EPNet | | | 95.20 67 | 94.56 72 | 97.14 54 | 92.80 305 | 92.68 65 | 97.85 48 | 94.87 282 | 96.64 1 | 92.46 128 | 97.80 63 | 86.23 99 | 99.65 41 | 93.72 80 | 98.62 74 | 99.10 61 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
NCCC | | | 97.30 9 | 97.03 10 | 98.11 7 | 98.77 35 | 95.06 10 | 97.34 106 | 98.04 64 | 95.96 2 | 97.09 27 | 97.88 54 | 93.18 11 | 99.71 29 | 95.84 35 | 99.17 53 | 99.56 15 |
|
CNVR-MVS | | | 97.68 2 | 97.44 5 | 98.37 3 | 98.90 32 | 95.86 2 | 97.27 112 | 98.08 50 | 95.81 3 | 97.87 11 | 98.31 33 | 94.26 4 | 99.68 37 | 97.02 4 | 99.49 23 | 99.57 13 |
|
HPM-MVS++ | | | 97.34 8 | 96.97 12 | 98.47 1 | 99.08 27 | 96.16 1 | 97.55 87 | 97.97 78 | 95.59 4 | 96.61 35 | 97.89 52 | 92.57 19 | 99.84 14 | 95.95 32 | 99.51 19 | 99.40 35 |
|
HSP-MVS | | | 97.53 5 | 97.49 4 | 97.63 34 | 99.40 5 | 93.77 40 | 98.53 9 | 97.85 88 | 95.55 5 | 98.56 3 | 97.81 61 | 93.90 6 | 99.65 41 | 96.62 13 | 99.21 50 | 99.48 28 |
|
MVS_0304 | | | 96.05 50 | 95.45 52 | 97.85 14 | 97.75 102 | 94.50 15 | 96.87 148 | 97.95 81 | 95.46 6 | 95.60 72 | 98.01 48 | 80.96 191 | 99.83 15 | 97.23 2 | 99.25 46 | 99.23 49 |
|
DeepPCF-MVS | | 93.97 1 | 96.61 36 | 97.09 8 | 95.15 135 | 98.09 80 | 86.63 254 | 96.00 227 | 98.15 38 | 95.43 7 | 97.95 9 | 98.56 7 | 93.40 10 | 99.36 91 | 96.77 12 | 99.48 24 | 99.45 30 |
|
CANet | | | 96.39 42 | 96.02 44 | 97.50 38 | 97.62 108 | 93.38 49 | 97.02 133 | 97.96 79 | 95.42 8 | 94.86 82 | 97.81 61 | 87.38 89 | 99.82 18 | 96.88 7 | 99.20 51 | 99.29 45 |
|
SteuartSystems-ACMMP | | | 97.62 3 | 97.53 2 | 97.87 13 | 98.39 59 | 94.25 22 | 98.43 16 | 98.27 24 | 95.34 9 | 98.11 5 | 98.56 7 | 94.53 3 | 99.71 29 | 96.57 16 | 99.62 7 | 99.65 3 |
Skip Steuart: Steuart Systems R&D Blog. |
Regformer-2 | | | 97.16 13 | 96.99 11 | 97.67 29 | 98.32 65 | 93.84 35 | 96.83 151 | 98.10 47 | 95.24 10 | 97.49 13 | 98.25 39 | 92.57 19 | 99.61 47 | 96.80 9 | 99.29 43 | 99.56 15 |
|
DELS-MVS | | | 96.61 36 | 96.38 37 | 97.30 44 | 97.79 99 | 93.19 53 | 95.96 228 | 98.18 35 | 95.23 11 | 95.87 61 | 97.65 72 | 91.45 40 | 99.70 34 | 95.87 33 | 99.44 29 | 99.00 69 |
Christian Sormann, Emanuele Santellani, Mattia Rossi, Andreas Kuhn, Friedrich Fraundorfer: DELS-MVS: Deep Epipolar Line Search for Multi-View Stereo. Winter Conference on Applications of Computer Vision (WACV), 2023 |
Regformer-1 | | | 97.10 15 | 96.96 13 | 97.54 37 | 98.32 65 | 93.48 46 | 96.83 151 | 97.99 76 | 95.20 12 | 97.46 14 | 98.25 39 | 92.48 22 | 99.58 55 | 96.79 11 | 99.29 43 | 99.55 17 |
|
Regformer-4 | | | 96.97 22 | 96.87 16 | 97.25 48 | 98.34 62 | 92.66 66 | 96.96 138 | 98.01 69 | 95.12 13 | 97.14 23 | 98.42 18 | 91.82 34 | 99.61 47 | 96.90 6 | 99.13 56 | 99.50 24 |
|
SMA-MVS | | | 97.07 17 | 96.77 24 | 97.97 11 | 99.37 10 | 94.42 18 | 97.15 126 | 98.08 50 | 95.07 14 | 96.11 51 | 98.59 5 | 90.88 49 | 99.90 1 | 96.18 27 | 99.50 21 | 99.58 11 |
|
MTAPA | | | 97.08 16 | 96.78 23 | 97.97 11 | 99.37 10 | 94.42 18 | 97.24 114 | 98.08 50 | 95.07 14 | 96.11 51 | 98.59 5 | 90.88 49 | 99.90 1 | 96.18 27 | 99.50 21 | 99.58 11 |
|
Regformer-3 | | | 96.85 27 | 96.80 22 | 97.01 57 | 98.34 62 | 92.02 84 | 96.96 138 | 97.76 91 | 95.01 16 | 97.08 28 | 98.42 18 | 91.71 35 | 99.54 67 | 96.80 9 | 99.13 56 | 99.48 28 |
|
XVS | | | 97.18 11 | 96.96 13 | 97.81 17 | 99.38 8 | 94.03 31 | 98.59 7 | 98.20 31 | 94.85 17 | 96.59 37 | 98.29 36 | 91.70 36 | 99.80 20 | 95.66 37 | 99.40 32 | 99.62 7 |
|
X-MVStestdata | | | 91.71 176 | 89.67 233 | 97.81 17 | 99.38 8 | 94.03 31 | 98.59 7 | 98.20 31 | 94.85 17 | 96.59 37 | 32.69 351 | 91.70 36 | 99.80 20 | 95.66 37 | 99.40 32 | 99.62 7 |
|
HQP_MVS | | | 93.78 104 | 93.43 99 | 94.82 153 | 96.21 165 | 89.99 137 | 97.74 56 | 97.51 117 | 94.85 17 | 91.34 153 | 96.64 117 | 81.32 187 | 98.60 153 | 93.02 92 | 92.23 192 | 95.86 204 |
|
plane_prior2 | | | | | | | | 97.74 56 | | 94.85 17 | | | | | | | |
|
SD-MVS | | | 97.41 7 | 97.53 2 | 97.06 56 | 98.57 51 | 94.46 16 | 97.92 42 | 98.14 40 | 94.82 21 | 99.01 1 | 98.55 9 | 94.18 5 | 97.41 277 | 96.94 5 | 99.64 3 | 99.32 43 |
|
UA-Net | | | 95.95 54 | 95.53 51 | 97.20 53 | 97.67 105 | 92.98 59 | 97.65 69 | 98.13 41 | 94.81 22 | 96.61 35 | 98.35 24 | 88.87 66 | 99.51 74 | 90.36 133 | 97.35 106 | 99.11 60 |
|
DeepC-MVS_fast | | 93.89 2 | 96.93 25 | 96.64 27 | 97.78 20 | 98.64 46 | 94.30 20 | 97.41 98 | 98.04 64 | 94.81 22 | 96.59 37 | 98.37 23 | 91.24 42 | 99.64 46 | 95.16 49 | 99.52 17 | 99.42 34 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
APDe-MVS | | | 97.82 1 | 97.73 1 | 98.08 8 | 99.15 25 | 94.82 12 | 98.81 2 | 98.30 22 | 94.76 24 | 98.30 4 | 98.90 1 | 93.77 8 | 99.68 37 | 97.93 1 | 99.69 1 | 99.75 1 |
|
EI-MVSNet-Vis-set | | | 96.51 38 | 96.47 33 | 96.63 65 | 98.24 71 | 91.20 107 | 96.89 147 | 97.73 94 | 94.74 25 | 96.49 41 | 98.49 13 | 90.88 49 | 99.58 55 | 96.44 18 | 98.32 80 | 99.13 57 |
|
EI-MVSNet-UG-set | | | 96.34 43 | 96.30 38 | 96.47 76 | 98.20 75 | 90.93 118 | 96.86 149 | 97.72 97 | 94.67 26 | 96.16 50 | 98.46 14 | 90.43 53 | 99.58 55 | 96.23 21 | 97.96 89 | 98.90 78 |
|
MSLP-MVS++ | | | 96.94 24 | 97.06 9 | 96.59 68 | 98.72 37 | 91.86 88 | 97.67 66 | 98.49 12 | 94.66 27 | 97.24 18 | 98.41 21 | 92.31 26 | 98.94 127 | 96.61 14 | 99.46 25 | 98.96 71 |
|
3Dnovator+ | | 91.43 4 | 95.40 60 | 94.48 77 | 98.16 6 | 96.90 135 | 95.34 6 | 98.48 14 | 97.87 85 | 94.65 28 | 88.53 234 | 98.02 47 | 83.69 127 | 99.71 29 | 93.18 91 | 98.96 66 | 99.44 32 |
|
canonicalmvs | | | 96.02 52 | 95.45 52 | 97.75 24 | 97.59 111 | 95.15 9 | 98.28 22 | 97.60 108 | 94.52 29 | 96.27 47 | 96.12 143 | 87.65 83 | 99.18 101 | 96.20 26 | 94.82 149 | 98.91 77 |
|
plane_prior3 | | | | | | | 90.00 135 | | | 94.46 30 | 91.34 153 | | | | | | |
|
UGNet | | | 94.04 96 | 93.28 104 | 96.31 85 | 96.85 136 | 91.19 108 | 97.88 45 | 97.68 102 | 94.40 31 | 93.00 120 | 96.18 140 | 73.39 288 | 99.61 47 | 91.72 114 | 98.46 77 | 98.13 123 |
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 |
alignmvs | | | 95.87 56 | 95.23 59 | 97.78 20 | 97.56 113 | 95.19 7 | 97.86 46 | 97.17 152 | 94.39 32 | 96.47 42 | 96.40 133 | 85.89 104 | 99.20 98 | 96.21 25 | 95.11 145 | 98.95 73 |
|
CANet_DTU | | | 94.37 84 | 93.65 90 | 96.55 69 | 96.46 157 | 92.13 80 | 96.21 215 | 96.67 203 | 94.38 33 | 93.53 102 | 97.03 102 | 79.34 220 | 99.71 29 | 90.76 129 | 98.45 78 | 97.82 138 |
|
Vis-MVSNet | | | 95.23 65 | 94.81 65 | 96.51 73 | 97.18 125 | 91.58 96 | 98.26 24 | 98.12 42 | 94.38 33 | 94.90 81 | 98.15 41 | 82.28 170 | 98.92 128 | 91.45 123 | 98.58 76 | 99.01 68 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
MVS_111021_HR | | | 96.68 35 | 96.58 30 | 96.99 58 | 98.46 53 | 92.31 73 | 96.20 216 | 98.90 2 | 94.30 35 | 95.86 62 | 97.74 66 | 92.33 23 | 99.38 90 | 96.04 30 | 99.42 30 | 99.28 48 |
|
TSAR-MVS + GP. | | | 96.69 33 | 96.49 32 | 97.27 47 | 98.31 67 | 93.39 48 | 96.79 158 | 96.72 196 | 94.17 36 | 97.44 15 | 97.66 71 | 92.76 13 | 99.33 92 | 96.86 8 | 97.76 95 | 99.08 62 |
|
3Dnovator | | 91.36 5 | 95.19 68 | 94.44 79 | 97.44 39 | 96.56 149 | 93.36 51 | 98.65 6 | 98.36 16 | 94.12 37 | 89.25 224 | 98.06 45 | 82.20 173 | 99.77 22 | 93.41 88 | 99.32 41 | 99.18 52 |
|
plane_prior | | | | | | | 89.99 137 | 97.24 114 | | 94.06 38 | | | | | | 92.16 196 | |
|
MVS_111021_LR | | | 96.24 46 | 96.19 43 | 96.39 80 | 98.23 74 | 91.35 102 | 96.24 214 | 98.79 4 | 93.99 39 | 95.80 65 | 97.65 72 | 89.92 60 | 99.24 97 | 95.87 33 | 99.20 51 | 98.58 94 |
|
DeepC-MVS | | 93.07 3 | 96.06 49 | 95.66 50 | 97.29 45 | 97.96 87 | 93.17 54 | 97.30 111 | 98.06 57 | 93.92 40 | 93.38 105 | 98.66 4 | 86.83 94 | 99.73 25 | 95.60 43 | 99.22 49 | 98.96 71 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
VNet | | | 95.89 55 | 95.45 52 | 97.21 52 | 98.07 81 | 92.94 60 | 97.50 90 | 98.15 38 | 93.87 41 | 97.52 12 | 97.61 78 | 85.29 110 | 99.53 70 | 95.81 36 | 95.27 143 | 99.16 53 |
|
Effi-MVS+-dtu | | | 93.08 124 | 93.21 105 | 92.68 252 | 96.02 176 | 83.25 288 | 97.14 127 | 96.72 196 | 93.85 42 | 91.20 168 | 93.44 271 | 83.08 140 | 98.30 183 | 91.69 117 | 95.73 138 | 96.50 181 |
|
mvs-test1 | | | 93.63 108 | 93.69 88 | 93.46 226 | 96.02 176 | 84.61 276 | 97.24 114 | 96.72 196 | 93.85 42 | 92.30 134 | 95.76 162 | 83.08 140 | 98.89 132 | 91.69 117 | 96.54 125 | 96.87 169 |
|
PS-MVSNAJ | | | 95.37 61 | 95.33 57 | 95.49 120 | 97.35 121 | 90.66 126 | 95.31 257 | 97.48 119 | 93.85 42 | 96.51 40 | 95.70 167 | 88.65 70 | 99.65 41 | 94.80 63 | 98.27 81 | 96.17 189 |
|
test_part3 | | | | | | | | 97.50 90 | | 93.81 45 | | 98.53 11 | | 99.87 5 | 95.19 47 | | |
|
ESAPD | | | 97.57 4 | 97.29 7 | 98.41 2 | 99.28 17 | 95.74 3 | 97.50 90 | 98.26 25 | 93.81 45 | 98.10 6 | 98.53 11 | 95.31 1 | 99.87 5 | 95.19 47 | 99.63 4 | 99.63 5 |
|
TSAR-MVS + MP. | | | 97.42 6 | 97.33 6 | 97.69 28 | 99.25 20 | 94.24 23 | 98.07 34 | 97.85 88 | 93.72 47 | 98.57 2 | 98.35 24 | 93.69 9 | 99.40 87 | 97.06 3 | 99.46 25 | 99.44 32 |
|
OPM-MVS | | | 93.28 119 | 92.76 113 | 94.82 153 | 94.63 236 | 90.77 124 | 96.65 176 | 97.18 150 | 93.72 47 | 91.68 146 | 97.26 92 | 79.33 221 | 98.63 150 | 92.13 103 | 92.28 191 | 95.07 250 |
|
xiu_mvs_v2_base | | | 95.32 63 | 95.29 58 | 95.40 126 | 97.22 123 | 90.50 129 | 95.44 252 | 97.44 131 | 93.70 49 | 96.46 43 | 96.18 140 | 88.59 73 | 99.53 70 | 94.79 65 | 97.81 92 | 96.17 189 |
|
HQP-NCC | | | | | | 95.86 179 | | 96.65 176 | | 93.55 50 | 90.14 181 | | | | | | |
|
ACMP_Plane | | | | | | 95.86 179 | | 96.65 176 | | 93.55 50 | 90.14 181 | | | | | | |
|
HQP-MVS | | | 93.19 122 | 92.74 117 | 94.54 171 | 95.86 179 | 89.33 177 | 96.65 176 | 97.39 136 | 93.55 50 | 90.14 181 | 95.87 152 | 80.95 192 | 98.50 162 | 92.13 103 | 92.10 197 | 95.78 211 |
|
MCST-MVS | | | 97.18 11 | 96.84 18 | 98.20 5 | 99.30 16 | 95.35 5 | 97.12 128 | 98.07 55 | 93.54 53 | 96.08 53 | 97.69 68 | 93.86 7 | 99.71 29 | 96.50 17 | 99.39 34 | 99.55 17 |
|
MG-MVS | | | 95.61 58 | 95.38 55 | 96.31 85 | 98.42 56 | 90.53 128 | 96.04 223 | 97.48 119 | 93.47 54 | 95.67 71 | 98.10 42 | 89.17 63 | 99.25 96 | 91.27 126 | 98.77 70 | 99.13 57 |
|
FC-MVSNet-test | | | 93.94 99 | 93.57 91 | 95.04 141 | 95.48 192 | 91.45 100 | 98.12 30 | 98.71 5 | 93.37 55 | 90.23 180 | 96.70 112 | 87.66 82 | 97.85 244 | 91.49 121 | 90.39 224 | 95.83 208 |
|
MP-MVS | | | 96.77 30 | 96.45 35 | 97.72 25 | 99.39 7 | 93.80 36 | 98.41 17 | 98.06 57 | 93.37 55 | 95.54 75 | 98.34 27 | 90.59 52 | 99.88 3 | 94.83 61 | 99.54 15 | 99.49 26 |
|
FIs | | | 94.09 93 | 93.70 87 | 95.27 128 | 95.70 186 | 92.03 83 | 98.10 31 | 98.68 7 | 93.36 57 | 90.39 177 | 96.70 112 | 87.63 84 | 97.94 234 | 92.25 99 | 90.50 223 | 95.84 207 |
|
abl_6 | | | 96.40 41 | 96.21 41 | 96.98 59 | 98.89 33 | 92.20 78 | 97.89 44 | 98.03 66 | 93.34 58 | 97.22 19 | 98.42 18 | 87.93 79 | 99.72 28 | 95.10 52 | 99.07 61 | 99.02 64 |
|
mPP-MVS | | | 96.86 26 | 96.60 28 | 97.64 32 | 99.40 5 | 93.44 47 | 98.50 13 | 98.09 49 | 93.27 59 | 95.95 60 | 98.33 30 | 91.04 45 | 99.88 3 | 95.20 46 | 99.57 13 | 99.60 10 |
|
HFP-MVS | | | 97.14 14 | 96.92 15 | 97.83 15 | 99.42 3 | 94.12 27 | 98.52 10 | 98.32 19 | 93.21 60 | 97.18 20 | 98.29 36 | 92.08 28 | 99.83 15 | 95.63 39 | 99.59 9 | 99.54 19 |
|
ACMMPR | | | 97.07 17 | 96.84 18 | 97.79 19 | 99.44 2 | 93.88 33 | 98.52 10 | 98.31 21 | 93.21 60 | 97.15 22 | 98.33 30 | 91.35 41 | 99.86 8 | 95.63 39 | 99.59 9 | 99.62 7 |
|
IS-MVSNet | | | 94.90 76 | 94.52 75 | 96.05 96 | 97.67 105 | 90.56 127 | 98.44 15 | 96.22 219 | 93.21 60 | 93.99 95 | 97.74 66 | 85.55 108 | 98.45 166 | 89.98 134 | 97.86 90 | 99.14 56 |
|
region2R | | | 97.07 17 | 96.84 18 | 97.77 22 | 99.46 1 | 93.79 37 | 98.52 10 | 98.24 28 | 93.19 63 | 97.14 23 | 98.34 27 | 91.59 39 | 99.87 5 | 95.46 44 | 99.59 9 | 99.64 4 |
|
EPNet_dtu | | | 91.71 176 | 91.28 167 | 92.99 242 | 93.76 278 | 83.71 283 | 96.69 173 | 95.28 259 | 93.15 64 | 87.02 264 | 95.95 149 | 83.37 131 | 97.38 280 | 79.46 297 | 96.84 115 | 97.88 134 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
UniMVSNet (Re) | | | 93.31 118 | 92.55 124 | 95.61 113 | 95.39 195 | 93.34 52 | 97.39 102 | 98.71 5 | 93.14 65 | 90.10 189 | 94.83 205 | 87.71 81 | 98.03 217 | 91.67 119 | 83.99 286 | 95.46 224 |
|
APD-MVS_3200maxsize | | | 96.81 28 | 96.71 26 | 97.12 55 | 99.01 30 | 92.31 73 | 97.98 40 | 98.06 57 | 93.11 66 | 97.44 15 | 98.55 9 | 90.93 47 | 99.55 65 | 96.06 29 | 99.25 46 | 99.51 23 |
|
testdata1 | | | | | | | | 95.26 261 | | 93.10 67 | | | | | | | |
|
DU-MVS | | | 92.90 132 | 92.04 135 | 95.49 120 | 94.95 222 | 92.83 61 | 97.16 125 | 98.24 28 | 93.02 68 | 90.13 185 | 95.71 165 | 83.47 129 | 97.85 244 | 91.71 115 | 83.93 287 | 95.78 211 |
|
xiu_mvs_v1_base_debu | | | 95.01 70 | 94.76 66 | 95.75 107 | 96.58 146 | 91.71 89 | 96.25 211 | 97.35 142 | 92.99 69 | 96.70 31 | 96.63 121 | 82.67 159 | 99.44 82 | 96.22 22 | 97.46 99 | 96.11 194 |
|
xiu_mvs_v1_base | | | 95.01 70 | 94.76 66 | 95.75 107 | 96.58 146 | 91.71 89 | 96.25 211 | 97.35 142 | 92.99 69 | 96.70 31 | 96.63 121 | 82.67 159 | 99.44 82 | 96.22 22 | 97.46 99 | 96.11 194 |
|
xiu_mvs_v1_base_debi | | | 95.01 70 | 94.76 66 | 95.75 107 | 96.58 146 | 91.71 89 | 96.25 211 | 97.35 142 | 92.99 69 | 96.70 31 | 96.63 121 | 82.67 159 | 99.44 82 | 96.22 22 | 97.46 99 | 96.11 194 |
|
CP-MVS | | | 97.02 20 | 96.81 21 | 97.64 32 | 99.33 14 | 93.54 44 | 98.80 3 | 98.28 23 | 92.99 69 | 96.45 44 | 98.30 35 | 91.90 33 | 99.85 11 | 95.61 41 | 99.68 2 | 99.54 19 |
|
ACMMP | | | 96.27 45 | 95.93 45 | 97.28 46 | 99.24 21 | 92.62 67 | 98.25 25 | 98.81 3 | 92.99 69 | 94.56 86 | 98.39 22 | 88.96 65 | 99.85 11 | 94.57 67 | 97.63 96 | 99.36 41 |
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 |
UniMVSNet_NR-MVSNet | | | 93.37 116 | 92.67 119 | 95.47 123 | 95.34 198 | 92.83 61 | 97.17 124 | 98.58 10 | 92.98 74 | 90.13 185 | 95.80 157 | 88.37 75 | 97.85 244 | 91.71 115 | 83.93 287 | 95.73 217 |
|
VPNet | | | 92.23 161 | 91.31 166 | 94.99 143 | 95.56 189 | 90.96 116 | 97.22 119 | 97.86 87 | 92.96 75 | 90.96 169 | 96.62 124 | 75.06 274 | 98.20 187 | 91.90 109 | 83.65 293 | 95.80 210 |
|
nrg030 | | | 94.05 95 | 93.31 103 | 96.27 89 | 95.22 208 | 94.59 14 | 98.34 19 | 97.46 124 | 92.93 76 | 91.21 167 | 96.64 117 | 87.23 91 | 98.22 186 | 94.99 58 | 85.80 260 | 95.98 202 |
|
TranMVSNet+NR-MVSNet | | | 92.50 145 | 91.63 152 | 95.14 136 | 94.76 231 | 92.07 81 | 97.53 88 | 98.11 45 | 92.90 77 | 89.56 212 | 96.12 143 | 83.16 133 | 97.60 265 | 89.30 147 | 83.20 297 | 95.75 215 |
|
ACMMP_Plus | | | 97.20 10 | 96.86 17 | 98.23 4 | 99.09 26 | 95.16 8 | 97.60 82 | 98.19 33 | 92.82 78 | 97.93 10 | 98.74 3 | 91.60 38 | 99.86 8 | 96.26 20 | 99.52 17 | 99.67 2 |
|
test_prior3 | | | 96.46 40 | 96.20 42 | 97.23 49 | 98.67 40 | 92.99 57 | 96.35 201 | 98.00 71 | 92.80 79 | 96.03 54 | 97.59 79 | 92.01 30 | 99.41 85 | 95.01 55 | 99.38 35 | 99.29 45 |
|
test_prior2 | | | | | | | | 96.35 201 | | 92.80 79 | 96.03 54 | 97.59 79 | 92.01 30 | | 95.01 55 | 99.38 35 | |
|
CLD-MVS | | | 92.98 128 | 92.53 126 | 94.32 179 | 96.12 174 | 89.20 184 | 95.28 258 | 97.47 122 | 92.66 81 | 89.90 194 | 95.62 170 | 80.58 201 | 98.40 174 | 92.73 95 | 92.40 190 | 95.38 233 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
NR-MVSNet | | | 92.34 154 | 91.27 168 | 95.53 117 | 94.95 222 | 93.05 56 | 97.39 102 | 98.07 55 | 92.65 82 | 84.46 281 | 95.71 165 | 85.00 114 | 97.77 253 | 89.71 139 | 83.52 294 | 95.78 211 |
|
#test# | | | 97.02 20 | 96.75 25 | 97.83 15 | 99.42 3 | 94.12 27 | 98.15 29 | 98.32 19 | 92.57 83 | 97.18 20 | 98.29 36 | 92.08 28 | 99.83 15 | 95.12 51 | 99.59 9 | 99.54 19 |
|
PS-MVSNAJss | | | 93.74 105 | 93.51 95 | 94.44 173 | 93.91 273 | 89.28 182 | 97.75 54 | 97.56 114 | 92.50 84 | 89.94 193 | 96.54 127 | 88.65 70 | 98.18 190 | 93.83 79 | 90.90 216 | 95.86 204 |
|
VDD-MVS | | | 93.82 102 | 93.08 106 | 96.02 97 | 97.88 96 | 89.96 142 | 97.72 60 | 95.85 237 | 92.43 85 | 95.86 62 | 98.44 16 | 68.42 309 | 99.39 88 | 96.31 19 | 94.85 147 | 98.71 90 |
|
LCM-MVSNet-Re | | | 92.50 145 | 92.52 127 | 92.44 255 | 96.82 140 | 81.89 296 | 96.92 145 | 93.71 310 | 92.41 86 | 84.30 283 | 94.60 215 | 85.08 113 | 97.03 290 | 91.51 120 | 97.36 105 | 98.40 114 |
|
VPA-MVSNet | | | 93.24 120 | 92.48 129 | 95.51 118 | 95.70 186 | 92.39 72 | 97.86 46 | 98.66 9 | 92.30 87 | 92.09 139 | 95.37 183 | 80.49 203 | 98.40 174 | 93.95 73 | 85.86 259 | 95.75 215 |
|
PGM-MVS | | | 96.81 28 | 96.53 31 | 97.65 30 | 99.35 13 | 93.53 45 | 97.65 69 | 98.98 1 | 92.22 88 | 97.14 23 | 98.44 16 | 91.17 43 | 99.85 11 | 94.35 68 | 99.46 25 | 99.57 13 |
|
Vis-MVSNet (Re-imp) | | | 94.15 89 | 93.88 83 | 94.95 148 | 97.61 109 | 87.92 226 | 98.10 31 | 95.80 240 | 92.22 88 | 93.02 119 | 97.45 88 | 84.53 121 | 97.91 241 | 88.24 168 | 97.97 88 | 99.02 64 |
|
tfpn111 | | | 92.45 148 | 91.58 154 | 95.06 139 | 97.92 91 | 89.37 174 | 97.71 62 | 94.66 284 | 92.20 90 | 93.31 107 | 94.90 198 | 78.06 253 | 99.11 108 | 81.37 280 | 94.06 161 | 96.70 174 |
|
conf200view11 | | | 92.45 148 | 91.58 154 | 95.05 140 | 97.92 91 | 89.37 174 | 97.71 62 | 94.66 284 | 92.20 90 | 93.31 107 | 94.90 198 | 78.06 253 | 99.08 119 | 81.40 276 | 94.08 157 | 96.70 174 |
|
thres100view900 | | | 92.43 150 | 91.58 154 | 94.98 145 | 97.92 91 | 89.37 174 | 97.71 62 | 94.66 284 | 92.20 90 | 93.31 107 | 94.90 198 | 78.06 253 | 99.08 119 | 81.40 276 | 94.08 157 | 96.48 182 |
|
tfpn200view9 | | | 92.38 153 | 91.52 159 | 94.95 148 | 97.85 97 | 89.29 180 | 97.41 98 | 94.88 279 | 92.19 93 | 93.27 111 | 94.46 221 | 78.17 246 | 99.08 119 | 81.40 276 | 94.08 157 | 96.48 182 |
|
thres400 | | | 92.42 151 | 91.52 159 | 95.12 138 | 97.85 97 | 89.29 180 | 97.41 98 | 94.88 279 | 92.19 93 | 93.27 111 | 94.46 221 | 78.17 246 | 99.08 119 | 81.40 276 | 94.08 157 | 96.98 159 |
|
thres600view7 | | | 92.49 147 | 91.60 153 | 95.18 130 | 97.91 94 | 89.47 165 | 97.65 69 | 94.66 284 | 92.18 95 | 93.33 106 | 94.91 197 | 78.06 253 | 99.10 114 | 81.61 269 | 94.06 161 | 96.98 159 |
|
view600 | | | 92.55 141 | 91.68 147 | 95.18 130 | 97.98 83 | 89.44 169 | 98.00 36 | 94.57 289 | 92.09 96 | 93.17 114 | 95.52 176 | 78.14 249 | 99.11 108 | 81.61 269 | 94.04 163 | 96.98 159 |
|
view800 | | | 92.55 141 | 91.68 147 | 95.18 130 | 97.98 83 | 89.44 169 | 98.00 36 | 94.57 289 | 92.09 96 | 93.17 114 | 95.52 176 | 78.14 249 | 99.11 108 | 81.61 269 | 94.04 163 | 96.98 159 |
|
conf0.05thres1000 | | | 92.55 141 | 91.68 147 | 95.18 130 | 97.98 83 | 89.44 169 | 98.00 36 | 94.57 289 | 92.09 96 | 93.17 114 | 95.52 176 | 78.14 249 | 99.11 108 | 81.61 269 | 94.04 163 | 96.98 159 |
|
tfpn | | | 92.55 141 | 91.68 147 | 95.18 130 | 97.98 83 | 89.44 169 | 98.00 36 | 94.57 289 | 92.09 96 | 93.17 114 | 95.52 176 | 78.14 249 | 99.11 108 | 81.61 269 | 94.04 163 | 96.98 159 |
|
Fast-Effi-MVS+-dtu | | | 92.29 158 | 91.99 138 | 93.21 237 | 95.27 203 | 85.52 265 | 97.03 131 | 96.63 206 | 92.09 96 | 89.11 225 | 95.14 192 | 80.33 207 | 98.08 200 | 87.54 187 | 94.74 152 | 96.03 201 |
|
thres200 | | | 92.23 161 | 91.39 162 | 94.75 160 | 97.61 109 | 89.03 187 | 96.60 183 | 95.09 269 | 92.08 101 | 93.28 110 | 94.00 250 | 78.39 244 | 99.04 124 | 81.26 288 | 94.18 156 | 96.19 188 |
|
mvs_tets | | | 92.31 156 | 91.76 143 | 93.94 197 | 93.41 288 | 88.29 199 | 97.63 80 | 97.53 115 | 92.04 102 | 88.76 229 | 96.45 131 | 74.62 278 | 98.09 199 | 93.91 75 | 91.48 207 | 95.45 225 |
|
OMC-MVS | | | 95.09 69 | 94.70 69 | 96.25 91 | 98.46 53 | 91.28 103 | 96.43 191 | 97.57 111 | 92.04 102 | 94.77 84 | 97.96 51 | 87.01 93 | 99.09 117 | 91.31 125 | 96.77 118 | 98.36 118 |
|
jajsoiax | | | 92.42 151 | 91.89 141 | 94.03 188 | 93.33 292 | 88.50 196 | 97.73 58 | 97.53 115 | 92.00 104 | 88.85 228 | 96.50 129 | 75.62 271 | 98.11 196 | 93.88 77 | 91.56 206 | 95.48 221 |
|
XVG-OURS | | | 93.72 106 | 93.35 102 | 94.80 156 | 97.07 129 | 88.61 193 | 94.79 267 | 97.46 124 | 91.97 105 | 93.99 95 | 97.86 57 | 81.74 182 | 98.88 134 | 92.64 96 | 92.67 188 | 96.92 167 |
|
WR-MVS | | | 92.34 154 | 91.53 158 | 94.77 159 | 95.13 214 | 90.83 121 | 96.40 197 | 97.98 77 | 91.88 106 | 89.29 221 | 95.54 175 | 82.50 164 | 97.80 249 | 89.79 138 | 85.27 266 | 95.69 218 |
|
PAPM_NR | | | 95.01 70 | 94.59 71 | 96.26 90 | 98.89 33 | 90.68 125 | 97.24 114 | 97.73 94 | 91.80 107 | 92.93 125 | 96.62 124 | 89.13 64 | 99.14 106 | 89.21 151 | 97.78 93 | 98.97 70 |
|
testgi | | | 87.97 274 | 87.21 271 | 90.24 302 | 92.86 303 | 80.76 302 | 96.67 175 | 94.97 275 | 91.74 108 | 85.52 275 | 95.83 155 | 62.66 325 | 94.47 325 | 76.25 309 | 88.36 243 | 95.48 221 |
|
CP-MVSNet | | | 91.89 171 | 91.24 169 | 93.82 200 | 95.05 217 | 88.57 194 | 97.82 50 | 98.19 33 | 91.70 109 | 88.21 241 | 95.76 162 | 81.96 177 | 97.52 269 | 87.86 175 | 84.65 280 | 95.37 234 |
|
XVG-OURS-SEG-HR | | | 93.86 101 | 93.55 92 | 94.81 155 | 97.06 131 | 88.53 195 | 95.28 258 | 97.45 128 | 91.68 110 | 94.08 94 | 97.68 69 | 82.41 168 | 98.90 130 | 93.84 78 | 92.47 189 | 96.98 159 |
|
OurMVSNet-221017-0 | | | 90.51 232 | 90.19 215 | 91.44 285 | 93.41 288 | 81.25 300 | 96.98 137 | 96.28 214 | 91.68 110 | 86.55 268 | 96.30 136 | 74.20 281 | 97.98 225 | 88.96 158 | 87.40 252 | 95.09 247 |
|
ACMP | | 89.59 10 | 92.62 140 | 92.14 133 | 94.05 187 | 96.40 159 | 88.20 207 | 97.36 105 | 97.25 149 | 91.52 112 | 88.30 238 | 96.64 117 | 78.46 242 | 98.72 147 | 91.86 112 | 91.48 207 | 95.23 244 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
APD-MVS | | | 96.95 23 | 96.60 28 | 98.01 9 | 99.03 29 | 94.93 11 | 97.72 60 | 98.10 47 | 91.50 113 | 98.01 8 | 98.32 32 | 92.33 23 | 99.58 55 | 94.85 60 | 99.51 19 | 99.53 22 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
ITE_SJBPF | | | | | 92.43 256 | 95.34 198 | 85.37 267 | | 95.92 229 | 91.47 114 | 87.75 247 | 96.39 134 | 71.00 297 | 97.96 232 | 82.36 266 | 89.86 230 | 93.97 292 |
|
PS-CasMVS | | | 91.55 193 | 90.84 186 | 93.69 213 | 94.96 221 | 88.28 200 | 97.84 49 | 98.24 28 | 91.46 115 | 88.04 243 | 95.80 157 | 79.67 216 | 97.48 271 | 87.02 198 | 84.54 282 | 95.31 237 |
|
WR-MVS_H | | | 92.00 168 | 91.35 163 | 93.95 194 | 95.09 216 | 89.47 165 | 98.04 35 | 98.68 7 | 91.46 115 | 88.34 236 | 94.68 211 | 85.86 105 | 97.56 266 | 85.77 217 | 84.24 284 | 94.82 268 |
|
MVSFormer | | | 95.37 61 | 95.16 61 | 95.99 99 | 96.34 161 | 91.21 105 | 98.22 26 | 97.57 111 | 91.42 117 | 96.22 48 | 97.32 89 | 86.20 101 | 97.92 238 | 94.07 70 | 99.05 62 | 98.85 82 |
|
test_djsdf | | | 93.07 125 | 92.76 113 | 94.00 189 | 93.49 286 | 88.70 192 | 98.22 26 | 97.57 111 | 91.42 117 | 90.08 191 | 95.55 174 | 82.85 156 | 97.92 238 | 94.07 70 | 91.58 205 | 95.40 231 |
|
ACMM | | 89.79 8 | 92.96 129 | 92.50 128 | 94.35 177 | 96.30 163 | 88.71 191 | 97.58 85 | 97.36 141 | 91.40 119 | 90.53 173 | 96.65 116 | 79.77 214 | 98.75 144 | 91.24 127 | 91.64 203 | 95.59 220 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
PEN-MVS | | | 91.20 208 | 90.44 203 | 93.48 224 | 94.49 240 | 87.91 228 | 97.76 53 | 98.18 35 | 91.29 120 | 87.78 246 | 95.74 164 | 80.35 206 | 97.33 282 | 85.46 222 | 82.96 298 | 95.19 246 |
|
LPG-MVS_test | | | 92.94 130 | 92.56 123 | 94.10 184 | 96.16 170 | 88.26 201 | 97.65 69 | 97.46 124 | 91.29 120 | 90.12 187 | 97.16 96 | 79.05 224 | 98.73 145 | 92.25 99 | 91.89 200 | 95.31 237 |
|
LGP-MVS_train | | | | | 94.10 184 | 96.16 170 | 88.26 201 | | 97.46 124 | 91.29 120 | 90.12 187 | 97.16 96 | 79.05 224 | 98.73 145 | 92.25 99 | 91.89 200 | 95.31 237 |
|
MVSTER | | | 93.20 121 | 92.81 112 | 94.37 176 | 96.56 149 | 89.59 159 | 97.06 130 | 97.12 159 | 91.24 123 | 91.30 156 | 95.96 148 | 82.02 176 | 98.05 212 | 93.48 85 | 90.55 221 | 95.47 223 |
|
MVS_Test | | | 94.89 77 | 94.62 70 | 95.68 111 | 96.83 139 | 89.55 161 | 96.70 171 | 97.17 152 | 91.17 124 | 95.60 72 | 96.11 145 | 87.87 80 | 98.76 143 | 93.01 94 | 97.17 110 | 98.72 88 |
|
HPM-MVS | | | 96.69 33 | 96.45 35 | 97.40 40 | 99.36 12 | 93.11 55 | 98.87 1 | 98.06 57 | 91.17 124 | 96.40 45 | 97.99 50 | 90.99 46 | 99.58 55 | 95.61 41 | 99.61 8 | 99.49 26 |
|
test-LLR | | | 91.42 199 | 91.19 172 | 92.12 267 | 94.59 237 | 80.66 303 | 94.29 277 | 92.98 323 | 91.11 126 | 90.76 171 | 92.37 286 | 79.02 226 | 98.07 204 | 88.81 163 | 96.74 119 | 97.63 143 |
|
test0.0.03 1 | | | 89.37 253 | 88.70 247 | 91.41 286 | 92.47 310 | 85.63 263 | 95.22 262 | 92.70 328 | 91.11 126 | 86.91 266 | 93.65 262 | 79.02 226 | 93.19 331 | 78.00 303 | 89.18 234 | 95.41 227 |
|
XVG-ACMP-BASELINE | | | 90.93 217 | 90.21 214 | 93.09 239 | 94.31 247 | 85.89 259 | 95.33 255 | 97.26 147 | 91.06 128 | 89.38 217 | 95.44 182 | 68.61 307 | 98.60 153 | 89.46 145 | 91.05 214 | 94.79 272 |
|
Effi-MVS+ | | | 94.93 75 | 94.45 78 | 96.36 83 | 96.61 144 | 91.47 98 | 96.41 193 | 97.41 135 | 91.02 129 | 94.50 87 | 95.92 150 | 87.53 86 | 98.78 140 | 93.89 76 | 96.81 117 | 98.84 84 |
|
Patchmatch-test1 | | | 91.54 194 | 90.85 184 | 93.59 218 | 95.59 188 | 84.95 272 | 94.72 268 | 95.58 247 | 90.82 130 | 92.25 135 | 93.58 264 | 75.80 268 | 97.41 277 | 83.35 251 | 95.98 132 | 98.40 114 |
|
SixPastTwentyTwo | | | 89.15 254 | 88.54 251 | 90.98 289 | 93.49 286 | 80.28 310 | 96.70 171 | 94.70 283 | 90.78 131 | 84.15 286 | 95.57 172 | 71.78 292 | 97.71 257 | 84.63 233 | 85.07 272 | 94.94 258 |
|
DTE-MVSNet | | | 90.56 230 | 89.75 231 | 93.01 241 | 93.95 271 | 87.25 238 | 97.64 73 | 97.65 105 | 90.74 132 | 87.12 260 | 95.68 168 | 79.97 212 | 97.00 293 | 83.33 253 | 81.66 305 | 94.78 273 |
|
GA-MVS | | | 91.38 201 | 90.31 206 | 94.59 166 | 94.65 235 | 87.62 233 | 94.34 275 | 96.19 220 | 90.73 133 | 90.35 178 | 93.83 255 | 71.84 291 | 97.96 232 | 87.22 194 | 93.61 174 | 98.21 121 |
|
EPP-MVSNet | | | 95.22 66 | 95.04 63 | 95.76 106 | 97.49 120 | 89.56 160 | 98.67 5 | 97.00 175 | 90.69 134 | 94.24 92 | 97.62 77 | 89.79 61 | 98.81 138 | 93.39 89 | 96.49 126 | 98.92 76 |
|
MP-MVS-pluss | | | 96.70 32 | 96.27 39 | 97.98 10 | 99.23 23 | 94.71 13 | 96.96 138 | 98.06 57 | 90.67 135 | 95.55 74 | 98.78 2 | 91.07 44 | 99.86 8 | 96.58 15 | 99.55 14 | 99.38 39 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
IterMVS-LS | | | 92.29 158 | 91.94 140 | 93.34 231 | 96.25 164 | 86.97 247 | 96.57 187 | 97.05 168 | 90.67 135 | 89.50 215 | 94.80 207 | 86.59 95 | 97.64 262 | 89.91 135 | 86.11 258 | 95.40 231 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
EI-MVSNet | | | 93.03 127 | 92.88 111 | 93.48 224 | 95.77 184 | 86.98 246 | 96.44 189 | 97.12 159 | 90.66 137 | 91.30 156 | 97.64 75 | 86.56 96 | 98.05 212 | 89.91 135 | 90.55 221 | 95.41 227 |
|
K. test v3 | | | 87.64 278 | 86.75 276 | 90.32 301 | 93.02 302 | 79.48 316 | 96.61 181 | 92.08 331 | 90.66 137 | 80.25 318 | 94.09 248 | 67.21 315 | 96.65 296 | 85.96 215 | 80.83 309 | 94.83 266 |
|
test_normal | | | 92.01 166 | 90.75 189 | 95.80 105 | 93.24 294 | 89.97 140 | 95.93 230 | 96.24 218 | 90.62 139 | 81.63 299 | 93.45 270 | 74.98 275 | 98.89 132 | 93.61 81 | 97.04 113 | 98.55 95 |
|
BH-RMVSNet | | | 92.72 139 | 91.97 139 | 94.97 146 | 97.16 126 | 87.99 221 | 96.15 217 | 95.60 245 | 90.62 139 | 91.87 142 | 97.15 98 | 78.41 243 | 98.57 156 | 83.16 254 | 97.60 97 | 98.36 118 |
|
semantic-postprocess | | | | | 91.82 275 | 95.52 190 | 84.20 279 | | 96.15 222 | 90.61 141 | 87.39 255 | 94.27 243 | 75.63 270 | 96.44 297 | 87.34 191 | 86.88 255 | 94.82 268 |
|
WTY-MVS | | | 94.71 81 | 94.02 81 | 96.79 61 | 97.71 104 | 92.05 82 | 96.59 184 | 97.35 142 | 90.61 141 | 94.64 85 | 96.93 103 | 86.41 98 | 99.39 88 | 91.20 128 | 94.71 153 | 98.94 74 |
|
DI_MVS_plusplus_test | | | 92.01 166 | 90.77 187 | 95.73 110 | 93.34 290 | 89.78 147 | 96.14 218 | 96.18 221 | 90.58 143 | 81.80 298 | 93.50 267 | 74.95 276 | 98.90 130 | 93.51 83 | 96.94 114 | 98.51 100 |
|
LFMVS | | | 93.60 109 | 92.63 120 | 96.52 70 | 98.13 79 | 91.27 104 | 97.94 41 | 93.39 315 | 90.57 144 | 96.29 46 | 98.31 33 | 69.00 305 | 99.16 103 | 94.18 69 | 95.87 135 | 99.12 59 |
|
HPM-MVS_fast | | | 96.51 38 | 96.27 39 | 97.22 51 | 99.32 15 | 92.74 63 | 98.74 4 | 98.06 57 | 90.57 144 | 96.77 30 | 98.35 24 | 90.21 56 | 99.53 70 | 94.80 63 | 99.63 4 | 99.38 39 |
|
