99.98 38 | 98.11 85 | 99.83 68 | 99.99 15 |
|
HFP-MVS | | | 98.56 32 | 98.37 35 | 99.14 55 | 99.96 8 | 97.43 86 | 99.95 37 | 98.61 68 | 94.77 80 | 99.31 53 | 99.85 26 | 94.22 73 | 100.00 1 | 98.70 63 | 99.98 30 | 99.98 47 |
|
region2R | | | 98.54 34 | 98.37 35 | 99.05 65 | 99.96 8 | 97.18 94 | 99.96 23 | 98.55 80 | 94.87 78 | 99.45 42 | 99.85 26 | 94.07 79 | 100.00 1 | 98.67 65 | 100.00 1 | 99.98 47 |
|
#test# | | | 98.59 30 | 98.41 29 | 99.14 55 | 99.96 8 | 97.43 86 | 99.95 37 | 98.61 68 | 95.00 74 | 99.31 53 | 99.85 26 | 94.22 73 | 100.00 1 | 98.78 60 | 99.98 30 | 99.98 47 |
|
ACMMPR | | | 98.50 37 | 98.32 39 | 99.05 65 | 99.96 8 | 97.18 94 | 99.95 37 | 98.60 70 | 94.77 80 | 99.31 53 | 99.84 39 | 93.73 88 | 100.00 1 | 98.70 63 | 99.98 30 | 99.98 47 |
|
NCCC | | | 99.37 2 | 99.25 2 | 99.71 8 | 99.96 8 | 99.15 12 | 99.97 16 | 98.62 66 | 98.02 6 | 99.90 2 | 99.95 3 | 97.33 12 | 100.00 1 | 99.54 24 | 100.00 1 | 100.00 1 |
|
CP-MVS | | | 98.45 41 | 98.32 39 | 98.87 78 | 99.96 8 | 96.62 111 | 99.97 16 | 98.39 126 | 94.43 91 | 98.90 74 | 99.87 20 | 94.30 71 | 100.00 1 | 99.04 44 | 99.99 17 | 99.99 15 |
|
testtj | | | 98.89 16 | 98.69 16 | 99.52 22 | 99.94 14 | 98.56 44 | 99.90 68 | 98.55 80 | 95.14 72 | 99.72 21 | 99.84 39 | 95.46 40 | 100.00 1 | 99.65 23 | 99.99 17 | 99.99 15 |
|
test_0728_SECOND | | | | | 99.82 4 | 99.94 14 | 99.47 4 | 99.95 37 | 98.43 110 | | | | | 100.00 1 | 99.99 1 | 100.00 1 | 100.00 1 |
|
XVS | | | 98.70 25 | 98.55 23 | 99.15 53 | 99.94 14 | 97.50 82 | 99.94 52 | 98.42 118 | 96.22 44 | 99.41 46 | 99.78 55 | 94.34 68 | 99.96 49 | 98.92 51 | 99.95 44 | 99.99 15 |
|
test_prior3 | | | 98.99 12 | 98.84 13 | 99.43 29 | 99.94 14 | 98.49 48 | 99.95 37 | 98.65 59 | 95.78 53 | 99.73 19 | 99.76 61 | 96.00 24 | 99.80 97 | 99.78 13 | 100.00 1 | 99.99 15 |
|
X-MVStestdata | | | 93.83 175 | 92.06 199 | 99.15 53 | 99.94 14 | 97.50 82 | 99.94 52 | 98.42 118 | 96.22 44 | 99.41 46 | 41.37 336 | 94.34 68 | 99.96 49 | 98.92 51 | 99.95 44 | 99.99 15 |
|
test_prior | | | | | 99.43 29 | 99.94 14 | 98.49 48 | | 98.65 59 | | | | | 99.80 97 | | | 99.99 15 |
|
MSLP-MVS++ | | | 99.13 6 | 99.01 8 | 99.49 26 | 99.94 14 | 98.46 50 | 99.98 8 | 98.86 44 | 97.10 20 | 99.80 12 | 99.94 4 | 95.92 28 | 100.00 1 | 99.51 25 | 100.00 1 | 100.00 1 |
|
APDe-MVS | | | 99.06 9 | 98.91 11 | 99.51 24 | 99.94 14 | 98.76 34 | 99.91 64 | 98.39 126 | 97.20 19 | 99.46 41 | 99.85 26 | 95.53 39 | 99.79 99 | 99.86 7 | 100.00 1 | 99.99 15 |
|
MP-MVS | | | 98.23 54 | 97.97 54 | 99.03 67 | 99.94 14 | 97.17 97 | 99.95 37 | 98.39 126 | 94.70 83 | 98.26 102 | 99.81 48 | 91.84 127 | 100.00 1 | 98.85 55 | 99.97 38 | 99.93 71 |
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
CDPH-MVS | | | 98.65 26 | 98.36 37 | 99.49 26 | 99.94 14 | 98.73 35 | 99.87 79 | 98.33 138 | 93.97 111 | 99.76 17 | 99.87 20 | 94.99 53 | 99.75 107 | 98.55 72 | 100.00 1 | 99.98 47 |
|
PAPM_NR | | | 98.12 57 | 97.93 58 | 98.70 84 | 99.94 14 | 96.13 130 | 99.82 103 | 98.43 110 | 94.56 87 | 97.52 118 | 99.70 75 | 94.40 64 | 99.98 38 | 97.00 118 | 99.98 30 | 99.99 15 |
|
MG-MVS | | | 98.91 15 | 98.65 18 | 99.68 9 | 99.94 14 | 99.07 14 | 99.64 146 | 99.44 18 | 97.33 15 | 99.00 71 | 99.72 71 | 94.03 80 | 99.98 38 | 98.73 62 | 100.00 1 | 100.00 1 |
|
DVP-MVS | | | 99.30 4 | 99.16 3 | 99.73 6 | 99.93 26 | 99.29 6 | 99.95 37 | 98.32 140 | 97.28 16 | 99.83 8 | 99.91 10 | 97.22 14 | 100.00 1 | 99.99 1 | 100.00 1 | 99.89 78 |
|
test0726 | | | | | | 99.93 26 | 99.29 6 | 99.96 23 | 98.42 118 | 97.28 16 | 99.86 4 | 99.94 4 | 97.22 14 | | | | |
|
MSP-MVS | | | 99.09 7 | 99.12 5 | 98.98 72 | 99.93 26 | 97.24 91 | 99.95 37 | 98.42 118 | 97.50 12 | 99.52 39 | 99.88 17 | 97.43 11 | 99.71 115 | 99.50 26 | 99.98 30 | 100.00 1 |
|
agg_prior1 | | | 98.88 17 | 98.66 17 | 99.54 20 | 99.93 26 | 98.77 30 | 99.96 23 | 98.43 110 | 94.63 86 | 99.63 27 | 99.85 26 | 95.79 33 | 99.85 86 | 99.72 20 | 99.99 17 | 99.99 15 |
|
agg_prior | | | | | | 99.93 26 | 98.77 30 | | 98.43 110 | | 99.63 27 | | | 99.85 86 | | | |
|
GST-MVS | | | 98.27 50 | 97.97 54 | 99.17 50 | 99.92 31 | 97.57 76 | 99.93 57 | 98.39 126 | 94.04 109 | 98.80 77 | 99.74 68 | 92.98 104 | 100.00 1 | 98.16 82 | 99.76 76 | 99.93 71 |
|
TEST9 | | | | | | 99.92 31 | 98.92 18 | 99.96 23 | 98.43 110 | 93.90 116 | 99.71 22 | 99.86 22 | 95.88 29 | 99.85 86 | | | |
|
train_agg | | | 98.88 17 | 98.65 18 | 99.59 16 | 99.92 31 | 98.92 18 | 99.96 23 | 98.43 110 | 94.35 94 | 99.71 22 | 99.86 22 | 95.94 26 | 99.85 86 | 99.69 22 | 99.98 30 | 99.99 15 |
|
test_8 | | | | | | 99.92 31 | 98.88 21 | 99.96 23 | 98.43 110 | 94.35 94 | 99.69 24 | 99.85 26 | 95.94 26 | 99.85 86 | | | |
|
PGM-MVS | | | 98.34 47 | 98.13 48 | 98.99 71 | 99.92 31 | 97.00 100 | 99.75 121 | 99.50 16 | 93.90 116 | 99.37 50 | 99.76 61 | 93.24 100 | 100.00 1 | 97.75 103 | 99.96 41 | 99.98 47 |
|
ACMMP | | | 97.74 74 | 97.44 72 | 98.66 87 | 99.92 31 | 96.13 130 | 99.18 198 | 99.45 17 | 94.84 79 | 96.41 145 | 99.71 73 | 91.40 130 | 99.99 33 | 97.99 92 | 98.03 131 | 99.87 81 |
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++ | | | 99.07 8 | 98.88 12 | 99.63 10 | 99.90 37 | 99.02 15 | 99.95 37 | 98.56 76 | 97.56 11 | 99.44 43 | 99.85 26 | 95.38 42 | 100.00 1 | 99.31 33 | 99.99 17 | 99.87 81 |
|
APD-MVS | | | 98.62 27 | 98.35 38 | 99.41 33 | 99.90 37 | 98.51 47 | 99.87 79 | 98.36 134 | 94.08 104 | 99.74 18 | 99.73 70 | 94.08 78 | 99.74 111 | 99.42 30 | 99.99 17 | 99.99 15 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
DeepC-MVS_fast | | 96.59 1 | 98.81 20 | 98.54 24 | 99.62 13 | 99.90 37 | 98.85 24 | 99.24 194 | 98.47 99 | 98.14 4 | 99.08 65 | 99.91 10 | 93.09 103 | 100.00 1 | 99.04 44 | 99.99 17 | 100.00 1 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
DPE-MVS | | | 99.26 5 | 99.10 6 | 99.74 5 | 99.89 40 | 99.24 10 | 99.87 79 | 98.44 103 | 97.48 13 | 99.64 26 | 99.94 4 | 96.68 18 | 99.99 33 | 99.99 1 | 100.00 1 | 99.99 15 |
|
test_part2 | | | | | | 99.89 40 | 99.25 9 | | | | 99.49 40 | | | | | | |
|
CSCG | | | 97.10 93 | 97.04 86 | 97.27 156 | 99.89 40 | 91.92 222 | 99.90 68 | 99.07 31 | 88.67 239 | 95.26 164 | 99.82 45 | 93.17 102 | 99.98 38 | 98.15 83 | 99.47 96 | 99.90 77 |
|
SR-MVS | | | 98.46 40 | 98.30 41 | 98.93 76 | 99.88 43 | 97.04 99 | 99.84 96 | 98.35 135 | 94.92 75 | 99.32 52 | 99.80 49 | 93.35 94 | 99.78 101 | 99.30 34 | 99.95 44 | 99.96 62 |
|
9.14 | | | | 98.38 33 | | 99.87 44 | | 99.91 64 | 98.33 138 | 93.22 134 | 99.78 15 | 99.89 16 | 94.57 61 | 99.85 86 | 99.84 8 | 99.97 38 | |
|
SMA-MVS | | | 98.76 23 | 98.48 26 | 99.62 13 | 99.87 44 | 98.87 22 | 99.86 90 | 98.38 130 | 93.19 135 | 99.77 16 | 99.94 4 | 95.54 36 | 100.00 1 | 99.74 17 | 99.99 17 | 100.00 1 |
|
PHI-MVS | | | 98.41 44 | 98.21 43 | 99.03 67 | 99.86 46 | 97.10 98 | 99.98 8 | 98.80 49 | 90.78 208 | 99.62 29 | 99.78 55 | 95.30 43 | 100.00 1 | 99.80 10 | 99.93 55 | 99.99 15 |
|
zzz-MVS | | | 98.33 48 | 98.00 52 | 99.30 40 | 99.85 47 | 97.93 67 | 99.80 109 | 98.28 144 | 95.76 55 | 97.18 125 | 99.88 17 | 92.74 109 | 100.00 1 | 98.67 65 | 99.88 63 | 99.99 15 |
|
MTAPA | | | 98.29 49 | 97.96 57 | 99.30 40 | 99.85 47 | 97.93 67 | 99.39 177 | 98.28 144 | 95.76 55 | 97.18 125 | 99.88 17 | 92.74 109 | 100.00 1 | 98.67 65 | 99.88 63 | 99.99 15 |
|
Regformer-1 | | | 98.79 21 | 98.60 21 | 99.36 38 | 99.85 47 | 98.34 52 | 99.87 79 | 98.52 87 | 96.05 48 | 99.41 46 | 99.79 51 | 94.93 55 | 99.76 104 | 99.07 39 | 99.90 59 | 99.99 15 |
|
Regformer-2 | | | 98.78 22 | 98.59 22 | 99.36 38 | 99.85 47 | 98.32 53 | 99.87 79 | 98.52 87 | 96.04 49 | 99.41 46 | 99.79 51 | 94.92 56 | 99.76 104 | 99.05 40 | 99.90 59 | 99.98 47 |
|
LS3D | | | 95.84 136 | 95.11 145 | 98.02 127 | 99.85 47 | 95.10 161 | 98.74 238 | 98.50 97 | 87.22 257 | 93.66 182 | 99.86 22 | 87.45 170 | 99.95 56 | 90.94 213 | 99.81 74 | 99.02 177 |
|
Regformer-3 | | | 98.58 31 | 98.41 29 | 99.10 61 | 99.84 52 | 97.57 76 | 99.66 139 | 98.52 87 | 95.79 52 | 99.01 69 | 99.77 57 | 94.40 64 | 99.75 107 | 98.82 56 | 99.83 68 | 99.98 47 |
|
Regformer-4 | | | 98.56 32 | 98.39 32 | 99.08 63 | 99.84 52 | 97.52 79 | 99.66 139 | 98.52 87 | 95.76 55 | 99.01 69 | 99.77 57 | 94.33 70 | 99.75 107 | 98.80 59 | 99.83 68 | 99.98 47 |
|
HPM-MVS | | | 97.96 61 | 97.72 62 | 98.68 85 | 99.84 52 | 96.39 119 | 99.90 68 | 98.17 157 | 92.61 158 | 98.62 86 | 99.57 92 | 91.87 126 | 99.67 122 | 98.87 54 | 99.99 17 | 99.99 15 |
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
EI-MVSNet-Vis-set | | | 98.27 50 | 98.11 49 | 98.75 83 | 99.83 55 | 96.59 113 | 99.40 174 | 98.51 93 | 95.29 68 | 98.51 90 | 99.76 61 | 93.60 92 | 99.71 115 | 98.53 73 | 99.52 93 | 99.95 68 |
