LTVRE_ROB | | 98.40 1 | 99.67 3 | 99.71 2 | 99.56 24 | 99.85 16 | 99.11 62 | 99.90 1 | 99.78 10 | 99.63 14 | 99.78 12 | 99.67 19 | 99.48 6 | 99.81 172 | 99.30 22 | 99.97 12 | 99.77 19 |
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 |
3Dnovator | | 98.27 2 | 98.81 72 | 98.73 69 | 99.05 132 | 98.76 253 | 97.81 177 | 99.25 39 | 99.30 151 | 98.57 112 | 98.55 204 | 99.33 74 | 97.95 84 | 99.90 54 | 97.16 143 | 99.67 156 | 99.44 143 |
|
3Dnovator+ | | 97.89 3 | 98.69 93 | 98.51 101 | 99.24 99 | 98.81 248 | 98.40 113 | 99.02 65 | 99.19 186 | 98.99 82 | 98.07 242 | 99.28 79 | 97.11 147 | 99.84 133 | 96.84 176 | 99.32 242 | 99.47 133 |
|
DeepC-MVS | | 97.60 4 | 98.97 53 | 98.93 52 | 99.10 118 | 99.35 131 | 97.98 156 | 98.01 165 | 99.46 85 | 97.56 180 | 99.54 35 | 99.50 44 | 98.97 16 | 99.84 133 | 98.06 96 | 99.92 42 | 99.49 115 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
DeepPCF-MVS | | 96.93 5 | 98.32 147 | 98.01 169 | 99.23 101 | 98.39 310 | 98.97 69 | 95.03 339 | 99.18 190 | 96.88 236 | 99.33 74 | 98.78 195 | 98.16 68 | 99.28 353 | 96.74 184 | 99.62 170 | 99.44 143 |
|
DeepC-MVS_fast | | 96.85 6 | 98.30 149 | 98.15 156 | 98.75 175 | 98.61 283 | 97.23 208 | 97.76 189 | 99.09 215 | 97.31 207 | 98.75 177 | 98.66 216 | 97.56 111 | 99.64 281 | 96.10 234 | 99.55 199 | 99.39 164 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
OpenMVS |  | 96.65 7 | 97.09 247 | 96.68 257 | 98.32 223 | 98.32 313 | 97.16 217 | 98.86 79 | 99.37 112 | 89.48 361 | 96.29 334 | 99.15 106 | 96.56 179 | 99.90 54 | 92.90 323 | 99.20 261 | 97.89 336 |
|
ACMH | | 96.65 7 | 99.25 27 | 99.24 27 | 99.26 94 | 99.72 37 | 98.38 115 | 99.07 60 | 99.55 52 | 98.30 123 | 99.65 26 | 99.45 55 | 99.22 9 | 99.76 220 | 98.44 75 | 99.77 105 | 99.64 48 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
ACMH+ | | 96.62 9 | 99.08 42 | 99.00 47 | 99.33 80 | 99.71 39 | 98.83 80 | 98.60 96 | 99.58 34 | 99.11 63 | 99.53 38 | 99.18 96 | 98.81 24 | 99.67 263 | 96.71 189 | 99.77 105 | 99.50 111 |
|
COLMAP_ROB |  | 96.50 10 | 98.99 48 | 98.85 59 | 99.41 65 | 99.58 60 | 99.10 63 | 98.74 83 | 99.56 48 | 99.09 73 | 99.33 74 | 99.19 94 | 98.40 47 | 99.72 243 | 95.98 237 | 99.76 115 | 99.42 150 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
TAPA-MVS | | 96.21 11 | 96.63 271 | 95.95 282 | 98.65 182 | 98.93 219 | 98.09 140 | 96.93 257 | 99.28 161 | 83.58 376 | 98.13 236 | 97.78 302 | 96.13 197 | 99.40 337 | 93.52 313 | 99.29 249 | 98.45 314 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
ACMM | | 96.08 12 | 98.91 60 | 98.73 69 | 99.48 55 | 99.55 75 | 99.14 55 | 98.07 153 | 99.37 112 | 97.62 173 | 99.04 123 | 98.96 150 | 98.84 22 | 99.79 194 | 97.43 131 | 99.65 162 | 99.49 115 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
HY-MVS | | 95.94 13 | 95.90 293 | 95.35 301 | 97.55 278 | 97.95 333 | 94.79 281 | 98.81 82 | 96.94 342 | 92.28 339 | 95.17 357 | 98.57 234 | 89.90 305 | 99.75 227 | 91.20 351 | 97.33 352 | 98.10 328 |
|
OpenMVS_ROB |  | 95.38 14 | 95.84 295 | 95.18 306 | 97.81 257 | 98.41 309 | 97.15 218 | 97.37 226 | 98.62 289 | 83.86 375 | 98.65 186 | 98.37 259 | 94.29 260 | 99.68 260 | 88.41 364 | 98.62 316 | 96.60 366 |
|
ACMP | | 95.32 15 | 98.41 138 | 98.09 161 | 99.36 69 | 99.51 84 | 98.79 85 | 97.68 196 | 99.38 108 | 95.76 277 | 98.81 170 | 98.82 189 | 98.36 49 | 99.82 158 | 94.75 273 | 99.77 105 | 99.48 125 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
PLC |  | 94.65 16 | 96.51 275 | 95.73 286 | 98.85 158 | 98.75 255 | 97.91 165 | 96.42 287 | 99.06 219 | 90.94 354 | 95.59 345 | 97.38 327 | 94.41 256 | 99.59 297 | 90.93 354 | 98.04 337 | 99.05 245 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
PVSNet | | 93.40 17 | 95.67 298 | 95.70 287 | 95.57 337 | 98.83 243 | 88.57 361 | 92.50 373 | 97.72 322 | 92.69 334 | 96.49 330 | 96.44 348 | 93.72 272 | 99.43 335 | 93.61 310 | 99.28 250 | 98.71 299 |
|
PCF-MVS | | 92.86 18 | 94.36 318 | 93.00 335 | 98.42 215 | 98.70 266 | 97.56 192 | 93.16 371 | 99.11 211 | 79.59 379 | 97.55 277 | 97.43 324 | 92.19 291 | 99.73 235 | 79.85 380 | 99.45 223 | 97.97 335 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
IB-MVS | | 91.63 19 | 92.24 344 | 90.90 348 | 96.27 322 | 97.22 363 | 91.24 353 | 94.36 358 | 93.33 370 | 92.37 337 | 92.24 375 | 94.58 375 | 66.20 388 | 99.89 64 | 93.16 321 | 94.63 375 | 97.66 349 |
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 |
PMVS |  | 91.26 20 | 97.86 187 | 97.94 175 | 97.65 268 | 99.71 39 | 97.94 164 | 98.52 106 | 98.68 285 | 98.99 82 | 97.52 280 | 99.35 68 | 97.41 127 | 98.18 377 | 91.59 345 | 99.67 156 | 96.82 363 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
PVSNet_0 | | 89.98 21 | 91.15 347 | 90.30 350 | 93.70 356 | 97.72 344 | 84.34 380 | 90.24 376 | 97.42 328 | 90.20 358 | 93.79 370 | 93.09 379 | 90.90 299 | 98.89 371 | 86.57 369 | 72.76 383 | 97.87 338 |
|
MVE |  | 83.40 22 | 92.50 340 | 91.92 343 | 94.25 350 | 98.83 243 | 91.64 344 | 92.71 372 | 83.52 386 | 95.92 272 | 86.46 383 | 95.46 364 | 95.20 234 | 95.40 382 | 80.51 379 | 98.64 314 | 95.73 375 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
CMPMVS |  | 75.91 23 | 96.29 284 | 95.44 297 | 98.84 159 | 96.25 377 | 98.69 93 | 97.02 250 | 99.12 209 | 88.90 364 | 97.83 257 | 98.86 177 | 89.51 307 | 98.90 370 | 91.92 339 | 99.51 210 | 98.92 270 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
FMVS2 | | | 99.12 39 | 99.41 14 | 98.25 229 | 99.76 28 | 95.07 277 | 99.05 64 | 99.94 1 | 97.78 163 | 99.82 10 | 99.84 2 | 98.56 38 | 99.71 244 | 99.96 1 | 99.96 15 | 99.97 1 |
|
mvsany_test | | | 98.87 65 | 98.92 53 | 98.74 179 | 99.38 120 | 96.94 225 | 98.58 100 | 99.10 213 | 96.49 250 | 99.96 2 | 99.81 5 | 98.18 64 | 99.45 332 | 98.97 42 | 99.79 96 | 99.83 11 |
|
FMVS1 | | | 99.25 27 | 99.16 31 | 99.51 46 | 99.89 6 | 99.63 3 | 98.71 88 | 99.69 18 | 98.90 92 | 99.43 53 | 99.35 68 | 98.86 20 | 99.67 263 | 97.81 111 | 99.81 81 | 99.24 215 |
|
APD_test | | | 99.25 27 | 99.16 31 | 99.51 46 | 99.89 6 | 99.63 3 | 98.71 88 | 99.69 18 | 98.90 92 | 99.43 53 | 99.35 68 | 98.86 20 | 99.67 263 | 97.81 111 | 99.81 81 | 99.24 215 |
|
FMVS | | | 98.67 100 | 98.87 55 | 98.05 246 | 99.72 37 | 95.59 257 | 98.51 110 | 99.81 9 | 96.30 259 | 99.78 12 | 99.82 4 | 96.14 196 | 98.63 374 | 99.82 2 | 99.93 32 | 99.95 2 |
|
FE-MVS | | | 95.66 299 | 94.95 311 | 97.77 260 | 98.53 295 | 95.28 268 | 99.40 15 | 96.09 353 | 93.11 328 | 97.96 249 | 99.26 83 | 79.10 369 | 99.77 212 | 92.40 335 | 98.71 309 | 98.27 322 |
|
FA-MVS(test-final) | | | 96.99 257 | 96.82 248 | 97.50 282 | 98.70 266 | 94.78 282 | 99.34 19 | 96.99 339 | 95.07 291 | 98.48 211 | 99.33 74 | 88.41 318 | 99.65 278 | 96.13 233 | 98.92 299 | 98.07 330 |
|
iter_conf_final | | | 97.10 245 | 96.65 262 | 98.45 212 | 98.53 295 | 96.08 247 | 98.30 130 | 99.11 211 | 98.10 143 | 98.85 160 | 98.95 154 | 79.38 367 | 99.87 92 | 98.68 61 | 99.91 48 | 99.40 162 |
|
bld_raw_dy_0_64 | | | 99.07 43 | 99.00 47 | 99.29 85 | 99.85 16 | 98.18 132 | 99.11 56 | 99.40 103 | 99.33 44 | 99.38 64 | 99.44 56 | 95.21 233 | 99.97 4 | 99.31 20 | 99.98 9 | 99.73 29 |
|
patch_mono-2 | | | 98.51 128 | 98.63 85 | 98.17 235 | 99.38 120 | 94.78 282 | 97.36 227 | 99.69 18 | 98.16 141 | 98.49 210 | 99.29 78 | 97.06 148 | 99.97 4 | 98.29 84 | 99.91 48 | 99.76 23 |
|
EGC-MVSNET | | | 85.24 348 | 80.54 351 | 99.34 77 | 99.77 25 | 99.20 35 | 99.08 57 | 99.29 158 | 12.08 384 | 20.84 385 | 99.42 58 | 97.55 112 | 99.85 116 | 97.08 152 | 99.72 129 | 98.96 263 |
|
test2506 | | | 92.39 341 | 91.89 344 | 93.89 354 | 99.38 120 | 82.28 383 | 99.32 22 | 66.03 390 | 99.08 75 | 98.77 174 | 99.57 32 | 66.26 387 | 99.84 133 | 98.71 58 | 99.95 19 | 99.54 92 |
|
test1111 | | | 96.49 278 | 96.82 248 | 95.52 338 | 99.42 115 | 87.08 369 | 99.22 41 | 87.14 382 | 99.11 63 | 99.46 48 | 99.58 31 | 88.69 312 | 99.86 101 | 98.80 51 | 99.95 19 | 99.62 52 |
|
ECVR-MVS |  | | 96.42 281 | 96.61 263 | 95.85 330 | 99.38 120 | 88.18 365 | 99.22 41 | 86.00 384 | 99.08 75 | 99.36 69 | 99.57 32 | 88.47 317 | 99.82 158 | 98.52 70 | 99.95 19 | 99.54 92 |
|
test_blank | | | 0.00 356 | 0.00 359 | 0.00 369 | 0.00 392 | 0.00 393 | 0.00 380 | 0.00 393 | 0.00 387 | 0.00 388 | 0.00 387 | 0.00 392 | 0.00 388 | 0.00 386 | 0.00 386 | 0.00 384 |
|
DVP-MVS++ | | | 98.90 62 | 98.70 76 | 99.51 46 | 98.43 305 | 99.15 50 | 99.43 11 | 99.32 135 | 98.17 138 | 99.26 89 | 99.02 129 | 98.18 64 | 99.88 75 | 97.07 153 | 99.45 223 | 99.49 115 |
|
FOURS1 | | | | | | 99.73 31 | 99.67 2 | 99.43 11 | 99.54 57 | 99.43 34 | 99.26 89 | | | | | | |
|
MSC_two_6792asdad | | | | | 99.32 82 | 98.43 305 | 98.37 116 | | 98.86 260 | | | | | 99.89 64 | 97.14 147 | 99.60 178 | 99.71 31 |
|
PC_three_1452 | | | | | | | | | | 93.27 325 | 99.40 60 | 98.54 236 | 98.22 60 | 97.00 380 | 95.17 265 | 99.45 223 | 99.49 115 |
|
No_MVS | | | | | 99.32 82 | 98.43 305 | 98.37 116 | | 98.86 260 | | | | | 99.89 64 | 97.14 147 | 99.60 178 | 99.71 31 |
|
test_one_0601 | | | | | | 99.39 119 | 99.20 35 | | 99.31 141 | 98.49 114 | 98.66 185 | 99.02 129 | 97.64 104 | | | | |
|
eth-test2 | | | | | | 0.00 392 | | | | | | | | | | | |
|
eth-test | | | | | | 0.00 392 | | | | | | | | | | | |
|
GeoE | | | 99.05 44 | 98.99 50 | 99.25 97 | 99.44 110 | 98.35 120 | 98.73 85 | 99.56 48 | 98.42 117 | 98.91 147 | 98.81 191 | 98.94 18 | 99.91 49 | 98.35 80 | 99.73 122 | 99.49 115 |
|
test_method | | | 79.78 349 | 79.50 352 | 80.62 365 | 80.21 388 | 45.76 390 | 70.82 379 | 98.41 300 | 31.08 383 | 80.89 384 | 97.71 306 | 84.85 338 | 97.37 379 | 91.51 347 | 80.03 382 | 98.75 296 |
|
Anonymous20240521 | | | 98.69 93 | 98.87 55 | 98.16 237 | 99.77 25 | 95.11 276 | 99.08 57 | 99.44 91 | 99.34 43 | 99.33 74 | 99.55 36 | 94.10 266 | 99.94 26 | 99.25 25 | 99.96 15 | 99.42 150 |
|
h-mvs33 | | | 97.77 198 | 97.33 219 | 99.10 118 | 99.21 153 | 97.84 171 | 98.35 128 | 98.57 291 | 99.11 63 | 98.58 198 | 99.02 129 | 88.65 315 | 99.96 11 | 98.11 91 | 96.34 363 | 99.49 115 |
|
hse-mvs2 | | | 97.46 218 | 97.07 231 | 98.64 183 | 98.73 257 | 97.33 202 | 97.45 222 | 97.64 327 | 99.11 63 | 98.58 198 | 97.98 290 | 88.65 315 | 99.79 194 | 98.11 91 | 97.39 347 | 98.81 285 |
|
