APDe-MVS | | | 99.66 1 | 99.57 1 | 99.92 1 | 99.77 38 | 99.89 1 | 99.75 34 | 99.56 48 | 99.02 10 | 99.88 3 | 99.85 26 | 99.18 5 | 99.96 19 | 99.22 31 | 99.92 12 | 99.90 1 |
|
UA-Net | | | 99.42 29 | 99.29 36 | 99.80 29 | 99.62 100 | 99.55 51 | 99.50 123 | 99.70 15 | 98.79 40 | 99.77 23 | 99.96 1 | 97.45 91 | 99.96 19 | 98.92 55 | 99.90 24 | 99.89 2 |
|
CHOSEN 1792x2688 | | | 99.19 55 | 99.10 55 | 99.45 94 | 99.89 8 | 98.52 181 | 99.39 171 | 99.94 1 | 98.73 44 | 99.11 161 | 99.89 10 | 95.50 143 | 99.94 40 | 99.50 8 | 99.97 3 | 99.89 2 |
|
DP-MVS | | | 99.16 60 | 98.95 75 | 99.78 33 | 99.77 38 | 99.53 55 | 99.41 164 | 99.50 99 | 97.03 191 | 99.04 176 | 99.88 14 | 97.39 92 | 99.92 63 | 98.66 85 | 99.90 24 | 99.87 4 |
|
EI-MVSNet-UG-set | | | 99.58 3 | 99.57 1 | 99.64 62 | 99.78 34 | 99.14 97 | 99.60 82 | 99.45 148 | 99.01 13 | 99.90 1 | 99.83 37 | 98.98 18 | 99.93 55 | 99.59 2 | 99.95 6 | 99.86 5 |
|
Test_1112_low_res | | | 98.89 96 | 98.66 110 | 99.57 72 | 99.69 76 | 98.95 122 | 99.03 262 | 99.47 127 | 96.98 193 | 99.15 156 | 99.23 247 | 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 57 | 99.90 3 | 99.37 73 | 99.02 265 | 99.91 3 | 97.67 137 | 99.59 59 | 99.75 90 | 95.90 133 | 99.73 156 | 99.53 6 | 99.02 132 | 99.86 5 |
|
EI-MVSNet-Vis-set | | | 99.58 3 | 99.56 3 | 99.64 62 | 99.78 34 | 99.15 96 | 99.61 81 | 99.45 148 | 99.01 13 | 99.89 2 | 99.82 44 | 99.01 11 | 99.92 63 | 99.56 5 | 99.95 6 | 99.85 8 |
|
CVMVSNet | | | 98.57 127 | 98.67 107 | 98.30 234 | 99.35 153 | 95.59 278 | 99.50 123 | 99.55 55 | 98.60 51 | 99.39 95 | 99.83 37 | 94.48 197 | 99.45 202 | 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 48 | 97.72 131 | 99.76 26 | 99.75 90 | 99.13 6 | 99.92 63 | 99.07 44 | 99.92 12 | 99.85 8 |
|
MG-MVS | | | 99.13 62 | 99.02 66 | 99.45 94 | 99.57 111 | 98.63 169 | 99.07 250 | 99.34 204 | 98.99 18 | 99.61 55 | 99.82 44 | 97.98 80 | 99.87 101 | 97.00 217 | 99.80 68 | 99.85 8 |
|
ACMMP_Plus | | | 99.47 20 | 99.34 24 | 99.88 4 | 99.87 15 | 99.86 3 | 99.47 140 | 99.48 113 | 98.05 98 | 99.76 26 | 99.86 22 | 98.82 32 | 99.93 55 | 98.82 71 | 99.91 17 | 99.84 12 |
|
HFP-MVS | | | 99.49 13 | 99.37 17 | 99.86 12 | 99.87 15 | 99.80 12 | 99.66 58 | 99.67 22 | 98.15 80 | 99.68 34 | 99.69 112 | 99.06 8 | 99.96 19 | 98.69 82 | 99.87 38 | 99.84 12 |
|
region2R | | | 99.48 17 | 99.35 22 | 99.87 6 | 99.88 11 | 99.80 12 | 99.65 68 | 99.66 25 | 98.13 82 | 99.66 45 | 99.68 117 | 98.96 20 | 99.96 19 | 98.62 90 | 99.87 38 | 99.84 12 |
|
#test# | | | 99.43 27 | 99.29 36 | 99.86 12 | 99.87 15 | 99.80 12 | 99.55 107 | 99.67 22 | 97.83 118 | 99.68 34 | 99.69 112 | 99.06 8 | 99.96 19 | 98.39 114 | 99.87 38 | 99.84 12 |
|
Regformer-4 | | | 99.59 2 | 99.54 4 | 99.73 45 | 99.76 41 | 99.41 70 | 99.58 89 | 99.49 104 | 99.02 10 | 99.88 3 | 99.80 64 | 99.00 17 | 99.94 40 | 99.45 15 | 99.92 12 | 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 19 | 99.37 99 | 99.74 95 | 98.81 33 | 99.94 40 | 98.79 72 | 99.86 48 | 99.84 12 |
|
X-MVStestdata | | | 96.55 258 | 95.45 279 | 99.87 6 | 99.85 23 | 99.83 7 | 99.69 44 | 99.68 19 | 98.98 19 | 99.37 99 | 64.01 343 | 98.81 33 | 99.94 40 | 98.79 72 | 99.86 48 | 99.84 12 |
|
ACMMPR | | | 99.49 13 | 99.36 19 | 99.86 12 | 99.87 15 | 99.79 16 | 99.66 58 | 99.67 22 | 98.15 80 | 99.67 40 | 99.69 112 | 98.95 23 | 99.96 19 | 98.69 82 | 99.87 38 | 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 62 | 97.59 140 | 99.68 34 | 99.63 139 | 98.91 26 | 99.94 40 | 98.58 95 | 99.91 17 | 99.84 12 |
|
SteuartSystems-ACMMP | | | 99.54 7 | 99.42 11 | 99.87 6 | 99.82 29 | 99.81 11 | 99.59 84 | 99.51 85 | 98.62 49 | 99.79 18 | 99.83 37 | 99.28 3 | 99.97 11 | 98.48 108 | 99.90 24 | 99.84 12 |
Skip Steuart: Steuart Systems R&D Blog. |
1112_ss | | | 98.98 90 | 98.77 97 | 99.59 68 | 99.68 79 | 99.02 108 | 99.25 216 | 99.48 113 | 97.23 173 | 99.13 157 | 99.58 155 | 96.93 105 | 99.90 84 | 98.87 61 | 98.78 152 | 99.84 12 |
|
MP-MVS-pluss | | | 99.37 37 | 99.20 46 | 99.88 4 | 99.90 3 | 99.87 2 | 99.30 196 | 99.52 76 | 97.18 176 | 99.60 56 | 99.79 72 | 98.79 35 | 99.95 33 | 98.83 68 | 99.91 17 | 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 | 99.36 182 | 99.47 127 | 98.79 40 | 99.68 34 | 99.81 53 | 98.43 61 | 99.97 11 | 98.88 57 | 99.90 24 | 99.83 23 |
|
MTAPA | | | 99.52 11 | 99.39 15 | 99.89 2 | 99.90 3 | 99.86 3 | 99.66 58 | 99.47 127 | 98.79 40 | 99.68 34 | 99.81 53 | 98.43 61 | 99.97 11 | 98.88 57 | 99.90 24 | 99.83 23 |
|
Regformer-3 | | | 99.57 6 | 99.53 5 | 99.68 50 | 99.76 41 | 99.29 81 | 99.58 89 | 99.44 156 | 99.01 13 | 99.87 6 | 99.80 64 | 98.97 19 | 99.91 72 | 99.44 16 | 99.92 12 | 99.83 23 |
|
PGM-MVS | | | 99.45 22 | 99.31 31 | 99.86 12 | 99.87 15 | 99.78 20 | 99.58 89 | 99.65 30 | 97.84 117 | 99.71 29 | 99.80 64 | 99.12 7 | 99.97 11 | 98.33 121 | 99.87 38 | 99.83 23 |
|
mPP-MVS | | | 99.44 25 | 99.30 33 | 99.86 12 | 99.88 11 | 99.79 16 | 99.69 44 | 99.48 113 | 98.12 84 | 99.50 73 | 99.75 90 | 98.78 36 | 99.97 11 | 98.57 97 | 99.89 32 | 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 76 | 98.07 93 | 99.53 68 | 99.63 139 | 98.93 25 | 99.97 11 | 98.74 75 | 99.91 17 | 99.83 23 |
|
TSAR-MVS + MP. | | | 99.58 3 | 99.50 7 | 99.81 27 | 99.91 1 | 99.66 34 | 99.63 72 | 99.39 178 | 98.91 29 | 99.78 22 | 99.85 26 | 99.36 2 | 99.94 40 | 98.84 66 | 99.88 34 | 99.82 30 |
|
MP-MVS | | | 99.33 41 | 99.15 50 | 99.87 6 | 99.88 11 | 99.82 10 | 99.66 58 | 99.46 137 | 98.09 89 | 99.48 77 | 99.74 95 | 98.29 70 | 99.96 19 | 97.93 148 | 99.87 38 | 99.82 30 |
|
MCST-MVS | | | 99.43 27 | 99.30 33 | 99.82 24 | 99.79 33 | 99.74 24 | 99.29 200 | 99.40 175 | 98.79 40 | 99.52 70 | 99.62 144 | 98.91 26 | 99.90 84 | 98.64 87 | 99.75 77 | 99.82 30 |
|
DeepC-MVS_fast | | 98.69 1 | 99.49 13 | 99.39 15 | 99.77 35 | 99.63 96 | 99.59 46 | 99.36 182 | 99.46 137 | 99.07 9 | 99.79 18 | 99.82 44 | 98.85 30 | 99.92 63 | 98.68 84 | 99.87 38 | 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 55 | 99.37 191 | 98.70 45 | 99.77 23 | 99.49 180 | 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 84 | 99.49 104 | 97.03 191 | 99.63 50 | 99.69 112 | 97.27 97 | 99.96 19 | 97.82 156 | 99.84 57 | 99.81 34 |
|
ACMMP | | | 99.45 22 | 99.32 26 | 99.82 24 | 99.89 8 | 99.67 32 | 99.62 75 | 99.69 18 | 98.12 84 | 99.63 50 | 99.84 35 | 98.73 46 | 99.96 19 | 98.55 103 | 99.83 61 | 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 | 98.81 109 | 99.37 17 | 97.12 289 | 99.60 106 | 91.75 316 | 98.61 307 | 99.44 156 | 99.35 1 | 99.83 11 | 99.85 26 | 98.70 48 | 99.81 132 | 99.02 48 | 99.91 17 | 99.81 34 |
|
3Dnovator+ | | 97.12 13 | 99.18 57 | 98.97 71 | 99.82 24 | 99.17 194 | 99.68 30 | 99.81 15 | 99.51 85 | 99.20 4 | 98.72 216 | 99.89 10 | 95.68 140 | 99.97 11 | 98.86 64 | 99.86 48 | 99.81 34 |
|
Regformer-1 | | | 99.53 9 | 99.47 8 | 99.72 47 | 99.71 69 | 99.44 67 | 99.49 131 | 99.46 137 | 98.95 24 | 99.83 11 | 99.76 85 | 99.01 11 | 99.93 55 | 99.17 36 | 99.87 38 | 99.80 39 |
|
Regformer-2 | | | 99.54 7 | 99.47 8 | 99.75 38 | 99.71 69 | 99.52 58 | 99.49 131 | 99.49 104 | 98.94 26 | 99.83 11 | 99.76 85 | 99.01 11 | 99.94 40 | 99.15 38 | 99.87 38 | 99.80 39 |
|
APD-MVS | | | 99.27 49 | 99.08 56 | 99.84 21 | 99.75 47 | 99.79 16 | 99.50 123 | 99.50 99 | 97.16 178 | 99.77 23 | 99.82 44 | 98.78 36 | 99.94 40 | 97.56 181 | 99.86 48 | 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 | 99.61 104 | 99.65 37 | 99.30 196 | 99.48 113 | 98.86 31 | 99.21 145 | 99.63 139 | 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 | 99.43 153 | 99.51 85 | 98.68 47 | 99.27 125 | 99.53 168 | 98.64 52 | 99.96 19 | 98.44 113 | 99.80 68 | 99.79 43 |
|
abl_6 | | | 99.44 25 | 99.31 31 | 99.83 22 | 99.85 23 | 99.75 21 | 99.66 58 | 99.59 38 | 98.13 82 | 99.82 14 | 99.81 53 | 98.60 54 | 99.96 19 | 98.46 111 | 99.88 34 | 99.79 43 |
|
PVSNet_Blended_VisFu | | | 99.36 38 | 99.28 38 | 99.61 66 | 99.86 20 | 99.07 103 | 99.47 140 | 99.93 2 | 97.66 138 | 99.71 29 | 99.86 22 | 97.73 86 | 99.96 19 | 99.47 13 | 99.82 65 | 99.79 43 |
|
3Dnovator | | 97.25 9 | 99.24 53 | 99.05 58 | 99.81 27 | 99.12 202 | 99.66 34 | 99.84 9 | 99.74 10 | 99.09 8 | 98.92 194 | 99.90 7 | 95.94 131 | 99.98 5 | 98.95 53 | 99.92 12 | 99.79 43 |
|
APD-MVS_3200maxsize | | | 99.48 17 | 99.35 22 | 99.85 17 | 99.76 41 | 99.83 7 | 99.63 72 | 99.54 62 | 98.36 65 | 99.79 18 | 99.82 44 | 98.86 29 | 99.95 33 | 98.62 90 | 99.81 66 | 99.78 47 |
|
CDPH-MVS | | | 99.13 62 | 98.91 79 | 99.80 29 | 99.75 47 | 99.71 26 | 99.15 235 | 99.41 168 | 96.60 215 | 99.60 56 | 99.55 164 | 98.83 31 | 99.90 84 | 97.48 189 | 99.83 61 | 99.78 47 |
|
SD-MVS | | | 99.41 32 | 99.52 6 | 99.05 136 | 99.74 57 | 99.68 30 | 99.46 143 | 99.52 76 | 99.11 7 | 99.88 3 | 99.91 5 | 99.43 1 | 97.70 317 | 98.72 79 | 99.93 11 | 99.77 49 |
|
CNVR-MVS | | | 99.42 29 | 99.30 33 | 99.78 33 | 99.62 100 | 99.71 26 | 99.26 214 | 99.52 76 | 98.82 35 | 99.39 95 | 99.71 103 | 98.96 20 | 99.85 108 | 98.59 94 | 99.80 68 | 99.77 49 |
|
MVS_111021_HR | | | 99.41 32 | 99.32 26 | 99.66 53 | 99.72 65 | 99.47 64 | 98.95 284 | 99.85 6 | 98.82 35 | 99.54 67 | 99.73 98 | 98.51 56 | 99.74 148 | 98.91 56 | 99.88 34 | 99.77 49 |
|
QAPM | | | 98.67 122 | 98.30 135 | 99.80 29 | 99.20 184 | 99.67 32 | 99.77 24 | 99.72 11 | 94.74 276 | 98.73 215 | 99.90 7 | 95.78 137 | 99.98 5 | 96.96 221 | 99.88 34 | 99.76 52 |
|
test9_res | | | | | | | | | | | | | | | 97.49 188 | 99.72 83 | 99.75 53 |
|
train_agg | | | 99.02 85 | 98.77 97 | 99.77 35 | 99.67 80 | 99.65 37 | 99.05 256 | 99.41 168 | 96.28 239 | 98.95 190 | 99.49 180 | 98.76 41 | 99.91 72 | 97.63 175 | 99.72 83 | 99.75 53 |
|
agg_prior3 | | | 98.97 92 | 98.71 103 | 99.75 38 | 99.67 80 | 99.60 44 | 99.04 261 | 99.41 168 | 95.93 261 | 98.87 200 | 99.48 186 | 98.61 53 | 99.91 72 | 97.63 175 | 99.72 83 | 99.75 53 |
|
agg_prior1 | | | 99.01 88 | 98.76 99 | 99.76 37 | 99.67 80 | 99.62 40 | 98.99 271 | 99.40 175 | 96.26 242 | 98.87 200 | 99.49 180 | 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 80 | 99.48 62 | 98.96 280 | 99.56 48 | 98.34 66 | 99.01 179 | 99.52 172 | 98.68 49 | 99.83 120 | 97.96 145 | 99.74 79 | 99.74 58 |
|
test_prior | | | | | 99.68 50 | 99.67 80 | 99.48 62 | | 99.56 48 | | | | | 99.83 120 | | | 99.74 58 |
|
test12 | | | | | 99.75 38 | 99.64 93 | 99.61 42 | | 99.29 225 | | 99.21 145 | | 98.38 65 | 99.89 92 | | 99.74 79 | 99.74 58 |
|
114514_t | | | 98.93 94 | 98.67 107 | 99.72 47 | 99.85 23 | 99.53 55 | 99.62 75 | 99.59 38 | 92.65 307 | 99.71 29 | 99.78 77 | 98.06 78 | 99.90 84 | 98.84 66 | 99.91 17 | 99.74 58 |
|
Vis-MVSNet | | | 99.12 67 | 98.97 71 | 99.56 74 | 99.78 34 | 99.10 100 | 99.68 53 | 99.66 25 | 98.49 56 | 99.86 7 | 99.87 19 | 94.77 183 | 99.84 113 | 99.19 33 | 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 57 | 99.59 46 | | 99.54 62 | | | 99.69 112 | 98.47 58 | | | 99.68 93 | 99.73 63 |
|
1121 | | | 99.09 75 | 98.87 84 | 99.75 38 | 99.74 57 | 99.60 44 | 99.27 206 | 99.48 113 | 96.82 202 | 99.25 131 | 99.65 128 | 98.38 65 | 99.93 55 | 97.53 184 | 99.67 94 | 99.73 63 |
|
EPNet | | | 98.86 100 | 98.71 103 | 99.30 113 | 97.20 314 | 98.18 196 | 99.62 75 | 98.91 279 | 99.28 2 | 98.63 234 | 99.81 53 | 95.96 128 | 99.99 1 | 99.24 30 | 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 81 | 98.87 84 | 99.57 72 | 99.73 62 | 99.32 77 | 99.75 34 | 99.20 245 | 98.02 102 | 99.56 64 | 99.86 22 | 96.54 116 | 99.67 177 | 98.09 134 | 99.13 123 | 99.73 63 |
|
F-COLMAP | | | 99.19 55 | 99.04 61 | 99.64 62 | 99.78 34 | 99.27 84 | 99.42 160 | 99.54 62 | 97.29 167 | 99.41 90 | 99.59 152 | 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 62 | 99.82 29 | 99.23 88 | 99.62 75 | 99.55 55 | 98.94 26 | 99.63 50 | 99.95 2 | 95.82 136 | 99.94 40 | 99.37 17 | 99.97 3 | 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 62 | 96.76 203 | 99.29 117 | 99.64 135 | 98.43 61 | 99.94 40 | 96.92 225 | 99.66 95 | 99.72 69 |
|
æ— å…ˆéªŒ | | | | | | | | 98.99 271 | 99.51 85 | 96.89 198 | | | | 99.93 55 | 97.53 184 | | 99.72 69 |
|
test222 | | | | | | 99.75 47 | 99.49 61 | 98.91 289 | 99.49 104 | 96.42 230 | 99.34 109 | 99.65 128 | 98.28 71 | | | 99.69 90 | 99.72 69 |
|
testdata | | | | | 99.54 75 | 99.75 47 | 98.95 122 | | 99.51 85 | 97.07 187 | 99.43 85 | 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 | 99.52 117 | 99.56 49 | 99.41 164 | 99.39 178 | 99.01 13 | 99.74 28 | 99.78 77 | 95.56 141 | 99.92 63 | 99.52 7 | 98.18 180 | 99.72 69 |
|
WTY-MVS | | | 99.06 79 | 98.88 83 | 99.61 66 | 99.62 100 | 99.16 93 | 99.37 178 | 99.56 48 | 98.04 99 | 99.53 68 | 99.62 144 | 96.84 106 | 99.94 40 | 98.85 65 | 98.49 165 | 99.72 69 |
|
CSCG | | | 99.32 42 | 99.32 26 | 99.32 109 | 99.85 23 | 98.29 192 | 99.71 41 | 99.66 25 | 98.11 86 | 99.41 90 | 99.80 64 | 98.37 67 | 99.96 19 | 98.99 50 | 99.96 5 | 99.72 69 |
|
原ACMM1 | | | | | 99.65 57 | 99.73 62 | 99.33 76 | | 99.47 127 | 97.46 151 | 99.12 159 | 99.66 127 | 98.67 51 | 99.91 72 | 97.70 171 | 99.69 90 | 99.71 76 |
|
LFMVS | | | 97.90 189 | 97.35 227 | 99.54 75 | 99.52 117 | 99.01 110 | 99.39 171 | 98.24 319 | 97.10 186 | 99.65 48 | 99.79 72 | 84.79 321 | 99.91 72 | 99.28 27 | 98.38 169 | 99.69 77 |
|
EPNet_dtu | | | 98.03 168 | 97.96 156 | 98.23 245 | 98.27 298 | 95.54 281 | 99.23 219 | 98.75 294 | 99.02 10 | 97.82 271 | 99.71 103 | 96.11 127 | 99.48 199 | 93.04 301 | 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 82 | 98.84 90 | 99.66 53 | 99.74 57 | 99.44 67 | 99.39 171 | 99.38 184 | 97.70 134 | 99.28 121 | 99.28 241 | 98.34 68 | 99.85 108 | 96.96 221 | 99.45 104 | 99.69 77 |
|
EPP-MVSNet | | | 99.13 62 | 98.99 68 | 99.53 79 | 99.65 92 | 99.06 104 | 99.81 15 | 99.33 212 | 97.43 155 | 99.60 56 | 99.88 14 | 97.14 99 | 99.84 113 | 99.13 39 | 98.94 139 | 99.69 77 |
|
sss | | | 99.17 58 | 99.05 58 | 99.53 79 | 99.62 100 | 98.97 117 | 99.36 182 | 99.62 31 | 97.83 118 | 99.67 40 | 99.65 128 | 97.37 95 | 99.95 33 | 99.19 33 | 99.19 120 | 99.68 81 |
|
PHI-MVS | | | 99.30 44 | 99.17 49 | 99.70 49 | 99.56 114 | 99.52 58 | 99.58 89 | 99.80 8 | 97.12 182 | 99.62 53 | 99.73 98 | 98.58 55 | 99.90 84 | 98.61 92 | 99.91 17 | 99.68 81 |
|
PVSNet_0 | | 94.43 19 | 96.09 276 | 95.47 278 | 97.94 263 | 99.31 165 | 94.34 300 | 97.81 326 | 99.70 15 | 97.12 182 | 97.46 275 | 98.75 285 | 89.71 288 | 99.79 139 | 97.69 172 | 81.69 330 | 99.68 81 |
|
TAMVS | | | 99.12 67 | 99.08 56 | 99.24 121 | 99.46 131 | 98.55 176 | 99.51 118 | 99.46 137 | 98.09 89 | 99.45 81 | 99.82 44 | 98.34 68 | 99.51 198 | 98.70 80 | 98.93 140 | 99.67 84 |
|
CHOSEN 280x420 | | | 99.12 67 | 99.13 52 | 99.08 132 | 99.66 90 | 97.89 208 | 98.43 314 | 99.71 13 | 98.88 30 | 99.62 53 | 99.76 85 | 96.63 114 | 99.70 172 | 99.46 14 | 99.99 1 | 99.66 85 |
|
CDS-MVSNet | | | 99.09 75 | 99.03 63 | 99.25 119 | 99.42 137 | 98.73 160 | 99.45 144 | 99.46 137 | 98.11 86 | 99.46 80 | 99.77 82 | 98.01 79 | 99.37 216 | 98.70 80 | 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 85 | 99.40 145 | 99.03 107 | 98.80 295 | 99.36 192 | 96.33 235 | 99.00 186 | 99.12 257 | 98.46 59 | 99.84 113 | 95.23 267 | 99.37 112 | 99.66 85 |
|
CANet | | | 99.25 52 | 99.14 51 | 99.59 68 | 99.41 140 | 99.16 93 | 99.35 186 | 99.57 44 | 98.82 35 | 99.51 72 | 99.61 147 | 96.46 117 | 99.95 33 | 99.59 2 | 99.98 2 | 99.65 88 |
|
TSAR-MVS + GP. | | | 99.36 38 | 99.36 19 | 99.36 104 | 99.67 80 | 98.61 174 | 99.07 250 | 99.33 212 | 99.00 17 | 99.82 14 | 99.81 53 | 99.06 8 | 99.84 113 | 99.09 42 | 99.42 106 | 99.65 88 |
|
MVSFormer | | | 99.17 58 | 99.12 53 | 99.29 116 | 99.51 119 | 98.94 125 | 99.88 1 | 99.46 137 | 97.55 145 | 99.80 16 | 99.65 128 | 97.39 92 | 99.28 239 | 99.03 46 | 99.85 52 | 99.65 88 |
|
jason | | | 99.13 62 | 99.03 63 | 99.45 94 | 99.46 131 | 98.87 133 | 99.12 239 | 99.26 238 | 98.03 101 | 99.79 18 | 99.65 128 | 97.02 102 | 99.85 108 | 99.02 48 | 99.90 24 | 99.65 88 |
jason: jason. |
PLC | | 97.94 4 | 99.02 85 | 98.85 89 | 99.53 79 | 99.66 90 | 99.01 110 | 99.24 218 | 99.52 76 | 96.85 200 | 99.27 125 | 99.48 186 | 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 | 97.74 214 | 97.34 230 | 98.94 149 | 99.70 74 | 97.53 221 | 99.25 216 | 99.51 85 | 91.90 311 | 99.30 113 | 99.63 139 | 98.78 36 | 99.64 183 | 88.09 318 | 99.87 38 | 99.65 88 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
MVS_0304 | | | 99.06 79 | 98.86 87 | 99.66 53 | 99.51 119 | 99.36 74 | 99.22 223 | 99.51 85 | 98.95 24 | 99.58 60 | 99.65 128 | 93.74 225 | 99.98 5 | 99.66 1 | 99.95 6 | 99.64 94 |
|
LCM-MVSNet-Re | | | 97.83 197 | 98.15 140 | 96.87 294 | 99.30 166 | 92.25 315 | 99.59 84 | 98.26 318 | 97.43 155 | 96.20 291 | 99.13 254 | 96.27 123 | 98.73 293 | 98.17 129 | 98.99 134 | 99.64 94 |
|
BH-RMVSNet | | | 98.41 134 | 98.08 147 | 99.40 102 | 99.41 140 | 98.83 140 | 99.30 196 | 98.77 293 | 97.70 134 | 98.94 192 | 99.65 128 | 92.91 236 | 99.74 148 | 96.52 241 | 99.55 102 | 99.64 94 |
|
MVS_111021_LR | | | 99.41 32 | 99.33 25 | 99.65 57 | 99.77 38 | 99.51 60 | 98.94 286 | 99.85 6 | 98.82 35 | 99.65 48 | 99.74 95 | 98.51 56 | 99.80 136 | 98.83 68 | 99.89 32 | 99.64 94 |
|
MVS | | | 97.28 247 | 96.55 254 | 99.48 88 | 98.78 268 | 98.95 122 | 99.27 206 | 99.39 178 | 83.53 327 | 98.08 261 | 99.54 167 | 96.97 103 | 99.87 101 | 94.23 290 | 99.16 121 | 99.63 98 |
|
MSLP-MVS++ | | | 99.46 21 | 99.47 8 | 99.44 97 | 99.60 106 | 99.16 93 | 99.41 164 | 99.71 13 | 98.98 19 | 99.45 81 | 99.78 77 | 99.19 4 | 99.54 197 | 99.28 27 | 99.84 57 | 99.63 98 |
|
GA-MVS | | | 97.85 193 | 97.47 208 | 99.00 141 | 99.38 148 | 97.99 203 | 98.57 309 | 99.15 250 | 97.04 190 | 98.90 197 | 99.30 238 | 89.83 287 | 99.38 213 | 96.70 234 | 98.33 170 | 99.62 100 |
|
Vis-MVSNet (Re-imp) | | | 98.87 97 | 98.72 101 | 99.31 110 | 99.71 69 | 98.88 132 | 99.80 19 | 99.44 156 | 97.91 111 | 99.36 103 | 99.78 77 | 95.49 144 | 99.43 211 | 97.91 149 | 99.11 124 | 99.62 100 |
|
VDD-MVS | | | 97.73 215 | 97.35 227 | 98.88 174 | 99.47 130 | 97.12 231 | 99.34 189 | 98.85 285 | 98.19 76 | 99.67 40 | 99.85 26 | 82.98 325 | 99.92 63 | 99.49 12 | 98.32 171 | 99.60 102 |
|
DELS-MVS | | | 99.48 17 | 99.42 11 | 99.65 57 | 99.72 65 | 99.40 72 | 99.05 256 | 99.66 25 | 99.14 6 | 99.57 63 | 99.80 64 | 98.46 59 | 99.94 40 | 99.57 4 | 99.84 57 | 99.60 102 |
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 | 99.42 101 | 99.76 41 | 98.79 156 | 98.78 296 | 99.91 3 | 96.74 204 | 99.67 40 | 99.49 180 | 97.53 89 | 99.88 99 | 98.98 51 | 99.85 52 | 99.60 102 |
|
OMC-MVS | | | 99.08 77 | 99.04 61 | 99.20 125 | 99.67 80 | 98.22 195 | 99.28 203 | 99.52 76 | 98.07 93 | 99.66 45 | 99.81 53 | 97.79 84 | 99.78 141 | 97.79 158 | 99.81 66 | 99.60 102 |
|
AllTest | | | 98.87 97 | 98.72 101 | 99.31 110 | 99.86 20 | 98.48 186 | 99.56 102 | 99.61 32 | 97.85 115 | 99.36 103 | 99.85 26 | 95.95 129 | 99.85 108 | 96.66 237 | 99.83 61 | 99.59 106 |
|
TestCases | | | | | 99.31 110 | 99.86 20 | 98.48 186 | | 99.61 32 | 97.85 115 | 99.36 103 | 99.85 26 | 95.95 129 | 99.85 108 | 96.66 237 | 99.83 61 | 99.59 106 |
|
lupinMVS | | | 99.13 62 | 99.01 67 | 99.46 93 | 99.51 119 | 98.94 125 | 99.05 256 | 99.16 249 | 97.86 113 | 99.80 16 | 99.56 161 | 97.39 92 | 99.86 104 | 98.94 54 | 99.85 52 | 99.58 108 |
|
RPSCF | | | 98.22 143 | 98.62 115 | 96.99 290 | 99.82 29 | 91.58 317 | 99.72 39 | 99.44 156 | 96.61 213 | 99.66 45 | 99.89 10 | 95.92 132 | 99.82 128 | 97.46 192 | 99.10 126 | 99.57 109 |
|
DSMNet-mixed | | | 97.25 248 | 97.35 227 | 96.95 292 | 97.84 303 | 93.61 308 | 99.57 95 | 96.63 334 | 96.13 255 | 98.87 200 | 98.61 290 | 94.59 192 | 97.70 317 | 95.08 269 | 98.86 147 | 99.55 110 |
|
AdaColmap | | | 99.01 88 | 98.80 94 | 99.66 53 | 99.56 114 | 99.54 52 | 99.18 230 | 99.70 15 | 98.18 79 | 99.35 106 | 99.63 139 | 96.32 121 | 99.90 84 | 97.48 189 | 99.77 74 | 99.55 110 |
|
alignmvs | | | 98.81 109 | 98.56 122 | 99.58 71 | 99.43 136 | 99.42 69 | 99.51 118 | 98.96 272 | 98.61 50 | 99.35 106 | 98.92 272 | 94.78 179 | 99.77 143 | 99.35 18 | 98.11 187 | 99.54 112 |
|
PatchmatchNet | | | 98.31 139 | 98.36 129 | 98.19 250 | 99.16 196 | 95.32 286 | 99.27 206 | 98.92 276 | 97.37 161 | 99.37 99 | 99.58 155 | 94.90 171 | 99.70 172 | 97.43 195 | 99.21 118 | 99.54 112 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
PVSNet | | 96.02 17 | 98.85 106 | 98.84 90 | 98.89 167 | 99.73 62 | 97.28 224 | 98.32 318 | 99.60 35 | 97.86 113 | 99.50 73 | 99.57 159 | 96.75 111 | 99.86 104 | 98.56 100 | 99.70 89 | 99.54 112 |
|
MSDG | | | 98.98 90 | 98.80 94 | 99.53 79 | 99.76 41 | 99.19 90 | 98.75 299 | 99.55 55 | 97.25 170 | 99.47 78 | 99.77 82 | 97.82 83 | 99.87 101 | 96.93 224 | 99.90 24 | 99.54 112 |
|
UGNet | | | 98.87 97 | 98.69 105 | 99.40 102 | 99.22 181 | 98.72 161 | 99.44 148 | 99.68 19 | 99.24 3 | 99.18 153 | 99.42 201 | 92.74 240 | 99.96 19 | 99.34 22 | 99.94 10 | 99.53 116 |
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 | | | 97.93 184 | 97.65 192 | 98.77 194 | 99.18 189 | 97.07 236 | 99.03 262 | 99.14 252 | 96.16 251 | 98.74 214 | 99.57 159 | 94.56 193 | 99.72 160 | 93.36 297 | 99.11 124 | 99.52 117 |
|
PMMVS | | | 98.80 112 | 98.62 115 | 99.34 105 | 99.27 174 | 98.70 162 | 98.76 298 | 99.31 219 | 97.34 162 | 99.21 145 | 99.07 259 | 97.20 98 | 99.82 128 | 98.56 100 | 98.87 146 | 99.52 117 |
|
LS3D | | | 99.27 49 | 99.12 53 | 99.74 43 | 99.18 189 | 99.75 21 | 99.56 102 | 99.57 44 | 98.45 59 | 99.49 76 | 99.85 26 | 97.77 85 | 99.94 40 | 98.33 121 | 99.84 57 | 99.52 117 |
|
Effi-MVS+ | | | 98.81 109 | 98.59 120 | 99.48 88 | 99.46 131 | 99.12 99 | 98.08 324 | 99.50 99 | 97.50 150 | 99.38 97 | 99.41 204 | 96.37 120 | 99.81 132 | 99.11 41 | 98.54 162 | 99.51 120 |
|
Patchmatch-RL test | | | 95.84 278 | 95.81 267 | 95.95 301 | 95.61 317 | 90.57 318 | 98.24 320 | 98.39 315 | 95.10 272 | 95.20 297 | 98.67 287 | 94.78 179 | 97.77 315 | 96.28 247 | 90.02 310 | 99.51 120 |
|
mvs_anonymous | | | 99.03 84 | 98.99 68 | 99.16 127 | 99.38 148 | 98.52 181 | 99.51 118 | 99.38 184 | 97.79 123 | 99.38 97 | 99.81 53 | 97.30 96 | 99.45 202 | 99.35 18 | 98.99 134 | 99.51 120 |
|
Patchmatch-test1 | | | 98.16 149 | 98.14 141 | 98.22 247 | 99.30 166 | 95.55 279 | 99.07 250 | 98.97 270 | 97.57 143 | 99.43 85 | 99.60 150 | 92.72 241 | 99.60 191 | 97.38 197 | 99.20 119 | 99.50 123 |
|
test_normal | | | 97.44 242 | 96.77 252 | 99.44 97 | 97.75 306 | 99.00 112 | 99.10 247 | 98.64 308 | 97.71 132 | 93.93 310 | 98.82 280 | 87.39 311 | 99.83 120 | 98.61 92 | 98.97 136 | 99.49 124 |
|
ab-mvs | | | 98.86 100 | 98.63 112 | 99.54 75 | 99.64 93 | 99.19 90 | 99.44 148 | 99.54 62 | 97.77 125 | 99.30 113 | 99.81 53 | 94.20 206 | 99.93 55 | 99.17 36 | 98.82 149 | 99.49 124 |
|
ADS-MVSNet2 | | | 98.02 170 | 98.07 149 | 97.87 268 | 99.33 157 | 95.19 289 | 99.23 219 | 99.08 257 | 96.24 244 | 99.10 164 | 99.67 121 | 94.11 211 | 98.93 288 | 96.81 228 | 99.05 130 | 99.48 126 |
|
ADS-MVSNet | | | 98.20 146 | 98.08 147 | 98.56 210 | 99.33 157 | 96.48 262 | 99.23 219 | 99.15 250 | 96.24 244 | 99.10 164 | 99.67 121 | 94.11 211 | 99.71 166 | 96.81 228 | 99.05 130 | 99.48 126 |
|
tpm | | | 97.67 226 | 97.55 198 | 98.03 256 | 99.02 220 | 95.01 292 | 99.43 153 | 98.54 314 | 96.44 228 | 99.12 159 | 99.34 230 | 91.83 263 | 99.60 191 | 97.75 164 | 96.46 238 | 99.48 126 |
|
CNLPA | | | 99.14 61 | 98.99 68 | 99.59 68 | 99.58 109 | 99.41 70 | 99.16 232 | 99.44 156 | 98.45 59 | 99.19 151 | 99.49 180 | 98.08 77 | 99.89 92 | 97.73 166 | 99.75 77 | 99.48 126 |
|
canonicalmvs | | | 99.02 85 | 98.86 87 | 99.51 85 | 99.42 137 | 99.32 77 | 99.80 19 | 99.48 113 | 98.63 48 | 99.31 112 | 98.81 281 | 97.09 100 | 99.75 147 | 99.27 29 | 97.90 193 | 99.47 130 |
|
Test4 | | | 95.05 286 | 93.67 294 | 99.22 124 | 96.07 316 | 98.94 125 | 99.20 228 | 99.27 237 | 97.71 132 | 89.96 325 | 97.59 316 | 66.18 333 | 99.25 248 | 98.06 141 | 98.96 137 | 99.47 130 |
|
MIMVSNet | | | 97.73 215 | 97.45 211 | 98.57 208 | 99.45 135 | 97.50 222 | 99.02 265 | 98.98 269 | 96.11 256 | 99.41 90 | 99.14 253 | 90.28 281 | 98.74 292 | 95.74 255 | 98.93 140 | 99.47 130 |
|
MVS_Test | | | 99.10 74 | 98.97 71 | 99.48 88 | 99.49 126 | 99.14 97 | 99.67 55 | 99.34 204 | 97.31 165 | 99.58 60 | 99.76 85 | 97.65 88 | 99.82 128 | 98.87 61 | 99.07 129 | 99.46 133 |
|
MDTV_nov1_ep13_2view | | | | | | | 95.18 290 | 99.35 186 | | 96.84 201 | 99.58 60 | | 95.19 155 | | 97.82 156 | | 99.46 133 |
|
MVS-HIRNet | | | 95.75 279 | 95.16 283 | 97.51 283 | 99.30 166 | 93.69 307 | 98.88 291 | 95.78 335 | 85.09 326 | 98.78 211 | 92.65 330 | 91.29 274 | 99.37 216 | 94.85 272 | 99.85 52 | 99.46 133 |
|
DI_MVS_plusplus_test | | | 97.45 241 | 96.79 250 | 99.44 97 | 97.76 305 | 99.04 106 | 99.21 226 | 98.61 311 | 97.74 129 | 94.01 307 | 98.83 279 | 87.38 312 | 99.83 120 | 98.63 88 | 98.90 144 | 99.44 136 |
|
DP-MVS Recon | | | 99.12 67 | 98.95 75 | 99.65 57 | 99.74 57 | 99.70 28 | 99.27 206 | 99.57 44 | 96.40 233 | 99.42 88 | 99.68 117 | 98.75 44 | 99.80 136 | 97.98 144 | 99.72 83 | 99.44 136 |
|
PatchMatch-RL | | | 98.84 108 | 98.62 115 | 99.52 83 | 99.71 69 | 99.28 82 | 99.06 254 | 99.77 9 | 97.74 129 | 99.50 73 | 99.53 168 | 95.41 145 | 99.84 113 | 97.17 209 | 99.64 98 | 99.44 136 |
|
VDDNet | | | 97.55 231 | 97.02 246 | 99.16 127 | 99.49 126 | 98.12 200 | 99.38 176 | 99.30 221 | 95.35 269 | 99.68 34 | 99.90 7 | 82.62 327 | 99.93 55 | 99.31 25 | 98.13 186 | 99.42 139 |
|
PCF-MVS | | 97.08 14 | 97.66 227 | 97.06 245 | 99.47 91 | 99.61 104 | 99.09 101 | 98.04 325 | 99.25 240 | 91.24 314 | 98.51 240 | 99.70 106 | 94.55 194 | 99.91 72 | 92.76 304 | 99.85 52 | 99.42 139 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
HY-MVS | | 97.30 7 | 98.85 106 | 98.64 111 | 99.47 91 | 99.42 137 | 99.08 102 | 99.62 75 | 99.36 192 | 97.39 160 | 99.28 121 | 99.68 117 | 96.44 118 | 99.92 63 | 98.37 117 | 98.22 176 | 99.40 141 |
|
Fast-Effi-MVS+ | | | 98.70 119 | 98.43 126 | 99.51 85 | 99.51 119 | 99.28 82 | 99.52 114 | 99.47 127 | 96.11 256 | 99.01 179 | 99.34 230 | 96.20 125 | 99.84 113 | 97.88 151 | 98.82 149 | 99.39 142 |
|
diffmvs | | | 98.72 118 | 98.49 124 | 99.43 100 | 99.48 129 | 99.19 90 | 99.62 75 | 99.42 165 | 95.58 267 | 99.37 99 | 99.67 121 | 96.14 126 | 99.74 148 | 98.14 131 | 98.96 137 | 99.37 143 |
|
CANet_DTU | | | 98.97 92 | 98.87 84 | 99.25 119 | 99.33 157 | 98.42 190 | 99.08 249 | 99.30 221 | 99.16 5 | 99.43 85 | 99.75 90 | 95.27 149 | 99.97 11 | 98.56 100 | 99.95 6 | 99.36 144 |
|
EPMVS | | | 97.82 200 | 97.65 192 | 98.35 230 | 98.88 252 | 95.98 273 | 99.49 131 | 94.71 338 | 97.57 143 | 99.26 129 | 99.48 186 | 92.46 254 | 99.71 166 | 97.87 152 | 99.08 128 | 99.35 145 |
|
CostFormer | | | 97.72 217 | 97.73 183 | 97.71 279 | 99.15 199 | 94.02 302 | 99.54 110 | 99.02 266 | 94.67 277 | 99.04 176 | 99.35 227 | 92.35 256 | 99.77 143 | 98.50 107 | 97.94 192 | 99.34 146 |
|
BH-untuned | | | 98.42 133 | 98.36 129 | 98.59 206 | 99.49 126 | 96.70 255 | 99.27 206 | 99.13 253 | 97.24 172 | 98.80 209 | 99.38 213 | 95.75 138 | 99.74 148 | 97.07 214 | 99.16 121 | 99.33 147 |
|
PAPM | | | 97.59 230 | 97.09 244 | 99.07 133 | 99.06 213 | 98.26 194 | 98.30 319 | 99.10 255 | 94.88 273 | 98.08 261 | 99.34 230 | 96.27 123 | 99.64 183 | 89.87 312 | 98.92 142 | 99.31 148 |
|
tpm2 | | | 97.44 242 | 97.34 230 | 97.74 278 | 99.15 199 | 94.36 299 | 99.45 144 | 98.94 273 | 93.45 302 | 98.90 197 | 99.44 198 | 91.35 273 | 99.59 193 | 97.31 200 | 98.07 188 | 99.29 149 |
|
JIA-IIPM | | | 97.50 238 | 97.02 246 | 98.93 152 | 98.73 274 | 97.80 216 | 99.30 196 | 98.97 270 | 91.73 312 | 98.91 195 | 94.86 328 | 95.10 158 | 99.71 166 | 97.58 178 | 97.98 191 | 99.28 150 |
|
LP | | | 97.04 253 | 96.80 249 | 97.77 276 | 98.90 248 | 95.23 287 | 98.97 278 | 99.06 262 | 94.02 292 | 98.09 260 | 99.41 204 | 93.88 218 | 98.82 290 | 90.46 310 | 98.42 168 | 99.26 151 |
|
dp | | | 97.75 212 | 97.80 169 | 97.59 281 | 99.10 207 | 93.71 306 | 99.32 191 | 98.88 283 | 96.48 226 | 99.08 169 | 99.55 164 | 92.67 245 | 99.82 128 | 96.52 241 | 98.58 158 | 99.24 152 |
|
TESTMET0.1,1 | | | 97.55 231 | 97.27 239 | 98.40 227 | 98.93 243 | 96.53 260 | 98.67 303 | 97.61 331 | 96.96 194 | 98.64 233 | 99.28 241 | 88.63 301 | 99.45 202 | 97.30 201 | 99.38 108 | 99.21 153 |
|
DWT-MVSNet_test | | | 97.53 233 | 97.40 221 | 97.93 264 | 99.03 219 | 94.86 293 | 99.57 95 | 98.63 309 | 96.59 217 | 98.36 249 | 98.79 282 | 89.32 291 | 99.74 148 | 98.14 131 | 98.16 185 | 99.20 154 |
|
CR-MVSNet | | | 98.17 148 | 97.93 159 | 98.87 178 | 99.18 189 | 98.49 184 | 99.22 223 | 99.33 212 | 96.96 194 | 99.56 64 | 99.38 213 | 94.33 202 | 99.00 278 | 94.83 273 | 98.58 158 | 99.14 155 |
|
RPMNet | | | 96.61 257 | 95.85 265 | 98.87 178 | 99.18 189 | 98.49 184 | 99.22 223 | 99.08 257 | 88.72 323 | 99.56 64 | 97.38 319 | 94.08 213 | 99.00 278 | 86.87 323 | 98.58 158 | 99.14 155 |
|
testgi | | | 97.65 228 | 97.50 204 | 98.13 253 | 99.36 152 | 96.45 263 | 99.42 160 | 99.48 113 | 97.76 126 | 97.87 269 | 99.45 197 | 91.09 275 | 98.81 291 | 94.53 277 | 98.52 163 | 99.13 157 |
|
test-LLR | | | 98.06 159 | 97.90 160 | 98.55 212 | 98.79 264 | 97.10 232 | 98.67 303 | 97.75 327 | 97.34 162 | 98.61 237 | 98.85 277 | 94.45 198 | 99.45 202 | 97.25 202 | 99.38 108 | 99.10 158 |
|
test-mter | | | 97.49 240 | 97.13 243 | 98.55 212 | 98.79 264 | 97.10 232 | 98.67 303 | 97.75 327 | 96.65 210 | 98.61 237 | 98.85 277 | 88.23 306 | 99.45 202 | 97.25 202 | 99.38 108 | 99.10 158 |
|
IB-MVS | | 95.67 18 | 96.22 272 | 95.44 280 | 98.57 208 | 99.21 182 | 96.70 255 | 98.65 306 | 97.74 329 | 96.71 206 | 97.27 278 | 98.54 293 | 86.03 315 | 99.92 63 | 98.47 110 | 86.30 326 | 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 | | | 98.86 100 | 98.63 112 | 99.54 75 | 99.37 150 | 99.66 34 | 99.45 144 | 99.54 62 | 96.61 213 | 99.01 179 | 99.40 208 | 97.09 100 | 99.86 104 | 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 | 97.90 267 | 99.16 196 | 94.78 294 | 99.31 194 | 99.11 254 | 97.27 168 | 99.45 81 | 99.59 152 | 95.33 146 | 99.84 113 | 98.48 108 | 98.61 155 | 99.09 162 |
|
xiu_mvs_v1_base_debu | | | 99.29 46 | 99.27 40 | 99.34 105 | 99.63 96 | 98.97 117 | 99.12 239 | 99.51 85 | 98.86 31 | 99.84 8 | 99.47 190 | 98.18 74 | 99.99 1 | 99.50 8 | 99.31 113 | 99.08 163 |
|
xiu_mvs_v1_base | | | 99.29 46 | 99.27 40 | 99.34 105 | 99.63 96 | 98.97 117 | 99.12 239 | 99.51 85 | 98.86 31 | 99.84 8 | 99.47 190 | 98.18 74 | 99.99 1 | 99.50 8 | 99.31 113 | 99.08 163 |
|
xiu_mvs_v1_base_debi | | | 99.29 46 | 99.27 40 | 99.34 105 | 99.63 96 | 98.97 117 | 99.12 239 | 99.51 85 | 98.86 31 | 99.84 8 | 99.47 190 | 98.18 74 | 99.99 1 | 99.50 8 | 99.31 113 | 99.08 163 |
|
COLMAP_ROB | | 97.56 6 | 98.86 100 | 98.75 100 | 99.17 126 | 99.88 11 | 98.53 178 | 99.34 189 | 99.59 38 | 97.55 145 | 98.70 223 | 99.89 10 | 95.83 135 | 99.90 84 | 98.10 133 | 99.90 24 | 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 | | | 97.34 245 | 97.29 236 | 97.52 282 | 99.25 178 | 93.73 304 | 99.58 89 | 99.19 248 | 94.00 293 | 98.20 256 | 99.41 204 | 90.74 279 | 99.74 148 | 97.13 210 | 98.07 188 | 99.07 167 |
|
PatchFormer-LS_test | | | 98.01 173 | 98.05 150 | 97.87 268 | 99.15 199 | 94.76 295 | 99.42 160 | 98.93 274 | 97.12 182 | 98.84 206 | 98.59 291 | 93.74 225 | 99.80 136 | 98.55 103 | 98.17 184 | 99.06 168 |
|
OpenMVS | | 96.50 16 | 98.47 129 | 98.12 143 | 99.52 83 | 99.04 217 | 99.53 55 | 99.82 13 | 99.72 11 | 94.56 282 | 98.08 261 | 99.88 14 | 94.73 186 | 99.98 5 | 97.47 191 | 99.76 76 | 99.06 168 |
|
PatchT | | | 97.03 254 | 96.44 255 | 98.79 192 | 98.99 223 | 98.34 191 | 99.16 232 | 99.07 260 | 92.13 308 | 99.52 70 | 97.31 321 | 94.54 195 | 98.98 280 | 88.54 316 | 98.73 154 | 99.03 170 |
|
BH-w/o | | | 98.00 174 | 97.89 164 | 98.32 232 | 99.35 153 | 96.20 271 | 99.01 269 | 98.90 281 | 96.42 230 | 98.38 247 | 99.00 265 | 95.26 151 | 99.72 160 | 96.06 249 | 98.61 155 | 99.03 170 |
|
Fast-Effi-MVS+-dtu | | | 98.77 115 | 98.83 93 | 98.60 205 | 99.41 140 | 96.99 243 | 99.52 114 | 99.49 104 | 98.11 86 | 99.24 136 | 99.34 230 | 96.96 104 | 99.79 139 | 97.95 147 | 99.45 104 | 99.02 172 |
|
XVG-OURS-SEG-HR | | | 98.69 120 | 98.62 115 | 98.89 167 | 99.71 69 | 97.74 218 | 99.12 239 | 99.54 62 | 98.44 62 | 99.42 88 | 99.71 103 | 94.20 206 | 99.92 63 | 98.54 105 | 98.90 144 | 99.00 173 |
|
XVG-OURS | | | 98.73 117 | 98.68 106 | 98.88 174 | 99.70 74 | 97.73 219 | 98.92 287 | 99.55 55 | 98.52 55 | 99.45 81 | 99.84 35 | 95.27 149 | 99.91 72 | 98.08 138 | 98.84 148 | 99.00 173 |
|
tpm cat1 | | | 97.39 244 | 97.36 225 | 97.50 284 | 99.17 194 | 93.73 304 | 99.43 153 | 99.31 219 | 91.27 313 | 98.71 217 | 99.08 258 | 94.31 204 | 99.77 143 | 96.41 245 | 98.50 164 | 99.00 173 |
|
xiu_mvs_v2_base | | | 99.26 51 | 99.25 44 | 99.29 116 | 99.53 116 | 98.91 130 | 99.02 265 | 99.45 148 | 98.80 39 | 99.71 29 | 99.26 244 | 98.94 24 | 99.98 5 | 99.34 22 | 99.23 117 | 98.98 176 |
|
PS-MVSNAJ | | | 99.32 42 | 99.32 26 | 99.30 113 | 99.57 111 | 98.94 125 | 98.97 278 | 99.46 137 | 98.92 28 | 99.71 29 | 99.24 246 | 99.01 11 | 99.98 5 | 99.35 18 | 99.66 95 | 98.97 177 |
|
tpmvs | | | 97.98 175 | 98.02 152 | 97.84 271 | 99.04 217 | 94.73 296 | 99.31 194 | 99.20 245 | 96.10 259 | 98.76 213 | 99.42 201 | 94.94 166 | 99.81 132 | 96.97 220 | 98.45 166 | 98.97 177 |
|
view600 | | | 97.97 178 | 97.66 187 | 98.89 167 | 99.75 47 | 97.81 212 | 99.69 44 | 98.80 289 | 98.02 102 | 99.25 131 | 98.88 273 | 91.95 258 | 99.89 92 | 94.36 282 | 98.29 172 | 98.96 179 |
|
view800 | | | 97.97 178 | 97.66 187 | 98.89 167 | 99.75 47 | 97.81 212 | 99.69 44 | 98.80 289 | 98.02 102 | 99.25 131 | 98.88 273 | 91.95 258 | 99.89 92 | 94.36 282 | 98.29 172 | 98.96 179 |
|
conf0.05thres1000 | | | 97.97 178 | 97.66 187 | 98.89 167 | 99.75 47 | 97.81 212 | 99.69 44 | 98.80 289 | 98.02 102 | 99.25 131 | 98.88 273 | 91.95 258 | 99.89 92 | 94.36 282 | 98.29 172 | 98.96 179 |
|
tfpn | | | 97.97 178 | 97.66 187 | 98.89 167 | 99.75 47 | 97.81 212 | 99.69 44 | 98.80 289 | 98.02 102 | 99.25 131 | 98.88 273 | 91.95 258 | 99.89 92 | 94.36 282 | 98.29 172 | 98.96 179 |
|
mvs-test1 | | | 98.86 100 | 98.84 90 | 98.89 167 | 99.33 157 | 97.77 217 | 99.44 148 | 99.30 221 | 98.47 57 | 99.10 164 | 99.43 199 | 96.78 108 | 99.95 33 | 98.73 77 | 99.02 132 | 98.96 179 |
|
thres600view7 | | | 97.86 192 | 97.51 202 | 98.92 157 | 99.72 65 | 97.95 207 | 99.59 84 | 98.74 297 | 97.94 109 | 99.27 125 | 98.62 288 | 91.75 264 | 99.86 104 | 93.73 294 | 98.19 179 | 98.96 179 |
|
thres400 | | | 97.77 207 | 97.38 223 | 98.92 157 | 99.69 76 | 97.96 205 | 99.50 123 | 98.73 304 | 97.83 118 | 99.17 154 | 98.45 295 | 91.67 268 | 99.83 120 | 93.22 298 | 98.18 180 | 98.96 179 |
|
TR-MVS | | | 97.76 208 | 97.41 220 | 98.82 188 | 99.06 213 | 97.87 209 | 98.87 292 | 98.56 313 | 96.63 212 | 98.68 225 | 99.22 248 | 92.49 250 | 99.65 181 | 95.40 264 | 97.79 195 | 98.95 186 |
|
test0.0.03 1 | | | 97.71 220 | 97.42 219 | 98.56 210 | 98.41 296 | 97.82 211 | 98.78 296 | 98.63 309 | 97.34 162 | 98.05 265 | 98.98 269 | 94.45 198 | 98.98 280 | 95.04 270 | 97.15 229 | 98.89 187 |
|
cascas | | | 97.69 221 | 97.43 218 | 98.48 217 | 98.60 288 | 97.30 223 | 98.18 323 | 99.39 178 | 92.96 304 | 98.41 245 | 98.78 284 | 93.77 222 | 99.27 242 | 98.16 130 | 98.61 155 | 98.86 188 |
|
1314 | | | 98.68 121 | 98.54 123 | 99.11 131 | 98.89 251 | 98.65 167 | 99.27 206 | 99.49 104 | 96.89 198 | 97.99 266 | 99.56 161 | 97.72 87 | 99.83 120 | 97.74 165 | 99.27 116 | 98.84 189 |
|
PS-MVSNAJss | | | 98.92 95 | 98.92 77 | 98.90 165 | 98.78 268 | 98.53 178 | 99.78 22 | 99.54 62 | 98.07 93 | 99.00 186 | 99.76 85 | 99.01 11 | 99.37 216 | 99.13 39 | 97.23 225 | 98.81 190 |
|
pcd1.5k->3k | | | 40.85 317 | 43.49 319 | 32.93 331 | 98.95 235 | 0.00 348 | 0.00 339 | 99.53 72 | 0.00 343 | 0.00 344 | 0.27 345 | 95.32 147 | 0.00 346 | 0.00 343 | 97.30 223 | 98.80 191 |
|
FC-MVSNet-test | | | 98.75 116 | 98.62 115 | 99.15 129 | 99.08 210 | 99.45 66 | 99.86 8 | 99.60 35 | 98.23 75 | 98.70 223 | 99.82 44 | 96.80 107 | 99.22 254 | 99.07 44 | 96.38 240 | 98.79 192 |
|
nrg030 | | | 98.64 125 | 98.42 127 | 99.28 118 | 99.05 216 | 99.69 29 | 99.81 15 | 99.46 137 | 98.04 99 | 99.01 179 | 99.82 44 | 96.69 113 | 99.38 213 | 99.34 22 | 94.59 278 | 98.78 193 |
|
FIs | | | 98.78 113 | 98.63 112 | 99.23 123 | 99.18 189 | 99.54 52 | 99.83 12 | 99.59 38 | 98.28 70 | 98.79 210 | 99.81 53 | 96.75 111 | 99.37 216 | 99.08 43 | 96.38 240 | 98.78 193 |
|
EU-MVSNet | | | 97.98 175 | 98.03 151 | 97.81 274 | 98.72 276 | 96.65 258 | 99.66 58 | 99.66 25 | 98.09 89 | 98.35 250 | 99.82 44 | 95.25 152 | 98.01 309 | 97.41 196 | 95.30 258 | 98.78 193 |
|
jajsoiax | | | 98.43 132 | 98.28 136 | 98.88 174 | 98.60 288 | 98.43 188 | 99.82 13 | 99.53 72 | 98.19 76 | 98.63 234 | 99.80 64 | 93.22 230 | 99.44 207 | 99.22 31 | 97.50 210 | 98.77 196 |
|
mvs_tets | | | 98.40 135 | 98.23 138 | 98.91 161 | 98.67 283 | 98.51 183 | 99.66 58 | 99.53 72 | 98.19 76 | 98.65 232 | 99.81 53 | 92.75 238 | 99.44 207 | 99.31 25 | 97.48 214 | 98.77 196 |
|
XXY-MVS | | | 98.38 136 | 98.09 146 | 99.24 121 | 99.26 176 | 99.32 77 | 99.56 102 | 99.55 55 | 97.45 154 | 98.71 217 | 99.83 37 | 93.23 229 | 99.63 188 | 98.88 57 | 96.32 242 | 98.76 198 |
|
v7n | | | 97.87 191 | 97.52 200 | 98.92 157 | 98.76 272 | 98.58 175 | 99.84 9 | 99.46 137 | 96.20 247 | 98.91 195 | 99.70 106 | 94.89 172 | 99.44 207 | 96.03 250 | 93.89 291 | 98.75 199 |
|
PS-CasMVS | | | 97.93 184 | 97.59 197 | 98.95 148 | 98.99 223 | 99.06 104 | 99.68 53 | 99.52 76 | 97.13 180 | 98.31 252 | 99.68 117 | 92.44 255 | 99.05 272 | 98.51 106 | 94.08 287 | 98.75 199 |
|
test_djsdf | | | 98.67 122 | 98.57 121 | 98.98 143 | 98.70 279 | 98.91 130 | 99.88 1 | 99.46 137 | 97.55 145 | 99.22 143 | 99.88 14 | 95.73 139 | 99.28 239 | 99.03 46 | 97.62 200 | 98.75 199 |
|
Effi-MVS+-dtu | | | 98.78 113 | 98.89 82 | 98.47 219 | 99.33 157 | 96.91 249 | 99.57 95 | 99.30 221 | 98.47 57 | 99.41 90 | 98.99 266 | 96.78 108 | 99.74 148 | 98.73 77 | 99.38 108 | 98.74 202 |
|
CP-MVSNet | | | 98.09 157 | 97.78 172 | 99.01 139 | 98.97 230 | 99.24 87 | 99.67 55 | 99.46 137 | 97.25 170 | 98.48 243 | 99.64 135 | 93.79 221 | 99.06 271 | 98.63 88 | 94.10 286 | 98.74 202 |
|
VPA-MVSNet | | | 98.29 140 | 97.95 157 | 99.30 113 | 99.16 196 | 99.54 52 | 99.50 123 | 99.58 43 | 98.27 71 | 99.35 106 | 99.37 216 | 92.53 249 | 99.65 181 | 99.35 18 | 94.46 279 | 98.72 204 |
|
PEN-MVS | | | 97.76 208 | 97.44 215 | 98.72 197 | 98.77 271 | 98.54 177 | 99.78 22 | 99.51 85 | 97.06 189 | 98.29 254 | 99.64 135 | 92.63 246 | 98.89 289 | 98.09 134 | 93.16 297 | 98.72 204 |
|
VPNet | | | 97.84 195 | 97.44 215 | 99.01 139 | 99.21 182 | 98.94 125 | 99.48 136 | 99.57 44 | 98.38 64 | 99.28 121 | 99.73 98 | 88.89 295 | 99.39 212 | 99.19 33 | 93.27 296 | 98.71 206 |
|
EI-MVSNet | | | 98.67 122 | 98.67 107 | 98.68 200 | 99.35 153 | 97.97 204 | 99.50 123 | 99.38 184 | 96.93 197 | 99.20 148 | 99.83 37 | 97.87 81 | 99.36 220 | 98.38 116 | 97.56 205 | 98.71 206 |
|
WR-MVS | | | 98.06 159 | 97.73 183 | 99.06 134 | 98.86 258 | 99.25 86 | 99.19 229 | 99.35 196 | 97.30 166 | 98.66 226 | 99.43 199 | 93.94 216 | 99.21 258 | 98.58 95 | 94.28 282 | 98.71 206 |
|
IterMVS-LS | | | 98.46 130 | 98.42 127 | 98.58 207 | 99.59 108 | 98.00 202 | 99.37 178 | 99.43 164 | 96.94 196 | 99.07 170 | 99.59 152 | 97.87 81 | 99.03 275 | 98.32 123 | 95.62 253 | 98.71 206 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
v144192 | | | 97.92 187 | 97.60 196 | 98.87 178 | 98.83 261 | 98.65 167 | 99.55 107 | 99.34 204 | 96.20 247 | 99.32 111 | 99.40 208 | 94.36 201 | 99.26 247 | 96.37 246 | 95.03 265 | 98.70 210 |
|
v748 | | | 97.52 234 | 97.23 240 | 98.41 226 | 98.69 280 | 97.23 229 | 99.87 4 | 99.45 148 | 95.72 264 | 98.51 240 | 99.53 168 | 94.13 210 | 99.30 236 | 96.78 230 | 92.39 305 | 98.70 210 |
|
v1240 | | | 97.69 221 | 97.32 233 | 98.79 192 | 98.85 259 | 98.43 188 | 99.48 136 | 99.36 192 | 96.11 256 | 99.27 125 | 99.36 223 | 93.76 223 | 99.24 250 | 94.46 279 | 95.23 259 | 98.70 210 |
|
DTE-MVSNet | | | 97.51 237 | 97.19 242 | 98.46 220 | 98.63 286 | 98.13 199 | 99.84 9 | 99.48 113 | 96.68 208 | 97.97 267 | 99.67 121 | 92.92 234 | 98.56 295 | 96.88 227 | 92.60 304 | 98.70 210 |
|
TranMVSNet+NR-MVSNet | | | 97.93 184 | 97.66 187 | 98.76 195 | 98.78 268 | 98.62 171 | 99.65 68 | 99.49 104 | 97.76 126 | 98.49 242 | 99.60 150 | 94.23 205 | 98.97 287 | 98.00 143 | 92.90 299 | 98.70 210 |
|
v1921920 | | | 97.80 203 | 97.45 211 | 98.84 186 | 98.80 262 | 98.53 178 | 99.52 114 | 99.34 204 | 96.15 253 | 99.24 136 | 99.47 190 | 93.98 215 | 99.29 238 | 95.40 264 | 95.13 263 | 98.69 215 |
|
v1192 | | | 97.81 201 | 97.44 215 | 98.91 161 | 98.88 252 | 98.68 163 | 99.51 118 | 99.34 204 | 96.18 249 | 99.20 148 | 99.34 230 | 94.03 214 | 99.36 220 | 95.32 266 | 95.18 260 | 98.69 215 |
|
v2v482 | | | 98.06 159 | 97.77 176 | 98.92 157 | 98.90 248 | 98.82 147 | 99.57 95 | 99.36 192 | 96.65 210 | 99.19 151 | 99.35 227 | 94.20 206 | 99.25 248 | 97.72 170 | 94.97 266 | 98.69 215 |
|
UniMVSNet_NR-MVSNet | | | 98.22 143 | 97.97 155 | 98.96 146 | 98.92 245 | 98.98 114 | 99.48 136 | 99.53 72 | 97.76 126 | 98.71 217 | 99.46 194 | 96.43 119 | 99.22 254 | 98.57 97 | 92.87 301 | 98.69 215 |
|
OurMVSNet-221017-0 | | | 97.88 190 | 97.77 176 | 98.19 250 | 98.71 278 | 96.53 260 | 99.88 1 | 99.00 267 | 97.79 123 | 98.78 211 | 99.94 3 | 91.68 267 | 99.35 223 | 97.21 204 | 96.99 231 | 98.69 215 |
|
gg-mvs-nofinetune | | | 96.17 274 | 95.32 281 | 98.73 196 | 98.79 264 | 98.14 198 | 99.38 176 | 94.09 339 | 91.07 316 | 98.07 264 | 91.04 334 | 89.62 290 | 99.35 223 | 96.75 231 | 99.09 127 | 98.68 220 |
|
v1144 | | | 97.98 175 | 97.69 186 | 98.85 185 | 98.87 255 | 98.66 166 | 99.54 110 | 99.35 196 | 96.27 241 | 99.23 141 | 99.35 227 | 94.67 189 | 99.23 251 | 96.73 232 | 95.16 261 | 98.68 220 |
|
v1141 | | | 98.05 165 | 97.76 179 | 98.91 161 | 98.91 247 | 98.78 158 | 99.57 95 | 99.35 196 | 96.41 232 | 99.23 141 | 99.36 223 | 94.93 168 | 99.27 242 | 97.38 197 | 94.72 272 | 98.68 220 |
|
testing_2 | | | 94.44 291 | 92.93 297 | 98.98 143 | 94.16 324 | 99.00 112 | 99.42 160 | 99.28 232 | 96.60 215 | 84.86 327 | 96.84 322 | 70.91 330 | 99.27 242 | 98.23 126 | 96.08 246 | 98.68 220 |
|
divwei89l23v2f112 | | | 98.06 159 | 97.78 172 | 98.91 161 | 98.90 248 | 98.77 159 | 99.57 95 | 99.35 196 | 96.45 227 | 99.24 136 | 99.37 216 | 94.92 169 | 99.27 242 | 97.50 187 | 94.71 274 | 98.68 220 |
|
v1 | | | 98.05 165 | 97.76 179 | 98.93 152 | 98.92 245 | 98.80 154 | 99.57 95 | 99.35 196 | 96.39 234 | 99.28 121 | 99.36 223 | 94.86 174 | 99.32 230 | 97.38 197 | 94.72 272 | 98.68 220 |
|
DU-MVS | | | 98.08 158 | 97.79 170 | 98.96 146 | 98.87 255 | 98.98 114 | 99.41 164 | 99.45 148 | 97.87 112 | 98.71 217 | 99.50 177 | 94.82 176 | 99.22 254 | 98.57 97 | 92.87 301 | 98.68 220 |
|
NR-MVSNet | | | 97.97 178 | 97.61 195 | 99.02 138 | 98.87 255 | 99.26 85 | 99.47 140 | 99.42 165 | 97.63 139 | 97.08 282 | 99.50 177 | 95.07 159 | 99.13 264 | 97.86 153 | 93.59 293 | 98.68 220 |
|
LPG-MVS_test | | | 98.22 143 | 98.13 142 | 98.49 215 | 99.33 157 | 97.05 238 | 99.58 89 | 99.55 55 | 97.46 151 | 99.24 136 | 99.83 37 | 92.58 247 | 99.72 160 | 98.09 134 | 97.51 208 | 98.68 220 |
|
LGP-MVS_train | | | | | 98.49 215 | 99.33 157 | 97.05 238 | | 99.55 55 | 97.46 151 | 99.24 136 | 99.83 37 | 92.58 247 | 99.72 160 | 98.09 134 | 97.51 208 | 98.68 220 |
|
LTVRE_ROB | | 97.16 12 | 98.02 170 | 97.90 160 | 98.40 227 | 99.23 179 | 96.80 253 | 99.70 42 | 99.60 35 | 97.12 182 | 98.18 257 | 99.70 106 | 91.73 266 | 99.72 160 | 98.39 114 | 97.45 215 | 98.68 220 |
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 | | | | | 98.06 255 | 99.57 111 | 96.36 266 | | 99.49 104 | 97.18 176 | 98.71 217 | 99.72 102 | 92.70 244 | 99.14 261 | 97.44 194 | 95.86 249 | 98.67 231 |
|
v1neww | | | 98.12 153 | 97.84 166 | 98.93 152 | 98.97 230 | 98.81 149 | 99.66 58 | 99.35 196 | 96.49 220 | 99.29 117 | 99.37 216 | 95.02 161 | 99.32 230 | 97.73 166 | 94.73 270 | 98.67 231 |
|
v7new | | | 98.12 153 | 97.84 166 | 98.93 152 | 98.97 230 | 98.81 149 | 99.66 58 | 99.35 196 | 96.49 220 | 99.29 117 | 99.37 216 | 95.02 161 | 99.32 230 | 97.73 166 | 94.73 270 | 98.67 231 |
|
pm-mvs1 | | | 97.68 223 | 97.28 237 | 98.88 174 | 99.06 213 | 98.62 171 | 99.50 123 | 99.45 148 | 96.32 236 | 97.87 269 | 99.79 72 | 92.47 251 | 99.35 223 | 97.54 183 | 93.54 294 | 98.67 231 |
|
v6 | | | 98.12 153 | 97.84 166 | 98.94 149 | 98.94 238 | 98.83 140 | 99.66 58 | 99.34 204 | 96.49 220 | 99.30 113 | 99.37 216 | 94.95 165 | 99.34 226 | 97.77 161 | 94.74 269 | 98.67 231 |
|
v10 | | | 97.85 193 | 97.52 200 | 98.86 182 | 98.99 223 | 98.67 164 | 99.75 34 | 99.41 168 | 95.70 265 | 98.98 188 | 99.41 204 | 94.75 185 | 99.23 251 | 96.01 251 | 94.63 277 | 98.67 231 |
|
HQP_MVS | | | 98.27 142 | 98.22 139 | 98.44 224 | 99.29 169 | 96.97 245 | 99.39 171 | 99.47 127 | 98.97 22 | 99.11 161 | 99.61 147 | 92.71 242 | 99.69 175 | 97.78 159 | 97.63 198 | 98.67 231 |
|
plane_prior5 | | | | | | | | | 99.47 127 | | | | | 99.69 175 | 97.78 159 | 97.63 198 | 98.67 231 |
|
SixPastTwentyTwo | | | 97.50 238 | 97.33 232 | 98.03 256 | 98.65 284 | 96.23 270 | 99.77 24 | 98.68 307 | 97.14 179 | 97.90 268 | 99.93 4 | 90.45 280 | 99.18 260 | 97.00 217 | 96.43 239 | 98.67 231 |
|
IterMVS | | | 97.83 197 | 97.77 176 | 98.02 258 | 99.58 109 | 96.27 269 | 99.02 265 | 99.48 113 | 97.22 174 | 98.71 217 | 99.70 106 | 92.75 238 | 99.13 264 | 97.46 192 | 96.00 247 | 98.67 231 |
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 | 98.44 224 | 99.41 140 | 96.96 247 | 99.60 82 | 99.56 48 | 98.09 89 | 98.15 258 | 99.91 5 | 90.87 278 | 99.70 172 | 98.88 57 | 97.45 215 | 98.67 231 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
v8 | | | 97.95 183 | 97.63 194 | 98.93 152 | 98.95 235 | 98.81 149 | 99.80 19 | 99.41 168 | 96.03 260 | 99.10 164 | 99.42 201 | 94.92 169 | 99.30 236 | 96.94 223 | 94.08 287 | 98.66 242 |
|
v7 | | | 98.05 165 | 97.78 172 | 98.87 178 | 98.99 223 | 98.67 164 | 99.64 70 | 99.34 204 | 96.31 238 | 99.29 117 | 99.51 175 | 94.78 179 | 99.27 242 | 97.03 215 | 95.15 262 | 98.66 242 |
|
UniMVSNet (Re) | | | 98.29 140 | 98.00 153 | 99.13 130 | 99.00 222 | 99.36 74 | 99.49 131 | 99.51 85 | 97.95 108 | 98.97 189 | 99.13 254 | 96.30 122 | 99.38 213 | 98.36 119 | 93.34 295 | 98.66 242 |
|
pmmvs6 | | | 96.53 259 | 96.09 260 | 97.82 273 | 98.69 280 | 95.47 283 | 99.37 178 | 99.47 127 | 93.46 301 | 97.41 276 | 99.78 77 | 87.06 313 | 99.33 227 | 96.92 225 | 92.70 303 | 98.65 245 |
|
K. test v3 | | | 97.10 252 | 96.79 250 | 98.01 259 | 98.72 276 | 96.33 267 | 99.87 4 | 97.05 333 | 97.59 140 | 96.16 292 | 99.80 64 | 88.71 297 | 99.04 273 | 96.69 235 | 96.55 237 | 98.65 245 |
|
YYNet1 | | | 95.36 284 | 94.51 289 | 97.92 265 | 97.89 302 | 97.10 232 | 99.10 247 | 99.23 242 | 93.26 303 | 80.77 331 | 99.04 263 | 92.81 237 | 98.02 308 | 94.30 287 | 94.18 285 | 98.64 247 |
|
MDA-MVSNet_test_wron | | | 95.45 282 | 94.60 287 | 98.01 259 | 98.16 300 | 97.21 230 | 99.11 245 | 99.24 241 | 93.49 300 | 80.73 332 | 98.98 269 | 93.02 231 | 98.18 297 | 94.22 291 | 94.45 280 | 98.64 247 |
|
Baseline_NR-MVSNet | | | 97.76 208 | 97.45 211 | 98.68 200 | 99.09 209 | 98.29 192 | 99.41 164 | 98.85 285 | 95.65 266 | 98.63 234 | 99.67 121 | 94.82 176 | 99.10 269 | 98.07 140 | 92.89 300 | 98.64 247 |
|
HQP4-MVS | | | | | | | | | | | 98.66 226 | | | 99.64 183 | | | 98.64 247 |
|
HQP-MVS | | | 98.02 170 | 97.90 160 | 98.37 229 | 99.19 186 | 96.83 250 | 98.98 275 | 99.39 178 | 98.24 72 | 98.66 226 | 99.40 208 | 92.47 251 | 99.64 183 | 97.19 206 | 97.58 203 | 98.64 247 |
|
ACMM | | 97.58 5 | 98.37 137 | 98.34 131 | 98.48 217 | 99.41 140 | 97.10 232 | 99.56 102 | 99.45 148 | 98.53 54 | 99.04 176 | 99.85 26 | 93.00 232 | 99.71 166 | 98.74 75 | 97.45 215 | 98.64 247 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
pmmvs5 | | | 97.52 234 | 97.30 235 | 98.16 252 | 98.57 290 | 96.73 254 | 99.27 206 | 98.90 281 | 96.14 254 | 98.37 248 | 99.53 168 | 91.54 272 | 99.14 261 | 97.51 186 | 95.87 248 | 98.63 253 |
|
v148 | | | 97.79 205 | 97.55 198 | 98.50 214 | 98.74 273 | 97.72 220 | 99.54 110 | 99.33 212 | 96.26 242 | 98.90 197 | 99.51 175 | 94.68 188 | 99.14 261 | 97.83 155 | 93.15 298 | 98.63 253 |
|
MDA-MVSNet-bldmvs | | | 94.96 287 | 93.98 292 | 97.92 265 | 98.24 299 | 97.27 225 | 99.15 235 | 99.33 212 | 93.80 296 | 80.09 333 | 99.03 264 | 88.31 305 | 97.86 313 | 93.49 296 | 94.36 281 | 98.62 255 |
|
TransMVSNet (Re) | | | 97.15 250 | 96.58 253 | 98.86 182 | 99.12 202 | 98.85 136 | 99.49 131 | 98.91 279 | 95.48 268 | 97.16 281 | 99.80 64 | 93.38 227 | 99.11 267 | 94.16 292 | 91.73 306 | 98.62 255 |
|
lessismore_v0 | | | | | 97.79 275 | 98.69 280 | 95.44 285 | | 94.75 337 | | 95.71 296 | 99.87 19 | 88.69 298 | 99.32 230 | 95.89 252 | 94.93 268 | 98.62 255 |
|
MVSTER | | | 98.49 128 | 98.32 133 | 99.00 141 | 99.35 153 | 99.02 108 | 99.54 110 | 99.38 184 | 97.41 158 | 99.20 148 | 99.73 98 | 93.86 220 | 99.36 220 | 98.87 61 | 97.56 205 | 98.62 255 |
|
GBi-Net | | | 97.68 223 | 97.48 206 | 98.29 235 | 99.51 119 | 97.26 226 | 99.43 153 | 99.48 113 | 96.49 220 | 99.07 170 | 99.32 235 | 90.26 282 | 98.98 280 | 97.10 211 | 96.65 233 | 98.62 255 |
|
test1 | | | 97.68 223 | 97.48 206 | 98.29 235 | 99.51 119 | 97.26 226 | 99.43 153 | 99.48 113 | 96.49 220 | 99.07 170 | 99.32 235 | 90.26 282 | 98.98 280 | 97.10 211 | 96.65 233 | 98.62 255 |
|
FMVSNet1 | | | 96.84 255 | 96.36 256 | 98.29 235 | 99.32 164 | 97.26 226 | 99.43 153 | 99.48 113 | 95.11 271 | 98.55 239 | 99.32 235 | 83.95 324 | 98.98 280 | 95.81 254 | 96.26 243 | 98.62 255 |
|
ACMP | | 97.20 11 | 98.06 159 | 97.94 158 | 98.45 221 | 99.37 150 | 97.01 241 | 99.44 148 | 99.49 104 | 97.54 148 | 98.45 244 | 99.79 72 | 91.95 258 | 99.72 160 | 97.91 149 | 97.49 213 | 98.62 255 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
ACMH+ | | 97.24 10 | 97.92 187 | 97.78 172 | 98.32 232 | 99.46 131 | 96.68 257 | 99.56 102 | 99.54 62 | 98.41 63 | 97.79 273 | 99.87 19 | 90.18 285 | 99.66 179 | 98.05 142 | 97.18 228 | 98.62 255 |
|
OPM-MVS | | | 98.19 147 | 98.10 144 | 98.45 221 | 98.88 252 | 97.07 236 | 99.28 203 | 99.38 184 | 98.57 52 | 99.22 143 | 99.81 53 | 92.12 257 | 99.66 179 | 98.08 138 | 97.54 207 | 98.61 264 |
|
WR-MVS_H | | | 98.13 151 | 97.87 165 | 98.90 165 | 99.02 220 | 98.84 137 | 99.70 42 | 99.59 38 | 97.27 168 | 98.40 246 | 99.19 250 | 95.53 142 | 99.23 251 | 98.34 120 | 93.78 292 | 98.61 264 |
|
MIMVSNet1 | | | 95.51 281 | 95.04 284 | 96.92 293 | 97.38 309 | 95.60 277 | 99.52 114 | 99.50 99 | 93.65 297 | 96.97 286 | 99.17 251 | 85.28 319 | 96.56 324 | 88.36 317 | 95.55 255 | 98.60 266 |
|
test2356 | | | 94.07 295 | 94.46 290 | 92.89 309 | 95.18 320 | 86.13 324 | 97.60 329 | 99.06 262 | 93.61 298 | 96.15 294 | 98.28 298 | 85.60 318 | 93.95 331 | 86.68 324 | 98.00 190 | 98.59 267 |
|
test1235678 | | | 92.91 298 | 93.30 295 | 91.71 315 | 93.14 327 | 83.01 328 | 98.75 299 | 98.58 312 | 92.80 306 | 92.45 317 | 97.91 302 | 88.51 303 | 93.54 332 | 82.26 328 | 95.35 257 | 98.59 267 |
|
N_pmnet | | | 94.95 288 | 95.83 266 | 92.31 312 | 98.47 294 | 79.33 334 | 99.12 239 | 92.81 344 | 93.87 295 | 97.68 274 | 99.13 254 | 93.87 219 | 99.01 277 | 91.38 308 | 96.19 244 | 98.59 267 |
|
FMVSNet2 | | | 97.72 217 | 97.36 225 | 98.80 191 | 99.51 119 | 98.84 137 | 99.45 144 | 99.42 165 | 96.49 220 | 98.86 205 | 99.29 240 | 90.26 282 | 98.98 280 | 96.44 243 | 96.56 236 | 98.58 270 |
|
anonymousdsp | | | 98.44 131 | 98.28 136 | 98.94 149 | 98.50 293 | 98.96 121 | 99.77 24 | 99.50 99 | 97.07 187 | 98.87 200 | 99.77 82 | 94.76 184 | 99.28 239 | 98.66 85 | 97.60 201 | 98.57 271 |
|
FMVSNet3 | | | 98.03 168 | 97.76 179 | 98.84 186 | 99.39 147 | 98.98 114 | 99.40 170 | 99.38 184 | 96.67 209 | 99.07 170 | 99.28 241 | 92.93 233 | 98.98 280 | 97.10 211 | 96.65 233 | 98.56 272 |
|
XVG-ACMP-BASELINE | | | 97.83 197 | 97.71 185 | 98.20 249 | 99.11 204 | 96.33 267 | 99.41 164 | 99.52 76 | 98.06 97 | 99.05 175 | 99.50 177 | 89.64 289 | 99.73 156 | 97.73 166 | 97.38 221 | 98.53 273 |
|
Patchmtry | | | 97.75 212 | 97.40 221 | 98.81 189 | 99.10 207 | 98.87 133 | 99.11 245 | 99.33 212 | 94.83 274 | 98.81 208 | 99.38 213 | 94.33 202 | 99.02 276 | 96.10 248 | 95.57 254 | 98.53 273 |
|
USDC | | | 97.34 245 | 97.20 241 | 97.75 277 | 99.07 211 | 95.20 288 | 98.51 312 | 99.04 264 | 97.99 107 | 98.31 252 | 99.86 22 | 89.02 293 | 99.55 196 | 95.67 259 | 97.36 222 | 98.49 275 |
|
CLD-MVS | | | 98.16 149 | 98.10 144 | 98.33 231 | 99.29 169 | 96.82 252 | 98.75 299 | 99.44 156 | 97.83 118 | 99.13 157 | 99.55 164 | 92.92 234 | 99.67 177 | 98.32 123 | 97.69 197 | 98.48 276 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
Anonymous20231206 | | | 96.22 272 | 96.03 261 | 96.79 296 | 97.31 312 | 94.14 301 | 99.63 72 | 99.08 257 | 96.17 250 | 97.04 283 | 99.06 261 | 93.94 216 | 97.76 316 | 86.96 322 | 95.06 264 | 98.47 277 |
|
FMVSNet5 | | | 96.43 261 | 96.19 258 | 97.15 287 | 99.11 204 | 95.89 275 | 99.32 191 | 99.52 76 | 94.47 286 | 98.34 251 | 99.07 259 | 87.54 310 | 97.07 320 | 92.61 305 | 95.72 251 | 98.47 277 |
|
pmmvs4 | | | 98.13 151 | 97.90 160 | 98.81 189 | 98.61 287 | 98.87 133 | 98.99 271 | 99.21 244 | 96.44 228 | 99.06 174 | 99.58 155 | 95.90 133 | 99.11 267 | 97.18 208 | 96.11 245 | 98.46 279 |
|
V42 | | | 98.06 159 | 97.79 170 | 98.86 182 | 98.98 227 | 98.84 137 | 99.69 44 | 99.34 204 | 96.53 219 | 99.30 113 | 99.37 216 | 94.67 189 | 99.32 230 | 97.57 180 | 94.66 275 | 98.42 280 |
|
PVSNet_BlendedMVS | | | 98.86 100 | 98.80 94 | 99.03 137 | 99.76 41 | 98.79 156 | 99.28 203 | 99.91 3 | 97.42 157 | 99.67 40 | 99.37 216 | 97.53 89 | 99.88 99 | 98.98 51 | 97.29 224 | 98.42 280 |
|
UnsupCasMVSNet_eth | | | 96.44 260 | 96.12 259 | 97.40 286 | 98.65 284 | 95.65 276 | 99.36 182 | 99.51 85 | 97.13 180 | 96.04 295 | 98.99 266 | 88.40 304 | 98.17 298 | 96.71 233 | 90.27 309 | 98.40 282 |
|
TinyColmap | | | 97.12 251 | 96.89 248 | 97.83 272 | 99.07 211 | 95.52 282 | 98.57 309 | 98.74 297 | 97.58 142 | 97.81 272 | 99.79 72 | 88.16 307 | 99.56 194 | 95.10 268 | 97.21 226 | 98.39 283 |
|
thres100view900 | | | 97.76 208 | 97.45 211 | 98.69 199 | 99.72 65 | 97.86 210 | 99.59 84 | 98.74 297 | 97.93 110 | 99.26 129 | 98.62 288 | 91.75 264 | 99.83 120 | 93.22 298 | 98.18 180 | 98.37 284 |
|
tfpn200view9 | | | 97.72 217 | 97.38 223 | 98.72 197 | 99.69 76 | 97.96 205 | 99.50 123 | 98.73 304 | 97.83 118 | 99.17 154 | 98.45 295 | 91.67 268 | 99.83 120 | 93.22 298 | 98.18 180 | 98.37 284 |
|
testus | | | 94.61 289 | 95.30 282 | 92.54 311 | 96.44 315 | 84.18 326 | 98.36 315 | 99.03 265 | 94.18 291 | 96.49 288 | 98.57 292 | 88.74 296 | 95.09 329 | 87.41 320 | 98.45 166 | 98.36 286 |
|
tfpnnormal | | | 97.84 195 | 97.47 208 | 98.98 143 | 99.20 184 | 99.22 89 | 99.64 70 | 99.61 32 | 96.32 236 | 98.27 255 | 99.70 106 | 93.35 228 | 99.44 207 | 95.69 257 | 95.40 256 | 98.27 287 |
|
test20.03 | | | 96.12 275 | 95.96 264 | 96.63 297 | 97.44 308 | 95.45 284 | 99.51 118 | 99.38 184 | 96.55 218 | 96.16 292 | 99.25 245 | 93.76 223 | 96.17 325 | 87.35 321 | 94.22 284 | 98.27 287 |
|
ITE_SJBPF | | | | | 98.08 254 | 99.29 169 | 96.37 265 | | 98.92 276 | 98.34 66 | 98.83 207 | 99.75 90 | 91.09 275 | 99.62 189 | 95.82 253 | 97.40 219 | 98.25 289 |
|
EG-PatchMatch MVS | | | 95.97 277 | 95.69 271 | 96.81 295 | 97.78 304 | 92.79 312 | 99.16 232 | 98.93 274 | 96.16 251 | 94.08 304 | 99.22 248 | 82.72 326 | 99.47 200 | 95.67 259 | 97.50 210 | 98.17 290 |
|
TDRefinement | | | 95.42 283 | 94.57 288 | 97.97 262 | 89.83 333 | 96.11 272 | 99.48 136 | 98.75 294 | 96.74 204 | 96.68 287 | 99.88 14 | 88.65 300 | 99.71 166 | 98.37 117 | 82.74 329 | 98.09 291 |
|
API-MVS | | | 99.04 82 | 99.03 63 | 99.06 134 | 99.40 145 | 99.31 80 | 99.55 107 | 99.56 48 | 98.54 53 | 99.33 110 | 99.39 212 | 98.76 41 | 99.78 141 | 96.98 219 | 99.78 72 | 98.07 292 |
|
v52 | | | 97.79 205 | 97.50 204 | 98.66 203 | 98.80 262 | 98.62 171 | 99.87 4 | 99.44 156 | 95.87 262 | 99.01 179 | 99.46 194 | 94.44 200 | 99.33 227 | 96.65 239 | 93.96 290 | 98.05 293 |
|
V4 | | | 97.80 203 | 97.51 202 | 98.67 202 | 98.79 264 | 98.63 169 | 99.87 4 | 99.44 156 | 95.87 262 | 99.01 179 | 99.46 194 | 94.52 196 | 99.33 227 | 96.64 240 | 93.97 289 | 98.05 293 |
|
new_pmnet | | | 96.38 265 | 96.03 261 | 97.41 285 | 98.13 301 | 95.16 291 | 99.05 256 | 99.20 245 | 93.94 294 | 97.39 277 | 98.79 282 | 91.61 271 | 99.04 273 | 90.43 311 | 95.77 250 | 98.05 293 |
|
thres200 | | | 97.61 229 | 97.28 237 | 98.62 204 | 99.64 93 | 98.03 201 | 99.26 214 | 98.74 297 | 97.68 136 | 99.09 168 | 98.32 297 | 91.66 270 | 99.81 132 | 92.88 303 | 98.22 176 | 98.03 296 |
|
DeepMVS_CX | | | | | 93.34 307 | 99.29 169 | 82.27 331 | | 99.22 243 | 85.15 325 | 96.33 290 | 99.05 262 | 90.97 277 | 99.73 156 | 93.57 295 | 97.77 196 | 98.01 297 |
|
GG-mvs-BLEND | | | | | 98.45 221 | 98.55 291 | 98.16 197 | 99.43 153 | 93.68 340 | | 97.23 279 | 98.46 294 | 89.30 292 | 99.22 254 | 95.43 263 | 98.22 176 | 97.98 298 |
|
pmmvs3 | | | 94.09 294 | 93.25 296 | 96.60 298 | 94.76 322 | 94.49 297 | 98.92 287 | 98.18 322 | 89.66 318 | 96.48 289 | 98.06 300 | 86.28 314 | 97.33 319 | 89.68 313 | 87.20 320 | 97.97 299 |
|
LF4IMVS | | | 97.52 234 | 97.46 210 | 97.70 280 | 98.98 227 | 95.55 279 | 99.29 200 | 98.82 288 | 98.07 93 | 98.66 226 | 99.64 135 | 89.97 286 | 99.61 190 | 97.01 216 | 96.68 232 | 97.94 300 |
|
test_0402 | | | 96.64 256 | 96.24 257 | 97.85 270 | 98.85 259 | 96.43 264 | 99.44 148 | 99.26 238 | 93.52 299 | 96.98 285 | 99.52 172 | 88.52 302 | 99.20 259 | 92.58 306 | 97.50 210 | 97.93 301 |
|
MVP-Stereo | | | 97.81 201 | 97.75 182 | 97.99 261 | 97.53 307 | 96.60 259 | 98.96 280 | 98.85 285 | 97.22 174 | 97.23 279 | 99.36 223 | 95.28 148 | 99.46 201 | 95.51 261 | 99.78 72 | 97.92 302 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
MS-PatchMatch | | | 97.24 249 | 97.32 233 | 96.99 290 | 98.45 295 | 93.51 309 | 98.82 294 | 99.32 218 | 97.41 158 | 98.13 259 | 99.30 238 | 88.99 294 | 99.56 194 | 95.68 258 | 99.80 68 | 97.90 303 |
|
v13 | | | 96.24 269 | 95.58 274 | 98.25 242 | 98.98 227 | 98.83 140 | 99.75 34 | 99.29 225 | 94.35 289 | 93.89 311 | 97.60 314 | 95.17 156 | 98.11 305 | 94.27 289 | 86.86 324 | 97.81 304 |
|
V9 | | | 96.25 268 | 95.58 274 | 98.26 238 | 98.94 238 | 98.83 140 | 99.75 34 | 99.29 225 | 94.45 287 | 93.96 308 | 97.62 312 | 94.94 166 | 98.14 302 | 94.40 281 | 86.87 323 | 97.81 304 |
|
v17 | | | 96.42 262 | 95.81 267 | 98.25 242 | 98.94 238 | 98.80 154 | 99.76 27 | 99.28 232 | 94.57 280 | 94.18 301 | 97.71 305 | 95.23 153 | 98.16 299 | 94.86 271 | 87.73 318 | 97.80 306 |
|
v16 | | | 96.39 264 | 95.76 270 | 98.26 238 | 98.96 233 | 98.81 149 | 99.76 27 | 99.28 232 | 94.57 280 | 94.10 303 | 97.70 306 | 95.04 160 | 98.16 299 | 94.70 275 | 87.77 317 | 97.80 306 |
|
v15 | | | 96.28 266 | 95.62 272 | 98.25 242 | 98.94 238 | 98.83 140 | 99.76 27 | 99.29 225 | 94.52 284 | 94.02 306 | 97.61 313 | 95.02 161 | 98.13 303 | 94.53 277 | 86.92 321 | 97.80 306 |
|
v12 | | | 96.24 269 | 95.58 274 | 98.23 245 | 98.96 233 | 98.81 149 | 99.76 27 | 99.29 225 | 94.42 288 | 93.85 312 | 97.60 314 | 95.12 157 | 98.09 306 | 94.32 286 | 86.85 325 | 97.80 306 |
|
V14 | | | 96.26 267 | 95.60 273 | 98.26 238 | 98.94 238 | 98.83 140 | 99.76 27 | 99.29 225 | 94.49 285 | 93.96 308 | 97.66 309 | 94.99 164 | 98.13 303 | 94.41 280 | 86.90 322 | 97.80 306 |
|
v18 | | | 96.42 262 | 95.80 269 | 98.26 238 | 98.95 235 | 98.82 147 | 99.76 27 | 99.28 232 | 94.58 279 | 94.12 302 | 97.70 306 | 95.22 154 | 98.16 299 | 94.83 273 | 87.80 316 | 97.79 311 |
|
Anonymous20231211 | | | 90.69 302 | 89.39 303 | 94.58 304 | 94.25 323 | 88.18 321 | 99.29 200 | 99.07 260 | 82.45 329 | 92.95 316 | 97.65 310 | 63.96 336 | 97.79 314 | 89.27 314 | 85.63 327 | 97.77 312 |
|
v11 | | | 96.23 271 | 95.57 277 | 98.21 248 | 98.93 243 | 98.83 140 | 99.72 39 | 99.29 225 | 94.29 290 | 94.05 305 | 97.64 311 | 94.88 173 | 98.04 307 | 92.89 302 | 88.43 314 | 97.77 312 |
|
ambc | | | | | 93.06 308 | 92.68 328 | 82.36 330 | 98.47 313 | 98.73 304 | | 95.09 298 | 97.41 318 | 55.55 338 | 99.10 269 | 96.42 244 | 91.32 307 | 97.71 314 |
|
new-patchmatchnet | | | 94.48 290 | 94.08 291 | 95.67 302 | 95.08 321 | 92.41 313 | 99.18 230 | 99.28 232 | 94.55 283 | 93.49 314 | 97.37 320 | 87.86 309 | 97.01 321 | 91.57 307 | 88.36 315 | 97.61 315 |
|
pmmvs-eth3d | | | 95.34 285 | 94.73 286 | 97.15 287 | 95.53 319 | 95.94 274 | 99.35 186 | 99.10 255 | 95.13 270 | 93.55 313 | 97.54 317 | 88.15 308 | 97.91 311 | 94.58 276 | 89.69 312 | 97.61 315 |
|
UnsupCasMVSNet_bld | | | 93.53 296 | 92.51 298 | 96.58 299 | 97.38 309 | 93.82 303 | 98.24 320 | 99.48 113 | 91.10 315 | 93.10 315 | 96.66 323 | 74.89 329 | 98.37 296 | 94.03 293 | 87.71 319 | 97.56 317 |
|
PM-MVS | | | 92.96 297 | 92.23 299 | 95.14 303 | 95.61 317 | 89.98 320 | 99.37 178 | 98.21 320 | 94.80 275 | 95.04 299 | 97.69 308 | 65.06 334 | 97.90 312 | 94.30 287 | 89.98 311 | 97.54 318 |
|
LCM-MVSNet | | | 86.80 305 | 85.22 308 | 91.53 316 | 87.81 335 | 80.96 332 | 98.23 322 | 98.99 268 | 71.05 333 | 90.13 324 | 96.51 324 | 48.45 341 | 96.88 322 | 90.51 309 | 85.30 328 | 96.76 319 |
|
OpenMVS_ROB | | 92.34 20 | 94.38 292 | 93.70 293 | 96.41 300 | 97.38 309 | 93.17 310 | 99.06 254 | 98.75 294 | 86.58 324 | 94.84 300 | 98.26 299 | 81.53 328 | 99.32 230 | 89.01 315 | 97.87 194 | 96.76 319 |
|
CMPMVS | | 69.68 23 | 94.13 293 | 94.90 285 | 91.84 313 | 97.24 313 | 80.01 333 | 98.52 311 | 99.48 113 | 89.01 321 | 91.99 319 | 99.67 121 | 85.67 317 | 99.13 264 | 95.44 262 | 97.03 230 | 96.39 321 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
1111 | | | 92.30 299 | 92.21 300 | 92.55 310 | 93.30 325 | 86.27 322 | 99.15 235 | 98.74 297 | 91.94 309 | 90.85 322 | 97.82 303 | 84.18 322 | 95.21 327 | 79.65 330 | 94.27 283 | 96.19 322 |
|
test12356 | | | 91.74 300 | 92.19 301 | 90.37 318 | 91.22 329 | 82.41 329 | 98.61 307 | 98.28 317 | 90.66 317 | 91.82 320 | 97.92 301 | 84.90 320 | 92.61 333 | 81.64 329 | 94.66 275 | 96.09 323 |
|
PMMVS2 | | | 86.87 304 | 85.37 307 | 91.35 317 | 90.21 332 | 83.80 327 | 98.89 290 | 97.45 332 | 83.13 328 | 91.67 321 | 95.03 326 | 48.49 340 | 94.70 330 | 85.86 325 | 77.62 331 | 95.54 324 |
|
tmp_tt | | | 82.80 309 | 81.52 309 | 86.66 320 | 66.61 344 | 68.44 342 | 92.79 337 | 97.92 324 | 68.96 335 | 80.04 334 | 99.85 26 | 85.77 316 | 96.15 326 | 97.86 153 | 43.89 339 | 95.39 325 |
|
testmv | | | 87.91 303 | 87.80 304 | 88.24 319 | 87.68 336 | 77.50 336 | 99.07 250 | 97.66 330 | 89.27 319 | 86.47 326 | 96.22 325 | 68.35 332 | 92.49 335 | 76.63 334 | 88.82 313 | 94.72 326 |
|
no-one | | | 83.04 308 | 80.12 310 | 91.79 314 | 89.44 334 | 85.65 325 | 99.32 191 | 98.32 316 | 89.06 320 | 79.79 335 | 89.16 336 | 44.86 342 | 96.67 323 | 84.33 327 | 46.78 338 | 93.05 327 |
|
testpf | | | 95.66 280 | 96.02 263 | 94.58 304 | 98.35 297 | 92.32 314 | 97.25 331 | 97.91 326 | 92.83 305 | 97.03 284 | 98.99 266 | 88.69 298 | 98.61 294 | 95.72 256 | 97.40 219 | 92.80 328 |
|
FPMVS | | | 84.93 306 | 85.65 306 | 82.75 326 | 86.77 337 | 63.39 343 | 98.35 317 | 98.92 276 | 74.11 332 | 83.39 329 | 98.98 269 | 50.85 339 | 92.40 336 | 84.54 326 | 94.97 266 | 92.46 329 |
|
Gipuma | | | 90.99 301 | 90.15 302 | 93.51 306 | 98.73 274 | 90.12 319 | 93.98 335 | 99.45 148 | 79.32 330 | 92.28 318 | 94.91 327 | 69.61 331 | 97.98 310 | 87.42 319 | 95.67 252 | 92.45 330 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
ANet_high | | | 77.30 313 | 74.86 315 | 84.62 323 | 75.88 342 | 77.61 335 | 97.63 328 | 93.15 343 | 88.81 322 | 64.27 338 | 89.29 335 | 36.51 343 | 83.93 342 | 75.89 335 | 52.31 337 | 92.33 331 |
|
PNet_i23d | | | 79.43 312 | 77.68 313 | 84.67 322 | 86.18 338 | 71.69 341 | 96.50 333 | 93.68 340 | 75.17 331 | 71.33 336 | 91.18 333 | 32.18 345 | 90.62 337 | 78.57 333 | 74.34 332 | 91.71 332 |
|
MVE | | 76.82 21 | 76.91 314 | 74.31 316 | 84.70 321 | 85.38 340 | 76.05 339 | 96.88 332 | 93.17 342 | 67.39 336 | 71.28 337 | 89.01 337 | 21.66 350 | 87.69 339 | 71.74 337 | 72.29 333 | 90.35 333 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
PMVS | | 70.75 22 | 75.98 315 | 74.97 314 | 79.01 328 | 70.98 343 | 55.18 344 | 93.37 336 | 98.21 320 | 65.08 339 | 61.78 340 | 93.83 329 | 21.74 349 | 92.53 334 | 78.59 332 | 91.12 308 | 89.34 334 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
wuykxyi23d | | | 74.42 316 | 71.19 317 | 84.14 324 | 76.16 341 | 74.29 340 | 96.00 334 | 92.57 345 | 69.57 334 | 63.84 339 | 87.49 338 | 21.98 347 | 88.86 338 | 75.56 336 | 57.50 336 | 89.26 335 |
|
EMVS | | | 80.02 311 | 79.22 312 | 82.43 327 | 91.19 330 | 76.40 337 | 97.55 330 | 92.49 346 | 66.36 338 | 83.01 330 | 91.27 332 | 64.63 335 | 85.79 341 | 65.82 339 | 60.65 335 | 85.08 336 |
|
E-PMN | | | 80.61 310 | 79.88 311 | 82.81 325 | 90.75 331 | 76.38 338 | 97.69 327 | 95.76 336 | 66.44 337 | 83.52 328 | 92.25 331 | 62.54 337 | 87.16 340 | 68.53 338 | 61.40 334 | 84.89 337 |
|
test123 | | | 39.01 320 | 42.50 320 | 28.53 332 | 39.17 345 | 20.91 346 | 98.75 299 | 19.17 349 | 19.83 342 | 38.57 341 | 66.67 340 | 33.16 344 | 15.42 344 | 37.50 342 | 29.66 342 | 49.26 338 |
|
.test1245 | | | 83.42 307 | 86.17 305 | 75.15 329 | 93.30 325 | 86.27 322 | 99.15 235 | 98.74 297 | 91.94 309 | 90.85 322 | 97.82 303 | 84.18 322 | 95.21 327 | 79.65 330 | 39.90 340 | 43.98 339 |
|
testmvs | | | 39.17 319 | 43.78 318 | 25.37 333 | 36.04 346 | 16.84 347 | 98.36 315 | 26.56 347 | 20.06 341 | 38.51 342 | 67.32 339 | 29.64 346 | 15.30 345 | 37.59 341 | 39.90 340 | 43.98 339 |
|
wuyk23d | | | 40.18 318 | 41.29 321 | 36.84 330 | 86.18 338 | 49.12 345 | 79.73 338 | 22.81 348 | 27.64 340 | 25.46 343 | 28.45 344 | 21.98 347 | 48.89 343 | 55.80 340 | 23.56 343 | 12.51 341 |
|
cdsmvs_eth3d_5k | | | 24.64 321 | 32.85 322 | 0.00 334 | 0.00 347 | 0.00 348 | 0.00 339 | 99.51 85 | 0.00 343 | 0.00 344 | 99.56 161 | 96.58 115 | 0.00 346 | 0.00 343 | 0.00 344 | 0.00 342 |
|
pcd_1.5k_mvsjas | | | 8.27 323 | 11.03 324 | 0.00 334 | 0.00 347 | 0.00 348 | 0.00 339 | 0.00 350 | 0.00 343 | 0.00 344 | 0.27 345 | 99.01 11 | 0.00 346 | 0.00 343 | 0.00 344 | 0.00 342 |
|
sosnet-low-res | | | 0.02 324 | 0.03 325 | 0.00 334 | 0.00 347 | 0.00 348 | 0.00 339 | 0.00 350 | 0.00 343 | 0.00 344 | 0.27 345 | 0.00 351 | 0.00 346 | 0.00 343 | 0.00 344 | 0.00 342 |
|
sosnet | | | 0.02 324 | 0.03 325 | 0.00 334 | 0.00 347 | 0.00 348 | 0.00 339 | 0.00 350 | 0.00 343 | 0.00 344 | 0.27 345 | 0.00 351 | 0.00 346 | 0.00 343 | 0.00 344 | 0.00 342 |
|
uncertanet | | | 0.02 324 | 0.03 325 | 0.00 334 | 0.00 347 | 0.00 348 | 0.00 339 | 0.00 350 | 0.00 343 | 0.00 344 | 0.27 345 | 0.00 351 | 0.00 346 | 0.00 343 | 0.00 344 | 0.00 342 |
|
Regformer | | | 0.02 324 | 0.03 325 | 0.00 334 | 0.00 347 | 0.00 348 | 0.00 339 | 0.00 350 | 0.00 343 | 0.00 344 | 0.27 345 | 0.00 351 | 0.00 346 | 0.00 343 | 0.00 344 | 0.00 342 |
|
ab-mvs-re | | | 8.30 322 | 11.06 323 | 0.00 334 | 0.00 347 | 0.00 348 | 0.00 339 | 0.00 350 | 0.00 343 | 0.00 344 | 99.58 155 | 0.00 351 | 0.00 346 | 0.00 343 | 0.00 344 | 0.00 342 |
|
uanet | | | 0.02 324 | 0.03 325 | 0.00 334 | 0.00 347 | 0.00 348 | 0.00 339 | 0.00 350 | 0.00 343 | 0.00 344 | 0.27 345 | 0.00 351 | 0.00 346 | 0.00 343 | 0.00 344 | 0.00 342 |
|
ESAPD | | | | | | | | | 99.47 127 | | | | | | | | |
|
sam_mvs1 | | | | | | | | | | | | | 94.86 174 | | | | |
|
sam_mvs | | | | | | | | | | | | | 94.72 187 | | | | |
|
MTGPA | | | | | | | | | 99.47 127 | | | | | | | | |
|
test_post1 | | | | | | | | 99.23 219 | | | | 65.14 342 | 94.18 209 | 99.71 166 | 97.58 178 | | |
|
test_post | | | | | | | | | | | | 65.99 341 | 94.65 191 | 99.73 156 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 98.70 286 | 94.79 178 | 99.74 148 | | | |
|
MTMP | | | | | | | | | 98.88 283 | | | | | | | | |
|
gm-plane-assit | | | | | | 98.54 292 | 92.96 311 | | | 94.65 278 | | 99.15 252 | | 99.64 183 | 97.56 181 | | |
|
TEST9 | | | | | | 99.67 80 | 99.65 37 | 99.05 256 | 99.41 168 | 96.22 246 | 98.95 190 | 99.49 180 | 98.77 39 | 99.91 72 | | | |
|
test_8 | | | | | | 99.67 80 | 99.61 42 | 99.03 262 | 99.41 168 | 96.28 239 | 98.93 193 | 99.48 186 | 98.76 41 | 99.91 72 | | | |
|
agg_prior | | | | | | 99.67 80 | 99.62 40 | | 99.40 175 | | 98.87 200 | | | 99.91 72 | | | |
|
test_prior4 | | | | | | | 99.56 49 | 98.99 271 | | | | | | | | | |
|
test_prior2 | | | | | | | | 98.96 280 | | 98.34 66 | 99.01 179 | 99.52 172 | 98.68 49 | | 97.96 145 | 99.74 79 | |
|
旧先验2 | | | | | | | | 98.96 280 | | 96.70 207 | 99.47 78 | | | 99.94 40 | 98.19 127 | | |
|
æ–°å‡ ä½•2 | | | | | | | | 99.01 269 | | | | | | | | | |
|
原ACMM2 | | | | | | | | 98.95 284 | | | | | | | | | |
|
testdata2 | | | | | | | | | | | | | | 99.95 33 | 96.67 236 | | |
|
segment_acmp | | | | | | | | | | | | | 98.96 20 | | | | |
|
testdata1 | | | | | | | | 98.85 293 | | 98.32 69 | | | | | | | |
|
plane_prior7 | | | | | | 99.29 169 | 97.03 240 | | | | | | | | | | |
|
plane_prior6 | | | | | | 99.27 174 | 96.98 244 | | | | | | 92.71 242 | | | | |
|
plane_prior4 | | | | | | | | | | | | 99.61 147 | | | | | |
|
plane_prior3 | | | | | | | 97.00 242 | | | 98.69 46 | 99.11 161 | | | | | | |
|
plane_prior2 | | | | | | | | 99.39 171 | | 98.97 22 | | | | | | | |
|
plane_prior1 | | | | | | 99.26 176 | | | | | | | | | | | |
|
plane_prior | | | | | | | 96.97 245 | 99.21 226 | | 98.45 59 | | | | | | 97.60 201 | |
|
n2 | | | | | | | | | 0.00 350 | | | | | | | | |
|
nn | | | | | | | | | 0.00 350 | | | | | | | | |
|
door-mid | | | | | | | | | 98.05 323 | | | | | | | | |
|
test11 | | | | | | | | | 99.35 196 | | | | | | | | |
|
door | | | | | | | | | 97.92 324 | | | | | | | | |
|
HQP5-MVS | | | | | | | 96.83 250 | | | | | | | | | | |
|
HQP-NCC | | | | | | 99.19 186 | | 98.98 275 | | 98.24 72 | 98.66 226 | | | | | | |
|
ACMP_Plane | | | | | | 99.19 186 | | 98.98 275 | | 98.24 72 | 98.66 226 | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 97.19 206 | | |
|
HQP3-MVS | | | | | | | | | 99.39 178 | | | | | | | 97.58 203 | |
|
HQP2-MVS | | | | | | | | | | | | | 92.47 251 | | | | |
|
NP-MVS | | | | | | 99.23 179 | 96.92 248 | | | | | 99.40 208 | | | | | |
|
MDTV_nov1_ep13 | | | | 98.32 133 | | 99.11 204 | 94.44 298 | 99.27 206 | 98.74 297 | 97.51 149 | 99.40 94 | 99.62 144 | 94.78 179 | 99.76 146 | 97.59 177 | 98.81 151 | |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 97.19 227 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 97.43 218 | |
|
Test By Simon | | | | | | | | | | | | | 98.75 44 | | | | |
|