Test4 | | | 89.48 250 | 87.50 260 | 95.44 125 | 90.76 319 | 89.72 148 | 95.78 238 | 97.09 162 | 90.28 146 | 77.67 324 | 91.74 298 | 55.42 337 | 98.08 200 | 91.92 108 | 96.83 116 | 98.52 98 |
|
PVSNet_Blended_VisFu | | | 95.27 64 | 94.91 64 | 96.38 81 | 98.20 75 | 90.86 120 | 97.27 112 | 98.25 27 | 90.21 147 | 94.18 93 | 97.27 91 | 87.48 87 | 99.73 25 | 93.53 82 | 97.77 94 | 98.55 95 |
|
PVSNet_BlendedMVS | | | 94.06 94 | 93.92 82 | 94.47 172 | 98.27 68 | 89.46 167 | 96.73 163 | 98.36 16 | 90.17 148 | 94.36 89 | 95.24 189 | 88.02 76 | 99.58 55 | 93.44 86 | 90.72 219 | 94.36 285 |
|
CNLPA | | | 94.28 86 | 93.53 94 | 96.52 70 | 98.38 60 | 92.55 69 | 96.59 184 | 96.88 190 | 90.13 149 | 91.91 141 | 97.24 93 | 85.21 111 | 99.09 117 | 87.64 184 | 97.83 91 | 97.92 131 |
|
BH-untuned | | | 92.94 130 | 92.62 121 | 93.92 198 | 97.22 123 | 86.16 258 | 96.40 197 | 96.25 217 | 90.06 150 | 89.79 201 | 96.17 142 | 83.19 132 | 98.35 178 | 87.19 195 | 97.27 108 | 97.24 156 |
|
IterMVS | | | 90.15 240 | 89.67 233 | 91.61 282 | 95.48 192 | 83.72 282 | 94.33 276 | 96.12 223 | 89.99 151 | 87.31 258 | 94.15 247 | 75.78 269 | 96.27 300 | 86.97 199 | 86.89 254 | 94.83 266 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
AdaColmap | | | 94.34 85 | 93.68 89 | 96.31 85 | 98.59 48 | 91.68 92 | 96.59 184 | 97.81 90 | 89.87 152 | 92.15 137 | 97.06 101 | 83.62 128 | 99.54 67 | 89.34 146 | 98.07 86 | 97.70 142 |
|
UnsupCasMVSNet_eth | | | 85.99 290 | 84.45 291 | 90.62 297 | 89.97 322 | 82.40 293 | 93.62 292 | 97.37 139 | 89.86 153 | 78.59 323 | 92.37 286 | 65.25 321 | 95.35 321 | 82.27 267 | 70.75 335 | 94.10 290 |
|
PHI-MVS | | | 96.77 30 | 96.46 34 | 97.71 27 | 98.40 57 | 94.07 29 | 98.21 28 | 98.45 15 | 89.86 153 | 97.11 26 | 98.01 48 | 92.52 21 | 99.69 35 | 96.03 31 | 99.53 16 | 99.36 41 |
|
mvs_anonymous | | | 93.82 102 | 93.74 86 | 94.06 186 | 96.44 158 | 85.41 266 | 95.81 235 | 97.05 168 | 89.85 155 | 90.09 190 | 96.36 135 | 87.44 88 | 97.75 254 | 93.97 72 | 96.69 122 | 99.02 64 |
|
PatchFormer-LS_test | | | 91.68 186 | 91.18 173 | 93.19 238 | 95.24 207 | 83.63 286 | 95.53 248 | 95.44 251 | 89.82 156 | 91.37 151 | 92.58 283 | 80.85 199 | 98.52 160 | 89.65 142 | 90.16 226 | 97.42 154 |
|
ab-mvs | | | 93.57 111 | 92.55 124 | 96.64 63 | 97.28 122 | 91.96 87 | 95.40 253 | 97.45 128 | 89.81 157 | 93.22 113 | 96.28 137 | 79.62 217 | 99.46 79 | 90.74 130 | 93.11 183 | 98.50 102 |
|
FMVSNet3 | | | 91.78 173 | 90.69 192 | 95.03 142 | 96.53 151 | 92.27 75 | 97.02 133 | 96.93 185 | 89.79 158 | 89.35 218 | 94.65 213 | 77.01 262 | 97.47 272 | 86.12 210 | 88.82 236 | 95.35 235 |
|
v2v482 | | | 91.59 190 | 90.85 184 | 93.80 201 | 93.87 275 | 88.17 209 | 96.94 144 | 96.88 190 | 89.54 159 | 89.53 213 | 94.90 198 | 81.70 183 | 98.02 220 | 89.25 149 | 85.04 274 | 95.20 245 |
|
PatchmatchNet | | | 91.91 170 | 91.35 163 | 93.59 218 | 95.38 196 | 84.11 280 | 93.15 300 | 95.39 252 | 89.54 159 | 92.10 138 | 93.68 260 | 82.82 157 | 98.13 193 | 84.81 229 | 95.32 142 | 98.52 98 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
EPMVS | | | 90.70 227 | 89.81 228 | 93.37 230 | 94.73 233 | 84.21 278 | 93.67 290 | 88.02 342 | 89.50 161 | 92.38 131 | 93.49 268 | 77.82 259 | 97.78 251 | 86.03 213 | 92.68 187 | 98.11 127 |
|
v148 | | | 90.99 215 | 90.38 205 | 92.81 247 | 93.83 276 | 85.80 260 | 96.78 160 | 96.68 201 | 89.45 162 | 88.75 230 | 93.93 253 | 82.96 152 | 97.82 248 | 87.83 176 | 83.25 295 | 94.80 270 |
|
anonymousdsp | | | 92.16 163 | 91.55 157 | 93.97 192 | 92.58 309 | 89.55 161 | 97.51 89 | 97.42 134 | 89.42 163 | 88.40 235 | 94.84 203 | 80.66 200 | 97.88 243 | 91.87 111 | 91.28 211 | 94.48 281 |
|
IB-MVS | | 87.33 17 | 89.91 243 | 88.28 254 | 94.79 158 | 95.26 206 | 87.70 232 | 95.12 264 | 93.95 308 | 89.35 164 | 87.03 263 | 92.49 284 | 70.74 299 | 99.19 99 | 89.18 152 | 81.37 306 | 97.49 152 |
Christian Sormann, Mattia Rossi, Andreas Kuhn and Friedrich Fraundorfer: IB-MVS: An Iterative Algorithm for Deep Multi-View Stereo based on Binary Decisions. BMVC 2021 |
jason | | | 94.84 79 | 94.39 80 | 96.18 93 | 95.52 190 | 90.93 118 | 96.09 220 | 96.52 208 | 89.28 165 | 96.01 58 | 97.32 89 | 84.70 118 | 98.77 142 | 95.15 50 | 98.91 68 | 98.85 82 |
jason: jason. |
TAMVS | | | 94.01 97 | 93.46 97 | 95.64 112 | 96.16 170 | 90.45 131 | 96.71 168 | 96.89 189 | 89.27 166 | 93.46 104 | 96.92 104 | 87.29 90 | 97.94 234 | 88.70 165 | 95.74 137 | 98.53 97 |
|
testing_2 | | | 87.33 280 | 85.03 287 | 94.22 180 | 87.77 331 | 89.32 179 | 94.97 265 | 97.11 161 | 89.22 167 | 71.64 333 | 88.73 319 | 55.16 338 | 97.94 234 | 91.95 107 | 88.73 240 | 95.41 227 |
|
v6 | | | 91.69 181 | 91.00 177 | 93.75 206 | 94.14 255 | 88.12 214 | 97.20 120 | 96.98 176 | 89.19 168 | 89.90 194 | 94.42 225 | 83.04 144 | 98.07 204 | 89.07 154 | 85.10 269 | 95.07 250 |
|
API-MVS | | | 94.84 79 | 94.49 76 | 95.90 101 | 97.90 95 | 92.00 85 | 97.80 51 | 97.48 119 | 89.19 168 | 94.81 83 | 96.71 110 | 88.84 67 | 99.17 102 | 88.91 159 | 98.76 71 | 96.53 179 |
|
v1neww | | | 91.70 179 | 91.01 175 | 93.75 206 | 94.19 250 | 88.14 212 | 97.20 120 | 96.98 176 | 89.18 170 | 89.87 197 | 94.44 223 | 83.10 138 | 98.06 209 | 89.06 155 | 85.09 270 | 95.06 253 |
|
v7new | | | 91.70 179 | 91.01 175 | 93.75 206 | 94.19 250 | 88.14 212 | 97.20 120 | 96.98 176 | 89.18 170 | 89.87 197 | 94.44 223 | 83.10 138 | 98.06 209 | 89.06 155 | 85.09 270 | 95.06 253 |
|
v1141 | | | 91.61 187 | 90.89 179 | 93.78 203 | 94.01 268 | 88.24 203 | 96.96 138 | 96.96 180 | 89.17 172 | 89.75 203 | 94.29 239 | 82.99 148 | 98.03 217 | 88.85 161 | 85.00 275 | 95.07 250 |
|
divwei89l23v2f112 | | | 91.61 187 | 90.89 179 | 93.78 203 | 94.01 268 | 88.22 205 | 96.96 138 | 96.96 180 | 89.17 172 | 89.75 203 | 94.28 241 | 83.02 146 | 98.03 217 | 88.86 160 | 84.98 277 | 95.08 248 |
|
v1 | | | 91.61 187 | 90.89 179 | 93.78 203 | 94.01 268 | 88.21 206 | 96.96 138 | 96.96 180 | 89.17 172 | 89.78 202 | 94.29 239 | 82.97 150 | 98.05 212 | 88.85 161 | 84.99 276 | 95.08 248 |
|
XXY-MVS | | | 92.16 163 | 91.23 170 | 94.95 148 | 94.75 232 | 90.94 117 | 97.47 96 | 97.43 133 | 89.14 175 | 88.90 226 | 96.43 132 | 79.71 215 | 98.24 185 | 89.56 143 | 87.68 247 | 95.67 219 |
|
pm-mvs1 | | | 90.72 225 | 89.65 235 | 93.96 193 | 94.29 248 | 89.63 156 | 97.79 52 | 96.82 193 | 89.07 176 | 86.12 272 | 95.48 181 | 78.61 240 | 97.78 251 | 86.97 199 | 81.67 304 | 94.46 282 |
|
HY-MVS | | 89.66 9 | 93.87 100 | 92.95 109 | 96.63 65 | 97.10 128 | 92.49 71 | 95.64 243 | 96.64 204 | 89.05 177 | 93.00 120 | 95.79 160 | 85.77 107 | 99.45 81 | 89.16 153 | 94.35 154 | 97.96 129 |
|
CSCG | | | 96.05 50 | 95.91 46 | 96.46 78 | 99.24 21 | 90.47 130 | 98.30 21 | 98.57 11 | 89.01 178 | 93.97 97 | 97.57 81 | 92.62 18 | 99.76 23 | 94.66 66 | 99.27 45 | 99.15 55 |
|
tfpn1000 | | | 91.99 169 | 91.05 174 | 94.80 156 | 97.78 100 | 89.66 155 | 97.91 43 | 92.90 326 | 88.99 179 | 91.73 144 | 94.84 203 | 78.99 230 | 98.33 181 | 82.41 265 | 93.91 169 | 96.40 184 |
|
v8 | | | 91.29 206 | 90.53 202 | 93.57 221 | 94.15 254 | 88.12 214 | 97.34 106 | 97.06 167 | 88.99 179 | 88.32 237 | 94.26 245 | 83.08 140 | 98.01 221 | 87.62 185 | 83.92 289 | 94.57 279 |
|
PAPR | | | 94.18 88 | 93.42 101 | 96.48 75 | 97.64 107 | 91.42 101 | 95.55 246 | 97.71 100 | 88.99 179 | 92.34 133 | 95.82 156 | 89.19 62 | 99.11 108 | 86.14 209 | 97.38 104 | 98.90 78 |
|
CDS-MVSNet | | | 94.14 91 | 93.54 93 | 95.93 100 | 96.18 168 | 91.46 99 | 96.33 204 | 97.04 171 | 88.97 182 | 93.56 100 | 96.51 128 | 87.55 85 | 97.89 242 | 89.80 137 | 95.95 133 | 98.44 111 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
sss | | | 94.51 83 | 93.80 85 | 96.64 63 | 97.07 129 | 91.97 86 | 96.32 205 | 98.06 57 | 88.94 183 | 94.50 87 | 96.78 107 | 84.60 119 | 99.27 95 | 91.90 109 | 96.02 131 | 98.68 92 |
|
tfpn_ndepth | | | 91.88 172 | 90.96 178 | 94.62 165 | 97.73 103 | 89.93 143 | 97.75 54 | 92.92 325 | 88.93 184 | 91.73 144 | 93.80 257 | 78.91 231 | 98.49 165 | 83.02 257 | 93.86 170 | 95.45 225 |
|
lupinMVS | | | 94.99 74 | 94.56 72 | 96.29 88 | 96.34 161 | 91.21 105 | 95.83 234 | 96.27 215 | 88.93 184 | 96.22 48 | 96.88 105 | 86.20 101 | 98.85 135 | 95.27 45 | 99.05 62 | 98.82 85 |
|
v7n | | | 90.76 221 | 89.86 225 | 93.45 227 | 93.54 283 | 87.60 234 | 97.70 65 | 97.37 139 | 88.85 186 | 87.65 250 | 94.08 249 | 81.08 189 | 98.10 197 | 84.68 232 | 83.79 292 | 94.66 277 |
|
PVSNet_Blended | | | 94.87 78 | 94.56 72 | 95.81 104 | 98.27 68 | 89.46 167 | 95.47 251 | 98.36 16 | 88.84 187 | 94.36 89 | 96.09 146 | 88.02 76 | 99.58 55 | 93.44 86 | 98.18 83 | 98.40 114 |
|
ACMH+ | | 87.92 14 | 90.20 238 | 89.18 242 | 93.25 234 | 96.48 155 | 86.45 255 | 96.99 136 | 96.68 201 | 88.83 188 | 84.79 280 | 96.22 139 | 70.16 303 | 98.53 159 | 84.42 238 | 88.04 244 | 94.77 274 |
|
GBi-Net | | | 91.35 203 | 90.27 209 | 94.59 166 | 96.51 152 | 91.18 109 | 97.50 90 | 96.93 185 | 88.82 189 | 89.35 218 | 94.51 217 | 73.87 282 | 97.29 284 | 86.12 210 | 88.82 236 | 95.31 237 |
|
test1 | | | 91.35 203 | 90.27 209 | 94.59 166 | 96.51 152 | 91.18 109 | 97.50 90 | 96.93 185 | 88.82 189 | 89.35 218 | 94.51 217 | 73.87 282 | 97.29 284 | 86.12 210 | 88.82 236 | 95.31 237 |
|
FMVSNet2 | | | 91.31 205 | 90.08 216 | 94.99 143 | 96.51 152 | 92.21 76 | 97.41 98 | 96.95 183 | 88.82 189 | 88.62 231 | 94.75 209 | 73.87 282 | 97.42 276 | 85.20 226 | 88.55 242 | 95.35 235 |
