LCM-MVSNet | | | 99.93 1 | 99.92 1 | 99.94 1 | 99.99 1 | 99.97 1 | 99.90 1 | 99.89 2 | 99.98 1 | 99.99 1 | 99.96 1 | 99.77 1 | 100.00 1 | 99.81 3 | 100.00 1 | 99.85 9 |
|
HyFIR lowres test | | | 97.19 219 | 96.60 235 | 98.96 114 | 99.62 54 | 97.28 164 | 95.17 318 | 99.50 65 | 94.21 285 | 99.01 119 | 98.32 230 | 86.61 289 | 99.99 2 | 97.10 141 | 99.84 73 | 99.60 52 |
|
jajsoiax | | | 99.58 8 | 99.61 7 | 99.48 44 | 99.87 12 | 98.61 71 | 99.28 29 | 99.66 19 | 99.09 68 | 99.89 8 | 99.68 19 | 99.53 4 | 99.97 3 | 99.50 22 | 99.99 11 | 99.87 6 |
|
mvs_tets | | | 99.63 5 | 99.67 5 | 99.49 43 | 99.88 8 | 98.61 71 | 99.34 15 | 99.71 12 | 99.27 45 | 99.90 5 | 99.74 8 | 99.68 3 | 99.97 3 | 99.55 20 | 99.99 11 | 99.88 5 |
|
DTE-MVSNet | | | 99.43 18 | 99.35 22 | 99.66 4 | 99.71 34 | 99.30 12 | 99.31 20 | 99.51 64 | 99.64 10 | 99.56 33 | 99.46 52 | 98.23 50 | 99.97 3 | 98.78 59 | 99.93 39 | 99.72 24 |
|
MVSFormer | | | 98.26 145 | 98.43 114 | 97.77 232 | 98.88 223 | 93.89 277 | 99.39 13 | 99.56 49 | 99.11 61 | 98.16 195 | 98.13 240 | 93.81 247 | 99.97 3 | 99.26 32 | 99.57 172 | 99.43 139 |
|
test_djsdf | | | 99.52 11 | 99.51 11 | 99.53 32 | 99.86 16 | 98.74 60 | 99.39 13 | 99.56 49 | 99.11 61 | 99.70 15 | 99.73 10 | 99.00 17 | 99.97 3 | 99.26 32 | 99.98 19 | 99.89 3 |
|
semantic-postprocess | | | | | 96.87 271 | 99.27 134 | 91.16 319 | | 99.25 152 | 99.10 65 | 99.41 58 | 99.35 68 | 92.91 259 | 99.96 8 | 98.65 66 | 99.94 33 | 99.49 110 |
|
UA-Net | | | 99.47 13 | 99.40 17 | 99.70 3 | 99.49 92 | 99.29 13 | 99.80 3 | 99.72 11 | 99.82 2 | 99.04 116 | 99.81 4 | 98.05 64 | 99.96 8 | 98.85 56 | 99.99 11 | 99.86 8 |
|
PS-MVSNAJss | | | 99.46 14 | 99.49 12 | 99.35 61 | 99.90 5 | 98.15 100 | 99.20 35 | 99.65 20 | 99.48 25 | 99.92 3 | 99.71 14 | 98.07 61 | 99.96 8 | 99.53 21 | 100.00 1 | 99.93 1 |
|
PEN-MVS | | | 99.41 20 | 99.34 24 | 99.62 6 | 99.73 28 | 99.14 34 | 99.29 25 | 99.54 58 | 99.62 16 | 99.56 33 | 99.42 59 | 98.16 57 | 99.96 8 | 98.78 59 | 99.93 39 | 99.77 16 |
|
K. test v3 | | | 98.00 164 | 97.66 178 | 99.03 105 | 99.79 24 | 97.56 152 | 99.19 39 | 92.47 344 | 99.62 16 | 99.52 39 | 99.66 22 | 89.61 278 | 99.96 8 | 99.25 34 | 99.81 88 | 99.56 75 |
|
Fast-Effi-MVS+-dtu | | | 98.27 143 | 98.09 150 | 98.81 133 | 98.43 282 | 98.11 103 | 97.61 191 | 99.50 65 | 98.64 95 | 97.39 260 | 97.52 276 | 98.12 60 | 99.95 13 | 96.90 148 | 98.71 268 | 98.38 278 |
|
Effi-MVS+-dtu | | | 98.26 145 | 97.90 166 | 99.35 61 | 98.02 302 | 99.49 3 | 98.02 148 | 99.16 182 | 98.29 118 | 97.64 237 | 97.99 253 | 96.44 170 | 99.95 13 | 96.66 165 | 98.93 259 | 98.60 267 |
|
anonymousdsp | | | 99.51 12 | 99.47 15 | 99.62 6 | 99.88 8 | 99.08 46 | 99.34 15 | 99.69 15 | 98.93 83 | 99.65 23 | 99.72 11 | 98.93 20 | 99.95 13 | 99.11 44 | 100.00 1 | 99.82 10 |
|
v7n | | | 99.53 10 | 99.57 10 | 99.41 52 | 99.88 8 | 98.54 79 | 99.45 10 | 99.61 30 | 99.66 9 | 99.68 20 | 99.66 22 | 98.44 42 | 99.95 13 | 99.73 8 | 99.96 28 | 99.75 21 |
|
PS-CasMVS | | | 99.40 21 | 99.33 26 | 99.62 6 | 99.71 34 | 99.10 42 | 99.29 25 | 99.53 59 | 99.53 24 | 99.46 50 | 99.41 61 | 98.23 50 | 99.95 13 | 98.89 55 | 99.95 30 | 99.81 12 |
|
TranMVSNet+NR-MVSNet | | | 99.17 35 | 99.07 47 | 99.46 49 | 99.37 120 | 98.87 55 | 98.39 114 | 99.42 96 | 99.42 31 | 99.36 66 | 99.06 117 | 98.38 44 | 99.95 13 | 98.34 81 | 99.90 57 | 99.57 70 |
|
Vis-MVSNet | | | 99.34 26 | 99.36 21 | 99.27 73 | 99.73 28 | 98.26 93 | 99.17 41 | 99.78 5 | 99.11 61 | 99.27 82 | 99.48 50 | 98.82 22 | 99.95 13 | 98.94 52 | 99.93 39 | 99.59 58 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
Anonymous20231211 | | | 99.71 2 | 99.70 3 | 99.74 2 | 99.97 2 | 99.52 2 | 99.74 4 | 99.82 4 | 99.73 6 | 99.91 4 | 99.89 2 | 99.27 9 | 99.94 20 | 99.02 49 | 99.94 33 | 99.75 21 |
|
CP-MVSNet | | | 99.21 32 | 99.09 45 | 99.56 18 | 99.65 47 | 98.96 53 | 99.13 46 | 99.34 121 | 99.42 31 | 99.33 72 | 99.26 79 | 97.01 132 | 99.94 20 | 98.74 63 | 99.93 39 | 99.79 14 |
|
PVSNet_Blended_VisFu | | | 98.17 155 | 98.15 144 | 98.22 210 | 99.73 28 | 95.15 242 | 97.36 210 | 99.68 16 | 94.45 279 | 98.99 122 | 99.27 77 | 96.87 143 | 99.94 20 | 97.13 138 | 99.91 54 | 99.57 70 |
|
IterMVS | | | 97.73 182 | 98.11 148 | 96.57 281 | 99.24 138 | 90.28 320 | 95.52 310 | 99.21 159 | 98.86 85 | 99.33 72 | 99.33 72 | 93.11 255 | 99.94 20 | 98.49 74 | 99.94 33 | 99.48 116 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
ANet_high | | | 99.57 9 | 99.67 5 | 99.28 70 | 99.89 7 | 98.09 104 | 99.14 44 | 99.93 1 | 99.82 2 | 99.93 2 | 99.81 4 | 99.17 14 | 99.94 20 | 99.31 30 | 100.00 1 | 99.82 10 |
|
wuykxyi23d | | | 99.36 25 | 99.31 28 | 99.50 41 | 99.81 21 | 98.67 67 | 98.08 134 | 99.75 8 | 98.03 126 | 99.90 5 | 99.60 34 | 99.18 12 | 99.94 20 | 99.46 25 | 99.98 19 | 99.89 3 |
|
CHOSEN 280x420 | | | 95.51 268 | 95.47 260 | 95.65 307 | 98.25 290 | 88.27 327 | 93.25 340 | 98.88 227 | 93.53 292 | 94.65 330 | 97.15 293 | 86.17 291 | 99.93 26 | 97.41 126 | 99.93 39 | 98.73 259 |
|
v52 | | | 99.59 6 | 99.60 8 | 99.55 20 | 99.87 12 | 99.00 47 | 99.59 7 | 99.56 49 | 99.56 22 | 99.68 20 | 99.72 11 | 98.57 34 | 99.93 26 | 99.85 1 | 99.99 11 | 99.72 24 |
|
V4 | | | 99.59 6 | 99.60 8 | 99.55 20 | 99.87 12 | 99.00 47 | 99.59 7 | 99.56 49 | 99.56 22 | 99.68 20 | 99.72 11 | 98.57 34 | 99.93 26 | 99.85 1 | 99.99 11 | 99.72 24 |
|
UniMVSNet_NR-MVSNet | | | 98.86 64 | 98.68 79 | 99.40 54 | 99.17 165 | 98.74 60 | 97.68 180 | 99.40 98 | 99.14 59 | 99.06 108 | 98.59 203 | 96.71 155 | 99.93 26 | 98.57 70 | 99.77 104 | 99.53 91 |
|
DU-MVS | | | 98.82 66 | 98.63 85 | 99.39 55 | 99.16 167 | 98.74 60 | 97.54 200 | 99.25 152 | 98.84 86 | 99.06 108 | 98.76 175 | 96.76 152 | 99.93 26 | 98.57 70 | 99.77 104 | 99.50 103 |
|
WR-MVS_H | | | 99.33 27 | 99.22 36 | 99.65 5 | 99.71 34 | 99.24 19 | 99.32 17 | 99.55 54 | 99.46 28 | 99.50 44 | 99.34 70 | 97.30 109 | 99.93 26 | 98.90 53 | 99.93 39 | 99.77 16 |
|
SixPastTwentyTwo | | | 98.75 75 | 98.62 86 | 99.16 84 | 99.83 19 | 97.96 121 | 99.28 29 | 98.20 272 | 99.37 36 | 99.70 15 | 99.65 25 | 92.65 263 | 99.93 26 | 99.04 48 | 99.84 73 | 99.60 52 |
|
IterMVS-LS | | | 98.55 113 | 98.70 74 | 98.09 216 | 99.48 97 | 94.73 249 | 97.22 221 | 99.39 100 | 98.97 78 | 99.38 62 | 99.31 74 | 96.00 185 | 99.93 26 | 98.58 68 | 99.97 23 | 99.60 52 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
xiu_mvs_v1_base_debu | | | 97.86 174 | 98.17 139 | 96.92 268 | 98.98 202 | 93.91 274 | 96.45 265 | 99.17 179 | 97.85 144 | 98.41 187 | 97.14 294 | 98.47 39 | 99.92 34 | 98.02 95 | 99.05 246 | 96.92 320 |
|
MPTG | | | 98.79 69 | 98.52 96 | 99.61 9 | 99.67 44 | 99.36 7 | 97.33 211 | 99.20 163 | 98.83 87 | 98.89 138 | 98.90 150 | 96.98 134 | 99.92 34 | 97.16 134 | 99.70 130 | 99.56 75 |
|
mvs-test1 | | | 97.83 180 | 97.48 190 | 98.89 124 | 98.02 302 | 99.20 23 | 97.20 222 | 99.16 182 | 98.29 118 | 96.46 299 | 97.17 291 | 96.44 170 | 99.92 34 | 96.66 165 | 97.90 309 | 97.54 313 |
|
xiu_mvs_v1_base | | | 97.86 174 | 98.17 139 | 96.92 268 | 98.98 202 | 93.91 274 | 96.45 265 | 99.17 179 | 97.85 144 | 98.41 187 | 97.14 294 | 98.47 39 | 99.92 34 | 98.02 95 | 99.05 246 | 96.92 320 |
|
xiu_mvs_v1_base_debi | | | 97.86 174 | 98.17 139 | 96.92 268 | 98.98 202 | 93.91 274 | 96.45 265 | 99.17 179 | 97.85 144 | 98.41 187 | 97.14 294 | 98.47 39 | 99.92 34 | 98.02 95 | 99.05 246 | 96.92 320 |
|
MTAPA | | | 98.88 61 | 98.64 84 | 99.61 9 | 99.67 44 | 99.36 7 | 98.43 111 | 99.20 163 | 98.83 87 | 98.89 138 | 98.90 150 | 96.98 134 | 99.92 34 | 97.16 134 | 99.70 130 | 99.56 75 |
|
LCM-MVSNet-Re | | | 98.64 96 | 98.48 103 | 99.11 90 | 98.85 228 | 98.51 81 | 98.49 97 | 99.83 3 | 98.37 108 | 99.69 17 | 99.46 52 | 98.21 54 | 99.92 34 | 94.13 253 | 99.30 214 | 98.91 239 |
|
lessismore_v0 | | | | | 98.97 113 | 99.73 28 | 97.53 154 | | 86.71 353 | | 99.37 64 | 99.52 45 | 89.93 276 | 99.92 34 | 98.99 51 | 99.72 123 | 99.44 134 |
|
OurMVSNet-221017-0 | | | 99.37 24 | 99.31 28 | 99.53 32 | 99.91 4 | 98.98 49 | 99.63 6 | 99.58 36 | 99.44 30 | 99.78 10 | 99.76 6 | 96.39 172 | 99.92 34 | 99.44 26 | 99.92 49 | 99.68 30 |
|
Fast-Effi-MVS+ | | | 97.67 186 | 97.38 196 | 98.57 168 | 98.71 248 | 97.43 159 | 97.23 218 | 99.45 85 | 94.82 272 | 96.13 303 | 96.51 302 | 98.52 38 | 99.91 43 | 96.19 192 | 98.83 261 | 98.37 280 |
|
v748 | | | 99.44 15 | 99.48 13 | 99.33 66 | 99.88 8 | 98.43 86 | 99.42 11 | 99.53 59 | 99.63 12 | 99.69 17 | 99.60 34 | 97.99 69 | 99.91 43 | 99.60 14 | 99.96 28 | 99.66 33 |
|
jason | | | 97.45 202 | 97.35 199 | 97.76 233 | 99.24 138 | 93.93 273 | 95.86 296 | 98.42 265 | 94.24 284 | 98.50 181 | 98.13 240 | 94.82 223 | 99.91 43 | 97.22 132 | 99.73 118 | 99.43 139 |
jason: jason. |
lupinMVS | | | 97.06 226 | 96.86 218 | 97.65 239 | 98.88 223 | 93.89 277 | 95.48 311 | 97.97 278 | 93.53 292 | 98.16 195 | 97.58 272 | 93.81 247 | 99.91 43 | 96.77 156 | 99.57 172 | 99.17 211 |
|
MVS_0304 | | | 98.02 161 | 97.88 168 | 98.46 187 | 98.22 295 | 96.39 201 | 96.50 262 | 99.49 71 | 98.03 126 | 97.24 266 | 98.33 229 | 94.80 226 | 99.90 47 | 98.31 84 | 99.95 30 | 99.08 217 |
|
xiu_mvs_v2_base | | | 97.16 221 | 97.49 187 | 96.17 293 | 98.54 274 | 92.46 295 | 95.45 312 | 98.84 234 | 97.25 191 | 97.48 251 | 96.49 303 | 98.31 47 | 99.90 47 | 96.34 187 | 98.68 270 | 96.15 336 |
|
PS-MVSNAJ | | | 97.08 225 | 97.39 195 | 96.16 295 | 98.56 271 | 92.46 295 | 95.24 317 | 98.85 233 | 97.25 191 | 97.49 250 | 95.99 311 | 98.07 61 | 99.90 47 | 96.37 185 | 98.67 271 | 96.12 337 |
|
DSMNet-mixed | | | 97.42 204 | 97.60 183 | 96.87 271 | 99.15 170 | 91.46 306 | 98.54 90 | 99.12 188 | 92.87 299 | 97.58 242 | 99.63 27 | 96.21 177 | 99.90 47 | 95.74 214 | 99.54 182 | 99.27 186 |
|
MIMVSNet1 | | | 99.38 23 | 99.32 27 | 99.55 20 | 99.86 16 | 99.19 24 | 99.41 12 | 99.59 34 | 99.59 19 | 99.71 14 | 99.57 39 | 97.12 124 | 99.90 47 | 99.21 38 | 99.87 68 | 99.54 86 |
|
QAPM | | | 97.31 209 | 96.81 221 | 98.82 132 | 98.80 240 | 97.49 155 | 99.06 53 | 99.19 169 | 90.22 327 | 97.69 235 | 99.16 98 | 96.91 137 | 99.90 47 | 90.89 316 | 99.41 200 | 99.07 219 |
|
EPP-MVSNet | | | 98.30 139 | 98.04 156 | 99.07 96 | 99.56 69 | 97.83 132 | 99.29 25 | 98.07 276 | 99.03 72 | 98.59 173 | 99.13 105 | 92.16 267 | 99.90 47 | 96.87 150 | 99.68 142 | 99.49 110 |
|
3Dnovator | | 98.27 2 | 98.81 68 | 98.73 67 | 99.05 102 | 98.76 242 | 97.81 137 | 99.25 32 | 99.30 138 | 98.57 103 | 98.55 178 | 99.33 72 | 97.95 73 | 99.90 47 | 97.16 134 | 99.67 147 | 99.44 134 |
|
OpenMVS | | 96.65 7 | 97.09 224 | 96.68 229 | 98.32 202 | 98.32 288 | 97.16 172 | 98.86 71 | 99.37 107 | 89.48 331 | 96.29 301 | 99.15 102 | 96.56 163 | 99.90 47 | 92.90 281 | 99.20 227 | 97.89 290 |
|
CANet | | | 97.87 173 | 97.76 172 | 98.19 212 | 97.75 310 | 95.51 234 | 96.76 248 | 99.05 199 | 97.74 147 | 96.93 275 | 98.21 238 | 95.59 202 | 99.89 56 | 97.86 104 | 99.93 39 | 99.19 206 |
|
APDe-MVS | | | 98.99 49 | 98.79 59 | 99.60 12 | 99.21 150 | 99.15 33 | 98.87 69 | 99.48 74 | 97.57 160 | 99.35 68 | 99.24 82 | 97.83 76 | 99.89 56 | 97.88 102 | 99.70 130 | 99.75 21 |
|
PGM-MVS | | | 98.66 93 | 98.37 122 | 99.55 20 | 99.53 79 | 99.18 25 | 98.23 120 | 99.49 71 | 97.01 204 | 98.69 160 | 98.88 156 | 98.00 67 | 99.89 56 | 95.87 208 | 99.59 162 | 99.58 65 |
|
abl_6 | | | 98.99 49 | 98.78 60 | 99.61 9 | 99.45 106 | 99.46 4 | 98.60 83 | 99.50 65 | 98.59 99 | 99.24 90 | 99.04 124 | 98.54 37 | 99.89 56 | 96.45 182 | 99.62 155 | 99.50 103 |
|
mPP-MVS | | | 98.64 96 | 98.34 126 | 99.54 25 | 99.54 77 | 99.17 26 | 98.63 80 | 99.24 156 | 97.47 169 | 98.09 200 | 98.68 184 | 97.62 88 | 99.89 56 | 96.22 190 | 99.62 155 | 99.57 70 |
|
CP-MVS | | | 98.70 82 | 98.42 115 | 99.52 37 | 99.36 121 | 99.12 39 | 98.72 77 | 99.36 111 | 97.54 164 | 98.30 192 | 98.40 222 | 97.86 75 | 99.89 56 | 96.53 177 | 99.72 123 | 99.56 75 |
|
IB-MVS | | 91.63 19 | 92.24 320 | 90.90 323 | 96.27 286 | 97.22 331 | 91.24 318 | 94.36 331 | 93.33 337 | 92.37 305 | 92.24 344 | 94.58 342 | 66.20 356 | 99.89 56 | 93.16 277 | 94.63 342 | 97.66 303 |
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 |
MP-MVS-pluss | | | 98.57 108 | 98.23 134 | 99.60 12 | 99.69 42 | 99.35 9 | 97.16 228 | 99.38 103 | 94.87 270 | 98.97 126 | 98.99 133 | 98.01 66 | 99.88 63 | 97.29 130 | 99.70 130 | 99.58 65 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
HSP-MVS | | | 98.34 135 | 97.94 162 | 99.54 25 | 99.57 62 | 99.25 18 | 98.57 86 | 98.84 234 | 97.55 163 | 99.31 79 | 97.71 265 | 94.61 231 | 99.88 63 | 96.14 197 | 99.19 231 | 99.48 116 |
|
region2R | | | 98.69 87 | 98.40 117 | 99.54 25 | 99.53 79 | 99.17 26 | 98.52 91 | 99.31 131 | 97.46 174 | 98.44 184 | 98.51 213 | 97.83 76 | 99.88 63 | 96.46 181 | 99.58 168 | 99.58 65 |
|
VPA-MVSNet | | | 99.30 28 | 99.30 31 | 99.28 70 | 99.49 92 | 98.36 91 | 99.00 59 | 99.45 85 | 99.63 12 | 99.52 39 | 99.44 57 | 98.25 48 | 99.88 63 | 99.09 45 | 99.84 73 | 99.62 45 |
|
ACMMPR | | | 98.70 82 | 98.42 115 | 99.54 25 | 99.52 81 | 99.14 34 | 98.52 91 | 99.31 131 | 97.47 169 | 98.56 177 | 98.54 211 | 97.75 81 | 99.88 63 | 96.57 171 | 99.59 162 | 99.58 65 |
|
MP-MVS | | | 98.46 125 | 98.09 150 | 99.54 25 | 99.57 62 | 99.22 20 | 98.50 96 | 99.19 169 | 97.61 156 | 97.58 242 | 98.66 188 | 97.40 104 | 99.88 63 | 94.72 236 | 99.60 161 | 99.54 86 |
|
CHOSEN 1792x2688 | | | 97.49 197 | 97.14 208 | 98.54 176 | 99.68 43 | 96.09 215 | 96.50 262 | 99.62 28 | 91.58 315 | 98.84 146 | 98.97 138 | 92.36 265 | 99.88 63 | 96.76 157 | 99.95 30 | 99.67 31 |
|
SteuartSystems-ACMMP | | | 98.79 69 | 98.54 94 | 99.54 25 | 99.73 28 | 99.16 28 | 98.23 120 | 99.31 131 | 97.92 130 | 98.90 136 | 98.90 150 | 98.00 67 | 99.88 63 | 96.15 196 | 99.72 123 | 99.58 65 |
Skip Steuart: Steuart Systems R&D Blog. |
FMVSNet5 | | | 96.01 258 | 95.20 269 | 98.41 192 | 97.53 320 | 96.10 213 | 98.74 75 | 99.50 65 | 97.22 199 | 98.03 205 | 99.04 124 | 69.80 351 | 99.88 63 | 97.27 131 | 99.71 127 | 99.25 191 |
|
pmmvs6 | | | 99.67 3 | 99.70 3 | 99.60 12 | 99.90 5 | 99.27 16 | 99.53 9 | 99.76 7 | 99.64 10 | 99.84 9 | 99.83 3 | 99.50 5 | 99.87 72 | 99.36 28 | 99.92 49 | 99.64 40 |
|
testmv | | | 98.51 120 | 98.47 105 | 98.61 161 | 99.24 138 | 96.53 193 | 96.66 255 | 99.73 10 | 98.56 105 | 99.50 44 | 99.23 86 | 97.24 117 | 99.87 72 | 96.16 195 | 99.93 39 | 99.44 134 |
|
HPM-MVS | | | 98.79 69 | 98.53 95 | 99.59 15 | 99.65 47 | 99.29 13 | 99.16 42 | 99.43 93 | 96.74 214 | 98.61 170 | 98.38 223 | 98.62 30 | 99.87 72 | 96.47 180 | 99.67 147 | 99.59 58 |
|
EPNet | | | 96.14 256 | 95.44 262 | 98.25 208 | 90.76 355 | 95.50 235 | 97.92 157 | 94.65 321 | 98.97 78 | 92.98 342 | 98.85 161 | 89.12 282 | 99.87 72 | 95.99 201 | 99.68 142 | 99.39 150 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
ACMMP | | | 98.75 75 | 98.50 99 | 99.52 37 | 99.56 69 | 99.16 28 | 98.87 69 | 99.37 107 | 97.16 200 | 98.82 150 | 99.01 130 | 97.71 82 | 99.87 72 | 96.29 188 | 99.69 137 | 99.54 86 |
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 |
test_part3 | | | | | | | | 97.25 216 | | 96.66 220 | | 98.71 179 | | 99.86 77 | 93.00 279 | | |
|
tfpnnormal | | | 98.90 60 | 98.90 52 | 98.91 121 | 99.67 44 | 97.82 135 | 99.00 59 | 99.44 88 | 99.45 29 | 99.51 43 | 99.24 82 | 98.20 55 | 99.86 77 | 95.92 204 | 99.69 137 | 99.04 222 |
|
ESAPD | | | 98.25 147 | 97.83 170 | 99.50 41 | 99.36 121 | 99.10 42 | 97.25 216 | 99.28 141 | 96.66 220 | 99.05 113 | 98.71 179 | 97.56 90 | 99.86 77 | 93.00 279 | 99.57 172 | 99.53 91 |
|
Regformer-4 | | | 98.73 78 | 98.68 79 | 98.89 124 | 99.02 196 | 97.22 167 | 97.17 226 | 99.06 195 | 99.21 47 | 99.17 99 | 98.85 161 | 97.45 100 | 99.86 77 | 98.48 75 | 99.70 130 | 99.60 52 |
|
UniMVSNet (Re) | | | 98.87 62 | 98.71 71 | 99.35 61 | 99.24 138 | 98.73 63 | 97.73 176 | 99.38 103 | 98.93 83 | 99.12 102 | 98.73 177 | 96.77 150 | 99.86 77 | 98.63 67 | 99.80 92 | 99.46 128 |
|
NR-MVSNet | | | 98.95 56 | 98.82 56 | 99.36 56 | 99.16 167 | 98.72 65 | 99.22 34 | 99.20 163 | 99.10 65 | 99.72 13 | 98.76 175 | 96.38 173 | 99.86 77 | 98.00 98 | 99.82 82 | 99.50 103 |
|
GBi-Net | | | 98.65 94 | 98.47 105 | 99.17 81 | 98.90 218 | 98.24 94 | 99.20 35 | 99.44 88 | 98.59 99 | 98.95 129 | 99.55 41 | 94.14 240 | 99.86 77 | 97.77 107 | 99.69 137 | 99.41 144 |
|
test1 | | | 98.65 94 | 98.47 105 | 99.17 81 | 98.90 218 | 98.24 94 | 99.20 35 | 99.44 88 | 98.59 99 | 98.95 129 | 99.55 41 | 94.14 240 | 99.86 77 | 97.77 107 | 99.69 137 | 99.41 144 |
|
FMVSNet1 | | | 99.17 35 | 99.17 39 | 99.17 81 | 99.55 73 | 98.24 94 | 99.20 35 | 99.44 88 | 99.21 47 | 99.43 55 | 99.55 41 | 97.82 79 | 99.86 77 | 98.42 78 | 99.89 63 | 99.41 144 |
|
XXY-MVS | | | 99.14 37 | 99.15 43 | 99.10 92 | 99.76 26 | 97.74 143 | 98.85 72 | 99.62 28 | 98.48 106 | 99.37 64 | 99.49 49 | 98.75 25 | 99.86 77 | 98.20 88 | 99.80 92 | 99.71 27 |
|
1112_ss | | | 97.29 212 | 96.86 218 | 98.58 166 | 99.34 127 | 96.32 203 | 96.75 249 | 99.58 36 | 93.14 296 | 96.89 281 | 97.48 279 | 92.11 268 | 99.86 77 | 96.91 146 | 99.54 182 | 99.57 70 |
|
patchmatchnet-post | | | | | | | | | | | | 98.77 173 | 84.37 306 | 99.85 88 | | | |
|
FC-MVSNet-test | | | 99.27 29 | 99.25 34 | 99.34 64 | 99.77 25 | 98.37 90 | 99.30 24 | 99.57 43 | 99.61 18 | 99.40 60 | 99.50 46 | 97.12 124 | 99.85 88 | 99.02 49 | 99.94 33 | 99.80 13 |
|
HFP-MVS | | | 98.71 80 | 98.44 112 | 99.51 39 | 99.49 92 | 99.16 28 | 98.52 91 | 99.31 131 | 97.47 169 | 98.58 175 | 98.50 216 | 97.97 71 | 99.85 88 | 96.57 171 | 99.59 162 | 99.53 91 |
|
#test# | | | 98.50 121 | 98.16 142 | 99.51 39 | 99.49 92 | 99.16 28 | 98.03 141 | 99.31 131 | 96.30 232 | 98.58 175 | 98.50 216 | 97.97 71 | 99.85 88 | 95.68 218 | 99.59 162 | 99.53 91 |
|
EI-MVSNet-UG-set | | | 98.69 87 | 98.71 71 | 98.62 158 | 99.10 174 | 96.37 202 | 97.23 218 | 98.87 228 | 99.20 50 | 99.19 95 | 98.99 133 | 97.30 109 | 99.85 88 | 98.77 62 | 99.79 96 | 99.65 37 |
|
EI-MVSNet-Vis-set | | | 98.68 90 | 98.70 74 | 98.63 156 | 99.09 177 | 96.40 200 | 97.23 218 | 98.86 232 | 99.20 50 | 99.18 98 | 98.97 138 | 97.29 111 | 99.85 88 | 98.72 64 | 99.78 100 | 99.64 40 |
|
v1240 | | | 98.55 113 | 98.62 86 | 98.32 202 | 99.22 144 | 95.58 231 | 97.51 203 | 99.45 85 | 97.16 200 | 99.45 53 | 99.24 82 | 96.12 180 | 99.85 88 | 99.60 14 | 99.88 64 | 99.55 83 |
|
APD-MVS_3200maxsize | | | 98.84 65 | 98.61 89 | 99.53 32 | 99.19 160 | 99.27 16 | 98.49 97 | 99.33 126 | 98.64 95 | 99.03 118 | 98.98 136 | 97.89 74 | 99.85 88 | 96.54 176 | 99.42 199 | 99.46 128 |
|
ADS-MVSNet2 | | | 95.43 269 | 94.98 274 | 96.76 275 | 98.14 298 | 91.74 302 | 97.92 157 | 97.76 282 | 90.23 325 | 96.51 295 | 98.91 147 | 85.61 297 | 99.85 88 | 92.88 282 | 96.90 325 | 98.69 263 |
|
MDA-MVSNet-bldmvs | | | 97.94 168 | 97.91 165 | 98.06 221 | 99.44 109 | 94.96 246 | 96.63 257 | 99.15 185 | 98.35 109 | 98.83 147 | 99.11 107 | 94.31 237 | 99.85 88 | 96.60 168 | 98.72 265 | 99.37 157 |
|
WR-MVS | | | 98.40 131 | 98.19 138 | 99.03 105 | 99.00 199 | 97.65 148 | 96.85 244 | 98.94 216 | 98.57 103 | 98.89 138 | 98.50 216 | 95.60 201 | 99.85 88 | 97.54 118 | 99.85 71 | 99.59 58 |
|
APD-MVS | | | 98.10 157 | 97.67 175 | 99.42 50 | 99.11 173 | 98.93 54 | 97.76 173 | 99.28 141 | 94.97 267 | 98.72 159 | 98.77 173 | 97.04 128 | 99.85 88 | 93.79 263 | 99.54 182 | 99.49 110 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
LP | | | 96.60 246 | 96.57 237 | 96.68 276 | 97.64 316 | 91.70 303 | 98.11 131 | 97.74 283 | 97.29 189 | 97.91 209 | 99.24 82 | 88.35 284 | 99.85 88 | 97.11 140 | 95.76 336 | 98.49 271 |
|
Patchmtry | | | 97.35 206 | 96.97 212 | 98.50 183 | 97.31 329 | 96.47 196 | 98.18 124 | 98.92 222 | 98.95 82 | 98.78 153 | 99.37 65 | 85.44 300 | 99.85 88 | 95.96 203 | 99.83 79 | 99.17 211 |
|
N_pmnet | | | 97.63 189 | 97.17 205 | 98.99 112 | 99.27 134 | 97.86 130 | 95.98 284 | 93.41 336 | 95.25 262 | 99.47 49 | 98.90 150 | 95.63 200 | 99.85 88 | 96.91 146 | 99.73 118 | 99.27 186 |
|
CANet_DTU | | | 97.26 213 | 97.06 209 | 97.84 229 | 97.57 317 | 94.65 253 | 96.19 280 | 98.79 243 | 97.23 196 | 95.14 327 | 98.24 235 | 93.22 253 | 99.84 103 | 97.34 128 | 99.84 73 | 99.04 222 |
|
ACMMP_Plus | | | 98.75 75 | 98.48 103 | 99.57 16 | 99.58 57 | 99.29 13 | 97.82 168 | 99.25 152 | 96.94 206 | 98.78 153 | 99.12 106 | 98.02 65 | 99.84 103 | 97.13 138 | 99.67 147 | 99.59 58 |
|
v144192 | | | 98.54 116 | 98.57 93 | 98.45 189 | 99.21 150 | 95.98 217 | 97.63 188 | 99.36 111 | 97.15 202 | 99.32 77 | 99.18 92 | 95.84 196 | 99.84 103 | 99.50 22 | 99.91 54 | 99.54 86 |
|
v1921920 | | | 98.54 116 | 98.60 91 | 98.38 198 | 99.20 159 | 95.76 227 | 97.56 197 | 99.36 111 | 97.23 196 | 99.38 62 | 99.17 97 | 96.02 183 | 99.84 103 | 99.57 18 | 99.90 57 | 99.54 86 |
|
Regformer-2 | | | 98.60 105 | 98.46 108 | 99.02 108 | 98.85 228 | 97.71 145 | 96.91 240 | 99.09 192 | 98.98 77 | 99.01 119 | 98.64 193 | 97.37 106 | 99.84 103 | 97.75 111 | 99.57 172 | 99.52 96 |
|
HPM-MVS++ | | | 98.10 157 | 97.64 180 | 99.48 44 | 99.09 177 | 99.13 37 | 97.52 201 | 98.75 248 | 97.46 174 | 96.90 280 | 97.83 260 | 96.01 184 | 99.84 103 | 95.82 212 | 99.35 206 | 99.46 128 |
|
v13 | | | 99.24 31 | 99.39 18 | 98.77 140 | 99.63 52 | 96.79 184 | 99.24 33 | 99.65 20 | 99.39 33 | 99.62 27 | 99.70 16 | 97.50 95 | 99.84 103 | 99.78 5 | 100.00 1 | 99.67 31 |
|
PMMVS2 | | | 98.07 160 | 98.08 153 | 98.04 223 | 99.41 115 | 94.59 255 | 94.59 329 | 99.40 98 | 97.50 166 | 98.82 150 | 98.83 164 | 96.83 145 | 99.84 103 | 97.50 121 | 99.81 88 | 99.71 27 |
|
XVG-ACMP-BASELINE | | | 98.56 109 | 98.34 126 | 99.22 79 | 99.54 77 | 98.59 73 | 97.71 177 | 99.46 82 | 97.25 191 | 98.98 124 | 98.99 133 | 97.54 93 | 99.84 103 | 95.88 205 | 99.74 115 | 99.23 195 |
|
CPTT-MVS | | | 97.84 179 | 97.36 197 | 99.27 73 | 99.31 130 | 98.46 84 | 98.29 116 | 99.27 146 | 94.90 269 | 97.83 220 | 98.37 224 | 94.90 218 | 99.84 103 | 93.85 262 | 99.54 182 | 99.51 98 |
|
UGNet | | | 98.53 118 | 98.45 110 | 98.79 135 | 97.94 305 | 96.96 179 | 99.08 49 | 98.54 260 | 99.10 65 | 96.82 285 | 99.47 51 | 96.55 164 | 99.84 103 | 98.56 73 | 99.94 33 | 99.55 83 |
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 |
CSCG | | | 98.68 90 | 98.50 99 | 99.20 80 | 99.45 106 | 98.63 68 | 98.56 87 | 99.57 43 | 97.87 142 | 98.85 144 | 98.04 251 | 97.66 83 | 99.84 103 | 96.72 159 | 99.81 88 | 99.13 215 |
|
DeepC-MVS | | 97.60 4 | 98.97 54 | 98.93 51 | 99.10 92 | 99.35 125 | 97.98 118 | 98.01 149 | 99.46 82 | 97.56 162 | 99.54 35 | 99.50 46 | 98.97 18 | 99.84 103 | 98.06 93 | 99.92 49 | 99.49 110 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
3Dnovator+ | | 97.89 3 | 98.69 87 | 98.51 97 | 99.24 77 | 98.81 238 | 98.40 87 | 99.02 54 | 99.19 169 | 98.99 75 | 98.07 201 | 99.28 75 | 97.11 126 | 99.84 103 | 96.84 152 | 99.32 211 | 99.47 124 |
|
Anonymous20231206 | | | 98.21 150 | 98.21 135 | 98.20 211 | 99.51 84 | 95.43 237 | 98.13 128 | 99.32 129 | 96.16 238 | 98.93 134 | 98.82 167 | 96.00 185 | 99.83 117 | 97.32 129 | 99.73 118 | 99.36 163 |
|
XVS | | | 98.72 79 | 98.45 110 | 99.53 32 | 99.46 103 | 99.21 21 | 98.65 78 | 99.34 121 | 98.62 97 | 97.54 246 | 98.63 197 | 97.50 95 | 99.83 117 | 96.79 154 | 99.53 186 | 99.56 75 |
|
X-MVStestdata | | | 94.32 295 | 92.59 312 | 99.53 32 | 99.46 103 | 99.21 21 | 98.65 78 | 99.34 121 | 98.62 97 | 97.54 246 | 45.85 352 | 97.50 95 | 99.83 117 | 96.79 154 | 99.53 186 | 99.56 75 |
|
v12 | | | 99.21 32 | 99.37 20 | 98.74 148 | 99.60 55 | 96.72 189 | 99.19 39 | 99.65 20 | 99.35 39 | 99.62 27 | 99.69 17 | 97.43 102 | 99.83 117 | 99.76 6 | 100.00 1 | 99.66 33 |
|
v11 | | | 99.12 40 | 99.31 28 | 98.53 177 | 99.59 56 | 96.11 212 | 99.08 49 | 99.65 20 | 99.15 56 | 99.60 30 | 99.69 17 | 97.26 115 | 99.83 117 | 99.81 3 | 100.00 1 | 99.66 33 |
|
v10 | | | 98.97 54 | 99.11 44 | 98.55 173 | 99.44 109 | 96.21 210 | 98.90 67 | 99.55 54 | 98.73 93 | 99.48 46 | 99.60 34 | 96.63 158 | 99.83 117 | 99.70 11 | 99.99 11 | 99.61 49 |
|
V9 | | | 99.18 34 | 99.34 24 | 98.70 149 | 99.58 57 | 96.63 192 | 99.14 44 | 99.64 24 | 99.30 42 | 99.61 29 | 99.68 19 | 97.33 107 | 99.83 117 | 99.75 7 | 100.00 1 | 99.65 37 |
|
TransMVSNet (Re) | | | 99.44 15 | 99.47 15 | 99.36 56 | 99.80 22 | 98.58 74 | 99.27 31 | 99.57 43 | 99.39 33 | 99.75 12 | 99.62 28 | 99.17 14 | 99.83 117 | 99.06 47 | 99.62 155 | 99.66 33 |
|
Baseline_NR-MVSNet | | | 98.98 53 | 98.86 53 | 99.36 56 | 99.82 20 | 98.55 76 | 97.47 206 | 99.57 43 | 99.37 36 | 99.21 94 | 99.61 30 | 96.76 152 | 99.83 117 | 98.06 93 | 99.83 79 | 99.71 27 |
|
LPG-MVS_test | | | 98.71 80 | 98.46 108 | 99.47 47 | 99.57 62 | 98.97 50 | 98.23 120 | 99.48 74 | 96.60 223 | 99.10 105 | 99.06 117 | 98.71 27 | 99.83 117 | 95.58 222 | 99.78 100 | 99.62 45 |
|
LGP-MVS_train | | | | | 99.47 47 | 99.57 62 | 98.97 50 | | 99.48 74 | 96.60 223 | 99.10 105 | 99.06 117 | 98.71 27 | 99.83 117 | 95.58 222 | 99.78 100 | 99.62 45 |
|
Test_1112_low_res | | | 96.99 231 | 96.55 238 | 98.31 204 | 99.35 125 | 95.47 236 | 95.84 299 | 99.53 59 | 91.51 317 | 96.80 286 | 98.48 219 | 91.36 271 | 99.83 117 | 96.58 169 | 99.53 186 | 99.62 45 |
|
new-patchmatchnet | | | 98.35 134 | 98.74 66 | 97.18 259 | 99.24 138 | 92.23 299 | 96.42 268 | 99.48 74 | 98.30 115 | 99.69 17 | 99.53 44 | 97.44 101 | 99.82 129 | 98.84 58 | 99.77 104 | 99.49 110 |
|
FIs | | | 99.14 37 | 99.09 45 | 99.29 69 | 99.70 40 | 98.28 92 | 99.13 46 | 99.52 63 | 99.48 25 | 99.24 90 | 99.41 61 | 96.79 149 | 99.82 129 | 98.69 65 | 99.88 64 | 99.76 19 |
|
v1192 | | | 98.60 105 | 98.66 82 | 98.41 192 | 99.27 134 | 95.88 223 | 97.52 201 | 99.36 111 | 97.41 177 | 99.33 72 | 99.20 89 | 96.37 174 | 99.82 129 | 99.57 18 | 99.92 49 | 99.55 83 |
|
pm-mvs1 | | | 99.44 15 | 99.48 13 | 99.33 66 | 99.80 22 | 98.63 68 | 99.29 25 | 99.63 25 | 99.30 42 | 99.65 23 | 99.60 34 | 99.16 16 | 99.82 129 | 99.07 46 | 99.83 79 | 99.56 75 |
|
V14 | | | 99.14 37 | 99.30 31 | 98.66 152 | 99.56 69 | 96.53 193 | 99.08 49 | 99.63 25 | 99.24 46 | 99.60 30 | 99.66 22 | 97.23 119 | 99.82 129 | 99.73 8 | 100.00 1 | 99.65 37 |
|
VPNet | | | 98.87 62 | 98.83 55 | 99.01 109 | 99.70 40 | 97.62 151 | 98.43 111 | 99.35 117 | 99.47 27 | 99.28 80 | 99.05 122 | 96.72 154 | 99.82 129 | 98.09 91 | 99.36 204 | 99.59 58 |
|
pmmvs3 | | | 95.03 274 | 94.40 283 | 96.93 267 | 97.70 314 | 92.53 294 | 95.08 320 | 97.71 285 | 88.57 335 | 97.71 233 | 98.08 249 | 79.39 333 | 99.82 129 | 96.19 192 | 99.11 244 | 98.43 275 |
|
test1235678 | | | 97.06 226 | 96.84 220 | 97.73 235 | 98.55 273 | 94.46 262 | 94.80 325 | 99.36 111 | 96.85 211 | 98.83 147 | 98.26 233 | 92.72 262 | 99.82 129 | 92.49 292 | 99.70 130 | 98.91 239 |
|
HPM-MVS_fast | | | 99.01 47 | 98.82 56 | 99.57 16 | 99.71 34 | 99.35 9 | 99.00 59 | 99.50 65 | 97.33 183 | 98.94 133 | 98.86 159 | 98.75 25 | 99.82 129 | 97.53 119 | 99.71 127 | 99.56 75 |
|
DELS-MVS | | | 98.27 143 | 98.20 136 | 98.48 185 | 98.86 225 | 96.70 190 | 95.60 307 | 99.20 163 | 97.73 148 | 98.45 183 | 98.71 179 | 97.50 95 | 99.82 129 | 98.21 87 | 99.59 162 | 98.93 236 |
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 |
FMVSNet2 | | | 98.49 122 | 98.40 117 | 98.75 144 | 98.90 218 | 97.14 174 | 98.61 82 | 99.13 186 | 98.59 99 | 99.19 95 | 99.28 75 | 94.14 240 | 99.82 129 | 97.97 99 | 99.80 92 | 99.29 184 |
|
WTY-MVS | | | 96.67 242 | 96.27 246 | 97.87 228 | 98.81 238 | 94.61 254 | 96.77 247 | 97.92 280 | 94.94 268 | 97.12 267 | 97.74 264 | 91.11 272 | 99.82 129 | 93.89 259 | 98.15 293 | 99.18 207 |
|
ACMP | | 95.32 15 | 98.41 129 | 98.09 150 | 99.36 56 | 99.51 84 | 98.79 59 | 97.68 180 | 99.38 103 | 95.76 248 | 98.81 152 | 98.82 167 | 98.36 45 | 99.82 129 | 94.75 233 | 99.77 104 | 99.48 116 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
TSAR-MVS + MP. | | | 98.63 98 | 98.49 102 | 99.06 101 | 99.64 50 | 97.90 127 | 98.51 95 | 98.94 216 | 96.96 205 | 99.24 90 | 98.89 155 | 97.83 76 | 99.81 142 | 96.88 149 | 99.49 195 | 99.48 116 |
|
Regformer-1 | | | 98.55 113 | 98.44 112 | 98.87 126 | 98.85 228 | 97.29 162 | 96.91 240 | 98.99 215 | 98.97 78 | 98.99 122 | 98.64 193 | 97.26 115 | 99.81 142 | 97.79 105 | 99.57 172 | 99.51 98 |
|
v17 | | | 99.07 43 | 99.22 36 | 98.61 161 | 99.50 86 | 96.42 198 | 99.01 55 | 99.60 32 | 99.15 56 | 99.48 46 | 99.61 30 | 97.05 127 | 99.81 142 | 99.64 12 | 99.98 19 | 99.61 49 |
|
v16 | | | 99.07 43 | 99.22 36 | 98.61 161 | 99.50 86 | 96.42 198 | 99.01 55 | 99.60 32 | 99.15 56 | 99.46 50 | 99.61 30 | 97.04 128 | 99.81 142 | 99.64 12 | 99.97 23 | 99.61 49 |
|
v15 | | | 99.11 41 | 99.27 33 | 98.62 158 | 99.52 81 | 96.43 197 | 99.01 55 | 99.63 25 | 99.18 55 | 99.59 32 | 99.64 26 | 97.13 123 | 99.81 142 | 99.71 10 | 100.00 1 | 99.64 40 |
|
v8 | | | 99.01 47 | 99.16 41 | 98.57 168 | 99.47 99 | 96.31 204 | 98.90 67 | 99.47 80 | 99.03 72 | 99.52 39 | 99.57 39 | 96.93 136 | 99.81 142 | 99.60 14 | 99.98 19 | 99.60 52 |
|
CR-MVSNet | | | 96.28 254 | 95.95 251 | 97.28 256 | 97.71 312 | 94.22 264 | 98.11 131 | 98.92 222 | 92.31 306 | 96.91 278 | 99.37 65 | 85.44 300 | 99.81 142 | 97.39 127 | 97.36 319 | 97.81 296 |
|
PatchT | | | 96.65 243 | 96.35 243 | 97.54 247 | 97.40 326 | 95.32 239 | 97.98 152 | 96.64 309 | 99.33 40 | 96.89 281 | 99.42 59 | 84.32 307 | 99.81 142 | 97.69 114 | 97.49 314 | 97.48 314 |
|
RPMNet | | | 96.82 238 | 96.66 232 | 97.28 256 | 97.71 312 | 94.22 264 | 98.11 131 | 96.90 303 | 99.37 36 | 96.91 278 | 99.34 70 | 86.72 288 | 99.81 142 | 97.53 119 | 97.36 319 | 97.81 296 |
|
no-one | | | 97.98 167 | 98.10 149 | 97.61 242 | 99.55 73 | 93.82 279 | 96.70 252 | 98.94 216 | 96.18 234 | 99.52 39 | 99.41 61 | 95.90 194 | 99.81 142 | 96.72 159 | 99.99 11 | 99.20 201 |
|
FMVSNet3 | | | 97.50 196 | 97.24 202 | 98.29 206 | 98.08 300 | 95.83 225 | 97.86 164 | 98.91 224 | 97.89 139 | 98.95 129 | 98.95 142 | 87.06 287 | 99.81 142 | 97.77 107 | 99.69 137 | 99.23 195 |
|
LTVRE_ROB | | 98.40 1 | 99.67 3 | 99.71 2 | 99.56 18 | 99.85 18 | 99.11 41 | 99.90 1 | 99.78 5 | 99.63 12 | 99.78 10 | 99.67 21 | 99.48 6 | 99.81 142 | 99.30 31 | 99.97 23 | 99.77 16 |
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 |
conf0.01 | | | 94.82 282 | 94.07 288 | 97.06 263 | 99.21 150 | 94.53 256 | 98.47 103 | 92.69 338 | 95.61 250 | 97.81 223 | 95.54 319 | 77.71 339 | 99.80 154 | 91.49 304 | 98.11 295 | 96.86 323 |
|
conf0.002 | | | 94.82 282 | 94.07 288 | 97.06 263 | 99.21 150 | 94.53 256 | 98.47 103 | 92.69 338 | 95.61 250 | 97.81 223 | 95.54 319 | 77.71 339 | 99.80 154 | 91.49 304 | 98.11 295 | 96.86 323 |
|
thresconf0.02 | | | 94.70 286 | 94.07 288 | 96.58 277 | 99.21 150 | 94.53 256 | 98.47 103 | 92.69 338 | 95.61 250 | 97.81 223 | 95.54 319 | 77.71 339 | 99.80 154 | 91.49 304 | 98.11 295 | 95.42 342 |
|
tfpn_n400 | | | 94.70 286 | 94.07 288 | 96.58 277 | 99.21 150 | 94.53 256 | 98.47 103 | 92.69 338 | 95.61 250 | 97.81 223 | 95.54 319 | 77.71 339 | 99.80 154 | 91.49 304 | 98.11 295 | 95.42 342 |
|
tfpnconf | | | 94.70 286 | 94.07 288 | 96.58 277 | 99.21 150 | 94.53 256 | 98.47 103 | 92.69 338 | 95.61 250 | 97.81 223 | 95.54 319 | 77.71 339 | 99.80 154 | 91.49 304 | 98.11 295 | 95.42 342 |
|
tfpnview11 | | | 94.70 286 | 94.07 288 | 96.58 277 | 99.21 150 | 94.53 256 | 98.47 103 | 92.69 338 | 95.61 250 | 97.81 223 | 95.54 319 | 77.71 339 | 99.80 154 | 91.49 304 | 98.11 295 | 95.42 342 |
|
Effi-MVS+ | | | 98.02 161 | 97.82 171 | 98.62 158 | 98.53 276 | 97.19 169 | 97.33 211 | 99.68 16 | 97.30 187 | 96.68 288 | 97.46 281 | 98.56 36 | 99.80 154 | 96.63 167 | 98.20 289 | 98.86 244 |
|
v1144 | | | 98.60 105 | 98.66 82 | 98.41 192 | 99.36 121 | 95.90 222 | 97.58 195 | 99.34 121 | 97.51 165 | 99.27 82 | 99.15 102 | 96.34 175 | 99.80 154 | 99.47 24 | 99.93 39 | 99.51 98 |
|
v18 | | | 99.02 46 | 99.17 39 | 98.57 168 | 99.45 106 | 96.31 204 | 98.94 64 | 99.58 36 | 99.06 70 | 99.43 55 | 99.58 38 | 96.91 137 | 99.80 154 | 99.60 14 | 99.97 23 | 99.59 58 |
|
v7 | | | 98.67 92 | 98.73 67 | 98.50 183 | 99.43 113 | 96.21 210 | 98.00 150 | 99.31 131 | 97.58 158 | 99.17 99 | 99.18 92 | 96.63 158 | 99.80 154 | 99.42 27 | 99.88 64 | 99.48 116 |
|
VDDNet | | | 98.21 150 | 97.95 160 | 99.01 109 | 99.58 57 | 97.74 143 | 99.01 55 | 97.29 292 | 99.67 8 | 98.97 126 | 99.50 46 | 90.45 275 | 99.80 154 | 97.88 102 | 99.20 227 | 99.48 116 |
|
EI-MVSNet | | | 98.40 131 | 98.51 97 | 98.04 223 | 99.10 174 | 94.73 249 | 97.20 222 | 98.87 228 | 98.97 78 | 99.06 108 | 99.02 128 | 96.00 185 | 99.80 154 | 98.58 68 | 99.82 82 | 99.60 52 |
|
CVMVSNet | | | 96.25 255 | 97.21 203 | 93.38 333 | 99.10 174 | 80.56 353 | 97.20 222 | 98.19 274 | 96.94 206 | 99.00 121 | 99.02 128 | 89.50 280 | 99.80 154 | 96.36 186 | 99.59 162 | 99.78 15 |
|
1111 | | | 93.99 304 | 93.72 300 | 94.80 316 | 99.33 128 | 85.20 339 | 95.97 285 | 99.39 100 | 97.88 140 | 98.64 164 | 98.56 208 | 57.79 359 | 99.80 154 | 96.02 199 | 99.87 68 | 99.40 149 |
|
.test1245 | | | 79.71 327 | 84.30 328 | 65.96 341 | 99.33 128 | 85.20 339 | 95.97 285 | 99.39 100 | 97.88 140 | 98.64 164 | 98.56 208 | 57.79 359 | 99.80 154 | 96.02 199 | 15.07 353 | 12.86 354 |
|
MVSTER | | | 96.86 235 | 96.55 238 | 97.79 231 | 97.91 307 | 94.21 266 | 97.56 197 | 98.87 228 | 97.49 168 | 99.06 108 | 99.05 122 | 80.72 320 | 99.80 154 | 98.44 76 | 99.82 82 | 99.37 157 |
|
sss | | | 97.21 217 | 96.93 213 | 98.06 221 | 98.83 233 | 95.22 240 | 96.75 249 | 98.48 263 | 94.49 275 | 97.27 265 | 97.90 258 | 92.77 261 | 99.80 154 | 96.57 171 | 99.32 211 | 99.16 214 |
|
ab-mvs | | | 98.41 129 | 98.36 123 | 98.59 165 | 99.19 160 | 97.23 165 | 99.32 17 | 98.81 240 | 97.66 151 | 98.62 168 | 99.40 64 | 96.82 146 | 99.80 154 | 95.88 205 | 99.51 189 | 98.75 258 |
|
TDRefinement | | | 99.42 19 | 99.38 19 | 99.55 20 | 99.76 26 | 99.33 11 | 99.68 5 | 99.71 12 | 99.38 35 | 99.53 37 | 99.61 30 | 98.64 29 | 99.80 154 | 98.24 85 | 99.84 73 | 99.52 96 |
|
LS3D | | | 98.63 98 | 98.38 121 | 99.36 56 | 97.25 330 | 99.38 6 | 99.12 48 | 99.32 129 | 99.21 47 | 98.44 184 | 98.88 156 | 97.31 108 | 99.80 154 | 96.58 169 | 99.34 208 | 98.92 237 |
|
Regformer-3 | | | 98.61 104 | 98.61 89 | 98.63 156 | 99.02 196 | 96.53 193 | 97.17 226 | 98.84 234 | 99.13 60 | 99.10 105 | 98.85 161 | 97.24 117 | 99.79 174 | 98.41 79 | 99.70 130 | 99.57 70 |
|
testdata2 | | | | | | | | | | | | | | 99.79 174 | 92.80 286 | | |
|
VDD-MVS | | | 98.56 109 | 98.39 119 | 99.07 96 | 99.13 172 | 98.07 109 | 98.59 85 | 97.01 297 | 99.59 19 | 99.11 103 | 99.27 77 | 94.82 223 | 99.79 174 | 98.34 81 | 99.63 154 | 99.34 169 |
|
v2v482 | | | 98.56 109 | 98.62 86 | 98.37 199 | 99.42 114 | 95.81 226 | 97.58 195 | 99.16 182 | 97.90 138 | 99.28 80 | 99.01 130 | 95.98 189 | 99.79 174 | 99.33 29 | 99.90 57 | 99.51 98 |
|
mvs_anonymous | | | 97.83 180 | 98.16 142 | 96.87 271 | 98.18 297 | 91.89 301 | 97.31 213 | 98.90 225 | 97.37 180 | 98.83 147 | 99.46 52 | 96.28 176 | 99.79 174 | 98.90 53 | 98.16 292 | 98.95 233 |
|
tpm | | | 94.67 290 | 94.34 285 | 95.66 306 | 97.68 315 | 88.42 325 | 97.88 161 | 94.90 320 | 94.46 277 | 96.03 309 | 98.56 208 | 78.66 334 | 99.79 174 | 95.88 205 | 95.01 340 | 98.78 254 |
|
IS-MVSNet | | | 98.19 152 | 97.90 166 | 99.08 95 | 99.57 62 | 97.97 119 | 99.31 20 | 98.32 268 | 99.01 74 | 98.98 124 | 99.03 127 | 91.59 270 | 99.79 174 | 95.49 224 | 99.80 92 | 99.48 116 |
|
test_0402 | | | 98.76 74 | 98.71 71 | 98.93 118 | 99.56 69 | 98.14 102 | 98.45 110 | 99.34 121 | 99.28 44 | 98.95 129 | 98.91 147 | 98.34 46 | 99.79 174 | 95.63 219 | 99.91 54 | 98.86 244 |
|
ACMM | | 96.08 12 | 98.91 59 | 98.73 67 | 99.48 44 | 99.55 73 | 99.14 34 | 98.07 136 | 99.37 107 | 97.62 154 | 99.04 116 | 98.96 141 | 98.84 21 | 99.79 174 | 97.43 125 | 99.65 152 | 99.49 110 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
v1141 | | | 98.63 98 | 98.70 74 | 98.41 192 | 99.39 117 | 95.96 219 | 97.64 185 | 99.21 159 | 97.92 130 | 99.35 68 | 99.08 111 | 96.61 161 | 99.78 183 | 99.25 34 | 99.90 57 | 99.50 103 |
|
v1neww | | | 98.70 82 | 98.76 63 | 98.52 178 | 99.47 99 | 96.30 206 | 98.03 141 | 99.18 173 | 97.92 130 | 99.26 87 | 99.08 111 | 96.91 137 | 99.78 183 | 99.19 40 | 99.82 82 | 99.47 124 |
|
v7new | | | 98.70 82 | 98.76 63 | 98.52 178 | 99.47 99 | 96.30 206 | 98.03 141 | 99.18 173 | 97.92 130 | 99.26 87 | 99.08 111 | 96.91 137 | 99.78 183 | 99.19 40 | 99.82 82 | 99.47 124 |
|
divwei89l23v2f112 | | | 98.63 98 | 98.70 74 | 98.41 192 | 99.39 117 | 95.96 219 | 97.64 185 | 99.21 159 | 97.92 130 | 99.35 68 | 99.08 111 | 96.61 161 | 99.78 183 | 99.25 34 | 99.90 57 | 99.50 103 |
|
æ–°å‡ ä½•1 | | | | | 98.91 121 | 98.94 208 | 97.76 140 | | 98.76 245 | 87.58 339 | 96.75 287 | 98.10 246 | 94.80 226 | 99.78 183 | 92.73 288 | 99.00 253 | 99.20 201 |
|
v6 | | | 98.70 82 | 98.76 63 | 98.52 178 | 99.47 99 | 96.30 206 | 98.03 141 | 99.18 173 | 97.92 130 | 99.27 82 | 99.08 111 | 96.91 137 | 99.78 183 | 99.19 40 | 99.82 82 | 99.48 116 |
|
v1 | | | 98.63 98 | 98.70 74 | 98.41 192 | 99.39 117 | 95.96 219 | 97.64 185 | 99.20 163 | 97.92 130 | 99.36 66 | 99.07 116 | 96.63 158 | 99.78 183 | 99.25 34 | 99.90 57 | 99.50 103 |
|
V42 | | | 98.78 72 | 98.78 60 | 98.76 142 | 99.44 109 | 97.04 175 | 98.27 118 | 99.19 169 | 97.87 142 | 99.25 89 | 99.16 98 | 96.84 144 | 99.78 183 | 99.21 38 | 99.84 73 | 99.46 128 |
|
VNet | | | 98.42 128 | 98.30 131 | 98.79 135 | 98.79 241 | 97.29 162 | 98.23 120 | 98.66 255 | 99.31 41 | 98.85 144 | 98.80 169 | 94.80 226 | 99.78 183 | 98.13 90 | 99.13 241 | 99.31 178 |
|
tfpn1000 | | | 94.81 284 | 94.25 287 | 96.47 284 | 99.01 198 | 93.47 286 | 98.56 87 | 92.30 347 | 96.17 235 | 97.90 210 | 96.29 308 | 76.70 345 | 99.77 192 | 93.02 278 | 98.29 284 | 96.16 334 |
|
agg_prior1 | | | 97.06 226 | 96.40 242 | 99.03 105 | 98.68 255 | 97.99 114 | 95.76 300 | 99.01 210 | 91.73 311 | 95.59 314 | 97.50 277 | 96.49 167 | 99.77 192 | 93.71 264 | 99.14 238 | 99.34 169 |
|
agg_prior | | | | | | 98.68 255 | 97.99 114 | | 99.01 210 | | 95.59 314 | | | 99.77 192 | | | |
|
PM-MVS | | | 98.82 66 | 98.72 70 | 99.12 89 | 99.64 50 | 98.54 79 | 97.98 152 | 99.68 16 | 97.62 154 | 99.34 71 | 99.18 92 | 97.54 93 | 99.77 192 | 97.79 105 | 99.74 115 | 99.04 222 |
|
TAMVS | | | 98.24 149 | 98.05 155 | 98.80 134 | 99.07 181 | 97.18 170 | 97.88 161 | 98.81 240 | 96.66 220 | 99.17 99 | 99.21 87 | 94.81 225 | 99.77 192 | 96.96 145 | 99.88 64 | 99.44 134 |
|
TEST9 | | | | | | 98.71 248 | 98.08 107 | 95.96 289 | 99.03 203 | 91.40 318 | 95.85 310 | 97.53 274 | 96.52 165 | 99.76 197 | | | |
|
train_agg | | | 97.10 223 | 96.45 241 | 99.07 96 | 98.71 248 | 98.08 107 | 95.96 289 | 99.03 203 | 91.64 312 | 95.85 310 | 97.53 274 | 96.47 168 | 99.76 197 | 93.67 265 | 99.16 234 | 99.36 163 |
|
test_8 | | | | | | 98.67 258 | 98.01 113 | 95.91 295 | 99.02 207 | 91.64 312 | 95.79 312 | 97.50 277 | 96.47 168 | 99.76 197 | | | |
|
test20.03 | | | 98.78 72 | 98.77 62 | 98.78 138 | 99.46 103 | 97.20 168 | 97.78 169 | 99.24 156 | 99.04 71 | 99.41 58 | 98.90 150 | 97.65 84 | 99.76 197 | 97.70 112 | 99.79 96 | 99.39 150 |
|
EG-PatchMatch MVS | | | 98.99 49 | 99.01 48 | 98.94 117 | 99.50 86 | 97.47 156 | 98.04 140 | 99.59 34 | 98.15 125 | 99.40 60 | 99.36 67 | 98.58 33 | 99.76 197 | 98.78 59 | 99.68 142 | 99.59 58 |
|
ACMH | | 96.65 7 | 99.25 30 | 99.24 35 | 99.26 75 | 99.72 33 | 98.38 89 | 99.07 52 | 99.55 54 | 98.30 115 | 99.65 23 | 99.45 56 | 99.22 10 | 99.76 197 | 98.44 76 | 99.77 104 | 99.64 40 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
view600 | | | 94.87 277 | 94.41 279 | 96.26 287 | 99.22 144 | 91.37 309 | 98.49 97 | 94.45 323 | 98.75 89 | 97.85 215 | 95.98 312 | 80.38 322 | 99.75 203 | 86.06 333 | 98.49 278 | 97.66 303 |
|
view800 | | | 94.87 277 | 94.41 279 | 96.26 287 | 99.22 144 | 91.37 309 | 98.49 97 | 94.45 323 | 98.75 89 | 97.85 215 | 95.98 312 | 80.38 322 | 99.75 203 | 86.06 333 | 98.49 278 | 97.66 303 |
|
conf0.05thres1000 | | | 94.87 277 | 94.41 279 | 96.26 287 | 99.22 144 | 91.37 309 | 98.49 97 | 94.45 323 | 98.75 89 | 97.85 215 | 95.98 312 | 80.38 322 | 99.75 203 | 86.06 333 | 98.49 278 | 97.66 303 |
|
tfpn | | | 94.87 277 | 94.41 279 | 96.26 287 | 99.22 144 | 91.37 309 | 98.49 97 | 94.45 323 | 98.75 89 | 97.85 215 | 95.98 312 | 80.38 322 | 99.75 203 | 86.06 333 | 98.49 278 | 97.66 303 |
|
pmmvs5 | | | 97.64 188 | 97.49 187 | 98.08 219 | 99.14 171 | 95.12 244 | 96.70 252 | 99.05 199 | 93.77 289 | 98.62 168 | 98.83 164 | 93.23 252 | 99.75 203 | 98.33 83 | 99.76 113 | 99.36 163 |
|
test12356 | | | 94.85 281 | 95.12 271 | 94.03 326 | 98.25 290 | 83.12 348 | 93.85 336 | 99.33 126 | 94.17 286 | 97.28 264 | 97.20 289 | 85.83 295 | 99.75 203 | 90.85 317 | 99.33 209 | 99.22 199 |
|
HY-MVS | | 95.94 13 | 95.90 259 | 95.35 264 | 97.55 246 | 97.95 304 | 94.79 248 | 98.81 74 | 96.94 301 | 92.28 307 | 95.17 326 | 98.57 205 | 89.90 277 | 99.75 203 | 91.20 311 | 97.33 321 | 98.10 285 |
|
DP-MVS | | | 98.93 57 | 98.81 58 | 99.28 70 | 99.21 150 | 98.45 85 | 98.46 109 | 99.33 126 | 99.63 12 | 99.48 46 | 99.15 102 | 97.23 119 | 99.75 203 | 97.17 133 | 99.66 151 | 99.63 44 |
|
PatchmatchNet | | | 95.58 264 | 95.67 257 | 95.30 312 | 97.34 328 | 87.32 330 | 97.65 184 | 96.65 308 | 95.30 261 | 97.07 270 | 98.69 182 | 84.77 302 | 99.75 203 | 94.97 230 | 98.64 272 | 98.83 246 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
agg_prior3 | | | 96.95 233 | 96.27 246 | 99.00 111 | 98.68 255 | 97.91 125 | 95.96 289 | 99.01 210 | 90.74 324 | 95.60 313 | 97.45 282 | 96.14 178 | 99.74 212 | 93.67 265 | 99.16 234 | 99.36 163 |
|
testing_2 | | | 98.93 57 | 98.99 50 | 98.76 142 | 99.57 62 | 97.03 176 | 97.85 165 | 99.13 186 | 98.46 107 | 99.44 54 | 99.44 57 | 98.22 52 | 99.74 212 | 98.85 56 | 99.94 33 | 99.51 98 |
|
ADS-MVSNet | | | 95.24 271 | 94.93 275 | 96.18 292 | 98.14 298 | 90.10 321 | 97.92 157 | 97.32 291 | 90.23 325 | 96.51 295 | 98.91 147 | 85.61 297 | 99.74 212 | 92.88 282 | 96.90 325 | 98.69 263 |
|
UnsupCasMVSNet_eth | | | 97.89 170 | 97.60 183 | 98.75 144 | 99.31 130 | 97.17 171 | 97.62 189 | 99.35 117 | 98.72 94 | 98.76 156 | 98.68 184 | 92.57 264 | 99.74 212 | 97.76 110 | 95.60 337 | 99.34 169 |
|
CDS-MVSNet | | | 97.69 184 | 97.35 199 | 98.69 150 | 98.73 245 | 97.02 178 | 96.92 239 | 98.75 248 | 95.89 246 | 98.59 173 | 98.67 186 | 92.08 269 | 99.74 212 | 96.72 159 | 99.81 88 | 99.32 174 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
tfpn_ndepth | | | 94.12 301 | 93.51 305 | 95.94 300 | 98.86 225 | 93.60 285 | 98.16 127 | 91.90 349 | 94.66 274 | 97.41 256 | 95.24 329 | 76.24 346 | 99.73 217 | 91.21 310 | 97.88 310 | 94.50 347 |
|
nrg030 | | | 99.40 21 | 99.35 22 | 99.54 25 | 99.58 57 | 99.13 37 | 98.98 62 | 99.48 74 | 99.68 7 | 99.46 50 | 99.26 79 | 98.62 30 | 99.73 217 | 99.17 43 | 99.92 49 | 99.76 19 |
|
æ— å…ˆéªŒ | | | | | | | | 95.74 302 | 98.74 250 | 89.38 332 | | | | 99.73 217 | 92.38 293 | | 99.22 199 |
|
1121 | | | 96.73 241 | 96.00 249 | 98.91 121 | 98.95 207 | 97.76 140 | 98.07 136 | 98.73 251 | 87.65 338 | 96.54 292 | 98.13 240 | 94.52 233 | 99.73 217 | 92.38 293 | 99.02 250 | 99.24 194 |
|
LFMVS | | | 97.20 218 | 96.72 225 | 98.64 154 | 98.72 246 | 96.95 180 | 98.93 66 | 94.14 334 | 99.74 5 | 98.78 153 | 99.01 130 | 84.45 305 | 99.73 217 | 97.44 124 | 99.27 219 | 99.25 191 |
|
YYNet1 | | | 97.60 190 | 97.67 175 | 97.39 255 | 99.04 191 | 93.04 291 | 95.27 315 | 98.38 267 | 97.25 191 | 98.92 135 | 98.95 142 | 95.48 207 | 99.73 217 | 96.99 143 | 98.74 264 | 99.41 144 |
|
MDA-MVSNet_test_wron | | | 97.60 190 | 97.66 178 | 97.41 254 | 99.04 191 | 93.09 288 | 95.27 315 | 98.42 265 | 97.26 190 | 98.88 141 | 98.95 142 | 95.43 208 | 99.73 217 | 97.02 142 | 98.72 265 | 99.41 144 |
|
Vis-MVSNet (Re-imp) | | | 97.46 201 | 97.16 206 | 98.34 201 | 99.55 73 | 96.10 213 | 98.94 64 | 98.44 264 | 98.32 114 | 98.16 195 | 98.62 199 | 88.76 283 | 99.73 217 | 93.88 260 | 99.79 96 | 99.18 207 |
|
PCF-MVS | | 92.86 18 | 94.36 293 | 93.00 311 | 98.42 191 | 98.70 252 | 97.56 152 | 93.16 341 | 99.11 190 | 79.59 349 | 97.55 245 | 97.43 283 | 92.19 266 | 99.73 217 | 79.85 349 | 99.45 197 | 97.97 289 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
COLMAP_ROB | | 96.50 10 | 98.99 49 | 98.85 54 | 99.41 52 | 99.58 57 | 99.10 42 | 98.74 75 | 99.56 49 | 99.09 68 | 99.33 72 | 99.19 90 | 98.40 43 | 99.72 226 | 95.98 202 | 99.76 113 | 99.42 142 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
原ACMM1 | | | | | 98.35 200 | 98.90 218 | 96.25 209 | | 98.83 239 | 92.48 303 | 96.07 307 | 98.10 246 | 95.39 209 | 99.71 227 | 92.61 290 | 98.99 254 | 99.08 217 |
|
UnsupCasMVSNet_bld | | | 97.30 210 | 96.92 214 | 98.45 189 | 99.28 133 | 96.78 188 | 96.20 279 | 99.27 146 | 95.42 260 | 98.28 193 | 98.30 231 | 93.16 254 | 99.71 227 | 94.99 229 | 97.37 317 | 98.87 243 |
|
test_post | | | | | | | | | | | | 21.25 355 | 83.86 311 | 99.70 229 | | | |
|
testdata | | | | | 98.09 216 | 98.93 210 | 95.40 238 | | 98.80 242 | 90.08 329 | 97.45 253 | 98.37 224 | 95.26 211 | 99.70 229 | 93.58 269 | 98.95 258 | 99.17 211 |
|
HQP_MVS | | | 97.99 166 | 97.67 175 | 98.93 118 | 99.19 160 | 97.65 148 | 97.77 171 | 99.27 146 | 98.20 121 | 97.79 229 | 97.98 254 | 94.90 218 | 99.70 229 | 94.42 244 | 99.51 189 | 99.45 132 |
|
plane_prior5 | | | | | | | | | 99.27 146 | | | | | 99.70 229 | 94.42 244 | 99.51 189 | 99.45 132 |
|
Patchmatch-test1 | | | 96.44 252 | 96.72 225 | 95.60 308 | 98.24 292 | 88.35 326 | 95.85 298 | 96.88 304 | 96.11 239 | 97.67 236 | 98.57 205 | 93.10 256 | 99.69 233 | 94.79 232 | 99.22 224 | 98.77 255 |
|
Patchmatch-test | | | 96.55 247 | 96.34 244 | 97.17 260 | 98.35 286 | 93.06 289 | 98.40 113 | 97.79 281 | 97.33 183 | 98.41 187 | 98.67 186 | 83.68 312 | 99.69 233 | 95.16 226 | 99.31 213 | 98.77 255 |
|
test_normal | | | 97.58 192 | 97.41 192 | 98.10 215 | 99.03 194 | 95.72 228 | 96.21 277 | 97.05 296 | 96.71 217 | 98.65 162 | 98.12 244 | 93.87 244 | 99.69 233 | 97.68 116 | 99.35 206 | 98.88 242 |
|
CDPH-MVS | | | 97.26 213 | 96.66 232 | 99.07 96 | 99.00 199 | 98.15 100 | 96.03 283 | 99.01 210 | 91.21 321 | 97.79 229 | 97.85 259 | 96.89 142 | 99.69 233 | 92.75 287 | 99.38 203 | 99.39 150 |
|
test12 | | | | | 98.93 118 | 98.58 269 | 97.83 132 | | 98.66 255 | | 96.53 293 | | 95.51 205 | 99.69 233 | | 99.13 241 | 99.27 186 |
|
tfpn111 | | | 94.33 294 | 93.78 298 | 95.96 299 | 99.06 184 | 91.35 313 | 98.03 141 | 94.24 330 | 98.33 111 | 97.40 257 | 94.98 334 | 79.84 327 | 99.68 238 | 83.94 340 | 98.22 288 | 96.86 323 |
|
EU-MVSNet | | | 97.66 187 | 98.50 99 | 95.13 313 | 99.63 52 | 85.84 335 | 98.35 115 | 98.21 271 | 98.23 120 | 99.54 35 | 99.46 52 | 95.02 216 | 99.68 238 | 98.24 85 | 99.87 68 | 99.87 6 |
|
DI_MVS_plusplus_test | | | 97.57 194 | 97.40 193 | 98.07 220 | 99.06 184 | 95.71 229 | 96.58 260 | 96.96 298 | 96.71 217 | 98.69 160 | 98.13 240 | 93.81 247 | 99.68 238 | 97.45 123 | 99.19 231 | 98.80 252 |
|
Test4 | | | 97.43 203 | 97.18 204 | 98.18 213 | 99.05 189 | 96.02 216 | 96.62 258 | 99.09 192 | 96.25 233 | 98.63 167 | 97.70 266 | 90.49 274 | 99.68 238 | 97.50 121 | 99.30 214 | 98.83 246 |
|
F-COLMAP | | | 97.30 210 | 96.68 229 | 99.14 87 | 99.19 160 | 98.39 88 | 97.27 215 | 99.30 138 | 92.93 297 | 96.62 290 | 98.00 252 | 95.73 198 | 99.68 238 | 92.62 289 | 98.46 282 | 99.35 168 |
|
OpenMVS_ROB | | 95.38 14 | 95.84 261 | 95.18 270 | 97.81 230 | 98.41 283 | 97.15 173 | 97.37 209 | 98.62 258 | 83.86 345 | 98.65 162 | 98.37 224 | 94.29 238 | 99.68 238 | 88.41 325 | 98.62 274 | 96.60 330 |
|
test-LLR | | | 93.90 306 | 93.85 296 | 94.04 324 | 96.53 340 | 84.62 343 | 94.05 333 | 92.39 345 | 96.17 235 | 94.12 336 | 95.07 330 | 82.30 317 | 99.67 244 | 95.87 208 | 98.18 290 | 97.82 294 |
|
test-mter | | | 92.33 319 | 91.76 321 | 94.04 324 | 96.53 340 | 84.62 343 | 94.05 333 | 92.39 345 | 94.00 288 | 94.12 336 | 95.07 330 | 65.63 358 | 99.67 244 | 95.87 208 | 98.18 290 | 97.82 294 |
|
thres600view7 | | | 94.45 292 | 93.83 297 | 96.29 285 | 99.06 184 | 91.53 305 | 97.99 151 | 94.24 330 | 98.34 110 | 97.44 254 | 95.01 332 | 79.84 327 | 99.67 244 | 84.33 339 | 98.23 286 | 97.66 303 |
|
114514_t | | | 96.50 250 | 95.77 253 | 98.69 150 | 99.48 97 | 97.43 159 | 97.84 166 | 99.55 54 | 81.42 348 | 96.51 295 | 98.58 204 | 95.53 203 | 99.67 244 | 93.41 274 | 99.58 168 | 98.98 229 |
|
PVSNet_BlendedMVS | | | 97.55 195 | 97.53 185 | 97.60 243 | 98.92 214 | 93.77 281 | 96.64 256 | 99.43 93 | 94.49 275 | 97.62 238 | 99.18 92 | 96.82 146 | 99.67 244 | 94.73 234 | 99.93 39 | 99.36 163 |
|
PVSNet_Blended | | | 96.88 234 | 96.68 229 | 97.47 250 | 98.92 214 | 93.77 281 | 94.71 327 | 99.43 93 | 90.98 322 | 97.62 238 | 97.36 288 | 96.82 146 | 99.67 244 | 94.73 234 | 99.56 179 | 98.98 229 |
|
PHI-MVS | | | 98.29 142 | 97.95 160 | 99.34 64 | 98.44 281 | 99.16 28 | 98.12 130 | 99.38 103 | 96.01 244 | 98.06 202 | 98.43 220 | 97.80 80 | 99.67 244 | 95.69 217 | 99.58 168 | 99.20 201 |
|
ACMH+ | | 96.62 9 | 99.08 42 | 99.00 49 | 99.33 66 | 99.71 34 | 98.83 56 | 98.60 83 | 99.58 36 | 99.11 61 | 99.53 37 | 99.18 92 | 98.81 23 | 99.67 244 | 96.71 162 | 99.77 104 | 99.50 103 |
|
test_post1 | | | | | | | | 97.59 194 | | | | 20.48 356 | 83.07 315 | 99.66 252 | 94.16 249 | | |
|
旧先验2 | | | | | | | | 95.76 300 | | 88.56 336 | 97.52 248 | | | 99.66 252 | 94.48 240 | | |
|
MCST-MVS | | | 98.00 164 | 97.63 181 | 99.10 92 | 99.24 138 | 98.17 99 | 96.89 242 | 98.73 251 | 95.66 249 | 97.92 207 | 97.70 266 | 97.17 122 | 99.66 252 | 96.18 194 | 99.23 223 | 99.47 124 |
|
NCCC | | | 97.86 174 | 97.47 191 | 99.05 102 | 98.61 266 | 98.07 109 | 96.98 234 | 98.90 225 | 97.63 153 | 97.04 272 | 97.93 257 | 95.99 188 | 99.66 252 | 95.31 225 | 98.82 262 | 99.43 139 |
|
PMMVS | | | 96.51 248 | 95.98 250 | 98.09 216 | 97.53 320 | 95.84 224 | 94.92 323 | 98.84 234 | 91.58 315 | 96.05 308 | 95.58 318 | 95.68 199 | 99.66 252 | 95.59 221 | 98.09 302 | 98.76 257 |
|
OPM-MVS | | | 98.56 109 | 98.32 130 | 99.25 76 | 99.41 115 | 98.73 63 | 97.13 230 | 99.18 173 | 97.10 203 | 98.75 157 | 98.92 146 | 98.18 56 | 99.65 257 | 96.68 164 | 99.56 179 | 99.37 157 |
|
MIMVSNet | | | 96.62 245 | 96.25 248 | 97.71 236 | 99.04 191 | 94.66 252 | 99.16 42 | 96.92 302 | 97.23 196 | 97.87 212 | 99.10 109 | 86.11 293 | 99.65 257 | 91.65 299 | 99.21 226 | 98.82 248 |
|
DeepC-MVS_fast | | 96.85 6 | 98.30 139 | 98.15 144 | 98.75 144 | 98.61 266 | 97.23 165 | 97.76 173 | 99.09 192 | 97.31 186 | 98.75 157 | 98.66 188 | 97.56 90 | 99.64 259 | 96.10 198 | 99.55 181 | 99.39 150 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
pmmvs-eth3d | | | 98.47 124 | 98.34 126 | 98.86 128 | 99.30 132 | 97.76 140 | 97.16 228 | 99.28 141 | 95.54 257 | 99.42 57 | 99.19 90 | 97.27 112 | 99.63 260 | 97.89 100 | 99.97 23 | 99.20 201 |
|
testus | | | 95.52 266 | 95.32 265 | 96.13 297 | 97.91 307 | 89.49 323 | 93.62 338 | 99.61 30 | 92.41 304 | 97.38 262 | 95.42 328 | 94.72 230 | 99.63 260 | 88.06 327 | 98.72 265 | 99.26 189 |
|
conf200view11 | | | 94.24 297 | 93.67 302 | 95.94 300 | 99.06 184 | 91.35 313 | 98.03 141 | 94.24 330 | 98.33 111 | 97.40 257 | 94.98 334 | 79.84 327 | 99.62 262 | 83.05 342 | 98.08 303 | 96.86 323 |
|
thres100view900 | | | 94.19 298 | 93.67 302 | 95.75 305 | 99.06 184 | 91.35 313 | 98.03 141 | 94.24 330 | 98.33 111 | 97.40 257 | 94.98 334 | 79.84 327 | 99.62 262 | 83.05 342 | 98.08 303 | 96.29 331 |
|
tfpn200view9 | | | 94.03 303 | 93.44 306 | 95.78 304 | 98.93 210 | 91.44 307 | 97.60 192 | 94.29 328 | 97.94 128 | 97.10 268 | 94.31 343 | 79.67 331 | 99.62 262 | 83.05 342 | 98.08 303 | 96.29 331 |
|
Patchmatch-RL test | | | 97.26 213 | 97.02 210 | 97.99 226 | 99.52 81 | 95.53 233 | 96.13 281 | 99.71 12 | 97.47 169 | 99.27 82 | 99.16 98 | 84.30 308 | 99.62 262 | 97.89 100 | 99.77 104 | 98.81 249 |
|
v148 | | | 98.45 126 | 98.60 91 | 98.00 225 | 99.44 109 | 94.98 245 | 97.44 207 | 99.06 195 | 98.30 115 | 99.32 77 | 98.97 138 | 96.65 157 | 99.62 262 | 98.37 80 | 99.85 71 | 99.39 150 |
|
thres400 | | | 94.14 300 | 93.44 306 | 96.24 291 | 98.93 210 | 91.44 307 | 97.60 192 | 94.29 328 | 97.94 128 | 97.10 268 | 94.31 343 | 79.67 331 | 99.62 262 | 83.05 342 | 98.08 303 | 97.66 303 |
|
CostFormer | | | 93.97 305 | 93.78 298 | 94.51 320 | 97.53 320 | 85.83 336 | 97.98 152 | 95.96 315 | 89.29 333 | 94.99 329 | 98.63 197 | 78.63 335 | 99.62 262 | 94.54 239 | 96.50 330 | 98.09 286 |
|
gm-plane-assit | | | | | | 94.83 350 | 81.97 351 | | | 88.07 337 | | 94.99 333 | | 99.60 269 | 91.76 297 | | |
|
MVP-Stereo | | | 98.08 159 | 97.92 164 | 98.57 168 | 98.96 205 | 96.79 184 | 97.90 160 | 99.18 173 | 96.41 228 | 98.46 182 | 98.95 142 | 95.93 191 | 99.60 269 | 96.51 178 | 98.98 256 | 99.31 178 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
pmmvs4 | | | 97.58 192 | 97.28 201 | 98.51 182 | 98.84 231 | 96.93 181 | 95.40 314 | 98.52 261 | 93.60 291 | 98.61 170 | 98.65 190 | 95.10 215 | 99.60 269 | 96.97 144 | 99.79 96 | 98.99 228 |
|
JIA-IIPM | | | 95.52 266 | 95.03 273 | 97.00 265 | 96.85 337 | 94.03 270 | 96.93 237 | 95.82 316 | 99.20 50 | 94.63 331 | 99.71 14 | 83.09 314 | 99.60 269 | 94.42 244 | 94.64 341 | 97.36 316 |
|
test_prior3 | | | 97.48 200 | 97.00 211 | 98.95 115 | 98.69 253 | 97.95 122 | 95.74 302 | 99.03 203 | 96.48 225 | 96.11 304 | 97.63 270 | 95.92 192 | 99.59 273 | 94.16 249 | 99.20 227 | 99.30 181 |
|
test_prior | | | | | 98.95 115 | 98.69 253 | 97.95 122 | | 99.03 203 | | | | | 99.59 273 | | | 99.30 181 |
|
PatchFormer-LS_test | | | 94.08 302 | 93.91 295 | 94.59 319 | 96.93 334 | 86.86 332 | 97.55 199 | 96.57 310 | 94.27 283 | 94.38 333 | 93.64 348 | 80.96 319 | 99.59 273 | 96.44 183 | 94.48 344 | 97.31 317 |
|
tpmp4_e23 | | | 92.91 315 | 92.45 314 | 94.29 322 | 97.41 325 | 85.62 338 | 97.95 155 | 96.77 306 | 87.55 340 | 91.33 347 | 98.57 205 | 74.21 349 | 99.59 273 | 91.62 301 | 96.64 329 | 97.65 310 |
|
tpmrst | | | 95.07 273 | 95.46 261 | 93.91 327 | 97.11 332 | 84.36 345 | 97.62 189 | 96.96 298 | 94.98 266 | 96.35 300 | 98.80 169 | 85.46 299 | 99.59 273 | 95.60 220 | 96.23 333 | 97.79 299 |
|
dp | | | 93.47 310 | 93.59 304 | 93.13 335 | 96.64 339 | 81.62 352 | 97.66 182 | 96.42 312 | 92.80 300 | 96.11 304 | 98.64 193 | 78.55 336 | 99.59 273 | 93.31 275 | 92.18 350 | 98.16 283 |
|
PLC | | 94.65 16 | 96.51 248 | 95.73 254 | 98.85 129 | 98.75 243 | 97.91 125 | 96.42 268 | 99.06 195 | 90.94 323 | 95.59 314 | 97.38 286 | 94.41 235 | 99.59 273 | 90.93 314 | 98.04 307 | 99.05 221 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
AllTest | | | 98.44 127 | 98.20 136 | 99.16 84 | 99.50 86 | 98.55 76 | 98.25 119 | 99.58 36 | 96.80 212 | 98.88 141 | 99.06 117 | 97.65 84 | 99.57 280 | 94.45 242 | 99.61 159 | 99.37 157 |
|
TestCases | | | | | 99.16 84 | 99.50 86 | 98.55 76 | | 99.58 36 | 96.80 212 | 98.88 141 | 99.06 117 | 97.65 84 | 99.57 280 | 94.45 242 | 99.61 159 | 99.37 157 |
|
CNVR-MVS | | | 98.17 155 | 97.87 169 | 99.07 96 | 98.67 258 | 98.24 94 | 97.01 233 | 98.93 219 | 97.25 191 | 97.62 238 | 98.34 227 | 97.27 112 | 99.57 280 | 96.42 184 | 99.33 209 | 99.39 150 |
|
TESTMET0.1,1 | | | 92.19 321 | 91.77 320 | 93.46 331 | 96.48 342 | 82.80 350 | 94.05 333 | 91.52 350 | 94.45 279 | 94.00 339 | 94.88 338 | 66.65 355 | 99.56 283 | 95.78 213 | 98.11 295 | 98.02 288 |
|
thres200 | | | 93.72 308 | 93.14 309 | 95.46 310 | 98.66 263 | 91.29 317 | 96.61 259 | 94.63 322 | 97.39 179 | 96.83 284 | 93.71 346 | 79.88 326 | 99.56 283 | 82.40 346 | 98.13 294 | 95.54 341 |
|
MVS_Test | | | 98.18 153 | 98.36 123 | 97.67 237 | 98.48 277 | 94.73 249 | 98.18 124 | 99.02 207 | 97.69 150 | 98.04 204 | 99.11 107 | 97.22 121 | 99.56 283 | 98.57 70 | 98.90 260 | 98.71 260 |
|
alignmvs | | | 97.35 206 | 96.88 217 | 98.78 138 | 98.54 274 | 98.09 104 | 97.71 177 | 97.69 286 | 99.20 50 | 97.59 241 | 95.90 316 | 88.12 286 | 99.55 286 | 98.18 89 | 98.96 257 | 98.70 262 |
|
HQP4-MVS | | | | | | | | | | | 95.56 317 | | | 99.54 287 | | | 99.32 174 |
|
HQP-MVS | | | 97.00 230 | 96.49 240 | 98.55 173 | 98.67 258 | 96.79 184 | 96.29 273 | 99.04 201 | 96.05 241 | 95.55 318 | 96.84 297 | 93.84 245 | 99.54 287 | 92.82 284 | 99.26 221 | 99.32 174 |
|
tpmvs | | | 95.02 275 | 95.25 267 | 94.33 321 | 96.39 344 | 85.87 334 | 98.08 134 | 96.83 305 | 95.46 259 | 95.51 322 | 98.69 182 | 85.91 294 | 99.53 289 | 94.16 249 | 96.23 333 | 97.58 311 |
|
tpm2 | | | 93.09 314 | 92.58 313 | 94.62 318 | 97.56 318 | 86.53 333 | 97.66 182 | 95.79 317 | 86.15 342 | 94.07 338 | 98.23 237 | 75.95 347 | 99.53 289 | 90.91 315 | 96.86 328 | 97.81 296 |
|
MDTV_nov1_ep13 | | | | 95.22 268 | | 97.06 333 | 83.20 347 | 97.74 175 | 96.16 314 | 94.37 281 | 96.99 274 | 98.83 164 | 83.95 310 | 99.53 289 | 93.90 258 | 97.95 308 | |
|
AdaColmap | | | 97.14 222 | 96.71 227 | 98.46 187 | 98.34 287 | 97.80 138 | 96.95 235 | 98.93 219 | 95.58 256 | 96.92 276 | 97.66 268 | 95.87 195 | 99.53 289 | 90.97 313 | 99.14 238 | 98.04 287 |
|
test2356 | | | 91.64 324 | 90.19 327 | 96.00 298 | 94.30 352 | 89.58 322 | 90.84 346 | 96.68 307 | 91.76 310 | 95.48 323 | 93.69 347 | 67.05 354 | 99.52 293 | 84.83 338 | 97.08 324 | 98.91 239 |
|
new_pmnet | | | 96.99 231 | 96.76 223 | 97.67 237 | 98.72 246 | 94.89 247 | 95.95 292 | 98.20 272 | 92.62 302 | 98.55 178 | 98.54 211 | 94.88 221 | 99.52 293 | 93.96 257 | 99.44 198 | 98.59 268 |
|
RPSCF | | | 98.62 103 | 98.36 123 | 99.42 50 | 99.65 47 | 99.42 5 | 98.55 89 | 99.57 43 | 97.72 149 | 98.90 136 | 99.26 79 | 96.12 180 | 99.52 293 | 95.72 215 | 99.71 127 | 99.32 174 |
|
MAR-MVS | | | 96.47 251 | 95.70 255 | 98.79 135 | 97.92 306 | 99.12 39 | 98.28 117 | 98.60 259 | 92.16 309 | 95.54 321 | 96.17 309 | 94.77 229 | 99.52 293 | 89.62 322 | 98.23 286 | 97.72 302 |
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 | | | 97.90 169 | 97.69 174 | 98.52 178 | 99.17 165 | 97.66 147 | 97.19 225 | 99.47 80 | 96.31 231 | 97.85 215 | 98.20 239 | 96.71 155 | 99.52 293 | 94.62 237 | 99.72 123 | 98.38 278 |
|
Gipuma | | | 99.03 45 | 99.16 41 | 98.64 154 | 99.94 3 | 98.51 81 | 99.32 17 | 99.75 8 | 99.58 21 | 98.60 172 | 99.62 28 | 98.22 52 | 99.51 298 | 97.70 112 | 99.73 118 | 97.89 290 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
ambc | | | | | 98.24 209 | 98.82 236 | 95.97 218 | 98.62 81 | 99.00 214 | | 99.27 82 | 99.21 87 | 96.99 133 | 99.50 299 | 96.55 175 | 99.50 194 | 99.26 189 |
|
testgi | | | 98.32 137 | 98.39 119 | 98.13 214 | 99.57 62 | 95.54 232 | 97.78 169 | 99.49 71 | 97.37 180 | 99.19 95 | 97.65 269 | 98.96 19 | 99.49 300 | 96.50 179 | 98.99 254 | 99.34 169 |
|
EPNet_dtu | | | 94.93 276 | 94.78 277 | 95.38 311 | 93.58 354 | 87.68 329 | 96.78 246 | 95.69 318 | 97.35 182 | 89.14 350 | 98.09 248 | 88.15 285 | 99.49 300 | 94.95 231 | 99.30 214 | 98.98 229 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
PatchMatch-RL | | | 97.24 216 | 96.78 222 | 98.61 161 | 99.03 194 | 97.83 132 | 96.36 270 | 99.06 195 | 93.49 294 | 97.36 263 | 97.78 262 | 95.75 197 | 99.49 300 | 93.44 273 | 98.77 263 | 98.52 270 |
|
CLD-MVS | | | 97.49 197 | 97.16 206 | 98.48 185 | 99.07 181 | 97.03 176 | 94.71 327 | 99.21 159 | 94.46 277 | 98.06 202 | 97.16 292 | 97.57 89 | 99.48 303 | 94.46 241 | 99.78 100 | 98.95 233 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
BH-untuned | | | 96.83 236 | 96.75 224 | 97.08 261 | 98.74 244 | 93.33 287 | 96.71 251 | 98.26 270 | 96.72 215 | 98.44 184 | 97.37 287 | 95.20 212 | 99.47 304 | 91.89 296 | 97.43 316 | 98.44 274 |
|
OMC-MVS | | | 97.88 172 | 97.49 187 | 99.04 104 | 98.89 222 | 98.63 68 | 96.94 236 | 99.25 152 | 95.02 265 | 98.53 180 | 98.51 213 | 97.27 112 | 99.47 304 | 93.50 272 | 99.51 189 | 99.01 226 |
|
canonicalmvs | | | 98.34 135 | 98.26 133 | 98.58 166 | 98.46 279 | 97.82 135 | 98.96 63 | 99.46 82 | 99.19 54 | 97.46 252 | 95.46 326 | 98.59 32 | 99.46 306 | 98.08 92 | 98.71 268 | 98.46 272 |
|
DWT-MVSNet_test | | | 92.75 316 | 92.05 318 | 94.85 315 | 96.48 342 | 87.21 331 | 97.83 167 | 94.99 319 | 92.22 308 | 92.72 343 | 94.11 345 | 70.75 350 | 99.46 306 | 95.01 228 | 94.33 345 | 97.87 292 |
|
CNLPA | | | 97.17 220 | 96.71 227 | 98.55 173 | 98.56 271 | 98.05 111 | 96.33 271 | 98.93 219 | 96.91 208 | 97.06 271 | 97.39 285 | 94.38 236 | 99.45 308 | 91.66 298 | 99.18 233 | 98.14 284 |
|
BH-RMVSNet | | | 96.83 236 | 96.58 236 | 97.58 245 | 98.47 278 | 94.05 269 | 96.67 254 | 97.36 290 | 96.70 219 | 97.87 212 | 97.98 254 | 95.14 214 | 99.44 309 | 90.47 319 | 98.58 276 | 99.25 191 |
|
diffmvs | | | 97.49 197 | 97.36 197 | 97.91 227 | 98.38 285 | 95.70 230 | 97.95 155 | 99.31 131 | 94.87 270 | 96.14 302 | 98.78 171 | 94.84 222 | 99.43 310 | 97.69 114 | 98.26 285 | 98.59 268 |
|
PVSNet | | 93.40 17 | 95.67 263 | 95.70 255 | 95.57 309 | 98.83 233 | 88.57 324 | 92.50 343 | 97.72 284 | 92.69 301 | 96.49 298 | 96.44 306 | 93.72 251 | 99.43 310 | 93.61 267 | 99.28 218 | 98.71 260 |
|
TSAR-MVS + GP. | | | 98.18 153 | 97.98 158 | 98.77 140 | 98.71 248 | 97.88 128 | 96.32 272 | 98.66 255 | 96.33 229 | 99.23 93 | 98.51 213 | 97.48 99 | 99.40 312 | 97.16 134 | 99.46 196 | 99.02 225 |
|
TAPA-MVS | | 96.21 11 | 96.63 244 | 95.95 251 | 98.65 153 | 98.93 210 | 98.09 104 | 96.93 237 | 99.28 141 | 83.58 346 | 98.13 198 | 97.78 262 | 96.13 179 | 99.40 312 | 93.52 270 | 99.29 217 | 98.45 273 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
tpm cat1 | | | 93.29 312 | 93.13 310 | 93.75 328 | 97.39 327 | 84.74 342 | 97.39 208 | 97.65 287 | 83.39 347 | 94.16 335 | 98.41 221 | 82.86 316 | 99.39 314 | 91.56 303 | 95.35 339 | 97.14 319 |
|
MG-MVS | | | 96.77 240 | 96.61 234 | 97.26 258 | 98.31 289 | 93.06 289 | 95.93 293 | 98.12 275 | 96.45 227 | 97.92 207 | 98.73 177 | 93.77 250 | 99.39 314 | 91.19 312 | 99.04 249 | 99.33 173 |
|
MVS_111021_HR | | | 98.25 147 | 98.08 153 | 98.75 144 | 99.09 177 | 97.46 157 | 95.97 285 | 99.27 146 | 97.60 157 | 97.99 206 | 98.25 234 | 98.15 59 | 99.38 316 | 96.87 150 | 99.57 172 | 99.42 142 |
|
MS-PatchMatch | | | 97.68 185 | 97.75 173 | 97.45 251 | 98.23 294 | 93.78 280 | 97.29 214 | 98.84 234 | 96.10 240 | 98.64 164 | 98.65 190 | 96.04 182 | 99.36 317 | 96.84 152 | 99.14 238 | 99.20 201 |
|
ITE_SJBPF | | | | | 98.87 126 | 99.22 144 | 98.48 83 | | 99.35 117 | 97.50 166 | 98.28 193 | 98.60 202 | 97.64 87 | 99.35 318 | 93.86 261 | 99.27 219 | 98.79 253 |
|
MVS_111021_LR | | | 98.30 139 | 98.12 147 | 98.83 131 | 99.16 167 | 98.03 112 | 96.09 282 | 99.30 138 | 97.58 158 | 98.10 199 | 98.24 235 | 98.25 48 | 99.34 319 | 96.69 163 | 99.65 152 | 99.12 216 |
|
USDC | | | 97.41 205 | 97.40 193 | 97.44 252 | 98.94 208 | 93.67 283 | 95.17 318 | 99.53 59 | 94.03 287 | 98.97 126 | 99.10 109 | 95.29 210 | 99.34 319 | 95.84 211 | 99.73 118 | 99.30 181 |
|
MSDG | | | 97.71 183 | 97.52 186 | 98.28 207 | 98.91 217 | 96.82 183 | 94.42 330 | 99.37 107 | 97.65 152 | 98.37 191 | 98.29 232 | 97.40 104 | 99.33 321 | 94.09 254 | 99.22 224 | 98.68 266 |
|
XVG-OURS | | | 98.53 118 | 98.34 126 | 99.11 90 | 99.50 86 | 98.82 58 | 95.97 285 | 99.50 65 | 97.30 187 | 99.05 113 | 98.98 136 | 99.35 7 | 99.32 322 | 95.72 215 | 99.68 142 | 99.18 207 |
|
DP-MVS Recon | | | 97.33 208 | 96.92 214 | 98.57 168 | 99.09 177 | 97.99 114 | 96.79 245 | 99.35 117 | 93.18 295 | 97.71 233 | 98.07 250 | 95.00 217 | 99.31 323 | 93.97 256 | 99.13 241 | 98.42 276 |
|
EPMVS | | | 93.72 308 | 93.27 308 | 95.09 314 | 96.04 347 | 87.76 328 | 98.13 128 | 85.01 354 | 94.69 273 | 96.92 276 | 98.64 193 | 78.47 337 | 99.31 323 | 95.04 227 | 96.46 331 | 98.20 282 |
|
MVS | | | 93.19 313 | 92.09 317 | 96.50 283 | 96.91 335 | 94.03 270 | 98.07 136 | 98.06 277 | 68.01 350 | 94.56 332 | 96.48 304 | 95.96 190 | 99.30 325 | 83.84 341 | 96.89 327 | 96.17 333 |
|
GA-MVS | | | 95.86 260 | 95.32 265 | 97.49 249 | 98.60 268 | 94.15 268 | 93.83 337 | 97.93 279 | 95.49 258 | 96.68 288 | 97.42 284 | 83.21 313 | 99.30 325 | 96.22 190 | 98.55 277 | 99.01 226 |
|
XVG-OURS-SEG-HR | | | 98.49 122 | 98.28 132 | 99.14 87 | 99.49 92 | 98.83 56 | 96.54 261 | 99.48 74 | 97.32 185 | 99.11 103 | 98.61 201 | 99.33 8 | 99.30 325 | 96.23 189 | 98.38 283 | 99.28 185 |
|
DeepPCF-MVS | | 96.93 5 | 98.32 137 | 98.01 157 | 99.23 78 | 98.39 284 | 98.97 50 | 95.03 321 | 99.18 173 | 96.88 209 | 99.33 72 | 98.78 171 | 98.16 57 | 99.28 328 | 96.74 158 | 99.62 155 | 99.44 134 |
|
TinyColmap | | | 97.89 170 | 97.98 158 | 97.60 243 | 98.86 225 | 94.35 263 | 96.21 277 | 99.44 88 | 97.45 176 | 99.06 108 | 98.88 156 | 97.99 69 | 99.28 328 | 94.38 248 | 99.58 168 | 99.18 207 |
|
PAPM | | | 91.88 322 | 90.34 324 | 96.51 282 | 98.06 301 | 92.56 293 | 92.44 344 | 97.17 293 | 86.35 341 | 90.38 349 | 96.01 310 | 86.61 289 | 99.21 330 | 70.65 352 | 95.43 338 | 97.75 300 |
|
MVS-HIRNet | | | 94.32 295 | 95.62 258 | 90.42 337 | 98.46 279 | 75.36 354 | 96.29 273 | 89.13 352 | 95.25 262 | 95.38 324 | 99.75 7 | 92.88 260 | 99.19 331 | 94.07 255 | 99.39 202 | 96.72 329 |
|
PAPM_NR | | | 96.82 238 | 96.32 245 | 98.30 205 | 99.07 181 | 96.69 191 | 97.48 204 | 98.76 245 | 95.81 247 | 96.61 291 | 96.47 305 | 94.12 243 | 99.17 332 | 90.82 318 | 97.78 311 | 99.06 220 |
|
TR-MVS | | | 95.55 265 | 95.12 271 | 96.86 274 | 97.54 319 | 93.94 272 | 96.49 264 | 96.53 311 | 94.36 282 | 97.03 273 | 96.61 301 | 94.26 239 | 99.16 333 | 86.91 330 | 96.31 332 | 97.47 315 |
|
API-MVS | | | 97.04 229 | 96.91 216 | 97.42 253 | 97.88 309 | 98.23 98 | 98.18 124 | 98.50 262 | 97.57 160 | 97.39 260 | 96.75 299 | 96.77 150 | 99.15 334 | 90.16 320 | 99.02 250 | 94.88 346 |
|
PAPR | | | 95.29 270 | 94.47 278 | 97.75 234 | 97.50 324 | 95.14 243 | 94.89 324 | 98.71 253 | 91.39 319 | 95.35 325 | 95.48 325 | 94.57 232 | 99.14 335 | 84.95 337 | 97.37 317 | 98.97 232 |
|
1314 | | | 95.74 262 | 95.60 259 | 96.17 293 | 97.53 320 | 92.75 292 | 98.07 136 | 98.31 269 | 91.22 320 | 94.25 334 | 96.68 300 | 95.53 203 | 99.03 336 | 91.64 300 | 97.18 322 | 96.74 328 |
|
gg-mvs-nofinetune | | | 92.37 318 | 91.20 322 | 95.85 303 | 95.80 349 | 92.38 297 | 99.31 20 | 81.84 356 | 99.75 4 | 91.83 345 | 99.74 8 | 68.29 352 | 99.02 337 | 87.15 329 | 97.12 323 | 96.16 334 |
|
BH-w/o | | | 95.13 272 | 94.89 276 | 95.86 302 | 98.20 296 | 91.31 316 | 95.65 305 | 97.37 289 | 93.64 290 | 96.52 294 | 95.70 317 | 93.04 257 | 99.02 337 | 88.10 326 | 95.82 335 | 97.24 318 |
|
test0.0.03 1 | | | 94.51 291 | 93.69 301 | 96.99 266 | 96.05 346 | 93.61 284 | 94.97 322 | 93.49 335 | 96.17 235 | 97.57 244 | 94.88 338 | 82.30 317 | 99.01 339 | 93.60 268 | 94.17 346 | 98.37 280 |
|
E-PMN | | | 94.17 299 | 94.37 284 | 93.58 330 | 96.86 336 | 85.71 337 | 90.11 348 | 97.07 295 | 98.17 124 | 97.82 222 | 97.19 290 | 84.62 304 | 98.94 340 | 89.77 321 | 97.68 313 | 96.09 338 |
|
EMVS | | | 93.83 307 | 94.02 294 | 93.23 334 | 96.83 338 | 84.96 341 | 89.77 349 | 96.32 313 | 97.92 130 | 97.43 255 | 96.36 307 | 86.17 291 | 98.93 341 | 87.68 328 | 97.73 312 | 95.81 339 |
|
CMPMVS | | 75.91 23 | 96.29 253 | 95.44 262 | 98.84 130 | 96.25 345 | 98.69 66 | 97.02 232 | 99.12 188 | 88.90 334 | 97.83 220 | 98.86 159 | 89.51 279 | 98.90 342 | 91.92 295 | 99.51 189 | 98.92 237 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
PVSNet_0 | | 89.98 21 | 91.15 325 | 90.30 325 | 93.70 329 | 97.72 311 | 84.34 346 | 90.24 347 | 97.42 288 | 90.20 328 | 93.79 340 | 93.09 349 | 90.90 273 | 98.89 343 | 86.57 331 | 72.76 352 | 97.87 292 |
|
PNet_i23d | | | 91.80 323 | 92.35 315 | 90.14 338 | 98.65 264 | 73.10 357 | 89.22 350 | 99.02 207 | 95.23 264 | 97.87 212 | 97.82 261 | 78.45 338 | 98.89 343 | 88.73 324 | 86.14 351 | 98.42 276 |
|
MSLP-MVS++ | | | 98.02 161 | 98.14 146 | 97.64 241 | 98.58 269 | 95.19 241 | 97.48 204 | 99.23 158 | 97.47 169 | 97.90 210 | 98.62 199 | 97.04 128 | 98.81 345 | 97.55 117 | 99.41 200 | 98.94 235 |
|
cascas | | | 94.79 285 | 94.33 286 | 96.15 296 | 96.02 348 | 92.36 298 | 92.34 345 | 99.26 151 | 85.34 344 | 95.08 328 | 94.96 337 | 92.96 258 | 98.53 346 | 94.41 247 | 98.59 275 | 97.56 312 |
|
wuyk23d | | | 96.06 257 | 97.62 182 | 91.38 336 | 98.65 264 | 98.57 75 | 98.85 72 | 96.95 300 | 96.86 210 | 99.90 5 | 99.16 98 | 99.18 12 | 98.40 347 | 89.23 323 | 99.77 104 | 77.18 352 |
|
PMVS | | 91.26 20 | 97.86 174 | 97.94 162 | 97.65 239 | 99.71 34 | 97.94 124 | 98.52 91 | 98.68 254 | 98.99 75 | 97.52 248 | 99.35 68 | 97.41 103 | 98.18 348 | 91.59 302 | 99.67 147 | 96.82 327 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
GG-mvs-BLEND | | | | | 94.76 317 | 94.54 351 | 92.13 300 | 99.31 20 | 80.47 357 | | 88.73 351 | 91.01 351 | 67.59 353 | 98.16 349 | 82.30 347 | 94.53 343 | 93.98 348 |
|
testpf | | | 89.08 326 | 90.27 326 | 85.50 339 | 94.03 353 | 82.85 349 | 96.87 243 | 91.09 351 | 91.61 314 | 90.96 348 | 94.86 341 | 66.15 357 | 95.83 350 | 94.58 238 | 92.27 349 | 77.82 351 |
|
FPMVS | | | 93.44 311 | 92.23 316 | 97.08 261 | 99.25 137 | 97.86 130 | 95.61 306 | 97.16 294 | 92.90 298 | 93.76 341 | 98.65 190 | 75.94 348 | 95.66 351 | 79.30 350 | 97.49 314 | 97.73 301 |
|
MVE | | 83.40 22 | 92.50 317 | 91.92 319 | 94.25 323 | 98.83 233 | 91.64 304 | 92.71 342 | 83.52 355 | 95.92 245 | 86.46 353 | 95.46 326 | 95.20 212 | 95.40 352 | 80.51 348 | 98.64 272 | 95.73 340 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
SD-MVS | | | 98.40 131 | 98.68 79 | 97.54 247 | 98.96 205 | 97.99 114 | 97.88 161 | 99.36 111 | 98.20 121 | 99.63 26 | 99.04 124 | 98.76 24 | 95.33 353 | 96.56 174 | 99.74 115 | 99.31 178 |
|
DeepMVS_CX | | | | | 93.44 332 | 98.24 292 | 94.21 266 | | 94.34 327 | 64.28 351 | 91.34 346 | 94.87 340 | 89.45 281 | 92.77 354 | 77.54 351 | 93.14 347 | 93.35 349 |
|
tmp_tt | | | 78.77 328 | 78.73 329 | 78.90 340 | 58.45 356 | 74.76 356 | 94.20 332 | 78.26 358 | 39.16 352 | 86.71 352 | 92.82 350 | 80.50 321 | 75.19 355 | 86.16 332 | 92.29 348 | 86.74 350 |
|
test123 | | | 17.04 332 | 20.11 333 | 7.82 343 | 10.25 358 | 4.91 358 | 94.80 325 | 4.47 360 | 4.93 353 | 10.00 355 | 24.28 354 | 9.69 361 | 3.64 356 | 10.14 353 | 12.43 355 | 14.92 353 |
|
testmvs | | | 17.12 331 | 20.53 332 | 6.87 344 | 12.05 357 | 4.20 359 | 93.62 338 | 6.73 359 | 4.62 354 | 10.41 354 | 24.33 353 | 8.28 362 | 3.56 357 | 9.69 354 | 15.07 353 | 12.86 354 |
|
cdsmvs_eth3d_5k | | | 24.66 330 | 32.88 331 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 99.10 191 | 0.00 355 | 0.00 356 | 97.58 272 | 99.21 11 | 0.00 358 | 0.00 355 | 0.00 356 | 0.00 356 |
|
pcd_1.5k_mvsjas | | | 8.17 333 | 10.90 334 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 0.00 361 | 0.00 355 | 0.00 356 | 0.00 357 | 98.07 61 | 0.00 358 | 0.00 355 | 0.00 356 | 0.00 356 |
|
pcd1.5k->3k | | | 41.59 329 | 44.35 330 | 33.30 342 | 99.87 12 | 0.00 360 | 0.00 351 | 99.58 36 | 0.00 355 | 0.00 356 | 0.00 357 | 99.70 2 | 0.00 358 | 0.00 355 | 99.99 11 | 99.91 2 |
|
sosnet-low-res | | | 0.00 335 | 0.00 336 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 0.00 361 | 0.00 355 | 0.00 356 | 0.00 357 | 0.00 363 | 0.00 358 | 0.00 355 | 0.00 356 | 0.00 356 |
|
sosnet | | | 0.00 335 | 0.00 336 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 0.00 361 | 0.00 355 | 0.00 356 | 0.00 357 | 0.00 363 | 0.00 358 | 0.00 355 | 0.00 356 | 0.00 356 |
|
uncertanet | | | 0.00 335 | 0.00 336 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 0.00 361 | 0.00 355 | 0.00 356 | 0.00 357 | 0.00 363 | 0.00 358 | 0.00 355 | 0.00 356 | 0.00 356 |
|
Regformer | | | 0.00 335 | 0.00 336 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 0.00 361 | 0.00 355 | 0.00 356 | 0.00 357 | 0.00 363 | 0.00 358 | 0.00 355 | 0.00 356 | 0.00 356 |
|
ab-mvs-re | | | 8.12 334 | 10.83 335 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 0.00 361 | 0.00 355 | 0.00 356 | 97.48 279 | 0.00 363 | 0.00 358 | 0.00 355 | 0.00 356 | 0.00 356 |
|
uanet | | | 0.00 335 | 0.00 336 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 0.00 361 | 0.00 355 | 0.00 356 | 0.00 357 | 0.00 363 | 0.00 358 | 0.00 355 | 0.00 356 | 0.00 356 |
|
GSMVS | | | | | | | | | | | | | | | | | 98.81 249 |
|
test_part2 | | | | | | 99.36 121 | 99.10 42 | | | | 99.05 113 | | | | | | |
|
test_part1 | | | | | | | | | 99.28 141 | | | | 97.56 90 | | | 99.57 172 | 99.53 91 |
|
sam_mvs1 | | | | | | | | | | | | | 84.74 303 | | | | 98.81 249 |
|
sam_mvs | | | | | | | | | | | | | 84.29 309 | | | | |
|
MTGPA | | | | | | | | | 99.20 163 | | | | | | | | |
|
MTMP | | | | | | | | | 91.91 348 | | | | | | | | |
|
test9_res | | | | | | | | | | | | | | | 93.28 276 | 99.15 237 | 99.38 156 |
|
agg_prior2 | | | | | | | | | | | | | | | 92.50 291 | 99.16 234 | 99.37 157 |
|
test_prior4 | | | | | | | 97.97 119 | 95.86 296 | | | | | | | | | |
|
test_prior2 | | | | | | | | 95.74 302 | | 96.48 225 | 96.11 304 | 97.63 270 | 95.92 192 | | 94.16 249 | 99.20 227 | |
|
æ–°å‡ ä½•2 | | | | | | | | 95.93 293 | | | | | | | | | |
|
旧先验1 | | | | | | 98.82 236 | 97.45 158 | | 98.76 245 | | | 98.34 227 | 95.50 206 | | | 99.01 252 | 99.23 195 |
|
原ACMM2 | | | | | | | | 95.53 309 | | | | | | | | | |
|
test222 | | | | | | 98.92 214 | 96.93 181 | 95.54 308 | 98.78 244 | 85.72 343 | 96.86 283 | 98.11 245 | 94.43 234 | | | 99.10 245 | 99.23 195 |
|
segment_acmp | | | | | | | | | | | | | 97.02 131 | | | | |
|
testdata1 | | | | | | | | 95.44 313 | | 96.32 230 | | | | | | | |
|
plane_prior7 | | | | | | 99.19 160 | 97.87 129 | | | | | | | | | | |
|
plane_prior6 | | | | | | 98.99 201 | 97.70 146 | | | | | | 94.90 218 | | | | |
|
plane_prior4 | | | | | | | | | | | | 97.98 254 | | | | | |
|
plane_prior3 | | | | | | | 97.78 139 | | | 97.41 177 | 97.79 229 | | | | | | |
|
plane_prior2 | | | | | | | | 97.77 171 | | 98.20 121 | | | | | | | |
|
plane_prior1 | | | | | | 99.05 189 | | | | | | | | | | | |
|
plane_prior | | | | | | | 97.65 148 | 97.07 231 | | 96.72 215 | | | | | | 99.36 204 | |
|
n2 | | | | | | | | | 0.00 361 | | | | | | | | |
|
nn | | | | | | | | | 0.00 361 | | | | | | | | |
|
door-mid | | | | | | | | | 99.57 43 | | | | | | | | |
|
test11 | | | | | | | | | 98.87 228 | | | | | | | | |
|
door | | | | | | | | | 99.41 97 | | | | | | | | |
|
HQP5-MVS | | | | | | | 96.79 184 | | | | | | | | | | |
|
HQP-NCC | | | | | | 98.67 258 | | 96.29 273 | | 96.05 241 | 95.55 318 | | | | | | |
|
ACMP_Plane | | | | | | 98.67 258 | | 96.29 273 | | 96.05 241 | 95.55 318 | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 92.82 284 | | |
|
HQP3-MVS | | | | | | | | | 99.04 201 | | | | | | | 99.26 221 | |
|
HQP2-MVS | | | | | | | | | | | | | 93.84 245 | | | | |
|
NP-MVS | | | | | | 98.84 231 | 97.39 161 | | | | | 96.84 297 | | | | | |
|
MDTV_nov1_ep13_2view | | | | | | | 74.92 355 | 97.69 179 | | 90.06 330 | 97.75 232 | | 85.78 296 | | 93.52 270 | | 98.69 263 |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 99.77 104 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 99.68 142 | |
|
Test By Simon | | | | | | | | | | | | | 96.52 165 | | | | |
|