CL-MVSNet_self_test | | | 97.44 221 | 97.22 224 | 98.08 242 | 98.57 290 | 95.78 255 | 94.30 359 | 98.79 273 | 96.58 248 | 98.60 194 | 98.19 275 | 94.74 251 | 99.64 281 | 96.41 215 | 98.84 301 | 98.82 282 |
|
KD-MVS_2432*1600 | | | 92.87 338 | 91.99 341 | 95.51 339 | 91.37 385 | 89.27 359 | 94.07 361 | 98.14 311 | 95.42 285 | 97.25 294 | 96.44 348 | 67.86 383 | 99.24 355 | 91.28 349 | 96.08 367 | 98.02 332 |
|
KD-MVS_self_test | | | 99.25 27 | 99.18 29 | 99.44 61 | 99.63 57 | 99.06 67 | 98.69 90 | 99.54 57 | 99.31 46 | 99.62 31 | 99.53 40 | 97.36 131 | 99.86 101 | 99.24 27 | 99.71 134 | 99.39 164 |
|
AUN-MVS | | | 96.24 287 | 95.45 296 | 98.60 191 | 98.70 266 | 97.22 210 | 97.38 225 | 97.65 325 | 95.95 271 | 95.53 353 | 97.96 294 | 82.11 358 | 99.79 194 | 96.31 220 | 97.44 345 | 98.80 290 |
|
ZD-MVS | | | | | | 99.01 206 | 98.84 79 | | 99.07 218 | 94.10 314 | 98.05 245 | 98.12 280 | 96.36 192 | 99.86 101 | 92.70 331 | 99.19 265 | |
|
test1172 | | | 98.76 81 | 98.49 106 | 99.57 18 | 99.18 167 | 99.37 11 | 98.39 124 | 99.31 141 | 98.43 116 | 98.90 148 | 98.88 173 | 97.49 122 | 99.86 101 | 96.43 213 | 99.37 235 | 99.48 125 |
|
SR-MVS-dyc-post | | | 98.81 72 | 98.55 96 | 99.57 18 | 99.20 157 | 99.38 8 | 98.48 116 | 99.30 151 | 98.64 102 | 98.95 138 | 98.96 150 | 97.49 122 | 99.86 101 | 96.56 201 | 99.39 231 | 99.45 139 |
|
RE-MVS-def | | | | 98.58 94 | | 99.20 157 | 99.38 8 | 98.48 116 | 99.30 151 | 98.64 102 | 98.95 138 | 98.96 150 | 97.75 95 | | 96.56 201 | 99.39 231 | 99.45 139 |
|
SED-MVS | | | 98.91 60 | 98.72 71 | 99.49 52 | 99.49 94 | 99.17 41 | 98.10 150 | 99.31 141 | 98.03 146 | 99.66 23 | 99.02 129 | 98.36 49 | 99.88 75 | 96.91 165 | 99.62 170 | 99.41 153 |
|
IU-MVS | | | | | | 99.49 94 | 99.15 50 | | 98.87 255 | 92.97 329 | 99.41 57 | | | | 96.76 182 | 99.62 170 | 99.66 43 |
|
OPU-MVS | | | | | 98.82 161 | 98.59 287 | 98.30 121 | 98.10 150 | | | | 98.52 239 | 98.18 64 | 98.75 373 | 94.62 277 | 99.48 220 | 99.41 153 |
|
test_241102_TWO | | | | | | | | | 99.30 151 | 98.03 146 | 99.26 89 | 99.02 129 | 97.51 118 | 99.88 75 | 96.91 165 | 99.60 178 | 99.66 43 |
|
test_241102_ONE | | | | | | 99.49 94 | 99.17 41 | | 99.31 141 | 97.98 148 | 99.66 23 | 98.90 164 | 98.36 49 | 99.48 327 | | | |
|
xxxxxxxxxxxxxcwj | | | 98.44 135 | 98.24 143 | 99.06 130 | 99.11 180 | 97.97 157 | 96.53 279 | 99.54 57 | 98.24 129 | 98.83 164 | 98.90 164 | 97.80 92 | 99.82 158 | 95.68 253 | 99.52 207 | 99.38 171 |
|
SF-MVS | | | 98.53 125 | 98.27 140 | 99.32 82 | 99.31 134 | 98.75 86 | 98.19 140 | 99.41 101 | 96.77 240 | 98.83 164 | 98.90 164 | 97.80 92 | 99.82 158 | 95.68 253 | 99.52 207 | 99.38 171 |
|
ETH3D cwj APD-0.16 | | | 97.55 211 | 97.00 235 | 99.19 105 | 98.51 298 | 98.64 94 | 96.85 263 | 99.13 207 | 94.19 312 | 97.65 268 | 98.40 254 | 95.78 216 | 99.81 172 | 93.37 318 | 99.16 268 | 99.12 239 |
|
cl22 | | | 95.79 296 | 95.39 300 | 96.98 303 | 96.77 370 | 92.79 330 | 94.40 357 | 98.53 293 | 94.59 301 | 97.89 253 | 98.17 276 | 82.82 354 | 99.24 355 | 96.37 216 | 99.03 286 | 98.92 270 |
|
miper_ehance_all_eth | | | 97.06 249 | 97.03 233 | 97.16 298 | 97.83 340 | 93.06 324 | 94.66 349 | 99.09 215 | 95.99 270 | 98.69 181 | 98.45 251 | 92.73 287 | 99.61 292 | 96.79 178 | 99.03 286 | 98.82 282 |
|
miper_enhance_ethall | | | 96.01 290 | 95.74 285 | 96.81 313 | 96.41 375 | 92.27 339 | 93.69 368 | 98.89 252 | 91.14 352 | 98.30 224 | 97.35 330 | 90.58 300 | 99.58 302 | 96.31 220 | 99.03 286 | 98.60 307 |
|
ZNCC-MVS | | | 98.68 97 | 98.40 122 | 99.54 30 | 99.57 64 | 99.21 29 | 98.46 118 | 99.29 158 | 97.28 210 | 98.11 239 | 98.39 256 | 98.00 78 | 99.87 92 | 96.86 175 | 99.64 164 | 99.55 88 |
|
ETH3 D test6400 | | | 96.46 280 | 95.59 292 | 99.08 122 | 98.88 233 | 98.21 131 | 96.53 279 | 99.18 190 | 88.87 365 | 97.08 299 | 97.79 301 | 93.64 274 | 99.77 212 | 88.92 363 | 99.40 230 | 99.28 206 |
|
dcpmvs_2 | | | 98.78 77 | 99.11 37 | 97.78 259 | 99.56 71 | 93.67 318 | 99.06 62 | 99.86 6 | 99.50 25 | 99.66 23 | 99.26 83 | 97.21 143 | 99.99 2 | 98.00 101 | 99.91 48 | 99.68 39 |
|
cl____ | | | 97.02 253 | 96.83 247 | 97.58 274 | 97.82 341 | 94.04 302 | 94.66 349 | 99.16 199 | 97.04 229 | 98.63 188 | 98.71 205 | 88.68 314 | 99.69 251 | 97.00 157 | 99.81 81 | 99.00 256 |
|
DIV-MVS_self_test | | | 97.02 253 | 96.84 246 | 97.58 274 | 97.82 341 | 94.03 303 | 94.66 349 | 99.16 199 | 97.04 229 | 98.63 188 | 98.71 205 | 88.69 312 | 99.69 251 | 97.00 157 | 99.81 81 | 99.01 253 |
|
eth_miper_zixun_eth | | | 97.23 237 | 97.25 221 | 97.17 296 | 98.00 332 | 92.77 331 | 94.71 346 | 99.18 190 | 97.27 211 | 98.56 202 | 98.74 201 | 91.89 295 | 99.69 251 | 97.06 155 | 99.81 81 | 99.05 245 |
|
9.14 | | | | 97.78 184 | | 99.07 191 | | 97.53 213 | 99.32 135 | 95.53 282 | 98.54 206 | 98.70 208 | 97.58 109 | 99.76 220 | 94.32 290 | 99.46 221 | |
|
testtj | | | 97.79 197 | 97.25 221 | 99.42 62 | 99.03 202 | 98.85 77 | 97.78 184 | 99.18 190 | 95.83 275 | 98.12 237 | 98.50 244 | 95.50 226 | 99.86 101 | 92.23 338 | 99.07 281 | 99.54 92 |
|
uanet_test | | | 0.00 356 | 0.00 359 | 0.00 369 | 0.00 392 | 0.00 393 | 0.00 380 | 0.00 393 | 0.00 387 | 0.00 388 | 0.00 387 | 0.00 392 | 0.00 388 | 0.00 386 | 0.00 386 | 0.00 384 |
|
ETH3D-3000-0.1 | | | 98.03 171 | 97.62 198 | 99.29 85 | 99.11 180 | 98.80 84 | 97.47 220 | 99.32 135 | 95.54 280 | 98.43 217 | 98.62 227 | 96.61 178 | 99.77 212 | 93.95 301 | 99.49 218 | 99.30 201 |
|
DCPMVS | | | 0.00 356 | 0.00 359 | 0.00 369 | 0.00 392 | 0.00 393 | 0.00 380 | 0.00 393 | 0.00 387 | 0.00 388 | 0.00 387 | 0.00 392 | 0.00 388 | 0.00 386 | 0.00 386 | 0.00 384 |
|
save fliter | | | | | | 99.11 180 | 97.97 157 | 96.53 279 | 99.02 232 | 98.24 129 | | | | | | | |
|
ET-MVSNet_ETH3D | | | 94.30 321 | 93.21 331 | 97.58 274 | 98.14 324 | 94.47 293 | 94.78 345 | 93.24 371 | 94.72 299 | 89.56 379 | 95.87 357 | 78.57 372 | 99.81 172 | 96.91 165 | 97.11 355 | 98.46 312 |
|
UniMVSNet_ETH3D | | | 99.69 2 | 99.69 4 | 99.69 3 | 99.84 18 | 99.34 17 | 99.69 4 | 99.58 34 | 99.90 2 | 99.86 8 | 99.78 8 | 99.58 3 | 99.95 17 | 99.00 40 | 99.95 19 | 99.78 17 |
|
EIA-MVS | | | 98.00 175 | 97.74 187 | 98.80 165 | 98.72 259 | 98.09 140 | 98.05 157 | 99.60 31 | 97.39 199 | 96.63 321 | 95.55 361 | 97.68 98 | 99.80 181 | 96.73 186 | 99.27 251 | 98.52 310 |
|
miper_refine_blended | | | 92.87 338 | 91.99 341 | 95.51 339 | 91.37 385 | 89.27 359 | 94.07 361 | 98.14 311 | 95.42 285 | 97.25 294 | 96.44 348 | 67.86 383 | 99.24 355 | 91.28 349 | 96.08 367 | 98.02 332 |
|
miper_lstm_enhance | | | 97.18 241 | 97.16 227 | 97.25 294 | 98.16 323 | 92.85 329 | 95.15 337 | 99.31 141 | 97.25 213 | 98.74 179 | 98.78 195 | 90.07 303 | 99.78 206 | 97.19 141 | 99.80 91 | 99.11 241 |
|
ETV-MVS | | | 98.03 171 | 97.86 181 | 98.56 199 | 98.69 271 | 98.07 146 | 97.51 216 | 99.50 67 | 98.10 143 | 97.50 282 | 95.51 362 | 98.41 46 | 99.88 75 | 96.27 223 | 99.24 256 | 97.71 348 |
|
CS-MVS | | | 99.13 37 | 99.10 39 | 99.24 99 | 99.06 195 | 99.15 50 | 99.36 18 | 99.88 4 | 99.36 42 | 98.21 229 | 98.46 250 | 98.68 31 | 99.93 31 | 99.03 38 | 99.85 64 | 98.64 306 |
|
D2MVS | | | 97.84 193 | 97.84 182 | 97.83 256 | 99.14 176 | 94.74 284 | 96.94 255 | 98.88 253 | 95.84 274 | 98.89 151 | 98.96 150 | 94.40 257 | 99.69 251 | 97.55 124 | 99.95 19 | 99.05 245 |
|
DVP-MVS |  | | 98.77 80 | 98.52 99 | 99.52 42 | 99.50 87 | 99.21 29 | 98.02 162 | 98.84 264 | 97.97 149 | 99.08 114 | 99.02 129 | 97.61 107 | 99.88 75 | 96.99 159 | 99.63 167 | 99.48 125 |
Zhenlong Yuan, Jinguo Luo, Fei Shen, Zhaoxin Li, Cong Liu, Tianlu Mao, Zhaoqi Wang: DVP-MVS: Synergize Depth-Edge and Visibility Prior for Multi-View Stereo. AAAI2025 |
test_0728_THIRD | | | | | | | | | | 98.17 138 | 99.08 114 | 99.02 129 | 97.89 85 | 99.88 75 | 97.07 153 | 99.71 134 | 99.70 36 |
|
test_0728_SECOND | | | | | 99.60 13 | 99.50 87 | 99.23 27 | 98.02 162 | 99.32 135 | | | | | 99.88 75 | 96.99 159 | 99.63 167 | 99.68 39 |
|
test0726 | | | | | | 99.50 87 | 99.21 29 | 98.17 144 | 99.35 122 | 97.97 149 | 99.26 89 | 99.06 116 | 97.61 107 | | | | |
|
SR-MVS | | | 98.71 88 | 98.43 118 | 99.57 18 | 99.18 167 | 99.35 14 | 98.36 127 | 99.29 158 | 98.29 126 | 98.88 156 | 98.85 180 | 97.53 115 | 99.87 92 | 96.14 231 | 99.31 244 | 99.48 125 |
|
DPM-MVS | | | 96.32 283 | 95.59 292 | 98.51 206 | 98.76 253 | 97.21 212 | 94.54 355 | 98.26 304 | 91.94 341 | 96.37 332 | 97.25 331 | 93.06 281 | 99.43 335 | 91.42 348 | 98.74 305 | 98.89 274 |
|
GST-MVS | | | 98.61 109 | 98.30 137 | 99.52 42 | 99.51 84 | 99.20 35 | 98.26 134 | 99.25 170 | 97.44 195 | 98.67 183 | 98.39 256 | 97.68 98 | 99.85 116 | 96.00 235 | 99.51 210 | 99.52 104 |
|
test_yl | | | 96.69 267 | 96.29 275 | 97.90 252 | 98.28 315 | 95.24 269 | 97.29 232 | 97.36 330 | 98.21 132 | 98.17 230 | 97.86 297 | 86.27 326 | 99.55 309 | 94.87 271 | 98.32 322 | 98.89 274 |
|
thisisatest0530 | | | 95.27 307 | 94.45 316 | 97.74 264 | 99.19 160 | 94.37 294 | 97.86 179 | 90.20 379 | 97.17 223 | 98.22 228 | 97.65 310 | 73.53 380 | 99.90 54 | 96.90 170 | 99.35 238 | 98.95 264 |
|
Anonymous20240529 | | | 98.93 58 | 98.87 55 | 99.12 114 | 99.19 160 | 98.22 130 | 99.01 66 | 98.99 239 | 99.25 51 | 99.54 35 | 99.37 64 | 97.04 149 | 99.80 181 | 97.89 105 | 99.52 207 | 99.35 184 |
|
Anonymous202405211 | | | 97.90 181 | 97.50 204 | 99.08 122 | 98.90 227 | 98.25 124 | 98.53 105 | 96.16 351 | 98.87 94 | 99.11 108 | 98.86 177 | 90.40 302 | 99.78 206 | 97.36 134 | 99.31 244 | 99.19 228 |
|
DCV-MVSNet | | | 96.69 267 | 96.29 275 | 97.90 252 | 98.28 315 | 95.24 269 | 97.29 232 | 97.36 330 | 98.21 132 | 98.17 230 | 97.86 297 | 86.27 326 | 99.55 309 | 94.87 271 | 98.32 322 | 98.89 274 |
|
tttt0517 | | | 95.64 300 | 94.98 309 | 97.64 270 | 99.36 127 | 93.81 314 | 98.72 86 | 90.47 378 | 98.08 145 | 98.67 183 | 98.34 263 | 73.88 379 | 99.92 39 | 97.77 115 | 99.51 210 | 99.20 223 |
|
our_test_3 | | | 97.39 224 | 97.73 189 | 96.34 320 | 98.70 266 | 89.78 358 | 94.61 352 | 98.97 241 | 96.50 249 | 99.04 123 | 98.85 180 | 95.98 207 | 99.84 133 | 97.26 139 | 99.67 156 | 99.41 153 |
|
thisisatest0515 | | | 94.12 325 | 93.16 332 | 96.97 304 | 98.60 285 | 92.90 328 | 93.77 367 | 90.61 377 | 94.10 314 | 96.91 308 | 95.87 357 | 74.99 378 | 99.80 181 | 94.52 280 | 99.12 278 | 98.20 324 |
|
ppachtmachnet_test | | | 97.50 213 | 97.74 187 | 96.78 314 | 98.70 266 | 91.23 354 | 94.55 354 | 99.05 223 | 96.36 255 | 99.21 98 | 98.79 194 | 96.39 188 | 99.78 206 | 96.74 184 | 99.82 77 | 99.34 186 |
|
SMA-MVS |  | | 98.40 140 | 98.03 168 | 99.51 46 | 99.16 171 | 99.21 29 | 98.05 157 | 99.22 178 | 94.16 313 | 98.98 132 | 99.10 113 | 97.52 117 | 99.79 194 | 96.45 211 | 99.64 164 | 99.53 100 |
Yufeng Yin; Xiaoyan Liu; Zichao Zhang: SMA-MVS: Segmentation-Guided Multi-Scale Anchor Deformation Patch Multi-View Stereo. IEEE Transactions on Circuits and Systems for Video Technology |
GSMVS | | | | | | | | | | | | | | | | | 98.81 285 |
|
DPE-MVS |  | | 98.59 114 | 98.26 141 | 99.57 18 | 99.27 141 | 99.15 50 | 97.01 251 | 99.39 106 | 97.67 169 | 99.44 52 | 98.99 141 | 97.53 115 | 99.89 64 | 95.40 263 | 99.68 150 | 99.66 43 |
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025 |
test_part2 | | | | | | 99.36 127 | 99.10 63 | | | | 99.05 121 | | | | | | |
|
test_part1 | | | 97.91 180 | 97.46 210 | 99.27 91 | 98.80 250 | 98.18 132 | 99.07 60 | 99.36 116 | 99.75 5 | 99.63 29 | 99.49 47 | 82.20 357 | 99.89 64 | 98.87 48 | 99.95 19 | 99.74 28 |
|
thres100view900 | | | 94.19 322 | 93.67 326 | 95.75 333 | 99.06 195 | 91.35 349 | 98.03 160 | 94.24 365 | 98.33 121 | 97.40 289 | 94.98 370 | 79.84 362 | 99.62 286 | 83.05 374 | 98.08 334 | 96.29 367 |
|
tfpnnormal | | | 98.90 62 | 98.90 54 | 98.91 150 | 99.67 49 | 97.82 175 | 99.00 68 | 99.44 91 | 99.45 31 | 99.51 43 | 99.24 88 | 98.20 63 | 99.86 101 | 95.92 239 | 99.69 145 | 99.04 249 |
|
tfpn200view9 | | | 94.03 326 | 93.44 328 | 95.78 332 | 98.93 219 | 91.44 347 | 97.60 205 | 94.29 363 | 97.94 151 | 97.10 297 | 94.31 376 | 79.67 364 | 99.62 286 | 83.05 374 | 98.08 334 | 96.29 367 |
|
c3_l | | | 97.36 225 | 97.37 214 | 97.31 290 | 98.09 327 | 93.25 322 | 95.01 340 | 99.16 199 | 97.05 228 | 98.77 174 | 98.72 204 | 92.88 284 | 99.64 281 | 96.93 164 | 99.76 115 | 99.05 245 |
|
CHOSEN 280x420 | | | 95.51 304 | 95.47 294 | 95.65 336 | 98.25 317 | 88.27 364 | 93.25 370 | 98.88 253 | 93.53 322 | 94.65 361 | 97.15 335 | 86.17 328 | 99.93 31 | 97.41 132 | 99.93 32 | 98.73 298 |
|
CANet | | | 97.87 186 | 97.76 185 | 98.19 234 | 97.75 343 | 95.51 261 | 96.76 269 | 99.05 223 | 97.74 164 | 96.93 305 | 98.21 273 | 95.59 222 | 99.89 64 | 97.86 110 | 99.93 32 | 99.19 228 |
|
Fast-Effi-MVS+-dtu | | | 98.27 153 | 98.09 161 | 98.81 163 | 98.43 305 | 98.11 139 | 97.61 204 | 99.50 67 | 98.64 102 | 97.39 290 | 97.52 318 | 98.12 71 | 99.95 17 | 96.90 170 | 98.71 309 | 98.38 318 |
|
Effi-MVS+-dtu | | | 98.26 155 | 97.90 178 | 99.35 74 | 98.02 330 | 99.49 5 | 98.02 162 | 99.16 199 | 98.29 126 | 97.64 269 | 97.99 289 | 96.44 186 | 99.95 17 | 96.66 192 | 98.93 298 | 98.60 307 |
|
CANet_DTU | | | 97.26 233 | 97.06 232 | 97.84 255 | 97.57 350 | 94.65 289 | 96.19 299 | 98.79 273 | 97.23 219 | 95.14 358 | 98.24 270 | 93.22 276 | 99.84 133 | 97.34 135 | 99.84 68 | 99.04 249 |
|
MVS_0304 | | | 97.64 205 | 97.35 216 | 98.52 204 | 97.87 339 | 96.69 234 | 98.59 98 | 98.05 316 | 97.44 195 | 93.74 372 | 98.85 180 | 93.69 273 | 99.88 75 | 98.11 91 | 99.81 81 | 98.98 258 |
|
MP-MVS-pluss | | | 98.57 115 | 98.23 145 | 99.60 13 | 99.69 47 | 99.35 14 | 97.16 246 | 99.38 108 | 94.87 297 | 98.97 135 | 98.99 141 | 98.01 77 | 99.88 75 | 97.29 137 | 99.70 139 | 99.58 70 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
MSP-MVS | | | 98.40 140 | 98.00 170 | 99.61 9 | 99.57 64 | 99.25 25 | 98.57 101 | 99.35 122 | 97.55 181 | 99.31 82 | 97.71 306 | 94.61 252 | 99.88 75 | 96.14 231 | 99.19 265 | 99.70 36 |
Zhenlong Yuan, Cong Liu, Fei Shen, Zhaoxin Li, Jingguo luo, Tianlu Mao and Zhaoqi Wang: MSP-MVS: Multi-granularity Segmentation Prior Guided Multi-View Stereo. AAAI2025 |
sam_mvs1 | | | | | | | | | | | | | 84.74 340 | | | | 98.81 285 |
|
sam_mvs | | | | | | | | | | | | | 84.29 346 | | | | |
|
IterMVS-SCA-FT | | | 97.85 192 | 98.18 150 | 96.87 309 | 99.27 141 | 91.16 355 | 95.53 325 | 99.25 170 | 99.10 70 | 99.41 57 | 99.35 68 | 93.10 279 | 99.96 11 | 98.65 62 | 99.94 28 | 99.49 115 |
|
TSAR-MVS + MP. | | | 98.63 106 | 98.49 106 | 99.06 130 | 99.64 55 | 97.90 166 | 98.51 110 | 98.94 242 | 96.96 232 | 99.24 94 | 98.89 172 | 97.83 88 | 99.81 172 | 96.88 172 | 99.49 218 | 99.48 125 |
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 | | | 97.86 187 | 98.17 151 | 96.92 306 | 98.98 211 | 93.91 309 | 96.45 284 | 99.17 196 | 97.85 159 | 98.41 218 | 97.14 336 | 98.47 42 | 99.92 39 | 98.02 98 | 99.05 282 | 96.92 360 |
|
OPM-MVS | | | 98.56 116 | 98.32 136 | 99.25 97 | 99.41 117 | 98.73 90 | 97.13 248 | 99.18 190 | 97.10 227 | 98.75 177 | 98.92 160 | 98.18 64 | 99.65 278 | 96.68 191 | 99.56 197 | 99.37 174 |
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS). |
ACMMP_NAP | | | 98.75 83 | 98.48 108 | 99.57 18 | 99.58 60 | 99.29 20 | 97.82 182 | 99.25 170 | 96.94 233 | 98.78 171 | 99.12 110 | 98.02 76 | 99.84 133 | 97.13 149 | 99.67 156 | 99.59 64 |
|
ambc | | | | | 98.24 231 | 98.82 246 | 95.97 249 | 98.62 94 | 99.00 238 | | 99.27 85 | 99.21 91 | 96.99 154 | 99.50 323 | 96.55 204 | 99.50 217 | 99.26 211 |
|
zzz-MVS | | | 98.79 74 | 98.52 99 | 99.61 9 | 99.67 49 | 99.36 12 | 97.33 229 | 99.20 181 | 98.83 98 | 98.89 151 | 98.90 164 | 96.98 155 | 99.92 39 | 97.16 143 | 99.70 139 | 99.56 80 |
|
MTGPA |  | | | | | | | | 99.20 181 | | | | | | | | |
|
mvs-test1 | | | 97.83 195 | 97.48 208 | 98.89 153 | 98.02 330 | 99.20 35 | 97.20 240 | 99.16 199 | 98.29 126 | 96.46 331 | 97.17 333 | 96.44 186 | 99.92 39 | 96.66 192 | 97.90 339 | 97.54 354 |
|
CS-MVS-test | | | 99.13 37 | 99.09 40 | 99.26 94 | 99.13 178 | 98.97 69 | 99.31 26 | 99.88 4 | 99.44 32 | 98.16 232 | 98.51 240 | 98.64 32 | 99.93 31 | 98.91 44 | 99.85 64 | 98.88 277 |
|
Effi-MVS+ | | | 98.02 173 | 97.82 183 | 98.62 188 | 98.53 295 | 97.19 214 | 97.33 229 | 99.68 22 | 97.30 208 | 96.68 319 | 97.46 323 | 98.56 38 | 99.80 181 | 96.63 194 | 98.20 326 | 98.86 279 |
|
xiu_mvs_v2_base | | | 97.16 243 | 97.49 205 | 96.17 325 | 98.54 293 | 92.46 335 | 95.45 329 | 98.84 264 | 97.25 213 | 97.48 284 | 96.49 345 | 98.31 54 | 99.90 54 | 96.34 219 | 98.68 312 | 96.15 371 |
|
xiu_mvs_v1_base | | | 97.86 187 | 98.17 151 | 96.92 306 | 98.98 211 | 93.91 309 | 96.45 284 | 99.17 196 | 97.85 159 | 98.41 218 | 97.14 336 | 98.47 42 | 99.92 39 | 98.02 98 | 99.05 282 | 96.92 360 |
|
new-patchmatchnet | | | 98.35 145 | 98.74 68 | 97.18 295 | 99.24 146 | 92.23 340 | 96.42 287 | 99.48 77 | 98.30 123 | 99.69 20 | 99.53 40 | 97.44 126 | 99.82 158 | 98.84 50 | 99.77 105 | 99.49 115 |
|
pmmvs6 | | | 99.67 3 | 99.70 3 | 99.60 13 | 99.90 4 | 99.27 23 | 99.53 7 | 99.76 12 | 99.64 12 | 99.84 9 | 99.83 3 | 99.50 5 | 99.87 92 | 99.36 17 | 99.92 42 | 99.64 48 |
|
pmmvs5 | | | 97.64 205 | 97.49 205 | 98.08 242 | 99.14 176 | 95.12 275 | 96.70 273 | 99.05 223 | 93.77 319 | 98.62 190 | 98.83 186 | 93.23 275 | 99.75 227 | 98.33 83 | 99.76 115 | 99.36 180 |
|
test_post1 | | | | | | | | 97.59 207 | | | | 20.48 386 | 83.07 352 | 99.66 273 | 94.16 291 | | |
|
test_post | | | | | | | | | | | | 21.25 385 | 83.86 348 | 99.70 247 | | | |
|
Fast-Effi-MVS+ | | | 97.67 203 | 97.38 213 | 98.57 195 | 98.71 262 | 97.43 199 | 97.23 236 | 99.45 88 | 94.82 298 | 96.13 335 | 96.51 344 | 98.52 41 | 99.91 49 | 96.19 227 | 98.83 302 | 98.37 320 |
|
patchmatchnet-post | | | | | | | | | | | | 98.77 197 | 84.37 343 | 99.85 116 | | | |
|
Anonymous20231211 | | | 99.27 25 | 99.27 25 | 99.26 94 | 99.29 138 | 98.18 132 | 99.49 8 | 99.51 65 | 99.70 8 | 99.80 11 | 99.68 17 | 96.84 161 | 99.83 148 | 99.21 28 | 99.91 48 | 99.77 19 |
|
pmmvs-eth3d | | | 98.47 132 | 98.34 132 | 98.86 157 | 99.30 137 | 97.76 180 | 97.16 246 | 99.28 161 | 95.54 280 | 99.42 56 | 99.19 94 | 97.27 136 | 99.63 284 | 97.89 105 | 99.97 12 | 99.20 223 |
|
GG-mvs-BLEND | | | | | 94.76 346 | 94.54 383 | 92.13 341 | 99.31 26 | 80.47 388 | | 88.73 381 | 91.01 381 | 67.59 385 | 98.16 378 | 82.30 378 | 94.53 376 | 93.98 378 |
|
xiu_mvs_v1_base_debi | | | 97.86 187 | 98.17 151 | 96.92 306 | 98.98 211 | 93.91 309 | 96.45 284 | 99.17 196 | 97.85 159 | 98.41 218 | 97.14 336 | 98.47 42 | 99.92 39 | 98.02 98 | 99.05 282 | 96.92 360 |
|
Anonymous20231206 | | | 98.21 160 | 98.21 146 | 98.20 233 | 99.51 84 | 95.43 265 | 98.13 145 | 99.32 135 | 96.16 263 | 98.93 145 | 98.82 189 | 96.00 203 | 99.83 148 | 97.32 136 | 99.73 122 | 99.36 180 |
|
MTAPA | | | 98.88 64 | 98.64 84 | 99.61 9 | 99.67 49 | 99.36 12 | 98.43 121 | 99.20 181 | 98.83 98 | 98.89 151 | 98.90 164 | 96.98 155 | 99.92 39 | 97.16 143 | 99.70 139 | 99.56 80 |
|
MTMP | | | | | | | | 97.93 170 | 91.91 375 | | | | | | | | |
|
gm-plane-assit | | | | | | 94.83 382 | 81.97 384 | | | 88.07 368 | | 94.99 369 | | 99.60 293 | 91.76 341 | | |
|
test9_res | | | | | | | | | | | | | | | 93.28 320 | 99.15 271 | 99.38 171 |
|
MVP-Stereo | | | 98.08 169 | 97.92 176 | 98.57 195 | 98.96 214 | 96.79 229 | 97.90 174 | 99.18 190 | 96.41 254 | 98.46 212 | 98.95 154 | 95.93 210 | 99.60 293 | 96.51 207 | 98.98 295 | 99.31 198 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
TEST9 | | | | | | 98.71 262 | 98.08 144 | 95.96 306 | 99.03 228 | 91.40 348 | 95.85 342 | 97.53 316 | 96.52 181 | 99.76 220 | | | |
|
train_agg | | | 97.10 245 | 96.45 270 | 99.07 125 | 98.71 262 | 98.08 144 | 95.96 306 | 99.03 228 | 91.64 343 | 95.85 342 | 97.53 316 | 96.47 184 | 99.76 220 | 93.67 309 | 99.16 268 | 99.36 180 |
|
gg-mvs-nofinetune | | | 92.37 342 | 91.20 347 | 95.85 330 | 95.80 381 | 92.38 337 | 99.31 26 | 81.84 387 | 99.75 5 | 91.83 376 | 99.74 11 | 68.29 382 | 99.02 365 | 87.15 367 | 97.12 354 | 96.16 370 |
|
SCA | | | 96.41 282 | 96.66 260 | 95.67 334 | 98.24 318 | 88.35 363 | 95.85 314 | 96.88 344 | 96.11 264 | 97.67 267 | 98.67 213 | 93.10 279 | 99.85 116 | 94.16 291 | 99.22 258 | 98.81 285 |
|
Patchmatch-test | | | 96.55 273 | 96.34 273 | 97.17 296 | 98.35 311 | 93.06 324 | 98.40 123 | 97.79 320 | 97.33 204 | 98.41 218 | 98.67 213 | 83.68 349 | 99.69 251 | 95.16 266 | 99.31 244 | 98.77 293 |
|
test_8 | | | | | | 98.67 276 | 98.01 151 | 95.91 311 | 99.02 232 | 91.64 343 | 95.79 344 | 97.50 319 | 96.47 184 | 99.76 220 | | | |
|
MS-PatchMatch | | | 97.68 202 | 97.75 186 | 97.45 285 | 98.23 320 | 93.78 315 | 97.29 232 | 98.84 264 | 96.10 265 | 98.64 187 | 98.65 218 | 96.04 200 | 99.36 342 | 96.84 176 | 99.14 272 | 99.20 223 |
|
Patchmatch-RL test | | | 97.26 233 | 97.02 234 | 97.99 250 | 99.52 82 | 95.53 260 | 96.13 300 | 99.71 15 | 97.47 187 | 99.27 85 | 99.16 102 | 84.30 345 | 99.62 286 | 97.89 105 | 99.77 105 | 98.81 285 |
|
cdsmvs_eth3d_5k | | | 24.66 351 | 32.88 354 | 0.00 369 | 0.00 392 | 0.00 393 | 0.00 380 | 99.10 213 | 0.00 387 | 0.00 388 | 97.58 314 | 99.21 10 | 0.00 388 | 0.00 386 | 0.00 386 | 0.00 384 |
|
pcd_1.5k_mvsjas | | | 8.17 354 | 10.90 357 | 0.00 369 | 0.00 392 | 0.00 393 | 0.00 380 | 0.00 393 | 0.00 387 | 0.00 388 | 0.00 387 | 98.07 72 | 0.00 388 | 0.00 386 | 0.00 386 | 0.00 384 |
|
agg_prior1 | | | 97.06 249 | 96.40 271 | 99.03 135 | 98.68 274 | 97.99 152 | 95.76 316 | 99.01 235 | 91.73 342 | 95.59 345 | 97.50 319 | 96.49 183 | 99.77 212 | 93.71 308 | 99.14 272 | 99.34 186 |
|
agg_prior2 | | | | | | | | | | | | | | | 92.50 334 | 99.16 268 | 99.37 174 |
|
agg_prior | | | | | | 98.68 274 | 97.99 152 | | 99.01 235 | | 95.59 345 | | | 99.77 212 | | | |
|
tmp_tt | | | 78.77 350 | 78.73 353 | 78.90 366 | 58.45 389 | 74.76 389 | 94.20 360 | 78.26 389 | 39.16 382 | 86.71 382 | 92.82 380 | 80.50 360 | 75.19 385 | 86.16 370 | 92.29 379 | 86.74 380 |
|
canonicalmvs | | | 98.34 146 | 98.26 141 | 98.58 193 | 98.46 302 | 97.82 175 | 98.96 72 | 99.46 85 | 99.19 59 | 97.46 285 | 95.46 364 | 98.59 36 | 99.46 331 | 98.08 95 | 98.71 309 | 98.46 312 |
|
anonymousdsp | | | 99.51 10 | 99.47 12 | 99.62 6 | 99.88 9 | 99.08 66 | 99.34 19 | 99.69 18 | 98.93 90 | 99.65 26 | 99.72 14 | 98.93 19 | 99.95 17 | 99.11 32 | 100.00 1 | 99.82 12 |
|
alignmvs | | | 97.35 226 | 96.88 243 | 98.78 170 | 98.54 293 | 98.09 140 | 97.71 193 | 97.69 324 | 99.20 55 | 97.59 273 | 95.90 356 | 88.12 320 | 99.55 309 | 98.18 89 | 98.96 296 | 98.70 301 |
|
nrg030 | | | 99.40 18 | 99.35 18 | 99.54 30 | 99.58 60 | 99.13 58 | 98.98 71 | 99.48 77 | 99.68 9 | 99.46 48 | 99.26 83 | 98.62 34 | 99.73 235 | 99.17 31 | 99.92 42 | 99.76 23 |
|
v144192 | | | 98.54 123 | 98.57 95 | 98.45 212 | 99.21 153 | 95.98 248 | 97.63 201 | 99.36 116 | 97.15 226 | 99.32 80 | 99.18 96 | 95.84 215 | 99.84 133 | 99.50 12 | 99.91 48 | 99.54 92 |
|
FIs | | | 99.14 35 | 99.09 40 | 99.29 85 | 99.70 45 | 98.28 122 | 99.13 53 | 99.52 64 | 99.48 27 | 99.24 94 | 99.41 61 | 96.79 167 | 99.82 158 | 98.69 60 | 99.88 59 | 99.76 23 |
|
v1921920 | | | 98.54 123 | 98.60 92 | 98.38 219 | 99.20 157 | 95.76 256 | 97.56 210 | 99.36 116 | 97.23 219 | 99.38 64 | 99.17 100 | 96.02 201 | 99.84 133 | 99.57 8 | 99.90 55 | 99.54 92 |
|
UA-Net | | | 99.47 11 | 99.40 15 | 99.70 2 | 99.49 94 | 99.29 20 | 99.80 3 | 99.72 14 | 99.82 3 | 99.04 123 | 99.81 5 | 98.05 75 | 99.96 11 | 98.85 49 | 99.99 5 | 99.86 9 |
|
v1192 | | | 98.60 111 | 98.66 82 | 98.41 216 | 99.27 141 | 95.88 251 | 97.52 214 | 99.36 116 | 97.41 197 | 99.33 74 | 99.20 93 | 96.37 191 | 99.82 158 | 99.57 8 | 99.92 42 | 99.55 88 |
|
FC-MVSNet-test | | | 99.27 25 | 99.25 26 | 99.34 77 | 99.77 25 | 98.37 116 | 99.30 31 | 99.57 41 | 99.61 19 | 99.40 60 | 99.50 44 | 97.12 145 | 99.85 116 | 99.02 39 | 99.94 28 | 99.80 15 |
|
v1144 | | | 98.60 111 | 98.66 82 | 98.41 216 | 99.36 127 | 95.90 250 | 97.58 208 | 99.34 128 | 97.51 183 | 99.27 85 | 99.15 106 | 96.34 193 | 99.80 181 | 99.47 14 | 99.93 32 | 99.51 107 |
|
sosnet-low-res | | | 0.00 356 | 0.00 359 | 0.00 369 | 0.00 392 | 0.00 393 | 0.00 380 | 0.00 393 | 0.00 387 | 0.00 388 | 0.00 387 | 0.00 392 | 0.00 388 | 0.00 386 | 0.00 386 | 0.00 384 |
|
HFP-MVS | | | 98.71 88 | 98.44 116 | 99.51 46 | 99.49 94 | 99.16 45 | 98.52 106 | 99.31 141 | 97.47 187 | 98.58 198 | 98.50 244 | 97.97 82 | 99.85 116 | 96.57 198 | 99.59 182 | 99.53 100 |
|
v148 | | | 98.45 134 | 98.60 92 | 98.00 249 | 99.44 110 | 94.98 278 | 97.44 223 | 99.06 219 | 98.30 123 | 99.32 80 | 98.97 147 | 96.65 176 | 99.62 286 | 98.37 79 | 99.85 64 | 99.39 164 |
|
sosnet | | | 0.00 356 | 0.00 359 | 0.00 369 | 0.00 392 | 0.00 393 | 0.00 380 | 0.00 393 | 0.00 387 | 0.00 388 | 0.00 387 | 0.00 392 | 0.00 388 | 0.00 386 | 0.00 386 | 0.00 384 |
|
uncertanet | | | 0.00 356 | 0.00 359 | 0.00 369 | 0.00 392 | 0.00 393 | 0.00 380 | 0.00 393 | 0.00 387 | 0.00 388 | 0.00 387 | 0.00 392 | 0.00 388 | 0.00 386 | 0.00 386 | 0.00 384 |
|
AllTest | | | 98.44 135 | 98.20 147 | 99.16 109 | 99.50 87 | 98.55 103 | 98.25 135 | 99.58 34 | 96.80 238 | 98.88 156 | 99.06 116 | 97.65 101 | 99.57 303 | 94.45 283 | 99.61 176 | 99.37 174 |
|
TestCases | | | | | 99.16 109 | 99.50 87 | 98.55 103 | | 99.58 34 | 96.80 238 | 98.88 156 | 99.06 116 | 97.65 101 | 99.57 303 | 94.45 283 | 99.61 176 | 99.37 174 |
|
v7n | | | 99.53 8 | 99.57 8 | 99.41 65 | 99.88 9 | 98.54 106 | 99.45 10 | 99.61 30 | 99.66 11 | 99.68 22 | 99.66 20 | 98.44 45 | 99.95 17 | 99.73 4 | 99.96 15 | 99.75 26 |
|
region2R | | | 98.69 93 | 98.40 122 | 99.54 30 | 99.53 80 | 99.17 41 | 98.52 106 | 99.31 141 | 97.46 192 | 98.44 214 | 98.51 240 | 97.83 88 | 99.88 75 | 96.46 210 | 99.58 188 | 99.58 70 |
|
iter_conf05 | | | 96.54 274 | 96.07 279 | 97.92 251 | 97.90 337 | 94.50 292 | 97.87 178 | 99.14 206 | 97.73 165 | 98.89 151 | 98.95 154 | 75.75 377 | 99.87 92 | 98.50 71 | 99.92 42 | 99.40 162 |
|
RRT_MVS | | | 99.09 40 | 98.94 51 | 99.55 26 | 99.87 12 | 98.82 82 | 99.48 9 | 98.16 310 | 99.49 26 | 99.59 32 | 99.65 22 | 94.79 249 | 99.95 17 | 99.45 15 | 99.96 15 | 99.88 5 |
|
PS-MVSNAJss | | | 99.46 12 | 99.49 10 | 99.35 74 | 99.90 4 | 98.15 136 | 99.20 44 | 99.65 26 | 99.48 27 | 99.92 4 | 99.71 15 | 98.07 72 | 99.96 11 | 99.53 11 | 100.00 1 | 99.93 3 |
|
PS-MVSNAJ | | | 97.08 248 | 97.39 212 | 96.16 327 | 98.56 291 | 92.46 335 | 95.24 334 | 98.85 263 | 97.25 213 | 97.49 283 | 95.99 354 | 98.07 72 | 99.90 54 | 96.37 216 | 98.67 313 | 96.12 372 |
|
jajsoiax | | | 99.58 6 | 99.61 7 | 99.48 55 | 99.87 12 | 98.61 98 | 99.28 36 | 99.66 25 | 99.09 73 | 99.89 7 | 99.68 17 | 99.53 4 | 99.97 4 | 99.50 12 | 99.99 5 | 99.87 7 |
|
mvs_tets | | | 99.63 5 | 99.67 5 | 99.49 52 | 99.88 9 | 98.61 98 | 99.34 19 | 99.71 15 | 99.27 50 | 99.90 5 | 99.74 11 | 99.68 2 | 99.97 4 | 99.55 10 | 99.99 5 | 99.88 5 |
|
#test# | | | 98.50 129 | 98.16 154 | 99.51 46 | 99.49 94 | 99.16 45 | 98.03 160 | 99.31 141 | 96.30 259 | 98.58 198 | 98.50 244 | 97.97 82 | 99.85 116 | 95.68 253 | 99.59 182 | 99.53 100 |
|
EI-MVSNet-UG-set | | | 98.69 93 | 98.71 73 | 98.62 188 | 99.10 184 | 96.37 239 | 97.23 236 | 98.87 255 | 99.20 55 | 99.19 100 | 98.99 141 | 97.30 133 | 99.85 116 | 98.77 55 | 99.79 96 | 99.65 47 |
|
EI-MVSNet-Vis-set | | | 98.68 97 | 98.70 76 | 98.63 186 | 99.09 187 | 96.40 238 | 97.23 236 | 98.86 260 | 99.20 55 | 99.18 104 | 98.97 147 | 97.29 135 | 99.85 116 | 98.72 57 | 99.78 101 | 99.64 48 |
|
Regformer-3 | | | 98.61 109 | 98.61 90 | 98.63 186 | 99.02 204 | 96.53 236 | 97.17 244 | 98.84 264 | 99.13 62 | 99.10 111 | 98.85 180 | 97.24 140 | 99.79 194 | 98.41 78 | 99.70 139 | 99.57 75 |
|
Regformer-4 | | | 98.73 86 | 98.68 79 | 98.89 153 | 99.02 204 | 97.22 210 | 97.17 244 | 99.06 219 | 99.21 52 | 99.17 105 | 98.85 180 | 97.45 125 | 99.86 101 | 98.48 73 | 99.70 139 | 99.60 58 |
|
Regformer-1 | | | 98.55 120 | 98.44 116 | 98.87 155 | 98.85 238 | 97.29 204 | 96.91 260 | 98.99 239 | 98.97 85 | 98.99 130 | 98.64 221 | 97.26 139 | 99.81 172 | 97.79 113 | 99.57 192 | 99.51 107 |
|
Regformer-2 | | | 98.60 111 | 98.46 112 | 99.02 138 | 98.85 238 | 97.71 185 | 96.91 260 | 99.09 215 | 98.98 84 | 99.01 127 | 98.64 221 | 97.37 130 | 99.84 133 | 97.75 120 | 99.57 192 | 99.52 104 |
|
HPM-MVS++ |  | | 98.10 167 | 97.64 196 | 99.48 55 | 99.09 187 | 99.13 58 | 97.52 214 | 98.75 279 | 97.46 192 | 96.90 311 | 97.83 300 | 96.01 202 | 99.84 133 | 95.82 247 | 99.35 238 | 99.46 135 |
|
test_prior4 | | | | | | | 97.97 157 | 95.86 312 | | | | | | | | | |
|
XVS | | | 98.72 87 | 98.45 114 | 99.53 37 | 99.46 105 | 99.21 29 | 98.65 91 | 99.34 128 | 98.62 106 | 97.54 278 | 98.63 225 | 97.50 119 | 99.83 148 | 96.79 178 | 99.53 204 | 99.56 80 |
|
v1240 | | | 98.55 120 | 98.62 87 | 98.32 223 | 99.22 151 | 95.58 258 | 97.51 216 | 99.45 88 | 97.16 224 | 99.45 51 | 99.24 88 | 96.12 198 | 99.85 116 | 99.60 6 | 99.88 59 | 99.55 88 |
|
test_prior3 | | | 97.48 217 | 97.00 235 | 98.95 144 | 98.69 271 | 97.95 162 | 95.74 318 | 99.03 228 | 96.48 251 | 96.11 336 | 97.63 312 | 95.92 211 | 99.59 297 | 94.16 291 | 99.20 261 | 99.30 201 |
|
pm-mvs1 | | | 99.44 13 | 99.48 11 | 99.33 80 | 99.80 22 | 98.63 95 | 99.29 32 | 99.63 27 | 99.30 48 | 99.65 26 | 99.60 29 | 99.16 14 | 99.82 158 | 99.07 34 | 99.83 74 | 99.56 80 |
|
test_prior2 | | | | | | | | 95.74 318 | | 96.48 251 | 96.11 336 | 97.63 312 | 95.92 211 | | 94.16 291 | 99.20 261 | |
|
X-MVStestdata | | | 94.32 319 | 92.59 337 | 99.53 37 | 99.46 105 | 99.21 29 | 98.65 91 | 99.34 128 | 98.62 106 | 97.54 278 | 45.85 382 | 97.50 119 | 99.83 148 | 96.79 178 | 99.53 204 | 99.56 80 |
|
test_prior | | | | | 98.95 144 | 98.69 271 | 97.95 162 | | 99.03 228 | | | | | 99.59 297 | | | 99.30 201 |
|
旧先验2 | | | | | | | | 95.76 316 | | 88.56 367 | 97.52 280 | | | 99.66 273 | 94.48 281 | | |
|
新几何2 | | | | | | | | 95.93 309 | | | | | | | | | |
|
新几何1 | | | | | 98.91 150 | 98.94 217 | 97.76 180 | | 98.76 276 | 87.58 370 | 96.75 318 | 98.10 282 | 94.80 247 | 99.78 206 | 92.73 330 | 99.00 292 | 99.20 223 |
|
旧先验1 | | | | | | 98.82 246 | 97.45 198 | | 98.76 276 | | | 98.34 263 | 95.50 226 | | | 99.01 291 | 99.23 218 |
|
无先验 | | | | | | | | 95.74 318 | 98.74 281 | 89.38 362 | | | | 99.73 235 | 92.38 336 | | 99.22 222 |
|
原ACMM2 | | | | | | | | 95.53 325 | | | | | | | | | |
|
原ACMM1 | | | | | 98.35 221 | 98.90 227 | 96.25 242 | | 98.83 269 | 92.48 336 | 96.07 339 | 98.10 282 | 95.39 230 | 99.71 244 | 92.61 333 | 98.99 293 | 99.08 242 |
|
test222 | | | | | | 98.92 223 | 96.93 226 | 95.54 324 | 98.78 275 | 85.72 373 | 96.86 314 | 98.11 281 | 94.43 255 | | | 99.10 280 | 99.23 218 |
|
testdata2 | | | | | | | | | | | | | | 99.79 194 | 92.80 328 | | |
|
segment_acmp | | | | | | | | | | | | | 97.02 152 | | | | |
|
testdata | | | | | 98.09 239 | 98.93 219 | 95.40 266 | | 98.80 272 | 90.08 359 | 97.45 286 | 98.37 259 | 95.26 232 | 99.70 247 | 93.58 312 | 98.95 297 | 99.17 234 |
|
testdata1 | | | | | | | | 95.44 330 | | 96.32 257 | | | | | | | |
|
v8 | | | 99.01 46 | 99.16 31 | 98.57 195 | 99.47 104 | 96.31 241 | 98.90 75 | 99.47 83 | 99.03 79 | 99.52 40 | 99.57 32 | 96.93 157 | 99.81 172 | 99.60 6 | 99.98 9 | 99.60 58 |
|
1314 | | | 95.74 297 | 95.60 291 | 96.17 325 | 97.53 353 | 92.75 332 | 98.07 153 | 98.31 303 | 91.22 350 | 94.25 364 | 96.68 342 | 95.53 223 | 99.03 364 | 91.64 344 | 97.18 353 | 96.74 364 |
|
1121 | | | 96.73 266 | 96.00 280 | 98.91 150 | 98.95 216 | 97.76 180 | 98.07 153 | 98.73 282 | 87.65 369 | 96.54 324 | 98.13 277 | 94.52 254 | 99.73 235 | 92.38 336 | 99.02 289 | 99.24 215 |
|
LFMVS | | | 97.20 239 | 96.72 254 | 98.64 183 | 98.72 259 | 96.95 224 | 98.93 74 | 94.14 367 | 99.74 7 | 98.78 171 | 99.01 138 | 84.45 342 | 99.73 235 | 97.44 130 | 99.27 251 | 99.25 212 |
|
VDD-MVS | | | 98.56 116 | 98.39 125 | 99.07 125 | 99.13 178 | 98.07 146 | 98.59 98 | 97.01 338 | 99.59 20 | 99.11 108 | 99.27 81 | 94.82 244 | 99.79 194 | 98.34 81 | 99.63 167 | 99.34 186 |
|
VDDNet | | | 98.21 160 | 97.95 173 | 99.01 139 | 99.58 60 | 97.74 183 | 99.01 66 | 97.29 334 | 99.67 10 | 98.97 135 | 99.50 44 | 90.45 301 | 99.80 181 | 97.88 108 | 99.20 261 | 99.48 125 |
|
v10 | | | 98.97 53 | 99.11 37 | 98.55 200 | 99.44 110 | 96.21 243 | 98.90 75 | 99.55 52 | 98.73 100 | 99.48 45 | 99.60 29 | 96.63 177 | 99.83 148 | 99.70 5 | 99.99 5 | 99.61 57 |
|
VPNet | | | 98.87 65 | 98.83 60 | 99.01 139 | 99.70 45 | 97.62 191 | 98.43 121 | 99.35 122 | 99.47 29 | 99.28 83 | 99.05 123 | 96.72 173 | 99.82 158 | 98.09 94 | 99.36 236 | 99.59 64 |
|
MVS | | | 93.19 336 | 92.09 340 | 96.50 318 | 96.91 366 | 94.03 303 | 98.07 153 | 98.06 315 | 68.01 380 | 94.56 363 | 96.48 346 | 95.96 209 | 99.30 350 | 83.84 373 | 96.89 358 | 96.17 369 |
|
v2v482 | | | 98.56 116 | 98.62 87 | 98.37 220 | 99.42 115 | 95.81 254 | 97.58 208 | 99.16 199 | 97.90 155 | 99.28 83 | 99.01 138 | 95.98 207 | 99.79 194 | 99.33 18 | 99.90 55 | 99.51 107 |
|
V42 | | | 98.78 77 | 98.78 65 | 98.76 173 | 99.44 110 | 97.04 220 | 98.27 133 | 99.19 186 | 97.87 157 | 99.25 93 | 99.16 102 | 96.84 161 | 99.78 206 | 99.21 28 | 99.84 68 | 99.46 135 |
|
SD-MVS | | | 98.40 140 | 98.68 79 | 97.54 279 | 98.96 214 | 97.99 152 | 97.88 175 | 99.36 116 | 98.20 135 | 99.63 29 | 99.04 125 | 98.76 25 | 95.33 383 | 96.56 201 | 99.74 119 | 99.31 198 |
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 | | | 95.86 294 | 95.32 302 | 97.49 283 | 98.60 285 | 94.15 300 | 93.83 366 | 97.93 318 | 95.49 283 | 96.68 319 | 97.42 325 | 83.21 350 | 99.30 350 | 96.22 225 | 98.55 319 | 99.01 253 |
|
MSLP-MVS++ | | | 98.02 173 | 98.14 158 | 97.64 270 | 98.58 288 | 95.19 272 | 97.48 218 | 99.23 177 | 97.47 187 | 97.90 252 | 98.62 227 | 97.04 149 | 98.81 372 | 97.55 124 | 99.41 228 | 98.94 268 |
|
APDe-MVS | | | 98.99 48 | 98.79 64 | 99.60 13 | 99.21 153 | 99.15 50 | 98.87 77 | 99.48 77 | 97.57 178 | 99.35 71 | 99.24 88 | 97.83 88 | 99.89 64 | 97.88 108 | 99.70 139 | 99.75 26 |
|
APD-MVS_3200maxsize | | | 98.84 69 | 98.61 90 | 99.53 37 | 99.19 160 | 99.27 23 | 98.49 113 | 99.33 133 | 98.64 102 | 99.03 126 | 98.98 145 | 97.89 85 | 99.85 116 | 96.54 205 | 99.42 227 | 99.46 135 |
|
ADS-MVSNet2 | | | 95.43 305 | 94.98 309 | 96.76 315 | 98.14 324 | 91.74 343 | 97.92 171 | 97.76 321 | 90.23 355 | 96.51 327 | 98.91 161 | 85.61 333 | 99.85 116 | 92.88 324 | 96.90 356 | 98.69 302 |
|
EI-MVSNet | | | 98.40 140 | 98.51 101 | 98.04 247 | 99.10 184 | 94.73 285 | 97.20 240 | 98.87 255 | 98.97 85 | 99.06 116 | 99.02 129 | 96.00 203 | 99.80 181 | 98.58 64 | 99.82 77 | 99.60 58 |
|
Regformer | | | 0.00 356 | 0.00 359 | 0.00 369 | 0.00 392 | 0.00 393 | 0.00 380 | 0.00 393 | 0.00 387 | 0.00 388 | 0.00 387 | 0.00 392 | 0.00 388 | 0.00 386 | 0.00 386 | 0.00 384 |
|
CVMVSNet | | | 96.25 286 | 97.21 225 | 93.38 360 | 99.10 184 | 80.56 386 | 97.20 240 | 98.19 309 | 96.94 233 | 99.00 129 | 99.02 129 | 89.50 308 | 99.80 181 | 96.36 218 | 99.59 182 | 99.78 17 |
|
pmmvs4 | | | 97.58 210 | 97.28 220 | 98.51 206 | 98.84 241 | 96.93 226 | 95.40 331 | 98.52 294 | 93.60 321 | 98.61 192 | 98.65 218 | 95.10 237 | 99.60 293 | 96.97 162 | 99.79 96 | 98.99 257 |
|
EU-MVSNet | | | 97.66 204 | 98.50 103 | 95.13 344 | 99.63 57 | 85.84 372 | 98.35 128 | 98.21 306 | 98.23 131 | 99.54 35 | 99.46 51 | 95.02 238 | 99.68 260 | 98.24 85 | 99.87 62 | 99.87 7 |
|
VNet | | | 98.42 137 | 98.30 137 | 98.79 167 | 98.79 252 | 97.29 204 | 98.23 136 | 98.66 286 | 99.31 46 | 98.85 160 | 98.80 192 | 94.80 247 | 99.78 206 | 98.13 90 | 99.13 275 | 99.31 198 |
|
test-LLR | | | 93.90 328 | 93.85 322 | 94.04 351 | 96.53 372 | 84.62 377 | 94.05 363 | 92.39 373 | 96.17 261 | 94.12 366 | 95.07 366 | 82.30 355 | 99.67 263 | 95.87 243 | 98.18 327 | 97.82 339 |
|
TESTMET0.1,1 | | | 92.19 345 | 91.77 345 | 93.46 358 | 96.48 374 | 82.80 382 | 94.05 363 | 91.52 376 | 94.45 306 | 94.00 369 | 94.88 372 | 66.65 386 | 99.56 306 | 95.78 248 | 98.11 332 | 98.02 332 |
|
test-mter | | | 92.33 343 | 91.76 346 | 94.04 351 | 96.53 372 | 84.62 377 | 94.05 363 | 92.39 373 | 94.00 317 | 94.12 366 | 95.07 366 | 65.63 389 | 99.67 263 | 95.87 243 | 98.18 327 | 97.82 339 |
|
VPA-MVSNet | | | 99.30 24 | 99.30 24 | 99.28 88 | 99.49 94 | 98.36 119 | 99.00 68 | 99.45 88 | 99.63 14 | 99.52 40 | 99.44 56 | 98.25 55 | 99.88 75 | 99.09 33 | 99.84 68 | 99.62 52 |
|
ACMMPR | | | 98.70 91 | 98.42 120 | 99.54 30 | 99.52 82 | 99.14 55 | 98.52 106 | 99.31 141 | 97.47 187 | 98.56 202 | 98.54 236 | 97.75 95 | 99.88 75 | 96.57 198 | 99.59 182 | 99.58 70 |
|
testgi | | | 98.32 147 | 98.39 125 | 98.13 238 | 99.57 64 | 95.54 259 | 97.78 184 | 99.49 75 | 97.37 201 | 99.19 100 | 97.65 310 | 98.96 17 | 99.49 324 | 96.50 208 | 98.99 293 | 99.34 186 |
|
test20.03 | | | 98.78 77 | 98.77 67 | 98.78 170 | 99.46 105 | 97.20 213 | 97.78 184 | 99.24 175 | 99.04 78 | 99.41 57 | 98.90 164 | 97.65 101 | 99.76 220 | 97.70 121 | 99.79 96 | 99.39 164 |
|
thres600view7 | | | 94.45 317 | 93.83 323 | 96.29 321 | 99.06 195 | 91.53 345 | 97.99 166 | 94.24 365 | 98.34 120 | 97.44 287 | 95.01 368 | 79.84 362 | 99.67 263 | 84.33 372 | 98.23 324 | 97.66 349 |
|
ADS-MVSNet | | | 95.24 308 | 94.93 312 | 96.18 324 | 98.14 324 | 90.10 357 | 97.92 171 | 97.32 333 | 90.23 355 | 96.51 327 | 98.91 161 | 85.61 333 | 99.74 231 | 92.88 324 | 96.90 356 | 98.69 302 |
|
MP-MVS |  | | 98.46 133 | 98.09 161 | 99.54 30 | 99.57 64 | 99.22 28 | 98.50 112 | 99.19 186 | 97.61 175 | 97.58 274 | 98.66 216 | 97.40 128 | 99.88 75 | 94.72 276 | 99.60 178 | 99.54 92 |
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
testmvs | | | 17.12 352 | 20.53 355 | 6.87 368 | 12.05 390 | 4.20 392 | 93.62 369 | 6.73 391 | 4.62 386 | 10.41 386 | 24.33 383 | 8.28 391 | 3.56 387 | 9.69 385 | 15.07 384 | 12.86 383 |
|
thres400 | | | 94.14 324 | 93.44 328 | 96.24 323 | 98.93 219 | 91.44 347 | 97.60 205 | 94.29 363 | 97.94 151 | 97.10 297 | 94.31 376 | 79.67 364 | 99.62 286 | 83.05 374 | 98.08 334 | 97.66 349 |
|
test123 | | | 17.04 353 | 20.11 356 | 7.82 367 | 10.25 391 | 4.91 391 | 94.80 344 | 4.47 392 | 4.93 385 | 10.00 387 | 24.28 384 | 9.69 390 | 3.64 386 | 10.14 384 | 12.43 385 | 14.92 382 |
|
thres200 | | | 93.72 331 | 93.14 333 | 95.46 341 | 98.66 281 | 91.29 351 | 96.61 277 | 94.63 361 | 97.39 199 | 96.83 315 | 93.71 378 | 79.88 361 | 99.56 306 | 82.40 377 | 98.13 331 | 95.54 376 |
|
test0.0.03 1 | | | 94.51 316 | 93.69 325 | 96.99 302 | 96.05 378 | 93.61 320 | 94.97 341 | 93.49 368 | 96.17 261 | 97.57 276 | 94.88 372 | 82.30 355 | 99.01 367 | 93.60 311 | 94.17 377 | 98.37 320 |
|
pmmvs3 | | | 95.03 311 | 94.40 317 | 96.93 305 | 97.70 347 | 92.53 334 | 95.08 338 | 97.71 323 | 88.57 366 | 97.71 264 | 98.08 285 | 79.39 366 | 99.82 158 | 96.19 227 | 99.11 279 | 98.43 316 |
|
EMVS | | | 93.83 329 | 94.02 321 | 93.23 361 | 96.83 369 | 84.96 375 | 89.77 378 | 96.32 350 | 97.92 153 | 97.43 288 | 96.36 351 | 86.17 328 | 98.93 369 | 87.68 366 | 97.73 341 | 95.81 374 |
|
E-PMN | | | 94.17 323 | 94.37 318 | 93.58 357 | 96.86 367 | 85.71 374 | 90.11 377 | 97.07 337 | 98.17 138 | 97.82 259 | 97.19 332 | 84.62 341 | 98.94 368 | 89.77 360 | 97.68 342 | 96.09 373 |
|
PGM-MVS | | | 98.66 101 | 98.37 128 | 99.55 26 | 99.53 80 | 99.18 40 | 98.23 136 | 99.49 75 | 97.01 231 | 98.69 181 | 98.88 173 | 98.00 78 | 99.89 64 | 95.87 243 | 99.59 182 | 99.58 70 |
|
LCM-MVSNet-Re | | | 98.64 104 | 98.48 108 | 99.11 116 | 98.85 238 | 98.51 108 | 98.49 113 | 99.83 8 | 98.37 118 | 99.69 20 | 99.46 51 | 98.21 62 | 99.92 39 | 94.13 296 | 99.30 247 | 98.91 273 |
|
LCM-MVSNet | | | 99.93 1 | 99.92 1 | 99.94 1 | 99.99 1 | 99.97 1 | 99.90 1 | 99.89 3 | 99.98 1 | 99.99 1 | 99.96 1 | 99.77 1 | 100.00 1 | 99.81 3 | 100.00 1 | 99.85 10 |
|
MCST-MVS | | | 98.00 175 | 97.63 197 | 99.10 118 | 99.24 146 | 98.17 135 | 96.89 262 | 98.73 282 | 95.66 278 | 97.92 250 | 97.70 308 | 97.17 144 | 99.66 273 | 96.18 229 | 99.23 257 | 99.47 133 |
|
mvs_anonymous | | | 97.83 195 | 98.16 154 | 96.87 309 | 98.18 322 | 91.89 342 | 97.31 231 | 98.90 250 | 97.37 201 | 98.83 164 | 99.46 51 | 96.28 194 | 99.79 194 | 98.90 45 | 98.16 329 | 98.95 264 |
|
MVS_Test | | | 98.18 163 | 98.36 129 | 97.67 266 | 98.48 300 | 94.73 285 | 98.18 141 | 99.02 232 | 97.69 168 | 98.04 246 | 99.11 111 | 97.22 142 | 99.56 306 | 98.57 66 | 98.90 300 | 98.71 299 |
|
MDA-MVSNet-bldmvs | | | 97.94 179 | 97.91 177 | 98.06 244 | 99.44 110 | 94.96 279 | 96.63 276 | 99.15 205 | 98.35 119 | 98.83 164 | 99.11 111 | 94.31 259 | 99.85 116 | 96.60 195 | 98.72 307 | 99.37 174 |
|
CDPH-MVS | | | 97.26 233 | 96.66 260 | 99.07 125 | 99.00 207 | 98.15 136 | 96.03 302 | 99.01 235 | 91.21 351 | 97.79 260 | 97.85 299 | 96.89 159 | 99.69 251 | 92.75 329 | 99.38 234 | 99.39 164 |
|
test12 | | | | | 98.93 147 | 98.58 288 | 97.83 172 | | 98.66 286 | | 96.53 325 | | 95.51 225 | 99.69 251 | | 99.13 275 | 99.27 208 |
|
casdiffmvs | | | 98.95 56 | 99.00 47 | 98.81 163 | 99.38 120 | 97.33 202 | 97.82 182 | 99.57 41 | 99.17 60 | 99.35 71 | 99.17 100 | 98.35 52 | 99.69 251 | 98.46 74 | 99.73 122 | 99.41 153 |
|
diffmvs | | | 98.22 159 | 98.24 143 | 98.17 235 | 99.00 207 | 95.44 264 | 96.38 289 | 99.58 34 | 97.79 162 | 98.53 207 | 98.50 244 | 96.76 170 | 99.74 231 | 97.95 104 | 99.64 164 | 99.34 186 |
|
baseline2 | | | 93.73 330 | 92.83 336 | 96.42 319 | 97.70 347 | 91.28 352 | 96.84 265 | 89.77 380 | 93.96 318 | 92.44 374 | 95.93 355 | 79.14 368 | 99.77 212 | 92.94 322 | 96.76 360 | 98.21 323 |
|
baseline1 | | | 95.96 292 | 95.44 297 | 97.52 281 | 98.51 298 | 93.99 306 | 98.39 124 | 96.09 353 | 98.21 132 | 98.40 222 | 97.76 304 | 86.88 322 | 99.63 284 | 95.42 262 | 89.27 381 | 98.95 264 |
|
YYNet1 | | | 97.60 208 | 97.67 191 | 97.39 289 | 99.04 199 | 93.04 327 | 95.27 332 | 98.38 301 | 97.25 213 | 98.92 146 | 98.95 154 | 95.48 228 | 99.73 235 | 96.99 159 | 98.74 305 | 99.41 153 |
|
PMMVS2 | | | 98.07 170 | 98.08 164 | 98.04 247 | 99.41 117 | 94.59 291 | 94.59 353 | 99.40 103 | 97.50 184 | 98.82 168 | 98.83 186 | 96.83 163 | 99.84 133 | 97.50 129 | 99.81 81 | 99.71 31 |
|
MDA-MVSNet_test_wron | | | 97.60 208 | 97.66 194 | 97.41 288 | 99.04 199 | 93.09 323 | 95.27 332 | 98.42 298 | 97.26 212 | 98.88 156 | 98.95 154 | 95.43 229 | 99.73 235 | 97.02 156 | 98.72 307 | 99.41 153 |
|
tpmvs | | | 95.02 312 | 95.25 303 | 94.33 349 | 96.39 376 | 85.87 371 | 98.08 152 | 96.83 345 | 95.46 284 | 95.51 354 | 98.69 209 | 85.91 331 | 99.53 314 | 94.16 291 | 96.23 365 | 97.58 352 |
|
PM-MVS | | | 98.82 70 | 98.72 71 | 99.12 114 | 99.64 55 | 98.54 106 | 97.98 167 | 99.68 22 | 97.62 173 | 99.34 73 | 99.18 96 | 97.54 113 | 99.77 212 | 97.79 113 | 99.74 119 | 99.04 249 |
|
HQP_MVS | | | 97.99 178 | 97.67 191 | 98.93 147 | 99.19 160 | 97.65 188 | 97.77 187 | 99.27 164 | 98.20 135 | 97.79 260 | 97.98 290 | 94.90 240 | 99.70 247 | 94.42 285 | 99.51 210 | 99.45 139 |
|
plane_prior7 | | | | | | 99.19 160 | 97.87 168 | | | | | | | | | | |
|
plane_prior6 | | | | | | 98.99 210 | 97.70 186 | | | | | | 94.90 240 | | | | |
|
plane_prior5 | | | | | | | | | 99.27 164 | | | | | 99.70 247 | 94.42 285 | 99.51 210 | 99.45 139 |
|
plane_prior4 | | | | | | | | | | | | 97.98 290 | | | | | |
|
plane_prior3 | | | | | | | 97.78 179 | | | 97.41 197 | 97.79 260 | | | | | | |
|
plane_prior2 | | | | | | | | 97.77 187 | | 98.20 135 | | | | | | | |
|
plane_prior1 | | | | | | 99.05 198 | | | | | | | | | | | |
|
plane_prior | | | | | | | 97.65 188 | 97.07 249 | | 96.72 242 | | | | | | 99.36 236 | |
|
PS-CasMVS | | | 99.40 18 | 99.33 21 | 99.62 6 | 99.71 39 | 99.10 63 | 99.29 32 | 99.53 61 | 99.53 24 | 99.46 48 | 99.41 61 | 98.23 57 | 99.95 17 | 98.89 47 | 99.95 19 | 99.81 14 |
|
UniMVSNet_NR-MVSNet | | | 98.86 68 | 98.68 79 | 99.40 67 | 99.17 169 | 98.74 87 | 97.68 196 | 99.40 103 | 99.14 61 | 99.06 116 | 98.59 232 | 96.71 174 | 99.93 31 | 98.57 66 | 99.77 105 | 99.53 100 |
|
PEN-MVS | | | 99.41 17 | 99.34 20 | 99.62 6 | 99.73 31 | 99.14 55 | 99.29 32 | 99.54 57 | 99.62 17 | 99.56 33 | 99.42 58 | 98.16 68 | 99.96 11 | 98.78 52 | 99.93 32 | 99.77 19 |
|
TransMVSNet (Re) | | | 99.44 13 | 99.47 12 | 99.36 69 | 99.80 22 | 98.58 101 | 99.27 38 | 99.57 41 | 99.39 37 | 99.75 15 | 99.62 25 | 99.17 12 | 99.83 148 | 99.06 35 | 99.62 170 | 99.66 43 |
|
DTE-MVSNet | | | 99.43 15 | 99.35 18 | 99.66 4 | 99.71 39 | 99.30 19 | 99.31 26 | 99.51 65 | 99.64 12 | 99.56 33 | 99.46 51 | 98.23 57 | 99.97 4 | 98.78 52 | 99.93 32 | 99.72 30 |
|
DU-MVS | | | 98.82 70 | 98.63 85 | 99.39 68 | 99.16 171 | 98.74 87 | 97.54 212 | 99.25 170 | 98.84 97 | 99.06 116 | 98.76 199 | 96.76 170 | 99.93 31 | 98.57 66 | 99.77 105 | 99.50 111 |
|
UniMVSNet (Re) | | | 98.87 65 | 98.71 73 | 99.35 74 | 99.24 146 | 98.73 90 | 97.73 192 | 99.38 108 | 98.93 90 | 99.12 107 | 98.73 202 | 96.77 168 | 99.86 101 | 98.63 63 | 99.80 91 | 99.46 135 |
|
CP-MVSNet | | | 99.21 32 | 99.09 40 | 99.56 24 | 99.65 52 | 98.96 73 | 99.13 53 | 99.34 128 | 99.42 35 | 99.33 74 | 99.26 83 | 97.01 153 | 99.94 26 | 98.74 56 | 99.93 32 | 99.79 16 |
|
WR-MVS_H | | | 99.33 23 | 99.22 28 | 99.65 5 | 99.71 39 | 99.24 26 | 99.32 22 | 99.55 52 | 99.46 30 | 99.50 44 | 99.34 72 | 97.30 133 | 99.93 31 | 98.90 45 | 99.93 32 | 99.77 19 |
|
WR-MVS | | | 98.40 140 | 98.19 149 | 99.03 135 | 99.00 207 | 97.65 188 | 96.85 263 | 98.94 242 | 98.57 112 | 98.89 151 | 98.50 244 | 95.60 221 | 99.85 116 | 97.54 126 | 99.85 64 | 99.59 64 |
|
NR-MVSNet | | | 98.95 56 | 98.82 61 | 99.36 69 | 99.16 171 | 98.72 92 | 99.22 41 | 99.20 181 | 99.10 70 | 99.72 16 | 98.76 199 | 96.38 190 | 99.86 101 | 98.00 101 | 99.82 77 | 99.50 111 |
|
Baseline_NR-MVSNet | | | 98.98 52 | 98.86 58 | 99.36 69 | 99.82 21 | 98.55 103 | 97.47 220 | 99.57 41 | 99.37 39 | 99.21 98 | 99.61 27 | 96.76 170 | 99.83 148 | 98.06 96 | 99.83 74 | 99.71 31 |
|
TranMVSNet+NR-MVSNet | | | 99.17 33 | 99.07 43 | 99.46 60 | 99.37 126 | 98.87 76 | 98.39 124 | 99.42 100 | 99.42 35 | 99.36 69 | 99.06 116 | 98.38 48 | 99.95 17 | 98.34 81 | 99.90 55 | 99.57 75 |
|
TSAR-MVS + GP. | | | 98.18 163 | 97.98 171 | 98.77 172 | 98.71 262 | 97.88 167 | 96.32 292 | 98.66 286 | 96.33 256 | 99.23 97 | 98.51 240 | 97.48 124 | 99.40 337 | 97.16 143 | 99.46 221 | 99.02 252 |
|
abl_6 | | | 98.99 48 | 98.78 65 | 99.61 9 | 99.45 108 | 99.46 6 | 98.60 96 | 99.50 67 | 98.59 108 | 99.24 94 | 99.04 125 | 98.54 40 | 99.89 64 | 96.45 211 | 99.62 170 | 99.50 111 |
|
n2 | | | | | | | | | 0.00 393 | | | | | | | | |
|
nn | | | | | | | | | 0.00 393 | | | | | | | | |
|
mPP-MVS | | | 98.64 104 | 98.34 132 | 99.54 30 | 99.54 78 | 99.17 41 | 98.63 93 | 99.24 175 | 97.47 187 | 98.09 241 | 98.68 211 | 97.62 106 | 99.89 64 | 96.22 225 | 99.62 170 | 99.57 75 |
|
door-mid | | | | | | | | | 99.57 41 | | | | | | | | |
|
XVG-OURS-SEG-HR | | | 98.49 130 | 98.28 139 | 99.14 112 | 99.49 94 | 98.83 80 | 96.54 278 | 99.48 77 | 97.32 206 | 99.11 108 | 98.61 230 | 99.33 8 | 99.30 350 | 96.23 224 | 98.38 321 | 99.28 206 |
|
mvsmamba | | | 99.24 31 | 99.15 35 | 99.49 52 | 99.83 19 | 98.85 77 | 99.41 13 | 99.55 52 | 99.54 23 | 99.40 60 | 99.52 42 | 95.86 214 | 99.91 49 | 99.32 19 | 99.95 19 | 99.70 36 |
|
MVSFormer | | | 98.26 155 | 98.43 118 | 97.77 260 | 98.88 233 | 93.89 312 | 99.39 16 | 99.56 48 | 99.11 63 | 98.16 232 | 98.13 277 | 93.81 269 | 99.97 4 | 99.26 23 | 99.57 192 | 99.43 147 |
|
jason | | | 97.45 220 | 97.35 216 | 97.76 262 | 99.24 146 | 93.93 308 | 95.86 312 | 98.42 298 | 94.24 310 | 98.50 209 | 98.13 277 | 94.82 244 | 99.91 49 | 97.22 140 | 99.73 122 | 99.43 147 |
jason: jason. |
lupinMVS | | | 97.06 249 | 96.86 244 | 97.65 268 | 98.88 233 | 93.89 312 | 95.48 328 | 97.97 317 | 93.53 322 | 98.16 232 | 97.58 314 | 93.81 269 | 99.91 49 | 96.77 181 | 99.57 192 | 99.17 234 |
|
test_djsdf | | | 99.52 9 | 99.51 9 | 99.53 37 | 99.86 14 | 98.74 87 | 99.39 16 | 99.56 48 | 99.11 63 | 99.70 18 | 99.73 13 | 99.00 15 | 99.97 4 | 99.26 23 | 99.98 9 | 99.89 4 |
|
HPM-MVS_fast | | | 99.01 46 | 98.82 61 | 99.57 18 | 99.71 39 | 99.35 14 | 99.00 68 | 99.50 67 | 97.33 204 | 98.94 144 | 98.86 177 | 98.75 26 | 99.82 158 | 97.53 127 | 99.71 134 | 99.56 80 |
|
K. test v3 | | | 98.00 175 | 97.66 194 | 99.03 135 | 99.79 24 | 97.56 192 | 99.19 48 | 92.47 372 | 99.62 17 | 99.52 40 | 99.66 20 | 89.61 306 | 99.96 11 | 99.25 25 | 99.81 81 | 99.56 80 |
|
lessismore_v0 | | | | | 98.97 142 | 99.73 31 | 97.53 194 | | 86.71 383 | | 99.37 67 | 99.52 42 | 89.93 304 | 99.92 39 | 98.99 41 | 99.72 129 | 99.44 143 |
|
SixPastTwentyTwo | | | 98.75 83 | 98.62 87 | 99.16 109 | 99.83 19 | 97.96 161 | 99.28 36 | 98.20 307 | 99.37 39 | 99.70 18 | 99.65 22 | 92.65 288 | 99.93 31 | 99.04 37 | 99.84 68 | 99.60 58 |
|
OurMVSNet-221017-0 | | | 99.37 21 | 99.31 23 | 99.53 37 | 99.91 3 | 98.98 68 | 99.63 6 | 99.58 34 | 99.44 32 | 99.78 12 | 99.76 9 | 96.39 188 | 99.92 39 | 99.44 16 | 99.92 42 | 99.68 39 |
|
HPM-MVS |  | | 98.79 74 | 98.53 98 | 99.59 17 | 99.65 52 | 99.29 20 | 99.16 50 | 99.43 97 | 96.74 241 | 98.61 192 | 98.38 258 | 98.62 34 | 99.87 92 | 96.47 209 | 99.67 156 | 99.59 64 |
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
XVG-OURS | | | 98.53 125 | 98.34 132 | 99.11 116 | 99.50 87 | 98.82 82 | 95.97 304 | 99.50 67 | 97.30 208 | 99.05 121 | 98.98 145 | 99.35 7 | 99.32 347 | 95.72 250 | 99.68 150 | 99.18 230 |
|
XVG-ACMP-BASELINE | | | 98.56 116 | 98.34 132 | 99.22 102 | 99.54 78 | 98.59 100 | 97.71 193 | 99.46 85 | 97.25 213 | 98.98 132 | 98.99 141 | 97.54 113 | 99.84 133 | 95.88 240 | 99.74 119 | 99.23 218 |
|
LPG-MVS_test | | | 98.71 88 | 98.46 112 | 99.47 58 | 99.57 64 | 98.97 69 | 98.23 136 | 99.48 77 | 96.60 246 | 99.10 111 | 99.06 116 | 98.71 29 | 99.83 148 | 95.58 259 | 99.78 101 | 99.62 52 |
|
LGP-MVS_train | | | | | 99.47 58 | 99.57 64 | 98.97 69 | | 99.48 77 | 96.60 246 | 99.10 111 | 99.06 116 | 98.71 29 | 99.83 148 | 95.58 259 | 99.78 101 | 99.62 52 |
|
baseline | | | 98.96 55 | 99.02 45 | 98.76 173 | 99.38 120 | 97.26 207 | 98.49 113 | 99.50 67 | 98.86 95 | 99.19 100 | 99.06 116 | 98.23 57 | 99.69 251 | 98.71 58 | 99.76 115 | 99.33 192 |
|
test11 | | | | | | | | | 98.87 255 | | | | | | | | |
|
door | | | | | | | | | 99.41 101 | | | | | | | | |
|
EPNet_dtu | | | 94.93 313 | 94.78 314 | 95.38 342 | 93.58 384 | 87.68 367 | 96.78 267 | 95.69 358 | 97.35 203 | 89.14 380 | 98.09 284 | 88.15 319 | 99.49 324 | 94.95 270 | 99.30 247 | 98.98 258 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
CHOSEN 1792x2688 | | | 97.49 215 | 97.14 230 | 98.54 203 | 99.68 48 | 96.09 246 | 96.50 282 | 99.62 28 | 91.58 345 | 98.84 163 | 98.97 147 | 92.36 290 | 99.88 75 | 96.76 182 | 99.95 19 | 99.67 42 |
|
EPNet | | | 96.14 288 | 95.44 297 | 98.25 229 | 90.76 387 | 95.50 262 | 97.92 171 | 94.65 360 | 98.97 85 | 92.98 373 | 98.85 180 | 89.12 310 | 99.87 92 | 95.99 236 | 99.68 150 | 99.39 164 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
HQP5-MVS | | | | | | | 96.79 229 | | | | | | | | | | |
|
HQP-NCC | | | | | | 98.67 276 | | 96.29 293 | | 96.05 266 | 95.55 349 | | | | | | |
|
ACMP_Plane | | | | | | 98.67 276 | | 96.29 293 | | 96.05 266 | 95.55 349 | | | | | | |
|
APD-MVS |  | | 98.10 167 | 97.67 191 | 99.42 62 | 99.11 180 | 98.93 74 | 97.76 189 | 99.28 161 | 94.97 294 | 98.72 180 | 98.77 197 | 97.04 149 | 99.85 116 | 93.79 307 | 99.54 200 | 99.49 115 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
BP-MVS | | | | | | | | | | | | | | | 92.82 326 | | |
|
HQP4-MVS | | | | | | | | | | | 95.56 348 | | | 99.54 312 | | | 99.32 194 |
|
HQP3-MVS | | | | | | | | | 99.04 226 | | | | | | | 99.26 254 | |
|
HQP2-MVS | | | | | | | | | | | | | 93.84 267 | | | | |
|
CNVR-MVS | | | 98.17 165 | 97.87 180 | 99.07 125 | 98.67 276 | 98.24 125 | 97.01 251 | 98.93 244 | 97.25 213 | 97.62 270 | 98.34 263 | 97.27 136 | 99.57 303 | 96.42 214 | 99.33 241 | 99.39 164 |
|
NCCC | | | 97.86 187 | 97.47 209 | 99.05 132 | 98.61 283 | 98.07 146 | 96.98 253 | 98.90 250 | 97.63 172 | 97.04 302 | 97.93 295 | 95.99 206 | 99.66 273 | 95.31 264 | 98.82 303 | 99.43 147 |
|
114514_t | | | 96.50 277 | 95.77 284 | 98.69 180 | 99.48 102 | 97.43 199 | 97.84 181 | 99.55 52 | 81.42 378 | 96.51 327 | 98.58 233 | 95.53 223 | 99.67 263 | 93.41 317 | 99.58 188 | 98.98 258 |
|
CP-MVS | | | 98.70 91 | 98.42 120 | 99.52 42 | 99.36 127 | 99.12 60 | 98.72 86 | 99.36 116 | 97.54 182 | 98.30 224 | 98.40 254 | 97.86 87 | 99.89 64 | 96.53 206 | 99.72 129 | 99.56 80 |
|
DSMNet-mixed | | | 97.42 222 | 97.60 200 | 96.87 309 | 99.15 175 | 91.46 346 | 98.54 104 | 99.12 209 | 92.87 332 | 97.58 274 | 99.63 24 | 96.21 195 | 99.90 54 | 95.74 249 | 99.54 200 | 99.27 208 |
|
tpm2 | | | 93.09 337 | 92.58 338 | 94.62 347 | 97.56 351 | 86.53 370 | 97.66 198 | 95.79 357 | 86.15 372 | 94.07 368 | 98.23 272 | 75.95 375 | 99.53 314 | 90.91 355 | 96.86 359 | 97.81 341 |
|
NP-MVS | | | | | | 98.84 241 | 97.39 201 | | | | | 96.84 339 | | | | | |
|
EG-PatchMatch MVS | | | 98.99 48 | 99.01 46 | 98.94 146 | 99.50 87 | 97.47 196 | 98.04 159 | 99.59 32 | 98.15 142 | 99.40 60 | 99.36 67 | 98.58 37 | 99.76 220 | 98.78 52 | 99.68 150 | 99.59 64 |
|
tpm cat1 | | | 93.29 335 | 93.13 334 | 93.75 355 | 97.39 359 | 84.74 376 | 97.39 224 | 97.65 325 | 83.39 377 | 94.16 365 | 98.41 253 | 82.86 353 | 99.39 339 | 91.56 346 | 95.35 372 | 97.14 359 |
|
SteuartSystems-ACMMP | | | 98.79 74 | 98.54 97 | 99.54 30 | 99.73 31 | 99.16 45 | 98.23 136 | 99.31 141 | 97.92 153 | 98.90 148 | 98.90 164 | 98.00 78 | 99.88 75 | 96.15 230 | 99.72 129 | 99.58 70 |
Skip Steuart: Steuart Systems R&D Blog. |
CostFormer | | | 93.97 327 | 93.78 324 | 94.51 348 | 97.53 353 | 85.83 373 | 97.98 167 | 95.96 355 | 89.29 363 | 94.99 360 | 98.63 225 | 78.63 371 | 99.62 286 | 94.54 279 | 96.50 361 | 98.09 329 |
|
CR-MVSNet | | | 96.28 285 | 95.95 282 | 97.28 292 | 97.71 345 | 94.22 296 | 98.11 148 | 98.92 247 | 92.31 338 | 96.91 308 | 99.37 64 | 85.44 336 | 99.81 172 | 97.39 133 | 97.36 350 | 97.81 341 |
|
JIA-IIPM | | | 95.52 303 | 95.03 308 | 97.00 301 | 96.85 368 | 94.03 303 | 96.93 257 | 95.82 356 | 99.20 55 | 94.63 362 | 99.71 15 | 83.09 351 | 99.60 293 | 94.42 285 | 94.64 374 | 97.36 357 |
|
Patchmtry | | | 97.35 226 | 96.97 237 | 98.50 208 | 97.31 361 | 96.47 237 | 98.18 141 | 98.92 247 | 98.95 89 | 98.78 171 | 99.37 64 | 85.44 336 | 99.85 116 | 95.96 238 | 99.83 74 | 99.17 234 |
|
PatchT | | | 96.65 270 | 96.35 272 | 97.54 279 | 97.40 358 | 95.32 267 | 97.98 167 | 96.64 347 | 99.33 44 | 96.89 312 | 99.42 58 | 84.32 344 | 99.81 172 | 97.69 123 | 97.49 343 | 97.48 355 |
|
tpmrst | | | 95.07 310 | 95.46 295 | 93.91 353 | 97.11 364 | 84.36 379 | 97.62 202 | 96.96 340 | 94.98 293 | 96.35 333 | 98.80 192 | 85.46 335 | 99.59 297 | 95.60 257 | 96.23 365 | 97.79 344 |
|
BH-w/o | | | 95.13 309 | 94.89 313 | 95.86 329 | 98.20 321 | 91.31 350 | 95.65 321 | 97.37 329 | 93.64 320 | 96.52 326 | 95.70 359 | 93.04 282 | 99.02 365 | 88.10 365 | 95.82 369 | 97.24 358 |
|
tpm | | | 94.67 315 | 94.34 319 | 95.66 335 | 97.68 349 | 88.42 362 | 97.88 175 | 94.90 359 | 94.46 304 | 96.03 341 | 98.56 235 | 78.66 370 | 99.79 194 | 95.88 240 | 95.01 373 | 98.78 292 |
|
DELS-MVS | | | 98.27 153 | 98.20 147 | 98.48 209 | 98.86 236 | 96.70 233 | 95.60 323 | 99.20 181 | 97.73 165 | 98.45 213 | 98.71 205 | 97.50 119 | 99.82 158 | 98.21 87 | 99.59 182 | 98.93 269 |
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 | | | 96.83 262 | 96.75 253 | 97.08 299 | 98.74 256 | 93.33 321 | 96.71 272 | 98.26 304 | 96.72 242 | 98.44 214 | 97.37 328 | 95.20 234 | 99.47 329 | 91.89 340 | 97.43 346 | 98.44 315 |
|
RPMNet | | | 97.02 253 | 96.93 238 | 97.30 291 | 97.71 345 | 94.22 296 | 98.11 148 | 99.30 151 | 99.37 39 | 96.91 308 | 99.34 72 | 86.72 323 | 99.87 92 | 97.53 127 | 97.36 350 | 97.81 341 |
|
MVSTER | | | 96.86 261 | 96.55 267 | 97.79 258 | 97.91 336 | 94.21 298 | 97.56 210 | 98.87 255 | 97.49 186 | 99.06 116 | 99.05 123 | 80.72 359 | 99.80 181 | 98.44 75 | 99.82 77 | 99.37 174 |
|
CPTT-MVS | | | 97.84 193 | 97.36 215 | 99.27 91 | 99.31 134 | 98.46 111 | 98.29 131 | 99.27 164 | 94.90 296 | 97.83 257 | 98.37 259 | 94.90 240 | 99.84 133 | 93.85 306 | 99.54 200 | 99.51 107 |
|
GBi-Net | | | 98.65 102 | 98.47 110 | 99.17 106 | 98.90 227 | 98.24 125 | 99.20 44 | 99.44 91 | 98.59 108 | 98.95 138 | 99.55 36 | 94.14 262 | 99.86 101 | 97.77 115 | 99.69 145 | 99.41 153 |
|
PVSNet_Blended_VisFu | | | 98.17 165 | 98.15 156 | 98.22 232 | 99.73 31 | 95.15 273 | 97.36 227 | 99.68 22 | 94.45 306 | 98.99 130 | 99.27 81 | 96.87 160 | 99.94 26 | 97.13 149 | 99.91 48 | 99.57 75 |
|
PVSNet_BlendedMVS | | | 97.55 211 | 97.53 202 | 97.60 272 | 98.92 223 | 93.77 316 | 96.64 275 | 99.43 97 | 94.49 302 | 97.62 270 | 99.18 96 | 96.82 164 | 99.67 263 | 94.73 274 | 99.93 32 | 99.36 180 |
|
UnsupCasMVSNet_eth | | | 97.89 183 | 97.60 200 | 98.75 175 | 99.31 134 | 97.17 216 | 97.62 202 | 99.35 122 | 98.72 101 | 98.76 176 | 98.68 211 | 92.57 289 | 99.74 231 | 97.76 119 | 95.60 370 | 99.34 186 |
|
UnsupCasMVSNet_bld | | | 97.30 230 | 96.92 240 | 98.45 212 | 99.28 139 | 96.78 232 | 96.20 298 | 99.27 164 | 95.42 285 | 98.28 226 | 98.30 267 | 93.16 277 | 99.71 244 | 94.99 268 | 97.37 348 | 98.87 278 |
|
PVSNet_Blended | | | 96.88 260 | 96.68 257 | 97.47 284 | 98.92 223 | 93.77 316 | 94.71 346 | 99.43 97 | 90.98 353 | 97.62 270 | 97.36 329 | 96.82 164 | 99.67 263 | 94.73 274 | 99.56 197 | 98.98 258 |
|
FMVSNet5 | | | 96.01 290 | 95.20 305 | 98.41 216 | 97.53 353 | 96.10 244 | 98.74 83 | 99.50 67 | 97.22 222 | 98.03 247 | 99.04 125 | 69.80 381 | 99.88 75 | 97.27 138 | 99.71 134 | 99.25 212 |
|
test1 | | | 98.65 102 | 98.47 110 | 99.17 106 | 98.90 227 | 98.24 125 | 99.20 44 | 99.44 91 | 98.59 108 | 98.95 138 | 99.55 36 | 94.14 262 | 99.86 101 | 97.77 115 | 99.69 145 | 99.41 153 |
|
new_pmnet | | | 96.99 257 | 96.76 252 | 97.67 266 | 98.72 259 | 94.89 280 | 95.95 308 | 98.20 307 | 92.62 335 | 98.55 204 | 98.54 236 | 94.88 243 | 99.52 318 | 93.96 300 | 99.44 226 | 98.59 309 |
|
FMVSNet3 | | | 97.50 213 | 97.24 223 | 98.29 227 | 98.08 328 | 95.83 253 | 97.86 179 | 98.91 249 | 97.89 156 | 98.95 138 | 98.95 154 | 87.06 321 | 99.81 172 | 97.77 115 | 99.69 145 | 99.23 218 |
|
dp | | | 93.47 333 | 93.59 327 | 93.13 362 | 96.64 371 | 81.62 385 | 97.66 198 | 96.42 349 | 92.80 333 | 96.11 336 | 98.64 221 | 78.55 373 | 99.59 297 | 93.31 319 | 92.18 380 | 98.16 326 |
|
FMVSNet2 | | | 98.49 130 | 98.40 122 | 98.75 175 | 98.90 227 | 97.14 219 | 98.61 95 | 99.13 207 | 98.59 108 | 99.19 100 | 99.28 79 | 94.14 262 | 99.82 158 | 97.97 103 | 99.80 91 | 99.29 205 |
|
FMVSNet1 | | | 99.17 33 | 99.17 30 | 99.17 106 | 99.55 75 | 98.24 125 | 99.20 44 | 99.44 91 | 99.21 52 | 99.43 53 | 99.55 36 | 97.82 91 | 99.86 101 | 98.42 77 | 99.89 58 | 99.41 153 |
|
N_pmnet | | | 97.63 207 | 97.17 226 | 98.99 141 | 99.27 141 | 97.86 169 | 95.98 303 | 93.41 369 | 95.25 289 | 99.47 47 | 98.90 164 | 95.63 220 | 99.85 116 | 96.91 165 | 99.73 122 | 99.27 208 |
|
cascas | | | 94.79 314 | 94.33 320 | 96.15 328 | 96.02 380 | 92.36 338 | 92.34 375 | 99.26 169 | 85.34 374 | 95.08 359 | 94.96 371 | 92.96 283 | 98.53 375 | 94.41 288 | 98.59 317 | 97.56 353 |
|
BH-RMVSNet | | | 96.83 262 | 96.58 266 | 97.58 274 | 98.47 301 | 94.05 301 | 96.67 274 | 97.36 330 | 96.70 244 | 97.87 254 | 97.98 290 | 95.14 236 | 99.44 334 | 90.47 358 | 98.58 318 | 99.25 212 |
|
UGNet | | | 98.53 125 | 98.45 114 | 98.79 167 | 97.94 334 | 96.96 223 | 99.08 57 | 98.54 292 | 99.10 70 | 96.82 316 | 99.47 50 | 96.55 180 | 99.84 133 | 98.56 69 | 99.94 28 | 99.55 88 |
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 | | | 96.67 269 | 96.27 277 | 97.87 254 | 98.81 248 | 94.61 290 | 96.77 268 | 97.92 319 | 94.94 295 | 97.12 296 | 97.74 305 | 91.11 298 | 99.82 158 | 93.89 303 | 98.15 330 | 99.18 230 |
|
XXY-MVS | | | 99.14 35 | 99.15 35 | 99.10 118 | 99.76 28 | 97.74 183 | 98.85 80 | 99.62 28 | 98.48 115 | 99.37 67 | 99.49 47 | 98.75 26 | 99.86 101 | 98.20 88 | 99.80 91 | 99.71 31 |
|
DROMVSNet | | | 99.09 40 | 99.05 44 | 99.20 103 | 99.28 139 | 98.93 74 | 99.24 40 | 99.84 7 | 99.08 75 | 98.12 237 | 98.37 259 | 98.72 28 | 99.90 54 | 99.05 36 | 99.77 105 | 98.77 293 |
|
sss | | | 97.21 238 | 96.93 238 | 98.06 244 | 98.83 243 | 95.22 271 | 96.75 270 | 98.48 296 | 94.49 302 | 97.27 293 | 97.90 296 | 92.77 286 | 99.80 181 | 96.57 198 | 99.32 242 | 99.16 237 |
|
Test_1112_low_res | | | 96.99 257 | 96.55 267 | 98.31 225 | 99.35 131 | 95.47 263 | 95.84 315 | 99.53 61 | 91.51 347 | 96.80 317 | 98.48 249 | 91.36 297 | 99.83 148 | 96.58 196 | 99.53 204 | 99.62 52 |
|
1112_ss | | | 97.29 232 | 96.86 244 | 98.58 193 | 99.34 133 | 96.32 240 | 96.75 270 | 99.58 34 | 93.14 327 | 96.89 312 | 97.48 321 | 92.11 293 | 99.86 101 | 96.91 165 | 99.54 200 | 99.57 75 |
|
ab-mvs-re | | | 8.12 355 | 10.83 358 | 0.00 369 | 0.00 392 | 0.00 393 | 0.00 380 | 0.00 393 | 0.00 387 | 0.00 388 | 97.48 321 | 0.00 392 | 0.00 388 | 0.00 386 | 0.00 386 | 0.00 384 |
|
ab-mvs | | | 98.41 138 | 98.36 129 | 98.59 192 | 99.19 160 | 97.23 208 | 99.32 22 | 98.81 270 | 97.66 170 | 98.62 190 | 99.40 63 | 96.82 164 | 99.80 181 | 95.88 240 | 99.51 210 | 98.75 296 |
|
TR-MVS | | | 95.55 302 | 95.12 307 | 96.86 312 | 97.54 352 | 93.94 307 | 96.49 283 | 96.53 348 | 94.36 309 | 97.03 303 | 96.61 343 | 94.26 261 | 99.16 361 | 86.91 368 | 96.31 364 | 97.47 356 |
|
MDTV_nov1_ep13_2view | | | | | | | 74.92 388 | 97.69 195 | | 90.06 360 | 97.75 263 | | 85.78 332 | | 93.52 313 | | 98.69 302 |
|
MDTV_nov1_ep13 | | | | 95.22 304 | | 97.06 365 | 83.20 381 | 97.74 191 | 96.16 351 | 94.37 308 | 96.99 304 | 98.83 186 | 83.95 347 | 99.53 314 | 93.90 302 | 97.95 338 | |
|
MIMVSNet1 | | | 99.38 20 | 99.32 22 | 99.55 26 | 99.86 14 | 99.19 39 | 99.41 13 | 99.59 32 | 99.59 20 | 99.71 17 | 99.57 32 | 97.12 145 | 99.90 54 | 99.21 28 | 99.87 62 | 99.54 92 |
|
MIMVSNet | | | 96.62 272 | 96.25 278 | 97.71 265 | 99.04 199 | 94.66 288 | 99.16 50 | 96.92 343 | 97.23 219 | 97.87 254 | 99.10 113 | 86.11 330 | 99.65 278 | 91.65 343 | 99.21 260 | 98.82 282 |
|
IterMVS-LS | | | 98.55 120 | 98.70 76 | 98.09 239 | 99.48 102 | 94.73 285 | 97.22 239 | 99.39 106 | 98.97 85 | 99.38 64 | 99.31 77 | 96.00 203 | 99.93 31 | 98.58 64 | 99.97 12 | 99.60 58 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
CDS-MVSNet | | | 97.69 201 | 97.35 216 | 98.69 180 | 98.73 257 | 97.02 222 | 96.92 259 | 98.75 279 | 95.89 273 | 98.59 196 | 98.67 213 | 92.08 294 | 99.74 231 | 96.72 187 | 99.81 81 | 99.32 194 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
ACMMP++_ref | | | | | | | | | | | | | | | | 99.77 105 | |
|
IterMVS | | | 97.73 199 | 98.11 160 | 96.57 316 | 99.24 146 | 90.28 356 | 95.52 327 | 99.21 179 | 98.86 95 | 99.33 74 | 99.33 74 | 93.11 278 | 99.94 26 | 98.49 72 | 99.94 28 | 99.48 125 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
DP-MVS Recon | | | 97.33 228 | 96.92 240 | 98.57 195 | 99.09 187 | 97.99 152 | 96.79 266 | 99.35 122 | 93.18 326 | 97.71 264 | 98.07 286 | 95.00 239 | 99.31 348 | 93.97 299 | 99.13 275 | 98.42 317 |
|
MVS_111021_LR | | | 98.30 149 | 98.12 159 | 98.83 160 | 99.16 171 | 98.03 150 | 96.09 301 | 99.30 151 | 97.58 177 | 98.10 240 | 98.24 270 | 98.25 55 | 99.34 344 | 96.69 190 | 99.65 162 | 99.12 239 |
|
DP-MVS | | | 98.93 58 | 98.81 63 | 99.28 88 | 99.21 153 | 98.45 112 | 98.46 118 | 99.33 133 | 99.63 14 | 99.48 45 | 99.15 106 | 97.23 141 | 99.75 227 | 97.17 142 | 99.66 161 | 99.63 51 |
|
ACMMP++ | | | | | | | | | | | | | | | | 99.68 150 | |
|
HQP-MVS | | | 97.00 256 | 96.49 269 | 98.55 200 | 98.67 276 | 96.79 229 | 96.29 293 | 99.04 226 | 96.05 266 | 95.55 349 | 96.84 339 | 93.84 267 | 99.54 312 | 92.82 326 | 99.26 254 | 99.32 194 |
|
QAPM | | | 97.31 229 | 96.81 250 | 98.82 161 | 98.80 250 | 97.49 195 | 99.06 62 | 99.19 186 | 90.22 357 | 97.69 266 | 99.16 102 | 96.91 158 | 99.90 54 | 90.89 356 | 99.41 228 | 99.07 243 |
|
Vis-MVSNet |  | | 99.34 22 | 99.36 17 | 99.27 91 | 99.73 31 | 98.26 123 | 99.17 49 | 99.78 10 | 99.11 63 | 99.27 85 | 99.48 49 | 98.82 23 | 99.95 17 | 98.94 43 | 99.93 32 | 99.59 64 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
MVS-HIRNet | | | 94.32 319 | 95.62 290 | 90.42 364 | 98.46 302 | 75.36 387 | 96.29 293 | 89.13 381 | 95.25 289 | 95.38 355 | 99.75 10 | 92.88 284 | 99.19 359 | 94.07 298 | 99.39 231 | 96.72 365 |
|
IS-MVSNet | | | 98.19 162 | 97.90 178 | 99.08 122 | 99.57 64 | 97.97 157 | 99.31 26 | 98.32 302 | 99.01 81 | 98.98 132 | 99.03 128 | 91.59 296 | 99.79 194 | 95.49 261 | 99.80 91 | 99.48 125 |
|
HyFIR lowres test | | | 97.19 240 | 96.60 265 | 98.96 143 | 99.62 59 | 97.28 206 | 95.17 335 | 99.50 67 | 94.21 311 | 99.01 127 | 98.32 266 | 86.61 324 | 99.99 2 | 97.10 151 | 99.84 68 | 99.60 58 |
|
EPMVS | | | 93.72 331 | 93.27 330 | 95.09 345 | 96.04 379 | 87.76 366 | 98.13 145 | 85.01 385 | 94.69 300 | 96.92 306 | 98.64 221 | 78.47 374 | 99.31 348 | 95.04 267 | 96.46 362 | 98.20 324 |
|
PAPM_NR | | | 96.82 264 | 96.32 274 | 98.30 226 | 99.07 191 | 96.69 234 | 97.48 218 | 98.76 276 | 95.81 276 | 96.61 323 | 96.47 347 | 94.12 265 | 99.17 360 | 90.82 357 | 97.78 340 | 99.06 244 |
|
TAMVS | | | 98.24 158 | 98.05 166 | 98.80 165 | 99.07 191 | 97.18 215 | 97.88 175 | 98.81 270 | 96.66 245 | 99.17 105 | 99.21 91 | 94.81 246 | 99.77 212 | 96.96 163 | 99.88 59 | 99.44 143 |
|
PAPR | | | 95.29 306 | 94.47 315 | 97.75 263 | 97.50 357 | 95.14 274 | 94.89 343 | 98.71 284 | 91.39 349 | 95.35 356 | 95.48 363 | 94.57 253 | 99.14 363 | 84.95 371 | 97.37 348 | 98.97 262 |
|
RPSCF | | | 98.62 108 | 98.36 129 | 99.42 62 | 99.65 52 | 99.42 7 | 98.55 103 | 99.57 41 | 97.72 167 | 98.90 148 | 99.26 83 | 96.12 198 | 99.52 318 | 95.72 250 | 99.71 134 | 99.32 194 |
|
Vis-MVSNet (Re-imp) | | | 97.46 218 | 97.16 227 | 98.34 222 | 99.55 75 | 96.10 244 | 98.94 73 | 98.44 297 | 98.32 122 | 98.16 232 | 98.62 227 | 88.76 311 | 99.73 235 | 93.88 304 | 99.79 96 | 99.18 230 |
|
test_0402 | | | 98.76 81 | 98.71 73 | 98.93 147 | 99.56 71 | 98.14 138 | 98.45 120 | 99.34 128 | 99.28 49 | 98.95 138 | 98.91 161 | 98.34 53 | 99.79 194 | 95.63 256 | 99.91 48 | 98.86 279 |
|
MVS_111021_HR | | | 98.25 157 | 98.08 164 | 98.75 175 | 99.09 187 | 97.46 197 | 95.97 304 | 99.27 164 | 97.60 176 | 97.99 248 | 98.25 269 | 98.15 70 | 99.38 341 | 96.87 173 | 99.57 192 | 99.42 150 |
|
CSCG | | | 98.68 97 | 98.50 103 | 99.20 103 | 99.45 108 | 98.63 95 | 98.56 102 | 99.57 41 | 97.87 157 | 98.85 160 | 98.04 287 | 97.66 100 | 99.84 133 | 96.72 187 | 99.81 81 | 99.13 238 |
|
PatchMatch-RL | | | 97.24 236 | 96.78 251 | 98.61 190 | 99.03 202 | 97.83 172 | 96.36 290 | 99.06 219 | 93.49 324 | 97.36 292 | 97.78 302 | 95.75 217 | 99.49 324 | 93.44 316 | 98.77 304 | 98.52 310 |
|
API-MVS | | | 97.04 252 | 96.91 242 | 97.42 287 | 97.88 338 | 98.23 129 | 98.18 141 | 98.50 295 | 97.57 178 | 97.39 290 | 96.75 341 | 96.77 168 | 99.15 362 | 90.16 359 | 99.02 289 | 94.88 377 |
|
Test By Simon | | | | | | | | | | | | | 96.52 181 | | | | |
|
TDRefinement | | | 99.42 16 | 99.38 16 | 99.55 26 | 99.76 28 | 99.33 18 | 99.68 5 | 99.71 15 | 99.38 38 | 99.53 38 | 99.61 27 | 98.64 32 | 99.80 181 | 98.24 85 | 99.84 68 | 99.52 104 |
|
USDC | | | 97.41 223 | 97.40 211 | 97.44 286 | 98.94 217 | 93.67 318 | 95.17 335 | 99.53 61 | 94.03 316 | 98.97 135 | 99.10 113 | 95.29 231 | 99.34 344 | 95.84 246 | 99.73 122 | 99.30 201 |
|
EPP-MVSNet | | | 98.30 149 | 98.04 167 | 99.07 125 | 99.56 71 | 97.83 172 | 99.29 32 | 98.07 314 | 99.03 79 | 98.59 196 | 99.13 109 | 92.16 292 | 99.90 54 | 96.87 173 | 99.68 150 | 99.49 115 |
|
PMMVS | | | 96.51 275 | 95.98 281 | 98.09 239 | 97.53 353 | 95.84 252 | 94.92 342 | 98.84 264 | 91.58 345 | 96.05 340 | 95.58 360 | 95.68 219 | 99.66 273 | 95.59 258 | 98.09 333 | 98.76 295 |
|
PAPM | | | 91.88 346 | 90.34 349 | 96.51 317 | 98.06 329 | 92.56 333 | 92.44 374 | 97.17 335 | 86.35 371 | 90.38 378 | 96.01 353 | 86.61 324 | 99.21 358 | 70.65 383 | 95.43 371 | 97.75 345 |
|
ACMMP |  | | 98.75 83 | 98.50 103 | 99.52 42 | 99.56 71 | 99.16 45 | 98.87 77 | 99.37 112 | 97.16 224 | 98.82 168 | 99.01 138 | 97.71 97 | 99.87 92 | 96.29 222 | 99.69 145 | 99.54 92 |
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 | | | 97.17 242 | 96.71 255 | 98.55 200 | 98.56 291 | 98.05 149 | 96.33 291 | 98.93 244 | 96.91 235 | 97.06 301 | 97.39 326 | 94.38 258 | 99.45 332 | 91.66 342 | 99.18 267 | 98.14 327 |
|
PatchmatchNet |  | | 95.58 301 | 95.67 289 | 95.30 343 | 97.34 360 | 87.32 368 | 97.65 200 | 96.65 346 | 95.30 288 | 97.07 300 | 98.69 209 | 84.77 339 | 99.75 227 | 94.97 269 | 98.64 314 | 98.83 281 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
PHI-MVS | | | 98.29 152 | 97.95 173 | 99.34 77 | 98.44 304 | 99.16 45 | 98.12 147 | 99.38 108 | 96.01 269 | 98.06 243 | 98.43 252 | 97.80 92 | 99.67 263 | 95.69 252 | 99.58 188 | 99.20 223 |
|
F-COLMAP | | | 97.30 230 | 96.68 257 | 99.14 112 | 99.19 160 | 98.39 114 | 97.27 235 | 99.30 151 | 92.93 330 | 96.62 322 | 98.00 288 | 95.73 218 | 99.68 260 | 92.62 332 | 98.46 320 | 99.35 184 |
|
ANet_high | | | 99.57 7 | 99.67 5 | 99.28 88 | 99.89 6 | 98.09 140 | 99.14 52 | 99.93 2 | 99.82 3 | 99.93 3 | 99.81 5 | 99.17 12 | 99.94 26 | 99.31 20 | 100.00 1 | 99.82 12 |
|
wuyk23d | | | 96.06 289 | 97.62 198 | 91.38 363 | 98.65 282 | 98.57 102 | 98.85 80 | 96.95 341 | 96.86 237 | 99.90 5 | 99.16 102 | 99.18 11 | 98.40 376 | 89.23 362 | 99.77 105 | 77.18 381 |
|
OMC-MVS | | | 97.88 185 | 97.49 205 | 99.04 134 | 98.89 232 | 98.63 95 | 96.94 255 | 99.25 170 | 95.02 292 | 98.53 207 | 98.51 240 | 97.27 136 | 99.47 329 | 93.50 315 | 99.51 210 | 99.01 253 |
|
MG-MVS | | | 96.77 265 | 96.61 263 | 97.26 293 | 98.31 314 | 93.06 324 | 95.93 309 | 98.12 313 | 96.45 253 | 97.92 250 | 98.73 202 | 93.77 271 | 99.39 339 | 91.19 352 | 99.04 285 | 99.33 192 |
|
AdaColmap |  | | 97.14 244 | 96.71 255 | 98.46 211 | 98.34 312 | 97.80 178 | 96.95 254 | 98.93 244 | 95.58 279 | 96.92 306 | 97.66 309 | 95.87 213 | 99.53 314 | 90.97 353 | 99.14 272 | 98.04 331 |
|
uanet | | | 0.00 356 | 0.00 359 | 0.00 369 | 0.00 392 | 0.00 393 | 0.00 380 | 0.00 393 | 0.00 387 | 0.00 388 | 0.00 387 | 0.00 392 | 0.00 388 | 0.00 386 | 0.00 386 | 0.00 384 |
|
ITE_SJBPF | | | | | 98.87 155 | 99.22 151 | 98.48 110 | | 99.35 122 | 97.50 184 | 98.28 226 | 98.60 231 | 97.64 104 | 99.35 343 | 93.86 305 | 99.27 251 | 98.79 291 |
|
DeepMVS_CX |  | | | | 93.44 359 | 98.24 318 | 94.21 298 | | 94.34 362 | 64.28 381 | 91.34 377 | 94.87 374 | 89.45 309 | 92.77 384 | 77.54 382 | 93.14 378 | 93.35 379 |
|
TinyColmap | | | 97.89 183 | 97.98 171 | 97.60 272 | 98.86 236 | 94.35 295 | 96.21 297 | 99.44 91 | 97.45 194 | 99.06 116 | 98.88 173 | 97.99 81 | 99.28 353 | 94.38 289 | 99.58 188 | 99.18 230 |
|
MAR-MVS | | | 96.47 279 | 95.70 287 | 98.79 167 | 97.92 335 | 99.12 60 | 98.28 132 | 98.60 290 | 92.16 340 | 95.54 352 | 96.17 352 | 94.77 250 | 99.52 318 | 89.62 361 | 98.23 324 | 97.72 347 |
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 | | | 97.90 181 | 97.69 190 | 98.52 204 | 99.17 169 | 97.66 187 | 97.19 243 | 99.47 83 | 96.31 258 | 97.85 256 | 98.20 274 | 96.71 174 | 99.52 318 | 94.62 277 | 99.72 129 | 98.38 318 |
|
MSDG | | | 97.71 200 | 97.52 203 | 98.28 228 | 98.91 226 | 96.82 228 | 94.42 356 | 99.37 112 | 97.65 171 | 98.37 223 | 98.29 268 | 97.40 128 | 99.33 346 | 94.09 297 | 99.22 258 | 98.68 305 |
|
LS3D | | | 98.63 106 | 98.38 127 | 99.36 69 | 97.25 362 | 99.38 8 | 99.12 55 | 99.32 135 | 99.21 52 | 98.44 214 | 98.88 173 | 97.31 132 | 99.80 181 | 96.58 196 | 99.34 240 | 98.92 270 |
|
CLD-MVS | | | 97.49 215 | 97.16 227 | 98.48 209 | 99.07 191 | 97.03 221 | 94.71 346 | 99.21 179 | 94.46 304 | 98.06 243 | 97.16 334 | 97.57 110 | 99.48 327 | 94.46 282 | 99.78 101 | 98.95 264 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
FPMVS | | | 93.44 334 | 92.23 339 | 97.08 299 | 99.25 145 | 97.86 169 | 95.61 322 | 97.16 336 | 92.90 331 | 93.76 371 | 98.65 218 | 75.94 376 | 95.66 381 | 79.30 381 | 97.49 343 | 97.73 346 |
|
Gipuma |  | | 99.03 45 | 99.16 31 | 98.64 183 | 99.94 2 | 98.51 108 | 99.32 22 | 99.75 13 | 99.58 22 | 98.60 194 | 99.62 25 | 98.22 60 | 99.51 322 | 97.70 121 | 99.73 122 | 97.89 336 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |