MVS | | | 90.60 75 | 88.64 93 | 96.50 1 | 94.25 140 | 90.53 4 | 93.33 234 | 97.21 22 | 77.59 233 | 78.88 190 | 97.31 68 | 71.52 156 | 99.69 27 | 89.60 73 | 98.03 44 | 99.27 6 |
|
DELS-MVS | | | 94.98 7 | 94.49 13 | 96.44 2 | 96.42 79 | 90.59 3 | 99.21 2 | 97.02 37 | 94.40 5 | 91.46 54 | 97.08 78 | 83.32 32 | 99.69 27 | 92.83 43 | 98.70 21 | 99.04 12 |
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 |
MCST-MVS | | | 96.17 2 | 96.12 4 | 96.32 3 | 99.42 2 | 89.36 5 | 98.94 9 | 97.10 32 | 95.17 2 | 92.11 47 | 98.46 10 | 87.33 8 | 99.97 1 | 97.21 6 | 99.31 1 | 99.63 2 |
|
PS-MVSNAJ | | | 94.17 18 | 93.52 28 | 96.10 4 | 95.65 101 | 92.35 1 | 98.21 23 | 95.79 133 | 92.42 12 | 96.24 5 | 98.18 17 | 71.04 161 | 99.17 73 | 96.77 9 | 97.39 58 | 96.79 125 |
|
MVS_0304 | | | 93.82 28 | 93.11 34 | 95.95 5 | 96.79 76 | 89.15 7 | 98.56 15 | 95.30 158 | 93.61 9 | 94.82 22 | 98.02 33 | 66.60 196 | 99.88 7 | 96.94 8 | 97.39 58 | 98.81 20 |
|
xiu_mvs_v2_base | | | 93.92 25 | 93.26 30 | 95.91 6 | 95.07 117 | 92.02 2 | 98.19 24 | 95.68 137 | 92.06 14 | 96.01 9 | 98.14 22 | 70.83 164 | 98.96 87 | 96.74 10 | 96.57 72 | 96.76 128 |
|
MG-MVS | | | 94.25 17 | 93.72 24 | 95.85 7 | 99.38 3 | 89.35 6 | 97.98 32 | 98.09 14 | 89.99 29 | 92.34 46 | 96.97 81 | 81.30 47 | 98.99 85 | 88.54 82 | 98.88 14 | 99.20 8 |
|
CANet | | | 94.89 8 | 94.64 11 | 95.63 8 | 97.55 60 | 88.12 11 | 99.06 5 | 96.39 97 | 94.07 7 | 95.34 13 | 97.80 47 | 76.83 96 | 99.87 8 | 97.08 7 | 97.64 51 | 98.89 17 |
|
WTY-MVS | | | 92.65 47 | 91.68 55 | 95.56 9 | 96.00 89 | 88.90 8 | 98.23 22 | 97.65 16 | 88.57 40 | 89.82 72 | 97.22 73 | 79.29 63 | 99.06 81 | 89.57 74 | 88.73 138 | 98.73 25 |
|
CNVR-MVS | | | 96.30 1 | 96.54 1 | 95.55 10 | 99.31 5 | 87.69 17 | 99.06 5 | 97.12 25 | 94.66 3 | 96.79 3 | 98.78 4 | 86.42 12 | 99.95 2 | 97.59 4 | 99.18 3 | 99.00 14 |
|
canonicalmvs | | | 92.27 52 | 91.22 60 | 95.41 11 | 95.80 98 | 88.31 9 | 97.09 93 | 94.64 189 | 88.49 43 | 92.99 41 | 97.31 68 | 72.68 146 | 98.57 99 | 93.38 37 | 88.58 140 | 99.36 4 |
|
HY-MVS | | 84.06 6 | 91.63 60 | 90.37 68 | 95.39 12 | 96.12 84 | 88.25 10 | 90.22 279 | 97.58 18 | 88.33 46 | 90.50 67 | 91.96 170 | 79.26 65 | 99.06 81 | 90.29 67 | 89.07 134 | 98.88 18 |
|
alignmvs | | | 92.97 38 | 92.26 48 | 95.12 13 | 95.54 103 | 87.77 15 | 98.67 11 | 96.38 98 | 88.04 50 | 93.01 40 | 97.45 62 | 79.20 67 | 98.60 97 | 93.25 40 | 88.76 137 | 98.99 16 |
|
DeepC-MVS_fast | | 89.06 2 | 94.48 13 | 94.30 19 | 95.02 14 | 98.86 10 | 85.68 33 | 98.06 29 | 96.64 69 | 93.64 8 | 91.74 52 | 98.54 7 | 80.17 57 | 99.90 4 | 92.28 50 | 98.75 18 | 99.49 3 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
3Dnovator+ | | 82.88 8 | 89.63 90 | 87.85 102 | 94.99 15 | 94.49 137 | 86.76 23 | 97.84 36 | 95.74 134 | 86.10 74 | 75.47 232 | 96.02 98 | 65.00 213 | 99.51 46 | 82.91 134 | 97.07 63 | 98.72 26 |
|
HPM-MVS++ | | | 95.32 5 | 95.48 7 | 94.85 16 | 98.62 24 | 86.04 27 | 97.81 39 | 96.93 45 | 92.45 11 | 95.69 10 | 98.50 8 | 85.38 14 | 99.85 10 | 94.75 23 | 99.18 3 | 98.65 28 |
|
VNet | | | 92.11 53 | 91.22 60 | 94.79 17 | 96.91 75 | 86.98 22 | 97.91 33 | 97.96 15 | 86.38 71 | 93.65 34 | 95.74 101 | 70.16 169 | 98.95 89 | 93.39 35 | 88.87 136 | 98.43 35 |
|
lupinMVS | | | 93.87 27 | 93.58 27 | 94.75 18 | 93.00 165 | 88.08 12 | 99.15 4 | 95.50 146 | 91.03 19 | 94.90 20 | 97.66 50 | 78.84 70 | 97.56 137 | 94.64 26 | 97.46 53 | 98.62 30 |
|
ESAPD | | | 95.32 5 | 95.52 6 | 94.70 19 | 98.90 7 | 85.14 43 | 98.15 25 | 96.77 53 | 84.95 101 | 96.07 7 | 98.83 2 | 89.33 6 | 99.80 13 | 97.78 2 | 98.95 12 | 99.18 10 |
|
NCCC | | | 95.63 3 | 95.94 5 | 94.69 20 | 99.21 6 | 85.15 42 | 99.16 3 | 96.96 42 | 94.11 6 | 95.59 11 | 98.64 6 | 85.07 15 | 99.91 3 | 95.61 18 | 99.10 5 | 99.00 14 |
|
PAPR | | | 92.74 41 | 92.17 50 | 94.45 21 | 98.89 9 | 84.87 50 | 97.20 76 | 96.20 110 | 87.73 57 | 88.40 90 | 98.12 26 | 78.71 73 | 99.76 15 | 87.99 90 | 96.28 74 | 98.74 23 |
|
3Dnovator | | 82.32 10 | 89.33 94 | 87.64 107 | 94.42 22 | 93.73 153 | 85.70 32 | 97.73 47 | 96.75 56 | 86.73 70 | 76.21 223 | 95.93 99 | 62.17 228 | 99.68 29 | 81.67 139 | 97.81 49 | 97.88 72 |
|
DP-MVS Recon | | | 91.72 58 | 90.85 64 | 94.34 23 | 99.50 1 | 85.00 45 | 98.51 16 | 95.96 124 | 80.57 187 | 88.08 95 | 97.63 55 | 76.84 95 | 99.89 6 | 85.67 104 | 94.88 90 | 98.13 53 |
|
PAPM | | | 92.87 40 | 92.40 45 | 94.30 24 | 92.25 182 | 87.85 14 | 96.40 142 | 96.38 98 | 91.07 18 | 88.72 87 | 96.90 82 | 82.11 38 | 97.37 147 | 90.05 69 | 97.70 50 | 97.67 85 |
|
SD-MVS | | | 94.84 9 | 95.02 9 | 94.29 25 | 97.87 53 | 84.61 52 | 97.76 45 | 96.19 112 | 89.59 32 | 96.66 4 | 98.17 21 | 84.33 22 | 99.60 36 | 96.09 12 | 98.50 26 | 98.66 27 |
|
test12 | | | | | 94.25 26 | 98.34 37 | 85.55 35 | | 96.35 100 | | 92.36 45 | | 80.84 48 | 99.22 63 | | 98.31 36 | 97.98 67 |
|
jason | | | 92.73 43 | 92.23 49 | 94.21 27 | 90.50 213 | 87.30 21 | 98.65 12 | 95.09 163 | 90.61 23 | 92.76 42 | 97.13 76 | 75.28 129 | 97.30 150 | 93.32 38 | 96.75 71 | 98.02 60 |
jason: jason. |
ACMMP_Plus | | | 93.46 31 | 93.23 31 | 94.17 28 | 97.16 72 | 84.28 60 | 96.82 111 | 96.65 66 | 86.24 72 | 94.27 27 | 97.99 36 | 77.94 82 | 99.83 12 | 93.39 35 | 98.57 24 | 98.39 37 |
|
1314 | | | 88.94 100 | 87.20 118 | 94.17 28 | 93.21 160 | 85.73 31 | 93.33 234 | 96.64 69 | 82.89 148 | 75.98 225 | 96.36 94 | 66.83 192 | 99.39 53 | 83.52 128 | 96.02 79 | 97.39 103 |
|
LFMVS | | | 89.27 95 | 87.64 107 | 94.16 30 | 97.16 72 | 85.52 36 | 97.18 78 | 94.66 186 | 79.17 218 | 89.63 76 | 96.57 92 | 55.35 281 | 98.22 111 | 89.52 76 | 89.54 131 | 98.74 23 |
|
QAPM | | | 86.88 142 | 84.51 158 | 93.98 31 | 94.04 146 | 85.89 29 | 97.19 77 | 96.05 120 | 73.62 280 | 75.12 235 | 95.62 106 | 62.02 231 | 99.74 20 | 70.88 225 | 96.06 78 | 96.30 143 |
|
MSLP-MVS++ | | | 94.28 15 | 94.39 16 | 93.97 32 | 98.30 40 | 84.06 62 | 98.64 13 | 96.93 45 | 90.71 22 | 93.08 39 | 98.70 5 | 79.98 59 | 99.21 65 | 94.12 30 | 99.07 6 | 98.63 29 |
|
APDe-MVS | | | 94.56 12 | 94.75 10 | 93.96 33 | 98.84 11 | 83.40 75 | 98.04 30 | 96.41 92 | 85.79 80 | 95.00 19 | 98.28 14 | 84.32 25 | 99.18 72 | 97.35 5 | 98.77 17 | 99.28 5 |
|
TSAR-MVS + GP. | | | 94.35 14 | 94.50 12 | 93.89 34 | 97.38 68 | 83.04 81 | 98.10 28 | 95.29 159 | 91.57 15 | 93.81 32 | 97.45 62 | 86.64 9 | 99.43 51 | 96.28 11 | 94.01 96 | 99.20 8 |
|
Regformer-1 | | | 94.00 24 | 94.04 22 | 93.87 35 | 98.41 34 | 84.29 59 | 97.43 65 | 97.04 36 | 89.50 33 | 92.75 43 | 98.13 23 | 82.60 36 | 99.26 60 | 93.55 33 | 96.99 64 | 98.06 57 |
|
CANet_DTU | | | 90.98 70 | 90.04 72 | 93.83 36 | 94.76 123 | 86.23 26 | 96.32 146 | 93.12 259 | 93.11 10 | 93.71 33 | 96.82 87 | 63.08 224 | 99.48 48 | 84.29 114 | 95.12 89 | 95.77 150 |
|
API-MVS | | | 90.18 83 | 88.97 89 | 93.80 37 | 98.66 18 | 82.95 85 | 97.50 60 | 95.63 140 | 75.16 262 | 86.31 107 | 97.69 49 | 72.49 147 | 99.90 4 | 81.26 141 | 96.07 77 | 98.56 32 |
|
EPNet | | | 94.06 22 | 94.15 21 | 93.76 38 | 97.27 71 | 84.35 57 | 98.29 20 | 97.64 17 | 94.57 4 | 95.36 12 | 96.88 84 | 79.96 60 | 99.12 78 | 91.30 56 | 96.11 76 | 97.82 77 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
train_agg | | | 94.28 15 | 94.45 14 | 93.74 39 | 98.64 21 | 83.71 68 | 97.82 37 | 96.65 66 | 84.50 113 | 95.16 14 | 98.09 28 | 84.33 22 | 99.36 55 | 95.91 15 | 98.96 10 | 98.16 49 |
|
CDPH-MVS | | | 93.12 35 | 92.91 37 | 93.74 39 | 98.65 20 | 83.88 63 | 97.67 50 | 96.26 106 | 83.00 147 | 93.22 38 | 98.24 15 | 81.31 46 | 99.21 65 | 89.12 78 | 98.74 19 | 98.14 52 |
|
MVSFormer | | | 91.36 65 | 90.57 67 | 93.73 41 | 93.00 165 | 88.08 12 | 94.80 204 | 94.48 194 | 80.74 183 | 94.90 20 | 97.13 76 | 78.84 70 | 95.10 256 | 83.77 119 | 97.46 53 | 98.02 60 |
|
APD-MVS | | | 93.61 29 | 93.59 26 | 93.69 42 | 98.76 12 | 83.26 76 | 97.21 74 | 96.09 117 | 82.41 157 | 94.65 24 | 98.21 16 | 81.96 39 | 98.81 95 | 94.65 25 | 98.36 35 | 99.01 13 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
Regformer-2 | | | 93.92 25 | 94.01 23 | 93.67 43 | 98.41 34 | 83.75 67 | 97.43 65 | 97.00 38 | 89.43 35 | 92.69 44 | 98.13 23 | 82.48 37 | 99.22 63 | 93.51 34 | 96.99 64 | 98.04 58 |
|
TSAR-MVS + MP. | | | 94.79 10 | 95.17 8 | 93.64 44 | 97.66 55 | 84.10 61 | 95.85 172 | 96.42 91 | 91.26 17 | 97.49 1 | 96.80 88 | 86.50 11 | 98.49 103 | 95.54 19 | 99.03 7 | 98.33 39 |
|
CHOSEN 1792x2688 | | | 91.07 69 | 90.21 70 | 93.64 44 | 95.18 113 | 83.53 72 | 96.26 152 | 96.13 114 | 88.92 38 | 84.90 116 | 93.10 162 | 72.86 145 | 99.62 35 | 88.86 79 | 95.67 84 | 97.79 79 |
|
MVS_Test | | | 90.29 82 | 89.18 88 | 93.62 46 | 95.23 111 | 84.93 46 | 94.41 210 | 94.66 186 | 84.31 119 | 90.37 69 | 91.02 183 | 75.13 130 | 97.82 126 | 83.11 132 | 94.42 92 | 98.12 54 |
|
sss | | | 90.87 71 | 89.96 74 | 93.60 47 | 94.15 142 | 83.84 66 | 97.14 84 | 98.13 13 | 85.93 78 | 89.68 74 | 96.09 97 | 71.67 153 | 99.30 57 | 87.69 92 | 89.16 133 | 97.66 86 |
|
PVSNet_Blended | | | 93.13 34 | 92.98 36 | 93.57 48 | 97.47 61 | 83.86 64 | 99.32 1 | 96.73 57 | 91.02 20 | 89.53 78 | 96.21 96 | 76.42 101 | 99.57 39 | 94.29 28 | 95.81 83 | 97.29 110 |
|
xiu_mvs_v1_base_debu | | | 90.54 76 | 89.54 83 | 93.55 49 | 92.31 175 | 87.58 18 | 96.99 99 | 94.87 172 | 87.23 62 | 93.27 35 | 97.56 57 | 57.43 264 | 98.32 107 | 92.72 44 | 93.46 104 | 94.74 172 |
|
xiu_mvs_v1_base | | | 90.54 76 | 89.54 83 | 93.55 49 | 92.31 175 | 87.58 18 | 96.99 99 | 94.87 172 | 87.23 62 | 93.27 35 | 97.56 57 | 57.43 264 | 98.32 107 | 92.72 44 | 93.46 104 | 94.74 172 |
|
xiu_mvs_v1_base_debi | | | 90.54 76 | 89.54 83 | 93.55 49 | 92.31 175 | 87.58 18 | 96.99 99 | 94.87 172 | 87.23 62 | 93.27 35 | 97.56 57 | 57.43 264 | 98.32 107 | 92.72 44 | 93.46 104 | 94.74 172 |
|
agg_prior3 | | | 94.10 20 | 94.29 20 | 93.53 52 | 98.62 24 | 83.03 82 | 97.80 41 | 96.64 69 | 84.28 122 | 95.01 18 | 98.03 32 | 83.40 31 | 99.41 52 | 95.91 15 | 98.96 10 | 98.16 49 |
|
OpenMVS | | 79.58 14 | 86.09 155 | 83.62 177 | 93.50 53 | 90.95 207 | 86.71 24 | 97.44 62 | 95.83 131 | 75.35 258 | 72.64 251 | 95.72 102 | 57.42 267 | 99.64 33 | 71.41 219 | 95.85 82 | 94.13 179 |
|
GG-mvs-BLEND | | | | | 93.49 54 | 94.94 119 | 86.26 25 | 81.62 322 | 97.00 38 | | 88.32 92 | 94.30 139 | 91.23 2 | 96.21 194 | 88.49 84 | 97.43 56 | 98.00 65 |
|
agg_prior1 | | | 94.10 20 | 94.31 18 | 93.48 55 | 98.59 26 | 83.13 78 | 97.77 42 | 96.56 77 | 84.38 117 | 94.19 28 | 98.13 23 | 84.66 19 | 99.16 74 | 95.74 17 | 98.74 19 | 98.15 51 |
|
ab-mvs | | | 87.08 139 | 84.94 154 | 93.48 55 | 93.34 159 | 83.67 70 | 88.82 289 | 95.70 136 | 81.18 173 | 84.55 123 | 90.14 198 | 62.72 225 | 98.94 91 | 85.49 106 | 82.54 203 | 97.85 75 |
|
PHI-MVS | | | 93.59 30 | 93.63 25 | 93.48 55 | 98.05 47 | 81.76 107 | 98.64 13 | 97.13 24 | 82.60 155 | 94.09 31 | 98.49 9 | 80.35 52 | 99.85 10 | 94.74 24 | 98.62 23 | 98.83 19 |
|
MVS_111021_HR | | | 93.41 32 | 93.39 29 | 93.47 58 | 97.34 69 | 82.83 86 | 97.56 56 | 98.27 12 | 89.16 36 | 89.71 73 | 97.14 75 | 79.77 61 | 99.56 41 | 93.65 32 | 97.94 46 | 98.02 60 |
|
PAPM_NR | | | 91.46 64 | 90.82 65 | 93.37 59 | 98.50 31 | 81.81 106 | 95.03 199 | 96.13 114 | 84.65 109 | 86.10 110 | 97.65 54 | 79.24 66 | 99.75 18 | 83.20 130 | 96.88 69 | 98.56 32 |
|
MP-MVS-pluss | | | 92.58 49 | 92.35 46 | 93.29 60 | 97.30 70 | 82.53 90 | 96.44 136 | 96.04 121 | 84.68 108 | 89.12 83 | 98.37 11 | 77.48 87 | 99.74 20 | 93.31 39 | 98.38 33 | 97.59 92 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
IB-MVS | | 85.34 4 | 88.67 108 | 87.14 122 | 93.26 61 | 93.12 164 | 84.32 58 | 98.76 10 | 97.27 20 | 87.19 65 | 79.36 187 | 90.45 192 | 83.92 28 | 98.53 101 | 84.41 113 | 69.79 268 | 96.93 120 |
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 |
gg-mvs-nofinetune | | | 85.48 171 | 82.90 187 | 93.24 62 | 94.51 136 | 85.82 30 | 79.22 326 | 96.97 41 | 61.19 323 | 87.33 100 | 53.01 340 | 90.58 3 | 96.07 198 | 86.07 102 | 97.23 61 | 97.81 78 |
|
SteuartSystems-ACMMP | | | 94.13 19 | 94.44 15 | 93.20 63 | 95.41 107 | 81.35 117 | 99.02 7 | 96.59 75 | 89.50 33 | 94.18 30 | 98.36 12 | 83.68 30 | 99.45 50 | 94.77 22 | 98.45 28 | 98.81 20 |
Skip Steuart: Steuart Systems R&D Blog. |
Regformer-3 | | | 93.19 33 | 93.19 32 | 93.19 64 | 98.10 45 | 83.01 83 | 97.08 95 | 96.98 40 | 88.98 37 | 91.35 59 | 97.89 43 | 80.80 49 | 99.23 61 | 92.30 49 | 95.20 86 | 97.32 105 |
|
1121 | | | 90.66 73 | 89.82 79 | 93.16 65 | 97.39 65 | 81.71 111 | 93.33 234 | 96.66 65 | 74.45 275 | 91.38 55 | 97.55 60 | 79.27 64 | 99.52 43 | 79.95 149 | 98.43 29 | 98.26 46 |
|
æ–°å‡ ä½•1 | | | | | 93.12 66 | 97.44 63 | 81.60 113 | | 96.71 60 | 74.54 274 | 91.22 62 | 97.57 56 | 79.13 68 | 99.51 46 | 77.40 173 | 98.46 27 | 98.26 46 |
|
CSCG | | | 92.02 54 | 91.65 56 | 93.12 66 | 98.53 28 | 80.59 131 | 97.47 61 | 97.18 23 | 77.06 242 | 84.64 122 | 97.98 38 | 83.98 27 | 99.52 43 | 90.72 63 | 97.33 60 | 99.23 7 |
|
Effi-MVS+ | | | 90.70 72 | 89.90 77 | 93.09 68 | 93.61 154 | 83.48 73 | 95.20 188 | 92.79 263 | 83.22 142 | 91.82 49 | 95.70 103 | 71.82 152 | 97.48 144 | 91.25 57 | 93.67 101 | 98.32 40 |
|
test_prior3 | | | 94.03 23 | 94.34 17 | 93.09 68 | 98.68 15 | 81.91 101 | 98.37 18 | 96.40 94 | 86.08 75 | 94.57 25 | 98.02 33 | 83.14 33 | 99.06 81 | 95.05 20 | 98.79 15 | 98.29 43 |
|
test_prior | | | | | 93.09 68 | 98.68 15 | 81.91 101 | | 96.40 94 | | | | | 99.06 81 | | | 98.29 43 |
|
HFP-MVS | | | 92.89 39 | 92.86 38 | 92.98 71 | 98.71 13 | 81.12 120 | 97.58 54 | 96.70 61 | 85.20 94 | 91.75 50 | 97.97 40 | 78.47 75 | 99.71 23 | 90.95 59 | 98.41 30 | 98.12 54 |
|
#test# | | | 92.99 37 | 92.99 35 | 92.98 71 | 98.71 13 | 81.12 120 | 97.77 42 | 96.70 61 | 85.75 81 | 91.75 50 | 97.97 40 | 78.47 75 | 99.71 23 | 91.36 55 | 98.41 30 | 98.12 54 |
|
DeepC-MVS | | 86.58 3 | 91.53 63 | 91.06 63 | 92.94 73 | 94.52 134 | 81.89 103 | 95.95 163 | 95.98 123 | 90.76 21 | 83.76 132 | 96.76 89 | 73.24 143 | 99.71 23 | 91.67 54 | 96.96 66 | 97.22 114 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
Regformer-4 | | | 93.06 36 | 93.12 33 | 92.89 74 | 98.10 45 | 82.20 96 | 97.08 95 | 96.92 47 | 88.87 39 | 91.23 61 | 97.89 43 | 80.57 51 | 99.19 70 | 92.21 51 | 95.20 86 | 97.29 110 |
|
SMA-MVS | | | 92.74 41 | 92.71 39 | 92.86 75 | 97.90 49 | 80.85 126 | 96.47 131 | 96.33 102 | 87.92 52 | 90.20 70 | 98.18 17 | 76.71 99 | 99.76 15 | 92.57 47 | 98.09 40 | 97.96 68 |
|
MTAPA | | | 92.45 51 | 92.31 47 | 92.86 75 | 97.90 49 | 80.85 126 | 92.88 247 | 96.33 102 | 87.92 52 | 90.20 70 | 98.18 17 | 76.71 99 | 99.76 15 | 92.57 47 | 98.09 40 | 97.96 68 |
|
DI_MVS_plusplus_test | | | 85.92 157 | 83.61 178 | 92.86 75 | 86.43 267 | 83.20 77 | 95.57 180 | 95.46 148 | 85.10 99 | 65.99 282 | 86.84 239 | 56.70 271 | 97.89 124 | 88.10 89 | 92.33 114 | 97.48 99 |
|
region2R | | | 92.72 44 | 92.70 41 | 92.79 78 | 98.68 15 | 80.53 135 | 97.53 58 | 96.51 82 | 85.22 92 | 91.94 48 | 97.98 38 | 77.26 89 | 99.67 31 | 90.83 62 | 98.37 34 | 98.18 48 |
|
test_normal | | | 85.83 159 | 83.51 180 | 92.78 79 | 86.33 272 | 83.01 83 | 95.56 182 | 95.46 148 | 85.11 98 | 65.73 284 | 86.63 244 | 56.62 273 | 97.86 125 | 87.87 91 | 92.29 115 | 97.47 100 |
|
ACMMPR | | | 92.69 45 | 92.67 42 | 92.75 80 | 98.66 18 | 80.57 132 | 97.58 54 | 96.69 63 | 85.20 94 | 91.57 53 | 97.92 42 | 77.01 93 | 99.67 31 | 90.95 59 | 98.41 30 | 98.00 65 |
|
thres200 | | | 88.92 101 | 87.65 106 | 92.73 81 | 96.30 80 | 85.62 34 | 97.85 35 | 98.86 1 | 84.38 117 | 84.82 117 | 93.99 144 | 75.12 131 | 98.01 115 | 70.86 226 | 86.67 152 | 94.56 175 |
|
PVSNet | | 82.34 9 | 89.02 98 | 87.79 104 | 92.71 82 | 95.49 104 | 81.50 114 | 97.70 48 | 97.29 19 | 87.76 56 | 85.47 112 | 95.12 126 | 56.90 269 | 98.90 93 | 80.33 144 | 94.02 95 | 97.71 83 |
|
DWT-MVSNet_test | | | 90.52 79 | 89.80 80 | 92.70 83 | 95.73 100 | 82.20 96 | 93.69 225 | 96.55 79 | 88.34 45 | 87.04 104 | 95.34 110 | 86.53 10 | 97.55 139 | 76.32 185 | 88.66 139 | 98.34 38 |
|
HSP-MVS | | | 95.55 4 | 96.51 2 | 92.66 84 | 98.31 39 | 80.10 146 | 97.42 67 | 96.46 87 | 92.20 13 | 97.11 2 | 98.29 13 | 93.46 1 | 99.10 79 | 96.01 13 | 99.30 2 | 98.77 22 |
|
PVSNet_Blended_VisFu | | | 91.24 67 | 90.77 66 | 92.66 84 | 95.09 115 | 82.40 92 | 97.77 42 | 95.87 130 | 88.26 47 | 86.39 106 | 93.94 145 | 76.77 97 | 99.27 58 | 88.80 81 | 94.00 97 | 96.31 142 |
|
PatchFormer-LS_test | | | 90.14 84 | 89.30 87 | 92.65 86 | 95.43 105 | 82.46 91 | 93.46 230 | 96.35 100 | 88.56 41 | 84.82 117 | 95.22 117 | 84.63 20 | 97.55 139 | 78.40 161 | 86.81 151 | 97.94 70 |
|
XVS | | | 92.69 45 | 92.71 39 | 92.63 87 | 98.52 29 | 80.29 139 | 97.37 69 | 96.44 89 | 87.04 67 | 91.38 55 | 97.83 46 | 77.24 91 | 99.59 37 | 90.46 65 | 98.07 42 | 98.02 60 |
|
X-MVStestdata | | | 86.26 154 | 84.14 171 | 92.63 87 | 98.52 29 | 80.29 139 | 97.37 69 | 96.44 89 | 87.04 67 | 91.38 55 | 20.73 353 | 77.24 91 | 99.59 37 | 90.46 65 | 98.07 42 | 98.02 60 |
|
cascas | | | 86.50 149 | 84.48 160 | 92.55 89 | 92.64 172 | 85.95 28 | 97.04 98 | 95.07 165 | 75.32 259 | 80.50 169 | 91.02 183 | 54.33 288 | 97.98 116 | 86.79 100 | 87.62 146 | 93.71 188 |
|
tfpn200view9 | | | 88.48 112 | 87.15 120 | 92.47 90 | 96.21 81 | 85.30 39 | 97.44 62 | 98.85 2 | 83.37 140 | 83.99 127 | 93.82 147 | 75.36 126 | 97.93 117 | 69.04 236 | 86.24 157 | 94.17 176 |
|
114514_t | | | 88.79 106 | 87.57 111 | 92.45 91 | 98.21 42 | 81.74 108 | 96.99 99 | 95.45 151 | 75.16 262 | 82.48 144 | 95.69 104 | 68.59 175 | 98.50 102 | 80.33 144 | 95.18 88 | 97.10 115 |
|
MP-MVS | | | 92.61 48 | 92.67 42 | 92.42 92 | 98.13 44 | 79.73 154 | 97.33 71 | 96.20 110 | 85.63 83 | 90.53 66 | 97.66 50 | 78.14 80 | 99.70 26 | 92.12 52 | 98.30 37 | 97.85 75 |
|
diffmvs | | | 87.96 126 | 86.47 132 | 92.42 92 | 94.26 139 | 82.70 87 | 92.79 251 | 94.03 219 | 77.94 228 | 88.99 85 | 89.98 200 | 70.72 165 | 97.56 137 | 77.75 163 | 91.80 121 | 96.98 117 |
|
AdaColmap | | | 88.81 104 | 87.61 110 | 92.39 94 | 99.33 4 | 79.95 147 | 96.70 120 | 95.58 141 | 77.51 234 | 83.05 141 | 96.69 91 | 61.90 235 | 99.72 22 | 84.29 114 | 93.47 103 | 97.50 97 |
|
CP-MVS | | | 92.54 50 | 92.60 44 | 92.34 95 | 98.50 31 | 79.90 149 | 98.40 17 | 96.40 94 | 84.75 106 | 90.48 68 | 98.09 28 | 77.40 88 | 99.21 65 | 91.15 58 | 98.23 39 | 97.92 71 |
|
thres100view900 | | | 88.30 117 | 86.95 125 | 92.33 96 | 96.10 85 | 84.90 47 | 97.14 84 | 98.85 2 | 82.69 152 | 83.41 134 | 93.66 150 | 75.43 121 | 97.93 117 | 69.04 236 | 86.24 157 | 94.17 176 |
|
PGM-MVS | | | 91.93 55 | 91.80 53 | 92.32 97 | 98.27 41 | 79.74 153 | 95.28 185 | 97.27 20 | 83.83 132 | 90.89 65 | 97.78 48 | 76.12 107 | 99.56 41 | 88.82 80 | 97.93 48 | 97.66 86 |
|
conf200view11 | | | 88.27 119 | 86.95 125 | 92.24 98 | 96.10 85 | 84.90 47 | 97.14 84 | 98.85 2 | 82.69 152 | 83.41 134 | 93.66 150 | 75.43 121 | 97.93 117 | 69.04 236 | 86.24 157 | 93.89 183 |
|
thres400 | | | 88.42 115 | 87.15 120 | 92.23 99 | 96.21 81 | 85.30 39 | 97.44 62 | 98.85 2 | 83.37 140 | 83.99 127 | 93.82 147 | 75.36 126 | 97.93 117 | 69.04 236 | 86.24 157 | 93.45 192 |
|
VDDNet | | | 86.44 151 | 84.51 158 | 92.22 100 | 91.56 198 | 81.83 105 | 97.10 92 | 94.64 189 | 69.50 301 | 87.84 96 | 95.19 120 | 48.01 303 | 97.92 123 | 89.82 72 | 86.92 149 | 96.89 122 |
|
tfpn111 | | | 88.08 121 | 86.70 129 | 92.20 101 | 96.10 85 | 84.90 47 | 97.14 84 | 98.85 2 | 82.69 152 | 83.41 134 | 93.66 150 | 75.43 121 | 97.82 126 | 67.13 251 | 85.88 162 | 93.89 183 |
|
EPMVS | | | 87.47 132 | 85.90 141 | 92.18 102 | 95.41 107 | 82.26 95 | 87.00 305 | 96.28 105 | 85.88 79 | 84.23 125 | 85.57 262 | 75.07 132 | 96.26 191 | 71.14 224 | 92.50 110 | 98.03 59 |
|
thres600view7 | | | 88.06 122 | 86.70 129 | 92.15 103 | 96.10 85 | 85.17 41 | 97.14 84 | 98.85 2 | 82.70 151 | 83.41 134 | 93.66 150 | 75.43 121 | 97.82 126 | 67.13 251 | 85.88 162 | 93.45 192 |
|
PCF-MVS | | 84.09 5 | 86.77 147 | 85.00 152 | 92.08 104 | 92.06 189 | 83.07 80 | 92.14 263 | 94.47 196 | 79.63 210 | 76.90 213 | 94.78 132 | 71.15 159 | 99.20 69 | 72.87 207 | 91.05 125 | 93.98 181 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
mPP-MVS | | | 91.88 56 | 91.82 52 | 92.07 105 | 98.38 36 | 78.63 195 | 97.29 72 | 96.09 117 | 85.12 96 | 88.45 89 | 97.66 50 | 75.53 113 | 99.68 29 | 89.83 71 | 98.02 45 | 97.88 72 |
|
VDD-MVS | | | 88.28 118 | 87.02 124 | 92.06 106 | 95.09 115 | 80.18 145 | 97.55 57 | 94.45 197 | 83.09 144 | 89.10 84 | 95.92 100 | 47.97 304 | 98.49 103 | 93.08 42 | 86.91 150 | 97.52 96 |
|
EI-MVSNet-Vis-set | | | 91.84 57 | 91.77 54 | 92.04 107 | 97.60 57 | 81.17 119 | 96.61 125 | 96.87 49 | 88.20 48 | 89.19 82 | 97.55 60 | 78.69 74 | 99.14 76 | 90.29 67 | 90.94 126 | 95.80 149 |
|
1112_ss | | | 88.60 111 | 87.47 114 | 92.00 108 | 93.21 160 | 80.97 123 | 96.47 131 | 92.46 266 | 83.64 137 | 80.86 166 | 97.30 70 | 80.24 55 | 97.62 135 | 77.60 170 | 85.49 167 | 97.40 102 |
|
PatchmatchNet | | | 86.83 144 | 85.12 149 | 91.95 109 | 94.12 143 | 82.27 94 | 86.55 309 | 95.64 139 | 84.59 111 | 82.98 142 | 84.99 272 | 77.26 89 | 95.96 209 | 68.61 244 | 91.34 124 | 97.64 88 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
Test_1112_low_res | | | 88.03 123 | 86.73 128 | 91.94 110 | 93.15 162 | 80.88 125 | 96.44 136 | 92.41 267 | 83.59 139 | 80.74 168 | 91.16 181 | 80.18 56 | 97.59 136 | 77.48 172 | 85.40 168 | 97.36 104 |
|
HPM-MVS | | | 91.62 61 | 91.53 58 | 91.89 111 | 97.88 52 | 79.22 172 | 96.99 99 | 95.73 135 | 82.07 161 | 89.50 80 | 97.19 74 | 75.59 112 | 98.93 92 | 90.91 61 | 97.94 46 | 97.54 93 |
|
view600 | | | 87.45 133 | 85.98 136 | 91.88 112 | 95.90 92 | 84.52 53 | 96.68 121 | 98.85 2 | 81.85 164 | 82.30 147 | 93.39 154 | 75.44 117 | 97.66 130 | 64.02 270 | 85.36 169 | 93.45 192 |
|
view800 | | | 87.45 133 | 85.98 136 | 91.88 112 | 95.90 92 | 84.52 53 | 96.68 121 | 98.85 2 | 81.85 164 | 82.30 147 | 93.39 154 | 75.44 117 | 97.66 130 | 64.02 270 | 85.36 169 | 93.45 192 |
|
conf0.05thres1000 | | | 87.45 133 | 85.98 136 | 91.88 112 | 95.90 92 | 84.52 53 | 96.68 121 | 98.85 2 | 81.85 164 | 82.30 147 | 93.39 154 | 75.44 117 | 97.66 130 | 64.02 270 | 85.36 169 | 93.45 192 |
|
tfpn | | | 87.45 133 | 85.98 136 | 91.88 112 | 95.90 92 | 84.52 53 | 96.68 121 | 98.85 2 | 81.85 164 | 82.30 147 | 93.39 154 | 75.44 117 | 97.66 130 | 64.02 270 | 85.36 169 | 93.45 192 |
|
mvs_anonymous | | | 88.68 107 | 87.62 109 | 91.86 116 | 94.80 122 | 81.69 112 | 93.53 229 | 94.92 170 | 82.03 162 | 78.87 191 | 90.43 193 | 75.77 111 | 95.34 247 | 85.04 109 | 93.16 107 | 98.55 34 |
|
MAR-MVS | | | 90.63 74 | 90.22 69 | 91.86 116 | 98.47 33 | 78.20 211 | 97.18 78 | 96.61 73 | 83.87 131 | 88.18 94 | 98.18 17 | 68.71 174 | 99.75 18 | 83.66 124 | 97.15 62 | 97.63 89 |
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 |
Test4 | | | 82.30 220 | 79.15 235 | 91.78 118 | 81.84 309 | 81.74 108 | 94.04 220 | 94.20 204 | 84.86 103 | 59.75 315 | 83.88 279 | 37.14 327 | 96.28 190 | 84.60 112 | 92.00 118 | 97.30 108 |
|
EI-MVSNet-UG-set | | | 91.35 66 | 91.22 60 | 91.73 119 | 97.39 65 | 80.68 129 | 96.47 131 | 96.83 51 | 87.92 52 | 88.30 93 | 97.36 67 | 77.84 84 | 99.13 77 | 89.43 77 | 89.45 132 | 95.37 159 |
|
CNLPA | | | 86.96 140 | 85.37 145 | 91.72 120 | 97.59 58 | 79.34 167 | 97.21 74 | 91.05 283 | 74.22 276 | 78.90 189 | 96.75 90 | 67.21 182 | 98.95 89 | 74.68 199 | 90.77 127 | 96.88 123 |
|
ACMMP | | | 90.39 80 | 89.97 73 | 91.64 121 | 97.58 59 | 78.21 210 | 96.78 113 | 96.72 59 | 84.73 107 | 84.72 120 | 97.23 72 | 71.22 158 | 99.63 34 | 88.37 87 | 92.41 112 | 97.08 116 |
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 |
HyFIR lowres test | | | 89.36 93 | 88.60 94 | 91.63 122 | 94.91 121 | 80.76 128 | 95.60 179 | 95.53 143 | 82.56 156 | 84.03 126 | 91.24 180 | 78.03 81 | 96.81 175 | 87.07 98 | 88.41 141 | 97.32 105 |
|
BH-RMVSNet | | | 86.84 143 | 85.28 146 | 91.49 123 | 95.35 109 | 80.26 142 | 96.95 105 | 92.21 268 | 82.86 149 | 81.77 160 | 95.46 108 | 59.34 247 | 97.64 134 | 69.79 233 | 93.81 100 | 96.57 133 |
|
MVS_111021_LR | | | 91.60 62 | 91.64 57 | 91.47 124 | 95.74 99 | 78.79 192 | 96.15 155 | 96.77 53 | 88.49 43 | 88.64 88 | 97.07 79 | 72.33 149 | 99.19 70 | 93.13 41 | 96.48 73 | 96.43 136 |
|
TESTMET0.1,1 | | | 89.83 86 | 89.34 86 | 91.31 125 | 92.54 173 | 80.19 144 | 97.11 89 | 96.57 76 | 86.15 73 | 86.85 105 | 91.83 174 | 79.32 62 | 96.95 167 | 81.30 140 | 92.35 113 | 96.77 127 |
|
tpmrst | | | 88.36 116 | 87.38 116 | 91.31 125 | 94.36 138 | 79.92 148 | 87.32 301 | 95.26 161 | 85.32 90 | 88.34 91 | 86.13 255 | 80.60 50 | 96.70 179 | 83.78 118 | 85.34 174 | 97.30 108 |
|
CHOSEN 280x420 | | | 91.71 59 | 91.85 51 | 91.29 127 | 94.94 119 | 82.69 88 | 87.89 297 | 96.17 113 | 85.94 77 | 87.27 101 | 94.31 138 | 90.27 4 | 95.65 231 | 94.04 31 | 95.86 81 | 95.53 156 |
|
Patchmatch-test1 | | | 84.89 178 | 82.76 190 | 91.27 128 | 92.30 178 | 81.86 104 | 92.88 247 | 95.56 142 | 84.85 104 | 82.52 143 | 85.19 267 | 58.04 258 | 94.21 274 | 65.93 261 | 87.58 148 | 97.74 81 |
|
UGNet | | | 87.73 129 | 86.55 131 | 91.27 128 | 95.16 114 | 79.11 176 | 96.35 144 | 96.23 108 | 88.14 49 | 87.83 97 | 90.48 191 | 50.65 293 | 99.09 80 | 80.13 148 | 94.03 94 | 95.60 155 |
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 |
Vis-MVSNet | | | 88.67 108 | 87.82 103 | 91.24 130 | 92.68 168 | 78.82 189 | 96.95 105 | 93.85 227 | 87.55 58 | 87.07 103 | 95.13 125 | 63.43 222 | 97.21 155 | 77.58 171 | 96.15 75 | 97.70 84 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
原ACMM1 | | | | | 91.22 131 | 97.77 54 | 78.10 213 | | 96.61 73 | 81.05 175 | 91.28 60 | 97.42 66 | 77.92 83 | 98.98 86 | 79.85 151 | 98.51 25 | 96.59 132 |
|
CostFormer | | | 89.08 97 | 88.39 97 | 91.15 132 | 93.13 163 | 79.15 175 | 88.61 292 | 96.11 116 | 83.14 143 | 89.58 77 | 86.93 235 | 83.83 29 | 96.87 172 | 88.22 88 | 85.92 161 | 97.42 101 |
|
CDS-MVSNet | | | 89.50 91 | 88.96 90 | 91.14 133 | 91.94 195 | 80.93 124 | 97.09 93 | 95.81 132 | 84.26 123 | 84.72 120 | 94.20 140 | 80.31 53 | 95.64 232 | 83.37 129 | 88.96 135 | 96.85 124 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
DP-MVS | | | 81.47 228 | 78.28 238 | 91.04 134 | 98.14 43 | 78.48 200 | 95.09 198 | 86.97 319 | 61.14 324 | 71.12 258 | 92.78 165 | 59.59 242 | 99.38 54 | 53.11 314 | 86.61 153 | 95.27 161 |
|
HPM-MVS_fast | | | 90.38 81 | 90.17 71 | 91.03 135 | 97.61 56 | 77.35 230 | 97.15 83 | 95.48 147 | 79.51 211 | 88.79 86 | 96.90 82 | 71.64 155 | 98.81 95 | 87.01 99 | 97.44 55 | 96.94 119 |
|
GA-MVS | | | 85.79 165 | 84.04 172 | 91.02 136 | 89.47 231 | 80.27 141 | 96.90 108 | 94.84 175 | 85.57 84 | 80.88 165 | 89.08 206 | 56.56 274 | 96.47 184 | 77.72 168 | 85.35 173 | 96.34 139 |
|
tfpn_ndepth | | | 87.25 138 | 86.00 135 | 91.01 137 | 95.86 96 | 81.46 115 | 96.53 128 | 97.09 33 | 77.35 237 | 81.36 161 | 95.07 128 | 84.74 18 | 95.86 214 | 60.88 285 | 85.14 175 | 95.72 152 |
|
tpmp4_e23 | | | 86.46 150 | 84.95 153 | 90.98 138 | 93.74 152 | 78.60 197 | 88.13 295 | 95.90 128 | 79.65 209 | 85.42 113 | 85.67 257 | 80.08 58 | 97.06 163 | 71.71 216 | 84.26 181 | 97.28 112 |
|
Fast-Effi-MVS+ | | | 87.93 127 | 86.94 127 | 90.92 139 | 94.04 146 | 79.16 174 | 98.26 21 | 93.72 236 | 81.29 172 | 83.94 130 | 92.90 163 | 69.83 170 | 96.68 180 | 76.70 181 | 91.74 122 | 96.93 120 |
|
APD-MVS_3200maxsize | | | 91.23 68 | 91.35 59 | 90.89 140 | 97.89 51 | 76.35 241 | 96.30 150 | 95.52 145 | 79.82 206 | 91.03 64 | 97.88 45 | 74.70 135 | 98.54 100 | 92.11 53 | 96.89 68 | 97.77 80 |
|
nrg030 | | | 86.79 146 | 85.43 143 | 90.87 141 | 88.76 237 | 85.34 38 | 97.06 97 | 94.33 200 | 84.31 119 | 80.45 171 | 91.98 169 | 72.36 148 | 96.36 187 | 88.48 85 | 71.13 251 | 90.93 207 |
|
OMC-MVS | | | 88.80 105 | 88.16 98 | 90.72 142 | 95.30 110 | 77.92 219 | 94.81 203 | 94.51 193 | 86.80 69 | 84.97 115 | 96.85 85 | 67.53 178 | 98.60 97 | 85.08 108 | 87.62 146 | 95.63 154 |
|
FMVSNet3 | | | 84.71 180 | 82.71 191 | 90.70 143 | 94.55 127 | 87.71 16 | 95.92 165 | 94.67 185 | 81.73 169 | 75.82 228 | 88.08 221 | 66.99 190 | 94.47 269 | 71.23 221 | 75.38 234 | 89.91 224 |
|
tpm2 | | | 87.35 137 | 86.26 133 | 90.62 144 | 92.93 167 | 78.67 193 | 88.06 296 | 95.99 122 | 79.33 214 | 87.40 98 | 86.43 251 | 80.28 54 | 96.40 185 | 80.23 146 | 85.73 166 | 96.79 125 |
|
TAMVS | | | 88.48 112 | 87.79 104 | 90.56 145 | 91.09 205 | 79.18 173 | 96.45 134 | 95.88 129 | 83.64 137 | 83.12 140 | 93.33 158 | 75.94 109 | 95.74 224 | 82.40 135 | 88.27 142 | 96.75 129 |
|
BH-w/o | | | 88.24 120 | 87.47 114 | 90.54 146 | 95.03 118 | 78.54 198 | 97.41 68 | 93.82 228 | 84.08 125 | 78.23 195 | 94.51 137 | 69.34 172 | 97.21 155 | 80.21 147 | 94.58 91 | 95.87 148 |
|
TR-MVS | | | 86.30 153 | 84.93 155 | 90.42 147 | 94.63 125 | 77.58 225 | 96.57 127 | 93.82 228 | 80.30 194 | 82.42 146 | 95.16 122 | 58.74 251 | 97.55 139 | 74.88 197 | 87.82 145 | 96.13 144 |
|
tfpn1000 | | | 86.43 152 | 85.10 150 | 90.41 148 | 95.56 102 | 80.51 136 | 95.90 168 | 97.09 33 | 75.91 251 | 80.02 177 | 94.82 131 | 84.78 17 | 95.47 242 | 57.36 294 | 84.46 178 | 95.26 162 |
|
tpm cat1 | | | 83.63 193 | 81.38 210 | 90.39 149 | 93.53 157 | 78.19 212 | 85.56 315 | 95.09 163 | 70.78 297 | 78.51 192 | 83.28 288 | 74.80 134 | 97.03 164 | 66.77 254 | 84.05 182 | 95.95 145 |
|
PVSNet_BlendedMVS | | | 90.05 85 | 89.96 74 | 90.33 150 | 97.47 61 | 83.86 64 | 98.02 31 | 96.73 57 | 87.98 51 | 89.53 78 | 89.61 203 | 76.42 101 | 99.57 39 | 94.29 28 | 79.59 212 | 87.57 273 |
|
dp | | | 84.30 186 | 82.31 195 | 90.28 151 | 94.24 141 | 77.97 215 | 86.57 308 | 95.53 143 | 79.94 204 | 80.75 167 | 85.16 269 | 71.49 157 | 96.39 186 | 63.73 275 | 83.36 187 | 96.48 135 |
|
UA-Net | | | 88.92 101 | 88.48 96 | 90.24 152 | 94.06 145 | 77.18 234 | 93.04 244 | 94.66 186 | 87.39 60 | 91.09 63 | 93.89 146 | 74.92 133 | 98.18 114 | 75.83 189 | 91.43 123 | 95.35 160 |
|
MVSTER | | | 89.25 96 | 88.92 91 | 90.24 152 | 95.98 90 | 84.66 51 | 96.79 112 | 95.36 154 | 87.19 65 | 80.33 173 | 90.61 190 | 90.02 5 | 95.97 205 | 85.38 107 | 78.64 221 | 90.09 220 |
|
IS-MVSNet | | | 88.67 108 | 88.16 98 | 90.20 154 | 93.61 154 | 76.86 236 | 96.77 115 | 93.07 260 | 84.02 127 | 83.62 133 | 95.60 107 | 74.69 136 | 96.24 193 | 78.43 160 | 93.66 102 | 97.49 98 |
|
thresconf0.02 | | | 85.80 160 | 84.35 163 | 90.17 155 | 94.53 128 | 79.70 155 | 95.17 189 | 97.11 26 | 75.97 245 | 79.44 180 | 95.31 111 | 81.90 40 | 95.73 225 | 56.78 299 | 82.91 193 | 95.09 163 |
|
tfpn_n400 | | | 85.80 160 | 84.35 163 | 90.17 155 | 94.53 128 | 79.70 155 | 95.17 189 | 97.11 26 | 75.97 245 | 79.44 180 | 95.31 111 | 81.90 40 | 95.73 225 | 56.78 299 | 82.91 193 | 95.09 163 |
|
tfpnconf | | | 85.80 160 | 84.35 163 | 90.17 155 | 94.53 128 | 79.70 155 | 95.17 189 | 97.11 26 | 75.97 245 | 79.44 180 | 95.31 111 | 81.90 40 | 95.73 225 | 56.78 299 | 82.91 193 | 95.09 163 |
|
tfpnview11 | | | 85.80 160 | 84.35 163 | 90.17 155 | 94.53 128 | 79.70 155 | 95.17 189 | 97.11 26 | 75.97 245 | 79.44 180 | 95.31 111 | 81.90 40 | 95.73 225 | 56.78 299 | 82.91 193 | 95.09 163 |
|
testdata | | | | | 90.13 159 | 95.92 91 | 74.17 257 | | 96.49 86 | 73.49 282 | 94.82 22 | 97.99 36 | 78.80 72 | 97.93 117 | 83.53 127 | 97.52 52 | 98.29 43 |
|
abl_6 | | | 89.80 87 | 89.71 82 | 90.07 160 | 96.53 78 | 75.52 247 | 94.48 207 | 95.04 166 | 81.12 174 | 89.22 81 | 97.00 80 | 68.83 173 | 98.96 87 | 89.86 70 | 95.27 85 | 95.73 151 |
|
CR-MVSNet | | | 83.53 194 | 81.36 211 | 90.06 161 | 90.16 219 | 79.75 151 | 79.02 328 | 91.12 280 | 84.24 124 | 82.27 155 | 80.35 300 | 75.45 115 | 93.67 284 | 63.37 278 | 86.25 155 | 96.75 129 |
|
RPMNet | | | 79.32 245 | 75.75 257 | 90.06 161 | 90.16 219 | 79.75 151 | 79.02 328 | 93.92 224 | 58.43 330 | 82.27 155 | 72.55 328 | 73.03 144 | 93.67 284 | 46.10 329 | 86.25 155 | 96.75 129 |
|
VPNet | | | 84.69 181 | 82.92 186 | 90.01 163 | 89.01 235 | 83.45 74 | 96.71 118 | 95.46 148 | 85.71 82 | 79.65 179 | 92.18 168 | 56.66 272 | 96.01 204 | 83.05 133 | 67.84 285 | 90.56 209 |
|
BH-untuned | | | 86.95 141 | 85.94 140 | 89.99 164 | 94.52 134 | 77.46 227 | 96.78 113 | 93.37 252 | 81.80 168 | 76.62 216 | 93.81 149 | 66.64 195 | 97.02 165 | 76.06 187 | 93.88 99 | 95.48 157 |
|
test-LLR | | | 88.48 112 | 87.98 100 | 89.98 165 | 92.26 180 | 77.23 232 | 97.11 89 | 95.96 124 | 83.76 134 | 86.30 108 | 91.38 177 | 72.30 150 | 96.78 177 | 80.82 142 | 91.92 119 | 95.94 146 |
|
test-mter | | | 88.95 99 | 88.60 94 | 89.98 165 | 92.26 180 | 77.23 232 | 97.11 89 | 95.96 124 | 85.32 90 | 86.30 108 | 91.38 177 | 76.37 103 | 96.78 177 | 80.82 142 | 91.92 119 | 95.94 146 |
|
ADS-MVSNet | | | 81.26 231 | 78.36 237 | 89.96 167 | 93.78 149 | 79.78 150 | 79.48 324 | 93.60 241 | 73.09 284 | 80.14 175 | 79.99 302 | 62.15 229 | 95.24 252 | 59.49 288 | 83.52 184 | 94.85 169 |
|
PVSNet_0 | | 77.72 15 | 81.70 226 | 78.95 236 | 89.94 168 | 90.77 210 | 76.72 238 | 95.96 162 | 96.95 43 | 85.01 100 | 70.24 266 | 88.53 215 | 52.32 290 | 98.20 112 | 86.68 101 | 44.08 340 | 94.89 168 |
|
DeepPCF-MVS | | 89.82 1 | 94.61 11 | 96.17 3 | 89.91 169 | 97.09 74 | 70.21 290 | 98.99 8 | 96.69 63 | 95.57 1 | 95.08 17 | 99.23 1 | 86.40 13 | 99.87 8 | 97.84 1 | 98.66 22 | 99.65 1 |
|
EPP-MVSNet | | | 89.76 88 | 89.72 81 | 89.87 170 | 93.78 149 | 76.02 244 | 97.22 73 | 96.51 82 | 79.35 213 | 85.11 114 | 95.01 130 | 84.82 16 | 97.10 162 | 87.46 95 | 88.21 143 | 96.50 134 |
|
tpmvs | | | 83.04 206 | 80.77 216 | 89.84 171 | 95.43 105 | 77.96 216 | 85.59 314 | 95.32 157 | 75.31 260 | 76.27 222 | 83.70 284 | 73.89 139 | 97.41 145 | 59.53 287 | 81.93 204 | 94.14 178 |
|
FMVSNet2 | | | 82.79 211 | 80.44 220 | 89.83 172 | 92.66 169 | 85.43 37 | 95.42 184 | 94.35 199 | 79.06 220 | 74.46 236 | 87.28 227 | 56.38 276 | 94.31 272 | 69.72 234 | 74.68 238 | 89.76 225 |
|
PLC | | 83.97 7 | 88.00 124 | 87.38 116 | 89.83 172 | 98.02 48 | 76.46 239 | 97.16 82 | 94.43 198 | 79.26 217 | 81.98 158 | 96.28 95 | 69.36 171 | 99.27 58 | 77.71 169 | 92.25 116 | 93.77 187 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
conf0.01 | | | 85.70 167 | 84.35 163 | 89.77 174 | 94.53 128 | 79.70 155 | 95.17 189 | 97.11 26 | 75.97 245 | 79.44 180 | 95.31 111 | 81.90 40 | 95.73 225 | 56.78 299 | 82.91 193 | 93.89 183 |
|
conf0.002 | | | 85.70 167 | 84.35 163 | 89.77 174 | 94.53 128 | 79.70 155 | 95.17 189 | 97.11 26 | 75.97 245 | 79.44 180 | 95.31 111 | 81.90 40 | 95.73 225 | 56.78 299 | 82.91 193 | 93.89 183 |
|
VPA-MVSNet | | | 85.32 172 | 83.83 173 | 89.77 174 | 90.25 216 | 82.63 89 | 96.36 143 | 97.07 35 | 83.03 146 | 81.21 164 | 89.02 208 | 61.58 236 | 96.31 189 | 85.02 110 | 70.95 253 | 90.36 211 |
|
CLD-MVS | | | 87.97 125 | 87.48 113 | 89.44 177 | 92.16 185 | 80.54 134 | 98.14 27 | 94.92 170 | 91.41 16 | 79.43 186 | 95.40 109 | 62.34 227 | 97.27 153 | 90.60 64 | 82.90 199 | 90.50 210 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
XXY-MVS | | | 83.84 190 | 82.00 196 | 89.35 178 | 87.13 253 | 81.38 116 | 95.72 175 | 94.26 202 | 80.15 199 | 75.92 227 | 90.63 189 | 61.96 234 | 96.52 182 | 78.98 157 | 73.28 245 | 90.14 216 |
|
CPTT-MVS | | | 89.72 89 | 89.87 78 | 89.29 179 | 98.33 38 | 73.30 261 | 97.70 48 | 95.35 156 | 75.68 254 | 87.40 98 | 97.44 65 | 70.43 166 | 98.25 110 | 89.56 75 | 96.90 67 | 96.33 141 |
|
MSDG | | | 80.62 237 | 77.77 242 | 89.14 180 | 93.43 158 | 77.24 231 | 91.89 267 | 90.18 297 | 69.86 300 | 68.02 273 | 91.94 172 | 52.21 291 | 98.84 94 | 59.32 290 | 83.12 188 | 91.35 202 |
|
TAPA-MVS | | 81.61 12 | 85.02 175 | 83.67 175 | 89.06 181 | 96.79 76 | 73.27 263 | 95.92 165 | 94.79 179 | 74.81 269 | 80.47 170 | 96.83 86 | 71.07 160 | 98.19 113 | 49.82 323 | 92.57 109 | 95.71 153 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
LS3D | | | 82.22 221 | 79.94 229 | 89.06 181 | 97.43 64 | 74.06 259 | 93.20 242 | 92.05 270 | 61.90 319 | 73.33 244 | 95.21 119 | 59.35 246 | 99.21 65 | 54.54 310 | 92.48 111 | 93.90 182 |
|
PatchMatch-RL | | | 85.00 176 | 83.66 176 | 89.02 183 | 95.86 96 | 74.55 254 | 92.49 255 | 93.60 241 | 79.30 216 | 79.29 188 | 91.47 175 | 58.53 253 | 98.45 105 | 70.22 229 | 92.17 117 | 94.07 180 |
|
HQP-MVS | | | 87.91 128 | 87.55 112 | 88.98 184 | 92.08 186 | 78.48 200 | 97.63 51 | 94.80 177 | 90.52 24 | 82.30 147 | 94.56 135 | 65.40 209 | 97.32 148 | 87.67 93 | 83.01 190 | 91.13 203 |
|
Vis-MVSNet (Re-imp) | | | 88.88 103 | 88.87 92 | 88.91 185 | 93.89 148 | 74.43 255 | 96.93 107 | 94.19 206 | 84.39 116 | 83.22 139 | 95.67 105 | 78.24 78 | 94.70 265 | 78.88 158 | 94.40 93 | 97.61 91 |
|
NR-MVSNet | | | 83.35 202 | 81.52 208 | 88.84 186 | 88.76 237 | 81.31 118 | 94.45 209 | 95.16 162 | 84.65 109 | 67.81 274 | 90.82 186 | 70.36 167 | 94.87 261 | 74.75 198 | 66.89 292 | 90.33 213 |
|
Patchmatch-test | | | 78.25 254 | 74.72 269 | 88.83 187 | 91.20 203 | 74.10 258 | 73.91 338 | 88.70 311 | 59.89 328 | 66.82 277 | 85.12 271 | 78.38 77 | 94.54 268 | 48.84 325 | 79.58 213 | 97.86 74 |
|
tpm | | | 85.55 169 | 84.47 161 | 88.80 188 | 90.19 218 | 75.39 249 | 88.79 290 | 94.69 182 | 84.83 105 | 83.96 129 | 85.21 266 | 78.22 79 | 94.68 266 | 76.32 185 | 78.02 226 | 96.34 139 |
|
HQP_MVS | | | 87.50 131 | 87.09 123 | 88.74 189 | 91.86 196 | 77.96 216 | 97.18 78 | 94.69 182 | 89.89 30 | 81.33 162 | 94.15 141 | 64.77 214 | 97.30 150 | 87.08 96 | 82.82 200 | 90.96 205 |
|
MIMVSNet | | | 79.18 247 | 75.99 256 | 88.72 190 | 87.37 252 | 80.66 130 | 79.96 323 | 91.82 273 | 77.38 236 | 74.33 237 | 81.87 293 | 41.78 319 | 90.74 315 | 66.36 260 | 83.10 189 | 94.76 171 |
|
FIs | | | 86.73 148 | 86.10 134 | 88.61 191 | 90.05 221 | 80.21 143 | 96.14 156 | 96.95 43 | 85.56 87 | 78.37 194 | 92.30 166 | 76.73 98 | 95.28 250 | 79.51 152 | 79.27 216 | 90.35 212 |
|
UniMVSNet (Re) | | | 85.31 173 | 84.23 170 | 88.55 192 | 89.75 224 | 80.55 133 | 96.72 116 | 96.89 48 | 85.42 88 | 78.40 193 | 88.93 209 | 75.38 125 | 95.52 239 | 78.58 159 | 68.02 283 | 89.57 227 |
|
PatchT | | | 79.75 240 | 76.85 250 | 88.42 193 | 89.55 229 | 75.49 248 | 77.37 332 | 94.61 191 | 63.07 313 | 82.46 145 | 73.32 327 | 75.52 114 | 93.41 287 | 51.36 317 | 84.43 179 | 96.36 137 |
|
WR-MVS | | | 84.32 185 | 82.96 185 | 88.41 194 | 89.38 233 | 80.32 138 | 96.59 126 | 96.25 107 | 83.97 128 | 76.63 215 | 90.36 194 | 67.53 178 | 94.86 262 | 75.82 190 | 70.09 263 | 90.06 222 |
|
GBi-Net | | | 82.42 216 | 80.43 221 | 88.39 195 | 92.66 169 | 81.95 98 | 94.30 214 | 93.38 249 | 79.06 220 | 75.82 228 | 85.66 258 | 56.38 276 | 93.84 280 | 71.23 221 | 75.38 234 | 89.38 231 |
|
test1 | | | 82.42 216 | 80.43 221 | 88.39 195 | 92.66 169 | 81.95 98 | 94.30 214 | 93.38 249 | 79.06 220 | 75.82 228 | 85.66 258 | 56.38 276 | 93.84 280 | 71.23 221 | 75.38 234 | 89.38 231 |
|
FMVSNet1 | | | 79.50 242 | 76.54 253 | 88.39 195 | 88.47 242 | 81.95 98 | 94.30 214 | 93.38 249 | 73.14 283 | 72.04 254 | 85.66 258 | 43.86 311 | 93.84 280 | 65.48 263 | 72.53 248 | 89.38 231 |
|
testing_2 | | | 76.96 271 | 73.18 281 | 88.30 198 | 75.87 330 | 79.64 162 | 89.92 281 | 94.21 203 | 80.16 198 | 51.23 329 | 75.94 320 | 33.94 332 | 95.81 217 | 82.28 136 | 75.12 237 | 89.46 228 |
|
DU-MVS | | | 84.57 183 | 83.33 183 | 88.28 199 | 88.76 237 | 79.36 165 | 96.43 140 | 95.41 153 | 85.42 88 | 78.11 196 | 90.82 186 | 67.61 176 | 95.14 254 | 79.14 155 | 68.30 280 | 90.33 213 |
|
v2v482 | | | 83.46 195 | 81.86 200 | 88.25 200 | 86.19 278 | 79.65 161 | 96.34 145 | 94.02 220 | 81.56 170 | 77.32 207 | 88.23 218 | 65.62 204 | 96.03 200 | 77.77 162 | 69.72 270 | 89.09 235 |
|
UniMVSNet_NR-MVSNet | | | 85.49 170 | 84.59 157 | 88.21 201 | 89.44 232 | 79.36 165 | 96.71 118 | 96.41 92 | 85.22 92 | 78.11 196 | 90.98 185 | 76.97 94 | 95.14 254 | 79.14 155 | 68.30 280 | 90.12 218 |
|
OPM-MVS | | | 85.84 158 | 85.10 150 | 88.06 202 | 88.34 243 | 77.83 222 | 95.72 175 | 94.20 204 | 87.89 55 | 80.45 171 | 94.05 143 | 58.57 252 | 97.26 154 | 83.88 117 | 82.76 202 | 89.09 235 |
|
PMMVS | | | 89.46 92 | 89.92 76 | 88.06 202 | 94.64 124 | 69.57 296 | 96.22 153 | 94.95 169 | 87.27 61 | 91.37 58 | 96.54 93 | 65.88 201 | 97.39 146 | 88.54 82 | 93.89 98 | 97.23 113 |
|
v1141 | | | 83.36 200 | 81.81 203 | 88.01 204 | 86.61 263 | 79.26 168 | 96.44 136 | 94.12 214 | 80.88 176 | 77.48 203 | 86.87 237 | 67.08 185 | 96.03 200 | 77.14 175 | 69.69 271 | 88.75 247 |
|
divwei89l23v2f112 | | | 83.36 200 | 81.81 203 | 88.01 204 | 86.60 264 | 79.23 171 | 96.44 136 | 94.12 214 | 80.88 176 | 77.49 201 | 86.87 237 | 67.08 185 | 96.03 200 | 77.14 175 | 69.67 272 | 88.76 245 |
|
v1 | | | 83.37 199 | 81.82 201 | 88.01 204 | 86.58 265 | 79.24 169 | 96.45 134 | 94.13 211 | 80.88 176 | 77.48 203 | 86.88 236 | 67.15 183 | 96.04 199 | 77.15 174 | 69.67 272 | 88.76 245 |
|
v1neww | | | 83.45 196 | 81.95 197 | 87.95 207 | 86.66 257 | 79.04 180 | 96.32 146 | 94.17 207 | 80.76 180 | 77.56 199 | 87.25 230 | 67.02 188 | 96.08 196 | 77.73 165 | 70.07 264 | 88.74 249 |
|
v7new | | | 83.45 196 | 81.95 197 | 87.95 207 | 86.66 257 | 79.04 180 | 96.32 146 | 94.17 207 | 80.76 180 | 77.56 199 | 87.25 230 | 67.02 188 | 96.08 196 | 77.73 165 | 70.07 264 | 88.74 249 |
|
v6 | | | 83.45 196 | 81.94 199 | 87.95 207 | 86.62 261 | 79.03 183 | 96.32 146 | 94.17 207 | 80.76 180 | 77.57 198 | 87.23 232 | 67.03 187 | 96.09 195 | 77.73 165 | 70.06 266 | 88.75 247 |
|
TranMVSNet+NR-MVSNet | | | 83.24 204 | 81.71 205 | 87.83 210 | 87.71 249 | 78.81 191 | 96.13 158 | 94.82 176 | 84.52 112 | 76.18 224 | 90.78 188 | 64.07 217 | 94.60 267 | 74.60 200 | 66.59 296 | 90.09 220 |
|
pmmvs4 | | | 82.54 214 | 80.79 215 | 87.79 211 | 86.11 281 | 80.49 137 | 93.55 228 | 93.18 256 | 77.29 238 | 73.35 243 | 89.40 205 | 65.26 212 | 95.05 259 | 75.32 194 | 73.61 241 | 87.83 267 |
|
v1144 | | | 82.90 210 | 81.27 212 | 87.78 212 | 86.29 274 | 79.07 179 | 96.14 156 | 93.93 223 | 80.05 201 | 77.38 205 | 86.80 241 | 65.50 205 | 95.93 211 | 75.21 195 | 70.13 260 | 88.33 259 |
|
v7 | | | 82.99 209 | 81.41 209 | 87.73 213 | 86.41 268 | 78.86 188 | 96.10 159 | 93.98 221 | 79.88 205 | 77.49 201 | 87.11 234 | 65.44 207 | 95.97 205 | 75.69 192 | 70.59 257 | 88.36 257 |
|
F-COLMAP | | | 84.50 184 | 83.44 182 | 87.67 214 | 95.22 112 | 72.22 268 | 95.95 163 | 93.78 233 | 75.74 252 | 76.30 221 | 95.18 121 | 59.50 244 | 98.45 105 | 72.67 209 | 86.59 154 | 92.35 200 |
|
FC-MVSNet-test | | | 85.96 156 | 85.39 144 | 87.66 215 | 89.38 233 | 78.02 214 | 95.65 178 | 96.87 49 | 85.12 96 | 77.34 206 | 91.94 172 | 76.28 105 | 94.74 264 | 77.09 177 | 78.82 219 | 90.21 215 |
|
v1192 | | | 82.31 219 | 80.55 219 | 87.60 216 | 85.94 284 | 78.47 203 | 95.85 172 | 93.80 231 | 79.33 214 | 76.97 212 | 86.51 246 | 63.33 223 | 95.87 213 | 73.11 206 | 70.13 260 | 88.46 254 |
|
EI-MVSNet | | | 85.80 160 | 85.20 147 | 87.59 217 | 91.55 199 | 77.41 228 | 95.13 195 | 95.36 154 | 80.43 191 | 80.33 173 | 94.71 133 | 73.72 141 | 95.97 205 | 76.96 180 | 78.64 221 | 89.39 229 |
|
XVG-OURS | | | 85.18 174 | 84.38 162 | 87.59 217 | 90.42 215 | 71.73 277 | 91.06 276 | 94.07 218 | 82.00 163 | 83.29 138 | 95.08 127 | 56.42 275 | 97.55 139 | 83.70 123 | 83.42 186 | 93.49 191 |
|
V42 | | | 83.04 206 | 81.53 207 | 87.57 219 | 86.27 276 | 79.09 178 | 95.87 170 | 94.11 216 | 80.35 193 | 77.22 209 | 86.79 242 | 65.32 211 | 96.02 203 | 77.74 164 | 70.14 259 | 87.61 272 |
|
v144192 | | | 82.43 215 | 80.73 217 | 87.54 220 | 85.81 287 | 78.22 208 | 95.98 161 | 93.78 233 | 79.09 219 | 77.11 210 | 86.49 247 | 64.66 216 | 95.91 212 | 74.20 202 | 69.42 274 | 88.49 252 |
|
XVG-OURS-SEG-HR | | | 85.74 166 | 85.16 148 | 87.49 221 | 90.22 217 | 71.45 280 | 91.29 273 | 94.09 217 | 81.37 171 | 83.90 131 | 95.22 117 | 60.30 239 | 97.53 143 | 85.58 105 | 84.42 180 | 93.50 190 |
|
v1921920 | | | 82.02 223 | 80.23 223 | 87.41 222 | 85.62 288 | 77.92 219 | 95.79 174 | 93.69 237 | 78.86 223 | 76.67 214 | 86.44 249 | 62.50 226 | 95.83 216 | 72.69 208 | 69.77 269 | 88.47 253 |
|
v8 | | | 81.88 224 | 80.06 227 | 87.32 223 | 86.63 260 | 79.04 180 | 94.41 210 | 93.65 239 | 78.77 224 | 73.19 246 | 85.57 262 | 66.87 191 | 95.81 217 | 73.84 205 | 67.61 287 | 87.11 280 |
|
IterMVS-LS | | | 83.93 189 | 82.80 189 | 87.31 224 | 91.46 202 | 77.39 229 | 95.66 177 | 93.43 246 | 80.44 189 | 75.51 231 | 87.26 229 | 73.72 141 | 95.16 253 | 76.99 178 | 70.72 255 | 89.39 229 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
v1240 | | | 81.70 226 | 79.83 230 | 87.30 225 | 85.50 289 | 77.70 224 | 95.48 183 | 93.44 244 | 78.46 227 | 76.53 217 | 86.44 249 | 60.85 238 | 95.84 215 | 71.59 218 | 70.17 258 | 88.35 258 |
|
v10 | | | 81.43 229 | 79.53 232 | 87.11 226 | 86.38 269 | 78.87 187 | 94.31 213 | 93.43 246 | 77.88 230 | 73.24 245 | 85.26 265 | 65.44 207 | 95.75 221 | 72.14 212 | 67.71 286 | 86.72 284 |
|
ACMH | | 75.40 17 | 77.99 256 | 74.96 265 | 87.10 227 | 90.67 211 | 76.41 240 | 93.19 243 | 91.64 276 | 72.47 290 | 63.44 293 | 87.61 225 | 43.34 314 | 97.16 158 | 58.34 292 | 73.94 240 | 87.72 268 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
v148 | | | 82.41 218 | 80.89 214 | 86.99 228 | 86.18 279 | 76.81 237 | 96.27 151 | 93.82 228 | 80.49 188 | 75.28 234 | 86.11 256 | 67.32 181 | 95.75 221 | 75.48 193 | 67.03 291 | 88.42 256 |
|
EPNet_dtu | | | 87.65 130 | 87.89 101 | 86.93 229 | 94.57 126 | 71.37 281 | 96.72 116 | 96.50 84 | 88.56 41 | 87.12 102 | 95.02 129 | 75.91 110 | 94.01 278 | 66.62 255 | 90.00 130 | 95.42 158 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
PS-MVSNAJss | | | 84.91 177 | 84.30 169 | 86.74 230 | 85.89 286 | 74.40 256 | 94.95 200 | 94.16 210 | 83.93 129 | 76.45 218 | 90.11 199 | 71.04 161 | 95.77 219 | 83.16 131 | 79.02 218 | 90.06 222 |
|
pmmvs5 | | | 81.34 230 | 79.54 231 | 86.73 231 | 85.02 294 | 76.91 235 | 96.22 153 | 91.65 275 | 77.65 232 | 73.55 240 | 88.61 212 | 55.70 279 | 94.43 270 | 74.12 203 | 73.35 244 | 88.86 244 |
|
MS-PatchMatch | | | 83.05 205 | 81.82 201 | 86.72 232 | 89.64 227 | 79.10 177 | 94.88 202 | 94.59 192 | 79.70 208 | 70.67 261 | 89.65 202 | 50.43 295 | 96.82 174 | 70.82 228 | 95.99 80 | 84.25 304 |
|
LPG-MVS_test | | | 84.20 187 | 83.49 181 | 86.33 233 | 90.88 208 | 73.06 264 | 95.28 185 | 94.13 211 | 82.20 159 | 76.31 219 | 93.20 159 | 54.83 286 | 96.95 167 | 83.72 121 | 80.83 206 | 88.98 239 |
|
LGP-MVS_train | | | | | 86.33 233 | 90.88 208 | 73.06 264 | | 94.13 211 | 82.20 159 | 76.31 219 | 93.20 159 | 54.83 286 | 96.95 167 | 83.72 121 | 80.83 206 | 88.98 239 |
|
ACMP | | 81.66 11 | 84.00 188 | 83.22 184 | 86.33 233 | 91.53 201 | 72.95 266 | 95.91 167 | 93.79 232 | 83.70 136 | 73.79 239 | 92.22 167 | 54.31 289 | 96.89 171 | 83.98 116 | 79.74 211 | 89.16 234 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
tfpnnormal | | | 78.14 255 | 75.42 261 | 86.31 236 | 88.33 244 | 79.24 169 | 94.41 210 | 96.22 109 | 73.51 281 | 69.81 267 | 85.52 264 | 55.43 280 | 95.75 221 | 47.65 327 | 67.86 284 | 83.95 308 |
|
ACMM | | 80.70 13 | 83.72 192 | 82.85 188 | 86.31 236 | 91.19 204 | 72.12 271 | 95.88 169 | 94.29 201 | 80.44 189 | 77.02 211 | 91.96 170 | 55.24 282 | 97.14 161 | 79.30 154 | 80.38 208 | 89.67 226 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
pm-mvs1 | | | 80.05 239 | 78.02 240 | 86.15 238 | 85.42 290 | 75.81 245 | 95.11 197 | 92.69 265 | 77.13 239 | 70.36 263 | 87.43 226 | 58.44 254 | 95.27 251 | 71.36 220 | 64.25 300 | 87.36 278 |
|
USDC | | | 78.65 252 | 76.25 254 | 85.85 239 | 87.58 250 | 74.60 253 | 89.58 283 | 90.58 296 | 84.05 126 | 63.13 295 | 88.23 218 | 40.69 323 | 96.86 173 | 66.57 257 | 75.81 232 | 86.09 292 |
|
mvs-test1 | | | 86.83 144 | 87.17 119 | 85.81 240 | 91.96 192 | 65.24 308 | 97.90 34 | 93.34 253 | 85.57 84 | 84.51 124 | 95.14 124 | 61.99 232 | 97.19 157 | 83.55 125 | 90.55 128 | 95.00 167 |
|
ADS-MVSNet2 | | | 79.57 241 | 77.53 243 | 85.71 241 | 93.78 149 | 72.13 270 | 79.48 324 | 86.11 324 | 73.09 284 | 80.14 175 | 79.99 302 | 62.15 229 | 90.14 320 | 59.49 288 | 83.52 184 | 94.85 169 |
|
Patchmtry | | | 77.36 265 | 74.59 272 | 85.67 242 | 89.75 224 | 75.75 246 | 77.85 331 | 91.12 280 | 60.28 326 | 71.23 256 | 80.35 300 | 75.45 115 | 93.56 286 | 57.94 293 | 67.34 290 | 87.68 270 |
|
MVP-Stereo | | | 82.65 213 | 81.67 206 | 85.59 243 | 86.10 282 | 78.29 206 | 93.33 234 | 92.82 262 | 77.75 231 | 69.17 272 | 87.98 222 | 59.28 248 | 95.76 220 | 71.77 215 | 96.88 69 | 82.73 322 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
Fast-Effi-MVS+-dtu | | | 83.33 203 | 82.60 192 | 85.50 244 | 89.55 229 | 69.38 297 | 96.09 160 | 91.38 277 | 82.30 158 | 75.96 226 | 91.41 176 | 56.71 270 | 95.58 237 | 75.13 196 | 84.90 177 | 91.54 201 |
|
v7n | | | 79.32 245 | 77.34 244 | 85.28 245 | 84.05 304 | 72.89 267 | 93.38 232 | 93.87 226 | 75.02 265 | 70.68 260 | 84.37 274 | 59.58 243 | 95.62 234 | 67.60 248 | 67.50 288 | 87.32 279 |
|
IterMVS | | | 80.67 236 | 79.16 234 | 85.20 246 | 89.79 223 | 76.08 243 | 92.97 246 | 91.86 272 | 80.28 195 | 71.20 257 | 85.14 270 | 57.93 262 | 91.34 310 | 72.52 210 | 70.74 254 | 88.18 262 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
ACMH+ | | 76.62 16 | 77.47 263 | 74.94 266 | 85.05 247 | 91.07 206 | 71.58 279 | 93.26 239 | 90.01 298 | 71.80 293 | 64.76 288 | 88.55 213 | 41.62 320 | 96.48 183 | 62.35 281 | 71.00 252 | 87.09 281 |
|
jajsoiax | | | 82.12 222 | 81.15 213 | 85.03 248 | 84.19 301 | 70.70 286 | 94.22 218 | 93.95 222 | 83.07 145 | 73.48 241 | 89.75 201 | 49.66 298 | 95.37 246 | 82.24 137 | 79.76 209 | 89.02 238 |
|
v18 | | | 77.96 258 | 75.61 259 | 84.98 249 | 86.66 257 | 79.01 184 | 93.02 245 | 90.94 285 | 75.69 253 | 63.19 294 | 77.62 309 | 67.11 184 | 92.07 297 | 70.05 230 | 56.24 316 | 83.87 309 |
|
v17 | | | 77.79 260 | 75.41 262 | 84.94 250 | 86.53 266 | 78.94 185 | 92.83 250 | 90.88 287 | 75.51 255 | 62.97 299 | 77.50 311 | 66.69 194 | 92.03 299 | 69.80 232 | 56.01 318 | 83.83 310 |
|
v16 | | | 77.84 259 | 75.47 260 | 84.93 251 | 86.62 261 | 78.93 186 | 92.84 249 | 90.89 286 | 75.50 256 | 63.03 298 | 77.54 310 | 66.82 193 | 92.04 298 | 69.82 231 | 56.22 317 | 83.82 311 |
|
mvs_tets | | | 81.74 225 | 80.71 218 | 84.84 252 | 84.22 300 | 70.29 289 | 93.91 221 | 93.78 233 | 82.77 150 | 73.37 242 | 89.46 204 | 47.36 307 | 95.31 249 | 81.99 138 | 79.55 215 | 88.92 243 |
|
v15 | | | 77.52 262 | 75.09 263 | 84.82 253 | 86.37 270 | 78.82 189 | 92.58 253 | 90.78 289 | 75.47 257 | 62.53 301 | 77.17 312 | 66.58 197 | 91.92 300 | 69.18 235 | 55.16 320 | 83.73 312 |
|
V14 | | | 77.43 264 | 74.99 264 | 84.75 254 | 86.32 273 | 78.67 193 | 92.44 257 | 90.77 290 | 75.28 261 | 62.42 302 | 77.13 313 | 66.40 198 | 91.88 301 | 69.01 240 | 55.14 321 | 83.70 313 |
|
LTVRE_ROB | | 73.68 18 | 77.99 256 | 75.74 258 | 84.74 255 | 90.45 214 | 72.02 272 | 86.41 310 | 91.12 280 | 72.57 289 | 66.63 278 | 87.27 228 | 54.95 285 | 96.98 166 | 56.29 305 | 75.98 230 | 85.21 297 |
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 | | | | | 84.73 256 | 89.63 228 | 74.66 252 | | 91.81 274 | 80.05 201 | 71.06 259 | 85.18 268 | 57.98 261 | 91.40 309 | 72.48 211 | 70.70 256 | 88.12 263 |
|
V9 | | | 77.32 266 | 74.87 267 | 84.69 257 | 86.26 277 | 78.52 199 | 92.33 260 | 90.72 291 | 75.11 264 | 62.21 304 | 77.08 315 | 66.19 200 | 91.87 302 | 68.84 241 | 55.06 323 | 83.69 314 |
|
v11 | | | 77.21 267 | 74.72 269 | 84.68 258 | 86.29 274 | 78.62 196 | 92.30 261 | 90.63 295 | 74.86 268 | 62.32 303 | 76.73 318 | 65.49 206 | 91.83 303 | 68.17 247 | 55.72 319 | 83.59 316 |
|
Baseline_NR-MVSNet | | | 81.22 232 | 80.07 226 | 84.68 258 | 85.32 292 | 75.12 251 | 96.48 130 | 88.80 308 | 76.24 244 | 77.28 208 | 86.40 252 | 67.61 176 | 94.39 271 | 75.73 191 | 66.73 295 | 84.54 302 |
|
test_djsdf | | | 83.00 208 | 82.45 194 | 84.64 260 | 84.07 303 | 69.78 293 | 94.80 204 | 94.48 194 | 80.74 183 | 75.41 233 | 87.70 224 | 61.32 237 | 95.10 256 | 83.77 119 | 79.76 209 | 89.04 237 |
|
v12 | | | 77.20 268 | 74.73 268 | 84.63 261 | 86.15 280 | 78.41 204 | 92.17 262 | 90.71 292 | 74.92 267 | 62.05 306 | 77.00 316 | 65.83 202 | 91.83 303 | 68.69 243 | 55.01 324 | 83.64 315 |
|
TransMVSNet (Re) | | | 76.94 272 | 74.38 275 | 84.62 262 | 85.92 285 | 75.25 250 | 95.28 185 | 89.18 305 | 73.88 279 | 67.22 275 | 86.46 248 | 59.64 241 | 94.10 276 | 59.24 291 | 52.57 330 | 84.50 303 |
|
Patchmatch-RL test | | | 76.65 274 | 74.01 278 | 84.55 263 | 77.37 325 | 64.23 310 | 78.49 330 | 82.84 338 | 78.48 226 | 64.63 289 | 73.40 326 | 76.05 108 | 91.70 308 | 76.99 178 | 57.84 312 | 97.72 82 |
|
v13 | | | 77.11 270 | 74.63 271 | 84.55 263 | 86.08 283 | 78.27 207 | 92.06 264 | 90.68 294 | 74.73 270 | 61.86 309 | 76.93 317 | 65.73 203 | 91.81 306 | 68.55 246 | 55.07 322 | 83.59 316 |
|
AllTest | | | 75.92 277 | 73.06 282 | 84.47 265 | 92.18 183 | 67.29 302 | 91.07 275 | 84.43 330 | 67.63 304 | 63.48 291 | 90.18 196 | 38.20 325 | 97.16 158 | 57.04 295 | 73.37 242 | 88.97 241 |
|
TestCases | | | | | 84.47 265 | 92.18 183 | 67.29 302 | | 84.43 330 | 67.63 304 | 63.48 291 | 90.18 196 | 38.20 325 | 97.16 158 | 57.04 295 | 73.37 242 | 88.97 241 |
|
MVS-HIRNet | | | 71.36 297 | 67.00 300 | 84.46 267 | 90.58 212 | 69.74 294 | 79.15 327 | 87.74 315 | 46.09 339 | 61.96 308 | 50.50 341 | 45.14 310 | 95.64 232 | 53.74 312 | 88.11 144 | 88.00 265 |
|
JIA-IIPM | | | 79.00 248 | 77.20 245 | 84.40 268 | 89.74 226 | 64.06 312 | 75.30 334 | 95.44 152 | 62.15 318 | 81.90 159 | 59.08 338 | 78.92 69 | 95.59 236 | 66.51 258 | 85.78 165 | 93.54 189 |
|
v748 | | | 78.69 251 | 76.79 251 | 84.39 269 | 83.40 307 | 70.78 285 | 93.25 240 | 93.62 240 | 74.96 266 | 69.40 269 | 83.74 281 | 59.40 245 | 95.39 244 | 68.74 242 | 64.59 299 | 86.99 283 |
|
LCM-MVSNet-Re | | | 83.75 191 | 83.54 179 | 84.39 269 | 93.54 156 | 64.14 311 | 92.51 254 | 84.03 333 | 83.90 130 | 66.14 281 | 86.59 245 | 67.36 180 | 92.68 288 | 84.89 111 | 92.87 108 | 96.35 138 |
|
anonymousdsp | | | 80.98 235 | 79.97 228 | 84.01 271 | 81.73 310 | 70.44 288 | 92.49 255 | 93.58 243 | 77.10 241 | 72.98 248 | 86.31 253 | 57.58 263 | 94.90 260 | 79.32 153 | 78.63 223 | 86.69 285 |
|
v52 | | | 78.70 249 | 76.95 247 | 83.95 272 | 81.71 311 | 71.34 282 | 91.93 266 | 93.43 246 | 74.69 272 | 70.36 263 | 83.71 283 | 58.04 258 | 95.50 240 | 71.84 213 | 66.82 294 | 85.00 299 |
|
V4 | | | 78.70 249 | 76.95 247 | 83.95 272 | 81.66 312 | 71.34 282 | 91.94 265 | 93.44 244 | 74.69 272 | 70.35 265 | 83.73 282 | 58.07 257 | 95.50 240 | 71.84 213 | 66.86 293 | 85.02 298 |
|
COLMAP_ROB | | 73.24 19 | 75.74 278 | 73.00 283 | 83.94 274 | 92.38 174 | 69.08 298 | 91.85 268 | 86.93 320 | 61.48 322 | 65.32 286 | 90.27 195 | 42.27 318 | 96.93 170 | 50.91 320 | 75.63 233 | 85.80 294 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
XVG-ACMP-BASELINE | | | 79.38 244 | 77.90 241 | 83.81 275 | 84.98 295 | 67.14 305 | 89.03 288 | 93.18 256 | 80.26 197 | 72.87 249 | 88.15 220 | 38.55 324 | 96.26 191 | 76.05 188 | 78.05 225 | 88.02 264 |
|
CP-MVSNet | | | 81.01 234 | 80.08 225 | 83.79 276 | 87.91 248 | 70.51 287 | 94.29 217 | 95.65 138 | 80.83 179 | 72.54 252 | 88.84 210 | 63.71 218 | 92.32 292 | 68.58 245 | 68.36 279 | 88.55 251 |
|
WR-MVS_H | | | 81.02 233 | 80.09 224 | 83.79 276 | 88.08 246 | 71.26 284 | 94.46 208 | 96.54 80 | 80.08 200 | 72.81 250 | 86.82 240 | 70.36 167 | 92.65 289 | 64.18 268 | 67.50 288 | 87.46 277 |
|
test0.0.03 1 | | | 82.79 211 | 82.48 193 | 83.74 278 | 86.81 255 | 72.22 268 | 96.52 129 | 95.03 167 | 83.76 134 | 73.00 247 | 93.20 159 | 72.30 150 | 88.88 322 | 64.15 269 | 77.52 228 | 90.12 218 |
|
Effi-MVS+-dtu | | | 84.61 182 | 84.90 156 | 83.72 279 | 91.96 192 | 63.14 315 | 94.95 200 | 93.34 253 | 85.57 84 | 79.79 178 | 87.12 233 | 61.99 232 | 95.61 235 | 83.55 125 | 85.83 164 | 92.41 199 |
|
EG-PatchMatch MVS | | | 74.92 281 | 72.02 285 | 83.62 280 | 83.76 306 | 73.28 262 | 93.62 226 | 92.04 271 | 68.57 303 | 58.88 317 | 83.80 280 | 31.87 336 | 95.57 238 | 56.97 297 | 78.67 220 | 82.00 328 |
|
pmmvs6 | | | 74.65 283 | 71.67 286 | 83.60 281 | 79.13 320 | 69.94 291 | 93.31 238 | 90.88 287 | 61.05 325 | 65.83 283 | 84.15 277 | 43.43 313 | 94.83 263 | 66.62 255 | 60.63 308 | 86.02 293 |
|
PS-CasMVS | | | 80.27 238 | 79.18 233 | 83.52 282 | 87.56 251 | 69.88 292 | 94.08 219 | 95.29 159 | 80.27 196 | 72.08 253 | 88.51 216 | 59.22 249 | 92.23 294 | 67.49 249 | 68.15 282 | 88.45 255 |
|
OpenMVS_ROB | | 68.52 20 | 73.02 291 | 69.57 295 | 83.37 283 | 80.54 316 | 71.82 274 | 93.60 227 | 88.22 312 | 62.37 317 | 61.98 307 | 83.15 289 | 35.31 331 | 95.47 242 | 45.08 330 | 75.88 231 | 82.82 320 |
|
FMVSNet5 | | | 76.46 275 | 74.16 277 | 83.35 284 | 90.05 221 | 76.17 242 | 89.58 283 | 89.85 299 | 71.39 296 | 65.29 287 | 80.42 299 | 50.61 294 | 87.70 326 | 61.05 284 | 69.24 275 | 86.18 290 |
|
PEN-MVS | | | 79.47 243 | 78.26 239 | 83.08 285 | 86.36 271 | 68.58 299 | 93.85 222 | 94.77 180 | 79.76 207 | 71.37 255 | 88.55 213 | 59.79 240 | 92.46 290 | 64.50 267 | 65.40 297 | 88.19 261 |
|
MDA-MVSNet_test_wron | | | 73.54 287 | 70.43 293 | 82.86 286 | 84.55 296 | 71.85 273 | 91.74 270 | 91.32 279 | 67.63 304 | 46.73 335 | 81.09 297 | 55.11 283 | 90.42 318 | 55.91 307 | 59.76 310 | 86.31 288 |
|
YYNet1 | | | 73.53 288 | 70.43 293 | 82.85 287 | 84.52 298 | 71.73 277 | 91.69 271 | 91.37 278 | 67.63 304 | 46.79 334 | 81.21 296 | 55.04 284 | 90.43 317 | 55.93 306 | 59.70 311 | 86.38 287 |
|
TinyColmap | | | 72.41 293 | 68.99 298 | 82.68 288 | 88.11 245 | 69.59 295 | 88.41 293 | 85.20 327 | 65.55 310 | 57.91 321 | 84.82 273 | 30.80 338 | 95.94 210 | 51.38 316 | 68.70 276 | 82.49 325 |
|
CVMVSNet | | | 84.83 179 | 85.57 142 | 82.63 289 | 91.55 199 | 60.38 321 | 95.13 195 | 95.03 167 | 80.60 186 | 82.10 157 | 94.71 133 | 66.40 198 | 90.19 319 | 74.30 201 | 90.32 129 | 97.31 107 |
|
LP | | | 68.54 305 | 63.92 307 | 82.39 290 | 87.93 247 | 71.79 276 | 72.37 341 | 86.01 326 | 55.89 333 | 58.33 320 | 71.46 332 | 49.58 299 | 90.10 321 | 32.25 342 | 61.48 307 | 85.27 295 |
|
pmmvs-eth3d | | | 73.59 286 | 70.66 290 | 82.38 291 | 76.40 327 | 73.38 260 | 89.39 287 | 89.43 302 | 72.69 288 | 60.34 314 | 77.79 308 | 46.43 309 | 91.26 312 | 66.42 259 | 57.06 313 | 82.51 323 |
|
ITE_SJBPF | | | | | 82.38 291 | 87.00 254 | 65.59 307 | | 89.55 301 | 79.99 203 | 69.37 270 | 91.30 179 | 41.60 321 | 95.33 248 | 62.86 280 | 74.63 239 | 86.24 289 |
|
DTE-MVSNet | | | 78.37 253 | 77.06 246 | 82.32 293 | 85.22 293 | 67.17 304 | 93.40 231 | 93.66 238 | 78.71 225 | 70.53 262 | 88.29 217 | 59.06 250 | 92.23 294 | 61.38 283 | 63.28 304 | 87.56 274 |
|
test_0402 | | | 72.68 292 | 69.54 296 | 82.09 294 | 88.67 240 | 71.81 275 | 92.72 252 | 86.77 321 | 61.52 321 | 62.21 304 | 83.91 278 | 43.22 315 | 93.76 283 | 34.60 340 | 72.23 249 | 80.72 330 |
|
MDA-MVSNet-bldmvs | | | 71.45 296 | 67.94 299 | 81.98 295 | 85.33 291 | 68.50 300 | 92.35 259 | 88.76 309 | 70.40 298 | 42.99 336 | 81.96 292 | 46.57 308 | 91.31 311 | 48.75 326 | 54.39 326 | 86.11 291 |
|
UnsupCasMVSNet_eth | | | 73.25 289 | 70.57 291 | 81.30 296 | 77.53 323 | 66.33 306 | 87.24 302 | 93.89 225 | 80.38 192 | 57.90 322 | 81.59 294 | 42.91 317 | 90.56 316 | 65.18 265 | 48.51 334 | 87.01 282 |
|
SixPastTwentyTwo | | | 76.04 276 | 74.32 276 | 81.22 297 | 84.54 297 | 61.43 320 | 91.16 274 | 89.30 304 | 77.89 229 | 64.04 290 | 86.31 253 | 48.23 301 | 94.29 273 | 63.54 277 | 63.84 302 | 87.93 266 |
|
RPSCF | | | 77.73 261 | 76.63 252 | 81.06 298 | 88.66 241 | 55.76 330 | 87.77 298 | 87.88 314 | 64.82 312 | 74.14 238 | 92.79 164 | 49.22 300 | 96.81 175 | 67.47 250 | 76.88 229 | 90.62 208 |
|
UnsupCasMVSNet_bld | | | 68.60 304 | 64.50 305 | 80.92 299 | 74.63 331 | 67.80 301 | 83.97 317 | 92.94 261 | 65.12 311 | 54.63 326 | 68.23 335 | 35.97 328 | 92.17 296 | 60.13 286 | 44.83 338 | 82.78 321 |
|
OurMVSNet-221017-0 | | | 77.18 269 | 76.06 255 | 80.55 300 | 83.78 305 | 60.00 322 | 90.35 278 | 91.05 283 | 77.01 243 | 66.62 279 | 87.92 223 | 47.73 305 | 94.03 277 | 71.63 217 | 68.44 278 | 87.62 271 |
|
Anonymous20231206 | | | 75.29 280 | 73.64 279 | 80.22 301 | 80.75 313 | 63.38 314 | 93.36 233 | 90.71 292 | 73.09 284 | 67.12 276 | 83.70 284 | 50.33 296 | 90.85 314 | 53.63 313 | 70.10 262 | 86.44 286 |
|
lessismore_v0 | | | | | 79.98 302 | 80.59 315 | 58.34 326 | | 80.87 341 | | 58.49 318 | 83.46 286 | 43.10 316 | 93.89 279 | 63.11 279 | 48.68 333 | 87.72 268 |
|
K. test v3 | | | 73.62 285 | 71.59 287 | 79.69 303 | 82.98 308 | 59.85 323 | 90.85 277 | 88.83 307 | 77.13 239 | 58.90 316 | 82.11 291 | 43.62 312 | 91.72 307 | 65.83 262 | 54.10 327 | 87.50 276 |
|
TDRefinement | | | 69.20 302 | 65.78 304 | 79.48 304 | 66.04 341 | 62.21 317 | 88.21 294 | 86.12 323 | 62.92 315 | 61.03 312 | 85.61 261 | 33.23 333 | 94.16 275 | 55.82 308 | 53.02 328 | 82.08 327 |
|
testgi | | | 74.88 282 | 73.40 280 | 79.32 305 | 80.13 317 | 61.75 318 | 93.21 241 | 86.64 322 | 79.49 212 | 66.56 280 | 91.06 182 | 35.51 330 | 88.67 323 | 56.79 298 | 71.25 250 | 87.56 274 |
|
CMPMVS | | 54.94 21 | 75.71 279 | 74.56 273 | 79.17 306 | 79.69 318 | 55.98 328 | 89.59 282 | 93.30 255 | 60.28 326 | 53.85 327 | 89.07 207 | 47.68 306 | 96.33 188 | 76.55 182 | 81.02 205 | 85.22 296 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
MIMVSNet1 | | | 69.44 300 | 66.65 302 | 77.84 307 | 76.48 326 | 62.84 316 | 87.42 300 | 88.97 306 | 66.96 309 | 57.75 323 | 79.72 304 | 32.77 335 | 85.83 332 | 46.32 328 | 63.42 303 | 84.85 301 |
|
new-patchmatchnet | | | 68.85 303 | 65.93 303 | 77.61 308 | 73.57 334 | 63.94 313 | 90.11 280 | 88.73 310 | 71.62 294 | 55.08 325 | 73.60 323 | 40.84 322 | 87.22 328 | 51.35 318 | 48.49 335 | 81.67 329 |
|
LF4IMVS | | | 72.36 294 | 70.82 289 | 76.95 309 | 79.18 319 | 56.33 327 | 86.12 311 | 86.11 324 | 69.30 302 | 63.06 297 | 86.66 243 | 33.03 334 | 92.25 293 | 65.33 264 | 68.64 277 | 82.28 326 |
|
EU-MVSNet | | | 76.92 273 | 76.95 247 | 76.83 310 | 84.10 302 | 54.73 331 | 91.77 269 | 92.71 264 | 72.74 287 | 69.57 268 | 88.69 211 | 58.03 260 | 87.43 327 | 64.91 266 | 70.00 267 | 88.33 259 |
|
PM-MVS | | | 69.32 301 | 66.93 301 | 76.49 311 | 73.60 333 | 55.84 329 | 85.91 312 | 79.32 345 | 74.72 271 | 61.09 311 | 78.18 307 | 21.76 342 | 91.10 313 | 70.86 226 | 56.90 314 | 82.51 323 |
|
pmmvs3 | | | 65.75 307 | 62.18 310 | 76.45 312 | 67.12 339 | 64.54 309 | 88.68 291 | 85.05 328 | 54.77 337 | 57.54 324 | 73.79 322 | 29.40 340 | 86.21 331 | 55.49 309 | 47.77 336 | 78.62 332 |
|
ambc | | | | | 76.02 313 | 68.11 338 | 51.43 335 | 64.97 343 | 89.59 300 | | 60.49 313 | 74.49 321 | 17.17 346 | 92.46 290 | 61.50 282 | 52.85 329 | 84.17 305 |
|
test20.03 | | | 72.36 294 | 71.15 288 | 75.98 314 | 77.79 322 | 59.16 325 | 92.40 258 | 89.35 303 | 74.09 277 | 61.50 310 | 84.32 275 | 48.09 302 | 85.54 335 | 50.63 321 | 62.15 306 | 83.24 318 |
|
DSMNet-mixed | | | 73.13 290 | 72.45 284 | 75.19 315 | 77.51 324 | 46.82 339 | 85.09 316 | 82.01 339 | 67.61 308 | 69.27 271 | 81.33 295 | 50.89 292 | 86.28 330 | 54.54 310 | 83.80 183 | 92.46 198 |
|
new_pmnet | | | 66.18 306 | 63.18 308 | 75.18 316 | 76.27 328 | 61.74 319 | 83.79 318 | 84.66 329 | 56.64 332 | 51.57 328 | 71.85 330 | 31.29 337 | 87.93 325 | 49.98 322 | 62.55 305 | 75.86 335 |
|
test2356 | | | 74.41 284 | 74.53 274 | 74.07 317 | 76.13 329 | 54.45 332 | 94.74 206 | 92.08 269 | 71.96 292 | 65.51 285 | 83.05 290 | 56.96 268 | 83.71 337 | 52.74 315 | 77.58 227 | 84.06 306 |
|
Anonymous20231211 | | | 61.03 311 | 56.76 313 | 73.82 318 | 71.24 335 | 53.47 333 | 87.60 299 | 81.65 340 | 44.19 340 | 51.08 332 | 71.82 331 | 20.79 343 | 88.46 324 | 35.45 339 | 47.07 337 | 79.52 331 |
|
testus | | | 70.06 299 | 69.09 297 | 72.98 319 | 74.54 332 | 51.28 337 | 93.78 223 | 87.34 316 | 71.49 295 | 62.69 300 | 83.46 286 | 24.44 341 | 84.77 336 | 51.22 319 | 72.85 246 | 82.90 319 |
|
testpf | | | 70.88 298 | 70.47 292 | 72.08 320 | 88.92 236 | 59.57 324 | 48.62 348 | 93.15 258 | 63.05 314 | 63.07 296 | 79.51 305 | 58.33 255 | 86.63 329 | 66.93 253 | 72.69 247 | 70.05 340 |
|
test1235678 | | | 64.50 309 | 62.19 309 | 71.42 321 | 66.82 340 | 48.00 338 | 89.44 285 | 87.90 313 | 62.82 316 | 49.12 333 | 71.31 333 | 30.14 339 | 82.19 339 | 41.88 333 | 60.32 309 | 84.06 306 |
|
1111 | | | 65.60 308 | 64.33 306 | 69.41 322 | 68.26 336 | 45.11 342 | 87.06 303 | 87.32 317 | 54.99 334 | 51.20 330 | 73.45 324 | 63.57 219 | 85.70 333 | 36.53 337 | 56.59 315 | 77.42 334 |
|
no-one | | | 51.12 317 | 45.81 319 | 67.03 323 | 53.16 349 | 52.22 334 | 75.21 335 | 80.40 342 | 54.89 336 | 28.26 344 | 48.50 343 | 15.54 347 | 82.81 338 | 39.29 335 | 17.06 346 | 66.07 343 |
|
LCM-MVSNet | | | 52.52 316 | 48.24 317 | 65.35 324 | 47.63 351 | 41.45 345 | 72.55 340 | 83.62 336 | 31.75 343 | 37.66 339 | 57.92 339 | 9.19 355 | 76.76 344 | 49.26 324 | 44.60 339 | 77.84 333 |
|
test12356 | | | 58.24 312 | 56.06 314 | 64.77 325 | 60.65 342 | 39.42 348 | 82.78 321 | 84.34 332 | 57.47 331 | 42.65 337 | 69.10 334 | 19.21 344 | 81.18 340 | 38.97 336 | 49.40 331 | 73.69 336 |
|
PMMVS2 | | | 50.90 318 | 46.31 318 | 64.67 326 | 55.53 344 | 46.67 340 | 77.30 333 | 71.02 347 | 40.89 341 | 34.16 342 | 59.32 337 | 9.83 354 | 76.14 346 | 40.09 334 | 28.63 343 | 71.21 338 |
|
N_pmnet | | | 61.30 310 | 60.20 311 | 64.60 327 | 84.32 299 | 17.00 357 | 91.67 272 | 10.98 357 | 61.77 320 | 58.45 319 | 78.55 306 | 49.89 297 | 91.83 303 | 42.27 332 | 63.94 301 | 84.97 300 |
|
DeepMVS_CX | | | | | 64.06 328 | 78.53 321 | 43.26 344 | | 68.11 350 | 69.94 299 | 38.55 338 | 76.14 319 | 18.53 345 | 79.34 341 | 43.72 331 | 41.62 342 | 69.57 341 |
|
testmv | | | 54.58 315 | 51.53 316 | 63.74 329 | 53.58 347 | 40.82 346 | 83.26 319 | 83.92 334 | 54.07 338 | 36.35 340 | 61.26 336 | 14.80 348 | 77.07 342 | 33.00 341 | 43.53 341 | 73.33 337 |
|
FPMVS | | | 55.09 313 | 52.93 315 | 61.57 330 | 55.98 343 | 40.51 347 | 83.11 320 | 83.41 337 | 37.61 342 | 34.95 341 | 71.95 329 | 14.40 349 | 76.95 343 | 29.81 344 | 65.16 298 | 67.25 342 |
|
ANet_high | | | 46.22 319 | 41.28 322 | 61.04 331 | 39.91 354 | 46.25 341 | 70.59 342 | 76.18 346 | 58.87 329 | 23.09 346 | 48.00 344 | 12.58 351 | 66.54 349 | 28.65 345 | 13.62 349 | 70.35 339 |
|
wuykxyi23d | | | 37.75 324 | 31.85 327 | 55.46 332 | 40.00 353 | 38.01 349 | 59.81 345 | 69.47 348 | 25.46 347 | 12.42 352 | 30.55 351 | 2.06 359 | 67.08 348 | 31.81 343 | 15.03 347 | 61.29 344 |
|
Gipuma | | | 45.11 320 | 42.05 320 | 54.30 333 | 80.69 314 | 51.30 336 | 35.80 349 | 83.81 335 | 28.13 345 | 27.94 345 | 34.53 347 | 11.41 353 | 76.70 345 | 21.45 347 | 54.65 325 | 34.90 349 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
PNet_i23d | | | 41.20 322 | 38.13 323 | 50.41 334 | 55.23 345 | 36.24 351 | 73.80 339 | 65.45 352 | 29.75 344 | 21.36 347 | 47.05 345 | 3.43 356 | 63.23 350 | 28.17 346 | 18.92 345 | 51.76 345 |
|
PMVS | | 34.80 23 | 39.19 323 | 35.53 324 | 50.18 335 | 29.72 355 | 30.30 352 | 59.60 346 | 66.20 351 | 26.06 346 | 17.91 349 | 49.53 342 | 3.12 357 | 74.09 347 | 18.19 349 | 49.40 331 | 46.14 346 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
MVE | | 35.65 22 | 33.85 326 | 29.49 329 | 46.92 336 | 41.86 352 | 36.28 350 | 50.45 347 | 56.52 354 | 18.75 350 | 18.28 348 | 37.84 346 | 2.41 358 | 58.41 351 | 18.71 348 | 20.62 344 | 46.06 347 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
.test1245 | | | 54.61 314 | 58.07 312 | 44.24 337 | 68.26 336 | 45.11 342 | 87.06 303 | 87.32 317 | 54.99 334 | 51.20 330 | 73.45 324 | 63.57 219 | 85.70 333 | 36.53 337 | 0.21 353 | 1.91 353 |
|
tmp_tt | | | 41.54 321 | 41.93 321 | 40.38 338 | 20.10 356 | 26.84 353 | 61.93 344 | 59.09 353 | 14.81 351 | 28.51 343 | 80.58 298 | 35.53 329 | 48.33 354 | 63.70 276 | 13.11 350 | 45.96 348 |
|
E-PMN | | | 32.70 327 | 32.39 326 | 33.65 339 | 53.35 348 | 25.70 354 | 74.07 337 | 53.33 355 | 21.08 348 | 17.17 350 | 33.63 349 | 11.85 352 | 54.84 352 | 12.98 350 | 14.04 348 | 20.42 350 |
|
EMVS | | | 31.70 328 | 31.45 328 | 32.48 340 | 50.72 350 | 23.95 355 | 74.78 336 | 52.30 356 | 20.36 349 | 16.08 351 | 31.48 350 | 12.80 350 | 53.60 353 | 11.39 351 | 13.10 351 | 19.88 351 |
|
pcd1.5k->3k | | | 34.11 325 | 35.46 325 | 30.05 341 | 86.70 256 | 0.00 360 | 0.00 351 | 94.74 181 | 0.00 355 | 0.00 356 | 0.00 357 | 58.13 256 | 0.00 358 | 0.00 355 | 79.56 214 | 90.14 216 |
|
wuyk23d | | | 14.10 330 | 13.89 331 | 14.72 342 | 55.23 345 | 22.91 356 | 33.83 350 | 3.56 358 | 4.94 352 | 4.11 353 | 2.28 356 | 2.06 359 | 19.66 355 | 10.23 352 | 8.74 352 | 1.59 355 |
|
test123 | | | 9.07 332 | 11.73 333 | 1.11 343 | 0.50 358 | 0.77 358 | 89.44 285 | 0.20 360 | 0.34 354 | 2.15 355 | 10.72 355 | 0.34 361 | 0.32 356 | 1.79 354 | 0.08 355 | 2.23 352 |
|
testmvs | | | 9.92 331 | 12.94 332 | 0.84 344 | 0.65 357 | 0.29 359 | 93.78 223 | 0.39 359 | 0.42 353 | 2.85 354 | 15.84 354 | 0.17 362 | 0.30 357 | 2.18 353 | 0.21 353 | 1.91 353 |
|
cdsmvs_eth3d_5k | | | 21.43 329 | 28.57 330 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 95.93 127 | 0.00 355 | 0.00 356 | 97.66 50 | 63.57 219 | 0.00 358 | 0.00 355 | 0.00 356 | 0.00 356 |
|
pcd_1.5k_mvsjas | | | 5.92 334 | 7.89 335 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 0.00 361 | 0.00 355 | 0.00 356 | 0.00 357 | 71.04 161 | 0.00 358 | 0.00 355 | 0.00 356 | 0.00 356 |
|
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 | | | 8.11 333 | 10.81 334 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 0.00 361 | 0.00 355 | 0.00 356 | 97.30 70 | 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 | | | | | | | | | | | | | | | | | 97.54 93 |
|
test_part3 | | | | | | | | 98.15 25 | | 84.95 101 | | 98.83 2 | | 99.80 13 | 97.78 2 | | |
|
test_part2 | | | | | | 98.90 7 | 85.14 43 | | | | 96.07 7 | | | | | | |
|
test_part1 | | | | | | | | | 96.77 53 | | | | 89.33 6 | | | 98.95 12 | 99.18 10 |
|
sam_mvs1 | | | | | | | | | | | | | 77.59 86 | | | | 97.54 93 |
|
sam_mvs | | | | | | | | | | | | | 75.35 128 | | | | |
|
MTGPA | | | | | | | | | 96.33 102 | | | | | | | | |
|
test_post1 | | | | | | | | 85.88 313 | | | | 30.24 352 | 73.77 140 | 95.07 258 | 73.89 204 | | |
|
test_post | | | | | | | | | | | | 33.80 348 | 76.17 106 | 95.97 205 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 77.09 314 | 77.78 85 | 95.39 244 | | | |
|
MTMP | | | | | | | | | 68.16 349 | | | | | | | | |
|
gm-plane-assit | | | | | | 92.27 179 | 79.64 162 | | | 84.47 115 | | 95.15 123 | | 97.93 117 | 85.81 103 | | |
|
test9_res | | | | | | | | | | | | | | | 96.00 14 | 99.03 7 | 98.31 41 |
|
TEST9 | | | | | | 98.64 21 | 83.71 68 | 97.82 37 | 96.65 66 | 84.29 121 | 95.16 14 | 98.09 28 | 84.39 21 | 99.36 55 | | | |
|
test_8 | | | | | | 98.63 23 | 83.64 71 | 97.81 39 | 96.63 72 | 84.50 113 | 95.10 16 | 98.11 27 | 84.33 22 | 99.23 61 | | | |
|
agg_prior2 | | | | | | | | | | | | | | | 94.30 27 | 99.00 9 | 98.57 31 |
|
agg_prior | | | | | | 98.59 26 | 83.13 78 | | 96.56 77 | | 94.19 28 | | | 99.16 74 | | | |
|
test_prior4 | | | | | | | 82.34 93 | 97.75 46 | | | | | | | | | |
|
test_prior2 | | | | | | | | 98.37 18 | | 86.08 75 | 94.57 25 | 98.02 33 | 83.14 33 | | 95.05 20 | 98.79 15 | |
|
旧先验2 | | | | | | | | 96.97 104 | | 74.06 278 | 96.10 6 | | | 97.76 129 | 88.38 86 | | |
|
æ–°å‡ ä½•2 | | | | | | | | 96.42 141 | | | | | | | | | |
|
旧先验1 | | | | | | 97.39 65 | 79.58 164 | | 96.54 80 | | | 98.08 31 | 84.00 26 | | | 97.42 57 | 97.62 90 |
|
æ— å…ˆéªŒ | | | | | | | | 96.87 109 | 96.78 52 | 77.39 235 | | | | 99.52 43 | 79.95 149 | | 98.43 35 |
|
原ACMM2 | | | | | | | | 96.84 110 | | | | | | | | | |
|
test222 | | | | | | 96.15 83 | 78.41 204 | 95.87 170 | 96.46 87 | 71.97 291 | 89.66 75 | 97.45 62 | 76.33 104 | | | 98.24 38 | 98.30 42 |
|
testdata2 | | | | | | | | | | | | | | 99.48 48 | 76.45 184 | | |
|
segment_acmp | | | | | | | | | | | | | 82.69 35 | | | | |
|
testdata1 | | | | | | | | 95.57 180 | | 87.44 59 | | | | | | | |
|
plane_prior7 | | | | | | 91.86 196 | 77.55 226 | | | | | | | | | | |
|
plane_prior6 | | | | | | 91.98 191 | 77.92 219 | | | | | | 64.77 214 | | | | |
|
plane_prior5 | | | | | | | | | 94.69 182 | | | | | 97.30 150 | 87.08 96 | 82.82 200 | 90.96 205 |
|
plane_prior4 | | | | | | | | | | | | 94.15 141 | | | | | |
|
plane_prior3 | | | | | | | 77.75 223 | | | 90.17 28 | 81.33 162 | | | | | | |
|
plane_prior2 | | | | | | | | 97.18 78 | | 89.89 30 | | | | | | | |
|
plane_prior1 | | | | | | 91.95 194 | | | | | | | | | | | |
|
plane_prior | | | | | | | 77.96 216 | 97.52 59 | | 90.36 27 | | | | | | 82.96 192 | |
|
n2 | | | | | | | | | 0.00 361 | | | | | | | | |
|
nn | | | | | | | | | 0.00 361 | | | | | | | | |
|
door-mid | | | | | | | | | 79.75 344 | | | | | | | | |
|
test11 | | | | | | | | | 96.50 84 | | | | | | | | |
|
door | | | | | | | | | 80.13 343 | | | | | | | | |
|
HQP5-MVS | | | | | | | 78.48 200 | | | | | | | | | | |
|
HQP-NCC | | | | | | 92.08 186 | | 97.63 51 | | 90.52 24 | 82.30 147 | | | | | | |
|
ACMP_Plane | | | | | | 92.08 186 | | 97.63 51 | | 90.52 24 | 82.30 147 | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 87.67 93 | | |
|
HQP4-MVS | | | | | | | | | | | 82.30 147 | | | 97.32 148 | | | 91.13 203 |
|
HQP3-MVS | | | | | | | | | 94.80 177 | | | | | | | 83.01 190 | |
|
HQP2-MVS | | | | | | | | | | | | | 65.40 209 | | | | |
|
NP-MVS | | | | | | 92.04 190 | 78.22 208 | | | | | 94.56 135 | | | | | |
|
MDTV_nov1_ep13_2view | | | | | | | 81.74 108 | 86.80 306 | | 80.65 185 | 85.65 111 | | 74.26 138 | | 76.52 183 | | 96.98 117 |
|
MDTV_nov1_ep13 | | | | 83.69 174 | | 94.09 144 | 81.01 122 | 86.78 307 | 96.09 117 | 83.81 133 | 84.75 119 | 84.32 275 | 74.44 137 | 96.54 181 | 63.88 274 | 85.07 176 | |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 78.45 224 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 79.05 217 | |
|
Test By Simon | | | | | | | | | | | | | 71.65 154 | | | | |
|