|
V42 | | | 91.58 191 | 90.87 182 | 93.73 209 | 94.05 267 | 88.50 196 | 97.32 109 | 96.97 179 | 88.80 192 | 89.71 205 | 94.33 230 | 82.54 163 | 98.05 212 | 89.01 157 | 85.07 272 | 94.64 278 |
|
agg_prior1 | | | 96.22 47 | 95.77 48 | 97.56 36 | 98.67 40 | 93.79 37 | 96.28 209 | 98.00 71 | 88.76 193 | 95.68 68 | 97.55 85 | 92.70 17 | 99.57 63 | 95.01 55 | 99.32 41 | 99.32 43 |
|
BH-w/o | | | 92.14 165 | 91.75 144 | 93.31 232 | 96.99 134 | 85.73 261 | 95.67 240 | 95.69 242 | 88.73 194 | 89.26 223 | 94.82 206 | 82.97 150 | 98.07 204 | 85.26 225 | 96.32 129 | 96.13 193 |
|
test20.03 | | | 86.14 289 | 85.40 285 | 88.35 307 | 90.12 320 | 80.06 312 | 95.90 231 | 95.20 264 | 88.59 195 | 81.29 301 | 93.62 263 | 71.43 294 | 92.65 332 | 71.26 324 | 81.17 307 | 92.34 321 |
|
train_agg | | | 96.30 44 | 95.83 47 | 97.72 25 | 98.70 38 | 94.19 24 | 96.41 193 | 98.02 67 | 88.58 196 | 96.03 54 | 97.56 83 | 92.73 15 | 99.59 52 | 95.04 53 | 99.37 39 | 99.39 36 |
|
test_8 | | | | | | 98.67 40 | 94.06 30 | 96.37 200 | 98.01 69 | 88.58 196 | 95.98 59 | 97.55 85 | 92.73 15 | 99.58 55 | | | |
|
tpmrst | | | 91.44 198 | 91.32 165 | 91.79 277 | 95.15 212 | 79.20 318 | 93.42 294 | 95.37 254 | 88.55 198 | 93.49 103 | 93.67 261 | 82.49 165 | 98.27 184 | 90.41 132 | 89.34 233 | 97.90 132 |
|
v748 | | | 90.34 234 | 89.54 236 | 92.75 249 | 93.25 293 | 85.71 262 | 97.61 81 | 97.17 152 | 88.54 199 | 87.20 259 | 93.54 265 | 81.02 190 | 98.01 221 | 85.73 219 | 81.80 302 | 94.52 280 |
|
ACMH | | 87.59 16 | 90.53 231 | 89.42 238 | 93.87 199 | 96.21 165 | 87.92 226 | 97.24 114 | 96.94 184 | 88.45 200 | 83.91 289 | 96.27 138 | 71.92 290 | 98.62 152 | 84.43 237 | 89.43 232 | 95.05 255 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
conf0.01 | | | 91.74 174 | 90.67 193 | 94.94 151 | 97.55 114 | 89.68 149 | 97.64 73 | 93.14 317 | 88.43 201 | 91.24 161 | 94.30 233 | 78.91 231 | 98.45 166 | 81.28 282 | 93.57 177 | 96.70 174 |
|
conf0.002 | | | 91.74 174 | 90.67 193 | 94.94 151 | 97.55 114 | 89.68 149 | 97.64 73 | 93.14 317 | 88.43 201 | 91.24 161 | 94.30 233 | 78.91 231 | 98.45 166 | 81.28 282 | 93.57 177 | 96.70 174 |
|
thresconf0.02 | | | 91.69 181 | 90.67 193 | 94.75 160 | 97.55 114 | 89.68 149 | 97.64 73 | 93.14 317 | 88.43 201 | 91.24 161 | 94.30 233 | 78.91 231 | 98.45 166 | 81.28 282 | 93.57 177 | 96.11 194 |
|
tfpn_n400 | | | 91.69 181 | 90.67 193 | 94.75 160 | 97.55 114 | 89.68 149 | 97.64 73 | 93.14 317 | 88.43 201 | 91.24 161 | 94.30 233 | 78.91 231 | 98.45 166 | 81.28 282 | 93.57 177 | 96.11 194 |
|
tfpnconf | | | 91.69 181 | 90.67 193 | 94.75 160 | 97.55 114 | 89.68 149 | 97.64 73 | 93.14 317 | 88.43 201 | 91.24 161 | 94.30 233 | 78.91 231 | 98.45 166 | 81.28 282 | 93.57 177 | 96.11 194 |
|
tfpnview11 | | | 91.69 181 | 90.67 193 | 94.75 160 | 97.55 114 | 89.68 149 | 97.64 73 | 93.14 317 | 88.43 201 | 91.24 161 | 94.30 233 | 78.91 231 | 98.45 166 | 81.28 282 | 93.57 177 | 96.11 194 |
|
Baseline_NR-MVSNet | | | 91.20 208 | 90.62 199 | 92.95 243 | 93.83 276 | 88.03 220 | 97.01 135 | 95.12 268 | 88.42 207 | 89.70 206 | 95.13 193 | 83.47 129 | 97.44 274 | 89.66 141 | 83.24 296 | 93.37 300 |
|
v7 | | | 91.47 197 | 90.73 190 | 93.68 214 | 94.13 256 | 88.16 210 | 97.09 129 | 97.05 168 | 88.38 208 | 89.80 200 | 94.52 216 | 82.21 172 | 98.01 221 | 88.00 172 | 85.42 263 | 94.87 262 |
|
v1144 | | | 91.37 202 | 90.60 200 | 93.68 214 | 93.89 274 | 88.23 204 | 96.84 150 | 97.03 173 | 88.37 209 | 89.69 207 | 94.39 226 | 82.04 175 | 97.98 225 | 87.80 177 | 85.37 264 | 94.84 264 |
|
DP-MVS Recon | | | 95.68 57 | 95.12 62 | 97.37 41 | 99.19 24 | 94.19 24 | 97.03 131 | 98.08 50 | 88.35 210 | 95.09 80 | 97.65 72 | 89.97 59 | 99.48 77 | 92.08 106 | 98.59 75 | 98.44 111 |
|
tpm | | | 90.25 236 | 89.74 232 | 91.76 280 | 93.92 272 | 79.73 314 | 93.98 284 | 93.54 314 | 88.28 211 | 91.99 140 | 93.25 274 | 77.51 261 | 97.44 274 | 87.30 193 | 87.94 245 | 98.12 124 |
|
v10 | | | 91.04 214 | 90.23 212 | 93.49 223 | 94.12 258 | 88.16 210 | 97.32 109 | 97.08 164 | 88.26 212 | 88.29 239 | 94.22 246 | 82.17 174 | 97.97 228 | 86.45 205 | 84.12 285 | 94.33 286 |
|
v52 | | | 90.70 227 | 90.00 220 | 92.82 244 | 93.24 294 | 87.03 244 | 97.60 82 | 97.14 156 | 88.21 213 | 87.69 248 | 93.94 252 | 80.91 195 | 98.07 204 | 87.39 189 | 83.87 291 | 93.36 301 |
|
V4 | | | 90.71 226 | 90.00 220 | 92.82 244 | 93.21 297 | 87.03 244 | 97.59 84 | 97.16 155 | 88.21 213 | 87.69 248 | 93.92 254 | 80.93 194 | 98.06 209 | 87.39 189 | 83.90 290 | 93.39 299 |
|
Fast-Effi-MVS+ | | | 93.46 113 | 92.75 115 | 95.59 114 | 96.77 141 | 90.03 134 | 96.81 155 | 97.13 158 | 88.19 215 | 91.30 156 | 94.27 243 | 86.21 100 | 98.63 150 | 87.66 183 | 96.46 128 | 98.12 124 |
|
DWT-MVSNet_test | | | 90.76 221 | 89.89 224 | 93.38 229 | 95.04 218 | 83.70 284 | 95.85 233 | 94.30 300 | 88.19 215 | 90.46 175 | 92.80 278 | 73.61 286 | 98.50 162 | 88.16 169 | 90.58 220 | 97.95 130 |
|
TEST9 | | | | | | 98.70 38 | 94.19 24 | 96.41 193 | 98.02 67 | 88.17 217 | 96.03 54 | 97.56 83 | 92.74 14 | 99.59 52 | | | |
|
MDTV_nov1_ep13 | | | | 90.76 188 | | 95.22 208 | 80.33 308 | 93.03 303 | 95.28 259 | 88.14 218 | 92.84 126 | 93.83 255 | 81.34 186 | 98.08 200 | 82.86 258 | 94.34 155 | |
|
MAR-MVS | | | 94.22 87 | 93.46 97 | 96.51 73 | 98.00 82 | 92.19 79 | 97.67 66 | 97.47 122 | 88.13 219 | 93.00 120 | 95.84 154 | 84.86 117 | 99.51 74 | 87.99 173 | 98.17 84 | 97.83 137 |
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 |
PatchMatch-RL | | | 92.90 132 | 92.02 137 | 95.56 115 | 98.19 77 | 90.80 122 | 95.27 260 | 97.18 150 | 87.96 220 | 91.86 143 | 95.68 168 | 80.44 204 | 98.99 125 | 84.01 245 | 97.54 98 | 96.89 168 |
|
agg_prior3 | | | 96.16 48 | 95.67 49 | 97.62 35 | 98.67 40 | 93.88 33 | 96.41 193 | 98.00 71 | 87.93 221 | 95.81 64 | 97.47 87 | 92.33 23 | 99.59 52 | 95.04 53 | 99.37 39 | 99.39 36 |
|
PVSNet | | 86.66 18 | 92.24 160 | 91.74 146 | 93.73 209 | 97.77 101 | 83.69 285 | 92.88 304 | 96.72 196 | 87.91 222 | 93.00 120 | 94.86 202 | 78.51 241 | 99.05 123 | 86.53 202 | 97.45 103 | 98.47 107 |
|
LTVRE_ROB | | 88.41 13 | 90.99 215 | 89.92 223 | 94.19 181 | 96.18 168 | 89.55 161 | 96.31 206 | 97.09 162 | 87.88 223 | 85.67 274 | 95.91 151 | 78.79 239 | 98.57 156 | 81.50 274 | 89.98 227 | 94.44 283 |
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 |
CPTT-MVS | | | 95.57 59 | 95.19 60 | 96.70 62 | 99.27 19 | 91.48 97 | 98.33 20 | 98.11 45 | 87.79 224 | 95.17 79 | 98.03 46 | 87.09 92 | 99.61 47 | 93.51 83 | 99.42 30 | 99.02 64 |
|
v1192 | | | 91.07 212 | 90.23 212 | 93.58 220 | 93.70 279 | 87.82 229 | 96.73 163 | 97.07 165 | 87.77 225 | 89.58 210 | 94.32 231 | 80.90 198 | 97.97 228 | 86.52 203 | 85.48 261 | 94.95 256 |
|
F-COLMAP | | | 93.58 110 | 92.98 108 | 95.37 127 | 98.40 57 | 88.98 188 | 97.18 123 | 97.29 146 | 87.75 226 | 90.49 174 | 97.10 100 | 85.21 111 | 99.50 76 | 86.70 201 | 96.72 121 | 97.63 143 |
|
1314 | | | 92.81 137 | 92.03 136 | 95.14 136 | 95.33 201 | 89.52 164 | 96.04 223 | 97.44 131 | 87.72 227 | 86.25 270 | 95.33 185 | 83.84 125 | 98.79 139 | 89.26 148 | 97.05 112 | 97.11 157 |
|
test-mter | | | 90.19 239 | 89.54 236 | 92.12 267 | 94.59 237 | 80.66 303 | 94.29 277 | 92.98 323 | 87.68 228 | 90.76 171 | 92.37 286 | 67.67 311 | 98.07 204 | 88.81 163 | 96.74 119 | 97.63 143 |
|
TR-MVS | | | 91.48 196 | 90.59 201 | 94.16 183 | 96.40 159 | 87.33 235 | 95.67 240 | 95.34 258 | 87.68 228 | 91.46 149 | 95.52 176 | 76.77 263 | 98.35 178 | 82.85 259 | 93.61 174 | 96.79 171 |
|
LF4IMVS | | | 87.94 275 | 87.25 267 | 89.98 304 | 92.38 311 | 80.05 313 | 94.38 274 | 95.25 262 | 87.59 230 | 84.34 282 | 94.74 210 | 64.31 322 | 97.66 261 | 84.83 228 | 87.45 249 | 92.23 322 |
|
TransMVSNet (Re) | | | 88.94 255 | 87.56 258 | 93.08 240 | 94.35 245 | 88.45 198 | 97.73 58 | 95.23 263 | 87.47 231 | 84.26 284 | 95.29 186 | 79.86 213 | 97.33 282 | 79.44 298 | 74.44 332 | 93.45 298 |
|
v144192 | | | 91.06 213 | 90.28 208 | 93.39 228 | 93.66 281 | 87.23 240 | 96.83 151 | 97.07 165 | 87.43 232 | 89.69 207 | 94.28 241 | 81.48 184 | 98.00 224 | 87.18 196 | 84.92 278 | 94.93 260 |
|
原ACMM1 | | | | | 96.38 81 | 98.59 48 | 91.09 113 | | 97.89 82 | 87.41 233 | 95.22 78 | 97.68 69 | 90.25 54 | 99.54 67 | 87.95 174 | 99.12 59 | 98.49 104 |
|
v1921920 | | | 90.85 219 | 90.03 219 | 93.29 233 | 93.55 282 | 86.96 248 | 96.74 162 | 97.04 171 | 87.36 234 | 89.52 214 | 94.34 229 | 80.23 209 | 97.97 228 | 86.27 206 | 85.21 267 | 94.94 258 |
|
USDC | | | 88.94 255 | 87.83 257 | 92.27 257 | 94.66 234 | 84.96 271 | 93.86 286 | 95.90 231 | 87.34 235 | 83.40 291 | 95.56 173 | 67.43 313 | 98.19 189 | 82.64 263 | 89.67 231 | 93.66 295 |
|
PLC | | 91.00 6 | 94.11 92 | 93.43 99 | 96.13 94 | 98.58 50 | 91.15 112 | 96.69 173 | 97.39 136 | 87.29 236 | 91.37 151 | 96.71 110 | 88.39 74 | 99.52 73 | 87.33 192 | 97.13 111 | 97.73 140 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
tfpnnormal | | | 89.70 248 | 88.40 252 | 93.60 217 | 95.15 212 | 90.10 133 | 97.56 86 | 98.16 37 | 87.28 237 | 86.16 271 | 94.63 214 | 77.57 260 | 98.05 212 | 74.48 312 | 84.59 281 | 92.65 307 |
|
TESTMET0.1,1 | | | 90.06 241 | 89.42 238 | 91.97 271 | 94.41 244 | 80.62 305 | 94.29 277 | 91.97 332 | 87.28 237 | 90.44 176 | 92.47 285 | 68.79 306 | 97.67 259 | 88.50 167 | 96.60 124 | 97.61 147 |
|
v1240 | | | 90.70 227 | 89.85 226 | 93.23 235 | 93.51 285 | 86.80 249 | 96.61 181 | 97.02 174 | 87.16 239 | 89.58 210 | 94.31 232 | 79.55 218 | 97.98 225 | 85.52 221 | 85.44 262 | 94.90 261 |
|
Patchmatch-RL test | | | 87.38 279 | 86.24 278 | 90.81 293 | 88.74 327 | 78.40 321 | 88.12 335 | 93.17 316 | 87.11 240 | 82.17 294 | 89.29 316 | 81.95 178 | 95.60 317 | 88.64 166 | 77.02 316 | 98.41 113 |
|
v18 | | | 88.71 260 | 87.52 259 | 92.27 257 | 94.16 253 | 88.11 216 | 96.82 154 | 95.96 226 | 87.03 241 | 80.76 305 | 89.81 306 | 83.15 134 | 96.22 301 | 84.69 231 | 75.31 323 | 92.49 311 |
|
v17 | | | 88.67 262 | 87.47 262 | 92.26 259 | 94.13 256 | 88.09 218 | 96.81 155 | 95.95 227 | 87.02 242 | 80.72 306 | 89.75 308 | 83.11 137 | 96.20 302 | 84.61 234 | 75.15 325 | 92.49 311 |
|
v16 | | | 88.69 261 | 87.50 260 | 92.26 259 | 94.19 250 | 88.11 216 | 96.81 155 | 95.95 227 | 87.01 243 | 80.71 307 | 89.80 307 | 83.08 140 | 96.20 302 | 84.61 234 | 75.34 322 | 92.48 313 |
|
v15 | | | 88.53 264 | 87.31 264 | 92.20 262 | 94.09 262 | 88.05 219 | 96.72 166 | 95.90 231 | 87.01 243 | 80.53 310 | 89.60 312 | 83.02 146 | 96.13 304 | 84.29 239 | 74.64 326 | 92.41 317 |
|
V14 | | | 88.52 265 | 87.30 265 | 92.17 264 | 94.12 258 | 87.99 221 | 96.72 166 | 95.91 230 | 86.98 245 | 80.50 311 | 89.63 309 | 83.03 145 | 96.12 306 | 84.23 240 | 74.60 328 | 92.40 318 |
|
CDPH-MVS | | | 95.97 53 | 95.38 55 | 97.77 22 | 98.93 31 | 94.44 17 | 96.35 201 | 97.88 83 | 86.98 245 | 96.65 34 | 97.89 52 | 91.99 32 | 99.47 78 | 92.26 97 | 99.46 25 | 99.39 36 |
|
V9 | | | 88.49 268 | 87.26 266 | 92.18 263 | 94.12 258 | 87.97 224 | 96.73 163 | 95.90 231 | 86.95 247 | 80.40 313 | 89.61 310 | 82.98 149 | 96.13 304 | 84.14 241 | 74.55 329 | 92.44 315 |
|
v12 | | | 88.46 269 | 87.23 269 | 92.17 264 | 94.10 261 | 87.99 221 | 96.71 168 | 95.90 231 | 86.91 248 | 80.34 315 | 89.58 313 | 82.92 153 | 96.11 308 | 84.09 242 | 74.50 331 | 92.42 316 |
|
PM-MVS | | | 83.48 299 | 81.86 302 | 88.31 308 | 87.83 330 | 77.59 322 | 93.43 293 | 91.75 333 | 86.91 248 | 80.63 308 | 89.91 304 | 44.42 344 | 95.84 313 | 85.17 227 | 76.73 318 | 91.50 329 |
|
CR-MVSNet | | | 90.82 220 | 89.77 229 | 93.95 194 | 94.45 242 | 87.19 241 | 90.23 326 | 95.68 243 | 86.89 250 | 92.40 129 | 92.36 289 | 80.91 195 | 97.05 288 | 81.09 289 | 93.95 167 | 97.60 148 |
|
1112_ss | | | 93.37 116 | 92.42 130 | 96.21 92 | 97.05 132 | 90.99 114 | 96.31 206 | 96.72 196 | 86.87 251 | 89.83 199 | 96.69 114 | 86.51 97 | 99.14 106 | 88.12 170 | 93.67 171 | 98.50 102 |
|
v13 | | | 88.45 270 | 87.22 270 | 92.16 266 | 94.08 264 | 87.95 225 | 96.71 168 | 95.90 231 | 86.86 252 | 80.27 317 | 89.55 314 | 82.92 153 | 96.12 306 | 84.02 244 | 74.63 327 | 92.40 318 |
|
v11 | | | 88.41 271 | 87.19 273 | 92.08 269 | 94.08 264 | 87.77 230 | 96.75 161 | 95.85 237 | 86.74 253 | 80.50 311 | 89.50 315 | 82.49 165 | 96.08 309 | 83.55 250 | 75.20 324 | 92.38 320 |
|
FMVSNet1 | | | 89.88 245 | 88.31 253 | 94.59 166 | 95.41 194 | 91.18 109 | 97.50 90 | 96.93 185 | 86.62 254 | 87.41 254 | 94.51 217 | 65.94 319 | 97.29 284 | 83.04 256 | 87.43 250 | 95.31 237 |
|
CHOSEN 280x420 | | | 93.12 123 | 92.72 118 | 94.34 178 | 96.71 143 | 87.27 237 | 90.29 325 | 97.72 97 | 86.61 255 | 91.34 153 | 95.29 186 | 84.29 123 | 98.41 173 | 93.25 90 | 98.94 67 | 97.35 155 |
|
MIMVSNet | | | 88.50 267 | 86.76 275 | 93.72 211 | 94.84 228 | 87.77 230 | 91.39 316 | 94.05 305 | 86.41 256 | 87.99 244 | 92.59 282 | 63.27 323 | 95.82 314 | 77.44 304 | 92.84 186 | 97.57 150 |
|
tpmvs | | | 89.83 247 | 89.15 243 | 91.89 273 | 94.92 224 | 80.30 309 | 93.11 301 | 95.46 250 | 86.28 257 | 88.08 242 | 92.65 280 | 80.44 204 | 98.52 160 | 81.47 275 | 89.92 229 | 96.84 170 |
|
PAPM | | | 91.52 195 | 90.30 207 | 95.20 129 | 95.30 202 | 89.83 145 | 93.38 295 | 96.85 192 | 86.26 258 | 88.59 233 | 95.80 157 | 84.88 115 | 98.15 192 | 75.67 311 | 95.93 134 | 97.63 143 |
|
VDDNet | | | 93.05 126 | 92.07 134 | 96.02 97 | 96.84 137 | 90.39 132 | 98.08 33 | 95.85 237 | 86.22 259 | 95.79 66 | 98.46 14 | 67.59 312 | 99.19 99 | 94.92 59 | 94.85 147 | 98.47 107 |
|
MS-PatchMatch | | | 90.27 235 | 89.77 229 | 91.78 278 | 94.33 246 | 84.72 275 | 95.55 246 | 96.73 195 | 86.17 260 | 86.36 269 | 95.28 188 | 71.28 295 | 97.80 249 | 84.09 242 | 98.14 85 | 92.81 306 |
|
MVP-Stereo | | | 90.74 224 | 90.08 216 | 92.71 250 | 93.19 299 | 88.20 207 | 95.86 232 | 96.27 215 | 86.07 261 | 84.86 279 | 94.76 208 | 77.84 258 | 97.75 254 | 83.88 248 | 98.01 87 | 92.17 324 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
diffmvs | | | 93.43 115 | 92.75 115 | 95.48 122 | 96.47 156 | 89.61 157 | 96.09 220 | 97.14 156 | 85.97 262 | 93.09 118 | 95.35 184 | 84.87 116 | 98.55 158 | 89.51 144 | 96.26 130 | 98.28 120 |
|
CVMVSNet | | | 91.23 207 | 91.75 144 | 89.67 306 | 95.77 184 | 74.69 326 | 96.44 189 | 94.88 279 | 85.81 263 | 92.18 136 | 97.64 75 | 79.07 223 | 95.58 318 | 88.06 171 | 95.86 136 | 98.74 86 |
|
MSDG | | | 91.42 199 | 90.24 211 | 94.96 147 | 97.15 127 | 88.91 189 | 93.69 289 | 96.32 213 | 85.72 264 | 86.93 265 | 96.47 130 | 80.24 208 | 98.98 126 | 80.57 290 | 95.05 146 | 96.98 159 |
|
CHOSEN 1792x2688 | | | 94.15 89 | 93.51 95 | 96.06 95 | 98.27 68 | 89.38 173 | 95.18 263 | 98.48 14 | 85.60 265 | 93.76 99 | 97.11 99 | 83.15 134 | 99.61 47 | 91.33 124 | 98.72 72 | 99.19 51 |
|
AllTest | | | 90.23 237 | 88.98 244 | 93.98 190 | 97.94 89 | 86.64 251 | 96.51 188 | 95.54 248 | 85.38 266 | 85.49 276 | 96.77 108 | 70.28 301 | 99.15 104 | 80.02 293 | 92.87 184 | 96.15 191 |
|
TestCases | | | | | 93.98 190 | 97.94 89 | 86.64 251 | | 95.54 248 | 85.38 266 | 85.49 276 | 96.77 108 | 70.28 301 | 99.15 104 | 80.02 293 | 92.87 184 | 96.15 191 |
|
Test_1112_low_res | | | 92.84 136 | 91.84 142 | 95.85 103 | 97.04 133 | 89.97 140 | 95.53 248 | 96.64 204 | 85.38 266 | 89.65 209 | 95.18 190 | 85.86 105 | 99.10 114 | 87.70 179 | 93.58 176 | 98.49 104 |
|
EU-MVSNet | | | 88.72 259 | 88.90 245 | 88.20 309 | 93.15 300 | 74.21 327 | 96.63 180 | 94.22 303 | 85.18 269 | 87.32 257 | 95.97 147 | 76.16 266 | 94.98 323 | 85.27 224 | 86.17 256 | 95.41 227 |
|
LS3D | | | 93.57 111 | 92.61 122 | 96.47 76 | 97.59 111 | 91.61 93 | 97.67 66 | 97.72 97 | 85.17 270 | 90.29 179 | 98.34 27 | 84.60 119 | 99.73 25 | 83.85 249 | 98.27 81 | 98.06 128 |
|
dp | | | 88.90 257 | 88.26 255 | 90.81 293 | 94.58 239 | 76.62 323 | 92.85 305 | 94.93 277 | 85.12 271 | 90.07 192 | 93.07 275 | 75.81 267 | 98.12 195 | 80.53 291 | 87.42 251 | 97.71 141 |
|
HyFIR lowres test | | | 93.66 107 | 92.92 110 | 95.87 102 | 98.24 71 | 89.88 144 | 94.58 270 | 98.49 12 | 85.06 272 | 93.78 98 | 95.78 161 | 82.86 155 | 98.67 148 | 91.77 113 | 95.71 139 | 99.07 63 |
|
new-patchmatchnet | | | 83.18 300 | 81.87 301 | 87.11 313 | 86.88 333 | 75.99 325 | 93.70 288 | 95.18 265 | 85.02 273 | 77.30 325 | 88.40 322 | 65.99 318 | 93.88 328 | 74.19 316 | 70.18 336 | 91.47 330 |
|
TDRefinement | | | 86.53 285 | 84.76 290 | 91.85 274 | 82.23 341 | 84.25 277 | 96.38 199 | 95.35 255 | 84.97 274 | 84.09 287 | 94.94 195 | 65.76 320 | 98.34 180 | 84.60 236 | 74.52 330 | 92.97 302 |
|
OpenMVS | | 89.19 12 | 92.86 134 | 91.68 147 | 96.40 79 | 95.34 198 | 92.73 64 | 98.27 23 | 98.12 42 | 84.86 275 | 85.78 273 | 97.75 65 | 78.89 238 | 99.74 24 | 87.50 188 | 98.65 73 | 96.73 172 |
|
gm-plane-assit | | | | | | 93.22 296 | 78.89 320 | | | 84.82 276 | | 93.52 266 | | 98.64 149 | 87.72 178 | | |
|
PMMVS | | | 92.86 134 | 92.34 131 | 94.42 175 | 94.92 224 | 86.73 250 | 94.53 272 | 96.38 211 | 84.78 277 | 94.27 91 | 95.12 194 | 83.13 136 | 98.40 174 | 91.47 122 | 96.49 126 | 98.12 124 |
|
pmmvs4 | | | 90.93 217 | 89.85 226 | 94.17 182 | 93.34 290 | 90.79 123 | 94.60 269 | 96.02 225 | 84.62 278 | 87.45 252 | 95.15 191 | 81.88 180 | 97.45 273 | 87.70 179 | 87.87 246 | 94.27 289 |
|
MDA-MVSNet-bldmvs | | | 85.00 295 | 82.95 297 | 91.17 288 | 93.13 301 | 83.33 287 | 94.56 271 | 95.00 273 | 84.57 279 | 65.13 339 | 92.65 280 | 70.45 300 | 95.85 312 | 73.57 317 | 77.49 315 | 94.33 286 |
|
QAPM | | | 93.45 114 | 92.27 132 | 96.98 59 | 96.77 141 | 92.62 67 | 98.39 18 | 98.12 42 | 84.50 280 | 88.27 240 | 97.77 64 | 82.39 169 | 99.81 19 | 85.40 223 | 98.81 69 | 98.51 100 |
|
pmmvs5 | | | 89.86 246 | 88.87 246 | 92.82 244 | 92.86 303 | 86.23 257 | 96.26 210 | 95.39 252 | 84.24 281 | 87.12 260 | 94.51 217 | 74.27 280 | 97.36 281 | 87.61 186 | 87.57 248 | 94.86 263 |
|
CostFormer | | | 91.18 211 | 90.70 191 | 92.62 253 | 94.84 228 | 81.76 297 | 94.09 283 | 94.43 294 | 84.15 282 | 92.72 127 | 93.77 258 | 79.43 219 | 98.20 187 | 90.70 131 | 92.18 195 | 97.90 132 |
|
FMVSNet5 | | | 87.29 281 | 85.79 282 | 91.78 278 | 94.80 230 | 87.28 236 | 95.49 250 | 95.28 259 | 84.09 283 | 83.85 290 | 91.82 295 | 62.95 324 | 94.17 326 | 78.48 301 | 85.34 265 | 93.91 293 |
|
MIMVSNet1 | | | 84.93 296 | 83.05 296 | 90.56 298 | 89.56 325 | 84.84 274 | 95.40 253 | 95.35 255 | 83.91 284 | 80.38 314 | 92.21 293 | 57.23 332 | 93.34 330 | 70.69 326 | 82.75 301 | 93.50 296 |
|
RPSCF | | | 90.75 223 | 90.86 183 | 90.42 300 | 96.84 137 | 76.29 324 | 95.61 245 | 96.34 212 | 83.89 285 | 91.38 150 | 97.87 55 | 76.45 264 | 98.78 140 | 87.16 197 | 92.23 192 | 96.20 187 |
|
MDTV_nov1_ep13_2view | | | | | | | 70.35 334 | 93.10 302 | | 83.88 286 | 93.55 101 | | 82.47 167 | | 86.25 207 | | 98.38 117 |
|
无先验 | | | | | | | | 95.79 236 | 97.87 85 | 83.87 287 | | | | 99.65 41 | 87.68 181 | | 98.89 80 |
|
PVSNet_0 | | 82.17 19 | 85.46 294 | 83.64 295 | 90.92 291 | 95.27 203 | 79.49 315 | 90.55 324 | 95.60 245 | 83.76 288 | 83.00 292 | 89.95 303 | 71.09 296 | 97.97 228 | 82.75 261 | 60.79 342 | 95.31 237 |
|
TinyColmap | | | 86.82 284 | 85.35 286 | 91.21 287 | 94.91 226 | 82.99 289 | 93.94 285 | 94.02 307 | 83.58 289 | 81.56 300 | 94.68 211 | 62.34 326 | 98.13 193 | 75.78 310 | 87.35 253 | 92.52 310 |
|
Anonymous20231206 | | | 87.09 282 | 86.14 280 | 89.93 305 | 91.22 317 | 80.35 307 | 96.11 219 | 95.35 255 | 83.57 290 | 84.16 285 | 93.02 276 | 73.54 287 | 95.61 316 | 72.16 320 | 86.14 257 | 93.84 294 |
|
pmmvs-eth3d | | | 86.22 288 | 84.45 291 | 91.53 283 | 88.34 328 | 87.25 238 | 94.47 273 | 95.01 272 | 83.47 291 | 79.51 321 | 89.61 310 | 69.75 304 | 95.71 315 | 83.13 255 | 76.73 318 | 91.64 326 |
|
EG-PatchMatch MVS | | | 87.02 283 | 85.44 284 | 91.76 280 | 92.67 307 | 85.00 270 | 96.08 222 | 96.45 209 | 83.41 292 | 79.52 320 | 93.49 268 | 57.10 333 | 97.72 256 | 79.34 299 | 90.87 217 | 92.56 309 |
|
ADS-MVSNet2 | | | 89.45 251 | 88.59 249 | 92.03 270 | 95.86 179 | 82.26 294 | 90.93 321 | 94.32 299 | 83.23 293 | 91.28 159 | 91.81 296 | 79.01 228 | 95.99 310 | 79.52 295 | 91.39 209 | 97.84 135 |
|
ADS-MVSNet | | | 89.89 244 | 88.68 248 | 93.53 222 | 95.86 179 | 84.89 273 | 90.93 321 | 95.07 271 | 83.23 293 | 91.28 159 | 91.81 296 | 79.01 228 | 97.85 244 | 79.52 295 | 91.39 209 | 97.84 135 |
|
COLMAP_ROB | | 87.81 15 | 90.40 233 | 89.28 240 | 93.79 202 | 97.95 88 | 87.13 243 | 96.92 145 | 95.89 236 | 82.83 295 | 86.88 267 | 97.18 95 | 73.77 285 | 99.29 94 | 78.44 302 | 93.62 173 | 94.95 256 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
testdata | | | | | 95.46 124 | 98.18 78 | 88.90 190 | | 97.66 103 | 82.73 296 | 97.03 29 | 98.07 44 | 90.06 57 | 98.85 135 | 89.67 140 | 98.98 65 | 98.64 93 |
|
testus | | | 82.63 303 | 82.15 299 | 84.07 319 | 87.31 332 | 67.67 338 | 93.18 296 | 94.29 301 | 82.47 297 | 82.14 295 | 90.69 301 | 53.01 339 | 91.94 335 | 66.30 330 | 89.96 228 | 92.62 308 |
|
DP-MVS | | | 92.76 138 | 91.51 161 | 96.52 70 | 98.77 35 | 90.99 114 | 97.38 104 | 96.08 224 | 82.38 298 | 89.29 221 | 97.87 55 | 83.77 126 | 99.69 35 | 81.37 280 | 96.69 122 | 98.89 80 |
|
MDA-MVSNet_test_wron | | | 85.87 291 | 84.23 293 | 90.80 295 | 92.38 311 | 82.57 290 | 93.17 298 | 95.15 266 | 82.15 299 | 67.65 335 | 92.33 292 | 78.20 245 | 95.51 319 | 77.33 305 | 79.74 310 | 94.31 288 |
|
YYNet1 | | | 85.87 291 | 84.23 293 | 90.78 296 | 92.38 311 | 82.46 292 | 93.17 298 | 95.14 267 | 82.12 300 | 67.69 334 | 92.36 289 | 78.16 248 | 95.50 320 | 77.31 306 | 79.73 311 | 94.39 284 |
|
PatchT | | | 88.87 258 | 87.42 263 | 93.22 236 | 94.08 264 | 85.10 269 | 89.51 330 | 94.64 288 | 81.92 301 | 92.36 132 | 88.15 325 | 80.05 211 | 97.01 292 | 72.43 319 | 93.65 172 | 97.54 151 |
|
TAPA-MVS | | 90.10 7 | 92.30 157 | 91.22 171 | 95.56 115 | 98.33 64 | 89.60 158 | 96.79 158 | 97.65 105 | 81.83 302 | 91.52 148 | 97.23 94 | 87.94 78 | 98.91 129 | 71.31 323 | 98.37 79 | 98.17 122 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
旧先验2 | | | | | | | | 95.94 229 | | 81.66 303 | 97.34 17 | | | 98.82 137 | 92.26 97 | | |
|
tpmp4_e23 | | | 89.58 249 | 88.59 249 | 92.54 254 | 95.16 211 | 81.53 298 | 94.11 282 | 95.09 269 | 81.66 303 | 88.60 232 | 93.44 271 | 75.11 273 | 98.33 181 | 82.45 264 | 91.72 202 | 97.75 139 |
|
新几何1 | | | | | 97.32 43 | 98.60 47 | 93.59 43 | | 97.75 92 | 81.58 305 | 95.75 67 | 97.85 58 | 90.04 58 | 99.67 39 | 86.50 204 | 99.13 56 | 98.69 91 |
|
test2356 | | | 82.77 302 | 82.14 300 | 84.65 318 | 85.77 335 | 70.36 333 | 91.22 319 | 93.69 313 | 81.58 305 | 81.82 297 | 89.00 318 | 60.63 329 | 90.77 338 | 64.74 331 | 90.80 218 | 92.82 304 |
|
1121 | | | 94.71 81 | 93.83 84 | 97.34 42 | 98.57 51 | 93.64 42 | 96.04 223 | 97.73 94 | 81.56 307 | 95.68 68 | 97.85 58 | 90.23 55 | 99.65 41 | 87.68 181 | 99.12 59 | 98.73 87 |
|
Patchmatch-test | | | 89.42 252 | 87.99 256 | 93.70 212 | 95.27 203 | 85.11 268 | 88.98 332 | 94.37 297 | 81.11 308 | 87.10 262 | 93.69 259 | 82.28 170 | 97.50 270 | 74.37 314 | 94.76 150 | 98.48 106 |
|
test_0402 | | | 86.46 286 | 84.79 289 | 91.45 284 | 95.02 219 | 85.55 264 | 96.29 208 | 94.89 278 | 80.90 309 | 82.21 293 | 93.97 251 | 68.21 310 | 97.29 284 | 62.98 333 | 88.68 241 | 91.51 328 |
|
gg-mvs-nofinetune | | | 87.82 276 | 85.61 283 | 94.44 173 | 94.46 241 | 89.27 183 | 91.21 320 | 84.61 348 | 80.88 310 | 89.89 196 | 74.98 340 | 71.50 293 | 97.53 268 | 85.75 218 | 97.21 109 | 96.51 180 |
|
JIA-IIPM | | | 88.26 273 | 87.04 274 | 91.91 272 | 93.52 284 | 81.42 299 | 89.38 331 | 94.38 296 | 80.84 311 | 90.93 170 | 80.74 337 | 79.22 222 | 97.92 238 | 82.76 260 | 91.62 204 | 96.38 185 |
|
Patchmtry | | | 88.64 263 | 87.25 267 | 92.78 248 | 94.09 262 | 86.64 251 | 89.82 329 | 95.68 243 | 80.81 312 | 87.63 251 | 92.36 289 | 80.91 195 | 97.03 290 | 78.86 300 | 85.12 268 | 94.67 276 |
|
tpm2 | | | 89.96 242 | 89.21 241 | 92.23 261 | 94.91 226 | 81.25 300 | 93.78 287 | 94.42 295 | 80.62 313 | 91.56 147 | 93.44 271 | 76.44 265 | 97.94 234 | 85.60 220 | 92.08 199 | 97.49 152 |
|
pmmvs6 | | | 87.81 277 | 86.19 279 | 92.69 251 | 91.32 316 | 86.30 256 | 97.34 106 | 96.41 210 | 80.59 314 | 84.05 288 | 94.37 228 | 67.37 314 | 97.67 259 | 84.75 230 | 79.51 312 | 94.09 291 |
|
cascas | | | 91.20 208 | 90.08 216 | 94.58 170 | 94.97 220 | 89.16 186 | 93.65 291 | 97.59 110 | 79.90 315 | 89.40 216 | 92.92 277 | 75.36 272 | 98.36 177 | 92.14 102 | 94.75 151 | 96.23 186 |
|
PCF-MVS | | 89.48 11 | 91.56 192 | 89.95 222 | 96.36 83 | 96.60 145 | 92.52 70 | 92.51 309 | 97.26 147 | 79.41 316 | 88.90 226 | 96.56 126 | 84.04 124 | 99.55 65 | 77.01 308 | 97.30 107 | 97.01 158 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
test1235678 | | | 79.82 308 | 78.53 309 | 83.69 320 | 82.55 340 | 67.55 339 | 92.50 310 | 94.13 304 | 79.28 317 | 72.10 332 | 86.45 333 | 57.27 331 | 90.68 339 | 61.60 336 | 80.90 308 | 92.82 304 |
|
test222 | | | | | | 98.24 71 | 92.21 76 | 95.33 255 | 97.60 108 | 79.22 318 | 95.25 77 | 97.84 60 | 88.80 68 | | | 99.15 54 | 98.72 88 |
|
UnsupCasMVSNet_bld | | | 82.13 305 | 79.46 307 | 90.14 303 | 88.00 329 | 82.47 291 | 90.89 323 | 96.62 207 | 78.94 319 | 75.61 326 | 84.40 335 | 56.63 334 | 96.31 299 | 77.30 307 | 66.77 341 | 91.63 327 |
|
testpf | | | 80.97 306 | 81.40 304 | 79.65 325 | 91.53 315 | 72.43 331 | 73.47 347 | 89.55 340 | 78.63 320 | 80.81 303 | 89.06 317 | 61.36 327 | 91.36 337 | 83.34 252 | 84.89 279 | 75.15 344 |
|
N_pmnet | | | 78.73 309 | 78.71 308 | 78.79 327 | 92.80 305 | 46.50 354 | 94.14 281 | 43.71 357 | 78.61 321 | 80.83 302 | 91.66 299 | 74.94 277 | 96.36 298 | 67.24 328 | 84.45 283 | 93.50 296 |
|
ANet_high | | | 63.94 320 | 59.58 321 | 77.02 329 | 61.24 354 | 66.06 340 | 85.66 340 | 87.93 343 | 78.53 322 | 42.94 346 | 71.04 344 | 25.42 354 | 80.71 348 | 52.60 345 | 30.83 349 | 84.28 339 |
|
114514_t | | | 93.95 98 | 93.06 107 | 96.63 65 | 99.07 28 | 91.61 93 | 97.46 97 | 97.96 79 | 77.99 323 | 93.00 120 | 97.57 81 | 86.14 103 | 99.33 92 | 89.22 150 | 99.15 54 | 98.94 74 |
|
DSMNet-mixed | | | 86.34 287 | 86.12 281 | 87.00 314 | 89.88 323 | 70.43 332 | 94.93 266 | 90.08 339 | 77.97 324 | 85.42 278 | 92.78 279 | 74.44 279 | 93.96 327 | 74.43 313 | 95.14 144 | 96.62 178 |
|
RPMNet | | | 88.52 265 | 86.72 277 | 93.95 194 | 94.45 242 | 87.19 241 | 90.23 326 | 94.99 274 | 77.87 325 | 92.40 129 | 87.55 330 | 80.17 210 | 97.05 288 | 68.84 327 | 93.95 167 | 97.60 148 |
|
LP | | | 84.13 298 | 81.85 303 | 90.97 290 | 93.20 298 | 82.12 295 | 87.68 336 | 94.27 302 | 76.80 326 | 81.93 296 | 88.52 320 | 72.97 289 | 95.95 311 | 59.53 338 | 81.73 303 | 94.84 264 |
|
new_pmnet | | | 82.89 301 | 81.12 306 | 88.18 310 | 89.63 324 | 80.18 311 | 91.77 315 | 92.57 329 | 76.79 327 | 75.56 327 | 88.23 324 | 61.22 328 | 94.48 324 | 71.43 322 | 82.92 299 | 89.87 333 |
|
test12356 | | | 74.97 312 | 74.13 313 | 77.49 328 | 78.81 342 | 56.23 350 | 88.53 334 | 92.75 327 | 75.14 328 | 67.50 336 | 85.07 334 | 44.88 343 | 89.96 340 | 58.71 339 | 75.75 320 | 86.26 336 |
|
1111 | | | 78.29 310 | 77.55 310 | 80.50 323 | 83.89 336 | 59.98 346 | 91.89 313 | 93.71 310 | 75.06 329 | 73.60 330 | 87.67 328 | 55.66 335 | 92.60 333 | 58.54 340 | 77.92 314 | 88.93 335 |
|
.test1245 | | | 65.38 319 | 69.22 317 | 53.86 339 | 83.89 336 | 59.98 346 | 91.89 313 | 93.71 310 | 75.06 329 | 73.60 330 | 87.67 328 | 55.66 335 | 92.60 333 | 58.54 340 | 2.96 353 | 9.00 353 |
|
tpm cat1 | | | 88.36 272 | 87.21 271 | 91.81 276 | 95.13 214 | 80.55 306 | 92.58 308 | 95.70 241 | 74.97 331 | 87.45 252 | 91.96 294 | 78.01 257 | 98.17 191 | 80.39 292 | 88.74 239 | 96.72 173 |
|
testmv | | | 72.22 314 | 70.02 314 | 78.82 326 | 73.06 349 | 61.75 344 | 91.24 318 | 92.31 330 | 74.45 332 | 61.06 341 | 80.51 338 | 34.21 347 | 88.63 343 | 55.31 343 | 68.07 340 | 86.06 337 |
|
CMPMVS | | 62.92 21 | 85.62 293 | 84.92 288 | 87.74 311 | 89.14 326 | 73.12 330 | 94.17 280 | 96.80 194 | 73.98 333 | 73.65 329 | 94.93 196 | 66.36 316 | 97.61 264 | 83.95 247 | 91.28 211 | 92.48 313 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
OpenMVS_ROB | | 81.14 20 | 84.42 297 | 82.28 298 | 90.83 292 | 90.06 321 | 84.05 281 | 95.73 239 | 94.04 306 | 73.89 334 | 80.17 319 | 91.53 300 | 59.15 330 | 97.64 262 | 66.92 329 | 89.05 235 | 90.80 331 |
|
MVS | | | 91.71 176 | 90.44 203 | 95.51 118 | 95.20 210 | 91.59 95 | 96.04 223 | 97.45 128 | 73.44 335 | 87.36 256 | 95.60 171 | 85.42 109 | 99.10 114 | 85.97 214 | 97.46 99 | 95.83 208 |
|
no-one | | | 68.12 317 | 63.78 320 | 81.13 322 | 74.01 346 | 70.22 335 | 87.61 337 | 90.71 338 | 72.63 336 | 53.13 344 | 71.89 343 | 30.29 349 | 91.45 336 | 61.53 337 | 32.21 347 | 81.72 341 |
|
pmmvs3 | | | 79.97 307 | 77.50 311 | 87.39 312 | 82.80 339 | 79.38 317 | 92.70 307 | 90.75 337 | 70.69 337 | 78.66 322 | 87.47 331 | 51.34 341 | 93.40 329 | 73.39 318 | 69.65 337 | 89.38 334 |
|
Anonymous20231211 | | | 78.22 311 | 75.30 312 | 86.99 315 | 86.14 334 | 74.16 328 | 95.62 244 | 93.88 309 | 66.43 338 | 74.44 328 | 87.86 327 | 41.39 345 | 95.11 322 | 62.49 334 | 69.46 338 | 91.71 325 |
|
MVS-HIRNet | | | 82.47 304 | 81.21 305 | 86.26 317 | 95.38 196 | 69.21 337 | 88.96 333 | 89.49 341 | 66.28 339 | 80.79 304 | 74.08 342 | 68.48 308 | 97.39 279 | 71.93 321 | 95.47 140 | 92.18 323 |
|
DeepMVS_CX | | | | | 74.68 332 | 90.84 318 | 64.34 343 | | 81.61 352 | 65.34 340 | 67.47 337 | 88.01 326 | 48.60 342 | 80.13 349 | 62.33 335 | 73.68 334 | 79.58 342 |
|
PMMVS2 | | | 70.19 316 | 66.92 318 | 80.01 324 | 76.35 343 | 65.67 341 | 86.22 338 | 87.58 344 | 64.83 341 | 62.38 340 | 80.29 339 | 26.78 353 | 88.49 344 | 63.79 332 | 54.07 343 | 85.88 338 |
|
FPMVS | | | 71.27 315 | 69.85 315 | 75.50 330 | 74.64 344 | 59.03 348 | 91.30 317 | 91.50 334 | 58.80 342 | 57.92 342 | 88.28 323 | 29.98 351 | 85.53 346 | 53.43 344 | 82.84 300 | 81.95 340 |
|
LCM-MVSNet | | | 72.55 313 | 69.39 316 | 82.03 321 | 70.81 351 | 65.42 342 | 90.12 328 | 94.36 298 | 55.02 343 | 65.88 338 | 81.72 336 | 24.16 355 | 89.96 340 | 74.32 315 | 68.10 339 | 90.71 332 |
|
Gipuma | | | 67.86 318 | 65.41 319 | 75.18 331 | 92.66 308 | 73.45 329 | 66.50 349 | 94.52 293 | 53.33 344 | 57.80 343 | 66.07 346 | 30.81 348 | 89.20 342 | 48.15 347 | 78.88 313 | 62.90 348 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
PNet_i23d | | | 59.01 321 | 55.87 322 | 68.44 334 | 73.98 347 | 51.37 351 | 81.36 343 | 82.41 350 | 52.37 345 | 42.49 348 | 70.39 345 | 11.39 356 | 79.99 350 | 49.77 346 | 38.71 345 | 73.97 345 |
|
wuykxyi23d | | | 56.92 323 | 51.11 327 | 74.38 333 | 62.30 353 | 61.47 345 | 80.09 344 | 84.87 347 | 49.62 346 | 30.80 352 | 57.20 350 | 7.03 358 | 82.94 347 | 55.69 342 | 32.36 346 | 78.72 343 |
|
PMVS | | 53.92 22 | 58.58 322 | 55.40 323 | 68.12 335 | 51.00 355 | 48.64 352 | 78.86 345 | 87.10 346 | 46.77 347 | 35.84 351 | 74.28 341 | 8.76 357 | 86.34 345 | 42.07 348 | 73.91 333 | 69.38 346 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
E-PMN | | | 53.28 324 | 52.56 325 | 55.43 337 | 74.43 345 | 47.13 353 | 83.63 342 | 76.30 353 | 42.23 348 | 42.59 347 | 62.22 348 | 28.57 352 | 74.40 351 | 31.53 350 | 31.51 348 | 44.78 349 |
|
EMVS | | | 52.08 326 | 51.31 326 | 54.39 338 | 72.62 350 | 45.39 355 | 83.84 341 | 75.51 354 | 41.13 349 | 40.77 349 | 59.65 349 | 30.08 350 | 73.60 352 | 28.31 351 | 29.90 350 | 44.18 350 |
|
MVE | | 50.73 23 | 53.25 325 | 48.81 328 | 66.58 336 | 65.34 352 | 57.50 349 | 72.49 348 | 70.94 355 | 40.15 350 | 39.28 350 | 63.51 347 | 6.89 360 | 73.48 353 | 38.29 349 | 42.38 344 | 68.76 347 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
tmp_tt | | | 51.94 327 | 53.82 324 | 46.29 340 | 33.73 356 | 45.30 356 | 78.32 346 | 67.24 356 | 18.02 351 | 50.93 345 | 87.05 332 | 52.99 340 | 53.11 354 | 70.76 325 | 25.29 351 | 40.46 351 |
|
wuyk23d | | | 25.11 329 | 24.57 331 | 26.74 342 | 73.98 347 | 39.89 357 | 57.88 350 | 9.80 358 | 12.27 352 | 10.39 353 | 6.97 356 | 7.03 358 | 36.44 355 | 25.43 352 | 17.39 352 | 3.89 355 |
|
testmvs | | | 13.36 331 | 16.33 332 | 4.48 344 | 5.04 357 | 2.26 359 | 93.18 296 | 3.28 359 | 2.70 353 | 8.24 354 | 21.66 352 | 2.29 362 | 2.19 356 | 7.58 353 | 2.96 353 | 9.00 353 |
|
test123 | | | 13.04 332 | 15.66 333 | 5.18 343 | 4.51 358 | 3.45 358 | 92.50 310 | 1.81 360 | 2.50 354 | 7.58 355 | 20.15 353 | 3.67 361 | 2.18 357 | 7.13 354 | 1.07 355 | 9.90 352 |
|
cdsmvs_eth3d_5k | | | 23.24 330 | 30.99 330 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 97.63 107 | 0.00 355 | 0.00 356 | 96.88 105 | 84.38 122 | 0.00 358 | 0.00 355 | 0.00 356 | 0.00 356 |
|
pcd_1.5k_mvsjas | | | 7.39 334 | 9.85 335 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 0.00 361 | 0.00 355 | 0.00 356 | 0.00 357 | 88.65 70 | 0.00 358 | 0.00 355 | 0.00 356 | 0.00 356 |
|
pcd1.5k->3k | | | 38.37 328 | 40.51 329 | 31.96 341 | 94.29 248 | 0.00 360 | 0.00 351 | 97.69 101 | 0.00 355 | 0.00 356 | 0.00 357 | 81.45 185 | 0.00 358 | 0.00 355 | 91.11 213 | 95.89 203 |
|
sosnet-low-res | | | 0.00 335 | 0.00 336 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 0.00 361 | 0.00 355 | 0.00 356 | 0.00 357 | 0.00 363 | 0.00 358 | 0.00 355 | 0.00 356 | 0.00 356 |
|
sosnet | | | 0.00 335 | 0.00 336 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 0.00 361 | 0.00 355 | 0.00 356 | 0.00 357 | 0.00 363 | 0.00 358 | 0.00 355 | 0.00 356 | 0.00 356 |
|
uncertanet | | | 0.00 335 | 0.00 336 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 0.00 361 | 0.00 355 | 0.00 356 | 0.00 357 | 0.00 363 | 0.00 358 | 0.00 355 | 0.00 356 | 0.00 356 |
|
Regformer | | | 0.00 335 | 0.00 336 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 0.00 361 | 0.00 355 | 0.00 356 | 0.00 357 | 0.00 363 | 0.00 358 | 0.00 355 | 0.00 356 | 0.00 356 |
|
ab-mvs-re | | | 8.06 333 | 10.74 334 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 0.00 361 | 0.00 355 | 0.00 356 | 96.69 114 | 0.00 363 | 0.00 358 | 0.00 355 | 0.00 356 | 0.00 356 |
|
uanet | | | 0.00 335 | 0.00 336 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 0.00 361 | 0.00 355 | 0.00 356 | 0.00 357 | 0.00 363 | 0.00 358 | 0.00 355 | 0.00 356 | 0.00 356 |
|
GSMVS | | | | | | | | | | | | | | | | | 98.45 109 |
|
test_part2 | | | | | | 99.28 17 | 95.74 3 | | | | 98.10 6 | | | | | | |
|
test_part1 | | | | | | | | | 98.26 25 | | | | 95.31 1 | | | 99.63 4 | 99.63 5 |
|
sam_mvs1 | | | | | | | | | | | | | 82.76 158 | | | | 98.45 109 |
|
sam_mvs | | | | | | | | | | | | | 81.94 179 | | | | |
|
ambc | | | | | 86.56 316 | 83.60 338 | 70.00 336 | 85.69 339 | 94.97 275 | | 80.60 309 | 88.45 321 | 37.42 346 | 96.84 295 | 82.69 262 | 75.44 321 | 92.86 303 |
|
MTGPA | | | | | | | | | 98.08 50 | | | | | | | | |
|
test_post1 | | | | | | | | 92.81 306 | | | | 16.58 355 | 80.53 202 | 97.68 258 | 86.20 208 | | |
|
test_post | | | | | | | | | | | | 17.58 354 | 81.76 181 | 98.08 200 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 90.45 302 | 82.65 162 | 98.10 197 | | | |
|
GG-mvs-BLEND | | | | | 93.62 216 | 93.69 280 | 89.20 184 | 92.39 312 | 83.33 349 | | 87.98 245 | 89.84 305 | 71.00 297 | 96.87 294 | 82.08 268 | 95.40 141 | 94.80 270 |
|
MTMP | | | | | | | | | 82.03 351 | | | | | | | | |
|
test9_res | | | | | | | | | | | | | | | 94.81 62 | 99.38 35 | 99.45 30 |
|
agg_prior2 | | | | | | | | | | | | | | | 93.94 74 | 99.38 35 | 99.50 24 |
|
agg_prior | | | | | | 98.67 40 | 93.79 37 | | 98.00 71 | | 95.68 68 | | | 99.57 63 | | | |
|
test_prior4 | | | | | | | 93.66 41 | 96.42 192 | | | | | | | | | |
|
test_prior | | | | | 97.23 49 | 98.67 40 | 92.99 57 | | 98.00 71 | | | | | 99.41 85 | | | 99.29 45 |
|
新几何2 | | | | | | | | 95.79 236 | | | | | | | | | |
|
旧先验1 | | | | | | 98.38 60 | 93.38 49 | | 97.75 92 | | | 98.09 43 | 92.30 27 | | | 99.01 64 | 99.16 53 |
|
原ACMM2 | | | | | | | | 95.67 240 | | | | | | | | | |
|
testdata2 | | | | | | | | | | | | | | 99.67 39 | 85.96 215 | | |
|
segment_acmp | | | | | | | | | | | | | 92.89 12 | | | | |
|
test12 | | | | | 97.65 30 | 98.46 53 | 94.26 21 | | 97.66 103 | | 95.52 76 | | 90.89 48 | 99.46 79 | | 99.25 46 | 99.22 50 |
|
plane_prior7 | | | | | | 96.21 165 | 89.98 139 | | | | | | | | | | |
|
plane_prior6 | | | | | | 96.10 175 | 90.00 135 | | | | | | 81.32 187 | | | | |
|
plane_prior5 | | | | | | | | | 97.51 117 | | | | | 98.60 153 | 93.02 92 | 92.23 192 | 95.86 204 |
|
plane_prior4 | | | | | | | | | | | | 96.64 117 | | | | | |
|
plane_prior1 | | | | | | 96.14 173 | | | | | | | | | | | |
|
n2 | | | | | | | | | 0.00 361 | | | | | | | | |
|
nn | | | | | | | | | 0.00 361 | | | | | | | | |
|
door-mid | | | | | | | | | 91.06 336 | | | | | | | | |
|
lessismore_v0 | | | | | 90.45 299 | 91.96 314 | 79.09 319 | | 87.19 345 | | 80.32 316 | 94.39 226 | 66.31 317 | 97.55 267 | 84.00 246 | 76.84 317 | 94.70 275 |
|
test11 | | | | | | | | | 97.88 83 | | | | | | | | |
|
door | | | | | | | | | 91.13 335 | | | | | | | | |
|
HQP5-MVS | | | | | | | 89.33 177 | | | | | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 92.13 103 | | |
|
HQP4-MVS | | | | | | | | | | | 90.14 181 | | | 98.50 162 | | | 95.78 211 |
|
HQP3-MVS | | | | | | | | | 97.39 136 | | | | | | | 92.10 197 | |
|
HQP2-MVS | | | | | | | | | | | | | 80.95 192 | | | | |
|
NP-MVS | | | | | | 95.99 178 | 89.81 146 | | | | | 95.87 152 | | | | | |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 90.30 225 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 91.02 215 | |
|
Test By Simon | | | | | | | | | | | | | 88.73 69 | | | | |
|