DeepC-MVS_fast | | 93.32 1 | 96.48 18 | 96.42 23 | 96.56 16 | 98.70 20 | 98.31 32 | 97.97 19 | 95.76 15 | 96.31 9 | 92.01 23 | 91.43 35 | 95.42 33 | 96.46 19 | 97.65 7 | 97.69 1 | 98.49 16 | 98.12 40 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
DeepPCF-MVS | | 92.65 2 | 95.50 29 | 96.96 14 | 93.79 45 | 96.44 50 | 98.21 33 | 93.51 84 | 94.08 30 | 96.94 1 | 89.29 38 | 93.08 26 | 96.77 21 | 93.82 46 | 97.68 5 | 97.40 3 | 95.59 181 | 98.65 11 |
|
DeepC-MVS | | 92.10 3 | 95.22 30 | 94.77 34 | 95.75 26 | 97.77 32 | 98.54 21 | 97.63 24 | 95.96 12 | 95.07 27 | 88.85 41 | 85.35 60 | 91.85 46 | 95.82 24 | 96.88 21 | 97.10 7 | 98.44 23 | 98.63 12 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
PLC | | 90.69 4 | 94.32 39 | 92.99 48 | 95.87 24 | 97.91 28 | 96.49 83 | 95.95 45 | 94.12 29 | 94.94 28 | 94.09 9 | 85.90 56 | 90.77 53 | 95.58 27 | 94.52 72 | 93.32 82 | 97.55 107 | 95.00 145 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
3Dnovator+ | | 90.56 5 | 95.06 31 | 94.56 36 | 95.65 27 | 98.11 26 | 98.15 36 | 97.19 28 | 91.59 46 | 95.11 26 | 93.23 18 | 81.99 89 | 94.71 36 | 95.43 29 | 96.48 28 | 96.88 13 | 98.35 35 | 98.63 12 |
|
TAPA-MVS | | 90.35 6 | 93.69 44 | 93.52 42 | 93.90 42 | 96.89 46 | 97.62 52 | 96.15 39 | 91.67 45 | 94.94 28 | 85.97 60 | 87.72 49 | 91.96 45 | 94.40 35 | 93.76 88 | 93.06 95 | 98.30 46 | 95.58 124 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
3Dnovator | | 90.28 7 | 94.70 37 | 94.34 39 | 95.11 30 | 98.06 27 | 98.21 33 | 96.89 32 | 91.03 52 | 94.72 32 | 91.45 25 | 82.87 80 | 93.10 42 | 94.61 34 | 96.24 37 | 97.08 8 | 98.63 9 | 98.16 36 |
|
PCF-MVS | | 90.19 8 | 92.98 47 | 92.07 61 | 94.04 38 | 96.39 51 | 97.87 43 | 96.03 42 | 95.47 23 | 87.16 99 | 85.09 74 | 84.81 68 | 93.21 41 | 93.46 50 | 91.98 119 | 91.98 116 | 97.78 92 | 97.51 58 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
ACMP | | 89.13 9 | 92.03 56 | 91.70 65 | 92.41 59 | 94.92 67 | 96.44 86 | 93.95 74 | 89.96 59 | 91.81 54 | 85.48 70 | 90.97 38 | 79.12 99 | 92.42 59 | 93.28 104 | 92.55 101 | 97.76 93 | 97.74 54 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
ACMM | | 88.76 10 | 91.70 63 | 90.43 72 | 93.19 51 | 95.56 59 | 95.14 100 | 93.35 87 | 91.48 47 | 92.26 51 | 87.12 53 | 84.02 75 | 79.34 98 | 93.99 42 | 94.07 82 | 92.68 100 | 97.62 106 | 95.50 125 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
OpenMVS | | 88.18 11 | 92.51 51 | 91.61 66 | 93.55 47 | 97.74 33 | 98.02 40 | 95.66 48 | 90.46 56 | 89.14 83 | 86.50 58 | 75.80 123 | 90.38 59 | 92.69 56 | 94.99 51 | 95.30 43 | 98.27 53 | 97.63 55 |
|
ACMH+ | | 85.75 12 | 87.19 114 | 86.02 125 | 88.56 103 | 93.42 101 | 94.41 108 | 89.91 149 | 87.66 102 | 83.45 140 | 72.25 130 | 76.42 120 | 71.99 128 | 90.78 77 | 89.86 153 | 90.94 128 | 97.32 112 | 95.11 144 |
|
ACMH | | 85.51 13 | 87.31 113 | 86.59 117 | 88.14 109 | 93.96 80 | 94.51 104 | 89.00 166 | 87.99 91 | 81.58 147 | 70.15 156 | 78.41 106 | 71.78 129 | 90.60 80 | 91.30 128 | 91.99 115 | 97.17 117 | 96.58 90 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
IB-MVS | | 85.10 14 | 87.98 106 | 87.97 100 | 87.99 111 | 94.55 69 | 96.86 75 | 84.52 198 | 88.21 89 | 86.48 108 | 88.54 44 | 74.41 132 | 77.74 107 | 74.10 205 | 89.65 158 | 92.85 96 | 98.06 78 | 97.80 53 |
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 |
COLMAP_ROB | | 84.39 15 | 87.61 110 | 86.03 124 | 89.46 93 | 95.54 61 | 94.48 105 | 91.77 114 | 90.14 58 | 87.16 99 | 75.50 116 | 73.41 138 | 76.86 114 | 87.33 113 | 90.05 152 | 89.76 176 | 96.48 162 | 90.46 193 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
LTVRE_ROB | | 81.71 16 | 82.44 188 | 81.84 186 | 83.13 179 | 89.01 141 | 92.99 148 | 88.90 167 | 82.32 155 | 66.26 220 | 54.02 219 | 74.68 131 | 59.62 213 | 88.87 101 | 90.71 139 | 92.02 114 | 95.68 178 | 96.62 83 |
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 |
CMPMVS | | 61.19 17 | 79.86 200 | 77.46 207 | 82.66 190 | 91.54 121 | 91.82 181 | 83.25 201 | 81.57 163 | 70.51 216 | 68.64 174 | 59.89 210 | 66.77 164 | 79.63 188 | 84.00 209 | 84.30 205 | 91.34 211 | 84.89 213 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
PMVS | | 56.77 18 | 61.27 223 | 58.64 225 | 64.35 223 | 75.66 223 | 54.60 234 | 53.62 232 | 74.23 204 | 53.69 227 | 58.37 212 | 44.27 228 | 49.38 222 | 44.16 229 | 69.51 228 | 65.35 229 | 80.07 229 | 73.66 225 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
MVE | | 39.81 19 | 39.52 230 | 41.58 230 | 37.11 232 | 33.93 236 | 49.06 235 | 26.45 238 | 54.22 232 | 29.46 236 | 24.15 235 | 20.77 234 | 10.60 240 | 34.42 231 | 51.12 232 | 65.27 230 | 49.49 236 | 64.81 231 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
tfpn111 | | | 90.16 78 | 88.99 87 | 91.52 70 | 93.90 84 | 97.26 59 | 94.31 63 | 89.75 64 | 85.87 110 | 81.10 89 | 84.41 71 | 70.38 135 | 91.76 64 | 94.92 55 | 93.51 71 | 98.29 50 | 96.61 84 |
|
conf0.01 | | | 89.34 90 | 87.39 114 | 91.61 65 | 93.88 88 | 97.34 57 | 94.31 63 | 89.82 63 | 85.87 110 | 81.53 85 | 77.93 108 | 66.15 175 | 91.76 64 | 94.90 62 | 93.51 71 | 98.32 42 | 96.05 110 |
|
conf0.002 | | | 89.25 94 | 87.21 115 | 91.62 64 | 93.87 89 | 97.35 56 | 94.31 63 | 89.83 61 | 85.87 110 | 81.62 84 | 78.72 104 | 63.89 192 | 91.76 64 | 94.90 62 | 93.98 64 | 98.33 41 | 95.77 117 |
|
thresconf0.02 | | | 88.86 96 | 88.70 92 | 89.04 98 | 93.59 99 | 96.40 87 | 92.97 91 | 89.75 64 | 90.16 71 | 74.34 119 | 84.41 71 | 71.00 131 | 85.16 149 | 93.32 102 | 93.12 92 | 98.41 28 | 92.52 179 |
|
tfpn_n400 | | | 88.58 100 | 88.91 89 | 88.19 106 | 93.63 97 | 96.34 89 | 92.22 103 | 89.04 77 | 87.37 97 | 72.14 132 | 85.12 63 | 73.93 120 | 84.04 164 | 93.65 90 | 93.20 87 | 98.09 72 | 92.77 172 |
|
tfpnconf | | | 88.58 100 | 88.91 89 | 88.19 106 | 93.63 97 | 96.34 89 | 92.22 103 | 89.04 77 | 87.37 97 | 72.14 132 | 85.12 63 | 73.93 120 | 84.04 164 | 93.65 90 | 93.20 87 | 98.09 72 | 92.77 172 |
|
tfpnview11 | | | 88.80 97 | 89.21 84 | 88.31 105 | 93.70 95 | 96.24 91 | 92.35 98 | 89.11 76 | 89.90 77 | 72.14 132 | 85.12 63 | 73.93 120 | 84.20 159 | 93.75 89 | 92.85 96 | 98.38 33 | 92.68 177 |
|
tfpn1000 | | | 89.30 91 | 89.72 81 | 88.81 100 | 93.83 91 | 96.50 82 | 91.53 117 | 88.74 83 | 91.20 58 | 76.74 112 | 84.96 66 | 75.44 119 | 83.50 168 | 93.63 92 | 92.42 104 | 98.51 13 | 93.88 159 |
|
tfpn_ndepth | | | 89.72 81 | 89.91 79 | 89.49 92 | 93.56 100 | 96.67 77 | 92.34 99 | 89.25 75 | 90.85 59 | 78.68 105 | 84.25 74 | 77.39 110 | 84.84 153 | 93.58 94 | 92.76 99 | 98.30 46 | 93.90 158 |
|
conf200view11 | | | 89.55 84 | 87.86 101 | 91.52 70 | 93.90 84 | 97.26 59 | 94.31 63 | 89.75 64 | 85.87 110 | 81.10 89 | 76.46 117 | 70.38 135 | 91.76 64 | 94.92 55 | 93.51 71 | 98.29 50 | 96.61 84 |
|
thres100view900 | | | 89.36 88 | 87.61 107 | 91.39 73 | 93.90 84 | 96.86 75 | 94.35 60 | 89.66 71 | 85.87 110 | 81.15 87 | 76.46 117 | 70.38 135 | 91.17 73 | 94.09 81 | 93.43 79 | 98.13 67 | 96.16 105 |
|
tfpnnormal | | | 83.80 165 | 81.26 194 | 86.77 126 | 89.60 138 | 93.26 140 | 89.72 156 | 87.60 103 | 72.78 208 | 70.44 150 | 60.53 209 | 61.15 206 | 85.55 145 | 92.72 107 | 91.44 124 | 97.71 97 | 96.92 73 |
|
tfpn200view9 | | | 89.55 84 | 87.86 101 | 91.53 68 | 93.90 84 | 97.26 59 | 94.31 63 | 89.74 67 | 85.87 110 | 81.15 87 | 76.46 117 | 70.38 135 | 91.76 64 | 94.92 55 | 93.51 71 | 98.28 52 | 96.61 84 |
|
view600 | | | 89.29 92 | 87.48 111 | 91.41 72 | 94.10 76 | 97.21 64 | 93.96 72 | 89.70 70 | 85.67 117 | 80.75 93 | 75.29 127 | 69.35 142 | 91.70 69 | 94.92 55 | 93.23 84 | 98.26 57 | 96.69 81 |
|
view800 | | | 89.21 95 | 87.44 113 | 91.27 77 | 94.13 73 | 97.18 66 | 93.74 79 | 89.53 73 | 85.60 121 | 80.34 96 | 75.29 127 | 68.89 144 | 91.57 71 | 94.97 52 | 93.36 80 | 98.34 37 | 96.79 77 |
|
conf0.05thres1000 | | | 87.90 107 | 85.88 129 | 90.26 85 | 93.74 93 | 96.39 88 | 92.67 93 | 88.94 80 | 80.97 154 | 77.71 108 | 70.15 152 | 68.40 149 | 90.42 83 | 94.46 75 | 93.29 83 | 98.09 72 | 97.49 59 |
|
tfpn | | | 88.67 98 | 86.57 118 | 91.12 78 | 94.14 72 | 97.15 67 | 93.51 84 | 89.37 74 | 85.49 122 | 79.91 99 | 75.26 129 | 62.24 198 | 91.39 72 | 95.00 50 | 93.95 65 | 98.41 28 | 96.88 75 |
|
ESAPD | | | 97.65 2 | 97.98 1 | 97.27 4 | 99.12 2 | 99.14 2 | 98.66 2 | 96.80 1 | 95.74 15 | 93.46 13 | 97.72 2 | 99.48 1 | 96.76 13 | 97.77 2 | 96.92 12 | 98.83 4 | 99.07 6 |
|
CHOSEN 280x420 | | | 90.77 69 | 92.14 60 | 89.17 97 | 93.86 90 | 92.81 155 | 93.16 88 | 80.22 180 | 90.21 68 | 84.67 76 | 89.89 41 | 91.38 51 | 90.57 81 | 94.94 54 | 92.11 111 | 92.52 203 | 93.65 162 |
|
CANet | | | 94.85 33 | 94.92 33 | 94.78 32 | 97.25 41 | 98.52 23 | 97.20 27 | 91.81 42 | 93.25 43 | 91.06 28 | 86.29 52 | 94.46 37 | 92.99 53 | 97.02 17 | 96.68 15 | 98.34 37 | 98.20 34 |
|
Fast-Effi-MVS+-dtu | | | 86.25 121 | 87.70 105 | 84.56 164 | 90.37 134 | 93.70 121 | 90.54 123 | 78.14 190 | 83.50 138 | 65.37 196 | 81.59 93 | 75.83 118 | 86.09 136 | 91.70 122 | 91.70 120 | 96.88 152 | 95.84 116 |
|
Effi-MVS+-dtu | | | 87.51 111 | 88.13 98 | 86.77 126 | 91.10 125 | 94.90 101 | 90.91 119 | 82.67 149 | 83.47 139 | 71.55 138 | 81.11 95 | 77.04 112 | 89.41 90 | 92.65 109 | 91.68 122 | 95.00 192 | 96.09 108 |
|
CANet_DTU | | | 90.74 70 | 92.93 49 | 88.19 106 | 94.36 70 | 96.61 78 | 94.34 61 | 84.66 126 | 90.66 61 | 68.75 173 | 90.41 40 | 86.89 64 | 89.78 87 | 95.46 47 | 94.87 49 | 97.25 114 | 95.62 122 |
|
MVS_0304 | | | 94.30 40 | 94.68 35 | 93.86 44 | 96.33 52 | 98.48 24 | 97.41 25 | 91.20 48 | 92.75 47 | 86.96 55 | 86.03 55 | 93.81 40 | 92.64 57 | 96.89 20 | 96.54 20 | 98.61 10 | 98.24 32 |
|
HSP-MVS | | | 97.51 3 | 97.70 4 | 97.29 3 | 99.00 10 | 99.17 1 | 98.61 3 | 96.41 5 | 95.88 14 | 94.34 7 | 97.72 2 | 99.04 3 | 96.93 8 | 97.29 12 | 95.90 35 | 98.45 22 | 98.94 8 |
|
TSAR-MVS + MP. | | | 97.31 5 | 97.64 5 | 96.92 9 | 97.28 40 | 98.56 19 | 98.61 3 | 95.48 22 | 96.72 4 | 94.03 10 | 96.73 9 | 98.29 5 | 97.15 3 | 97.61 8 | 96.42 21 | 98.96 2 | 99.13 3 |
|
OPM-MVS | | | 91.08 66 | 89.34 82 | 93.11 54 | 96.18 53 | 96.13 94 | 96.39 37 | 92.39 37 | 82.97 142 | 81.74 83 | 82.55 86 | 80.20 95 | 93.97 44 | 94.62 68 | 93.23 84 | 98.00 83 | 95.73 119 |
|
ACMMP_Plus | | | 96.93 12 | 97.27 10 | 96.53 19 | 99.06 5 | 98.95 5 | 98.24 11 | 96.06 10 | 95.66 17 | 90.96 29 | 95.63 19 | 97.71 11 | 96.53 17 | 97.66 6 | 96.68 15 | 98.30 46 | 98.61 15 |
|
ambc | | | | 67.96 218 | | 73.69 225 | 79.79 223 | 73.82 217 | | 71.61 211 | 59.80 210 | 46.00 224 | 20.79 236 | 66.15 214 | 86.92 194 | 80.11 221 | 89.13 223 | 90.50 192 |
|
MPTG | | | 96.98 11 | 96.68 19 | 97.33 2 | 99.09 3 | 98.71 9 | 98.43 6 | 96.01 11 | 96.11 12 | 95.19 3 | 92.89 28 | 97.32 17 | 96.84 9 | 97.20 13 | 96.09 32 | 98.44 23 | 98.46 26 |
|
Effi-MVS+ | | | 89.79 80 | 89.83 80 | 89.74 89 | 92.98 104 | 96.45 85 | 93.48 86 | 84.24 130 | 87.62 96 | 76.45 113 | 81.76 90 | 77.56 109 | 93.48 49 | 94.61 69 | 93.59 70 | 97.82 90 | 97.22 66 |
|
new-patchmatchnet | | | 72.32 214 | 71.09 216 | 73.74 211 | 81.17 216 | 84.86 216 | 72.21 222 | 77.48 193 | 68.32 218 | 54.89 217 | 55.10 216 | 49.31 223 | 63.68 217 | 79.30 219 | 76.46 224 | 93.03 198 | 84.32 215 |
|
pmmvs6 | | | 80.90 197 | 78.77 201 | 83.38 178 | 85.84 199 | 91.61 184 | 86.01 191 | 82.54 151 | 64.17 221 | 70.43 151 | 54.14 219 | 67.06 160 | 80.73 186 | 90.50 143 | 89.17 184 | 94.74 193 | 94.75 146 |
|
pmmvs5 | | | 83.37 176 | 82.68 171 | 84.18 169 | 87.13 189 | 93.18 143 | 86.74 185 | 82.08 157 | 76.48 195 | 67.28 184 | 71.26 144 | 62.70 196 | 84.71 154 | 90.77 136 | 90.12 166 | 97.15 118 | 94.24 152 |
|
Fast-Effi-MVS+ | | | 88.56 103 | 87.99 99 | 89.22 96 | 91.56 120 | 95.21 98 | 92.29 101 | 82.69 148 | 86.82 101 | 77.73 107 | 76.24 121 | 73.39 123 | 93.36 51 | 94.22 79 | 93.64 69 | 97.65 103 | 96.43 93 |
|
Anonymous20231211 | | | 69.76 218 | 67.18 219 | 72.76 213 | 78.31 218 | 83.47 217 | 74.12 216 | 78.37 189 | 51.44 230 | 52.48 220 | 36.04 229 | 45.46 229 | 62.33 218 | 80.49 218 | 82.43 211 | 90.96 214 | 90.93 189 |
|
pmmvs-eth3d | | | 79.78 201 | 77.58 205 | 82.34 194 | 81.57 214 | 87.46 211 | 82.92 202 | 81.28 166 | 75.33 204 | 71.34 140 | 61.88 204 | 52.41 218 | 81.59 183 | 87.56 188 | 86.90 192 | 95.36 187 | 91.48 182 |
|
GG-mvs-BLEND | | | 62.84 222 | 90.21 73 | 30.91 233 | 0.57 238 | 94.45 106 | 86.99 183 | 0.34 237 | 88.71 86 | 0.98 240 | 81.55 94 | 91.58 49 | 0.86 237 | 92.66 108 | 91.43 125 | 95.73 176 | 91.11 187 |
|
Anonymous20231206 | | | 78.09 204 | 78.11 204 | 78.07 206 | 85.19 205 | 89.17 204 | 80.99 206 | 81.24 168 | 75.46 203 | 58.25 213 | 54.78 218 | 59.90 212 | 66.73 213 | 88.94 181 | 88.26 187 | 96.01 171 | 90.25 195 |
|
MTAPA | | | | | | | | | | | 95.36 2 | | 97.46 15 | | | | | |
|
MTMP | | | | | | | | | | | 95.70 1 | | 96.90 20 | | | | | |
|
gm-plane-assit | | | 77.65 205 | 78.50 202 | 76.66 207 | 87.96 155 | 85.43 215 | 64.70 225 | 74.50 203 | 64.15 222 | 51.26 222 | 61.32 207 | 58.17 215 | 84.11 162 | 95.16 49 | 93.83 67 | 97.45 110 | 91.41 183 |
|
train_agg | | | 96.15 21 | 96.64 21 | 95.58 29 | 98.44 22 | 98.03 39 | 98.14 16 | 95.40 25 | 93.90 39 | 87.72 49 | 96.26 12 | 98.10 6 | 95.75 25 | 96.25 36 | 95.45 42 | 98.01 82 | 98.47 24 |
|
gg-mvs-nofinetune | | | 81.83 193 | 83.58 148 | 79.80 201 | 91.57 119 | 96.54 81 | 93.79 77 | 68.80 221 | 62.71 223 | 43.01 231 | 55.28 215 | 85.06 74 | 83.65 166 | 96.13 38 | 94.86 50 | 97.98 86 | 94.46 149 |
|
MS-PatchMatch | | | 87.63 109 | 87.61 107 | 87.65 116 | 93.95 81 | 94.09 112 | 92.60 95 | 81.52 164 | 86.64 103 | 76.41 114 | 73.46 137 | 85.94 70 | 85.01 152 | 92.23 116 | 90.00 169 | 96.43 164 | 90.93 189 |
|
Patchmatch-RL test | | | | | | | | 18.47 239 | | | | | | | | | | |
|
tmp_tt | | | | | 50.24 229 | 68.55 229 | 46.86 236 | 48.90 234 | 18.28 234 | 86.51 107 | 68.32 176 | 70.19 151 | 65.33 180 | 26.69 234 | 74.37 224 | 66.80 228 | 70.72 233 | |
|
canonicalmvs | | | 93.08 46 | 93.09 46 | 93.07 55 | 94.24 71 | 97.86 44 | 95.45 51 | 87.86 98 | 94.00 38 | 87.47 51 | 88.32 47 | 82.37 87 | 95.13 31 | 93.96 87 | 96.41 22 | 98.27 53 | 98.73 9 |
|
anonymousdsp | | | 84.51 146 | 85.85 131 | 82.95 184 | 86.30 198 | 93.51 126 | 85.77 195 | 80.38 175 | 78.25 186 | 63.42 202 | 73.51 136 | 72.20 126 | 84.64 155 | 93.21 105 | 92.16 110 | 97.19 116 | 98.14 38 |
|
v144192 | | | 83.48 175 | 82.23 180 | 84.94 159 | 86.65 194 | 92.84 152 | 89.63 158 | 82.48 152 | 77.87 187 | 67.36 183 | 65.33 193 | 63.50 193 | 86.51 122 | 89.72 156 | 89.99 170 | 97.03 126 | 96.35 96 |
|
v1921920 | | | 83.30 177 | 82.09 183 | 84.70 161 | 86.59 196 | 92.67 158 | 89.82 155 | 82.23 156 | 78.32 184 | 65.76 193 | 64.64 197 | 62.35 197 | 86.78 121 | 90.34 145 | 90.02 168 | 97.02 127 | 96.31 100 |
|
FC-MVSNet-train | | | 90.55 71 | 90.19 74 | 90.97 80 | 93.78 92 | 95.16 99 | 92.11 109 | 88.85 81 | 87.64 95 | 83.38 80 | 84.36 73 | 78.41 102 | 89.53 88 | 94.69 66 | 93.15 91 | 98.15 65 | 97.92 46 |
|
UA-Net | | | 90.81 68 | 92.58 52 | 88.74 102 | 94.87 68 | 97.44 54 | 92.61 94 | 88.22 88 | 82.35 145 | 78.93 103 | 85.20 62 | 95.61 31 | 79.56 189 | 96.52 27 | 96.57 19 | 98.23 59 | 94.37 151 |
|
v1192 | | | 83.56 173 | 82.35 176 | 84.98 158 | 86.84 193 | 92.84 152 | 90.01 146 | 82.70 147 | 78.54 183 | 66.48 189 | 64.88 195 | 62.91 194 | 86.91 118 | 90.72 138 | 90.25 149 | 96.94 138 | 96.32 98 |
|
FC-MVSNet-test | | | 86.15 123 | 89.10 86 | 82.71 189 | 89.83 135 | 93.18 143 | 87.88 176 | 84.69 125 | 86.54 105 | 62.18 205 | 82.39 87 | 83.31 79 | 74.18 204 | 92.52 111 | 91.86 117 | 97.50 109 | 93.88 159 |
|
v1144 | | | 84.03 162 | 82.88 168 | 85.37 147 | 87.17 187 | 93.15 146 | 90.18 139 | 83.31 142 | 78.83 181 | 67.85 179 | 65.99 187 | 64.99 184 | 86.79 120 | 90.75 137 | 90.33 145 | 96.90 147 | 96.15 106 |
|
sosnet-low-res | | | 0.00 234 | 0.00 235 | 0.00 236 | 0.00 240 | 0.00 241 | 0.00 242 | 0.00 238 | 0.00 239 | 0.00 243 | 0.00 238 | 0.00 243 | 0.00 238 | 0.00 237 | 0.00 236 | 0.00 240 | 0.00 237 |
|
HFP-MVS | | | 97.11 9 | 97.19 11 | 97.00 8 | 98.97 12 | 98.73 8 | 98.37 9 | 95.69 16 | 96.60 5 | 93.28 16 | 96.87 5 | 96.64 22 | 97.27 1 | 96.64 24 | 96.33 27 | 98.44 23 | 98.56 16 |
|
v148 | | | 83.61 170 | 82.10 182 | 85.37 147 | 87.34 177 | 92.94 150 | 87.48 178 | 85.72 114 | 78.92 180 | 73.87 123 | 65.71 191 | 64.69 187 | 81.78 181 | 87.82 184 | 89.35 182 | 96.01 171 | 95.26 136 |
|
sosnet | | | 0.00 234 | 0.00 235 | 0.00 236 | 0.00 240 | 0.00 241 | 0.00 242 | 0.00 238 | 0.00 239 | 0.00 243 | 0.00 238 | 0.00 243 | 0.00 238 | 0.00 237 | 0.00 236 | 0.00 240 | 0.00 237 |
|
v748 | | | 81.57 196 | 80.68 198 | 82.60 191 | 85.55 202 | 92.07 173 | 83.57 200 | 82.06 158 | 74.64 205 | 69.97 161 | 63.11 202 | 61.46 204 | 78.09 193 | 87.30 191 | 89.88 172 | 96.37 165 | 96.32 98 |
|
v7n | | | 82.25 189 | 81.54 189 | 83.07 182 | 85.55 202 | 92.58 160 | 86.68 187 | 81.10 169 | 76.54 194 | 65.97 192 | 62.91 203 | 60.56 208 | 82.36 175 | 91.07 132 | 90.35 144 | 96.77 157 | 96.80 76 |
|
v1141 | | | 84.40 151 | 83.00 165 | 86.03 135 | 87.41 173 | 93.42 130 | 90.28 135 | 85.53 115 | 79.58 170 | 70.12 158 | 66.62 177 | 66.27 172 | 85.94 137 | 89.16 175 | 90.19 160 | 96.89 149 | 95.73 119 |
|
v1neww | | | 84.65 143 | 83.34 157 | 86.18 133 | 87.53 167 | 93.49 127 | 90.32 127 | 85.17 121 | 80.57 158 | 71.02 147 | 66.93 169 | 67.04 161 | 86.13 133 | 89.26 169 | 90.23 155 | 96.93 141 | 95.88 114 |
|
DI_MVS_plusplus_trai | | | 91.05 67 | 90.15 75 | 92.11 61 | 92.67 110 | 96.61 78 | 96.03 42 | 88.44 86 | 90.25 66 | 85.92 62 | 73.73 133 | 84.89 75 | 91.92 61 | 94.17 80 | 94.07 62 | 97.68 101 | 97.31 65 |
|
v7new | | | 84.65 143 | 83.34 157 | 86.18 133 | 87.53 167 | 93.49 127 | 90.32 127 | 85.17 121 | 80.57 158 | 71.02 147 | 66.93 169 | 67.04 161 | 86.13 133 | 89.26 169 | 90.23 155 | 96.93 141 | 95.88 114 |
|
HPM-MVS++ | | | 97.22 7 | 97.40 8 | 97.01 7 | 99.08 4 | 98.55 20 | 98.19 12 | 96.48 4 | 96.02 13 | 93.28 16 | 96.26 12 | 98.71 4 | 96.76 13 | 97.30 11 | 96.25 29 | 98.30 46 | 98.68 10 |
|
XVS | | | | | | 95.68 56 | 98.66 10 | 94.96 54 | | | 88.03 45 | | 96.06 25 | | | | 98.46 19 | |
|
v1240 | | | 82.88 183 | 81.66 187 | 84.29 167 | 86.46 197 | 92.52 165 | 89.06 164 | 81.82 161 | 77.16 191 | 65.09 197 | 64.17 198 | 61.50 203 | 86.36 123 | 90.12 149 | 90.13 163 | 96.95 136 | 96.04 111 |
|
v18 | | | 84.21 155 | 82.90 167 | 85.74 141 | 87.63 163 | 89.75 195 | 90.56 122 | 80.82 170 | 81.42 149 | 72.24 131 | 67.16 164 | 67.23 155 | 86.27 126 | 89.25 172 | 90.24 152 | 96.92 145 | 95.27 135 |
|
pm-mvs1 | | | 84.55 145 | 83.46 149 | 85.82 138 | 88.16 154 | 93.39 134 | 89.05 165 | 85.36 120 | 74.03 206 | 72.43 129 | 65.08 194 | 71.11 130 | 82.30 176 | 93.48 98 | 91.70 120 | 97.64 104 | 95.43 129 |
|
X-MVStestdata | | | | | | 95.68 56 | 98.66 10 | 94.96 54 | | | 88.03 45 | | 96.06 25 | | | | 98.46 19 | |
|
v17 | | | 84.10 159 | 82.83 170 | 85.57 146 | 87.58 165 | 89.72 196 | 90.30 134 | 80.70 172 | 81.00 153 | 71.72 136 | 67.01 166 | 67.24 154 | 86.19 130 | 89.32 166 | 90.25 149 | 96.95 136 | 95.29 133 |
|
v16 | | | 84.14 157 | 82.86 169 | 85.64 144 | 87.61 164 | 89.71 197 | 90.36 125 | 80.70 172 | 81.36 150 | 71.99 135 | 66.91 171 | 67.19 156 | 86.23 129 | 89.32 166 | 90.25 149 | 96.94 138 | 95.29 133 |
|
divwei89l23v2f112 | | | 84.40 151 | 83.00 165 | 86.02 137 | 87.42 172 | 93.42 130 | 90.28 135 | 85.52 116 | 79.57 171 | 70.11 159 | 66.64 176 | 66.29 171 | 85.91 138 | 89.16 175 | 90.19 160 | 96.90 147 | 95.73 119 |
|
v15 | | | 83.67 168 | 82.37 175 | 85.19 152 | 87.39 175 | 89.63 198 | 90.19 138 | 80.43 174 | 79.49 175 | 70.27 152 | 66.37 178 | 66.33 169 | 85.88 140 | 89.34 165 | 90.23 155 | 96.96 135 | 95.22 140 |
|
v13 | | | 83.55 174 | 82.29 179 | 85.01 157 | 87.31 184 | 89.55 203 | 89.89 152 | 80.13 182 | 79.34 178 | 69.93 162 | 65.92 189 | 66.25 173 | 85.80 144 | 89.45 159 | 90.27 146 | 97.01 128 | 95.25 138 |
|
v12 | | | 83.59 172 | 82.32 178 | 85.07 155 | 87.32 183 | 89.57 201 | 89.87 154 | 80.19 181 | 79.46 176 | 70.19 154 | 66.05 186 | 66.23 174 | 85.84 142 | 89.44 160 | 90.26 148 | 97.01 128 | 95.26 136 |
|
X-MVS | | | 96.07 22 | 96.33 24 | 95.77 25 | 98.94 14 | 98.66 10 | 97.94 20 | 95.41 24 | 95.12 24 | 88.03 45 | 93.00 27 | 96.06 25 | 95.85 23 | 96.65 23 | 96.35 24 | 98.47 17 | 98.48 23 |
|
v8 | | | 84.45 150 | 83.30 159 | 85.80 139 | 87.53 167 | 92.95 149 | 90.31 131 | 82.46 153 | 80.46 160 | 71.43 139 | 66.99 167 | 67.16 158 | 86.14 131 | 89.26 169 | 90.22 158 | 96.94 138 | 96.06 109 |
|
v7 | | | 84.37 154 | 83.23 160 | 85.69 142 | 87.34 177 | 93.19 142 | 90.32 127 | 83.10 145 | 79.88 169 | 69.33 167 | 66.33 181 | 65.75 176 | 87.06 115 | 90.83 135 | 90.38 142 | 96.97 132 | 96.26 103 |
|
v6 | | | 84.67 142 | 83.36 155 | 86.20 131 | 87.53 167 | 93.49 127 | 90.34 126 | 85.16 123 | 80.58 157 | 71.13 143 | 66.97 168 | 67.10 159 | 86.11 135 | 89.25 172 | 90.22 158 | 96.93 141 | 95.89 113 |
|
v11 | | | 83.72 166 | 82.61 173 | 85.02 156 | 87.34 177 | 89.56 202 | 89.89 152 | 79.92 183 | 79.55 172 | 69.21 171 | 66.36 180 | 65.48 179 | 86.84 119 | 91.43 127 | 90.51 141 | 96.92 145 | 95.37 132 |
|
v52 | | | 82.11 190 | 81.50 191 | 82.82 187 | 84.59 208 | 92.51 166 | 85.96 194 | 80.24 178 | 76.38 198 | 66.83 188 | 63.12 201 | 64.62 189 | 82.56 172 | 87.70 186 | 89.55 178 | 96.73 158 | 96.61 84 |
|
V14 | | | 83.66 169 | 82.38 174 | 85.16 153 | 87.37 176 | 89.62 199 | 90.15 140 | 80.33 176 | 79.51 173 | 70.26 153 | 66.30 184 | 66.37 167 | 85.87 141 | 89.38 162 | 90.24 152 | 96.98 131 | 95.22 140 |
|
v10 | | | 84.18 156 | 83.17 162 | 85.37 147 | 87.34 177 | 92.68 157 | 90.32 127 | 81.33 165 | 79.93 168 | 69.23 170 | 66.33 181 | 65.74 178 | 87.03 116 | 90.84 134 | 90.38 142 | 96.97 132 | 96.29 101 |
|
V4 | | | 82.11 190 | 81.49 192 | 82.83 186 | 84.60 207 | 92.53 164 | 85.97 192 | 80.24 178 | 76.35 199 | 66.87 187 | 63.17 200 | 64.55 190 | 82.54 173 | 87.70 186 | 89.55 178 | 96.73 158 | 96.61 84 |
|
v2v482 | | | 84.51 146 | 83.05 163 | 86.20 131 | 87.25 185 | 93.28 138 | 90.22 137 | 85.40 119 | 79.94 167 | 69.78 164 | 67.74 162 | 65.15 183 | 87.57 108 | 89.12 178 | 90.55 139 | 96.97 132 | 95.60 123 |
|
v1 | | | 84.40 151 | 83.01 164 | 86.03 135 | 87.41 173 | 93.42 130 | 90.31 131 | 85.52 116 | 79.51 173 | 70.13 157 | 66.66 175 | 66.40 166 | 85.89 139 | 89.15 177 | 90.19 160 | 96.89 149 | 95.74 118 |
|
V42 | | | 84.48 148 | 83.36 155 | 85.79 140 | 87.14 188 | 93.28 138 | 90.03 144 | 83.98 134 | 80.30 162 | 71.20 142 | 66.90 173 | 67.17 157 | 85.55 145 | 89.35 163 | 90.27 146 | 96.82 155 | 96.27 102 |
|
V9 | | | 83.61 170 | 82.33 177 | 85.11 154 | 87.34 177 | 89.59 200 | 90.10 143 | 80.25 177 | 79.38 177 | 70.17 155 | 66.15 185 | 66.33 169 | 85.82 143 | 89.41 161 | 90.24 152 | 96.99 130 | 95.23 139 |
|
SD-MVS | | | 97.35 4 | 97.73 3 | 96.90 10 | 97.35 38 | 98.66 10 | 97.85 22 | 96.25 7 | 96.86 2 | 94.54 5 | 96.75 8 | 99.13 2 | 96.99 5 | 96.94 19 | 96.58 18 | 98.39 32 | 99.20 1 |
|
GA-MVS | | | 85.08 137 | 85.65 132 | 84.42 166 | 89.77 136 | 94.25 110 | 89.26 161 | 84.62 127 | 81.19 152 | 62.25 204 | 75.72 124 | 68.44 148 | 84.14 161 | 93.57 96 | 91.68 122 | 96.49 161 | 94.71 147 |
|
MSLP-MVS++ | | | 96.05 23 | 95.63 27 | 96.55 17 | 98.33 24 | 98.17 35 | 96.94 31 | 94.61 28 | 94.70 33 | 94.37 6 | 89.20 44 | 95.96 28 | 96.81 10 | 95.57 45 | 97.33 4 | 98.24 58 | 98.47 24 |
|
APDe-MVS | | | 97.79 1 | 97.96 2 | 97.60 1 | 99.20 1 | 99.10 3 | 98.88 1 | 96.68 2 | 96.81 3 | 94.64 4 | 97.84 1 | 98.02 7 | 97.24 2 | 97.74 4 | 97.02 9 | 98.97 1 | 99.16 2 |
|
TSAR-MVS + COLMAP | | | 92.39 53 | 92.31 58 | 92.47 58 | 95.35 66 | 96.46 84 | 96.13 40 | 92.04 41 | 95.33 22 | 80.11 97 | 94.95 24 | 77.35 111 | 94.05 41 | 94.49 74 | 93.08 93 | 97.15 118 | 94.53 148 |
|
CVMVSNet | | | 83.83 164 | 85.53 133 | 81.85 197 | 89.60 138 | 90.92 190 | 87.81 177 | 83.21 143 | 80.11 164 | 60.16 209 | 76.47 116 | 78.57 101 | 76.79 197 | 89.76 154 | 90.13 163 | 93.51 195 | 92.75 175 |
|
TSAR-MVS + ACMM | | | 96.19 19 | 97.39 9 | 94.78 32 | 97.70 34 | 98.41 29 | 97.72 23 | 95.49 21 | 96.47 7 | 86.66 57 | 96.35 10 | 97.85 9 | 93.99 42 | 97.19 14 | 96.37 23 | 97.12 121 | 99.13 3 |
|
pmmvs4 | | | 86.00 127 | 84.28 143 | 88.00 110 | 87.80 157 | 92.01 177 | 89.94 148 | 84.91 124 | 86.79 102 | 80.98 92 | 73.41 138 | 66.34 168 | 88.12 104 | 89.31 168 | 88.90 186 | 96.24 169 | 93.20 168 |
|
EU-MVSNet | | | 78.43 202 | 80.25 199 | 76.30 208 | 83.81 210 | 87.27 213 | 80.99 206 | 79.52 185 | 76.01 200 | 54.12 218 | 70.44 149 | 64.87 185 | 67.40 212 | 86.23 197 | 85.54 199 | 91.95 210 | 91.41 183 |
|
test-LLR | | | 86.88 115 | 88.28 95 | 85.24 150 | 91.22 123 | 92.07 173 | 87.41 179 | 83.62 137 | 84.58 126 | 69.33 167 | 83.00 78 | 82.79 81 | 84.24 157 | 92.26 114 | 89.81 173 | 95.64 179 | 93.44 163 |
|
TESTMET0.1,1 | | | 86.11 125 | 88.28 95 | 83.59 174 | 87.80 157 | 92.07 173 | 87.41 179 | 77.12 194 | 84.58 126 | 69.33 167 | 83.00 78 | 82.79 81 | 84.24 157 | 92.26 114 | 89.81 173 | 95.64 179 | 93.44 163 |
|
test-mter | | | 86.09 126 | 88.38 94 | 83.43 177 | 87.89 156 | 92.61 159 | 86.89 184 | 77.11 195 | 84.30 131 | 68.62 175 | 82.57 85 | 82.45 85 | 84.34 156 | 92.40 112 | 90.11 167 | 95.74 175 | 94.21 154 |
|
ACMMPR | | | 96.92 13 | 96.96 14 | 96.87 11 | 98.99 11 | 98.78 7 | 98.38 8 | 95.52 19 | 96.57 6 | 92.81 20 | 96.06 15 | 95.90 29 | 97.07 4 | 96.60 26 | 96.34 26 | 98.46 19 | 98.42 27 |
|
testgi | | | 81.94 192 | 84.09 145 | 79.43 202 | 89.53 140 | 90.83 192 | 82.49 204 | 81.75 162 | 80.59 156 | 59.46 211 | 82.82 81 | 65.75 176 | 67.97 209 | 90.10 150 | 89.52 180 | 95.39 185 | 89.03 199 |
|
test20.03 | | | 76.41 208 | 78.49 203 | 73.98 210 | 85.64 201 | 87.50 210 | 75.89 213 | 80.71 171 | 70.84 215 | 51.07 223 | 68.06 161 | 61.40 205 | 54.99 224 | 88.28 182 | 87.20 191 | 95.58 182 | 86.15 209 |
|
thres600view7 | | | 89.28 93 | 87.47 112 | 91.39 73 | 94.12 75 | 97.25 62 | 93.94 75 | 89.74 67 | 85.62 120 | 80.63 94 | 75.24 130 | 69.33 143 | 91.66 70 | 94.92 55 | 93.23 84 | 98.27 53 | 96.72 79 |
|
1111 | | | 66.22 219 | 66.42 221 | 65.98 220 | 75.69 221 | 76.42 225 | 58.90 226 | 63.25 226 | 57.86 225 | 48.33 227 | 45.46 225 | 49.13 224 | 61.32 220 | 81.57 214 | 82.80 210 | 88.38 224 | 71.69 229 |
|
.test1245 | | | 48.95 228 | 46.78 229 | 51.48 226 | 75.69 221 | 76.42 225 | 58.90 226 | 63.25 226 | 57.86 225 | 48.33 227 | 45.46 225 | 49.13 224 | 61.32 220 | 81.57 214 | 5.58 233 | 1.40 237 | 11.42 235 |
|
ADS-MVSNet | | | 84.08 160 | 84.95 136 | 83.05 183 | 91.53 122 | 91.75 182 | 88.16 173 | 70.70 217 | 89.96 76 | 69.51 166 | 78.83 102 | 76.97 113 | 86.29 125 | 84.08 208 | 84.60 204 | 92.13 209 | 88.48 204 |
|
MP-MVS | | | 96.56 17 | 96.72 18 | 96.37 20 | 98.93 15 | 98.48 24 | 98.04 17 | 95.55 18 | 94.32 35 | 90.95 31 | 95.88 17 | 97.02 19 | 96.29 22 | 96.77 22 | 96.01 34 | 98.47 17 | 98.56 16 |
|
testmvs | | | 4.35 232 | 6.54 233 | 1.79 234 | 0.60 237 | 1.82 239 | 3.06 240 | 0.95 235 | 7.22 237 | 0.88 241 | 12.38 236 | 1.25 241 | 3.87 236 | 6.09 235 | 5.58 233 | 1.40 237 | 11.42 235 |
|
thres400 | | | 89.40 87 | 87.58 109 | 91.53 68 | 94.06 79 | 97.21 64 | 94.19 71 | 89.83 61 | 85.69 116 | 81.08 91 | 75.50 125 | 69.76 141 | 91.80 62 | 94.79 65 | 93.51 71 | 98.20 62 | 96.60 89 |
|
test123 | | | 3.48 233 | 5.31 234 | 1.34 235 | 0.20 239 | 1.52 240 | 2.17 241 | 0.58 236 | 6.13 238 | 0.31 242 | 9.85 237 | 0.31 242 | 3.90 235 | 2.65 236 | 5.28 235 | 0.87 239 | 11.46 234 |
|
thres200 | | | 89.49 86 | 87.72 104 | 91.55 67 | 93.95 81 | 97.25 62 | 94.34 61 | 89.74 67 | 85.66 118 | 81.18 86 | 76.12 122 | 70.19 140 | 91.80 62 | 94.92 55 | 93.51 71 | 98.27 53 | 96.40 94 |
|
test0.0.03 1 | | | 85.58 131 | 87.69 106 | 83.11 180 | 91.22 123 | 92.54 162 | 85.60 197 | 83.62 137 | 85.66 118 | 67.84 180 | 82.79 82 | 79.70 97 | 73.51 207 | 91.15 131 | 90.79 130 | 96.88 152 | 91.23 186 |
|
test12356 | | | 60.37 224 | 61.08 224 | 59.53 225 | 72.42 228 | 70.09 230 | 57.72 230 | 69.53 219 | 51.31 231 | 36.05 234 | 47.32 223 | 32.04 233 | 36.19 230 | 74.15 225 | 80.35 220 | 85.27 226 | 72.29 227 |
|
testus | | | 73.65 212 | 74.92 211 | 72.17 217 | 80.93 217 | 81.11 219 | 73.02 221 | 75.23 202 | 73.23 207 | 48.77 225 | 69.38 156 | 46.10 228 | 62.28 219 | 84.84 202 | 86.01 195 | 92.77 200 | 83.75 217 |
|
pmmvs3 | | | 71.13 216 | 71.06 217 | 71.21 218 | 73.54 226 | 80.19 222 | 71.69 223 | 64.86 225 | 62.04 224 | 52.10 221 | 54.92 217 | 48.00 226 | 75.03 202 | 83.75 210 | 83.24 209 | 90.04 221 | 85.27 211 |
|
testmv | | | 65.29 220 | 65.25 222 | 65.34 221 | 77.73 219 | 75.55 227 | 58.75 228 | 73.56 210 | 53.22 228 | 38.47 232 | 49.33 221 | 38.30 231 | 53.38 225 | 79.13 220 | 81.65 214 | 90.15 219 | 79.58 221 |
|
EMVS | | | 39.04 231 | 34.32 232 | 44.54 231 | 58.25 234 | 39.35 237 | 27.61 237 | 62.55 229 | 35.99 233 | 16.40 239 | 20.04 235 | 14.77 238 | 44.80 227 | 33.12 234 | 44.10 232 | 57.61 235 | 52.89 233 |
|
E-PMN | | | 40.00 229 | 35.74 231 | 44.98 230 | 57.69 235 | 39.15 238 | 28.05 236 | 62.70 228 | 35.52 234 | 17.78 238 | 20.90 233 | 14.36 239 | 44.47 228 | 35.89 233 | 47.86 231 | 59.15 234 | 56.47 232 |
|
test2356 | | | 73.82 210 | 74.82 212 | 72.66 215 | 81.25 215 | 80.70 221 | 73.47 219 | 75.91 198 | 72.55 209 | 48.73 226 | 68.14 160 | 50.74 220 | 63.96 215 | 84.44 206 | 85.57 198 | 92.63 202 | 81.60 218 |
|
test1235678 | | | 65.29 220 | 65.24 223 | 65.34 221 | 77.73 219 | 75.54 228 | 58.75 228 | 73.56 210 | 53.19 229 | 38.47 232 | 49.32 222 | 38.28 232 | 53.38 225 | 79.13 220 | 81.65 214 | 90.15 219 | 79.57 222 |
|
PGM-MVS | | | 96.16 20 | 96.33 24 | 95.95 22 | 99.04 6 | 98.63 15 | 98.32 10 | 92.76 36 | 93.42 42 | 90.49 34 | 96.30 11 | 95.31 34 | 96.71 15 | 96.46 29 | 96.02 33 | 98.38 33 | 98.19 35 |
|
MCST-MVS | | | 96.83 14 | 97.06 12 | 96.57 15 | 98.88 16 | 98.47 26 | 98.02 18 | 96.16 9 | 95.58 19 | 90.96 29 | 95.78 18 | 97.84 10 | 96.46 19 | 97.00 18 | 96.17 31 | 98.94 3 | 98.55 21 |
|
MVS_Test | | | 91.81 61 | 92.19 59 | 91.37 75 | 93.24 102 | 96.95 72 | 94.43 58 | 86.25 106 | 91.45 57 | 83.45 79 | 86.31 51 | 85.15 73 | 92.93 54 | 93.99 83 | 94.71 51 | 97.92 87 | 96.77 78 |
|
MDA-MVSNet-bldmvs | | | 73.81 211 | 72.56 215 | 75.28 209 | 72.52 227 | 88.87 205 | 74.95 215 | 82.67 149 | 71.57 212 | 55.02 216 | 65.96 188 | 42.84 230 | 76.11 199 | 70.61 227 | 81.47 217 | 90.38 218 | 86.59 208 |
|
CDPH-MVS | | | 94.80 36 | 95.50 29 | 93.98 41 | 98.34 23 | 98.06 38 | 97.41 25 | 93.23 33 | 92.81 46 | 82.98 81 | 92.51 29 | 94.82 35 | 93.53 48 | 96.08 39 | 96.30 28 | 98.42 26 | 97.94 44 |
|
diffmvs | | | 91.35 65 | 91.81 64 | 90.82 81 | 92.80 107 | 95.62 97 | 93.74 79 | 86.04 107 | 93.17 44 | 85.82 64 | 84.48 70 | 89.74 61 | 90.23 84 | 90.49 144 | 92.45 102 | 96.29 167 | 96.72 79 |
|
PMMVS2 | | | 53.68 226 | 55.72 227 | 51.30 227 | 58.84 233 | 67.02 232 | 54.23 231 | 60.97 230 | 47.50 232 | 19.42 237 | 34.81 230 | 31.97 234 | 30.88 232 | 65.84 229 | 69.99 226 | 83.47 228 | 72.92 226 |
|
PM-MVS | | | 80.29 199 | 79.30 200 | 81.45 199 | 81.91 213 | 88.23 207 | 82.61 203 | 79.01 187 | 79.99 166 | 67.15 185 | 69.07 157 | 51.39 219 | 82.92 170 | 87.55 189 | 85.59 197 | 95.08 189 | 93.28 166 |
|
PS-CasMVS | | | 82.53 186 | 81.54 189 | 83.68 173 | 87.08 191 | 92.54 162 | 86.20 190 | 83.46 141 | 76.46 196 | 65.73 194 | 65.71 191 | 59.41 214 | 81.61 182 | 89.06 179 | 90.55 139 | 98.03 80 | 97.07 70 |
|
UniMVSNet_NR-MVSNet | | | 86.80 117 | 85.86 130 | 87.89 114 | 88.17 152 | 94.07 113 | 90.15 140 | 88.51 85 | 84.20 134 | 73.45 125 | 72.38 143 | 70.30 139 | 88.95 98 | 90.25 146 | 92.21 108 | 98.12 68 | 97.62 56 |
|
PEN-MVS | | | 82.49 187 | 81.58 188 | 83.56 175 | 86.93 192 | 92.05 176 | 86.71 186 | 83.84 135 | 76.94 193 | 64.68 198 | 67.24 163 | 60.11 210 | 81.17 184 | 87.78 185 | 90.70 136 | 98.02 81 | 96.21 104 |
|
TransMVSNet (Re) | | | 82.67 185 | 80.93 197 | 84.69 162 | 88.71 144 | 91.50 186 | 87.90 175 | 87.15 104 | 71.54 214 | 68.24 177 | 63.69 199 | 64.67 188 | 78.51 192 | 91.65 123 | 90.73 135 | 97.64 104 | 92.73 176 |
|
DTE-MVSNet | | | 81.76 194 | 81.04 195 | 82.60 191 | 86.63 195 | 91.48 188 | 85.97 192 | 83.70 136 | 76.45 197 | 62.44 203 | 67.16 164 | 59.98 211 | 78.98 191 | 87.15 192 | 89.93 171 | 97.88 88 | 95.12 143 |
|
DU-MVS | | | 86.12 124 | 84.81 138 | 87.66 115 | 87.77 159 | 93.78 118 | 90.15 140 | 87.87 96 | 84.40 128 | 73.45 125 | 70.59 147 | 64.82 186 | 88.95 98 | 90.14 147 | 92.33 105 | 97.76 93 | 97.62 56 |
|
UniMVSNet (Re) | | | 86.22 122 | 85.46 135 | 87.11 121 | 88.34 150 | 94.42 107 | 89.65 157 | 87.10 105 | 84.39 130 | 74.61 118 | 70.41 150 | 68.10 150 | 85.10 151 | 91.17 130 | 91.79 118 | 97.84 89 | 97.94 44 |
|
CP-MVSNet | | | 83.11 181 | 82.15 181 | 84.23 168 | 87.20 186 | 92.70 156 | 86.42 188 | 83.53 140 | 77.83 188 | 67.67 181 | 66.89 174 | 60.53 209 | 82.47 174 | 89.23 174 | 90.65 137 | 98.08 75 | 97.20 67 |
|
WR-MVS_H | | | 82.86 184 | 82.66 172 | 83.10 181 | 87.44 171 | 93.33 136 | 85.71 196 | 83.20 144 | 77.36 190 | 68.20 178 | 66.37 178 | 65.23 182 | 76.05 200 | 89.35 163 | 90.13 163 | 97.99 84 | 96.89 74 |
|
WR-MVS | | | 83.14 179 | 83.38 154 | 82.87 185 | 87.55 166 | 93.29 137 | 86.36 189 | 84.21 131 | 80.05 165 | 66.41 190 | 66.91 171 | 66.92 163 | 75.66 201 | 88.96 180 | 90.56 138 | 97.05 125 | 96.96 71 |
|
NR-MVSNet | | | 85.46 134 | 84.54 140 | 86.52 129 | 88.33 151 | 93.78 118 | 90.45 124 | 87.87 96 | 84.40 128 | 71.61 137 | 70.59 147 | 62.09 201 | 82.79 171 | 91.75 121 | 91.75 119 | 98.10 71 | 97.44 61 |
|
Baseline_NR-MVSNet | | | 85.28 135 | 83.42 152 | 87.46 119 | 87.77 159 | 90.80 193 | 89.90 151 | 87.69 100 | 83.93 137 | 74.16 121 | 64.72 196 | 66.43 165 | 87.48 112 | 90.14 147 | 90.83 129 | 97.73 96 | 97.11 69 |
|
TranMVSNet+NR-MVSNet | | | 85.57 132 | 84.41 142 | 86.92 123 | 87.67 162 | 93.34 135 | 90.31 131 | 88.43 87 | 83.07 141 | 70.11 159 | 69.99 154 | 65.28 181 | 86.96 117 | 89.73 155 | 92.27 106 | 98.06 78 | 97.17 68 |
|
TSAR-MVS + GP. | | | 95.86 24 | 96.95 16 | 94.60 37 | 94.07 78 | 98.11 37 | 96.30 38 | 91.76 44 | 95.67 16 | 91.07 27 | 96.82 7 | 97.69 12 | 95.71 26 | 95.96 40 | 95.75 38 | 98.68 6 | 98.63 12 |
|
abl_6 | | | | | 94.78 32 | 97.46 37 | 97.99 41 | 95.76 46 | 91.80 43 | 93.72 40 | 91.25 26 | 91.33 36 | 96.47 23 | 94.28 39 | | | 98.14 66 | 97.39 63 |
|
mPP-MVS | | | | | | 98.76 18 | | | | | | | 95.49 32 | | | | | |
|
DWT-MVSNet_training | | | 86.83 116 | 84.44 141 | 89.61 90 | 92.75 109 | 93.82 116 | 91.66 115 | 82.85 146 | 88.57 88 | 87.48 50 | 79.00 101 | 64.24 191 | 88.82 102 | 85.18 200 | 87.50 190 | 94.07 194 | 92.79 171 |
|
testpf | | | 74.66 209 | 76.34 210 | 72.71 214 | 87.34 177 | 80.91 220 | 73.15 220 | 60.30 231 | 78.73 182 | 61.68 206 | 69.83 155 | 62.22 199 | 67.48 210 | 76.83 222 | 78.17 223 | 86.28 225 | 87.68 207 |
|
SixPastTwentyTwo | | | 83.12 180 | 83.44 151 | 82.74 188 | 87.71 161 | 93.11 147 | 82.30 205 | 82.33 154 | 79.24 179 | 64.33 199 | 78.77 103 | 62.75 195 | 84.11 162 | 88.11 183 | 87.89 188 | 95.70 177 | 94.21 154 |
|
LGP-MVS_train | | | 91.83 60 | 92.04 62 | 91.58 66 | 95.46 62 | 96.18 93 | 95.97 44 | 89.85 60 | 90.45 64 | 77.76 106 | 91.92 33 | 80.07 96 | 92.34 60 | 94.27 77 | 93.47 78 | 98.11 70 | 97.90 49 |
|
EPNet_dtu | | | 88.32 105 | 90.61 71 | 85.64 144 | 96.79 48 | 92.27 169 | 92.03 111 | 90.31 57 | 89.05 84 | 65.44 195 | 89.43 42 | 85.90 71 | 74.22 203 | 92.76 106 | 92.09 112 | 95.02 191 | 92.76 174 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
CHOSEN 1792x2688 | | | 88.57 102 | 87.82 103 | 89.44 94 | 95.46 62 | 96.89 74 | 93.74 79 | 85.87 110 | 89.63 79 | 77.42 109 | 61.38 206 | 83.31 79 | 88.80 103 | 93.44 100 | 93.16 90 | 95.37 186 | 96.95 72 |
|
EPNet | | | 93.92 42 | 94.40 37 | 93.36 48 | 97.89 29 | 96.55 80 | 96.08 41 | 92.14 39 | 91.65 55 | 89.16 39 | 94.07 25 | 90.17 60 | 87.78 106 | 95.24 48 | 94.97 48 | 97.09 123 | 98.15 37 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
APD-MVS | | | 97.12 8 | 97.05 13 | 97.19 5 | 99.04 6 | 98.63 15 | 98.45 5 | 96.54 3 | 94.81 31 | 93.50 11 | 96.10 14 | 97.40 16 | 96.81 10 | 97.05 16 | 96.82 14 | 98.80 5 | 98.56 16 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
LP | | | 77.28 207 | 76.57 209 | 78.12 205 | 88.17 152 | 88.06 208 | 80.85 208 | 68.35 224 | 80.78 155 | 61.49 207 | 57.59 212 | 61.80 202 | 77.59 194 | 81.45 216 | 82.34 212 | 92.25 206 | 83.96 216 |
|
CNVR-MVS | | | 97.30 6 | 97.41 7 | 97.18 6 | 99.02 9 | 98.60 17 | 98.15 14 | 96.24 8 | 96.12 11 | 94.10 8 | 95.54 20 | 97.99 8 | 96.99 5 | 97.97 1 | 97.17 5 | 98.57 11 | 98.50 22 |
|
NCCC | | | 96.75 15 | 96.67 20 | 96.85 12 | 99.03 8 | 98.44 28 | 98.15 14 | 96.28 6 | 96.32 8 | 92.39 21 | 92.16 30 | 97.55 14 | 96.68 16 | 97.32 9 | 96.65 17 | 98.55 12 | 98.26 31 |
|
CP-MVS | | | 96.68 16 | 96.59 22 | 96.77 13 | 98.85 17 | 98.58 18 | 98.18 13 | 95.51 20 | 95.34 21 | 92.94 19 | 95.21 23 | 96.25 24 | 96.79 12 | 96.44 31 | 95.77 37 | 98.35 35 | 98.56 16 |
|
NP-MVS | | | | | | | | | | 91.63 56 | | | | | | | | |
|
EG-PatchMatch MVS | | | 81.70 195 | 81.31 193 | 82.15 195 | 88.75 143 | 93.81 117 | 87.14 182 | 78.89 188 | 71.57 212 | 64.12 201 | 61.20 208 | 68.46 147 | 76.73 198 | 91.48 124 | 90.77 132 | 97.28 113 | 91.90 180 |
|
tpm cat1 | | | 84.13 158 | 81.99 185 | 86.63 128 | 91.74 117 | 91.50 186 | 90.68 120 | 75.69 200 | 86.12 109 | 85.44 71 | 72.39 142 | 70.72 133 | 85.16 149 | 80.89 217 | 81.56 216 | 91.07 213 | 90.71 191 |
|
SteuartSystems-ACMMP | | | 97.10 10 | 97.49 6 | 96.65 14 | 98.97 12 | 98.95 5 | 98.43 6 | 95.96 12 | 95.12 24 | 91.46 24 | 96.85 6 | 97.60 13 | 96.37 21 | 97.76 3 | 97.16 6 | 98.68 6 | 98.97 7 |
Skip Steuart: Steuart Systems R&D Blog. |
tpmp4_e23 | | | 85.67 130 | 84.28 143 | 87.30 120 | 91.96 115 | 92.00 178 | 92.06 110 | 76.27 197 | 87.95 94 | 83.59 78 | 76.97 114 | 70.88 132 | 87.52 110 | 84.80 204 | 84.73 203 | 92.40 205 | 92.61 178 |
|
CostFormer | | | 86.78 118 | 86.05 123 | 87.62 118 | 92.15 112 | 93.20 141 | 91.55 116 | 75.83 199 | 88.11 93 | 85.29 72 | 81.76 90 | 76.22 116 | 87.80 105 | 84.45 205 | 85.21 201 | 93.12 197 | 93.42 165 |
|
CR-MVSNet | | | 85.48 133 | 86.29 121 | 84.53 165 | 91.08 127 | 92.10 171 | 89.18 162 | 73.30 212 | 84.75 124 | 71.08 144 | 73.12 141 | 77.91 106 | 86.27 126 | 91.48 124 | 90.75 133 | 96.27 168 | 93.94 156 |
|
Patchmtry | | | | | | | 92.39 168 | 89.18 162 | 73.30 212 | | 71.08 144 | | | | | | | |
|
PatchT | | | 83.86 163 | 85.51 134 | 81.94 196 | 88.41 149 | 91.56 185 | 78.79 211 | 71.57 215 | 84.08 136 | 71.08 144 | 70.62 146 | 76.13 117 | 86.27 126 | 91.48 124 | 90.75 133 | 95.52 184 | 93.94 156 |
|
tpmrst | | | 83.72 166 | 83.45 150 | 84.03 171 | 92.21 111 | 91.66 183 | 88.74 169 | 73.58 209 | 88.14 92 | 72.67 127 | 77.37 112 | 72.11 127 | 86.34 124 | 82.94 211 | 82.05 213 | 90.63 216 | 89.86 198 |
|
tpm | | | 83.16 178 | 83.64 147 | 82.60 191 | 90.75 129 | 91.05 189 | 88.49 171 | 73.99 205 | 82.36 144 | 67.08 186 | 78.10 107 | 68.79 145 | 84.17 160 | 85.95 198 | 85.96 196 | 91.09 212 | 93.23 167 |
|
DELS-MVS | | | 93.71 43 | 93.47 43 | 94.00 39 | 96.82 47 | 98.39 30 | 96.80 33 | 91.07 51 | 89.51 81 | 89.94 36 | 83.80 76 | 89.29 62 | 90.95 76 | 97.32 9 | 97.65 2 | 98.42 26 | 98.32 30 |
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 | | | 84.82 141 | 85.90 128 | 83.56 175 | 91.10 125 | 92.10 171 | 88.73 170 | 71.11 216 | 84.75 124 | 68.79 172 | 73.56 134 | 77.62 108 | 85.33 148 | 90.08 151 | 89.43 181 | 96.32 166 | 93.77 161 |
|
no-one | | | 49.70 227 | 49.06 228 | 50.46 228 | 65.32 232 | 67.46 231 | 38.16 235 | 68.73 222 | 34.38 235 | 22.88 236 | 24.40 231 | 22.99 235 | 28.55 233 | 51.41 231 | 70.93 225 | 79.08 231 | 71.81 228 |
|
MVSTER | | | 91.73 62 | 91.61 66 | 91.86 63 | 93.18 103 | 94.56 102 | 94.37 59 | 87.90 94 | 90.16 71 | 88.69 43 | 89.23 43 | 81.28 93 | 88.92 100 | 95.75 43 | 93.95 65 | 98.12 68 | 96.37 95 |
|
CPTT-MVS | | | 95.54 27 | 95.07 32 | 96.10 21 | 97.88 30 | 97.98 42 | 97.92 21 | 94.86 26 | 94.56 34 | 92.16 22 | 91.01 37 | 95.71 30 | 96.97 7 | 94.56 71 | 93.50 77 | 96.81 156 | 98.14 38 |
|
GBi-Net | | | 90.21 75 | 90.11 76 | 90.32 83 | 88.66 146 | 93.65 123 | 94.25 68 | 85.78 111 | 90.03 73 | 85.56 67 | 77.38 109 | 86.13 67 | 89.38 91 | 93.97 84 | 94.16 58 | 98.31 43 | 95.47 126 |
|
PVSNet_Blended_VisFu | | | 91.92 58 | 92.39 57 | 91.36 76 | 95.45 64 | 97.85 45 | 92.25 102 | 89.54 72 | 88.53 90 | 87.47 51 | 79.82 98 | 90.53 56 | 85.47 147 | 96.31 35 | 95.16 46 | 97.99 84 | 98.56 16 |
|
PVSNet_BlendedMVS | | | 92.80 48 | 92.44 55 | 93.23 49 | 96.02 54 | 97.83 46 | 93.74 79 | 90.58 54 | 91.86 52 | 90.69 32 | 85.87 58 | 82.04 88 | 90.01 85 | 96.39 32 | 95.26 44 | 98.34 37 | 97.81 51 |
|
PVSNet_Blended | | | 92.80 48 | 92.44 55 | 93.23 49 | 96.02 54 | 97.83 46 | 93.74 79 | 90.58 54 | 91.86 52 | 90.69 32 | 85.87 58 | 82.04 88 | 90.01 85 | 96.39 32 | 95.26 44 | 98.34 37 | 97.81 51 |
|
FMVSNet5 | | | 84.47 149 | 84.72 139 | 84.18 169 | 83.30 211 | 88.43 206 | 88.09 174 | 79.42 186 | 84.25 132 | 74.14 122 | 73.15 140 | 78.74 100 | 83.65 166 | 91.19 129 | 91.19 127 | 96.46 163 | 86.07 210 |
|
test1 | | | 90.21 75 | 90.11 76 | 90.32 83 | 88.66 146 | 93.65 123 | 94.25 68 | 85.78 111 | 90.03 73 | 85.56 67 | 77.38 109 | 86.13 67 | 89.38 91 | 93.97 84 | 94.16 58 | 98.31 43 | 95.47 126 |
|
new_pmnet | | | 72.29 215 | 73.25 214 | 71.16 219 | 75.35 224 | 81.38 218 | 73.72 218 | 69.27 220 | 75.97 201 | 49.84 224 | 56.27 213 | 56.12 217 | 69.08 208 | 81.73 213 | 80.86 218 | 89.72 222 | 80.44 220 |
|
FMVSNet3 | | | 90.19 77 | 90.06 78 | 90.34 82 | 88.69 145 | 93.85 115 | 94.58 57 | 85.78 111 | 90.03 73 | 85.56 67 | 77.38 109 | 86.13 67 | 89.22 94 | 93.29 103 | 94.36 55 | 98.20 62 | 95.40 130 |
|
dps | | | 85.00 138 | 83.21 161 | 87.08 122 | 90.73 130 | 92.55 161 | 89.34 159 | 75.29 201 | 84.94 123 | 87.01 54 | 79.27 100 | 67.69 153 | 87.27 114 | 84.22 207 | 83.56 207 | 92.83 199 | 90.25 195 |
|
FMVSNet2 | | | 89.61 83 | 89.14 85 | 90.16 87 | 88.66 146 | 93.65 123 | 94.25 68 | 85.44 118 | 88.57 88 | 84.96 75 | 73.53 135 | 83.82 77 | 89.38 91 | 94.23 78 | 94.68 52 | 98.31 43 | 95.47 126 |
|
FMVSNet1 | | | 87.33 112 | 86.00 126 | 88.89 99 | 87.13 189 | 92.83 154 | 93.08 90 | 84.46 129 | 81.35 151 | 82.20 82 | 66.33 181 | 77.96 105 | 88.96 97 | 93.97 84 | 94.16 58 | 97.54 108 | 95.38 131 |
|
N_pmnet | | | 77.55 206 | 76.68 208 | 78.56 204 | 85.43 204 | 87.30 212 | 78.84 210 | 81.88 160 | 78.30 185 | 60.61 208 | 61.46 205 | 62.15 200 | 74.03 206 | 82.04 212 | 80.69 219 | 90.59 217 | 84.81 214 |
|
UGNet | | | 91.52 64 | 93.41 44 | 89.32 95 | 94.13 73 | 97.15 67 | 91.83 113 | 89.01 79 | 90.62 62 | 85.86 63 | 86.83 50 | 91.73 48 | 77.40 195 | 94.68 67 | 94.43 53 | 97.71 97 | 98.40 29 |
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 | | | 80.43 198 | 80.94 196 | 79.84 200 | 84.82 206 | 90.87 191 | 84.23 199 | 73.80 206 | 80.28 163 | 64.33 199 | 70.05 153 | 68.77 146 | 79.67 187 | 84.83 203 | 83.50 208 | 92.17 207 | 88.25 206 |
|
MDTV_nov1_ep13 | | | 86.64 120 | 87.50 110 | 85.65 143 | 90.73 130 | 93.69 122 | 89.96 147 | 78.03 192 | 89.48 82 | 76.85 111 | 84.92 67 | 82.42 86 | 86.14 131 | 86.85 195 | 86.15 193 | 92.17 207 | 88.97 201 |
|
MIMVSNet1 | | | 73.19 213 | 73.70 213 | 72.60 216 | 65.42 231 | 86.69 214 | 75.56 214 | 79.65 184 | 67.87 219 | 55.30 215 | 45.24 227 | 56.41 216 | 63.79 216 | 86.98 193 | 87.66 189 | 95.85 173 | 85.04 212 |
|
MIMVSNet | | | 82.97 182 | 84.00 146 | 81.77 198 | 82.23 212 | 92.25 170 | 87.40 181 | 72.73 214 | 81.48 148 | 69.55 165 | 68.79 158 | 72.42 125 | 81.82 180 | 92.23 116 | 92.25 107 | 96.89 149 | 88.61 202 |
|
IterMVS-LS | | | 88.60 99 | 88.45 93 | 88.78 101 | 92.02 114 | 92.44 167 | 92.00 112 | 83.57 139 | 86.52 106 | 78.90 104 | 78.61 105 | 81.34 92 | 89.12 95 | 90.68 140 | 93.18 89 | 97.10 122 | 96.35 96 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
CDS-MVSNet | | | 88.34 104 | 88.71 91 | 87.90 113 | 90.70 132 | 94.54 103 | 92.38 96 | 86.02 108 | 80.37 161 | 79.42 101 | 79.30 99 | 83.43 78 | 82.04 177 | 93.39 101 | 94.01 63 | 96.86 154 | 95.93 112 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
IterMVS | | | 85.25 136 | 86.49 119 | 83.80 172 | 90.42 133 | 90.77 194 | 90.02 145 | 78.04 191 | 84.10 135 | 66.27 191 | 77.28 113 | 78.41 102 | 83.01 169 | 90.88 133 | 89.72 177 | 95.04 190 | 94.24 152 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
MVS_111021_LR | | | 94.84 34 | 95.57 28 | 94.00 39 | 97.11 43 | 97.72 51 | 94.88 56 | 91.16 50 | 95.24 23 | 88.74 42 | 96.03 16 | 91.52 50 | 94.33 38 | 95.96 40 | 95.01 47 | 97.79 91 | 97.49 59 |
|
HQP-MVS | | | 92.39 53 | 92.49 54 | 92.29 60 | 95.65 58 | 95.94 95 | 95.64 49 | 92.12 40 | 92.46 50 | 79.65 100 | 91.97 32 | 82.68 84 | 92.92 55 | 93.47 99 | 92.77 98 | 97.74 95 | 98.12 40 |
|
QAPM | | | 94.13 41 | 94.33 40 | 93.90 42 | 97.82 31 | 98.37 31 | 96.47 36 | 90.89 53 | 92.73 48 | 85.63 66 | 85.35 60 | 93.87 38 | 94.17 40 | 95.71 44 | 95.90 35 | 98.40 30 | 98.42 27 |
|
Vis-MVSNet | | | 89.36 88 | 91.49 68 | 86.88 124 | 92.10 113 | 97.60 53 | 92.16 108 | 85.89 109 | 84.21 133 | 75.20 117 | 82.58 84 | 87.13 63 | 77.40 195 | 95.90 42 | 95.63 39 | 98.51 13 | 97.36 64 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
MVS-HIRNet | | | 78.16 203 | 77.57 206 | 78.83 203 | 85.83 200 | 87.76 209 | 76.67 212 | 70.22 218 | 75.82 202 | 67.39 182 | 55.61 214 | 70.52 134 | 81.96 179 | 86.67 196 | 85.06 202 | 90.93 215 | 81.58 219 |
|
HyFIR lowres test | | | 87.87 108 | 86.42 120 | 89.57 91 | 95.56 59 | 96.99 71 | 92.37 97 | 84.15 132 | 86.64 103 | 77.17 110 | 57.65 211 | 83.97 76 | 91.08 75 | 92.09 118 | 92.44 103 | 97.09 123 | 95.16 142 |
|
EPMVS | | | 85.77 128 | 86.24 122 | 85.23 151 | 92.76 108 | 93.78 118 | 89.91 149 | 73.60 208 | 90.19 69 | 74.22 120 | 82.18 88 | 78.06 104 | 87.55 109 | 85.61 199 | 85.38 200 | 93.32 196 | 88.48 204 |
|
TAMVS | | | 84.94 140 | 84.95 136 | 84.93 160 | 88.82 142 | 93.18 143 | 88.44 172 | 81.28 166 | 77.16 191 | 73.76 124 | 75.43 126 | 76.57 115 | 82.04 177 | 90.59 141 | 90.79 130 | 95.22 188 | 90.94 188 |
|
IS_MVSNet | | | 91.87 59 | 93.35 45 | 90.14 88 | 94.09 77 | 97.73 49 | 93.09 89 | 88.12 90 | 88.71 86 | 79.98 98 | 84.49 69 | 90.63 55 | 87.49 111 | 97.07 15 | 96.96 10 | 98.07 76 | 97.88 50 |
|
RPSCF | | | 89.68 82 | 89.24 83 | 90.20 86 | 92.97 105 | 92.93 151 | 92.30 100 | 87.69 100 | 90.44 65 | 85.12 73 | 91.68 34 | 85.84 72 | 90.69 79 | 87.34 190 | 86.07 194 | 92.46 204 | 90.37 194 |
|
Vis-MVSNet (Re-imp) | | | 90.54 72 | 92.76 50 | 87.94 112 | 93.73 94 | 96.94 73 | 92.17 107 | 87.91 93 | 88.77 85 | 76.12 115 | 83.68 77 | 90.80 52 | 79.49 190 | 96.34 34 | 96.35 24 | 98.21 61 | 96.46 92 |
|
MVS_111021_HR | | | 94.84 34 | 95.91 26 | 93.60 46 | 97.35 38 | 98.46 27 | 95.08 53 | 91.19 49 | 94.18 36 | 85.97 60 | 95.38 21 | 92.56 44 | 93.61 47 | 96.61 25 | 96.25 29 | 98.40 30 | 97.92 46 |
|
CSCG | | | 95.68 26 | 95.46 31 | 95.93 23 | 98.71 19 | 99.07 4 | 97.13 30 | 93.55 31 | 95.48 20 | 93.35 15 | 90.61 39 | 93.82 39 | 95.16 30 | 94.60 70 | 95.57 40 | 97.70 99 | 99.08 5 |
|
PatchMatch-RL | | | 90.30 74 | 88.93 88 | 91.89 62 | 95.41 65 | 95.68 96 | 90.94 118 | 88.67 84 | 89.80 78 | 86.95 56 | 85.90 56 | 72.51 124 | 92.46 58 | 93.56 97 | 92.18 109 | 96.93 141 | 92.89 170 |
|
TDRefinement | | | 84.97 139 | 83.39 153 | 86.81 125 | 92.97 105 | 94.12 111 | 92.18 105 | 87.77 99 | 82.78 143 | 71.31 141 | 68.43 159 | 68.07 151 | 81.10 185 | 89.70 157 | 89.03 185 | 95.55 183 | 91.62 181 |
|
USDC | | | 86.73 119 | 85.96 127 | 87.63 117 | 91.64 118 | 93.97 114 | 92.76 92 | 84.58 128 | 88.19 91 | 70.67 149 | 80.10 97 | 67.86 152 | 89.43 89 | 91.81 120 | 89.77 175 | 96.69 160 | 90.05 197 |
|
EPP-MVSNet | | | 92.13 55 | 93.06 47 | 91.05 79 | 93.66 96 | 97.30 58 | 92.18 105 | 87.90 94 | 90.24 67 | 83.63 77 | 86.14 54 | 90.52 58 | 90.76 78 | 94.82 64 | 94.38 54 | 98.18 64 | 97.98 43 |
|
PMMVS | | | 89.88 79 | 91.19 69 | 88.35 104 | 89.73 137 | 91.97 179 | 90.62 121 | 81.92 159 | 90.57 63 | 80.58 95 | 92.16 30 | 86.85 65 | 91.17 73 | 92.31 113 | 91.35 126 | 96.11 170 | 93.11 169 |
|
ACMMP | | | 95.54 27 | 95.49 30 | 95.61 28 | 98.27 25 | 98.53 22 | 97.16 29 | 94.86 26 | 94.88 30 | 89.34 37 | 95.36 22 | 91.74 47 | 95.50 28 | 95.51 46 | 94.16 58 | 98.50 15 | 98.22 33 |
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 | | | 93.69 44 | 92.50 53 | 95.06 31 | 97.11 43 | 97.36 55 | 93.88 76 | 93.30 32 | 95.64 18 | 93.44 14 | 80.32 96 | 90.73 54 | 94.99 32 | 93.58 94 | 93.33 81 | 97.67 102 | 96.57 91 |
|
PatchmatchNet | | | 85.70 129 | 86.65 116 | 84.60 163 | 91.79 116 | 93.40 133 | 89.27 160 | 73.62 207 | 90.19 69 | 72.63 128 | 82.74 83 | 81.93 90 | 87.64 107 | 84.99 201 | 84.29 206 | 92.64 201 | 89.00 200 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
PHI-MVS | | | 95.86 24 | 96.93 17 | 94.61 36 | 97.60 36 | 98.65 14 | 96.49 35 | 93.13 34 | 94.07 37 | 87.91 48 | 97.12 4 | 97.17 18 | 93.90 45 | 96.46 29 | 96.93 11 | 98.64 8 | 98.10 42 |
|
OMC-MVS | | | 94.49 38 | 94.36 38 | 94.64 35 | 97.17 42 | 97.73 49 | 95.49 50 | 92.25 38 | 96.18 10 | 90.34 35 | 88.51 46 | 92.88 43 | 94.90 33 | 94.92 55 | 94.17 57 | 97.69 100 | 96.15 106 |
|
AdaColmap | | | 95.02 32 | 93.71 41 | 96.54 18 | 98.51 21 | 97.76 48 | 96.69 34 | 95.94 14 | 93.72 40 | 93.50 11 | 89.01 45 | 90.53 56 | 96.49 18 | 94.51 73 | 93.76 68 | 98.07 76 | 96.69 81 |
|
DeepMVS_CX | | | | | | | 71.82 229 | 68.37 224 | 48.05 233 | 77.38 189 | 46.88 229 | 65.77 190 | 47.03 227 | 67.48 210 | 64.27 230 | | 76.89 232 | 76.72 223 |
|
TinyColmap | | | 84.04 161 | 82.01 184 | 86.42 130 | 90.87 128 | 91.84 180 | 88.89 168 | 84.07 133 | 82.11 146 | 69.89 163 | 71.08 145 | 60.81 207 | 89.04 96 | 90.52 142 | 89.19 183 | 95.76 174 | 88.50 203 |
|
MAR-MVS | | | 92.71 50 | 92.63 51 | 92.79 57 | 97.70 34 | 97.15 67 | 93.75 78 | 87.98 92 | 90.71 60 | 85.76 65 | 86.28 53 | 86.38 66 | 94.35 37 | 94.95 53 | 95.49 41 | 97.22 115 | 97.44 61 |
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 | | | 90.42 73 | 88.25 97 | 92.94 56 | 96.67 49 | 94.41 108 | 93.96 72 | 92.91 35 | 89.59 80 | 86.26 59 | 76.74 115 | 80.92 94 | 90.43 82 | 92.60 110 | 92.08 113 | 97.44 111 | 91.41 183 |
|
LS3D | | | 91.97 57 | 90.98 70 | 93.12 53 | 97.03 45 | 97.09 70 | 95.33 52 | 95.59 17 | 92.47 49 | 79.26 102 | 81.60 92 | 82.77 83 | 94.39 36 | 94.28 76 | 94.23 56 | 97.14 120 | 94.45 150 |
|
CLD-MVS | | | 92.50 52 | 91.96 63 | 93.13 52 | 93.93 83 | 96.24 91 | 95.69 47 | 88.77 82 | 92.92 45 | 89.01 40 | 88.19 48 | 81.74 91 | 93.13 52 | 93.63 92 | 93.08 93 | 98.23 59 | 97.91 48 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
FPMVS | | | 69.87 217 | 67.10 220 | 73.10 212 | 84.09 209 | 78.35 224 | 79.40 209 | 76.41 196 | 71.92 210 | 57.71 214 | 54.06 220 | 50.04 221 | 56.72 222 | 71.19 226 | 68.70 227 | 84.25 227 | 75.43 224 |
|
Gipuma | | | 58.52 225 | 56.17 226 | 61.27 224 | 67.14 230 | 58.06 233 | 52.16 233 | 68.40 223 | 69.00 217 | 45.02 230 | 22.79 232 | 20.57 237 | 55.11 223 | 76.27 223 | 79.33 222 | 79.80 230 | 67.16 230 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |