LCM-MVSNet | | | 99.86 1 | 99.86 1 | 99.87 1 | 99.99 1 | 99.77 1 | 99.77 1 | 99.80 1 | 99.97 1 | 99.97 1 | 99.95 1 | 99.74 1 | 99.98 1 | 99.56 1 | 100.00 1 | 99.85 4 |
|
Effi-MVS+-dtu | | | 96.81 136 | 96.09 161 | 98.99 10 | 96.90 288 | 98.69 2 | 96.42 130 | 98.09 203 | 95.86 124 | 95.15 242 | 95.54 277 | 94.26 146 | 99.81 33 | 94.06 170 | 98.51 241 | 98.47 215 |
|
RPSCF | | | 97.87 62 | 97.51 85 | 98.95 14 | 99.15 68 | 98.43 3 | 97.56 81 | 99.06 36 | 96.19 112 | 98.48 70 | 98.70 69 | 94.72 125 | 99.24 245 | 94.37 160 | 99.33 166 | 99.17 131 |
|
mvs-test1 | | | 96.20 162 | 95.50 180 | 98.32 62 | 96.90 288 | 98.16 4 | 95.07 219 | 98.09 203 | 95.86 124 | 93.63 290 | 94.32 303 | 94.26 146 | 99.71 81 | 94.06 170 | 97.27 301 | 97.07 288 |
|
abl_6 | | | 98.42 27 | 98.19 42 | 99.09 4 | 99.16 65 | 98.10 5 | 97.73 70 | 99.11 23 | 97.76 51 | 98.62 58 | 98.27 105 | 97.88 21 | 99.80 37 | 95.67 106 | 99.50 113 | 99.38 97 |
|
TDRefinement | | | 98.90 5 | 98.86 11 | 99.02 8 | 99.54 23 | 98.06 6 | 99.34 5 | 99.44 7 | 98.85 19 | 99.00 41 | 99.20 31 | 97.42 31 | 99.59 145 | 97.21 63 | 99.76 51 | 99.40 92 |
|
wuykxyi23d | | | 98.68 17 | 98.53 27 | 99.13 3 | 99.44 35 | 97.97 7 | 96.85 118 | 99.02 51 | 95.81 127 | 99.88 2 | 99.38 13 | 98.14 14 | 99.69 98 | 98.32 29 | 99.95 13 | 99.73 16 |
|
zzz-MVS | | | 98.01 47 | 97.66 70 | 99.06 5 | 99.44 35 | 97.90 8 | 95.66 178 | 98.73 114 | 97.69 58 | 97.90 129 | 97.96 139 | 95.81 95 | 99.82 31 | 96.13 89 | 99.61 85 | 99.45 72 |
|
MTAPA | | | 98.14 38 | 97.84 58 | 99.06 5 | 99.44 35 | 97.90 8 | 97.25 93 | 98.73 114 | 97.69 58 | 97.90 129 | 97.96 139 | 95.81 95 | 99.82 31 | 96.13 89 | 99.61 85 | 99.45 72 |
|
UA-Net | | | 98.88 7 | 98.76 16 | 99.22 2 | 99.11 78 | 97.89 10 | 99.47 3 | 99.32 8 | 99.08 9 | 97.87 138 | 99.67 3 | 96.47 74 | 99.92 4 | 97.88 35 | 99.98 3 | 99.85 4 |
|
mPP-MVS | | | 97.91 58 | 97.53 83 | 99.04 7 | 99.22 57 | 97.87 11 | 97.74 68 | 98.78 106 | 96.04 116 | 97.10 169 | 97.73 163 | 96.53 69 | 99.78 40 | 95.16 132 | 99.50 113 | 99.46 67 |
|
CP-MVS | | | 97.92 56 | 97.56 82 | 98.99 10 | 98.99 91 | 97.82 12 | 97.93 55 | 98.96 70 | 96.11 113 | 96.89 184 | 97.45 184 | 96.85 54 | 99.78 40 | 95.19 128 | 99.63 79 | 99.38 97 |
|
PMVS | | 89.60 17 | 96.71 144 | 96.97 121 | 95.95 212 | 99.51 27 | 97.81 13 | 97.42 89 | 97.49 240 | 97.93 46 | 95.95 222 | 98.58 76 | 96.88 52 | 96.91 346 | 89.59 257 | 99.36 156 | 93.12 345 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
MP-MVS | | | 97.64 80 | 97.18 107 | 99.00 9 | 99.32 50 | 97.77 14 | 97.49 85 | 98.73 114 | 96.27 108 | 95.59 235 | 97.75 160 | 96.30 79 | 99.78 40 | 93.70 182 | 99.48 123 | 99.45 72 |
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
HSP-MVS | | | 97.37 98 | 96.85 127 | 98.92 19 | 99.26 52 | 97.70 15 | 97.66 71 | 98.23 186 | 95.65 130 | 98.51 67 | 96.46 243 | 92.15 205 | 99.81 33 | 95.14 134 | 98.58 238 | 99.26 123 |
|
XVS | | | 97.96 49 | 97.63 75 | 98.94 15 | 99.15 68 | 97.66 16 | 97.77 63 | 98.83 96 | 97.42 72 | 96.32 207 | 97.64 168 | 96.49 72 | 99.72 71 | 95.66 108 | 99.37 153 | 99.45 72 |
|
X-MVStestdata | | | 92.86 259 | 90.83 293 | 98.94 15 | 99.15 68 | 97.66 16 | 97.77 63 | 98.83 96 | 97.42 72 | 96.32 207 | 36.50 356 | 96.49 72 | 99.72 71 | 95.66 108 | 99.37 153 | 99.45 72 |
|
PGM-MVS | | | 97.88 61 | 97.52 84 | 98.96 13 | 99.20 61 | 97.62 18 | 97.09 106 | 99.06 36 | 95.45 139 | 97.55 146 | 97.94 143 | 97.11 42 | 99.78 40 | 94.77 148 | 99.46 127 | 99.48 62 |
|
ACMMP | | | 98.05 43 | 97.75 64 | 98.93 18 | 99.23 56 | 97.60 19 | 98.09 46 | 98.96 70 | 95.75 129 | 97.91 128 | 98.06 131 | 96.89 50 | 99.76 49 | 95.32 123 | 99.57 96 | 99.43 85 |
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 |
HPM-MVS++ | | | 96.99 114 | 96.38 152 | 98.81 27 | 98.64 123 | 97.59 20 | 95.97 158 | 98.20 190 | 95.51 137 | 95.06 243 | 96.53 239 | 94.10 152 | 99.70 89 | 94.29 164 | 99.15 184 | 99.13 138 |
|
LS3D | | | 97.77 71 | 97.50 86 | 98.57 44 | 96.24 300 | 97.58 21 | 98.45 26 | 98.85 85 | 98.58 24 | 97.51 148 | 97.94 143 | 95.74 98 | 99.63 123 | 95.19 128 | 98.97 202 | 98.51 213 |
|
ACMMPR | | | 97.95 51 | 97.62 77 | 98.94 15 | 99.20 61 | 97.56 22 | 97.59 79 | 98.83 96 | 96.05 114 | 97.46 155 | 97.63 169 | 96.77 58 | 99.76 49 | 95.61 112 | 99.46 127 | 99.49 59 |
|
region2R | | | 97.92 56 | 97.59 79 | 98.92 19 | 99.22 57 | 97.55 23 | 97.60 78 | 98.84 88 | 96.00 118 | 97.22 162 | 97.62 170 | 96.87 53 | 99.76 49 | 95.48 116 | 99.43 141 | 99.46 67 |
|
ACMM | | 93.33 11 | 98.05 43 | 97.79 60 | 98.85 24 | 99.15 68 | 97.55 23 | 96.68 125 | 98.83 96 | 95.21 149 | 98.36 78 | 98.13 122 | 98.13 16 | 99.62 129 | 96.04 93 | 99.54 104 | 99.39 95 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
HFP-MVS | | | 97.94 53 | 97.64 73 | 98.83 25 | 99.15 68 | 97.50 25 | 97.59 79 | 98.84 88 | 96.05 114 | 97.49 150 | 97.54 176 | 97.07 45 | 99.70 89 | 95.61 112 | 99.46 127 | 99.30 112 |
|
#test# | | | 97.62 81 | 97.22 104 | 98.83 25 | 99.15 68 | 97.50 25 | 96.81 120 | 98.84 88 | 94.25 189 | 97.49 150 | 97.54 176 | 97.07 45 | 99.70 89 | 94.37 160 | 99.46 127 | 99.30 112 |
|
HPM-MVS_fast | | | 98.32 31 | 98.13 45 | 98.88 23 | 99.54 23 | 97.48 27 | 98.35 29 | 99.03 50 | 95.88 123 | 97.88 133 | 98.22 110 | 98.15 13 | 99.74 60 | 96.50 81 | 99.62 80 | 99.42 87 |
|
HPM-MVS | | | 98.11 41 | 97.83 59 | 98.92 19 | 99.42 40 | 97.46 28 | 98.57 18 | 99.05 38 | 95.43 141 | 97.41 157 | 97.50 181 | 97.98 17 | 99.79 39 | 95.58 115 | 99.57 96 | 99.50 51 |
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
XVG-OURS | | | 97.12 111 | 96.74 135 | 98.26 67 | 98.99 91 | 97.45 29 | 93.82 272 | 99.05 38 | 95.19 151 | 98.32 83 | 97.70 166 | 95.22 115 | 98.41 321 | 94.27 165 | 98.13 255 | 98.93 171 |
|
MAR-MVS | | | 94.21 233 | 93.03 248 | 97.76 92 | 96.94 286 | 97.44 30 | 96.97 117 | 97.15 253 | 87.89 289 | 92.00 321 | 92.73 323 | 92.14 206 | 99.12 254 | 83.92 319 | 97.51 291 | 96.73 302 |
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 |
XVG-OURS-SEG-HR | | | 97.38 97 | 97.07 117 | 98.30 65 | 99.01 90 | 97.41 31 | 94.66 236 | 99.02 51 | 95.20 150 | 98.15 99 | 97.52 179 | 98.83 5 | 98.43 320 | 94.87 141 | 96.41 314 | 99.07 153 |
|
COLMAP_ROB | | 94.48 6 | 98.25 35 | 98.11 46 | 98.64 40 | 99.21 60 | 97.35 32 | 97.96 53 | 99.16 16 | 98.34 32 | 98.78 49 | 98.52 82 | 97.32 34 | 99.45 192 | 94.08 169 | 99.67 74 | 99.13 138 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
APD-MVS_3200maxsize | | | 98.13 40 | 97.90 55 | 98.79 28 | 98.79 105 | 97.31 33 | 97.55 82 | 98.92 74 | 97.72 56 | 98.25 90 | 98.13 122 | 97.10 43 | 99.75 55 | 95.44 118 | 99.24 177 | 99.32 108 |
|
anonymousdsp | | | 98.72 16 | 98.63 22 | 98.99 10 | 99.62 14 | 97.29 34 | 98.65 16 | 99.19 14 | 95.62 132 | 99.35 20 | 99.37 14 | 97.38 32 | 99.90 13 | 98.59 23 | 99.91 27 | 99.77 9 |
|
DeepPCF-MVS | | 94.58 5 | 96.90 126 | 96.43 151 | 98.31 64 | 97.48 257 | 97.23 35 | 92.56 305 | 98.60 141 | 92.84 232 | 98.54 65 | 97.40 187 | 96.64 64 | 98.78 296 | 94.40 159 | 99.41 150 | 98.93 171 |
|
SteuartSystems-ACMMP | | | 98.02 45 | 97.76 63 | 98.79 28 | 99.43 38 | 97.21 36 | 97.15 97 | 98.90 76 | 96.58 99 | 98.08 108 | 97.87 150 | 97.02 47 | 99.76 49 | 95.25 125 | 99.59 90 | 99.40 92 |
Skip Steuart: Steuart Systems R&D Blog. |
Anonymous20231211 | | | 99.29 2 | 99.41 2 | 98.91 22 | 99.94 2 | 97.08 37 | 99.47 3 | 99.51 5 | 99.56 2 | 99.83 3 | 99.80 2 | 99.13 3 | 99.90 13 | 97.55 50 | 99.93 21 | 99.75 13 |
|
LPG-MVS_test | | | 97.94 53 | 97.67 69 | 98.74 32 | 99.15 68 | 97.02 38 | 97.09 106 | 99.02 51 | 95.15 154 | 98.34 80 | 98.23 107 | 97.91 19 | 99.70 89 | 94.41 157 | 99.73 57 | 99.50 51 |
|
LGP-MVS_train | | | | | 98.74 32 | 99.15 68 | 97.02 38 | | 99.02 51 | 95.15 154 | 98.34 80 | 98.23 107 | 97.91 19 | 99.70 89 | 94.41 157 | 99.73 57 | 99.50 51 |
|
LTVRE_ROB | | 96.88 1 | 99.18 3 | 99.34 3 | 98.72 35 | 99.71 7 | 96.99 40 | 99.69 2 | 99.57 3 | 99.02 14 | 99.62 10 | 99.36 16 | 98.53 8 | 99.52 164 | 98.58 24 | 99.95 13 | 99.66 24 |
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 |
FPMVS | | | 89.92 307 | 88.63 314 | 93.82 281 | 98.37 156 | 96.94 41 | 91.58 319 | 93.34 306 | 88.00 287 | 90.32 335 | 97.10 204 | 70.87 337 | 91.13 355 | 71.91 351 | 96.16 318 | 93.39 344 |
|
XVG-ACMP-BASELINE | | | 97.58 85 | 97.28 96 | 98.49 47 | 99.16 65 | 96.90 42 | 96.39 131 | 98.98 67 | 95.05 162 | 98.06 111 | 98.02 134 | 95.86 87 | 99.56 153 | 94.37 160 | 99.64 78 | 99.00 159 |
|
MP-MVS-pluss | | | 97.69 77 | 97.36 91 | 98.70 36 | 99.50 30 | 96.84 43 | 95.38 198 | 98.99 65 | 92.45 238 | 98.11 102 | 98.31 98 | 97.25 39 | 99.77 48 | 96.60 76 | 99.62 80 | 99.48 62 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
ACMMP_Plus | | | 97.89 60 | 97.63 75 | 98.67 38 | 99.35 47 | 96.84 43 | 96.36 136 | 98.79 103 | 95.07 161 | 97.88 133 | 98.35 94 | 97.24 40 | 99.72 71 | 96.05 92 | 99.58 93 | 99.45 72 |
|
PM-MVS | | | 97.36 101 | 97.10 114 | 98.14 73 | 98.91 98 | 96.77 45 | 96.20 146 | 98.63 138 | 93.82 205 | 98.54 65 | 98.33 96 | 93.98 155 | 99.05 264 | 95.99 97 | 99.45 131 | 98.61 206 |
|
SMA-MVS | | | 97.55 86 | 97.19 106 | 98.61 42 | 98.83 102 | 96.71 46 | 96.74 122 | 98.81 102 | 91.81 250 | 98.78 49 | 98.36 93 | 96.63 65 | 99.68 104 | 95.17 130 | 99.59 90 | 99.45 72 |
|
MIMVSNet1 | | | 98.51 24 | 98.45 32 | 98.67 38 | 99.72 6 | 96.71 46 | 98.76 11 | 98.89 78 | 98.49 25 | 99.38 18 | 99.14 42 | 95.44 107 | 99.84 28 | 96.47 82 | 99.80 47 | 99.47 65 |
|
ACMP | | 92.54 13 | 97.47 92 | 97.10 114 | 98.55 46 | 99.04 86 | 96.70 48 | 96.24 144 | 98.89 78 | 93.71 208 | 97.97 120 | 97.75 160 | 97.44 29 | 99.63 123 | 93.22 190 | 99.70 67 | 99.32 108 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
ITE_SJBPF | | | | | 97.85 88 | 98.64 123 | 96.66 49 | | 98.51 149 | 95.63 131 | 97.22 162 | 97.30 195 | 95.52 102 | 98.55 315 | 90.97 227 | 98.90 209 | 98.34 229 |
|
CPTT-MVS | | | 96.69 145 | 96.08 162 | 98.49 47 | 98.89 100 | 96.64 50 | 97.25 93 | 98.77 107 | 92.89 231 | 96.01 221 | 97.13 201 | 92.23 204 | 99.67 111 | 92.24 202 | 99.34 161 | 99.17 131 |
|
OPM-MVS | | | 97.54 88 | 97.25 97 | 98.41 52 | 99.11 78 | 96.61 51 | 95.24 210 | 98.46 152 | 94.58 177 | 98.10 105 | 98.07 128 | 97.09 44 | 99.39 217 | 95.16 132 | 99.44 132 | 99.21 126 |
|
WR-MVS_H | | | 98.65 18 | 98.62 24 | 98.75 30 | 99.51 27 | 96.61 51 | 98.55 20 | 99.17 15 | 99.05 12 | 99.17 32 | 98.79 61 | 95.47 105 | 99.89 17 | 97.95 33 | 99.91 27 | 99.75 13 |
|
N_pmnet | | | 95.18 201 | 94.23 225 | 98.06 76 | 97.85 217 | 96.55 53 | 92.49 306 | 91.63 322 | 89.34 271 | 98.09 106 | 97.41 186 | 90.33 236 | 99.06 263 | 91.58 215 | 99.31 168 | 98.56 209 |
|
PHI-MVS | | | 96.96 121 | 96.53 147 | 98.25 69 | 97.48 257 | 96.50 54 | 96.76 121 | 98.85 85 | 93.52 211 | 96.19 216 | 96.85 218 | 95.94 85 | 99.42 197 | 93.79 180 | 99.43 141 | 98.83 188 |
|
jajsoiax | | | 98.77 11 | 98.79 15 | 98.74 32 | 99.66 10 | 96.48 55 | 98.45 26 | 99.12 22 | 95.83 126 | 99.67 7 | 99.37 14 | 98.25 11 | 99.92 4 | 98.77 14 | 99.94 19 | 99.82 7 |
|
mvs_tets | | | 98.90 5 | 98.94 8 | 98.75 30 | 99.69 8 | 96.48 55 | 98.54 21 | 99.22 10 | 96.23 111 | 99.71 5 | 99.48 7 | 98.77 7 | 99.93 2 | 98.89 10 | 99.95 13 | 99.84 6 |
|
pmmvs6 | | | 99.07 4 | 99.24 4 | 98.56 45 | 99.81 3 | 96.38 57 | 98.87 10 | 99.30 9 | 99.01 15 | 99.63 9 | 99.66 4 | 99.27 2 | 99.68 104 | 97.75 42 | 99.89 33 | 99.62 32 |
|
OurMVSNet-221017-0 | | | 98.61 19 | 98.61 26 | 98.63 41 | 99.77 4 | 96.35 58 | 99.17 6 | 99.05 38 | 98.05 42 | 99.61 11 | 99.52 5 | 93.72 165 | 99.88 19 | 98.72 20 | 99.88 34 | 99.65 25 |
|
APD-MVS | | | 97.00 113 | 96.53 147 | 98.41 52 | 98.55 137 | 96.31 59 | 96.32 139 | 98.77 107 | 92.96 230 | 97.44 156 | 97.58 175 | 95.84 88 | 99.74 60 | 91.96 204 | 99.35 159 | 99.19 128 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
test_djsdf | | | 98.73 13 | 98.74 18 | 98.69 37 | 99.63 13 | 96.30 60 | 98.67 13 | 99.02 51 | 96.50 100 | 99.32 21 | 99.44 10 | 97.43 30 | 99.92 4 | 98.73 17 | 99.95 13 | 99.86 3 |
|
Gipuma | | | 98.07 42 | 98.31 38 | 97.36 127 | 99.76 5 | 96.28 61 | 98.51 22 | 99.10 25 | 98.76 20 | 96.79 186 | 99.34 20 | 96.61 66 | 98.82 292 | 96.38 84 | 99.50 113 | 96.98 291 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
AllTest | | | 97.20 110 | 96.92 125 | 98.06 76 | 99.08 80 | 96.16 62 | 97.14 99 | 99.16 16 | 94.35 186 | 97.78 143 | 98.07 128 | 95.84 88 | 99.12 254 | 91.41 216 | 99.42 144 | 98.91 174 |
|
TestCases | | | | | 98.06 76 | 99.08 80 | 96.16 62 | | 99.16 16 | 94.35 186 | 97.78 143 | 98.07 128 | 95.84 88 | 99.12 254 | 91.41 216 | 99.42 144 | 98.91 174 |
|
DTE-MVSNet | | | 98.79 10 | 98.86 11 | 98.59 43 | 99.55 21 | 96.12 64 | 98.48 25 | 99.10 25 | 99.36 3 | 99.29 25 | 99.06 48 | 97.27 37 | 99.93 2 | 97.71 44 | 99.91 27 | 99.70 19 |
|
test_part2 | | | | | | 99.03 87 | 96.07 65 | | | | 98.08 108 | | | | | | |
|
ESAPD | | | 97.22 109 | 96.82 130 | 98.40 54 | 99.03 87 | 96.07 65 | 95.64 182 | 98.84 88 | 94.84 166 | 98.08 108 | 97.60 172 | 96.69 61 | 99.76 49 | 91.22 222 | 99.44 132 | 99.37 102 |
|
APDe-MVS | | | 98.14 38 | 98.03 51 | 98.47 49 | 98.72 112 | 96.04 67 | 98.07 47 | 99.10 25 | 95.96 120 | 98.59 62 | 98.69 70 | 96.94 48 | 99.81 33 | 96.64 75 | 99.58 93 | 99.57 41 |
|
F-COLMAP | | | 95.30 197 | 94.38 222 | 98.05 79 | 98.64 123 | 96.04 67 | 95.61 186 | 98.66 131 | 89.00 274 | 93.22 305 | 96.40 249 | 92.90 185 | 99.35 228 | 87.45 294 | 97.53 290 | 98.77 194 |
|
OMC-MVS | | | 96.48 154 | 96.00 165 | 97.91 85 | 98.30 160 | 96.01 69 | 94.86 230 | 98.60 141 | 91.88 248 | 97.18 164 | 97.21 198 | 96.11 82 | 99.04 265 | 90.49 245 | 99.34 161 | 98.69 200 |
|
TranMVSNet+NR-MVSNet | | | 98.33 30 | 98.30 40 | 98.43 51 | 99.07 82 | 95.87 70 | 96.73 123 | 99.05 38 | 98.67 21 | 98.84 46 | 98.45 87 | 97.58 27 | 99.88 19 | 96.45 83 | 99.86 39 | 99.54 46 |
|
UniMVSNet (Re) | | | 97.83 65 | 97.65 71 | 98.35 61 | 98.80 104 | 95.86 71 | 95.92 166 | 99.04 45 | 97.51 69 | 98.22 92 | 97.81 155 | 94.68 129 | 99.78 40 | 97.14 68 | 99.75 55 | 99.41 89 |
|
UniMVSNet_NR-MVSNet | | | 97.83 65 | 97.65 71 | 98.37 56 | 98.72 112 | 95.78 72 | 95.66 178 | 99.02 51 | 98.11 40 | 98.31 85 | 97.69 167 | 94.65 131 | 99.85 24 | 97.02 71 | 99.71 64 | 99.48 62 |
|
DU-MVS | | | 97.79 70 | 97.60 78 | 98.36 59 | 98.73 110 | 95.78 72 | 95.65 180 | 98.87 82 | 97.57 64 | 98.31 85 | 97.83 151 | 94.69 127 | 99.85 24 | 97.02 71 | 99.71 64 | 99.46 67 |
|
PatchMatch-RL | | | 94.61 222 | 93.81 236 | 97.02 146 | 98.19 183 | 95.72 74 | 93.66 277 | 97.23 249 | 88.17 284 | 94.94 247 | 95.62 275 | 91.43 224 | 98.57 312 | 87.36 295 | 97.68 282 | 96.76 301 |
|
DeepC-MVS | | 95.41 4 | 97.82 68 | 97.70 66 | 98.16 71 | 98.78 106 | 95.72 74 | 96.23 145 | 99.02 51 | 93.92 198 | 98.62 58 | 98.99 50 | 97.69 23 | 99.62 129 | 96.18 88 | 99.87 37 | 99.15 135 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
NCCC | | | 96.52 152 | 95.99 166 | 98.10 74 | 97.81 224 | 95.68 76 | 95.00 225 | 98.20 190 | 95.39 142 | 95.40 238 | 96.36 250 | 93.81 162 | 99.45 192 | 93.55 185 | 98.42 244 | 99.17 131 |
|
PEN-MVS | | | 98.75 12 | 98.85 13 | 98.44 50 | 99.58 18 | 95.67 77 | 98.45 26 | 99.15 19 | 99.33 4 | 99.30 24 | 99.00 49 | 97.27 37 | 99.92 4 | 97.64 45 | 99.92 24 | 99.75 13 |
|
nrg030 | | | 98.54 22 | 98.62 24 | 98.32 62 | 99.22 57 | 95.66 78 | 97.90 57 | 99.08 30 | 98.31 33 | 99.02 38 | 98.74 66 | 97.68 24 | 99.61 135 | 97.77 41 | 99.85 40 | 99.70 19 |
|
Anonymous20240521 | | | 98.58 20 | 98.65 21 | 98.36 59 | 99.52 25 | 95.60 79 | 98.96 9 | 98.95 72 | 98.36 30 | 99.25 27 | 99.17 39 | 95.28 113 | 99.80 37 | 98.46 25 | 99.88 34 | 99.68 23 |
|
3Dnovator+ | | 96.13 3 | 97.73 73 | 97.59 79 | 98.15 72 | 98.11 197 | 95.60 79 | 98.04 49 | 98.70 123 | 98.13 39 | 96.93 182 | 98.45 87 | 95.30 112 | 99.62 129 | 95.64 110 | 98.96 203 | 99.24 124 |
|
LF4IMVS | | | 96.07 166 | 95.63 177 | 97.36 127 | 98.19 183 | 95.55 81 | 95.44 189 | 98.82 100 | 92.29 240 | 95.70 233 | 96.55 237 | 92.63 193 | 98.69 304 | 91.75 213 | 99.33 166 | 97.85 263 |
|
NR-MVSNet | | | 97.96 49 | 97.86 57 | 98.26 67 | 98.73 110 | 95.54 82 | 98.14 43 | 98.73 114 | 97.79 49 | 99.42 16 | 97.83 151 | 94.40 141 | 99.78 40 | 95.91 101 | 99.76 51 | 99.46 67 |
|
CNVR-MVS | | | 96.92 124 | 96.55 144 | 98.03 80 | 98.00 207 | 95.54 82 | 94.87 229 | 98.17 195 | 94.60 174 | 96.38 201 | 97.05 206 | 95.67 99 | 99.36 226 | 95.12 136 | 99.08 193 | 99.19 128 |
|
v52 | | | 98.85 8 | 99.01 5 | 98.37 56 | 99.61 15 | 95.53 84 | 99.01 7 | 99.04 45 | 98.48 26 | 99.31 22 | 99.41 11 | 96.82 56 | 99.87 21 | 99.44 2 | 99.95 13 | 99.70 19 |
|
V4 | | | 98.85 8 | 99.01 5 | 98.37 56 | 99.61 15 | 95.53 84 | 99.01 7 | 99.04 45 | 98.48 26 | 99.31 22 | 99.41 11 | 96.81 57 | 99.87 21 | 99.44 2 | 99.95 13 | 99.70 19 |
|
PS-CasMVS | | | 98.73 13 | 98.85 13 | 98.39 55 | 99.55 21 | 95.47 86 | 98.49 23 | 99.13 21 | 99.22 7 | 99.22 29 | 98.96 53 | 97.35 33 | 99.92 4 | 97.79 40 | 99.93 21 | 99.79 8 |
|
test_prior4 | | | | | | | 95.38 87 | 93.61 281 | | | | | | | | | |
|
wuyk23d | | | 93.25 256 | 95.20 187 | 87.40 337 | 96.07 308 | 95.38 87 | 97.04 108 | 94.97 289 | 95.33 143 | 99.70 6 | 98.11 125 | 98.14 14 | 91.94 354 | 77.76 343 | 99.68 72 | 74.89 354 |
|
MVS_111021_LR | | | 96.82 135 | 96.55 144 | 97.62 102 | 98.27 166 | 95.34 89 | 93.81 273 | 98.33 172 | 94.59 176 | 96.56 193 | 96.63 234 | 96.61 66 | 98.73 300 | 94.80 145 | 99.34 161 | 98.78 193 |
|
CNLPA | | | 95.04 206 | 94.47 217 | 96.75 157 | 97.81 224 | 95.25 90 | 94.12 260 | 97.89 214 | 94.41 182 | 94.57 260 | 95.69 271 | 90.30 239 | 98.35 328 | 86.72 300 | 98.76 222 | 96.64 305 |
|
TEST9 | | | | | | 97.84 221 | 95.23 91 | 93.62 279 | 98.39 163 | 86.81 297 | 93.78 283 | 95.99 262 | 94.68 129 | 99.52 164 | | | |
|
train_agg | | | 95.46 188 | 94.66 207 | 97.88 86 | 97.84 221 | 95.23 91 | 93.62 279 | 98.39 163 | 87.04 295 | 93.78 283 | 95.99 262 | 94.58 134 | 99.52 164 | 91.76 211 | 98.90 209 | 98.89 178 |
|
TSAR-MVS + GP. | | | 96.47 155 | 96.12 159 | 97.49 116 | 97.74 239 | 95.23 91 | 94.15 257 | 96.90 262 | 93.26 214 | 98.04 113 | 96.70 230 | 94.41 140 | 98.89 284 | 94.77 148 | 99.14 185 | 98.37 223 |
|
CP-MVSNet | | | 98.42 27 | 98.46 30 | 98.30 65 | 99.46 33 | 95.22 94 | 98.27 34 | 98.84 88 | 99.05 12 | 99.01 39 | 98.65 74 | 95.37 108 | 99.90 13 | 97.57 49 | 99.91 27 | 99.77 9 |
|
ACMH+ | | 93.58 10 | 98.23 36 | 98.31 38 | 97.98 82 | 99.39 43 | 95.22 94 | 97.55 82 | 99.20 13 | 98.21 37 | 99.25 27 | 98.51 83 | 98.21 12 | 99.40 211 | 94.79 146 | 99.72 60 | 99.32 108 |
|
Vis-MVSNet | | | 98.27 33 | 98.34 36 | 98.07 75 | 99.33 48 | 95.21 96 | 98.04 49 | 99.46 6 | 97.32 83 | 97.82 142 | 99.11 44 | 96.75 59 | 99.86 23 | 97.84 37 | 99.36 156 | 99.15 135 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
SD-MVS | | | 97.37 98 | 97.70 66 | 96.35 180 | 98.14 193 | 95.13 97 | 96.54 126 | 98.92 74 | 95.94 121 | 99.19 30 | 98.08 127 | 97.74 22 | 95.06 352 | 95.24 126 | 99.54 104 | 98.87 184 |
|
PLC | | 91.02 16 | 94.05 240 | 92.90 250 | 97.51 110 | 98.00 207 | 95.12 98 | 94.25 248 | 98.25 185 | 86.17 302 | 91.48 326 | 95.25 281 | 91.01 228 | 99.19 249 | 85.02 313 | 96.69 310 | 98.22 240 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
test_8 | | | | | | 97.81 224 | 95.07 99 | 93.54 282 | 98.38 165 | 87.04 295 | 93.71 287 | 95.96 266 | 94.58 134 | 99.52 164 | | | |
|
TSAR-MVS + MP. | | | 97.42 94 | 97.23 103 | 98.00 81 | 99.38 44 | 95.00 100 | 97.63 74 | 98.20 190 | 93.00 224 | 98.16 97 | 98.06 131 | 95.89 86 | 99.72 71 | 95.67 106 | 99.10 191 | 99.28 119 |
|
agg_prior3 | | | 95.30 197 | 94.46 220 | 97.80 91 | 97.80 228 | 95.00 100 | 93.63 278 | 98.34 171 | 86.33 301 | 93.40 303 | 95.84 269 | 94.15 151 | 99.50 176 | 91.76 211 | 98.90 209 | 98.89 178 |
|
agg_prior1 | | | 95.39 192 | 94.60 211 | 97.75 93 | 97.80 228 | 94.96 102 | 93.39 287 | 98.36 167 | 87.20 293 | 93.49 296 | 95.97 265 | 94.65 131 | 99.53 161 | 91.69 214 | 98.86 216 | 98.77 194 |
|
agg_prior | | | | | | 97.80 228 | 94.96 102 | | 98.36 167 | | 93.49 296 | | | 99.53 161 | | | |
|
CDPH-MVS | | | 95.45 190 | 94.65 208 | 97.84 89 | 98.28 164 | 94.96 102 | 93.73 275 | 98.33 172 | 85.03 316 | 95.44 236 | 96.60 235 | 95.31 111 | 99.44 195 | 90.01 252 | 99.13 187 | 99.11 146 |
|
CSCG | | | 97.40 96 | 97.30 93 | 97.69 98 | 98.95 94 | 94.83 105 | 97.28 92 | 98.99 65 | 96.35 107 | 98.13 101 | 95.95 267 | 95.99 84 | 99.66 116 | 94.36 163 | 99.73 57 | 98.59 207 |
|
PS-MVSNAJss | | | 98.53 23 | 98.63 22 | 98.21 70 | 99.68 9 | 94.82 106 | 98.10 45 | 99.21 11 | 96.91 88 | 99.75 4 | 99.45 9 | 95.82 91 | 99.92 4 | 98.80 13 | 99.96 11 | 99.89 1 |
|
DP-MVS | | | 97.87 62 | 97.89 56 | 97.81 90 | 98.62 128 | 94.82 106 | 97.13 100 | 98.79 103 | 98.98 16 | 98.74 53 | 98.49 84 | 95.80 97 | 99.49 178 | 95.04 139 | 99.44 132 | 99.11 146 |
|
1121 | | | 94.26 228 | 93.26 244 | 97.27 131 | 98.26 174 | 94.73 108 | 95.86 167 | 97.71 226 | 77.96 346 | 94.53 262 | 96.71 229 | 91.93 215 | 99.40 211 | 87.71 281 | 98.64 233 | 97.69 269 |
|
Regformer-2 | | | 97.41 95 | 97.24 99 | 97.93 84 | 97.21 276 | 94.72 109 | 94.85 231 | 98.27 182 | 97.74 52 | 98.11 102 | 97.50 181 | 95.58 101 | 99.69 98 | 96.57 78 | 99.31 168 | 99.37 102 |
|
alignmvs | | | 96.01 168 | 95.52 179 | 97.50 113 | 97.77 238 | 94.71 110 | 96.07 151 | 96.84 263 | 97.48 70 | 96.78 187 | 94.28 304 | 85.50 275 | 99.40 211 | 96.22 87 | 98.73 227 | 98.40 220 |
|
新几何1 | | | | | 97.25 134 | 98.29 161 | 94.70 111 | | 97.73 224 | 77.98 345 | 94.83 250 | 96.67 232 | 92.08 209 | 99.45 192 | 88.17 279 | 98.65 232 | 97.61 272 |
|
plane_prior7 | | | | | | 98.70 117 | 94.67 112 | | | | | | | | | | |
|
CMPMVS | | 73.10 23 | 92.74 261 | 91.39 273 | 96.77 156 | 93.57 344 | 94.67 112 | 94.21 252 | 97.67 228 | 80.36 337 | 93.61 292 | 96.60 235 | 82.85 285 | 97.35 343 | 84.86 314 | 98.78 220 | 98.29 235 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
pm-mvs1 | | | 98.47 25 | 98.67 19 | 97.86 87 | 99.52 25 | 94.58 114 | 98.28 32 | 99.00 62 | 97.57 64 | 99.27 26 | 99.22 30 | 98.32 10 | 99.50 176 | 97.09 69 | 99.75 55 | 99.50 51 |
|
plane_prior3 | | | | | | | 94.51 115 | | | 95.29 145 | 96.16 217 | | | | | | |
|
TAPA-MVS | | 93.32 12 | 94.93 210 | 94.23 225 | 97.04 143 | 98.18 186 | 94.51 115 | 95.22 211 | 98.73 114 | 81.22 333 | 96.25 213 | 95.95 267 | 93.80 163 | 98.98 274 | 89.89 253 | 98.87 214 | 97.62 271 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
VDD-MVS | | | 97.37 98 | 97.25 97 | 97.74 94 | 98.69 121 | 94.50 117 | 97.04 108 | 95.61 286 | 98.59 23 | 98.51 67 | 98.72 67 | 92.54 197 | 99.58 147 | 96.02 95 | 99.49 120 | 99.12 143 |
|
AdaColmap | | | 95.11 203 | 94.62 210 | 96.58 167 | 97.33 271 | 94.45 118 | 94.92 227 | 98.08 205 | 93.15 221 | 93.98 280 | 95.53 278 | 94.34 143 | 99.10 259 | 85.69 306 | 98.61 235 | 96.20 317 |
|
Fast-Effi-MVS+-dtu | | | 96.44 156 | 96.12 159 | 97.39 126 | 97.18 278 | 94.39 119 | 95.46 188 | 98.73 114 | 96.03 117 | 94.72 251 | 94.92 289 | 96.28 81 | 99.69 98 | 93.81 179 | 97.98 259 | 98.09 247 |
|
canonicalmvs | | | 97.23 108 | 97.21 105 | 97.30 130 | 97.65 248 | 94.39 119 | 97.84 60 | 99.05 38 | 97.42 72 | 96.68 189 | 93.85 307 | 97.63 26 | 99.33 232 | 96.29 86 | 98.47 243 | 98.18 245 |
|
plane_prior6 | | | | | | 98.38 155 | 94.37 121 | | | | | | 91.91 217 | | | | |
|
pmmvs-eth3d | | | 96.49 153 | 96.18 158 | 97.42 123 | 98.25 175 | 94.29 122 | 94.77 235 | 98.07 207 | 89.81 269 | 97.97 120 | 98.33 96 | 93.11 179 | 99.08 261 | 95.46 117 | 99.84 41 | 98.89 178 |
|
HQP_MVS | | | 96.66 147 | 96.33 155 | 97.68 99 | 98.70 117 | 94.29 122 | 96.50 128 | 98.75 111 | 96.36 105 | 96.16 217 | 96.77 225 | 91.91 217 | 99.46 188 | 92.59 198 | 99.20 180 | 99.28 119 |
|
plane_prior | | | | | | | 94.29 122 | 95.42 194 | | 94.31 188 | | | | | | 98.93 208 | |
|
test_prior3 | | | 95.91 171 | 95.39 183 | 97.46 119 | 97.79 233 | 94.26 125 | 93.33 290 | 98.42 160 | 94.21 191 | 94.02 277 | 96.25 254 | 93.64 166 | 99.34 229 | 91.90 205 | 98.96 203 | 98.79 191 |
|
test_prior | | | | | 97.46 119 | 97.79 233 | 94.26 125 | | 98.42 160 | | | | | 99.34 229 | | | 98.79 191 |
|
v7n | | | 98.73 13 | 98.99 7 | 97.95 83 | 99.64 12 | 94.20 127 | 98.67 13 | 99.14 20 | 99.08 9 | 99.42 16 | 99.23 29 | 96.53 69 | 99.91 12 | 99.27 4 | 99.93 21 | 99.73 16 |
|
DeepC-MVS_fast | | 94.34 7 | 96.74 139 | 96.51 149 | 97.44 122 | 97.69 243 | 94.15 128 | 96.02 154 | 98.43 157 | 93.17 220 | 97.30 160 | 97.38 192 | 95.48 104 | 99.28 240 | 93.74 181 | 99.34 161 | 98.88 182 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
MCST-MVS | | | 96.24 160 | 95.80 172 | 97.56 105 | 98.75 108 | 94.13 129 | 94.66 236 | 98.17 195 | 90.17 266 | 96.21 215 | 96.10 261 | 95.14 116 | 99.43 196 | 94.13 168 | 98.85 218 | 99.13 138 |
|
test12 | | | | | 97.46 119 | 97.61 251 | 94.07 130 | | 97.78 221 | | 93.57 294 | | 93.31 176 | 99.42 197 | | 98.78 220 | 98.89 178 |
|
test_0402 | | | 97.84 64 | 97.97 52 | 97.47 118 | 99.19 63 | 94.07 130 | 96.71 124 | 98.73 114 | 98.66 22 | 98.56 64 | 98.41 89 | 96.84 55 | 99.69 98 | 94.82 143 | 99.81 44 | 98.64 202 |
|
API-MVS | | | 95.09 205 | 95.01 194 | 95.31 233 | 96.61 292 | 94.02 132 | 96.83 119 | 97.18 252 | 95.60 133 | 95.79 228 | 94.33 302 | 94.54 136 | 98.37 327 | 85.70 305 | 98.52 239 | 93.52 342 |
|
IS-MVSNet | | | 96.93 122 | 96.68 137 | 97.70 96 | 99.25 55 | 94.00 133 | 98.57 18 | 96.74 268 | 98.36 30 | 98.14 100 | 97.98 138 | 88.23 258 | 99.71 81 | 93.10 193 | 99.72 60 | 99.38 97 |
|
DP-MVS Recon | | | 95.55 181 | 95.13 189 | 96.80 154 | 98.51 144 | 93.99 134 | 94.60 238 | 98.69 124 | 90.20 265 | 95.78 229 | 96.21 257 | 92.73 189 | 98.98 274 | 90.58 241 | 98.86 216 | 97.42 278 |
|
Regformer-4 | | | 97.53 90 | 97.47 88 | 97.71 95 | 97.35 267 | 93.91 135 | 95.26 208 | 98.14 199 | 97.97 45 | 98.34 80 | 97.89 148 | 95.49 103 | 99.71 81 | 97.41 58 | 99.42 144 | 99.51 50 |
|
旧先验1 | | | | | | 97.80 228 | 93.87 136 | | 97.75 222 | | | 97.04 207 | 93.57 168 | | | 98.68 230 | 98.72 198 |
|
Regformer-1 | | | 97.27 105 | 97.16 109 | 97.61 103 | 97.21 276 | 93.86 137 | 94.85 231 | 98.04 210 | 97.62 62 | 98.03 114 | 97.50 181 | 95.34 109 | 99.63 123 | 96.52 79 | 99.31 168 | 99.35 106 |
|
UGNet | | | 96.81 136 | 96.56 143 | 97.58 104 | 96.64 291 | 93.84 138 | 97.75 66 | 97.12 255 | 96.47 103 | 93.62 291 | 98.88 59 | 93.22 178 | 99.53 161 | 95.61 112 | 99.69 68 | 99.36 105 |
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 |
VPA-MVSNet | | | 98.27 33 | 98.46 30 | 97.70 96 | 99.06 83 | 93.80 139 | 97.76 65 | 99.00 62 | 98.40 29 | 99.07 36 | 98.98 51 | 96.89 50 | 99.75 55 | 97.19 66 | 99.79 48 | 99.55 45 |
|
LCM-MVSNet-Re | | | 97.33 102 | 97.33 92 | 97.32 129 | 98.13 196 | 93.79 140 | 96.99 110 | 99.65 2 | 96.74 95 | 99.47 13 | 98.93 56 | 96.91 49 | 99.84 28 | 90.11 250 | 99.06 197 | 98.32 230 |
|
EPP-MVSNet | | | 96.84 131 | 96.58 141 | 97.65 101 | 99.18 64 | 93.78 141 | 98.68 12 | 96.34 271 | 97.91 47 | 97.30 160 | 98.06 131 | 88.46 256 | 99.85 24 | 93.85 178 | 99.40 151 | 99.32 108 |
|
NP-MVS | | | | | | 98.14 193 | 93.72 142 | | | | | 95.08 283 | | | | | |
|
GBi-Net | | | 96.99 114 | 96.80 132 | 97.56 105 | 97.96 210 | 93.67 143 | 98.23 35 | 98.66 131 | 95.59 134 | 97.99 116 | 99.19 32 | 89.51 248 | 99.73 65 | 94.60 152 | 99.44 132 | 99.30 112 |
|
test1 | | | 96.99 114 | 96.80 132 | 97.56 105 | 97.96 210 | 93.67 143 | 98.23 35 | 98.66 131 | 95.59 134 | 97.99 116 | 99.19 32 | 89.51 248 | 99.73 65 | 94.60 152 | 99.44 132 | 99.30 112 |
|
FMVSNet1 | | | 97.95 51 | 98.08 47 | 97.56 105 | 99.14 76 | 93.67 143 | 98.23 35 | 98.66 131 | 97.41 79 | 99.00 41 | 99.19 32 | 95.47 105 | 99.73 65 | 95.83 102 | 99.76 51 | 99.30 112 |
|
MVS_111021_HR | | | 96.73 141 | 96.54 146 | 97.27 131 | 98.35 158 | 93.66 146 | 93.42 286 | 98.36 167 | 94.74 171 | 96.58 191 | 96.76 227 | 96.54 68 | 98.99 272 | 94.87 141 | 99.27 175 | 99.15 135 |
|
3Dnovator | | 96.53 2 | 97.61 82 | 97.64 73 | 97.50 113 | 97.74 239 | 93.65 147 | 98.49 23 | 98.88 80 | 96.86 92 | 97.11 168 | 98.55 80 | 95.82 91 | 99.73 65 | 95.94 99 | 99.42 144 | 99.13 138 |
|
CDS-MVSNet | | | 94.88 211 | 94.12 230 | 97.14 137 | 97.64 249 | 93.57 148 | 93.96 267 | 97.06 257 | 90.05 267 | 96.30 210 | 96.55 237 | 86.10 272 | 99.47 183 | 90.10 251 | 99.31 168 | 98.40 220 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
ACMH | | 93.61 9 | 98.44 26 | 98.76 16 | 97.51 110 | 99.43 38 | 93.54 149 | 98.23 35 | 99.05 38 | 97.40 80 | 99.37 19 | 99.08 47 | 98.79 6 | 99.47 183 | 97.74 43 | 99.71 64 | 99.50 51 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
v748 | | | 98.58 20 | 98.89 10 | 97.67 100 | 99.61 15 | 93.53 150 | 98.59 17 | 98.90 76 | 98.97 17 | 99.43 15 | 99.15 41 | 96.53 69 | 99.85 24 | 98.88 11 | 99.91 27 | 99.64 28 |
|
EG-PatchMatch MVS | | | 97.69 77 | 97.79 60 | 97.40 125 | 99.06 83 | 93.52 151 | 95.96 162 | 98.97 69 | 94.55 178 | 98.82 47 | 98.76 64 | 97.31 35 | 99.29 239 | 97.20 65 | 99.44 132 | 99.38 97 |
|
PCF-MVS | | 89.43 18 | 92.12 275 | 90.64 296 | 96.57 169 | 97.80 228 | 93.48 152 | 89.88 339 | 98.45 153 | 74.46 351 | 96.04 220 | 95.68 272 | 90.71 232 | 99.31 234 | 73.73 347 | 99.01 201 | 96.91 295 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
TAMVS | | | 95.49 184 | 94.94 196 | 97.16 135 | 98.31 159 | 93.41 153 | 95.07 219 | 96.82 265 | 91.09 256 | 97.51 148 | 97.82 154 | 89.96 242 | 99.42 197 | 88.42 275 | 99.44 132 | 98.64 202 |
|
TransMVSNet (Re) | | | 98.38 29 | 98.67 19 | 97.51 110 | 99.51 27 | 93.39 154 | 98.20 40 | 98.87 82 | 98.23 36 | 99.48 12 | 99.27 25 | 98.47 9 | 99.55 157 | 96.52 79 | 99.53 106 | 99.60 35 |
|
Baseline_NR-MVSNet | | | 97.72 74 | 97.79 60 | 97.50 113 | 99.56 19 | 93.29 155 | 95.44 189 | 98.86 84 | 98.20 38 | 98.37 77 | 99.24 27 | 94.69 127 | 99.55 157 | 95.98 98 | 99.79 48 | 99.65 25 |
|
VDDNet | | | 96.98 117 | 96.84 128 | 97.41 124 | 99.40 42 | 93.26 156 | 97.94 54 | 95.31 288 | 99.26 6 | 98.39 76 | 99.18 35 | 87.85 264 | 99.62 129 | 95.13 135 | 99.09 192 | 99.35 106 |
|
test222 | | | | | | 98.17 188 | 93.24 157 | 92.74 302 | 97.61 238 | 75.17 350 | 94.65 253 | 96.69 231 | 90.96 230 | | | 98.66 231 | 97.66 270 |
|
FC-MVSNet-test | | | 98.16 37 | 98.37 34 | 97.56 105 | 99.49 31 | 93.10 158 | 98.35 29 | 99.21 11 | 98.43 28 | 98.89 45 | 98.83 60 | 94.30 144 | 99.81 33 | 97.87 36 | 99.91 27 | 99.77 9 |
|
MVP-Stereo | | | 95.69 175 | 95.28 185 | 96.92 149 | 98.15 192 | 93.03 159 | 95.64 182 | 98.20 190 | 90.39 263 | 96.63 190 | 97.73 163 | 91.63 220 | 99.10 259 | 91.84 209 | 97.31 299 | 98.63 204 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
FIs | | | 97.93 55 | 98.07 48 | 97.48 117 | 99.38 44 | 92.95 160 | 98.03 51 | 99.11 23 | 98.04 43 | 98.62 58 | 98.66 72 | 93.75 164 | 99.78 40 | 97.23 62 | 99.84 41 | 99.73 16 |
|
Fast-Effi-MVS+ | | | 95.49 184 | 95.07 191 | 96.75 157 | 97.67 247 | 92.82 161 | 94.22 251 | 98.60 141 | 91.61 251 | 93.42 301 | 92.90 318 | 96.73 60 | 99.70 89 | 92.60 197 | 97.89 267 | 97.74 268 |
|
PMMVS | | | 92.39 268 | 91.08 281 | 96.30 185 | 93.12 347 | 92.81 162 | 90.58 331 | 95.96 277 | 79.17 341 | 91.85 324 | 92.27 326 | 90.29 240 | 98.66 309 | 89.85 254 | 96.68 311 | 97.43 277 |
|
pmmvs4 | | | 94.82 214 | 94.19 228 | 96.70 160 | 97.42 264 | 92.75 163 | 92.09 314 | 96.76 266 | 86.80 298 | 95.73 232 | 97.22 197 | 89.28 251 | 98.89 284 | 93.28 188 | 99.14 185 | 98.46 217 |
|
MVS_0304 | | | 96.22 161 | 95.94 170 | 97.04 143 | 97.07 282 | 92.54 164 | 94.19 253 | 99.04 45 | 95.17 153 | 93.74 286 | 96.92 215 | 91.77 219 | 99.73 65 | 95.76 104 | 99.81 44 | 98.85 187 |
|
CLD-MVS | | | 95.47 187 | 95.07 191 | 96.69 161 | 98.27 166 | 92.53 165 | 91.36 323 | 98.67 129 | 91.22 255 | 95.78 229 | 94.12 305 | 95.65 100 | 98.98 274 | 90.81 232 | 99.72 60 | 98.57 208 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
HQP5-MVS | | | | | | | 92.47 166 | | | | | | | | | | |
|
HQP-MVS | | | 95.17 202 | 94.58 213 | 96.92 149 | 97.85 217 | 92.47 166 | 94.26 245 | 98.43 157 | 93.18 217 | 92.86 309 | 95.08 283 | 90.33 236 | 99.23 247 | 90.51 243 | 98.74 224 | 99.05 156 |
|
SixPastTwentyTwo | | | 97.49 91 | 97.57 81 | 97.26 133 | 99.56 19 | 92.33 168 | 98.28 32 | 96.97 260 | 98.30 34 | 99.45 14 | 99.35 18 | 88.43 257 | 99.89 17 | 98.01 32 | 99.76 51 | 99.54 46 |
|
Regformer-3 | | | 97.25 107 | 97.29 94 | 97.11 138 | 97.35 267 | 92.32 169 | 95.26 208 | 97.62 237 | 97.67 60 | 98.17 96 | 97.89 148 | 95.05 117 | 99.56 153 | 97.16 67 | 99.42 144 | 99.46 67 |
|
EPNet | | | 93.72 245 | 92.62 257 | 97.03 145 | 87.61 359 | 92.25 170 | 96.27 140 | 91.28 324 | 96.74 95 | 87.65 347 | 97.39 190 | 85.00 279 | 99.64 120 | 92.14 203 | 99.48 123 | 99.20 127 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
tfpnnormal | | | 97.72 74 | 97.97 52 | 96.94 148 | 99.26 52 | 92.23 171 | 97.83 61 | 98.45 153 | 98.25 35 | 99.13 33 | 98.66 72 | 96.65 63 | 99.69 98 | 93.92 176 | 99.62 80 | 98.91 174 |
|
XXY-MVS | | | 97.54 88 | 97.70 66 | 97.07 141 | 99.46 33 | 92.21 172 | 97.22 96 | 99.00 62 | 94.93 165 | 98.58 63 | 98.92 57 | 97.31 35 | 99.41 208 | 94.44 155 | 99.43 141 | 99.59 36 |
|
ab-mvs | | | 96.59 149 | 96.59 140 | 96.60 164 | 98.64 123 | 92.21 172 | 98.35 29 | 97.67 228 | 94.45 179 | 96.99 174 | 98.79 61 | 94.96 121 | 99.49 178 | 90.39 247 | 99.07 195 | 98.08 248 |
|
WR-MVS | | | 96.90 126 | 96.81 131 | 97.16 135 | 98.56 136 | 92.20 174 | 94.33 244 | 98.12 201 | 97.34 81 | 98.20 94 | 97.33 194 | 92.81 186 | 99.75 55 | 94.79 146 | 99.81 44 | 99.54 46 |
|
Effi-MVS+ | | | 96.19 163 | 96.01 164 | 96.71 159 | 97.43 263 | 92.19 175 | 96.12 150 | 99.10 25 | 95.45 139 | 93.33 304 | 94.71 291 | 97.23 41 | 99.56 153 | 93.21 191 | 97.54 289 | 98.37 223 |
|
原ACMM1 | | | | | 96.58 167 | 98.16 190 | 92.12 176 | | 98.15 198 | 85.90 306 | 93.49 296 | 96.43 246 | 92.47 201 | 99.38 222 | 87.66 284 | 98.62 234 | 98.23 239 |
|
lessismore_v0 | | | | | 97.05 142 | 99.36 46 | 92.12 176 | | 84.07 355 | | 98.77 52 | 98.98 51 | 85.36 276 | 99.74 60 | 97.34 60 | 99.37 153 | 99.30 112 |
|
EI-MVSNet-Vis-set | | | 97.32 103 | 97.39 90 | 97.11 138 | 97.36 266 | 92.08 178 | 95.34 201 | 97.65 232 | 97.74 52 | 98.29 88 | 98.11 125 | 95.05 117 | 99.68 104 | 97.50 54 | 99.50 113 | 99.56 42 |
|
VNet | | | 96.84 131 | 96.83 129 | 96.88 152 | 98.06 199 | 92.02 179 | 96.35 137 | 97.57 239 | 97.70 57 | 97.88 133 | 97.80 156 | 92.40 202 | 99.54 159 | 94.73 150 | 98.96 203 | 99.08 151 |
|
EI-MVSNet-UG-set | | | 97.32 103 | 97.40 89 | 97.09 140 | 97.34 270 | 92.01 180 | 95.33 202 | 97.65 232 | 97.74 52 | 98.30 87 | 98.14 121 | 95.04 119 | 99.69 98 | 97.55 50 | 99.52 110 | 99.58 37 |
|
OpenMVS | | 94.22 8 | 95.48 186 | 95.20 187 | 96.32 183 | 97.16 279 | 91.96 181 | 97.74 68 | 98.84 88 | 87.26 291 | 94.36 267 | 98.01 135 | 93.95 156 | 99.67 111 | 90.70 238 | 98.75 223 | 97.35 285 |
|
FMVSNet2 | | | 96.72 142 | 96.67 138 | 96.87 153 | 97.96 210 | 91.88 182 | 97.15 97 | 98.06 208 | 95.59 134 | 98.50 69 | 98.62 75 | 89.51 248 | 99.65 117 | 94.99 140 | 99.60 88 | 99.07 153 |
|
MSDG | | | 95.33 195 | 95.13 189 | 95.94 214 | 97.40 265 | 91.85 183 | 91.02 326 | 98.37 166 | 95.30 144 | 96.31 209 | 95.99 262 | 94.51 138 | 98.38 325 | 89.59 257 | 97.65 285 | 97.60 273 |
|
QAPM | | | 95.88 173 | 95.57 178 | 96.80 154 | 97.90 215 | 91.84 184 | 98.18 42 | 98.73 114 | 88.41 279 | 96.42 199 | 98.13 122 | 94.73 124 | 99.75 55 | 88.72 270 | 98.94 207 | 98.81 189 |
|
HyFIR lowres test | | | 93.72 245 | 92.65 256 | 96.91 151 | 98.93 95 | 91.81 185 | 91.23 325 | 98.52 147 | 82.69 326 | 96.46 198 | 96.52 241 | 80.38 292 | 99.90 13 | 90.36 248 | 98.79 219 | 99.03 157 |
|
test20.03 | | | 96.58 150 | 96.61 139 | 96.48 174 | 98.49 146 | 91.72 186 | 95.68 177 | 97.69 227 | 96.81 93 | 98.27 89 | 97.92 146 | 94.18 150 | 98.71 302 | 90.78 234 | 99.66 76 | 99.00 159 |
|
ambc | | | | | 96.56 170 | 98.23 177 | 91.68 187 | 97.88 58 | 98.13 200 | | 98.42 75 | 98.56 79 | 94.22 148 | 99.04 265 | 94.05 172 | 99.35 159 | 98.95 165 |
|
K. test v3 | | | 96.44 156 | 96.28 156 | 96.95 147 | 99.41 41 | 91.53 188 | 97.65 72 | 90.31 335 | 98.89 18 | 98.93 44 | 99.36 16 | 84.57 282 | 99.92 4 | 97.81 38 | 99.56 98 | 99.39 95 |
|
UnsupCasMVSNet_eth | | | 95.91 171 | 95.73 174 | 96.44 176 | 98.48 148 | 91.52 189 | 95.31 204 | 98.45 153 | 95.76 128 | 97.48 153 | 97.54 176 | 89.53 247 | 98.69 304 | 94.43 156 | 94.61 331 | 99.13 138 |
|
LFMVS | | | 95.32 196 | 94.88 200 | 96.62 163 | 98.03 201 | 91.47 190 | 97.65 72 | 90.72 330 | 99.11 8 | 97.89 131 | 98.31 98 | 79.20 295 | 99.48 181 | 93.91 177 | 99.12 190 | 98.93 171 |
|
PAPM_NR | | | 94.61 222 | 94.17 229 | 95.96 210 | 98.36 157 | 91.23 191 | 95.93 165 | 97.95 211 | 92.98 225 | 93.42 301 | 94.43 301 | 90.53 233 | 98.38 325 | 87.60 291 | 96.29 316 | 98.27 236 |
|
OpenMVS_ROB | | 91.80 14 | 93.64 248 | 93.05 247 | 95.42 230 | 97.31 273 | 91.21 192 | 95.08 218 | 96.68 270 | 81.56 330 | 96.88 185 | 96.41 247 | 90.44 235 | 99.25 244 | 85.39 310 | 97.67 283 | 95.80 322 |
|
V42 | | | 97.04 112 | 97.16 109 | 96.68 162 | 98.59 132 | 91.05 193 | 96.33 138 | 98.36 167 | 94.60 174 | 97.99 116 | 98.30 101 | 93.32 175 | 99.62 129 | 97.40 59 | 99.53 106 | 99.38 97 |
|
JIA-IIPM | | | 91.79 284 | 90.69 295 | 95.11 238 | 93.80 341 | 90.98 194 | 94.16 256 | 91.78 321 | 96.38 104 | 90.30 336 | 99.30 23 | 72.02 334 | 98.90 281 | 88.28 277 | 90.17 343 | 95.45 328 |
|
114514_t | | | 93.96 241 | 93.22 246 | 96.19 194 | 99.06 83 | 90.97 195 | 95.99 156 | 98.94 73 | 73.88 352 | 93.43 300 | 96.93 214 | 92.38 203 | 99.37 225 | 89.09 264 | 99.28 173 | 98.25 238 |
|
testing_2 | | | 97.43 93 | 97.71 65 | 96.60 164 | 98.91 98 | 90.85 196 | 96.01 155 | 98.54 145 | 94.78 170 | 98.78 49 | 98.96 53 | 96.35 78 | 99.54 159 | 97.25 61 | 99.82 43 | 99.40 92 |
|
1112_ss | | | 94.12 236 | 93.42 241 | 96.23 189 | 98.59 132 | 90.85 196 | 94.24 249 | 98.85 85 | 85.49 309 | 92.97 307 | 94.94 287 | 86.01 273 | 99.64 120 | 91.78 210 | 97.92 264 | 98.20 242 |
|
CANet | | | 95.86 174 | 95.65 176 | 96.49 173 | 96.41 298 | 90.82 198 | 94.36 243 | 98.41 162 | 94.94 163 | 92.62 316 | 96.73 228 | 92.68 190 | 99.71 81 | 95.12 136 | 99.60 88 | 98.94 167 |
|
Patchmtry | | | 95.03 207 | 94.59 212 | 96.33 182 | 94.83 327 | 90.82 198 | 96.38 135 | 97.20 250 | 96.59 98 | 97.49 150 | 98.57 77 | 77.67 301 | 99.38 222 | 92.95 196 | 99.62 80 | 98.80 190 |
|
FMVSNet5 | | | 93.39 253 | 92.35 259 | 96.50 172 | 95.83 313 | 90.81 200 | 97.31 90 | 98.27 182 | 92.74 233 | 96.27 211 | 98.28 103 | 62.23 353 | 99.67 111 | 90.86 230 | 99.36 156 | 99.03 157 |
|
PVSNet_Blended_VisFu | | | 95.95 170 | 95.80 172 | 96.42 177 | 99.28 51 | 90.62 201 | 95.31 204 | 99.08 30 | 88.40 280 | 96.97 180 | 98.17 117 | 92.11 207 | 99.78 40 | 93.64 183 | 99.21 179 | 98.86 185 |
|
testdata | | | | | 95.70 223 | 98.16 190 | 90.58 202 | | 97.72 225 | 80.38 336 | 95.62 234 | 97.02 208 | 92.06 211 | 98.98 274 | 89.06 266 | 98.52 239 | 97.54 275 |
|
VPNet | | | 97.26 106 | 97.49 87 | 96.59 166 | 99.47 32 | 90.58 202 | 96.27 140 | 98.53 146 | 97.77 50 | 98.46 72 | 98.41 89 | 94.59 133 | 99.68 104 | 94.61 151 | 99.29 172 | 99.52 49 |
|
MSLP-MVS++ | | | 96.42 158 | 96.71 136 | 95.57 225 | 97.82 223 | 90.56 204 | 95.71 173 | 98.84 88 | 94.72 172 | 96.71 188 | 97.39 190 | 94.91 122 | 98.10 336 | 95.28 124 | 99.02 199 | 98.05 253 |
|
UnsupCasMVSNet_bld | | | 94.72 217 | 94.26 224 | 96.08 202 | 98.62 128 | 90.54 205 | 93.38 288 | 98.05 209 | 90.30 264 | 97.02 172 | 96.80 223 | 89.54 245 | 99.16 253 | 88.44 274 | 96.18 317 | 98.56 209 |
|
v13 | | | 98.02 45 | 98.52 28 | 96.51 171 | 99.02 89 | 90.14 206 | 98.07 47 | 99.09 29 | 98.10 41 | 99.13 33 | 99.35 18 | 94.84 123 | 99.74 60 | 99.12 5 | 99.98 3 | 99.65 25 |
|
FMVSNet3 | | | 95.26 200 | 94.94 196 | 96.22 193 | 96.53 294 | 90.06 207 | 95.99 156 | 97.66 230 | 94.11 195 | 97.99 116 | 97.91 147 | 80.22 293 | 99.63 123 | 94.60 152 | 99.44 132 | 98.96 164 |
|
CHOSEN 1792x2688 | | | 94.10 237 | 93.41 242 | 96.18 195 | 99.16 65 | 90.04 208 | 92.15 311 | 98.68 126 | 79.90 338 | 96.22 214 | 97.83 151 | 87.92 263 | 99.42 197 | 89.18 263 | 99.65 77 | 99.08 151 |
|
DELS-MVS | | | 96.17 164 | 96.23 157 | 95.99 208 | 97.55 255 | 90.04 208 | 92.38 309 | 98.52 147 | 94.13 194 | 96.55 196 | 97.06 205 | 94.99 120 | 99.58 147 | 95.62 111 | 99.28 173 | 98.37 223 |
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 |
v12 | | | 97.97 48 | 98.47 29 | 96.46 175 | 98.98 93 | 90.01 210 | 97.97 52 | 99.08 30 | 98.00 44 | 99.11 35 | 99.34 20 | 94.70 126 | 99.73 65 | 99.07 6 | 99.98 3 | 99.64 28 |
|
sss | | | 94.22 230 | 93.72 237 | 95.74 220 | 97.71 242 | 89.95 211 | 93.84 271 | 96.98 259 | 88.38 282 | 93.75 285 | 95.74 270 | 87.94 260 | 98.89 284 | 91.02 225 | 98.10 256 | 98.37 223 |
|
V9 | | | 97.90 59 | 98.40 33 | 96.40 179 | 98.93 95 | 89.86 212 | 97.86 59 | 99.07 34 | 97.88 48 | 99.05 37 | 99.30 23 | 94.53 137 | 99.72 71 | 99.01 8 | 99.98 3 | 99.63 30 |
|
V14 | | | 97.83 65 | 98.33 37 | 96.35 180 | 98.88 101 | 89.72 213 | 97.75 66 | 99.05 38 | 97.74 52 | 99.01 39 | 99.27 25 | 94.35 142 | 99.71 81 | 98.95 9 | 99.97 8 | 99.62 32 |
|
CANet_DTU | | | 94.65 220 | 94.21 227 | 95.96 210 | 95.90 311 | 89.68 214 | 93.92 268 | 97.83 219 | 93.19 216 | 90.12 337 | 95.64 274 | 88.52 255 | 99.57 152 | 93.27 189 | 99.47 125 | 98.62 205 |
|
v7 | | | 96.93 122 | 97.17 108 | 96.23 189 | 98.59 132 | 89.64 215 | 95.96 162 | 98.66 131 | 94.41 182 | 97.87 138 | 98.38 92 | 93.47 170 | 99.64 120 | 97.93 34 | 99.24 177 | 99.43 85 |
|
v10 | | | 97.55 86 | 97.97 52 | 96.31 184 | 98.60 130 | 89.64 215 | 97.44 87 | 99.02 51 | 96.60 97 | 98.72 55 | 99.16 40 | 93.48 169 | 99.72 71 | 98.76 15 | 99.92 24 | 99.58 37 |
|
ANet_high | | | 98.31 32 | 98.94 8 | 96.41 178 | 99.33 48 | 89.64 215 | 97.92 56 | 99.56 4 | 99.27 5 | 99.66 8 | 99.50 6 | 97.67 25 | 99.83 30 | 97.55 50 | 99.98 3 | 99.77 9 |
|
v16 | | | 97.69 77 | 98.16 44 | 96.29 187 | 98.75 108 | 89.60 218 | 97.62 75 | 99.01 60 | 97.53 68 | 98.69 57 | 99.18 35 | 94.05 154 | 99.68 104 | 98.73 17 | 99.88 34 | 99.58 37 |
|
Test4 | | | 95.39 192 | 95.24 186 | 95.82 218 | 98.07 198 | 89.60 218 | 94.40 242 | 98.49 150 | 91.39 254 | 97.40 158 | 96.32 252 | 87.32 268 | 99.41 208 | 95.09 138 | 98.71 229 | 98.44 218 |
|
v17 | | | 97.70 76 | 98.17 43 | 96.28 188 | 98.77 107 | 89.59 220 | 97.62 75 | 99.01 60 | 97.54 66 | 98.72 55 | 99.18 35 | 94.06 153 | 99.68 104 | 98.74 16 | 99.92 24 | 99.58 37 |
|
v15 | | | 97.77 71 | 98.26 41 | 96.30 185 | 98.81 103 | 89.59 220 | 97.62 75 | 99.04 45 | 97.59 63 | 98.97 43 | 99.24 27 | 94.19 149 | 99.70 89 | 98.88 11 | 99.97 8 | 99.61 34 |
|
testmv | | | 95.51 182 | 95.33 184 | 96.05 203 | 98.23 177 | 89.51 222 | 93.50 284 | 98.63 138 | 94.25 189 | 98.22 92 | 97.73 163 | 92.51 199 | 99.47 183 | 85.22 311 | 99.72 60 | 99.17 131 |
|
v18 | | | 97.60 83 | 98.06 49 | 96.23 189 | 98.68 122 | 89.46 223 | 97.48 86 | 98.98 67 | 97.33 82 | 98.60 61 | 99.13 43 | 93.86 157 | 99.67 111 | 98.62 21 | 99.87 37 | 99.56 42 |
|
v1neww | | | 96.97 118 | 97.24 99 | 96.15 197 | 98.70 117 | 89.44 224 | 95.97 158 | 98.33 172 | 95.25 146 | 97.88 133 | 98.15 118 | 93.83 160 | 99.61 135 | 97.50 54 | 99.50 113 | 99.41 89 |
|
v7new | | | 96.97 118 | 97.24 99 | 96.15 197 | 98.70 117 | 89.44 224 | 95.97 158 | 98.33 172 | 95.25 146 | 97.88 133 | 98.15 118 | 93.83 160 | 99.61 135 | 97.50 54 | 99.50 113 | 99.41 89 |
|
v8 | | | 97.60 83 | 98.06 49 | 96.23 189 | 98.71 115 | 89.44 224 | 97.43 88 | 98.82 100 | 97.29 84 | 98.74 53 | 99.10 45 | 93.86 157 | 99.68 104 | 98.61 22 | 99.94 19 | 99.56 42 |
|
v6 | | | 96.97 118 | 97.24 99 | 96.15 197 | 98.71 115 | 89.44 224 | 95.97 158 | 98.33 172 | 95.25 146 | 97.89 131 | 98.15 118 | 93.86 157 | 99.61 135 | 97.51 53 | 99.50 113 | 99.42 87 |
|
Anonymous20231206 | | | 95.27 199 | 95.06 193 | 95.88 216 | 98.72 112 | 89.37 228 | 95.70 174 | 97.85 216 | 88.00 287 | 96.98 175 | 97.62 170 | 91.95 213 | 99.34 229 | 89.21 262 | 99.53 106 | 98.94 167 |
|
v1192 | | | 96.83 134 | 97.06 118 | 96.15 197 | 98.28 164 | 89.29 229 | 95.36 199 | 98.77 107 | 93.73 207 | 98.11 102 | 98.34 95 | 93.02 184 | 99.67 111 | 98.35 27 | 99.58 93 | 99.50 51 |
|
v1144 | | | 96.84 131 | 97.08 116 | 96.13 201 | 98.42 154 | 89.28 230 | 95.41 196 | 98.67 129 | 94.21 191 | 97.97 120 | 98.31 98 | 93.06 180 | 99.65 117 | 98.06 31 | 99.62 80 | 99.45 72 |
|
Vis-MVSNet (Re-imp) | | | 95.11 203 | 94.85 201 | 95.87 217 | 99.12 77 | 89.17 231 | 97.54 84 | 94.92 290 | 96.50 100 | 96.58 191 | 97.27 196 | 83.64 283 | 99.48 181 | 88.42 275 | 99.67 74 | 98.97 163 |
|
v11 | | | 97.82 68 | 98.36 35 | 96.17 196 | 98.93 95 | 89.16 232 | 97.79 62 | 99.08 30 | 97.64 61 | 99.19 30 | 99.32 22 | 94.28 145 | 99.72 71 | 99.07 6 | 99.97 8 | 99.63 30 |
|
new_pmnet | | | 92.34 270 | 91.69 271 | 94.32 267 | 96.23 302 | 89.16 232 | 92.27 310 | 92.88 311 | 84.39 322 | 95.29 239 | 96.35 251 | 85.66 274 | 96.74 349 | 84.53 316 | 97.56 288 | 97.05 289 |
|
test_normal | | | 95.51 182 | 95.46 181 | 95.68 224 | 97.97 209 | 89.12 234 | 93.73 275 | 95.86 280 | 91.98 244 | 97.17 165 | 96.94 212 | 91.55 221 | 99.42 197 | 95.21 127 | 98.73 227 | 98.51 213 |
|
v1141 | | | 96.86 128 | 97.14 111 | 96.04 204 | 98.55 137 | 89.06 235 | 95.44 189 | 98.33 172 | 95.14 156 | 97.93 126 | 98.19 112 | 93.36 173 | 99.62 129 | 97.61 46 | 99.69 68 | 99.44 81 |
|
divwei89l23v2f112 | | | 96.86 128 | 97.14 111 | 96.04 204 | 98.54 140 | 89.06 235 | 95.44 189 | 98.33 172 | 95.14 156 | 97.93 126 | 98.19 112 | 93.36 173 | 99.61 135 | 97.61 46 | 99.68 72 | 99.44 81 |
|
v1 | | | 96.86 128 | 97.14 111 | 96.04 204 | 98.55 137 | 89.06 235 | 95.44 189 | 98.33 172 | 95.14 156 | 97.94 123 | 98.18 116 | 93.39 172 | 99.61 135 | 97.61 46 | 99.69 68 | 99.44 81 |
|
v144192 | | | 96.69 145 | 96.90 126 | 96.03 207 | 98.25 175 | 88.92 238 | 95.49 187 | 98.77 107 | 93.05 223 | 98.09 106 | 98.29 102 | 92.51 199 | 99.70 89 | 98.11 30 | 99.56 98 | 99.47 65 |
|
Patchmatch-RL test | | | 94.66 219 | 94.49 216 | 95.19 236 | 98.54 140 | 88.91 239 | 92.57 304 | 98.74 113 | 91.46 253 | 98.32 83 | 97.75 160 | 77.31 306 | 98.81 294 | 96.06 91 | 99.61 85 | 97.85 263 |
|
HY-MVS | | 91.43 15 | 92.58 262 | 91.81 270 | 94.90 247 | 96.49 296 | 88.87 240 | 97.31 90 | 94.62 292 | 85.92 305 | 90.50 334 | 96.84 219 | 85.05 278 | 99.40 211 | 83.77 322 | 95.78 322 | 96.43 314 |
|
Test_1112_low_res | | | 93.53 251 | 92.86 251 | 95.54 227 | 98.60 130 | 88.86 241 | 92.75 300 | 98.69 124 | 82.66 327 | 92.65 314 | 96.92 215 | 84.75 280 | 99.56 153 | 90.94 228 | 97.76 268 | 98.19 243 |
|
DI_MVS_plusplus_test | | | 95.46 188 | 95.43 182 | 95.55 226 | 98.05 200 | 88.84 242 | 94.18 254 | 95.75 282 | 91.92 247 | 97.32 159 | 96.94 212 | 91.44 223 | 99.39 217 | 94.81 144 | 98.48 242 | 98.43 219 |
|
PAPR | | | 92.22 272 | 91.27 277 | 95.07 241 | 95.73 316 | 88.81 243 | 91.97 315 | 97.87 215 | 85.80 307 | 90.91 328 | 92.73 323 | 91.16 226 | 98.33 329 | 79.48 335 | 95.76 323 | 98.08 248 |
|
v1921920 | | | 96.72 142 | 96.96 123 | 95.99 208 | 98.21 179 | 88.79 244 | 95.42 194 | 98.79 103 | 93.22 215 | 98.19 95 | 98.26 106 | 92.68 190 | 99.70 89 | 98.34 28 | 99.55 102 | 99.49 59 |
|
v2v482 | | | 96.78 138 | 97.06 118 | 95.95 212 | 98.57 135 | 88.77 245 | 95.36 199 | 98.26 184 | 95.18 152 | 97.85 140 | 98.23 107 | 92.58 194 | 99.63 123 | 97.80 39 | 99.69 68 | 99.45 72 |
|
MDA-MVSNet-bldmvs | | | 95.69 175 | 95.67 175 | 95.74 220 | 98.48 148 | 88.76 246 | 92.84 297 | 97.25 248 | 96.00 118 | 97.59 145 | 97.95 142 | 91.38 225 | 99.46 188 | 93.16 192 | 96.35 315 | 98.99 162 |
|
v1240 | | | 96.74 139 | 97.02 120 | 95.91 215 | 98.18 186 | 88.52 247 | 95.39 197 | 98.88 80 | 93.15 221 | 98.46 72 | 98.40 91 | 92.80 187 | 99.71 81 | 98.45 26 | 99.49 120 | 99.49 59 |
|
xiu_mvs_v1_base_debu | | | 95.62 178 | 95.96 167 | 94.60 258 | 98.01 204 | 88.42 248 | 93.99 264 | 98.21 187 | 92.98 225 | 95.91 223 | 94.53 293 | 96.39 75 | 99.72 71 | 95.43 120 | 98.19 252 | 95.64 324 |
|
xiu_mvs_v1_base | | | 95.62 178 | 95.96 167 | 94.60 258 | 98.01 204 | 88.42 248 | 93.99 264 | 98.21 187 | 92.98 225 | 95.91 223 | 94.53 293 | 96.39 75 | 99.72 71 | 95.43 120 | 98.19 252 | 95.64 324 |
|
xiu_mvs_v1_base_debi | | | 95.62 178 | 95.96 167 | 94.60 258 | 98.01 204 | 88.42 248 | 93.99 264 | 98.21 187 | 92.98 225 | 95.91 223 | 94.53 293 | 96.39 75 | 99.72 71 | 95.43 120 | 98.19 252 | 95.64 324 |
|
pmmvs5 | | | 94.63 221 | 94.34 223 | 95.50 228 | 97.63 250 | 88.34 251 | 94.02 262 | 97.13 254 | 87.15 294 | 95.22 241 | 97.15 200 | 87.50 265 | 99.27 241 | 93.99 174 | 99.26 176 | 98.88 182 |
|
MIMVSNet | | | 93.42 252 | 92.86 251 | 95.10 239 | 98.17 188 | 88.19 252 | 98.13 44 | 93.69 299 | 92.07 241 | 95.04 245 | 98.21 111 | 80.95 290 | 99.03 268 | 81.42 331 | 98.06 257 | 98.07 250 |
|
CR-MVSNet | | | 93.29 255 | 92.79 253 | 94.78 251 | 95.44 320 | 88.15 253 | 96.18 147 | 97.20 250 | 84.94 317 | 94.10 273 | 98.57 77 | 77.67 301 | 99.39 217 | 95.17 130 | 95.81 319 | 96.81 299 |
|
RPMNet | | | 94.22 230 | 94.03 233 | 94.78 251 | 95.44 320 | 88.15 253 | 96.18 147 | 93.73 298 | 97.43 71 | 94.10 273 | 98.49 84 | 79.40 294 | 99.39 217 | 95.69 105 | 95.81 319 | 96.81 299 |
|
EI-MVSNet | | | 96.63 148 | 96.93 124 | 95.74 220 | 97.26 274 | 88.13 255 | 95.29 206 | 97.65 232 | 96.99 85 | 97.94 123 | 98.19 112 | 92.55 195 | 99.58 147 | 96.91 73 | 99.56 98 | 99.50 51 |
|
IterMVS-LS | | | 96.92 124 | 97.29 94 | 95.79 219 | 98.51 144 | 88.13 255 | 95.10 214 | 98.66 131 | 96.99 85 | 98.46 72 | 98.68 71 | 92.55 195 | 99.74 60 | 96.91 73 | 99.79 48 | 99.50 51 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
conf0.01 | | | 91.90 279 | 90.98 284 | 94.67 254 | 98.27 166 | 88.03 257 | 96.98 111 | 88.58 344 | 93.90 199 | 94.64 254 | 91.45 332 | 69.62 341 | 99.52 164 | 87.62 285 | 97.74 269 | 96.46 310 |
|
conf0.002 | | | 91.90 279 | 90.98 284 | 94.67 254 | 98.27 166 | 88.03 257 | 96.98 111 | 88.58 344 | 93.90 199 | 94.64 254 | 91.45 332 | 69.62 341 | 99.52 164 | 87.62 285 | 97.74 269 | 96.46 310 |
|
thresconf0.02 | | | 91.72 286 | 90.98 284 | 93.97 272 | 98.27 166 | 88.03 257 | 96.98 111 | 88.58 344 | 93.90 199 | 94.64 254 | 91.45 332 | 69.62 341 | 99.52 164 | 87.62 285 | 97.74 269 | 94.35 336 |
|
tfpn_n400 | | | 91.72 286 | 90.98 284 | 93.97 272 | 98.27 166 | 88.03 257 | 96.98 111 | 88.58 344 | 93.90 199 | 94.64 254 | 91.45 332 | 69.62 341 | 99.52 164 | 87.62 285 | 97.74 269 | 94.35 336 |
|
tfpnconf | | | 91.72 286 | 90.98 284 | 93.97 272 | 98.27 166 | 88.03 257 | 96.98 111 | 88.58 344 | 93.90 199 | 94.64 254 | 91.45 332 | 69.62 341 | 99.52 164 | 87.62 285 | 97.74 269 | 94.35 336 |
|
tfpnview11 | | | 91.72 286 | 90.98 284 | 93.97 272 | 98.27 166 | 88.03 257 | 96.98 111 | 88.58 344 | 93.90 199 | 94.64 254 | 91.45 332 | 69.62 341 | 99.52 164 | 87.62 285 | 97.74 269 | 94.35 336 |
|
diffmvs | | | 95.00 209 | 95.00 195 | 95.01 243 | 96.53 294 | 87.96 263 | 95.73 171 | 98.32 181 | 90.67 261 | 91.89 323 | 97.43 185 | 92.07 210 | 98.90 281 | 95.44 118 | 96.88 304 | 98.16 246 |
|
TinyColmap | | | 96.00 169 | 96.34 154 | 94.96 244 | 97.90 215 | 87.91 264 | 94.13 259 | 98.49 150 | 94.41 182 | 98.16 97 | 97.76 157 | 96.29 80 | 98.68 307 | 90.52 242 | 99.42 144 | 98.30 233 |
|
WTY-MVS | | | 93.55 250 | 93.00 249 | 95.19 236 | 97.81 224 | 87.86 265 | 93.89 269 | 96.00 275 | 89.02 273 | 94.07 275 | 95.44 279 | 86.27 271 | 99.33 232 | 87.69 283 | 96.82 306 | 98.39 222 |
|
jason | | | 94.39 227 | 94.04 232 | 95.41 232 | 98.29 161 | 87.85 266 | 92.74 302 | 96.75 267 | 85.38 314 | 95.29 239 | 96.15 258 | 88.21 259 | 99.65 117 | 94.24 166 | 99.34 161 | 98.74 196 |
jason: jason. |
MVSFormer | | | 96.14 165 | 96.36 153 | 95.49 229 | 97.68 244 | 87.81 267 | 98.67 13 | 99.02 51 | 96.50 100 | 94.48 265 | 96.15 258 | 86.90 269 | 99.92 4 | 98.73 17 | 99.13 187 | 98.74 196 |
|
lupinMVS | | | 93.77 243 | 93.28 243 | 95.24 235 | 97.68 244 | 87.81 267 | 92.12 312 | 96.05 274 | 84.52 319 | 94.48 265 | 95.06 285 | 86.90 269 | 99.63 123 | 93.62 184 | 99.13 187 | 98.27 236 |
|
testgi | | | 96.07 166 | 96.50 150 | 94.80 250 | 99.26 52 | 87.69 269 | 95.96 162 | 98.58 144 | 95.08 160 | 98.02 115 | 96.25 254 | 97.92 18 | 97.60 342 | 88.68 272 | 98.74 224 | 99.11 146 |
|
v148 | | | 96.58 150 | 96.97 121 | 95.42 230 | 98.63 127 | 87.57 270 | 95.09 216 | 97.90 213 | 95.91 122 | 98.24 91 | 97.96 139 | 93.42 171 | 99.39 217 | 96.04 93 | 99.52 110 | 99.29 118 |
|
BH-untuned | | | 94.69 218 | 94.75 206 | 94.52 263 | 97.95 214 | 87.53 271 | 94.07 261 | 97.01 258 | 93.99 196 | 97.10 169 | 95.65 273 | 92.65 192 | 98.95 279 | 87.60 291 | 96.74 309 | 97.09 287 |
|
no-one | | | 94.84 212 | 94.76 205 | 95.09 240 | 98.29 161 | 87.49 272 | 91.82 317 | 97.49 240 | 88.21 283 | 97.84 141 | 98.75 65 | 91.51 222 | 99.27 241 | 88.96 267 | 99.99 2 | 98.52 212 |
|
Patchmatch-test | | | 93.60 249 | 93.25 245 | 94.63 256 | 96.14 307 | 87.47 273 | 96.04 153 | 94.50 294 | 93.57 210 | 96.47 197 | 96.97 210 | 76.50 309 | 98.61 310 | 90.67 239 | 98.41 245 | 97.81 266 |
|
BH-RMVSNet | | | 94.56 224 | 94.44 221 | 94.91 245 | 97.57 252 | 87.44 274 | 93.78 274 | 96.26 272 | 93.69 209 | 96.41 200 | 96.50 242 | 92.10 208 | 99.00 271 | 85.96 303 | 97.71 279 | 98.31 231 |
|
PVSNet_BlendedMVS | | | 95.02 208 | 94.93 198 | 95.27 234 | 97.79 233 | 87.40 275 | 94.14 258 | 98.68 126 | 88.94 275 | 94.51 263 | 98.01 135 | 93.04 181 | 99.30 236 | 89.77 255 | 99.49 120 | 99.11 146 |
|
PVSNet_Blended | | | 93.96 241 | 93.65 238 | 94.91 245 | 97.79 233 | 87.40 275 | 91.43 322 | 98.68 126 | 84.50 320 | 94.51 263 | 94.48 296 | 93.04 181 | 99.30 236 | 89.77 255 | 98.61 235 | 98.02 258 |
|
PatchT | | | 93.75 244 | 93.57 240 | 94.29 269 | 95.05 325 | 87.32 277 | 96.05 152 | 92.98 309 | 97.54 66 | 94.25 268 | 98.72 67 | 75.79 314 | 99.24 245 | 95.92 100 | 95.81 319 | 96.32 315 |
|
GA-MVS | | | 92.83 260 | 92.15 262 | 94.87 248 | 96.97 284 | 87.27 278 | 90.03 335 | 96.12 273 | 91.83 249 | 94.05 276 | 94.57 292 | 76.01 313 | 98.97 278 | 92.46 200 | 97.34 298 | 98.36 228 |
|
tfpn_ndepth | | | 90.98 297 | 90.24 302 | 93.20 297 | 97.72 241 | 87.18 279 | 96.52 127 | 88.20 350 | 92.63 234 | 93.69 289 | 90.70 345 | 68.22 349 | 99.42 197 | 86.98 297 | 97.47 294 | 93.00 346 |
|
tfpn1000 | | | 91.88 282 | 91.20 280 | 93.89 280 | 97.96 210 | 87.13 280 | 97.13 100 | 88.16 351 | 94.41 182 | 94.87 249 | 92.77 320 | 68.34 348 | 99.47 183 | 89.24 261 | 97.95 260 | 95.06 330 |
|
MS-PatchMatch | | | 94.83 213 | 94.91 199 | 94.57 261 | 96.81 290 | 87.10 281 | 94.23 250 | 97.34 246 | 88.74 277 | 97.14 166 | 97.11 203 | 91.94 214 | 98.23 332 | 92.99 195 | 97.92 264 | 98.37 223 |
|
MVS | | | 90.02 303 | 89.20 310 | 92.47 309 | 94.71 328 | 86.90 282 | 95.86 167 | 96.74 268 | 64.72 354 | 90.62 330 | 92.77 320 | 92.54 197 | 98.39 323 | 79.30 336 | 95.56 326 | 92.12 347 |
|
test0.0.03 1 | | | 90.11 302 | 89.21 309 | 92.83 304 | 93.89 340 | 86.87 283 | 91.74 318 | 88.74 343 | 92.02 242 | 94.71 252 | 91.14 341 | 73.92 319 | 94.48 353 | 83.75 323 | 92.94 335 | 97.16 286 |
|
test1235678 | | | 92.95 258 | 92.40 258 | 94.61 257 | 96.95 285 | 86.87 283 | 90.75 328 | 97.75 222 | 91.00 258 | 96.33 203 | 95.38 280 | 85.21 277 | 98.92 280 | 79.00 337 | 99.20 180 | 98.03 256 |
|
TR-MVS | | | 92.54 267 | 92.20 261 | 93.57 286 | 96.49 296 | 86.66 285 | 93.51 283 | 94.73 291 | 89.96 268 | 94.95 246 | 93.87 306 | 90.24 241 | 98.61 310 | 81.18 332 | 94.88 328 | 95.45 328 |
|
MVS_Test | | | 96.27 159 | 96.79 134 | 94.73 253 | 96.94 286 | 86.63 286 | 96.18 147 | 98.33 172 | 94.94 163 | 96.07 219 | 98.28 103 | 95.25 114 | 99.26 243 | 97.21 63 | 97.90 266 | 98.30 233 |
|
MVSTER | | | 94.21 233 | 93.93 235 | 95.05 242 | 95.83 313 | 86.46 287 | 95.18 212 | 97.65 232 | 92.41 239 | 97.94 123 | 98.00 137 | 72.39 332 | 99.58 147 | 96.36 85 | 99.56 98 | 99.12 143 |
|
USDC | | | 94.56 224 | 94.57 215 | 94.55 262 | 97.78 237 | 86.43 288 | 92.75 300 | 98.65 137 | 85.96 304 | 96.91 183 | 97.93 145 | 90.82 231 | 98.74 299 | 90.71 237 | 99.59 90 | 98.47 215 |
|
MG-MVS | | | 94.08 239 | 94.00 234 | 94.32 267 | 97.09 281 | 85.89 289 | 93.19 294 | 95.96 277 | 92.52 235 | 94.93 248 | 97.51 180 | 89.54 245 | 98.77 297 | 87.52 293 | 97.71 279 | 98.31 231 |
|
ADS-MVSNet2 | | | 91.47 292 | 90.51 298 | 94.36 266 | 95.51 318 | 85.63 290 | 95.05 222 | 95.70 283 | 83.46 324 | 92.69 312 | 96.84 219 | 79.15 296 | 99.41 208 | 85.66 307 | 90.52 341 | 98.04 254 |
|
cascas | | | 91.89 281 | 91.35 275 | 93.51 287 | 94.27 335 | 85.60 291 | 88.86 342 | 98.61 140 | 79.32 340 | 92.16 320 | 91.44 338 | 89.22 252 | 98.12 335 | 90.80 233 | 97.47 294 | 96.82 298 |
|
semantic-postprocess | | | | | 94.85 249 | 97.68 244 | 85.53 292 | | 97.63 236 | 96.99 85 | 98.36 78 | 98.54 81 | 87.44 266 | 99.75 55 | 97.07 70 | 99.08 193 | 99.27 122 |
|
LP | | | 93.12 257 | 92.78 255 | 94.14 271 | 94.50 332 | 85.48 293 | 95.73 171 | 95.68 284 | 92.97 229 | 95.05 244 | 97.17 199 | 81.93 287 | 99.40 211 | 93.06 194 | 88.96 346 | 97.55 274 |
|
pmmvs3 | | | 90.00 304 | 88.90 313 | 93.32 291 | 94.20 338 | 85.34 294 | 91.25 324 | 92.56 316 | 78.59 343 | 93.82 282 | 95.17 282 | 67.36 351 | 98.69 304 | 89.08 265 | 98.03 258 | 95.92 318 |
|
BH-w/o | | | 92.14 274 | 91.94 267 | 92.73 306 | 97.13 280 | 85.30 295 | 92.46 307 | 95.64 285 | 89.33 272 | 94.21 269 | 92.74 322 | 89.60 244 | 98.24 331 | 81.68 330 | 94.66 330 | 94.66 333 |
|
DeepMVS_CX | | | | | 77.17 343 | 90.94 356 | 85.28 296 | | 74.08 360 | 52.51 355 | 80.87 356 | 88.03 351 | 75.25 316 | 70.63 358 | 59.23 356 | 84.94 351 | 75.62 353 |
|
MVE | | 73.61 22 | 86.48 326 | 85.92 326 | 88.18 335 | 96.23 302 | 85.28 296 | 81.78 354 | 75.79 357 | 86.01 303 | 82.53 354 | 91.88 330 | 92.74 188 | 87.47 357 | 71.42 352 | 94.86 329 | 91.78 348 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
1314 | | | 92.38 269 | 92.30 260 | 92.64 308 | 95.42 322 | 85.15 298 | 95.86 167 | 96.97 260 | 85.40 313 | 90.62 330 | 93.06 316 | 91.12 227 | 97.80 340 | 86.74 299 | 95.49 327 | 94.97 332 |
|
MDA-MVSNet_test_wron | | | 94.73 215 | 94.83 204 | 94.42 264 | 97.48 257 | 85.15 298 | 90.28 334 | 95.87 279 | 92.52 235 | 97.48 153 | 97.76 157 | 91.92 216 | 99.17 252 | 93.32 186 | 96.80 308 | 98.94 167 |
|
YYNet1 | | | 94.73 215 | 94.84 202 | 94.41 265 | 97.47 261 | 85.09 300 | 90.29 333 | 95.85 281 | 92.52 235 | 97.53 147 | 97.76 157 | 91.97 212 | 99.18 250 | 93.31 187 | 96.86 305 | 98.95 165 |
|
PAPM | | | 87.64 324 | 85.84 327 | 93.04 299 | 96.54 293 | 84.99 301 | 88.42 343 | 95.57 287 | 79.52 339 | 83.82 352 | 93.05 317 | 80.57 291 | 98.41 321 | 62.29 355 | 92.79 337 | 95.71 323 |
|
PS-MVSNAJ | | | 94.10 237 | 94.47 217 | 93.00 301 | 97.35 267 | 84.88 302 | 91.86 316 | 97.84 217 | 91.96 245 | 94.17 270 | 92.50 325 | 95.82 91 | 99.71 81 | 91.27 219 | 97.48 292 | 94.40 335 |
|
xiu_mvs_v2_base | | | 94.22 230 | 94.63 209 | 92.99 302 | 97.32 272 | 84.84 303 | 92.12 312 | 97.84 217 | 91.96 245 | 94.17 270 | 93.43 308 | 96.07 83 | 99.71 81 | 91.27 219 | 97.48 292 | 94.42 334 |
|
IB-MVS | | 85.98 20 | 88.63 314 | 86.95 323 | 93.68 284 | 95.12 324 | 84.82 304 | 90.85 327 | 90.17 340 | 87.55 290 | 88.48 344 | 91.34 339 | 58.01 355 | 99.59 145 | 87.24 296 | 93.80 334 | 96.63 307 |
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 |
view600 | | | 92.56 263 | 92.11 263 | 93.91 276 | 98.45 150 | 84.76 305 | 97.10 102 | 90.23 336 | 97.42 72 | 96.98 175 | 94.48 296 | 73.62 322 | 99.60 141 | 82.49 326 | 98.28 247 | 97.36 279 |
|
view800 | | | 92.56 263 | 92.11 263 | 93.91 276 | 98.45 150 | 84.76 305 | 97.10 102 | 90.23 336 | 97.42 72 | 96.98 175 | 94.48 296 | 73.62 322 | 99.60 141 | 82.49 326 | 98.28 247 | 97.36 279 |
|
conf0.05thres1000 | | | 92.56 263 | 92.11 263 | 93.91 276 | 98.45 150 | 84.76 305 | 97.10 102 | 90.23 336 | 97.42 72 | 96.98 175 | 94.48 296 | 73.62 322 | 99.60 141 | 82.49 326 | 98.28 247 | 97.36 279 |
|
tfpn | | | 92.56 263 | 92.11 263 | 93.91 276 | 98.45 150 | 84.76 305 | 97.10 102 | 90.23 336 | 97.42 72 | 96.98 175 | 94.48 296 | 73.62 322 | 99.60 141 | 82.49 326 | 98.28 247 | 97.36 279 |
|
thres600view7 | | | 92.03 276 | 91.43 272 | 93.82 281 | 98.19 183 | 84.61 309 | 96.27 140 | 90.39 331 | 96.81 93 | 96.37 202 | 93.11 311 | 73.44 328 | 99.49 178 | 80.32 333 | 97.95 260 | 97.36 279 |
|
tfpn111 | | | 91.92 278 | 91.39 273 | 93.49 288 | 98.21 179 | 84.50 310 | 96.39 131 | 90.39 331 | 96.87 89 | 96.33 203 | 93.08 313 | 73.44 328 | 99.51 174 | 79.87 334 | 97.94 263 | 96.46 310 |
|
conf200view11 | | | 91.81 283 | 91.26 278 | 93.46 289 | 98.21 179 | 84.50 310 | 96.39 131 | 90.39 331 | 96.87 89 | 96.33 203 | 93.08 313 | 73.44 328 | 99.42 197 | 78.85 339 | 97.74 269 | 96.46 310 |
|
thres100view900 | | | 91.76 285 | 91.26 278 | 93.26 293 | 98.21 179 | 84.50 310 | 96.39 131 | 90.39 331 | 96.87 89 | 96.33 203 | 93.08 313 | 73.44 328 | 99.42 197 | 78.85 339 | 97.74 269 | 95.85 320 |
|
gg-mvs-nofinetune | | | 88.28 318 | 86.96 322 | 92.23 313 | 92.84 350 | 84.44 313 | 98.19 41 | 74.60 358 | 99.08 9 | 87.01 349 | 99.47 8 | 56.93 356 | 98.23 332 | 78.91 338 | 95.61 325 | 94.01 340 |
|
tfpn200view9 | | | 91.55 291 | 91.00 282 | 93.21 295 | 98.02 202 | 84.35 314 | 95.70 174 | 90.79 328 | 96.26 109 | 95.90 226 | 92.13 328 | 73.62 322 | 99.42 197 | 78.85 339 | 97.74 269 | 95.85 320 |
|
thres400 | | | 91.68 290 | 91.00 282 | 93.71 283 | 98.02 202 | 84.35 314 | 95.70 174 | 90.79 328 | 96.26 109 | 95.90 226 | 92.13 328 | 73.62 322 | 99.42 197 | 78.85 339 | 97.74 269 | 97.36 279 |
|
GG-mvs-BLEND | | | | | 90.60 325 | 91.00 355 | 84.21 316 | 98.23 35 | 72.63 361 | | 82.76 353 | 84.11 354 | 56.14 357 | 96.79 348 | 72.20 350 | 92.09 340 | 90.78 351 |
|
thres200 | | | 91.00 296 | 90.42 300 | 92.77 305 | 97.47 261 | 83.98 317 | 94.01 263 | 91.18 326 | 95.12 159 | 95.44 236 | 91.21 340 | 73.93 318 | 99.31 234 | 77.76 343 | 97.63 287 | 95.01 331 |
|
IterMVS | | | 95.42 191 | 95.83 171 | 94.20 270 | 97.52 256 | 83.78 318 | 92.41 308 | 97.47 245 | 95.49 138 | 98.06 111 | 98.49 84 | 87.94 260 | 99.58 147 | 96.02 95 | 99.02 199 | 99.23 125 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
DSMNet-mixed | | | 92.19 273 | 91.83 269 | 93.25 294 | 96.18 304 | 83.68 319 | 96.27 140 | 93.68 301 | 76.97 349 | 92.54 317 | 99.18 35 | 89.20 253 | 98.55 315 | 83.88 320 | 98.60 237 | 97.51 276 |
|
EPNet_dtu | | | 91.39 293 | 90.75 294 | 93.31 292 | 90.48 357 | 82.61 320 | 94.80 233 | 92.88 311 | 93.39 212 | 81.74 355 | 94.90 290 | 81.36 289 | 99.11 257 | 88.28 277 | 98.87 214 | 98.21 241 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
EU-MVSNet | | | 94.25 229 | 94.47 217 | 93.60 285 | 98.14 193 | 82.60 321 | 97.24 95 | 92.72 314 | 85.08 315 | 98.48 70 | 98.94 55 | 82.59 286 | 98.76 298 | 97.47 57 | 99.53 106 | 99.44 81 |
|
ADS-MVSNet | | | 90.95 298 | 90.26 301 | 93.04 299 | 95.51 318 | 82.37 322 | 95.05 222 | 93.41 305 | 83.46 324 | 92.69 312 | 96.84 219 | 79.15 296 | 98.70 303 | 85.66 307 | 90.52 341 | 98.04 254 |
|
ppachtmachnet_test | | | 94.49 226 | 94.84 202 | 93.46 289 | 96.16 305 | 82.10 323 | 90.59 330 | 97.48 242 | 90.53 262 | 97.01 173 | 97.59 174 | 91.01 228 | 99.36 226 | 93.97 175 | 99.18 183 | 98.94 167 |
|
mvs_anonymous | | | 95.36 194 | 96.07 163 | 93.21 295 | 96.29 299 | 81.56 324 | 94.60 238 | 97.66 230 | 93.30 213 | 96.95 181 | 98.91 58 | 93.03 183 | 99.38 222 | 96.60 76 | 97.30 300 | 98.69 200 |
|
Patchmatch-test1 | | | 93.38 254 | 93.59 239 | 92.73 306 | 96.24 300 | 81.40 325 | 93.24 292 | 94.00 297 | 91.58 252 | 94.57 260 | 96.67 232 | 87.94 260 | 99.03 268 | 90.42 246 | 97.66 284 | 97.77 267 |
|
our_test_3 | | | 94.20 235 | 94.58 213 | 93.07 298 | 96.16 305 | 81.20 326 | 90.42 332 | 96.84 263 | 90.72 260 | 97.14 166 | 97.13 201 | 90.47 234 | 99.11 257 | 94.04 173 | 98.25 251 | 98.91 174 |
|
CHOSEN 280x420 | | | 89.98 305 | 89.19 311 | 92.37 311 | 95.60 317 | 81.13 327 | 86.22 347 | 97.09 256 | 81.44 332 | 87.44 348 | 93.15 310 | 73.99 317 | 99.47 183 | 88.69 271 | 99.07 195 | 96.52 309 |
|
test2356 | | | 85.45 327 | 83.26 330 | 92.01 315 | 91.12 354 | 80.76 328 | 85.16 348 | 92.90 310 | 83.90 323 | 90.63 329 | 87.71 352 | 53.10 360 | 97.24 344 | 69.20 353 | 95.65 324 | 98.03 256 |
|
PMMVS2 | | | 93.66 247 | 94.07 231 | 92.45 310 | 97.57 252 | 80.67 329 | 86.46 346 | 96.00 275 | 93.99 196 | 97.10 169 | 97.38 192 | 89.90 243 | 97.82 339 | 88.76 269 | 99.47 125 | 98.86 185 |
|
new-patchmatchnet | | | 95.67 177 | 96.58 141 | 92.94 303 | 97.48 257 | 80.21 330 | 92.96 296 | 98.19 194 | 94.83 168 | 98.82 47 | 98.79 61 | 93.31 176 | 99.51 174 | 95.83 102 | 99.04 198 | 99.12 143 |
|
PatchmatchNet | | | 91.98 277 | 91.87 268 | 92.30 312 | 94.60 330 | 79.71 331 | 95.12 213 | 93.59 304 | 89.52 270 | 93.61 292 | 97.02 208 | 77.94 299 | 99.18 250 | 90.84 231 | 94.57 332 | 98.01 259 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
testus | | | 90.90 299 | 90.51 298 | 92.06 314 | 96.07 308 | 79.45 332 | 88.99 340 | 98.44 156 | 85.46 311 | 94.15 272 | 90.77 342 | 89.12 254 | 98.01 338 | 73.66 348 | 97.95 260 | 98.71 199 |
|
EPMVS | | | 89.26 311 | 88.55 315 | 91.39 318 | 92.36 352 | 79.11 333 | 95.65 180 | 79.86 356 | 88.60 278 | 93.12 306 | 96.53 239 | 70.73 338 | 98.10 336 | 90.75 235 | 89.32 345 | 96.98 291 |
|
DWT-MVSNet_test | | | 87.92 322 | 86.77 324 | 91.39 318 | 93.18 345 | 78.62 334 | 95.10 214 | 91.42 323 | 85.58 308 | 88.00 345 | 88.73 349 | 60.60 354 | 98.90 281 | 90.60 240 | 87.70 348 | 96.65 304 |
|
PatchFormer-LS_test | | | 89.62 309 | 89.12 312 | 91.11 322 | 93.62 342 | 78.42 335 | 94.57 240 | 93.62 303 | 88.39 281 | 90.54 333 | 88.40 350 | 72.33 333 | 99.03 268 | 92.41 201 | 88.20 347 | 95.89 319 |
|
tpm | | | 91.08 295 | 90.85 292 | 91.75 316 | 95.33 323 | 78.09 336 | 95.03 224 | 91.27 325 | 88.75 276 | 93.53 295 | 97.40 187 | 71.24 335 | 99.30 236 | 91.25 221 | 93.87 333 | 97.87 262 |
|
tpmp4_e23 | | | 88.46 316 | 87.54 319 | 91.22 321 | 94.56 331 | 78.08 337 | 95.63 185 | 93.17 307 | 79.08 342 | 85.85 350 | 96.80 223 | 65.86 352 | 98.85 291 | 84.10 318 | 92.85 336 | 96.72 303 |
|
PVSNet | | 86.72 19 | 91.10 294 | 90.97 290 | 91.49 317 | 97.56 254 | 78.04 338 | 87.17 344 | 94.60 293 | 84.65 318 | 92.34 318 | 92.20 327 | 87.37 267 | 98.47 318 | 85.17 312 | 97.69 281 | 97.96 260 |
|
CostFormer | | | 89.75 308 | 89.25 307 | 91.26 320 | 94.69 329 | 78.00 339 | 95.32 203 | 91.98 319 | 81.50 331 | 90.55 332 | 96.96 211 | 71.06 336 | 98.89 284 | 88.59 273 | 92.63 338 | 96.87 296 |
|
E-PMN | | | 89.52 310 | 89.78 305 | 88.73 332 | 93.14 346 | 77.61 340 | 83.26 351 | 92.02 318 | 94.82 169 | 93.71 287 | 93.11 311 | 75.31 315 | 96.81 347 | 85.81 304 | 96.81 307 | 91.77 349 |
|
EMVS | | | 89.06 312 | 89.22 308 | 88.61 333 | 93.00 348 | 77.34 341 | 82.91 352 | 90.92 327 | 94.64 173 | 92.63 315 | 91.81 331 | 76.30 311 | 97.02 345 | 83.83 321 | 96.90 303 | 91.48 350 |
|
tpm2 | | | 88.47 315 | 87.69 318 | 90.79 324 | 94.98 326 | 77.34 341 | 95.09 216 | 91.83 320 | 77.51 348 | 89.40 340 | 96.41 247 | 67.83 350 | 98.73 300 | 83.58 324 | 92.60 339 | 96.29 316 |
|
tpmvs | | | 90.79 300 | 90.87 291 | 90.57 326 | 92.75 351 | 76.30 343 | 95.79 170 | 93.64 302 | 91.04 257 | 91.91 322 | 96.26 253 | 77.19 307 | 98.86 290 | 89.38 260 | 89.85 344 | 96.56 308 |
|
tpm cat1 | | | 88.01 320 | 87.33 320 | 90.05 329 | 94.48 333 | 76.28 344 | 94.47 241 | 94.35 296 | 73.84 353 | 89.26 341 | 95.61 276 | 73.64 321 | 98.30 330 | 84.13 317 | 86.20 350 | 95.57 327 |
|
CVMVSNet | | | 92.33 271 | 92.79 253 | 90.95 323 | 97.26 274 | 75.84 345 | 95.29 206 | 92.33 317 | 81.86 328 | 96.27 211 | 98.19 112 | 81.44 288 | 98.46 319 | 94.23 167 | 98.29 246 | 98.55 211 |
|
test-LLR | | | 89.97 306 | 89.90 304 | 90.16 327 | 94.24 336 | 74.98 346 | 89.89 336 | 89.06 341 | 92.02 242 | 89.97 338 | 90.77 342 | 73.92 319 | 98.57 312 | 91.88 207 | 97.36 296 | 96.92 293 |
|
test-mter | | | 87.92 322 | 87.17 321 | 90.16 327 | 94.24 336 | 74.98 346 | 89.89 336 | 89.06 341 | 86.44 300 | 89.97 338 | 90.77 342 | 54.96 359 | 98.57 312 | 91.88 207 | 97.36 296 | 96.92 293 |
|
PVSNet_0 | | 81.89 21 | 84.49 328 | 83.21 331 | 88.34 334 | 95.76 315 | 74.97 348 | 83.49 350 | 92.70 315 | 78.47 344 | 87.94 346 | 86.90 353 | 83.38 284 | 96.63 350 | 73.44 349 | 66.86 356 | 93.40 343 |
|
MDTV_nov1_ep13 | | | | 91.28 276 | | 94.31 334 | 73.51 349 | 94.80 233 | 93.16 308 | 86.75 299 | 93.45 299 | 97.40 187 | 76.37 310 | 98.55 315 | 88.85 268 | 96.43 313 | |
|
testpf | | | 82.70 330 | 84.35 328 | 77.74 342 | 88.97 358 | 73.23 350 | 93.85 270 | 84.33 354 | 88.10 285 | 85.06 351 | 90.42 346 | 52.62 362 | 91.05 356 | 91.00 226 | 84.82 352 | 68.93 355 |
|
TESTMET0.1,1 | | | 87.20 325 | 86.57 325 | 89.07 331 | 93.62 342 | 72.84 351 | 89.89 336 | 87.01 352 | 85.46 311 | 89.12 342 | 90.20 347 | 56.00 358 | 97.72 341 | 90.91 229 | 96.92 302 | 96.64 305 |
|
tpmrst | | | 90.31 301 | 90.61 297 | 89.41 330 | 94.06 339 | 72.37 352 | 95.06 221 | 93.69 299 | 88.01 286 | 92.32 319 | 96.86 217 | 77.45 303 | 98.82 292 | 91.04 224 | 87.01 349 | 97.04 290 |
|
gm-plane-assit | | | | | | 91.79 353 | 71.40 353 | | | 81.67 329 | | 90.11 348 | | 98.99 272 | 84.86 314 | | |
|
dp | | | 88.08 319 | 88.05 317 | 88.16 336 | 92.85 349 | 68.81 354 | 94.17 255 | 92.88 311 | 85.47 310 | 91.38 327 | 96.14 260 | 68.87 347 | 98.81 294 | 86.88 298 | 83.80 353 | 96.87 296 |
|
PNet_i23d | | | 83.82 329 | 83.39 329 | 85.10 340 | 96.07 308 | 65.16 355 | 81.87 353 | 94.37 295 | 90.87 259 | 93.92 281 | 92.89 319 | 52.80 361 | 96.44 351 | 77.52 345 | 70.22 355 | 93.70 341 |
|
test12356 | | | 87.98 321 | 88.41 316 | 86.69 339 | 95.84 312 | 63.49 356 | 87.15 345 | 97.32 247 | 87.21 292 | 91.78 325 | 93.36 309 | 70.66 339 | 98.39 323 | 74.70 346 | 97.64 286 | 98.19 243 |
|
1111 | | | 88.78 313 | 89.39 306 | 86.96 338 | 98.53 142 | 62.84 357 | 91.49 320 | 97.48 242 | 94.45 179 | 96.56 193 | 96.45 244 | 43.83 363 | 98.87 288 | 86.33 301 | 99.40 151 | 99.18 130 |
|
.test1245 | | | 73.49 331 | 79.27 332 | 56.15 344 | 98.53 142 | 62.84 357 | 91.49 320 | 97.48 242 | 94.45 179 | 96.56 193 | 96.45 244 | 43.83 363 | 98.87 288 | 86.33 301 | 8.32 358 | 6.75 358 |
|
MVS-HIRNet | | | 88.40 317 | 90.20 303 | 82.99 341 | 97.01 283 | 60.04 359 | 93.11 295 | 85.61 353 | 84.45 321 | 88.72 343 | 99.09 46 | 84.72 281 | 98.23 332 | 82.52 325 | 96.59 312 | 90.69 352 |
|
MDTV_nov1_ep13_2view | | | | | | | 57.28 360 | 94.89 228 | | 80.59 335 | 94.02 277 | | 78.66 298 | | 85.50 309 | | 97.82 265 |
|
tmp_tt | | | 57.23 332 | 62.50 333 | 41.44 345 | 34.77 360 | 49.21 361 | 83.93 349 | 60.22 362 | 15.31 356 | 71.11 357 | 79.37 355 | 70.09 340 | 44.86 359 | 64.76 354 | 82.93 354 | 30.25 356 |
|
test123 | | | 12.59 335 | 15.49 336 | 3.87 347 | 6.07 361 | 2.55 362 | 90.75 328 | 2.59 364 | 2.52 357 | 5.20 359 | 13.02 358 | 4.96 365 | 1.85 361 | 5.20 357 | 9.09 357 | 7.23 357 |
|
testmvs | | | 12.33 336 | 15.23 337 | 3.64 348 | 5.77 362 | 2.23 363 | 88.99 340 | 3.62 363 | 2.30 358 | 5.29 358 | 13.09 357 | 4.52 366 | 1.95 360 | 5.16 358 | 8.32 358 | 6.75 358 |
|
cdsmvs_eth3d_5k | | | 24.22 334 | 32.30 335 | 0.00 349 | 0.00 363 | 0.00 364 | 0.00 355 | 98.10 202 | 0.00 359 | 0.00 360 | 95.06 285 | 97.54 28 | 0.00 362 | 0.00 359 | 0.00 360 | 0.00 360 |
|
pcd_1.5k_mvsjas | | | 7.98 337 | 10.65 338 | 0.00 349 | 0.00 363 | 0.00 364 | 0.00 355 | 0.00 365 | 0.00 359 | 0.00 360 | 0.00 361 | 95.82 91 | 0.00 362 | 0.00 359 | 0.00 360 | 0.00 360 |
|
pcd1.5k->3k | | | 41.47 333 | 44.19 334 | 33.29 346 | 99.65 11 | 0.00 364 | 0.00 355 | 99.07 34 | 0.00 359 | 0.00 360 | 0.00 361 | 99.04 4 | 0.00 362 | 0.00 359 | 99.96 11 | 99.87 2 |
|
sosnet-low-res | | | 0.00 339 | 0.00 340 | 0.00 349 | 0.00 363 | 0.00 364 | 0.00 355 | 0.00 365 | 0.00 359 | 0.00 360 | 0.00 361 | 0.00 367 | 0.00 362 | 0.00 359 | 0.00 360 | 0.00 360 |
|
sosnet | | | 0.00 339 | 0.00 340 | 0.00 349 | 0.00 363 | 0.00 364 | 0.00 355 | 0.00 365 | 0.00 359 | 0.00 360 | 0.00 361 | 0.00 367 | 0.00 362 | 0.00 359 | 0.00 360 | 0.00 360 |
|
uncertanet | | | 0.00 339 | 0.00 340 | 0.00 349 | 0.00 363 | 0.00 364 | 0.00 355 | 0.00 365 | 0.00 359 | 0.00 360 | 0.00 361 | 0.00 367 | 0.00 362 | 0.00 359 | 0.00 360 | 0.00 360 |
|
Regformer | | | 0.00 339 | 0.00 340 | 0.00 349 | 0.00 363 | 0.00 364 | 0.00 355 | 0.00 365 | 0.00 359 | 0.00 360 | 0.00 361 | 0.00 367 | 0.00 362 | 0.00 359 | 0.00 360 | 0.00 360 |
|
ab-mvs-re | | | 7.91 338 | 10.55 339 | 0.00 349 | 0.00 363 | 0.00 364 | 0.00 355 | 0.00 365 | 0.00 359 | 0.00 360 | 94.94 287 | 0.00 367 | 0.00 362 | 0.00 359 | 0.00 360 | 0.00 360 |
|
uanet | | | 0.00 339 | 0.00 340 | 0.00 349 | 0.00 363 | 0.00 364 | 0.00 355 | 0.00 365 | 0.00 359 | 0.00 360 | 0.00 361 | 0.00 367 | 0.00 362 | 0.00 359 | 0.00 360 | 0.00 360 |
|
GSMVS | | | | | | | | | | | | | | | | | 98.06 251 |
|
test_part3 | | | | | | | | 95.64 182 | | 94.84 166 | | 97.60 172 | | 99.76 49 | 91.22 222 | | |
|
test_part1 | | | | | | | | | 98.84 88 | | | | 96.69 61 | | | 99.44 132 | 99.37 102 |
|
sam_mvs1 | | | | | | | | | | | | | 77.80 300 | | | | 98.06 251 |
|
sam_mvs | | | | | | | | | | | | | 77.38 304 | | | | |
|
MTGPA | | | | | | | | | 98.73 114 | | | | | | | | |
|
test_post1 | | | | | | | | 94.98 226 | | | | 10.37 360 | 76.21 312 | 99.04 265 | 89.47 259 | | |
|
test_post | | | | | | | | | | | | 10.87 359 | 76.83 308 | 99.07 262 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 96.84 219 | 77.36 305 | 99.42 197 | | | |
|
MTMP | | | | | | | | | 74.60 358 | | | | | | | | |
|
test9_res | | | | | | | | | | | | | | | 91.29 218 | 98.89 213 | 99.00 159 |
|
agg_prior2 | | | | | | | | | | | | | | | 90.34 249 | 98.90 209 | 99.10 150 |
|
test_prior2 | | | | | | | | 93.33 290 | | 94.21 191 | 94.02 277 | 96.25 254 | 93.64 166 | | 91.90 205 | 98.96 203 | |
|
旧先验2 | | | | | | | | 93.35 289 | | 77.95 347 | 95.77 231 | | | 98.67 308 | 90.74 236 | | |
|
新几何2 | | | | | | | | 93.43 285 | | | | | | | | | |
|
无先验 | | | | | | | | 93.20 293 | 97.91 212 | 80.78 334 | | | | 99.40 211 | 87.71 281 | | 97.94 261 |
|
原ACMM2 | | | | | | | | 92.82 298 | | | | | | | | | |
|
testdata2 | | | | | | | | | | | | | | 99.46 188 | 87.84 280 | | |
|
segment_acmp | | | | | | | | | | | | | 95.34 109 | | | | |
|
testdata1 | | | | | | | | 92.77 299 | | 93.78 206 | | | | | | | |
|
plane_prior5 | | | | | | | | | 98.75 111 | | | | | 99.46 188 | 92.59 198 | 99.20 180 | 99.28 119 |
|
plane_prior4 | | | | | | | | | | | | 96.77 225 | | | | | |
|
plane_prior2 | | | | | | | | 96.50 128 | | 96.36 105 | | | | | | | |
|
plane_prior1 | | | | | | 98.49 146 | | | | | | | | | | | |
|
n2 | | | | | | | | | 0.00 365 | | | | | | | | |
|
nn | | | | | | | | | 0.00 365 | | | | | | | | |
|
door-mid | | | | | | | | | 98.17 195 | | | | | | | | |
|
test11 | | | | | | | | | 98.08 205 | | | | | | | | |
|
door | | | | | | | | | 97.81 220 | | | | | | | | |
|
HQP-NCC | | | | | | 97.85 217 | | 94.26 245 | | 93.18 217 | 92.86 309 | | | | | | |
|
ACMP_Plane | | | | | | 97.85 217 | | 94.26 245 | | 93.18 217 | 92.86 309 | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 90.51 243 | | |
|
HQP4-MVS | | | | | | | | | | | 92.87 308 | | | 99.23 247 | | | 99.06 155 |
|
HQP3-MVS | | | | | | | | | 98.43 157 | | | | | | | 98.74 224 | |
|
HQP2-MVS | | | | | | | | | | | | | 90.33 236 | | | | |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 99.52 110 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 99.55 102 | |
|
Test By Simon | | | | | | | | | | | | | 94.51 138 | | | | |
|