DeepPCF-MVS | | 69.58 1 | 79.03 11 | 79.00 12 | 79.13 15 | 84.92 57 | 60.32 46 | 83.03 55 | 85.33 28 | 62.86 52 | 80.17 13 | 90.03 37 | 61.76 11 | 88.95 20 | 74.21 34 | 88.67 27 | 88.12 14 |
|
DeepC-MVS | | 69.38 2 | 78.56 17 | 78.14 23 | 79.83 4 | 83.60 65 | 61.62 26 | 84.17 38 | 86.85 8 | 63.23 44 | 73.84 59 | 90.25 33 | 57.68 26 | 89.96 10 | 74.62 32 | 89.03 22 | 87.89 19 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
DeepC-MVS_fast | | 68.24 3 | 77.25 34 | 76.63 38 | 79.12 16 | 86.15 33 | 60.86 39 | 84.71 31 | 84.85 38 | 61.98 72 | 73.06 69 | 88.88 57 | 53.72 60 | 89.06 19 | 68.27 67 | 88.04 38 | 87.42 39 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
3Dnovator+ | | 66.72 4 | 75.84 49 | 74.57 56 | 79.66 6 | 82.40 78 | 59.92 51 | 85.83 20 | 86.32 18 | 66.92 8 | 67.80 144 | 89.24 51 | 42.03 180 | 89.38 14 | 64.07 102 | 86.50 56 | 89.69 1 |
|
3Dnovator | | 64.47 5 | 72.49 81 | 71.39 87 | 75.79 70 | 77.70 166 | 58.99 66 | 80.66 93 | 83.15 77 | 62.24 64 | 65.46 180 | 86.59 85 | 42.38 178 | 85.52 94 | 59.59 141 | 84.72 63 | 82.85 182 |
|
ACMP | | 63.53 6 | 72.30 84 | 71.20 92 | 75.59 79 | 80.28 109 | 57.54 87 | 82.74 61 | 82.84 84 | 60.58 89 | 65.24 187 | 86.18 93 | 39.25 209 | 86.03 83 | 66.95 81 | 76.79 150 | 83.22 171 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
ACMM | | 61.98 7 | 70.80 104 | 69.73 109 | 74.02 106 | 80.59 106 | 58.59 73 | 82.68 63 | 82.02 93 | 55.46 182 | 67.18 152 | 84.39 125 | 38.51 216 | 83.17 143 | 60.65 131 | 76.10 154 | 80.30 221 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
PCF-MVS | | 61.88 8 | 70.95 101 | 69.49 113 | 75.35 81 | 77.63 169 | 55.71 117 | 76.04 175 | 81.81 97 | 50.30 240 | 69.66 108 | 85.40 111 | 52.51 70 | 84.89 108 | 51.82 191 | 80.24 105 | 85.45 103 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
OpenMVS | | 61.03 9 | 68.85 140 | 67.56 143 | 72.70 144 | 74.26 231 | 53.99 136 | 81.21 87 | 81.34 108 | 52.70 214 | 62.75 215 | 85.55 107 | 38.86 214 | 84.14 122 | 48.41 216 | 83.01 73 | 79.97 226 |
|
TAPA-MVS | | 59.36 10 | 66.60 189 | 65.20 194 | 70.81 181 | 76.63 191 | 48.75 210 | 76.52 163 | 80.04 135 | 50.64 238 | 65.24 187 | 84.93 113 | 39.15 211 | 78.54 230 | 36.77 290 | 76.88 147 | 85.14 113 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
ACMH+ | | 57.40 11 | 66.12 195 | 64.06 199 | 72.30 153 | 77.79 165 | 52.83 152 | 80.39 97 | 78.03 175 | 57.30 142 | 57.47 266 | 82.55 157 | 27.68 306 | 84.17 121 | 45.54 238 | 69.78 228 | 79.90 227 |
|
IB-MVS | | 56.42 12 | 65.40 205 | 62.73 218 | 73.40 129 | 74.89 217 | 52.78 153 | 73.09 222 | 75.13 216 | 55.69 178 | 58.48 260 | 73.73 291 | 32.86 268 | 86.32 79 | 50.63 198 | 70.11 221 | 81.10 211 |
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 |
HY-MVS | | 56.14 13 | 64.55 214 | 63.89 201 | 66.55 235 | 74.73 222 | 41.02 282 | 69.96 263 | 74.43 224 | 49.29 248 | 61.66 231 | 80.92 192 | 47.43 129 | 76.68 253 | 44.91 245 | 71.69 202 | 81.94 195 |
|
PLC | | 56.13 14 | 65.09 208 | 63.21 212 | 70.72 184 | 81.04 99 | 54.87 131 | 78.57 123 | 77.47 184 | 48.51 255 | 55.71 275 | 81.89 172 | 33.71 258 | 79.71 208 | 41.66 270 | 70.37 216 | 77.58 251 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
ACMH | | 55.70 15 | 65.20 207 | 63.57 208 | 70.07 194 | 78.07 158 | 52.01 168 | 79.48 115 | 79.69 139 | 55.75 177 | 56.59 271 | 80.98 190 | 27.12 310 | 80.94 190 | 42.90 262 | 71.58 204 | 77.25 257 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
LTVRE_ROB | | 55.42 16 | 63.15 227 | 61.23 235 | 68.92 213 | 76.57 193 | 47.80 219 | 59.92 311 | 76.39 198 | 54.35 203 | 58.67 256 | 82.46 160 | 29.44 296 | 81.49 178 | 42.12 266 | 71.14 207 | 77.46 252 |
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 | | 52.97 17 | 61.27 245 | 58.81 247 | 68.64 216 | 74.63 223 | 52.51 159 | 78.42 128 | 73.30 235 | 49.92 245 | 50.96 309 | 81.51 180 | 23.06 326 | 79.40 213 | 31.63 316 | 65.85 266 | 74.01 292 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
OpenMVS_ROB | | 52.78 18 | 60.03 249 | 58.14 254 | 65.69 251 | 70.47 276 | 44.82 250 | 75.33 183 | 70.86 248 | 45.04 285 | 56.06 273 | 76.00 270 | 26.89 313 | 79.65 209 | 35.36 300 | 67.29 257 | 72.60 300 |
|
PVSNet | | 50.76 19 | 58.40 259 | 57.39 257 | 61.42 279 | 75.53 211 | 44.04 259 | 61.43 304 | 63.45 294 | 47.04 272 | 56.91 268 | 73.61 292 | 27.00 312 | 64.76 302 | 39.12 279 | 72.40 194 | 75.47 274 |
|
PVSNet_0 | | 43.31 20 | 47.46 303 | 45.64 305 | 52.92 311 | 67.60 304 | 44.65 253 | 54.06 325 | 54.64 326 | 41.59 312 | 46.15 324 | 58.75 332 | 30.99 283 | 58.66 319 | 32.18 309 | 24.81 340 | 55.46 335 |
|
CMPMVS | | 42.80 21 | 57.81 265 | 55.97 269 | 63.32 266 | 60.98 334 | 47.38 226 | 64.66 293 | 69.50 258 | 32.06 331 | 46.83 322 | 77.80 249 | 29.50 295 | 71.36 275 | 48.68 213 | 73.75 170 | 71.21 314 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
PMVS | | 28.69 22 | 36.22 312 | 33.29 315 | 45.02 323 | 36.82 350 | 35.98 317 | 54.68 324 | 48.74 336 | 26.31 337 | 21.02 342 | 51.61 337 | 2.88 353 | 60.10 316 | 9.99 345 | 47.58 331 | 38.99 341 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
MVE | | 17.77 23 | 21.41 318 | 17.77 321 | 32.34 328 | 34.34 351 | 25.44 342 | 16.11 346 | 24.11 350 | 11.19 346 | 13.22 346 | 31.92 341 | 1.58 354 | 30.95 348 | 10.47 343 | 17.03 342 | 40.62 340 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
SED-MVS | | | 81.56 1 | 82.30 1 | 79.32 9 | 87.77 4 | 58.90 67 | 87.82 5 | 86.78 11 | 64.18 32 | 85.97 1 | 91.84 6 | 66.87 2 | 90.83 2 | 78.63 12 | 90.87 3 | 88.23 10 |
|
IU-MVS | | | | | | 87.77 4 | 59.15 59 | | 85.53 25 | 53.93 205 | 84.64 3 | | | | 79.07 6 | 90.87 3 | 88.37 7 |
|
OPU-MVS | | | | | 79.83 4 | 87.54 10 | 60.93 38 | 87.82 5 | | | | 89.89 41 | 67.01 1 | 90.33 8 | 73.16 44 | 91.15 2 | 88.23 10 |
|
test_241102_TWO | | | | | | | | | 86.73 13 | 64.18 32 | 84.26 4 | 91.84 6 | 65.19 4 | 90.83 2 | 78.63 12 | 90.70 5 | 87.65 29 |
|
test_241102_ONE | | | | | | 87.77 4 | 58.90 67 | | 86.78 11 | 64.20 31 | 85.97 1 | 91.34 10 | 66.87 2 | 90.78 4 | | | |
|
xxxxxxxxxxxxxcwj | | | 78.37 20 | 78.25 22 | 78.76 26 | 86.17 31 | 61.30 31 | 83.98 44 | 79.95 136 | 59.00 120 | 79.16 16 | 90.75 15 | 57.96 22 | 87.09 54 | 77.08 20 | 90.18 11 | 87.87 21 |
|
SF-MVS | | | 78.82 12 | 79.22 11 | 77.60 46 | 82.88 75 | 57.83 83 | 84.99 30 | 88.13 3 | 61.86 73 | 79.16 16 | 90.75 15 | 57.96 22 | 87.09 54 | 77.08 20 | 90.18 11 | 87.87 21 |
|
ETH3D cwj APD-0.16 | | | 78.02 24 | 78.13 24 | 77.71 44 | 82.10 80 | 58.65 72 | 82.72 62 | 87.55 5 | 58.33 134 | 78.05 25 | 90.06 35 | 58.35 21 | 87.65 43 | 76.15 25 | 89.86 15 | 86.82 54 |
|
cl-mvsnet2 | | | 67.47 170 | 66.45 169 | 70.54 187 | 69.85 288 | 46.49 232 | 73.85 213 | 77.35 188 | 55.07 191 | 65.51 179 | 77.92 245 | 47.64 124 | 81.10 186 | 61.58 127 | 69.32 235 | 84.01 145 |
|
miper_ehance_all_eth | | | 68.03 161 | 67.24 159 | 70.40 189 | 70.54 275 | 46.21 237 | 73.98 208 | 78.68 159 | 55.07 191 | 66.05 169 | 77.80 249 | 52.16 76 | 81.31 181 | 61.53 128 | 69.32 235 | 83.67 158 |
|
miper_enhance_ethall | | | 67.11 178 | 66.09 181 | 70.17 193 | 69.21 294 | 45.98 240 | 72.85 226 | 78.41 171 | 51.38 229 | 65.65 177 | 75.98 273 | 51.17 87 | 81.25 182 | 60.82 130 | 69.32 235 | 83.29 170 |
|
ZNCC-MVS | | | 78.82 12 | 78.67 16 | 79.30 10 | 86.43 25 | 62.05 21 | 86.62 9 | 86.01 19 | 63.32 42 | 75.08 38 | 90.47 25 | 53.96 56 | 88.68 23 | 76.48 23 | 89.63 20 | 87.16 46 |
|
ETH3 D test6400 | | | 79.14 10 | 79.32 9 | 78.61 29 | 86.34 26 | 58.11 79 | 84.65 32 | 87.66 4 | 58.56 129 | 78.87 20 | 89.54 46 | 63.67 10 | 89.57 13 | 74.60 33 | 89.98 13 | 88.14 13 |
|
cl-mvsnet_ | | | 67.18 175 | 66.26 179 | 69.94 196 | 70.20 280 | 45.74 242 | 73.30 218 | 76.83 195 | 55.10 187 | 65.27 183 | 79.57 222 | 47.39 130 | 80.53 199 | 59.41 144 | 69.22 239 | 83.53 164 |
|
cl-mvsnet1 | | | 67.18 175 | 66.26 179 | 69.94 196 | 70.20 280 | 45.74 242 | 73.29 219 | 76.83 195 | 55.10 187 | 65.27 183 | 79.58 221 | 47.38 131 | 80.53 199 | 59.43 143 | 69.22 239 | 83.54 163 |
|
eth_miper_zixun_eth | | | 67.63 167 | 66.28 178 | 71.67 161 | 71.60 264 | 48.33 214 | 73.68 216 | 77.88 176 | 55.80 176 | 65.91 172 | 78.62 238 | 47.35 132 | 82.88 150 | 59.45 142 | 66.25 263 | 83.81 151 |
|
9.14 | | | | 78.75 15 | | 83.10 69 | | 84.15 39 | 88.26 2 | 59.90 105 | 78.57 23 | 90.36 26 | 57.51 28 | 86.86 60 | 77.39 15 | 89.52 21 | |
|
testtj | | | 78.47 18 | 78.43 18 | 78.61 29 | 86.82 13 | 60.67 42 | 86.07 16 | 85.38 27 | 62.12 66 | 78.65 22 | 90.29 31 | 55.76 38 | 89.31 15 | 73.55 42 | 87.22 45 | 85.84 84 |
|
uanet_test | | | 0.00 326 | 0.00 328 | 0.00 337 | 0.00 356 | 0.00 356 | 0.00 348 | 0.00 356 | 0.00 352 | 0.00 353 | 0.00 353 | 0.00 357 | 0.00 352 | 0.00 351 | 0.00 349 | 0.00 350 |
|
ETH3D-3000-0.1 | | | 78.58 15 | 78.91 13 | 77.61 45 | 83.06 70 | 57.86 82 | 84.14 41 | 88.31 1 | 60.37 93 | 79.14 18 | 90.35 27 | 57.76 25 | 87.00 57 | 77.16 19 | 89.90 14 | 87.97 18 |
|
save fliter | | | | | | 86.17 31 | 61.30 31 | 83.98 44 | 79.66 141 | 59.00 120 | | | | | | | |
|
ET-MVSNet_ETH3D | | | 67.96 163 | 65.72 186 | 74.68 92 | 76.67 190 | 55.62 121 | 75.11 189 | 74.74 221 | 52.91 212 | 60.03 241 | 80.12 210 | 33.68 259 | 82.64 159 | 61.86 123 | 76.34 153 | 85.78 86 |
|
UniMVSNet_ETH3D | | | 67.60 168 | 67.07 162 | 69.18 211 | 77.39 178 | 42.29 272 | 74.18 206 | 75.59 209 | 60.37 93 | 66.77 157 | 86.06 97 | 37.64 225 | 78.93 229 | 52.16 189 | 73.49 176 | 86.32 71 |
|
EIA-MVS | | | 71.78 92 | 70.60 98 | 75.30 83 | 79.85 119 | 53.54 142 | 77.27 149 | 83.26 75 | 57.92 137 | 66.49 161 | 79.39 226 | 52.07 77 | 86.69 65 | 60.05 136 | 79.14 122 | 85.66 94 |
|
miper_lstm_enhance | | | 62.03 237 | 60.88 238 | 65.49 253 | 66.71 309 | 46.25 235 | 56.29 322 | 75.70 207 | 50.68 236 | 61.27 234 | 75.48 278 | 40.21 201 | 68.03 289 | 56.31 154 | 65.25 271 | 82.18 191 |
|
ETV-MVS | | | 74.46 60 | 73.84 63 | 76.33 64 | 79.27 127 | 55.24 127 | 79.22 116 | 85.00 35 | 64.97 21 | 72.65 74 | 79.46 225 | 53.65 64 | 87.87 38 | 67.45 76 | 82.91 77 | 85.89 83 |
|
CS-MVS | | | 74.18 65 | 73.60 65 | 75.92 68 | 78.99 133 | 52.53 157 | 80.61 94 | 85.93 20 | 61.17 82 | 71.15 88 | 79.34 229 | 54.52 50 | 88.86 22 | 66.07 84 | 84.67 64 | 86.38 62 |
|
D2MVS | | | 62.30 234 | 60.29 241 | 68.34 220 | 66.46 311 | 48.42 213 | 65.70 283 | 73.42 234 | 47.71 265 | 58.16 262 | 75.02 281 | 30.51 286 | 77.71 241 | 53.96 175 | 71.68 203 | 78.90 240 |
|
MSP-MVS | | | 80.84 3 | 81.64 2 | 78.42 33 | 87.75 7 | 59.07 62 | 87.85 3 | 85.03 33 | 64.26 29 | 83.82 6 | 92.00 3 | 64.82 6 | 90.75 5 | 78.66 10 | 90.61 7 | 85.45 103 |
|
test_0728_THIRD | | | | | | | | | | 65.04 19 | 83.82 6 | 92.00 3 | 64.69 8 | 90.75 5 | 79.48 4 | 90.63 6 | 88.09 15 |
|
test_0728_SECOND | | | | | 79.19 12 | 87.82 3 | 59.11 61 | 87.85 3 | 87.15 6 | | | | | 90.84 1 | 78.66 10 | 90.61 7 | 87.62 31 |
|
test0726 | | | | | | 87.75 7 | 59.07 62 | 87.86 2 | 86.83 9 | 64.26 29 | 84.19 5 | 91.92 5 | 64.82 6 | | | | |
|
SR-MVS | | | 76.13 45 | 75.70 46 | 77.40 51 | 85.87 39 | 61.20 33 | 85.52 26 | 82.19 89 | 59.99 104 | 75.10 37 | 90.35 27 | 47.66 123 | 86.52 73 | 71.64 52 | 82.99 74 | 84.47 135 |
|
DPM-MVS | | | 75.47 51 | 75.00 50 | 76.88 55 | 81.38 92 | 59.16 58 | 79.94 103 | 85.71 24 | 56.59 157 | 72.46 77 | 86.76 76 | 56.89 29 | 87.86 39 | 66.36 83 | 88.91 26 | 83.64 162 |
|
GST-MVS | | | 78.14 23 | 77.85 26 | 78.99 22 | 86.05 37 | 61.82 25 | 85.84 19 | 85.21 29 | 63.56 41 | 74.29 51 | 90.03 37 | 52.56 69 | 88.53 25 | 74.79 31 | 88.34 30 | 86.63 59 |
|
test_yl | | | 69.69 124 | 69.13 118 | 71.36 170 | 78.37 148 | 45.74 242 | 74.71 198 | 80.20 133 | 57.91 138 | 70.01 102 | 83.83 134 | 42.44 176 | 82.87 151 | 54.97 165 | 79.72 109 | 85.48 101 |
|
thisisatest0530 | | | 67.92 164 | 65.78 185 | 74.33 103 | 76.29 196 | 51.03 172 | 76.89 157 | 74.25 227 | 53.67 207 | 65.59 178 | 81.76 174 | 35.15 244 | 85.50 96 | 55.94 155 | 72.47 193 | 86.47 61 |
|
Anonymous20240529 | | | 69.91 121 | 69.02 121 | 72.56 146 | 80.19 114 | 47.65 222 | 77.56 140 | 80.99 119 | 55.45 183 | 69.88 105 | 86.76 76 | 39.24 210 | 82.18 167 | 54.04 173 | 77.10 145 | 87.85 23 |
|
Anonymous202405211 | | | 66.84 184 | 65.99 182 | 69.40 207 | 80.19 114 | 42.21 273 | 71.11 251 | 71.31 245 | 58.80 125 | 67.90 137 | 86.39 90 | 29.83 293 | 79.65 209 | 49.60 208 | 78.78 127 | 86.33 69 |
|
DCV-MVSNet | | | 69.69 124 | 69.13 118 | 71.36 170 | 78.37 148 | 45.74 242 | 74.71 198 | 80.20 133 | 57.91 138 | 70.01 102 | 83.83 134 | 42.44 176 | 82.87 151 | 54.97 165 | 79.72 109 | 85.48 101 |
|
tttt0517 | | | 67.83 166 | 65.66 187 | 74.33 103 | 76.69 189 | 50.82 177 | 77.86 133 | 73.99 230 | 54.54 200 | 64.64 197 | 82.53 158 | 35.06 245 | 85.50 96 | 55.71 160 | 69.91 225 | 86.67 58 |
|
our_test_3 | | | 56.49 270 | 54.42 279 | 62.68 272 | 69.51 290 | 45.48 247 | 66.08 281 | 61.49 306 | 44.11 297 | 50.73 312 | 69.60 313 | 33.05 265 | 68.15 288 | 38.38 282 | 56.86 310 | 74.40 287 |
|
thisisatest0515 | | | 65.83 198 | 63.50 209 | 72.82 141 | 73.75 234 | 49.50 201 | 71.32 245 | 73.12 238 | 49.39 247 | 63.82 206 | 76.50 267 | 34.95 247 | 84.84 111 | 53.20 183 | 75.49 159 | 84.13 144 |
|
ppachtmachnet_test | | | 58.06 263 | 55.38 273 | 66.10 243 | 69.51 290 | 48.99 207 | 68.01 274 | 66.13 279 | 44.50 291 | 54.05 294 | 70.74 305 | 32.09 280 | 72.34 272 | 36.68 293 | 56.71 312 | 76.99 262 |
|
SMA-MVS | | | 80.28 5 | 80.39 6 | 79.95 3 | 86.60 20 | 61.95 22 | 86.33 11 | 85.75 23 | 62.49 60 | 82.20 12 | 92.28 1 | 56.53 31 | 89.70 12 | 79.85 3 | 91.48 1 | 88.19 12 |
|
GSMVS | | | | | | | | | | | | | | | | | 78.05 246 |
|
DPE-MVS | | | 80.56 4 | 80.98 4 | 79.29 11 | 87.27 12 | 60.56 44 | 85.71 24 | 86.42 16 | 63.28 43 | 83.27 10 | 91.83 8 | 64.96 5 | 90.47 7 | 76.41 24 | 89.67 18 | 86.84 53 |
|
test_part2 | | | | | | 87.58 9 | 60.47 45 | | | | 83.42 9 | | | | | | |
|
test_part1 | | | | | 0.00 337 | | 0.00 356 | 0.00 348 | 86.64 14 | | | | 0.00 357 | 0.00 352 | 0.00 351 | 0.00 349 | 0.00 350 |
|
thres100view900 | | | 63.28 224 | 62.41 221 | 65.89 248 | 77.31 179 | 38.66 297 | 72.65 227 | 69.11 263 | 57.07 145 | 62.45 223 | 81.03 189 | 37.01 235 | 79.17 218 | 31.84 312 | 73.25 181 | 79.83 228 |
|
tfpnnormal | | | 62.47 231 | 61.63 229 | 64.99 258 | 74.81 220 | 39.01 294 | 71.22 247 | 73.72 232 | 55.22 186 | 60.21 239 | 80.09 212 | 41.26 197 | 76.98 251 | 30.02 324 | 68.09 250 | 78.97 239 |
|
tfpn200view9 | | | 63.18 226 | 62.18 224 | 66.21 240 | 76.85 187 | 39.62 289 | 71.96 239 | 69.44 259 | 56.63 152 | 62.61 218 | 79.83 215 | 37.18 230 | 79.17 218 | 31.84 312 | 73.25 181 | 79.83 228 |
|
cl_fuxian | | | 68.33 154 | 67.56 143 | 70.62 185 | 70.87 272 | 46.21 237 | 74.47 203 | 78.80 155 | 56.22 166 | 66.19 167 | 78.53 240 | 51.88 78 | 81.40 179 | 62.08 120 | 69.04 241 | 84.25 139 |
|
CHOSEN 280x420 | | | 47.83 301 | 46.36 304 | 52.24 315 | 67.37 305 | 49.78 195 | 38.91 342 | 43.11 343 | 35.00 328 | 43.27 331 | 63.30 329 | 28.95 298 | 49.19 339 | 36.53 295 | 60.80 300 | 57.76 333 |
|
CANet | | | 76.46 42 | 75.93 44 | 78.06 39 | 81.29 93 | 57.53 88 | 82.35 68 | 83.31 72 | 67.78 3 | 70.09 97 | 86.34 91 | 54.92 45 | 88.90 21 | 72.68 46 | 84.55 65 | 87.76 26 |
|
Fast-Effi-MVS+-dtu | | | 67.37 171 | 65.33 192 | 73.48 125 | 72.94 244 | 57.78 85 | 77.47 143 | 76.88 193 | 57.60 140 | 61.97 227 | 76.85 259 | 39.31 208 | 80.49 201 | 54.72 168 | 70.28 219 | 82.17 193 |
|
Effi-MVS+-dtu | | | 69.64 128 | 67.53 146 | 75.95 67 | 76.10 199 | 62.29 18 | 80.20 100 | 76.06 203 | 59.83 109 | 65.26 186 | 77.09 255 | 41.56 189 | 84.02 127 | 60.60 132 | 71.09 209 | 81.53 200 |
|
CANet_DTU | | | 68.18 158 | 67.71 142 | 69.59 203 | 74.83 219 | 46.24 236 | 78.66 121 | 76.85 194 | 59.60 111 | 63.45 208 | 82.09 171 | 35.25 243 | 77.41 245 | 59.88 138 | 78.76 128 | 85.14 113 |
|
MVS_0304 | | | 58.51 257 | 57.36 258 | 61.96 276 | 70.04 284 | 41.83 276 | 69.40 268 | 65.46 282 | 50.73 235 | 53.30 302 | 74.06 289 | 22.65 327 | 70.18 282 | 42.16 265 | 68.44 247 | 73.86 294 |
|
MP-MVS-pluss | | | 78.35 21 | 78.46 17 | 78.03 40 | 84.96 53 | 59.52 53 | 82.93 57 | 85.39 26 | 62.15 65 | 76.41 31 | 91.51 9 | 52.47 72 | 86.78 63 | 80.66 2 | 89.64 19 | 87.80 24 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
DVP-MVS | | | 81.06 2 | 81.40 3 | 80.02 1 | 86.21 29 | 62.73 12 | 86.09 15 | 86.83 9 | 65.51 14 | 83.81 8 | 90.51 21 | 63.71 9 | 89.23 16 | 81.51 1 | 88.44 28 | 88.09 15 |
|
sam_mvs1 | | | | | | | | | | | | | 34.74 248 | | | | 78.05 246 |
|
sam_mvs | | | | | | | | | | | | | 33.43 262 | | | | |
|
IterMVS-SCA-FT | | | 62.49 230 | 61.52 230 | 65.40 254 | 71.99 259 | 50.80 178 | 71.15 250 | 69.63 256 | 45.71 283 | 60.61 237 | 77.93 244 | 37.45 227 | 65.99 299 | 55.67 161 | 63.50 282 | 79.42 234 |
|
TSAR-MVS + MP. | | | 78.44 19 | 78.28 20 | 78.90 23 | 84.96 53 | 61.41 29 | 84.03 42 | 83.82 58 | 59.34 117 | 79.37 15 | 89.76 44 | 59.84 13 | 87.62 44 | 76.69 22 | 86.74 53 | 87.68 28 |
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition |
xiu_mvs_v1_base_debu | | | 68.58 148 | 67.28 155 | 72.48 148 | 78.19 154 | 57.19 95 | 75.28 184 | 75.09 217 | 51.61 223 | 70.04 98 | 81.41 181 | 32.79 269 | 79.02 224 | 63.81 106 | 77.31 140 | 81.22 207 |
|
OPM-MVS | | | 74.73 57 | 74.25 59 | 76.19 65 | 80.81 101 | 59.01 65 | 82.60 65 | 83.64 61 | 63.74 39 | 72.52 76 | 87.49 69 | 47.18 133 | 85.88 88 | 69.47 62 | 80.78 93 | 83.66 160 |
|
ACMMP_NAP | | | 78.77 14 | 78.78 14 | 78.74 27 | 85.44 45 | 61.04 36 | 83.84 46 | 85.16 30 | 62.88 51 | 78.10 24 | 91.26 11 | 52.51 70 | 88.39 26 | 79.34 5 | 90.52 9 | 86.78 57 |
|
ambc | | | | | 65.13 257 | 63.72 325 | 37.07 307 | 47.66 335 | 78.78 156 | | 54.37 291 | 71.42 301 | 11.24 342 | 80.94 190 | 45.64 236 | 53.85 321 | 77.38 253 |
|
zzz-MVS | | | 77.61 31 | 77.36 31 | 78.35 34 | 86.08 35 | 63.57 2 | 83.37 51 | 80.97 120 | 65.13 17 | 75.77 33 | 90.88 13 | 48.63 111 | 86.66 66 | 77.23 16 | 88.17 34 | 84.81 124 |
|
MTGPA | | | | | | | | | 80.97 120 | | | | | | | | |
|
mvs-test1 | | | 70.44 110 | 68.19 135 | 77.18 52 | 76.10 199 | 63.22 6 | 80.59 95 | 76.06 203 | 59.83 109 | 66.32 165 | 79.87 214 | 41.56 189 | 85.53 93 | 60.60 132 | 72.77 188 | 82.80 183 |
|
Effi-MVS+ | | | 73.31 73 | 72.54 76 | 75.62 77 | 77.87 163 | 53.64 139 | 79.62 111 | 79.61 142 | 61.63 75 | 72.02 82 | 82.61 155 | 56.44 33 | 85.97 86 | 63.99 105 | 79.07 123 | 87.25 44 |
|
xiu_mvs_v2_base | | | 70.52 107 | 69.75 108 | 72.84 139 | 81.21 96 | 55.63 120 | 75.11 189 | 78.92 152 | 54.92 194 | 69.96 104 | 79.68 220 | 47.00 139 | 82.09 168 | 61.60 126 | 79.37 115 | 80.81 216 |
|
xiu_mvs_v1_base | | | 68.58 148 | 67.28 155 | 72.48 148 | 78.19 154 | 57.19 95 | 75.28 184 | 75.09 217 | 51.61 223 | 70.04 98 | 81.41 181 | 32.79 269 | 79.02 224 | 63.81 106 | 77.31 140 | 81.22 207 |
|
new-patchmatchnet | | | 47.56 302 | 47.73 302 | 47.06 320 | 58.81 338 | 9.37 351 | 48.78 333 | 59.21 311 | 43.28 301 | 44.22 329 | 68.66 315 | 25.67 319 | 57.20 325 | 31.57 318 | 49.35 329 | 74.62 286 |
|
pmmvs6 | | | 63.69 219 | 62.82 217 | 66.27 239 | 70.63 274 | 39.27 293 | 73.13 221 | 75.47 211 | 52.69 215 | 59.75 246 | 82.30 163 | 39.71 205 | 77.03 250 | 47.40 220 | 64.35 277 | 82.53 185 |
|
pmmvs5 | | | 56.47 271 | 55.68 271 | 58.86 287 | 61.41 331 | 36.71 310 | 66.37 279 | 62.75 299 | 40.38 318 | 53.70 296 | 76.62 262 | 34.56 249 | 67.05 293 | 40.02 277 | 65.27 270 | 72.83 298 |
|
test_post1 | | | | | | | | 68.67 271 | | | | 3.64 348 | 32.39 278 | 69.49 283 | 44.17 247 | | |
|
test_post | | | | | | | | | | | | 3.55 349 | 33.90 257 | 66.52 296 | | | |
|
Fast-Effi-MVS+ | | | 70.28 114 | 69.12 120 | 73.73 116 | 78.50 144 | 51.50 170 | 75.01 192 | 79.46 146 | 56.16 167 | 68.59 123 | 79.55 223 | 53.97 55 | 84.05 123 | 53.34 181 | 77.53 139 | 85.65 95 |
|
patchmatchnet-post | | | | | | | | | | | | 64.03 326 | 34.50 250 | 74.27 266 | | | |
|
Anonymous20231211 | | | 69.28 134 | 68.47 130 | 71.73 159 | 80.28 109 | 47.18 228 | 79.98 102 | 82.37 87 | 54.61 197 | 67.24 151 | 84.01 131 | 39.43 207 | 82.41 164 | 55.45 163 | 72.83 187 | 85.62 97 |
|
pmmvs-eth3d | | | 58.81 255 | 56.31 267 | 66.30 238 | 67.61 303 | 52.42 162 | 72.30 234 | 64.76 287 | 43.55 300 | 54.94 283 | 74.19 288 | 28.95 298 | 72.60 270 | 43.31 255 | 57.21 309 | 73.88 293 |
|
GG-mvs-BLEND | | | | | 62.34 273 | 71.36 270 | 37.04 308 | 69.20 269 | 57.33 319 | | 54.73 286 | 65.48 325 | 30.37 287 | 77.82 239 | 34.82 301 | 74.93 161 | 72.17 309 |
|
xiu_mvs_v1_base_debi | | | 68.58 148 | 67.28 155 | 72.48 148 | 78.19 154 | 57.19 95 | 75.28 184 | 75.09 217 | 51.61 223 | 70.04 98 | 81.41 181 | 32.79 269 | 79.02 224 | 63.81 106 | 77.31 140 | 81.22 207 |
|
Anonymous20231206 | | | 55.10 281 | 55.30 274 | 54.48 305 | 69.81 289 | 33.94 325 | 62.91 299 | 62.13 304 | 41.08 314 | 55.18 282 | 75.65 275 | 32.75 272 | 56.59 328 | 30.32 323 | 67.86 252 | 72.91 297 |
|
MTAPA | | | 76.90 38 | 76.42 40 | 78.35 34 | 86.08 35 | 63.57 2 | 74.92 195 | 80.97 120 | 65.13 17 | 75.77 33 | 90.88 13 | 48.63 111 | 86.66 66 | 77.23 16 | 88.17 34 | 84.81 124 |
|
MTMP | | | | | | | | 86.03 17 | 17.08 351 | | | | | | | | |
|
gm-plane-assit | | | | | | 71.40 269 | 41.72 279 | | | 48.85 253 | | 73.31 293 | | 82.48 163 | 48.90 212 | | |
|
test9_res | | | | | | | | | | | | | | | 75.28 28 | 88.31 33 | 83.81 151 |
|
MVP-Stereo | | | 65.41 204 | 63.80 204 | 70.22 190 | 77.62 173 | 55.53 122 | 76.30 167 | 78.53 163 | 50.59 239 | 56.47 272 | 78.65 236 | 39.84 203 | 82.68 157 | 44.10 250 | 72.12 199 | 72.44 304 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
TEST9 | | | | | | 85.58 43 | 61.59 27 | 81.62 80 | 81.26 111 | 55.65 179 | 74.93 41 | 88.81 58 | 53.70 61 | 84.68 112 | | | |
|
train_agg | | | 76.27 44 | 76.15 41 | 76.64 61 | 85.58 43 | 61.59 27 | 81.62 80 | 81.26 111 | 55.86 172 | 74.93 41 | 88.81 58 | 53.70 61 | 84.68 112 | 75.24 29 | 88.33 31 | 83.65 161 |
|
gg-mvs-nofinetune | | | 57.86 264 | 56.43 266 | 62.18 274 | 72.62 249 | 35.35 318 | 66.57 277 | 56.33 322 | 50.65 237 | 57.64 265 | 57.10 333 | 30.65 285 | 76.36 256 | 37.38 287 | 78.88 124 | 74.82 283 |
|
SCA | | | 60.49 247 | 58.38 251 | 66.80 231 | 74.14 233 | 48.06 217 | 63.35 297 | 63.23 296 | 49.13 250 | 59.33 251 | 72.10 297 | 37.45 227 | 74.27 266 | 44.17 247 | 62.57 289 | 78.05 246 |
|
Patchmatch-test | | | 49.08 299 | 48.28 300 | 51.50 316 | 64.40 322 | 30.85 335 | 45.68 336 | 48.46 338 | 35.60 327 | 46.10 325 | 72.10 297 | 34.47 252 | 46.37 340 | 27.08 332 | 60.65 301 | 77.27 255 |
|
test_8 | | | | | | 85.40 46 | 60.96 37 | 81.54 83 | 81.18 114 | 55.86 172 | 74.81 44 | 88.80 60 | 53.70 61 | 84.45 117 | | | |
|
MS-PatchMatch | | | 62.42 232 | 61.46 231 | 65.31 256 | 75.21 216 | 52.10 164 | 72.05 237 | 74.05 229 | 46.41 275 | 57.42 267 | 74.36 286 | 34.35 253 | 77.57 244 | 45.62 237 | 73.67 171 | 66.26 326 |
|
Patchmatch-RL test | | | 58.16 261 | 55.49 272 | 66.15 241 | 67.92 302 | 48.89 209 | 60.66 310 | 51.07 332 | 47.86 264 | 59.36 248 | 62.71 330 | 34.02 256 | 72.27 273 | 56.41 153 | 59.40 304 | 77.30 254 |
|
cdsmvs_eth3d_5k | | | 17.50 319 | 23.34 318 | 0.00 337 | 0.00 356 | 0.00 356 | 0.00 348 | 78.63 160 | 0.00 352 | 0.00 353 | 82.18 165 | 49.25 104 | 0.00 352 | 0.00 351 | 0.00 349 | 0.00 350 |
|
pcd_1.5k_mvsjas | | | 3.92 325 | 5.23 327 | 0.00 337 | 0.00 356 | 0.00 356 | 0.00 348 | 0.00 356 | 0.00 352 | 0.00 353 | 0.00 353 | 47.05 135 | 0.00 352 | 0.00 351 | 0.00 349 | 0.00 350 |
|
agg_prior1 | | | 75.94 47 | 76.01 43 | 75.72 73 | 85.04 50 | 59.96 49 | 81.44 84 | 81.04 117 | 56.14 168 | 74.68 45 | 88.90 56 | 53.91 57 | 84.04 124 | 75.01 30 | 87.92 41 | 83.16 176 |
|
agg_prior2 | | | | | | | | | | | | | | | 73.09 45 | 87.93 40 | 84.33 136 |
|
agg_prior | | | | | | 85.04 50 | 59.96 49 | | 81.04 117 | | 74.68 45 | | | 84.04 124 | | | |
|
tmp_tt | | | 9.43 321 | 11.14 323 | 4.30 334 | 2.38 353 | 4.40 353 | 13.62 347 | 16.08 352 | 0.39 349 | 15.89 345 | 13.06 346 | 15.80 336 | 5.54 351 | 12.63 342 | 10.46 347 | 2.95 346 |
|
canonicalmvs | | | 74.67 58 | 74.98 52 | 73.71 117 | 78.94 135 | 50.56 183 | 80.23 98 | 83.87 56 | 60.30 99 | 77.15 28 | 86.56 87 | 59.65 14 | 82.00 169 | 66.01 87 | 82.12 85 | 88.58 6 |
|
anonymousdsp | | | 67.00 181 | 64.82 197 | 73.57 123 | 70.09 283 | 56.13 109 | 76.35 166 | 77.35 188 | 48.43 257 | 64.99 193 | 80.84 196 | 33.01 266 | 80.34 202 | 64.66 98 | 67.64 256 | 84.23 140 |
|
alignmvs | | | 73.86 69 | 73.99 61 | 73.45 126 | 78.20 153 | 50.50 184 | 78.57 123 | 82.43 86 | 59.40 115 | 76.57 29 | 86.71 80 | 56.42 34 | 81.23 184 | 65.84 89 | 81.79 87 | 88.62 4 |
|
nrg030 | | | 72.96 76 | 73.01 72 | 72.84 139 | 75.41 213 | 50.24 187 | 80.02 101 | 82.89 83 | 58.36 133 | 74.44 48 | 86.73 78 | 58.90 19 | 80.83 193 | 65.84 89 | 74.46 162 | 87.44 38 |
|
v144192 | | | 69.71 123 | 68.51 128 | 73.33 131 | 73.10 240 | 50.13 190 | 77.54 141 | 80.64 125 | 56.65 151 | 68.57 125 | 80.55 200 | 46.87 140 | 84.96 107 | 62.98 113 | 69.66 232 | 84.89 122 |
|
FIs | | | 70.82 103 | 71.43 85 | 68.98 212 | 78.33 150 | 38.14 301 | 76.96 155 | 83.59 62 | 61.02 83 | 67.33 150 | 86.73 78 | 55.07 43 | 81.64 174 | 54.61 171 | 79.22 119 | 87.14 47 |
|
v1921920 | | | 69.47 132 | 68.17 136 | 73.36 130 | 73.06 241 | 50.10 191 | 77.39 144 | 80.56 126 | 56.58 158 | 68.59 123 | 80.37 202 | 44.72 159 | 84.98 105 | 62.47 119 | 69.82 227 | 85.00 118 |
|
UA-Net | | | 73.13 74 | 72.93 73 | 73.76 113 | 83.58 66 | 51.66 169 | 78.75 118 | 77.66 181 | 67.75 4 | 72.61 75 | 89.42 47 | 49.82 97 | 83.29 140 | 53.61 179 | 83.14 71 | 86.32 71 |
|
v1192 | | | 69.97 120 | 68.68 126 | 73.85 109 | 73.19 238 | 50.94 173 | 77.68 137 | 81.36 107 | 57.51 141 | 68.95 121 | 80.85 195 | 45.28 156 | 85.33 101 | 62.97 114 | 70.37 216 | 85.27 111 |
|
FC-MVSNet-test | | | 69.80 122 | 70.58 100 | 67.46 226 | 77.61 174 | 34.73 321 | 76.05 174 | 83.19 76 | 60.84 84 | 65.88 174 | 86.46 88 | 54.52 50 | 80.76 197 | 52.52 186 | 78.12 134 | 86.91 50 |
|
v1144 | | | 70.42 111 | 69.31 116 | 73.76 113 | 73.22 237 | 50.64 180 | 77.83 134 | 81.43 105 | 58.58 127 | 69.40 113 | 81.16 185 | 47.53 126 | 85.29 102 | 64.01 104 | 70.64 211 | 85.34 108 |
|
sosnet-low-res | | | 0.00 326 | 0.00 328 | 0.00 337 | 0.00 356 | 0.00 356 | 0.00 348 | 0.00 356 | 0.00 352 | 0.00 353 | 0.00 353 | 0.00 357 | 0.00 352 | 0.00 351 | 0.00 349 | 0.00 350 |
|
HFP-MVS | | | 78.01 26 | 77.65 27 | 79.10 17 | 86.71 16 | 62.81 10 | 86.29 12 | 84.32 44 | 62.82 53 | 73.96 54 | 90.50 22 | 53.20 66 | 88.35 27 | 74.02 36 | 87.05 46 | 86.13 76 |
|
v148 | | | 68.24 157 | 67.19 160 | 71.40 169 | 70.43 277 | 47.77 221 | 75.76 179 | 77.03 192 | 58.91 122 | 67.36 149 | 80.10 211 | 48.60 114 | 81.89 170 | 60.01 137 | 66.52 262 | 84.53 132 |
|
sosnet | | | 0.00 326 | 0.00 328 | 0.00 337 | 0.00 356 | 0.00 356 | 0.00 348 | 0.00 356 | 0.00 352 | 0.00 353 | 0.00 353 | 0.00 357 | 0.00 352 | 0.00 351 | 0.00 349 | 0.00 350 |
|
uncertanet | | | 0.00 326 | 0.00 328 | 0.00 337 | 0.00 356 | 0.00 356 | 0.00 348 | 0.00 356 | 0.00 352 | 0.00 353 | 0.00 353 | 0.00 357 | 0.00 352 | 0.00 351 | 0.00 349 | 0.00 350 |
|
AllTest | | | 57.08 269 | 54.65 277 | 64.39 261 | 71.44 266 | 49.03 204 | 69.92 264 | 67.30 270 | 45.97 280 | 47.16 320 | 79.77 217 | 17.47 333 | 67.56 291 | 33.65 305 | 59.16 305 | 76.57 264 |
|
TestCases | | | | | 64.39 261 | 71.44 266 | 49.03 204 | | 67.30 270 | 45.97 280 | 47.16 320 | 79.77 217 | 17.47 333 | 67.56 291 | 33.65 305 | 59.16 305 | 76.57 264 |
|
v7n | | | 69.01 139 | 67.36 152 | 73.98 107 | 72.51 252 | 52.65 154 | 78.54 125 | 81.30 109 | 60.26 100 | 62.67 216 | 81.62 176 | 43.61 168 | 84.49 116 | 57.01 151 | 68.70 246 | 84.79 126 |
|
region2R | | | 77.67 30 | 77.18 33 | 79.15 14 | 86.76 14 | 62.95 8 | 86.29 12 | 84.16 48 | 62.81 55 | 73.30 65 | 90.58 19 | 49.90 96 | 88.21 31 | 73.78 38 | 87.03 48 | 86.29 74 |
|
testing_2 | | | 66.02 196 | 63.77 205 | 72.76 143 | 66.03 315 | 50.48 185 | 72.93 223 | 80.36 131 | 54.41 202 | 54.25 292 | 76.76 261 | 30.89 284 | 83.16 144 | 64.19 101 | 74.08 167 | 84.65 129 |
|
RRT_MVS | | | 68.77 144 | 66.71 165 | 74.95 86 | 75.93 203 | 58.55 74 | 80.50 96 | 75.84 205 | 56.09 169 | 68.17 132 | 83.74 137 | 28.50 301 | 82.98 147 | 65.67 91 | 65.91 265 | 83.33 167 |
|
PS-MVSNAJss | | | 72.24 85 | 71.21 91 | 75.31 82 | 78.50 144 | 55.93 114 | 81.63 79 | 82.12 91 | 56.24 165 | 70.02 101 | 85.68 105 | 47.05 135 | 84.34 119 | 65.27 94 | 74.41 164 | 85.67 93 |
|
PS-MVSNAJ | | | 70.51 108 | 69.70 110 | 72.93 137 | 81.52 87 | 55.79 116 | 74.92 195 | 79.00 151 | 55.04 193 | 69.88 105 | 78.66 235 | 47.05 135 | 82.19 166 | 61.61 125 | 79.58 112 | 80.83 215 |
|
jajsoiax | | | 68.25 156 | 66.45 169 | 73.66 119 | 75.62 208 | 55.49 123 | 80.82 90 | 78.51 164 | 52.33 218 | 64.33 200 | 84.11 128 | 28.28 302 | 81.81 173 | 63.48 111 | 70.62 212 | 83.67 158 |
|
mvs_tets | | | 68.18 158 | 66.36 174 | 73.63 122 | 75.61 209 | 55.35 126 | 80.77 91 | 78.56 162 | 52.48 217 | 64.27 202 | 84.10 129 | 27.45 308 | 81.84 172 | 63.45 112 | 70.56 213 | 83.69 157 |
|
#test# | | | 77.83 27 | 77.41 30 | 79.10 17 | 86.71 16 | 62.81 10 | 85.69 25 | 84.32 44 | 61.61 76 | 73.96 54 | 90.50 22 | 53.20 66 | 88.35 27 | 73.68 39 | 87.05 46 | 86.13 76 |
|
EI-MVSNet-UG-set | | | 71.92 90 | 71.06 93 | 74.52 99 | 77.98 161 | 53.56 141 | 76.62 160 | 79.16 149 | 64.40 27 | 71.18 87 | 78.95 233 | 52.19 75 | 84.66 114 | 65.47 93 | 73.57 174 | 85.32 109 |
|
EI-MVSNet-Vis-set | | | 72.42 83 | 71.59 83 | 74.91 87 | 78.47 146 | 54.02 135 | 77.05 153 | 79.33 148 | 65.03 20 | 71.68 85 | 79.35 228 | 52.75 68 | 84.89 108 | 66.46 82 | 74.23 165 | 85.83 85 |
|
Regformer-3 | | | 73.89 68 | 73.28 71 | 75.71 74 | 79.75 120 | 55.48 124 | 78.54 125 | 79.93 137 | 66.58 11 | 73.62 61 | 80.30 206 | 54.87 46 | 84.54 115 | 69.09 65 | 76.84 148 | 87.10 48 |
|
Regformer-4 | | | 74.25 64 | 73.48 67 | 76.57 62 | 79.75 120 | 56.54 103 | 78.54 125 | 81.49 104 | 66.93 7 | 73.90 57 | 80.30 206 | 53.84 59 | 85.98 85 | 69.76 59 | 76.84 148 | 87.17 45 |
|
Regformer-1 | | | 75.47 51 | 74.93 53 | 77.09 54 | 80.43 107 | 57.70 86 | 79.50 113 | 82.13 90 | 67.84 1 | 75.73 35 | 80.75 198 | 56.50 32 | 86.07 80 | 71.07 56 | 80.38 101 | 87.50 35 |
|
Regformer-2 | | | 75.63 50 | 74.99 51 | 77.54 47 | 80.43 107 | 58.32 77 | 79.50 113 | 82.92 80 | 67.84 1 | 75.94 32 | 80.75 198 | 55.73 39 | 86.80 61 | 71.44 55 | 80.38 101 | 87.50 35 |
|
HPM-MVS++ | | | 79.88 7 | 80.14 7 | 79.10 17 | 88.17 1 | 64.80 1 | 86.59 10 | 83.70 60 | 65.37 15 | 78.78 21 | 90.64 17 | 58.63 20 | 87.24 47 | 79.00 7 | 90.37 10 | 85.26 112 |
|
test_prior4 | | | | | | | 62.51 17 | 82.08 75 | | | | | | | | | |
|
XVS | | | 77.17 35 | 76.56 39 | 79.00 20 | 86.32 27 | 62.62 14 | 85.83 20 | 83.92 52 | 64.55 23 | 72.17 80 | 90.01 39 | 47.95 119 | 88.01 35 | 71.55 53 | 86.74 53 | 86.37 66 |
|
v1240 | | | 69.24 136 | 67.91 138 | 73.25 134 | 73.02 243 | 49.82 194 | 77.21 150 | 80.54 127 | 56.43 160 | 68.34 129 | 80.51 201 | 43.33 171 | 84.99 103 | 62.03 122 | 69.77 230 | 84.95 121 |
|
test_prior3 | | | 76.89 39 | 76.96 34 | 76.69 58 | 84.20 62 | 57.27 91 | 81.75 77 | 84.88 36 | 60.37 93 | 75.01 39 | 89.06 52 | 56.22 35 | 86.43 76 | 72.19 48 | 88.96 24 | 86.38 62 |
|
pm-mvs1 | | | 65.24 206 | 64.97 196 | 66.04 244 | 72.38 253 | 39.40 292 | 72.62 229 | 75.63 208 | 55.53 181 | 62.35 226 | 83.18 147 | 47.45 128 | 76.47 255 | 49.06 211 | 66.54 261 | 82.24 190 |
|
test_prior2 | | | | | | | | 81.75 77 | | 60.37 93 | 75.01 39 | 89.06 52 | 56.22 35 | | 72.19 48 | 88.96 24 | |
|
X-MVStestdata | | | 70.21 115 | 67.28 155 | 79.00 20 | 86.32 27 | 62.62 14 | 85.83 20 | 83.92 52 | 64.55 23 | 72.17 80 | 6.49 347 | 47.95 119 | 88.01 35 | 71.55 53 | 86.74 53 | 86.37 66 |
|
test_prior | | | | | 76.69 58 | 84.20 62 | 57.27 91 | | 84.88 36 | | | | | 86.43 76 | | | 86.38 62 |
|
旧先验2 | | | | | | | | 76.08 172 | | 45.32 284 | 76.55 30 | | | 65.56 301 | 58.75 145 | | |
|
æ–°å‡ ä½•2 | | | | | | | | 76.12 170 | | | | | | | | | |
|
æ–°å‡ ä½•1 | | | | | 70.76 182 | 85.66 40 | 61.13 35 | | 66.43 278 | 44.68 288 | 70.29 94 | 86.64 82 | 41.29 195 | 75.23 261 | 49.72 205 | 81.75 89 | 75.93 269 |
|
旧先验1 | | | | | | 83.04 71 | 53.15 148 | | 67.52 269 | | | 87.85 67 | 44.08 164 | | | 80.76 94 | 78.03 249 |
|
æ— å…ˆéªŒ | | | | | | | | 79.66 110 | 74.30 226 | 48.40 258 | | | | 80.78 195 | 53.62 177 | | 79.03 238 |
|
原ACMM2 | | | | | | | | 79.02 117 | | | | | | | | | |
|
原ACMM1 | | | | | 74.69 91 | 85.39 47 | 59.40 54 | | 83.42 67 | 51.47 228 | 70.27 96 | 86.61 84 | 48.61 113 | 86.51 74 | 53.85 176 | 87.96 39 | 78.16 244 |
|
test222 | | | | | | 83.14 68 | 58.68 71 | 72.57 230 | 63.45 294 | 41.78 309 | 67.56 147 | 86.12 94 | 37.13 233 | | | 78.73 129 | 74.98 280 |
|
testdata2 | | | | | | | | | | | | | | 72.18 274 | 46.95 226 | | |
|
segment_acmp | | | | | | | | | | | | | 54.23 53 | | | | |
|
testdata | | | | | 64.66 259 | 81.52 87 | 52.93 151 | | 65.29 284 | 46.09 278 | 73.88 58 | 87.46 70 | 38.08 223 | 66.26 298 | 53.31 182 | 78.48 132 | 74.78 284 |
|
testdata1 | | | | | | | | 72.65 227 | | 60.50 90 | | | | | | | |
|
v8 | | | 70.33 113 | 69.28 117 | 73.49 124 | 73.15 239 | 50.22 188 | 78.62 122 | 80.78 124 | 60.79 85 | 66.45 163 | 82.11 170 | 49.35 101 | 84.98 105 | 63.58 110 | 68.71 245 | 85.28 110 |
|
1314 | | | 64.61 213 | 63.21 212 | 68.80 214 | 71.87 262 | 47.46 225 | 73.95 209 | 78.39 173 | 42.88 306 | 59.97 242 | 76.60 264 | 38.11 222 | 79.39 214 | 54.84 167 | 72.32 196 | 79.55 232 |
|
1121 | | | 68.53 152 | 67.16 161 | 72.63 145 | 85.64 42 | 61.14 34 | 73.95 209 | 66.46 277 | 44.61 289 | 70.28 95 | 86.68 81 | 41.42 193 | 80.78 195 | 53.62 177 | 81.79 87 | 75.97 267 |
|
LFMVS | | | 71.78 92 | 71.59 83 | 72.32 152 | 83.40 67 | 46.38 233 | 79.75 108 | 71.08 246 | 64.18 32 | 72.80 72 | 88.64 61 | 42.58 175 | 83.72 132 | 57.41 150 | 84.49 66 | 86.86 52 |
|
VDD-MVS | | | 72.50 80 | 72.09 79 | 73.75 115 | 81.58 86 | 49.69 198 | 77.76 136 | 77.63 182 | 63.21 45 | 73.21 66 | 89.02 54 | 42.14 179 | 83.32 139 | 61.72 124 | 82.50 83 | 88.25 9 |
|
VDDNet | | | 71.81 91 | 71.33 89 | 73.26 133 | 82.80 76 | 47.60 224 | 78.74 119 | 75.27 213 | 59.59 114 | 72.94 70 | 89.40 48 | 41.51 192 | 83.91 129 | 58.75 145 | 82.99 74 | 88.26 8 |
|
v10 | | | 70.21 115 | 69.02 121 | 73.81 110 | 73.51 236 | 50.92 175 | 78.74 119 | 81.39 106 | 60.05 103 | 66.39 164 | 81.83 173 | 47.58 125 | 85.41 100 | 62.80 115 | 68.86 244 | 85.09 116 |
|
VPNet | | | 67.52 169 | 68.11 137 | 65.74 250 | 79.18 129 | 36.80 309 | 72.17 236 | 72.83 239 | 62.04 70 | 67.79 145 | 85.83 102 | 48.88 110 | 76.60 254 | 51.30 195 | 72.97 186 | 83.81 151 |
|
MVS | | | 67.37 171 | 66.33 175 | 70.51 188 | 75.46 212 | 50.94 173 | 73.95 209 | 81.85 96 | 41.57 313 | 62.54 220 | 78.57 239 | 47.98 118 | 85.47 98 | 52.97 184 | 82.05 86 | 75.14 276 |
|
v2v482 | | | 70.50 109 | 69.45 115 | 73.66 119 | 72.62 249 | 50.03 192 | 77.58 138 | 80.51 128 | 59.90 105 | 69.52 109 | 82.14 169 | 47.53 126 | 84.88 110 | 65.07 96 | 70.17 220 | 86.09 78 |
|
V42 | | | 68.65 146 | 67.35 153 | 72.56 146 | 68.93 296 | 50.18 189 | 72.90 225 | 79.47 145 | 56.92 148 | 69.45 112 | 80.26 208 | 46.29 144 | 82.99 146 | 64.07 102 | 67.82 254 | 84.53 132 |
|
SD-MVS | | | 77.70 29 | 77.62 28 | 77.93 42 | 84.47 60 | 61.88 24 | 84.55 33 | 83.87 56 | 60.37 93 | 79.89 14 | 89.38 49 | 54.97 44 | 85.58 92 | 76.12 26 | 84.94 62 | 86.33 69 |
Zhenlong Yuan, Jiakai Cao, Zhaoxin Li, Hao Jiang and Zhaoqi Wang: SD-MVS: Segmentation-driven Deformation Multi-View Stereo with Spherical Refinement and EM optimization. AAAI2024 |
GA-MVS | | | 65.53 202 | 63.70 206 | 71.02 180 | 70.87 272 | 48.10 216 | 70.48 258 | 74.40 225 | 56.69 150 | 64.70 196 | 76.77 260 | 33.66 260 | 81.10 186 | 55.42 164 | 70.32 218 | 83.87 150 |
|
MSLP-MVS++ | | | 73.77 70 | 73.47 68 | 74.66 93 | 83.02 72 | 59.29 57 | 82.30 73 | 81.88 94 | 59.34 117 | 71.59 86 | 86.83 75 | 45.94 146 | 83.65 134 | 65.09 95 | 85.22 61 | 81.06 212 |
|
APDe-MVS | | | 80.16 6 | 80.59 5 | 78.86 25 | 86.64 19 | 60.02 48 | 88.12 1 | 86.42 16 | 62.94 49 | 82.40 11 | 92.12 2 | 59.64 15 | 89.76 11 | 78.70 8 | 88.32 32 | 86.79 56 |
|
APD-MVS_3200maxsize | | | 74.96 53 | 74.39 58 | 76.67 60 | 82.20 79 | 58.24 78 | 83.67 47 | 83.29 73 | 58.41 131 | 73.71 60 | 90.14 34 | 45.62 148 | 85.99 84 | 69.64 60 | 82.85 80 | 85.78 86 |
|
ADS-MVSNet2 | | | 51.33 295 | 48.76 299 | 59.07 286 | 66.02 316 | 44.60 254 | 50.90 329 | 59.76 310 | 36.90 324 | 50.74 310 | 66.18 323 | 26.38 314 | 63.11 306 | 27.17 330 | 54.76 317 | 69.50 320 |
|
EI-MVSNet | | | 69.27 135 | 68.44 132 | 71.73 159 | 74.47 226 | 49.39 203 | 75.20 187 | 78.45 168 | 59.60 111 | 69.16 119 | 76.51 265 | 51.29 84 | 82.50 161 | 59.86 140 | 71.45 206 | 83.30 168 |
|
Regformer | | | 0.00 326 | 0.00 328 | 0.00 337 | 0.00 356 | 0.00 356 | 0.00 348 | 0.00 356 | 0.00 352 | 0.00 353 | 0.00 353 | 0.00 357 | 0.00 352 | 0.00 351 | 0.00 349 | 0.00 350 |
|
CVMVSNet | | | 59.63 253 | 59.14 246 | 61.08 282 | 74.47 226 | 38.84 296 | 75.20 187 | 68.74 265 | 31.15 332 | 58.24 261 | 76.51 265 | 32.39 278 | 68.58 287 | 49.77 203 | 65.84 267 | 75.81 270 |
|
pmmvs4 | | | 61.48 243 | 59.39 244 | 67.76 224 | 71.57 265 | 53.86 137 | 71.42 243 | 65.34 283 | 44.20 294 | 59.46 247 | 77.92 245 | 35.90 239 | 74.71 263 | 43.87 252 | 64.87 273 | 74.71 285 |
|
EU-MVSNet | | | 55.61 278 | 54.41 280 | 59.19 285 | 65.41 318 | 33.42 327 | 72.44 232 | 71.91 244 | 28.81 334 | 51.27 307 | 73.87 290 | 24.76 323 | 69.08 285 | 43.04 259 | 58.20 308 | 75.06 277 |
|
VNet | | | 69.68 126 | 70.19 105 | 68.16 221 | 79.73 123 | 41.63 280 | 70.53 257 | 77.38 187 | 60.37 93 | 70.69 90 | 86.63 83 | 51.08 88 | 77.09 249 | 53.61 179 | 81.69 91 | 85.75 91 |
|
test-LLR | | | 58.15 262 | 58.13 255 | 58.22 290 | 68.57 297 | 44.80 251 | 65.46 286 | 57.92 316 | 50.08 243 | 55.44 278 | 69.82 311 | 32.62 274 | 57.44 323 | 49.66 206 | 73.62 172 | 72.41 305 |
|
TESTMET0.1,1 | | | 55.28 279 | 54.90 276 | 56.42 297 | 66.56 310 | 43.67 262 | 65.46 286 | 56.27 323 | 39.18 323 | 53.83 295 | 67.44 319 | 24.21 325 | 55.46 333 | 48.04 218 | 73.11 184 | 70.13 318 |
|
test-mter | | | 56.42 272 | 55.82 270 | 58.22 290 | 68.57 297 | 44.80 251 | 65.46 286 | 57.92 316 | 39.94 321 | 55.44 278 | 69.82 311 | 21.92 330 | 57.44 323 | 49.66 206 | 73.62 172 | 72.41 305 |
|
VPA-MVSNet | | | 69.02 138 | 69.47 114 | 67.69 225 | 77.42 177 | 41.00 284 | 74.04 207 | 79.68 140 | 60.06 102 | 69.26 117 | 84.81 115 | 51.06 89 | 77.58 243 | 54.44 172 | 74.43 163 | 84.48 134 |
|
ACMMPR | | | 77.71 28 | 77.23 32 | 79.16 13 | 86.75 15 | 62.93 9 | 86.29 12 | 84.24 46 | 62.82 53 | 73.55 63 | 90.56 20 | 49.80 98 | 88.24 30 | 74.02 36 | 87.03 48 | 86.32 71 |
|
testgi | | | 51.90 292 | 52.37 290 | 50.51 318 | 60.39 336 | 23.55 345 | 58.42 315 | 58.15 314 | 49.03 251 | 51.83 306 | 79.21 231 | 22.39 328 | 55.59 332 | 29.24 327 | 62.64 288 | 72.40 307 |
|
test20.03 | | | 53.87 285 | 54.02 284 | 53.41 309 | 61.47 330 | 28.11 339 | 61.30 306 | 59.21 311 | 51.34 231 | 52.09 305 | 77.43 253 | 33.29 264 | 58.55 320 | 29.76 325 | 60.27 302 | 73.58 295 |
|
thres600view7 | | | 63.30 223 | 62.27 222 | 66.41 236 | 77.18 181 | 38.87 295 | 72.35 233 | 69.11 263 | 56.98 147 | 62.37 225 | 80.96 191 | 37.01 235 | 79.00 227 | 31.43 319 | 73.05 185 | 81.36 203 |
|
ADS-MVSNet | | | 48.48 300 | 47.77 301 | 50.63 317 | 66.02 316 | 29.92 336 | 50.90 329 | 50.87 334 | 36.90 324 | 50.74 310 | 66.18 323 | 26.38 314 | 52.47 337 | 27.17 330 | 54.76 317 | 69.50 320 |
|
MP-MVS | | | 78.35 21 | 78.26 21 | 78.64 28 | 86.54 22 | 63.47 5 | 86.02 18 | 83.55 63 | 63.89 37 | 73.60 62 | 90.60 18 | 54.85 47 | 86.72 64 | 77.20 18 | 88.06 37 | 85.74 92 |
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
testmvs | | | 4.52 324 | 6.03 326 | 0.01 336 | 0.01 354 | 0.00 356 | 53.86 326 | 0.00 356 | 0.01 350 | 0.04 351 | 0.27 351 | 0.00 357 | 0.00 352 | 0.04 349 | 0.00 349 | 0.03 349 |
|
thres400 | | | 63.31 222 | 62.18 224 | 66.72 232 | 76.85 187 | 39.62 289 | 71.96 239 | 69.44 259 | 56.63 152 | 62.61 218 | 79.83 215 | 37.18 230 | 79.17 218 | 31.84 312 | 73.25 181 | 81.36 203 |
|
test123 | | | 4.73 323 | 6.30 325 | 0.02 335 | 0.01 354 | 0.01 355 | 56.36 321 | 0.00 356 | 0.01 350 | 0.04 351 | 0.21 352 | 0.01 356 | 0.00 352 | 0.03 350 | 0.00 349 | 0.04 348 |
|
thres200 | | | 62.20 235 | 61.16 236 | 65.34 255 | 75.38 214 | 39.99 286 | 69.60 265 | 69.29 261 | 55.64 180 | 61.87 229 | 76.99 256 | 37.07 234 | 78.96 228 | 31.28 320 | 73.28 180 | 77.06 258 |
|
test0.0.03 1 | | | 53.32 288 | 53.59 286 | 52.50 313 | 62.81 326 | 29.45 337 | 59.51 312 | 54.11 329 | 50.08 243 | 54.40 290 | 74.31 287 | 32.62 274 | 55.92 331 | 30.50 322 | 63.95 279 | 72.15 310 |
|
pmmvs3 | | | 44.92 305 | 41.95 308 | 53.86 306 | 52.58 341 | 43.55 263 | 62.11 303 | 46.90 341 | 26.05 338 | 40.63 334 | 60.19 331 | 11.08 343 | 57.91 322 | 31.83 315 | 46.15 332 | 60.11 330 |
|
EMVS | | | 22.97 317 | 21.84 320 | 26.36 331 | 40.20 347 | 19.53 348 | 41.95 341 | 34.64 346 | 17.09 344 | 9.73 349 | 22.83 345 | 7.29 347 | 42.22 345 | 9.18 346 | 13.66 344 | 17.32 344 |
|
E-PMN | | | 23.77 316 | 22.73 319 | 26.90 330 | 42.02 346 | 20.67 346 | 42.66 340 | 35.70 345 | 17.43 343 | 10.28 348 | 25.05 344 | 6.42 348 | 42.39 344 | 10.28 344 | 14.71 343 | 17.63 343 |
|
PGM-MVS | | | 76.77 40 | 76.06 42 | 78.88 24 | 86.14 34 | 62.73 12 | 82.55 66 | 83.74 59 | 61.71 74 | 72.45 79 | 90.34 29 | 48.48 115 | 88.13 32 | 72.32 47 | 86.85 51 | 85.78 86 |
|
LCM-MVSNet-Re | | | 61.88 240 | 61.35 232 | 63.46 265 | 74.58 224 | 31.48 333 | 61.42 305 | 58.14 315 | 58.71 126 | 53.02 303 | 79.55 223 | 43.07 172 | 76.80 252 | 45.69 235 | 77.96 135 | 82.11 194 |
|
LCM-MVSNet | | | 40.30 309 | 35.88 313 | 53.57 308 | 42.24 345 | 29.15 338 | 45.21 338 | 60.53 309 | 22.23 342 | 28.02 340 | 50.98 338 | 3.72 351 | 61.78 311 | 31.22 321 | 38.76 338 | 69.78 319 |
|
MCST-MVS | | | 77.48 32 | 77.45 29 | 77.54 47 | 86.67 18 | 58.36 76 | 83.22 53 | 86.93 7 | 56.91 149 | 74.91 43 | 88.19 62 | 59.15 18 | 87.68 42 | 73.67 40 | 87.45 43 | 86.57 60 |
|
mvs_anonymous | | | 68.03 161 | 67.51 147 | 69.59 203 | 72.08 257 | 44.57 255 | 71.99 238 | 75.23 214 | 51.67 222 | 67.06 153 | 82.57 156 | 54.68 48 | 77.94 237 | 56.56 152 | 75.71 157 | 86.26 75 |
|
MVS_Test | | | 72.45 82 | 72.46 77 | 72.42 151 | 74.88 218 | 48.50 212 | 76.28 168 | 83.14 78 | 59.40 115 | 72.46 77 | 84.68 116 | 55.66 40 | 81.12 185 | 65.98 88 | 79.66 111 | 87.63 30 |
|
MDA-MVSNet-bldmvs | | | 53.87 285 | 50.81 293 | 63.05 269 | 66.25 312 | 48.58 211 | 56.93 320 | 63.82 292 | 48.09 261 | 41.22 333 | 70.48 308 | 30.34 288 | 68.00 290 | 34.24 303 | 45.92 333 | 72.57 301 |
|
CDPH-MVS | | | 76.31 43 | 75.67 47 | 78.22 37 | 85.35 48 | 59.14 60 | 81.31 86 | 84.02 49 | 56.32 162 | 74.05 52 | 88.98 55 | 53.34 65 | 87.92 37 | 69.23 64 | 88.42 29 | 87.59 32 |
|
test12 | | | | | 77.76 43 | 84.52 59 | 58.41 75 | | 83.36 70 | | 72.93 71 | | 54.61 49 | 88.05 34 | | 88.12 36 | 86.81 55 |
|
casdiffmvs | | | 74.80 55 | 74.89 54 | 74.53 98 | 75.59 210 | 50.37 186 | 78.17 130 | 85.06 32 | 62.80 56 | 74.40 49 | 87.86 66 | 57.88 24 | 83.61 135 | 69.46 63 | 82.79 81 | 89.59 2 |
|
diffmvs | | | 70.69 105 | 70.43 101 | 71.46 165 | 69.45 292 | 48.95 208 | 72.93 223 | 78.46 167 | 57.27 143 | 71.69 84 | 83.97 133 | 51.48 83 | 77.92 238 | 70.70 58 | 77.95 136 | 87.53 34 |
|
baseline2 | | | 63.42 221 | 61.26 234 | 69.89 200 | 72.55 251 | 47.62 223 | 71.54 242 | 68.38 267 | 50.11 241 | 54.82 284 | 75.55 277 | 43.06 173 | 80.96 189 | 48.13 217 | 67.16 259 | 81.11 210 |
|
baseline1 | | | 63.81 218 | 63.87 203 | 63.62 264 | 76.29 196 | 36.36 312 | 71.78 241 | 67.29 272 | 56.05 171 | 64.23 203 | 82.95 149 | 47.11 134 | 74.41 265 | 47.30 221 | 61.85 293 | 80.10 225 |
|
YYNet1 | | | 50.73 296 | 48.96 296 | 56.03 299 | 61.10 333 | 41.78 277 | 51.94 327 | 56.44 321 | 40.94 316 | 44.84 326 | 67.80 318 | 30.08 291 | 55.08 334 | 36.77 290 | 50.71 326 | 71.22 313 |
|
PMMVS2 | | | 27.40 315 | 25.91 317 | 31.87 329 | 39.46 349 | 6.57 352 | 31.17 343 | 28.52 349 | 23.96 339 | 20.45 343 | 48.94 340 | 4.20 350 | 37.94 346 | 16.51 339 | 19.97 341 | 51.09 336 |
|
MDA-MVSNet_test_wron | | | 50.71 297 | 48.95 297 | 56.00 300 | 61.17 332 | 41.84 275 | 51.90 328 | 56.45 320 | 40.96 315 | 44.79 327 | 67.84 317 | 30.04 292 | 55.07 335 | 36.71 292 | 50.69 327 | 71.11 316 |
|
tpmvs | | | 58.47 258 | 56.95 262 | 63.03 270 | 70.20 280 | 41.21 281 | 67.90 275 | 67.23 273 | 49.62 246 | 54.73 286 | 70.84 304 | 34.14 254 | 76.24 258 | 36.64 294 | 61.29 297 | 71.64 311 |
|
PM-MVS | | | 52.33 291 | 50.19 295 | 58.75 288 | 62.10 328 | 45.14 249 | 65.75 282 | 40.38 344 | 43.60 299 | 53.52 299 | 72.65 294 | 9.16 346 | 65.87 300 | 50.41 199 | 54.18 319 | 65.24 328 |
|
HQP_MVS | | | 74.31 62 | 73.73 64 | 76.06 66 | 81.41 90 | 56.31 104 | 84.22 36 | 84.01 50 | 64.52 25 | 69.27 115 | 86.10 95 | 45.26 157 | 87.21 49 | 68.16 68 | 80.58 97 | 84.65 129 |
|
plane_prior7 | | | | | | 81.41 90 | 55.96 113 | | | | | | | | | | |
|
plane_prior6 | | | | | | 81.20 97 | 56.24 108 | | | | | | 45.26 157 | | | | |
|
plane_prior5 | | | | | | | | | 84.01 50 | | | | | 87.21 49 | 68.16 68 | 80.58 97 | 84.65 129 |
|
plane_prior4 | | | | | | | | | | | | 86.10 95 | | | | | |
|
plane_prior3 | | | | | | | 56.09 110 | | | 63.92 36 | 69.27 115 | | | | | | |
|
plane_prior2 | | | | | | | | 84.22 36 | | 64.52 25 | | | | | | | |
|
plane_prior1 | | | | | | 81.27 95 | | | | | | | | | | | |
|
plane_prior | | | | | | | 56.31 104 | 83.58 49 | | 63.19 46 | | | | | | 80.48 100 | |
|
PS-CasMVS | | | 66.42 193 | 66.32 176 | 66.70 234 | 77.60 175 | 36.30 316 | 76.94 156 | 79.61 142 | 62.36 63 | 62.43 224 | 83.66 138 | 45.69 147 | 78.37 231 | 45.35 243 | 63.26 284 | 85.42 106 |
|
UniMVSNet_NR-MVSNet | | | 71.11 100 | 71.00 94 | 71.44 166 | 79.20 128 | 44.13 257 | 76.02 176 | 82.60 85 | 66.48 13 | 68.20 130 | 84.60 120 | 56.82 30 | 82.82 155 | 54.62 169 | 70.43 214 | 87.36 42 |
|
PEN-MVS | | | 66.60 189 | 66.45 169 | 67.04 230 | 77.11 182 | 36.56 311 | 77.03 154 | 80.42 129 | 62.95 48 | 62.51 222 | 84.03 130 | 46.69 141 | 79.07 223 | 44.22 246 | 63.08 286 | 85.51 100 |
|
TransMVSNet (Re) | | | 64.72 210 | 64.33 198 | 65.87 249 | 75.22 215 | 38.56 298 | 74.66 200 | 75.08 220 | 58.90 123 | 61.79 230 | 82.63 154 | 51.18 86 | 78.07 236 | 43.63 254 | 55.87 314 | 80.99 213 |
|
DTE-MVSNet | | | 65.58 201 | 65.34 191 | 66.31 237 | 76.06 201 | 34.79 319 | 76.43 164 | 79.38 147 | 62.55 59 | 61.66 231 | 83.83 134 | 45.60 149 | 79.15 221 | 41.64 272 | 60.88 299 | 85.00 118 |
|
DU-MVS | | | 70.01 118 | 69.53 112 | 71.44 166 | 78.05 159 | 44.13 257 | 75.01 192 | 81.51 103 | 64.37 28 | 68.20 130 | 84.52 121 | 49.12 108 | 82.82 155 | 54.62 169 | 70.43 214 | 87.37 40 |
|
UniMVSNet (Re) | | | 70.63 106 | 70.20 104 | 71.89 155 | 78.55 143 | 45.29 248 | 75.94 177 | 82.92 80 | 63.68 40 | 68.16 133 | 83.59 140 | 53.89 58 | 83.49 138 | 53.97 174 | 71.12 208 | 86.89 51 |
|
CP-MVSNet | | | 66.49 192 | 66.41 173 | 66.72 232 | 77.67 168 | 36.33 314 | 76.83 159 | 79.52 144 | 62.45 61 | 62.54 220 | 83.47 144 | 46.32 143 | 78.37 231 | 45.47 241 | 63.43 283 | 85.45 103 |
|
WR-MVS_H | | | 67.02 180 | 66.92 163 | 67.33 229 | 77.95 162 | 37.75 304 | 77.57 139 | 82.11 92 | 62.03 71 | 62.65 217 | 82.48 159 | 50.57 93 | 79.46 212 | 42.91 261 | 64.01 278 | 84.79 126 |
|
WR-MVS | | | 68.47 153 | 68.47 130 | 68.44 219 | 80.20 113 | 39.84 287 | 73.75 215 | 76.07 202 | 64.68 22 | 68.11 135 | 83.63 139 | 50.39 95 | 79.14 222 | 49.78 202 | 69.66 232 | 86.34 68 |
|
NR-MVSNet | | | 69.54 130 | 68.85 123 | 71.59 164 | 78.05 159 | 43.81 261 | 74.20 205 | 80.86 123 | 65.18 16 | 62.76 214 | 84.52 121 | 52.35 74 | 83.59 136 | 50.96 197 | 70.78 210 | 87.37 40 |
|
Baseline_NR-MVSNet | | | 67.05 179 | 67.56 143 | 65.50 252 | 75.65 207 | 37.70 305 | 75.42 182 | 74.65 223 | 59.90 105 | 68.14 134 | 83.15 148 | 49.12 108 | 77.20 247 | 52.23 188 | 69.78 228 | 81.60 199 |
|
TranMVSNet+NR-MVSNet | | | 70.36 112 | 70.10 107 | 71.17 176 | 78.64 142 | 42.97 268 | 76.53 162 | 81.16 115 | 66.95 6 | 68.53 126 | 85.42 110 | 51.61 82 | 83.07 145 | 52.32 187 | 69.70 231 | 87.46 37 |
|
TSAR-MVS + GP. | | | 74.90 54 | 74.15 60 | 77.17 53 | 82.00 82 | 58.77 70 | 81.80 76 | 78.57 161 | 58.58 127 | 74.32 50 | 84.51 123 | 55.94 37 | 87.22 48 | 67.11 78 | 84.48 67 | 85.52 99 |
|
abl_6 | | | 74.34 61 | 73.50 66 | 76.86 56 | 82.43 77 | 60.16 47 | 83.48 50 | 81.86 95 | 58.81 124 | 73.95 56 | 89.86 42 | 41.87 183 | 86.62 68 | 67.98 70 | 81.23 92 | 83.80 155 |
|
n2 | | | | | | | | | 0.00 356 | | | | | | | | |
|
nn | | | | | | | | | 0.00 356 | | | | | | | | |
|
mPP-MVS | | | 76.54 41 | 75.93 44 | 78.34 36 | 86.47 23 | 63.50 4 | 85.74 23 | 82.28 88 | 62.90 50 | 71.77 83 | 90.26 32 | 46.61 142 | 86.55 72 | 71.71 51 | 85.66 60 | 84.97 120 |
|
door-mid | | | | | | | | | 47.19 340 | | | | | | | | |
|
XVG-OURS-SEG-HR | | | 68.81 141 | 67.47 148 | 72.82 141 | 74.40 229 | 56.87 101 | 70.59 256 | 79.04 150 | 54.77 196 | 66.99 154 | 86.01 98 | 39.57 206 | 78.21 234 | 62.54 117 | 73.33 179 | 83.37 166 |
|
DWT-MVSNet_test | | | 61.90 238 | 59.93 243 | 67.83 223 | 71.98 260 | 46.09 239 | 71.03 253 | 69.71 253 | 50.09 242 | 58.51 259 | 70.62 306 | 30.21 290 | 77.63 242 | 49.28 209 | 67.91 251 | 79.78 230 |
|
MVSFormer | | | 71.50 97 | 70.38 103 | 74.88 88 | 78.76 138 | 57.15 98 | 82.79 59 | 78.48 165 | 51.26 232 | 69.49 110 | 83.22 145 | 43.99 166 | 83.24 141 | 66.06 85 | 79.37 115 | 84.23 140 |
|
jason | | | 69.65 127 | 68.39 133 | 73.43 128 | 78.27 152 | 56.88 100 | 77.12 151 | 73.71 233 | 46.53 274 | 69.34 114 | 83.22 145 | 43.37 170 | 79.18 217 | 64.77 97 | 79.20 120 | 84.23 140 |
jason: jason. |
lupinMVS | | | 69.57 129 | 68.28 134 | 73.44 127 | 78.76 138 | 57.15 98 | 76.57 161 | 73.29 236 | 46.19 277 | 69.49 110 | 82.18 165 | 43.99 166 | 79.23 216 | 64.66 98 | 79.37 115 | 83.93 146 |
|
test_djsdf | | | 69.45 133 | 67.74 139 | 74.58 97 | 74.57 225 | 54.92 130 | 82.79 59 | 78.48 165 | 51.26 232 | 65.41 181 | 83.49 143 | 38.37 218 | 83.24 141 | 66.06 85 | 69.25 238 | 85.56 98 |
|
HPM-MVS_fast | | | 74.30 63 | 73.46 69 | 76.80 57 | 84.45 61 | 59.04 64 | 83.65 48 | 81.05 116 | 60.15 101 | 70.43 92 | 89.84 43 | 41.09 198 | 85.59 91 | 67.61 74 | 82.90 78 | 85.77 89 |
|
RRT_test8_iter05 | | | 68.17 160 | 66.86 164 | 72.07 154 | 75.81 204 | 46.33 234 | 76.41 165 | 81.81 97 | 56.43 160 | 66.52 160 | 81.30 184 | 31.90 281 | 84.25 120 | 63.77 109 | 67.83 253 | 85.64 96 |
|
K. test v3 | | | 60.47 248 | 57.11 259 | 70.56 186 | 73.74 235 | 48.22 215 | 75.10 191 | 62.55 300 | 58.27 135 | 53.62 298 | 76.31 268 | 27.81 305 | 81.59 176 | 47.42 219 | 39.18 337 | 81.88 197 |
|
lessismore_v0 | | | | | 69.91 198 | 71.42 268 | 47.80 219 | | 50.90 333 | | 50.39 314 | 75.56 276 | 27.43 309 | 81.33 180 | 45.91 233 | 34.10 339 | 80.59 217 |
|
SixPastTwentyTwo | | | 61.65 242 | 58.80 248 | 70.20 192 | 75.80 205 | 47.22 227 | 75.59 180 | 69.68 255 | 54.61 197 | 54.11 293 | 79.26 230 | 27.07 311 | 82.96 148 | 43.27 256 | 49.79 328 | 80.41 220 |
|
OurMVSNet-221017-0 | | | 61.37 244 | 58.63 250 | 69.61 202 | 72.05 258 | 48.06 217 | 73.93 212 | 72.51 240 | 47.23 270 | 54.74 285 | 80.92 192 | 21.49 331 | 81.24 183 | 48.57 215 | 56.22 313 | 79.53 233 |
|
HPM-MVS | | | 77.28 33 | 76.85 35 | 78.54 31 | 85.00 52 | 60.81 40 | 82.91 58 | 85.08 31 | 62.57 58 | 73.09 68 | 89.97 40 | 50.90 92 | 87.48 45 | 75.30 27 | 86.85 51 | 87.33 43 |
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
XVG-OURS | | | 68.76 145 | 67.37 151 | 72.90 138 | 74.32 230 | 57.22 93 | 70.09 262 | 78.81 154 | 55.24 185 | 67.79 145 | 85.81 104 | 36.54 238 | 78.28 233 | 62.04 121 | 75.74 156 | 83.19 173 |
|
XVG-ACMP-BASELINE | | | 64.36 215 | 62.23 223 | 70.74 183 | 72.35 254 | 52.45 161 | 70.80 255 | 78.45 168 | 53.84 206 | 59.87 243 | 81.10 187 | 16.24 335 | 79.32 215 | 55.64 162 | 71.76 201 | 80.47 218 |
|
LPG-MVS_test | | | 72.74 78 | 71.74 82 | 75.76 71 | 80.22 111 | 57.51 89 | 82.55 66 | 83.40 68 | 61.32 78 | 66.67 158 | 87.33 72 | 39.15 211 | 86.59 69 | 67.70 72 | 77.30 143 | 83.19 173 |
|
LGP-MVS_train | | | | | 75.76 71 | 80.22 111 | 57.51 89 | | 83.40 68 | 61.32 78 | 66.67 158 | 87.33 72 | 39.15 211 | 86.59 69 | 67.70 72 | 77.30 143 | 83.19 173 |
|
baseline | | | 74.61 59 | 74.70 55 | 74.34 102 | 75.70 206 | 49.99 193 | 77.54 141 | 84.63 40 | 62.73 57 | 73.98 53 | 87.79 68 | 57.67 27 | 83.82 131 | 69.49 61 | 82.74 82 | 89.20 3 |
|
test11 | | | | | | | | | 83.47 65 | | | | | | | | |
|
door | | | | | | | | | 47.60 339 | | | | | | | | |
|
EPNet_dtu | | | 61.90 238 | 61.97 226 | 61.68 277 | 72.89 245 | 39.78 288 | 75.85 178 | 65.62 281 | 55.09 189 | 54.56 288 | 79.36 227 | 37.59 226 | 67.02 294 | 39.80 278 | 76.95 146 | 78.25 243 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
CHOSEN 1792x2688 | | | 65.08 209 | 62.84 216 | 71.82 157 | 81.49 89 | 56.26 107 | 66.32 280 | 74.20 228 | 40.53 317 | 63.16 211 | 78.65 236 | 41.30 194 | 77.80 240 | 45.80 234 | 74.09 166 | 81.40 202 |
|
EPNet | | | 73.09 75 | 72.16 78 | 75.90 69 | 75.95 202 | 56.28 106 | 83.05 54 | 72.39 241 | 66.53 12 | 65.27 183 | 87.00 74 | 50.40 94 | 85.47 98 | 62.48 118 | 86.32 57 | 85.94 81 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
HQP5-MVS | | | | | | | 54.94 128 | | | | | | | | | | |
|
HQP-NCC | | | | | | 80.66 102 | | 82.31 70 | | 62.10 67 | 67.85 139 | | | | | | |
|
ACMP_Plane | | | | | | 80.66 102 | | 82.31 70 | | 62.10 67 | 67.85 139 | | | | | | |
|
APD-MVS | | | 78.02 24 | 78.04 25 | 77.98 41 | 86.44 24 | 60.81 40 | 85.52 26 | 84.36 43 | 60.61 88 | 79.05 19 | 90.30 30 | 55.54 41 | 88.32 29 | 73.48 43 | 87.03 48 | 84.83 123 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
BP-MVS | | | | | | | | | | | | | | | 67.04 79 | | |
|
HQP4-MVS | | | | | | | | | | | 67.85 139 | | | 86.93 58 | | | 84.32 137 |
|
HQP3-MVS | | | | | | | | | 83.90 54 | | | | | | | 80.35 103 | |
|
HQP2-MVS | | | | | | | | | | | | | 45.46 151 | | | | |
|
CNVR-MVS | | | 79.84 8 | 79.97 8 | 79.45 7 | 87.90 2 | 62.17 20 | 84.37 34 | 85.03 33 | 66.96 5 | 77.58 27 | 90.06 35 | 59.47 17 | 89.13 18 | 78.67 9 | 89.73 16 | 87.03 49 |
|
NCCC | | | 78.58 15 | 78.31 19 | 79.39 8 | 87.51 11 | 62.61 16 | 85.20 29 | 84.42 42 | 66.73 9 | 74.67 47 | 89.38 49 | 55.30 42 | 89.18 17 | 74.19 35 | 87.34 44 | 86.38 62 |
|
114514_t | | | 70.83 102 | 69.56 111 | 74.64 95 | 86.21 29 | 54.63 132 | 82.34 69 | 81.81 97 | 48.22 259 | 63.01 212 | 85.83 102 | 40.92 199 | 87.10 53 | 57.91 147 | 79.79 108 | 82.18 191 |
|
CP-MVS | | | 77.12 36 | 76.68 37 | 78.43 32 | 86.05 37 | 63.18 7 | 87.55 8 | 83.45 66 | 62.44 62 | 72.68 73 | 90.50 22 | 48.18 117 | 87.34 46 | 73.59 41 | 85.71 59 | 84.76 128 |
|
DSMNet-mixed | | | 39.30 311 | 38.72 311 | 41.03 325 | 51.22 342 | 19.66 347 | 45.53 337 | 31.35 348 | 15.83 345 | 39.80 336 | 67.42 320 | 22.19 329 | 45.13 341 | 22.43 336 | 52.69 322 | 58.31 332 |
|
tpm2 | | | 62.07 236 | 60.10 242 | 67.99 222 | 72.79 246 | 43.86 260 | 71.05 252 | 66.85 275 | 43.14 304 | 62.77 213 | 75.39 279 | 38.32 219 | 80.80 194 | 41.69 269 | 68.88 243 | 79.32 235 |
|
NP-MVS | | | | | | 80.98 100 | 56.05 112 | | | | | 85.54 108 | | | | | |
|
EG-PatchMatch MVS | | | 64.71 211 | 62.87 215 | 70.22 190 | 77.68 167 | 53.48 143 | 77.99 132 | 78.82 153 | 53.37 209 | 56.03 274 | 77.41 254 | 24.75 324 | 84.04 124 | 46.37 229 | 73.42 178 | 73.14 296 |
|
tpm cat1 | | | 59.25 254 | 56.95 262 | 66.15 241 | 72.19 256 | 46.96 229 | 68.09 273 | 65.76 280 | 40.03 320 | 57.81 264 | 70.56 307 | 38.32 219 | 74.51 264 | 38.26 283 | 61.50 296 | 77.00 260 |
|
SteuartSystems-ACMMP | | | 79.48 9 | 79.31 10 | 79.98 2 | 83.01 73 | 62.18 19 | 87.60 7 | 85.83 21 | 66.69 10 | 78.03 26 | 90.98 12 | 54.26 52 | 90.06 9 | 78.42 14 | 89.02 23 | 87.69 27 |
Skip Steuart: Steuart Systems R&D Blog. |
CostFormer | | | 64.04 216 | 62.51 219 | 68.61 217 | 71.88 261 | 45.77 241 | 71.30 246 | 70.60 250 | 47.55 267 | 64.31 201 | 76.61 263 | 41.63 187 | 79.62 211 | 49.74 204 | 69.00 242 | 80.42 219 |
|
CR-MVSNet | | | 59.91 250 | 57.90 256 | 65.96 245 | 69.96 286 | 52.07 165 | 65.31 289 | 63.15 297 | 42.48 308 | 59.36 248 | 74.84 282 | 35.83 240 | 70.75 278 | 45.50 239 | 64.65 275 | 75.06 277 |
|
JIA-IIPM | | | 51.56 294 | 47.68 303 | 63.21 267 | 64.61 321 | 50.73 179 | 47.71 334 | 58.77 313 | 42.90 305 | 48.46 317 | 51.72 336 | 24.97 322 | 70.24 281 | 36.06 299 | 53.89 320 | 68.64 324 |
|
Patchmtry | | | 57.16 268 | 56.47 265 | 59.23 284 | 69.17 295 | 34.58 322 | 62.98 298 | 63.15 297 | 44.53 290 | 56.83 269 | 74.84 282 | 35.83 240 | 68.71 286 | 40.03 276 | 60.91 298 | 74.39 288 |
|
PatchT | | | 53.17 289 | 53.44 287 | 52.33 314 | 68.29 301 | 25.34 343 | 58.21 316 | 54.41 328 | 44.46 292 | 54.56 288 | 69.05 314 | 33.32 263 | 60.94 312 | 36.93 289 | 61.76 295 | 70.73 317 |
|
tpmrst | | | 58.24 260 | 58.70 249 | 56.84 296 | 66.97 306 | 34.32 323 | 69.57 266 | 61.14 307 | 47.17 271 | 58.58 258 | 71.60 300 | 41.28 196 | 60.41 315 | 49.20 210 | 62.84 287 | 75.78 271 |
|
BH-w/o | | | 66.85 183 | 65.83 184 | 69.90 199 | 79.29 125 | 52.46 160 | 74.66 200 | 76.65 197 | 54.51 201 | 64.85 194 | 78.12 241 | 45.59 150 | 82.95 149 | 43.26 257 | 75.54 158 | 74.27 289 |
|
tpm | | | 57.34 267 | 58.16 253 | 54.86 303 | 71.80 263 | 34.77 320 | 67.47 276 | 56.04 325 | 48.20 260 | 60.10 240 | 76.92 257 | 37.17 232 | 53.41 336 | 40.76 274 | 65.01 272 | 76.40 266 |
|
DELS-MVS | | | 74.76 56 | 74.46 57 | 75.65 76 | 77.84 164 | 52.25 163 | 75.59 180 | 84.17 47 | 63.76 38 | 73.15 67 | 82.79 150 | 59.58 16 | 86.80 61 | 67.24 77 | 86.04 58 | 87.89 19 |
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 |
BH-untuned | | | 68.27 155 | 67.29 154 | 71.21 174 | 79.74 122 | 53.22 147 | 76.06 173 | 77.46 186 | 57.19 144 | 66.10 168 | 81.61 177 | 45.37 155 | 83.50 137 | 45.42 242 | 76.68 152 | 76.91 263 |
|
RPMNet | | | 58.70 256 | 56.29 268 | 65.96 245 | 69.96 286 | 52.07 165 | 65.31 289 | 62.15 303 | 43.20 303 | 59.36 248 | 70.15 310 | 35.37 242 | 70.75 278 | 36.42 297 | 64.65 275 | 75.06 277 |
|
MVSTER | | | 67.16 177 | 65.58 189 | 71.88 156 | 70.37 279 | 49.70 196 | 70.25 261 | 78.45 168 | 51.52 226 | 69.16 119 | 80.37 202 | 38.45 217 | 82.50 161 | 60.19 135 | 71.46 205 | 83.44 165 |
|
CPTT-MVS | | | 72.78 77 | 72.08 80 | 74.87 89 | 84.88 58 | 61.41 29 | 84.15 39 | 77.86 177 | 55.27 184 | 67.51 148 | 88.08 65 | 41.93 182 | 81.85 171 | 69.04 66 | 80.01 107 | 81.35 205 |
|
GBi-Net | | | 67.21 173 | 66.55 167 | 69.19 208 | 77.63 169 | 43.33 264 | 77.31 145 | 77.83 178 | 56.62 154 | 65.04 190 | 82.70 151 | 41.85 184 | 80.33 203 | 47.18 222 | 72.76 189 | 83.92 147 |
|
PVSNet_Blended_VisFu | | | 71.45 98 | 70.39 102 | 74.65 94 | 82.01 81 | 58.82 69 | 79.93 104 | 80.35 132 | 55.09 189 | 65.82 176 | 82.16 168 | 49.17 105 | 82.64 159 | 60.34 134 | 78.62 131 | 82.50 187 |
|
PVSNet_BlendedMVS | | | 68.56 151 | 67.72 140 | 71.07 179 | 77.03 184 | 50.57 181 | 74.50 202 | 81.52 101 | 53.66 208 | 64.22 204 | 79.72 219 | 49.13 106 | 82.87 151 | 55.82 157 | 73.92 169 | 79.77 231 |
|
UnsupCasMVSNet_eth | | | 53.16 290 | 52.47 289 | 55.23 301 | 59.45 337 | 33.39 328 | 59.43 313 | 69.13 262 | 45.98 279 | 50.35 315 | 72.32 296 | 29.30 297 | 58.26 321 | 42.02 268 | 44.30 334 | 74.05 291 |
|
UnsupCasMVSNet_bld | | | 50.07 298 | 48.87 298 | 53.66 307 | 60.97 335 | 33.67 326 | 57.62 318 | 64.56 289 | 39.47 322 | 47.38 319 | 64.02 328 | 27.47 307 | 59.32 318 | 34.69 302 | 43.68 335 | 67.98 325 |
|
PVSNet_Blended | | | 68.59 147 | 67.72 140 | 71.19 175 | 77.03 184 | 50.57 181 | 72.51 231 | 81.52 101 | 51.91 221 | 64.22 204 | 77.77 251 | 49.13 106 | 82.87 151 | 55.82 157 | 79.58 112 | 80.14 224 |
|
FMVSNet5 | | | 55.86 276 | 54.93 275 | 58.66 289 | 71.05 271 | 36.35 313 | 64.18 296 | 62.48 301 | 46.76 273 | 50.66 313 | 74.73 284 | 25.80 318 | 64.04 304 | 33.11 307 | 65.57 269 | 75.59 273 |
|
test1 | | | 67.21 173 | 66.55 167 | 69.19 208 | 77.63 169 | 43.33 264 | 77.31 145 | 77.83 178 | 56.62 154 | 65.04 190 | 82.70 151 | 41.85 184 | 80.33 203 | 47.18 222 | 72.76 189 | 83.92 147 |
|
new_pmnet | | | 34.13 314 | 34.29 314 | 33.64 327 | 52.63 340 | 18.23 349 | 44.43 339 | 33.90 347 | 22.81 341 | 30.89 339 | 53.18 334 | 10.48 344 | 35.72 347 | 20.77 338 | 39.51 336 | 46.98 338 |
|
FMVSNet3 | | | 66.32 194 | 65.61 188 | 68.46 218 | 76.48 195 | 42.34 271 | 74.98 194 | 77.15 191 | 55.83 174 | 65.04 190 | 81.16 185 | 39.91 202 | 80.14 207 | 47.18 222 | 72.76 189 | 82.90 181 |
|
dp | | | 51.89 293 | 51.60 292 | 52.77 312 | 68.44 300 | 32.45 330 | 62.36 301 | 54.57 327 | 44.16 295 | 49.31 316 | 67.91 316 | 28.87 300 | 56.61 327 | 33.89 304 | 54.89 316 | 69.24 323 |
|
FMVSNet2 | | | 66.93 182 | 66.31 177 | 68.79 215 | 77.63 169 | 42.98 267 | 76.11 171 | 77.47 184 | 56.62 154 | 65.22 189 | 82.17 167 | 41.85 184 | 80.18 206 | 47.05 225 | 72.72 192 | 83.20 172 |
|
FMVSNet1 | | | 66.70 187 | 65.87 183 | 69.19 208 | 77.49 176 | 43.33 264 | 77.31 145 | 77.83 178 | 56.45 159 | 64.60 198 | 82.70 151 | 38.08 223 | 80.33 203 | 46.08 231 | 72.31 197 | 83.92 147 |
|
N_pmnet | | | 39.35 310 | 40.28 310 | 36.54 326 | 63.76 324 | 1.62 354 | 49.37 332 | 0.76 355 | 34.62 329 | 43.61 330 | 66.38 322 | 26.25 316 | 42.57 343 | 26.02 335 | 51.77 323 | 65.44 327 |
|
cascas | | | 65.98 197 | 63.42 210 | 73.64 121 | 77.26 180 | 52.58 156 | 72.26 235 | 77.21 190 | 48.56 254 | 61.21 235 | 74.60 285 | 32.57 277 | 85.82 89 | 50.38 200 | 76.75 151 | 82.52 186 |
|
BH-RMVSNet | | | 68.81 141 | 67.42 149 | 72.97 136 | 80.11 116 | 52.53 157 | 74.26 204 | 76.29 199 | 58.48 130 | 68.38 128 | 84.20 126 | 42.59 174 | 83.83 130 | 46.53 227 | 75.91 155 | 82.56 184 |
|
UGNet | | | 68.81 141 | 67.39 150 | 73.06 135 | 78.33 150 | 54.47 133 | 79.77 107 | 75.40 212 | 60.45 91 | 63.22 209 | 84.40 124 | 32.71 273 | 80.91 192 | 51.71 193 | 80.56 99 | 83.81 151 |
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 |
WTY-MVS | | | 59.75 252 | 60.39 240 | 57.85 293 | 72.32 255 | 37.83 303 | 61.05 309 | 64.18 291 | 45.95 282 | 61.91 228 | 79.11 232 | 47.01 138 | 60.88 313 | 42.50 263 | 69.49 234 | 74.83 282 |
|
XXY-MVS | | | 60.68 246 | 61.67 228 | 57.70 295 | 70.43 277 | 38.45 299 | 64.19 295 | 66.47 276 | 48.05 262 | 63.22 209 | 80.86 194 | 49.28 103 | 60.47 314 | 45.25 244 | 67.28 258 | 74.19 290 |
|
sss | | | 56.17 275 | 56.57 264 | 54.96 302 | 66.93 307 | 36.32 315 | 57.94 317 | 61.69 305 | 41.67 311 | 58.64 257 | 75.32 280 | 38.72 215 | 56.25 329 | 42.04 267 | 66.19 264 | 72.31 308 |
|
Test_1112_low_res | | | 62.32 233 | 61.77 227 | 64.00 263 | 79.08 132 | 39.53 291 | 68.17 272 | 70.17 251 | 43.25 302 | 59.03 253 | 79.90 213 | 44.08 164 | 71.24 276 | 43.79 253 | 68.42 248 | 81.25 206 |
|
1112_ss | | | 64.00 217 | 63.36 211 | 65.93 247 | 79.28 126 | 42.58 270 | 71.35 244 | 72.36 242 | 46.41 275 | 60.55 238 | 77.89 247 | 46.27 145 | 73.28 268 | 46.18 230 | 69.97 223 | 81.92 196 |
|
ab-mvs-re | | | 6.49 322 | 8.65 324 | 0.00 337 | 0.00 356 | 0.00 356 | 0.00 348 | 0.00 356 | 0.00 352 | 0.00 353 | 77.89 247 | 0.00 357 | 0.00 352 | 0.00 351 | 0.00 349 | 0.00 350 |
|
ab-mvs | | | 66.65 188 | 66.42 172 | 67.37 227 | 76.17 198 | 41.73 278 | 70.41 260 | 76.14 201 | 53.99 204 | 65.98 170 | 83.51 142 | 49.48 100 | 76.24 258 | 48.60 214 | 73.46 177 | 84.14 143 |
|
TR-MVS | | | 66.59 191 | 65.07 195 | 71.17 176 | 79.18 129 | 49.63 200 | 73.48 217 | 75.20 215 | 52.95 211 | 67.90 137 | 80.33 205 | 39.81 204 | 83.68 133 | 43.20 258 | 73.56 175 | 80.20 222 |
|
MDTV_nov1_ep13_2view | | | | | | | 25.89 341 | 61.22 307 | | 40.10 319 | 51.10 308 | | 32.97 267 | | 38.49 281 | | 78.61 241 |
|
MDTV_nov1_ep13 | | | | 57.00 261 | | 72.73 247 | 38.26 300 | 65.02 292 | 64.73 288 | 44.74 287 | 55.46 277 | 72.48 295 | 32.61 276 | 70.47 280 | 37.47 286 | 67.75 255 | |
|
MIMVSNet1 | | | 55.17 280 | 54.31 281 | 57.77 294 | 70.03 285 | 32.01 331 | 65.68 284 | 64.81 286 | 49.19 249 | 46.75 323 | 76.00 270 | 25.53 320 | 64.04 304 | 28.65 328 | 62.13 292 | 77.26 256 |
|
MIMVSNet | | | 57.35 266 | 57.07 260 | 58.22 290 | 74.21 232 | 37.18 306 | 62.46 300 | 60.88 308 | 48.88 252 | 55.29 281 | 75.99 272 | 31.68 282 | 62.04 310 | 31.87 311 | 72.35 195 | 75.43 275 |
|
IterMVS-LS | | | 69.22 137 | 68.48 129 | 71.43 168 | 74.44 228 | 49.40 202 | 76.23 169 | 77.55 183 | 59.60 111 | 65.85 175 | 81.59 179 | 51.28 85 | 81.58 177 | 59.87 139 | 69.90 226 | 83.30 168 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
CDS-MVSNet | | | 66.80 185 | 65.37 190 | 71.10 178 | 78.98 134 | 53.13 150 | 73.27 220 | 71.07 247 | 52.15 220 | 64.72 195 | 80.23 209 | 43.56 169 | 77.10 248 | 45.48 240 | 78.88 124 | 83.05 178 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
ACMMP++_ref | | | | | | | | | | | | | | | | 74.07 168 | |
|
IterMVS | | | 62.79 229 | 61.27 233 | 67.35 228 | 69.37 293 | 52.04 167 | 71.17 248 | 68.24 268 | 52.63 216 | 59.82 244 | 76.91 258 | 37.32 229 | 72.36 271 | 52.80 185 | 63.19 285 | 77.66 250 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
DP-MVS Recon | | | 72.15 89 | 70.73 97 | 76.40 63 | 86.57 21 | 57.99 81 | 81.15 88 | 82.96 79 | 57.03 146 | 66.78 156 | 85.56 106 | 44.50 161 | 88.11 33 | 51.77 192 | 80.23 106 | 83.10 177 |
|
MVS_111021_LR | | | 69.50 131 | 68.78 125 | 71.65 162 | 78.38 147 | 59.33 56 | 74.82 197 | 70.11 252 | 58.08 136 | 67.83 143 | 84.68 116 | 41.96 181 | 76.34 257 | 65.62 92 | 77.54 138 | 79.30 236 |
|
DP-MVS | | | 65.68 199 | 63.66 207 | 71.75 158 | 84.93 56 | 56.87 101 | 80.74 92 | 73.16 237 | 53.06 210 | 59.09 252 | 82.35 161 | 36.79 237 | 85.94 87 | 32.82 308 | 69.96 224 | 72.45 303 |
|
ACMMP++ | | | | | | | | | | | | | | | | 72.16 198 | |
|
HQP-MVS | | | 73.45 71 | 72.80 74 | 75.40 80 | 80.66 102 | 54.94 128 | 82.31 70 | 83.90 54 | 62.10 67 | 67.85 139 | 85.54 108 | 45.46 151 | 86.93 58 | 67.04 79 | 80.35 103 | 84.32 137 |
|
QAPM | | | 70.05 117 | 68.81 124 | 73.78 111 | 76.54 194 | 53.43 144 | 83.23 52 | 83.48 64 | 52.89 213 | 65.90 173 | 86.29 92 | 41.55 191 | 86.49 75 | 51.01 196 | 78.40 133 | 81.42 201 |
|
Vis-MVSNet | | | 72.18 86 | 71.37 88 | 74.61 96 | 81.29 93 | 55.41 125 | 80.90 89 | 78.28 174 | 60.73 87 | 69.23 118 | 88.09 64 | 44.36 163 | 82.65 158 | 57.68 148 | 81.75 89 | 85.77 89 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
MVS-HIRNet | | | 45.52 304 | 44.48 306 | 48.65 319 | 68.49 299 | 34.05 324 | 59.41 314 | 44.50 342 | 27.03 336 | 37.96 337 | 50.47 339 | 26.16 317 | 64.10 303 | 26.74 333 | 59.52 303 | 47.82 337 |
|
IS-MVSNet | | | 71.57 95 | 71.00 94 | 73.27 132 | 78.86 136 | 45.63 246 | 80.22 99 | 78.69 158 | 64.14 35 | 66.46 162 | 87.36 71 | 49.30 102 | 85.60 90 | 50.26 201 | 83.71 70 | 88.59 5 |
|
HyFIR lowres test | | | 65.67 200 | 63.01 214 | 73.67 118 | 79.97 118 | 55.65 119 | 69.07 270 | 75.52 210 | 42.68 307 | 63.53 207 | 77.95 243 | 40.43 200 | 81.64 174 | 46.01 232 | 71.91 200 | 83.73 156 |
|
EPMVS | | | 53.96 283 | 53.69 285 | 54.79 304 | 66.12 314 | 31.96 332 | 62.34 302 | 49.05 335 | 44.42 293 | 55.54 276 | 71.33 302 | 30.22 289 | 56.70 326 | 41.65 271 | 62.54 290 | 75.71 272 |
|
PAPM_NR | | | 72.63 79 | 71.80 81 | 75.13 85 | 81.72 85 | 53.42 145 | 79.91 105 | 83.28 74 | 59.14 119 | 66.31 166 | 85.90 100 | 51.86 79 | 86.06 81 | 57.45 149 | 80.62 95 | 85.91 82 |
|
TAMVS | | | 66.78 186 | 65.27 193 | 71.33 173 | 79.16 131 | 53.67 138 | 73.84 214 | 69.59 257 | 52.32 219 | 65.28 182 | 81.72 175 | 44.49 162 | 77.40 246 | 42.32 264 | 78.66 130 | 82.92 179 |
|
PAPR | | | 71.72 94 | 70.82 96 | 74.41 101 | 81.20 97 | 51.17 171 | 79.55 112 | 83.33 71 | 55.81 175 | 66.93 155 | 84.61 119 | 50.95 90 | 86.06 81 | 55.79 159 | 79.20 120 | 86.00 80 |
|
RPSCF | | | 55.80 277 | 54.22 283 | 60.53 283 | 65.13 319 | 42.91 269 | 64.30 294 | 57.62 318 | 36.84 326 | 58.05 263 | 82.28 164 | 28.01 303 | 56.24 330 | 37.14 288 | 58.61 307 | 82.44 189 |
|
Vis-MVSNet (Re-imp) | | | 63.69 219 | 63.88 202 | 63.14 268 | 74.75 221 | 31.04 334 | 71.16 249 | 63.64 293 | 56.32 162 | 59.80 245 | 84.99 112 | 44.51 160 | 75.46 260 | 39.12 279 | 80.62 95 | 82.92 179 |
|
test_0402 | | | 63.25 225 | 61.01 237 | 69.96 195 | 80.00 117 | 54.37 134 | 76.86 158 | 72.02 243 | 54.58 199 | 58.71 255 | 80.79 197 | 35.00 246 | 84.36 118 | 26.41 334 | 64.71 274 | 71.15 315 |
|
MVS_111021_HR | | | 74.02 66 | 73.46 69 | 75.69 75 | 83.01 73 | 60.63 43 | 77.29 148 | 78.40 172 | 61.18 81 | 70.58 91 | 85.97 99 | 54.18 54 | 84.00 128 | 67.52 75 | 82.98 76 | 82.45 188 |
|
CSCG | | | 76.92 37 | 76.75 36 | 77.41 49 | 83.96 64 | 59.60 52 | 82.95 56 | 86.50 15 | 60.78 86 | 75.27 36 | 84.83 114 | 60.76 12 | 86.56 71 | 67.86 71 | 87.87 42 | 86.06 79 |
|
PatchMatch-RL | | | 56.25 274 | 54.55 278 | 61.32 281 | 77.06 183 | 56.07 111 | 65.57 285 | 54.10 330 | 44.13 296 | 53.49 301 | 71.27 303 | 25.20 321 | 66.78 295 | 36.52 296 | 63.66 280 | 61.12 329 |
|
API-MVS | | | 72.17 87 | 71.41 86 | 74.45 100 | 81.95 83 | 57.22 93 | 84.03 42 | 80.38 130 | 59.89 108 | 68.40 127 | 82.33 162 | 49.64 99 | 87.83 40 | 51.87 190 | 84.16 69 | 78.30 242 |
|
Test By Simon | | | | | | | | | | | | | 48.33 116 | | | | |
|
TDRefinement | | | 53.44 287 | 50.72 294 | 61.60 278 | 64.31 323 | 46.96 229 | 70.89 254 | 65.27 285 | 41.78 309 | 44.61 328 | 77.98 242 | 11.52 341 | 66.36 297 | 28.57 329 | 51.59 324 | 71.49 312 |
|
USDC | | | 56.35 273 | 54.24 282 | 62.69 271 | 64.74 320 | 40.31 285 | 65.05 291 | 73.83 231 | 43.93 298 | 47.58 318 | 77.71 252 | 15.36 337 | 75.05 262 | 38.19 284 | 61.81 294 | 72.70 299 |
|
EPP-MVSNet | | | 72.16 88 | 71.31 90 | 74.71 90 | 78.68 141 | 49.70 196 | 82.10 74 | 81.65 100 | 60.40 92 | 65.94 171 | 85.84 101 | 51.74 81 | 86.37 78 | 55.93 156 | 79.55 114 | 88.07 17 |
|
PMMVS | | | 53.96 283 | 53.26 288 | 56.04 298 | 62.60 327 | 50.92 175 | 61.17 308 | 56.09 324 | 32.81 330 | 53.51 300 | 66.84 321 | 34.04 255 | 59.93 317 | 44.14 249 | 68.18 249 | 57.27 334 |
|
PAPM | | | 67.92 164 | 66.69 166 | 71.63 163 | 78.09 157 | 49.02 206 | 77.09 152 | 81.24 113 | 51.04 234 | 60.91 236 | 83.98 132 | 47.71 122 | 84.99 103 | 40.81 273 | 79.32 118 | 80.90 214 |
|
ACMMP | | | 76.02 46 | 75.33 49 | 78.07 38 | 85.20 49 | 61.91 23 | 85.49 28 | 84.44 41 | 63.04 47 | 69.80 107 | 89.74 45 | 45.43 153 | 87.16 51 | 72.01 50 | 82.87 79 | 85.14 113 |
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 | | | 65.43 203 | 64.02 200 | 69.68 201 | 78.73 140 | 58.07 80 | 77.82 135 | 70.71 249 | 51.49 227 | 61.57 233 | 83.58 141 | 38.23 221 | 70.82 277 | 43.90 251 | 70.10 222 | 80.16 223 |
|
PatchmatchNet | | | 59.84 251 | 58.24 252 | 64.65 260 | 73.05 242 | 46.70 231 | 69.42 267 | 62.18 302 | 47.55 267 | 58.88 254 | 71.96 299 | 34.49 251 | 69.16 284 | 42.99 260 | 63.60 281 | 78.07 245 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
PHI-MVS | | | 75.87 48 | 75.36 48 | 77.41 49 | 80.62 105 | 55.91 115 | 84.28 35 | 85.78 22 | 56.08 170 | 73.41 64 | 86.58 86 | 50.94 91 | 88.54 24 | 70.79 57 | 89.71 17 | 87.79 25 |
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F-COLMAP | | | 63.05 228 | 60.87 239 | 69.58 205 | 76.99 186 | 53.63 140 | 78.12 131 | 76.16 200 | 47.97 263 | 52.41 304 | 81.61 177 | 27.87 304 | 78.11 235 | 40.07 275 | 66.66 260 | 77.00 260 |
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ANet_high | | | 41.38 308 | 37.47 312 | 53.11 310 | 39.73 348 | 24.45 344 | 56.94 319 | 69.69 254 | 47.65 266 | 26.04 341 | 52.32 335 | 12.44 338 | 62.38 309 | 21.80 337 | 10.61 346 | 72.49 302 |
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wuyk23d | | | 13.32 320 | 12.52 322 | 15.71 332 | 47.54 344 | 26.27 340 | 31.06 344 | 1.98 354 | 4.93 348 | 5.18 350 | 1.94 350 | 0.45 355 | 18.54 349 | 6.81 348 | 12.83 345 | 2.33 347 |
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OMC-MVS | | | 71.40 99 | 70.60 98 | 73.78 111 | 76.60 192 | 53.15 148 | 79.74 109 | 79.78 138 | 58.37 132 | 68.75 122 | 86.45 89 | 45.43 153 | 80.60 198 | 62.58 116 | 77.73 137 | 87.58 33 |
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MG-MVS | | | 73.96 67 | 73.89 62 | 74.16 105 | 85.65 41 | 49.69 198 | 81.59 82 | 81.29 110 | 61.45 77 | 71.05 89 | 88.11 63 | 51.77 80 | 87.73 41 | 61.05 129 | 83.09 72 | 85.05 117 |
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AdaColmap | | | 69.99 119 | 68.66 127 | 73.97 108 | 84.94 55 | 57.83 83 | 82.63 64 | 78.71 157 | 56.28 164 | 64.34 199 | 84.14 127 | 41.57 188 | 87.06 56 | 46.45 228 | 78.88 124 | 77.02 259 |
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uanet | | | 0.00 326 | 0.00 328 | 0.00 337 | 0.00 356 | 0.00 356 | 0.00 348 | 0.00 356 | 0.00 352 | 0.00 353 | 0.00 353 | 0.00 357 | 0.00 352 | 0.00 351 | 0.00 349 | 0.00 350 |
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ITE_SJBPF | | | | | 62.09 275 | 66.16 313 | 44.55 256 | | 64.32 290 | 47.36 269 | 55.31 280 | 80.34 204 | 19.27 332 | 62.68 308 | 36.29 298 | 62.39 291 | 79.04 237 |
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DeepMVS_CX | | | | | 12.03 333 | 17.97 352 | 10.91 350 | | 10.60 353 | 7.46 347 | 11.07 347 | 28.36 342 | 3.28 352 | 11.29 350 | 8.01 347 | 9.74 348 | 13.89 345 |
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TinyColmap | | | 54.14 282 | 51.72 291 | 61.40 280 | 66.84 308 | 41.97 274 | 66.52 278 | 68.51 266 | 44.81 286 | 42.69 332 | 75.77 274 | 11.66 340 | 72.94 269 | 31.96 310 | 56.77 311 | 69.27 322 |
|
MAR-MVS | | | 71.51 96 | 70.15 106 | 75.60 78 | 81.84 84 | 59.39 55 | 81.38 85 | 82.90 82 | 54.90 195 | 68.08 136 | 78.70 234 | 47.73 121 | 85.51 95 | 51.68 194 | 84.17 68 | 81.88 197 |
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 |
LF4IMVS | | | 42.95 306 | 42.26 307 | 45.04 322 | 48.30 343 | 32.50 329 | 54.80 323 | 48.49 337 | 28.03 335 | 40.51 335 | 70.16 309 | 9.24 345 | 43.89 342 | 31.63 316 | 49.18 330 | 58.72 331 |
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MSDG | | | 61.81 241 | 59.23 245 | 69.55 206 | 72.64 248 | 52.63 155 | 70.45 259 | 75.81 206 | 51.38 229 | 53.70 296 | 76.11 269 | 29.52 294 | 81.08 188 | 37.70 285 | 65.79 268 | 74.93 281 |
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LS3D | | | 64.71 211 | 62.50 220 | 71.34 172 | 79.72 124 | 55.71 117 | 79.82 106 | 74.72 222 | 48.50 256 | 56.62 270 | 84.62 118 | 33.59 261 | 82.34 165 | 29.65 326 | 75.23 160 | 75.97 267 |
|
CLD-MVS | | | 73.33 72 | 72.68 75 | 75.29 84 | 78.82 137 | 53.33 146 | 78.23 129 | 84.79 39 | 61.30 80 | 70.41 93 | 81.04 188 | 52.41 73 | 87.12 52 | 64.61 100 | 82.49 84 | 85.41 107 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
FPMVS | | | 42.18 307 | 41.11 309 | 45.39 321 | 58.03 339 | 41.01 283 | 49.50 331 | 53.81 331 | 30.07 333 | 33.71 338 | 64.03 326 | 11.69 339 | 52.08 338 | 14.01 341 | 55.11 315 | 43.09 339 |
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Gipuma | | | 34.77 313 | 31.91 316 | 43.33 324 | 62.05 329 | 37.87 302 | 20.39 345 | 67.03 274 | 23.23 340 | 18.41 344 | 25.84 343 | 4.24 349 | 62.73 307 | 14.71 340 | 51.32 325 | 29.38 342 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |