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