CS-MVS | | | 99.50 12 | 99.48 10 | 99.54 82 | 99.76 56 | 99.42 85 | 99.90 1 | 99.55 65 | 98.56 71 | 99.78 35 | 99.70 142 | 98.65 65 | 99.79 166 | 99.65 9 | 99.78 90 | 99.41 174 |
|
CS-MVS-test | | | 99.49 14 | 99.48 10 | 99.54 82 | 99.78 47 | 99.30 96 | 99.89 2 | 99.58 49 | 98.56 71 | 99.73 48 | 99.69 152 | 98.55 70 | 99.82 152 | 99.69 6 | 99.85 55 | 99.48 159 |
|
RRT_MVS | | | 98.70 135 | 98.66 124 | 98.83 207 | 98.90 290 | 98.45 201 | 99.89 2 | 99.28 265 | 97.76 163 | 98.94 229 | 99.92 10 | 96.98 126 | 99.25 282 | 99.28 47 | 97.00 266 | 98.80 225 |
|
mvsmamba | | | 98.92 106 | 98.87 100 | 99.08 157 | 99.07 268 | 99.16 111 | 99.88 4 | 99.51 103 | 98.15 117 | 99.40 136 | 99.89 20 | 97.12 119 | 99.33 268 | 99.38 32 | 97.40 254 | 98.73 239 |
|
MVSFormer | | | 99.17 68 | 99.12 64 | 99.29 136 | 99.51 156 | 98.94 151 | 99.88 4 | 99.46 169 | 97.55 184 | 99.80 28 | 99.65 170 | 97.39 110 | 99.28 277 | 99.03 69 | 99.85 55 | 99.65 113 |
|
test_djsdf | | | 98.67 140 | 98.57 141 | 98.98 172 | 98.70 319 | 98.91 155 | 99.88 4 | 99.46 169 | 97.55 184 | 99.22 179 | 99.88 26 | 95.73 169 | 99.28 277 | 99.03 69 | 97.62 230 | 98.75 234 |
|
OurMVSNet-221017-0 | | | 97.88 218 | 97.77 209 | 98.19 270 | 98.71 318 | 96.53 290 | 99.88 4 | 99.00 301 | 97.79 160 | 98.78 253 | 99.94 4 | 91.68 291 | 99.35 265 | 97.21 251 | 96.99 267 | 98.69 251 |
|
DROMVSNet | | | 99.44 29 | 99.39 19 | 99.58 75 | 99.56 144 | 99.49 78 | 99.88 4 | 99.58 49 | 98.38 86 | 99.73 48 | 99.69 152 | 98.20 90 | 99.70 202 | 99.64 10 | 99.82 76 | 99.54 142 |
|
DVP-MVS++ | | | 99.59 3 | 99.50 8 | 99.88 5 | 99.51 156 | 99.88 8 | 99.87 9 | 99.51 103 | 98.99 33 | 99.88 11 | 99.81 76 | 99.27 5 | 99.96 22 | 98.85 96 | 99.80 83 | 99.81 47 |
|
FOURS1 | | | | | | 99.91 1 | 99.93 1 | 99.87 9 | 99.56 57 | 99.10 16 | 99.81 25 | | | | | | |
|
K. test v3 | | | 97.10 283 | 96.79 284 | 98.01 282 | 98.72 316 | 96.33 297 | 99.87 9 | 97.05 362 | 97.59 179 | 96.16 342 | 99.80 89 | 88.71 326 | 99.04 313 | 96.69 283 | 96.55 273 | 98.65 273 |
|
FC-MVSNet-test | | | 98.75 131 | 98.62 132 | 99.15 154 | 99.08 267 | 99.45 83 | 99.86 12 | 99.60 41 | 98.23 105 | 98.70 265 | 99.82 63 | 96.80 131 | 99.22 288 | 99.07 67 | 96.38 276 | 98.79 226 |
|
v7n | | | 97.87 220 | 97.52 234 | 98.92 182 | 98.76 312 | 98.58 185 | 99.84 13 | 99.46 169 | 96.20 294 | 98.91 233 | 99.70 142 | 94.89 197 | 99.44 244 | 96.03 297 | 93.89 327 | 98.75 234 |
|
DTE-MVSNet | | | 97.51 267 | 97.19 275 | 98.46 245 | 98.63 325 | 98.13 216 | 99.84 13 | 99.48 142 | 96.68 256 | 97.97 313 | 99.67 164 | 92.92 256 | 98.56 341 | 96.88 276 | 92.60 341 | 98.70 247 |
|
3Dnovator | | 97.25 9 | 99.24 62 | 99.05 71 | 99.81 36 | 99.12 258 | 99.66 53 | 99.84 13 | 99.74 10 | 99.09 20 | 98.92 232 | 99.90 16 | 95.94 160 | 99.98 8 | 98.95 77 | 99.92 13 | 99.79 60 |
|
FIs | | | 98.78 128 | 98.63 127 | 99.23 145 | 99.18 245 | 99.54 70 | 99.83 16 | 99.59 44 | 98.28 97 | 98.79 252 | 99.81 76 | 96.75 134 | 99.37 258 | 99.08 66 | 96.38 276 | 98.78 227 |
|
test_fmvs3 | | | 92.10 326 | 91.77 329 | 93.08 342 | 96.19 360 | 86.25 363 | 99.82 17 | 98.62 341 | 96.65 259 | 95.19 349 | 96.90 359 | 55.05 374 | 95.93 370 | 96.63 287 | 90.92 349 | 97.06 358 |
|
jajsoiax | | | 98.43 153 | 98.28 159 | 98.88 193 | 98.60 329 | 98.43 203 | 99.82 17 | 99.53 84 | 98.19 111 | 98.63 276 | 99.80 89 | 93.22 252 | 99.44 244 | 99.22 53 | 97.50 242 | 98.77 230 |
|
OpenMVS |  | 96.50 16 | 98.47 150 | 98.12 169 | 99.52 96 | 99.04 275 | 99.53 73 | 99.82 17 | 99.72 11 | 94.56 331 | 98.08 306 | 99.88 26 | 94.73 209 | 99.98 8 | 97.47 238 | 99.76 96 | 99.06 206 |
|
nrg030 | | | 98.64 143 | 98.42 149 | 99.28 138 | 99.05 274 | 99.69 47 | 99.81 20 | 99.46 169 | 98.04 137 | 99.01 217 | 99.82 63 | 96.69 136 | 99.38 253 | 99.34 39 | 94.59 316 | 98.78 227 |
|
HPM-MVS |  | | 99.42 34 | 99.28 46 | 99.83 32 | 99.90 4 | 99.72 42 | 99.81 20 | 99.54 73 | 97.59 179 | 99.68 60 | 99.63 182 | 98.91 34 | 99.94 57 | 98.58 136 | 99.91 18 | 99.84 26 |
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
EPP-MVSNet | | | 99.13 75 | 98.99 83 | 99.53 90 | 99.65 114 | 99.06 128 | 99.81 20 | 99.33 241 | 97.43 198 | 99.60 90 | 99.88 26 | 97.14 118 | 99.84 135 | 99.13 60 | 98.94 172 | 99.69 99 |
|
3Dnovator+ | | 97.12 13 | 99.18 66 | 98.97 87 | 99.82 33 | 99.17 251 | 99.68 48 | 99.81 20 | 99.51 103 | 99.20 8 | 98.72 258 | 99.89 20 | 95.68 172 | 99.97 14 | 98.86 94 | 99.86 48 | 99.81 47 |
|
FA-MVS(test-final) | | | 98.75 131 | 98.53 144 | 99.41 114 | 99.55 148 | 99.05 130 | 99.80 24 | 99.01 300 | 96.59 268 | 99.58 94 | 99.59 196 | 95.39 179 | 99.90 101 | 97.78 205 | 99.49 129 | 99.28 187 |
|
bld_raw_dy_0_64 | | | 98.69 137 | 98.58 140 | 98.99 170 | 98.88 293 | 98.96 143 | 99.80 24 | 99.41 199 | 97.91 147 | 99.32 156 | 99.87 32 | 95.70 171 | 99.31 274 | 99.09 64 | 97.27 259 | 98.71 242 |
|
GeoE | | | 98.85 120 | 98.62 132 | 99.53 90 | 99.61 129 | 99.08 125 | 99.80 24 | 99.51 103 | 97.10 229 | 99.31 158 | 99.78 106 | 95.23 188 | 99.77 173 | 98.21 170 | 99.03 167 | 99.75 74 |
|
canonicalmvs | | | 99.02 97 | 98.86 103 | 99.51 98 | 99.42 185 | 99.32 92 | 99.80 24 | 99.48 142 | 98.63 66 | 99.31 158 | 98.81 331 | 97.09 121 | 99.75 179 | 99.27 50 | 97.90 222 | 99.47 165 |
|
v8 | | | 97.95 210 | 97.63 226 | 98.93 180 | 98.95 287 | 98.81 168 | 99.80 24 | 99.41 199 | 96.03 308 | 99.10 203 | 99.42 249 | 94.92 195 | 99.30 275 | 96.94 271 | 94.08 325 | 98.66 271 |
|
Vis-MVSNet (Re-imp) | | | 98.87 110 | 98.72 115 | 99.31 128 | 99.71 87 | 98.88 157 | 99.80 24 | 99.44 188 | 97.91 147 | 99.36 148 | 99.78 106 | 95.49 177 | 99.43 248 | 97.91 193 | 99.11 158 | 99.62 125 |
|
Anonymous20240521 | | | 96.20 299 | 95.89 301 | 97.13 317 | 97.72 348 | 94.96 328 | 99.79 30 | 99.29 263 | 93.01 345 | 97.20 330 | 99.03 316 | 89.69 319 | 98.36 345 | 91.16 351 | 96.13 281 | 98.07 335 |
|
PS-MVSNAJss | | | 98.92 106 | 98.92 93 | 98.90 188 | 98.78 308 | 98.53 189 | 99.78 31 | 99.54 73 | 98.07 131 | 99.00 221 | 99.76 119 | 99.01 18 | 99.37 258 | 99.13 60 | 97.23 260 | 98.81 224 |
|
PEN-MVS | | | 97.76 238 | 97.44 248 | 98.72 218 | 98.77 311 | 98.54 188 | 99.78 31 | 99.51 103 | 97.06 233 | 98.29 299 | 99.64 176 | 92.63 269 | 98.89 335 | 98.09 179 | 93.16 334 | 98.72 240 |
|
anonymousdsp | | | 98.44 152 | 98.28 159 | 98.94 178 | 98.50 334 | 98.96 143 | 99.77 33 | 99.50 122 | 97.07 231 | 98.87 241 | 99.77 113 | 94.76 207 | 99.28 277 | 98.66 123 | 97.60 231 | 98.57 301 |
|
SixPastTwentyTwo | | | 97.50 268 | 97.33 265 | 98.03 279 | 98.65 323 | 96.23 300 | 99.77 33 | 98.68 339 | 97.14 222 | 97.90 314 | 99.93 6 | 90.45 309 | 99.18 296 | 97.00 265 | 96.43 275 | 98.67 263 |
|
QAPM | | | 98.67 140 | 98.30 158 | 99.80 38 | 99.20 240 | 99.67 51 | 99.77 33 | 99.72 11 | 94.74 328 | 98.73 257 | 99.90 16 | 95.78 167 | 99.98 8 | 96.96 269 | 99.88 37 | 99.76 73 |
|
test_vis3_rt | | | 87.04 332 | 85.81 335 | 90.73 348 | 93.99 370 | 81.96 369 | 99.76 36 | 90.23 381 | 92.81 347 | 81.35 369 | 91.56 369 | 40.06 378 | 99.07 310 | 94.27 327 | 88.23 356 | 91.15 369 |
|
dcpmvs_2 | | | 99.23 63 | 99.58 2 | 98.16 272 | 99.83 35 | 94.68 332 | 99.76 36 | 99.52 89 | 99.07 23 | 99.98 4 | 99.88 26 | 98.56 69 | 99.93 70 | 99.67 8 | 99.98 2 | 99.87 17 |
|
HPM-MVS_fast | | | 99.51 11 | 99.40 18 | 99.85 25 | 99.91 1 | 99.79 30 | 99.76 36 | 99.56 57 | 97.72 168 | 99.76 43 | 99.75 122 | 99.13 12 | 99.92 80 | 99.07 67 | 99.92 13 | 99.85 22 |
|
v10 | | | 97.85 223 | 97.52 234 | 98.86 201 | 98.99 280 | 98.67 176 | 99.75 39 | 99.41 199 | 95.70 312 | 98.98 223 | 99.41 253 | 94.75 208 | 99.23 285 | 96.01 298 | 94.63 315 | 98.67 263 |
|
APDe-MVS | | | 99.66 1 | 99.57 3 | 99.92 1 | 99.77 53 | 99.89 4 | 99.75 39 | 99.56 57 | 99.02 26 | 99.88 11 | 99.85 42 | 99.18 10 | 99.96 22 | 99.22 53 | 99.92 13 | 99.90 4 |
|
IS-MVSNet | | | 99.05 93 | 98.87 100 | 99.57 77 | 99.73 78 | 99.32 92 | 99.75 39 | 99.20 278 | 98.02 140 | 99.56 98 | 99.86 37 | 96.54 140 | 99.67 209 | 98.09 179 | 99.13 157 | 99.73 83 |
|
test_vis1_n | | | 97.92 214 | 97.44 248 | 99.34 121 | 99.53 150 | 98.08 218 | 99.74 42 | 99.49 130 | 99.15 10 | 100.00 1 | 99.94 4 | 79.51 362 | 99.98 8 | 99.88 2 | 99.76 96 | 99.97 2 |
|
test_fmvs1_n | | | 98.41 156 | 98.14 166 | 99.21 146 | 99.82 37 | 97.71 241 | 99.74 42 | 99.49 130 | 99.32 4 | 99.99 2 | 99.95 2 | 85.32 349 | 99.97 14 | 99.82 3 | 99.84 63 | 99.96 3 |
|
tttt0517 | | | 98.42 154 | 98.14 166 | 99.28 138 | 99.66 108 | 98.38 206 | 99.74 42 | 96.85 363 | 97.68 172 | 99.79 30 | 99.74 127 | 91.39 299 | 99.89 111 | 98.83 102 | 99.56 124 | 99.57 138 |
|
test_fmvs2 | | | 97.25 278 | 97.30 268 | 97.09 319 | 99.43 183 | 93.31 349 | 99.73 45 | 98.87 319 | 98.83 52 | 99.28 164 | 99.80 89 | 84.45 352 | 99.66 212 | 97.88 195 | 97.45 248 | 98.30 324 |
|
baseline | | | 99.15 71 | 99.02 78 | 99.53 90 | 99.66 108 | 99.14 117 | 99.72 46 | 99.48 142 | 98.35 91 | 99.42 127 | 99.84 52 | 96.07 153 | 99.79 166 | 99.51 19 | 99.14 156 | 99.67 106 |
|
RPSCF | | | 98.22 170 | 98.62 132 | 96.99 320 | 99.82 37 | 91.58 357 | 99.72 46 | 99.44 188 | 96.61 264 | 99.66 69 | 99.89 20 | 95.92 161 | 99.82 152 | 97.46 239 | 99.10 161 | 99.57 138 |
|
CSCG | | | 99.32 49 | 99.32 32 | 99.32 127 | 99.85 25 | 98.29 208 | 99.71 48 | 99.66 26 | 98.11 123 | 99.41 131 | 99.80 89 | 98.37 83 | 99.96 22 | 98.99 73 | 99.96 7 | 99.72 89 |
|
WR-MVS_H | | | 98.13 181 | 97.87 200 | 98.90 188 | 99.02 277 | 98.84 162 | 99.70 49 | 99.59 44 | 97.27 211 | 98.40 292 | 99.19 300 | 95.53 175 | 99.23 285 | 98.34 162 | 93.78 328 | 98.61 295 |
|
LTVRE_ROB | | 97.16 12 | 98.02 198 | 97.90 195 | 98.40 253 | 99.23 233 | 96.80 281 | 99.70 49 | 99.60 41 | 97.12 225 | 98.18 303 | 99.70 142 | 91.73 290 | 99.72 190 | 98.39 156 | 97.45 248 | 98.68 256 |
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 |
test_f | | | 91.90 327 | 91.26 331 | 93.84 339 | 95.52 367 | 85.92 364 | 99.69 51 | 98.53 345 | 95.31 317 | 93.87 355 | 96.37 362 | 55.33 373 | 98.27 346 | 95.70 304 | 90.98 348 | 97.32 357 |
|
XVS | | | 99.53 9 | 99.42 15 | 99.87 11 | 99.85 25 | 99.83 16 | 99.69 51 | 99.68 19 | 98.98 36 | 99.37 144 | 99.74 127 | 98.81 44 | 99.94 57 | 98.79 107 | 99.86 48 | 99.84 26 |
|
X-MVStestdata | | | 96.55 291 | 95.45 308 | 99.87 11 | 99.85 25 | 99.83 16 | 99.69 51 | 99.68 19 | 98.98 36 | 99.37 144 | 64.01 378 | 98.81 44 | 99.94 57 | 98.79 107 | 99.86 48 | 99.84 26 |
|
V42 | | | 98.06 188 | 97.79 204 | 98.86 201 | 98.98 283 | 98.84 162 | 99.69 51 | 99.34 234 | 96.53 270 | 99.30 160 | 99.37 264 | 94.67 212 | 99.32 271 | 97.57 228 | 94.66 314 | 98.42 316 |
|
mPP-MVS | | | 99.44 29 | 99.30 40 | 99.86 20 | 99.88 11 | 99.79 30 | 99.69 51 | 99.48 142 | 98.12 121 | 99.50 110 | 99.75 122 | 98.78 47 | 99.97 14 | 98.57 139 | 99.89 34 | 99.83 35 |
|
CP-MVS | | | 99.45 25 | 99.32 32 | 99.85 25 | 99.83 35 | 99.75 39 | 99.69 51 | 99.52 89 | 98.07 131 | 99.53 105 | 99.63 182 | 98.93 33 | 99.97 14 | 98.74 111 | 99.91 18 | 99.83 35 |
|
FE-MVS | | | 98.48 149 | 98.17 163 | 99.40 115 | 99.54 149 | 98.96 143 | 99.68 57 | 98.81 324 | 95.54 314 | 99.62 84 | 99.70 142 | 93.82 241 | 99.93 70 | 97.35 245 | 99.46 130 | 99.32 184 |
|
PS-CasMVS | | | 97.93 211 | 97.59 229 | 98.95 177 | 98.99 280 | 99.06 128 | 99.68 57 | 99.52 89 | 97.13 223 | 98.31 297 | 99.68 158 | 92.44 278 | 99.05 312 | 98.51 147 | 94.08 325 | 98.75 234 |
|
Vis-MVSNet |  | | 99.12 81 | 98.97 87 | 99.56 79 | 99.78 47 | 99.10 121 | 99.68 57 | 99.66 26 | 98.49 77 | 99.86 16 | 99.87 32 | 94.77 206 | 99.84 135 | 99.19 55 | 99.41 134 | 99.74 78 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
test_vis1_n_1920 | | | 98.63 144 | 98.40 151 | 99.31 128 | 99.86 20 | 97.94 229 | 99.67 60 | 99.62 33 | 99.43 1 | 99.99 2 | 99.91 11 | 87.29 342 | 100.00 1 | 99.92 1 | 99.92 13 | 99.98 1 |
|
EIA-MVS | | | 99.18 66 | 99.09 68 | 99.45 108 | 99.49 167 | 99.18 108 | 99.67 60 | 99.53 84 | 97.66 175 | 99.40 136 | 99.44 245 | 98.10 94 | 99.81 157 | 98.94 78 | 99.62 120 | 99.35 180 |
|
MSP-MVS | | | 99.42 34 | 99.27 48 | 99.88 5 | 99.89 8 | 99.80 27 | 99.67 60 | 99.50 122 | 98.70 63 | 99.77 38 | 99.49 231 | 98.21 89 | 99.95 48 | 98.46 153 | 99.77 93 | 99.88 12 |
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 |
MVS_Test | | | 99.10 88 | 98.97 87 | 99.48 102 | 99.49 167 | 99.14 117 | 99.67 60 | 99.34 234 | 97.31 208 | 99.58 94 | 99.76 119 | 97.65 106 | 99.82 152 | 98.87 89 | 99.07 164 | 99.46 167 |
|
CP-MVSNet | | | 98.09 185 | 97.78 207 | 99.01 166 | 98.97 285 | 99.24 103 | 99.67 60 | 99.46 169 | 97.25 213 | 98.48 288 | 99.64 176 | 93.79 242 | 99.06 311 | 98.63 126 | 94.10 324 | 98.74 237 |
|
MTAPA | | | 99.52 10 | 99.39 19 | 99.89 4 | 99.90 4 | 99.86 13 | 99.66 65 | 99.47 160 | 98.79 58 | 99.68 60 | 99.81 76 | 98.43 78 | 99.97 14 | 98.88 86 | 99.90 25 | 99.83 35 |
|
HFP-MVS | | | 99.49 14 | 99.37 22 | 99.86 20 | 99.87 15 | 99.80 27 | 99.66 65 | 99.67 22 | 98.15 117 | 99.68 60 | 99.69 152 | 99.06 16 | 99.96 22 | 98.69 119 | 99.87 40 | 99.84 26 |
|
mvs_tets | | | 98.40 159 | 98.23 161 | 98.91 186 | 98.67 322 | 98.51 195 | 99.66 65 | 99.53 84 | 98.19 111 | 98.65 274 | 99.81 76 | 92.75 260 | 99.44 244 | 99.31 42 | 97.48 246 | 98.77 230 |
|
EU-MVSNet | | | 97.98 205 | 98.03 181 | 97.81 297 | 98.72 316 | 96.65 286 | 99.66 65 | 99.66 26 | 98.09 126 | 98.35 295 | 99.82 63 | 95.25 187 | 98.01 352 | 97.41 243 | 95.30 303 | 98.78 227 |
|
ACMMPR | | | 99.49 14 | 99.36 24 | 99.86 20 | 99.87 15 | 99.79 30 | 99.66 65 | 99.67 22 | 98.15 117 | 99.67 64 | 99.69 152 | 98.95 27 | 99.96 22 | 98.69 119 | 99.87 40 | 99.84 26 |
|
MP-MVS |  | | 99.33 48 | 99.15 61 | 99.87 11 | 99.88 11 | 99.82 22 | 99.66 65 | 99.46 169 | 98.09 126 | 99.48 114 | 99.74 127 | 98.29 86 | 99.96 22 | 97.93 192 | 99.87 40 | 99.82 40 |
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
region2R | | | 99.48 18 | 99.35 26 | 99.87 11 | 99.88 11 | 99.80 27 | 99.65 71 | 99.66 26 | 98.13 120 | 99.66 69 | 99.68 158 | 98.96 24 | 99.96 22 | 98.62 127 | 99.87 40 | 99.84 26 |
|
TranMVSNet+NR-MVSNet | | | 97.93 211 | 97.66 222 | 98.76 216 | 98.78 308 | 98.62 181 | 99.65 71 | 99.49 130 | 97.76 163 | 98.49 287 | 99.60 194 | 94.23 227 | 98.97 329 | 98.00 188 | 92.90 336 | 98.70 247 |
|
mvsany_test3 | | | 93.77 323 | 93.45 325 | 94.74 337 | 95.78 363 | 88.01 362 | 99.64 73 | 98.25 348 | 98.28 97 | 94.31 353 | 97.97 351 | 68.89 366 | 98.51 343 | 97.50 234 | 90.37 350 | 97.71 349 |
|
ZNCC-MVS | | | 99.47 21 | 99.33 30 | 99.87 11 | 99.87 15 | 99.81 25 | 99.64 73 | 99.67 22 | 98.08 130 | 99.55 102 | 99.64 176 | 98.91 34 | 99.96 22 | 98.72 114 | 99.90 25 | 99.82 40 |
|
tfpnnormal | | | 97.84 226 | 97.47 240 | 98.98 172 | 99.20 240 | 99.22 105 | 99.64 73 | 99.61 36 | 96.32 285 | 98.27 300 | 99.70 142 | 93.35 249 | 99.44 244 | 95.69 305 | 95.40 301 | 98.27 326 |
|
casdiffmvs_mvg |  | | 99.15 71 | 99.02 78 | 99.55 81 | 99.66 108 | 99.09 122 | 99.64 73 | 99.56 57 | 98.26 100 | 99.45 118 | 99.87 32 | 96.03 155 | 99.81 157 | 99.54 15 | 99.15 155 | 99.73 83 |
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025 |
iter_conf_final | | | 98.71 134 | 98.61 138 | 98.99 170 | 99.49 167 | 98.96 143 | 99.63 77 | 99.41 199 | 98.19 111 | 99.39 139 | 99.77 113 | 94.82 199 | 99.38 253 | 99.30 45 | 97.52 238 | 98.64 275 |
|
SR-MVS-dyc-post | | | 99.45 25 | 99.31 38 | 99.85 25 | 99.76 56 | 99.82 22 | 99.63 77 | 99.52 89 | 98.38 86 | 99.76 43 | 99.82 63 | 98.53 71 | 99.95 48 | 98.61 130 | 99.81 79 | 99.77 68 |
|
RE-MVS-def | | | | 99.34 28 | | 99.76 56 | 99.82 22 | 99.63 77 | 99.52 89 | 98.38 86 | 99.76 43 | 99.82 63 | 98.75 54 | | 98.61 130 | 99.81 79 | 99.77 68 |
|
TSAR-MVS + MP. | | | 99.58 4 | 99.50 8 | 99.81 36 | 99.91 1 | 99.66 53 | 99.63 77 | 99.39 210 | 98.91 46 | 99.78 35 | 99.85 42 | 99.36 2 | 99.94 57 | 98.84 99 | 99.88 37 | 99.82 40 |
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition |
Anonymous20231206 | | | 96.22 297 | 96.03 297 | 96.79 327 | 97.31 354 | 94.14 339 | 99.63 77 | 99.08 292 | 96.17 297 | 97.04 334 | 99.06 313 | 93.94 237 | 97.76 358 | 86.96 365 | 95.06 308 | 98.47 309 |
|
APD-MVS_3200maxsize | | | 99.48 18 | 99.35 26 | 99.85 25 | 99.76 56 | 99.83 16 | 99.63 77 | 99.54 73 | 98.36 90 | 99.79 30 | 99.82 63 | 98.86 38 | 99.95 48 | 98.62 127 | 99.81 79 | 99.78 66 |
|
test0726 | | | | | | 99.85 25 | 99.89 4 | 99.62 83 | 99.50 122 | 99.10 16 | 99.86 16 | 99.82 63 | 98.94 29 | | | | |
|
EPNet | | | 98.86 113 | 98.71 117 | 99.30 133 | 97.20 356 | 98.18 212 | 99.62 83 | 98.91 313 | 99.28 6 | 98.63 276 | 99.81 76 | 95.96 157 | 99.99 2 | 99.24 52 | 99.72 104 | 99.73 83 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
114514_t | | | 98.93 105 | 98.67 121 | 99.72 52 | 99.85 25 | 99.53 73 | 99.62 83 | 99.59 44 | 92.65 348 | 99.71 54 | 99.78 106 | 98.06 96 | 99.90 101 | 98.84 99 | 99.91 18 | 99.74 78 |
|
HY-MVS | | 97.30 7 | 98.85 120 | 98.64 126 | 99.47 105 | 99.42 185 | 99.08 125 | 99.62 83 | 99.36 225 | 97.39 203 | 99.28 164 | 99.68 158 | 96.44 144 | 99.92 80 | 98.37 159 | 98.22 208 | 99.40 176 |
|
ACMMP |  | | 99.45 25 | 99.32 32 | 99.82 33 | 99.89 8 | 99.67 51 | 99.62 83 | 99.69 18 | 98.12 121 | 99.63 80 | 99.84 52 | 98.73 57 | 99.96 22 | 98.55 145 | 99.83 72 | 99.81 47 |
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 |
DeepC-MVS | | 98.35 2 | 99.30 51 | 99.19 58 | 99.64 64 | 99.82 37 | 99.23 104 | 99.62 83 | 99.55 65 | 98.94 42 | 99.63 80 | 99.95 2 | 95.82 166 | 99.94 57 | 99.37 34 | 99.97 5 | 99.73 83 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
EI-MVSNet-Vis-set | | | 99.58 4 | 99.56 5 | 99.64 64 | 99.78 47 | 99.15 116 | 99.61 89 | 99.45 180 | 99.01 28 | 99.89 10 | 99.82 63 | 99.01 18 | 99.92 80 | 99.56 14 | 99.95 8 | 99.85 22 |
|
test2506 | | | 96.81 287 | 96.65 285 | 97.29 314 | 99.74 71 | 92.21 355 | 99.60 90 | 85.06 382 | 99.13 12 | 99.77 38 | 99.93 6 | 87.82 340 | 99.85 129 | 99.38 32 | 99.38 135 | 99.80 56 |
|
SED-MVS | | | 99.61 2 | 99.52 6 | 99.88 5 | 99.84 31 | 99.90 2 | 99.60 90 | 99.48 142 | 99.08 21 | 99.91 7 | 99.81 76 | 99.20 7 | 99.96 22 | 98.91 83 | 99.85 55 | 99.79 60 |
|
OPU-MVS | | | | | 99.64 64 | 99.56 144 | 99.72 42 | 99.60 90 | | | | 99.70 142 | 99.27 5 | 99.42 249 | 98.24 169 | 99.80 83 | 99.79 60 |
|
GST-MVS | | | 99.40 41 | 99.24 53 | 99.85 25 | 99.86 20 | 99.79 30 | 99.60 90 | 99.67 22 | 97.97 142 | 99.63 80 | 99.68 158 | 98.52 72 | 99.95 48 | 98.38 157 | 99.86 48 | 99.81 47 |
|
EI-MVSNet-UG-set | | | 99.58 4 | 99.57 3 | 99.64 64 | 99.78 47 | 99.14 117 | 99.60 90 | 99.45 180 | 99.01 28 | 99.90 9 | 99.83 56 | 98.98 23 | 99.93 70 | 99.59 11 | 99.95 8 | 99.86 19 |
|
ACMH | | 97.28 8 | 98.10 184 | 97.99 185 | 98.44 249 | 99.41 188 | 96.96 275 | 99.60 90 | 99.56 57 | 98.09 126 | 98.15 304 | 99.91 11 | 90.87 306 | 99.70 202 | 98.88 86 | 97.45 248 | 98.67 263 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
ECVR-MVS |  | | 98.04 194 | 98.05 179 | 98.00 284 | 99.74 71 | 94.37 336 | 99.59 96 | 94.98 372 | 99.13 12 | 99.66 69 | 99.93 6 | 90.67 308 | 99.84 135 | 99.40 31 | 99.38 135 | 99.80 56 |
|
SR-MVS | | | 99.43 32 | 99.29 44 | 99.86 20 | 99.75 64 | 99.83 16 | 99.59 96 | 99.62 33 | 98.21 108 | 99.73 48 | 99.79 100 | 98.68 61 | 99.96 22 | 98.44 154 | 99.77 93 | 99.79 60 |
|
thres100view900 | | | 97.76 238 | 97.45 243 | 98.69 220 | 99.72 82 | 97.86 233 | 99.59 96 | 98.74 331 | 97.93 145 | 99.26 172 | 98.62 337 | 91.75 288 | 99.83 146 | 93.22 338 | 98.18 213 | 98.37 322 |
|
thres600view7 | | | 97.86 222 | 97.51 236 | 98.92 182 | 99.72 82 | 97.95 227 | 99.59 96 | 98.74 331 | 97.94 144 | 99.27 168 | 98.62 337 | 91.75 288 | 99.86 123 | 93.73 333 | 98.19 212 | 98.96 217 |
|
LCM-MVSNet-Re | | | 97.83 228 | 98.15 165 | 96.87 325 | 99.30 216 | 92.25 354 | 99.59 96 | 98.26 347 | 97.43 198 | 96.20 341 | 99.13 306 | 96.27 149 | 98.73 340 | 98.17 175 | 98.99 170 | 99.64 120 |
|
baseline1 | | | 98.31 164 | 97.95 190 | 99.38 119 | 99.50 165 | 98.74 171 | 99.59 96 | 98.93 308 | 98.41 84 | 99.14 195 | 99.60 194 | 94.59 215 | 99.79 166 | 98.48 149 | 93.29 332 | 99.61 127 |
|
SteuartSystems-ACMMP | | | 99.54 8 | 99.42 15 | 99.87 11 | 99.82 37 | 99.81 25 | 99.59 96 | 99.51 103 | 98.62 67 | 99.79 30 | 99.83 56 | 99.28 4 | 99.97 14 | 98.48 149 | 99.90 25 | 99.84 26 |
Skip Steuart: Steuart Systems R&D Blog. |
CPTT-MVS | | | 99.11 85 | 98.90 96 | 99.74 49 | 99.80 44 | 99.46 82 | 99.59 96 | 99.49 130 | 97.03 235 | 99.63 80 | 99.69 152 | 97.27 116 | 99.96 22 | 97.82 202 | 99.84 63 | 99.81 47 |
|
test1111 | | | 98.04 194 | 98.11 170 | 97.83 294 | 99.74 71 | 93.82 341 | 99.58 104 | 95.40 371 | 99.12 14 | 99.65 75 | 99.93 6 | 90.73 307 | 99.84 135 | 99.43 30 | 99.38 135 | 99.82 40 |
|
PGM-MVS | | | 99.45 25 | 99.31 38 | 99.86 20 | 99.87 15 | 99.78 36 | 99.58 104 | 99.65 31 | 97.84 154 | 99.71 54 | 99.80 89 | 99.12 13 | 99.97 14 | 98.33 163 | 99.87 40 | 99.83 35 |
|
LPG-MVS_test | | | 98.22 170 | 98.13 168 | 98.49 238 | 99.33 208 | 97.05 264 | 99.58 104 | 99.55 65 | 97.46 192 | 99.24 174 | 99.83 56 | 92.58 270 | 99.72 190 | 98.09 179 | 97.51 240 | 98.68 256 |
|
PHI-MVS | | | 99.30 51 | 99.17 60 | 99.70 53 | 99.56 144 | 99.52 76 | 99.58 104 | 99.80 8 | 97.12 225 | 99.62 84 | 99.73 133 | 98.58 67 | 99.90 101 | 98.61 130 | 99.91 18 | 99.68 103 |
|
SF-MVS | | | 99.38 43 | 99.24 53 | 99.79 41 | 99.79 45 | 99.68 48 | 99.57 108 | 99.54 73 | 97.82 159 | 99.71 54 | 99.80 89 | 98.95 27 | 99.93 70 | 98.19 172 | 99.84 63 | 99.74 78 |
|
DVP-MVS |  | | 99.57 7 | 99.47 12 | 99.88 5 | 99.85 25 | 99.89 4 | 99.57 108 | 99.37 224 | 99.10 16 | 99.81 25 | 99.80 89 | 98.94 29 | 99.96 22 | 98.93 80 | 99.86 48 | 99.81 47 |
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_SECOND | | | | | 99.91 2 | 99.84 31 | 99.89 4 | 99.57 108 | 99.51 103 | | | | | 99.96 22 | 98.93 80 | 99.86 48 | 99.88 12 |
|
Effi-MVS+-dtu | | | 98.78 128 | 98.89 98 | 98.47 244 | 99.33 208 | 96.91 277 | 99.57 108 | 99.30 259 | 98.47 78 | 99.41 131 | 98.99 320 | 96.78 132 | 99.74 180 | 98.73 113 | 99.38 135 | 98.74 237 |
|
v2v482 | | | 98.06 188 | 97.77 209 | 98.92 182 | 98.90 290 | 98.82 166 | 99.57 108 | 99.36 225 | 96.65 259 | 99.19 188 | 99.35 270 | 94.20 228 | 99.25 282 | 97.72 214 | 94.97 310 | 98.69 251 |
|
DSMNet-mixed | | | 97.25 278 | 97.35 260 | 96.95 323 | 97.84 344 | 93.61 347 | 99.57 108 | 96.63 367 | 96.13 302 | 98.87 241 | 98.61 339 | 94.59 215 | 97.70 359 | 95.08 317 | 98.86 179 | 99.55 140 |
|
KD-MVS_self_test | | | 95.00 313 | 94.34 318 | 96.96 322 | 97.07 359 | 95.39 319 | 99.56 114 | 99.44 188 | 95.11 320 | 97.13 332 | 97.32 357 | 91.86 286 | 97.27 362 | 90.35 354 | 81.23 366 | 98.23 330 |
|
ETV-MVS | | | 99.26 58 | 99.21 56 | 99.40 115 | 99.46 177 | 99.30 96 | 99.56 114 | 99.52 89 | 98.52 75 | 99.44 123 | 99.27 290 | 98.41 81 | 99.86 123 | 99.10 63 | 99.59 122 | 99.04 207 |
|
SMA-MVS |  | | 99.44 29 | 99.30 40 | 99.85 25 | 99.73 78 | 99.83 16 | 99.56 114 | 99.47 160 | 97.45 195 | 99.78 35 | 99.82 63 | 99.18 10 | 99.91 90 | 98.79 107 | 99.89 34 | 99.81 47 |
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 |
AllTest | | | 98.87 110 | 98.72 115 | 99.31 128 | 99.86 20 | 98.48 199 | 99.56 114 | 99.61 36 | 97.85 152 | 99.36 148 | 99.85 42 | 95.95 158 | 99.85 129 | 96.66 285 | 99.83 72 | 99.59 133 |
|
casdiffmvs |  | | 99.13 75 | 98.98 86 | 99.56 79 | 99.65 114 | 99.16 111 | 99.56 114 | 99.50 122 | 98.33 94 | 99.41 131 | 99.86 37 | 95.92 161 | 99.83 146 | 99.45 29 | 99.16 152 | 99.70 97 |
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025 |
XXY-MVS | | | 98.38 160 | 98.09 174 | 99.24 143 | 99.26 227 | 99.32 92 | 99.56 114 | 99.55 65 | 97.45 195 | 98.71 259 | 99.83 56 | 93.23 250 | 99.63 225 | 98.88 86 | 96.32 278 | 98.76 232 |
|
ACMH+ | | 97.24 10 | 97.92 214 | 97.78 207 | 98.32 260 | 99.46 177 | 96.68 285 | 99.56 114 | 99.54 73 | 98.41 84 | 97.79 319 | 99.87 32 | 90.18 315 | 99.66 212 | 98.05 187 | 97.18 263 | 98.62 286 |
|
ACMM | | 97.58 5 | 98.37 161 | 98.34 154 | 98.48 240 | 99.41 188 | 97.10 258 | 99.56 114 | 99.45 180 | 98.53 74 | 99.04 214 | 99.85 42 | 93.00 254 | 99.71 196 | 98.74 111 | 97.45 248 | 98.64 275 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
LS3D | | | 99.27 56 | 99.12 64 | 99.74 49 | 99.18 245 | 99.75 39 | 99.56 114 | 99.57 52 | 98.45 80 | 99.49 113 | 99.85 42 | 97.77 103 | 99.94 57 | 98.33 163 | 99.84 63 | 99.52 148 |
|
test_fmvs1 | | | 98.88 109 | 98.79 111 | 99.16 151 | 99.69 95 | 97.61 243 | 99.55 123 | 99.49 130 | 99.32 4 | 99.98 4 | 99.91 11 | 91.41 298 | 99.96 22 | 99.82 3 | 99.92 13 | 99.90 4 |
|
v144192 | | | 97.92 214 | 97.60 228 | 98.87 197 | 98.83 303 | 98.65 178 | 99.55 123 | 99.34 234 | 96.20 294 | 99.32 156 | 99.40 256 | 94.36 223 | 99.26 281 | 96.37 293 | 95.03 309 | 98.70 247 |
|
iter_conf05 | | | 98.55 147 | 98.44 147 | 98.87 197 | 99.34 206 | 98.60 184 | 99.55 123 | 99.42 196 | 98.21 108 | 99.37 144 | 99.77 113 | 93.55 246 | 99.38 253 | 99.30 45 | 97.48 246 | 98.63 283 |
|
API-MVS | | | 99.04 94 | 99.03 75 | 99.06 160 | 99.40 193 | 99.31 95 | 99.55 123 | 99.56 57 | 98.54 73 | 99.33 155 | 99.39 260 | 98.76 51 | 99.78 171 | 96.98 267 | 99.78 90 | 98.07 335 |
|
APD_test1 | | | 95.87 304 | 96.49 289 | 94.00 338 | 99.53 150 | 84.01 365 | 99.54 127 | 99.32 251 | 95.91 310 | 97.99 311 | 99.85 42 | 85.49 348 | 99.88 116 | 91.96 348 | 98.84 181 | 98.12 333 |
|
thisisatest0530 | | | 98.35 162 | 98.03 181 | 99.31 128 | 99.63 119 | 98.56 186 | 99.54 127 | 96.75 365 | 97.53 188 | 99.73 48 | 99.65 170 | 91.25 302 | 99.89 111 | 98.62 127 | 99.56 124 | 99.48 159 |
|
MTMP | | | | | | | | 99.54 127 | 98.88 317 | | | | | | | | |
|
v1144 | | | 97.98 205 | 97.69 219 | 98.85 204 | 98.87 297 | 98.66 177 | 99.54 127 | 99.35 230 | 96.27 289 | 99.23 178 | 99.35 270 | 94.67 212 | 99.23 285 | 96.73 280 | 95.16 306 | 98.68 256 |
|
v148 | | | 97.79 236 | 97.55 230 | 98.50 237 | 98.74 313 | 97.72 238 | 99.54 127 | 99.33 241 | 96.26 290 | 98.90 235 | 99.51 225 | 94.68 211 | 99.14 298 | 97.83 201 | 93.15 335 | 98.63 283 |
|
CostFormer | | | 97.72 247 | 97.73 216 | 97.71 301 | 99.15 256 | 94.02 340 | 99.54 127 | 99.02 299 | 94.67 329 | 99.04 214 | 99.35 270 | 92.35 280 | 99.77 173 | 98.50 148 | 97.94 221 | 99.34 182 |
|
MVSTER | | | 98.49 148 | 98.32 156 | 99.00 168 | 99.35 202 | 99.02 132 | 99.54 127 | 99.38 216 | 97.41 201 | 99.20 185 | 99.73 133 | 93.86 240 | 99.36 262 | 98.87 89 | 97.56 235 | 98.62 286 |
|
patch_mono-2 | | | 99.26 58 | 99.62 1 | 98.16 272 | 99.81 41 | 94.59 333 | 99.52 134 | 99.64 32 | 99.33 3 | 99.73 48 | 99.90 16 | 99.00 22 | 99.99 2 | 99.69 6 | 99.98 2 | 99.89 6 |
|
Fast-Effi-MVS+-dtu | | | 98.77 130 | 98.83 107 | 98.60 224 | 99.41 188 | 96.99 271 | 99.52 134 | 99.49 130 | 98.11 123 | 99.24 174 | 99.34 273 | 96.96 128 | 99.79 166 | 97.95 191 | 99.45 131 | 99.02 210 |
|
Fast-Effi-MVS+ | | | 98.70 135 | 98.43 148 | 99.51 98 | 99.51 156 | 99.28 98 | 99.52 134 | 99.47 160 | 96.11 303 | 99.01 217 | 99.34 273 | 96.20 151 | 99.84 135 | 97.88 195 | 98.82 183 | 99.39 177 |
|
v1921920 | | | 97.80 235 | 97.45 243 | 98.84 205 | 98.80 304 | 98.53 189 | 99.52 134 | 99.34 234 | 96.15 300 | 99.24 174 | 99.47 239 | 93.98 236 | 99.29 276 | 95.40 312 | 95.13 307 | 98.69 251 |
|
MIMVSNet1 | | | 95.51 308 | 95.04 312 | 96.92 324 | 97.38 351 | 95.60 310 | 99.52 134 | 99.50 122 | 93.65 339 | 96.97 336 | 99.17 301 | 85.28 350 | 96.56 367 | 88.36 361 | 95.55 298 | 98.60 298 |
|
UniMVSNet_ETH3D | | | 97.32 276 | 96.81 283 | 98.87 197 | 99.40 193 | 97.46 246 | 99.51 139 | 99.53 84 | 95.86 311 | 98.54 284 | 99.77 113 | 82.44 358 | 99.66 212 | 98.68 121 | 97.52 238 | 99.50 157 |
|
alignmvs | | | 98.81 124 | 98.56 142 | 99.58 75 | 99.43 183 | 99.42 85 | 99.51 139 | 98.96 306 | 98.61 68 | 99.35 151 | 98.92 328 | 94.78 203 | 99.77 173 | 99.35 35 | 98.11 218 | 99.54 142 |
|
v1192 | | | 97.81 233 | 97.44 248 | 98.91 186 | 98.88 293 | 98.68 175 | 99.51 139 | 99.34 234 | 96.18 296 | 99.20 185 | 99.34 273 | 94.03 235 | 99.36 262 | 95.32 314 | 95.18 305 | 98.69 251 |
|
test20.03 | | | 96.12 301 | 95.96 299 | 96.63 328 | 97.44 350 | 95.45 317 | 99.51 139 | 99.38 216 | 96.55 269 | 96.16 342 | 99.25 293 | 93.76 244 | 96.17 368 | 87.35 364 | 94.22 322 | 98.27 326 |
|
mvs_anonymous | | | 99.03 96 | 98.99 83 | 99.16 151 | 99.38 197 | 98.52 193 | 99.51 139 | 99.38 216 | 97.79 160 | 99.38 142 | 99.81 76 | 97.30 114 | 99.45 239 | 99.35 35 | 98.99 170 | 99.51 154 |
|
TAMVS | | | 99.12 81 | 99.08 69 | 99.24 143 | 99.46 177 | 98.55 187 | 99.51 139 | 99.46 169 | 98.09 126 | 99.45 118 | 99.82 63 | 98.34 84 | 99.51 235 | 98.70 116 | 98.93 173 | 99.67 106 |
|
test_yl | | | 98.86 113 | 98.63 127 | 99.54 82 | 99.49 167 | 99.18 108 | 99.50 145 | 99.07 295 | 98.22 106 | 99.61 87 | 99.51 225 | 95.37 180 | 99.84 135 | 98.60 133 | 98.33 202 | 99.59 133 |
|
DCV-MVSNet | | | 98.86 113 | 98.63 127 | 99.54 82 | 99.49 167 | 99.18 108 | 99.50 145 | 99.07 295 | 98.22 106 | 99.61 87 | 99.51 225 | 95.37 180 | 99.84 135 | 98.60 133 | 98.33 202 | 99.59 133 |
|
tfpn200view9 | | | 97.72 247 | 97.38 256 | 98.72 218 | 99.69 95 | 97.96 225 | 99.50 145 | 98.73 336 | 97.83 155 | 99.17 192 | 98.45 342 | 91.67 292 | 99.83 146 | 93.22 338 | 98.18 213 | 98.37 322 |
|
UA-Net | | | 99.42 34 | 99.29 44 | 99.80 38 | 99.62 125 | 99.55 68 | 99.50 145 | 99.70 15 | 98.79 58 | 99.77 38 | 99.96 1 | 97.45 109 | 99.96 22 | 98.92 82 | 99.90 25 | 99.89 6 |
|
pm-mvs1 | | | 97.68 254 | 97.28 270 | 98.88 193 | 99.06 271 | 98.62 181 | 99.50 145 | 99.45 180 | 96.32 285 | 97.87 315 | 99.79 100 | 92.47 274 | 99.35 265 | 97.54 231 | 93.54 330 | 98.67 263 |
|
EI-MVSNet | | | 98.67 140 | 98.67 121 | 98.68 221 | 99.35 202 | 97.97 223 | 99.50 145 | 99.38 216 | 96.93 244 | 99.20 185 | 99.83 56 | 97.87 99 | 99.36 262 | 98.38 157 | 97.56 235 | 98.71 242 |
|
CVMVSNet | | | 98.57 146 | 98.67 121 | 98.30 262 | 99.35 202 | 95.59 311 | 99.50 145 | 99.55 65 | 98.60 69 | 99.39 139 | 99.83 56 | 94.48 220 | 99.45 239 | 98.75 110 | 98.56 195 | 99.85 22 |
|
VPA-MVSNet | | | 98.29 167 | 97.95 190 | 99.30 133 | 99.16 253 | 99.54 70 | 99.50 145 | 99.58 49 | 98.27 99 | 99.35 151 | 99.37 264 | 92.53 272 | 99.65 217 | 99.35 35 | 94.46 317 | 98.72 240 |
|
thres400 | | | 97.77 237 | 97.38 256 | 98.92 182 | 99.69 95 | 97.96 225 | 99.50 145 | 98.73 336 | 97.83 155 | 99.17 192 | 98.45 342 | 91.67 292 | 99.83 146 | 93.22 338 | 98.18 213 | 98.96 217 |
|
APD-MVS |  | | 99.27 56 | 99.08 69 | 99.84 31 | 99.75 64 | 99.79 30 | 99.50 145 | 99.50 122 | 97.16 221 | 99.77 38 | 99.82 63 | 98.78 47 | 99.94 57 | 97.56 229 | 99.86 48 | 99.80 56 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
test_vis1_rt | | | 95.81 306 | 95.65 305 | 96.32 332 | 99.67 100 | 91.35 358 | 99.49 155 | 96.74 366 | 98.25 101 | 95.24 347 | 98.10 349 | 74.96 363 | 99.90 101 | 99.53 16 | 98.85 180 | 97.70 351 |
|
TransMVSNet (Re) | | | 97.15 281 | 96.58 286 | 98.86 201 | 99.12 258 | 98.85 161 | 99.49 155 | 98.91 313 | 95.48 315 | 97.16 331 | 99.80 89 | 93.38 248 | 99.11 306 | 94.16 330 | 91.73 343 | 98.62 286 |
|
UniMVSNet (Re) | | | 98.29 167 | 98.00 184 | 99.13 155 | 99.00 279 | 99.36 90 | 99.49 155 | 99.51 103 | 97.95 143 | 98.97 225 | 99.13 306 | 96.30 148 | 99.38 253 | 98.36 161 | 93.34 331 | 98.66 271 |
|
EPMVS | | | 97.82 231 | 97.65 223 | 98.35 257 | 98.88 293 | 95.98 304 | 99.49 155 | 94.71 374 | 97.57 182 | 99.26 172 | 99.48 236 | 92.46 277 | 99.71 196 | 97.87 197 | 99.08 163 | 99.35 180 |
|
Anonymous20231211 | | | 97.88 218 | 97.54 233 | 98.90 188 | 99.71 87 | 98.53 189 | 99.48 159 | 99.57 52 | 94.16 334 | 98.81 248 | 99.68 158 | 93.23 250 | 99.42 249 | 98.84 99 | 94.42 319 | 98.76 232 |
|
v1240 | | | 97.69 252 | 97.32 266 | 98.79 213 | 98.85 301 | 98.43 203 | 99.48 159 | 99.36 225 | 96.11 303 | 99.27 168 | 99.36 267 | 93.76 244 | 99.24 284 | 94.46 324 | 95.23 304 | 98.70 247 |
|
VPNet | | | 97.84 226 | 97.44 248 | 99.01 166 | 99.21 238 | 98.94 151 | 99.48 159 | 99.57 52 | 98.38 86 | 99.28 164 | 99.73 133 | 88.89 325 | 99.39 251 | 99.19 55 | 93.27 333 | 98.71 242 |
|
UniMVSNet_NR-MVSNet | | | 98.22 170 | 97.97 187 | 98.96 175 | 98.92 289 | 98.98 136 | 99.48 159 | 99.53 84 | 97.76 163 | 98.71 259 | 99.46 243 | 96.43 145 | 99.22 288 | 98.57 139 | 92.87 338 | 98.69 251 |
|
TDRefinement | | | 95.42 310 | 94.57 316 | 97.97 286 | 89.83 375 | 96.11 303 | 99.48 159 | 98.75 328 | 96.74 252 | 96.68 337 | 99.88 26 | 88.65 329 | 99.71 196 | 98.37 159 | 82.74 364 | 98.09 334 |
|
ACMMP_NAP | | | 99.47 21 | 99.34 28 | 99.88 5 | 99.87 15 | 99.86 13 | 99.47 164 | 99.48 142 | 98.05 136 | 99.76 43 | 99.86 37 | 98.82 43 | 99.93 70 | 98.82 106 | 99.91 18 | 99.84 26 |
|
NR-MVSNet | | | 97.97 208 | 97.61 227 | 99.02 165 | 98.87 297 | 99.26 101 | 99.47 164 | 99.42 196 | 97.63 177 | 97.08 333 | 99.50 228 | 95.07 191 | 99.13 301 | 97.86 198 | 93.59 329 | 98.68 256 |
|
PVSNet_Blended_VisFu | | | 99.36 45 | 99.28 46 | 99.61 70 | 99.86 20 | 99.07 127 | 99.47 164 | 99.93 2 | 97.66 175 | 99.71 54 | 99.86 37 | 97.73 104 | 99.96 22 | 99.47 27 | 99.82 76 | 99.79 60 |
|
SD-MVS | | | 99.41 38 | 99.52 6 | 99.05 162 | 99.74 71 | 99.68 48 | 99.46 167 | 99.52 89 | 99.11 15 | 99.88 11 | 99.91 11 | 99.43 1 | 97.70 359 | 98.72 114 | 99.93 12 | 99.77 68 |
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 |
tt0805 | | | 97.97 208 | 97.77 209 | 98.57 229 | 99.59 136 | 96.61 288 | 99.45 168 | 99.08 292 | 98.21 108 | 98.88 238 | 99.80 89 | 88.66 328 | 99.70 202 | 98.58 136 | 97.72 226 | 99.39 177 |
|
tpm2 | | | 97.44 273 | 97.34 263 | 97.74 300 | 99.15 256 | 94.36 337 | 99.45 168 | 98.94 307 | 93.45 343 | 98.90 235 | 99.44 245 | 91.35 300 | 99.59 229 | 97.31 246 | 98.07 219 | 99.29 186 |
|
FMVSNet2 | | | 97.72 247 | 97.36 258 | 98.80 212 | 99.51 156 | 98.84 162 | 99.45 168 | 99.42 196 | 96.49 272 | 98.86 245 | 99.29 285 | 90.26 311 | 98.98 322 | 96.44 290 | 96.56 272 | 98.58 300 |
|
CDS-MVSNet | | | 99.09 89 | 99.03 75 | 99.25 141 | 99.42 185 | 98.73 172 | 99.45 168 | 99.46 169 | 98.11 123 | 99.46 117 | 99.77 113 | 98.01 97 | 99.37 258 | 98.70 116 | 98.92 175 | 99.66 109 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
MAR-MVS | | | 98.86 113 | 98.63 127 | 99.54 82 | 99.37 199 | 99.66 53 | 99.45 168 | 99.54 73 | 96.61 264 | 99.01 217 | 99.40 256 | 97.09 121 | 99.86 123 | 97.68 219 | 99.53 127 | 99.10 195 |
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 |
UGNet | | | 98.87 110 | 98.69 119 | 99.40 115 | 99.22 236 | 98.72 173 | 99.44 173 | 99.68 19 | 99.24 7 | 99.18 191 | 99.42 249 | 92.74 262 | 99.96 22 | 99.34 39 | 99.94 11 | 99.53 147 |
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 |
ab-mvs | | | 98.86 113 | 98.63 127 | 99.54 82 | 99.64 116 | 99.19 106 | 99.44 173 | 99.54 73 | 97.77 162 | 99.30 160 | 99.81 76 | 94.20 228 | 99.93 70 | 99.17 58 | 98.82 183 | 99.49 158 |
|
test_0402 | | | 96.64 290 | 96.24 293 | 97.85 292 | 98.85 301 | 96.43 294 | 99.44 173 | 99.26 268 | 93.52 340 | 96.98 335 | 99.52 222 | 88.52 331 | 99.20 295 | 92.58 347 | 97.50 242 | 97.93 346 |
|
ACMP | | 97.20 11 | 98.06 188 | 97.94 192 | 98.45 246 | 99.37 199 | 97.01 269 | 99.44 173 | 99.49 130 | 97.54 187 | 98.45 289 | 99.79 100 | 91.95 284 | 99.72 190 | 97.91 193 | 97.49 245 | 98.62 286 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
GG-mvs-BLEND | | | | | 98.45 246 | 98.55 332 | 98.16 213 | 99.43 177 | 93.68 376 | | 97.23 328 | 98.46 341 | 89.30 322 | 99.22 288 | 95.43 311 | 98.22 208 | 97.98 343 |
|
HPM-MVS++ |  | | 99.39 42 | 99.23 55 | 99.87 11 | 99.75 64 | 99.84 15 | 99.43 177 | 99.51 103 | 98.68 65 | 99.27 168 | 99.53 219 | 98.64 66 | 99.96 22 | 98.44 154 | 99.80 83 | 99.79 60 |
|
tpm cat1 | | | 97.39 274 | 97.36 258 | 97.50 309 | 99.17 251 | 93.73 343 | 99.43 177 | 99.31 255 | 91.27 352 | 98.71 259 | 99.08 310 | 94.31 226 | 99.77 173 | 96.41 292 | 98.50 198 | 99.00 211 |
|
tpm | | | 97.67 257 | 97.55 230 | 98.03 279 | 99.02 277 | 95.01 326 | 99.43 177 | 98.54 344 | 96.44 279 | 99.12 198 | 99.34 273 | 91.83 287 | 99.60 228 | 97.75 210 | 96.46 274 | 99.48 159 |
|
GBi-Net | | | 97.68 254 | 97.48 238 | 98.29 263 | 99.51 156 | 97.26 253 | 99.43 177 | 99.48 142 | 96.49 272 | 99.07 208 | 99.32 280 | 90.26 311 | 98.98 322 | 97.10 260 | 96.65 269 | 98.62 286 |
|
test1 | | | 97.68 254 | 97.48 238 | 98.29 263 | 99.51 156 | 97.26 253 | 99.43 177 | 99.48 142 | 96.49 272 | 99.07 208 | 99.32 280 | 90.26 311 | 98.98 322 | 97.10 260 | 96.65 269 | 98.62 286 |
|
FMVSNet1 | | | 96.84 286 | 96.36 291 | 98.29 263 | 99.32 214 | 97.26 253 | 99.43 177 | 99.48 142 | 95.11 320 | 98.55 283 | 99.32 280 | 83.95 354 | 98.98 322 | 95.81 301 | 96.26 279 | 98.62 286 |
|
testgi | | | 97.65 259 | 97.50 237 | 98.13 276 | 99.36 201 | 96.45 293 | 99.42 184 | 99.48 142 | 97.76 163 | 97.87 315 | 99.45 244 | 91.09 303 | 98.81 336 | 94.53 323 | 98.52 197 | 99.13 194 |
|
F-COLMAP | | | 99.19 64 | 99.04 73 | 99.64 64 | 99.78 47 | 99.27 100 | 99.42 184 | 99.54 73 | 97.29 210 | 99.41 131 | 99.59 196 | 98.42 80 | 99.93 70 | 98.19 172 | 99.69 109 | 99.73 83 |
|
Anonymous202405211 | | | 98.30 166 | 97.98 186 | 99.26 140 | 99.57 140 | 98.16 213 | 99.41 186 | 98.55 343 | 96.03 308 | 99.19 188 | 99.74 127 | 91.87 285 | 99.92 80 | 99.16 59 | 98.29 207 | 99.70 97 |
|
MSLP-MVS++ | | | 99.46 23 | 99.47 12 | 99.44 112 | 99.60 134 | 99.16 111 | 99.41 186 | 99.71 13 | 98.98 36 | 99.45 118 | 99.78 106 | 99.19 9 | 99.54 234 | 99.28 47 | 99.84 63 | 99.63 123 |
|
VNet | | | 99.11 85 | 98.90 96 | 99.73 51 | 99.52 154 | 99.56 66 | 99.41 186 | 99.39 210 | 99.01 28 | 99.74 47 | 99.78 106 | 95.56 174 | 99.92 80 | 99.52 18 | 98.18 213 | 99.72 89 |
|
baseline2 | | | 97.87 220 | 97.55 230 | 98.82 208 | 99.18 245 | 98.02 220 | 99.41 186 | 96.58 368 | 96.97 238 | 96.51 338 | 99.17 301 | 93.43 247 | 99.57 230 | 97.71 215 | 99.03 167 | 98.86 221 |
|
DU-MVS | | | 98.08 187 | 97.79 204 | 98.96 175 | 98.87 297 | 98.98 136 | 99.41 186 | 99.45 180 | 97.87 149 | 98.71 259 | 99.50 228 | 94.82 199 | 99.22 288 | 98.57 139 | 92.87 338 | 98.68 256 |
|
Baseline_NR-MVSNet | | | 97.76 238 | 97.45 243 | 98.68 221 | 99.09 265 | 98.29 208 | 99.41 186 | 98.85 320 | 95.65 313 | 98.63 276 | 99.67 164 | 94.82 199 | 99.10 308 | 98.07 186 | 92.89 337 | 98.64 275 |
|
XVG-ACMP-BASELINE | | | 97.83 228 | 97.71 218 | 98.20 269 | 99.11 260 | 96.33 297 | 99.41 186 | 99.52 89 | 98.06 135 | 99.05 213 | 99.50 228 | 89.64 320 | 99.73 186 | 97.73 212 | 97.38 256 | 98.53 303 |
|
DP-MVS | | | 99.16 70 | 98.95 91 | 99.78 43 | 99.77 53 | 99.53 73 | 99.41 186 | 99.50 122 | 97.03 235 | 99.04 214 | 99.88 26 | 97.39 110 | 99.92 80 | 98.66 123 | 99.90 25 | 99.87 17 |
|
9.14 | | | | 99.10 66 | | 99.72 82 | | 99.40 194 | 99.51 103 | 97.53 188 | 99.64 79 | 99.78 106 | 98.84 41 | 99.91 90 | 97.63 220 | 99.82 76 | |
|
D2MVS | | | 98.41 156 | 98.50 145 | 98.15 275 | 99.26 227 | 96.62 287 | 99.40 194 | 99.61 36 | 97.71 169 | 98.98 223 | 99.36 267 | 96.04 154 | 99.67 209 | 98.70 116 | 97.41 253 | 98.15 332 |
|
Anonymous20240529 | | | 98.09 185 | 97.68 220 | 99.34 121 | 99.66 108 | 98.44 202 | 99.40 194 | 99.43 194 | 93.67 338 | 99.22 179 | 99.89 20 | 90.23 314 | 99.93 70 | 99.26 51 | 98.33 202 | 99.66 109 |
|
FMVSNet3 | | | 98.03 196 | 97.76 213 | 98.84 205 | 99.39 196 | 98.98 136 | 99.40 194 | 99.38 216 | 96.67 257 | 99.07 208 | 99.28 287 | 92.93 255 | 98.98 322 | 97.10 260 | 96.65 269 | 98.56 302 |
|
LFMVS | | | 97.90 217 | 97.35 260 | 99.54 82 | 99.52 154 | 99.01 134 | 99.39 198 | 98.24 349 | 97.10 229 | 99.65 75 | 99.79 100 | 84.79 351 | 99.91 90 | 99.28 47 | 98.38 201 | 99.69 99 |
|
HQP_MVS | | | 98.27 169 | 98.22 162 | 98.44 249 | 99.29 220 | 96.97 273 | 99.39 198 | 99.47 160 | 98.97 39 | 99.11 200 | 99.61 191 | 92.71 265 | 99.69 207 | 97.78 205 | 97.63 228 | 98.67 263 |
|
plane_prior2 | | | | | | | | 99.39 198 | | 98.97 39 | | | | | | | |
|
CHOSEN 1792x2688 | | | 99.19 64 | 99.10 66 | 99.45 108 | 99.89 8 | 98.52 193 | 99.39 198 | 99.94 1 | 98.73 61 | 99.11 200 | 99.89 20 | 95.50 176 | 99.94 57 | 99.50 20 | 99.97 5 | 99.89 6 |
|
PAPM_NR | | | 99.04 94 | 98.84 105 | 99.66 55 | 99.74 71 | 99.44 84 | 99.39 198 | 99.38 216 | 97.70 170 | 99.28 164 | 99.28 287 | 98.34 84 | 99.85 129 | 96.96 269 | 99.45 131 | 99.69 99 |
|
gg-mvs-nofinetune | | | 96.17 300 | 95.32 310 | 98.73 217 | 98.79 305 | 98.14 215 | 99.38 203 | 94.09 375 | 91.07 355 | 98.07 309 | 91.04 371 | 89.62 321 | 99.35 265 | 96.75 279 | 99.09 162 | 98.68 256 |
|
VDDNet | | | 97.55 263 | 97.02 280 | 99.16 151 | 99.49 167 | 98.12 217 | 99.38 203 | 99.30 259 | 95.35 316 | 99.68 60 | 99.90 16 | 82.62 357 | 99.93 70 | 99.31 42 | 98.13 217 | 99.42 172 |
|
pmmvs6 | | | 96.53 292 | 96.09 296 | 97.82 296 | 98.69 320 | 95.47 316 | 99.37 205 | 99.47 160 | 93.46 342 | 97.41 324 | 99.78 106 | 87.06 343 | 99.33 268 | 96.92 274 | 92.70 340 | 98.65 273 |
|
PM-MVS | | | 92.96 325 | 92.23 328 | 95.14 336 | 95.61 364 | 89.98 361 | 99.37 205 | 98.21 350 | 94.80 327 | 95.04 351 | 97.69 352 | 65.06 367 | 97.90 355 | 94.30 325 | 89.98 353 | 97.54 355 |
|
WTY-MVS | | | 99.06 92 | 98.88 99 | 99.61 70 | 99.62 125 | 99.16 111 | 99.37 205 | 99.56 57 | 98.04 137 | 99.53 105 | 99.62 187 | 96.84 130 | 99.94 57 | 98.85 96 | 98.49 199 | 99.72 89 |
|
IterMVS-LS | | | 98.46 151 | 98.42 149 | 98.58 228 | 99.59 136 | 98.00 221 | 99.37 205 | 99.43 194 | 96.94 243 | 99.07 208 | 99.59 196 | 97.87 99 | 99.03 315 | 98.32 165 | 95.62 296 | 98.71 242 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
h-mvs33 | | | 97.70 251 | 97.28 270 | 98.97 174 | 99.70 92 | 97.27 251 | 99.36 209 | 99.45 180 | 98.94 42 | 99.66 69 | 99.64 176 | 94.93 193 | 99.99 2 | 99.48 25 | 84.36 361 | 99.65 113 |
|
DPE-MVS |  | | 99.46 23 | 99.32 32 | 99.91 2 | 99.78 47 | 99.88 8 | 99.36 209 | 99.51 103 | 98.73 61 | 99.88 11 | 99.84 52 | 98.72 58 | 99.96 22 | 98.16 176 | 99.87 40 | 99.88 12 |
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025 |
UnsupCasMVSNet_eth | | | 96.44 294 | 96.12 295 | 97.40 311 | 98.65 323 | 95.65 309 | 99.36 209 | 99.51 103 | 97.13 223 | 96.04 344 | 98.99 320 | 88.40 332 | 98.17 348 | 96.71 281 | 90.27 351 | 98.40 319 |
|
sss | | | 99.17 68 | 99.05 71 | 99.53 90 | 99.62 125 | 98.97 139 | 99.36 209 | 99.62 33 | 97.83 155 | 99.67 64 | 99.65 170 | 97.37 113 | 99.95 48 | 99.19 55 | 99.19 151 | 99.68 103 |
|
DeepC-MVS_fast | | 98.69 1 | 99.49 14 | 99.39 19 | 99.77 45 | 99.63 119 | 99.59 62 | 99.36 209 | 99.46 169 | 99.07 23 | 99.79 30 | 99.82 63 | 98.85 39 | 99.92 80 | 98.68 121 | 99.87 40 | 99.82 40 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
CANet | | | 99.25 61 | 99.14 62 | 99.59 72 | 99.41 188 | 99.16 111 | 99.35 214 | 99.57 52 | 98.82 53 | 99.51 109 | 99.61 191 | 96.46 142 | 99.95 48 | 99.59 11 | 99.98 2 | 99.65 113 |
|
pmmvs-eth3d | | | 95.34 312 | 94.73 314 | 97.15 315 | 95.53 366 | 95.94 305 | 99.35 214 | 99.10 289 | 95.13 318 | 93.55 356 | 97.54 353 | 88.15 336 | 97.91 354 | 94.58 322 | 89.69 354 | 97.61 352 |
|
MDTV_nov1_ep13_2view | | | | | | | 95.18 324 | 99.35 214 | | 96.84 248 | 99.58 94 | | 95.19 189 | | 97.82 202 | | 99.46 167 |
|
VDD-MVS | | | 97.73 245 | 97.35 260 | 98.88 193 | 99.47 176 | 97.12 257 | 99.34 217 | 98.85 320 | 98.19 111 | 99.67 64 | 99.85 42 | 82.98 355 | 99.92 80 | 99.49 24 | 98.32 206 | 99.60 129 |
|
COLMAP_ROB |  | 97.56 6 | 98.86 113 | 98.75 114 | 99.17 150 | 99.88 11 | 98.53 189 | 99.34 217 | 99.59 44 | 97.55 184 | 98.70 265 | 99.89 20 | 95.83 165 | 99.90 101 | 98.10 178 | 99.90 25 | 99.08 200 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
EGC-MVSNET | | | 82.80 336 | 77.86 342 | 97.62 303 | 97.91 342 | 96.12 302 | 99.33 219 | 99.28 265 | 8.40 379 | 25.05 380 | 99.27 290 | 84.11 353 | 99.33 268 | 89.20 357 | 98.22 208 | 97.42 356 |
|
FMVSNet5 | | | 96.43 295 | 96.19 294 | 97.15 315 | 99.11 260 | 95.89 306 | 99.32 220 | 99.52 89 | 94.47 333 | 98.34 296 | 99.07 311 | 87.54 341 | 97.07 363 | 92.61 346 | 95.72 294 | 98.47 309 |
|
dp | | | 97.75 242 | 97.80 203 | 97.59 305 | 99.10 263 | 93.71 344 | 99.32 220 | 98.88 317 | 96.48 276 | 99.08 207 | 99.55 210 | 92.67 268 | 99.82 152 | 96.52 288 | 98.58 192 | 99.24 189 |
|
tpmvs | | | 97.98 205 | 98.02 183 | 97.84 293 | 99.04 275 | 94.73 331 | 99.31 222 | 99.20 278 | 96.10 307 | 98.76 255 | 99.42 249 | 94.94 192 | 99.81 157 | 96.97 268 | 98.45 200 | 98.97 215 |
|
tpmrst | | | 98.33 163 | 98.48 146 | 97.90 290 | 99.16 253 | 94.78 330 | 99.31 222 | 99.11 288 | 97.27 211 | 99.45 118 | 99.59 196 | 95.33 182 | 99.84 135 | 98.48 149 | 98.61 189 | 99.09 199 |
|
MP-MVS-pluss | | | 99.37 44 | 99.20 57 | 99.88 5 | 99.90 4 | 99.87 12 | 99.30 224 | 99.52 89 | 97.18 219 | 99.60 90 | 99.79 100 | 98.79 46 | 99.95 48 | 98.83 102 | 99.91 18 | 99.83 35 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
NCCC | | | 99.34 47 | 99.19 58 | 99.79 41 | 99.61 129 | 99.65 56 | 99.30 224 | 99.48 142 | 98.86 48 | 99.21 182 | 99.63 182 | 98.72 58 | 99.90 101 | 98.25 168 | 99.63 119 | 99.80 56 |
|
JIA-IIPM | | | 97.50 268 | 97.02 280 | 98.93 180 | 98.73 314 | 97.80 235 | 99.30 224 | 98.97 304 | 91.73 351 | 98.91 233 | 94.86 365 | 95.10 190 | 99.71 196 | 97.58 224 | 97.98 220 | 99.28 187 |
|
BH-RMVSNet | | | 98.41 156 | 98.08 175 | 99.40 115 | 99.41 188 | 98.83 165 | 99.30 224 | 98.77 327 | 97.70 170 | 98.94 229 | 99.65 170 | 92.91 258 | 99.74 180 | 96.52 288 | 99.55 126 | 99.64 120 |
|
MCST-MVS | | | 99.43 32 | 99.30 40 | 99.82 33 | 99.79 45 | 99.74 41 | 99.29 228 | 99.40 207 | 98.79 58 | 99.52 107 | 99.62 187 | 98.91 34 | 99.90 101 | 98.64 125 | 99.75 98 | 99.82 40 |
|
LF4IMVS | | | 97.52 265 | 97.46 242 | 97.70 302 | 98.98 283 | 95.55 312 | 99.29 228 | 98.82 323 | 98.07 131 | 98.66 268 | 99.64 176 | 89.97 316 | 99.61 227 | 97.01 264 | 96.68 268 | 97.94 345 |
|
hse-mvs2 | | | 97.50 268 | 97.14 276 | 98.59 225 | 99.49 167 | 97.05 264 | 99.28 230 | 99.22 274 | 98.94 42 | 99.66 69 | 99.42 249 | 94.93 193 | 99.65 217 | 99.48 25 | 83.80 363 | 99.08 200 |
|
OPM-MVS | | | 98.19 174 | 98.10 171 | 98.45 246 | 98.88 293 | 97.07 262 | 99.28 230 | 99.38 216 | 98.57 70 | 99.22 179 | 99.81 76 | 92.12 281 | 99.66 212 | 98.08 183 | 97.54 237 | 98.61 295 |
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS). |
diffmvs |  | | 99.14 73 | 99.02 78 | 99.51 98 | 99.61 129 | 98.96 143 | 99.28 230 | 99.49 130 | 98.46 79 | 99.72 53 | 99.71 138 | 96.50 141 | 99.88 116 | 99.31 42 | 99.11 158 | 99.67 106 |
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025 |
PVSNet_BlendedMVS | | | 98.86 113 | 98.80 108 | 99.03 164 | 99.76 56 | 98.79 169 | 99.28 230 | 99.91 3 | 97.42 200 | 99.67 64 | 99.37 264 | 97.53 107 | 99.88 116 | 98.98 74 | 97.29 258 | 98.42 316 |
|
OMC-MVS | | | 99.08 90 | 99.04 73 | 99.20 147 | 99.67 100 | 98.22 211 | 99.28 230 | 99.52 89 | 98.07 131 | 99.66 69 | 99.81 76 | 97.79 102 | 99.78 171 | 97.79 204 | 99.81 79 | 99.60 129 |
|
AUN-MVS | | | 96.88 285 | 96.31 292 | 98.59 225 | 99.48 175 | 97.04 267 | 99.27 235 | 99.22 274 | 97.44 197 | 98.51 285 | 99.41 253 | 91.97 283 | 99.66 212 | 97.71 215 | 83.83 362 | 99.07 205 |
|
pmmvs5 | | | 97.52 265 | 97.30 268 | 98.16 272 | 98.57 331 | 96.73 282 | 99.27 235 | 98.90 315 | 96.14 301 | 98.37 294 | 99.53 219 | 91.54 297 | 99.14 298 | 97.51 233 | 95.87 289 | 98.63 283 |
|
1314 | | | 98.68 139 | 98.54 143 | 99.11 156 | 98.89 292 | 98.65 178 | 99.27 235 | 99.49 130 | 96.89 245 | 97.99 311 | 99.56 207 | 97.72 105 | 99.83 146 | 97.74 211 | 99.27 146 | 98.84 223 |
|
MVS | | | 97.28 277 | 96.55 287 | 99.48 102 | 98.78 308 | 98.95 148 | 99.27 235 | 99.39 210 | 83.53 365 | 98.08 306 | 99.54 215 | 96.97 127 | 99.87 120 | 94.23 328 | 99.16 152 | 99.63 123 |
|
BH-untuned | | | 98.42 154 | 98.36 152 | 98.59 225 | 99.49 167 | 96.70 283 | 99.27 235 | 99.13 287 | 97.24 215 | 98.80 250 | 99.38 261 | 95.75 168 | 99.74 180 | 97.07 263 | 99.16 152 | 99.33 183 |
|
MDTV_nov1_ep13 | | | | 98.32 156 | | 99.11 260 | 94.44 335 | 99.27 235 | 98.74 331 | 97.51 190 | 99.40 136 | 99.62 187 | 94.78 203 | 99.76 177 | 97.59 223 | 98.81 185 | |
|
DP-MVS Recon | | | 99.12 81 | 98.95 91 | 99.65 59 | 99.74 71 | 99.70 46 | 99.27 235 | 99.57 52 | 96.40 283 | 99.42 127 | 99.68 158 | 98.75 54 | 99.80 163 | 97.98 189 | 99.72 104 | 99.44 170 |
|
PatchmatchNet |  | | 98.31 164 | 98.36 152 | 98.19 270 | 99.16 253 | 95.32 320 | 99.27 235 | 98.92 310 | 97.37 204 | 99.37 144 | 99.58 200 | 94.90 196 | 99.70 202 | 97.43 242 | 99.21 149 | 99.54 142 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
thres200 | | | 97.61 261 | 97.28 270 | 98.62 223 | 99.64 116 | 98.03 219 | 99.26 243 | 98.74 331 | 97.68 172 | 99.09 206 | 98.32 346 | 91.66 294 | 99.81 157 | 92.88 342 | 98.22 208 | 98.03 338 |
|
CNVR-MVS | | | 99.42 34 | 99.30 40 | 99.78 43 | 99.62 125 | 99.71 44 | 99.26 243 | 99.52 89 | 98.82 53 | 99.39 139 | 99.71 138 | 98.96 24 | 99.85 129 | 98.59 135 | 99.80 83 | 99.77 68 |
|
1112_ss | | | 98.98 101 | 98.77 112 | 99.59 72 | 99.68 99 | 99.02 132 | 99.25 245 | 99.48 142 | 97.23 216 | 99.13 196 | 99.58 200 | 96.93 129 | 99.90 101 | 98.87 89 | 98.78 186 | 99.84 26 |
|
TAPA-MVS | | 97.07 15 | 97.74 244 | 97.34 263 | 98.94 178 | 99.70 92 | 97.53 244 | 99.25 245 | 99.51 103 | 91.90 350 | 99.30 160 | 99.63 182 | 98.78 47 | 99.64 220 | 88.09 362 | 99.87 40 | 99.65 113 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
PLC |  | 97.94 4 | 99.02 97 | 98.85 104 | 99.53 90 | 99.66 108 | 99.01 134 | 99.24 247 | 99.52 89 | 96.85 247 | 99.27 168 | 99.48 236 | 98.25 88 | 99.91 90 | 97.76 208 | 99.62 120 | 99.65 113 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
test_post1 | | | | | | | | 99.23 248 | | | | 65.14 377 | 94.18 231 | 99.71 196 | 97.58 224 | | |
|
ADS-MVSNet2 | | | 98.02 198 | 98.07 178 | 97.87 291 | 99.33 208 | 95.19 323 | 99.23 248 | 99.08 292 | 96.24 291 | 99.10 203 | 99.67 164 | 94.11 232 | 98.93 332 | 96.81 277 | 99.05 165 | 99.48 159 |
|
ADS-MVSNet | | | 98.20 173 | 98.08 175 | 98.56 232 | 99.33 208 | 96.48 292 | 99.23 248 | 99.15 284 | 96.24 291 | 99.10 203 | 99.67 164 | 94.11 232 | 99.71 196 | 96.81 277 | 99.05 165 | 99.48 159 |
|
EPNet_dtu | | | 98.03 196 | 97.96 188 | 98.23 268 | 98.27 338 | 95.54 314 | 99.23 248 | 98.75 328 | 99.02 26 | 97.82 317 | 99.71 138 | 96.11 152 | 99.48 236 | 93.04 341 | 99.65 116 | 99.69 99 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
CR-MVSNet | | | 98.17 177 | 97.93 193 | 98.87 197 | 99.18 245 | 98.49 197 | 99.22 252 | 99.33 241 | 96.96 239 | 99.56 98 | 99.38 261 | 94.33 224 | 99.00 320 | 94.83 321 | 98.58 192 | 99.14 192 |
|
RPMNet | | | 96.72 289 | 95.90 300 | 99.19 148 | 99.18 245 | 98.49 197 | 99.22 252 | 99.52 89 | 88.72 361 | 99.56 98 | 97.38 355 | 94.08 234 | 99.95 48 | 86.87 366 | 98.58 192 | 99.14 192 |
|
plane_prior | | | | | | | 96.97 273 | 99.21 254 | | 98.45 80 | | | | | | 97.60 231 | |
|
WR-MVS | | | 98.06 188 | 97.73 216 | 99.06 160 | 98.86 300 | 99.25 102 | 99.19 255 | 99.35 230 | 97.30 209 | 98.66 268 | 99.43 247 | 93.94 237 | 99.21 293 | 98.58 136 | 94.28 321 | 98.71 242 |
|
new-patchmatchnet | | | 94.48 319 | 94.08 319 | 95.67 335 | 95.08 368 | 92.41 353 | 99.18 256 | 99.28 265 | 94.55 332 | 93.49 357 | 97.37 356 | 87.86 339 | 97.01 364 | 91.57 349 | 88.36 355 | 97.61 352 |
|
AdaColmap |  | | 99.01 100 | 98.80 108 | 99.66 55 | 99.56 144 | 99.54 70 | 99.18 256 | 99.70 15 | 98.18 115 | 99.35 151 | 99.63 182 | 96.32 147 | 99.90 101 | 97.48 236 | 99.77 93 | 99.55 140 |
|
EG-PatchMatch MVS | | | 95.97 303 | 95.69 304 | 96.81 326 | 97.78 345 | 92.79 352 | 99.16 258 | 98.93 308 | 96.16 298 | 94.08 354 | 99.22 296 | 82.72 356 | 99.47 237 | 95.67 307 | 97.50 242 | 98.17 331 |
|
PatchT | | | 97.03 284 | 96.44 290 | 98.79 213 | 98.99 280 | 98.34 207 | 99.16 258 | 99.07 295 | 92.13 349 | 99.52 107 | 97.31 358 | 94.54 219 | 98.98 322 | 88.54 360 | 98.73 188 | 99.03 208 |
|
CNLPA | | | 99.14 73 | 98.99 83 | 99.59 72 | 99.58 138 | 99.41 87 | 99.16 258 | 99.44 188 | 98.45 80 | 99.19 188 | 99.49 231 | 98.08 95 | 99.89 111 | 97.73 212 | 99.75 98 | 99.48 159 |
|
MDA-MVSNet-bldmvs | | | 94.96 314 | 93.98 320 | 97.92 288 | 98.24 339 | 97.27 251 | 99.15 261 | 99.33 241 | 93.80 337 | 80.09 372 | 99.03 316 | 88.31 333 | 97.86 356 | 93.49 336 | 94.36 320 | 98.62 286 |
|
CDPH-MVS | | | 99.13 75 | 98.91 95 | 99.80 38 | 99.75 64 | 99.71 44 | 99.15 261 | 99.41 199 | 96.60 266 | 99.60 90 | 99.55 210 | 98.83 42 | 99.90 101 | 97.48 236 | 99.83 72 | 99.78 66 |
|
save fliter | | | | | | 99.76 56 | 99.59 62 | 99.14 263 | 99.40 207 | 99.00 31 | | | | | | | |
|
testf1 | | | 90.42 330 | 90.68 332 | 89.65 350 | 97.78 345 | 73.97 377 | 99.13 264 | 98.81 324 | 89.62 357 | 91.80 361 | 98.93 326 | 62.23 370 | 98.80 337 | 86.61 367 | 91.17 345 | 96.19 362 |
|
APD_test2 | | | 90.42 330 | 90.68 332 | 89.65 350 | 97.78 345 | 73.97 377 | 99.13 264 | 98.81 324 | 89.62 357 | 91.80 361 | 98.93 326 | 62.23 370 | 98.80 337 | 86.61 367 | 91.17 345 | 96.19 362 |
|
xiu_mvs_v1_base_debu | | | 99.29 53 | 99.27 48 | 99.34 121 | 99.63 119 | 98.97 139 | 99.12 266 | 99.51 103 | 98.86 48 | 99.84 18 | 99.47 239 | 98.18 91 | 99.99 2 | 99.50 20 | 99.31 143 | 99.08 200 |
|
xiu_mvs_v1_base | | | 99.29 53 | 99.27 48 | 99.34 121 | 99.63 119 | 98.97 139 | 99.12 266 | 99.51 103 | 98.86 48 | 99.84 18 | 99.47 239 | 98.18 91 | 99.99 2 | 99.50 20 | 99.31 143 | 99.08 200 |
|
xiu_mvs_v1_base_debi | | | 99.29 53 | 99.27 48 | 99.34 121 | 99.63 119 | 98.97 139 | 99.12 266 | 99.51 103 | 98.86 48 | 99.84 18 | 99.47 239 | 98.18 91 | 99.99 2 | 99.50 20 | 99.31 143 | 99.08 200 |
|
XVG-OURS-SEG-HR | | | 98.69 137 | 98.62 132 | 98.89 191 | 99.71 87 | 97.74 236 | 99.12 266 | 99.54 73 | 98.44 83 | 99.42 127 | 99.71 138 | 94.20 228 | 99.92 80 | 98.54 146 | 98.90 177 | 99.00 211 |
|
jason | | | 99.13 75 | 99.03 75 | 99.45 108 | 99.46 177 | 98.87 158 | 99.12 266 | 99.26 268 | 98.03 139 | 99.79 30 | 99.65 170 | 97.02 124 | 99.85 129 | 99.02 71 | 99.90 25 | 99.65 113 |
jason: jason. |
N_pmnet | | | 94.95 315 | 95.83 302 | 92.31 344 | 98.47 335 | 79.33 372 | 99.12 266 | 92.81 379 | 93.87 336 | 97.68 320 | 99.13 306 | 93.87 239 | 99.01 319 | 91.38 350 | 96.19 280 | 98.59 299 |
|
MDA-MVSNet_test_wron | | | 95.45 309 | 94.60 315 | 98.01 282 | 98.16 340 | 97.21 256 | 99.11 272 | 99.24 272 | 93.49 341 | 80.73 371 | 98.98 323 | 93.02 253 | 98.18 347 | 94.22 329 | 94.45 318 | 98.64 275 |
|
Patchmtry | | | 97.75 242 | 97.40 255 | 98.81 210 | 99.10 263 | 98.87 158 | 99.11 272 | 99.33 241 | 94.83 326 | 98.81 248 | 99.38 261 | 94.33 224 | 99.02 317 | 96.10 295 | 95.57 297 | 98.53 303 |
|
YYNet1 | | | 95.36 311 | 94.51 317 | 97.92 288 | 97.89 343 | 97.10 258 | 99.10 274 | 99.23 273 | 93.26 344 | 80.77 370 | 99.04 315 | 92.81 259 | 98.02 351 | 94.30 325 | 94.18 323 | 98.64 275 |
|
CANet_DTU | | | 98.97 103 | 98.87 100 | 99.25 141 | 99.33 208 | 98.42 205 | 99.08 275 | 99.30 259 | 99.16 9 | 99.43 124 | 99.75 122 | 95.27 184 | 99.97 14 | 98.56 142 | 99.95 8 | 99.36 179 |
|
SCA | | | 98.19 174 | 98.16 164 | 98.27 267 | 99.30 216 | 95.55 312 | 99.07 276 | 98.97 304 | 97.57 182 | 99.43 124 | 99.57 204 | 92.72 263 | 99.74 180 | 97.58 224 | 99.20 150 | 99.52 148 |
|
TSAR-MVS + GP. | | | 99.36 45 | 99.36 24 | 99.36 120 | 99.67 100 | 98.61 183 | 99.07 276 | 99.33 241 | 99.00 31 | 99.82 24 | 99.81 76 | 99.06 16 | 99.84 135 | 99.09 64 | 99.42 133 | 99.65 113 |
|
MG-MVS | | | 99.13 75 | 99.02 78 | 99.45 108 | 99.57 140 | 98.63 180 | 99.07 276 | 99.34 234 | 98.99 33 | 99.61 87 | 99.82 63 | 97.98 98 | 99.87 120 | 97.00 265 | 99.80 83 | 99.85 22 |
|
PatchMatch-RL | | | 98.84 123 | 98.62 132 | 99.52 96 | 99.71 87 | 99.28 98 | 99.06 279 | 99.77 9 | 97.74 167 | 99.50 110 | 99.53 219 | 95.41 178 | 99.84 135 | 97.17 258 | 99.64 117 | 99.44 170 |
|
OpenMVS_ROB |  | 92.34 20 | 94.38 320 | 93.70 324 | 96.41 331 | 97.38 351 | 93.17 350 | 99.06 279 | 98.75 328 | 86.58 362 | 94.84 352 | 98.26 347 | 81.53 359 | 99.32 271 | 89.01 358 | 97.87 223 | 96.76 359 |
|
TEST9 | | | | | | 99.67 100 | 99.65 56 | 99.05 281 | 99.41 199 | 96.22 293 | 98.95 227 | 99.49 231 | 98.77 50 | 99.91 90 | | | |
|
train_agg | | | 99.02 97 | 98.77 112 | 99.77 45 | 99.67 100 | 99.65 56 | 99.05 281 | 99.41 199 | 96.28 287 | 98.95 227 | 99.49 231 | 98.76 51 | 99.91 90 | 97.63 220 | 99.72 104 | 99.75 74 |
|
lupinMVS | | | 99.13 75 | 99.01 82 | 99.46 107 | 99.51 156 | 98.94 151 | 99.05 281 | 99.16 283 | 97.86 150 | 99.80 28 | 99.56 207 | 97.39 110 | 99.86 123 | 98.94 78 | 99.85 55 | 99.58 137 |
|
DELS-MVS | | | 99.48 18 | 99.42 15 | 99.65 59 | 99.72 82 | 99.40 88 | 99.05 281 | 99.66 26 | 99.14 11 | 99.57 97 | 99.80 89 | 98.46 76 | 99.94 57 | 99.57 13 | 99.84 63 | 99.60 129 |
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 |
new_pmnet | | | 96.38 296 | 96.03 297 | 97.41 310 | 98.13 341 | 95.16 325 | 99.05 281 | 99.20 278 | 93.94 335 | 97.39 325 | 98.79 332 | 91.61 296 | 99.04 313 | 90.43 353 | 95.77 291 | 98.05 337 |
|
MVS_0304 | | | 96.79 288 | 96.52 288 | 97.59 305 | 99.22 236 | 94.92 329 | 99.04 286 | 99.59 44 | 96.49 272 | 98.43 290 | 98.99 320 | 80.48 361 | 99.39 251 | 97.15 259 | 99.27 146 | 98.47 309 |
|
Patchmatch-test | | | 97.93 211 | 97.65 223 | 98.77 215 | 99.18 245 | 97.07 262 | 99.03 287 | 99.14 286 | 96.16 298 | 98.74 256 | 99.57 204 | 94.56 217 | 99.72 190 | 93.36 337 | 99.11 158 | 99.52 148 |
|
test_8 | | | | | | 99.67 100 | 99.61 60 | 99.03 287 | 99.41 199 | 96.28 287 | 98.93 231 | 99.48 236 | 98.76 51 | 99.91 90 | | | |
|
Test_1112_low_res | | | 98.89 108 | 98.66 124 | 99.57 77 | 99.69 95 | 98.95 148 | 99.03 287 | 99.47 160 | 96.98 237 | 99.15 194 | 99.23 295 | 96.77 133 | 99.89 111 | 98.83 102 | 98.78 186 | 99.86 19 |
|
IterMVS-SCA-FT | | | 97.82 231 | 97.75 214 | 98.06 278 | 99.57 140 | 96.36 296 | 99.02 290 | 99.49 130 | 97.18 219 | 98.71 259 | 99.72 137 | 92.72 263 | 99.14 298 | 97.44 241 | 95.86 290 | 98.67 263 |
|
xiu_mvs_v2_base | | | 99.26 58 | 99.25 52 | 99.29 136 | 99.53 150 | 98.91 155 | 99.02 290 | 99.45 180 | 98.80 57 | 99.71 54 | 99.26 292 | 98.94 29 | 99.98 8 | 99.34 39 | 99.23 148 | 98.98 214 |
|
MIMVSNet | | | 97.73 245 | 97.45 243 | 98.57 229 | 99.45 182 | 97.50 245 | 99.02 290 | 98.98 303 | 96.11 303 | 99.41 131 | 99.14 305 | 90.28 310 | 98.74 339 | 95.74 303 | 98.93 173 | 99.47 165 |
|
IterMVS | | | 97.83 228 | 97.77 209 | 98.02 281 | 99.58 138 | 96.27 299 | 99.02 290 | 99.48 142 | 97.22 217 | 98.71 259 | 99.70 142 | 92.75 260 | 99.13 301 | 97.46 239 | 96.00 284 | 98.67 263 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
HyFIR lowres test | | | 99.11 85 | 98.92 93 | 99.65 59 | 99.90 4 | 99.37 89 | 99.02 290 | 99.91 3 | 97.67 174 | 99.59 93 | 99.75 122 | 95.90 163 | 99.73 186 | 99.53 16 | 99.02 169 | 99.86 19 |
|
æ–°å‡ ä½•2 | | | | | | | | 99.01 295 | | | | | | | | | |
|
BH-w/o | | | 98.00 203 | 97.89 199 | 98.32 260 | 99.35 202 | 96.20 301 | 99.01 295 | 98.90 315 | 96.42 281 | 98.38 293 | 99.00 319 | 95.26 186 | 99.72 190 | 96.06 296 | 98.61 189 | 99.03 208 |
|
test_prior4 | | | | | | | 99.56 66 | 98.99 297 | | | | | | | | | |
|
æ— å…ˆéªŒ | | | | | | | | 98.99 297 | 99.51 103 | 96.89 245 | | | | 99.93 70 | 97.53 232 | | 99.72 89 |
|
pmmvs4 | | | 98.13 181 | 97.90 195 | 98.81 210 | 98.61 328 | 98.87 158 | 98.99 297 | 99.21 277 | 96.44 279 | 99.06 212 | 99.58 200 | 95.90 163 | 99.11 306 | 97.18 257 | 96.11 282 | 98.46 313 |
|
HQP-NCC | | | | | | 99.19 242 | | 98.98 300 | | 98.24 102 | 98.66 268 | | | | | | |
|
ACMP_Plane | | | | | | 99.19 242 | | 98.98 300 | | 98.24 102 | 98.66 268 | | | | | | |
|
HQP-MVS | | | 98.02 198 | 97.90 195 | 98.37 256 | 99.19 242 | 96.83 278 | 98.98 300 | 99.39 210 | 98.24 102 | 98.66 268 | 99.40 256 | 92.47 274 | 99.64 220 | 97.19 255 | 97.58 233 | 98.64 275 |
|
PS-MVSNAJ | | | 99.32 49 | 99.32 32 | 99.30 133 | 99.57 140 | 98.94 151 | 98.97 303 | 99.46 169 | 98.92 45 | 99.71 54 | 99.24 294 | 99.01 18 | 99.98 8 | 99.35 35 | 99.66 114 | 98.97 215 |
|
MVP-Stereo | | | 97.81 233 | 97.75 214 | 97.99 285 | 97.53 349 | 96.60 289 | 98.96 304 | 98.85 320 | 97.22 217 | 97.23 328 | 99.36 267 | 95.28 183 | 99.46 238 | 95.51 309 | 99.78 90 | 97.92 347 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
test_prior2 | | | | | | | | 98.96 304 | | 98.34 92 | 99.01 217 | 99.52 222 | 98.68 61 | | 97.96 190 | 99.74 101 | |
|
旧先验2 | | | | | | | | 98.96 304 | | 96.70 255 | 99.47 115 | | | 99.94 57 | 98.19 172 | | |
|
原ACMM2 | | | | | | | | 98.95 307 | | | | | | | | | |
|
MVS_111021_HR | | | 99.41 38 | 99.32 32 | 99.66 55 | 99.72 82 | 99.47 81 | 98.95 307 | 99.85 6 | 98.82 53 | 99.54 103 | 99.73 133 | 98.51 73 | 99.74 180 | 98.91 83 | 99.88 37 | 99.77 68 |
|
mvsany_test1 | | | 99.50 12 | 99.46 14 | 99.62 69 | 99.61 129 | 99.09 122 | 98.94 309 | 99.48 142 | 99.10 16 | 99.96 6 | 99.91 11 | 98.85 39 | 99.96 22 | 99.72 5 | 99.58 123 | 99.82 40 |
|
MVS_111021_LR | | | 99.41 38 | 99.33 30 | 99.65 59 | 99.77 53 | 99.51 77 | 98.94 309 | 99.85 6 | 98.82 53 | 99.65 75 | 99.74 127 | 98.51 73 | 99.80 163 | 98.83 102 | 99.89 34 | 99.64 120 |
|
pmmvs3 | | | 94.09 322 | 93.25 326 | 96.60 329 | 94.76 369 | 94.49 334 | 98.92 311 | 98.18 352 | 89.66 356 | 96.48 339 | 98.06 350 | 86.28 344 | 97.33 361 | 89.68 356 | 87.20 358 | 97.97 344 |
|
XVG-OURS | | | 98.73 133 | 98.68 120 | 98.88 193 | 99.70 92 | 97.73 237 | 98.92 311 | 99.55 65 | 98.52 75 | 99.45 118 | 99.84 52 | 95.27 184 | 99.91 90 | 98.08 183 | 98.84 181 | 99.00 211 |
|
test222 | | | | | | 99.75 64 | 99.49 78 | 98.91 313 | 99.49 130 | 96.42 281 | 99.34 154 | 99.65 170 | 98.28 87 | | | 99.69 109 | 99.72 89 |
|
PMMVS2 | | | 86.87 333 | 85.37 337 | 91.35 347 | 90.21 374 | 83.80 366 | 98.89 314 | 97.45 361 | 83.13 366 | 91.67 363 | 95.03 363 | 48.49 376 | 94.70 371 | 85.86 369 | 77.62 368 | 95.54 364 |
|
miper_lstm_enhance | | | 98.00 203 | 97.91 194 | 98.28 266 | 99.34 206 | 97.43 247 | 98.88 315 | 99.36 225 | 96.48 276 | 98.80 250 | 99.55 210 | 95.98 156 | 98.91 333 | 97.27 248 | 95.50 300 | 98.51 305 |
|
MVS-HIRNet | | | 95.75 307 | 95.16 311 | 97.51 308 | 99.30 216 | 93.69 345 | 98.88 315 | 95.78 369 | 85.09 364 | 98.78 253 | 92.65 367 | 91.29 301 | 99.37 258 | 94.85 320 | 99.85 55 | 99.46 167 |
|
TR-MVS | | | 97.76 238 | 97.41 254 | 98.82 208 | 99.06 271 | 97.87 231 | 98.87 317 | 98.56 342 | 96.63 263 | 98.68 267 | 99.22 296 | 92.49 273 | 99.65 217 | 95.40 312 | 97.79 224 | 98.95 219 |
|
testdata1 | | | | | | | | 98.85 318 | | 98.32 95 | | | | | | | |
|
ET-MVSNet_ETH3D | | | 96.49 293 | 95.64 306 | 99.05 162 | 99.53 150 | 98.82 166 | 98.84 319 | 97.51 360 | 97.63 177 | 84.77 365 | 99.21 299 | 92.09 282 | 98.91 333 | 98.98 74 | 92.21 342 | 99.41 174 |
|
our_test_3 | | | 97.65 259 | 97.68 220 | 97.55 307 | 98.62 326 | 94.97 327 | 98.84 319 | 99.30 259 | 96.83 250 | 98.19 302 | 99.34 273 | 97.01 125 | 99.02 317 | 95.00 319 | 96.01 283 | 98.64 275 |
|
MS-PatchMatch | | | 97.24 280 | 97.32 266 | 96.99 320 | 98.45 336 | 93.51 348 | 98.82 321 | 99.32 251 | 97.41 201 | 98.13 305 | 99.30 283 | 88.99 324 | 99.56 231 | 95.68 306 | 99.80 83 | 97.90 348 |
|
c3_l | | | 98.12 183 | 98.04 180 | 98.38 255 | 99.30 216 | 97.69 242 | 98.81 322 | 99.33 241 | 96.67 257 | 98.83 246 | 99.34 273 | 97.11 120 | 98.99 321 | 97.58 224 | 95.34 302 | 98.48 307 |
|
ppachtmachnet_test | | | 97.49 271 | 97.45 243 | 97.61 304 | 98.62 326 | 95.24 321 | 98.80 323 | 99.46 169 | 96.11 303 | 98.22 301 | 99.62 187 | 96.45 143 | 98.97 329 | 93.77 332 | 95.97 288 | 98.61 295 |
|
PAPR | | | 98.63 144 | 98.34 154 | 99.51 98 | 99.40 193 | 99.03 131 | 98.80 323 | 99.36 225 | 96.33 284 | 99.00 221 | 99.12 309 | 98.46 76 | 99.84 135 | 95.23 315 | 99.37 142 | 99.66 109 |
|
test0.0.03 1 | | | 97.71 250 | 97.42 253 | 98.56 232 | 98.41 337 | 97.82 234 | 98.78 325 | 98.63 340 | 97.34 205 | 98.05 310 | 98.98 323 | 94.45 221 | 98.98 322 | 95.04 318 | 97.15 264 | 98.89 220 |
|
PVSNet_Blended | | | 99.08 90 | 98.97 87 | 99.42 113 | 99.76 56 | 98.79 169 | 98.78 325 | 99.91 3 | 96.74 252 | 99.67 64 | 99.49 231 | 97.53 107 | 99.88 116 | 98.98 74 | 99.85 55 | 99.60 129 |
|
PMMVS | | | 98.80 127 | 98.62 132 | 99.34 121 | 99.27 225 | 98.70 174 | 98.76 327 | 99.31 255 | 97.34 205 | 99.21 182 | 99.07 311 | 97.20 117 | 99.82 152 | 98.56 142 | 98.87 178 | 99.52 148 |
|
test123 | | | 39.01 345 | 42.50 347 | 28.53 360 | 39.17 383 | 20.91 384 | 98.75 328 | 19.17 385 | 19.83 378 | 38.57 377 | 66.67 375 | 33.16 380 | 15.42 379 | 37.50 378 | 29.66 377 | 49.26 374 |
|
MSDG | | | 98.98 101 | 98.80 108 | 99.53 90 | 99.76 56 | 99.19 106 | 98.75 328 | 99.55 65 | 97.25 213 | 99.47 115 | 99.77 113 | 97.82 101 | 99.87 120 | 96.93 272 | 99.90 25 | 99.54 142 |
|
CLD-MVS | | | 98.16 178 | 98.10 171 | 98.33 258 | 99.29 220 | 96.82 280 | 98.75 328 | 99.44 188 | 97.83 155 | 99.13 196 | 99.55 210 | 92.92 256 | 99.67 209 | 98.32 165 | 97.69 227 | 98.48 307 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
miper_ehance_all_eth | | | 98.18 176 | 98.10 171 | 98.41 251 | 99.23 233 | 97.72 238 | 98.72 331 | 99.31 255 | 96.60 266 | 98.88 238 | 99.29 285 | 97.29 115 | 99.13 301 | 97.60 222 | 95.99 285 | 98.38 321 |
|
cl____ | | | 98.01 201 | 97.84 202 | 98.55 234 | 99.25 231 | 97.97 223 | 98.71 332 | 99.34 234 | 96.47 278 | 98.59 282 | 99.54 215 | 95.65 173 | 99.21 293 | 97.21 251 | 95.77 291 | 98.46 313 |
|
DIV-MVS_self_test | | | 98.01 201 | 97.85 201 | 98.48 240 | 99.24 232 | 97.95 227 | 98.71 332 | 99.35 230 | 96.50 271 | 98.60 281 | 99.54 215 | 95.72 170 | 99.03 315 | 97.21 251 | 95.77 291 | 98.46 313 |
|
test-LLR | | | 98.06 188 | 97.90 195 | 98.55 234 | 98.79 305 | 97.10 258 | 98.67 334 | 97.75 356 | 97.34 205 | 98.61 279 | 98.85 329 | 94.45 221 | 99.45 239 | 97.25 249 | 99.38 135 | 99.10 195 |
|
TESTMET0.1,1 | | | 97.55 263 | 97.27 273 | 98.40 253 | 98.93 288 | 96.53 290 | 98.67 334 | 97.61 359 | 96.96 239 | 98.64 275 | 99.28 287 | 88.63 330 | 99.45 239 | 97.30 247 | 99.38 135 | 99.21 191 |
|
test-mter | | | 97.49 271 | 97.13 277 | 98.55 234 | 98.79 305 | 97.10 258 | 98.67 334 | 97.75 356 | 96.65 259 | 98.61 279 | 98.85 329 | 88.23 334 | 99.45 239 | 97.25 249 | 99.38 135 | 99.10 195 |
|
IB-MVS | | 95.67 18 | 96.22 297 | 95.44 309 | 98.57 229 | 99.21 238 | 96.70 283 | 98.65 337 | 97.74 358 | 96.71 254 | 97.27 327 | 98.54 340 | 86.03 345 | 99.92 80 | 98.47 152 | 86.30 359 | 99.10 195 |
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 |
DPM-MVS | | | 98.95 104 | 98.71 117 | 99.66 55 | 99.63 119 | 99.55 68 | 98.64 338 | 99.10 289 | 97.93 145 | 99.42 127 | 99.55 210 | 98.67 63 | 99.80 163 | 95.80 302 | 99.68 112 | 99.61 127 |
|
thisisatest0515 | | | 98.14 180 | 97.79 204 | 99.19 148 | 99.50 165 | 98.50 196 | 98.61 339 | 96.82 364 | 96.95 241 | 99.54 103 | 99.43 247 | 91.66 294 | 99.86 123 | 98.08 183 | 99.51 128 | 99.22 190 |
|
DeepPCF-MVS | | 98.18 3 | 98.81 124 | 99.37 22 | 97.12 318 | 99.60 134 | 91.75 356 | 98.61 339 | 99.44 188 | 99.35 2 | 99.83 23 | 99.85 42 | 98.70 60 | 99.81 157 | 99.02 71 | 99.91 18 | 99.81 47 |
|
cl22 | | | 97.85 223 | 97.64 225 | 98.48 240 | 99.09 265 | 97.87 231 | 98.60 341 | 99.33 241 | 97.11 228 | 98.87 241 | 99.22 296 | 92.38 279 | 99.17 297 | 98.21 170 | 95.99 285 | 98.42 316 |
|
GA-MVS | | | 97.85 223 | 97.47 240 | 99.00 168 | 99.38 197 | 97.99 222 | 98.57 342 | 99.15 284 | 97.04 234 | 98.90 235 | 99.30 283 | 89.83 317 | 99.38 253 | 96.70 282 | 98.33 202 | 99.62 125 |
|
TinyColmap | | | 97.12 282 | 96.89 282 | 97.83 294 | 99.07 268 | 95.52 315 | 98.57 342 | 98.74 331 | 97.58 181 | 97.81 318 | 99.79 100 | 88.16 335 | 99.56 231 | 95.10 316 | 97.21 261 | 98.39 320 |
|
eth_miper_zixun_eth | | | 98.05 193 | 97.96 188 | 98.33 258 | 99.26 227 | 97.38 248 | 98.56 344 | 99.31 255 | 96.65 259 | 98.88 238 | 99.52 222 | 96.58 138 | 99.12 305 | 97.39 244 | 95.53 299 | 98.47 309 |
|
CMPMVS |  | 69.68 23 | 94.13 321 | 94.90 313 | 91.84 345 | 97.24 355 | 80.01 371 | 98.52 345 | 99.48 142 | 89.01 359 | 91.99 360 | 99.67 164 | 85.67 347 | 99.13 301 | 95.44 310 | 97.03 265 | 96.39 361 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
USDC | | | 97.34 275 | 97.20 274 | 97.75 299 | 99.07 268 | 95.20 322 | 98.51 346 | 99.04 298 | 97.99 141 | 98.31 297 | 99.86 37 | 89.02 323 | 99.55 233 | 95.67 307 | 97.36 257 | 98.49 306 |
|
ambc | | | | | 93.06 343 | 92.68 371 | 82.36 367 | 98.47 347 | 98.73 336 | | 95.09 350 | 97.41 354 | 55.55 372 | 99.10 308 | 96.42 291 | 91.32 344 | 97.71 349 |
|
miper_enhance_ethall | | | 98.16 178 | 98.08 175 | 98.41 251 | 98.96 286 | 97.72 238 | 98.45 348 | 99.32 251 | 96.95 241 | 98.97 225 | 99.17 301 | 97.06 123 | 99.22 288 | 97.86 198 | 95.99 285 | 98.29 325 |
|
CHOSEN 280x420 | | | 99.12 81 | 99.13 63 | 99.08 157 | 99.66 108 | 97.89 230 | 98.43 349 | 99.71 13 | 98.88 47 | 99.62 84 | 99.76 119 | 96.63 137 | 99.70 202 | 99.46 28 | 99.99 1 | 99.66 109 |
|
testmvs | | | 39.17 344 | 43.78 346 | 25.37 361 | 36.04 384 | 16.84 385 | 98.36 350 | 26.56 383 | 20.06 377 | 38.51 378 | 67.32 374 | 29.64 381 | 15.30 380 | 37.59 377 | 39.90 376 | 43.98 375 |
|
FPMVS | | | 84.93 335 | 85.65 336 | 82.75 356 | 86.77 377 | 63.39 381 | 98.35 351 | 98.92 310 | 74.11 368 | 83.39 367 | 98.98 323 | 50.85 375 | 92.40 373 | 84.54 370 | 94.97 310 | 92.46 366 |
|
KD-MVS_2432*1600 | | | 94.62 316 | 93.72 322 | 97.31 312 | 97.19 357 | 95.82 307 | 98.34 352 | 99.20 278 | 95.00 323 | 97.57 321 | 98.35 344 | 87.95 337 | 98.10 349 | 92.87 343 | 77.00 369 | 98.01 339 |
|
miper_refine_blended | | | 94.62 316 | 93.72 322 | 97.31 312 | 97.19 357 | 95.82 307 | 98.34 352 | 99.20 278 | 95.00 323 | 97.57 321 | 98.35 344 | 87.95 337 | 98.10 349 | 92.87 343 | 77.00 369 | 98.01 339 |
|
CL-MVSNet_self_test | | | 94.49 318 | 93.97 321 | 96.08 333 | 96.16 361 | 93.67 346 | 98.33 354 | 99.38 216 | 95.13 318 | 97.33 326 | 98.15 348 | 92.69 267 | 96.57 366 | 88.67 359 | 79.87 367 | 97.99 342 |
|
PVSNet | | 96.02 17 | 98.85 120 | 98.84 105 | 98.89 191 | 99.73 78 | 97.28 250 | 98.32 355 | 99.60 41 | 97.86 150 | 99.50 110 | 99.57 204 | 96.75 134 | 99.86 123 | 98.56 142 | 99.70 108 | 99.54 142 |
|
PAPM | | | 97.59 262 | 97.09 278 | 99.07 159 | 99.06 271 | 98.26 210 | 98.30 356 | 99.10 289 | 94.88 325 | 98.08 306 | 99.34 273 | 96.27 149 | 99.64 220 | 89.87 355 | 98.92 175 | 99.31 185 |
|
Patchmatch-RL test | | | 95.84 305 | 95.81 303 | 95.95 334 | 95.61 364 | 90.57 359 | 98.24 357 | 98.39 346 | 95.10 322 | 95.20 348 | 98.67 336 | 94.78 203 | 97.77 357 | 96.28 294 | 90.02 352 | 99.51 154 |
|
UnsupCasMVSNet_bld | | | 93.53 324 | 92.51 327 | 96.58 330 | 97.38 351 | 93.82 341 | 98.24 357 | 99.48 142 | 91.10 354 | 93.10 358 | 96.66 360 | 74.89 364 | 98.37 344 | 94.03 331 | 87.71 357 | 97.56 354 |
|
LCM-MVSNet | | | 86.80 334 | 85.22 338 | 91.53 346 | 87.81 376 | 80.96 370 | 98.23 359 | 98.99 302 | 71.05 369 | 90.13 364 | 96.51 361 | 48.45 377 | 96.88 365 | 90.51 352 | 85.30 360 | 96.76 359 |
|
cascas | | | 97.69 252 | 97.43 252 | 98.48 240 | 98.60 329 | 97.30 249 | 98.18 360 | 99.39 210 | 92.96 346 | 98.41 291 | 98.78 333 | 93.77 243 | 99.27 280 | 98.16 176 | 98.61 189 | 98.86 221 |
|
Effi-MVS+ | | | 98.81 124 | 98.59 139 | 99.48 102 | 99.46 177 | 99.12 120 | 98.08 361 | 99.50 122 | 97.50 191 | 99.38 142 | 99.41 253 | 96.37 146 | 99.81 157 | 99.11 62 | 98.54 196 | 99.51 154 |
|
PCF-MVS | | 97.08 14 | 97.66 258 | 97.06 279 | 99.47 105 | 99.61 129 | 99.09 122 | 98.04 362 | 99.25 270 | 91.24 353 | 98.51 285 | 99.70 142 | 94.55 218 | 99.91 90 | 92.76 345 | 99.85 55 | 99.42 172 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
PVSNet_0 | | 94.43 19 | 96.09 302 | 95.47 307 | 97.94 287 | 99.31 215 | 94.34 338 | 97.81 363 | 99.70 15 | 97.12 225 | 97.46 323 | 98.75 334 | 89.71 318 | 99.79 166 | 97.69 218 | 81.69 365 | 99.68 103 |
|
E-PMN | | | 80.61 338 | 79.88 340 | 82.81 355 | 90.75 373 | 76.38 375 | 97.69 364 | 95.76 370 | 66.44 373 | 83.52 366 | 92.25 368 | 62.54 369 | 87.16 375 | 68.53 374 | 61.40 372 | 84.89 373 |
|
ANet_high | | | 77.30 340 | 74.86 344 | 84.62 354 | 75.88 380 | 77.61 373 | 97.63 365 | 93.15 378 | 88.81 360 | 64.27 375 | 89.29 372 | 36.51 379 | 83.93 377 | 75.89 372 | 52.31 374 | 92.33 368 |
|
EMVS | | | 80.02 339 | 79.22 341 | 82.43 357 | 91.19 372 | 76.40 374 | 97.55 366 | 92.49 380 | 66.36 374 | 83.01 368 | 91.27 370 | 64.63 368 | 85.79 376 | 65.82 375 | 60.65 373 | 85.08 372 |
|
MVE |  | 76.82 21 | 76.91 341 | 74.31 345 | 84.70 353 | 85.38 379 | 76.05 376 | 96.88 367 | 93.17 377 | 67.39 372 | 71.28 374 | 89.01 373 | 21.66 384 | 87.69 374 | 71.74 373 | 72.29 371 | 90.35 370 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
test_method | | | 91.10 328 | 91.36 330 | 90.31 349 | 95.85 362 | 73.72 379 | 94.89 368 | 99.25 270 | 68.39 371 | 95.82 345 | 99.02 318 | 80.50 360 | 98.95 331 | 93.64 334 | 94.89 313 | 98.25 328 |
|
Gipuma |  | | 90.99 329 | 90.15 334 | 93.51 340 | 98.73 314 | 90.12 360 | 93.98 369 | 99.45 180 | 79.32 367 | 92.28 359 | 94.91 364 | 69.61 365 | 97.98 353 | 87.42 363 | 95.67 295 | 92.45 367 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
PMVS |  | 70.75 22 | 75.98 342 | 74.97 343 | 79.01 358 | 70.98 381 | 55.18 382 | 93.37 370 | 98.21 350 | 65.08 375 | 61.78 376 | 93.83 366 | 21.74 383 | 92.53 372 | 78.59 371 | 91.12 347 | 89.34 371 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
tmp_tt | | | 82.80 336 | 81.52 339 | 86.66 352 | 66.61 382 | 68.44 380 | 92.79 371 | 97.92 354 | 68.96 370 | 80.04 373 | 99.85 42 | 85.77 346 | 96.15 369 | 97.86 198 | 43.89 375 | 95.39 365 |
|
wuyk23d | | | 40.18 343 | 41.29 348 | 36.84 359 | 86.18 378 | 49.12 383 | 79.73 372 | 22.81 384 | 27.64 376 | 25.46 379 | 28.45 379 | 21.98 382 | 48.89 378 | 55.80 376 | 23.56 378 | 12.51 376 |
|
test_blank | | | 0.13 349 | 0.17 352 | 0.00 362 | 0.00 385 | 0.00 386 | 0.00 373 | 0.00 386 | 0.00 380 | 0.00 381 | 1.57 380 | 0.00 385 | 0.00 381 | 0.00 379 | 0.00 379 | 0.00 377 |
|
uanet_test | | | 0.02 350 | 0.03 353 | 0.00 362 | 0.00 385 | 0.00 386 | 0.00 373 | 0.00 386 | 0.00 380 | 0.00 381 | 0.27 381 | 0.00 385 | 0.00 381 | 0.00 379 | 0.00 379 | 0.00 377 |
|
DCPMVS | | | 0.02 350 | 0.03 353 | 0.00 362 | 0.00 385 | 0.00 386 | 0.00 373 | 0.00 386 | 0.00 380 | 0.00 381 | 0.27 381 | 0.00 385 | 0.00 381 | 0.00 379 | 0.00 379 | 0.00 377 |
|
cdsmvs_eth3d_5k | | | 24.64 346 | 32.85 349 | 0.00 362 | 0.00 385 | 0.00 386 | 0.00 373 | 99.51 103 | 0.00 380 | 0.00 381 | 99.56 207 | 96.58 138 | 0.00 381 | 0.00 379 | 0.00 379 | 0.00 377 |
|
pcd_1.5k_mvsjas | | | 8.27 348 | 11.03 351 | 0.00 362 | 0.00 385 | 0.00 386 | 0.00 373 | 0.00 386 | 0.00 380 | 0.00 381 | 0.27 381 | 99.01 18 | 0.00 381 | 0.00 379 | 0.00 379 | 0.00 377 |
|
sosnet-low-res | | | 0.02 350 | 0.03 353 | 0.00 362 | 0.00 385 | 0.00 386 | 0.00 373 | 0.00 386 | 0.00 380 | 0.00 381 | 0.27 381 | 0.00 385 | 0.00 381 | 0.00 379 | 0.00 379 | 0.00 377 |
|
sosnet | | | 0.02 350 | 0.03 353 | 0.00 362 | 0.00 385 | 0.00 386 | 0.00 373 | 0.00 386 | 0.00 380 | 0.00 381 | 0.27 381 | 0.00 385 | 0.00 381 | 0.00 379 | 0.00 379 | 0.00 377 |
|
uncertanet | | | 0.02 350 | 0.03 353 | 0.00 362 | 0.00 385 | 0.00 386 | 0.00 373 | 0.00 386 | 0.00 380 | 0.00 381 | 0.27 381 | 0.00 385 | 0.00 381 | 0.00 379 | 0.00 379 | 0.00 377 |
|
Regformer | | | 0.02 350 | 0.03 353 | 0.00 362 | 0.00 385 | 0.00 386 | 0.00 373 | 0.00 386 | 0.00 380 | 0.00 381 | 0.27 381 | 0.00 385 | 0.00 381 | 0.00 379 | 0.00 379 | 0.00 377 |
|
ab-mvs-re | | | 8.30 347 | 11.06 350 | 0.00 362 | 0.00 385 | 0.00 386 | 0.00 373 | 0.00 386 | 0.00 380 | 0.00 381 | 99.58 200 | 0.00 385 | 0.00 381 | 0.00 379 | 0.00 379 | 0.00 377 |
|
uanet | | | 0.02 350 | 0.03 353 | 0.00 362 | 0.00 385 | 0.00 386 | 0.00 373 | 0.00 386 | 0.00 380 | 0.00 381 | 0.27 381 | 0.00 385 | 0.00 381 | 0.00 379 | 0.00 379 | 0.00 377 |
|
MSC_two_6792asdad | | | | | 99.87 11 | 99.51 156 | 99.76 37 | | 99.33 241 | | | | | 99.96 22 | 98.87 89 | 99.84 63 | 99.89 6 |
|
PC_three_1452 | | | | | | | | | | 98.18 115 | 99.84 18 | 99.70 142 | 99.31 3 | 98.52 342 | 98.30 167 | 99.80 83 | 99.81 47 |
|
No_MVS | | | | | 99.87 11 | 99.51 156 | 99.76 37 | | 99.33 241 | | | | | 99.96 22 | 98.87 89 | 99.84 63 | 99.89 6 |
|
test_one_0601 | | | | | | 99.81 41 | 99.88 8 | | 99.49 130 | 98.97 39 | 99.65 75 | 99.81 76 | 99.09 14 | | | | |
|
eth-test2 | | | | | | 0.00 385 | | | | | | | | | | | |
|
eth-test | | | | | | 0.00 385 | | | | | | | | | | | |
|
ZD-MVS | | | | | | 99.71 87 | 99.79 30 | | 99.61 36 | 96.84 248 | 99.56 98 | 99.54 215 | 98.58 67 | 99.96 22 | 96.93 272 | 99.75 98 | |
|
IU-MVS | | | | | | 99.84 31 | 99.88 8 | | 99.32 251 | 98.30 96 | 99.84 18 | | | | 98.86 94 | 99.85 55 | 99.89 6 |
|
test_241102_TWO | | | | | | | | | 99.48 142 | 99.08 21 | 99.88 11 | 99.81 76 | 98.94 29 | 99.96 22 | 98.91 83 | 99.84 63 | 99.88 12 |
|
test_241102_ONE | | | | | | 99.84 31 | 99.90 2 | | 99.48 142 | 99.07 23 | 99.91 7 | 99.74 127 | 99.20 7 | 99.76 177 | | | |
|
test_0728_THIRD | | | | | | | | | | 98.99 33 | 99.81 25 | 99.80 89 | 99.09 14 | 99.96 22 | 98.85 96 | 99.90 25 | 99.88 12 |
|
GSMVS | | | | | | | | | | | | | | | | | 99.52 148 |
|
test_part2 | | | | | | 99.81 41 | 99.83 16 | | | | 99.77 38 | | | | | | |
|
sam_mvs1 | | | | | | | | | | | | | 94.86 198 | | | | 99.52 148 |
|
sam_mvs | | | | | | | | | | | | | 94.72 210 | | | | |
|
MTGPA |  | | | | | | | | 99.47 160 | | | | | | | | |
|
test_post | | | | | | | | | | | | 65.99 376 | 94.65 214 | 99.73 186 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 98.70 335 | 94.79 202 | 99.74 180 | | | |
|
gm-plane-assit | | | | | | 98.54 333 | 92.96 351 | | | 94.65 330 | | 99.15 304 | | 99.64 220 | 97.56 229 | | |
|
test9_res | | | | | | | | | | | | | | | 97.49 235 | 99.72 104 | 99.75 74 |
|
agg_prior2 | | | | | | | | | | | | | | | 97.21 251 | 99.73 103 | 99.75 74 |
|
agg_prior | | | | | | 99.67 100 | 99.62 59 | | 99.40 207 | | 98.87 241 | | | 99.91 90 | | | |
|
TestCases | | | | | 99.31 128 | 99.86 20 | 98.48 199 | | 99.61 36 | 97.85 152 | 99.36 148 | 99.85 42 | 95.95 158 | 99.85 129 | 96.66 285 | 99.83 72 | 99.59 133 |
|
test_prior | | | | | 99.68 54 | 99.67 100 | 99.48 80 | | 99.56 57 | | | | | 99.83 146 | | | 99.74 78 |
|
æ–°å‡ ä½•1 | | | | | 99.75 47 | 99.75 64 | 99.59 62 | | 99.54 73 | 96.76 251 | 99.29 163 | 99.64 176 | 98.43 78 | 99.94 57 | 96.92 274 | 99.66 114 | 99.72 89 |
|
旧先验1 | | | | | | 99.74 71 | 99.59 62 | | 99.54 73 | | | 99.69 152 | 98.47 75 | | | 99.68 112 | 99.73 83 |
|
原ACMM1 | | | | | 99.65 59 | 99.73 78 | 99.33 91 | | 99.47 160 | 97.46 192 | 99.12 198 | 99.66 169 | 98.67 63 | 99.91 90 | 97.70 217 | 99.69 109 | 99.71 96 |
|
testdata2 | | | | | | | | | | | | | | 99.95 48 | 96.67 284 | | |
|
segment_acmp | | | | | | | | | | | | | 98.96 24 | | | | |
|
testdata | | | | | 99.54 82 | 99.75 64 | 98.95 148 | | 99.51 103 | 97.07 231 | 99.43 124 | 99.70 142 | 98.87 37 | 99.94 57 | 97.76 208 | 99.64 117 | 99.72 89 |
|
test12 | | | | | 99.75 47 | 99.64 116 | 99.61 60 | | 99.29 263 | | 99.21 182 | | 98.38 82 | 99.89 111 | | 99.74 101 | 99.74 78 |
|
plane_prior7 | | | | | | 99.29 220 | 97.03 268 | | | | | | | | | | |
|
plane_prior6 | | | | | | 99.27 225 | 96.98 272 | | | | | | 92.71 265 | | | | |
|
plane_prior5 | | | | | | | | | 99.47 160 | | | | | 99.69 207 | 97.78 205 | 97.63 228 | 98.67 263 |
|
plane_prior4 | | | | | | | | | | | | 99.61 191 | | | | | |
|
plane_prior3 | | | | | | | 97.00 270 | | | 98.69 64 | 99.11 200 | | | | | | |
|
plane_prior1 | | | | | | 99.26 227 | | | | | | | | | | | |
|
n2 | | | | | | | | | 0.00 386 | | | | | | | | |
|
nn | | | | | | | | | 0.00 386 | | | | | | | | |
|
door-mid | | | | | | | | | 98.05 353 | | | | | | | | |
|
lessismore_v0 | | | | | 97.79 298 | 98.69 320 | 95.44 318 | | 94.75 373 | | 95.71 346 | 99.87 32 | 88.69 327 | 99.32 271 | 95.89 299 | 94.93 312 | 98.62 286 |
|
LGP-MVS_train | | | | | 98.49 238 | 99.33 208 | 97.05 264 | | 99.55 65 | 97.46 192 | 99.24 174 | 99.83 56 | 92.58 270 | 99.72 190 | 98.09 179 | 97.51 240 | 98.68 256 |
|
test11 | | | | | | | | | 99.35 230 | | | | | | | | |
|
door | | | | | | | | | 97.92 354 | | | | | | | | |
|
HQP5-MVS | | | | | | | 96.83 278 | | | | | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 97.19 255 | | |
|
HQP4-MVS | | | | | | | | | | | 98.66 268 | | | 99.64 220 | | | 98.64 275 |
|
HQP3-MVS | | | | | | | | | 99.39 210 | | | | | | | 97.58 233 | |
|
HQP2-MVS | | | | | | | | | | | | | 92.47 274 | | | | |
|
NP-MVS | | | | | | 99.23 233 | 96.92 276 | | | | | 99.40 256 | | | | | |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 97.19 262 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 97.43 252 | |
|
Test By Simon | | | | | | | | | | | | | 98.75 54 | | | | |
|
ITE_SJBPF | | | | | 98.08 277 | 99.29 220 | 96.37 295 | | 98.92 310 | 98.34 92 | 98.83 246 | 99.75 122 | 91.09 303 | 99.62 226 | 95.82 300 | 97.40 254 | 98.25 328 |
|
DeepMVS_CX |  | | | | 93.34 341 | 99.29 220 | 82.27 368 | | 99.22 274 | 85.15 363 | 96.33 340 | 99.05 314 | 90.97 305 | 99.73 186 | 93.57 335 | 97.77 225 | 98.01 339 |
|