LTVRE_ROB | | 95.06 1 | 97.73 1 | 98.39 2 | 96.95 1 | 96.33 48 | 96.94 32 | 98.30 22 | 94.90 15 | 98.61 2 | 97.73 3 | 97.97 32 | 98.57 28 | 95.74 7 | 99.24 1 | 98.70 4 | 98.72 7 | 98.70 1 |
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 |
COLMAP_ROB | | 93.74 2 | 97.09 8 | 97.98 5 | 96.05 18 | 95.97 58 | 97.78 9 | 98.56 12 | 91.72 73 | 97.53 7 | 96.01 17 | 98.14 26 | 98.76 19 | 95.28 8 | 98.76 11 | 98.23 11 | 98.77 5 | 96.67 36 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
3Dnovator+ | | 92.82 3 | 95.22 50 | 95.16 61 | 95.29 35 | 96.17 52 | 96.55 38 | 97.64 44 | 94.02 31 | 94.16 39 | 94.29 49 | 92.09 140 | 93.71 149 | 91.90 56 | 96.68 62 | 96.51 45 | 97.70 47 | 96.40 39 |
|
DeepC-MVS | | 92.47 4 | 96.44 16 | 96.75 22 | 96.08 17 | 97.57 7 | 97.19 28 | 97.96 34 | 94.28 24 | 95.29 21 | 94.92 37 | 98.31 22 | 96.92 85 | 93.69 29 | 96.81 59 | 96.50 46 | 98.06 38 | 96.27 42 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
3Dnovator | | 91.81 5 | 93.36 98 | 94.27 86 | 92.29 113 | 92.99 151 | 95.03 87 | 95.76 103 | 87.79 158 | 93.82 44 | 92.38 95 | 92.19 139 | 93.37 153 | 88.14 123 | 95.26 90 | 94.85 85 | 96.69 74 | 95.40 56 |
|
DeepC-MVS_fast | | 91.38 6 | 94.73 58 | 94.98 63 | 94.44 51 | 96.83 34 | 96.12 52 | 96.69 69 | 92.17 60 | 92.98 57 | 93.72 64 | 94.14 118 | 95.45 121 | 90.49 103 | 95.73 79 | 95.30 73 | 96.71 73 | 95.13 63 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
DeepPCF-MVS | | 90.68 7 | 94.56 61 | 94.92 65 | 94.15 58 | 94.11 103 | 95.71 64 | 97.03 51 | 90.65 95 | 93.39 51 | 94.08 54 | 95.29 96 | 94.15 143 | 93.21 37 | 95.22 91 | 94.92 84 | 95.82 115 | 95.75 52 |
|
ACMH | | 90.17 8 | 96.61 11 | 97.69 11 | 95.35 31 | 95.29 75 | 96.94 32 | 98.43 16 | 92.05 65 | 98.04 5 | 95.38 22 | 98.07 29 | 99.25 7 | 93.23 36 | 98.35 16 | 97.16 36 | 97.72 45 | 96.00 46 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
ACMM | | 90.06 9 | 96.31 19 | 96.42 31 | 96.19 15 | 97.21 19 | 97.16 30 | 98.71 5 | 93.79 36 | 94.35 35 | 93.81 61 | 92.80 133 | 98.23 44 | 95.11 9 | 98.07 23 | 97.45 25 | 98.51 18 | 96.86 30 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
ACMH+ | | 89.90 10 | 96.27 20 | 97.52 12 | 94.81 47 | 95.19 77 | 97.18 29 | 97.97 33 | 92.52 49 | 96.72 9 | 90.50 131 | 97.31 59 | 99.11 9 | 94.10 23 | 98.67 12 | 97.90 15 | 98.56 16 | 95.79 50 |
|
ACMP | | 89.62 11 | 95.96 32 | 96.28 37 | 95.59 24 | 96.58 42 | 97.23 27 | 98.26 24 | 93.22 44 | 92.33 70 | 92.31 97 | 94.29 117 | 98.73 21 | 94.68 15 | 98.04 24 | 97.14 37 | 98.47 21 | 96.17 44 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
OpenMVS | | 89.22 12 | 91.09 137 | 91.42 141 | 90.71 130 | 92.79 157 | 93.61 134 | 92.74 167 | 85.47 187 | 86.10 168 | 90.73 124 | 85.71 197 | 93.07 156 | 86.69 131 | 94.07 120 | 93.34 118 | 95.86 111 | 94.02 81 |
|
TAPA-MVS | | 88.94 13 | 93.78 84 | 94.31 84 | 93.18 99 | 94.14 101 | 95.99 57 | 95.74 104 | 86.98 171 | 93.43 49 | 93.88 60 | 90.16 159 | 96.88 87 | 91.05 86 | 94.33 108 | 93.95 105 | 97.28 57 | 95.40 56 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
PCF-MVS | | 87.46 14 | 92.44 122 | 91.80 136 | 93.19 98 | 94.66 86 | 95.80 62 | 96.37 92 | 90.19 100 | 87.57 153 | 92.23 98 | 89.26 166 | 93.97 145 | 89.24 111 | 91.32 168 | 90.82 164 | 96.46 80 | 93.86 84 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
PLC | | 87.27 15 | 93.08 107 | 92.92 123 | 93.26 94 | 94.67 85 | 95.03 87 | 94.38 129 | 90.10 101 | 91.69 84 | 92.14 99 | 87.24 185 | 93.91 146 | 91.61 65 | 95.05 95 | 94.73 95 | 96.67 75 | 92.80 103 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
PMVS | | 87.16 16 | 95.88 36 | 96.47 30 | 95.19 38 | 97.00 26 | 96.02 55 | 96.70 67 | 91.57 77 | 94.43 33 | 95.33 23 | 97.16 63 | 95.37 123 | 92.39 50 | 98.89 10 | 98.72 3 | 98.17 33 | 94.71 69 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
IB-MVS | | 86.01 17 | 88.24 168 | 87.63 177 | 88.94 157 | 92.03 177 | 91.77 163 | 92.40 172 | 85.58 186 | 78.24 215 | 84.85 169 | 71.99 231 | 93.45 151 | 83.96 146 | 93.48 128 | 92.33 128 | 94.84 144 | 92.15 120 |
Christian Sormann, Mattia Rossi, Andreas Kuhn and Friedrich Fraundorfer: IB-MVS: An Iterative Algorithm for Deep Multi-View Stereo based on Binary Decisions. BMVC 2021 |
CMPMVS | | 66.55 18 | 85.55 187 | 87.46 180 | 83.32 203 | 84.99 221 | 81.97 210 | 79.19 232 | 75.93 219 | 79.32 208 | 88.82 145 | 85.09 198 | 91.07 163 | 82.12 159 | 92.56 144 | 89.63 174 | 88.84 194 | 92.56 111 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
MVE | | 60.41 19 | 73.21 227 | 80.84 208 | 64.30 230 | 56.34 236 | 57.24 237 | 75.28 236 | 72.76 223 | 87.14 161 | 41.39 238 | 86.31 193 | 85.30 186 | 80.66 171 | 86.17 205 | 83.36 200 | 59.35 235 | 80.38 201 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
SMA-MVS | | | 96.11 27 | 96.61 26 | 95.53 28 | 97.49 11 | 97.41 20 | 97.62 46 | 93.78 37 | 94.14 40 | 94.18 51 | 97.16 63 | 94.67 137 | 92.42 49 | 97.74 39 | 97.33 33 | 97.70 47 | 97.79 4 |
|
tfpn111 | | | 87.59 178 | 86.89 181 | 88.41 166 | 92.28 167 | 93.64 131 | 93.36 149 | 88.12 150 | 80.90 193 | 80.71 193 | 73.93 228 | 82.25 189 | 79.65 178 | 94.27 112 | 94.76 90 | 96.36 83 | 88.48 163 |
|
conf0.01 | | | 85.72 186 | 83.49 197 | 88.32 169 | 92.11 174 | 93.35 140 | 93.36 149 | 88.02 154 | 80.90 193 | 80.51 196 | 74.83 226 | 59.86 231 | 79.65 178 | 93.80 122 | 94.76 90 | 96.29 92 | 86.94 176 |
|
conf0.002 | | | 84.82 189 | 81.84 203 | 88.30 170 | 92.05 176 | 93.28 142 | 93.36 149 | 88.00 157 | 80.90 193 | 80.48 197 | 73.43 230 | 52.48 236 | 79.65 178 | 93.72 123 | 92.82 124 | 96.28 93 | 86.22 180 |
|
thresconf0.02 | | | 84.34 193 | 82.02 202 | 87.06 182 | 92.23 171 | 90.93 170 | 91.05 189 | 86.43 179 | 88.83 140 | 77.65 211 | 73.93 228 | 55.81 232 | 79.68 177 | 90.62 173 | 90.28 167 | 95.30 123 | 83.73 188 |
|
tfpn_n400 | | | 89.03 155 | 89.39 156 | 88.61 162 | 93.98 108 | 92.33 154 | 91.83 177 | 88.97 136 | 92.97 58 | 78.90 201 | 84.93 199 | 78.24 206 | 81.77 166 | 95.00 96 | 93.67 110 | 96.22 99 | 88.59 161 |
|
tfpnconf | | | 89.03 155 | 89.39 156 | 88.61 162 | 93.98 108 | 92.33 154 | 91.83 177 | 88.97 136 | 92.97 58 | 78.90 201 | 84.93 199 | 78.24 206 | 81.77 166 | 95.00 96 | 93.67 110 | 96.22 99 | 88.59 161 |
|
tfpnview11 | | | 88.74 160 | 88.95 161 | 88.50 164 | 93.91 115 | 92.43 153 | 91.70 183 | 88.90 141 | 90.93 108 | 78.90 201 | 84.93 199 | 78.24 206 | 81.71 168 | 94.32 110 | 94.60 97 | 95.86 111 | 87.23 174 |
|
