APDe-MVS | | | 99.66 1 | 99.57 1 | 99.92 1 | 99.77 38 | 99.89 1 | 99.75 34 | 99.56 46 | 99.02 11 | 99.88 3 | 99.85 26 | 99.18 5 | 99.96 18 | 99.22 30 | 99.92 9 | 99.90 1 |
|
UA-Net | | | 99.42 29 | 99.29 36 | 99.80 29 | 99.62 91 | 99.55 51 | 99.50 116 | 99.70 15 | 98.79 40 | 99.77 23 | 99.96 1 | 97.45 91 | 99.96 18 | 98.92 54 | 99.90 22 | 99.89 2 |
|
CHOSEN 1792x2688 | | | 99.19 55 | 99.10 55 | 99.45 93 | 99.89 8 | 98.52 179 | 99.39 162 | 99.94 1 | 98.73 44 | 99.11 151 | 99.89 10 | 95.50 143 | 99.94 40 | 99.50 7 | 99.97 2 | 99.89 2 |
|
DP-MVS | | | 99.16 60 | 98.95 75 | 99.78 33 | 99.77 38 | 99.53 55 | 99.41 155 | 99.50 97 | 97.03 182 | 99.04 165 | 99.88 14 | 97.39 92 | 99.92 63 | 98.66 86 | 99.90 22 | 99.87 4 |
|
EI-MVSNet-UG-set | | | 99.58 3 | 99.57 1 | 99.64 61 | 99.78 34 | 99.14 94 | 99.60 77 | 99.45 145 | 99.01 14 | 99.90 1 | 99.83 37 | 98.98 18 | 99.93 55 | 99.59 1 | 99.95 5 | 99.86 5 |
|
Test_1112_low_res | | | 98.89 94 | 98.66 108 | 99.57 70 | 99.69 70 | 98.95 120 | 99.03 251 | 99.47 125 | 96.98 184 | 99.15 146 | 99.23 246 | 96.77 110 | 99.89 92 | 98.83 68 | 98.78 152 | 99.86 5 |
|
HyFIR lowres test | | | 99.11 71 | 98.92 77 | 99.65 56 | 99.90 3 | 99.37 73 | 99.02 254 | 99.91 3 | 97.67 128 | 99.59 59 | 99.75 90 | 95.90 133 | 99.73 147 | 99.53 5 | 99.02 132 | 99.86 5 |
|
EI-MVSNet-Vis-set | | | 99.58 3 | 99.56 3 | 99.64 61 | 99.78 34 | 99.15 93 | 99.61 76 | 99.45 145 | 99.01 14 | 99.89 2 | 99.82 44 | 99.01 11 | 99.92 63 | 99.56 4 | 99.95 5 | 99.85 8 |
|
CVMVSNet | | | 98.57 127 | 98.67 105 | 98.30 224 | 99.35 143 | 95.59 268 | 99.50 116 | 99.55 53 | 98.60 51 | 99.39 93 | 99.83 37 | 94.48 196 | 99.45 193 | 98.75 74 | 98.56 161 | 99.85 8 |
|
HPM-MVS_fast | | | 99.51 12 | 99.40 14 | 99.85 17 | 99.91 1 | 99.79 16 | 99.76 27 | 99.56 46 | 97.72 123 | 99.76 26 | 99.75 90 | 99.13 6 | 99.92 63 | 99.07 43 | 99.92 9 | 99.85 8 |
|
MG-MVS | | | 99.13 62 | 99.02 66 | 99.45 93 | 99.57 102 | 98.63 167 | 99.07 239 | 99.34 201 | 98.99 19 | 99.61 55 | 99.82 44 | 97.98 80 | 99.87 97 | 97.00 217 | 99.80 67 | 99.85 8 |
|
ACMMP_Plus | | | 99.47 20 | 99.34 24 | 99.88 4 | 99.87 15 | 99.86 3 | 99.47 131 | 99.48 111 | 98.05 98 | 99.76 26 | 99.86 22 | 98.82 32 | 99.93 55 | 98.82 71 | 99.91 15 | 99.84 12 |
|
HFP-MVS | | | 99.49 13 | 99.37 17 | 99.86 12 | 99.87 15 | 99.80 12 | 99.66 54 | 99.67 22 | 98.15 80 | 99.68 34 | 99.69 111 | 99.06 8 | 99.96 18 | 98.69 83 | 99.87 37 | 99.84 12 |
|
region2R | | | 99.48 17 | 99.35 22 | 99.87 6 | 99.88 11 | 99.80 12 | 99.65 64 | 99.66 25 | 98.13 82 | 99.66 45 | 99.68 116 | 98.96 20 | 99.96 18 | 98.62 91 | 99.87 37 | 99.84 12 |
|
#test# | | | 99.43 27 | 99.29 36 | 99.86 12 | 99.87 15 | 99.80 12 | 99.55 100 | 99.67 22 | 97.83 112 | 99.68 34 | 99.69 111 | 99.06 8 | 99.96 18 | 98.39 114 | 99.87 37 | 99.84 12 |
|
Regformer-4 | | | 99.59 2 | 99.54 4 | 99.73 45 | 99.76 41 | 99.41 70 | 99.58 82 | 99.49 102 | 99.02 11 | 99.88 3 | 99.80 64 | 99.00 17 | 99.94 40 | 99.45 14 | 99.92 9 | 99.84 12 |
|
XVS | | | 99.53 9 | 99.42 11 | 99.87 6 | 99.85 23 | 99.83 7 | 99.69 44 | 99.68 19 | 98.98 20 | 99.37 97 | 99.74 94 | 98.81 33 | 99.94 40 | 98.79 72 | 99.86 47 | 99.84 12 |
|
X-MVStestdata | | | 96.55 248 | 95.45 269 | 99.87 6 | 99.85 23 | 99.83 7 | 99.69 44 | 99.68 19 | 98.98 20 | 99.37 97 | 64.01 333 | 98.81 33 | 99.94 40 | 98.79 72 | 99.86 47 | 99.84 12 |
|
ACMMPR | | | 99.49 13 | 99.36 19 | 99.86 12 | 99.87 15 | 99.79 16 | 99.66 54 | 99.67 22 | 98.15 80 | 99.67 40 | 99.69 111 | 98.95 23 | 99.96 18 | 98.69 83 | 99.87 37 | 99.84 12 |
|
HPM-MVS | | | 99.42 29 | 99.28 38 | 99.83 22 | 99.90 3 | 99.72 25 | 99.81 15 | 99.54 61 | 97.59 131 | 99.68 34 | 99.63 138 | 98.91 26 | 99.94 40 | 98.58 96 | 99.91 15 | 99.84 12 |
|
SteuartSystems-ACMMP | | | 99.54 7 | 99.42 11 | 99.87 6 | 99.82 29 | 99.81 11 | 99.59 79 | 99.51 84 | 98.62 49 | 99.79 18 | 99.83 37 | 99.28 3 | 99.97 10 | 98.48 108 | 99.90 22 | 99.84 12 |
Skip Steuart: Steuart Systems R&D Blog. |
1112_ss | | | 98.98 89 | 98.77 95 | 99.59 67 | 99.68 71 | 99.02 106 | 99.25 206 | 99.48 111 | 97.23 164 | 99.13 147 | 99.58 154 | 96.93 105 | 99.90 84 | 98.87 60 | 98.78 152 | 99.84 12 |
|
MP-MVS-pluss | | | 99.37 37 | 99.20 46 | 99.88 4 | 99.90 3 | 99.87 2 | 99.30 186 | 99.52 75 | 97.18 167 | 99.60 56 | 99.79 72 | 98.79 35 | 99.95 33 | 98.83 68 | 99.91 15 | 99.83 23 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
MPTG | | | 99.49 13 | 99.36 19 | 99.89 2 | 99.90 3 | 99.86 3 | 99.36 173 | 99.47 125 | 98.79 40 | 99.68 34 | 99.81 53 | 98.43 61 | 99.97 10 | 98.88 56 | 99.90 22 | 99.83 23 |
|
MTAPA | | | 99.52 11 | 99.39 15 | 99.89 2 | 99.90 3 | 99.86 3 | 99.66 54 | 99.47 125 | 98.79 40 | 99.68 34 | 99.81 53 | 98.43 61 | 99.97 10 | 98.88 56 | 99.90 22 | 99.83 23 |
|
Regformer-3 | | | 99.57 6 | 99.53 5 | 99.68 50 | 99.76 41 | 99.29 80 | 99.58 82 | 99.44 153 | 99.01 14 | 99.87 6 | 99.80 64 | 98.97 19 | 99.91 72 | 99.44 15 | 99.92 9 | 99.83 23 |
|
PGM-MVS | | | 99.45 22 | 99.31 31 | 99.86 12 | 99.87 15 | 99.78 20 | 99.58 82 | 99.65 30 | 97.84 111 | 99.71 29 | 99.80 64 | 99.12 7 | 99.97 10 | 98.33 121 | 99.87 37 | 99.83 23 |
|
mPP-MVS | | | 99.44 25 | 99.30 33 | 99.86 12 | 99.88 11 | 99.79 16 | 99.69 44 | 99.48 111 | 98.12 84 | 99.50 72 | 99.75 90 | 98.78 36 | 99.97 10 | 98.57 98 | 99.89 30 | 99.83 23 |
|
CP-MVS | | | 99.45 22 | 99.32 26 | 99.85 17 | 99.83 28 | 99.75 21 | 99.69 44 | 99.52 75 | 98.07 93 | 99.53 67 | 99.63 138 | 98.93 25 | 99.97 10 | 98.74 75 | 99.91 15 | 99.83 23 |
|
TSAR-MVS + MP. | | | 99.58 3 | 99.50 7 | 99.81 27 | 99.91 1 | 99.66 34 | 99.63 67 | 99.39 175 | 98.91 30 | 99.78 22 | 99.85 26 | 99.36 2 | 99.94 40 | 98.84 66 | 99.88 33 | 99.82 30 |
|
MP-MVS | | | 99.33 41 | 99.15 50 | 99.87 6 | 99.88 11 | 99.82 10 | 99.66 54 | 99.46 134 | 98.09 89 | 99.48 76 | 99.74 94 | 98.29 70 | 99.96 18 | 97.93 148 | 99.87 37 | 99.82 30 |
|
MCST-MVS | | | 99.43 27 | 99.30 33 | 99.82 24 | 99.79 33 | 99.74 24 | 99.29 190 | 99.40 172 | 98.79 40 | 99.52 69 | 99.62 143 | 98.91 26 | 99.90 84 | 98.64 88 | 99.75 77 | 99.82 30 |
|
DeepC-MVS_fast | | 98.69 1 | 99.49 13 | 99.39 15 | 99.77 35 | 99.63 87 | 99.59 46 | 99.36 173 | 99.46 134 | 99.07 10 | 99.79 18 | 99.82 44 | 98.85 30 | 99.92 63 | 98.68 85 | 99.87 37 | 99.82 30 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
HSP-MVS | | | 99.41 32 | 99.26 43 | 99.85 17 | 99.89 8 | 99.80 12 | 99.67 51 | 99.37 188 | 98.70 45 | 99.77 23 | 99.49 179 | 98.21 73 | 99.95 33 | 98.46 111 | 99.77 74 | 99.81 34 |
|
CPTT-MVS | | | 99.11 71 | 98.90 80 | 99.74 43 | 99.80 32 | 99.46 65 | 99.59 79 | 99.49 102 | 97.03 182 | 99.63 50 | 99.69 111 | 97.27 97 | 99.96 18 | 97.82 156 | 99.84 56 | 99.81 34 |
|
ACMMP | | | 99.45 22 | 99.32 26 | 99.82 24 | 99.89 8 | 99.67 32 | 99.62 70 | 99.69 18 | 98.12 84 | 99.63 50 | 99.84 35 | 98.73 46 | 99.96 18 | 98.55 103 | 99.83 60 | 99.81 34 |
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 |
DeepPCF-MVS | | 98.18 3 | 98.81 107 | 99.37 17 | 97.12 279 | 99.60 97 | 91.75 306 | 98.61 297 | 99.44 153 | 99.35 1 | 99.83 11 | 99.85 26 | 98.70 48 | 99.81 124 | 99.02 47 | 99.91 15 | 99.81 34 |
|
3Dnovator+ | | 97.12 13 | 99.18 57 | 98.97 71 | 99.82 24 | 99.17 182 | 99.68 30 | 99.81 15 | 99.51 84 | 99.20 6 | 98.72 206 | 99.89 10 | 95.68 140 | 99.97 10 | 98.86 63 | 99.86 47 | 99.81 34 |
|
Regformer-1 | | | 99.53 9 | 99.47 8 | 99.72 47 | 99.71 63 | 99.44 67 | 99.49 122 | 99.46 134 | 98.95 25 | 99.83 11 | 99.76 85 | 99.01 11 | 99.93 55 | 99.17 35 | 99.87 37 | 99.80 39 |
|
Regformer-2 | | | 99.54 7 | 99.47 8 | 99.75 38 | 99.71 63 | 99.52 58 | 99.49 122 | 99.49 102 | 98.94 26 | 99.83 11 | 99.76 85 | 99.01 11 | 99.94 40 | 99.15 37 | 99.87 37 | 99.80 39 |
|
APD-MVS | | | 99.27 49 | 99.08 56 | 99.84 21 | 99.75 47 | 99.79 16 | 99.50 116 | 99.50 97 | 97.16 169 | 99.77 23 | 99.82 44 | 98.78 36 | 99.94 40 | 97.56 181 | 99.86 47 | 99.80 39 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
NCCC | | | 99.34 40 | 99.19 47 | 99.79 32 | 99.61 95 | 99.65 37 | 99.30 186 | 99.48 111 | 98.86 32 | 99.21 137 | 99.63 138 | 98.72 47 | 99.90 84 | 98.25 125 | 99.63 100 | 99.80 39 |
|
HPM-MVS++ | | | 99.39 36 | 99.23 45 | 99.87 6 | 99.75 47 | 99.84 6 | 99.43 144 | 99.51 84 | 98.68 47 | 99.27 123 | 99.53 167 | 98.64 52 | 99.96 18 | 98.44 113 | 99.80 67 | 99.79 43 |
|
abl_6 | | | 99.44 25 | 99.31 31 | 99.83 22 | 99.85 23 | 99.75 21 | 99.66 54 | 99.59 37 | 98.13 82 | 99.82 14 | 99.81 53 | 98.60 54 | 99.96 18 | 98.46 111 | 99.88 33 | 99.79 43 |
|
PVSNet_Blended_VisFu | | | 99.36 38 | 99.28 38 | 99.61 65 | 99.86 20 | 99.07 101 | 99.47 131 | 99.93 2 | 97.66 129 | 99.71 29 | 99.86 22 | 97.73 86 | 99.96 18 | 99.47 12 | 99.82 64 | 99.79 43 |
|
3Dnovator | | 97.25 9 | 99.24 52 | 99.05 58 | 99.81 27 | 99.12 190 | 99.66 34 | 99.84 9 | 99.74 10 | 99.09 9 | 98.92 184 | 99.90 7 | 95.94 131 | 99.98 5 | 98.95 52 | 99.92 9 | 99.79 43 |
|
APD-MVS_3200maxsize | | | 99.48 17 | 99.35 22 | 99.85 17 | 99.76 41 | 99.83 7 | 99.63 67 | 99.54 61 | 98.36 65 | 99.79 18 | 99.82 44 | 98.86 29 | 99.95 33 | 98.62 91 | 99.81 65 | 99.78 47 |
|
CDPH-MVS | | | 99.13 62 | 98.91 79 | 99.80 29 | 99.75 47 | 99.71 26 | 99.15 224 | 99.41 165 | 96.60 206 | 99.60 56 | 99.55 163 | 98.83 31 | 99.90 84 | 97.48 189 | 99.83 60 | 99.78 47 |
|
SD-MVS | | | 99.41 32 | 99.52 6 | 99.05 136 | 99.74 53 | 99.68 30 | 99.46 134 | 99.52 75 | 99.11 8 | 99.88 3 | 99.91 5 | 99.43 1 | 97.70 307 | 98.72 80 | 99.93 8 | 99.77 49 |
|
CNVR-MVS | | | 99.42 29 | 99.30 33 | 99.78 33 | 99.62 91 | 99.71 26 | 99.26 205 | 99.52 75 | 98.82 36 | 99.39 93 | 99.71 102 | 98.96 20 | 99.85 103 | 98.59 95 | 99.80 67 | 99.77 49 |
|
MVS_111021_HR | | | 99.41 32 | 99.32 26 | 99.66 53 | 99.72 61 | 99.47 64 | 98.95 274 | 99.85 6 | 98.82 36 | 99.54 66 | 99.73 97 | 98.51 56 | 99.74 139 | 98.91 55 | 99.88 33 | 99.77 49 |
|
QAPM | | | 98.67 122 | 98.30 135 | 99.80 29 | 99.20 173 | 99.67 32 | 99.77 24 | 99.72 11 | 94.74 266 | 98.73 205 | 99.90 7 | 95.78 137 | 99.98 5 | 96.96 221 | 99.88 33 | 99.76 52 |
|
test9_res | | | | | | | | | | | | | | | 97.49 188 | 99.72 83 | 99.75 53 |
|
train_agg | | | 99.02 84 | 98.77 95 | 99.77 35 | 99.67 72 | 99.65 37 | 99.05 245 | 99.41 165 | 96.28 229 | 98.95 179 | 99.49 179 | 98.76 41 | 99.91 72 | 97.63 175 | 99.72 83 | 99.75 53 |
|
agg_prior3 | | | 98.97 91 | 98.71 101 | 99.75 38 | 99.67 72 | 99.60 44 | 99.04 250 | 99.41 165 | 95.93 251 | 98.87 190 | 99.48 185 | 98.61 53 | 99.91 72 | 97.63 175 | 99.72 83 | 99.75 53 |
|
agg_prior1 | | | 99.01 87 | 98.76 97 | 99.76 37 | 99.67 72 | 99.62 40 | 98.99 261 | 99.40 172 | 96.26 232 | 98.87 190 | 99.49 179 | 98.77 39 | 99.91 72 | 97.69 172 | 99.72 83 | 99.75 53 |
|
agg_prior2 | | | | | | | | | | | | | | | 97.21 204 | 99.73 82 | 99.75 53 |
|
test_prior3 | | | 99.21 54 | 99.05 58 | 99.68 50 | 99.67 72 | 99.48 62 | 98.96 270 | 99.56 46 | 98.34 66 | 99.01 168 | 99.52 171 | 98.68 49 | 99.83 115 | 97.96 145 | 99.74 79 | 99.74 58 |
|
test_prior | | | | | 99.68 50 | 99.67 72 | 99.48 62 | | 99.56 46 | | | | | 99.83 115 | | | 99.74 58 |
|
test12 | | | | | 99.75 38 | 99.64 85 | 99.61 42 | | 99.29 221 | | 99.21 137 | | 98.38 65 | 99.89 92 | | 99.74 79 | 99.74 58 |
|
114514_t | | | 98.93 92 | 98.67 105 | 99.72 47 | 99.85 23 | 99.53 55 | 99.62 70 | 99.59 37 | 92.65 297 | 99.71 29 | 99.78 77 | 98.06 78 | 99.90 84 | 98.84 66 | 99.91 15 | 99.74 58 |
|
Vis-MVSNet | | | 99.12 67 | 98.97 71 | 99.56 73 | 99.78 34 | 99.10 98 | 99.68 49 | 99.66 25 | 98.49 56 | 99.86 7 | 99.87 19 | 94.77 182 | 99.84 108 | 99.19 32 | 99.41 107 | 99.74 58 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
旧先验1 | | | | | | 99.74 53 | 99.59 46 | | 99.54 61 | | | 99.69 111 | 98.47 58 | | | 99.68 93 | 99.73 63 |
|
1121 | | | 99.09 75 | 98.87 84 | 99.75 38 | 99.74 53 | 99.60 44 | 99.27 197 | 99.48 111 | 96.82 193 | 99.25 127 | 99.65 128 | 98.38 65 | 99.93 55 | 97.53 184 | 99.67 94 | 99.73 63 |
|
EPNet | | | 98.86 98 | 98.71 101 | 99.30 112 | 97.20 304 | 98.18 195 | 99.62 70 | 98.91 277 | 99.28 2 | 98.63 225 | 99.81 53 | 95.96 128 | 99.99 1 | 99.24 29 | 99.72 83 | 99.73 63 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
IS-MVSNet | | | 99.05 80 | 98.87 84 | 99.57 70 | 99.73 58 | 99.32 76 | 99.75 34 | 99.20 242 | 98.02 102 | 99.56 63 | 99.86 22 | 96.54 116 | 99.67 168 | 98.09 134 | 99.13 123 | 99.73 63 |
|
F-COLMAP | | | 99.19 55 | 99.04 61 | 99.64 61 | 99.78 34 | 99.27 83 | 99.42 151 | 99.54 61 | 97.29 158 | 99.41 88 | 99.59 151 | 98.42 64 | 99.93 55 | 98.19 127 | 99.69 90 | 99.73 63 |
|
DeepC-MVS | | 98.35 2 | 99.30 44 | 99.19 47 | 99.64 61 | 99.82 29 | 99.23 87 | 99.62 70 | 99.55 53 | 98.94 26 | 99.63 50 | 99.95 2 | 95.82 136 | 99.94 40 | 99.37 16 | 99.97 2 | 99.73 63 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
æ–°å‡ ä½•1 | | | | | 99.75 38 | 99.75 47 | 99.59 46 | | 99.54 61 | 96.76 194 | 99.29 115 | 99.64 134 | 98.43 61 | 99.94 40 | 96.92 225 | 99.66 95 | 99.72 69 |
|
æ— å…ˆéªŒ | | | | | | | | 98.99 261 | 99.51 84 | 96.89 189 | | | | 99.93 55 | 97.53 184 | | 99.72 69 |
|
test222 | | | | | | 99.75 47 | 99.49 61 | 98.91 279 | 99.49 102 | 96.42 221 | 99.34 107 | 99.65 128 | 98.28 71 | | | 99.69 90 | 99.72 69 |
|
testdata | | | | | 99.54 74 | 99.75 47 | 98.95 120 | | 99.51 84 | 97.07 178 | 99.43 84 | 99.70 106 | 98.87 28 | 99.94 40 | 97.76 162 | 99.64 98 | 99.72 69 |
|
VNet | | | 99.11 71 | 98.90 80 | 99.73 45 | 99.52 108 | 99.56 49 | 99.41 155 | 99.39 175 | 99.01 14 | 99.74 28 | 99.78 77 | 95.56 141 | 99.92 63 | 99.52 6 | 98.18 174 | 99.72 69 |
|
WTY-MVS | | | 99.06 79 | 98.88 83 | 99.61 65 | 99.62 91 | 99.16 91 | 99.37 169 | 99.56 46 | 98.04 99 | 99.53 67 | 99.62 143 | 96.84 106 | 99.94 40 | 98.85 65 | 98.49 165 | 99.72 69 |
|
CSCG | | | 99.32 42 | 99.32 26 | 99.32 108 | 99.85 23 | 98.29 191 | 99.71 41 | 99.66 25 | 98.11 86 | 99.41 88 | 99.80 64 | 98.37 67 | 99.96 18 | 98.99 49 | 99.96 4 | 99.72 69 |
|
原ACMM1 | | | | | 99.65 56 | 99.73 58 | 99.33 75 | | 99.47 125 | 97.46 142 | 99.12 149 | 99.66 127 | 98.67 51 | 99.91 72 | 97.70 171 | 99.69 90 | 99.71 76 |
|
LFMVS | | | 97.90 185 | 97.35 218 | 99.54 74 | 99.52 108 | 99.01 108 | 99.39 162 | 98.24 308 | 97.10 177 | 99.65 48 | 99.79 72 | 84.79 311 | 99.91 72 | 99.28 26 | 98.38 169 | 99.69 77 |
|
EPNet_dtu | | | 98.03 168 | 97.96 156 | 98.23 235 | 98.27 288 | 95.54 271 | 99.23 209 | 98.75 288 | 99.02 11 | 97.82 261 | 99.71 102 | 96.11 127 | 99.48 190 | 93.04 292 | 99.65 97 | 99.69 77 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
PAPM_NR | | | 99.04 81 | 98.84 88 | 99.66 53 | 99.74 53 | 99.44 67 | 99.39 162 | 99.38 181 | 97.70 126 | 99.28 119 | 99.28 240 | 98.34 68 | 99.85 103 | 96.96 221 | 99.45 104 | 99.69 77 |
|
EPP-MVSNet | | | 99.13 62 | 98.99 68 | 99.53 78 | 99.65 84 | 99.06 102 | 99.81 15 | 99.33 209 | 97.43 146 | 99.60 56 | 99.88 14 | 97.14 99 | 99.84 108 | 99.13 38 | 98.94 139 | 99.69 77 |
|
sss | | | 99.17 58 | 99.05 58 | 99.53 78 | 99.62 91 | 98.97 115 | 99.36 173 | 99.62 31 | 97.83 112 | 99.67 40 | 99.65 128 | 97.37 95 | 99.95 33 | 99.19 32 | 99.19 120 | 99.68 81 |
|
PHI-MVS | | | 99.30 44 | 99.17 49 | 99.70 49 | 99.56 105 | 99.52 58 | 99.58 82 | 99.80 8 | 97.12 173 | 99.62 53 | 99.73 97 | 98.58 55 | 99.90 84 | 98.61 93 | 99.91 15 | 99.68 81 |
|
PVSNet_0 | | 94.43 19 | 96.09 266 | 95.47 268 | 97.94 253 | 99.31 154 | 94.34 290 | 97.81 316 | 99.70 15 | 97.12 173 | 97.46 265 | 98.75 280 | 89.71 278 | 99.79 130 | 97.69 172 | 81.69 320 | 99.68 81 |
|
TAMVS | | | 99.12 67 | 99.08 56 | 99.24 121 | 99.46 121 | 98.55 174 | 99.51 111 | 99.46 134 | 98.09 89 | 99.45 80 | 99.82 44 | 98.34 68 | 99.51 189 | 98.70 81 | 98.93 140 | 99.67 84 |
|
CHOSEN 280x420 | | | 99.12 67 | 99.13 51 | 99.08 132 | 99.66 82 | 97.89 203 | 98.43 304 | 99.71 13 | 98.88 31 | 99.62 53 | 99.76 85 | 96.63 114 | 99.70 163 | 99.46 13 | 99.99 1 | 99.66 85 |
|
CDS-MVSNet | | | 99.09 75 | 99.03 63 | 99.25 120 | 99.42 128 | 98.73 158 | 99.45 135 | 99.46 134 | 98.11 86 | 99.46 79 | 99.77 82 | 98.01 79 | 99.37 206 | 98.70 81 | 98.92 142 | 99.66 85 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
PAPR | | | 98.63 126 | 98.34 131 | 99.51 84 | 99.40 135 | 99.03 105 | 98.80 285 | 99.36 189 | 96.33 226 | 99.00 175 | 99.12 256 | 98.46 59 | 99.84 108 | 95.23 266 | 99.37 112 | 99.66 85 |
|
TSAR-MVS + GP. | | | 99.36 38 | 99.36 19 | 99.36 103 | 99.67 72 | 98.61 172 | 99.07 239 | 99.33 209 | 99.00 18 | 99.82 14 | 99.81 53 | 99.06 8 | 99.84 108 | 99.09 41 | 99.42 106 | 99.65 88 |
|
MVSFormer | | | 99.17 58 | 99.12 53 | 99.29 116 | 99.51 110 | 98.94 123 | 99.88 1 | 99.46 134 | 97.55 136 | 99.80 16 | 99.65 128 | 97.39 92 | 99.28 229 | 99.03 45 | 99.85 51 | 99.65 88 |
|
jason | | | 99.13 62 | 99.03 63 | 99.45 93 | 99.46 121 | 98.87 131 | 99.12 228 | 99.26 235 | 98.03 101 | 99.79 18 | 99.65 128 | 97.02 102 | 99.85 103 | 99.02 47 | 99.90 22 | 99.65 88 |
jason: jason. |
PLC | | 97.94 4 | 99.02 84 | 98.85 87 | 99.53 78 | 99.66 82 | 99.01 108 | 99.24 208 | 99.52 75 | 96.85 191 | 99.27 123 | 99.48 185 | 98.25 72 | 99.91 72 | 97.76 162 | 99.62 101 | 99.65 88 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
TAPA-MVS | | 97.07 15 | 97.74 206 | 97.34 221 | 98.94 148 | 99.70 68 | 97.53 211 | 99.25 206 | 99.51 84 | 91.90 301 | 99.30 111 | 99.63 138 | 98.78 36 | 99.64 174 | 88.09 308 | 99.87 37 | 99.65 88 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
LCM-MVSNet-Re | | | 97.83 191 | 98.15 140 | 96.87 284 | 99.30 155 | 92.25 305 | 99.59 79 | 98.26 307 | 97.43 146 | 96.20 281 | 99.13 253 | 96.27 123 | 98.73 283 | 98.17 129 | 98.99 134 | 99.64 93 |
|
BH-RMVSNet | | | 98.41 134 | 98.08 147 | 99.40 101 | 99.41 131 | 98.83 138 | 99.30 186 | 98.77 287 | 97.70 126 | 98.94 181 | 99.65 128 | 92.91 235 | 99.74 139 | 96.52 241 | 99.55 102 | 99.64 93 |
|
MVS_111021_LR | | | 99.41 32 | 99.33 25 | 99.65 56 | 99.77 38 | 99.51 60 | 98.94 276 | 99.85 6 | 98.82 36 | 99.65 48 | 99.74 94 | 98.51 56 | 99.80 127 | 98.83 68 | 99.89 30 | 99.64 93 |
|
MVS_0305 | | | 99.24 52 | 99.13 51 | 99.57 70 | 99.44 126 | 99.12 96 | 99.29 190 | 99.55 53 | 98.93 28 | 99.52 69 | 99.61 146 | 96.36 120 | 99.97 10 | 99.57 2 | 99.92 9 | 99.63 96 |
|
MVS | | | 97.28 237 | 96.55 244 | 99.48 87 | 98.78 258 | 98.95 120 | 99.27 197 | 99.39 175 | 83.53 317 | 98.08 251 | 99.54 166 | 96.97 103 | 99.87 97 | 94.23 285 | 99.16 121 | 99.63 96 |
|
MSLP-MVS++ | | | 99.46 21 | 99.47 8 | 99.44 96 | 99.60 97 | 99.16 91 | 99.41 155 | 99.71 13 | 98.98 20 | 99.45 80 | 99.78 77 | 99.19 4 | 99.54 188 | 99.28 26 | 99.84 56 | 99.63 96 |
|
GA-MVS | | | 97.85 188 | 97.47 203 | 99.00 141 | 99.38 138 | 97.99 201 | 98.57 299 | 99.15 247 | 97.04 181 | 98.90 187 | 99.30 237 | 89.83 277 | 99.38 203 | 96.70 234 | 98.33 170 | 99.62 99 |
|
Vis-MVSNet (Re-imp) | | | 98.87 95 | 98.72 99 | 99.31 109 | 99.71 63 | 98.88 130 | 99.80 19 | 99.44 153 | 97.91 105 | 99.36 101 | 99.78 77 | 95.49 144 | 99.43 201 | 97.91 149 | 99.11 124 | 99.62 99 |
|
VDD-MVS | | | 97.73 207 | 97.35 218 | 98.88 167 | 99.47 120 | 97.12 221 | 99.34 179 | 98.85 283 | 98.19 76 | 99.67 40 | 99.85 26 | 82.98 315 | 99.92 63 | 99.49 11 | 98.32 171 | 99.60 101 |
|
DELS-MVS | | | 99.48 17 | 99.42 11 | 99.65 56 | 99.72 61 | 99.40 72 | 99.05 245 | 99.66 25 | 99.14 7 | 99.57 62 | 99.80 64 | 98.46 59 | 99.94 40 | 99.57 2 | 99.84 56 | 99.60 101 |
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 |
PVSNet_Blended | | | 99.08 77 | 98.97 71 | 99.42 100 | 99.76 41 | 98.79 154 | 98.78 286 | 99.91 3 | 96.74 195 | 99.67 40 | 99.49 179 | 97.53 89 | 99.88 95 | 98.98 50 | 99.85 51 | 99.60 101 |
|
OMC-MVS | | | 99.08 77 | 99.04 61 | 99.20 125 | 99.67 72 | 98.22 194 | 99.28 194 | 99.52 75 | 98.07 93 | 99.66 45 | 99.81 53 | 97.79 84 | 99.78 132 | 97.79 158 | 99.81 65 | 99.60 101 |
|
AllTest | | | 98.87 95 | 98.72 99 | 99.31 109 | 99.86 20 | 98.48 184 | 99.56 95 | 99.61 32 | 97.85 109 | 99.36 101 | 99.85 26 | 95.95 129 | 99.85 103 | 96.66 237 | 99.83 60 | 99.59 105 |
|
TestCases | | | | | 99.31 109 | 99.86 20 | 98.48 184 | | 99.61 32 | 97.85 109 | 99.36 101 | 99.85 26 | 95.95 129 | 99.85 103 | 96.66 237 | 99.83 60 | 99.59 105 |
|
lupinMVS | | | 99.13 62 | 99.01 67 | 99.46 92 | 99.51 110 | 98.94 123 | 99.05 245 | 99.16 246 | 97.86 107 | 99.80 16 | 99.56 160 | 97.39 92 | 99.86 100 | 98.94 53 | 99.85 51 | 99.58 107 |
|
RPSCF | | | 98.22 143 | 98.62 113 | 96.99 280 | 99.82 29 | 91.58 307 | 99.72 39 | 99.44 153 | 96.61 204 | 99.66 45 | 99.89 10 | 95.92 132 | 99.82 120 | 97.46 192 | 99.10 126 | 99.57 108 |
|
DSMNet-mixed | | | 97.25 238 | 97.35 218 | 96.95 282 | 97.84 293 | 93.61 298 | 99.57 88 | 96.63 323 | 96.13 245 | 98.87 190 | 98.61 283 | 94.59 191 | 97.70 307 | 95.08 268 | 98.86 147 | 99.55 109 |
|
AdaColmap | | | 99.01 87 | 98.80 92 | 99.66 53 | 99.56 105 | 99.54 52 | 99.18 219 | 99.70 15 | 98.18 79 | 99.35 104 | 99.63 138 | 96.32 121 | 99.90 84 | 97.48 189 | 99.77 74 | 99.55 109 |
|
alignmvs | | | 98.81 107 | 98.56 122 | 99.58 69 | 99.43 127 | 99.42 69 | 99.51 111 | 98.96 270 | 98.61 50 | 99.35 104 | 98.92 271 | 94.78 178 | 99.77 134 | 99.35 17 | 98.11 178 | 99.54 111 |
|
PatchmatchNet | | | 98.31 139 | 98.36 129 | 98.19 240 | 99.16 184 | 95.32 276 | 99.27 197 | 98.92 274 | 97.37 152 | 99.37 97 | 99.58 154 | 94.90 170 | 99.70 163 | 97.43 195 | 99.21 118 | 99.54 111 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
PVSNet | | 96.02 17 | 98.85 104 | 98.84 88 | 98.89 164 | 99.73 58 | 97.28 214 | 98.32 308 | 99.60 34 | 97.86 107 | 99.50 72 | 99.57 158 | 96.75 111 | 99.86 100 | 98.56 101 | 99.70 89 | 99.54 111 |
|
MSDG | | | 98.98 89 | 98.80 92 | 99.53 78 | 99.76 41 | 99.19 88 | 98.75 289 | 99.55 53 | 97.25 161 | 99.47 77 | 99.77 82 | 97.82 83 | 99.87 97 | 96.93 224 | 99.90 22 | 99.54 111 |
|
UGNet | | | 98.87 95 | 98.69 103 | 99.40 101 | 99.22 170 | 98.72 159 | 99.44 139 | 99.68 19 | 99.24 4 | 99.18 145 | 99.42 200 | 92.74 239 | 99.96 18 | 99.34 21 | 99.94 7 | 99.53 115 |
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 |
Patchmatch-test | | | 97.93 180 | 97.65 188 | 98.77 187 | 99.18 177 | 97.07 226 | 99.03 251 | 99.14 249 | 96.16 241 | 98.74 204 | 99.57 158 | 94.56 192 | 99.72 151 | 93.36 291 | 99.11 124 | 99.52 116 |
|
PMMVS | | | 98.80 110 | 98.62 113 | 99.34 104 | 99.27 163 | 98.70 160 | 98.76 288 | 99.31 216 | 97.34 153 | 99.21 137 | 99.07 258 | 97.20 98 | 99.82 120 | 98.56 101 | 98.87 146 | 99.52 116 |
|
LS3D | | | 99.27 49 | 99.12 53 | 99.74 43 | 99.18 177 | 99.75 21 | 99.56 95 | 99.57 43 | 98.45 59 | 99.49 75 | 99.85 26 | 97.77 85 | 99.94 40 | 98.33 121 | 99.84 56 | 99.52 116 |
|
Effi-MVS+ | | | 98.81 107 | 98.59 120 | 99.48 87 | 99.46 121 | 99.12 96 | 98.08 314 | 99.50 97 | 97.50 141 | 99.38 95 | 99.41 203 | 96.37 119 | 99.81 124 | 99.11 40 | 98.54 162 | 99.51 119 |
|
Patchmatch-RL test | | | 95.84 268 | 95.81 257 | 95.95 291 | 95.61 307 | 90.57 308 | 98.24 310 | 98.39 304 | 95.10 262 | 95.20 287 | 98.67 282 | 94.78 178 | 97.77 305 | 96.28 247 | 90.02 300 | 99.51 119 |
|
mvs_anonymous | | | 99.03 83 | 98.99 68 | 99.16 127 | 99.38 138 | 98.52 179 | 99.51 111 | 99.38 181 | 97.79 115 | 99.38 95 | 99.81 53 | 97.30 96 | 99.45 193 | 99.35 17 | 98.99 134 | 99.51 119 |
|
Patchmatch-test1 | | | 98.16 149 | 98.14 141 | 98.22 237 | 99.30 155 | 95.55 269 | 99.07 239 | 98.97 268 | 97.57 134 | 99.43 84 | 99.60 149 | 92.72 240 | 99.60 182 | 97.38 197 | 99.20 119 | 99.50 122 |
|
test_normal | | | 97.44 232 | 96.77 242 | 99.44 96 | 97.75 296 | 99.00 110 | 99.10 236 | 98.64 297 | 97.71 124 | 93.93 300 | 98.82 275 | 87.39 301 | 99.83 115 | 98.61 93 | 98.97 136 | 99.49 123 |
|
ab-mvs | | | 98.86 98 | 98.63 110 | 99.54 74 | 99.64 85 | 99.19 88 | 99.44 139 | 99.54 61 | 97.77 117 | 99.30 111 | 99.81 53 | 94.20 206 | 99.93 55 | 99.17 35 | 98.82 149 | 99.49 123 |
|
ADS-MVSNet2 | | | 98.02 170 | 98.07 149 | 97.87 258 | 99.33 147 | 95.19 279 | 99.23 209 | 99.08 255 | 96.24 234 | 99.10 154 | 99.67 121 | 94.11 211 | 98.93 278 | 96.81 228 | 99.05 130 | 99.48 125 |
|
ADS-MVSNet | | | 98.20 146 | 98.08 147 | 98.56 200 | 99.33 147 | 96.48 252 | 99.23 209 | 99.15 247 | 96.24 234 | 99.10 154 | 99.67 121 | 94.11 211 | 99.71 157 | 96.81 228 | 99.05 130 | 99.48 125 |
|
tpm | | | 97.67 217 | 97.55 194 | 98.03 246 | 99.02 208 | 95.01 282 | 99.43 144 | 98.54 303 | 96.44 219 | 99.12 149 | 99.34 229 | 91.83 258 | 99.60 182 | 97.75 164 | 96.46 229 | 99.48 125 |
|
CNLPA | | | 99.14 61 | 98.99 68 | 99.59 67 | 99.58 100 | 99.41 70 | 99.16 221 | 99.44 153 | 98.45 59 | 99.19 143 | 99.49 179 | 98.08 77 | 99.89 92 | 97.73 166 | 99.75 77 | 99.48 125 |
|
canonicalmvs | | | 99.02 84 | 98.86 86 | 99.51 84 | 99.42 128 | 99.32 76 | 99.80 19 | 99.48 111 | 98.63 48 | 99.31 110 | 98.81 276 | 97.09 100 | 99.75 138 | 99.27 28 | 97.90 184 | 99.47 129 |
|
Test4 | | | 95.05 276 | 93.67 284 | 99.22 124 | 96.07 306 | 98.94 123 | 99.20 217 | 99.27 233 | 97.71 124 | 89.96 315 | 97.59 306 | 66.18 323 | 99.25 238 | 98.06 141 | 98.96 137 | 99.47 129 |
|
MIMVSNet | | | 97.73 207 | 97.45 205 | 98.57 198 | 99.45 125 | 97.50 212 | 99.02 254 | 98.98 267 | 96.11 246 | 99.41 88 | 99.14 252 | 90.28 271 | 98.74 282 | 95.74 255 | 98.93 140 | 99.47 129 |
|
MVS_test0326 | | | 98.79 111 | 98.62 113 | 99.28 118 | 99.00 210 | 98.41 189 | 99.01 258 | 99.09 254 | 99.23 5 | 98.67 216 | 99.68 116 | 94.31 203 | 99.95 33 | 98.74 75 | 99.89 30 | 99.46 132 |
|
MVS_Test | | | 99.10 74 | 98.97 71 | 99.48 87 | 99.49 116 | 99.14 94 | 99.67 51 | 99.34 201 | 97.31 156 | 99.58 60 | 99.76 85 | 97.65 88 | 99.82 120 | 98.87 60 | 99.07 129 | 99.46 132 |
|
MDTV_nov1_ep13_2view | | | | | | | 95.18 280 | 99.35 177 | | 96.84 192 | 99.58 60 | | 95.19 154 | | 97.82 156 | | 99.46 132 |
|
MVS-HIRNet | | | 95.75 269 | 95.16 273 | 97.51 273 | 99.30 155 | 93.69 297 | 98.88 281 | 95.78 324 | 85.09 316 | 98.78 201 | 92.65 320 | 91.29 264 | 99.37 206 | 94.85 271 | 99.85 51 | 99.46 132 |
|
MVS_dtu | | | 98.77 114 | 98.60 119 | 99.30 112 | 98.95 224 | 98.47 186 | 99.08 238 | 99.27 233 | 99.26 3 | 98.94 181 | 99.71 102 | 93.54 226 | 99.96 18 | 98.86 63 | 99.79 71 | 99.45 136 |
|
DI_MVS_plusplus_test | | | 97.45 231 | 96.79 240 | 99.44 96 | 97.76 295 | 99.04 104 | 99.21 215 | 98.61 300 | 97.74 121 | 94.01 297 | 98.83 274 | 87.38 302 | 99.83 115 | 98.63 89 | 98.90 144 | 99.44 137 |
|
DP-MVS Recon | | | 99.12 67 | 98.95 75 | 99.65 56 | 99.74 53 | 99.70 28 | 99.27 197 | 99.57 43 | 96.40 224 | 99.42 86 | 99.68 116 | 98.75 44 | 99.80 127 | 97.98 144 | 99.72 83 | 99.44 137 |
|
PatchMatch-RL | | | 98.84 106 | 98.62 113 | 99.52 82 | 99.71 63 | 99.28 81 | 99.06 243 | 99.77 9 | 97.74 121 | 99.50 72 | 99.53 167 | 95.41 145 | 99.84 108 | 97.17 209 | 99.64 98 | 99.44 137 |
|
VDDNet | | | 97.55 221 | 97.02 236 | 99.16 127 | 99.49 116 | 98.12 199 | 99.38 167 | 99.30 218 | 95.35 259 | 99.68 34 | 99.90 7 | 82.62 317 | 99.93 55 | 99.31 24 | 98.13 177 | 99.42 140 |
|
PCF-MVS | | 97.08 14 | 97.66 218 | 97.06 235 | 99.47 90 | 99.61 95 | 99.09 99 | 98.04 315 | 99.25 237 | 91.24 304 | 98.51 231 | 99.70 106 | 94.55 193 | 99.91 72 | 92.76 294 | 99.85 51 | 99.42 140 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
HY-MVS | | 97.30 7 | 98.85 104 | 98.64 109 | 99.47 90 | 99.42 128 | 99.08 100 | 99.62 70 | 99.36 189 | 97.39 151 | 99.28 119 | 99.68 116 | 96.44 117 | 99.92 63 | 98.37 117 | 98.22 172 | 99.40 142 |
|
Fast-Effi-MVS+ | | | 98.70 119 | 98.43 126 | 99.51 84 | 99.51 110 | 99.28 81 | 99.52 107 | 99.47 125 | 96.11 246 | 99.01 168 | 99.34 229 | 96.20 125 | 99.84 108 | 97.88 151 | 98.82 149 | 99.39 143 |
|
diffmvs | | | 98.72 118 | 98.49 124 | 99.43 99 | 99.48 119 | 99.19 88 | 99.62 70 | 99.42 162 | 95.58 257 | 99.37 97 | 99.67 121 | 96.14 126 | 99.74 139 | 98.14 131 | 98.96 137 | 99.37 144 |
|
EPMVS | | | 97.82 194 | 97.65 188 | 98.35 220 | 98.88 242 | 95.98 263 | 99.49 122 | 94.71 327 | 97.57 134 | 99.26 126 | 99.48 185 | 92.46 253 | 99.71 157 | 97.87 152 | 99.08 128 | 99.35 145 |
|
CostFormer | | | 97.72 209 | 97.73 183 | 97.71 269 | 99.15 187 | 94.02 292 | 99.54 103 | 99.02 264 | 94.67 267 | 99.04 165 | 99.35 226 | 92.35 255 | 99.77 134 | 98.50 107 | 97.94 183 | 99.34 146 |
|
BH-untuned | | | 98.42 133 | 98.36 129 | 98.59 196 | 99.49 116 | 96.70 245 | 99.27 197 | 99.13 250 | 97.24 163 | 98.80 199 | 99.38 212 | 95.75 138 | 99.74 139 | 97.07 214 | 99.16 121 | 99.33 147 |
|
PAPM | | | 97.59 220 | 97.09 234 | 99.07 133 | 99.06 201 | 98.26 193 | 98.30 309 | 99.10 252 | 94.88 263 | 98.08 251 | 99.34 229 | 96.27 123 | 99.64 174 | 89.87 302 | 98.92 142 | 99.31 148 |
|
tpm2 | | | 97.44 232 | 97.34 221 | 97.74 268 | 99.15 187 | 94.36 289 | 99.45 135 | 98.94 271 | 93.45 292 | 98.90 187 | 99.44 197 | 91.35 263 | 99.59 184 | 97.31 200 | 98.07 179 | 99.29 149 |
|
JIA-IIPM | | | 97.50 228 | 97.02 236 | 98.93 151 | 98.73 264 | 97.80 206 | 99.30 186 | 98.97 268 | 91.73 302 | 98.91 185 | 94.86 318 | 95.10 157 | 99.71 157 | 97.58 178 | 97.98 182 | 99.28 150 |
|
LP | | | 97.04 243 | 96.80 239 | 97.77 266 | 98.90 238 | 95.23 277 | 98.97 268 | 99.06 260 | 94.02 282 | 98.09 250 | 99.41 203 | 93.88 218 | 98.82 280 | 90.46 300 | 98.42 168 | 99.26 151 |
|
dp | | | 97.75 204 | 97.80 169 | 97.59 271 | 99.10 195 | 93.71 296 | 99.32 181 | 98.88 281 | 96.48 217 | 99.08 158 | 99.55 163 | 92.67 244 | 99.82 120 | 96.52 241 | 98.58 158 | 99.24 152 |
|
TESTMET0.1,1 | | | 97.55 221 | 97.27 229 | 98.40 217 | 98.93 233 | 96.53 250 | 98.67 293 | 97.61 320 | 96.96 185 | 98.64 224 | 99.28 240 | 88.63 291 | 99.45 193 | 97.30 201 | 99.38 108 | 99.21 153 |
|
DWT-MVSNet_test | | | 97.53 223 | 97.40 214 | 97.93 254 | 99.03 207 | 94.86 283 | 99.57 88 | 98.63 298 | 96.59 208 | 98.36 240 | 98.79 277 | 89.32 281 | 99.74 139 | 98.14 131 | 98.16 176 | 99.20 154 |
|
CR-MVSNet | | | 98.17 148 | 97.93 159 | 98.87 171 | 99.18 177 | 98.49 182 | 99.22 213 | 99.33 209 | 96.96 185 | 99.56 63 | 99.38 212 | 94.33 201 | 99.00 268 | 94.83 272 | 98.58 158 | 99.14 155 |
|
RPMNet | | | 96.61 247 | 95.85 255 | 98.87 171 | 99.18 177 | 98.49 182 | 99.22 213 | 99.08 255 | 88.72 313 | 99.56 63 | 97.38 309 | 94.08 213 | 99.00 268 | 86.87 313 | 98.58 158 | 99.14 155 |
|
testgi | | | 97.65 219 | 97.50 199 | 98.13 243 | 99.36 142 | 96.45 253 | 99.42 151 | 99.48 111 | 97.76 118 | 97.87 259 | 99.45 196 | 91.09 265 | 98.81 281 | 94.53 276 | 98.52 163 | 99.13 157 |
|
test-LLR | | | 98.06 159 | 97.90 160 | 98.55 202 | 98.79 254 | 97.10 222 | 98.67 293 | 97.75 316 | 97.34 153 | 98.61 228 | 98.85 272 | 94.45 197 | 99.45 193 | 97.25 202 | 99.38 108 | 99.10 158 |
|
test-mter | | | 97.49 230 | 97.13 233 | 98.55 202 | 98.79 254 | 97.10 222 | 98.67 293 | 97.75 316 | 96.65 201 | 98.61 228 | 98.85 272 | 88.23 296 | 99.45 193 | 97.25 202 | 99.38 108 | 99.10 158 |
|
IB-MVS | | 95.67 18 | 96.22 262 | 95.44 270 | 98.57 198 | 99.21 171 | 96.70 245 | 98.65 296 | 97.74 318 | 96.71 197 | 97.27 268 | 98.54 286 | 86.03 305 | 99.92 63 | 98.47 110 | 86.30 316 | 99.10 158 |
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 |
MAR-MVS | | | 98.86 98 | 98.63 110 | 99.54 74 | 99.37 140 | 99.66 34 | 99.45 135 | 99.54 61 | 96.61 204 | 99.01 168 | 99.40 207 | 97.09 100 | 99.86 100 | 97.68 174 | 99.53 103 | 99.10 158 |
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 |
tpmrst | | | 98.33 138 | 98.48 125 | 97.90 257 | 99.16 184 | 94.78 284 | 99.31 184 | 99.11 251 | 97.27 159 | 99.45 80 | 99.59 151 | 95.33 146 | 99.84 108 | 98.48 108 | 98.61 155 | 99.09 162 |
|
xiu_mvs_v1_base_debu | | | 99.29 46 | 99.27 40 | 99.34 104 | 99.63 87 | 98.97 115 | 99.12 228 | 99.51 84 | 98.86 32 | 99.84 8 | 99.47 189 | 98.18 74 | 99.99 1 | 99.50 7 | 99.31 113 | 99.08 163 |
|
xiu_mvs_v1_base | | | 99.29 46 | 99.27 40 | 99.34 104 | 99.63 87 | 98.97 115 | 99.12 228 | 99.51 84 | 98.86 32 | 99.84 8 | 99.47 189 | 98.18 74 | 99.99 1 | 99.50 7 | 99.31 113 | 99.08 163 |
|
xiu_mvs_v1_base_debi | | | 99.29 46 | 99.27 40 | 99.34 104 | 99.63 87 | 98.97 115 | 99.12 228 | 99.51 84 | 98.86 32 | 99.84 8 | 99.47 189 | 98.18 74 | 99.99 1 | 99.50 7 | 99.31 113 | 99.08 163 |
|
COLMAP_ROB | | 97.56 6 | 98.86 98 | 98.75 98 | 99.17 126 | 99.88 11 | 98.53 176 | 99.34 179 | 99.59 37 | 97.55 136 | 98.70 213 | 99.89 10 | 95.83 135 | 99.90 84 | 98.10 133 | 99.90 22 | 99.08 163 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
tpmp4_e23 | | | 97.34 235 | 97.29 227 | 97.52 272 | 99.25 167 | 93.73 294 | 99.58 82 | 99.19 245 | 94.00 283 | 98.20 246 | 99.41 203 | 90.74 269 | 99.74 139 | 97.13 210 | 98.07 179 | 99.07 167 |
|
PatchFormer-LS_test | | | 98.01 173 | 98.05 150 | 97.87 258 | 99.15 187 | 94.76 285 | 99.42 151 | 98.93 272 | 97.12 173 | 98.84 196 | 98.59 284 | 93.74 225 | 99.80 127 | 98.55 103 | 98.17 175 | 99.06 168 |
|
OpenMVS | | 96.50 16 | 98.47 129 | 98.12 143 | 99.52 82 | 99.04 205 | 99.53 55 | 99.82 13 | 99.72 11 | 94.56 272 | 98.08 251 | 99.88 14 | 94.73 185 | 99.98 5 | 97.47 191 | 99.76 76 | 99.06 168 |
|
PatchT | | | 97.03 244 | 96.44 245 | 98.79 185 | 98.99 212 | 98.34 190 | 99.16 221 | 99.07 258 | 92.13 298 | 99.52 69 | 97.31 311 | 94.54 194 | 98.98 270 | 88.54 306 | 98.73 154 | 99.03 170 |
|
BH-w/o | | | 98.00 174 | 97.89 164 | 98.32 222 | 99.35 143 | 96.20 261 | 99.01 258 | 98.90 279 | 96.42 221 | 98.38 238 | 99.00 264 | 95.26 150 | 99.72 151 | 96.06 249 | 98.61 155 | 99.03 170 |
|
Fast-Effi-MVS+-dtu | | | 98.77 114 | 98.83 91 | 98.60 195 | 99.41 131 | 96.99 233 | 99.52 107 | 99.49 102 | 98.11 86 | 99.24 128 | 99.34 229 | 96.96 104 | 99.79 130 | 97.95 147 | 99.45 104 | 99.02 172 |
|
XVG-OURS-SEG-HR | | | 98.69 120 | 98.62 113 | 98.89 164 | 99.71 63 | 97.74 208 | 99.12 228 | 99.54 61 | 98.44 62 | 99.42 86 | 99.71 102 | 94.20 206 | 99.92 63 | 98.54 105 | 98.90 144 | 99.00 173 |
|
XVG-OURS | | | 98.73 117 | 98.68 104 | 98.88 167 | 99.70 68 | 97.73 209 | 98.92 277 | 99.55 53 | 98.52 55 | 99.45 80 | 99.84 35 | 95.27 149 | 99.91 72 | 98.08 138 | 98.84 148 | 99.00 173 |
|
tpm cat1 | | | 97.39 234 | 97.36 216 | 97.50 274 | 99.17 182 | 93.73 294 | 99.43 144 | 99.31 216 | 91.27 303 | 98.71 207 | 99.08 257 | 94.31 203 | 99.77 134 | 96.41 245 | 98.50 164 | 99.00 173 |
|
xiu_mvs_v2_base | | | 99.26 51 | 99.25 44 | 99.29 116 | 99.53 107 | 98.91 128 | 99.02 254 | 99.45 145 | 98.80 39 | 99.71 29 | 99.26 243 | 98.94 24 | 99.98 5 | 99.34 21 | 99.23 117 | 98.98 176 |
|
PS-MVSNAJ | | | 99.32 42 | 99.32 26 | 99.30 112 | 99.57 102 | 98.94 123 | 98.97 268 | 99.46 134 | 98.92 29 | 99.71 29 | 99.24 245 | 99.01 11 | 99.98 5 | 99.35 17 | 99.66 95 | 98.97 177 |
|
tpmvs | | | 97.98 175 | 98.02 152 | 97.84 261 | 99.04 205 | 94.73 286 | 99.31 184 | 99.20 242 | 96.10 249 | 98.76 203 | 99.42 200 | 94.94 165 | 99.81 124 | 96.97 220 | 98.45 166 | 98.97 177 |
|
mvs-test1 | | | 98.86 98 | 98.84 88 | 98.89 164 | 99.33 147 | 97.77 207 | 99.44 139 | 99.30 218 | 98.47 57 | 99.10 154 | 99.43 198 | 96.78 108 | 99.95 33 | 98.73 78 | 99.02 132 | 98.96 179 |
|
TR-MVS | | | 97.76 201 | 97.41 213 | 98.82 181 | 99.06 201 | 97.87 204 | 98.87 282 | 98.56 302 | 96.63 203 | 98.68 215 | 99.22 247 | 92.49 249 | 99.65 172 | 95.40 263 | 97.79 186 | 98.95 180 |
|
test0.0.03 1 | | | 97.71 211 | 97.42 212 | 98.56 200 | 98.41 286 | 97.82 205 | 98.78 286 | 98.63 298 | 97.34 153 | 98.05 255 | 98.98 268 | 94.45 197 | 98.98 270 | 95.04 269 | 97.15 220 | 98.89 181 |
|
cascas | | | 97.69 212 | 97.43 211 | 98.48 207 | 98.60 278 | 97.30 213 | 98.18 313 | 99.39 175 | 92.96 294 | 98.41 236 | 98.78 279 | 93.77 222 | 99.27 232 | 98.16 130 | 98.61 155 | 98.86 182 |
|
1314 | | | 98.68 121 | 98.54 123 | 99.11 131 | 98.89 241 | 98.65 165 | 99.27 197 | 99.49 102 | 96.89 189 | 97.99 256 | 99.56 160 | 97.72 87 | 99.83 115 | 97.74 165 | 99.27 116 | 98.84 183 |
|
PS-MVSNAJss | | | 98.92 93 | 98.92 77 | 98.90 162 | 98.78 258 | 98.53 176 | 99.78 22 | 99.54 61 | 98.07 93 | 99.00 175 | 99.76 85 | 99.01 11 | 99.37 206 | 99.13 38 | 97.23 216 | 98.81 184 |
|
pcd1.5k->3k | | | 40.85 307 | 43.49 309 | 32.93 321 | 98.95 224 | 0.00 338 | 0.00 329 | 99.53 71 | 0.00 333 | 0.00 334 | 0.27 335 | 95.32 147 | 0.00 336 | 0.00 333 | 97.30 214 | 98.80 185 |
|
FC-MVSNet-test | | | 98.75 116 | 98.62 113 | 99.15 129 | 99.08 198 | 99.45 66 | 99.86 8 | 99.60 34 | 98.23 75 | 98.70 213 | 99.82 44 | 96.80 107 | 99.22 244 | 99.07 43 | 96.38 231 | 98.79 186 |
|
nrg030 | | | 98.64 125 | 98.42 127 | 99.28 118 | 99.05 204 | 99.69 29 | 99.81 15 | 99.46 134 | 98.04 99 | 99.01 168 | 99.82 44 | 96.69 113 | 99.38 203 | 99.34 21 | 94.59 268 | 98.78 187 |
|
FIs | | | 98.78 112 | 98.63 110 | 99.23 123 | 99.18 177 | 99.54 52 | 99.83 12 | 99.59 37 | 98.28 70 | 98.79 200 | 99.81 53 | 96.75 111 | 99.37 206 | 99.08 42 | 96.38 231 | 98.78 187 |
|
EU-MVSNet | | | 97.98 175 | 98.03 151 | 97.81 264 | 98.72 266 | 96.65 248 | 99.66 54 | 99.66 25 | 98.09 89 | 98.35 241 | 99.82 44 | 95.25 151 | 98.01 299 | 97.41 196 | 95.30 248 | 98.78 187 |
|
jajsoiax | | | 98.43 132 | 98.28 136 | 98.88 167 | 98.60 278 | 98.43 187 | 99.82 13 | 99.53 71 | 98.19 76 | 98.63 225 | 99.80 64 | 93.22 229 | 99.44 198 | 99.22 30 | 97.50 201 | 98.77 190 |
|
mvs_tets | | | 98.40 135 | 98.23 138 | 98.91 158 | 98.67 273 | 98.51 181 | 99.66 54 | 99.53 71 | 98.19 76 | 98.65 223 | 99.81 53 | 92.75 237 | 99.44 198 | 99.31 24 | 97.48 205 | 98.77 190 |
|
XXY-MVS | | | 98.38 136 | 98.09 146 | 99.24 121 | 99.26 165 | 99.32 76 | 99.56 95 | 99.55 53 | 97.45 145 | 98.71 207 | 99.83 37 | 93.23 228 | 99.63 179 | 98.88 56 | 96.32 233 | 98.76 192 |
|
v7n | | | 97.87 187 | 97.52 196 | 98.92 156 | 98.76 262 | 98.58 173 | 99.84 9 | 99.46 134 | 96.20 237 | 98.91 185 | 99.70 106 | 94.89 171 | 99.44 198 | 96.03 250 | 93.89 281 | 98.75 193 |
|
PS-CasMVS | | | 97.93 180 | 97.59 193 | 98.95 147 | 98.99 212 | 99.06 102 | 99.68 49 | 99.52 75 | 97.13 171 | 98.31 243 | 99.68 116 | 92.44 254 | 99.05 262 | 98.51 106 | 94.08 277 | 98.75 193 |
|
test_djsdf | | | 98.67 122 | 98.57 121 | 98.98 143 | 98.70 269 | 98.91 128 | 99.88 1 | 99.46 134 | 97.55 136 | 99.22 135 | 99.88 14 | 95.73 139 | 99.28 229 | 99.03 45 | 97.62 191 | 98.75 193 |
|
Effi-MVS+-dtu | | | 98.78 112 | 98.89 82 | 98.47 209 | 99.33 147 | 96.91 239 | 99.57 88 | 99.30 218 | 98.47 57 | 99.41 88 | 98.99 265 | 96.78 108 | 99.74 139 | 98.73 78 | 99.38 108 | 98.74 196 |
|
CP-MVSNet | | | 98.09 157 | 97.78 172 | 99.01 139 | 98.97 219 | 99.24 86 | 99.67 51 | 99.46 134 | 97.25 161 | 98.48 234 | 99.64 134 | 93.79 221 | 99.06 261 | 98.63 89 | 94.10 276 | 98.74 196 |
|
VPA-MVSNet | | | 98.29 140 | 97.95 157 | 99.30 112 | 99.16 184 | 99.54 52 | 99.50 116 | 99.58 42 | 98.27 71 | 99.35 104 | 99.37 215 | 92.53 248 | 99.65 172 | 99.35 17 | 94.46 269 | 98.72 198 |
|
PEN-MVS | | | 97.76 201 | 97.44 208 | 98.72 190 | 98.77 261 | 98.54 175 | 99.78 22 | 99.51 84 | 97.06 180 | 98.29 245 | 99.64 134 | 92.63 245 | 98.89 279 | 98.09 134 | 93.16 287 | 98.72 198 |
|
VPNet | | | 97.84 190 | 97.44 208 | 99.01 139 | 99.21 171 | 98.94 123 | 99.48 127 | 99.57 43 | 98.38 64 | 99.28 119 | 99.73 97 | 88.89 285 | 99.39 202 | 99.19 32 | 93.27 286 | 98.71 200 |
|
EI-MVSNet | | | 98.67 122 | 98.67 105 | 98.68 191 | 99.35 143 | 97.97 202 | 99.50 116 | 99.38 181 | 96.93 188 | 99.20 140 | 99.83 37 | 97.87 81 | 99.36 210 | 98.38 116 | 97.56 196 | 98.71 200 |
|
WR-MVS | | | 98.06 159 | 97.73 183 | 99.06 134 | 98.86 248 | 99.25 85 | 99.19 218 | 99.35 193 | 97.30 157 | 98.66 217 | 99.43 198 | 93.94 216 | 99.21 248 | 98.58 96 | 94.28 272 | 98.71 200 |
|
IterMVS-LS | | | 98.46 130 | 98.42 127 | 98.58 197 | 99.59 99 | 98.00 200 | 99.37 169 | 99.43 161 | 96.94 187 | 99.07 159 | 99.59 151 | 97.87 81 | 99.03 265 | 98.32 123 | 95.62 244 | 98.71 200 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
v144192 | | | 97.92 183 | 97.60 192 | 98.87 171 | 98.83 251 | 98.65 165 | 99.55 100 | 99.34 201 | 96.20 237 | 99.32 109 | 99.40 207 | 94.36 200 | 99.26 237 | 96.37 246 | 95.03 255 | 98.70 204 |
|
v748 | | | 97.52 224 | 97.23 230 | 98.41 216 | 98.69 270 | 97.23 219 | 99.87 4 | 99.45 145 | 95.72 254 | 98.51 231 | 99.53 167 | 94.13 210 | 99.30 226 | 96.78 230 | 92.39 295 | 98.70 204 |
|
v1240 | | | 97.69 212 | 97.32 224 | 98.79 185 | 98.85 249 | 98.43 187 | 99.48 127 | 99.36 189 | 96.11 246 | 99.27 123 | 99.36 222 | 93.76 223 | 99.24 240 | 94.46 278 | 95.23 249 | 98.70 204 |
|
DTE-MVSNet | | | 97.51 227 | 97.19 232 | 98.46 210 | 98.63 276 | 98.13 198 | 99.84 9 | 99.48 111 | 96.68 199 | 97.97 257 | 99.67 121 | 92.92 233 | 98.56 285 | 96.88 227 | 92.60 294 | 98.70 204 |
|
TranMVSNet+NR-MVSNet | | | 97.93 180 | 97.66 187 | 98.76 188 | 98.78 258 | 98.62 169 | 99.65 64 | 99.49 102 | 97.76 118 | 98.49 233 | 99.60 149 | 94.23 205 | 98.97 277 | 98.00 143 | 92.90 289 | 98.70 204 |
|
v1921920 | | | 97.80 197 | 97.45 205 | 98.84 179 | 98.80 252 | 98.53 176 | 99.52 107 | 99.34 201 | 96.15 243 | 99.24 128 | 99.47 189 | 93.98 215 | 99.29 228 | 95.40 263 | 95.13 253 | 98.69 209 |
|
v1192 | | | 97.81 195 | 97.44 208 | 98.91 158 | 98.88 242 | 98.68 161 | 99.51 111 | 99.34 201 | 96.18 239 | 99.20 140 | 99.34 229 | 94.03 214 | 99.36 210 | 95.32 265 | 95.18 250 | 98.69 209 |
|
v2v482 | | | 98.06 159 | 97.77 176 | 98.92 156 | 98.90 238 | 98.82 145 | 99.57 88 | 99.36 189 | 96.65 201 | 99.19 143 | 99.35 226 | 94.20 206 | 99.25 238 | 97.72 170 | 94.97 256 | 98.69 209 |
|
UniMVSNet_NR-MVSNet | | | 98.22 143 | 97.97 155 | 98.96 145 | 98.92 235 | 98.98 112 | 99.48 127 | 99.53 71 | 97.76 118 | 98.71 207 | 99.46 193 | 96.43 118 | 99.22 244 | 98.57 98 | 92.87 291 | 98.69 209 |
|
OurMVSNet-221017-0 | | | 97.88 186 | 97.77 176 | 98.19 240 | 98.71 268 | 96.53 250 | 99.88 1 | 99.00 265 | 97.79 115 | 98.78 201 | 99.94 3 | 91.68 260 | 99.35 213 | 97.21 204 | 96.99 222 | 98.69 209 |
|
gg-mvs-nofinetune | | | 96.17 264 | 95.32 271 | 98.73 189 | 98.79 254 | 98.14 197 | 99.38 167 | 94.09 328 | 91.07 306 | 98.07 254 | 91.04 324 | 89.62 280 | 99.35 213 | 96.75 231 | 99.09 127 | 98.68 214 |
|
v1144 | | | 97.98 175 | 97.69 186 | 98.85 178 | 98.87 245 | 98.66 164 | 99.54 103 | 99.35 193 | 96.27 231 | 99.23 133 | 99.35 226 | 94.67 188 | 99.23 241 | 96.73 232 | 95.16 251 | 98.68 214 |
|
v1141 | | | 98.05 165 | 97.76 179 | 98.91 158 | 98.91 237 | 98.78 156 | 99.57 88 | 99.35 193 | 96.41 223 | 99.23 133 | 99.36 222 | 94.93 167 | 99.27 232 | 97.38 197 | 94.72 262 | 98.68 214 |
|
testing_2 | | | 94.44 281 | 92.93 287 | 98.98 143 | 94.16 314 | 99.00 110 | 99.42 151 | 99.28 228 | 96.60 206 | 84.86 317 | 96.84 312 | 70.91 320 | 99.27 232 | 98.23 126 | 96.08 237 | 98.68 214 |
|
divwei89l23v2f112 | | | 98.06 159 | 97.78 172 | 98.91 158 | 98.90 238 | 98.77 157 | 99.57 88 | 99.35 193 | 96.45 218 | 99.24 128 | 99.37 215 | 94.92 168 | 99.27 232 | 97.50 187 | 94.71 264 | 98.68 214 |
|
v1 | | | 98.05 165 | 97.76 179 | 98.93 151 | 98.92 235 | 98.80 152 | 99.57 88 | 99.35 193 | 96.39 225 | 99.28 119 | 99.36 222 | 94.86 173 | 99.32 220 | 97.38 197 | 94.72 262 | 98.68 214 |
|
DU-MVS | | | 98.08 158 | 97.79 170 | 98.96 145 | 98.87 245 | 98.98 112 | 99.41 155 | 99.45 145 | 97.87 106 | 98.71 207 | 99.50 176 | 94.82 175 | 99.22 244 | 98.57 98 | 92.87 291 | 98.68 214 |
|
NR-MVSNet | | | 97.97 178 | 97.61 191 | 99.02 138 | 98.87 245 | 99.26 84 | 99.47 131 | 99.42 162 | 97.63 130 | 97.08 272 | 99.50 176 | 95.07 158 | 99.13 254 | 97.86 153 | 93.59 283 | 98.68 214 |
|
LPG-MVS_test | | | 98.22 143 | 98.13 142 | 98.49 205 | 99.33 147 | 97.05 228 | 99.58 82 | 99.55 53 | 97.46 142 | 99.24 128 | 99.83 37 | 92.58 246 | 99.72 151 | 98.09 134 | 97.51 199 | 98.68 214 |
|
LGP-MVS_train | | | | | 98.49 205 | 99.33 147 | 97.05 228 | | 99.55 53 | 97.46 142 | 99.24 128 | 99.83 37 | 92.58 246 | 99.72 151 | 98.09 134 | 97.51 199 | 98.68 214 |
|
LTVRE_ROB | | 97.16 12 | 98.02 170 | 97.90 160 | 98.40 217 | 99.23 168 | 96.80 243 | 99.70 42 | 99.60 34 | 97.12 173 | 98.18 247 | 99.70 106 | 91.73 259 | 99.72 151 | 98.39 114 | 97.45 206 | 98.68 214 |
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 |
semantic-postprocess | | | | | 98.06 245 | 99.57 102 | 96.36 256 | | 99.49 102 | 97.18 167 | 98.71 207 | 99.72 101 | 92.70 243 | 99.14 251 | 97.44 194 | 95.86 240 | 98.67 225 |
|
v1neww | | | 98.12 153 | 97.84 166 | 98.93 151 | 98.97 219 | 98.81 147 | 99.66 54 | 99.35 193 | 96.49 211 | 99.29 115 | 99.37 215 | 95.02 160 | 99.32 220 | 97.73 166 | 94.73 260 | 98.67 225 |
|
v7new | | | 98.12 153 | 97.84 166 | 98.93 151 | 98.97 219 | 98.81 147 | 99.66 54 | 99.35 193 | 96.49 211 | 99.29 115 | 99.37 215 | 95.02 160 | 99.32 220 | 97.73 166 | 94.73 260 | 98.67 225 |
|
pm-mvs1 | | | 97.68 214 | 97.28 228 | 98.88 167 | 99.06 201 | 98.62 169 | 99.50 116 | 99.45 145 | 96.32 227 | 97.87 259 | 99.79 72 | 92.47 250 | 99.35 213 | 97.54 183 | 93.54 284 | 98.67 225 |
|
v6 | | | 98.12 153 | 97.84 166 | 98.94 148 | 98.94 228 | 98.83 138 | 99.66 54 | 99.34 201 | 96.49 211 | 99.30 111 | 99.37 215 | 94.95 164 | 99.34 216 | 97.77 161 | 94.74 259 | 98.67 225 |
|
v10 | | | 97.85 188 | 97.52 196 | 98.86 175 | 98.99 212 | 98.67 162 | 99.75 34 | 99.41 165 | 95.70 255 | 98.98 177 | 99.41 203 | 94.75 184 | 99.23 241 | 96.01 251 | 94.63 267 | 98.67 225 |
|
HQP_MVS | | | 98.27 142 | 98.22 139 | 98.44 214 | 99.29 158 | 96.97 235 | 99.39 162 | 99.47 125 | 98.97 23 | 99.11 151 | 99.61 146 | 92.71 241 | 99.69 166 | 97.78 159 | 97.63 189 | 98.67 225 |
|
plane_prior5 | | | | | | | | | 99.47 125 | | | | | 99.69 166 | 97.78 159 | 97.63 189 | 98.67 225 |
|
SixPastTwentyTwo | | | 97.50 228 | 97.33 223 | 98.03 246 | 98.65 274 | 96.23 260 | 99.77 24 | 98.68 296 | 97.14 170 | 97.90 258 | 99.93 4 | 90.45 270 | 99.18 250 | 97.00 217 | 96.43 230 | 98.67 225 |
|
IterMVS | | | 97.83 191 | 97.77 176 | 98.02 248 | 99.58 100 | 96.27 259 | 99.02 254 | 99.48 111 | 97.22 165 | 98.71 207 | 99.70 106 | 92.75 237 | 99.13 254 | 97.46 192 | 96.00 238 | 98.67 225 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
ACMH | | 97.28 8 | 98.10 156 | 97.99 154 | 98.44 214 | 99.41 131 | 96.96 237 | 99.60 77 | 99.56 46 | 98.09 89 | 98.15 248 | 99.91 5 | 90.87 268 | 99.70 163 | 98.88 56 | 97.45 206 | 98.67 225 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
v8 | | | 97.95 179 | 97.63 190 | 98.93 151 | 98.95 224 | 98.81 147 | 99.80 19 | 99.41 165 | 96.03 250 | 99.10 154 | 99.42 200 | 94.92 168 | 99.30 226 | 96.94 223 | 94.08 277 | 98.66 236 |
|
v7 | | | 98.05 165 | 97.78 172 | 98.87 171 | 98.99 212 | 98.67 162 | 99.64 66 | 99.34 201 | 96.31 228 | 99.29 115 | 99.51 174 | 94.78 178 | 99.27 232 | 97.03 215 | 95.15 252 | 98.66 236 |
|
UniMVSNet (Re) | | | 98.29 140 | 98.00 153 | 99.13 130 | 99.00 210 | 99.36 74 | 99.49 122 | 99.51 84 | 97.95 104 | 98.97 178 | 99.13 253 | 96.30 122 | 99.38 203 | 98.36 119 | 93.34 285 | 98.66 236 |
|
pmmvs6 | | | 96.53 249 | 96.09 250 | 97.82 263 | 98.69 270 | 95.47 273 | 99.37 169 | 99.47 125 | 93.46 291 | 97.41 266 | 99.78 77 | 87.06 303 | 99.33 217 | 96.92 225 | 92.70 293 | 98.65 239 |
|
K. test v3 | | | 97.10 242 | 96.79 240 | 98.01 249 | 98.72 266 | 96.33 257 | 99.87 4 | 97.05 322 | 97.59 131 | 96.16 282 | 99.80 64 | 88.71 287 | 99.04 263 | 96.69 235 | 96.55 228 | 98.65 239 |
|
YYNet1 | | | 95.36 274 | 94.51 279 | 97.92 255 | 97.89 292 | 97.10 222 | 99.10 236 | 99.23 239 | 93.26 293 | 80.77 321 | 99.04 262 | 92.81 236 | 98.02 298 | 94.30 282 | 94.18 275 | 98.64 241 |
|
MDA-MVSNet_test_wron | | | 95.45 272 | 94.60 277 | 98.01 249 | 98.16 290 | 97.21 220 | 99.11 234 | 99.24 238 | 93.49 290 | 80.73 322 | 98.98 268 | 93.02 230 | 98.18 287 | 94.22 286 | 94.45 270 | 98.64 241 |
|
Baseline_NR-MVSNet | | | 97.76 201 | 97.45 205 | 98.68 191 | 99.09 197 | 98.29 191 | 99.41 155 | 98.85 283 | 95.65 256 | 98.63 225 | 99.67 121 | 94.82 175 | 99.10 259 | 98.07 140 | 92.89 290 | 98.64 241 |
|
HQP4-MVS | | | | | | | | | | | 98.66 217 | | | 99.64 174 | | | 98.64 241 |
|
HQP-MVS | | | 98.02 170 | 97.90 160 | 98.37 219 | 99.19 174 | 96.83 240 | 98.98 265 | 99.39 175 | 98.24 72 | 98.66 217 | 99.40 207 | 92.47 250 | 99.64 174 | 97.19 206 | 97.58 194 | 98.64 241 |
|
ACMM | | 97.58 5 | 98.37 137 | 98.34 131 | 98.48 207 | 99.41 131 | 97.10 222 | 99.56 95 | 99.45 145 | 98.53 54 | 99.04 165 | 99.85 26 | 93.00 231 | 99.71 157 | 98.74 75 | 97.45 206 | 98.64 241 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
pmmvs5 | | | 97.52 224 | 97.30 226 | 98.16 242 | 98.57 280 | 96.73 244 | 99.27 197 | 98.90 279 | 96.14 244 | 98.37 239 | 99.53 167 | 91.54 262 | 99.14 251 | 97.51 186 | 95.87 239 | 98.63 247 |
|
v148 | | | 97.79 199 | 97.55 194 | 98.50 204 | 98.74 263 | 97.72 210 | 99.54 103 | 99.33 209 | 96.26 232 | 98.90 187 | 99.51 174 | 94.68 187 | 99.14 251 | 97.83 155 | 93.15 288 | 98.63 247 |
|
MDA-MVSNet-bldmvs | | | 94.96 277 | 93.98 282 | 97.92 255 | 98.24 289 | 97.27 215 | 99.15 224 | 99.33 209 | 93.80 286 | 80.09 323 | 99.03 263 | 88.31 295 | 97.86 303 | 93.49 290 | 94.36 271 | 98.62 249 |
|
TransMVSNet (Re) | | | 97.15 240 | 96.58 243 | 98.86 175 | 99.12 190 | 98.85 134 | 99.49 122 | 98.91 277 | 95.48 258 | 97.16 271 | 99.80 64 | 93.38 227 | 99.11 257 | 94.16 287 | 91.73 296 | 98.62 249 |
|
lessismore_v0 | | | | | 97.79 265 | 98.69 270 | 95.44 275 | | 94.75 326 | | 95.71 286 | 99.87 19 | 88.69 288 | 99.32 220 | 95.89 252 | 94.93 258 | 98.62 249 |
|
MVSTER | | | 98.49 128 | 98.32 133 | 99.00 141 | 99.35 143 | 99.02 106 | 99.54 103 | 99.38 181 | 97.41 149 | 99.20 140 | 99.73 97 | 93.86 220 | 99.36 210 | 98.87 60 | 97.56 196 | 98.62 249 |
|
GBi-Net | | | 97.68 214 | 97.48 201 | 98.29 225 | 99.51 110 | 97.26 216 | 99.43 144 | 99.48 111 | 96.49 211 | 99.07 159 | 99.32 234 | 90.26 272 | 98.98 270 | 97.10 211 | 96.65 224 | 98.62 249 |
|
test1 | | | 97.68 214 | 97.48 201 | 98.29 225 | 99.51 110 | 97.26 216 | 99.43 144 | 99.48 111 | 96.49 211 | 99.07 159 | 99.32 234 | 90.26 272 | 98.98 270 | 97.10 211 | 96.65 224 | 98.62 249 |
|
FMVSNet1 | | | 96.84 245 | 96.36 246 | 98.29 225 | 99.32 153 | 97.26 216 | 99.43 144 | 99.48 111 | 95.11 261 | 98.55 230 | 99.32 234 | 83.95 314 | 98.98 270 | 95.81 254 | 96.26 234 | 98.62 249 |
|
ACMP | | 97.20 11 | 98.06 159 | 97.94 158 | 98.45 211 | 99.37 140 | 97.01 231 | 99.44 139 | 99.49 102 | 97.54 139 | 98.45 235 | 99.79 72 | 91.95 257 | 99.72 151 | 97.91 149 | 97.49 204 | 98.62 249 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
ACMH+ | | 97.24 10 | 97.92 183 | 97.78 172 | 98.32 222 | 99.46 121 | 96.68 247 | 99.56 95 | 99.54 61 | 98.41 63 | 97.79 263 | 99.87 19 | 90.18 275 | 99.66 170 | 98.05 142 | 97.18 219 | 98.62 249 |
|
OPM-MVS | | | 98.19 147 | 98.10 144 | 98.45 211 | 98.88 242 | 97.07 226 | 99.28 194 | 99.38 181 | 98.57 52 | 99.22 135 | 99.81 53 | 92.12 256 | 99.66 170 | 98.08 138 | 97.54 198 | 98.61 258 |
|
WR-MVS_H | | | 98.13 151 | 97.87 165 | 98.90 162 | 99.02 208 | 98.84 135 | 99.70 42 | 99.59 37 | 97.27 159 | 98.40 237 | 99.19 249 | 95.53 142 | 99.23 241 | 98.34 120 | 93.78 282 | 98.61 258 |
|
MIMVSNet1 | | | 95.51 271 | 95.04 274 | 96.92 283 | 97.38 299 | 95.60 267 | 99.52 107 | 99.50 97 | 93.65 287 | 96.97 276 | 99.17 250 | 85.28 309 | 96.56 314 | 88.36 307 | 95.55 246 | 98.60 260 |
|
test2356 | | | 94.07 285 | 94.46 280 | 92.89 299 | 95.18 310 | 86.13 314 | 97.60 319 | 99.06 260 | 93.61 288 | 96.15 284 | 98.28 288 | 85.60 308 | 93.95 321 | 86.68 314 | 98.00 181 | 98.59 261 |
|
test1235678 | | | 92.91 288 | 93.30 285 | 91.71 305 | 93.14 317 | 83.01 318 | 98.75 289 | 98.58 301 | 92.80 296 | 92.45 307 | 97.91 292 | 88.51 293 | 93.54 322 | 82.26 318 | 95.35 247 | 98.59 261 |
|
N_pmnet | | | 94.95 278 | 95.83 256 | 92.31 302 | 98.47 284 | 79.33 324 | 99.12 228 | 92.81 333 | 93.87 285 | 97.68 264 | 99.13 253 | 93.87 219 | 99.01 267 | 91.38 298 | 96.19 235 | 98.59 261 |
|
FMVSNet2 | | | 97.72 209 | 97.36 216 | 98.80 184 | 99.51 110 | 98.84 135 | 99.45 135 | 99.42 162 | 96.49 211 | 98.86 195 | 99.29 239 | 90.26 272 | 98.98 270 | 96.44 243 | 96.56 227 | 98.58 264 |
|
anonymousdsp | | | 98.44 131 | 98.28 136 | 98.94 148 | 98.50 283 | 98.96 119 | 99.77 24 | 99.50 97 | 97.07 178 | 98.87 190 | 99.77 82 | 94.76 183 | 99.28 229 | 98.66 86 | 97.60 192 | 98.57 265 |
|
FMVSNet3 | | | 98.03 168 | 97.76 179 | 98.84 179 | 99.39 137 | 98.98 112 | 99.40 161 | 99.38 181 | 96.67 200 | 99.07 159 | 99.28 240 | 92.93 232 | 98.98 270 | 97.10 211 | 96.65 224 | 98.56 266 |
|
XVG-ACMP-BASELINE | | | 97.83 191 | 97.71 185 | 98.20 239 | 99.11 192 | 96.33 257 | 99.41 155 | 99.52 75 | 98.06 97 | 99.05 164 | 99.50 176 | 89.64 279 | 99.73 147 | 97.73 166 | 97.38 212 | 98.53 267 |
|
Patchmtry | | | 97.75 204 | 97.40 214 | 98.81 182 | 99.10 195 | 98.87 131 | 99.11 234 | 99.33 209 | 94.83 264 | 98.81 198 | 99.38 212 | 94.33 201 | 99.02 266 | 96.10 248 | 95.57 245 | 98.53 267 |
|
USDC | | | 97.34 235 | 97.20 231 | 97.75 267 | 99.07 199 | 95.20 278 | 98.51 302 | 99.04 262 | 97.99 103 | 98.31 243 | 99.86 22 | 89.02 283 | 99.55 187 | 95.67 258 | 97.36 213 | 98.49 269 |
|
CLD-MVS | | | 98.16 149 | 98.10 144 | 98.33 221 | 99.29 158 | 96.82 242 | 98.75 289 | 99.44 153 | 97.83 112 | 99.13 147 | 99.55 163 | 92.92 233 | 99.67 168 | 98.32 123 | 97.69 188 | 98.48 270 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
Anonymous20231206 | | | 96.22 262 | 96.03 251 | 96.79 286 | 97.31 302 | 94.14 291 | 99.63 67 | 99.08 255 | 96.17 240 | 97.04 273 | 99.06 260 | 93.94 216 | 97.76 306 | 86.96 312 | 95.06 254 | 98.47 271 |
|
FMVSNet5 | | | 96.43 251 | 96.19 248 | 97.15 277 | 99.11 192 | 95.89 265 | 99.32 181 | 99.52 75 | 94.47 276 | 98.34 242 | 99.07 258 | 87.54 300 | 97.07 310 | 92.61 295 | 95.72 242 | 98.47 271 |
|
pmmvs4 | | | 98.13 151 | 97.90 160 | 98.81 182 | 98.61 277 | 98.87 131 | 98.99 261 | 99.21 241 | 96.44 219 | 99.06 163 | 99.58 154 | 95.90 133 | 99.11 257 | 97.18 208 | 96.11 236 | 98.46 273 |
|
V42 | | | 98.06 159 | 97.79 170 | 98.86 175 | 98.98 216 | 98.84 135 | 99.69 44 | 99.34 201 | 96.53 210 | 99.30 111 | 99.37 215 | 94.67 188 | 99.32 220 | 97.57 180 | 94.66 265 | 98.42 274 |
|
PVSNet_BlendedMVS | | | 98.86 98 | 98.80 92 | 99.03 137 | 99.76 41 | 98.79 154 | 99.28 194 | 99.91 3 | 97.42 148 | 99.67 40 | 99.37 215 | 97.53 89 | 99.88 95 | 98.98 50 | 97.29 215 | 98.42 274 |
|
UnsupCasMVSNet_eth | | | 96.44 250 | 96.12 249 | 97.40 276 | 98.65 274 | 95.65 266 | 99.36 173 | 99.51 84 | 97.13 171 | 96.04 285 | 98.99 265 | 88.40 294 | 98.17 288 | 96.71 233 | 90.27 299 | 98.40 276 |
|
TinyColmap | | | 97.12 241 | 96.89 238 | 97.83 262 | 99.07 199 | 95.52 272 | 98.57 299 | 98.74 291 | 97.58 133 | 97.81 262 | 99.79 72 | 88.16 297 | 99.56 185 | 95.10 267 | 97.21 217 | 98.39 277 |
|
testus | | | 94.61 279 | 95.30 272 | 92.54 301 | 96.44 305 | 84.18 316 | 98.36 305 | 99.03 263 | 94.18 281 | 96.49 278 | 98.57 285 | 88.74 286 | 95.09 319 | 87.41 310 | 98.45 166 | 98.36 278 |
|
test20.03 | | | 96.12 265 | 95.96 254 | 96.63 287 | 97.44 298 | 95.45 274 | 99.51 111 | 99.38 181 | 96.55 209 | 96.16 282 | 99.25 244 | 93.76 223 | 96.17 315 | 87.35 311 | 94.22 274 | 98.27 279 |
|
ITE_SJBPF | | | | | 98.08 244 | 99.29 158 | 96.37 255 | | 98.92 274 | 98.34 66 | 98.83 197 | 99.75 90 | 91.09 265 | 99.62 180 | 95.82 253 | 97.40 210 | 98.25 280 |
|
EG-PatchMatch MVS | | | 95.97 267 | 95.69 261 | 96.81 285 | 97.78 294 | 92.79 302 | 99.16 221 | 98.93 272 | 96.16 241 | 94.08 294 | 99.22 247 | 82.72 316 | 99.47 191 | 95.67 258 | 97.50 201 | 98.17 281 |
|
TDRefinement | | | 95.42 273 | 94.57 278 | 97.97 252 | 89.83 323 | 96.11 262 | 99.48 127 | 98.75 288 | 96.74 195 | 96.68 277 | 99.88 14 | 88.65 290 | 99.71 157 | 98.37 117 | 82.74 319 | 98.09 282 |
|
API-MVS | | | 99.04 81 | 99.03 63 | 99.06 134 | 99.40 135 | 99.31 79 | 99.55 100 | 99.56 46 | 98.54 53 | 99.33 108 | 99.39 211 | 98.76 41 | 99.78 132 | 96.98 219 | 99.78 72 | 98.07 283 |
|
v52 | | | 97.79 199 | 97.50 199 | 98.66 194 | 98.80 252 | 98.62 169 | 99.87 4 | 99.44 153 | 95.87 252 | 99.01 168 | 99.46 193 | 94.44 199 | 99.33 217 | 96.65 239 | 93.96 280 | 98.05 284 |
|
V4 | | | 97.80 197 | 97.51 198 | 98.67 193 | 98.79 254 | 98.63 167 | 99.87 4 | 99.44 153 | 95.87 252 | 99.01 168 | 99.46 193 | 94.52 195 | 99.33 217 | 96.64 240 | 93.97 279 | 98.05 284 |
|
new_pmnet | | | 96.38 255 | 96.03 251 | 97.41 275 | 98.13 291 | 95.16 281 | 99.05 245 | 99.20 242 | 93.94 284 | 97.39 267 | 98.79 277 | 91.61 261 | 99.04 263 | 90.43 301 | 95.77 241 | 98.05 284 |
|
DeepMVS_CX | | | | | 93.34 297 | 99.29 158 | 82.27 321 | | 99.22 240 | 85.15 315 | 96.33 280 | 99.05 261 | 90.97 267 | 99.73 147 | 93.57 289 | 97.77 187 | 98.01 287 |
|
GG-mvs-BLEND | | | | | 98.45 211 | 98.55 281 | 98.16 196 | 99.43 144 | 93.68 329 | | 97.23 269 | 98.46 287 | 89.30 282 | 99.22 244 | 95.43 262 | 98.22 172 | 97.98 288 |
|
pmmvs3 | | | 94.09 284 | 93.25 286 | 96.60 288 | 94.76 312 | 94.49 287 | 98.92 277 | 98.18 311 | 89.66 308 | 96.48 279 | 98.06 290 | 86.28 304 | 97.33 309 | 89.68 303 | 87.20 310 | 97.97 289 |
|
LF4IMVS | | | 97.52 224 | 97.46 204 | 97.70 270 | 98.98 216 | 95.55 269 | 99.29 190 | 98.82 286 | 98.07 93 | 98.66 217 | 99.64 134 | 89.97 276 | 99.61 181 | 97.01 216 | 96.68 223 | 97.94 290 |
|
test_0402 | | | 96.64 246 | 96.24 247 | 97.85 260 | 98.85 249 | 96.43 254 | 99.44 139 | 99.26 235 | 93.52 289 | 96.98 275 | 99.52 171 | 88.52 292 | 99.20 249 | 92.58 296 | 97.50 201 | 97.93 291 |
|
MVP-Stereo | | | 97.81 195 | 97.75 182 | 97.99 251 | 97.53 297 | 96.60 249 | 98.96 270 | 98.85 283 | 97.22 165 | 97.23 269 | 99.36 222 | 95.28 148 | 99.46 192 | 95.51 260 | 99.78 72 | 97.92 292 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
MS-PatchMatch | | | 97.24 239 | 97.32 224 | 96.99 280 | 98.45 285 | 93.51 299 | 98.82 284 | 99.32 215 | 97.41 149 | 98.13 249 | 99.30 237 | 88.99 284 | 99.56 185 | 95.68 257 | 99.80 67 | 97.90 293 |
|
v13 | | | 96.24 259 | 95.58 264 | 98.25 232 | 98.98 216 | 98.83 138 | 99.75 34 | 99.29 221 | 94.35 279 | 93.89 301 | 97.60 304 | 95.17 155 | 98.11 295 | 94.27 284 | 86.86 314 | 97.81 294 |
|
V9 | | | 96.25 258 | 95.58 264 | 98.26 228 | 98.94 228 | 98.83 138 | 99.75 34 | 99.29 221 | 94.45 277 | 93.96 298 | 97.62 302 | 94.94 165 | 98.14 292 | 94.40 280 | 86.87 313 | 97.81 294 |
|
v17 | | | 96.42 252 | 95.81 257 | 98.25 232 | 98.94 228 | 98.80 152 | 99.76 27 | 99.28 228 | 94.57 270 | 94.18 291 | 97.71 295 | 95.23 152 | 98.16 289 | 94.86 270 | 87.73 308 | 97.80 296 |
|
v16 | | | 96.39 254 | 95.76 260 | 98.26 228 | 98.96 222 | 98.81 147 | 99.76 27 | 99.28 228 | 94.57 270 | 94.10 293 | 97.70 296 | 95.04 159 | 98.16 289 | 94.70 274 | 87.77 307 | 97.80 296 |
|
v15 | | | 96.28 256 | 95.62 262 | 98.25 232 | 98.94 228 | 98.83 138 | 99.76 27 | 99.29 221 | 94.52 274 | 94.02 296 | 97.61 303 | 95.02 160 | 98.13 293 | 94.53 276 | 86.92 311 | 97.80 296 |
|
v12 | | | 96.24 259 | 95.58 264 | 98.23 235 | 98.96 222 | 98.81 147 | 99.76 27 | 99.29 221 | 94.42 278 | 93.85 302 | 97.60 304 | 95.12 156 | 98.09 296 | 94.32 281 | 86.85 315 | 97.80 296 |
|
V14 | | | 96.26 257 | 95.60 263 | 98.26 228 | 98.94 228 | 98.83 138 | 99.76 27 | 99.29 221 | 94.49 275 | 93.96 298 | 97.66 299 | 94.99 163 | 98.13 293 | 94.41 279 | 86.90 312 | 97.80 296 |
|
v18 | | | 96.42 252 | 95.80 259 | 98.26 228 | 98.95 224 | 98.82 145 | 99.76 27 | 99.28 228 | 94.58 269 | 94.12 292 | 97.70 296 | 95.22 153 | 98.16 289 | 94.83 272 | 87.80 306 | 97.79 301 |
|
Anonymous20231211 | | | 90.69 292 | 89.39 293 | 94.58 294 | 94.25 313 | 88.18 311 | 99.29 190 | 99.07 258 | 82.45 319 | 92.95 306 | 97.65 300 | 63.96 326 | 97.79 304 | 89.27 304 | 85.63 317 | 97.77 302 |
|
v11 | | | 96.23 261 | 95.57 267 | 98.21 238 | 98.93 233 | 98.83 138 | 99.72 39 | 99.29 221 | 94.29 280 | 94.05 295 | 97.64 301 | 94.88 172 | 98.04 297 | 92.89 293 | 88.43 304 | 97.77 302 |
|
ambc | | | | | 93.06 298 | 92.68 318 | 82.36 320 | 98.47 303 | 98.73 295 | | 95.09 288 | 97.41 308 | 55.55 328 | 99.10 259 | 96.42 244 | 91.32 297 | 97.71 304 |
|
new-patchmatchnet | | | 94.48 280 | 94.08 281 | 95.67 292 | 95.08 311 | 92.41 303 | 99.18 219 | 99.28 228 | 94.55 273 | 93.49 304 | 97.37 310 | 87.86 299 | 97.01 311 | 91.57 297 | 88.36 305 | 97.61 305 |
|
pmmvs-eth3d | | | 95.34 275 | 94.73 276 | 97.15 277 | 95.53 309 | 95.94 264 | 99.35 177 | 99.10 252 | 95.13 260 | 93.55 303 | 97.54 307 | 88.15 298 | 97.91 301 | 94.58 275 | 89.69 302 | 97.61 305 |
|
UnsupCasMVSNet_bld | | | 93.53 286 | 92.51 288 | 96.58 289 | 97.38 299 | 93.82 293 | 98.24 310 | 99.48 111 | 91.10 305 | 93.10 305 | 96.66 313 | 74.89 319 | 98.37 286 | 94.03 288 | 87.71 309 | 97.56 307 |
|
PM-MVS | | | 92.96 287 | 92.23 289 | 95.14 293 | 95.61 307 | 89.98 310 | 99.37 169 | 98.21 309 | 94.80 265 | 95.04 289 | 97.69 298 | 65.06 324 | 97.90 302 | 94.30 282 | 89.98 301 | 97.54 308 |
|
LCM-MVSNet | | | 86.80 295 | 85.22 298 | 91.53 306 | 87.81 325 | 80.96 322 | 98.23 312 | 98.99 266 | 71.05 323 | 90.13 314 | 96.51 314 | 48.45 331 | 96.88 312 | 90.51 299 | 85.30 318 | 96.76 309 |
|
OpenMVS_ROB | | 92.34 20 | 94.38 282 | 93.70 283 | 96.41 290 | 97.38 299 | 93.17 300 | 99.06 243 | 98.75 288 | 86.58 314 | 94.84 290 | 98.26 289 | 81.53 318 | 99.32 220 | 89.01 305 | 97.87 185 | 96.76 309 |
|
CMPMVS | | 69.68 23 | 94.13 283 | 94.90 275 | 91.84 303 | 97.24 303 | 80.01 323 | 98.52 301 | 99.48 111 | 89.01 311 | 91.99 309 | 99.67 121 | 85.67 307 | 99.13 254 | 95.44 261 | 97.03 221 | 96.39 311 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
1111 | | | 92.30 289 | 92.21 290 | 92.55 300 | 93.30 315 | 86.27 312 | 99.15 224 | 98.74 291 | 91.94 299 | 90.85 312 | 97.82 293 | 84.18 312 | 95.21 317 | 79.65 320 | 94.27 273 | 96.19 312 |
|
test12356 | | | 91.74 290 | 92.19 291 | 90.37 308 | 91.22 319 | 82.41 319 | 98.61 297 | 98.28 306 | 90.66 307 | 91.82 310 | 97.92 291 | 84.90 310 | 92.61 323 | 81.64 319 | 94.66 265 | 96.09 313 |
|
PMMVS2 | | | 86.87 294 | 85.37 297 | 91.35 307 | 90.21 322 | 83.80 317 | 98.89 280 | 97.45 321 | 83.13 318 | 91.67 311 | 95.03 316 | 48.49 330 | 94.70 320 | 85.86 315 | 77.62 321 | 95.54 314 |
|
tmp_tt | | | 82.80 299 | 81.52 299 | 86.66 310 | 66.61 334 | 68.44 332 | 92.79 327 | 97.92 313 | 68.96 325 | 80.04 324 | 99.85 26 | 85.77 306 | 96.15 316 | 97.86 153 | 43.89 329 | 95.39 315 |
|
testmv | | | 87.91 293 | 87.80 294 | 88.24 309 | 87.68 326 | 77.50 326 | 99.07 239 | 97.66 319 | 89.27 309 | 86.47 316 | 96.22 315 | 68.35 322 | 92.49 325 | 76.63 324 | 88.82 303 | 94.72 316 |
|
no-one | | | 83.04 298 | 80.12 300 | 91.79 304 | 89.44 324 | 85.65 315 | 99.32 181 | 98.32 305 | 89.06 310 | 79.79 325 | 89.16 326 | 44.86 332 | 96.67 313 | 84.33 317 | 46.78 328 | 93.05 317 |
|
testpf | | | 95.66 270 | 96.02 253 | 94.58 294 | 98.35 287 | 92.32 304 | 97.25 321 | 97.91 315 | 92.83 295 | 97.03 274 | 98.99 265 | 88.69 288 | 98.61 284 | 95.72 256 | 97.40 210 | 92.80 318 |
|
FPMVS | | | 84.93 296 | 85.65 296 | 82.75 316 | 86.77 327 | 63.39 333 | 98.35 307 | 98.92 274 | 74.11 322 | 83.39 319 | 98.98 268 | 50.85 329 | 92.40 326 | 84.54 316 | 94.97 256 | 92.46 319 |
|
Gipuma | | | 90.99 291 | 90.15 292 | 93.51 296 | 98.73 264 | 90.12 309 | 93.98 325 | 99.45 145 | 79.32 320 | 92.28 308 | 94.91 317 | 69.61 321 | 97.98 300 | 87.42 309 | 95.67 243 | 92.45 320 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
ANet_high | | | 77.30 303 | 74.86 305 | 84.62 313 | 75.88 332 | 77.61 325 | 97.63 318 | 93.15 332 | 88.81 312 | 64.27 328 | 89.29 325 | 36.51 333 | 83.93 332 | 75.89 325 | 52.31 327 | 92.33 321 |
|
PNet_i23d | | | 79.43 302 | 77.68 303 | 84.67 312 | 86.18 328 | 71.69 331 | 96.50 323 | 93.68 329 | 75.17 321 | 71.33 326 | 91.18 323 | 32.18 335 | 90.62 327 | 78.57 323 | 74.34 322 | 91.71 322 |
|
MVE | | 76.82 21 | 76.91 304 | 74.31 306 | 84.70 311 | 85.38 330 | 76.05 329 | 96.88 322 | 93.17 331 | 67.39 326 | 71.28 327 | 89.01 327 | 21.66 340 | 87.69 329 | 71.74 327 | 72.29 323 | 90.35 323 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
PMVS | | 70.75 22 | 75.98 305 | 74.97 304 | 79.01 318 | 70.98 333 | 55.18 334 | 93.37 326 | 98.21 309 | 65.08 329 | 61.78 330 | 93.83 319 | 21.74 339 | 92.53 324 | 78.59 322 | 91.12 298 | 89.34 324 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
wuykxyi23d | | | 74.42 306 | 71.19 307 | 84.14 314 | 76.16 331 | 74.29 330 | 96.00 324 | 92.57 334 | 69.57 324 | 63.84 329 | 87.49 328 | 21.98 337 | 88.86 328 | 75.56 326 | 57.50 326 | 89.26 325 |
|
EMVS | | | 80.02 301 | 79.22 302 | 82.43 317 | 91.19 320 | 76.40 327 | 97.55 320 | 92.49 335 | 66.36 328 | 83.01 320 | 91.27 322 | 64.63 325 | 85.79 331 | 65.82 329 | 60.65 325 | 85.08 326 |
|
E-PMN | | | 80.61 300 | 79.88 301 | 82.81 315 | 90.75 321 | 76.38 328 | 97.69 317 | 95.76 325 | 66.44 327 | 83.52 318 | 92.25 321 | 62.54 327 | 87.16 330 | 68.53 328 | 61.40 324 | 84.89 327 |
|
test123 | | | 39.01 310 | 42.50 310 | 28.53 322 | 39.17 335 | 20.91 336 | 98.75 289 | 19.17 338 | 19.83 332 | 38.57 331 | 66.67 330 | 33.16 334 | 15.42 334 | 37.50 332 | 29.66 332 | 49.26 328 |
|
.test1245 | | | 83.42 297 | 86.17 295 | 75.15 319 | 93.30 315 | 86.27 312 | 99.15 224 | 98.74 291 | 91.94 299 | 90.85 312 | 97.82 293 | 84.18 312 | 95.21 317 | 79.65 320 | 39.90 330 | 43.98 329 |
|
testmvs | | | 39.17 309 | 43.78 308 | 25.37 323 | 36.04 336 | 16.84 337 | 98.36 305 | 26.56 336 | 20.06 331 | 38.51 332 | 67.32 329 | 29.64 336 | 15.30 335 | 37.59 331 | 39.90 330 | 43.98 329 |
|
wuyk23d | | | 40.18 308 | 41.29 311 | 36.84 320 | 86.18 328 | 49.12 335 | 79.73 328 | 22.81 337 | 27.64 330 | 25.46 333 | 28.45 334 | 21.98 337 | 48.89 333 | 55.80 330 | 23.56 333 | 12.51 331 |
|
cdsmvs_eth3d_5k | | | 24.64 311 | 32.85 312 | 0.00 324 | 0.00 337 | 0.00 338 | 0.00 329 | 99.51 84 | 0.00 333 | 0.00 334 | 99.56 160 | 96.58 115 | 0.00 336 | 0.00 333 | 0.00 334 | 0.00 332 |
|
pcd_1.5k_mvsjas | | | 8.27 313 | 11.03 314 | 0.00 324 | 0.00 337 | 0.00 338 | 0.00 329 | 0.00 339 | 0.00 333 | 0.00 334 | 0.27 335 | 99.01 11 | 0.00 336 | 0.00 333 | 0.00 334 | 0.00 332 |
|
sosnet-low-res | | | 0.02 314 | 0.03 315 | 0.00 324 | 0.00 337 | 0.00 338 | 0.00 329 | 0.00 339 | 0.00 333 | 0.00 334 | 0.27 335 | 0.00 341 | 0.00 336 | 0.00 333 | 0.00 334 | 0.00 332 |
|
sosnet | | | 0.02 314 | 0.03 315 | 0.00 324 | 0.00 337 | 0.00 338 | 0.00 329 | 0.00 339 | 0.00 333 | 0.00 334 | 0.27 335 | 0.00 341 | 0.00 336 | 0.00 333 | 0.00 334 | 0.00 332 |
|
uncertanet | | | 0.02 314 | 0.03 315 | 0.00 324 | 0.00 337 | 0.00 338 | 0.00 329 | 0.00 339 | 0.00 333 | 0.00 334 | 0.27 335 | 0.00 341 | 0.00 336 | 0.00 333 | 0.00 334 | 0.00 332 |
|
Regformer | | | 0.02 314 | 0.03 315 | 0.00 324 | 0.00 337 | 0.00 338 | 0.00 329 | 0.00 339 | 0.00 333 | 0.00 334 | 0.27 335 | 0.00 341 | 0.00 336 | 0.00 333 | 0.00 334 | 0.00 332 |
|
ab-mvs-re | | | 8.30 312 | 11.06 313 | 0.00 324 | 0.00 337 | 0.00 338 | 0.00 329 | 0.00 339 | 0.00 333 | 0.00 334 | 99.58 154 | 0.00 341 | 0.00 336 | 0.00 333 | 0.00 334 | 0.00 332 |
|
uanet | | | 0.02 314 | 0.03 315 | 0.00 324 | 0.00 337 | 0.00 338 | 0.00 329 | 0.00 339 | 0.00 333 | 0.00 334 | 0.27 335 | 0.00 341 | 0.00 336 | 0.00 333 | 0.00 334 | 0.00 332 |
|
sam_mvs1 | | | | | | | | | | | | | 94.86 173 | | | | |
|
sam_mvs | | | | | | | | | | | | | 94.72 186 | | | | |
|
MTGPA | | | | | | | | | 99.47 125 | | | | | | | | |
|
test_post1 | | | | | | | | 99.23 209 | | | | 65.14 332 | 94.18 209 | 99.71 157 | 97.58 178 | | |
|
test_post | | | | | | | | | | | | 65.99 331 | 94.65 190 | 99.73 147 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 98.70 281 | 94.79 177 | 99.74 139 | | | |
|
MTMP | | | | | | | | | 98.88 281 | | | | | | | | |
|
gm-plane-assit | | | | | | 98.54 282 | 92.96 301 | | | 94.65 268 | | 99.15 251 | | 99.64 174 | 97.56 181 | | |
|
TEST9 | | | | | | 99.67 72 | 99.65 37 | 99.05 245 | 99.41 165 | 96.22 236 | 98.95 179 | 99.49 179 | 98.77 39 | 99.91 72 | | | |
|
test_8 | | | | | | 99.67 72 | 99.61 42 | 99.03 251 | 99.41 165 | 96.28 229 | 98.93 183 | 99.48 185 | 98.76 41 | 99.91 72 | | | |
|
agg_prior | | | | | | 99.67 72 | 99.62 40 | | 99.40 172 | | 98.87 190 | | | 99.91 72 | | | |
|
test_prior4 | | | | | | | 99.56 49 | 98.99 261 | | | | | | | | | |
|
test_prior2 | | | | | | | | 98.96 270 | | 98.34 66 | 99.01 168 | 99.52 171 | 98.68 49 | | 97.96 145 | 99.74 79 | |
|
旧先验2 | | | | | | | | 98.96 270 | | 96.70 198 | 99.47 77 | | | 99.94 40 | 98.19 127 | | |
|
æ–°å‡ ä½•2 | | | | | | | | 99.01 258 | | | | | | | | | |
|
原ACMM2 | | | | | | | | 98.95 274 | | | | | | | | | |
|
testdata2 | | | | | | | | | | | | | | 99.95 33 | 96.67 236 | | |
|
segment_acmp | | | | | | | | | | | | | 98.96 20 | | | | |
|
testdata1 | | | | | | | | 98.85 283 | | 98.32 69 | | | | | | | |
|
plane_prior7 | | | | | | 99.29 158 | 97.03 230 | | | | | | | | | | |
|
plane_prior6 | | | | | | 99.27 163 | 96.98 234 | | | | | | 92.71 241 | | | | |
|
plane_prior4 | | | | | | | | | | | | 99.61 146 | | | | | |
|
plane_prior3 | | | | | | | 97.00 232 | | | 98.69 46 | 99.11 151 | | | | | | |
|
plane_prior2 | | | | | | | | 99.39 162 | | 98.97 23 | | | | | | | |
|
plane_prior1 | | | | | | 99.26 165 | | | | | | | | | | | |
|
plane_prior | | | | | | | 96.97 235 | 99.21 215 | | 98.45 59 | | | | | | 97.60 192 | |
|
n2 | | | | | | | | | 0.00 339 | | | | | | | | |
|
nn | | | | | | | | | 0.00 339 | | | | | | | | |
|
door-mid | | | | | | | | | 98.05 312 | | | | | | | | |
|
test11 | | | | | | | | | 99.35 193 | | | | | | | | |
|
door | | | | | | | | | 97.92 313 | | | | | | | | |
|
HQP5-MVS | | | | | | | 96.83 240 | | | | | | | | | | |
|
HQP-NCC | | | | | | 99.19 174 | | 98.98 265 | | 98.24 72 | 98.66 217 | | | | | | |
|
ACMP_Plane | | | | | | 99.19 174 | | 98.98 265 | | 98.24 72 | 98.66 217 | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 97.19 206 | | |
|
HQP3-MVS | | | | | | | | | 99.39 175 | | | | | | | 97.58 194 | |
|
HQP2-MVS | | | | | | | | | | | | | 92.47 250 | | | | |
|
NP-MVS | | | | | | 99.23 168 | 96.92 238 | | | | | 99.40 207 | | | | | |
|
MDTV_nov1_ep13 | | | | 98.32 133 | | 99.11 192 | 94.44 288 | 99.27 197 | 98.74 291 | 97.51 140 | 99.40 92 | 99.62 143 | 94.78 178 | 99.76 137 | 97.59 177 | 98.81 151 | |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 97.19 218 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 97.43 209 | |
|
Test By Simon | | | | | | | | | | | | | 98.75 44 | | | | |
|