|
save fliter | | | | | | 99.82 56 | 98.79 28 | 99.96 23 | 98.40 123 | 97.66 9 | | | | | | | |
|
PLC | | 95.54 3 | 97.93 63 | 97.89 59 | 98.05 126 | 99.82 56 | 94.77 171 | 99.92 60 | 98.46 101 | 93.93 114 | 97.20 124 | 99.27 114 | 95.44 41 | 99.97 47 | 97.41 108 | 99.51 95 | 99.41 148 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
APD-MVS_3200maxsize | | | 98.25 53 | 98.08 50 | 98.78 81 | 99.81 58 | 96.60 112 | 99.82 103 | 98.30 142 | 93.95 113 | 99.37 50 | 99.77 57 | 92.84 106 | 99.76 104 | 98.95 48 | 99.92 57 | 99.97 58 |
|
EI-MVSNet-UG-set | | | 98.14 56 | 97.99 53 | 98.60 92 | 99.80 59 | 96.27 120 | 99.36 182 | 98.50 97 | 95.21 71 | 98.30 99 | 99.75 66 | 93.29 98 | 99.73 114 | 98.37 77 | 99.30 102 | 99.81 86 |
|
HPM-MVS_fast | | | 97.80 71 | 97.50 70 | 98.68 85 | 99.79 60 | 96.42 116 | 99.88 76 | 98.16 160 | 91.75 184 | 98.94 73 | 99.54 95 | 91.82 128 | 99.65 124 | 97.62 105 | 99.99 17 | 99.99 15 |
|
旧先验1 | | | | | | 99.76 61 | 97.52 79 | | 98.64 62 | | | 99.85 26 | 95.63 35 | | | 99.94 49 | 99.99 15 |
|
OMC-MVS | | | 97.28 87 | 97.23 79 | 97.41 149 | 99.76 61 | 93.36 195 | 99.65 142 | 97.95 178 | 96.03 50 | 97.41 121 | 99.70 75 | 89.61 151 | 99.51 129 | 96.73 125 | 98.25 125 | 99.38 150 |
|
新几何1 | | | | | 99.42 32 | 99.75 63 | 98.27 54 | | 98.63 65 | 92.69 152 | 99.55 34 | 99.82 45 | 94.40 64 | 100.00 1 | 91.21 205 | 99.94 49 | 99.99 15 |
|
MP-MVS-pluss | | | 98.07 59 | 97.64 65 | 99.38 37 | 99.74 64 | 98.41 51 | 99.74 124 | 98.18 156 | 93.35 131 | 96.45 142 | 99.85 26 | 92.64 112 | 99.97 47 | 98.91 53 | 99.89 61 | 99.77 92 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
TSAR-MVS + MP. | | | 98.93 13 | 98.77 14 | 99.41 33 | 99.74 64 | 98.67 38 | 99.77 115 | 98.38 130 | 96.73 30 | 99.88 3 | 99.74 68 | 94.89 57 | 99.59 126 | 99.80 10 | 99.98 30 | 99.97 58 |
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition |
1121 | | | 98.03 60 | 97.57 69 | 99.40 35 | 99.74 64 | 98.21 55 | 98.31 262 | 98.62 66 | 92.78 147 | 99.53 36 | 99.83 42 | 95.08 47 | 100.00 1 | 94.36 160 | 99.92 57 | 99.99 15 |
|
test12 | | | | | 99.43 29 | 99.74 64 | 98.56 44 | | 98.40 123 | | 99.65 25 | | 94.76 58 | 99.75 107 | | 99.98 30 | 99.99 15 |
|
原ACMM1 | | | | | 98.96 74 | 99.73 68 | 96.99 101 | | 98.51 93 | 94.06 107 | 99.62 29 | 99.85 26 | 94.97 54 | 99.96 49 | 95.11 141 | 99.95 44 | 99.92 75 |
|
TSAR-MVS + GP. | | | 98.60 28 | 98.51 25 | 98.86 79 | 99.73 68 | 96.63 110 | 99.97 16 | 97.92 182 | 98.07 5 | 98.76 79 | 99.55 93 | 95.00 52 | 99.94 64 | 99.91 6 | 97.68 135 | 99.99 15 |
|
CANet | | | 98.27 50 | 97.82 60 | 99.63 10 | 99.72 70 | 99.10 13 | 99.98 8 | 98.51 93 | 97.00 23 | 98.52 89 | 99.71 73 | 87.80 166 | 99.95 56 | 99.75 15 | 99.38 100 | 99.83 84 |
|
F-COLMAP | | | 96.93 100 | 96.95 89 | 96.87 163 | 99.71 71 | 91.74 227 | 99.85 92 | 97.95 178 | 93.11 138 | 95.72 157 | 99.16 123 | 92.35 116 | 99.94 64 | 95.32 139 | 99.35 101 | 98.92 179 |
|
SD-MVS | | | 98.92 14 | 98.70 15 | 99.56 18 | 99.70 72 | 98.73 35 | 99.94 52 | 98.34 137 | 96.38 39 | 99.81 11 | 99.76 61 | 94.59 60 | 99.98 38 | 99.84 8 | 99.96 41 | 99.97 58 |
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 |
abl_6 | | | 97.67 76 | 97.34 76 | 98.66 87 | 99.68 73 | 96.11 134 | 99.68 136 | 98.14 163 | 93.80 119 | 99.27 57 | 99.70 75 | 88.65 162 | 99.98 38 | 97.46 107 | 99.72 79 | 99.89 78 |
|
ACMMP_NAP | | | 98.49 38 | 98.14 47 | 99.54 20 | 99.66 74 | 98.62 43 | 99.85 92 | 98.37 133 | 94.68 84 | 99.53 36 | 99.83 42 | 92.87 105 | 100.00 1 | 98.66 68 | 99.84 67 | 99.99 15 |
|
DeepPCF-MVS | | 95.94 2 | 97.71 75 | 98.98 9 | 93.92 244 | 99.63 75 | 81.76 310 | 99.96 23 | 98.56 76 | 99.47 1 | 99.19 62 | 99.99 1 | 94.16 77 | 100.00 1 | 99.92 4 | 99.93 55 | 100.00 1 |
|
EPNet | | | 98.49 38 | 98.40 31 | 98.77 82 | 99.62 76 | 96.80 107 | 99.90 68 | 99.51 15 | 97.60 10 | 99.20 60 | 99.36 110 | 93.71 89 | 99.91 70 | 97.99 92 | 98.71 114 | 99.61 115 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
PVSNet_BlendedMVS | | | 96.05 131 | 95.82 128 | 96.72 168 | 99.59 77 | 96.99 101 | 99.95 37 | 99.10 28 | 94.06 107 | 98.27 100 | 95.80 238 | 89.00 157 | 99.95 56 | 99.12 37 | 87.53 238 | 93.24 289 |
|
PVSNet_Blended | | | 97.94 62 | 97.64 65 | 98.83 80 | 99.59 77 | 96.99 101 | 100.00 1 | 99.10 28 | 95.38 65 | 98.27 100 | 99.08 126 | 89.00 157 | 99.95 56 | 99.12 37 | 99.25 103 | 99.57 126 |
|
PatchMatch-RL | | | 96.04 132 | 95.40 135 | 97.95 128 | 99.59 77 | 95.22 159 | 99.52 161 | 99.07 31 | 93.96 112 | 96.49 141 | 98.35 177 | 82.28 209 | 99.82 96 | 90.15 225 | 99.22 104 | 98.81 186 |
|
test222 | | | | | | 99.55 80 | 97.41 89 | 99.34 183 | 98.55 80 | 91.86 180 | 99.27 57 | 99.83 42 | 93.84 86 | | | 99.95 44 | 99.99 15 |
|
CNLPA | | | 97.76 73 | 97.38 73 | 98.92 77 | 99.53 81 | 96.84 105 | 99.87 79 | 98.14 163 | 93.78 120 | 96.55 140 | 99.69 78 | 92.28 118 | 99.98 38 | 97.13 114 | 99.44 98 | 99.93 71 |
|
API-MVS | | | 97.86 65 | 97.66 64 | 98.47 104 | 99.52 82 | 95.41 152 | 99.47 168 | 98.87 43 | 91.68 185 | 98.84 75 | 99.85 26 | 92.34 117 | 99.99 33 | 98.44 75 | 99.96 41 | 100.00 1 |
|
PVSNet | | 91.05 13 | 97.13 92 | 96.69 97 | 98.45 106 | 99.52 82 | 95.81 139 | 99.95 37 | 99.65 10 | 94.73 82 | 99.04 67 | 99.21 121 | 84.48 196 | 99.95 56 | 94.92 144 | 98.74 113 | 99.58 125 |
|
114514_t | | | 97.41 84 | 96.83 91 | 99.14 55 | 99.51 84 | 97.83 69 | 99.89 74 | 98.27 147 | 88.48 242 | 99.06 66 | 99.66 84 | 90.30 145 | 99.64 125 | 96.32 128 | 99.97 38 | 99.96 62 |
|
testdata | | | | | 98.42 109 | 99.47 85 | 95.33 154 | | 98.56 76 | 93.78 120 | 99.79 14 | 99.85 26 | 93.64 91 | 99.94 64 | 94.97 143 | 99.94 49 | 100.00 1 |
|
MAR-MVS | | | 97.43 80 | 97.19 80 | 98.15 122 | 99.47 85 | 94.79 170 | 99.05 214 | 98.76 50 | 92.65 156 | 98.66 84 | 99.82 45 | 88.52 163 | 99.98 38 | 98.12 84 | 99.63 84 | 99.67 105 |
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 |
DP-MVS | | | 94.54 164 | 93.42 175 | 97.91 131 | 99.46 87 | 94.04 181 | 98.93 225 | 97.48 224 | 81.15 301 | 90.04 212 | 99.55 93 | 87.02 175 | 99.95 56 | 88.97 233 | 98.11 126 | 99.73 96 |
|
MVS_111021_LR | | | 98.42 43 | 98.38 33 | 98.53 101 | 99.39 88 | 95.79 140 | 99.87 79 | 99.86 2 | 96.70 31 | 98.78 78 | 99.79 51 | 92.03 123 | 99.90 71 | 99.17 36 | 99.86 66 | 99.88 80 |
|
CHOSEN 280x420 | | | 99.01 11 | 99.03 7 | 98.95 75 | 99.38 89 | 98.87 22 | 98.46 255 | 99.42 20 | 97.03 22 | 99.02 68 | 99.09 125 | 99.35 1 | 98.21 202 | 99.73 19 | 99.78 75 | 99.77 92 |
|
MVS_111021_HR | | | 98.72 24 | 98.62 20 | 99.01 70 | 99.36 90 | 97.18 94 | 99.93 57 | 99.90 1 | 96.81 28 | 98.67 83 | 99.77 57 | 93.92 82 | 99.89 75 | 99.27 35 | 99.94 49 | 99.96 62 |
|
DPM-MVS | | | 98.83 19 | 98.46 27 | 99.97 1 | 99.33 91 | 99.92 1 | 99.96 23 | 98.44 103 | 97.96 7 | 99.55 34 | 99.94 4 | 97.18 16 | 100.00 1 | 93.81 174 | 99.94 49 | 99.98 47 |
|
TAPA-MVS | | 92.12 8 | 94.42 168 | 93.60 169 | 96.90 162 | 99.33 91 | 91.78 226 | 99.78 112 | 98.00 172 | 89.89 221 | 94.52 170 | 99.47 99 | 91.97 124 | 99.18 141 | 69.90 315 | 99.52 93 | 99.73 96 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
test_yl | | | 97.83 68 | 97.37 74 | 99.21 44 | 99.18 93 | 97.98 64 | 99.64 146 | 99.27 25 | 91.43 193 | 97.88 111 | 98.99 134 | 95.84 31 | 99.84 94 | 98.82 56 | 95.32 183 | 99.79 88 |
|
DCV-MVSNet | | | 97.83 68 | 97.37 74 | 99.21 44 | 99.18 93 | 97.98 64 | 99.64 146 | 99.27 25 | 91.43 193 | 97.88 111 | 98.99 134 | 95.84 31 | 99.84 94 | 98.82 56 | 95.32 183 | 99.79 88 |
|
DeepC-MVS | | 94.51 4 | 96.92 101 | 96.40 106 | 98.45 106 | 99.16 95 | 95.90 137 | 99.66 139 | 98.06 169 | 96.37 42 | 94.37 173 | 99.49 98 | 83.29 205 | 99.90 71 | 97.63 104 | 99.61 88 | 99.55 128 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
DELS-MVS | | | 98.54 34 | 98.22 42 | 99.50 25 | 99.15 96 | 98.65 41 | 100.00 1 | 98.58 72 | 97.70 8 | 98.21 104 | 99.24 119 | 92.58 113 | 99.94 64 | 98.63 70 | 99.94 49 | 99.92 75 |
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 |
Anonymous202405211 | | | 93.10 190 | 91.99 200 | 96.40 176 | 99.10 97 | 89.65 262 | 98.88 229 | 97.93 180 | 83.71 291 | 94.00 178 | 98.75 157 | 68.79 291 | 99.88 81 | 95.08 142 | 91.71 206 | 99.68 103 |
|
HyFIR lowres test | | | 96.66 114 | 96.43 105 | 97.36 153 | 99.05 98 | 93.91 184 | 99.70 133 | 99.80 3 | 90.54 210 | 96.26 147 | 98.08 182 | 92.15 121 | 98.23 201 | 96.84 124 | 95.46 180 | 99.93 71 |
|
LFMVS | | | 94.75 158 | 93.56 172 | 98.30 115 | 99.03 99 | 95.70 146 | 98.74 238 | 97.98 175 | 87.81 250 | 98.47 91 | 99.39 107 | 67.43 298 | 99.53 127 | 98.01 90 | 95.20 185 | 99.67 105 |
|
AllTest | | | 92.48 202 | 91.64 203 | 95.00 205 | 99.01 100 | 88.43 275 | 98.94 224 | 96.82 278 | 86.50 265 | 88.71 239 | 98.47 175 | 74.73 269 | 99.88 81 | 85.39 265 | 96.18 163 | 96.71 207 |
|
TestCases | | | | | 95.00 205 | 99.01 100 | 88.43 275 | | 96.82 278 | 86.50 265 | 88.71 239 | 98.47 175 | 74.73 269 | 99.88 81 | 85.39 265 | 96.18 163 | 96.71 207 |
|
COLMAP_ROB | | 90.47 14 | 92.18 207 | 91.49 207 | 94.25 231 | 99.00 102 | 88.04 281 | 98.42 260 | 96.70 282 | 82.30 298 | 88.43 245 | 99.01 131 | 76.97 250 | 99.85 86 | 86.11 262 | 96.50 160 | 94.86 214 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
HY-MVS | | 92.50 7 | 97.79 72 | 97.17 82 | 99.63 10 | 98.98 103 | 99.32 5 | 97.49 284 | 99.52 13 | 95.69 59 | 98.32 98 | 97.41 194 | 93.32 96 | 99.77 102 | 98.08 88 | 95.75 176 | 99.81 86 |
|
VNet | | | 97.21 91 | 96.57 101 | 99.13 60 | 98.97 104 | 97.82 70 | 99.03 216 | 99.21 27 | 94.31 97 | 99.18 63 | 98.88 147 | 86.26 182 | 99.89 75 | 98.93 50 | 94.32 191 | 99.69 102 |
|
thres200 | | | 96.96 98 | 96.21 109 | 99.22 43 | 98.97 104 | 98.84 25 | 99.85 92 | 99.71 5 | 93.17 136 | 96.26 147 | 98.88 147 | 89.87 149 | 99.51 129 | 94.26 164 | 94.91 186 | 99.31 158 |
|
tfpn200view9 | | | 96.79 105 | 95.99 114 | 99.19 46 | 98.94 106 | 98.82 26 | 99.78 112 | 99.71 5 | 92.86 141 | 96.02 150 | 98.87 149 | 89.33 152 | 99.50 131 | 93.84 171 | 94.57 187 | 99.27 161 |
|
thres400 | | | 96.78 106 | 95.99 114 | 99.16 51 | 98.94 106 | 98.82 26 | 99.78 112 | 99.71 5 | 92.86 141 | 96.02 150 | 98.87 149 | 89.33 152 | 99.50 131 | 93.84 171 | 94.57 187 | 99.16 168 |
|
Anonymous20231211 | | | 89.86 254 | 88.44 259 | 94.13 235 | 98.93 108 | 90.68 245 | 98.54 252 | 98.26 148 | 76.28 311 | 86.73 264 | 95.54 247 | 70.60 286 | 97.56 226 | 90.82 216 | 80.27 283 | 94.15 244 |
|
canonicalmvs | | | 97.09 95 | 96.32 107 | 99.39 36 | 98.93 108 | 98.95 17 | 99.72 131 | 97.35 235 | 94.45 89 | 97.88 111 | 99.42 103 | 86.71 177 | 99.52 128 | 98.48 74 | 93.97 196 | 99.72 99 |
|
EPNet_dtu | | | 95.71 140 | 95.39 136 | 96.66 170 | 98.92 110 | 93.41 193 | 99.57 154 | 98.90 40 | 96.19 46 | 97.52 118 | 98.56 169 | 92.65 111 | 97.36 231 | 77.89 301 | 98.33 121 | 99.20 166 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
WTY-MVS | | | 98.10 58 | 97.60 67 | 99.60 15 | 98.92 110 | 99.28 8 | 99.89 74 | 99.52 13 | 95.58 62 | 98.24 103 | 99.39 107 | 93.33 95 | 99.74 111 | 97.98 94 | 95.58 179 | 99.78 91 |
|
CHOSEN 1792x2688 | | | 96.81 104 | 96.53 102 | 97.64 141 | 98.91 112 | 93.07 197 | 99.65 142 | 99.80 3 | 95.64 60 | 95.39 161 | 98.86 151 | 84.35 198 | 99.90 71 | 96.98 119 | 99.16 105 | 99.95 68 |
|
thres100view900 | | | 96.74 109 | 95.92 124 | 99.18 47 | 98.90 113 | 98.77 30 | 99.74 124 | 99.71 5 | 92.59 160 | 95.84 153 | 98.86 151 | 89.25 154 | 99.50 131 | 93.84 171 | 94.57 187 | 99.27 161 |
|
thres600view7 | | | 96.69 112 | 95.87 127 | 99.14 55 | 98.90 113 | 98.78 29 | 99.74 124 | 99.71 5 | 92.59 160 | 95.84 153 | 98.86 151 | 89.25 154 | 99.50 131 | 93.44 183 | 94.50 190 | 99.16 168 |
|
MSDG | | | 94.37 169 | 93.36 179 | 97.40 150 | 98.88 115 | 93.95 183 | 99.37 180 | 97.38 233 | 85.75 276 | 90.80 205 | 99.17 122 | 84.11 200 | 99.88 81 | 86.35 259 | 98.43 119 | 98.36 191 |
|
Anonymous20240529 | | | 92.10 208 | 90.65 217 | 96.47 172 | 98.82 116 | 90.61 246 | 98.72 240 | 98.67 58 | 75.54 315 | 93.90 180 | 98.58 167 | 66.23 301 | 99.90 71 | 94.70 154 | 90.67 207 | 98.90 182 |
|
PVSNet_Blended_VisFu | | | 97.27 88 | 96.81 92 | 98.66 87 | 98.81 117 | 96.67 109 | 99.92 60 | 98.64 62 | 94.51 88 | 96.38 146 | 98.49 171 | 89.05 156 | 99.88 81 | 97.10 116 | 98.34 120 | 99.43 146 |
|
PS-MVSNAJ | | | 98.44 42 | 98.20 44 | 99.16 51 | 98.80 118 | 98.92 18 | 99.54 159 | 98.17 157 | 97.34 14 | 99.85 6 | 99.85 26 | 91.20 133 | 99.89 75 | 99.41 31 | 99.67 82 | 98.69 189 |
|
CANet_DTU | | | 96.76 107 | 96.15 110 | 98.60 92 | 98.78 119 | 97.53 78 | 99.84 96 | 97.63 201 | 97.25 18 | 99.20 60 | 99.64 87 | 81.36 217 | 99.98 38 | 92.77 193 | 98.89 109 | 98.28 192 |
|
alignmvs | | | 97.81 70 | 97.33 77 | 99.25 42 | 98.77 120 | 98.66 39 | 99.99 4 | 98.44 103 | 94.40 93 | 98.41 93 | 99.47 99 | 93.65 90 | 99.42 137 | 98.57 71 | 94.26 192 | 99.67 105 |
|
SteuartSystems-ACMMP | | | 99.02 10 | 98.97 10 | 99.18 47 | 98.72 121 | 97.71 72 | 99.98 8 | 98.44 103 | 96.85 24 | 99.80 12 | 99.91 10 | 97.57 6 | 99.85 86 | 99.44 29 | 99.99 17 | 99.99 15 |
Skip Steuart: Steuart Systems R&D Blog. |
xiu_mvs_v2_base | | | 98.23 54 | 97.97 54 | 99.02 69 | 98.69 122 | 98.66 39 | 99.52 161 | 98.08 168 | 97.05 21 | 99.86 4 | 99.86 22 | 90.65 142 | 99.71 115 | 99.39 32 | 98.63 115 | 98.69 189 |
|
MVSTER | | | 95.53 143 | 95.22 141 | 96.45 174 | 98.56 123 | 97.72 71 | 99.91 64 | 97.67 199 | 92.38 168 | 91.39 200 | 97.14 201 | 97.24 13 | 97.30 235 | 94.80 149 | 87.85 233 | 94.34 232 |
|
VDD-MVS | | | 93.77 179 | 92.94 183 | 96.27 180 | 98.55 124 | 90.22 254 | 98.77 237 | 97.79 193 | 90.85 206 | 96.82 133 | 99.42 103 | 61.18 315 | 99.77 102 | 98.95 48 | 94.13 193 | 98.82 185 |
|
tpmvs | | | 94.28 171 | 93.57 171 | 96.40 176 | 98.55 124 | 91.50 236 | 95.70 307 | 98.55 80 | 87.47 252 | 92.15 195 | 94.26 289 | 91.42 129 | 98.95 149 | 88.15 240 | 95.85 172 | 98.76 188 |
|
UGNet | | | 95.33 147 | 94.57 153 | 97.62 143 | 98.55 124 | 94.85 165 | 98.67 245 | 99.32 24 | 95.75 58 | 96.80 134 | 96.27 230 | 72.18 279 | 99.96 49 | 94.58 157 | 99.05 107 | 98.04 196 |
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 |
PCF-MVS | | 94.20 5 | 95.18 148 | 94.10 160 | 98.43 108 | 98.55 124 | 95.99 135 | 97.91 278 | 97.31 239 | 90.35 213 | 89.48 227 | 99.22 120 | 85.19 191 | 99.89 75 | 90.40 222 | 98.47 118 | 99.41 148 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
BH-w/o | | | 95.71 140 | 95.38 137 | 96.68 169 | 98.49 128 | 92.28 213 | 99.84 96 | 97.50 222 | 92.12 173 | 92.06 196 | 98.79 156 | 84.69 194 | 98.67 166 | 95.29 140 | 99.66 83 | 99.09 175 |
|
baseline1 | | | 95.78 137 | 94.86 148 | 98.54 99 | 98.47 129 | 98.07 59 | 99.06 210 | 97.99 173 | 92.68 154 | 94.13 177 | 98.62 164 | 93.28 99 | 98.69 165 | 93.79 176 | 85.76 246 | 98.84 184 |
|
EPMVS | | | 96.53 117 | 96.01 113 | 98.09 124 | 98.43 130 | 96.12 133 | 96.36 297 | 99.43 19 | 93.53 128 | 97.64 116 | 95.04 267 | 94.41 63 | 98.38 190 | 91.13 207 | 98.11 126 | 99.75 94 |
|
sss | | | 97.57 78 | 97.03 87 | 99.18 47 | 98.37 131 | 98.04 61 | 99.73 129 | 99.38 21 | 93.46 129 | 98.76 79 | 99.06 127 | 91.21 132 | 99.89 75 | 96.33 127 | 97.01 152 | 99.62 113 |
|
BH-untuned | | | 95.18 148 | 94.83 149 | 96.22 181 | 98.36 132 | 91.22 238 | 99.80 109 | 97.32 238 | 90.91 204 | 91.08 202 | 98.67 160 | 83.51 202 | 98.54 173 | 94.23 165 | 99.61 88 | 98.92 179 |
|
ET-MVSNet_ETH3D | | | 94.37 169 | 93.28 181 | 97.64 141 | 98.30 133 | 97.99 63 | 99.99 4 | 97.61 207 | 94.35 94 | 71.57 317 | 99.45 102 | 96.23 22 | 95.34 301 | 96.91 123 | 85.14 254 | 99.59 119 |
|
FMVSNet3 | | | 92.69 199 | 91.58 204 | 95.99 185 | 98.29 134 | 97.42 88 | 99.26 193 | 97.62 204 | 89.80 222 | 89.68 220 | 95.32 257 | 81.62 215 | 96.27 282 | 87.01 255 | 85.65 247 | 94.29 235 |
|
CS-MVS | | | 97.84 67 | 97.69 63 | 98.31 114 | 98.28 135 | 96.27 120 | 100.00 1 | 97.52 219 | 95.29 68 | 99.25 59 | 99.65 86 | 91.18 136 | 98.94 150 | 98.96 47 | 99.04 108 | 99.73 96 |
|
PMMVS | | | 96.76 107 | 96.76 95 | 96.76 166 | 98.28 135 | 92.10 217 | 99.91 64 | 97.98 175 | 94.12 102 | 99.53 36 | 99.39 107 | 86.93 176 | 98.73 161 | 96.95 121 | 97.73 133 | 99.45 143 |
|
PVSNet_0 | | 88.03 19 | 91.80 215 | 90.27 226 | 96.38 178 | 98.27 137 | 90.46 250 | 99.94 52 | 99.61 11 | 93.99 110 | 86.26 274 | 97.39 196 | 71.13 285 | 99.89 75 | 98.77 61 | 67.05 321 | 98.79 187 |
|
PatchFormer-LS_test | | | 97.01 96 | 96.79 94 | 97.69 139 | 98.26 138 | 94.80 168 | 98.66 248 | 98.13 165 | 93.70 124 | 97.86 114 | 98.80 155 | 95.54 36 | 98.67 166 | 94.12 167 | 96.00 167 | 99.60 117 |
|
DWT-MVSNet_test | | | 97.31 86 | 97.19 80 | 97.66 140 | 98.24 139 | 94.67 172 | 98.86 233 | 98.20 155 | 93.60 127 | 98.09 105 | 98.89 145 | 97.51 7 | 98.78 156 | 94.04 168 | 97.28 144 | 99.55 128 |
|
UA-Net | | | 96.54 116 | 95.96 121 | 98.27 116 | 98.23 140 | 95.71 145 | 98.00 276 | 98.45 102 | 93.72 123 | 98.41 93 | 99.27 114 | 88.71 161 | 99.66 123 | 91.19 206 | 97.69 134 | 99.44 145 |
|
GG-mvs-BLEND | | | | | 98.54 99 | 98.21 141 | 98.01 62 | 93.87 312 | 98.52 87 | | 97.92 109 | 97.92 187 | 99.02 2 | 97.94 216 | 98.17 81 | 99.58 90 | 99.67 105 |
|
mvs_anonymous | | | 95.65 142 | 95.03 146 | 97.53 144 | 98.19 142 | 95.74 143 | 99.33 184 | 97.49 223 | 90.87 205 | 90.47 208 | 97.10 203 | 88.23 164 | 97.16 243 | 95.92 133 | 97.66 136 | 99.68 103 |
|
MVS_Test | | | 96.46 119 | 95.74 129 | 98.61 91 | 98.18 143 | 97.23 92 | 99.31 187 | 97.15 250 | 91.07 201 | 98.84 75 | 97.05 207 | 88.17 165 | 98.97 148 | 94.39 159 | 97.50 138 | 99.61 115 |
|
BH-RMVSNet | | | 95.18 148 | 94.31 157 | 97.80 132 | 98.17 144 | 95.23 158 | 99.76 120 | 97.53 217 | 92.52 164 | 94.27 175 | 99.25 118 | 76.84 252 | 98.80 154 | 90.89 215 | 99.54 92 | 99.35 154 |
|
RPSCF | | | 91.80 215 | 92.79 186 | 88.83 297 | 98.15 145 | 69.87 323 | 98.11 272 | 96.60 285 | 83.93 289 | 94.33 174 | 99.27 114 | 79.60 235 | 99.46 136 | 91.99 197 | 93.16 203 | 97.18 205 |
|
EIA-MVS | | | 97.92 64 | 97.80 61 | 98.25 117 | 98.14 146 | 96.48 114 | 99.98 8 | 97.63 201 | 95.61 61 | 99.29 56 | 99.46 101 | 92.55 114 | 98.82 153 | 99.02 46 | 98.54 116 | 99.46 141 |
|
IS-MVSNet | | | 96.29 127 | 95.90 125 | 97.45 147 | 98.13 147 | 94.80 168 | 99.08 205 | 97.61 207 | 92.02 177 | 95.54 160 | 98.96 140 | 90.64 143 | 98.08 206 | 93.73 179 | 97.41 142 | 99.47 140 |
|
ab-mvs | | | 94.69 159 | 93.42 175 | 98.51 102 | 98.07 148 | 96.26 122 | 96.49 296 | 98.68 55 | 90.31 214 | 94.54 169 | 97.00 209 | 76.30 257 | 99.71 115 | 95.98 132 | 93.38 201 | 99.56 127 |
|
XVG-OURS-SEG-HR | | | 94.79 155 | 94.70 152 | 95.08 202 | 98.05 149 | 89.19 265 | 99.08 205 | 97.54 215 | 93.66 125 | 94.87 167 | 99.58 91 | 78.78 241 | 99.79 99 | 97.31 110 | 93.40 200 | 96.25 209 |
|
ETV-MVS | | | 97.53 79 | 97.46 71 | 97.76 136 | 98.04 150 | 94.84 166 | 99.98 8 | 97.61 207 | 94.41 92 | 97.90 110 | 99.59 90 | 92.40 115 | 98.87 151 | 98.04 89 | 99.13 106 | 99.59 119 |
|
XVG-OURS | | | 94.82 154 | 94.74 151 | 95.06 203 | 98.00 151 | 89.19 265 | 99.08 205 | 97.55 213 | 94.10 103 | 94.71 168 | 99.62 88 | 80.51 228 | 99.74 111 | 96.04 131 | 93.06 204 | 96.25 209 |
|
dp | | | 95.05 151 | 94.43 155 | 96.91 161 | 97.99 152 | 92.73 203 | 96.29 299 | 97.98 175 | 89.70 223 | 95.93 152 | 94.67 280 | 93.83 87 | 98.45 179 | 86.91 258 | 96.53 159 | 99.54 132 |
|
tpmrst | | | 96.27 129 | 95.98 116 | 97.13 157 | 97.96 153 | 93.15 196 | 96.34 298 | 98.17 157 | 92.07 174 | 98.71 82 | 95.12 265 | 93.91 83 | 98.73 161 | 94.91 146 | 96.62 157 | 99.50 138 |
|
TR-MVS | | | 94.54 164 | 93.56 172 | 97.49 146 | 97.96 153 | 94.34 176 | 98.71 241 | 97.51 221 | 90.30 215 | 94.51 171 | 98.69 159 | 75.56 262 | 98.77 158 | 92.82 192 | 95.99 168 | 99.35 154 |
|
Vis-MVSNet (Re-imp) | | | 96.32 124 | 95.98 116 | 97.35 154 | 97.93 155 | 94.82 167 | 99.47 168 | 98.15 162 | 91.83 181 | 95.09 165 | 99.11 124 | 91.37 131 | 97.47 229 | 93.47 182 | 97.43 139 | 99.74 95 |
|
MDTV_nov1_ep13 | | | | 95.69 130 | | 97.90 156 | 94.15 179 | 95.98 303 | 98.44 103 | 93.12 137 | 97.98 108 | 95.74 240 | 95.10 46 | 98.58 170 | 90.02 226 | 96.92 154 | |
|
Fast-Effi-MVS+ | | | 95.02 152 | 94.19 158 | 97.52 145 | 97.88 157 | 94.55 173 | 99.97 16 | 97.08 254 | 88.85 237 | 94.47 172 | 97.96 186 | 84.59 195 | 98.41 182 | 89.84 227 | 97.10 149 | 99.59 119 |
|
ADS-MVSNet2 | | | 93.80 178 | 93.88 164 | 93.55 253 | 97.87 158 | 85.94 290 | 94.24 308 | 96.84 275 | 90.07 217 | 96.43 143 | 94.48 285 | 90.29 146 | 95.37 300 | 87.44 246 | 97.23 146 | 99.36 152 |
|
ADS-MVSNet | | | 94.79 155 | 94.02 161 | 97.11 159 | 97.87 158 | 93.79 185 | 94.24 308 | 98.16 160 | 90.07 217 | 96.43 143 | 94.48 285 | 90.29 146 | 98.19 203 | 87.44 246 | 97.23 146 | 99.36 152 |
|
Effi-MVS+ | | | 96.30 126 | 95.69 130 | 98.16 119 | 97.85 160 | 96.26 122 | 97.41 285 | 97.21 243 | 90.37 212 | 98.65 85 | 98.58 167 | 86.61 179 | 98.70 164 | 97.11 115 | 97.37 143 | 99.52 135 |
|
PatchmatchNet | | | 95.94 134 | 95.45 134 | 97.39 151 | 97.83 161 | 94.41 175 | 96.05 302 | 98.40 123 | 92.86 141 | 97.09 127 | 95.28 262 | 94.21 76 | 98.07 208 | 89.26 231 | 98.11 126 | 99.70 100 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
cascas | | | 94.64 162 | 93.61 167 | 97.74 138 | 97.82 162 | 96.26 122 | 99.96 23 | 97.78 194 | 85.76 274 | 94.00 178 | 97.54 191 | 76.95 251 | 99.21 140 | 97.23 112 | 95.43 181 | 97.76 202 |
|
1112_ss | | | 96.01 133 | 95.20 142 | 98.42 109 | 97.80 163 | 96.41 117 | 99.65 142 | 96.66 283 | 92.71 150 | 92.88 191 | 99.40 105 | 92.16 120 | 99.30 138 | 91.92 198 | 93.66 197 | 99.55 128 |
|
Test_1112_low_res | | | 95.72 138 | 94.83 149 | 98.42 109 | 97.79 164 | 96.41 117 | 99.65 142 | 96.65 284 | 92.70 151 | 92.86 192 | 96.13 234 | 92.15 121 | 99.30 138 | 91.88 199 | 93.64 198 | 99.55 128 |
|
Effi-MVS+-dtu | | | 94.53 166 | 95.30 139 | 92.22 271 | 97.77 165 | 82.54 304 | 99.59 152 | 97.06 255 | 94.92 75 | 95.29 163 | 95.37 255 | 85.81 184 | 97.89 217 | 94.80 149 | 97.07 150 | 96.23 211 |
|
mvs-test1 | | | 95.53 143 | 95.97 119 | 94.20 232 | 97.77 165 | 85.44 294 | 99.95 37 | 97.06 255 | 94.92 75 | 96.58 138 | 98.72 158 | 85.81 184 | 98.98 147 | 94.80 149 | 98.11 126 | 98.18 193 |
|
tpm cat1 | | | 93.51 184 | 92.52 192 | 96.47 172 | 97.77 165 | 91.47 237 | 96.13 300 | 98.06 169 | 80.98 302 | 92.91 190 | 93.78 294 | 89.66 150 | 98.87 151 | 87.03 254 | 96.39 161 | 99.09 175 |
|
xiu_mvs_v1_base_debu | | | 97.43 80 | 97.06 83 | 98.55 96 | 97.74 168 | 98.14 56 | 99.31 187 | 97.86 188 | 96.43 36 | 99.62 29 | 99.69 78 | 85.56 187 | 99.68 119 | 99.05 40 | 98.31 122 | 97.83 198 |
|
xiu_mvs_v1_base | | | 97.43 80 | 97.06 83 | 98.55 96 | 97.74 168 | 98.14 56 | 99.31 187 | 97.86 188 | 96.43 36 | 99.62 29 | 99.69 78 | 85.56 187 | 99.68 119 | 99.05 40 | 98.31 122 | 97.83 198 |
|
xiu_mvs_v1_base_debi | | | 97.43 80 | 97.06 83 | 98.55 96 | 97.74 168 | 98.14 56 | 99.31 187 | 97.86 188 | 96.43 36 | 99.62 29 | 99.69 78 | 85.56 187 | 99.68 119 | 99.05 40 | 98.31 122 | 97.83 198 |
|
EPP-MVSNet | | | 96.69 112 | 96.60 99 | 96.96 160 | 97.74 168 | 93.05 199 | 99.37 180 | 98.56 76 | 88.75 238 | 95.83 155 | 99.01 131 | 96.01 23 | 98.56 171 | 96.92 122 | 97.20 148 | 99.25 163 |
|
gg-mvs-nofinetune | | | 93.51 184 | 91.86 202 | 98.47 104 | 97.72 172 | 97.96 66 | 92.62 316 | 98.51 93 | 74.70 317 | 97.33 122 | 69.59 327 | 98.91 3 | 97.79 219 | 97.77 101 | 99.56 91 | 99.67 105 |
|
IB-MVS | | 92.85 6 | 94.99 153 | 93.94 162 | 98.16 119 | 97.72 172 | 95.69 147 | 99.99 4 | 98.81 47 | 94.28 98 | 92.70 193 | 96.90 211 | 95.08 47 | 99.17 142 | 96.07 130 | 73.88 312 | 99.60 117 |
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 |
thisisatest0515 | | | 97.41 84 | 97.02 88 | 98.59 94 | 97.71 174 | 97.52 79 | 99.97 16 | 98.54 84 | 91.83 181 | 97.45 120 | 99.04 128 | 97.50 8 | 99.10 143 | 94.75 152 | 96.37 162 | 99.16 168 |
|
diffmvs | | | 97.00 97 | 96.64 98 | 98.09 124 | 97.64 175 | 96.17 129 | 99.81 105 | 97.19 244 | 94.67 85 | 98.95 72 | 99.28 111 | 86.43 180 | 98.76 159 | 98.37 77 | 97.42 141 | 99.33 156 |
|
Vis-MVSNet | | | 95.72 138 | 95.15 144 | 97.45 147 | 97.62 176 | 94.28 177 | 99.28 191 | 98.24 149 | 94.27 99 | 96.84 132 | 98.94 143 | 79.39 236 | 98.76 159 | 93.25 184 | 98.49 117 | 99.30 159 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
thisisatest0530 | | | 97.10 93 | 96.72 96 | 98.22 118 | 97.60 177 | 96.70 108 | 99.92 60 | 98.54 84 | 91.11 200 | 97.07 128 | 98.97 138 | 97.47 9 | 99.03 145 | 93.73 179 | 96.09 165 | 98.92 179 |
|
LCM-MVSNet-Re | | | 92.31 205 | 92.60 189 | 91.43 279 | 97.53 178 | 79.27 318 | 99.02 217 | 91.83 326 | 92.07 174 | 80.31 297 | 94.38 288 | 83.50 203 | 95.48 298 | 97.22 113 | 97.58 137 | 99.54 132 |
|
GBi-Net | | | 90.88 230 | 89.82 234 | 94.08 236 | 97.53 178 | 91.97 218 | 98.43 257 | 96.95 266 | 87.05 258 | 89.68 220 | 94.72 276 | 71.34 282 | 96.11 286 | 87.01 255 | 85.65 247 | 94.17 241 |
|
test1 | | | 90.88 230 | 89.82 234 | 94.08 236 | 97.53 178 | 91.97 218 | 98.43 257 | 96.95 266 | 87.05 258 | 89.68 220 | 94.72 276 | 71.34 282 | 96.11 286 | 87.01 255 | 85.65 247 | 94.17 241 |
|
FMVSNet2 | | | 91.02 227 | 89.56 238 | 95.41 196 | 97.53 178 | 95.74 143 | 98.98 219 | 97.41 231 | 87.05 258 | 88.43 245 | 95.00 270 | 71.34 282 | 96.24 284 | 85.12 267 | 85.21 252 | 94.25 238 |
|
tttt0517 | | | 96.85 102 | 96.49 103 | 97.92 130 | 97.48 182 | 95.89 138 | 99.85 92 | 98.54 84 | 90.72 209 | 96.63 137 | 98.93 144 | 97.47 9 | 99.02 146 | 93.03 191 | 95.76 175 | 98.85 183 |
|
CDS-MVSNet | | | 96.34 123 | 96.07 111 | 97.13 157 | 97.37 183 | 94.96 163 | 99.53 160 | 97.91 183 | 91.55 188 | 95.37 162 | 98.32 178 | 95.05 49 | 97.13 246 | 93.80 175 | 95.75 176 | 99.30 159 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
TESTMET0.1,1 | | | 96.74 109 | 96.26 108 | 98.16 119 | 97.36 184 | 96.48 114 | 99.96 23 | 98.29 143 | 91.93 178 | 95.77 156 | 98.07 183 | 95.54 36 | 98.29 196 | 90.55 218 | 98.89 109 | 99.70 100 |
|
miper_lstm_enhance | | | 91.81 212 | 91.39 209 | 93.06 263 | 97.34 185 | 89.18 267 | 99.38 178 | 96.79 280 | 86.70 263 | 87.47 256 | 95.22 263 | 90.00 148 | 95.86 296 | 88.26 238 | 81.37 271 | 94.15 244 |
|
baseline | | | 96.43 120 | 95.98 116 | 97.76 136 | 97.34 185 | 95.17 160 | 99.51 163 | 97.17 247 | 93.92 115 | 96.90 131 | 99.28 111 | 85.37 190 | 98.64 168 | 97.50 106 | 96.86 156 | 99.46 141 |
|
casdiffmvs | | | 96.42 121 | 95.97 119 | 97.77 135 | 97.30 187 | 94.98 162 | 99.84 96 | 97.09 253 | 93.75 122 | 96.58 138 | 99.26 117 | 85.07 192 | 98.78 156 | 97.77 101 | 97.04 151 | 99.54 132 |
|
MVSFormer | | | 96.94 99 | 96.60 99 | 97.95 128 | 97.28 188 | 97.70 74 | 99.55 157 | 97.27 240 | 91.17 197 | 99.43 44 | 99.54 95 | 90.92 140 | 96.89 261 | 94.67 155 | 99.62 85 | 99.25 163 |
|
lupinMVS | | | 97.85 66 | 97.60 67 | 98.62 90 | 97.28 188 | 97.70 74 | 99.99 4 | 97.55 213 | 95.50 64 | 99.43 44 | 99.67 82 | 90.92 140 | 98.71 163 | 98.40 76 | 99.62 85 | 99.45 143 |
|
SCA | | | 94.69 159 | 93.81 166 | 97.33 155 | 97.10 190 | 94.44 174 | 98.86 233 | 98.32 140 | 93.30 133 | 96.17 149 | 95.59 245 | 76.48 255 | 97.95 214 | 91.06 209 | 97.43 139 | 99.59 119 |
|
TAMVS | | | 95.85 135 | 95.58 132 | 96.65 171 | 97.07 191 | 93.50 190 | 99.17 199 | 97.82 192 | 91.39 196 | 95.02 166 | 98.01 184 | 92.20 119 | 97.30 235 | 93.75 178 | 95.83 173 | 99.14 171 |
|
Fast-Effi-MVS+-dtu | | | 93.72 181 | 93.86 165 | 93.29 256 | 97.06 192 | 86.16 288 | 99.80 109 | 96.83 276 | 92.66 155 | 92.58 194 | 97.83 188 | 81.39 216 | 97.67 223 | 89.75 228 | 96.87 155 | 96.05 213 |
|
MVS_0304 | | | 89.28 263 | 88.31 261 | 92.21 272 | 97.05 193 | 86.53 287 | 97.76 281 | 99.57 12 | 85.58 279 | 93.86 181 | 92.71 302 | 51.04 325 | 96.30 281 | 84.49 271 | 92.72 205 | 93.79 272 |
|
CostFormer | | | 96.10 130 | 95.88 126 | 96.78 165 | 97.03 194 | 92.55 209 | 97.08 289 | 97.83 191 | 90.04 219 | 98.72 81 | 94.89 274 | 95.01 51 | 98.29 196 | 96.54 126 | 95.77 174 | 99.50 138 |
|
test-LLR | | | 96.47 118 | 96.04 112 | 97.78 133 | 97.02 195 | 95.44 150 | 99.96 23 | 98.21 152 | 94.07 105 | 95.55 158 | 96.38 226 | 93.90 84 | 98.27 199 | 90.42 220 | 98.83 111 | 99.64 111 |
|
test-mter | | | 96.39 122 | 95.93 123 | 97.78 133 | 97.02 195 | 95.44 150 | 99.96 23 | 98.21 152 | 91.81 183 | 95.55 158 | 96.38 226 | 95.17 44 | 98.27 199 | 90.42 220 | 98.83 111 | 99.64 111 |
|
gm-plane-assit | | | | | | 96.97 197 | 93.76 187 | | | 91.47 191 | | 98.96 140 | | 98.79 155 | 94.92 144 | | |
|
QAPM | | | 95.40 146 | 94.17 159 | 99.10 61 | 96.92 198 | 97.71 72 | 99.40 174 | 98.68 55 | 89.31 225 | 88.94 238 | 98.89 145 | 82.48 208 | 99.96 49 | 93.12 190 | 99.83 68 | 99.62 113 |
|
tpm2 | | | 95.47 145 | 95.18 143 | 96.35 179 | 96.91 199 | 91.70 231 | 96.96 292 | 97.93 180 | 88.04 248 | 98.44 92 | 95.40 251 | 93.32 96 | 97.97 211 | 94.00 169 | 95.61 178 | 99.38 150 |
|
FMVSNet5 | | | 88.32 268 | 87.47 269 | 90.88 282 | 96.90 200 | 88.39 277 | 97.28 287 | 95.68 302 | 82.60 297 | 84.67 283 | 92.40 305 | 79.83 234 | 91.16 321 | 76.39 308 | 81.51 270 | 93.09 291 |
|
3Dnovator+ | | 91.53 11 | 96.31 125 | 95.24 140 | 99.52 22 | 96.88 201 | 98.64 42 | 99.72 131 | 98.24 149 | 95.27 70 | 88.42 247 | 98.98 136 | 82.76 207 | 99.94 64 | 97.10 116 | 99.83 68 | 99.96 62 |
|
Patchmatch-test | | | 92.65 201 | 91.50 206 | 96.10 184 | 96.85 202 | 90.49 249 | 91.50 321 | 97.19 244 | 82.76 296 | 90.23 209 | 95.59 245 | 95.02 50 | 98.00 210 | 77.41 303 | 96.98 153 | 99.82 85 |
|
MVS | | | 96.60 115 | 95.56 133 | 99.72 7 | 96.85 202 | 99.22 11 | 98.31 262 | 98.94 36 | 91.57 187 | 90.90 204 | 99.61 89 | 86.66 178 | 99.96 49 | 97.36 109 | 99.88 63 | 99.99 15 |
|
3Dnovator | | 91.47 12 | 96.28 128 | 95.34 138 | 99.08 63 | 96.82 204 | 97.47 85 | 99.45 171 | 98.81 47 | 95.52 63 | 89.39 228 | 99.00 133 | 81.97 210 | 99.95 56 | 97.27 111 | 99.83 68 | 99.84 83 |
|
EI-MVSNet | | | 93.73 180 | 93.40 178 | 94.74 212 | 96.80 205 | 92.69 204 | 99.06 210 | 97.67 199 | 88.96 233 | 91.39 200 | 99.02 129 | 88.75 160 | 97.30 235 | 91.07 208 | 87.85 233 | 94.22 239 |
|
CVMVSNet | | | 94.68 161 | 94.94 147 | 93.89 246 | 96.80 205 | 86.92 286 | 99.06 210 | 98.98 34 | 94.45 89 | 94.23 176 | 99.02 129 | 85.60 186 | 95.31 302 | 90.91 214 | 95.39 182 | 99.43 146 |
|
IterMVS-LS | | | 92.69 199 | 92.11 197 | 94.43 227 | 96.80 205 | 92.74 202 | 99.45 171 | 96.89 272 | 88.98 231 | 89.65 223 | 95.38 254 | 88.77 159 | 96.34 278 | 90.98 212 | 82.04 267 | 94.22 239 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
IterMVS | | | 90.91 229 | 90.17 229 | 93.12 260 | 96.78 208 | 90.42 252 | 98.89 227 | 97.05 257 | 89.03 229 | 86.49 269 | 95.42 250 | 76.59 254 | 95.02 304 | 87.22 251 | 84.09 258 | 93.93 262 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
1314 | | | 96.84 103 | 95.96 121 | 99.48 28 | 96.74 209 | 98.52 46 | 98.31 262 | 98.86 44 | 95.82 51 | 89.91 215 | 98.98 136 | 87.49 169 | 99.96 49 | 97.80 98 | 99.73 78 | 99.96 62 |
|
IterMVS-SCA-FT | | | 90.85 232 | 90.16 230 | 92.93 264 | 96.72 210 | 89.96 257 | 98.89 227 | 96.99 262 | 88.95 234 | 86.63 266 | 95.67 242 | 76.48 255 | 95.00 305 | 87.04 253 | 84.04 261 | 93.84 269 |
|
MVS-HIRNet | | | 86.22 275 | 83.19 285 | 95.31 197 | 96.71 211 | 90.29 253 | 92.12 318 | 97.33 237 | 62.85 323 | 86.82 263 | 70.37 326 | 69.37 290 | 97.49 228 | 75.12 310 | 97.99 132 | 98.15 194 |
|
VDDNet | | | 93.12 189 | 91.91 201 | 96.76 166 | 96.67 212 | 92.65 207 | 98.69 243 | 98.21 152 | 82.81 295 | 97.75 115 | 99.28 111 | 61.57 313 | 99.48 135 | 98.09 87 | 94.09 194 | 98.15 194 |
|
MIMVSNet | | | 90.30 245 | 88.67 256 | 95.17 201 | 96.45 213 | 91.64 233 | 92.39 317 | 97.15 250 | 85.99 271 | 90.50 207 | 93.19 300 | 66.95 299 | 94.86 308 | 82.01 287 | 93.43 199 | 99.01 178 |
|
CR-MVSNet | | | 93.45 187 | 92.62 188 | 95.94 186 | 96.29 214 | 92.66 205 | 92.01 319 | 96.23 292 | 92.62 157 | 96.94 129 | 93.31 298 | 91.04 138 | 96.03 291 | 79.23 297 | 95.96 169 | 99.13 173 |
|
RPMNet | | | 89.39 260 | 87.20 271 | 95.94 186 | 96.29 214 | 92.66 205 | 92.01 319 | 97.63 201 | 70.19 322 | 96.94 129 | 85.87 320 | 87.25 172 | 96.03 291 | 62.69 324 | 95.96 169 | 99.13 173 |
|
Patchmtry | | | 89.70 256 | 88.49 258 | 93.33 255 | 96.24 216 | 89.94 260 | 91.37 322 | 96.23 292 | 78.22 308 | 87.69 253 | 93.31 298 | 91.04 138 | 96.03 291 | 80.18 296 | 82.10 266 | 94.02 252 |
|
JIA-IIPM | | | 91.76 218 | 90.70 216 | 94.94 207 | 96.11 217 | 87.51 283 | 93.16 315 | 98.13 165 | 75.79 314 | 97.58 117 | 77.68 324 | 92.84 106 | 97.97 211 | 88.47 237 | 96.54 158 | 99.33 156 |
|
OpenMVS | | 90.15 15 | 94.77 157 | 93.59 170 | 98.33 113 | 96.07 218 | 97.48 84 | 99.56 155 | 98.57 74 | 90.46 211 | 86.51 268 | 98.95 142 | 78.57 243 | 99.94 64 | 93.86 170 | 99.74 77 | 97.57 203 |
|
PAPM | | | 98.60 28 | 98.42 28 | 99.14 55 | 96.05 219 | 98.96 16 | 99.90 68 | 99.35 23 | 96.68 32 | 98.35 97 | 99.66 84 | 96.45 20 | 98.51 174 | 99.45 28 | 99.89 61 | 99.96 62 |
|
CLD-MVS | | | 94.06 173 | 93.90 163 | 94.55 221 | 96.02 220 | 90.69 244 | 99.98 8 | 97.72 196 | 96.62 34 | 91.05 203 | 98.85 154 | 77.21 248 | 98.47 175 | 98.11 85 | 89.51 213 | 94.48 219 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
PatchT | | | 90.38 242 | 88.75 255 | 95.25 198 | 95.99 221 | 90.16 255 | 91.22 323 | 97.54 215 | 76.80 310 | 97.26 123 | 86.01 319 | 91.88 125 | 96.07 290 | 66.16 321 | 95.91 171 | 99.51 136 |
|
ACMH+ | | 89.98 16 | 90.35 243 | 89.54 239 | 92.78 267 | 95.99 221 | 86.12 289 | 98.81 235 | 97.18 246 | 89.38 224 | 83.14 289 | 97.76 189 | 68.42 295 | 98.43 180 | 89.11 232 | 86.05 245 | 93.78 273 |
|
DeepMVS_CX | | | | | 82.92 308 | 95.98 223 | 58.66 328 | | 96.01 297 | 92.72 149 | 78.34 304 | 95.51 248 | 58.29 318 | 98.08 206 | 82.57 283 | 85.29 250 | 92.03 302 |
|
ACMP | | 92.05 9 | 92.74 197 | 92.42 194 | 93.73 247 | 95.91 224 | 88.72 270 | 99.81 105 | 97.53 217 | 94.13 101 | 87.00 262 | 98.23 179 | 74.07 273 | 98.47 175 | 96.22 129 | 88.86 220 | 93.99 257 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
HQP-NCC | | | | | | 95.78 225 | | 99.87 79 | | 96.82 25 | 93.37 183 | | | | | | |
|
ACMP_Plane | | | | | | 95.78 225 | | 99.87 79 | | 96.82 25 | 93.37 183 | | | | | | |
|
HQP-MVS | | | 94.61 163 | 94.50 154 | 94.92 208 | 95.78 225 | 91.85 223 | 99.87 79 | 97.89 184 | 96.82 25 | 93.37 183 | 98.65 161 | 80.65 226 | 98.39 186 | 97.92 96 | 89.60 208 | 94.53 215 |
|
NP-MVS | | | | | | 95.77 228 | 91.79 225 | | | | | 98.65 161 | | | | | |
|
plane_prior6 | | | | | | 95.76 229 | 91.72 230 | | | | | | 80.47 230 | | | | |
|
ACMM | | 91.95 10 | 92.88 194 | 92.52 192 | 93.98 243 | 95.75 230 | 89.08 268 | 99.77 115 | 97.52 219 | 93.00 139 | 89.95 214 | 97.99 185 | 76.17 259 | 98.46 178 | 93.63 181 | 88.87 219 | 94.39 227 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
GA-MVS | | | 93.83 175 | 92.84 184 | 96.80 164 | 95.73 231 | 93.57 189 | 99.88 76 | 97.24 242 | 92.57 162 | 92.92 189 | 96.66 219 | 78.73 242 | 97.67 223 | 87.75 244 | 94.06 195 | 99.17 167 |
|
plane_prior1 | | | | | | 95.73 231 | | | | | | | | | | | |
|
jason | | | 97.24 89 | 96.86 90 | 98.38 112 | 95.73 231 | 97.32 90 | 99.97 16 | 97.40 232 | 95.34 67 | 98.60 88 | 99.54 95 | 87.70 167 | 98.56 171 | 97.94 95 | 99.47 96 | 99.25 163 |
jason: jason. |
HQP_MVS | | | 94.49 167 | 94.36 156 | 94.87 209 | 95.71 234 | 91.74 227 | 99.84 96 | 97.87 186 | 96.38 39 | 93.01 187 | 98.59 165 | 80.47 230 | 98.37 191 | 97.79 99 | 89.55 211 | 94.52 217 |
|
plane_prior7 | | | | | | 95.71 234 | 91.59 235 | | | | | | | | | | |
|
ITE_SJBPF | | | | | 92.38 269 | 95.69 236 | 85.14 295 | | 95.71 301 | 92.81 144 | 89.33 231 | 98.11 181 | 70.23 288 | 98.42 181 | 85.91 263 | 88.16 231 | 93.59 281 |
|
ACMH | | 89.72 17 | 90.64 236 | 89.63 236 | 93.66 251 | 95.64 237 | 88.64 273 | 98.55 250 | 97.45 225 | 89.03 229 | 81.62 293 | 97.61 190 | 69.75 289 | 98.41 182 | 89.37 229 | 87.62 237 | 93.92 263 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
baseline2 | | | 96.71 111 | 96.49 103 | 97.37 152 | 95.63 238 | 95.96 136 | 99.74 124 | 98.88 42 | 92.94 140 | 91.61 198 | 98.97 138 | 97.72 5 | 98.62 169 | 94.83 148 | 98.08 130 | 97.53 204 |
|
FMVSNet1 | | | 88.50 267 | 86.64 272 | 94.08 236 | 95.62 239 | 91.97 218 | 98.43 257 | 96.95 266 | 83.00 294 | 86.08 276 | 94.72 276 | 59.09 317 | 96.11 286 | 81.82 289 | 84.07 259 | 94.17 241 |
|
LPG-MVS_test | | | 92.96 192 | 92.71 187 | 93.71 249 | 95.43 240 | 88.67 271 | 99.75 121 | 97.62 204 | 92.81 144 | 90.05 210 | 98.49 171 | 75.24 265 | 98.40 184 | 95.84 136 | 89.12 215 | 94.07 249 |
|
LGP-MVS_train | | | | | 93.71 249 | 95.43 240 | 88.67 271 | | 97.62 204 | 92.81 144 | 90.05 210 | 98.49 171 | 75.24 265 | 98.40 184 | 95.84 136 | 89.12 215 | 94.07 249 |
|
tpm | | | 93.70 182 | 93.41 177 | 94.58 219 | 95.36 242 | 87.41 284 | 97.01 290 | 96.90 271 | 90.85 206 | 96.72 136 | 94.14 290 | 90.40 144 | 96.84 264 | 90.75 217 | 88.54 227 | 99.51 136 |
|
D2MVS | | | 92.76 196 | 92.59 190 | 93.27 257 | 95.13 243 | 89.54 264 | 99.69 134 | 99.38 21 | 92.26 170 | 87.59 254 | 94.61 282 | 85.05 193 | 97.79 219 | 91.59 202 | 88.01 232 | 92.47 298 |
|
VPA-MVSNet | | | 92.70 198 | 91.55 205 | 96.16 182 | 95.09 244 | 96.20 127 | 98.88 229 | 99.00 33 | 91.02 203 | 91.82 197 | 95.29 261 | 76.05 261 | 97.96 213 | 95.62 138 | 81.19 272 | 94.30 234 |
|
LTVRE_ROB | | 88.28 18 | 90.29 246 | 89.05 250 | 94.02 239 | 95.08 245 | 90.15 256 | 97.19 288 | 97.43 227 | 84.91 284 | 83.99 286 | 97.06 206 | 74.00 274 | 98.28 198 | 84.08 273 | 87.71 235 | 93.62 280 |
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 |
TinyColmap | | | 87.87 271 | 86.51 273 | 91.94 275 | 95.05 246 | 85.57 292 | 97.65 282 | 94.08 320 | 84.40 287 | 81.82 292 | 96.85 215 | 62.14 312 | 98.33 193 | 80.25 295 | 86.37 244 | 91.91 304 |
|
test0.0.03 1 | | | 93.86 174 | 93.61 167 | 94.64 216 | 95.02 247 | 92.18 216 | 99.93 57 | 98.58 72 | 94.07 105 | 87.96 251 | 98.50 170 | 93.90 84 | 94.96 306 | 81.33 290 | 93.17 202 | 96.78 206 |
|
UniMVSNet (Re) | | | 93.07 191 | 92.13 196 | 95.88 188 | 94.84 248 | 96.24 126 | 99.88 76 | 98.98 34 | 92.49 166 | 89.25 232 | 95.40 251 | 87.09 174 | 97.14 245 | 93.13 189 | 78.16 294 | 94.26 236 |
|
USDC | | | 90.00 253 | 88.96 251 | 93.10 262 | 94.81 249 | 88.16 279 | 98.71 241 | 95.54 306 | 93.66 125 | 83.75 288 | 97.20 200 | 65.58 303 | 98.31 195 | 83.96 276 | 87.49 239 | 92.85 295 |
|
VPNet | | | 91.81 212 | 90.46 220 | 95.85 190 | 94.74 250 | 95.54 149 | 98.98 219 | 98.59 71 | 92.14 172 | 90.77 206 | 97.44 193 | 68.73 293 | 97.54 227 | 94.89 147 | 77.89 296 | 94.46 220 |
|
FIs | | | 94.10 172 | 93.43 174 | 96.11 183 | 94.70 251 | 96.82 106 | 99.58 153 | 98.93 39 | 92.54 163 | 89.34 230 | 97.31 197 | 87.62 168 | 97.10 249 | 94.22 166 | 86.58 242 | 94.40 226 |
|
UniMVSNet_ETH3D | | | 90.06 252 | 88.58 257 | 94.49 223 | 94.67 252 | 88.09 280 | 97.81 280 | 97.57 212 | 83.91 290 | 88.44 243 | 97.41 194 | 57.44 319 | 97.62 225 | 91.41 203 | 88.59 226 | 97.77 201 |
|
UniMVSNet_NR-MVSNet | | | 92.95 193 | 92.11 197 | 95.49 193 | 94.61 253 | 95.28 156 | 99.83 102 | 99.08 30 | 91.49 189 | 89.21 234 | 96.86 214 | 87.14 173 | 96.73 268 | 93.20 185 | 77.52 299 | 94.46 220 |
|
WR-MVS | | | 92.31 205 | 91.25 210 | 95.48 195 | 94.45 254 | 95.29 155 | 99.60 151 | 98.68 55 | 90.10 216 | 88.07 250 | 96.89 212 | 80.68 225 | 96.80 267 | 93.14 188 | 79.67 286 | 94.36 228 |
|
nrg030 | | | 93.51 184 | 92.53 191 | 96.45 174 | 94.36 255 | 97.20 93 | 99.81 105 | 97.16 249 | 91.60 186 | 89.86 217 | 97.46 192 | 86.37 181 | 97.68 222 | 95.88 134 | 80.31 282 | 94.46 220 |
|
tfpnnormal | | | 89.29 262 | 87.61 268 | 94.34 229 | 94.35 256 | 94.13 180 | 98.95 223 | 98.94 36 | 83.94 288 | 84.47 284 | 95.51 248 | 74.84 268 | 97.39 230 | 77.05 306 | 80.41 280 | 91.48 307 |
|
FC-MVSNet-test | | | 93.81 177 | 93.15 182 | 95.80 191 | 94.30 257 | 96.20 127 | 99.42 173 | 98.89 41 | 92.33 169 | 89.03 237 | 97.27 199 | 87.39 171 | 96.83 265 | 93.20 185 | 86.48 243 | 94.36 228 |
|
MS-PatchMatch | | | 90.65 235 | 90.30 225 | 91.71 278 | 94.22 258 | 85.50 293 | 98.24 266 | 97.70 197 | 88.67 239 | 86.42 271 | 96.37 228 | 67.82 297 | 98.03 209 | 83.62 278 | 99.62 85 | 91.60 306 |
|
WR-MVS_H | | | 91.30 221 | 90.35 223 | 94.15 233 | 94.17 259 | 92.62 208 | 99.17 199 | 98.94 36 | 88.87 236 | 86.48 270 | 94.46 287 | 84.36 197 | 96.61 271 | 88.19 239 | 78.51 292 | 93.21 290 |
|
DU-MVS | | | 92.46 204 | 91.45 208 | 95.49 193 | 94.05 260 | 95.28 156 | 99.81 105 | 98.74 51 | 92.25 171 | 89.21 234 | 96.64 221 | 81.66 213 | 96.73 268 | 93.20 185 | 77.52 299 | 94.46 220 |
|
NR-MVSNet | | | 91.56 220 | 90.22 227 | 95.60 192 | 94.05 260 | 95.76 142 | 98.25 265 | 98.70 53 | 91.16 199 | 80.78 296 | 96.64 221 | 83.23 206 | 96.57 272 | 91.41 203 | 77.73 298 | 94.46 220 |
|
CP-MVSNet | | | 91.23 224 | 90.22 227 | 94.26 230 | 93.96 262 | 92.39 212 | 99.09 203 | 98.57 74 | 88.95 234 | 86.42 271 | 96.57 223 | 79.19 238 | 96.37 276 | 90.29 223 | 78.95 289 | 94.02 252 |
|
XXY-MVS | | | 91.82 211 | 90.46 220 | 95.88 188 | 93.91 263 | 95.40 153 | 98.87 232 | 97.69 198 | 88.63 241 | 87.87 252 | 97.08 204 | 74.38 272 | 97.89 217 | 91.66 201 | 84.07 259 | 94.35 231 |
|
PS-CasMVS | | | 90.63 237 | 89.51 241 | 93.99 242 | 93.83 264 | 91.70 231 | 98.98 219 | 98.52 87 | 88.48 242 | 86.15 275 | 96.53 225 | 75.46 263 | 96.31 280 | 88.83 234 | 78.86 291 | 93.95 260 |
|
test_0402 | | | 85.58 277 | 83.94 280 | 90.50 286 | 93.81 265 | 85.04 296 | 98.55 250 | 95.20 312 | 76.01 312 | 79.72 300 | 95.13 264 | 64.15 308 | 96.26 283 | 66.04 322 | 86.88 241 | 90.21 315 |
|
XVG-ACMP-BASELINE | | | 91.22 225 | 90.75 215 | 92.63 268 | 93.73 266 | 85.61 291 | 98.52 254 | 97.44 226 | 92.77 148 | 89.90 216 | 96.85 215 | 66.64 300 | 98.39 186 | 92.29 195 | 88.61 224 | 93.89 265 |
|
TranMVSNet+NR-MVSNet | | | 91.68 219 | 90.61 218 | 94.87 209 | 93.69 267 | 93.98 182 | 99.69 134 | 98.65 59 | 91.03 202 | 88.44 243 | 96.83 218 | 80.05 233 | 96.18 285 | 90.26 224 | 76.89 306 | 94.45 225 |
|
TransMVSNet (Re) | | | 87.25 272 | 85.28 276 | 93.16 259 | 93.56 268 | 91.03 239 | 98.54 252 | 94.05 321 | 83.69 292 | 81.09 295 | 96.16 232 | 75.32 264 | 96.40 275 | 76.69 307 | 68.41 318 | 92.06 301 |
|
v10 | | | 90.25 247 | 88.82 253 | 94.57 220 | 93.53 269 | 93.43 192 | 99.08 205 | 96.87 274 | 85.00 283 | 87.34 260 | 94.51 283 | 80.93 222 | 97.02 257 | 82.85 282 | 79.23 287 | 93.26 288 |
|
testgi | | | 89.01 265 | 88.04 265 | 91.90 276 | 93.49 270 | 84.89 297 | 99.73 129 | 95.66 303 | 93.89 118 | 85.14 281 | 98.17 180 | 59.68 316 | 94.66 310 | 77.73 302 | 88.88 218 | 96.16 212 |
|
v8 | | | 90.54 239 | 89.17 246 | 94.66 215 | 93.43 271 | 93.40 194 | 99.20 196 | 96.94 269 | 85.76 274 | 87.56 255 | 94.51 283 | 81.96 211 | 97.19 241 | 84.94 269 | 78.25 293 | 93.38 286 |
|
V42 | | | 91.28 223 | 90.12 231 | 94.74 212 | 93.42 272 | 93.46 191 | 99.68 136 | 97.02 258 | 87.36 254 | 89.85 218 | 95.05 266 | 81.31 218 | 97.34 233 | 87.34 249 | 80.07 284 | 93.40 284 |
|
pm-mvs1 | | | 89.36 261 | 87.81 267 | 94.01 240 | 93.40 273 | 91.93 221 | 98.62 249 | 96.48 290 | 86.25 269 | 83.86 287 | 96.14 233 | 73.68 275 | 97.04 253 | 86.16 261 | 75.73 310 | 93.04 293 |
|
v1144 | | | 91.09 226 | 89.83 233 | 94.87 209 | 93.25 274 | 93.69 188 | 99.62 150 | 96.98 264 | 86.83 262 | 89.64 224 | 94.99 271 | 80.94 221 | 97.05 252 | 85.08 268 | 81.16 273 | 93.87 267 |
|
v1192 | | | 90.62 238 | 89.25 245 | 94.72 214 | 93.13 275 | 93.07 197 | 99.50 164 | 97.02 258 | 86.33 268 | 89.56 226 | 95.01 268 | 79.22 237 | 97.09 251 | 82.34 285 | 81.16 273 | 94.01 254 |
|
v2v482 | | | 91.30 221 | 90.07 232 | 95.01 204 | 93.13 275 | 93.79 185 | 99.77 115 | 97.02 258 | 88.05 247 | 89.25 232 | 95.37 255 | 80.73 224 | 97.15 244 | 87.28 250 | 80.04 285 | 94.09 248 |
|
OPM-MVS | | | 93.21 188 | 92.80 185 | 94.44 225 | 93.12 277 | 90.85 243 | 99.77 115 | 97.61 207 | 96.19 46 | 91.56 199 | 98.65 161 | 75.16 267 | 98.47 175 | 93.78 177 | 89.39 214 | 93.99 257 |
|
v144192 | | | 90.79 233 | 89.52 240 | 94.59 218 | 93.11 278 | 92.77 201 | 99.56 155 | 96.99 262 | 86.38 267 | 89.82 219 | 94.95 273 | 80.50 229 | 97.10 249 | 83.98 275 | 80.41 280 | 93.90 264 |
|
PEN-MVS | | | 90.19 249 | 89.06 249 | 93.57 252 | 93.06 279 | 90.90 242 | 99.06 210 | 98.47 99 | 88.11 246 | 85.91 277 | 96.30 229 | 76.67 253 | 95.94 295 | 87.07 252 | 76.91 305 | 93.89 265 |
|
v1240 | | | 90.20 248 | 88.79 254 | 94.44 225 | 93.05 280 | 92.27 214 | 99.38 178 | 96.92 270 | 85.89 272 | 89.36 229 | 94.87 275 | 77.89 247 | 97.03 255 | 80.66 293 | 81.08 275 | 94.01 254 |
|
v148 | | | 90.70 234 | 89.63 236 | 93.92 244 | 92.97 281 | 90.97 240 | 99.75 121 | 96.89 272 | 87.51 251 | 88.27 248 | 95.01 268 | 81.67 212 | 97.04 253 | 87.40 248 | 77.17 303 | 93.75 274 |
|
v1921920 | | | 90.46 240 | 89.12 247 | 94.50 222 | 92.96 282 | 92.46 210 | 99.49 165 | 96.98 264 | 86.10 270 | 89.61 225 | 95.30 258 | 78.55 244 | 97.03 255 | 82.17 286 | 80.89 279 | 94.01 254 |
|
Baseline_NR-MVSNet | | | 90.33 244 | 89.51 241 | 92.81 266 | 92.84 283 | 89.95 258 | 99.77 115 | 93.94 322 | 84.69 286 | 89.04 236 | 95.66 243 | 81.66 213 | 96.52 273 | 90.99 211 | 76.98 304 | 91.97 303 |
|
pmmvs4 | | | 92.10 208 | 91.07 213 | 95.18 200 | 92.82 284 | 94.96 163 | 99.48 167 | 96.83 276 | 87.45 253 | 88.66 241 | 96.56 224 | 83.78 201 | 96.83 265 | 89.29 230 | 84.77 256 | 93.75 274 |
|
LF4IMVS | | | 89.25 264 | 88.85 252 | 90.45 288 | 92.81 285 | 81.19 312 | 98.12 271 | 94.79 315 | 91.44 192 | 86.29 273 | 97.11 202 | 65.30 305 | 98.11 205 | 88.53 236 | 85.25 251 | 92.07 300 |
|
DTE-MVSNet | | | 89.40 259 | 88.24 263 | 92.88 265 | 92.66 286 | 89.95 258 | 99.10 202 | 98.22 151 | 87.29 255 | 85.12 282 | 96.22 231 | 76.27 258 | 95.30 303 | 83.56 279 | 75.74 309 | 93.41 283 |
|
EU-MVSNet | | | 90.14 251 | 90.34 224 | 89.54 294 | 92.55 287 | 81.06 313 | 98.69 243 | 98.04 171 | 91.41 195 | 86.59 267 | 96.84 217 | 80.83 223 | 93.31 319 | 86.20 260 | 81.91 268 | 94.26 236 |
|
our_test_3 | | | 90.39 241 | 89.48 243 | 93.12 260 | 92.40 288 | 89.57 263 | 99.33 184 | 96.35 291 | 87.84 249 | 85.30 280 | 94.99 271 | 84.14 199 | 96.09 289 | 80.38 294 | 84.56 257 | 93.71 279 |
|
ppachtmachnet_test | | | 89.58 258 | 88.35 260 | 93.25 258 | 92.40 288 | 90.44 251 | 99.33 184 | 96.73 281 | 85.49 280 | 85.90 278 | 95.77 239 | 81.09 220 | 96.00 294 | 76.00 309 | 82.49 265 | 93.30 287 |
|
v7n | | | 89.65 257 | 88.29 262 | 93.72 248 | 92.22 290 | 90.56 248 | 99.07 209 | 97.10 252 | 85.42 282 | 86.73 264 | 94.72 276 | 80.06 232 | 97.13 246 | 81.14 291 | 78.12 295 | 93.49 282 |
|
PS-MVSNAJss | | | 93.64 183 | 93.31 180 | 94.61 217 | 92.11 291 | 92.19 215 | 99.12 201 | 97.38 233 | 92.51 165 | 88.45 242 | 96.99 210 | 91.20 133 | 97.29 238 | 94.36 160 | 87.71 235 | 94.36 228 |
|
pmmvs5 | | | 90.17 250 | 89.09 248 | 93.40 254 | 92.10 292 | 89.77 261 | 99.74 124 | 95.58 305 | 85.88 273 | 87.24 261 | 95.74 240 | 73.41 276 | 96.48 274 | 88.54 235 | 83.56 262 | 93.95 260 |
|
N_pmnet | | | 80.06 294 | 80.78 292 | 77.89 309 | 91.94 293 | 45.28 334 | 98.80 236 | 56.82 338 | 78.10 309 | 80.08 299 | 93.33 296 | 77.03 249 | 95.76 297 | 68.14 318 | 82.81 264 | 92.64 296 |
|
test_djsdf | | | 92.83 195 | 92.29 195 | 94.47 224 | 91.90 294 | 92.46 210 | 99.55 157 | 97.27 240 | 91.17 197 | 89.96 213 | 96.07 236 | 81.10 219 | 96.89 261 | 94.67 155 | 88.91 217 | 94.05 251 |
|
DI_MVS_plusplus_test | | | 92.48 202 | 90.60 219 | 98.11 123 | 91.88 295 | 96.13 130 | 99.64 146 | 97.73 195 | 92.69 152 | 76.02 310 | 93.79 293 | 70.49 287 | 99.07 144 | 95.88 134 | 97.26 145 | 99.14 171 |
|
SixPastTwentyTwo | | | 88.73 266 | 88.01 266 | 90.88 282 | 91.85 296 | 82.24 306 | 98.22 268 | 95.18 313 | 88.97 232 | 82.26 291 | 96.89 212 | 71.75 281 | 96.67 270 | 84.00 274 | 82.98 263 | 93.72 278 |
|
K. test v3 | | | 88.05 270 | 87.24 270 | 90.47 287 | 91.82 297 | 82.23 307 | 98.96 222 | 97.42 229 | 89.05 228 | 76.93 307 | 95.60 244 | 68.49 294 | 95.42 299 | 85.87 264 | 81.01 277 | 93.75 274 |
|
OurMVSNet-221017-0 | | | 89.81 255 | 89.48 243 | 90.83 284 | 91.64 298 | 81.21 311 | 98.17 270 | 95.38 308 | 91.48 190 | 85.65 279 | 97.31 197 | 72.66 277 | 97.29 238 | 88.15 240 | 84.83 255 | 93.97 259 |
|
mvs_tets | | | 91.81 212 | 91.08 212 | 94.00 241 | 91.63 299 | 90.58 247 | 98.67 245 | 97.43 227 | 92.43 167 | 87.37 259 | 97.05 207 | 71.76 280 | 97.32 234 | 94.75 152 | 88.68 223 | 94.11 247 |
|
Gipuma | | | 66.95 300 | 65.00 300 | 72.79 312 | 91.52 300 | 67.96 324 | 66.16 331 | 95.15 314 | 47.89 326 | 58.54 324 | 67.99 328 | 29.74 331 | 87.54 326 | 50.20 328 | 77.83 297 | 62.87 329 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
jajsoiax | | | 91.92 210 | 91.18 211 | 94.15 233 | 91.35 301 | 90.95 241 | 99.00 218 | 97.42 229 | 92.61 158 | 87.38 258 | 97.08 204 | 72.46 278 | 97.36 231 | 94.53 158 | 88.77 221 | 94.13 246 |
|
MDA-MVSNet-bldmvs | | | 84.09 287 | 81.52 291 | 91.81 277 | 91.32 302 | 88.00 282 | 98.67 245 | 95.92 299 | 80.22 304 | 55.60 327 | 93.32 297 | 68.29 296 | 93.60 317 | 73.76 311 | 76.61 307 | 93.82 271 |
|
MVP-Stereo | | | 90.93 228 | 90.45 222 | 92.37 270 | 91.25 303 | 88.76 269 | 98.05 275 | 96.17 294 | 87.27 256 | 84.04 285 | 95.30 258 | 78.46 245 | 97.27 240 | 83.78 277 | 99.70 81 | 91.09 308 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
MDA-MVSNet_test_wron | | | 85.51 279 | 83.32 284 | 92.10 273 | 90.96 304 | 88.58 274 | 99.20 196 | 96.52 287 | 79.70 305 | 57.12 326 | 92.69 303 | 79.11 239 | 93.86 314 | 77.10 305 | 77.46 301 | 93.86 268 |
|
YYNet1 | | | 85.50 280 | 83.33 283 | 92.00 274 | 90.89 305 | 88.38 278 | 99.22 195 | 96.55 286 | 79.60 306 | 57.26 325 | 92.72 301 | 79.09 240 | 93.78 315 | 77.25 304 | 77.37 302 | 93.84 269 |
|
anonymousdsp | | | 91.79 217 | 90.92 214 | 94.41 228 | 90.76 306 | 92.93 200 | 98.93 225 | 97.17 247 | 89.08 227 | 87.46 257 | 95.30 258 | 78.43 246 | 96.92 260 | 92.38 194 | 88.73 222 | 93.39 285 |
|
lessismore_v0 | | | | | 90.53 285 | 90.58 307 | 80.90 314 | | 95.80 300 | | 77.01 306 | 95.84 237 | 66.15 302 | 96.95 258 | 83.03 281 | 75.05 311 | 93.74 277 |
|
EG-PatchMatch MVS | | | 85.35 281 | 83.81 282 | 89.99 292 | 90.39 308 | 81.89 309 | 98.21 269 | 96.09 296 | 81.78 300 | 74.73 314 | 93.72 295 | 51.56 324 | 97.12 248 | 79.16 298 | 88.61 224 | 90.96 310 |
|
CMPMVS | | 61.59 21 | 84.75 284 | 85.14 277 | 83.57 306 | 90.32 309 | 62.54 326 | 96.98 291 | 97.59 211 | 74.33 318 | 69.95 319 | 96.66 219 | 64.17 307 | 98.32 194 | 87.88 243 | 88.41 229 | 89.84 317 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
new_pmnet | | | 84.49 286 | 82.92 286 | 89.21 295 | 90.03 310 | 82.60 303 | 96.89 293 | 95.62 304 | 80.59 303 | 75.77 313 | 89.17 311 | 65.04 306 | 94.79 309 | 72.12 312 | 81.02 276 | 90.23 314 |
|
pmmvs6 | | | 85.69 276 | 83.84 281 | 91.26 281 | 90.00 311 | 84.41 299 | 97.82 279 | 96.15 295 | 75.86 313 | 81.29 294 | 95.39 253 | 61.21 314 | 96.87 263 | 83.52 280 | 73.29 313 | 92.50 297 |
|
DSMNet-mixed | | | 88.28 269 | 88.24 263 | 88.42 300 | 89.64 312 | 75.38 320 | 98.06 274 | 89.86 329 | 85.59 278 | 88.20 249 | 92.14 306 | 76.15 260 | 91.95 320 | 78.46 299 | 96.05 166 | 97.92 197 |
|
UnsupCasMVSNet_eth | | | 85.52 278 | 83.99 278 | 90.10 290 | 89.36 313 | 83.51 301 | 96.65 294 | 97.99 173 | 89.14 226 | 75.89 312 | 93.83 292 | 63.25 310 | 93.92 312 | 81.92 288 | 67.90 320 | 92.88 294 |
|
Anonymous20231206 | | | 86.32 274 | 85.42 275 | 89.02 296 | 89.11 314 | 80.53 316 | 99.05 214 | 95.28 309 | 85.43 281 | 82.82 290 | 93.92 291 | 74.40 271 | 93.44 318 | 66.99 319 | 81.83 269 | 93.08 292 |
|
OpenMVS_ROB | | 79.82 20 | 83.77 289 | 81.68 290 | 90.03 291 | 88.30 315 | 82.82 302 | 98.46 255 | 95.22 311 | 73.92 319 | 76.00 311 | 91.29 308 | 55.00 321 | 96.94 259 | 68.40 317 | 88.51 228 | 90.34 313 |
|
test20.03 | | | 84.72 285 | 83.99 278 | 86.91 302 | 88.19 316 | 80.62 315 | 98.88 229 | 95.94 298 | 88.36 244 | 78.87 301 | 94.62 281 | 68.75 292 | 89.11 325 | 66.52 320 | 75.82 308 | 91.00 309 |
|
MIMVSNet1 | | | 82.58 290 | 80.51 293 | 88.78 298 | 86.68 317 | 84.20 300 | 96.65 294 | 95.41 307 | 78.75 307 | 78.59 303 | 92.44 304 | 51.88 323 | 89.76 324 | 65.26 323 | 78.95 289 | 92.38 299 |
|
UnsupCasMVSNet_bld | | | 79.97 295 | 77.03 297 | 88.78 298 | 85.62 318 | 81.98 308 | 93.66 313 | 97.35 235 | 75.51 316 | 70.79 318 | 83.05 321 | 48.70 326 | 94.91 307 | 78.31 300 | 60.29 325 | 89.46 320 |
|
Patchmatch-RL test | | | 86.90 273 | 85.98 274 | 89.67 293 | 84.45 319 | 75.59 319 | 89.71 324 | 92.43 324 | 86.89 261 | 77.83 305 | 90.94 309 | 94.22 73 | 93.63 316 | 87.75 244 | 69.61 315 | 99.79 88 |
|
pmmvs-eth3d | | | 84.03 288 | 81.97 288 | 90.20 289 | 84.15 320 | 87.09 285 | 98.10 273 | 94.73 317 | 83.05 293 | 74.10 315 | 87.77 314 | 65.56 304 | 94.01 311 | 81.08 292 | 69.24 317 | 89.49 319 |
|
PM-MVS | | | 80.47 292 | 78.88 295 | 85.26 305 | 83.79 321 | 72.22 321 | 95.89 305 | 91.08 327 | 85.71 277 | 76.56 309 | 88.30 312 | 36.64 328 | 93.90 313 | 82.39 284 | 69.57 316 | 89.66 318 |
|
new-patchmatchnet | | | 81.19 291 | 79.34 294 | 86.76 303 | 82.86 322 | 80.36 317 | 97.92 277 | 95.27 310 | 82.09 299 | 72.02 316 | 86.87 316 | 62.81 311 | 90.74 323 | 71.10 313 | 63.08 323 | 89.19 321 |
|
testing_2 | | | 85.10 282 | 81.72 289 | 95.22 199 | 82.25 323 | 94.16 178 | 97.54 283 | 97.01 261 | 88.15 245 | 62.23 321 | 86.43 318 | 44.43 327 | 97.18 242 | 92.28 196 | 85.20 253 | 94.31 233 |
|
pmmvs3 | | | 80.27 293 | 77.77 296 | 87.76 301 | 80.32 324 | 82.43 305 | 98.23 267 | 91.97 325 | 72.74 320 | 78.75 302 | 87.97 313 | 57.30 320 | 90.99 322 | 70.31 314 | 62.37 324 | 89.87 316 |
|
test_normal | | | 73.75 296 | 69.52 298 | 86.45 304 | 78.71 325 | 71.20 322 | 52.76 332 | 96.50 288 | 86.56 264 | 46.73 331 | 66.99 329 | 34.02 329 | 96.33 279 | 84.42 272 | 78.96 288 | 91.81 305 |
|
ambc | | | | | 83.23 307 | 77.17 326 | 62.61 325 | 87.38 326 | 94.55 319 | | 76.72 308 | 86.65 317 | 30.16 330 | 96.36 277 | 84.85 270 | 69.86 314 | 90.73 312 |
|
TDRefinement | | | 84.76 283 | 82.56 287 | 91.38 280 | 74.58 327 | 84.80 298 | 97.36 286 | 94.56 318 | 84.73 285 | 80.21 298 | 96.12 235 | 63.56 309 | 98.39 186 | 87.92 242 | 63.97 322 | 90.95 311 |
|
E-PMN | | | 52.30 304 | 52.18 305 | 52.67 318 | 71.51 328 | 45.40 333 | 93.62 314 | 76.60 336 | 36.01 330 | 43.50 332 | 64.13 331 | 27.11 333 | 67.31 334 | 31.06 333 | 26.06 329 | 45.30 333 |
|
EMVS | | | 51.44 306 | 51.22 307 | 52.11 319 | 70.71 329 | 44.97 335 | 94.04 310 | 75.66 337 | 35.34 332 | 42.40 333 | 61.56 334 | 28.93 332 | 65.87 335 | 27.64 334 | 24.73 330 | 45.49 332 |
|
PMMVS2 | | | 67.15 299 | 64.15 302 | 76.14 311 | 70.56 330 | 62.07 327 | 93.89 311 | 87.52 333 | 58.09 324 | 60.02 323 | 78.32 323 | 22.38 335 | 84.54 328 | 59.56 326 | 47.03 327 | 81.80 324 |
|
FPMVS | | | 68.72 297 | 68.72 299 | 68.71 314 | 65.95 331 | 44.27 336 | 95.97 304 | 94.74 316 | 51.13 325 | 53.26 328 | 90.50 310 | 25.11 334 | 83.00 329 | 60.80 325 | 80.97 278 | 78.87 325 |
|
wuyk23d | | | 20.37 310 | 20.84 312 | 18.99 322 | 65.34 332 | 27.73 338 | 50.43 333 | 7.67 341 | 9.50 335 | 8.01 337 | 6.34 337 | 6.13 341 | 26.24 336 | 23.40 335 | 10.69 334 | 2.99 334 |
|
LCM-MVSNet | | | 67.77 298 | 64.73 301 | 76.87 310 | 62.95 333 | 56.25 330 | 89.37 325 | 93.74 323 | 44.53 327 | 61.99 322 | 80.74 322 | 20.42 336 | 86.53 327 | 69.37 316 | 59.50 326 | 87.84 322 |
|
MVE | | 53.74 22 | 51.54 305 | 47.86 308 | 62.60 316 | 59.56 334 | 50.93 331 | 79.41 329 | 77.69 335 | 35.69 331 | 36.27 334 | 61.76 333 | 5.79 342 | 69.63 332 | 37.97 332 | 36.61 328 | 67.24 327 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
ANet_high | | | 56.10 302 | 52.24 304 | 67.66 315 | 49.27 335 | 56.82 329 | 83.94 327 | 82.02 334 | 70.47 321 | 33.28 335 | 64.54 330 | 17.23 338 | 69.16 333 | 45.59 330 | 23.85 331 | 77.02 326 |
|
tmp_tt | | | 65.23 301 | 62.94 303 | 72.13 313 | 44.90 336 | 50.03 332 | 81.05 328 | 89.42 332 | 38.45 328 | 48.51 330 | 99.90 15 | 54.09 322 | 78.70 331 | 91.84 200 | 18.26 332 | 87.64 323 |
|
PMVS | | 49.05 23 | 53.75 303 | 51.34 306 | 60.97 317 | 40.80 337 | 34.68 337 | 74.82 330 | 89.62 331 | 37.55 329 | 28.67 336 | 72.12 325 | 7.09 340 | 81.63 330 | 43.17 331 | 68.21 319 | 66.59 328 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
test123 | | | 37.68 308 | 39.14 310 | 33.31 320 | 19.94 338 | 24.83 339 | 98.36 261 | 9.75 340 | 15.53 334 | 51.31 329 | 87.14 315 | 19.62 337 | 17.74 337 | 47.10 329 | 3.47 335 | 57.36 330 |
|
testmvs | | | 40.60 307 | 44.45 309 | 29.05 321 | 19.49 339 | 14.11 340 | 99.68 136 | 18.47 339 | 20.74 333 | 64.59 320 | 98.48 174 | 10.95 339 | 17.09 338 | 56.66 327 | 11.01 333 | 55.94 331 |
|
cdsmvs_eth3d_5k | | | 23.43 309 | 31.24 311 | 0.00 323 | 0.00 340 | 0.00 341 | 0.00 334 | 98.09 167 | 0.00 336 | 0.00 338 | 99.67 82 | 83.37 204 | 0.00 339 | 0.00 336 | 0.00 336 | 0.00 335 |
|
pcd_1.5k_mvsjas | | | 7.60 312 | 10.13 314 | 0.00 323 | 0.00 340 | 0.00 341 | 0.00 334 | 0.00 342 | 0.00 336 | 0.00 338 | 0.00 338 | 91.20 133 | 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 | | | 8.28 311 | 11.04 313 | 0.00 323 | 0.00 340 | 0.00 341 | 0.00 334 | 0.00 342 | 0.00 336 | 0.00 338 | 99.40 105 | 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 filter2 | | | | | | | | | | | 99.83 8 | 99.91 10 | 95.88 29 | 100.00 1 | 99.80 10 | 99.99 17 | 99.99 15 |
|
test_0728_THIRD | | | | | | | | | | 96.48 35 | 99.83 8 | 99.91 10 | 97.87 4 | 100.00 1 | 99.92 4 | 100.00 1 | 100.00 1 |
|
GSMVS | | | | | | | | | | | | | | | | | 99.59 119 |
|
test_part1 | | | | | 0.00 323 | | 0.00 341 | 0.00 334 | 98.41 122 | | | | 0.00 343 | 0.00 339 | 0.00 336 | 0.00 336 | 0.00 335 |
|
sam_mvs1 | | | | | | | | | | | | | 94.72 59 | | | | 99.59 119 |
|
sam_mvs | | | | | | | | | | | | | 94.25 72 | | | | |
|
MTGPA | | | | | | | | | 98.28 144 | | | | | | | | |
|
test_post1 | | | | | | | | 95.78 306 | | | | 59.23 335 | 93.20 101 | 97.74 221 | 91.06 209 | | |
|
test_post | | | | | | | | | | | | 63.35 332 | 94.43 62 | 98.13 204 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 91.70 307 | 95.12 45 | 97.95 214 | | | |
|
MTMP | | | | | | | | 99.87 79 | 96.49 289 | | | | | | | | |
|
test9_res | | | | | | | | | | | | | | | 99.71 21 | 99.99 17 | 100.00 1 |
|
agg_prior2 | | | | | | | | | | | | | | | 99.48 27 | 100.00 1 | 100.00 1 |
|
test_prior4 | | | | | | | 98.05 60 | 99.94 52 | | | | | | | | | |
|
test_prior2 | | | | | | | | 99.95 37 | | 95.78 53 | 99.73 19 | 99.76 61 | 96.00 24 | | 99.78 13 | 100.00 1 | |
|
旧先验2 | | | | | | | | 99.46 170 | | 94.21 100 | 99.85 6 | | | 99.95 56 | 96.96 120 | | |
|
新几何2 | | | | | | | | 99.40 174 | | | | | | | | | |
|
无先验 | | | | | | | | 99.49 165 | 98.71 52 | 93.46 129 | | | | 100.00 1 | 94.36 160 | | 99.99 15 |
|
原ACMM2 | | | | | | | | 99.90 68 | | | | | | | | | |
|
testdata2 | | | | | | | | | | | | | | 99.99 33 | 90.54 219 | | |
|
segment_acmp | | | | | | | | | | | | | 96.68 18 | | | | |
|
testdata1 | | | | | | | | 99.28 191 | | 96.35 43 | | | | | | | |
|
plane_prior5 | | | | | | | | | 97.87 186 | | | | | 98.37 191 | 97.79 99 | 89.55 211 | 94.52 217 |
|
plane_prior4 | | | | | | | | | | | | 98.59 165 | | | | | |
|
plane_prior3 | | | | | | | 91.64 233 | | | 96.63 33 | 93.01 187 | | | | | | |
|
plane_prior2 | | | | | | | | 99.84 96 | | 96.38 39 | | | | | | | |
|
plane_prior | | | | | | | 91.74 227 | 99.86 90 | | 96.76 29 | | | | | | 89.59 210 | |
|
n2 | | | | | | | | | 0.00 342 | | | | | | | | |
|
nn | | | | | | | | | 0.00 342 | | | | | | | | |
|
door-mid | | | | | | | | | 89.69 330 | | | | | | | | |
|
test11 | | | | | | | | | 98.44 103 | | | | | | | | |
|
door | | | | | | | | | 90.31 328 | | | | | | | | |
|
HQP5-MVS | | | | | | | 91.85 223 | | | | | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 97.92 96 | | |
|
HQP4-MVS | | | | | | | | | | | 93.37 183 | | | 98.39 186 | | | 94.53 215 |
|
HQP3-MVS | | | | | | | | | 97.89 184 | | | | | | | 89.60 208 | |
|
HQP2-MVS | | | | | | | | | | | | | 80.65 226 | | | | |
|
MDTV_nov1_ep13_2view | | | | | | | 96.26 122 | 96.11 301 | | 91.89 179 | 98.06 106 | | 94.40 64 | | 94.30 163 | | 99.67 105 |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 87.04 240 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 88.23 230 | |
|
Test By Simon | | | | | | | | | | | | | 92.82 108 | | | | |
|