tfpn1000 | | | 88.13 172 | 88.68 168 | 87.49 180 | 93.94 113 | 92.64 150 | 91.50 185 | 88.70 145 | 90.12 117 | 74.35 216 | 86.74 191 | 75.27 212 | 80.14 174 | 94.16 118 | 94.66 96 | 96.33 90 | 87.16 175 |
|
tfpn_ndepth | | | 85.89 185 | 86.40 185 | 85.30 195 | 91.31 183 | 92.47 152 | 90.78 192 | 87.75 160 | 84.79 175 | 71.04 223 | 76.95 223 | 78.80 205 | 74.52 208 | 92.72 137 | 93.43 116 | 96.39 81 | 85.65 183 |
|
conf200view11 | | | 87.93 174 | 87.51 178 | 88.41 166 | 92.28 167 | 93.64 131 | 93.36 149 | 88.12 150 | 80.90 193 | 80.71 193 | 78.25 219 | 82.25 189 | 79.65 178 | 94.27 112 | 94.76 90 | 96.36 83 | 88.48 163 |
|
thres100view900 | | | 86.46 183 | 86.00 188 | 86.99 184 | 92.28 167 | 91.03 169 | 91.09 188 | 84.49 195 | 80.90 193 | 80.89 191 | 78.25 219 | 82.25 189 | 77.57 196 | 90.17 176 | 92.84 123 | 95.63 117 | 86.57 179 |
|
tfpnnormal | | | 92.45 121 | 94.77 71 | 89.74 146 | 93.95 111 | 93.44 139 | 93.25 156 | 88.49 147 | 95.27 23 | 83.20 178 | 96.51 73 | 96.23 105 | 83.17 150 | 95.47 81 | 94.52 100 | 96.38 82 | 91.97 124 |
|
tfpn200view9 | | | 87.94 173 | 87.51 178 | 88.44 165 | 92.28 167 | 93.63 133 | 93.35 153 | 88.11 152 | 80.90 193 | 80.89 191 | 78.25 219 | 82.25 189 | 79.65 178 | 94.27 112 | 94.76 90 | 96.36 83 | 88.48 163 |
|
view600 | | | 89.09 154 | 88.78 166 | 89.46 153 | 93.59 130 | 93.33 141 | 93.92 141 | 87.76 159 | 87.40 154 | 82.79 180 | 81.29 213 | 80.71 199 | 82.59 157 | 94.28 111 | 95.72 65 | 96.12 105 | 88.70 160 |
|
view800 | | | 89.42 150 | 89.11 159 | 89.78 144 | 94.00 104 | 93.71 128 | 93.96 139 | 88.47 148 | 88.10 146 | 82.91 179 | 82.61 211 | 79.85 202 | 83.10 151 | 94.92 98 | 95.38 71 | 96.26 97 | 89.19 153 |
|
conf0.05thres1000 | | | 91.24 136 | 91.85 135 | 90.53 132 | 94.59 91 | 94.56 106 | 94.33 133 | 89.52 123 | 93.67 45 | 83.77 176 | 91.04 146 | 79.10 204 | 83.98 144 | 96.66 64 | 95.56 69 | 96.98 70 | 92.36 116 |
|
tfpn | | | 87.65 177 | 85.66 189 | 89.96 142 | 94.36 95 | 93.94 124 | 93.85 142 | 89.02 134 | 88.71 141 | 82.78 181 | 83.79 206 | 53.79 233 | 83.43 149 | 95.35 84 | 94.54 99 | 96.35 87 | 89.51 151 |
|
ESAPD | | | 95.63 42 | 96.35 33 | 94.80 49 | 96.76 35 | 97.29 24 | 97.74 42 | 94.15 28 | 91.69 84 | 90.01 137 | 96.65 71 | 97.29 76 | 92.45 48 | 97.41 42 | 97.18 34 | 97.67 50 | 96.95 25 |
|
CHOSEN 280x420 | | | 79.24 213 | 78.26 217 | 80.38 209 | 79.60 228 | 68.80 235 | 89.32 206 | 75.38 220 | 77.25 219 | 78.02 210 | 75.57 225 | 76.17 211 | 81.19 170 | 88.61 189 | 81.39 206 | 78.79 224 | 80.03 204 |
|
CANet | | | 93.07 108 | 93.05 122 | 93.10 103 | 95.90 61 | 95.41 74 | 95.88 100 | 91.94 68 | 84.77 176 | 93.36 71 | 94.05 120 | 95.25 130 | 86.25 134 | 94.33 108 | 93.94 106 | 95.30 123 | 93.58 88 |
|
Fast-Effi-MVS+-dtu | | | 89.57 149 | 88.42 171 | 90.92 128 | 93.35 139 | 91.57 165 | 93.01 160 | 95.71 9 | 78.94 213 | 87.65 154 | 84.68 202 | 93.14 155 | 82.00 160 | 90.84 171 | 91.01 162 | 93.78 170 | 88.77 159 |
|
Effi-MVS+-dtu | | | 92.32 127 | 91.66 138 | 93.09 104 | 95.13 79 | 94.73 98 | 94.57 128 | 92.14 61 | 81.74 189 | 90.33 133 | 88.13 176 | 95.91 114 | 89.24 111 | 94.23 117 | 93.65 113 | 97.12 62 | 93.23 94 |
|
CANet_DTU | | | 88.95 158 | 89.51 155 | 88.29 171 | 93.12 148 | 91.22 168 | 93.61 144 | 83.47 202 | 80.07 204 | 90.71 128 | 89.19 167 | 93.68 150 | 76.27 204 | 91.44 167 | 91.17 161 | 92.59 181 | 89.83 145 |
|
MVS_0304 | | | 93.92 75 | 93.81 97 | 94.05 62 | 96.06 56 | 96.00 56 | 96.43 82 | 92.76 47 | 85.99 169 | 94.43 46 | 94.04 121 | 97.08 80 | 88.12 124 | 94.65 104 | 94.20 104 | 96.47 78 | 94.71 69 |
|
HSP-MVS | | | 95.04 53 | 95.45 57 | 94.57 50 | 96.87 28 | 97.77 10 | 98.71 5 | 93.88 34 | 91.21 102 | 91.48 113 | 95.36 93 | 98.37 38 | 90.73 94 | 94.37 107 | 92.98 121 | 95.77 116 | 98.08 3 |
|
TSAR-MVS + MP. | | | 95.99 31 | 96.57 28 | 95.31 33 | 96.87 28 | 96.50 43 | 98.71 5 | 91.58 76 | 93.25 52 | 92.71 86 | 96.86 69 | 96.57 96 | 93.92 24 | 98.09 21 | 97.91 14 | 98.08 36 | 96.81 32 |
|
OPM-MVS | | | 95.96 32 | 96.59 27 | 95.23 36 | 96.67 39 | 96.52 42 | 97.86 37 | 93.28 43 | 95.27 23 | 93.46 70 | 96.26 76 | 98.85 17 | 92.89 43 | 97.09 48 | 96.37 49 | 97.22 61 | 95.78 51 |
|
ACMMP_Plus | | | 95.86 37 | 96.18 39 | 95.47 30 | 97.11 22 | 97.26 25 | 98.37 21 | 93.48 42 | 93.49 47 | 93.99 56 | 95.61 86 | 94.11 144 | 92.49 47 | 97.87 31 | 97.44 26 | 97.40 53 | 97.52 8 |
|
ambc | | | | 94.61 75 | | 98.09 5 | 95.14 84 | 91.71 182 | | 94.18 38 | 96.46 14 | 96.26 76 | 96.30 102 | 91.26 75 | 94.70 102 | 92.00 140 | 93.45 172 | 93.67 85 |
|
zzz-MVS | | | 96.18 23 | 96.01 44 | 96.38 8 | 98.30 2 | 96.18 50 | 98.51 14 | 94.48 22 | 94.56 29 | 94.81 42 | 91.73 143 | 96.96 83 | 94.30 22 | 98.09 21 | 97.83 16 | 97.91 42 | 96.73 33 |
|
Effi-MVS+ | | | 92.93 110 | 92.16 133 | 93.83 74 | 94.29 96 | 93.53 137 | 95.04 118 | 92.98 46 | 85.27 173 | 94.46 44 | 90.24 158 | 95.34 125 | 89.99 107 | 93.72 123 | 94.23 103 | 96.22 99 | 92.79 104 |
|
new-patchmatchnet | | | 84.45 192 | 88.75 167 | 79.43 212 | 93.28 140 | 81.87 211 | 81.68 229 | 83.48 201 | 94.47 30 | 71.53 222 | 98.33 19 | 97.88 66 | 58.61 225 | 90.35 174 | 77.33 217 | 87.99 196 | 81.05 198 |
|
pmmvs6 | | | 94.58 60 | 97.30 16 | 91.40 124 | 94.84 84 | 94.61 102 | 93.40 148 | 92.43 53 | 98.51 3 | 85.61 166 | 98.73 10 | 99.53 3 | 84.40 143 | 97.88 30 | 97.03 38 | 97.72 45 | 94.79 67 |
|
pmmvs5 | | | 88.63 161 | 89.70 153 | 87.39 181 | 89.24 202 | 90.64 174 | 91.87 176 | 82.13 206 | 83.34 184 | 87.86 153 | 94.58 110 | 96.15 109 | 79.87 175 | 87.33 199 | 89.07 181 | 93.39 174 | 86.76 177 |
|
Fast-Effi-MVS+ | | | 92.93 110 | 92.64 127 | 93.27 93 | 93.81 121 | 93.88 125 | 95.90 99 | 90.61 96 | 83.98 181 | 92.71 86 | 92.81 132 | 96.22 106 | 90.67 96 | 94.90 100 | 93.92 107 | 95.92 110 | 92.77 105 |
|
Anonymous20231211 | | | 96.59 12 | 98.43 1 | 94.44 51 | 95.89 63 | 96.12 52 | 95.23 116 | 95.91 8 | 99.42 1 | 92.75 85 | 98.87 5 | 99.94 1 | 88.19 122 | 98.64 13 | 98.50 5 | 98.66 10 | 97.49 9 |
|
pmmvs-eth3d | | | 92.34 125 | 92.33 129 | 92.34 112 | 92.67 158 | 90.67 173 | 96.37 92 | 89.06 133 | 90.98 107 | 93.60 68 | 97.13 65 | 97.02 82 | 88.29 121 | 90.20 175 | 91.42 156 | 94.07 166 | 88.89 158 |
|
GG-mvs-BLEND | | | 54.28 232 | 77.89 221 | 26.72 234 | 0.37 240 | 83.31 206 | 70.04 237 | 0.39 238 | 74.71 225 | 5.36 241 | 68.78 233 | 83.06 188 | 0.62 238 | 83.73 215 | 78.99 215 | 83.55 216 | 72.68 226 |
|
Anonymous20231206 | | | 87.45 179 | 89.66 154 | 84.87 197 | 94.00 104 | 87.73 189 | 91.36 186 | 86.41 180 | 88.89 138 | 75.03 213 | 92.59 135 | 96.82 89 | 72.48 211 | 89.72 180 | 88.06 184 | 89.93 190 | 83.81 187 |
|
MTAPA | | | | | | | | | | | 94.88 39 | | 96.88 87 | | | | | |
|
MTMP | | | | | | | | | | | 95.43 21 | | 97.25 77 | | | | | |
|
gm-plane-assit | | | 86.15 184 | 82.51 200 | 90.40 134 | 95.81 65 | 92.29 156 | 97.99 31 | 84.66 194 | 92.15 75 | 93.15 79 | 97.84 38 | 44.65 238 | 78.60 185 | 88.02 196 | 85.95 193 | 92.20 182 | 76.69 214 |
|
train_agg | | | 93.89 78 | 93.46 112 | 94.40 54 | 97.35 14 | 93.78 127 | 97.63 45 | 92.19 59 | 88.12 145 | 90.52 130 | 93.57 126 | 95.78 115 | 92.31 52 | 94.78 101 | 93.46 114 | 96.36 83 | 94.70 71 |
|
gg-mvs-nofinetune | | | 88.32 164 | 88.81 164 | 87.75 177 | 93.07 150 | 89.37 180 | 89.06 207 | 95.94 7 | 95.29 21 | 87.15 156 | 97.38 58 | 76.38 210 | 68.05 217 | 91.04 170 | 89.10 180 | 93.24 176 | 83.10 192 |
|
MS-PatchMatch | | | 87.72 176 | 88.62 170 | 86.66 188 | 90.81 192 | 88.18 182 | 90.92 190 | 82.25 205 | 85.86 170 | 80.40 198 | 90.14 160 | 89.29 173 | 84.93 138 | 89.39 184 | 89.12 179 | 90.67 186 | 88.34 167 |
|
Patchmatch-RL test | | | | | | | | 8.96 240 | | | | | | | | | | |
|
tmp_tt | | | | | 28.44 233 | 36.05 237 | 15.86 239 | 21.29 239 | 6.40 235 | 54.52 237 | 51.96 236 | 50.37 236 | 38.68 241 | 9.55 235 | 61.75 235 | 59.66 233 | 45.36 237 | |
|
canonicalmvs | | | 93.38 97 | 94.36 82 | 92.24 114 | 93.94 113 | 96.41 47 | 94.18 136 | 90.47 99 | 93.07 56 | 88.47 149 | 88.66 170 | 93.78 148 | 88.80 115 | 95.74 78 | 95.75 64 | 97.57 51 | 97.13 16 |
|
anonymousdsp | | | 95.45 46 | 96.70 25 | 93.99 66 | 88.43 208 | 92.05 161 | 99.18 1 | 85.42 189 | 94.29 36 | 96.10 16 | 98.63 13 | 99.08 11 | 96.11 1 | 97.77 37 | 97.41 29 | 98.70 8 | 97.69 7 |
|
v144192 | | | 93.89 78 | 93.85 93 | 93.94 70 | 93.50 132 | 94.33 107 | 97.12 48 | 89.49 124 | 90.89 109 | 96.49 13 | 97.78 42 | 98.27 41 | 91.89 57 | 92.17 154 | 91.70 145 | 95.19 128 | 91.78 129 |
|
v1921920 | | | 93.90 77 | 93.82 95 | 94.00 65 | 93.74 125 | 94.31 108 | 97.12 48 | 89.33 130 | 91.13 103 | 96.77 10 | 97.90 34 | 98.06 55 | 91.95 55 | 91.93 162 | 91.54 150 | 95.10 132 | 91.85 126 |
|
FC-MVSNet-train | | | 92.75 116 | 95.40 58 | 89.66 149 | 95.21 76 | 94.82 95 | 97.00 53 | 89.40 127 | 91.13 103 | 81.71 189 | 97.72 44 | 96.43 100 | 77.57 196 | 96.89 55 | 96.72 42 | 97.05 67 | 94.09 80 |
|
UA-Net | | | 96.56 13 | 96.73 23 | 96.36 10 | 98.99 1 | 97.90 7 | 97.79 41 | 95.64 10 | 92.78 61 | 92.54 90 | 96.23 79 | 95.02 134 | 94.31 21 | 98.43 15 | 98.12 12 | 98.89 3 | 98.58 2 |
|
v1192 | | | 93.98 72 | 93.94 90 | 94.01 64 | 93.91 115 | 94.63 100 | 97.00 53 | 89.75 113 | 91.01 106 | 96.50 12 | 97.93 33 | 98.26 42 | 91.74 61 | 92.06 155 | 92.05 137 | 95.18 129 | 91.66 131 |
|
FC-MVSNet-test | | | 91.49 135 | 94.43 80 | 88.07 174 | 94.97 81 | 90.53 176 | 95.42 113 | 91.18 84 | 93.24 53 | 72.94 219 | 98.37 18 | 93.86 147 | 78.78 183 | 97.82 35 | 96.13 56 | 95.13 130 | 91.05 134 |
|
v1144 | | | 93.83 82 | 93.87 91 | 93.78 77 | 93.72 126 | 94.57 105 | 96.85 60 | 89.98 106 | 91.31 99 | 95.90 19 | 97.89 35 | 98.40 36 | 91.13 81 | 92.01 158 | 92.01 139 | 95.10 132 | 90.94 135 |
|
sosnet-low-res | | | 0.00 235 | 0.00 236 | 0.00 237 | 0.00 241 | 0.00 242 | 0.00 243 | 0.00 239 | 0.00 240 | 0.00 244 | 0.00 239 | 0.00 244 | 0.00 239 | 0.00 238 | 0.00 237 | 0.00 241 | 0.00 238 |
|
HFP-MVS | | | 96.18 23 | 96.53 29 | 95.77 21 | 97.34 16 | 97.26 25 | 98.16 29 | 94.54 18 | 94.45 31 | 92.52 91 | 95.05 102 | 96.95 84 | 93.89 26 | 97.28 44 | 97.46 24 | 98.19 31 | 97.25 10 |
|
v148 | | | 92.38 124 | 92.78 125 | 91.91 118 | 92.86 155 | 92.13 160 | 94.84 121 | 87.03 170 | 91.47 91 | 93.07 82 | 96.92 68 | 98.89 14 | 90.10 106 | 92.05 156 | 89.69 172 | 93.56 171 | 88.27 168 |
|
sosnet | | | 0.00 235 | 0.00 236 | 0.00 237 | 0.00 241 | 0.00 242 | 0.00 243 | 0.00 239 | 0.00 240 | 0.00 244 | 0.00 239 | 0.00 244 | 0.00 239 | 0.00 238 | 0.00 237 | 0.00 241 | 0.00 238 |
|
v748 | | | 96.05 30 | 97.00 20 | 94.95 45 | 94.41 93 | 94.77 97 | 96.72 66 | 91.03 88 | 96.12 16 | 96.71 11 | 98.74 8 | 99.59 2 | 93.55 31 | 97.97 29 | 95.96 58 | 97.28 57 | 95.84 49 |
|
v7n | | | 96.49 15 | 97.20 18 | 95.65 23 | 95.57 71 | 96.04 54 | 97.93 35 | 92.49 51 | 96.40 12 | 97.13 7 | 98.99 4 | 99.41 4 | 93.79 28 | 97.84 34 | 96.15 54 | 97.00 69 | 95.60 54 |
|
v1141 | | | 93.47 94 | 93.56 107 | 93.36 87 | 93.48 133 | 94.17 116 | 96.42 85 | 89.62 116 | 91.44 95 | 94.99 35 | 97.81 40 | 98.42 34 | 90.94 91 | 92.00 159 | 91.38 157 | 94.74 148 | 89.69 149 |
|
v1neww | | | 93.27 100 | 93.40 116 | 93.12 100 | 93.13 144 | 94.20 112 | 96.39 88 | 89.56 119 | 89.87 125 | 93.95 57 | 97.71 46 | 98.21 47 | 91.09 83 | 92.36 147 | 91.49 151 | 94.62 154 | 89.96 142 |
|
DI_MVS_plusplus_trai | | | 90.68 139 | 90.40 147 | 91.00 127 | 92.43 162 | 92.61 151 | 94.17 137 | 88.98 135 | 88.32 144 | 88.76 147 | 93.67 125 | 87.58 178 | 86.44 133 | 89.74 179 | 90.33 166 | 95.24 127 | 90.56 139 |
|
v7new | | | 93.27 100 | 93.40 116 | 93.12 100 | 93.13 144 | 94.20 112 | 96.39 88 | 89.56 119 | 89.87 125 | 93.95 57 | 97.71 46 | 98.21 47 | 91.09 83 | 92.36 147 | 91.49 151 | 94.62 154 | 89.96 142 |
|
HPM-MVS++ | | | 95.21 51 | 94.89 66 | 95.59 24 | 97.79 6 | 95.39 76 | 97.68 43 | 94.05 30 | 91.91 81 | 94.35 48 | 93.38 127 | 95.07 133 | 92.94 41 | 96.01 73 | 95.88 62 | 96.73 72 | 96.61 37 |
|
XVS | | | | | | 96.86 30 | 97.48 16 | 98.73 3 | | | 93.28 73 | | 96.82 89 | | | | 98.17 33 | |
|
v1240 | | | 93.89 78 | 93.72 100 | 94.09 59 | 93.98 108 | 94.31 108 | 97.12 48 | 89.37 128 | 90.74 113 | 96.92 9 | 98.05 30 | 97.89 63 | 92.15 54 | 91.53 166 | 91.60 148 | 94.99 137 | 91.93 125 |
|
v18 | | | 93.33 99 | 93.59 105 | 93.04 105 | 92.94 152 | 94.87 94 | 96.31 95 | 90.59 97 | 88.96 135 | 92.89 84 | 97.51 54 | 97.90 62 | 91.01 89 | 92.33 151 | 91.48 154 | 94.50 159 | 92.05 122 |
|
pm-mvs1 | | | 93.27 100 | 95.94 46 | 90.16 137 | 94.13 102 | 93.66 129 | 92.61 168 | 89.91 110 | 95.73 18 | 84.28 174 | 98.51 16 | 98.29 40 | 82.80 153 | 96.44 67 | 95.76 63 | 97.25 59 | 93.21 95 |
|
X-MVStestdata | | | | | | 96.86 30 | 97.48 16 | 98.73 3 | | | 93.28 73 | | 96.82 89 | | | | 98.17 33 | |
|
v17 | | | 93.60 87 | 93.85 93 | 93.30 92 | 93.15 143 | 94.99 91 | 96.46 80 | 90.81 91 | 89.58 130 | 93.61 67 | 97.66 50 | 98.15 51 | 91.19 77 | 92.60 142 | 91.61 147 | 94.61 156 | 92.37 115 |
|
v16 | | | 93.53 92 | 93.80 98 | 93.20 97 | 93.10 149 | 94.98 92 | 96.43 82 | 90.81 91 | 89.39 133 | 93.12 81 | 97.63 52 | 98.01 59 | 91.19 77 | 92.60 142 | 91.65 146 | 94.58 158 | 92.36 116 |
|
divwei89l23v2f112 | | | 93.47 94 | 93.56 107 | 93.37 85 | 93.48 133 | 94.17 116 | 96.42 85 | 89.62 116 | 91.46 92 | 95.00 33 | 97.81 40 | 98.42 34 | 90.94 91 | 92.00 159 | 91.38 157 | 94.75 146 | 89.70 147 |
|
v15 | | | 94.09 71 | 94.37 81 | 93.77 78 | 93.56 131 | 95.18 82 | 96.68 71 | 91.34 81 | 91.64 86 | 94.83 41 | 98.09 28 | 98.51 31 | 91.37 71 | 92.84 135 | 91.80 143 | 94.85 143 | 92.53 113 |
|
v13 | | | 94.54 63 | 94.93 64 | 94.09 59 | 93.81 121 | 95.44 72 | 96.99 55 | 91.67 74 | 92.43 67 | 95.20 27 | 98.33 19 | 98.73 21 | 91.87 58 | 93.67 125 | 92.26 130 | 95.00 136 | 93.63 87 |
|
v12 | | | 94.44 64 | 94.79 70 | 94.02 63 | 93.75 124 | 95.37 77 | 96.92 56 | 91.61 75 | 92.21 72 | 95.10 29 | 98.27 23 | 98.69 23 | 91.73 62 | 93.49 127 | 92.15 135 | 94.97 140 | 93.37 92 |
|
X-MVS | | | 95.33 49 | 95.13 62 | 95.57 26 | 97.35 14 | 97.48 16 | 98.43 16 | 94.28 24 | 92.30 71 | 93.28 73 | 86.89 189 | 96.82 89 | 91.87 58 | 97.85 32 | 97.59 21 | 98.19 31 | 96.95 25 |
|
v8 | | | 93.60 87 | 93.82 95 | 93.34 88 | 93.13 144 | 95.06 86 | 96.39 88 | 90.75 93 | 89.90 123 | 94.03 55 | 97.70 48 | 98.21 47 | 91.08 85 | 92.36 147 | 91.47 155 | 94.63 152 | 92.07 121 |
|
v7 | | | 93.65 85 | 93.73 99 | 93.57 82 | 93.38 137 | 94.60 103 | 96.83 62 | 89.92 109 | 89.69 128 | 95.02 31 | 97.89 35 | 98.24 43 | 91.27 73 | 92.38 146 | 92.18 133 | 94.99 137 | 91.12 133 |
|
v6 | | | 93.27 100 | 93.41 114 | 93.12 100 | 93.13 144 | 94.20 112 | 96.39 88 | 89.55 121 | 89.89 124 | 93.93 59 | 97.72 44 | 98.22 46 | 91.10 82 | 92.36 147 | 91.49 151 | 94.63 152 | 89.95 144 |
|
v11 | | | 94.32 67 | 94.62 74 | 93.97 67 | 93.95 111 | 95.31 78 | 96.83 62 | 91.30 82 | 91.95 79 | 95.51 20 | 98.32 21 | 98.61 26 | 91.44 69 | 92.83 136 | 92.23 132 | 94.77 145 | 93.08 98 |
|
v52 | | | 96.35 17 | 97.40 14 | 95.12 40 | 93.83 119 | 95.54 68 | 97.82 39 | 88.95 139 | 96.27 14 | 97.22 5 | 99.11 2 | 99.40 5 | 95.80 5 | 98.16 19 | 96.37 49 | 97.10 64 | 96.96 23 |
|
V14 | | | 94.21 70 | 94.52 77 | 93.85 73 | 93.62 129 | 95.25 81 | 96.76 65 | 91.42 79 | 91.83 82 | 94.91 38 | 98.15 25 | 98.57 28 | 91.49 68 | 93.06 134 | 91.93 141 | 94.90 142 | 92.82 102 |
|
v10 | | | 93.96 73 | 94.12 88 | 93.77 78 | 93.37 138 | 95.45 71 | 96.83 62 | 91.13 85 | 89.70 127 | 95.02 31 | 97.88 37 | 98.23 44 | 91.27 73 | 92.39 145 | 92.18 133 | 94.99 137 | 93.00 100 |
|
V4 | | | 96.35 17 | 97.40 14 | 95.12 40 | 93.83 119 | 95.54 68 | 97.82 39 | 88.95 139 | 96.27 14 | 97.21 6 | 99.10 3 | 99.40 5 | 95.79 6 | 98.17 18 | 96.37 49 | 97.10 64 | 96.96 23 |
|
v2v482 | | | 93.42 96 | 93.49 111 | 93.32 89 | 93.44 136 | 94.05 118 | 96.36 94 | 89.76 112 | 91.41 96 | 95.24 25 | 97.63 52 | 98.34 39 | 90.44 104 | 91.65 164 | 91.76 144 | 94.69 149 | 89.62 150 |
|
v1 | | | 93.48 93 | 93.57 106 | 93.37 85 | 93.48 133 | 94.18 115 | 96.41 87 | 89.61 118 | 91.46 92 | 95.03 30 | 97.82 39 | 98.43 33 | 90.95 90 | 92.00 159 | 91.37 159 | 94.75 146 | 89.70 147 |
|
V42 | | | 92.67 117 | 93.50 110 | 91.71 121 | 91.41 181 | 92.96 144 | 95.71 106 | 85.00 190 | 89.67 129 | 93.22 76 | 97.67 49 | 98.01 59 | 91.02 88 | 92.65 139 | 92.12 136 | 93.86 168 | 91.42 132 |
|
V9 | | | 94.33 66 | 94.66 73 | 93.94 70 | 93.69 128 | 95.31 78 | 96.84 61 | 91.53 78 | 92.04 78 | 95.00 33 | 98.22 24 | 98.64 24 | 91.62 64 | 93.29 129 | 92.05 137 | 94.93 141 | 93.10 97 |
|
SD-MVS | | | 95.77 40 | 96.17 40 | 95.30 34 | 96.72 37 | 96.19 49 | 97.01 52 | 93.04 45 | 94.03 41 | 92.71 86 | 96.45 74 | 96.78 93 | 93.91 25 | 96.79 60 | 95.89 61 | 98.42 25 | 97.09 18 |
|
GA-MVS | | | 88.76 159 | 88.04 174 | 89.59 150 | 92.32 166 | 91.46 166 | 92.28 173 | 86.62 175 | 83.82 183 | 89.84 139 | 92.51 136 | 81.94 194 | 83.53 148 | 89.41 183 | 89.27 177 | 92.95 179 | 87.90 169 |
|
MSLP-MVS++ | | | 93.91 76 | 94.30 85 | 93.45 84 | 95.51 72 | 95.83 61 | 93.12 158 | 91.93 69 | 91.45 94 | 91.40 114 | 87.42 184 | 96.12 110 | 93.27 34 | 96.57 66 | 96.40 48 | 95.49 120 | 96.29 40 |
|
APDe-MVS | | | 96.23 21 | 97.22 17 | 95.08 42 | 96.66 40 | 97.56 14 | 98.63 9 | 93.69 39 | 94.62 28 | 89.80 140 | 97.73 43 | 98.13 52 | 93.84 27 | 97.79 36 | 97.63 19 | 97.87 43 | 97.08 19 |
|
TSAR-MVS + COLMAP | | | 93.06 109 | 93.65 102 | 92.36 111 | 94.62 88 | 94.28 110 | 95.36 115 | 89.46 126 | 92.18 74 | 91.64 111 | 95.55 89 | 95.27 129 | 88.60 118 | 93.24 130 | 92.50 127 | 94.46 160 | 92.55 112 |
|
CVMVSNet | | | 88.97 157 | 89.73 152 | 88.10 173 | 87.33 216 | 85.22 196 | 94.68 126 | 78.68 213 | 88.94 137 | 86.98 159 | 95.55 89 | 85.71 184 | 89.87 108 | 91.19 169 | 89.69 172 | 91.05 185 | 91.78 129 |
|
TSAR-MVS + ACMM | | | 95.17 52 | 95.95 45 | 94.26 56 | 96.07 55 | 96.46 44 | 95.67 108 | 94.21 27 | 93.84 43 | 90.99 123 | 97.18 62 | 95.24 131 | 93.55 31 | 96.60 65 | 95.61 68 | 95.06 134 | 96.69 35 |
|
pmmvs4 | | | 89.95 146 | 89.32 158 | 90.69 131 | 91.60 180 | 89.17 181 | 94.37 130 | 87.63 161 | 88.07 149 | 91.02 122 | 94.50 112 | 90.50 168 | 86.13 135 | 86.33 203 | 89.40 175 | 93.39 174 | 87.29 173 |
|
EU-MVSNet | | | 91.63 134 | 92.73 126 | 90.35 135 | 88.36 209 | 87.89 187 | 96.53 76 | 81.51 210 | 92.45 66 | 91.82 108 | 96.44 75 | 97.05 81 | 93.26 35 | 94.10 119 | 88.94 182 | 90.61 187 | 92.24 119 |
|
test-LLR | | | 80.62 209 | 77.20 225 | 84.62 201 | 93.99 106 | 75.11 226 | 87.04 214 | 87.32 166 | 70.11 231 | 78.59 208 | 83.17 208 | 71.60 215 | 73.88 209 | 82.32 217 | 79.20 213 | 86.91 202 | 78.87 210 |
|
TESTMET0.1,1 | | | 77.47 223 | 77.20 225 | 77.78 220 | 81.94 225 | 75.11 226 | 87.04 214 | 58.33 233 | 70.11 231 | 78.59 208 | 83.17 208 | 71.60 215 | 73.88 209 | 82.32 217 | 79.20 213 | 86.91 202 | 78.87 210 |
|
test-mter | | | 78.71 218 | 78.35 216 | 79.12 217 | 84.03 223 | 76.58 222 | 88.51 210 | 59.06 231 | 71.06 229 | 78.87 204 | 83.73 207 | 71.83 214 | 76.44 203 | 83.41 216 | 80.61 208 | 87.79 199 | 81.24 196 |
|
ACMMPR | | | 96.54 14 | 96.71 24 | 96.35 11 | 97.55 9 | 97.63 11 | 98.62 10 | 94.54 18 | 94.45 31 | 94.19 50 | 95.04 104 | 97.35 75 | 94.92 13 | 97.85 32 | 97.50 23 | 98.26 29 | 97.17 15 |
|
testgi | | | 86.49 182 | 90.31 148 | 82.03 205 | 95.63 70 | 88.18 182 | 93.47 146 | 84.89 192 | 93.23 54 | 69.54 228 | 87.16 186 | 97.96 61 | 60.66 222 | 91.90 163 | 89.90 170 | 87.99 196 | 83.84 186 |
|
test20.03 | | | 88.20 170 | 91.26 142 | 84.63 200 | 96.64 41 | 89.39 179 | 90.73 194 | 89.97 107 | 91.07 105 | 72.02 221 | 94.98 105 | 95.45 121 | 69.35 213 | 92.70 138 | 91.19 160 | 89.06 193 | 84.02 185 |
|
thres600view7 | | | 89.14 153 | 88.83 163 | 89.51 152 | 93.71 127 | 93.55 135 | 93.93 140 | 88.02 154 | 87.30 157 | 82.40 184 | 81.18 214 | 80.63 200 | 82.69 156 | 94.27 112 | 95.90 60 | 96.27 95 | 88.94 157 |
|
1111 | | | 76.85 224 | 78.03 220 | 75.46 224 | 94.16 99 | 78.29 219 | 86.40 220 | 89.12 131 | 87.23 158 | 61.26 232 | 95.15 99 | 44.14 239 | 51.46 231 | 86.04 206 | 81.00 207 | 70.40 234 | 74.37 220 |
|
.test1245 | | | 60.07 231 | 56.75 233 | 63.93 231 | 94.16 99 | 78.29 219 | 86.40 220 | 89.12 131 | 87.23 158 | 61.26 232 | 95.15 99 | 44.14 239 | 51.46 231 | 86.04 206 | 2.51 235 | 1.21 239 | 3.92 236 |
|
ADS-MVSNet | | | 79.11 215 | 79.38 211 | 78.80 218 | 81.90 226 | 75.59 224 | 84.36 225 | 83.69 198 | 87.31 155 | 76.76 212 | 87.58 182 | 76.90 209 | 68.55 216 | 78.70 225 | 75.56 221 | 77.53 225 | 74.07 222 |
|
MP-MVS | | | 96.13 25 | 95.93 47 | 96.37 9 | 98.19 4 | 97.31 23 | 98.49 15 | 94.53 21 | 91.39 97 | 94.38 47 | 94.32 116 | 96.43 100 | 94.59 17 | 97.75 38 | 97.44 26 | 98.04 39 | 96.88 29 |
|
testmvs | | | 2.38 233 | 3.35 234 | 1.26 236 | 0.83 238 | 0.96 241 | 1.53 241 | 0.83 236 | 3.59 238 | 1.63 243 | 6.03 237 | 2.93 242 | 1.55 237 | 3.49 236 | 2.51 235 | 1.21 239 | 3.92 236 |
|
thres400 | | | 88.54 162 | 88.15 173 | 88.98 156 | 93.17 142 | 92.84 145 | 93.56 145 | 86.93 172 | 86.45 165 | 82.37 185 | 79.96 216 | 81.46 197 | 81.83 164 | 93.21 132 | 94.76 90 | 96.04 106 | 88.39 166 |
|
test123 | | | 2.16 234 | 2.82 235 | 1.41 235 | 0.62 239 | 1.18 240 | 1.53 241 | 0.82 237 | 2.78 239 | 2.27 242 | 4.18 238 | 1.98 243 | 1.64 236 | 2.58 237 | 3.01 234 | 1.56 238 | 4.00 235 |
|
thres200 | | | 88.29 166 | 87.88 175 | 88.76 159 | 92.50 161 | 93.55 135 | 92.47 171 | 88.02 154 | 84.80 174 | 81.44 190 | 79.28 218 | 82.20 193 | 81.83 164 | 94.27 112 | 93.67 110 | 96.27 95 | 87.40 172 |
|
test0.0.03 1 | | | 81.51 205 | 83.30 199 | 79.42 213 | 93.99 106 | 86.50 193 | 85.93 224 | 87.32 166 | 78.16 216 | 61.62 231 | 80.78 215 | 81.78 195 | 59.87 223 | 88.40 192 | 87.27 188 | 87.78 200 | 80.19 202 |
|
test12356 | | | 75.40 226 | 80.89 207 | 69.01 228 | 77.43 232 | 75.75 223 | 83.03 227 | 61.48 229 | 78.13 217 | 59.08 234 | 87.69 181 | 94.95 136 | 57.37 226 | 88.18 194 | 80.59 209 | 75.65 229 | 60.93 232 |
|
testus | | | 78.20 220 | 81.50 205 | 74.36 226 | 85.59 219 | 79.36 216 | 86.99 216 | 65.76 226 | 76.01 221 | 73.00 218 | 77.98 222 | 93.35 154 | 51.30 233 | 86.33 203 | 82.79 202 | 83.50 217 | 74.68 219 |
|
pmmvs3 | | | 81.69 203 | 83.83 194 | 79.19 216 | 78.33 230 | 78.57 218 | 89.53 204 | 58.71 232 | 78.88 214 | 84.34 173 | 88.36 173 | 91.96 159 | 77.69 195 | 87.48 197 | 82.42 203 | 86.54 204 | 79.18 209 |
|
testmv | | | 81.49 207 | 84.76 191 | 77.67 222 | 87.67 212 | 80.25 214 | 90.12 198 | 77.62 215 | 80.34 202 | 69.71 225 | 90.92 150 | 96.47 98 | 56.57 227 | 88.58 191 | 84.92 198 | 84.33 212 | 71.86 228 |
|
EMVS | | | 77.65 222 | 77.49 224 | 77.83 219 | 87.75 211 | 71.02 232 | 81.13 230 | 70.54 225 | 86.38 166 | 74.52 215 | 89.38 165 | 80.19 201 | 78.22 191 | 89.48 182 | 67.13 231 | 74.83 232 | 58.84 234 |
|
E-PMN | | | 77.81 221 | 77.88 222 | 77.73 221 | 88.26 210 | 70.48 233 | 80.19 231 | 71.20 224 | 86.66 163 | 72.89 220 | 88.09 177 | 81.74 196 | 78.75 184 | 90.02 178 | 68.30 230 | 75.10 230 | 59.85 233 |
|
test2356 | | | 72.95 228 | 71.24 231 | 74.95 225 | 84.89 222 | 75.49 225 | 82.67 228 | 75.38 220 | 68.02 234 | 68.65 229 | 74.40 227 | 52.81 235 | 55.61 230 | 81.50 220 | 79.80 211 | 82.50 219 | 66.70 231 |
|
test1235678 | | | 81.50 206 | 84.78 190 | 77.67 222 | 87.67 212 | 80.27 213 | 90.12 198 | 77.62 215 | 80.36 201 | 69.71 225 | 90.93 149 | 96.51 97 | 56.57 227 | 88.60 190 | 84.93 197 | 84.34 211 | 71.87 227 |
|
PGM-MVS | | | 95.90 35 | 95.72 50 | 96.10 16 | 97.53 10 | 97.45 19 | 98.55 13 | 94.12 29 | 90.25 115 | 93.71 65 | 93.20 129 | 97.18 79 | 94.63 16 | 97.68 40 | 97.34 32 | 98.08 36 | 96.97 22 |
|
MCST-MVS | | | 93.60 87 | 93.40 116 | 93.83 74 | 95.30 74 | 95.40 75 | 96.49 78 | 90.87 90 | 90.08 118 | 91.72 110 | 90.28 157 | 95.99 113 | 91.69 63 | 93.94 121 | 92.99 120 | 96.93 71 | 95.13 63 |
|
MVS_Test | | | 90.19 142 | 90.58 144 | 89.74 146 | 92.12 173 | 91.74 164 | 92.51 169 | 88.54 146 | 82.80 186 | 87.50 155 | 94.62 109 | 95.02 134 | 83.97 145 | 88.69 188 | 89.32 176 | 93.79 169 | 91.85 126 |
|
MDA-MVSNet-bldmvs | | | 89.75 147 | 91.67 137 | 87.50 179 | 74.25 234 | 90.88 171 | 94.68 126 | 85.89 182 | 91.64 86 | 91.03 121 | 95.86 83 | 94.35 142 | 89.10 113 | 96.87 57 | 86.37 192 | 90.04 188 | 85.72 182 |
|
CDPH-MVS | | | 93.96 73 | 93.86 92 | 94.08 61 | 96.31 49 | 95.84 60 | 96.92 56 | 91.85 70 | 87.21 160 | 91.25 119 | 92.83 131 | 96.06 111 | 91.05 86 | 95.57 80 | 94.81 86 | 97.12 62 | 94.72 68 |
|
diffmvs | | | 88.28 167 | 88.88 162 | 87.58 178 | 89.51 200 | 88.07 185 | 91.88 175 | 85.83 185 | 87.31 155 | 86.34 161 | 96.01 81 | 88.90 175 | 81.90 161 | 85.49 210 | 86.61 191 | 90.04 188 | 89.77 146 |
|
PMMVS2 | | | 69.86 230 | 82.14 201 | 55.52 232 | 75.19 233 | 63.08 236 | 75.52 235 | 60.97 230 | 88.50 143 | 25.11 240 | 91.77 141 | 96.44 99 | 25.43 234 | 88.70 187 | 79.34 212 | 70.93 233 | 67.17 229 |
|
PM-MVS | | | 92.65 118 | 93.20 121 | 92.00 117 | 92.11 174 | 90.16 177 | 95.99 98 | 84.81 193 | 91.31 99 | 92.41 94 | 95.87 82 | 96.64 95 | 92.35 51 | 93.65 126 | 92.91 122 | 94.34 163 | 91.85 126 |
|
PS-CasMVS | | | 97.22 5 | 97.84 7 | 96.50 5 | 97.08 23 | 97.92 6 | 98.17 28 | 97.02 2 | 94.71 27 | 95.32 24 | 98.52 15 | 98.97 12 | 92.91 42 | 99.04 4 | 98.47 6 | 98.49 19 | 97.24 12 |
|
UniMVSNet_NR-MVSNet | | | 95.34 48 | 95.51 55 | 95.14 39 | 95.80 66 | 96.55 38 | 96.61 74 | 94.79 16 | 90.04 120 | 93.78 62 | 97.51 54 | 97.25 77 | 91.19 77 | 96.68 62 | 96.31 52 | 98.65 12 | 94.22 77 |
|
PEN-MVS | | | 97.16 6 | 97.87 6 | 96.33 12 | 97.20 20 | 97.97 4 | 98.25 25 | 96.86 5 | 95.09 25 | 94.93 36 | 98.66 11 | 99.16 8 | 92.27 53 | 98.98 6 | 98.39 8 | 98.49 19 | 96.83 31 |
|
TransMVSNet (Re) | | | 93.55 91 | 96.32 35 | 90.32 136 | 94.38 94 | 94.05 118 | 93.30 155 | 89.53 122 | 97.15 8 | 85.12 168 | 98.83 6 | 97.89 63 | 82.21 158 | 96.75 61 | 96.14 55 | 97.35 55 | 93.46 90 |
|
DTE-MVSNet | | | 97.16 6 | 97.75 9 | 96.47 6 | 97.40 12 | 97.95 5 | 98.20 27 | 96.89 4 | 95.30 20 | 95.15 28 | 98.66 11 | 98.80 18 | 92.77 46 | 98.97 7 | 98.27 10 | 98.44 23 | 96.28 41 |
|
DU-MVS | | | 95.51 43 | 95.68 51 | 95.33 32 | 96.45 46 | 96.44 45 | 96.61 74 | 95.32 11 | 89.97 121 | 93.78 62 | 97.46 56 | 98.07 54 | 91.19 77 | 97.03 49 | 96.53 44 | 98.61 14 | 94.22 77 |
|
UniMVSNet (Re) | | | 95.46 44 | 95.86 48 | 95.00 44 | 96.09 53 | 96.60 37 | 96.68 71 | 94.99 13 | 90.36 114 | 92.13 100 | 97.64 51 | 98.13 52 | 91.38 70 | 96.90 54 | 96.74 41 | 98.73 6 | 94.63 72 |
|
CP-MVSNet | | | 96.97 10 | 97.42 13 | 96.44 7 | 97.06 24 | 97.82 8 | 98.12 30 | 96.98 3 | 93.50 46 | 95.21 26 | 97.98 31 | 98.44 32 | 92.83 45 | 98.93 8 | 98.37 9 | 98.46 22 | 96.91 28 |
|
WR-MVS_H | | | 97.06 9 | 97.78 8 | 96.23 14 | 96.74 36 | 98.04 3 | 98.25 25 | 97.32 1 | 94.40 34 | 93.71 65 | 98.55 14 | 98.89 14 | 92.97 39 | 98.91 9 | 98.45 7 | 98.38 28 | 97.19 14 |
|
WR-MVS | | | 97.53 3 | 98.20 4 | 96.76 3 | 96.93 27 | 98.17 1 | 98.60 11 | 96.67 6 | 96.39 13 | 94.46 44 | 99.14 1 | 98.92 13 | 94.57 18 | 99.06 3 | 98.80 2 | 99.32 1 | 96.92 27 |
|
NR-MVSNet | | | 94.55 62 | 95.66 53 | 93.25 96 | 94.26 98 | 96.44 45 | 96.69 69 | 95.32 11 | 89.97 121 | 91.79 109 | 97.46 56 | 98.39 37 | 82.85 152 | 96.87 57 | 96.48 47 | 98.57 15 | 93.98 82 |
|
Baseline_NR-MVSNet | | | 94.85 55 | 95.35 59 | 94.26 56 | 96.45 46 | 93.86 126 | 96.70 67 | 94.54 18 | 90.07 119 | 90.17 136 | 98.77 7 | 97.89 63 | 90.64 98 | 97.03 49 | 96.16 53 | 97.04 68 | 93.67 85 |
|
TranMVSNet+NR-MVSNet | | | 95.72 41 | 96.42 31 | 94.91 46 | 96.21 51 | 96.77 36 | 96.90 59 | 94.99 13 | 92.62 63 | 91.92 104 | 98.51 16 | 98.63 25 | 90.82 93 | 97.27 45 | 96.83 40 | 98.63 13 | 94.31 76 |
|
TSAR-MVS + GP. | | | 94.25 68 | 94.81 69 | 93.60 81 | 96.52 44 | 95.80 62 | 94.37 130 | 92.47 52 | 90.89 109 | 88.92 143 | 95.34 94 | 94.38 141 | 92.85 44 | 96.36 69 | 95.62 67 | 96.47 78 | 95.28 60 |
|
abl_6 | | | | | 91.88 119 | 93.76 123 | 94.98 92 | 95.64 109 | 88.97 136 | 86.20 167 | 90.00 138 | 86.31 193 | 94.50 140 | 87.31 126 | | | 95.60 118 | 92.48 114 |
|
mPP-MVS | | | | | | 98.24 3 | | | | | | | 97.65 71 | | | | | |
|
DWT-MVSNet_training | | | 79.22 214 | 73.99 230 | 85.33 194 | 88.57 206 | 84.41 201 | 90.56 196 | 80.96 212 | 73.90 228 | 85.72 165 | 75.62 224 | 50.09 237 | 81.30 169 | 76.91 230 | 77.02 218 | 84.88 207 | 79.97 205 |
|
testpf | | | 72.68 229 | 66.81 232 | 79.53 211 | 86.52 218 | 73.89 229 | 83.56 226 | 88.74 144 | 58.70 236 | 79.68 200 | 71.31 232 | 53.64 234 | 62.23 221 | 68.68 233 | 66.64 232 | 76.46 227 | 74.82 217 |
|
SixPastTwentyTwo | | | 97.36 4 | 97.73 10 | 96.92 2 | 97.36 13 | 96.15 51 | 98.29 23 | 94.43 23 | 96.50 11 | 96.96 8 | 98.74 8 | 98.74 20 | 96.04 3 | 99.03 5 | 97.74 17 | 98.44 23 | 97.22 13 |
|
LGP-MVS_train | | | 96.10 28 | 96.29 36 | 95.87 20 | 96.72 37 | 97.35 22 | 98.43 16 | 93.83 35 | 90.81 112 | 92.67 89 | 95.05 102 | 98.86 16 | 95.01 10 | 98.11 20 | 97.37 31 | 98.52 17 | 96.50 38 |
|
EPNet_dtu | | | 87.40 180 | 86.27 186 | 88.72 160 | 95.68 69 | 83.37 205 | 92.09 174 | 90.08 102 | 78.11 218 | 91.29 116 | 86.33 192 | 89.74 170 | 75.39 205 | 89.07 185 | 87.89 185 | 87.81 198 | 89.38 152 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
CHOSEN 1792x2688 | | | 86.64 181 | 86.62 183 | 86.65 189 | 90.33 195 | 87.86 188 | 93.19 157 | 83.30 203 | 83.95 182 | 82.32 186 | 87.93 178 | 89.34 172 | 86.92 129 | 85.64 209 | 84.95 196 | 83.85 215 | 86.68 178 |
|
EPNet | | | 90.17 143 | 89.07 160 | 91.45 123 | 97.25 18 | 90.62 175 | 94.84 121 | 93.54 41 | 80.96 192 | 91.85 106 | 86.98 188 | 85.88 183 | 77.79 193 | 92.30 152 | 92.58 126 | 93.41 173 | 94.20 79 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
APD-MVS | | | 95.38 47 | 95.68 51 | 95.03 43 | 97.30 17 | 96.90 34 | 97.83 38 | 93.92 32 | 89.40 131 | 90.35 132 | 95.41 92 | 97.69 70 | 92.97 39 | 97.24 46 | 97.17 35 | 97.83 44 | 95.96 47 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
LP | | | 84.09 194 | 84.31 192 | 83.85 202 | 79.40 229 | 84.34 202 | 90.26 197 | 84.02 196 | 87.99 150 | 84.66 170 | 91.61 144 | 79.13 203 | 80.58 172 | 85.90 208 | 81.59 205 | 84.16 214 | 79.59 206 |
|
CNVR-MVS | | | 94.24 69 | 94.47 79 | 93.96 69 | 96.56 43 | 95.67 65 | 96.43 82 | 91.95 67 | 92.08 76 | 91.28 117 | 90.51 155 | 95.35 124 | 91.20 76 | 96.34 70 | 95.50 70 | 96.34 88 | 95.88 48 |
|
NCCC | | | 93.87 81 | 93.42 113 | 94.40 54 | 96.84 32 | 95.42 73 | 96.47 79 | 92.62 48 | 92.36 69 | 92.05 101 | 83.83 205 | 95.55 117 | 91.84 60 | 95.89 75 | 95.23 76 | 96.56 76 | 95.63 53 |
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CP-MVS | | | 96.21 22 | 96.16 42 | 96.27 13 | 97.56 8 | 97.13 31 | 98.43 16 | 94.70 17 | 92.62 63 | 94.13 53 | 92.71 134 | 98.03 58 | 94.54 19 | 98.00 27 | 97.60 20 | 98.23 30 | 97.05 20 |
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NP-MVS | | | | | | | | | | 85.48 171 | | | | | | | | |
|
EG-PatchMatch MVS | | | 94.81 56 | 95.53 54 | 93.97 67 | 95.89 63 | 94.62 101 | 95.55 112 | 88.18 149 | 92.77 62 | 94.88 39 | 97.04 67 | 98.61 26 | 93.31 33 | 96.89 55 | 95.19 77 | 95.99 108 | 93.56 89 |
|
tpm cat1 | | | 80.03 210 | 75.93 228 | 84.81 198 | 89.31 201 | 83.26 207 | 88.86 208 | 86.55 178 | 79.24 210 | 86.10 162 | 84.22 204 | 63.62 228 | 77.37 198 | 73.43 231 | 70.88 229 | 80.67 222 | 76.87 213 |
|
SteuartSystems-ACMMP | | | 95.96 32 | 96.13 43 | 95.76 22 | 97.06 24 | 97.36 21 | 98.40 20 | 94.24 26 | 91.49 89 | 91.91 105 | 94.50 112 | 96.89 86 | 94.99 11 | 98.01 26 | 97.44 26 | 97.97 41 | 97.25 10 |
Skip Steuart: Steuart Systems R&D Blog. |
tpmp4_e23 | | | 82.16 200 | 78.26 217 | 86.70 187 | 89.92 196 | 84.82 198 | 91.17 187 | 89.95 108 | 81.21 191 | 87.10 157 | 81.91 212 | 64.01 227 | 77.88 192 | 79.89 224 | 74.99 224 | 84.18 213 | 81.00 199 |
|
CostFormer | | | 82.15 201 | 79.54 210 | 85.20 196 | 88.92 204 | 85.70 195 | 90.87 191 | 86.26 181 | 79.19 211 | 83.87 175 | 87.89 180 | 69.20 219 | 76.62 202 | 77.50 229 | 75.28 222 | 84.69 208 | 82.02 194 |
|
CR-MVSNet | | | 85.32 188 | 81.58 204 | 89.69 148 | 90.36 194 | 84.79 199 | 86.72 218 | 92.22 56 | 75.38 223 | 90.73 124 | 90.41 156 | 67.88 221 | 84.86 139 | 83.76 213 | 85.74 194 | 93.24 176 | 83.14 190 |
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Patchmtry | | | | | | | 83.74 204 | 86.72 218 | 92.22 56 | | 90.73 124 | | | | | | | |
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PatchT | | | 83.44 195 | 81.10 206 | 86.18 190 | 77.92 231 | 82.58 209 | 89.87 201 | 87.39 165 | 75.88 222 | 90.73 124 | 89.86 161 | 66.71 224 | 84.86 139 | 83.76 213 | 85.74 194 | 86.33 205 | 83.14 190 |
|
tpmrst | | | 78.81 217 | 76.18 227 | 81.87 206 | 88.56 207 | 77.45 221 | 86.74 217 | 81.52 209 | 80.08 203 | 83.48 177 | 90.84 151 | 66.88 222 | 74.54 206 | 73.04 232 | 71.02 228 | 76.38 228 | 73.95 223 |
|
tpm | | | 81.58 204 | 78.84 212 | 84.79 199 | 91.11 188 | 79.50 215 | 89.79 202 | 83.75 197 | 79.30 209 | 92.05 101 | 90.98 147 | 64.78 226 | 74.54 206 | 80.50 222 | 76.67 219 | 77.49 226 | 80.15 203 |
|
DELS-MVS | | | 92.33 126 | 93.61 104 | 90.83 129 | 92.84 156 | 95.13 85 | 94.76 124 | 87.22 169 | 87.78 152 | 88.42 151 | 95.78 85 | 95.28 128 | 85.71 137 | 94.44 106 | 93.91 108 | 96.01 107 | 92.97 101 |
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 |
RPMNet | | | 83.42 196 | 78.40 215 | 89.28 154 | 89.79 198 | 84.79 199 | 90.64 195 | 92.11 63 | 75.38 223 | 87.10 157 | 79.80 217 | 61.99 230 | 82.79 154 | 81.88 219 | 82.07 204 | 93.23 178 | 82.87 193 |
|
no-one | | | 92.05 132 | 94.57 76 | 89.12 155 | 85.55 220 | 87.65 190 | 94.21 135 | 77.34 217 | 93.43 49 | 89.64 141 | 95.11 101 | 99.11 9 | 95.86 4 | 95.38 83 | 95.24 75 | 92.08 184 | 96.11 45 |
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MVSTER | | | 84.79 190 | 83.79 195 | 85.96 191 | 89.14 203 | 89.80 178 | 89.39 205 | 82.99 204 | 74.16 227 | 82.78 181 | 85.97 195 | 66.81 223 | 76.84 200 | 90.77 172 | 88.83 183 | 94.66 150 | 90.19 141 |
|
CPTT-MVS | | | 95.00 54 | 94.52 77 | 95.57 26 | 96.84 32 | 96.78 35 | 97.88 36 | 93.67 40 | 92.20 73 | 92.35 96 | 85.87 196 | 97.56 72 | 94.98 12 | 96.96 52 | 96.07 57 | 97.70 47 | 96.18 43 |
|
GBi-Net | | | 89.35 151 | 90.58 144 | 87.91 175 | 91.22 185 | 94.05 118 | 92.88 163 | 90.05 103 | 79.40 205 | 78.60 205 | 90.58 152 | 87.05 179 | 78.54 186 | 95.32 86 | 94.98 81 | 96.17 102 | 92.67 107 |
|
PVSNet_Blended_VisFu | | | 93.60 87 | 93.41 114 | 93.83 74 | 96.31 49 | 95.65 66 | 95.71 106 | 90.58 98 | 88.08 148 | 93.17 78 | 95.29 96 | 92.20 158 | 90.72 95 | 94.69 103 | 93.41 117 | 96.51 77 | 94.54 73 |
|
PVSNet_BlendedMVS | | | 90.09 144 | 90.12 149 | 90.05 140 | 92.40 163 | 92.74 148 | 91.74 179 | 85.89 182 | 80.54 199 | 90.30 134 | 88.54 171 | 95.51 118 | 84.69 141 | 92.64 140 | 90.25 168 | 95.28 125 | 90.61 137 |
|
PVSNet_Blended | | | 90.09 144 | 90.12 149 | 90.05 140 | 92.40 163 | 92.74 148 | 91.74 179 | 85.89 182 | 80.54 199 | 90.30 134 | 88.54 171 | 95.51 118 | 84.69 141 | 92.64 140 | 90.25 168 | 95.28 125 | 90.61 137 |
|
FMVSNet5 | | | 79.08 216 | 78.83 213 | 79.38 214 | 87.52 215 | 86.78 191 | 87.64 212 | 78.15 214 | 69.54 233 | 70.64 224 | 65.97 235 | 65.44 225 | 63.87 220 | 90.17 176 | 90.46 165 | 88.48 195 | 83.45 189 |
|
test1 | | | 89.35 151 | 90.58 144 | 87.91 175 | 91.22 185 | 94.05 118 | 92.88 163 | 90.05 103 | 79.40 205 | 78.60 205 | 90.58 152 | 87.05 179 | 78.54 186 | 95.32 86 | 94.98 81 | 96.17 102 | 92.67 107 |
|
new_pmnet | | | 76.65 225 | 83.52 196 | 68.63 229 | 82.60 224 | 72.08 231 | 76.76 234 | 64.17 227 | 84.41 178 | 49.73 237 | 91.77 141 | 91.53 161 | 56.16 229 | 86.59 201 | 83.26 201 | 82.37 220 | 75.02 216 |
|
FMVSNet3 | | | 87.90 175 | 88.63 169 | 87.04 183 | 89.78 199 | 93.46 138 | 91.62 184 | 90.05 103 | 79.40 205 | 78.60 205 | 90.58 152 | 87.05 179 | 77.07 199 | 88.03 195 | 89.86 171 | 95.12 131 | 92.04 123 |
|
dps | | | 81.42 208 | 77.88 222 | 85.56 192 | 87.67 212 | 85.17 197 | 88.37 211 | 87.46 163 | 74.37 226 | 84.55 171 | 86.80 190 | 62.18 229 | 80.20 173 | 81.13 221 | 77.52 216 | 85.10 206 | 77.98 212 |
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FMVSNet2 | | | 90.28 141 | 92.04 134 | 88.23 172 | 91.22 185 | 94.05 118 | 92.88 163 | 90.69 94 | 86.53 164 | 79.89 199 | 94.38 115 | 92.73 157 | 78.54 186 | 91.64 165 | 92.26 130 | 96.17 102 | 92.67 107 |
|
FMVSNet1 | | | 92.86 113 | 95.26 60 | 90.06 139 | 92.40 163 | 95.16 83 | 94.37 130 | 92.22 56 | 93.18 55 | 82.16 188 | 96.76 70 | 97.48 73 | 81.85 163 | 95.32 86 | 94.98 81 | 97.34 56 | 93.93 83 |
|
N_pmnet | | | 79.33 211 | 84.22 193 | 73.62 227 | 91.72 178 | 73.72 230 | 86.11 222 | 76.36 218 | 92.38 68 | 53.38 235 | 95.54 91 | 95.62 116 | 59.14 224 | 84.23 212 | 74.84 225 | 75.03 231 | 73.25 224 |
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UGNet | | | 92.31 128 | 94.70 72 | 89.53 151 | 90.99 189 | 95.53 70 | 96.19 96 | 92.10 64 | 91.35 98 | 85.76 163 | 95.31 95 | 95.48 120 | 76.84 200 | 95.22 91 | 94.79 88 | 95.32 122 | 95.19 61 |
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 |
MDTV_nov1_ep13_2view | | | 88.22 169 | 87.85 176 | 88.65 161 | 91.40 182 | 86.75 192 | 94.07 138 | 84.97 191 | 88.86 139 | 93.20 77 | 96.11 80 | 96.21 108 | 83.70 147 | 87.29 200 | 80.29 210 | 84.56 209 | 79.46 207 |
|
MDTV_nov1_ep13 | | | 82.33 199 | 79.66 209 | 85.45 193 | 88.83 205 | 83.88 203 | 90.09 200 | 81.98 207 | 79.07 212 | 88.82 145 | 88.70 169 | 73.77 213 | 78.41 190 | 80.29 223 | 76.08 220 | 84.56 209 | 75.83 215 |
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MIMVSNet1 | | | 92.52 120 | 94.88 67 | 89.77 145 | 96.09 53 | 91.99 162 | 96.92 56 | 89.68 115 | 95.92 17 | 84.55 171 | 96.64 72 | 98.21 47 | 78.44 189 | 96.08 72 | 95.10 78 | 92.91 180 | 90.22 140 |
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MIMVSNet | | | 84.76 191 | 86.75 182 | 82.44 204 | 91.71 179 | 85.95 194 | 89.74 203 | 89.49 124 | 85.28 172 | 69.69 227 | 87.93 178 | 90.88 166 | 64.85 219 | 88.26 193 | 87.74 186 | 89.18 192 | 81.24 196 |
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IterMVS-LS | | | 92.10 130 | 92.33 129 | 91.82 120 | 93.18 141 | 93.66 129 | 92.80 166 | 92.27 55 | 90.82 111 | 90.59 129 | 97.19 61 | 90.97 165 | 87.76 125 | 89.60 181 | 90.94 163 | 94.34 163 | 93.16 96 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
CDS-MVSNet | | | 88.41 163 | 89.79 151 | 86.79 186 | 94.55 92 | 90.82 172 | 92.50 170 | 89.85 111 | 83.26 185 | 80.52 195 | 91.05 145 | 89.93 169 | 69.11 214 | 93.17 133 | 92.71 125 | 94.21 165 | 87.63 170 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
IterMVS | | | 88.32 164 | 88.25 172 | 88.41 166 | 90.83 191 | 91.24 167 | 93.07 159 | 81.69 208 | 86.77 162 | 88.55 148 | 95.61 86 | 86.91 182 | 87.01 127 | 87.38 198 | 83.77 199 | 89.29 191 | 86.06 181 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
MVS_111021_LR | | | 93.15 105 | 93.65 102 | 92.56 109 | 93.89 117 | 92.28 157 | 95.09 117 | 86.92 173 | 91.26 101 | 92.99 83 | 94.46 114 | 96.22 106 | 90.64 98 | 95.11 94 | 93.45 115 | 95.85 113 | 92.74 106 |
|
HQP-MVS | | | 92.87 112 | 92.49 128 | 93.31 90 | 95.75 67 | 95.01 90 | 95.64 109 | 91.06 87 | 88.54 142 | 91.62 112 | 88.16 175 | 96.25 104 | 89.47 110 | 92.26 153 | 91.81 142 | 96.34 88 | 95.40 56 |
|
QAPM | | | 92.57 119 | 93.51 109 | 91.47 122 | 92.91 154 | 94.82 95 | 93.01 160 | 87.51 162 | 91.49 89 | 91.21 120 | 92.24 137 | 91.70 160 | 88.74 116 | 94.54 105 | 94.39 102 | 95.41 121 | 95.37 59 |
|
Vis-MVSNet | | | 94.39 65 | 95.85 49 | 92.68 108 | 90.91 190 | 95.88 59 | 97.62 46 | 91.41 80 | 91.95 79 | 89.20 142 | 97.29 60 | 96.26 103 | 90.60 102 | 96.95 53 | 95.91 59 | 96.32 91 | 96.71 34 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
MVS-HIRNet | | | 78.28 219 | 75.28 229 | 81.79 207 | 80.33 227 | 69.38 234 | 76.83 233 | 86.59 176 | 70.76 230 | 86.66 160 | 89.57 163 | 81.04 198 | 77.74 194 | 77.81 228 | 71.65 227 | 82.62 218 | 66.73 230 |
|
HyFIR lowres test | | | 88.19 171 | 86.56 184 | 90.09 138 | 91.24 184 | 92.17 159 | 94.30 134 | 88.79 143 | 84.06 179 | 85.45 167 | 89.52 164 | 85.64 185 | 88.64 117 | 85.40 211 | 87.28 187 | 92.14 183 | 81.87 195 |
|
EPMVS | | | 79.26 212 | 78.20 219 | 80.49 208 | 87.04 217 | 78.86 217 | 86.08 223 | 83.51 200 | 82.63 187 | 73.94 217 | 89.59 162 | 68.67 220 | 72.03 212 | 78.17 227 | 75.08 223 | 80.37 223 | 74.37 220 |
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TAMVS | | | 82.96 197 | 86.15 187 | 79.24 215 | 90.57 193 | 83.12 208 | 87.29 213 | 75.12 222 | 84.06 179 | 65.81 230 | 92.22 138 | 88.27 177 | 69.11 214 | 88.72 186 | 87.26 189 | 87.56 201 | 79.38 208 |
|
IS_MVSNet | | | 92.76 115 | 93.25 120 | 92.19 115 | 94.91 83 | 95.56 67 | 95.86 101 | 92.12 62 | 88.10 146 | 82.71 183 | 93.15 130 | 88.30 176 | 88.86 114 | 97.29 43 | 96.95 39 | 98.66 10 | 93.38 91 |
|
RPSCF | | | 95.46 44 | 96.95 21 | 93.73 80 | 95.72 68 | 95.94 58 | 95.58 111 | 88.08 153 | 95.31 19 | 91.34 115 | 96.26 76 | 98.04 57 | 93.63 30 | 98.28 17 | 97.67 18 | 98.01 40 | 97.13 16 |
|
Vis-MVSNet (Re-imp) | | | 90.68 139 | 92.18 131 | 88.92 158 | 94.63 87 | 92.75 147 | 92.91 162 | 91.20 83 | 89.21 134 | 75.01 214 | 93.96 124 | 89.07 174 | 82.72 155 | 95.88 76 | 95.30 73 | 97.08 66 | 89.08 156 |
|
MVS_111021_HR | | | 93.82 83 | 94.26 87 | 93.31 90 | 95.01 80 | 93.97 123 | 95.73 105 | 89.75 113 | 92.06 77 | 92.49 92 | 94.01 123 | 96.05 112 | 90.61 101 | 95.95 74 | 94.78 89 | 96.28 93 | 93.04 99 |
|
CSCG | | | 96.07 29 | 97.15 19 | 94.81 47 | 96.06 56 | 97.58 13 | 96.52 77 | 90.98 89 | 96.51 10 | 93.60 68 | 97.13 65 | 98.55 30 | 93.01 38 | 97.17 47 | 95.36 72 | 98.68 9 | 97.78 5 |
|
PatchMatch-RL | | | 89.59 148 | 88.80 165 | 90.51 133 | 92.20 172 | 88.00 186 | 91.72 181 | 86.64 174 | 84.75 177 | 88.25 152 | 87.10 187 | 90.66 167 | 89.85 109 | 93.23 131 | 92.28 129 | 94.41 162 | 85.60 184 |
|
TDRefinement | | | 97.59 2 | 98.32 3 | 96.73 4 | 95.90 61 | 98.10 2 | 99.08 2 | 93.92 32 | 98.24 4 | 96.44 15 | 98.12 27 | 97.86 68 | 96.06 2 | 99.24 1 | 98.93 1 | 99.00 2 | 97.77 6 |
|
USDC | | | 92.17 129 | 92.17 132 | 92.18 116 | 92.93 153 | 92.22 158 | 93.66 143 | 87.41 164 | 93.49 47 | 97.99 1 | 94.10 119 | 96.68 94 | 86.46 132 | 92.04 157 | 89.18 178 | 94.61 156 | 87.47 171 |
|
EPP-MVSNet | | | 93.63 86 | 93.95 89 | 93.26 94 | 95.15 78 | 96.54 41 | 96.18 97 | 91.97 66 | 91.74 83 | 85.76 163 | 94.95 106 | 84.27 187 | 91.60 66 | 97.61 41 | 97.38 30 | 98.87 4 | 95.18 62 |
|
PMMVS | | | 81.93 202 | 83.48 198 | 80.12 210 | 72.35 235 | 75.05 228 | 88.54 209 | 64.01 228 | 77.02 220 | 82.22 187 | 87.51 183 | 91.12 162 | 79.70 176 | 86.59 201 | 86.64 190 | 93.88 167 | 80.41 200 |
|
ACMMP | | | 96.12 26 | 96.27 38 | 95.93 19 | 97.20 20 | 97.60 12 | 98.64 8 | 93.74 38 | 92.47 65 | 93.13 80 | 93.23 128 | 98.06 55 | 94.51 20 | 97.99 28 | 97.57 22 | 98.39 27 | 96.99 21 |
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 |
CNLPA | | | 93.14 106 | 93.67 101 | 92.53 110 | 94.62 88 | 94.73 98 | 95.00 119 | 86.57 177 | 92.85 60 | 92.43 93 | 90.94 148 | 94.67 137 | 90.35 105 | 95.41 82 | 93.70 109 | 96.23 98 | 93.37 92 |
|
PatchmatchNet | | | 82.44 198 | 78.69 214 | 86.83 185 | 89.81 197 | 81.55 212 | 90.78 192 | 87.27 168 | 82.39 188 | 88.85 144 | 88.31 174 | 70.96 217 | 81.90 161 | 78.58 226 | 74.33 226 | 82.35 221 | 74.69 218 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
PHI-MVS | | | 94.65 59 | 94.84 68 | 94.44 51 | 94.95 82 | 96.55 38 | 96.46 80 | 91.10 86 | 88.96 135 | 96.00 18 | 94.55 111 | 95.32 126 | 90.67 96 | 96.97 51 | 96.69 43 | 97.44 52 | 94.84 65 |
|
OMC-MVS | | | 94.74 57 | 95.46 56 | 93.91 72 | 94.62 88 | 96.26 48 | 96.64 73 | 89.36 129 | 94.20 37 | 94.15 52 | 94.02 122 | 97.73 69 | 91.34 72 | 96.15 71 | 95.04 80 | 97.37 54 | 94.80 66 |
|
AdaColmap | | | 92.41 123 | 91.49 140 | 93.48 83 | 95.96 59 | 95.02 89 | 95.37 114 | 91.73 72 | 87.97 151 | 91.28 117 | 82.82 210 | 91.04 164 | 90.62 100 | 95.82 77 | 95.07 79 | 95.95 109 | 92.67 107 |
|
DeepMVS_CX | | | | | | | 47.68 238 | 53.20 238 | 19.21 234 | 63.24 235 | 26.96 239 | 66.50 234 | 69.82 218 | 66.91 218 | 64.27 234 | | 54.91 236 | 72.72 225 |
|
TinyColmap | | | 93.17 104 | 93.33 119 | 93.00 106 | 93.84 118 | 92.76 146 | 94.75 125 | 88.90 141 | 93.97 42 | 97.48 4 | 95.28 98 | 95.29 127 | 88.37 120 | 95.31 89 | 91.58 149 | 94.65 151 | 89.10 155 |
|
MAR-MVS | | | 91.86 133 | 91.14 143 | 92.71 107 | 94.29 96 | 94.24 111 | 94.91 120 | 91.82 71 | 81.66 190 | 93.32 72 | 84.51 203 | 93.42 152 | 86.86 130 | 95.16 93 | 94.44 101 | 95.05 135 | 94.53 74 |
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 |
MSDG | | | 92.09 131 | 92.84 124 | 91.22 125 | 92.55 159 | 92.97 143 | 93.42 147 | 85.43 188 | 90.24 116 | 91.83 107 | 94.70 108 | 94.59 139 | 88.48 119 | 94.91 99 | 93.31 119 | 95.59 119 | 89.15 154 |
|
LS3D | | | 95.83 39 | 96.35 33 | 95.22 37 | 96.47 45 | 97.49 15 | 97.99 31 | 92.35 54 | 94.92 26 | 94.58 43 | 94.88 107 | 95.11 132 | 91.52 67 | 98.48 14 | 98.05 13 | 98.42 25 | 95.49 55 |
|
CLD-MVS | | | 92.81 114 | 94.32 83 | 91.05 126 | 95.39 73 | 95.31 78 | 95.82 102 | 81.44 211 | 89.40 131 | 91.94 103 | 95.86 83 | 97.36 74 | 85.83 136 | 95.35 84 | 94.59 98 | 95.85 113 | 92.34 118 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
FPMVS | | | 90.81 138 | 91.60 139 | 89.88 143 | 92.52 160 | 88.18 182 | 93.31 154 | 83.62 199 | 91.59 88 | 88.45 150 | 88.96 168 | 89.73 171 | 86.96 128 | 96.42 68 | 95.69 66 | 94.43 161 | 90.65 136 |
|
Gipuma | | | 95.86 37 | 96.17 40 | 95.50 29 | 95.92 60 | 94.59 104 | 94.77 123 | 92.50 50 | 97.82 6 | 97.90 2 | 95.56 88 | 97.88 66 | 94.71 14 | 98.02 25 | 94.81 86 | 97.23 60 | 94.48 75 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |