LCM-MVSNet | | | 99.93 1 | 99.92 1 | 99.94 1 | 99.99 1 | 99.97 1 | 99.90 1 | 99.89 2 | 99.98 1 | 99.99 1 | 99.96 1 | 99.77 1 | 100.00 1 | 99.81 3 | 100.00 1 | 99.85 9 |
|
LTVRE_ROB | | 98.40 1 | 99.67 3 | 99.71 2 | 99.56 18 | 99.85 18 | 99.11 42 | 99.90 1 | 99.78 5 | 99.63 12 | 99.78 10 | 99.67 21 | 99.48 6 | 99.81 144 | 99.30 32 | 99.97 23 | 99.77 16 |
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 |
pmmvs6 | | | 99.67 3 | 99.70 3 | 99.60 12 | 99.90 5 | 99.27 16 | 99.53 10 | 99.76 7 | 99.64 10 | 99.84 9 | 99.83 3 | 99.50 5 | 99.87 73 | 99.36 28 | 99.92 49 | 99.64 41 |
|
Anonymous20231211 | | | 99.71 2 | 99.70 3 | 99.74 2 | 99.97 2 | 99.52 2 | 99.74 4 | 99.82 4 | 99.73 6 | 99.91 4 | 99.89 2 | 99.27 9 | 99.94 20 | 99.02 50 | 99.94 33 | 99.75 21 |
|
mvs_tets | | | 99.63 5 | 99.67 5 | 99.49 45 | 99.88 8 | 98.61 73 | 99.34 16 | 99.71 12 | 99.27 46 | 99.90 5 | 99.74 8 | 99.68 3 | 99.97 3 | 99.55 20 | 99.99 11 | 99.88 5 |
|
ANet_high | | | 99.57 9 | 99.67 5 | 99.28 72 | 99.89 7 | 98.09 106 | 99.14 45 | 99.93 1 | 99.82 2 | 99.93 2 | 99.81 4 | 99.17 14 | 99.94 20 | 99.31 31 | 100.00 1 | 99.82 10 |
|
jajsoiax | | | 99.58 8 | 99.61 7 | 99.48 46 | 99.87 12 | 98.61 73 | 99.28 30 | 99.66 19 | 99.09 69 | 99.89 8 | 99.68 19 | 99.53 4 | 99.97 3 | 99.50 22 | 99.99 11 | 99.87 6 |
|
v52 | | | 99.59 6 | 99.60 8 | 99.55 20 | 99.87 12 | 99.00 48 | 99.59 7 | 99.56 49 | 99.56 22 | 99.68 20 | 99.72 11 | 98.57 34 | 99.93 26 | 99.85 1 | 99.99 11 | 99.72 25 |
|
V4 | | | 99.59 6 | 99.60 8 | 99.55 20 | 99.87 12 | 99.00 48 | 99.59 7 | 99.56 49 | 99.56 22 | 99.68 20 | 99.72 11 | 98.57 34 | 99.93 26 | 99.85 1 | 99.99 11 | 99.72 25 |
|
v7n | | | 99.53 10 | 99.57 10 | 99.41 54 | 99.88 8 | 98.54 81 | 99.45 11 | 99.61 30 | 99.66 9 | 99.68 20 | 99.66 22 | 98.44 42 | 99.95 13 | 99.73 8 | 99.96 28 | 99.75 21 |
|
test_djsdf | | | 99.52 11 | 99.51 11 | 99.53 32 | 99.86 16 | 98.74 62 | 99.39 14 | 99.56 49 | 99.11 62 | 99.70 15 | 99.73 10 | 99.00 17 | 99.97 3 | 99.26 33 | 99.98 19 | 99.89 3 |
|
PS-MVSNAJss | | | 99.46 14 | 99.49 12 | 99.35 63 | 99.90 5 | 98.15 102 | 99.20 36 | 99.65 20 | 99.48 25 | 99.92 3 | 99.71 14 | 98.07 61 | 99.96 8 | 99.53 21 | 100.00 1 | 99.93 1 |
|
v748 | | | 99.44 15 | 99.48 13 | 99.33 68 | 99.88 8 | 98.43 88 | 99.42 12 | 99.53 59 | 99.63 12 | 99.69 17 | 99.60 34 | 97.99 69 | 99.91 43 | 99.60 14 | 99.96 28 | 99.66 34 |
|
pm-mvs1 | | | 99.44 15 | 99.48 13 | 99.33 68 | 99.80 22 | 98.63 70 | 99.29 26 | 99.63 25 | 99.30 43 | 99.65 23 | 99.60 34 | 99.16 16 | 99.82 131 | 99.07 47 | 99.83 80 | 99.56 76 |
|
anonymousdsp | | | 99.51 12 | 99.47 15 | 99.62 6 | 99.88 8 | 99.08 47 | 99.34 16 | 99.69 15 | 98.93 84 | 99.65 23 | 99.72 11 | 98.93 20 | 99.95 13 | 99.11 45 | 100.00 1 | 99.82 10 |
|
TransMVSNet (Re) | | | 99.44 15 | 99.47 15 | 99.36 58 | 99.80 22 | 98.58 76 | 99.27 32 | 99.57 43 | 99.39 34 | 99.75 12 | 99.62 28 | 99.17 14 | 99.83 119 | 99.06 48 | 99.62 159 | 99.66 34 |
|
UA-Net | | | 99.47 13 | 99.40 17 | 99.70 3 | 99.49 93 | 99.29 13 | 99.80 3 | 99.72 11 | 99.82 2 | 99.04 119 | 99.81 4 | 98.05 64 | 99.96 8 | 98.85 57 | 99.99 11 | 99.86 8 |
|
v13 | | | 99.24 32 | 99.39 18 | 98.77 142 | 99.63 53 | 96.79 186 | 99.24 34 | 99.65 20 | 99.39 34 | 99.62 27 | 99.70 16 | 97.50 96 | 99.84 104 | 99.78 5 | 100.00 1 | 99.67 32 |
|
TDRefinement | | | 99.42 19 | 99.38 19 | 99.55 20 | 99.76 27 | 99.33 11 | 99.68 5 | 99.71 12 | 99.38 36 | 99.53 38 | 99.61 30 | 98.64 29 | 99.80 156 | 98.24 86 | 99.84 74 | 99.52 98 |
|
v12 | | | 99.21 33 | 99.37 20 | 98.74 150 | 99.60 56 | 96.72 191 | 99.19 40 | 99.65 20 | 99.35 40 | 99.62 27 | 99.69 17 | 97.43 103 | 99.83 119 | 99.76 6 | 100.00 1 | 99.66 34 |
|
Vis-MVSNet | | | 99.34 27 | 99.36 21 | 99.27 75 | 99.73 29 | 98.26 95 | 99.17 42 | 99.78 5 | 99.11 62 | 99.27 83 | 99.48 51 | 98.82 22 | 99.95 13 | 98.94 53 | 99.93 39 | 99.59 59 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
nrg030 | | | 99.40 21 | 99.35 22 | 99.54 25 | 99.58 58 | 99.13 38 | 98.98 63 | 99.48 74 | 99.68 7 | 99.46 51 | 99.26 80 | 98.62 30 | 99.73 221 | 99.17 44 | 99.92 49 | 99.76 19 |
|
DTE-MVSNet | | | 99.43 18 | 99.35 22 | 99.66 4 | 99.71 35 | 99.30 12 | 99.31 21 | 99.51 64 | 99.64 10 | 99.56 34 | 99.46 53 | 98.23 50 | 99.97 3 | 98.78 60 | 99.93 39 | 99.72 25 |
|
V9 | | | 99.18 35 | 99.34 24 | 98.70 151 | 99.58 58 | 96.63 194 | 99.14 45 | 99.64 24 | 99.30 43 | 99.61 29 | 99.68 19 | 97.33 108 | 99.83 119 | 99.75 7 | 100.00 1 | 99.65 38 |
|
PEN-MVS | | | 99.41 20 | 99.34 24 | 99.62 6 | 99.73 29 | 99.14 35 | 99.29 26 | 99.54 58 | 99.62 16 | 99.56 34 | 99.42 60 | 98.16 57 | 99.96 8 | 98.78 60 | 99.93 39 | 99.77 16 |
|
PS-CasMVS | | | 99.40 21 | 99.33 26 | 99.62 6 | 99.71 35 | 99.10 43 | 99.29 26 | 99.53 59 | 99.53 24 | 99.46 51 | 99.41 62 | 98.23 50 | 99.95 13 | 98.89 56 | 99.95 30 | 99.81 12 |
|
MIMVSNet1 | | | 99.38 23 | 99.32 27 | 99.55 20 | 99.86 16 | 99.19 25 | 99.41 13 | 99.59 34 | 99.59 19 | 99.71 14 | 99.57 39 | 97.12 126 | 99.90 47 | 99.21 39 | 99.87 69 | 99.54 87 |
|
Anonymous20240521 | | | 99.36 25 | 99.31 28 | 99.53 32 | 99.80 22 | 98.97 51 | 99.54 9 | 99.48 74 | 99.44 30 | 99.58 33 | 99.55 41 | 97.17 123 | 99.88 63 | 99.34 29 | 99.91 54 | 99.74 24 |
|
v11 | | | 99.12 41 | 99.31 28 | 98.53 179 | 99.59 57 | 96.11 214 | 99.08 50 | 99.65 20 | 99.15 57 | 99.60 30 | 99.69 17 | 97.26 116 | 99.83 119 | 99.81 3 | 100.00 1 | 99.66 34 |
|
OurMVSNet-221017-0 | | | 99.37 24 | 99.31 28 | 99.53 32 | 99.91 4 | 98.98 50 | 99.63 6 | 99.58 36 | 99.44 30 | 99.78 10 | 99.76 6 | 96.39 174 | 99.92 34 | 99.44 26 | 99.92 49 | 99.68 31 |
|
wuykxyi23d | | | 99.36 25 | 99.31 28 | 99.50 43 | 99.81 21 | 98.67 69 | 98.08 135 | 99.75 8 | 98.03 127 | 99.90 5 | 99.60 34 | 99.18 12 | 99.94 20 | 99.46 25 | 99.98 19 | 99.89 3 |
|
V14 | | | 99.14 38 | 99.30 32 | 98.66 154 | 99.56 70 | 96.53 195 | 99.08 50 | 99.63 25 | 99.24 47 | 99.60 30 | 99.66 22 | 97.23 120 | 99.82 131 | 99.73 8 | 100.00 1 | 99.65 38 |
|
VPA-MVSNet | | | 99.30 29 | 99.30 32 | 99.28 72 | 99.49 93 | 98.36 93 | 99.00 60 | 99.45 86 | 99.63 12 | 99.52 40 | 99.44 58 | 98.25 48 | 99.88 63 | 99.09 46 | 99.84 74 | 99.62 46 |
|
v15 | | | 99.11 42 | 99.27 34 | 98.62 160 | 99.52 82 | 96.43 199 | 99.01 56 | 99.63 25 | 99.18 56 | 99.59 32 | 99.64 26 | 97.13 125 | 99.81 144 | 99.71 10 | 100.00 1 | 99.64 41 |
|
FC-MVSNet-test | | | 99.27 30 | 99.25 35 | 99.34 66 | 99.77 26 | 98.37 92 | 99.30 25 | 99.57 43 | 99.61 18 | 99.40 61 | 99.50 47 | 97.12 126 | 99.85 89 | 99.02 50 | 99.94 33 | 99.80 13 |
|
ACMH | | 96.65 7 | 99.25 31 | 99.24 36 | 99.26 77 | 99.72 34 | 98.38 91 | 99.07 53 | 99.55 54 | 98.30 116 | 99.65 23 | 99.45 57 | 99.22 10 | 99.76 201 | 98.44 77 | 99.77 106 | 99.64 41 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
v17 | | | 99.07 44 | 99.22 37 | 98.61 163 | 99.50 87 | 96.42 200 | 99.01 56 | 99.60 32 | 99.15 57 | 99.48 47 | 99.61 30 | 97.05 129 | 99.81 144 | 99.64 12 | 99.98 19 | 99.61 50 |
|
v16 | | | 99.07 44 | 99.22 37 | 98.61 163 | 99.50 87 | 96.42 200 | 99.01 56 | 99.60 32 | 99.15 57 | 99.46 51 | 99.61 30 | 97.04 130 | 99.81 144 | 99.64 12 | 99.97 23 | 99.61 50 |
|
WR-MVS_H | | | 99.33 28 | 99.22 37 | 99.65 5 | 99.71 35 | 99.24 20 | 99.32 18 | 99.55 54 | 99.46 28 | 99.50 45 | 99.34 71 | 97.30 110 | 99.93 26 | 98.90 54 | 99.93 39 | 99.77 16 |
|
v18 | | | 99.02 47 | 99.17 40 | 98.57 170 | 99.45 107 | 96.31 206 | 98.94 65 | 99.58 36 | 99.06 71 | 99.43 56 | 99.58 38 | 96.91 139 | 99.80 156 | 99.60 14 | 99.97 23 | 99.59 59 |
|
FMVSNet1 | | | 99.17 36 | 99.17 40 | 99.17 83 | 99.55 74 | 98.24 96 | 99.20 36 | 99.44 89 | 99.21 48 | 99.43 56 | 99.55 41 | 97.82 79 | 99.86 78 | 98.42 79 | 99.89 64 | 99.41 146 |
|
v8 | | | 99.01 48 | 99.16 42 | 98.57 170 | 99.47 100 | 96.31 206 | 98.90 68 | 99.47 81 | 99.03 73 | 99.52 40 | 99.57 39 | 96.93 138 | 99.81 144 | 99.60 14 | 99.98 19 | 99.60 53 |
|
Gipuma | | | 99.03 46 | 99.16 42 | 98.64 156 | 99.94 3 | 98.51 83 | 99.32 18 | 99.75 8 | 99.58 21 | 98.60 176 | 99.62 28 | 98.22 52 | 99.51 302 | 97.70 113 | 99.73 120 | 97.89 294 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
XXY-MVS | | | 99.14 38 | 99.15 44 | 99.10 94 | 99.76 27 | 97.74 145 | 98.85 73 | 99.62 28 | 98.48 107 | 99.37 65 | 99.49 50 | 98.75 25 | 99.86 78 | 98.20 89 | 99.80 94 | 99.71 28 |
|
v10 | | | 98.97 55 | 99.11 45 | 98.55 175 | 99.44 110 | 96.21 212 | 98.90 68 | 99.55 54 | 98.73 94 | 99.48 47 | 99.60 34 | 96.63 160 | 99.83 119 | 99.70 11 | 99.99 11 | 99.61 50 |
|
FIs | | | 99.14 38 | 99.09 46 | 99.29 71 | 99.70 41 | 98.28 94 | 99.13 47 | 99.52 63 | 99.48 25 | 99.24 91 | 99.41 62 | 96.79 151 | 99.82 131 | 98.69 66 | 99.88 65 | 99.76 19 |
|
CP-MVSNet | | | 99.21 33 | 99.09 46 | 99.56 18 | 99.65 48 | 98.96 55 | 99.13 47 | 99.34 122 | 99.42 32 | 99.33 73 | 99.26 80 | 97.01 134 | 99.94 20 | 98.74 64 | 99.93 39 | 99.79 14 |
|
TranMVSNet+NR-MVSNet | | | 99.17 36 | 99.07 48 | 99.46 51 | 99.37 121 | 98.87 57 | 98.39 115 | 99.42 97 | 99.42 32 | 99.36 67 | 99.06 119 | 98.38 44 | 99.95 13 | 98.34 82 | 99.90 58 | 99.57 71 |
|
EG-PatchMatch MVS | | | 98.99 50 | 99.01 49 | 98.94 119 | 99.50 87 | 97.47 158 | 98.04 142 | 99.59 34 | 98.15 126 | 99.40 61 | 99.36 68 | 98.58 33 | 99.76 201 | 98.78 60 | 99.68 144 | 99.59 59 |
|
ACMH+ | | 96.62 9 | 99.08 43 | 99.00 50 | 99.33 68 | 99.71 35 | 98.83 58 | 98.60 84 | 99.58 36 | 99.11 62 | 99.53 38 | 99.18 93 | 98.81 23 | 99.67 248 | 96.71 165 | 99.77 106 | 99.50 105 |
|
testing_2 | | | 98.93 58 | 98.99 51 | 98.76 144 | 99.57 63 | 97.03 178 | 97.85 167 | 99.13 188 | 98.46 108 | 99.44 55 | 99.44 58 | 98.22 52 | 99.74 216 | 98.85 57 | 99.94 33 | 99.51 100 |
|
DeepC-MVS | | 97.60 4 | 98.97 55 | 98.93 52 | 99.10 94 | 99.35 126 | 97.98 120 | 98.01 151 | 99.46 83 | 97.56 163 | 99.54 36 | 99.50 47 | 98.97 18 | 99.84 104 | 98.06 94 | 99.92 49 | 99.49 112 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
tfpnnormal | | | 98.90 61 | 98.90 53 | 98.91 123 | 99.67 45 | 97.82 137 | 99.00 60 | 99.44 89 | 99.45 29 | 99.51 44 | 99.24 83 | 98.20 55 | 99.86 78 | 95.92 208 | 99.69 139 | 99.04 226 |
|
Baseline_NR-MVSNet | | | 98.98 54 | 98.86 54 | 99.36 58 | 99.82 20 | 98.55 78 | 97.47 208 | 99.57 43 | 99.37 37 | 99.21 96 | 99.61 30 | 96.76 154 | 99.83 119 | 98.06 94 | 99.83 80 | 99.71 28 |
|
COLMAP_ROB | | 96.50 10 | 98.99 50 | 98.85 55 | 99.41 54 | 99.58 58 | 99.10 43 | 98.74 76 | 99.56 49 | 99.09 69 | 99.33 73 | 99.19 91 | 98.40 43 | 99.72 230 | 95.98 206 | 99.76 115 | 99.42 144 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
VPNet | | | 98.87 63 | 98.83 56 | 99.01 111 | 99.70 41 | 97.62 153 | 98.43 112 | 99.35 118 | 99.47 27 | 99.28 81 | 99.05 124 | 96.72 156 | 99.82 131 | 98.09 92 | 99.36 208 | 99.59 59 |
|
NR-MVSNet | | | 98.95 57 | 98.82 57 | 99.36 58 | 99.16 168 | 98.72 67 | 99.22 35 | 99.20 165 | 99.10 66 | 99.72 13 | 98.76 179 | 96.38 176 | 99.86 78 | 98.00 99 | 99.82 83 | 99.50 105 |
|
HPM-MVS_fast | | | 99.01 48 | 98.82 57 | 99.57 16 | 99.71 35 | 99.35 9 | 99.00 60 | 99.50 65 | 97.33 184 | 98.94 137 | 98.86 161 | 98.75 25 | 99.82 131 | 97.53 120 | 99.71 129 | 99.56 76 |
|
DP-MVS | | | 98.93 58 | 98.81 59 | 99.28 72 | 99.21 151 | 98.45 87 | 98.46 110 | 99.33 127 | 99.63 12 | 99.48 47 | 99.15 103 | 97.23 120 | 99.75 207 | 97.17 135 | 99.66 155 | 99.63 45 |
|
APDe-MVS | | | 98.99 50 | 98.79 60 | 99.60 12 | 99.21 151 | 99.15 34 | 98.87 70 | 99.48 74 | 97.57 161 | 99.35 69 | 99.24 83 | 97.83 76 | 99.89 56 | 97.88 103 | 99.70 132 | 99.75 21 |
|
V42 | | | 98.78 73 | 98.78 61 | 98.76 144 | 99.44 110 | 97.04 177 | 98.27 119 | 99.19 171 | 97.87 143 | 99.25 90 | 99.16 99 | 96.84 146 | 99.78 186 | 99.21 39 | 99.84 74 | 99.46 130 |
|
abl_6 | | | 98.99 50 | 98.78 61 | 99.61 9 | 99.45 107 | 99.46 4 | 98.60 84 | 99.50 65 | 98.59 100 | 99.24 91 | 99.04 126 | 98.54 37 | 99.89 56 | 96.45 185 | 99.62 159 | 99.50 105 |
|
test20.03 | | | 98.78 73 | 98.77 63 | 98.78 140 | 99.46 104 | 97.20 170 | 97.78 171 | 99.24 158 | 99.04 72 | 99.41 59 | 98.90 152 | 97.65 85 | 99.76 201 | 97.70 113 | 99.79 98 | 99.39 153 |
|
v1neww | | | 98.70 83 | 98.76 64 | 98.52 180 | 99.47 100 | 96.30 208 | 98.03 143 | 99.18 175 | 97.92 131 | 99.26 88 | 99.08 113 | 96.91 139 | 99.78 186 | 99.19 41 | 99.82 83 | 99.47 126 |
|
v7new | | | 98.70 83 | 98.76 64 | 98.52 180 | 99.47 100 | 96.30 208 | 98.03 143 | 99.18 175 | 97.92 131 | 99.26 88 | 99.08 113 | 96.91 139 | 99.78 186 | 99.19 41 | 99.82 83 | 99.47 126 |
|
v6 | | | 98.70 83 | 98.76 64 | 98.52 180 | 99.47 100 | 96.30 208 | 98.03 143 | 99.18 175 | 97.92 131 | 99.27 83 | 99.08 113 | 96.91 139 | 99.78 186 | 99.19 41 | 99.82 83 | 99.48 118 |
|
new-patchmatchnet | | | 98.35 136 | 98.74 67 | 97.18 261 | 99.24 139 | 92.23 301 | 96.42 270 | 99.48 74 | 98.30 116 | 99.69 17 | 99.53 45 | 97.44 102 | 99.82 131 | 98.84 59 | 99.77 106 | 99.49 112 |
|
v7 | | | 98.67 93 | 98.73 68 | 98.50 185 | 99.43 114 | 96.21 212 | 98.00 152 | 99.31 132 | 97.58 159 | 99.17 102 | 99.18 93 | 96.63 160 | 99.80 156 | 99.42 27 | 99.88 65 | 99.48 118 |
|
3Dnovator | | 98.27 2 | 98.81 69 | 98.73 68 | 99.05 104 | 98.76 244 | 97.81 139 | 99.25 33 | 99.30 139 | 98.57 104 | 98.55 182 | 99.33 73 | 97.95 73 | 99.90 47 | 97.16 136 | 99.67 150 | 99.44 136 |
|
ACMM | | 96.08 12 | 98.91 60 | 98.73 68 | 99.48 46 | 99.55 74 | 99.14 35 | 98.07 137 | 99.37 108 | 97.62 155 | 99.04 119 | 98.96 143 | 98.84 21 | 99.79 176 | 97.43 126 | 99.65 156 | 99.49 112 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
PM-MVS | | | 98.82 67 | 98.72 71 | 99.12 91 | 99.64 51 | 98.54 81 | 97.98 154 | 99.68 16 | 97.62 155 | 99.34 72 | 99.18 93 | 97.54 94 | 99.77 196 | 97.79 106 | 99.74 117 | 99.04 226 |
|
EI-MVSNet-UG-set | | | 98.69 88 | 98.71 72 | 98.62 160 | 99.10 176 | 96.37 204 | 97.23 220 | 98.87 232 | 99.20 51 | 99.19 98 | 98.99 135 | 97.30 110 | 99.85 89 | 98.77 63 | 99.79 98 | 99.65 38 |
|
UniMVSNet (Re) | | | 98.87 63 | 98.71 72 | 99.35 63 | 99.24 139 | 98.73 65 | 97.73 178 | 99.38 104 | 98.93 84 | 99.12 105 | 98.73 181 | 96.77 152 | 99.86 78 | 98.63 68 | 99.80 94 | 99.46 130 |
|
test_0402 | | | 98.76 75 | 98.71 72 | 98.93 120 | 99.56 70 | 98.14 104 | 98.45 111 | 99.34 122 | 99.28 45 | 98.95 133 | 98.91 149 | 98.34 46 | 99.79 176 | 95.63 223 | 99.91 54 | 98.86 248 |
|
v1141 | | | 98.63 99 | 98.70 75 | 98.41 194 | 99.39 118 | 95.96 221 | 97.64 187 | 99.21 161 | 97.92 131 | 99.35 69 | 99.08 113 | 96.61 163 | 99.78 186 | 99.25 35 | 99.90 58 | 99.50 105 |
|
EI-MVSNet-Vis-set | | | 98.68 91 | 98.70 75 | 98.63 158 | 99.09 179 | 96.40 202 | 97.23 220 | 98.86 236 | 99.20 51 | 99.18 101 | 98.97 140 | 97.29 112 | 99.85 89 | 98.72 65 | 99.78 102 | 99.64 41 |
|
divwei89l23v2f112 | | | 98.63 99 | 98.70 75 | 98.41 194 | 99.39 118 | 95.96 221 | 97.64 187 | 99.21 161 | 97.92 131 | 99.35 69 | 99.08 113 | 96.61 163 | 99.78 186 | 99.25 35 | 99.90 58 | 99.50 105 |
|
v1 | | | 98.63 99 | 98.70 75 | 98.41 194 | 99.39 118 | 95.96 221 | 97.64 187 | 99.20 165 | 97.92 131 | 99.36 67 | 99.07 118 | 96.63 160 | 99.78 186 | 99.25 35 | 99.90 58 | 99.50 105 |
|
IterMVS-LS | | | 98.55 114 | 98.70 75 | 98.09 218 | 99.48 98 | 94.73 251 | 97.22 223 | 99.39 101 | 98.97 79 | 99.38 63 | 99.31 75 | 96.00 188 | 99.93 26 | 98.58 69 | 99.97 23 | 99.60 53 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
Regformer-4 | | | 98.73 79 | 98.68 80 | 98.89 126 | 99.02 198 | 97.22 169 | 97.17 228 | 99.06 197 | 99.21 48 | 99.17 102 | 98.85 163 | 97.45 101 | 99.86 78 | 98.48 76 | 99.70 132 | 99.60 53 |
|
SD-MVS | | | 98.40 133 | 98.68 80 | 97.54 249 | 98.96 207 | 97.99 116 | 97.88 163 | 99.36 112 | 98.20 122 | 99.63 26 | 99.04 126 | 98.76 24 | 95.33 357 | 96.56 177 | 99.74 117 | 99.31 182 |
|
UniMVSNet_NR-MVSNet | | | 98.86 65 | 98.68 80 | 99.40 56 | 99.17 166 | 98.74 62 | 97.68 182 | 99.40 99 | 99.14 60 | 99.06 111 | 98.59 207 | 96.71 157 | 99.93 26 | 98.57 71 | 99.77 106 | 99.53 92 |
|
v1192 | | | 98.60 106 | 98.66 83 | 98.41 194 | 99.27 135 | 95.88 225 | 97.52 203 | 99.36 112 | 97.41 178 | 99.33 73 | 99.20 90 | 96.37 177 | 99.82 131 | 99.57 18 | 99.92 49 | 99.55 84 |
|
v1144 | | | 98.60 106 | 98.66 83 | 98.41 194 | 99.36 122 | 95.90 224 | 97.58 197 | 99.34 122 | 97.51 166 | 99.27 83 | 99.15 103 | 96.34 178 | 99.80 156 | 99.47 24 | 99.93 39 | 99.51 100 |
|
MTAPA | | | 98.88 62 | 98.64 85 | 99.61 9 | 99.67 45 | 99.36 7 | 98.43 112 | 99.20 165 | 98.83 88 | 98.89 142 | 98.90 152 | 96.98 136 | 99.92 34 | 97.16 136 | 99.70 132 | 99.56 76 |
|
DU-MVS | | | 98.82 67 | 98.63 86 | 99.39 57 | 99.16 168 | 98.74 62 | 97.54 202 | 99.25 154 | 98.84 87 | 99.06 111 | 98.76 179 | 96.76 154 | 99.93 26 | 98.57 71 | 99.77 106 | 99.50 105 |
|
v1240 | | | 98.55 114 | 98.62 87 | 98.32 204 | 99.22 145 | 95.58 233 | 97.51 205 | 99.45 86 | 97.16 201 | 99.45 54 | 99.24 83 | 96.12 183 | 99.85 89 | 99.60 14 | 99.88 65 | 99.55 84 |
|
v2v482 | | | 98.56 110 | 98.62 87 | 98.37 201 | 99.42 115 | 95.81 228 | 97.58 197 | 99.16 184 | 97.90 139 | 99.28 81 | 99.01 132 | 95.98 192 | 99.79 176 | 99.33 30 | 99.90 58 | 99.51 100 |
|
SixPastTwentyTwo | | | 98.75 76 | 98.62 87 | 99.16 86 | 99.83 19 | 97.96 123 | 99.28 30 | 98.20 276 | 99.37 37 | 99.70 15 | 99.65 25 | 92.65 267 | 99.93 26 | 99.04 49 | 99.84 74 | 99.60 53 |
|
Regformer-3 | | | 98.61 105 | 98.61 90 | 98.63 158 | 99.02 198 | 96.53 195 | 97.17 228 | 98.84 238 | 99.13 61 | 99.10 108 | 98.85 163 | 97.24 118 | 99.79 176 | 98.41 80 | 99.70 132 | 99.57 71 |
|
APD-MVS_3200maxsize | | | 98.84 66 | 98.61 90 | 99.53 32 | 99.19 161 | 99.27 16 | 98.49 98 | 99.33 127 | 98.64 96 | 99.03 122 | 98.98 138 | 97.89 74 | 99.85 89 | 96.54 179 | 99.42 203 | 99.46 130 |
|
v1921920 | | | 98.54 117 | 98.60 92 | 98.38 200 | 99.20 160 | 95.76 229 | 97.56 199 | 99.36 112 | 97.23 197 | 99.38 63 | 99.17 98 | 96.02 186 | 99.84 104 | 99.57 18 | 99.90 58 | 99.54 87 |
|
v148 | | | 98.45 128 | 98.60 92 | 98.00 227 | 99.44 110 | 94.98 247 | 97.44 209 | 99.06 197 | 98.30 116 | 99.32 78 | 98.97 140 | 96.65 159 | 99.62 266 | 98.37 81 | 99.85 72 | 99.39 153 |
|
v144192 | | | 98.54 117 | 98.57 94 | 98.45 191 | 99.21 151 | 95.98 219 | 97.63 190 | 99.36 112 | 97.15 203 | 99.32 78 | 99.18 93 | 95.84 200 | 99.84 104 | 99.50 22 | 99.91 54 | 99.54 87 |
|
SteuartSystems-ACMMP | | | 98.79 70 | 98.54 95 | 99.54 25 | 99.73 29 | 99.16 29 | 98.23 121 | 99.31 132 | 97.92 131 | 98.90 140 | 98.90 152 | 98.00 67 | 99.88 63 | 96.15 200 | 99.72 125 | 99.58 66 |
Skip Steuart: Steuart Systems R&D Blog. |
HPM-MVS | | | 98.79 70 | 98.53 96 | 99.59 15 | 99.65 48 | 99.29 13 | 99.16 43 | 99.43 94 | 96.74 215 | 98.61 174 | 98.38 227 | 98.62 30 | 99.87 73 | 96.47 183 | 99.67 150 | 99.59 59 |
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
zzz-MVS | | | 98.79 70 | 98.52 97 | 99.61 9 | 99.67 45 | 99.36 7 | 97.33 213 | 99.20 165 | 98.83 88 | 98.89 142 | 98.90 152 | 96.98 136 | 99.92 34 | 97.16 136 | 99.70 132 | 99.56 76 |
|
EI-MVSNet | | | 98.40 133 | 98.51 98 | 98.04 225 | 99.10 176 | 94.73 251 | 97.20 224 | 98.87 232 | 98.97 79 | 99.06 111 | 99.02 130 | 96.00 188 | 99.80 156 | 98.58 69 | 99.82 83 | 99.60 53 |
|
3Dnovator+ | | 97.89 3 | 98.69 88 | 98.51 98 | 99.24 79 | 98.81 240 | 98.40 89 | 99.02 55 | 99.19 171 | 98.99 76 | 98.07 205 | 99.28 76 | 97.11 128 | 99.84 104 | 96.84 154 | 99.32 215 | 99.47 126 |
|
EU-MVSNet | | | 97.66 189 | 98.50 100 | 95.13 317 | 99.63 53 | 85.84 339 | 98.35 116 | 98.21 275 | 98.23 121 | 99.54 36 | 99.46 53 | 95.02 220 | 99.68 242 | 98.24 86 | 99.87 69 | 99.87 6 |
|
CSCG | | | 98.68 91 | 98.50 100 | 99.20 82 | 99.45 107 | 98.63 70 | 98.56 88 | 99.57 43 | 97.87 143 | 98.85 148 | 98.04 255 | 97.66 84 | 99.84 104 | 96.72 162 | 99.81 90 | 99.13 219 |
|
ACMMP | | | 98.75 76 | 98.50 100 | 99.52 39 | 99.56 70 | 99.16 29 | 98.87 70 | 99.37 108 | 97.16 201 | 98.82 154 | 99.01 132 | 97.71 83 | 99.87 73 | 96.29 192 | 99.69 139 | 99.54 87 |
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 |
TSAR-MVS + MP. | | | 98.63 99 | 98.49 103 | 99.06 103 | 99.64 51 | 97.90 129 | 98.51 96 | 98.94 220 | 96.96 206 | 99.24 91 | 98.89 157 | 97.83 76 | 99.81 144 | 96.88 151 | 99.49 199 | 99.48 118 |
|
ACMMP_Plus | | | 98.75 76 | 98.48 104 | 99.57 16 | 99.58 58 | 99.29 13 | 97.82 170 | 99.25 154 | 96.94 207 | 98.78 157 | 99.12 107 | 98.02 65 | 99.84 104 | 97.13 140 | 99.67 150 | 99.59 59 |
|
LCM-MVSNet-Re | | | 98.64 97 | 98.48 104 | 99.11 92 | 98.85 230 | 98.51 83 | 98.49 98 | 99.83 3 | 98.37 109 | 99.69 17 | 99.46 53 | 98.21 54 | 99.92 34 | 94.13 257 | 99.30 218 | 98.91 243 |
|
testmv | | | 98.51 121 | 98.47 106 | 98.61 163 | 99.24 139 | 96.53 195 | 96.66 257 | 99.73 10 | 98.56 106 | 99.50 45 | 99.23 87 | 97.24 118 | 99.87 73 | 96.16 199 | 99.93 39 | 99.44 136 |
|
GBi-Net | | | 98.65 95 | 98.47 106 | 99.17 83 | 98.90 220 | 98.24 96 | 99.20 36 | 99.44 89 | 98.59 100 | 98.95 133 | 99.55 41 | 94.14 244 | 99.86 78 | 97.77 108 | 99.69 139 | 99.41 146 |
|
test1 | | | 98.65 95 | 98.47 106 | 99.17 83 | 98.90 220 | 98.24 96 | 99.20 36 | 99.44 89 | 98.59 100 | 98.95 133 | 99.55 41 | 94.14 244 | 99.86 78 | 97.77 108 | 99.69 139 | 99.41 146 |
|
Regformer-2 | | | 98.60 106 | 98.46 109 | 99.02 110 | 98.85 230 | 97.71 147 | 96.91 242 | 99.09 194 | 98.98 78 | 99.01 123 | 98.64 197 | 97.37 107 | 99.84 104 | 97.75 112 | 99.57 176 | 99.52 98 |
|
LPG-MVS_test | | | 98.71 81 | 98.46 109 | 99.47 49 | 99.57 63 | 98.97 51 | 98.23 121 | 99.48 74 | 96.60 224 | 99.10 108 | 99.06 119 | 98.71 27 | 99.83 119 | 95.58 226 | 99.78 102 | 99.62 46 |
|
XVS | | | 98.72 80 | 98.45 111 | 99.53 32 | 99.46 104 | 99.21 22 | 98.65 79 | 99.34 122 | 98.62 98 | 97.54 250 | 98.63 201 | 97.50 96 | 99.83 119 | 96.79 156 | 99.53 190 | 99.56 76 |
|
UGNet | | | 98.53 119 | 98.45 111 | 98.79 137 | 97.94 309 | 96.96 181 | 99.08 50 | 98.54 264 | 99.10 66 | 96.82 289 | 99.47 52 | 96.55 166 | 99.84 104 | 98.56 74 | 99.94 33 | 99.55 84 |
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 |
HFP-MVS | | | 98.71 81 | 98.44 113 | 99.51 41 | 99.49 93 | 99.16 29 | 98.52 92 | 99.31 132 | 97.47 170 | 98.58 179 | 98.50 220 | 97.97 71 | 99.85 89 | 96.57 174 | 99.59 166 | 99.53 92 |
|
Regformer-1 | | | 98.55 114 | 98.44 113 | 98.87 128 | 98.85 230 | 97.29 164 | 96.91 242 | 98.99 218 | 98.97 79 | 98.99 126 | 98.64 197 | 97.26 116 | 99.81 144 | 97.79 106 | 99.57 176 | 99.51 100 |
|
MVSFormer | | | 98.26 147 | 98.43 115 | 97.77 234 | 98.88 225 | 93.89 279 | 99.39 14 | 99.56 49 | 99.11 62 | 98.16 199 | 98.13 244 | 93.81 251 | 99.97 3 | 99.26 33 | 99.57 176 | 99.43 141 |
|
ACMMPR | | | 98.70 83 | 98.42 116 | 99.54 25 | 99.52 82 | 99.14 35 | 98.52 92 | 99.31 132 | 97.47 170 | 98.56 181 | 98.54 215 | 97.75 81 | 99.88 63 | 96.57 174 | 99.59 166 | 99.58 66 |
|
CP-MVS | | | 98.70 83 | 98.42 116 | 99.52 39 | 99.36 122 | 99.12 40 | 98.72 78 | 99.36 112 | 97.54 165 | 98.30 196 | 98.40 226 | 97.86 75 | 99.89 56 | 96.53 180 | 99.72 125 | 99.56 76 |
|
region2R | | | 98.69 88 | 98.40 118 | 99.54 25 | 99.53 80 | 99.17 27 | 98.52 92 | 99.31 132 | 97.46 175 | 98.44 188 | 98.51 217 | 97.83 76 | 99.88 63 | 96.46 184 | 99.58 172 | 99.58 66 |
|
FMVSNet2 | | | 98.49 123 | 98.40 118 | 98.75 146 | 98.90 220 | 97.14 176 | 98.61 83 | 99.13 188 | 98.59 100 | 99.19 98 | 99.28 76 | 94.14 244 | 99.82 131 | 97.97 100 | 99.80 94 | 99.29 188 |
|
VDD-MVS | | | 98.56 110 | 98.39 120 | 99.07 98 | 99.13 174 | 98.07 111 | 98.59 86 | 97.01 301 | 99.59 19 | 99.11 106 | 99.27 78 | 94.82 227 | 99.79 176 | 98.34 82 | 99.63 158 | 99.34 172 |
|
testgi | | | 98.32 139 | 98.39 120 | 98.13 216 | 99.57 63 | 95.54 234 | 97.78 171 | 99.49 71 | 97.37 181 | 99.19 98 | 97.65 273 | 98.96 19 | 99.49 304 | 96.50 182 | 98.99 258 | 99.34 172 |
|
LS3D | | | 98.63 99 | 98.38 122 | 99.36 58 | 97.25 334 | 99.38 6 | 99.12 49 | 99.32 130 | 99.21 48 | 98.44 188 | 98.88 158 | 97.31 109 | 99.80 156 | 96.58 172 | 99.34 212 | 98.92 241 |
|
PGM-MVS | | | 98.66 94 | 98.37 123 | 99.55 20 | 99.53 80 | 99.18 26 | 98.23 121 | 99.49 71 | 97.01 205 | 98.69 164 | 98.88 158 | 98.00 67 | 99.89 56 | 95.87 212 | 99.59 166 | 99.58 66 |
|
MVS_Test | | | 98.18 155 | 98.36 124 | 97.67 239 | 98.48 281 | 94.73 251 | 98.18 125 | 99.02 210 | 97.69 151 | 98.04 208 | 99.11 108 | 97.22 122 | 99.56 287 | 98.57 71 | 98.90 264 | 98.71 264 |
|
ab-mvs | | | 98.41 131 | 98.36 124 | 98.59 167 | 99.19 161 | 97.23 167 | 99.32 18 | 98.81 244 | 97.66 152 | 98.62 172 | 99.40 65 | 96.82 148 | 99.80 156 | 95.88 209 | 99.51 193 | 98.75 262 |
|
RPSCF | | | 98.62 104 | 98.36 124 | 99.42 52 | 99.65 48 | 99.42 5 | 98.55 90 | 99.57 43 | 97.72 150 | 98.90 140 | 99.26 80 | 96.12 183 | 99.52 297 | 95.72 219 | 99.71 129 | 99.32 178 |
|
pmmvs-eth3d | | | 98.47 125 | 98.34 127 | 98.86 130 | 99.30 133 | 97.76 142 | 97.16 230 | 99.28 143 | 95.54 260 | 99.42 58 | 99.19 91 | 97.27 113 | 99.63 264 | 97.89 101 | 99.97 23 | 99.20 205 |
|
mPP-MVS | | | 98.64 97 | 98.34 127 | 99.54 25 | 99.54 78 | 99.17 27 | 98.63 81 | 99.24 158 | 97.47 170 | 98.09 204 | 98.68 188 | 97.62 89 | 99.89 56 | 96.22 194 | 99.62 159 | 99.57 71 |
|
XVG-OURS | | | 98.53 119 | 98.34 127 | 99.11 92 | 99.50 87 | 98.82 60 | 95.97 287 | 99.50 65 | 97.30 188 | 99.05 116 | 98.98 138 | 99.35 7 | 99.32 326 | 95.72 219 | 99.68 144 | 99.18 211 |
|
XVG-ACMP-BASELINE | | | 98.56 110 | 98.34 127 | 99.22 81 | 99.54 78 | 98.59 75 | 97.71 179 | 99.46 83 | 97.25 192 | 98.98 128 | 98.99 135 | 97.54 94 | 99.84 104 | 95.88 209 | 99.74 117 | 99.23 199 |
|
OPM-MVS | | | 98.56 110 | 98.32 131 | 99.25 78 | 99.41 116 | 98.73 65 | 97.13 232 | 99.18 175 | 97.10 204 | 98.75 161 | 98.92 148 | 98.18 56 | 99.65 261 | 96.68 167 | 99.56 183 | 99.37 160 |
|
VNet | | | 98.42 130 | 98.30 132 | 98.79 137 | 98.79 243 | 97.29 164 | 98.23 121 | 98.66 259 | 99.31 42 | 98.85 148 | 98.80 172 | 94.80 230 | 99.78 186 | 98.13 91 | 99.13 245 | 99.31 182 |
|
XVG-OURS-SEG-HR | | | 98.49 123 | 98.28 133 | 99.14 89 | 99.49 93 | 98.83 58 | 96.54 263 | 99.48 74 | 97.32 186 | 99.11 106 | 98.61 205 | 99.33 8 | 99.30 329 | 96.23 193 | 98.38 287 | 99.28 189 |
|
canonicalmvs | | | 98.34 137 | 98.26 134 | 98.58 168 | 98.46 283 | 97.82 137 | 98.96 64 | 99.46 83 | 99.19 55 | 97.46 256 | 95.46 330 | 98.59 32 | 99.46 310 | 98.08 93 | 98.71 272 | 98.46 276 |
|
MP-MVS-pluss | | | 98.57 109 | 98.23 135 | 99.60 12 | 99.69 43 | 99.35 9 | 97.16 230 | 99.38 104 | 94.87 273 | 98.97 130 | 98.99 135 | 98.01 66 | 99.88 63 | 97.29 131 | 99.70 132 | 99.58 66 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
Anonymous20231206 | | | 98.21 152 | 98.21 136 | 98.20 213 | 99.51 85 | 95.43 239 | 98.13 129 | 99.32 130 | 96.16 241 | 98.93 138 | 98.82 170 | 96.00 188 | 99.83 119 | 97.32 130 | 99.73 120 | 99.36 166 |
|
AllTest | | | 98.44 129 | 98.20 137 | 99.16 86 | 99.50 87 | 98.55 78 | 98.25 120 | 99.58 36 | 96.80 213 | 98.88 145 | 99.06 119 | 97.65 85 | 99.57 284 | 94.45 246 | 99.61 163 | 99.37 160 |
|
DELS-MVS | | | 98.27 145 | 98.20 137 | 98.48 187 | 98.86 227 | 96.70 192 | 95.60 309 | 99.20 165 | 97.73 149 | 98.45 187 | 98.71 183 | 97.50 96 | 99.82 131 | 98.21 88 | 99.59 166 | 98.93 240 |
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 |
WR-MVS | | | 98.40 133 | 98.19 139 | 99.03 107 | 99.00 201 | 97.65 150 | 96.85 246 | 98.94 220 | 98.57 104 | 98.89 142 | 98.50 220 | 95.60 205 | 99.85 89 | 97.54 119 | 99.85 72 | 99.59 59 |
|
xiu_mvs_v1_base_debu | | | 97.86 176 | 98.17 140 | 96.92 270 | 98.98 204 | 93.91 276 | 96.45 267 | 99.17 181 | 97.85 145 | 98.41 191 | 97.14 298 | 98.47 39 | 99.92 34 | 98.02 96 | 99.05 250 | 96.92 324 |
|
xiu_mvs_v1_base | | | 97.86 176 | 98.17 140 | 96.92 270 | 98.98 204 | 93.91 276 | 96.45 267 | 99.17 181 | 97.85 145 | 98.41 191 | 97.14 298 | 98.47 39 | 99.92 34 | 98.02 96 | 99.05 250 | 96.92 324 |
|
xiu_mvs_v1_base_debi | | | 97.86 176 | 98.17 140 | 96.92 270 | 98.98 204 | 93.91 276 | 96.45 267 | 99.17 181 | 97.85 145 | 98.41 191 | 97.14 298 | 98.47 39 | 99.92 34 | 98.02 96 | 99.05 250 | 96.92 324 |
|
#test# | | | 98.50 122 | 98.16 143 | 99.51 41 | 99.49 93 | 99.16 29 | 98.03 143 | 99.31 132 | 96.30 235 | 98.58 179 | 98.50 220 | 97.97 71 | 99.85 89 | 95.68 222 | 99.59 166 | 99.53 92 |
|
mvs_anonymous | | | 97.83 182 | 98.16 143 | 96.87 273 | 98.18 301 | 91.89 303 | 97.31 215 | 98.90 229 | 97.37 181 | 98.83 151 | 99.46 53 | 96.28 179 | 99.79 176 | 98.90 54 | 98.16 296 | 98.95 237 |
|
PVSNet_Blended_VisFu | | | 98.17 157 | 98.15 145 | 98.22 212 | 99.73 29 | 95.15 244 | 97.36 212 | 99.68 16 | 94.45 282 | 98.99 126 | 99.27 78 | 96.87 145 | 99.94 20 | 97.13 140 | 99.91 54 | 99.57 71 |
|
DeepC-MVS_fast | | 96.85 6 | 98.30 141 | 98.15 145 | 98.75 146 | 98.61 270 | 97.23 167 | 97.76 175 | 99.09 194 | 97.31 187 | 98.75 161 | 98.66 192 | 97.56 91 | 99.64 263 | 96.10 202 | 99.55 185 | 99.39 153 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
MSLP-MVS++ | | | 98.02 163 | 98.14 147 | 97.64 243 | 98.58 273 | 95.19 243 | 97.48 206 | 99.23 160 | 97.47 170 | 97.90 214 | 98.62 203 | 97.04 130 | 98.81 349 | 97.55 118 | 99.41 204 | 98.94 239 |
|
MVS_111021_LR | | | 98.30 141 | 98.12 148 | 98.83 133 | 99.16 168 | 98.03 114 | 96.09 284 | 99.30 139 | 97.58 159 | 98.10 203 | 98.24 239 | 98.25 48 | 99.34 323 | 96.69 166 | 99.65 156 | 99.12 220 |
|
SMA-MVS | | | 98.47 125 | 98.11 149 | 99.53 32 | 99.16 168 | 99.27 16 | 98.05 141 | 99.30 139 | 94.34 286 | 99.22 95 | 99.10 110 | 97.72 82 | 99.79 176 | 96.45 185 | 99.68 144 | 99.53 92 |
|
IterMVS | | | 97.73 184 | 98.11 149 | 96.57 284 | 99.24 139 | 90.28 323 | 95.52 312 | 99.21 161 | 98.86 86 | 99.33 73 | 99.33 73 | 93.11 259 | 99.94 20 | 98.49 75 | 99.94 33 | 99.48 118 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
no-one | | | 97.98 169 | 98.10 151 | 97.61 244 | 99.55 74 | 93.82 281 | 96.70 254 | 98.94 220 | 96.18 237 | 99.52 40 | 99.41 62 | 95.90 198 | 99.81 144 | 96.72 162 | 99.99 11 | 99.20 205 |
|
Fast-Effi-MVS+-dtu | | | 98.27 145 | 98.09 152 | 98.81 135 | 98.43 286 | 98.11 105 | 97.61 193 | 99.50 65 | 98.64 96 | 97.39 264 | 97.52 280 | 98.12 60 | 99.95 13 | 96.90 150 | 98.71 272 | 98.38 282 |
|
MP-MVS | | | 98.46 127 | 98.09 152 | 99.54 25 | 99.57 63 | 99.22 21 | 98.50 97 | 99.19 171 | 97.61 157 | 97.58 246 | 98.66 192 | 97.40 105 | 99.88 63 | 94.72 240 | 99.60 165 | 99.54 87 |
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
ACMP | | 95.32 15 | 98.41 131 | 98.09 152 | 99.36 58 | 99.51 85 | 98.79 61 | 97.68 182 | 99.38 104 | 95.76 251 | 98.81 156 | 98.82 170 | 98.36 45 | 99.82 131 | 94.75 237 | 99.77 106 | 99.48 118 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
PMMVS2 | | | 98.07 162 | 98.08 155 | 98.04 225 | 99.41 116 | 94.59 257 | 94.59 332 | 99.40 99 | 97.50 167 | 98.82 154 | 98.83 167 | 96.83 147 | 99.84 104 | 97.50 122 | 99.81 90 | 99.71 28 |
|
MVS_111021_HR | | | 98.25 149 | 98.08 155 | 98.75 146 | 99.09 179 | 97.46 159 | 95.97 287 | 99.27 148 | 97.60 158 | 97.99 210 | 98.25 238 | 98.15 59 | 99.38 320 | 96.87 152 | 99.57 176 | 99.42 144 |
|
TAMVS | | | 98.24 151 | 98.05 157 | 98.80 136 | 99.07 183 | 97.18 172 | 97.88 163 | 98.81 244 | 96.66 221 | 99.17 102 | 99.21 88 | 94.81 229 | 99.77 196 | 96.96 147 | 99.88 65 | 99.44 136 |
|
EPP-MVSNet | | | 98.30 141 | 98.04 158 | 99.07 98 | 99.56 70 | 97.83 134 | 99.29 26 | 98.07 280 | 99.03 73 | 98.59 177 | 99.13 106 | 92.16 271 | 99.90 47 | 96.87 152 | 99.68 144 | 99.49 112 |
|
DeepPCF-MVS | | 96.93 5 | 98.32 139 | 98.01 159 | 99.23 80 | 98.39 288 | 98.97 51 | 95.03 323 | 99.18 175 | 96.88 210 | 99.33 73 | 98.78 175 | 98.16 57 | 99.28 332 | 96.74 160 | 99.62 159 | 99.44 136 |
|
TSAR-MVS + GP. | | | 98.18 155 | 97.98 160 | 98.77 142 | 98.71 250 | 97.88 130 | 96.32 274 | 98.66 259 | 96.33 232 | 99.23 94 | 98.51 217 | 97.48 100 | 99.40 316 | 97.16 136 | 99.46 200 | 99.02 229 |
|
TinyColmap | | | 97.89 172 | 97.98 160 | 97.60 245 | 98.86 227 | 94.35 265 | 96.21 279 | 99.44 89 | 97.45 177 | 99.06 111 | 98.88 158 | 97.99 69 | 99.28 332 | 94.38 252 | 99.58 172 | 99.18 211 |
|
VDDNet | | | 98.21 152 | 97.95 162 | 99.01 111 | 99.58 58 | 97.74 145 | 99.01 56 | 97.29 296 | 99.67 8 | 98.97 130 | 99.50 47 | 90.45 279 | 99.80 156 | 97.88 103 | 99.20 231 | 99.48 118 |
|
PHI-MVS | | | 98.29 144 | 97.95 162 | 99.34 66 | 98.44 285 | 99.16 29 | 98.12 131 | 99.38 104 | 96.01 247 | 98.06 206 | 98.43 224 | 97.80 80 | 99.67 248 | 95.69 221 | 99.58 172 | 99.20 205 |
|
HSP-MVS | | | 98.34 137 | 97.94 164 | 99.54 25 | 99.57 63 | 99.25 19 | 98.57 87 | 98.84 238 | 97.55 164 | 99.31 80 | 97.71 269 | 94.61 235 | 99.88 63 | 96.14 201 | 99.19 235 | 99.48 118 |
|
PMVS | | 91.26 20 | 97.86 176 | 97.94 164 | 97.65 241 | 99.71 35 | 97.94 126 | 98.52 92 | 98.68 258 | 98.99 76 | 97.52 252 | 99.35 69 | 97.41 104 | 98.18 352 | 91.59 306 | 99.67 150 | 96.82 331 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
MVP-Stereo | | | 98.08 161 | 97.92 166 | 98.57 170 | 98.96 207 | 96.79 186 | 97.90 162 | 99.18 175 | 96.41 230 | 98.46 186 | 98.95 144 | 95.93 195 | 99.60 273 | 96.51 181 | 98.98 260 | 99.31 182 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
MDA-MVSNet-bldmvs | | | 97.94 170 | 97.91 167 | 98.06 223 | 99.44 110 | 94.96 248 | 96.63 259 | 99.15 187 | 98.35 110 | 98.83 151 | 99.11 108 | 94.31 241 | 99.85 89 | 96.60 171 | 98.72 269 | 99.37 160 |
|
Effi-MVS+-dtu | | | 98.26 147 | 97.90 168 | 99.35 63 | 98.02 306 | 99.49 3 | 98.02 150 | 99.16 184 | 98.29 119 | 97.64 241 | 97.99 257 | 96.44 172 | 99.95 13 | 96.66 168 | 98.93 263 | 98.60 271 |
|
IS-MVSNet | | | 98.19 154 | 97.90 168 | 99.08 97 | 99.57 63 | 97.97 121 | 99.31 21 | 98.32 272 | 99.01 75 | 98.98 128 | 99.03 129 | 91.59 274 | 99.79 176 | 95.49 228 | 99.80 94 | 99.48 118 |
|
MVS_0304 | | | 98.02 163 | 97.88 170 | 98.46 189 | 98.22 299 | 96.39 203 | 96.50 264 | 99.49 71 | 98.03 127 | 97.24 270 | 98.33 233 | 94.80 230 | 99.90 47 | 98.31 85 | 99.95 30 | 99.08 221 |
|
CNVR-MVS | | | 98.17 157 | 97.87 171 | 99.07 98 | 98.67 262 | 98.24 96 | 97.01 235 | 98.93 223 | 97.25 192 | 97.62 242 | 98.34 231 | 97.27 113 | 99.57 284 | 96.42 188 | 99.33 213 | 99.39 153 |
|
ESAPD | | | 98.25 149 | 97.83 172 | 99.50 43 | 99.36 122 | 99.10 43 | 97.25 218 | 99.28 143 | 96.66 221 | 99.05 116 | 98.71 183 | 97.56 91 | 99.86 78 | 93.00 283 | 99.57 176 | 99.53 92 |
|
Effi-MVS+ | | | 98.02 163 | 97.82 173 | 98.62 160 | 98.53 280 | 97.19 171 | 97.33 213 | 99.68 16 | 97.30 188 | 96.68 292 | 97.46 285 | 98.56 36 | 99.80 156 | 96.63 170 | 98.20 293 | 98.86 248 |
|
CANet | | | 97.87 175 | 97.76 174 | 98.19 214 | 97.75 314 | 95.51 236 | 96.76 250 | 99.05 201 | 97.74 148 | 96.93 279 | 98.21 242 | 95.59 206 | 99.89 56 | 97.86 105 | 99.93 39 | 99.19 210 |
|
MS-PatchMatch | | | 97.68 187 | 97.75 175 | 97.45 253 | 98.23 298 | 93.78 282 | 97.29 216 | 98.84 238 | 96.10 243 | 98.64 168 | 98.65 194 | 96.04 185 | 99.36 321 | 96.84 154 | 99.14 242 | 99.20 205 |
|
ppachtmachnet_test | | | 97.50 198 | 97.74 176 | 96.78 277 | 98.70 254 | 91.23 321 | 94.55 333 | 99.05 201 | 96.36 231 | 99.21 96 | 98.79 174 | 96.39 174 | 99.78 186 | 96.74 160 | 99.82 83 | 99.34 172 |
|
our_test_3 | | | 97.39 209 | 97.73 177 | 96.34 288 | 98.70 254 | 89.78 325 | 94.61 331 | 98.97 219 | 96.50 226 | 99.04 119 | 98.85 163 | 95.98 192 | 99.84 104 | 97.26 133 | 99.67 150 | 99.41 146 |
|
LF4IMVS | | | 97.90 171 | 97.69 178 | 98.52 180 | 99.17 166 | 97.66 149 | 97.19 227 | 99.47 81 | 96.31 234 | 97.85 219 | 98.20 243 | 96.71 157 | 99.52 297 | 94.62 241 | 99.72 125 | 98.38 282 |
|
YYNet1 | | | 97.60 192 | 97.67 179 | 97.39 257 | 99.04 193 | 93.04 293 | 95.27 317 | 98.38 271 | 97.25 192 | 98.92 139 | 98.95 144 | 95.48 211 | 99.73 221 | 96.99 145 | 98.74 268 | 99.41 146 |
|
HQP_MVS | | | 97.99 168 | 97.67 179 | 98.93 120 | 99.19 161 | 97.65 150 | 97.77 173 | 99.27 148 | 98.20 122 | 97.79 233 | 97.98 258 | 94.90 222 | 99.70 233 | 94.42 248 | 99.51 193 | 99.45 134 |
|
APD-MVS | | | 98.10 159 | 97.67 179 | 99.42 52 | 99.11 175 | 98.93 56 | 97.76 175 | 99.28 143 | 94.97 270 | 98.72 163 | 98.77 177 | 97.04 130 | 99.85 89 | 93.79 267 | 99.54 186 | 99.49 112 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
MDA-MVSNet_test_wron | | | 97.60 192 | 97.66 182 | 97.41 256 | 99.04 193 | 93.09 290 | 95.27 317 | 98.42 269 | 97.26 191 | 98.88 145 | 98.95 144 | 95.43 212 | 99.73 221 | 97.02 144 | 98.72 269 | 99.41 146 |
|
K. test v3 | | | 98.00 166 | 97.66 182 | 99.03 107 | 99.79 25 | 97.56 154 | 99.19 40 | 92.47 348 | 99.62 16 | 99.52 40 | 99.66 22 | 89.61 282 | 99.96 8 | 99.25 35 | 99.81 90 | 99.56 76 |
|
HPM-MVS++ | | | 98.10 159 | 97.64 184 | 99.48 46 | 99.09 179 | 99.13 38 | 97.52 203 | 98.75 252 | 97.46 175 | 96.90 284 | 97.83 264 | 96.01 187 | 99.84 104 | 95.82 216 | 99.35 210 | 99.46 130 |
|
MCST-MVS | | | 98.00 166 | 97.63 185 | 99.10 94 | 99.24 139 | 98.17 101 | 96.89 244 | 98.73 255 | 95.66 252 | 97.92 211 | 97.70 270 | 97.17 123 | 99.66 256 | 96.18 198 | 99.23 227 | 99.47 126 |
|
wuyk23d | | | 96.06 261 | 97.62 186 | 91.38 340 | 98.65 268 | 98.57 77 | 98.85 73 | 96.95 304 | 96.86 211 | 99.90 5 | 99.16 99 | 99.18 12 | 98.40 351 | 89.23 327 | 99.77 106 | 77.18 356 |
|
DSMNet-mixed | | | 97.42 207 | 97.60 187 | 96.87 273 | 99.15 172 | 91.46 308 | 98.54 91 | 99.12 190 | 92.87 303 | 97.58 246 | 99.63 27 | 96.21 180 | 99.90 47 | 95.74 218 | 99.54 186 | 99.27 190 |
|
UnsupCasMVSNet_eth | | | 97.89 172 | 97.60 187 | 98.75 146 | 99.31 131 | 97.17 173 | 97.62 191 | 99.35 118 | 98.72 95 | 98.76 160 | 98.68 188 | 92.57 268 | 99.74 216 | 97.76 111 | 95.60 341 | 99.34 172 |
|
PVSNet_BlendedMVS | | | 97.55 197 | 97.53 189 | 97.60 245 | 98.92 216 | 93.77 283 | 96.64 258 | 99.43 94 | 94.49 278 | 97.62 242 | 99.18 93 | 96.82 148 | 99.67 248 | 94.73 238 | 99.93 39 | 99.36 166 |
|
MSDG | | | 97.71 185 | 97.52 190 | 98.28 209 | 98.91 219 | 96.82 185 | 94.42 334 | 99.37 108 | 97.65 153 | 98.37 195 | 98.29 236 | 97.40 105 | 99.33 325 | 94.09 258 | 99.22 228 | 98.68 270 |
|
xiu_mvs_v2_base | | | 97.16 225 | 97.49 191 | 96.17 297 | 98.54 278 | 92.46 297 | 95.45 314 | 98.84 238 | 97.25 192 | 97.48 255 | 96.49 307 | 98.31 47 | 99.90 47 | 96.34 191 | 98.68 274 | 96.15 340 |
|
pmmvs5 | | | 97.64 190 | 97.49 191 | 98.08 221 | 99.14 173 | 95.12 246 | 96.70 254 | 99.05 201 | 93.77 293 | 98.62 172 | 98.83 167 | 93.23 256 | 99.75 207 | 98.33 84 | 99.76 115 | 99.36 166 |
|
OMC-MVS | | | 97.88 174 | 97.49 191 | 99.04 106 | 98.89 224 | 98.63 70 | 96.94 238 | 99.25 154 | 95.02 268 | 98.53 184 | 98.51 217 | 97.27 113 | 99.47 308 | 93.50 276 | 99.51 193 | 99.01 230 |
|
mvs-test1 | | | 97.83 182 | 97.48 194 | 98.89 126 | 98.02 306 | 99.20 24 | 97.20 224 | 99.16 184 | 98.29 119 | 96.46 303 | 97.17 295 | 96.44 172 | 99.92 34 | 96.66 168 | 97.90 313 | 97.54 317 |
|
NCCC | | | 97.86 176 | 97.47 195 | 99.05 104 | 98.61 270 | 98.07 111 | 96.98 236 | 98.90 229 | 97.63 154 | 97.04 276 | 97.93 261 | 95.99 191 | 99.66 256 | 95.31 229 | 98.82 266 | 99.43 141 |
|
test_normal | | | 97.58 194 | 97.41 196 | 98.10 217 | 99.03 196 | 95.72 230 | 96.21 279 | 97.05 300 | 96.71 218 | 98.65 166 | 98.12 248 | 93.87 248 | 99.69 237 | 97.68 117 | 99.35 210 | 98.88 246 |
|
DI_MVS_plusplus_test | | | 97.57 196 | 97.40 197 | 98.07 222 | 99.06 186 | 95.71 231 | 96.58 262 | 96.96 302 | 96.71 218 | 98.69 164 | 98.13 244 | 93.81 251 | 99.68 242 | 97.45 124 | 99.19 235 | 98.80 256 |
|
USDC | | | 97.41 208 | 97.40 197 | 97.44 254 | 98.94 210 | 93.67 285 | 95.17 320 | 99.53 59 | 94.03 291 | 98.97 130 | 99.10 110 | 95.29 214 | 99.34 323 | 95.84 215 | 99.73 120 | 99.30 185 |
|
PS-MVSNAJ | | | 97.08 229 | 97.39 199 | 96.16 299 | 98.56 275 | 92.46 297 | 95.24 319 | 98.85 237 | 97.25 192 | 97.49 254 | 95.99 315 | 98.07 61 | 99.90 47 | 96.37 189 | 98.67 275 | 96.12 341 |
|
Fast-Effi-MVS+ | | | 97.67 188 | 97.38 200 | 98.57 170 | 98.71 250 | 97.43 161 | 97.23 220 | 99.45 86 | 94.82 275 | 96.13 307 | 96.51 306 | 98.52 38 | 99.91 43 | 96.19 196 | 98.83 265 | 98.37 284 |
|
diffmvs | | | 97.49 200 | 97.36 201 | 97.91 229 | 98.38 289 | 95.70 232 | 97.95 157 | 99.31 132 | 94.87 273 | 96.14 306 | 98.78 175 | 94.84 226 | 99.43 314 | 97.69 115 | 98.26 289 | 98.59 272 |
|
CPTT-MVS | | | 97.84 181 | 97.36 201 | 99.27 75 | 99.31 131 | 98.46 86 | 98.29 117 | 99.27 148 | 94.90 272 | 97.83 224 | 98.37 228 | 94.90 222 | 99.84 104 | 93.85 266 | 99.54 186 | 99.51 100 |
|
jason | | | 97.45 205 | 97.35 203 | 97.76 235 | 99.24 139 | 93.93 275 | 95.86 298 | 98.42 269 | 94.24 288 | 98.50 185 | 98.13 244 | 94.82 227 | 99.91 43 | 97.22 134 | 99.73 120 | 99.43 141 |
jason: jason. |
CDS-MVSNet | | | 97.69 186 | 97.35 203 | 98.69 152 | 98.73 247 | 97.02 180 | 96.92 241 | 98.75 252 | 95.89 249 | 98.59 177 | 98.67 190 | 92.08 273 | 99.74 216 | 96.72 162 | 99.81 90 | 99.32 178 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
pmmvs4 | | | 97.58 194 | 97.28 205 | 98.51 184 | 98.84 233 | 96.93 183 | 95.40 316 | 98.52 265 | 93.60 295 | 98.61 174 | 98.65 194 | 95.10 219 | 99.60 273 | 96.97 146 | 99.79 98 | 98.99 232 |
|
FMVSNet3 | | | 97.50 198 | 97.24 206 | 98.29 208 | 98.08 304 | 95.83 227 | 97.86 166 | 98.91 228 | 97.89 140 | 98.95 133 | 98.95 144 | 87.06 291 | 99.81 144 | 97.77 108 | 99.69 139 | 99.23 199 |
|
CVMVSNet | | | 96.25 259 | 97.21 207 | 93.38 337 | 99.10 176 | 80.56 357 | 97.20 224 | 98.19 278 | 96.94 207 | 99.00 125 | 99.02 130 | 89.50 284 | 99.80 156 | 96.36 190 | 99.59 166 | 99.78 15 |
|
Test4 | | | 97.43 206 | 97.18 208 | 98.18 215 | 99.05 191 | 96.02 218 | 96.62 260 | 99.09 194 | 96.25 236 | 98.63 171 | 97.70 270 | 90.49 278 | 99.68 242 | 97.50 122 | 99.30 218 | 98.83 250 |
|
N_pmnet | | | 97.63 191 | 97.17 209 | 98.99 114 | 99.27 135 | 97.86 132 | 95.98 286 | 93.41 340 | 95.25 265 | 99.47 50 | 98.90 152 | 95.63 204 | 99.85 89 | 96.91 148 | 99.73 120 | 99.27 190 |
|
Vis-MVSNet (Re-imp) | | | 97.46 204 | 97.16 210 | 98.34 203 | 99.55 74 | 96.10 215 | 98.94 65 | 98.44 268 | 98.32 115 | 98.16 199 | 98.62 203 | 88.76 287 | 99.73 221 | 93.88 264 | 99.79 98 | 99.18 211 |
|
CLD-MVS | | | 97.49 200 | 97.16 210 | 98.48 187 | 99.07 183 | 97.03 178 | 94.71 329 | 99.21 161 | 94.46 280 | 98.06 206 | 97.16 296 | 97.57 90 | 99.48 307 | 94.46 245 | 99.78 102 | 98.95 237 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
CHOSEN 1792x2688 | | | 97.49 200 | 97.14 212 | 98.54 178 | 99.68 44 | 96.09 217 | 96.50 264 | 99.62 28 | 91.58 319 | 98.84 150 | 98.97 140 | 92.36 269 | 99.88 63 | 96.76 159 | 99.95 30 | 99.67 32 |
|
CANet_DTU | | | 97.26 217 | 97.06 213 | 97.84 231 | 97.57 321 | 94.65 255 | 96.19 282 | 98.79 247 | 97.23 197 | 95.14 331 | 98.24 239 | 93.22 257 | 99.84 104 | 97.34 129 | 99.84 74 | 99.04 226 |
|
Patchmatch-RL test | | | 97.26 217 | 97.02 214 | 97.99 228 | 99.52 82 | 95.53 235 | 96.13 283 | 99.71 12 | 97.47 170 | 99.27 83 | 99.16 99 | 84.30 312 | 99.62 266 | 97.89 101 | 99.77 106 | 98.81 253 |
|
test_prior3 | | | 97.48 203 | 97.00 215 | 98.95 117 | 98.69 257 | 97.95 124 | 95.74 304 | 99.03 206 | 96.48 227 | 96.11 308 | 97.63 274 | 95.92 196 | 99.59 277 | 94.16 253 | 99.20 231 | 99.30 185 |
|
Patchmtry | | | 97.35 210 | 96.97 216 | 98.50 185 | 97.31 333 | 96.47 198 | 98.18 125 | 98.92 226 | 98.95 83 | 98.78 157 | 99.37 66 | 85.44 304 | 99.85 89 | 95.96 207 | 99.83 80 | 99.17 215 |
|
sss | | | 97.21 221 | 96.93 217 | 98.06 223 | 98.83 235 | 95.22 242 | 96.75 251 | 98.48 267 | 94.49 278 | 97.27 269 | 97.90 262 | 92.77 265 | 99.80 156 | 96.57 174 | 99.32 215 | 99.16 218 |
|
UnsupCasMVSNet_bld | | | 97.30 214 | 96.92 218 | 98.45 191 | 99.28 134 | 96.78 190 | 96.20 281 | 99.27 148 | 95.42 263 | 98.28 197 | 98.30 235 | 93.16 258 | 99.71 231 | 94.99 233 | 97.37 321 | 98.87 247 |
|
DP-MVS Recon | | | 97.33 212 | 96.92 218 | 98.57 170 | 99.09 179 | 97.99 116 | 96.79 247 | 99.35 118 | 93.18 299 | 97.71 237 | 98.07 254 | 95.00 221 | 99.31 327 | 93.97 260 | 99.13 245 | 98.42 280 |
|
API-MVS | | | 97.04 233 | 96.91 220 | 97.42 255 | 97.88 313 | 98.23 100 | 98.18 125 | 98.50 266 | 97.57 161 | 97.39 264 | 96.75 303 | 96.77 152 | 99.15 338 | 90.16 324 | 99.02 254 | 94.88 350 |
|
alignmvs | | | 97.35 210 | 96.88 221 | 98.78 140 | 98.54 278 | 98.09 106 | 97.71 179 | 97.69 290 | 99.20 51 | 97.59 245 | 95.90 320 | 88.12 290 | 99.55 290 | 98.18 90 | 98.96 261 | 98.70 266 |
|
lupinMVS | | | 97.06 230 | 96.86 222 | 97.65 241 | 98.88 225 | 93.89 279 | 95.48 313 | 97.97 282 | 93.53 296 | 98.16 199 | 97.58 276 | 93.81 251 | 99.91 43 | 96.77 158 | 99.57 176 | 99.17 215 |
|
1112_ss | | | 97.29 216 | 96.86 222 | 98.58 168 | 99.34 128 | 96.32 205 | 96.75 251 | 99.58 36 | 93.14 300 | 96.89 285 | 97.48 283 | 92.11 272 | 99.86 78 | 96.91 148 | 99.54 186 | 99.57 71 |
|
test1235678 | | | 97.06 230 | 96.84 224 | 97.73 237 | 98.55 277 | 94.46 264 | 94.80 327 | 99.36 112 | 96.85 212 | 98.83 151 | 98.26 237 | 92.72 266 | 99.82 131 | 92.49 296 | 99.70 132 | 98.91 243 |
|
QAPM | | | 97.31 213 | 96.81 225 | 98.82 134 | 98.80 242 | 97.49 157 | 99.06 54 | 99.19 171 | 90.22 331 | 97.69 239 | 99.16 99 | 96.91 139 | 99.90 47 | 90.89 320 | 99.41 204 | 99.07 223 |
|
PatchMatch-RL | | | 97.24 220 | 96.78 226 | 98.61 163 | 99.03 196 | 97.83 134 | 96.36 272 | 99.06 197 | 93.49 298 | 97.36 267 | 97.78 266 | 95.75 201 | 99.49 304 | 93.44 277 | 98.77 267 | 98.52 274 |
|
new_pmnet | | | 96.99 235 | 96.76 227 | 97.67 239 | 98.72 248 | 94.89 249 | 95.95 294 | 98.20 276 | 92.62 306 | 98.55 182 | 98.54 215 | 94.88 225 | 99.52 297 | 93.96 261 | 99.44 202 | 98.59 272 |
|
BH-untuned | | | 96.83 240 | 96.75 228 | 97.08 263 | 98.74 246 | 93.33 289 | 96.71 253 | 98.26 274 | 96.72 216 | 98.44 188 | 97.37 291 | 95.20 216 | 99.47 308 | 91.89 300 | 97.43 320 | 98.44 278 |
|
Patchmatch-test1 | | | 96.44 256 | 96.72 229 | 95.60 312 | 98.24 296 | 88.35 330 | 95.85 300 | 96.88 308 | 96.11 242 | 97.67 240 | 98.57 209 | 93.10 260 | 99.69 237 | 94.79 236 | 99.22 228 | 98.77 259 |
|
LFMVS | | | 97.20 222 | 96.72 229 | 98.64 156 | 98.72 248 | 96.95 182 | 98.93 67 | 94.14 338 | 99.74 5 | 98.78 157 | 99.01 132 | 84.45 309 | 99.73 221 | 97.44 125 | 99.27 223 | 99.25 195 |
|
CNLPA | | | 97.17 224 | 96.71 231 | 98.55 175 | 98.56 275 | 98.05 113 | 96.33 273 | 98.93 223 | 96.91 209 | 97.06 275 | 97.39 289 | 94.38 240 | 99.45 312 | 91.66 302 | 99.18 237 | 98.14 288 |
|
AdaColmap | | | 97.14 226 | 96.71 231 | 98.46 189 | 98.34 291 | 97.80 140 | 96.95 237 | 98.93 223 | 95.58 259 | 96.92 280 | 97.66 272 | 95.87 199 | 99.53 293 | 90.97 317 | 99.14 242 | 98.04 291 |
|
PVSNet_Blended | | | 96.88 238 | 96.68 233 | 97.47 252 | 98.92 216 | 93.77 283 | 94.71 329 | 99.43 94 | 90.98 326 | 97.62 242 | 97.36 292 | 96.82 148 | 99.67 248 | 94.73 238 | 99.56 183 | 98.98 233 |
|
F-COLMAP | | | 97.30 214 | 96.68 233 | 99.14 89 | 99.19 161 | 98.39 90 | 97.27 217 | 99.30 139 | 92.93 301 | 96.62 294 | 98.00 256 | 95.73 202 | 99.68 242 | 92.62 293 | 98.46 286 | 99.35 171 |
|
OpenMVS | | 96.65 7 | 97.09 228 | 96.68 233 | 98.32 204 | 98.32 292 | 97.16 174 | 98.86 72 | 99.37 108 | 89.48 335 | 96.29 305 | 99.15 103 | 96.56 165 | 99.90 47 | 92.90 285 | 99.20 231 | 97.89 294 |
|
CDPH-MVS | | | 97.26 217 | 96.66 236 | 99.07 98 | 99.00 201 | 98.15 102 | 96.03 285 | 99.01 213 | 91.21 325 | 97.79 233 | 97.85 263 | 96.89 144 | 99.69 237 | 92.75 291 | 99.38 207 | 99.39 153 |
|
RPMNet | | | 96.82 242 | 96.66 236 | 97.28 258 | 97.71 316 | 94.22 266 | 98.11 132 | 96.90 307 | 99.37 37 | 96.91 282 | 99.34 71 | 86.72 292 | 99.81 144 | 97.53 120 | 97.36 323 | 97.81 300 |
|
MG-MVS | | | 96.77 244 | 96.61 238 | 97.26 260 | 98.31 293 | 93.06 291 | 95.93 295 | 98.12 279 | 96.45 229 | 97.92 211 | 98.73 181 | 93.77 254 | 99.39 318 | 91.19 316 | 99.04 253 | 99.33 177 |
|
HyFIR lowres test | | | 97.19 223 | 96.60 239 | 98.96 116 | 99.62 55 | 97.28 166 | 95.17 320 | 99.50 65 | 94.21 289 | 99.01 123 | 98.32 234 | 86.61 293 | 99.99 2 | 97.10 143 | 99.84 74 | 99.60 53 |
|
BH-RMVSNet | | | 96.83 240 | 96.58 240 | 97.58 247 | 98.47 282 | 94.05 271 | 96.67 256 | 97.36 294 | 96.70 220 | 97.87 216 | 97.98 258 | 95.14 218 | 99.44 313 | 90.47 323 | 98.58 280 | 99.25 195 |
|
LP | | | 96.60 250 | 96.57 241 | 96.68 279 | 97.64 320 | 91.70 305 | 98.11 132 | 97.74 287 | 97.29 190 | 97.91 213 | 99.24 83 | 88.35 288 | 99.85 89 | 97.11 142 | 95.76 340 | 98.49 275 |
|
MVSTER | | | 96.86 239 | 96.55 242 | 97.79 233 | 97.91 311 | 94.21 268 | 97.56 199 | 98.87 232 | 97.49 169 | 99.06 111 | 99.05 124 | 80.72 324 | 99.80 156 | 98.44 77 | 99.82 83 | 99.37 160 |
|
Test_1112_low_res | | | 96.99 235 | 96.55 242 | 98.31 206 | 99.35 126 | 95.47 238 | 95.84 301 | 99.53 59 | 91.51 321 | 96.80 290 | 98.48 223 | 91.36 275 | 99.83 119 | 96.58 172 | 99.53 190 | 99.62 46 |
|
HQP-MVS | | | 97.00 234 | 96.49 244 | 98.55 175 | 98.67 262 | 96.79 186 | 96.29 275 | 99.04 204 | 96.05 244 | 95.55 322 | 96.84 301 | 93.84 249 | 99.54 291 | 92.82 288 | 99.26 225 | 99.32 178 |
|
train_agg | | | 97.10 227 | 96.45 245 | 99.07 98 | 98.71 250 | 98.08 109 | 95.96 291 | 99.03 206 | 91.64 316 | 95.85 314 | 97.53 278 | 96.47 170 | 99.76 201 | 93.67 269 | 99.16 238 | 99.36 166 |
|
agg_prior1 | | | 97.06 230 | 96.40 246 | 99.03 107 | 98.68 259 | 97.99 116 | 95.76 302 | 99.01 213 | 91.73 315 | 95.59 318 | 97.50 281 | 96.49 169 | 99.77 196 | 93.71 268 | 99.14 242 | 99.34 172 |
|
PatchT | | | 96.65 247 | 96.35 247 | 97.54 249 | 97.40 330 | 95.32 241 | 97.98 154 | 96.64 313 | 99.33 41 | 96.89 285 | 99.42 60 | 84.32 311 | 99.81 144 | 97.69 115 | 97.49 318 | 97.48 318 |
|
Patchmatch-test | | | 96.55 251 | 96.34 248 | 97.17 262 | 98.35 290 | 93.06 291 | 98.40 114 | 97.79 285 | 97.33 184 | 98.41 191 | 98.67 190 | 83.68 316 | 99.69 237 | 95.16 230 | 99.31 217 | 98.77 259 |
|
PAPM_NR | | | 96.82 242 | 96.32 249 | 98.30 207 | 99.07 183 | 96.69 193 | 97.48 206 | 98.76 249 | 95.81 250 | 96.61 295 | 96.47 309 | 94.12 247 | 99.17 336 | 90.82 322 | 97.78 315 | 99.06 224 |
|
agg_prior3 | | | 96.95 237 | 96.27 250 | 99.00 113 | 98.68 259 | 97.91 127 | 95.96 291 | 99.01 213 | 90.74 328 | 95.60 317 | 97.45 286 | 96.14 181 | 99.74 216 | 93.67 269 | 99.16 238 | 99.36 166 |
|
WTY-MVS | | | 96.67 246 | 96.27 250 | 97.87 230 | 98.81 240 | 94.61 256 | 96.77 249 | 97.92 284 | 94.94 271 | 97.12 271 | 97.74 268 | 91.11 276 | 99.82 131 | 93.89 263 | 98.15 297 | 99.18 211 |
|
MIMVSNet | | | 96.62 249 | 96.25 252 | 97.71 238 | 99.04 193 | 94.66 254 | 99.16 43 | 96.92 306 | 97.23 197 | 97.87 216 | 99.10 110 | 86.11 297 | 99.65 261 | 91.65 303 | 99.21 230 | 98.82 252 |
|
1121 | | | 96.73 245 | 96.00 253 | 98.91 123 | 98.95 209 | 97.76 142 | 98.07 137 | 98.73 255 | 87.65 342 | 96.54 296 | 98.13 244 | 94.52 237 | 99.73 221 | 92.38 297 | 99.02 254 | 99.24 198 |
|
PMMVS | | | 96.51 252 | 95.98 254 | 98.09 218 | 97.53 324 | 95.84 226 | 94.92 325 | 98.84 238 | 91.58 319 | 96.05 312 | 95.58 322 | 95.68 203 | 99.66 256 | 95.59 225 | 98.09 306 | 98.76 261 |
|
CR-MVSNet | | | 96.28 258 | 95.95 255 | 97.28 258 | 97.71 316 | 94.22 266 | 98.11 132 | 98.92 226 | 92.31 310 | 96.91 282 | 99.37 66 | 85.44 304 | 99.81 144 | 97.39 128 | 97.36 323 | 97.81 300 |
|
TAPA-MVS | | 96.21 11 | 96.63 248 | 95.95 255 | 98.65 155 | 98.93 212 | 98.09 106 | 96.93 239 | 99.28 143 | 83.58 350 | 98.13 202 | 97.78 266 | 96.13 182 | 99.40 316 | 93.52 274 | 99.29 221 | 98.45 277 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
114514_t | | | 96.50 254 | 95.77 257 | 98.69 152 | 99.48 98 | 97.43 161 | 97.84 168 | 99.55 54 | 81.42 352 | 96.51 299 | 98.58 208 | 95.53 207 | 99.67 248 | 93.41 278 | 99.58 172 | 98.98 233 |
|
PLC | | 94.65 16 | 96.51 252 | 95.73 258 | 98.85 131 | 98.75 245 | 97.91 127 | 96.42 270 | 99.06 197 | 90.94 327 | 95.59 318 | 97.38 290 | 94.41 239 | 99.59 277 | 90.93 318 | 98.04 311 | 99.05 225 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
PVSNet | | 93.40 17 | 95.67 267 | 95.70 259 | 95.57 313 | 98.83 235 | 88.57 328 | 92.50 347 | 97.72 288 | 92.69 305 | 96.49 302 | 96.44 310 | 93.72 255 | 99.43 314 | 93.61 271 | 99.28 222 | 98.71 264 |
|
MAR-MVS | | | 96.47 255 | 95.70 259 | 98.79 137 | 97.92 310 | 99.12 40 | 98.28 118 | 98.60 263 | 92.16 313 | 95.54 325 | 96.17 313 | 94.77 233 | 99.52 297 | 89.62 326 | 98.23 290 | 97.72 306 |
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 |
PatchmatchNet | | | 95.58 268 | 95.67 261 | 95.30 316 | 97.34 332 | 87.32 334 | 97.65 186 | 96.65 312 | 95.30 264 | 97.07 274 | 98.69 186 | 84.77 306 | 99.75 207 | 94.97 234 | 98.64 276 | 98.83 250 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
MVS-HIRNet | | | 94.32 299 | 95.62 262 | 90.42 341 | 98.46 283 | 75.36 358 | 96.29 275 | 89.13 356 | 95.25 265 | 95.38 328 | 99.75 7 | 92.88 264 | 99.19 335 | 94.07 259 | 99.39 206 | 96.72 333 |
|
1314 | | | 95.74 266 | 95.60 263 | 96.17 297 | 97.53 324 | 92.75 294 | 98.07 137 | 98.31 273 | 91.22 324 | 94.25 338 | 96.68 304 | 95.53 207 | 99.03 340 | 91.64 304 | 97.18 326 | 96.74 332 |
|
CHOSEN 280x420 | | | 95.51 272 | 95.47 264 | 95.65 311 | 98.25 294 | 88.27 331 | 93.25 344 | 98.88 231 | 93.53 296 | 94.65 334 | 97.15 297 | 86.17 295 | 99.93 26 | 97.41 127 | 99.93 39 | 98.73 263 |
|
tpmrst | | | 95.07 277 | 95.46 265 | 93.91 331 | 97.11 336 | 84.36 349 | 97.62 191 | 96.96 302 | 94.98 269 | 96.35 304 | 98.80 172 | 85.46 303 | 99.59 277 | 95.60 224 | 96.23 337 | 97.79 303 |
|
EPNet | | | 96.14 260 | 95.44 266 | 98.25 210 | 90.76 359 | 95.50 237 | 97.92 159 | 94.65 325 | 98.97 79 | 92.98 346 | 98.85 163 | 89.12 286 | 99.87 73 | 95.99 205 | 99.68 144 | 99.39 153 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
CMPMVS | | 75.91 23 | 96.29 257 | 95.44 266 | 98.84 132 | 96.25 349 | 98.69 68 | 97.02 234 | 99.12 190 | 88.90 338 | 97.83 224 | 98.86 161 | 89.51 283 | 98.90 346 | 91.92 299 | 99.51 193 | 98.92 241 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
HY-MVS | | 95.94 13 | 95.90 263 | 95.35 268 | 97.55 248 | 97.95 308 | 94.79 250 | 98.81 75 | 96.94 305 | 92.28 311 | 95.17 330 | 98.57 209 | 89.90 281 | 99.75 207 | 91.20 315 | 97.33 325 | 98.10 289 |
|
GA-MVS | | | 95.86 264 | 95.32 269 | 97.49 251 | 98.60 272 | 94.15 270 | 93.83 341 | 97.93 283 | 95.49 261 | 96.68 292 | 97.42 288 | 83.21 317 | 99.30 329 | 96.22 194 | 98.55 281 | 99.01 230 |
|
testus | | | 95.52 270 | 95.32 269 | 96.13 301 | 97.91 311 | 89.49 327 | 93.62 342 | 99.61 30 | 92.41 308 | 97.38 266 | 95.42 332 | 94.72 234 | 99.63 264 | 88.06 331 | 98.72 269 | 99.26 193 |
|
tpmvs | | | 95.02 279 | 95.25 271 | 94.33 325 | 96.39 348 | 85.87 338 | 98.08 135 | 96.83 309 | 95.46 262 | 95.51 326 | 98.69 186 | 85.91 298 | 99.53 293 | 94.16 253 | 96.23 337 | 97.58 315 |
|
MDTV_nov1_ep13 | | | | 95.22 272 | | 97.06 337 | 83.20 351 | 97.74 177 | 96.16 318 | 94.37 284 | 96.99 278 | 98.83 167 | 83.95 314 | 99.53 293 | 93.90 262 | 97.95 312 | |
|
FMVSNet5 | | | 96.01 262 | 95.20 273 | 98.41 194 | 97.53 324 | 96.10 215 | 98.74 76 | 99.50 65 | 97.22 200 | 98.03 209 | 99.04 126 | 69.80 355 | 99.88 63 | 97.27 132 | 99.71 129 | 99.25 195 |
|
OpenMVS_ROB | | 95.38 14 | 95.84 265 | 95.18 274 | 97.81 232 | 98.41 287 | 97.15 175 | 97.37 211 | 98.62 262 | 83.86 349 | 98.65 166 | 98.37 228 | 94.29 242 | 99.68 242 | 88.41 329 | 98.62 278 | 96.60 334 |
|
test12356 | | | 94.85 285 | 95.12 275 | 94.03 330 | 98.25 294 | 83.12 352 | 93.85 340 | 99.33 127 | 94.17 290 | 97.28 268 | 97.20 293 | 85.83 299 | 99.75 207 | 90.85 321 | 99.33 213 | 99.22 203 |
|
TR-MVS | | | 95.55 269 | 95.12 275 | 96.86 276 | 97.54 323 | 93.94 274 | 96.49 266 | 96.53 315 | 94.36 285 | 97.03 277 | 96.61 305 | 94.26 243 | 99.16 337 | 86.91 334 | 96.31 336 | 97.47 319 |
|
JIA-IIPM | | | 95.52 270 | 95.03 277 | 97.00 267 | 96.85 341 | 94.03 272 | 96.93 239 | 95.82 320 | 99.20 51 | 94.63 335 | 99.71 14 | 83.09 318 | 99.60 273 | 94.42 248 | 94.64 345 | 97.36 320 |
|
ADS-MVSNet2 | | | 95.43 273 | 94.98 278 | 96.76 278 | 98.14 302 | 91.74 304 | 97.92 159 | 97.76 286 | 90.23 329 | 96.51 299 | 98.91 149 | 85.61 301 | 99.85 89 | 92.88 286 | 96.90 329 | 98.69 267 |
|
ADS-MVSNet | | | 95.24 275 | 94.93 279 | 96.18 296 | 98.14 302 | 90.10 324 | 97.92 159 | 97.32 295 | 90.23 329 | 96.51 299 | 98.91 149 | 85.61 301 | 99.74 216 | 92.88 286 | 96.90 329 | 98.69 267 |
|
BH-w/o | | | 95.13 276 | 94.89 280 | 95.86 306 | 98.20 300 | 91.31 318 | 95.65 307 | 97.37 293 | 93.64 294 | 96.52 298 | 95.70 321 | 93.04 261 | 99.02 341 | 88.10 330 | 95.82 339 | 97.24 322 |
|
EPNet_dtu | | | 94.93 280 | 94.78 281 | 95.38 315 | 93.58 358 | 87.68 333 | 96.78 248 | 95.69 322 | 97.35 183 | 89.14 354 | 98.09 252 | 88.15 289 | 99.49 304 | 94.95 235 | 99.30 218 | 98.98 233 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
PAPR | | | 95.29 274 | 94.47 282 | 97.75 236 | 97.50 328 | 95.14 245 | 94.89 326 | 98.71 257 | 91.39 323 | 95.35 329 | 95.48 329 | 94.57 236 | 99.14 339 | 84.95 341 | 97.37 321 | 98.97 236 |
|
view600 | | | 94.87 281 | 94.41 283 | 96.26 291 | 99.22 145 | 91.37 311 | 98.49 98 | 94.45 327 | 98.75 90 | 97.85 219 | 95.98 316 | 80.38 326 | 99.75 207 | 86.06 337 | 98.49 282 | 97.66 307 |
|
view800 | | | 94.87 281 | 94.41 283 | 96.26 291 | 99.22 145 | 91.37 311 | 98.49 98 | 94.45 327 | 98.75 90 | 97.85 219 | 95.98 316 | 80.38 326 | 99.75 207 | 86.06 337 | 98.49 282 | 97.66 307 |
|
conf0.05thres1000 | | | 94.87 281 | 94.41 283 | 96.26 291 | 99.22 145 | 91.37 311 | 98.49 98 | 94.45 327 | 98.75 90 | 97.85 219 | 95.98 316 | 80.38 326 | 99.75 207 | 86.06 337 | 98.49 282 | 97.66 307 |
|
tfpn | | | 94.87 281 | 94.41 283 | 96.26 291 | 99.22 145 | 91.37 311 | 98.49 98 | 94.45 327 | 98.75 90 | 97.85 219 | 95.98 316 | 80.38 326 | 99.75 207 | 86.06 337 | 98.49 282 | 97.66 307 |
|
pmmvs3 | | | 95.03 278 | 94.40 287 | 96.93 269 | 97.70 318 | 92.53 296 | 95.08 322 | 97.71 289 | 88.57 339 | 97.71 237 | 98.08 253 | 79.39 337 | 99.82 131 | 96.19 196 | 99.11 248 | 98.43 279 |
|
E-PMN | | | 94.17 303 | 94.37 288 | 93.58 334 | 96.86 340 | 85.71 341 | 90.11 352 | 97.07 299 | 98.17 125 | 97.82 226 | 97.19 294 | 84.62 308 | 98.94 344 | 89.77 325 | 97.68 317 | 96.09 342 |
|
tpm | | | 94.67 294 | 94.34 289 | 95.66 310 | 97.68 319 | 88.42 329 | 97.88 163 | 94.90 324 | 94.46 280 | 96.03 313 | 98.56 212 | 78.66 338 | 99.79 176 | 95.88 209 | 95.01 344 | 98.78 258 |
|
cascas | | | 94.79 289 | 94.33 290 | 96.15 300 | 96.02 352 | 92.36 300 | 92.34 349 | 99.26 153 | 85.34 348 | 95.08 332 | 94.96 341 | 92.96 262 | 98.53 350 | 94.41 251 | 98.59 279 | 97.56 316 |
|
tfpn1000 | | | 94.81 288 | 94.25 291 | 96.47 287 | 99.01 200 | 93.47 288 | 98.56 88 | 92.30 351 | 96.17 238 | 97.90 214 | 96.29 312 | 76.70 349 | 99.77 196 | 93.02 282 | 98.29 288 | 96.16 338 |
|
conf0.01 | | | 94.82 286 | 94.07 292 | 97.06 265 | 99.21 151 | 94.53 258 | 98.47 104 | 92.69 342 | 95.61 253 | 97.81 227 | 95.54 323 | 77.71 343 | 99.80 156 | 91.49 308 | 98.11 299 | 96.86 327 |
|
conf0.002 | | | 94.82 286 | 94.07 292 | 97.06 265 | 99.21 151 | 94.53 258 | 98.47 104 | 92.69 342 | 95.61 253 | 97.81 227 | 95.54 323 | 77.71 343 | 99.80 156 | 91.49 308 | 98.11 299 | 96.86 327 |
|
thresconf0.02 | | | 94.70 290 | 94.07 292 | 96.58 280 | 99.21 151 | 94.53 258 | 98.47 104 | 92.69 342 | 95.61 253 | 97.81 227 | 95.54 323 | 77.71 343 | 99.80 156 | 91.49 308 | 98.11 299 | 95.42 346 |
|
tfpn_n400 | | | 94.70 290 | 94.07 292 | 96.58 280 | 99.21 151 | 94.53 258 | 98.47 104 | 92.69 342 | 95.61 253 | 97.81 227 | 95.54 323 | 77.71 343 | 99.80 156 | 91.49 308 | 98.11 299 | 95.42 346 |
|
tfpnconf | | | 94.70 290 | 94.07 292 | 96.58 280 | 99.21 151 | 94.53 258 | 98.47 104 | 92.69 342 | 95.61 253 | 97.81 227 | 95.54 323 | 77.71 343 | 99.80 156 | 91.49 308 | 98.11 299 | 95.42 346 |
|
tfpnview11 | | | 94.70 290 | 94.07 292 | 96.58 280 | 99.21 151 | 94.53 258 | 98.47 104 | 92.69 342 | 95.61 253 | 97.81 227 | 95.54 323 | 77.71 343 | 99.80 156 | 91.49 308 | 98.11 299 | 95.42 346 |
|
EMVS | | | 93.83 311 | 94.02 298 | 93.23 338 | 96.83 342 | 84.96 345 | 89.77 353 | 96.32 317 | 97.92 131 | 97.43 259 | 96.36 311 | 86.17 295 | 98.93 345 | 87.68 332 | 97.73 316 | 95.81 343 |
|
PatchFormer-LS_test | | | 94.08 306 | 93.91 299 | 94.59 323 | 96.93 338 | 86.86 336 | 97.55 201 | 96.57 314 | 94.27 287 | 94.38 337 | 93.64 352 | 80.96 323 | 99.59 277 | 96.44 187 | 94.48 348 | 97.31 321 |
|
test-LLR | | | 93.90 310 | 93.85 300 | 94.04 328 | 96.53 344 | 84.62 347 | 94.05 337 | 92.39 349 | 96.17 238 | 94.12 340 | 95.07 334 | 82.30 321 | 99.67 248 | 95.87 212 | 98.18 294 | 97.82 298 |
|
thres600view7 | | | 94.45 296 | 93.83 301 | 96.29 289 | 99.06 186 | 91.53 307 | 97.99 153 | 94.24 334 | 98.34 111 | 97.44 258 | 95.01 336 | 79.84 331 | 99.67 248 | 84.33 343 | 98.23 290 | 97.66 307 |
|
tfpn111 | | | 94.33 298 | 93.78 302 | 95.96 303 | 99.06 186 | 91.35 315 | 98.03 143 | 94.24 334 | 98.33 112 | 97.40 261 | 94.98 338 | 79.84 331 | 99.68 242 | 83.94 344 | 98.22 292 | 96.86 327 |
|
CostFormer | | | 93.97 309 | 93.78 302 | 94.51 324 | 97.53 324 | 85.83 340 | 97.98 154 | 95.96 319 | 89.29 337 | 94.99 333 | 98.63 201 | 78.63 339 | 99.62 266 | 94.54 243 | 96.50 334 | 98.09 290 |
|
1111 | | | 93.99 308 | 93.72 304 | 94.80 320 | 99.33 129 | 85.20 343 | 95.97 287 | 99.39 101 | 97.88 141 | 98.64 168 | 98.56 212 | 57.79 363 | 99.80 156 | 96.02 203 | 99.87 69 | 99.40 152 |
|
test0.0.03 1 | | | 94.51 295 | 93.69 305 | 96.99 268 | 96.05 350 | 93.61 286 | 94.97 324 | 93.49 339 | 96.17 238 | 97.57 248 | 94.88 342 | 82.30 321 | 99.01 343 | 93.60 272 | 94.17 350 | 98.37 284 |
|
conf200view11 | | | 94.24 301 | 93.67 306 | 95.94 304 | 99.06 186 | 91.35 315 | 98.03 143 | 94.24 334 | 98.33 112 | 97.40 261 | 94.98 338 | 79.84 331 | 99.62 266 | 83.05 346 | 98.08 307 | 96.86 327 |
|
thres100view900 | | | 94.19 302 | 93.67 306 | 95.75 309 | 99.06 186 | 91.35 315 | 98.03 143 | 94.24 334 | 98.33 112 | 97.40 261 | 94.98 338 | 79.84 331 | 99.62 266 | 83.05 346 | 98.08 307 | 96.29 335 |
|
dp | | | 93.47 314 | 93.59 308 | 93.13 339 | 96.64 343 | 81.62 356 | 97.66 184 | 96.42 316 | 92.80 304 | 96.11 308 | 98.64 197 | 78.55 340 | 99.59 277 | 93.31 279 | 92.18 354 | 98.16 287 |
|
tfpn_ndepth | | | 94.12 305 | 93.51 309 | 95.94 304 | 98.86 227 | 93.60 287 | 98.16 128 | 91.90 353 | 94.66 277 | 97.41 260 | 95.24 333 | 76.24 350 | 99.73 221 | 91.21 314 | 97.88 314 | 94.50 351 |
|
tfpn200view9 | | | 94.03 307 | 93.44 310 | 95.78 308 | 98.93 212 | 91.44 309 | 97.60 194 | 94.29 332 | 97.94 129 | 97.10 272 | 94.31 347 | 79.67 335 | 99.62 266 | 83.05 346 | 98.08 307 | 96.29 335 |
|
thres400 | | | 94.14 304 | 93.44 310 | 96.24 295 | 98.93 212 | 91.44 309 | 97.60 194 | 94.29 332 | 97.94 129 | 97.10 272 | 94.31 347 | 79.67 335 | 99.62 266 | 83.05 346 | 98.08 307 | 97.66 307 |
|
EPMVS | | | 93.72 312 | 93.27 312 | 95.09 318 | 96.04 351 | 87.76 332 | 98.13 129 | 85.01 358 | 94.69 276 | 96.92 280 | 98.64 197 | 78.47 341 | 99.31 327 | 95.04 231 | 96.46 335 | 98.20 286 |
|
thres200 | | | 93.72 312 | 93.14 313 | 95.46 314 | 98.66 267 | 91.29 319 | 96.61 261 | 94.63 326 | 97.39 180 | 96.83 288 | 93.71 350 | 79.88 330 | 99.56 287 | 82.40 350 | 98.13 298 | 95.54 345 |
|
tpm cat1 | | | 93.29 316 | 93.13 314 | 93.75 332 | 97.39 331 | 84.74 346 | 97.39 210 | 97.65 291 | 83.39 351 | 94.16 339 | 98.41 225 | 82.86 320 | 99.39 318 | 91.56 307 | 95.35 343 | 97.14 323 |
|
PCF-MVS | | 92.86 18 | 94.36 297 | 93.00 315 | 98.42 193 | 98.70 254 | 97.56 154 | 93.16 345 | 99.11 192 | 79.59 353 | 97.55 249 | 97.43 287 | 92.19 270 | 99.73 221 | 79.85 353 | 99.45 201 | 97.97 293 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
X-MVStestdata | | | 94.32 299 | 92.59 316 | 99.53 32 | 99.46 104 | 99.21 22 | 98.65 79 | 99.34 122 | 98.62 98 | 97.54 250 | 45.85 356 | 97.50 96 | 99.83 119 | 96.79 156 | 99.53 190 | 99.56 76 |
|
tpm2 | | | 93.09 318 | 92.58 317 | 94.62 322 | 97.56 322 | 86.53 337 | 97.66 184 | 95.79 321 | 86.15 346 | 94.07 342 | 98.23 241 | 75.95 351 | 99.53 293 | 90.91 319 | 96.86 332 | 97.81 300 |
|
tpmp4_e23 | | | 92.91 319 | 92.45 318 | 94.29 326 | 97.41 329 | 85.62 342 | 97.95 157 | 96.77 310 | 87.55 344 | 91.33 351 | 98.57 209 | 74.21 353 | 99.59 277 | 91.62 305 | 96.64 333 | 97.65 314 |
|
PNet_i23d | | | 91.80 327 | 92.35 319 | 90.14 342 | 98.65 268 | 73.10 361 | 89.22 354 | 99.02 210 | 95.23 267 | 97.87 216 | 97.82 265 | 78.45 342 | 98.89 347 | 88.73 328 | 86.14 355 | 98.42 280 |
|
FPMVS | | | 93.44 315 | 92.23 320 | 97.08 263 | 99.25 138 | 97.86 132 | 95.61 308 | 97.16 298 | 92.90 302 | 93.76 345 | 98.65 194 | 75.94 352 | 95.66 355 | 79.30 354 | 97.49 318 | 97.73 305 |
|
MVS | | | 93.19 317 | 92.09 321 | 96.50 286 | 96.91 339 | 94.03 272 | 98.07 137 | 98.06 281 | 68.01 354 | 94.56 336 | 96.48 308 | 95.96 194 | 99.30 329 | 83.84 345 | 96.89 331 | 96.17 337 |
|
DWT-MVSNet_test | | | 92.75 320 | 92.05 322 | 94.85 319 | 96.48 346 | 87.21 335 | 97.83 169 | 94.99 323 | 92.22 312 | 92.72 347 | 94.11 349 | 70.75 354 | 99.46 310 | 95.01 232 | 94.33 349 | 97.87 296 |
|
MVE | | 83.40 22 | 92.50 321 | 91.92 323 | 94.25 327 | 98.83 235 | 91.64 306 | 92.71 346 | 83.52 359 | 95.92 248 | 86.46 357 | 95.46 330 | 95.20 216 | 95.40 356 | 80.51 352 | 98.64 276 | 95.73 344 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
TESTMET0.1,1 | | | 92.19 325 | 91.77 324 | 93.46 335 | 96.48 346 | 82.80 354 | 94.05 337 | 91.52 354 | 94.45 282 | 94.00 343 | 94.88 342 | 66.65 359 | 99.56 287 | 95.78 217 | 98.11 299 | 98.02 292 |
|
test-mter | | | 92.33 323 | 91.76 325 | 94.04 328 | 96.53 344 | 84.62 347 | 94.05 337 | 92.39 349 | 94.00 292 | 94.12 340 | 95.07 334 | 65.63 362 | 99.67 248 | 95.87 212 | 98.18 294 | 97.82 298 |
|
gg-mvs-nofinetune | | | 92.37 322 | 91.20 326 | 95.85 307 | 95.80 353 | 92.38 299 | 99.31 21 | 81.84 360 | 99.75 4 | 91.83 349 | 99.74 8 | 68.29 356 | 99.02 341 | 87.15 333 | 97.12 327 | 96.16 338 |
|
IB-MVS | | 91.63 19 | 92.24 324 | 90.90 327 | 96.27 290 | 97.22 335 | 91.24 320 | 94.36 335 | 93.33 341 | 92.37 309 | 92.24 348 | 94.58 346 | 66.20 360 | 99.89 56 | 93.16 281 | 94.63 346 | 97.66 307 |
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 |
PAPM | | | 91.88 326 | 90.34 328 | 96.51 285 | 98.06 305 | 92.56 295 | 92.44 348 | 97.17 297 | 86.35 345 | 90.38 353 | 96.01 314 | 86.61 293 | 99.21 334 | 70.65 356 | 95.43 342 | 97.75 304 |
|
PVSNet_0 | | 89.98 21 | 91.15 329 | 90.30 329 | 93.70 333 | 97.72 315 | 84.34 350 | 90.24 351 | 97.42 292 | 90.20 332 | 93.79 344 | 93.09 353 | 90.90 277 | 98.89 347 | 86.57 335 | 72.76 356 | 97.87 296 |
|
testpf | | | 89.08 330 | 90.27 330 | 85.50 343 | 94.03 357 | 82.85 353 | 96.87 245 | 91.09 355 | 91.61 318 | 90.96 352 | 94.86 345 | 66.15 361 | 95.83 354 | 94.58 242 | 92.27 353 | 77.82 355 |
|
test2356 | | | 91.64 328 | 90.19 331 | 96.00 302 | 94.30 356 | 89.58 326 | 90.84 350 | 96.68 311 | 91.76 314 | 95.48 327 | 93.69 351 | 67.05 358 | 99.52 297 | 84.83 342 | 97.08 328 | 98.91 243 |
|
.test1245 | | | 79.71 331 | 84.30 332 | 65.96 345 | 99.33 129 | 85.20 343 | 95.97 287 | 99.39 101 | 97.88 141 | 98.64 168 | 98.56 212 | 57.79 363 | 99.80 156 | 96.02 203 | 15.07 357 | 12.86 358 |
|
tmp_tt | | | 78.77 332 | 78.73 333 | 78.90 344 | 58.45 360 | 74.76 360 | 94.20 336 | 78.26 362 | 39.16 356 | 86.71 356 | 92.82 354 | 80.50 325 | 75.19 359 | 86.16 336 | 92.29 352 | 86.74 354 |
|
pcd1.5k->3k | | | 41.59 333 | 44.35 334 | 33.30 346 | 99.87 12 | 0.00 364 | 0.00 355 | 99.58 36 | 0.00 359 | 0.00 360 | 0.00 361 | 99.70 2 | 0.00 362 | 0.00 359 | 99.99 11 | 99.91 2 |
|
cdsmvs_eth3d_5k | | | 24.66 334 | 32.88 335 | 0.00 349 | 0.00 363 | 0.00 364 | 0.00 355 | 99.10 193 | 0.00 359 | 0.00 360 | 97.58 276 | 99.21 11 | 0.00 362 | 0.00 359 | 0.00 360 | 0.00 360 |
|
testmvs | | | 17.12 335 | 20.53 336 | 6.87 348 | 12.05 361 | 4.20 363 | 93.62 342 | 6.73 363 | 4.62 358 | 10.41 358 | 24.33 357 | 8.28 366 | 3.56 361 | 9.69 358 | 15.07 357 | 12.86 358 |
|
test123 | | | 17.04 336 | 20.11 337 | 7.82 347 | 10.25 362 | 4.91 362 | 94.80 327 | 4.47 364 | 4.93 357 | 10.00 359 | 24.28 358 | 9.69 365 | 3.64 360 | 10.14 357 | 12.43 359 | 14.92 357 |
|
pcd_1.5k_mvsjas | | | 8.17 337 | 10.90 338 | 0.00 349 | 0.00 363 | 0.00 364 | 0.00 355 | 0.00 365 | 0.00 359 | 0.00 360 | 0.00 361 | 98.07 61 | 0.00 362 | 0.00 359 | 0.00 360 | 0.00 360 |
|
ab-mvs-re | | | 8.12 338 | 10.83 339 | 0.00 349 | 0.00 363 | 0.00 364 | 0.00 355 | 0.00 365 | 0.00 359 | 0.00 360 | 97.48 283 | 0.00 367 | 0.00 362 | 0.00 359 | 0.00 360 | 0.00 360 |
|
sosnet-low-res | | | 0.00 339 | 0.00 340 | 0.00 349 | 0.00 363 | 0.00 364 | 0.00 355 | 0.00 365 | 0.00 359 | 0.00 360 | 0.00 361 | 0.00 367 | 0.00 362 | 0.00 359 | 0.00 360 | 0.00 360 |
|
sosnet | | | 0.00 339 | 0.00 340 | 0.00 349 | 0.00 363 | 0.00 364 | 0.00 355 | 0.00 365 | 0.00 359 | 0.00 360 | 0.00 361 | 0.00 367 | 0.00 362 | 0.00 359 | 0.00 360 | 0.00 360 |
|
uncertanet | | | 0.00 339 | 0.00 340 | 0.00 349 | 0.00 363 | 0.00 364 | 0.00 355 | 0.00 365 | 0.00 359 | 0.00 360 | 0.00 361 | 0.00 367 | 0.00 362 | 0.00 359 | 0.00 360 | 0.00 360 |
|
Regformer | | | 0.00 339 | 0.00 340 | 0.00 349 | 0.00 363 | 0.00 364 | 0.00 355 | 0.00 365 | 0.00 359 | 0.00 360 | 0.00 361 | 0.00 367 | 0.00 362 | 0.00 359 | 0.00 360 | 0.00 360 |
|
uanet | | | 0.00 339 | 0.00 340 | 0.00 349 | 0.00 363 | 0.00 364 | 0.00 355 | 0.00 365 | 0.00 359 | 0.00 360 | 0.00 361 | 0.00 367 | 0.00 362 | 0.00 359 | 0.00 360 | 0.00 360 |
|
GSMVS | | | | | | | | | | | | | | | | | 98.81 253 |
|
test_part3 | | | | | | | | 97.25 218 | | 96.66 221 | | 98.71 183 | | 99.86 78 | 93.00 283 | | |
|
test_part2 | | | | | | 99.36 122 | 99.10 43 | | | | 99.05 116 | | | | | | |
|
test_part1 | | | | | | | | | 99.28 143 | | | | 97.56 91 | | | 99.57 176 | 99.53 92 |
|
sam_mvs1 | | | | | | | | | | | | | 84.74 307 | | | | 98.81 253 |
|
sam_mvs | | | | | | | | | | | | | 84.29 313 | | | | |
|
semantic-postprocess | | | | | 96.87 273 | 99.27 135 | 91.16 322 | | 99.25 154 | 99.10 66 | 99.41 59 | 99.35 69 | 92.91 263 | 99.96 8 | 98.65 67 | 99.94 33 | 99.49 112 |
|
ambc | | | | | 98.24 211 | 98.82 238 | 95.97 220 | 98.62 82 | 99.00 217 | | 99.27 83 | 99.21 88 | 96.99 135 | 99.50 303 | 96.55 178 | 99.50 198 | 99.26 193 |
|
MTGPA | | | | | | | | | 99.20 165 | | | | | | | | |
|
test_post1 | | | | | | | | 97.59 196 | | | | 20.48 360 | 83.07 319 | 99.66 256 | 94.16 253 | | |
|
test_post | | | | | | | | | | | | 21.25 359 | 83.86 315 | 99.70 233 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 98.77 177 | 84.37 310 | 99.85 89 | | | |
|
GG-mvs-BLEND | | | | | 94.76 321 | 94.54 355 | 92.13 302 | 99.31 21 | 80.47 361 | | 88.73 355 | 91.01 355 | 67.59 357 | 98.16 353 | 82.30 351 | 94.53 347 | 93.98 352 |
|
MTMP | | | | | | | | | 91.91 352 | | | | | | | | |
|
gm-plane-assit | | | | | | 94.83 354 | 81.97 355 | | | 88.07 341 | | 94.99 337 | | 99.60 273 | 91.76 301 | | |
|
test9_res | | | | | | | | | | | | | | | 93.28 280 | 99.15 241 | 99.38 159 |
|
TEST9 | | | | | | 98.71 250 | 98.08 109 | 95.96 291 | 99.03 206 | 91.40 322 | 95.85 314 | 97.53 278 | 96.52 167 | 99.76 201 | | | |
|
test_8 | | | | | | 98.67 262 | 98.01 115 | 95.91 297 | 99.02 210 | 91.64 316 | 95.79 316 | 97.50 281 | 96.47 170 | 99.76 201 | | | |
|
agg_prior2 | | | | | | | | | | | | | | | 92.50 295 | 99.16 238 | 99.37 160 |
|
agg_prior | | | | | | 98.68 259 | 97.99 116 | | 99.01 213 | | 95.59 318 | | | 99.77 196 | | | |
|
TestCases | | | | | 99.16 86 | 99.50 87 | 98.55 78 | | 99.58 36 | 96.80 213 | 98.88 145 | 99.06 119 | 97.65 85 | 99.57 284 | 94.45 246 | 99.61 163 | 99.37 160 |
|
test_prior4 | | | | | | | 97.97 121 | 95.86 298 | | | | | | | | | |
|
test_prior2 | | | | | | | | 95.74 304 | | 96.48 227 | 96.11 308 | 97.63 274 | 95.92 196 | | 94.16 253 | 99.20 231 | |
|
test_prior | | | | | 98.95 117 | 98.69 257 | 97.95 124 | | 99.03 206 | | | | | 99.59 277 | | | 99.30 185 |
|
旧先验2 | | | | | | | | 95.76 302 | | 88.56 340 | 97.52 252 | | | 99.66 256 | 94.48 244 | | |
|
新几何2 | | | | | | | | 95.93 295 | | | | | | | | | |
|
新几何1 | | | | | 98.91 123 | 98.94 210 | 97.76 142 | | 98.76 249 | 87.58 343 | 96.75 291 | 98.10 250 | 94.80 230 | 99.78 186 | 92.73 292 | 99.00 257 | 99.20 205 |
|
旧先验1 | | | | | | 98.82 238 | 97.45 160 | | 98.76 249 | | | 98.34 231 | 95.50 210 | | | 99.01 256 | 99.23 199 |
|
无先验 | | | | | | | | 95.74 304 | 98.74 254 | 89.38 336 | | | | 99.73 221 | 92.38 297 | | 99.22 203 |
|
原ACMM2 | | | | | | | | 95.53 311 | | | | | | | | | |
|
原ACMM1 | | | | | 98.35 202 | 98.90 220 | 96.25 211 | | 98.83 243 | 92.48 307 | 96.07 311 | 98.10 250 | 95.39 213 | 99.71 231 | 92.61 294 | 98.99 258 | 99.08 221 |
|
test222 | | | | | | 98.92 216 | 96.93 183 | 95.54 310 | 98.78 248 | 85.72 347 | 96.86 287 | 98.11 249 | 94.43 238 | | | 99.10 249 | 99.23 199 |
|
testdata2 | | | | | | | | | | | | | | 99.79 176 | 92.80 290 | | |
|
segment_acmp | | | | | | | | | | | | | 97.02 133 | | | | |
|
testdata | | | | | 98.09 218 | 98.93 212 | 95.40 240 | | 98.80 246 | 90.08 333 | 97.45 257 | 98.37 228 | 95.26 215 | 99.70 233 | 93.58 273 | 98.95 262 | 99.17 215 |
|
testdata1 | | | | | | | | 95.44 315 | | 96.32 233 | | | | | | | |
|
test12 | | | | | 98.93 120 | 98.58 273 | 97.83 134 | | 98.66 259 | | 96.53 297 | | 95.51 209 | 99.69 237 | | 99.13 245 | 99.27 190 |
|
plane_prior7 | | | | | | 99.19 161 | 97.87 131 | | | | | | | | | | |
|
plane_prior6 | | | | | | 98.99 203 | 97.70 148 | | | | | | 94.90 222 | | | | |
|
plane_prior5 | | | | | | | | | 99.27 148 | | | | | 99.70 233 | 94.42 248 | 99.51 193 | 99.45 134 |
|
plane_prior4 | | | | | | | | | | | | 97.98 258 | | | | | |
|
plane_prior3 | | | | | | | 97.78 141 | | | 97.41 178 | 97.79 233 | | | | | | |
|
plane_prior2 | | | | | | | | 97.77 173 | | 98.20 122 | | | | | | | |
|
plane_prior1 | | | | | | 99.05 191 | | | | | | | | | | | |
|
plane_prior | | | | | | | 97.65 150 | 97.07 233 | | 96.72 216 | | | | | | 99.36 208 | |
|
n2 | | | | | | | | | 0.00 365 | | | | | | | | |
|
nn | | | | | | | | | 0.00 365 | | | | | | | | |
|
door-mid | | | | | | | | | 99.57 43 | | | | | | | | |
|
lessismore_v0 | | | | | 98.97 115 | 99.73 29 | 97.53 156 | | 86.71 357 | | 99.37 65 | 99.52 46 | 89.93 280 | 99.92 34 | 98.99 52 | 99.72 125 | 99.44 136 |
|
LGP-MVS_train | | | | | 99.47 49 | 99.57 63 | 98.97 51 | | 99.48 74 | 96.60 224 | 99.10 108 | 99.06 119 | 98.71 27 | 99.83 119 | 95.58 226 | 99.78 102 | 99.62 46 |
|
test11 | | | | | | | | | 98.87 232 | | | | | | | | |
|
door | | | | | | | | | 99.41 98 | | | | | | | | |
|
HQP5-MVS | | | | | | | 96.79 186 | | | | | | | | | | |
|
HQP-NCC | | | | | | 98.67 262 | | 96.29 275 | | 96.05 244 | 95.55 322 | | | | | | |
|
ACMP_Plane | | | | | | 98.67 262 | | 96.29 275 | | 96.05 244 | 95.55 322 | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 92.82 288 | | |
|
HQP4-MVS | | | | | | | | | | | 95.56 321 | | | 99.54 291 | | | 99.32 178 |
|
HQP3-MVS | | | | | | | | | 99.04 204 | | | | | | | 99.26 225 | |
|
HQP2-MVS | | | | | | | | | | | | | 93.84 249 | | | | |
|
NP-MVS | | | | | | 98.84 233 | 97.39 163 | | | | | 96.84 301 | | | | | |
|
MDTV_nov1_ep13_2view | | | | | | | 74.92 359 | 97.69 181 | | 90.06 334 | 97.75 236 | | 85.78 300 | | 93.52 274 | | 98.69 267 |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 99.77 106 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 99.68 144 | |
|
Test By Simon | | | | | | | | | | | | | 96.52 167 | | | | |
|
ITE_SJBPF | | | | | 98.87 128 | 99.22 145 | 98.48 85 | | 99.35 118 | 97.50 167 | 98.28 197 | 98.60 206 | 97.64 88 | 99.35 322 | 93.86 265 | 99.27 223 | 98.79 257 |
|
DeepMVS_CX | | | | | 93.44 336 | 98.24 296 | 94.21 268 | | 94.34 331 | 64.28 355 | 91.34 350 | 94.87 344 | 89.45 285 | 92.77 358 | 77.54 355 | 93.14 351 | 93.35 353 |
|