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 |
|
mvs_tets | | | 98.90 4 | 98.94 7 | 98.75 30 | 99.69 7 | 96.48 55 | 98.54 20 | 99.22 9 | 96.23 114 | 99.71 4 | 99.48 6 | 98.77 6 | 99.93 2 | 98.89 10 | 99.95 13 | 99.84 6 |
|
DTE-MVSNet | | | 98.79 9 | 98.86 10 | 98.59 43 | 99.55 20 | 96.12 65 | 98.48 24 | 99.10 25 | 99.36 3 | 99.29 25 | 99.06 47 | 97.27 36 | 99.93 2 | 97.71 46 | 99.91 26 | 99.70 19 |
|
UA-Net | | | 98.88 6 | 98.76 15 | 99.22 2 | 99.11 77 | 97.89 10 | 99.47 3 | 99.32 7 | 99.08 9 | 97.87 140 | 99.67 2 | 96.47 73 | 99.92 4 | 97.88 37 | 99.98 3 | 99.85 4 |
|
PS-MVSNAJss | | | 98.53 22 | 98.63 21 | 98.21 69 | 99.68 8 | 94.82 105 | 98.10 44 | 99.21 10 | 96.91 89 | 99.75 3 | 99.45 8 | 95.82 90 | 99.92 4 | 98.80 13 | 99.96 11 | 99.89 1 |
|
jajsoiax | | | 98.77 10 | 98.79 14 | 98.74 32 | 99.66 9 | 96.48 55 | 98.45 25 | 99.12 22 | 95.83 133 | 99.67 6 | 99.37 14 | 98.25 10 | 99.92 4 | 98.77 14 | 99.94 19 | 99.82 7 |
|
PS-CasMVS | | | 98.73 12 | 98.85 12 | 98.39 55 | 99.55 20 | 95.47 85 | 98.49 22 | 99.13 21 | 99.22 7 | 99.22 29 | 98.96 52 | 97.35 32 | 99.92 4 | 97.79 42 | 99.93 21 | 99.79 8 |
|
PEN-MVS | | | 98.75 11 | 98.85 12 | 98.44 51 | 99.58 17 | 95.67 77 | 98.45 25 | 99.15 18 | 99.33 4 | 99.30 24 | 99.00 48 | 97.27 36 | 99.92 4 | 97.64 47 | 99.92 23 | 99.75 13 |
|
MVSFormer | | | 96.14 170 | 96.36 158 | 95.49 238 | 97.68 250 | 87.81 276 | 98.67 12 | 99.02 51 | 96.50 102 | 94.48 274 | 96.15 264 | 86.90 273 | 99.92 4 | 98.73 17 | 99.13 188 | 98.74 199 |
|
test_djsdf | | | 98.73 12 | 98.74 18 | 98.69 37 | 99.63 12 | 96.30 60 | 98.67 12 | 99.02 51 | 96.50 102 | 99.32 21 | 99.44 9 | 97.43 29 | 99.92 4 | 98.73 17 | 99.95 13 | 99.86 3 |
|
K. test v3 | | | 96.44 159 | 96.28 161 | 96.95 149 | 99.41 39 | 91.53 192 | 97.65 72 | 90.31 343 | 98.89 18 | 98.93 44 | 99.36 16 | 84.57 286 | 99.92 4 | 97.81 40 | 99.56 97 | 99.39 96 |
|
v7n | | | 98.73 12 | 98.99 6 | 97.95 82 | 99.64 11 | 94.20 128 | 98.67 12 | 99.14 20 | 99.08 9 | 99.42 16 | 99.23 29 | 96.53 67 | 99.91 12 | 99.27 4 | 99.93 21 | 99.73 15 |
|
anonymousdsp | | | 98.72 15 | 98.63 21 | 98.99 10 | 99.62 13 | 97.29 34 | 98.65 15 | 99.19 13 | 95.62 140 | 99.35 20 | 99.37 14 | 97.38 31 | 99.90 13 | 98.59 23 | 99.91 26 | 99.77 9 |
|
CP-MVSNet | | | 98.42 26 | 98.46 29 | 98.30 64 | 99.46 31 | 95.22 93 | 98.27 33 | 98.84 88 | 99.05 12 | 99.01 39 | 98.65 74 | 95.37 109 | 99.90 13 | 97.57 52 | 99.91 26 | 99.77 9 |
|
HyFIR lowres test | | | 93.72 252 | 92.65 263 | 96.91 153 | 98.93 94 | 91.81 189 | 91.23 334 | 98.52 150 | 82.69 336 | 96.46 205 | 96.52 247 | 80.38 298 | 99.90 13 | 90.36 257 | 98.79 222 | 99.03 157 |
|
WR-MVS_H | | | 98.65 17 | 98.62 23 | 98.75 30 | 99.51 25 | 96.61 51 | 98.55 19 | 99.17 14 | 99.05 12 | 99.17 32 | 98.79 61 | 95.47 106 | 99.89 16 | 97.95 35 | 99.91 26 | 99.75 13 |
|
SixPastTwentyTwo | | | 97.49 92 | 97.57 81 | 97.26 135 | 99.56 18 | 92.33 170 | 98.28 31 | 96.97 265 | 98.30 34 | 99.45 14 | 99.35 18 | 88.43 260 | 99.89 16 | 98.01 34 | 99.76 50 | 99.54 45 |
|
TranMVSNet+NR-MVSNet | | | 98.33 29 | 98.30 39 | 98.43 52 | 99.07 81 | 95.87 70 | 96.73 128 | 99.05 38 | 98.67 22 | 98.84 46 | 98.45 88 | 97.58 26 | 99.88 18 | 96.45 86 | 99.86 37 | 99.54 45 |
|
OurMVSNet-221017-0 | | | 98.61 18 | 98.61 25 | 98.63 41 | 99.77 3 | 96.35 58 | 99.17 5 | 99.05 38 | 98.05 42 | 99.61 11 | 99.52 4 | 93.72 168 | 99.88 18 | 98.72 20 | 99.88 33 | 99.65 24 |
|
v52 | | | 98.85 7 | 99.01 4 | 98.37 56 | 99.61 14 | 95.53 83 | 99.01 6 | 99.04 45 | 98.48 27 | 99.31 22 | 99.41 11 | 96.82 57 | 99.87 20 | 99.44 2 | 99.95 13 | 99.70 19 |
|
V4 | | | 98.85 7 | 99.01 4 | 98.37 56 | 99.61 14 | 95.53 83 | 99.01 6 | 99.04 45 | 98.48 27 | 99.31 22 | 99.41 11 | 96.81 58 | 99.87 20 | 99.44 2 | 99.95 13 | 99.70 19 |
|
Vis-MVSNet | ![Method available under a permissive open source license. permissive](img/icon_permissive.png) | | 98.27 32 | 98.34 35 | 98.07 74 | 99.33 46 | 95.21 95 | 98.04 48 | 99.46 5 | 97.32 84 | 97.82 144 | 99.11 43 | 96.75 60 | 99.86 22 | 97.84 39 | 99.36 154 | 99.15 135 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
v748 | | | 98.58 19 | 98.89 9 | 97.67 101 | 99.61 14 | 93.53 152 | 98.59 16 | 98.90 76 | 98.97 17 | 99.43 15 | 99.15 40 | 96.53 67 | 99.85 23 | 98.88 11 | 99.91 26 | 99.64 27 |
|
UniMVSNet_NR-MVSNet | | | 97.83 65 | 97.65 71 | 98.37 56 | 98.72 113 | 95.78 72 | 95.66 186 | 99.02 51 | 98.11 40 | 98.31 87 | 97.69 173 | 94.65 131 | 99.85 23 | 97.02 74 | 99.71 63 | 99.48 62 |
|
DU-MVS | | | 97.79 71 | 97.60 78 | 98.36 59 | 98.73 111 | 95.78 72 | 95.65 188 | 98.87 82 | 97.57 65 | 98.31 87 | 97.83 157 | 94.69 127 | 99.85 23 | 97.02 74 | 99.71 63 | 99.46 67 |
|
EPP-MVSNet | | | 96.84 132 | 96.58 144 | 97.65 102 | 99.18 63 | 93.78 143 | 98.68 11 | 96.34 276 | 97.91 47 | 97.30 164 | 98.06 136 | 88.46 259 | 99.85 23 | 93.85 186 | 99.40 149 | 99.32 107 |
|
LCM-MVSNet-Re | | | 97.33 104 | 97.33 94 | 97.32 131 | 98.13 201 | 93.79 142 | 96.99 114 | 99.65 2 | 96.74 96 | 99.47 13 | 98.93 55 | 96.91 49 | 99.84 27 | 90.11 259 | 99.06 200 | 98.32 236 |
|
MIMVSNet1 | | | 98.51 23 | 98.45 31 | 98.67 38 | 99.72 5 | 96.71 46 | 98.76 10 | 98.89 78 | 98.49 26 | 99.38 18 | 99.14 41 | 95.44 108 | 99.84 27 | 96.47 85 | 99.80 46 | 99.47 65 |
|
ANet_high | | | 98.31 31 | 98.94 7 | 96.41 182 | 99.33 46 | 89.64 219 | 97.92 55 | 99.56 4 | 99.27 5 | 99.66 8 | 99.50 5 | 97.67 24 | 99.83 29 | 97.55 53 | 99.98 3 | 99.77 9 |
|
zzz-MVS | | | 98.01 46 | 97.66 70 | 99.06 5 | 99.44 33 | 97.90 8 | 95.66 186 | 98.73 114 | 97.69 59 | 97.90 131 | 97.96 145 | 95.81 94 | 99.82 30 | 96.13 93 | 99.61 84 | 99.45 72 |
|
MTAPA | | | 98.14 37 | 97.84 58 | 99.06 5 | 99.44 33 | 97.90 8 | 97.25 94 | 98.73 114 | 97.69 59 | 97.90 131 | 97.96 145 | 95.81 94 | 99.82 30 | 96.13 93 | 99.61 84 | 99.45 72 |
|
tttt0517 | | | 93.31 262 | 92.56 265 | 95.57 232 | 98.71 116 | 87.86 272 | 97.44 87 | 87.17 362 | 95.79 135 | 97.47 158 | 96.84 224 | 64.12 360 | 99.81 32 | 96.20 91 | 99.32 168 | 99.02 159 |
|
ESAPD | | | 97.64 81 | 97.35 93 | 98.50 47 | 98.85 101 | 96.18 62 | 95.21 218 | 98.99 65 | 95.84 132 | 98.78 49 | 98.08 131 | 96.84 55 | 99.81 32 | 93.98 182 | 99.57 94 | 99.52 48 |
|
Effi-MVS+-dtu | | | 96.81 138 | 96.09 166 | 98.99 10 | 96.90 298 | 98.69 2 | 96.42 136 | 98.09 207 | 95.86 130 | 95.15 250 | 95.54 285 | 94.26 148 | 99.81 32 | 94.06 176 | 98.51 247 | 98.47 220 |
|
HSP-MVS | | | 97.37 100 | 96.85 130 | 98.92 19 | 99.26 50 | 97.70 15 | 97.66 71 | 98.23 190 | 95.65 138 | 98.51 67 | 96.46 249 | 92.15 209 | 99.81 32 | 95.14 138 | 98.58 244 | 99.26 122 |
|
FC-MVSNet-test | | | 98.16 36 | 98.37 33 | 97.56 106 | 99.49 29 | 93.10 160 | 98.35 28 | 99.21 10 | 98.43 29 | 98.89 45 | 98.83 60 | 94.30 145 | 99.81 32 | 97.87 38 | 99.91 26 | 99.77 9 |
|
APDe-MVS | | | 98.14 37 | 98.03 51 | 98.47 50 | 98.72 113 | 96.04 67 | 98.07 46 | 99.10 25 | 95.96 125 | 98.59 62 | 98.69 70 | 96.94 47 | 99.81 32 | 96.64 78 | 99.58 91 | 99.57 40 |
|
abl_6 | | | 98.42 26 | 98.19 41 | 99.09 4 | 99.16 64 | 98.10 5 | 97.73 70 | 99.11 23 | 97.76 51 | 98.62 58 | 98.27 108 | 97.88 20 | 99.80 38 | 95.67 110 | 99.50 113 | 99.38 98 |
|
HPM-MVS | ![Method available under an open source license with copyleft or other restrictive terms. copyleft](img/icon_copyleft.png) | | 98.11 40 | 97.83 59 | 98.92 19 | 99.42 38 | 97.46 28 | 98.57 17 | 99.05 38 | 95.43 149 | 97.41 161 | 97.50 186 | 97.98 16 | 99.79 39 | 95.58 119 | 99.57 94 | 99.50 51 |
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
FIs | | | 97.93 55 | 98.07 47 | 97.48 118 | 99.38 42 | 92.95 162 | 98.03 50 | 99.11 23 | 98.04 43 | 98.62 58 | 98.66 72 | 93.75 167 | 99.78 40 | 97.23 64 | 99.84 40 | 99.73 15 |
|
MP-MVS | ![Method available under an open source license with copyleft or other restrictive terms. copyleft](img/icon_copyleft.png) | | 97.64 81 | 97.18 108 | 99.00 9 | 99.32 48 | 97.77 14 | 97.49 85 | 98.73 114 | 96.27 111 | 95.59 243 | 97.75 166 | 96.30 78 | 99.78 40 | 93.70 190 | 99.48 123 | 99.45 72 |
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
PGM-MVS | | | 97.88 61 | 97.52 84 | 98.96 13 | 99.20 60 | 97.62 18 | 97.09 109 | 99.06 36 | 95.45 147 | 97.55 148 | 97.94 149 | 97.11 41 | 99.78 40 | 94.77 154 | 99.46 127 | 99.48 62 |
|
UniMVSNet (Re) | | | 97.83 65 | 97.65 71 | 98.35 60 | 98.80 104 | 95.86 71 | 95.92 174 | 99.04 45 | 97.51 70 | 98.22 94 | 97.81 161 | 94.68 129 | 99.78 40 | 97.14 70 | 99.75 54 | 99.41 90 |
|
NR-MVSNet | | | 97.96 48 | 97.86 57 | 98.26 66 | 98.73 111 | 95.54 81 | 98.14 42 | 98.73 114 | 97.79 49 | 99.42 16 | 97.83 157 | 94.40 142 | 99.78 40 | 95.91 105 | 99.76 50 | 99.46 67 |
|
mPP-MVS | | | 97.91 58 | 97.53 83 | 99.04 7 | 99.22 56 | 97.87 11 | 97.74 68 | 98.78 106 | 96.04 121 | 97.10 173 | 97.73 169 | 96.53 67 | 99.78 40 | 95.16 136 | 99.50 113 | 99.46 67 |
|
CP-MVS | | | 97.92 56 | 97.56 82 | 98.99 10 | 98.99 90 | 97.82 12 | 97.93 54 | 98.96 71 | 96.11 118 | 96.89 188 | 97.45 189 | 96.85 54 | 99.78 40 | 95.19 132 | 99.63 78 | 99.38 98 |
|
PVSNet_Blended_VisFu | | | 95.95 176 | 95.80 178 | 96.42 181 | 99.28 49 | 90.62 205 | 95.31 210 | 99.08 30 | 88.40 289 | 96.97 184 | 98.17 121 | 92.11 211 | 99.78 40 | 93.64 191 | 99.21 180 | 98.86 187 |
|
GST-MVS | | | 97.82 68 | 97.49 87 | 98.81 26 | 99.23 54 | 97.25 35 | 97.16 99 | 98.79 102 | 95.96 125 | 97.53 149 | 97.40 191 | 96.93 48 | 99.77 48 | 95.04 143 | 99.35 158 | 99.42 87 |
|
thisisatest0530 | | | 92.71 270 | 91.76 279 | 95.56 234 | 98.42 157 | 88.23 259 | 96.03 160 | 87.35 361 | 94.04 203 | 96.56 199 | 95.47 287 | 64.03 361 | 99.77 48 | 94.78 153 | 99.11 192 | 98.68 205 |
|
MP-MVS-pluss | | | 97.69 78 | 97.36 92 | 98.70 36 | 99.50 28 | 96.84 43 | 95.38 204 | 98.99 65 | 92.45 247 | 98.11 104 | 98.31 101 | 97.25 38 | 99.77 48 | 96.60 79 | 99.62 79 | 99.48 62 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
region2R | | | 97.92 56 | 97.59 79 | 98.92 19 | 99.22 56 | 97.55 23 | 97.60 78 | 98.84 88 | 96.00 123 | 97.22 166 | 97.62 176 | 96.87 53 | 99.76 51 | 95.48 121 | 99.43 139 | 99.46 67 |
|
ACMMPR | | | 97.95 51 | 97.62 77 | 98.94 15 | 99.20 60 | 97.56 22 | 97.59 79 | 98.83 96 | 96.05 119 | 97.46 159 | 97.63 175 | 96.77 59 | 99.76 51 | 95.61 116 | 99.46 127 | 99.49 59 |
|
SteuartSystems-ACMMP | | | 98.02 44 | 97.76 63 | 98.79 28 | 99.43 36 | 97.21 37 | 97.15 100 | 98.90 76 | 96.58 100 | 98.08 110 | 97.87 156 | 97.02 46 | 99.76 51 | 95.25 129 | 99.59 89 | 99.40 93 |
Skip Steuart: Steuart Systems R&D Blog. |
ACMMP | ![Method available under an open source license with copyleft or other restrictive terms. copyleft](img/icon_copyleft.png) | | 98.05 42 | 97.75 64 | 98.93 18 | 99.23 54 | 97.60 19 | 98.09 45 | 98.96 71 | 95.75 137 | 97.91 130 | 98.06 136 | 96.89 50 | 99.76 51 | 95.32 127 | 99.57 94 | 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 |
semantic-postprocess | | | | | 94.85 258 | 97.68 250 | 85.53 301 | | 97.63 241 | 96.99 86 | 98.36 80 | 98.54 82 | 87.44 269 | 99.75 55 | 97.07 73 | 99.08 195 | 99.27 121 |
|
APD-MVS_3200maxsize | | | 98.13 39 | 97.90 55 | 98.79 28 | 98.79 105 | 97.31 33 | 97.55 82 | 98.92 74 | 97.72 56 | 98.25 92 | 98.13 126 | 97.10 42 | 99.75 55 | 95.44 123 | 99.24 178 | 99.32 107 |
|
VPA-MVSNet | | | 98.27 32 | 98.46 29 | 97.70 97 | 99.06 82 | 93.80 141 | 97.76 65 | 99.00 62 | 98.40 30 | 99.07 36 | 98.98 50 | 96.89 50 | 99.75 55 | 97.19 68 | 99.79 47 | 99.55 44 |
|
WR-MVS | | | 96.90 127 | 96.81 134 | 97.16 137 | 98.56 139 | 92.20 176 | 94.33 253 | 98.12 205 | 97.34 82 | 98.20 96 | 97.33 199 | 92.81 190 | 99.75 55 | 94.79 151 | 99.81 43 | 99.54 45 |
|
QAPM | | | 95.88 179 | 95.57 184 | 96.80 156 | 97.90 221 | 91.84 188 | 98.18 41 | 98.73 114 | 88.41 288 | 96.42 206 | 98.13 126 | 94.73 124 | 99.75 55 | 88.72 279 | 98.94 210 | 98.81 191 |
|
v13 | | | 98.02 44 | 98.52 27 | 96.51 175 | 99.02 88 | 90.14 210 | 98.07 46 | 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 24 |
|
HPM-MVS_fast | | | 98.32 30 | 98.13 44 | 98.88 22 | 99.54 22 | 97.48 27 | 98.35 28 | 99.03 50 | 95.88 129 | 97.88 135 | 98.22 114 | 98.15 12 | 99.74 60 | 96.50 84 | 99.62 79 | 99.42 87 |
|
lessismore_v0 | | | | | 97.05 144 | 99.36 44 | 92.12 178 | | 84.07 366 | | 98.77 52 | 98.98 50 | 85.36 280 | 99.74 60 | 97.34 62 | 99.37 151 | 99.30 111 |
|
APD-MVS | ![Method available under an open source license with copyleft or other restrictive terms. copyleft](img/icon_copyleft.png) | | 97.00 114 | 96.53 150 | 98.41 53 | 98.55 140 | 96.31 59 | 96.32 145 | 98.77 107 | 92.96 239 | 97.44 160 | 97.58 180 | 95.84 87 | 99.74 60 | 91.96 212 | 99.35 158 | 99.19 128 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
IterMVS-LS | | | 96.92 125 | 97.29 96 | 95.79 223 | 98.51 147 | 88.13 263 | 95.10 221 | 98.66 133 | 96.99 86 | 98.46 73 | 98.68 71 | 92.55 199 | 99.74 60 | 96.91 76 | 99.79 47 | 99.50 51 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
MVS_0304 | | | 96.22 166 | 95.94 176 | 97.04 145 | 97.07 289 | 92.54 166 | 94.19 262 | 99.04 45 | 95.17 161 | 93.74 296 | 96.92 220 | 91.77 222 | 99.73 65 | 95.76 108 | 99.81 43 | 98.85 189 |
|
v12 | | | 97.97 47 | 98.47 28 | 96.46 179 | 98.98 92 | 90.01 214 | 97.97 51 | 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 27 |
|
GBi-Net | | | 96.99 115 | 96.80 135 | 97.56 106 | 97.96 216 | 93.67 145 | 98.23 34 | 98.66 133 | 95.59 142 | 97.99 118 | 99.19 32 | 89.51 251 | 99.73 65 | 94.60 158 | 99.44 132 | 99.30 111 |
|
test1 | | | 96.99 115 | 96.80 135 | 97.56 106 | 97.96 216 | 93.67 145 | 98.23 34 | 98.66 133 | 95.59 142 | 97.99 118 | 99.19 32 | 89.51 251 | 99.73 65 | 94.60 158 | 99.44 132 | 99.30 111 |
|
FMVSNet1 | | | 97.95 51 | 98.08 46 | 97.56 106 | 99.14 75 | 93.67 145 | 98.23 34 | 98.66 133 | 97.41 80 | 99.00 41 | 99.19 32 | 95.47 106 | 99.73 65 | 95.83 106 | 99.76 50 | 99.30 111 |
|
3Dnovator | | 96.53 2 | 97.61 84 | 97.64 73 | 97.50 114 | 97.74 245 | 93.65 149 | 98.49 22 | 98.88 80 | 96.86 93 | 97.11 172 | 98.55 81 | 95.82 90 | 99.73 65 | 95.94 103 | 99.42 142 | 99.13 138 |
|
TSAR-MVS + MP. | | | 97.42 96 | 97.23 105 | 98.00 80 | 99.38 42 | 95.00 99 | 97.63 74 | 98.20 194 | 93.00 233 | 98.16 99 | 98.06 136 | 95.89 85 | 99.72 71 | 95.67 110 | 99.10 193 | 99.28 118 |
|
xiu_mvs_v1_base_debu | | | 95.62 184 | 95.96 173 | 94.60 267 | 98.01 209 | 88.42 255 | 93.99 273 | 98.21 191 | 92.98 234 | 95.91 231 | 94.53 302 | 96.39 74 | 99.72 71 | 95.43 124 | 98.19 259 | 95.64 333 |
|
ACMMP_Plus | | | 97.89 60 | 97.63 75 | 98.67 38 | 99.35 45 | 96.84 43 | 96.36 142 | 98.79 102 | 95.07 169 | 97.88 135 | 98.35 96 | 97.24 39 | 99.72 71 | 96.05 96 | 99.58 91 | 99.45 72 |
|
xiu_mvs_v1_base | | | 95.62 184 | 95.96 173 | 94.60 267 | 98.01 209 | 88.42 255 | 93.99 273 | 98.21 191 | 92.98 234 | 95.91 231 | 94.53 302 | 96.39 74 | 99.72 71 | 95.43 124 | 98.19 259 | 95.64 333 |
|
Anonymous20231211 | | | 98.55 20 | 98.76 15 | 97.94 83 | 98.79 105 | 94.37 120 | 98.84 9 | 99.15 18 | 99.37 2 | 99.67 6 | 99.43 10 | 95.61 101 | 99.72 71 | 98.12 30 | 99.86 37 | 99.73 15 |
|
xiu_mvs_v1_base_debi | | | 95.62 184 | 95.96 173 | 94.60 267 | 98.01 209 | 88.42 255 | 93.99 273 | 98.21 191 | 92.98 234 | 95.91 231 | 94.53 302 | 96.39 74 | 99.72 71 | 95.43 124 | 98.19 259 | 95.64 333 |
|
XVS | | | 97.96 48 | 97.63 75 | 98.94 15 | 99.15 67 | 97.66 16 | 97.77 63 | 98.83 96 | 97.42 73 | 96.32 214 | 97.64 174 | 96.49 71 | 99.72 71 | 95.66 112 | 99.37 151 | 99.45 72 |
|
X-MVStestdata | | | 92.86 267 | 90.83 302 | 98.94 15 | 99.15 67 | 97.66 16 | 97.77 63 | 98.83 96 | 97.42 73 | 96.32 214 | 36.50 366 | 96.49 71 | 99.72 71 | 95.66 112 | 99.37 151 | 99.45 72 |
|
v11 | | | 97.82 68 | 98.36 34 | 96.17 200 | 98.93 94 | 89.16 239 | 97.79 62 | 99.08 30 | 97.64 62 | 99.19 30 | 99.32 22 | 94.28 146 | 99.72 71 | 99.07 6 | 99.97 8 | 99.63 29 |
|
v10 | | | 97.55 88 | 97.97 52 | 96.31 188 | 98.60 133 | 89.64 219 | 97.44 87 | 99.02 51 | 96.60 98 | 98.72 55 | 99.16 39 | 93.48 172 | 99.72 71 | 98.76 15 | 99.92 23 | 99.58 36 |
|
V9 | | | 97.90 59 | 98.40 32 | 96.40 183 | 98.93 94 | 89.86 216 | 97.86 58 | 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 29 |
|
CANet | | | 95.86 180 | 95.65 182 | 96.49 177 | 96.41 309 | 90.82 202 | 94.36 252 | 98.41 165 | 94.94 171 | 92.62 328 | 96.73 234 | 92.68 194 | 99.71 82 | 95.12 140 | 99.60 87 | 98.94 168 |
|
mvs-test1 | | | 96.20 167 | 95.50 186 | 98.32 61 | 96.90 298 | 98.16 4 | 95.07 226 | 98.09 207 | 95.86 130 | 93.63 301 | 94.32 312 | 94.26 148 | 99.71 82 | 94.06 176 | 97.27 311 | 97.07 297 |
|
xiu_mvs_v2_base | | | 94.22 237 | 94.63 214 | 92.99 312 | 97.32 279 | 84.84 313 | 92.12 321 | 97.84 222 | 91.96 255 | 94.17 279 | 93.43 317 | 96.07 82 | 99.71 82 | 91.27 227 | 97.48 301 | 94.42 343 |
|
PS-MVSNAJ | | | 94.10 244 | 94.47 222 | 93.00 311 | 97.35 274 | 84.88 312 | 91.86 325 | 97.84 222 | 91.96 255 | 94.17 279 | 92.50 334 | 95.82 90 | 99.71 82 | 91.27 227 | 97.48 301 | 94.40 344 |
|
Regformer-4 | | | 97.53 91 | 97.47 89 | 97.71 95 | 97.35 274 | 93.91 136 | 95.26 214 | 98.14 203 | 97.97 45 | 98.34 82 | 97.89 154 | 95.49 104 | 99.71 82 | 97.41 60 | 99.42 142 | 99.51 50 |
|
v1240 | | | 96.74 141 | 97.02 122 | 95.91 219 | 98.18 191 | 88.52 254 | 95.39 203 | 98.88 80 | 93.15 230 | 98.46 73 | 98.40 92 | 92.80 191 | 99.71 82 | 98.45 25 | 99.49 120 | 99.49 59 |
|
V14 | | | 97.83 65 | 98.33 36 | 96.35 184 | 98.88 100 | 89.72 217 | 97.75 66 | 99.05 38 | 97.74 52 | 99.01 39 | 99.27 25 | 94.35 143 | 99.71 82 | 98.95 9 | 99.97 8 | 99.62 31 |
|
IS-MVSNet | | | 96.93 123 | 96.68 140 | 97.70 97 | 99.25 53 | 94.00 134 | 98.57 17 | 96.74 273 | 98.36 31 | 98.14 102 | 97.98 144 | 88.23 261 | 99.71 82 | 93.10 201 | 99.72 59 | 99.38 98 |
|
Fast-Effi-MVS+ | | | 95.49 190 | 95.07 197 | 96.75 160 | 97.67 253 | 92.82 163 | 94.22 260 | 98.60 143 | 91.61 260 | 93.42 312 | 92.90 327 | 96.73 61 | 99.70 90 | 92.60 205 | 97.89 274 | 97.74 276 |
|
v144192 | | | 96.69 147 | 96.90 128 | 96.03 211 | 98.25 179 | 88.92 245 | 95.49 193 | 98.77 107 | 93.05 232 | 98.09 108 | 98.29 105 | 92.51 203 | 99.70 90 | 98.11 31 | 99.56 97 | 99.47 65 |
|
v1921920 | | | 96.72 144 | 96.96 125 | 95.99 212 | 98.21 184 | 88.79 251 | 95.42 200 | 98.79 102 | 93.22 224 | 98.19 97 | 98.26 109 | 92.68 194 | 99.70 90 | 98.34 27 | 99.55 101 | 99.49 59 |
|
HFP-MVS | | | 97.94 53 | 97.64 73 | 98.83 24 | 99.15 67 | 97.50 25 | 97.59 79 | 98.84 88 | 96.05 119 | 97.49 153 | 97.54 181 | 97.07 44 | 99.70 90 | 95.61 116 | 99.46 127 | 99.30 111 |
|
#test# | | | 97.62 83 | 97.22 106 | 98.83 24 | 99.15 67 | 97.50 25 | 96.81 124 | 98.84 88 | 94.25 196 | 97.49 153 | 97.54 181 | 97.07 44 | 99.70 90 | 94.37 166 | 99.46 127 | 99.30 111 |
|
HPM-MVS++ | ![Method available under an open source license with copyleft or other restrictive terms. copyleft](img/icon_copyleft.png) | | 96.99 115 | 96.38 156 | 98.81 26 | 98.64 126 | 97.59 20 | 95.97 165 | 98.20 194 | 95.51 145 | 95.06 251 | 96.53 245 | 94.10 154 | 99.70 90 | 94.29 170 | 99.15 185 | 99.13 138 |
|
v15 | | | 97.77 72 | 98.26 40 | 96.30 189 | 98.81 103 | 89.59 224 | 97.62 75 | 99.04 45 | 97.59 64 | 98.97 43 | 99.24 27 | 94.19 151 | 99.70 90 | 98.88 11 | 99.97 8 | 99.61 33 |
|
LPG-MVS_test | | | 97.94 53 | 97.67 69 | 98.74 32 | 99.15 67 | 97.02 38 | 97.09 109 | 99.02 51 | 95.15 162 | 98.34 82 | 98.23 111 | 97.91 18 | 99.70 90 | 94.41 163 | 99.73 56 | 99.50 51 |
|
LGP-MVS_train | | | | | 98.74 32 | 99.15 67 | 97.02 38 | | 99.02 51 | 95.15 162 | 98.34 82 | 98.23 111 | 97.91 18 | 99.70 90 | 94.41 163 | 99.73 56 | 99.50 51 |
|
tfpnnormal | | | 97.72 75 | 97.97 52 | 96.94 150 | 99.26 50 | 92.23 173 | 97.83 61 | 98.45 156 | 98.25 35 | 99.13 33 | 98.66 72 | 96.65 62 | 99.69 99 | 93.92 184 | 99.62 79 | 98.91 176 |
|
Fast-Effi-MVS+-dtu | | | 96.44 159 | 96.12 164 | 97.39 128 | 97.18 285 | 94.39 118 | 95.46 194 | 98.73 114 | 96.03 122 | 94.72 260 | 94.92 298 | 96.28 80 | 99.69 99 | 93.81 187 | 97.98 266 | 98.09 253 |
|
EI-MVSNet-UG-set | | | 97.32 105 | 97.40 90 | 97.09 142 | 97.34 277 | 92.01 183 | 95.33 208 | 97.65 237 | 97.74 52 | 98.30 89 | 98.14 125 | 95.04 119 | 99.69 99 | 97.55 53 | 99.52 110 | 99.58 36 |
|
Regformer-2 | | | 97.41 97 | 97.24 101 | 97.93 84 | 97.21 283 | 94.72 108 | 94.85 238 | 98.27 186 | 97.74 52 | 98.11 104 | 97.50 186 | 95.58 102 | 99.69 99 | 96.57 81 | 99.31 169 | 99.37 103 |
|
test_0402 | | | 97.84 64 | 97.97 52 | 97.47 119 | 99.19 62 | 94.07 131 | 96.71 129 | 98.73 114 | 98.66 23 | 98.56 64 | 98.41 90 | 96.84 55 | 99.69 99 | 94.82 148 | 99.81 43 | 98.64 206 |
|
wuykxyi23d | | | 98.68 16 | 98.53 26 | 99.13 3 | 99.44 33 | 97.97 7 | 96.85 122 | 99.02 51 | 95.81 134 | 99.88 2 | 99.38 13 | 98.14 13 | 99.69 99 | 98.32 28 | 99.95 13 | 99.73 15 |
|
SMA-MVS | | | 97.48 93 | 97.11 115 | 98.60 42 | 98.83 102 | 96.67 48 | 96.74 126 | 98.73 114 | 91.61 260 | 98.48 70 | 98.36 95 | 96.53 67 | 99.68 105 | 95.17 134 | 99.54 103 | 99.45 72 |
|
pmmvs6 | | | 99.07 3 | 99.24 3 | 98.56 45 | 99.81 2 | 96.38 57 | 98.87 8 | 99.30 8 | 99.01 15 | 99.63 9 | 99.66 3 | 99.27 2 | 99.68 105 | 97.75 44 | 99.89 32 | 99.62 31 |
|
EI-MVSNet-Vis-set | | | 97.32 105 | 97.39 91 | 97.11 140 | 97.36 273 | 92.08 180 | 95.34 207 | 97.65 237 | 97.74 52 | 98.29 90 | 98.11 129 | 95.05 117 | 99.68 105 | 97.50 56 | 99.50 113 | 99.56 41 |
|
v17 | | | 97.70 77 | 98.17 42 | 96.28 192 | 98.77 108 | 89.59 224 | 97.62 75 | 99.01 60 | 97.54 67 | 98.72 55 | 99.18 35 | 94.06 155 | 99.68 105 | 98.74 16 | 99.92 23 | 99.58 36 |
|
v16 | | | 97.69 78 | 98.16 43 | 96.29 191 | 98.75 109 | 89.60 222 | 97.62 75 | 99.01 60 | 97.53 69 | 98.69 57 | 99.18 35 | 94.05 156 | 99.68 105 | 98.73 17 | 99.88 33 | 99.58 36 |
|
v8 | | | 97.60 85 | 98.06 48 | 96.23 193 | 98.71 116 | 89.44 230 | 97.43 89 | 98.82 100 | 97.29 85 | 98.74 53 | 99.10 44 | 93.86 159 | 99.68 105 | 98.61 22 | 99.94 19 | 99.56 41 |
|
VPNet | | | 97.26 108 | 97.49 87 | 96.59 170 | 99.47 30 | 90.58 206 | 96.27 146 | 98.53 149 | 97.77 50 | 98.46 73 | 98.41 90 | 94.59 133 | 99.68 105 | 94.61 157 | 99.29 173 | 99.52 48 |
|
v1192 | | | 96.83 135 | 97.06 120 | 96.15 201 | 98.28 168 | 89.29 236 | 95.36 205 | 98.77 107 | 93.73 215 | 98.11 104 | 98.34 97 | 93.02 188 | 99.67 112 | 98.35 26 | 99.58 91 | 99.50 51 |
|
v18 | | | 97.60 85 | 98.06 48 | 96.23 193 | 98.68 125 | 89.46 229 | 97.48 86 | 98.98 68 | 97.33 83 | 98.60 61 | 99.13 42 | 93.86 159 | 99.67 112 | 98.62 21 | 99.87 35 | 99.56 41 |
|
CPTT-MVS | | | 96.69 147 | 96.08 167 | 98.49 48 | 98.89 99 | 96.64 50 | 97.25 94 | 98.77 107 | 92.89 240 | 96.01 229 | 97.13 206 | 92.23 208 | 99.67 112 | 92.24 210 | 99.34 161 | 99.17 131 |
|
FMVSNet5 | | | 93.39 260 | 92.35 267 | 96.50 176 | 95.83 324 | 90.81 204 | 97.31 91 | 98.27 186 | 92.74 242 | 96.27 218 | 98.28 106 | 62.23 362 | 99.67 112 | 90.86 236 | 99.36 154 | 99.03 157 |
|
OpenMVS | ![Method available under an open source license with copyleft or other restrictive terms. copyleft](img/icon_copyleft.png) | 94.22 8 | 95.48 192 | 95.20 193 | 96.32 187 | 97.16 286 | 91.96 184 | 97.74 68 | 98.84 88 | 87.26 301 | 94.36 276 | 98.01 141 | 93.95 158 | 99.67 112 | 90.70 246 | 98.75 226 | 97.35 294 |
|
CSCG | | | 97.40 98 | 97.30 95 | 97.69 99 | 98.95 93 | 94.83 104 | 97.28 93 | 98.99 65 | 96.35 109 | 98.13 103 | 95.95 275 | 95.99 83 | 99.66 117 | 94.36 169 | 99.73 56 | 98.59 211 |
|
v1144 | | | 96.84 132 | 97.08 118 | 96.13 205 | 98.42 157 | 89.28 237 | 95.41 202 | 98.67 130 | 94.21 198 | 97.97 122 | 98.31 101 | 93.06 183 | 99.65 118 | 98.06 33 | 99.62 79 | 99.45 72 |
|
jason | | | 94.39 234 | 94.04 237 | 95.41 241 | 98.29 165 | 87.85 274 | 92.74 311 | 96.75 272 | 85.38 324 | 95.29 247 | 96.15 264 | 88.21 262 | 99.65 118 | 94.24 172 | 99.34 161 | 98.74 199 |
jason: jason. |
FMVSNet2 | | | 96.72 144 | 96.67 141 | 96.87 155 | 97.96 216 | 91.88 186 | 97.15 100 | 98.06 212 | 95.59 142 | 98.50 69 | 98.62 76 | 89.51 251 | 99.65 118 | 94.99 145 | 99.60 87 | 99.07 153 |
|
v7 | | | 96.93 123 | 97.17 109 | 96.23 193 | 98.59 135 | 89.64 219 | 95.96 169 | 98.66 133 | 94.41 189 | 97.87 140 | 98.38 93 | 93.47 173 | 99.64 121 | 97.93 36 | 99.24 178 | 99.43 85 |
|
EPNet | | | 93.72 252 | 92.62 264 | 97.03 147 | 87.61 370 | 92.25 172 | 96.27 146 | 91.28 332 | 96.74 96 | 87.65 358 | 97.39 195 | 85.00 283 | 99.64 121 | 92.14 211 | 99.48 123 | 99.20 127 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
1112_ss | | | 94.12 243 | 93.42 248 | 96.23 193 | 98.59 135 | 90.85 200 | 94.24 258 | 98.85 85 | 85.49 319 | 92.97 319 | 94.94 296 | 86.01 277 | 99.64 121 | 91.78 218 | 97.92 271 | 98.20 249 |
|
Regformer-1 | | | 97.27 107 | 97.16 110 | 97.61 104 | 97.21 283 | 93.86 138 | 94.85 238 | 98.04 214 | 97.62 63 | 98.03 116 | 97.50 186 | 95.34 110 | 99.63 124 | 96.52 82 | 99.31 169 | 99.35 105 |
|
v2v482 | | | 96.78 140 | 97.06 120 | 95.95 216 | 98.57 138 | 88.77 252 | 95.36 205 | 98.26 188 | 95.18 160 | 97.85 142 | 98.23 111 | 92.58 198 | 99.63 124 | 97.80 41 | 99.69 67 | 99.45 72 |
|
lupinMVS | | | 93.77 250 | 93.28 250 | 95.24 244 | 97.68 250 | 87.81 276 | 92.12 321 | 96.05 279 | 84.52 329 | 94.48 274 | 95.06 294 | 86.90 273 | 99.63 124 | 93.62 192 | 99.13 188 | 98.27 242 |
|
FMVSNet3 | | | 95.26 206 | 94.94 201 | 96.22 197 | 96.53 305 | 90.06 211 | 95.99 163 | 97.66 235 | 94.11 202 | 97.99 118 | 97.91 153 | 80.22 299 | 99.63 124 | 94.60 158 | 99.44 132 | 98.96 165 |
|
ACMP | | 92.54 13 | 97.47 94 | 97.10 116 | 98.55 46 | 99.04 85 | 96.70 47 | 96.24 150 | 98.89 78 | 93.71 216 | 97.97 122 | 97.75 166 | 97.44 28 | 99.63 124 | 93.22 198 | 99.70 66 | 99.32 107 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
LS3D | | | 97.77 72 | 97.50 86 | 98.57 44 | 96.24 311 | 97.58 21 | 98.45 25 | 98.85 85 | 98.58 25 | 97.51 151 | 97.94 149 | 95.74 98 | 99.63 124 | 95.19 132 | 98.97 205 | 98.51 218 |
|
v1141 | | | 96.86 129 | 97.14 112 | 96.04 208 | 98.55 140 | 89.06 242 | 95.44 195 | 98.33 176 | 95.14 164 | 97.93 128 | 98.19 116 | 93.36 176 | 99.62 130 | 97.61 48 | 99.69 67 | 99.44 81 |
|
VDDNet | | | 96.98 118 | 96.84 131 | 97.41 126 | 99.40 40 | 93.26 158 | 97.94 53 | 95.31 295 | 99.26 6 | 98.39 77 | 99.18 35 | 87.85 267 | 99.62 130 | 95.13 139 | 99.09 194 | 99.35 105 |
|
V42 | | | 97.04 113 | 97.16 110 | 96.68 165 | 98.59 135 | 91.05 197 | 96.33 144 | 98.36 171 | 94.60 181 | 97.99 118 | 98.30 104 | 93.32 178 | 99.62 130 | 97.40 61 | 99.53 106 | 99.38 98 |
|
DeepC-MVS | | 95.41 4 | 97.82 68 | 97.70 66 | 98.16 70 | 98.78 107 | 95.72 74 | 96.23 151 | 99.02 51 | 93.92 206 | 98.62 58 | 98.99 49 | 97.69 22 | 99.62 130 | 96.18 92 | 99.87 35 | 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 |
3Dnovator+ | | 96.13 3 | 97.73 74 | 97.59 79 | 98.15 71 | 98.11 202 | 95.60 79 | 98.04 48 | 98.70 124 | 98.13 39 | 96.93 186 | 98.45 88 | 95.30 113 | 99.62 130 | 95.64 114 | 98.96 206 | 99.24 123 |
|
ACMM | | 93.33 11 | 98.05 42 | 97.79 60 | 98.85 23 | 99.15 67 | 97.55 23 | 96.68 130 | 98.83 96 | 95.21 157 | 98.36 80 | 98.13 126 | 98.13 15 | 99.62 130 | 96.04 97 | 99.54 103 | 99.39 96 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
Anonymous20240529 | | | 97.96 48 | 98.04 50 | 97.71 95 | 98.69 123 | 94.28 125 | 97.86 58 | 98.31 185 | 98.79 20 | 99.23 28 | 98.86 59 | 95.76 97 | 99.61 136 | 95.49 120 | 99.36 154 | 99.23 124 |
|
nrg030 | | | 98.54 21 | 98.62 23 | 98.32 61 | 99.22 56 | 95.66 78 | 97.90 56 | 99.08 30 | 98.31 33 | 99.02 38 | 98.74 66 | 97.68 23 | 99.61 136 | 97.77 43 | 99.85 39 | 99.70 19 |
|
v1neww | | | 96.97 119 | 97.24 101 | 96.15 201 | 98.70 119 | 89.44 230 | 95.97 165 | 98.33 176 | 95.25 154 | 97.88 135 | 98.15 122 | 93.83 162 | 99.61 136 | 97.50 56 | 99.50 113 | 99.41 90 |
|
v7new | | | 96.97 119 | 97.24 101 | 96.15 201 | 98.70 119 | 89.44 230 | 95.97 165 | 98.33 176 | 95.25 154 | 97.88 135 | 98.15 122 | 93.83 162 | 99.61 136 | 97.50 56 | 99.50 113 | 99.41 90 |
|
divwei89l23v2f112 | | | 96.86 129 | 97.14 112 | 96.04 208 | 98.54 143 | 89.06 242 | 95.44 195 | 98.33 176 | 95.14 164 | 97.93 128 | 98.19 116 | 93.36 176 | 99.61 136 | 97.61 48 | 99.68 71 | 99.44 81 |
|
v6 | | | 96.97 119 | 97.24 101 | 96.15 201 | 98.71 116 | 89.44 230 | 95.97 165 | 98.33 176 | 95.25 154 | 97.89 133 | 98.15 122 | 93.86 159 | 99.61 136 | 97.51 55 | 99.50 113 | 99.42 87 |
|
v1 | | | 96.86 129 | 97.14 112 | 96.04 208 | 98.55 140 | 89.06 242 | 95.44 195 | 98.33 176 | 95.14 164 | 97.94 125 | 98.18 120 | 93.39 175 | 99.61 136 | 97.61 48 | 99.69 67 | 99.44 81 |
|
view600 | | | 92.56 272 | 92.11 271 | 93.91 286 | 98.45 153 | 84.76 315 | 97.10 105 | 90.23 344 | 97.42 73 | 96.98 179 | 94.48 305 | 73.62 328 | 99.60 143 | 82.49 335 | 98.28 253 | 97.36 288 |
|
view800 | | | 92.56 272 | 92.11 271 | 93.91 286 | 98.45 153 | 84.76 315 | 97.10 105 | 90.23 344 | 97.42 73 | 96.98 179 | 94.48 305 | 73.62 328 | 99.60 143 | 82.49 335 | 98.28 253 | 97.36 288 |
|
conf0.05thres1000 | | | 92.56 272 | 92.11 271 | 93.91 286 | 98.45 153 | 84.76 315 | 97.10 105 | 90.23 344 | 97.42 73 | 96.98 179 | 94.48 305 | 73.62 328 | 99.60 143 | 82.49 335 | 98.28 253 | 97.36 288 |
|
tfpn | | | 92.56 272 | 92.11 271 | 93.91 286 | 98.45 153 | 84.76 315 | 97.10 105 | 90.23 344 | 97.42 73 | 96.98 179 | 94.48 305 | 73.62 328 | 99.60 143 | 82.49 335 | 98.28 253 | 97.36 288 |
|
IB-MVS | | 85.98 20 | 88.63 324 | 86.95 333 | 93.68 294 | 95.12 335 | 84.82 314 | 90.85 336 | 90.17 348 | 87.55 300 | 88.48 355 | 91.34 349 | 58.01 364 | 99.59 147 | 87.24 305 | 93.80 343 | 96.63 316 |
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 |
TDRefinement | | | 98.90 4 | 98.86 10 | 99.02 8 | 99.54 22 | 98.06 6 | 99.34 4 | 99.44 6 | 98.85 19 | 99.00 41 | 99.20 31 | 97.42 30 | 99.59 147 | 97.21 65 | 99.76 50 | 99.40 93 |
|
thisisatest0515 | | | 90.43 310 | 89.18 321 | 94.17 280 | 97.07 289 | 85.44 303 | 89.75 349 | 87.58 360 | 88.28 292 | 93.69 299 | 91.72 341 | 65.27 359 | 99.58 149 | 90.59 249 | 98.67 235 | 97.50 285 |
|
VDD-MVS | | | 97.37 100 | 97.25 99 | 97.74 94 | 98.69 123 | 94.50 116 | 97.04 112 | 95.61 291 | 98.59 24 | 98.51 67 | 98.72 67 | 92.54 201 | 99.58 149 | 96.02 99 | 99.49 120 | 99.12 143 |
|
EI-MVSNet | | | 96.63 150 | 96.93 126 | 95.74 224 | 97.26 281 | 88.13 263 | 95.29 212 | 97.65 237 | 96.99 86 | 97.94 125 | 98.19 116 | 92.55 199 | 99.58 149 | 96.91 76 | 99.56 97 | 99.50 51 |
|
DELS-MVS | | | 96.17 169 | 96.23 162 | 95.99 212 | 97.55 261 | 90.04 212 | 92.38 318 | 98.52 150 | 94.13 201 | 96.55 203 | 97.06 210 | 94.99 120 | 99.58 149 | 95.62 115 | 99.28 174 | 98.37 229 |
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 |
MVSTER | | | 94.21 240 | 93.93 242 | 95.05 252 | 95.83 324 | 86.46 296 | 95.18 219 | 97.65 237 | 92.41 248 | 97.94 125 | 98.00 143 | 72.39 338 | 99.58 149 | 96.36 88 | 99.56 97 | 99.12 143 |
|
IterMVS | | | 95.42 197 | 95.83 177 | 94.20 279 | 97.52 262 | 83.78 328 | 92.41 317 | 97.47 250 | 95.49 146 | 98.06 113 | 98.49 85 | 87.94 263 | 99.58 149 | 96.02 99 | 99.02 202 | 99.23 124 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
CANet_DTU | | | 94.65 225 | 94.21 232 | 95.96 214 | 95.90 322 | 89.68 218 | 93.92 277 | 97.83 224 | 93.19 225 | 90.12 348 | 95.64 282 | 88.52 258 | 99.57 155 | 93.27 197 | 99.47 125 | 98.62 209 |
|
Effi-MVS+ | | | 96.19 168 | 96.01 169 | 96.71 162 | 97.43 270 | 92.19 177 | 96.12 156 | 99.10 25 | 95.45 147 | 93.33 315 | 94.71 300 | 97.23 40 | 99.56 156 | 93.21 199 | 97.54 298 | 98.37 229 |
|
Regformer-3 | | | 97.25 109 | 97.29 96 | 97.11 140 | 97.35 274 | 92.32 171 | 95.26 214 | 97.62 242 | 97.67 61 | 98.17 98 | 97.89 154 | 95.05 117 | 99.56 156 | 97.16 69 | 99.42 142 | 99.46 67 |
|
XVG-ACMP-BASELINE | | | 97.58 87 | 97.28 98 | 98.49 48 | 99.16 64 | 96.90 42 | 96.39 137 | 98.98 68 | 95.05 170 | 98.06 113 | 98.02 140 | 95.86 86 | 99.56 156 | 94.37 166 | 99.64 77 | 99.00 160 |
|
Test_1112_low_res | | | 93.53 258 | 92.86 258 | 95.54 236 | 98.60 133 | 88.86 248 | 92.75 309 | 98.69 125 | 82.66 337 | 92.65 326 | 96.92 220 | 84.75 284 | 99.56 156 | 90.94 234 | 97.76 277 | 98.19 250 |
|
TransMVSNet (Re) | | | 98.38 28 | 98.67 19 | 97.51 111 | 99.51 25 | 93.39 156 | 98.20 39 | 98.87 82 | 98.23 36 | 99.48 12 | 99.27 25 | 98.47 8 | 99.55 160 | 96.52 82 | 99.53 106 | 99.60 34 |
|
Baseline_NR-MVSNet | | | 97.72 75 | 97.79 60 | 97.50 114 | 99.56 18 | 93.29 157 | 95.44 195 | 98.86 84 | 98.20 38 | 98.37 78 | 99.24 27 | 94.69 127 | 99.55 160 | 95.98 102 | 99.79 47 | 99.65 24 |
|
testing_2 | | | 97.43 95 | 97.71 65 | 96.60 167 | 98.91 97 | 90.85 200 | 96.01 162 | 98.54 148 | 94.78 177 | 98.78 49 | 98.96 52 | 96.35 77 | 99.54 162 | 97.25 63 | 99.82 42 | 99.40 93 |
|
VNet | | | 96.84 132 | 96.83 133 | 96.88 154 | 98.06 204 | 92.02 181 | 96.35 143 | 97.57 244 | 97.70 58 | 97.88 135 | 97.80 162 | 92.40 206 | 99.54 162 | 94.73 156 | 98.96 206 | 99.08 151 |
|
Anonymous202405211 | | | 96.34 163 | 95.98 172 | 97.43 124 | 98.25 179 | 93.85 139 | 96.74 126 | 94.41 302 | 97.72 56 | 98.37 78 | 98.03 139 | 87.15 272 | 99.53 164 | 94.06 176 | 99.07 197 | 98.92 175 |
|
agg_prior1 | | | 95.39 198 | 94.60 216 | 97.75 93 | 97.80 234 | 94.96 101 | 93.39 296 | 98.36 171 | 87.20 303 | 93.49 307 | 95.97 273 | 94.65 131 | 99.53 164 | 91.69 222 | 98.86 219 | 98.77 197 |
|
agg_prior | | | | | | 97.80 234 | 94.96 101 | | 98.36 171 | | 93.49 307 | | | 99.53 164 | | | |
|
UGNet | | | 96.81 138 | 96.56 146 | 97.58 105 | 96.64 302 | 93.84 140 | 97.75 66 | 97.12 260 | 96.47 105 | 93.62 302 | 98.88 58 | 93.22 181 | 99.53 164 | 95.61 116 | 99.69 67 | 99.36 104 |
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 |
conf0.01 | | | 91.90 288 | 90.98 293 | 94.67 263 | 98.27 170 | 88.03 265 | 96.98 115 | 88.58 352 | 93.90 207 | 94.64 263 | 91.45 342 | 69.62 347 | 99.52 168 | 87.62 294 | 97.74 278 | 96.46 319 |
|
conf0.002 | | | 91.90 288 | 90.98 293 | 94.67 263 | 98.27 170 | 88.03 265 | 96.98 115 | 88.58 352 | 93.90 207 | 94.64 263 | 91.45 342 | 69.62 347 | 99.52 168 | 87.62 294 | 97.74 278 | 96.46 319 |
|
thresconf0.02 | | | 91.72 295 | 90.98 293 | 93.97 282 | 98.27 170 | 88.03 265 | 96.98 115 | 88.58 352 | 93.90 207 | 94.64 263 | 91.45 342 | 69.62 347 | 99.52 168 | 87.62 294 | 97.74 278 | 94.35 345 |
|
tfpn_n400 | | | 91.72 295 | 90.98 293 | 93.97 282 | 98.27 170 | 88.03 265 | 96.98 115 | 88.58 352 | 93.90 207 | 94.64 263 | 91.45 342 | 69.62 347 | 99.52 168 | 87.62 294 | 97.74 278 | 94.35 345 |
|
tfpnconf | | | 91.72 295 | 90.98 293 | 93.97 282 | 98.27 170 | 88.03 265 | 96.98 115 | 88.58 352 | 93.90 207 | 94.64 263 | 91.45 342 | 69.62 347 | 99.52 168 | 87.62 294 | 97.74 278 | 94.35 345 |
|
tfpnview11 | | | 91.72 295 | 90.98 293 | 93.97 282 | 98.27 170 | 88.03 265 | 96.98 115 | 88.58 352 | 93.90 207 | 94.64 263 | 91.45 342 | 69.62 347 | 99.52 168 | 87.62 294 | 97.74 278 | 94.35 345 |
|
TEST9 | | | | | | 97.84 227 | 95.23 90 | 93.62 288 | 98.39 167 | 86.81 307 | 93.78 293 | 95.99 270 | 94.68 129 | 99.52 168 | | | |
|
train_agg | | | 95.46 194 | 94.66 212 | 97.88 86 | 97.84 227 | 95.23 90 | 93.62 288 | 98.39 167 | 87.04 305 | 93.78 293 | 95.99 270 | 94.58 134 | 99.52 168 | 91.76 219 | 98.90 212 | 98.89 180 |
|
test_8 | | | | | | 97.81 230 | 95.07 98 | 93.54 291 | 98.38 169 | 87.04 305 | 93.71 297 | 95.96 274 | 94.58 134 | 99.52 168 | | | |
|
LTVRE_ROB | | 96.88 1 | 99.18 2 | 99.34 2 | 98.72 35 | 99.71 6 | 96.99 40 | 99.69 2 | 99.57 3 | 99.02 14 | 99.62 10 | 99.36 16 | 98.53 7 | 99.52 168 | 98.58 24 | 99.95 13 | 99.66 23 |
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 |
tfpn111 | | | 91.92 287 | 91.39 282 | 93.49 298 | 98.21 184 | 84.50 320 | 96.39 137 | 90.39 339 | 96.87 90 | 96.33 210 | 93.08 322 | 73.44 334 | 99.51 178 | 79.87 343 | 97.94 270 | 96.46 319 |
|
new-patchmatchnet | | | 95.67 183 | 96.58 144 | 92.94 313 | 97.48 264 | 80.21 340 | 92.96 305 | 98.19 198 | 94.83 175 | 98.82 47 | 98.79 61 | 93.31 179 | 99.51 178 | 95.83 106 | 99.04 201 | 99.12 143 |
|
agg_prior3 | | | 95.30 203 | 94.46 225 | 97.80 91 | 97.80 234 | 95.00 99 | 93.63 287 | 98.34 175 | 86.33 311 | 93.40 314 | 95.84 277 | 94.15 153 | 99.50 180 | 91.76 219 | 98.90 212 | 98.89 180 |
|
pm-mvs1 | | | 98.47 24 | 98.67 19 | 97.86 87 | 99.52 24 | 94.58 113 | 98.28 31 | 99.00 62 | 97.57 65 | 99.27 26 | 99.22 30 | 98.32 9 | 99.50 180 | 97.09 72 | 99.75 54 | 99.50 51 |
|
casdiffmvs1 | | | 96.82 136 | 96.84 131 | 96.77 158 | 98.01 209 | 92.02 181 | 97.20 98 | 98.67 130 | 92.30 249 | 96.09 226 | 98.64 75 | 93.81 164 | 99.50 180 | 98.22 29 | 98.62 239 | 98.79 193 |
|
thres600view7 | | | 92.03 285 | 91.43 281 | 93.82 291 | 98.19 188 | 84.61 319 | 96.27 146 | 90.39 339 | 96.81 94 | 96.37 209 | 93.11 320 | 73.44 334 | 99.49 183 | 80.32 342 | 97.95 267 | 97.36 288 |
|
ab-mvs | | | 96.59 151 | 96.59 143 | 96.60 167 | 98.64 126 | 92.21 174 | 98.35 28 | 97.67 233 | 94.45 186 | 96.99 178 | 98.79 61 | 94.96 121 | 99.49 183 | 90.39 256 | 99.07 197 | 98.08 254 |
|
DP-MVS | | | 97.87 62 | 97.89 56 | 97.81 90 | 98.62 131 | 94.82 105 | 97.13 103 | 98.79 102 | 98.98 16 | 98.74 53 | 98.49 85 | 95.80 96 | 99.49 183 | 95.04 143 | 99.44 132 | 99.11 146 |
|
LFMVS | | | 95.32 202 | 94.88 205 | 96.62 166 | 98.03 206 | 91.47 194 | 97.65 72 | 90.72 338 | 99.11 8 | 97.89 133 | 98.31 101 | 79.20 301 | 99.48 186 | 93.91 185 | 99.12 191 | 98.93 172 |
|
Vis-MVSNet (Re-imp) | | | 95.11 209 | 94.85 206 | 95.87 221 | 99.12 76 | 89.17 238 | 97.54 84 | 94.92 297 | 96.50 102 | 96.58 197 | 97.27 201 | 83.64 287 | 99.48 186 | 88.42 284 | 99.67 73 | 98.97 164 |
|
tfpn1000 | | | 91.88 291 | 91.20 289 | 93.89 290 | 97.96 216 | 87.13 289 | 97.13 103 | 88.16 359 | 94.41 189 | 94.87 258 | 92.77 329 | 68.34 354 | 99.47 188 | 89.24 270 | 97.95 267 | 95.06 339 |
|
CHOSEN 280x420 | | | 89.98 315 | 89.19 320 | 92.37 321 | 95.60 328 | 81.13 337 | 86.22 357 | 97.09 261 | 81.44 342 | 87.44 359 | 93.15 319 | 73.99 323 | 99.47 188 | 88.69 280 | 99.07 197 | 96.52 318 |
|
testmv | | | 95.51 188 | 95.33 190 | 96.05 207 | 98.23 182 | 89.51 228 | 93.50 293 | 98.63 140 | 94.25 196 | 98.22 94 | 97.73 169 | 92.51 203 | 99.47 188 | 85.22 320 | 99.72 59 | 99.17 131 |
|
CDS-MVSNet | | | 94.88 216 | 94.12 235 | 97.14 139 | 97.64 255 | 93.57 150 | 93.96 276 | 97.06 262 | 90.05 276 | 96.30 217 | 96.55 243 | 86.10 276 | 99.47 188 | 90.10 260 | 99.31 169 | 98.40 225 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
ACMH | | 93.61 9 | 98.44 25 | 98.76 15 | 97.51 111 | 99.43 36 | 93.54 151 | 98.23 34 | 99.05 38 | 97.40 81 | 99.37 19 | 99.08 46 | 98.79 5 | 99.47 188 | 97.74 45 | 99.71 63 | 99.50 51 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
testdata2 | | | | | | | | | | | | | | 99.46 193 | 87.84 289 | | |
|
MDA-MVSNet-bldmvs | | | 95.69 181 | 95.67 181 | 95.74 224 | 98.48 151 | 88.76 253 | 92.84 306 | 97.25 253 | 96.00 123 | 97.59 147 | 97.95 148 | 91.38 228 | 99.46 193 | 93.16 200 | 96.35 324 | 98.99 163 |
|
HQP_MVS | | | 96.66 149 | 96.33 160 | 97.68 100 | 98.70 119 | 94.29 122 | 96.50 134 | 98.75 111 | 96.36 107 | 96.16 224 | 96.77 231 | 91.91 220 | 99.46 193 | 92.59 206 | 99.20 181 | 99.28 118 |
|
plane_prior5 | | | | | | | | | 98.75 111 | | | | | 99.46 193 | 92.59 206 | 99.20 181 | 99.28 118 |
|
æ–°å‡ ä½•1 | | | | | 97.25 136 | 98.29 165 | 94.70 110 | | 97.73 229 | 77.98 355 | 94.83 259 | 96.67 238 | 92.08 213 | 99.45 197 | 88.17 288 | 98.65 237 | 97.61 280 |
|
casdiffmvs | | | 96.43 161 | 96.38 156 | 96.60 167 | 97.51 263 | 91.95 185 | 97.08 111 | 98.41 165 | 93.69 217 | 93.95 290 | 98.34 97 | 93.03 186 | 99.45 197 | 98.09 32 | 97.30 309 | 98.39 227 |
|
NCCC | | | 96.52 155 | 95.99 171 | 98.10 73 | 97.81 230 | 95.68 76 | 95.00 232 | 98.20 194 | 95.39 150 | 95.40 246 | 96.36 256 | 93.81 164 | 99.45 197 | 93.55 193 | 98.42 250 | 99.17 131 |
|
COLMAP_ROB | ![Method available under an open source license with copyleft or other restrictive terms. copyleft](img/icon_copyleft.png) | 94.48 6 | 98.25 34 | 98.11 45 | 98.64 40 | 99.21 59 | 97.35 32 | 97.96 52 | 99.16 15 | 98.34 32 | 98.78 49 | 98.52 83 | 97.32 33 | 99.45 197 | 94.08 175 | 99.67 73 | 99.13 138 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
CDPH-MVS | | | 95.45 196 | 94.65 213 | 97.84 89 | 98.28 168 | 94.96 101 | 93.73 284 | 98.33 176 | 85.03 326 | 95.44 244 | 96.60 241 | 95.31 112 | 99.44 201 | 90.01 261 | 99.13 188 | 99.11 146 |
|
MCST-MVS | | | 96.24 165 | 95.80 178 | 97.56 106 | 98.75 109 | 94.13 130 | 94.66 245 | 98.17 199 | 90.17 275 | 96.21 222 | 96.10 269 | 95.14 116 | 99.43 202 | 94.13 174 | 98.85 221 | 99.13 138 |
|
tfpn_ndepth | | | 90.98 306 | 90.24 311 | 93.20 307 | 97.72 247 | 87.18 288 | 96.52 133 | 88.20 358 | 92.63 243 | 93.69 299 | 90.70 355 | 68.22 355 | 99.42 203 | 86.98 306 | 97.47 303 | 93.00 355 |
|
conf200view11 | | | 91.81 292 | 91.26 287 | 93.46 299 | 98.21 184 | 84.50 320 | 96.39 137 | 90.39 339 | 96.87 90 | 96.33 210 | 93.08 322 | 73.44 334 | 99.42 203 | 78.85 348 | 97.74 278 | 96.46 319 |
|
thres100view900 | | | 91.76 294 | 91.26 287 | 93.26 303 | 98.21 184 | 84.50 320 | 96.39 137 | 90.39 339 | 96.87 90 | 96.33 210 | 93.08 322 | 73.44 334 | 99.42 203 | 78.85 348 | 97.74 278 | 95.85 329 |
|
tfpn200view9 | | | 91.55 300 | 91.00 291 | 93.21 305 | 98.02 207 | 84.35 324 | 95.70 182 | 90.79 336 | 96.26 112 | 95.90 234 | 92.13 337 | 73.62 328 | 99.42 203 | 78.85 348 | 97.74 278 | 95.85 329 |
|
patchmatchnet-post | | | | | | | | | | | | 96.84 224 | 77.36 311 | 99.42 203 | | | |
|
test_normal | | | 95.51 188 | 95.46 187 | 95.68 229 | 97.97 215 | 89.12 241 | 93.73 284 | 95.86 285 | 91.98 254 | 97.17 169 | 96.94 217 | 91.55 224 | 99.42 203 | 95.21 131 | 98.73 230 | 98.51 218 |
|
thres400 | | | 91.68 299 | 91.00 291 | 93.71 293 | 98.02 207 | 84.35 324 | 95.70 182 | 90.79 336 | 96.26 112 | 95.90 234 | 92.13 337 | 73.62 328 | 99.42 203 | 78.85 348 | 97.74 278 | 97.36 288 |
|
test12 | | | | | 97.46 120 | 97.61 257 | 94.07 131 | | 97.78 226 | | 93.57 305 | | 93.31 179 | 99.42 203 | | 98.78 223 | 98.89 180 |
|
CHOSEN 1792x2688 | | | 94.10 244 | 93.41 249 | 96.18 199 | 99.16 64 | 90.04 212 | 92.15 320 | 98.68 127 | 79.90 348 | 96.22 221 | 97.83 157 | 87.92 266 | 99.42 203 | 89.18 272 | 99.65 76 | 99.08 151 |
|
TAMVS | | | 95.49 190 | 94.94 201 | 97.16 137 | 98.31 163 | 93.41 155 | 95.07 226 | 96.82 270 | 91.09 266 | 97.51 151 | 97.82 160 | 89.96 245 | 99.42 203 | 88.42 284 | 99.44 132 | 98.64 206 |
|
PHI-MVS | | | 96.96 122 | 96.53 150 | 98.25 68 | 97.48 264 | 96.50 54 | 96.76 125 | 98.85 85 | 93.52 220 | 96.19 223 | 96.85 223 | 95.94 84 | 99.42 203 | 93.79 188 | 99.43 139 | 98.83 190 |
|
ADS-MVSNet2 | | | 91.47 301 | 90.51 307 | 94.36 275 | 95.51 329 | 85.63 299 | 95.05 229 | 95.70 288 | 83.46 334 | 92.69 324 | 96.84 224 | 79.15 302 | 99.41 214 | 85.66 316 | 90.52 350 | 98.04 262 |
|
Test4 | | | 95.39 198 | 95.24 192 | 95.82 222 | 98.07 203 | 89.60 222 | 94.40 251 | 98.49 153 | 91.39 264 | 97.40 162 | 96.32 258 | 87.32 271 | 99.41 214 | 95.09 142 | 98.71 233 | 98.44 223 |
|
XXY-MVS | | | 97.54 89 | 97.70 66 | 97.07 143 | 99.46 31 | 92.21 174 | 97.22 97 | 99.00 62 | 94.93 173 | 98.58 63 | 98.92 56 | 97.31 34 | 99.41 214 | 94.44 161 | 99.43 139 | 99.59 35 |
|
alignmvs | | | 96.01 174 | 95.52 185 | 97.50 114 | 97.77 244 | 94.71 109 | 96.07 157 | 96.84 268 | 97.48 71 | 96.78 193 | 94.28 313 | 85.50 279 | 99.40 217 | 96.22 90 | 98.73 230 | 98.40 225 |
|
æ— å…ˆéªŒ | | | | | | | | 93.20 302 | 97.91 216 | 80.78 344 | | | | 99.40 217 | 87.71 290 | | 97.94 269 |
|
1121 | | | 94.26 235 | 93.26 251 | 97.27 133 | 98.26 178 | 94.73 107 | 95.86 176 | 97.71 231 | 77.96 356 | 94.53 271 | 96.71 235 | 91.93 218 | 99.40 217 | 87.71 290 | 98.64 238 | 97.69 277 |
|
LP | | | 93.12 265 | 92.78 262 | 94.14 281 | 94.50 343 | 85.48 302 | 95.73 180 | 95.68 289 | 92.97 238 | 95.05 252 | 97.17 204 | 81.93 291 | 99.40 217 | 93.06 202 | 88.96 355 | 97.55 282 |
|
HY-MVS | | 91.43 15 | 92.58 271 | 91.81 278 | 94.90 256 | 96.49 307 | 88.87 247 | 97.31 91 | 94.62 299 | 85.92 315 | 90.50 345 | 96.84 224 | 85.05 282 | 99.40 217 | 83.77 331 | 95.78 331 | 96.43 323 |
|
ACMH+ | | 93.58 10 | 98.23 35 | 98.31 37 | 97.98 81 | 99.39 41 | 95.22 93 | 97.55 82 | 99.20 12 | 98.21 37 | 99.25 27 | 98.51 84 | 98.21 11 | 99.40 217 | 94.79 151 | 99.72 59 | 99.32 107 |
|
OPM-MVS | | | 97.54 89 | 97.25 99 | 98.41 53 | 99.11 77 | 96.61 51 | 95.24 216 | 98.46 155 | 94.58 184 | 98.10 107 | 98.07 133 | 97.09 43 | 99.39 223 | 95.16 136 | 99.44 132 | 99.21 126 |
|
v148 | | | 96.58 152 | 96.97 123 | 95.42 239 | 98.63 130 | 87.57 279 | 95.09 223 | 97.90 218 | 95.91 128 | 98.24 93 | 97.96 145 | 93.42 174 | 99.39 223 | 96.04 97 | 99.52 110 | 99.29 117 |
|
DI_MVS_plusplus_test | | | 95.46 194 | 95.43 188 | 95.55 235 | 98.05 205 | 88.84 249 | 94.18 263 | 95.75 287 | 91.92 257 | 97.32 163 | 96.94 217 | 91.44 226 | 99.39 223 | 94.81 149 | 98.48 248 | 98.43 224 |
|
CR-MVSNet | | | 93.29 263 | 92.79 260 | 94.78 260 | 95.44 331 | 88.15 261 | 96.18 153 | 97.20 255 | 84.94 327 | 94.10 282 | 98.57 78 | 77.67 307 | 99.39 223 | 95.17 134 | 95.81 328 | 96.81 308 |
|
RPMNet | | | 94.22 237 | 94.03 238 | 94.78 260 | 95.44 331 | 88.15 261 | 96.18 153 | 93.73 306 | 97.43 72 | 94.10 282 | 98.49 85 | 79.40 300 | 99.39 223 | 95.69 109 | 95.81 328 | 96.81 308 |
|
原ACMM1 | | | | | 96.58 171 | 98.16 195 | 92.12 178 | | 98.15 202 | 85.90 316 | 93.49 307 | 96.43 252 | 92.47 205 | 99.38 228 | 87.66 293 | 98.62 239 | 98.23 246 |
|
mvs_anonymous | | | 95.36 200 | 96.07 168 | 93.21 305 | 96.29 310 | 81.56 334 | 94.60 247 | 97.66 235 | 93.30 222 | 96.95 185 | 98.91 57 | 93.03 186 | 99.38 228 | 96.60 79 | 97.30 309 | 98.69 203 |
|
Patchmtry | | | 95.03 213 | 94.59 217 | 96.33 186 | 94.83 338 | 90.82 202 | 96.38 141 | 97.20 255 | 96.59 99 | 97.49 153 | 98.57 78 | 77.67 307 | 99.38 228 | 92.95 204 | 99.62 79 | 98.80 192 |
|
114514_t | | | 93.96 248 | 93.22 253 | 96.19 198 | 99.06 82 | 90.97 199 | 95.99 163 | 98.94 73 | 73.88 362 | 93.43 311 | 96.93 219 | 92.38 207 | 99.37 231 | 89.09 273 | 99.28 174 | 98.25 244 |
|
ppachtmachnet_test | | | 94.49 231 | 94.84 207 | 93.46 299 | 96.16 316 | 82.10 333 | 90.59 339 | 97.48 247 | 90.53 271 | 97.01 177 | 97.59 179 | 91.01 231 | 99.36 232 | 93.97 183 | 99.18 184 | 98.94 168 |
|
CNVR-MVS | | | 96.92 125 | 96.55 147 | 98.03 79 | 98.00 213 | 95.54 81 | 94.87 236 | 98.17 199 | 94.60 181 | 96.38 208 | 97.05 211 | 95.67 99 | 99.36 232 | 95.12 140 | 99.08 195 | 99.19 128 |
|
F-COLMAP | | | 95.30 203 | 94.38 227 | 98.05 78 | 98.64 126 | 96.04 67 | 95.61 192 | 98.66 133 | 89.00 283 | 93.22 316 | 96.40 255 | 92.90 189 | 99.35 234 | 87.45 303 | 97.53 299 | 98.77 197 |
|
Anonymous20231206 | | | 95.27 205 | 95.06 199 | 95.88 220 | 98.72 113 | 89.37 234 | 95.70 182 | 97.85 221 | 88.00 297 | 96.98 179 | 97.62 176 | 91.95 216 | 99.34 235 | 89.21 271 | 99.53 106 | 98.94 168 |
|
test_prior3 | | | 95.91 177 | 95.39 189 | 97.46 120 | 97.79 239 | 94.26 126 | 93.33 299 | 98.42 163 | 94.21 198 | 94.02 286 | 96.25 260 | 93.64 169 | 99.34 235 | 91.90 213 | 98.96 206 | 98.79 193 |
|
test_prior | | | | | 97.46 120 | 97.79 239 | 94.26 126 | | 98.42 163 | | | | | 99.34 235 | | | 98.79 193 |
|
canonicalmvs | | | 97.23 110 | 97.21 107 | 97.30 132 | 97.65 254 | 94.39 118 | 97.84 60 | 99.05 38 | 97.42 73 | 96.68 195 | 93.85 316 | 97.63 25 | 99.33 238 | 96.29 89 | 98.47 249 | 98.18 252 |
|
WTY-MVS | | | 93.55 257 | 93.00 256 | 95.19 245 | 97.81 230 | 87.86 272 | 93.89 278 | 96.00 280 | 89.02 282 | 94.07 284 | 95.44 288 | 86.27 275 | 99.33 238 | 87.69 292 | 96.82 315 | 98.39 227 |
|
thres200 | | | 91.00 305 | 90.42 309 | 92.77 315 | 97.47 268 | 83.98 327 | 94.01 272 | 91.18 334 | 95.12 167 | 95.44 244 | 91.21 350 | 73.93 324 | 99.31 240 | 77.76 352 | 97.63 296 | 95.01 340 |
|
PCF-MVS | | 89.43 18 | 92.12 284 | 90.64 305 | 96.57 173 | 97.80 234 | 93.48 154 | 89.88 348 | 98.45 156 | 74.46 361 | 96.04 228 | 95.68 280 | 90.71 235 | 99.31 240 | 73.73 356 | 99.01 204 | 96.91 304 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
tpm | | | 91.08 304 | 90.85 301 | 91.75 326 | 95.33 334 | 78.09 346 | 95.03 231 | 91.27 333 | 88.75 285 | 93.53 306 | 97.40 191 | 71.24 341 | 99.30 242 | 91.25 229 | 93.87 342 | 97.87 270 |
|
PVSNet_BlendedMVS | | | 95.02 214 | 94.93 203 | 95.27 243 | 97.79 239 | 87.40 284 | 94.14 267 | 98.68 127 | 88.94 284 | 94.51 272 | 98.01 141 | 93.04 184 | 99.30 242 | 89.77 264 | 99.49 120 | 99.11 146 |
|
PVSNet_Blended | | | 93.96 248 | 93.65 245 | 94.91 254 | 97.79 239 | 87.40 284 | 91.43 331 | 98.68 127 | 84.50 330 | 94.51 272 | 94.48 305 | 93.04 184 | 99.30 242 | 89.77 264 | 98.61 241 | 98.02 266 |
|
diffmvs1 | | | 96.57 154 | 96.86 129 | 95.72 227 | 96.74 301 | 89.30 235 | 95.90 175 | 98.58 146 | 96.33 110 | 94.93 256 | 98.37 94 | 94.52 138 | 99.29 245 | 97.60 51 | 98.73 230 | 98.58 212 |
|
EG-PatchMatch MVS | | | 97.69 78 | 97.79 60 | 97.40 127 | 99.06 82 | 93.52 153 | 95.96 169 | 98.97 70 | 94.55 185 | 98.82 47 | 98.76 64 | 97.31 34 | 99.29 245 | 97.20 67 | 99.44 132 | 99.38 98 |
|
diffmvs | | | 96.10 171 | 96.43 154 | 95.12 247 | 96.52 306 | 87.85 274 | 95.95 172 | 97.91 216 | 96.52 101 | 93.02 318 | 98.25 110 | 94.28 146 | 99.28 247 | 97.11 71 | 98.26 257 | 98.24 245 |
|
DeepC-MVS_fast | | 94.34 7 | 96.74 141 | 96.51 152 | 97.44 123 | 97.69 249 | 94.15 129 | 96.02 161 | 98.43 160 | 93.17 229 | 97.30 164 | 97.38 197 | 95.48 105 | 99.28 247 | 93.74 189 | 99.34 161 | 98.88 184 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
pmmvs5 | | | 94.63 226 | 94.34 228 | 95.50 237 | 97.63 256 | 88.34 258 | 94.02 271 | 97.13 259 | 87.15 304 | 95.22 249 | 97.15 205 | 87.50 268 | 99.27 249 | 93.99 181 | 99.26 177 | 98.88 184 |
|
no-one | | | 94.84 217 | 94.76 210 | 95.09 250 | 98.29 165 | 87.49 281 | 91.82 326 | 97.49 245 | 88.21 293 | 97.84 143 | 98.75 65 | 91.51 225 | 99.27 249 | 88.96 276 | 99.99 2 | 98.52 217 |
|
MVS_Test | | | 96.27 164 | 96.79 137 | 94.73 262 | 96.94 296 | 86.63 295 | 96.18 153 | 98.33 176 | 94.94 171 | 96.07 227 | 98.28 106 | 95.25 114 | 99.26 251 | 97.21 65 | 97.90 273 | 98.30 239 |
|
OpenMVS_ROB | ![Method available under an open source license with copyleft or other restrictive terms. copyleft](img/icon_copyleft.png) | 91.80 14 | 93.64 255 | 93.05 254 | 95.42 239 | 97.31 280 | 91.21 196 | 95.08 225 | 96.68 275 | 81.56 340 | 96.88 189 | 96.41 253 | 90.44 238 | 99.25 252 | 85.39 319 | 97.67 292 | 95.80 331 |
|
PatchT | | | 93.75 251 | 93.57 247 | 94.29 278 | 95.05 336 | 87.32 286 | 96.05 158 | 92.98 317 | 97.54 67 | 94.25 277 | 98.72 67 | 75.79 320 | 99.24 253 | 95.92 104 | 95.81 328 | 96.32 324 |
|
RPSCF | | | 97.87 62 | 97.51 85 | 98.95 14 | 99.15 67 | 98.43 3 | 97.56 81 | 99.06 36 | 96.19 115 | 98.48 70 | 98.70 69 | 94.72 125 | 99.24 253 | 94.37 166 | 99.33 166 | 99.17 131 |
|
HQP4-MVS | | | | | | | | | | | 92.87 320 | | | 99.23 255 | | | 99.06 155 |
|
HQP-MVS | | | 95.17 208 | 94.58 218 | 96.92 151 | 97.85 223 | 92.47 168 | 94.26 254 | 98.43 160 | 93.18 226 | 92.86 321 | 95.08 292 | 90.33 239 | 99.23 255 | 90.51 252 | 98.74 227 | 99.05 156 |
|
PLC | ![Method available under an open source license with copyleft or other restrictive terms. copyleft](img/icon_copyleft.png) | 91.02 16 | 94.05 247 | 92.90 257 | 97.51 111 | 98.00 213 | 95.12 97 | 94.25 257 | 98.25 189 | 86.17 312 | 91.48 337 | 95.25 290 | 91.01 231 | 99.19 257 | 85.02 322 | 96.69 319 | 98.22 247 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
0601test | | | 94.40 232 | 94.00 239 | 95.59 230 | 96.95 293 | 89.52 226 | 94.75 243 | 95.55 293 | 96.18 116 | 96.79 190 | 96.14 266 | 81.09 294 | 99.18 258 | 90.75 241 | 97.77 275 | 98.07 256 |
|
Anonymous20240521 | | | 94.40 232 | 94.00 239 | 95.59 230 | 96.95 293 | 89.52 226 | 94.75 243 | 95.55 293 | 96.18 116 | 96.79 190 | 96.14 266 | 81.09 294 | 99.18 258 | 90.75 241 | 97.77 275 | 98.07 256 |
|
YYNet1 | | | 94.73 220 | 94.84 207 | 94.41 274 | 97.47 268 | 85.09 310 | 90.29 342 | 95.85 286 | 92.52 244 | 97.53 149 | 97.76 163 | 91.97 215 | 99.18 258 | 93.31 195 | 96.86 314 | 98.95 166 |
|
PatchmatchNet | ![Method available under a permissive open source license. permissive](img/icon_permissive.png) | | 91.98 286 | 91.87 276 | 92.30 322 | 94.60 341 | 79.71 341 | 95.12 220 | 93.59 312 | 89.52 279 | 93.61 303 | 97.02 213 | 77.94 305 | 99.18 258 | 90.84 237 | 94.57 341 | 98.01 267 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
MDA-MVSNet_test_wron | | | 94.73 220 | 94.83 209 | 94.42 273 | 97.48 264 | 85.15 308 | 90.28 343 | 95.87 284 | 92.52 244 | 97.48 156 | 97.76 163 | 91.92 219 | 99.17 262 | 93.32 194 | 96.80 317 | 98.94 168 |
|
UnsupCasMVSNet_bld | | | 94.72 222 | 94.26 229 | 96.08 206 | 98.62 131 | 90.54 209 | 93.38 297 | 98.05 213 | 90.30 273 | 97.02 176 | 96.80 229 | 89.54 248 | 99.16 263 | 88.44 283 | 96.18 326 | 98.56 214 |
|
AllTest | | | 97.20 111 | 96.92 127 | 98.06 75 | 99.08 79 | 96.16 63 | 97.14 102 | 99.16 15 | 94.35 193 | 97.78 145 | 98.07 133 | 95.84 87 | 99.12 264 | 91.41 224 | 99.42 142 | 98.91 176 |
|
TestCases | | | | | 98.06 75 | 99.08 79 | 96.16 63 | | 99.16 15 | 94.35 193 | 97.78 145 | 98.07 133 | 95.84 87 | 99.12 264 | 91.41 224 | 99.42 142 | 98.91 176 |
|
MAR-MVS | | | 94.21 240 | 93.03 255 | 97.76 92 | 96.94 296 | 97.44 30 | 96.97 121 | 97.15 258 | 87.89 299 | 92.00 333 | 92.73 332 | 92.14 210 | 99.12 264 | 83.92 328 | 97.51 300 | 96.73 311 |
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 |
our_test_3 | | | 94.20 242 | 94.58 218 | 93.07 308 | 96.16 316 | 81.20 336 | 90.42 341 | 96.84 268 | 90.72 270 | 97.14 170 | 97.13 206 | 90.47 237 | 99.11 267 | 94.04 180 | 98.25 258 | 98.91 176 |
|
EPNet_dtu | | | 91.39 302 | 90.75 303 | 93.31 302 | 90.48 368 | 82.61 330 | 94.80 240 | 92.88 319 | 93.39 221 | 81.74 366 | 94.90 299 | 81.36 293 | 99.11 267 | 88.28 286 | 98.87 217 | 98.21 248 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
MVP-Stereo | | | 95.69 181 | 95.28 191 | 96.92 151 | 98.15 197 | 93.03 161 | 95.64 190 | 98.20 194 | 90.39 272 | 96.63 196 | 97.73 169 | 91.63 223 | 99.10 269 | 91.84 217 | 97.31 308 | 98.63 208 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
AdaColmap | ![Method available as binary. binary](img/icon_binary.png) | | 95.11 209 | 94.62 215 | 96.58 171 | 97.33 278 | 94.45 117 | 94.92 234 | 98.08 209 | 93.15 230 | 93.98 289 | 95.53 286 | 94.34 144 | 99.10 269 | 85.69 315 | 98.61 241 | 96.20 326 |
|
pmmvs-eth3d | | | 96.49 156 | 96.18 163 | 97.42 125 | 98.25 179 | 94.29 122 | 94.77 242 | 98.07 211 | 89.81 278 | 97.97 122 | 98.33 99 | 93.11 182 | 99.08 271 | 95.46 122 | 99.84 40 | 98.89 180 |
|
test_post | | | | | | | | | | | | 10.87 369 | 76.83 314 | 99.07 272 | | | |
|
N_pmnet | | | 95.18 207 | 94.23 230 | 98.06 75 | 97.85 223 | 96.55 53 | 92.49 315 | 91.63 330 | 89.34 280 | 98.09 108 | 97.41 190 | 90.33 239 | 99.06 273 | 91.58 223 | 99.31 169 | 98.56 214 |
|
PM-MVS | | | 97.36 103 | 97.10 116 | 98.14 72 | 98.91 97 | 96.77 45 | 96.20 152 | 98.63 140 | 93.82 213 | 98.54 65 | 98.33 99 | 93.98 157 | 99.05 274 | 95.99 101 | 99.45 131 | 98.61 210 |
|
ambc | | | | | 96.56 174 | 98.23 182 | 91.68 191 | 97.88 57 | 98.13 204 | | 98.42 76 | 98.56 80 | 94.22 150 | 99.04 275 | 94.05 179 | 99.35 158 | 98.95 166 |
|
test_post1 | | | | | | | | 94.98 233 | | | | 10.37 370 | 76.21 318 | 99.04 275 | 89.47 268 | | |
|
OMC-MVS | | | 96.48 157 | 96.00 170 | 97.91 85 | 98.30 164 | 96.01 69 | 94.86 237 | 98.60 143 | 91.88 258 | 97.18 168 | 97.21 203 | 96.11 81 | 99.04 275 | 90.49 254 | 99.34 161 | 98.69 203 |
|
Patchmatch-test1 | | | 93.38 261 | 93.59 246 | 92.73 316 | 96.24 311 | 81.40 335 | 93.24 301 | 94.00 305 | 91.58 262 | 94.57 269 | 96.67 238 | 87.94 263 | 99.03 278 | 90.42 255 | 97.66 293 | 97.77 275 |
|
PatchFormer-LS_test | | | 89.62 319 | 89.12 322 | 91.11 332 | 93.62 353 | 78.42 345 | 94.57 249 | 93.62 311 | 88.39 290 | 90.54 344 | 88.40 360 | 72.33 339 | 99.03 278 | 92.41 209 | 88.20 356 | 95.89 328 |
|
MIMVSNet | | | 93.42 259 | 92.86 258 | 95.10 249 | 98.17 193 | 88.19 260 | 98.13 43 | 93.69 307 | 92.07 251 | 95.04 253 | 98.21 115 | 80.95 296 | 99.03 278 | 81.42 340 | 98.06 264 | 98.07 256 |
|
BH-RMVSNet | | | 94.56 229 | 94.44 226 | 94.91 254 | 97.57 258 | 87.44 283 | 93.78 283 | 96.26 277 | 93.69 217 | 96.41 207 | 96.50 248 | 92.10 212 | 99.00 281 | 85.96 312 | 97.71 288 | 98.31 237 |
|
gm-plane-assit | | | | | | 91.79 364 | 71.40 363 | | | 81.67 339 | | 90.11 358 | | 98.99 282 | 84.86 323 | | |
|
MVS_111021_HR | | | 96.73 143 | 96.54 149 | 97.27 133 | 98.35 162 | 93.66 148 | 93.42 295 | 98.36 171 | 94.74 178 | 96.58 197 | 96.76 233 | 96.54 66 | 98.99 282 | 94.87 146 | 99.27 176 | 99.15 135 |
|
testdata | | | | | 95.70 228 | 98.16 195 | 90.58 206 | | 97.72 230 | 80.38 346 | 95.62 242 | 97.02 213 | 92.06 214 | 98.98 284 | 89.06 275 | 98.52 245 | 97.54 283 |
|
DP-MVS Recon | | | 95.55 187 | 95.13 195 | 96.80 156 | 98.51 147 | 93.99 135 | 94.60 247 | 98.69 125 | 90.20 274 | 95.78 237 | 96.21 263 | 92.73 193 | 98.98 284 | 90.58 250 | 98.86 219 | 97.42 287 |
|
TAPA-MVS | | 93.32 12 | 94.93 215 | 94.23 230 | 97.04 145 | 98.18 191 | 94.51 114 | 95.22 217 | 98.73 114 | 81.22 343 | 96.25 220 | 95.95 275 | 93.80 166 | 98.98 284 | 89.89 262 | 98.87 217 | 97.62 279 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
CLD-MVS | | | 95.47 193 | 95.07 197 | 96.69 164 | 98.27 170 | 92.53 167 | 91.36 332 | 98.67 130 | 91.22 265 | 95.78 237 | 94.12 314 | 95.65 100 | 98.98 284 | 90.81 238 | 99.72 59 | 98.57 213 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
GA-MVS | | | 92.83 268 | 92.15 270 | 94.87 257 | 96.97 292 | 87.27 287 | 90.03 344 | 96.12 278 | 91.83 259 | 94.05 285 | 94.57 301 | 76.01 319 | 98.97 288 | 92.46 208 | 97.34 307 | 98.36 234 |
|
BH-untuned | | | 94.69 223 | 94.75 211 | 94.52 272 | 97.95 220 | 87.53 280 | 94.07 270 | 97.01 263 | 93.99 204 | 97.10 173 | 95.65 281 | 92.65 196 | 98.95 289 | 87.60 300 | 96.74 318 | 97.09 296 |
|
test1235678 | | | 92.95 266 | 92.40 266 | 94.61 266 | 96.95 293 | 86.87 292 | 90.75 337 | 97.75 227 | 91.00 268 | 96.33 210 | 95.38 289 | 85.21 281 | 98.92 290 | 79.00 346 | 99.20 181 | 98.03 264 |
|
DWT-MVSNet_test | | | 87.92 332 | 86.77 334 | 91.39 328 | 93.18 356 | 78.62 344 | 95.10 221 | 91.42 331 | 85.58 318 | 88.00 356 | 88.73 359 | 60.60 363 | 98.90 291 | 90.60 248 | 87.70 357 | 96.65 313 |
|
JIA-IIPM | | | 91.79 293 | 90.69 304 | 95.11 248 | 93.80 352 | 90.98 198 | 94.16 265 | 91.78 329 | 96.38 106 | 90.30 347 | 99.30 23 | 72.02 340 | 98.90 291 | 88.28 286 | 90.17 352 | 95.45 337 |
|
pmmvs4 | | | 94.82 219 | 94.19 233 | 96.70 163 | 97.42 271 | 92.75 165 | 92.09 323 | 96.76 271 | 86.80 308 | 95.73 240 | 97.22 202 | 89.28 254 | 98.89 293 | 93.28 196 | 99.14 186 | 98.46 222 |
|
TSAR-MVS + GP. | | | 96.47 158 | 96.12 164 | 97.49 117 | 97.74 245 | 95.23 90 | 94.15 266 | 96.90 267 | 93.26 223 | 98.04 115 | 96.70 236 | 94.41 141 | 98.89 293 | 94.77 154 | 99.14 186 | 98.37 229 |
|
CostFormer | | | 89.75 318 | 89.25 316 | 91.26 330 | 94.69 340 | 78.00 349 | 95.32 209 | 91.98 327 | 81.50 341 | 90.55 343 | 96.96 216 | 71.06 342 | 98.89 293 | 88.59 282 | 92.63 347 | 96.87 305 |
|
sss | | | 94.22 237 | 93.72 244 | 95.74 224 | 97.71 248 | 89.95 215 | 93.84 280 | 96.98 264 | 88.38 291 | 93.75 295 | 95.74 278 | 87.94 263 | 98.89 293 | 91.02 231 | 98.10 263 | 98.37 229 |
|
1111 | | | 88.78 323 | 89.39 315 | 86.96 348 | 98.53 145 | 62.84 367 | 91.49 329 | 97.48 247 | 94.45 186 | 96.56 199 | 96.45 250 | 43.83 372 | 98.87 297 | 86.33 310 | 99.40 149 | 99.18 130 |
|
.test1245 | | | 73.49 341 | 79.27 342 | 56.15 354 | 98.53 145 | 62.84 367 | 91.49 329 | 97.48 247 | 94.45 186 | 96.56 199 | 96.45 250 | 43.83 372 | 98.87 297 | 86.33 310 | 8.32 367 | 6.75 367 |
|
tpmvs | | | 90.79 309 | 90.87 300 | 90.57 336 | 92.75 362 | 76.30 353 | 95.79 179 | 93.64 310 | 91.04 267 | 91.91 334 | 96.26 259 | 77.19 313 | 98.86 299 | 89.38 269 | 89.85 353 | 96.56 317 |
|
tpmp4_e23 | | | 88.46 326 | 87.54 329 | 91.22 331 | 94.56 342 | 78.08 347 | 95.63 191 | 93.17 315 | 79.08 352 | 85.85 361 | 96.80 229 | 65.86 358 | 98.85 300 | 84.10 327 | 92.85 345 | 96.72 312 |
|
tpmrst | | | 90.31 311 | 90.61 306 | 89.41 340 | 94.06 350 | 72.37 362 | 95.06 228 | 93.69 307 | 88.01 296 | 92.32 331 | 96.86 222 | 77.45 309 | 98.82 301 | 91.04 230 | 87.01 358 | 97.04 299 |
|
Gipuma | ![Method available under an open source license with copyleft or other restrictive terms. copyleft](img/icon_copyleft.png) | | 98.07 41 | 98.31 37 | 97.36 129 | 99.76 4 | 96.28 61 | 98.51 21 | 99.10 25 | 98.76 21 | 96.79 190 | 99.34 20 | 96.61 64 | 98.82 301 | 96.38 87 | 99.50 113 | 96.98 300 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
Patchmatch-RL test | | | 94.66 224 | 94.49 221 | 95.19 245 | 98.54 143 | 88.91 246 | 92.57 313 | 98.74 113 | 91.46 263 | 98.32 85 | 97.75 166 | 77.31 312 | 98.81 303 | 96.06 95 | 99.61 84 | 97.85 271 |
|
dp | | | 88.08 329 | 88.05 327 | 88.16 346 | 92.85 360 | 68.81 364 | 94.17 264 | 92.88 319 | 85.47 320 | 91.38 338 | 96.14 266 | 68.87 353 | 98.81 303 | 86.88 307 | 83.80 362 | 96.87 305 |
|
DeepPCF-MVS | | 94.58 5 | 96.90 127 | 96.43 154 | 98.31 63 | 97.48 264 | 97.23 36 | 92.56 314 | 98.60 143 | 92.84 241 | 98.54 65 | 97.40 191 | 96.64 63 | 98.78 305 | 94.40 165 | 99.41 148 | 98.93 172 |
|
MG-MVS | | | 94.08 246 | 94.00 239 | 94.32 276 | 97.09 288 | 85.89 298 | 93.19 303 | 95.96 282 | 92.52 244 | 94.93 256 | 97.51 185 | 89.54 248 | 98.77 306 | 87.52 302 | 97.71 288 | 98.31 237 |
|
EU-MVSNet | | | 94.25 236 | 94.47 222 | 93.60 295 | 98.14 198 | 82.60 331 | 97.24 96 | 92.72 322 | 85.08 325 | 98.48 70 | 98.94 54 | 82.59 290 | 98.76 307 | 97.47 59 | 99.53 106 | 99.44 81 |
|
USDC | | | 94.56 229 | 94.57 220 | 94.55 271 | 97.78 243 | 86.43 297 | 92.75 309 | 98.65 139 | 85.96 314 | 96.91 187 | 97.93 151 | 90.82 234 | 98.74 308 | 90.71 245 | 99.59 89 | 98.47 220 |
|
tpm2 | | | 88.47 325 | 87.69 328 | 90.79 334 | 94.98 337 | 77.34 351 | 95.09 223 | 91.83 328 | 77.51 358 | 89.40 351 | 96.41 253 | 67.83 356 | 98.73 309 | 83.58 333 | 92.60 348 | 96.29 325 |
|
MVS_111021_LR | | | 96.82 136 | 96.55 147 | 97.62 103 | 98.27 170 | 95.34 88 | 93.81 282 | 98.33 176 | 94.59 183 | 96.56 199 | 96.63 240 | 96.61 64 | 98.73 309 | 94.80 150 | 99.34 161 | 98.78 196 |
|
test20.03 | | | 96.58 152 | 96.61 142 | 96.48 178 | 98.49 149 | 91.72 190 | 95.68 185 | 97.69 232 | 96.81 94 | 98.27 91 | 97.92 152 | 94.18 152 | 98.71 311 | 90.78 240 | 99.66 75 | 99.00 160 |
|
ADS-MVSNet | | | 90.95 307 | 90.26 310 | 93.04 309 | 95.51 329 | 82.37 332 | 95.05 229 | 93.41 313 | 83.46 334 | 92.69 324 | 96.84 224 | 79.15 302 | 98.70 312 | 85.66 316 | 90.52 350 | 98.04 262 |
|
pmmvs3 | | | 90.00 314 | 88.90 323 | 93.32 301 | 94.20 349 | 85.34 304 | 91.25 333 | 92.56 324 | 78.59 353 | 93.82 292 | 95.17 291 | 67.36 357 | 98.69 313 | 89.08 274 | 98.03 265 | 95.92 327 |
|
UnsupCasMVSNet_eth | | | 95.91 177 | 95.73 180 | 96.44 180 | 98.48 151 | 91.52 193 | 95.31 210 | 98.45 156 | 95.76 136 | 97.48 156 | 97.54 181 | 89.53 250 | 98.69 313 | 94.43 162 | 94.61 340 | 99.13 138 |
|
LF4IMVS | | | 96.07 172 | 95.63 183 | 97.36 129 | 98.19 188 | 95.55 80 | 95.44 195 | 98.82 100 | 92.29 250 | 95.70 241 | 96.55 243 | 92.63 197 | 98.69 313 | 91.75 221 | 99.33 166 | 97.85 271 |
|
TinyColmap | | | 96.00 175 | 96.34 159 | 94.96 253 | 97.90 221 | 87.91 271 | 94.13 268 | 98.49 153 | 94.41 189 | 98.16 99 | 97.76 163 | 96.29 79 | 98.68 316 | 90.52 251 | 99.42 142 | 98.30 239 |
|
旧先验2 | | | | | | | | 93.35 298 | | 77.95 357 | 95.77 239 | | | 98.67 317 | 90.74 244 | | |
|
PMMVS | | | 92.39 277 | 91.08 290 | 96.30 189 | 93.12 358 | 92.81 164 | 90.58 340 | 95.96 282 | 79.17 351 | 91.85 335 | 92.27 335 | 90.29 243 | 98.66 318 | 89.85 263 | 96.68 320 | 97.43 286 |
|
Patchmatch-test | | | 93.60 256 | 93.25 252 | 94.63 265 | 96.14 318 | 87.47 282 | 96.04 159 | 94.50 301 | 93.57 219 | 96.47 204 | 96.97 215 | 76.50 315 | 98.61 319 | 90.67 247 | 98.41 251 | 97.81 274 |
|
TR-MVS | | | 92.54 276 | 92.20 269 | 93.57 296 | 96.49 307 | 86.66 294 | 93.51 292 | 94.73 298 | 89.96 277 | 94.95 254 | 93.87 315 | 90.24 244 | 98.61 319 | 81.18 341 | 94.88 337 | 95.45 337 |
|
test-LLR | | | 89.97 316 | 89.90 313 | 90.16 337 | 94.24 347 | 74.98 356 | 89.89 345 | 89.06 349 | 92.02 252 | 89.97 349 | 90.77 352 | 73.92 325 | 98.57 321 | 91.88 215 | 97.36 305 | 96.92 302 |
|
test-mter | | | 87.92 332 | 87.17 331 | 90.16 337 | 94.24 347 | 74.98 356 | 89.89 345 | 89.06 349 | 86.44 310 | 89.97 349 | 90.77 352 | 54.96 368 | 98.57 321 | 91.88 215 | 97.36 305 | 96.92 302 |
|
PatchMatch-RL | | | 94.61 227 | 93.81 243 | 97.02 148 | 98.19 188 | 95.72 74 | 93.66 286 | 97.23 254 | 88.17 294 | 94.94 255 | 95.62 283 | 91.43 227 | 98.57 321 | 87.36 304 | 97.68 291 | 96.76 310 |
|
DSMNet-mixed | | | 92.19 282 | 91.83 277 | 93.25 304 | 96.18 315 | 83.68 329 | 96.27 146 | 93.68 309 | 76.97 359 | 92.54 329 | 99.18 35 | 89.20 256 | 98.55 324 | 83.88 329 | 98.60 243 | 97.51 284 |
|
MDTV_nov1_ep13 | | | | 91.28 285 | | 94.31 345 | 73.51 359 | 94.80 240 | 93.16 316 | 86.75 309 | 93.45 310 | 97.40 191 | 76.37 316 | 98.55 324 | 88.85 277 | 96.43 322 | |
|
ITE_SJBPF | | | | | 97.85 88 | 98.64 126 | 96.66 49 | | 98.51 152 | 95.63 139 | 97.22 166 | 97.30 200 | 95.52 103 | 98.55 324 | 90.97 233 | 98.90 212 | 98.34 235 |
|
PVSNet | | 86.72 19 | 91.10 303 | 90.97 299 | 91.49 327 | 97.56 260 | 78.04 348 | 87.17 354 | 94.60 300 | 84.65 328 | 92.34 330 | 92.20 336 | 87.37 270 | 98.47 327 | 85.17 321 | 97.69 290 | 97.96 268 |
|
CVMVSNet | | | 92.33 280 | 92.79 260 | 90.95 333 | 97.26 281 | 75.84 355 | 95.29 212 | 92.33 325 | 81.86 338 | 96.27 218 | 98.19 116 | 81.44 292 | 98.46 328 | 94.23 173 | 98.29 252 | 98.55 216 |
|
XVG-OURS-SEG-HR | | | 97.38 99 | 97.07 119 | 98.30 64 | 99.01 89 | 97.41 31 | 94.66 245 | 99.02 51 | 95.20 158 | 98.15 101 | 97.52 184 | 98.83 4 | 98.43 329 | 94.87 146 | 96.41 323 | 99.07 153 |
|
XVG-OURS | | | 97.12 112 | 96.74 138 | 98.26 66 | 98.99 90 | 97.45 29 | 93.82 281 | 99.05 38 | 95.19 159 | 98.32 85 | 97.70 172 | 95.22 115 | 98.41 330 | 94.27 171 | 98.13 262 | 98.93 172 |
|
PAPM | | | 87.64 334 | 85.84 337 | 93.04 309 | 96.54 304 | 84.99 311 | 88.42 353 | 95.57 292 | 79.52 349 | 83.82 363 | 93.05 326 | 80.57 297 | 98.41 330 | 62.29 364 | 92.79 346 | 95.71 332 |
|
MVS | | | 90.02 313 | 89.20 319 | 92.47 319 | 94.71 339 | 86.90 291 | 95.86 176 | 96.74 273 | 64.72 364 | 90.62 341 | 92.77 329 | 92.54 201 | 98.39 332 | 79.30 345 | 95.56 335 | 92.12 356 |
|
test12356 | | | 87.98 331 | 88.41 326 | 86.69 349 | 95.84 323 | 63.49 366 | 87.15 355 | 97.32 252 | 87.21 302 | 91.78 336 | 93.36 318 | 70.66 345 | 98.39 332 | 74.70 355 | 97.64 295 | 98.19 250 |
|
PAPM_NR | | | 94.61 227 | 94.17 234 | 95.96 214 | 98.36 161 | 91.23 195 | 95.93 173 | 97.95 215 | 92.98 234 | 93.42 312 | 94.43 310 | 90.53 236 | 98.38 334 | 87.60 300 | 96.29 325 | 98.27 242 |
|
MSDG | | | 95.33 201 | 95.13 195 | 95.94 218 | 97.40 272 | 91.85 187 | 91.02 335 | 98.37 170 | 95.30 152 | 96.31 216 | 95.99 270 | 94.51 139 | 98.38 334 | 89.59 266 | 97.65 294 | 97.60 281 |
|
API-MVS | | | 95.09 211 | 95.01 200 | 95.31 242 | 96.61 303 | 94.02 133 | 96.83 123 | 97.18 257 | 95.60 141 | 95.79 236 | 94.33 311 | 94.54 136 | 98.37 336 | 85.70 314 | 98.52 245 | 93.52 351 |
|
CNLPA | | | 95.04 212 | 94.47 222 | 96.75 160 | 97.81 230 | 95.25 89 | 94.12 269 | 97.89 219 | 94.41 189 | 94.57 269 | 95.69 279 | 90.30 242 | 98.35 337 | 86.72 309 | 98.76 225 | 96.64 314 |
|
PAPR | | | 92.22 281 | 91.27 286 | 95.07 251 | 95.73 327 | 88.81 250 | 91.97 324 | 97.87 220 | 85.80 317 | 90.91 339 | 92.73 332 | 91.16 229 | 98.33 338 | 79.48 344 | 95.76 332 | 98.08 254 |
|
tpm cat1 | | | 88.01 330 | 87.33 330 | 90.05 339 | 94.48 344 | 76.28 354 | 94.47 250 | 94.35 304 | 73.84 363 | 89.26 352 | 95.61 284 | 73.64 327 | 98.30 339 | 84.13 326 | 86.20 359 | 95.57 336 |
|
BH-w/o | | | 92.14 283 | 91.94 275 | 92.73 316 | 97.13 287 | 85.30 305 | 92.46 316 | 95.64 290 | 89.33 281 | 94.21 278 | 92.74 331 | 89.60 247 | 98.24 340 | 81.68 339 | 94.66 339 | 94.66 342 |
|
gg-mvs-nofinetune | | | 88.28 328 | 86.96 332 | 92.23 323 | 92.84 361 | 84.44 323 | 98.19 40 | 74.60 369 | 99.08 9 | 87.01 360 | 99.47 7 | 56.93 365 | 98.23 341 | 78.91 347 | 95.61 334 | 94.01 349 |
|
MS-PatchMatch | | | 94.83 218 | 94.91 204 | 94.57 270 | 96.81 300 | 87.10 290 | 94.23 259 | 97.34 251 | 88.74 286 | 97.14 170 | 97.11 208 | 91.94 217 | 98.23 341 | 92.99 203 | 97.92 271 | 98.37 229 |
|
MVS-HIRNet | | | 88.40 327 | 90.20 312 | 82.99 351 | 97.01 291 | 60.04 369 | 93.11 304 | 85.61 364 | 84.45 331 | 88.72 354 | 99.09 45 | 84.72 285 | 98.23 341 | 82.52 334 | 96.59 321 | 90.69 361 |
|
cascas | | | 91.89 290 | 91.35 284 | 93.51 297 | 94.27 346 | 85.60 300 | 88.86 352 | 98.61 142 | 79.32 350 | 92.16 332 | 91.44 348 | 89.22 255 | 98.12 344 | 90.80 239 | 97.47 303 | 96.82 307 |
|
MSLP-MVS++ | | | 96.42 162 | 96.71 139 | 95.57 232 | 97.82 229 | 90.56 208 | 95.71 181 | 98.84 88 | 94.72 179 | 96.71 194 | 97.39 195 | 94.91 122 | 98.10 345 | 95.28 128 | 99.02 202 | 98.05 261 |
|
EPMVS | | | 89.26 321 | 88.55 325 | 91.39 328 | 92.36 363 | 79.11 343 | 95.65 188 | 79.86 367 | 88.60 287 | 93.12 317 | 96.53 245 | 70.73 344 | 98.10 345 | 90.75 241 | 89.32 354 | 96.98 300 |
|
testus | | | 90.90 308 | 90.51 307 | 92.06 324 | 96.07 319 | 79.45 342 | 88.99 350 | 98.44 159 | 85.46 321 | 94.15 281 | 90.77 352 | 89.12 257 | 98.01 347 | 73.66 357 | 97.95 267 | 98.71 202 |
|
PMMVS2 | | | 93.66 254 | 94.07 236 | 92.45 320 | 97.57 258 | 80.67 339 | 86.46 356 | 96.00 280 | 93.99 204 | 97.10 173 | 97.38 197 | 89.90 246 | 97.82 348 | 88.76 278 | 99.47 125 | 98.86 187 |
|
1314 | | | 92.38 278 | 92.30 268 | 92.64 318 | 95.42 333 | 85.15 308 | 95.86 176 | 96.97 265 | 85.40 323 | 90.62 341 | 93.06 325 | 91.12 230 | 97.80 349 | 86.74 308 | 95.49 336 | 94.97 341 |
|
TESTMET0.1,1 | | | 87.20 335 | 86.57 335 | 89.07 341 | 93.62 353 | 72.84 361 | 89.89 345 | 87.01 363 | 85.46 321 | 89.12 353 | 90.20 357 | 56.00 367 | 97.72 350 | 90.91 235 | 96.92 312 | 96.64 314 |
|
testgi | | | 96.07 172 | 96.50 153 | 94.80 259 | 99.26 50 | 87.69 278 | 95.96 169 | 98.58 146 | 95.08 168 | 98.02 117 | 96.25 260 | 97.92 17 | 97.60 351 | 88.68 281 | 98.74 227 | 99.11 146 |
|
CMPMVS | ![Method available as binary. binary](img/icon_binary.png) | 73.10 23 | 92.74 269 | 91.39 282 | 96.77 158 | 93.57 355 | 94.67 111 | 94.21 261 | 97.67 233 | 80.36 347 | 93.61 303 | 96.60 241 | 82.85 289 | 97.35 352 | 84.86 323 | 98.78 223 | 98.29 241 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
test2356 | | | 85.45 337 | 83.26 340 | 92.01 325 | 91.12 365 | 80.76 338 | 85.16 358 | 92.90 318 | 83.90 333 | 90.63 340 | 87.71 362 | 53.10 369 | 97.24 353 | 69.20 362 | 95.65 333 | 98.03 264 |
|
EMVS | | | 89.06 322 | 89.22 317 | 88.61 343 | 93.00 359 | 77.34 351 | 82.91 362 | 90.92 335 | 94.64 180 | 92.63 327 | 91.81 340 | 76.30 317 | 97.02 354 | 83.83 330 | 96.90 313 | 91.48 359 |
|
PMVS | ![Method available under an open source license with copyleft or other restrictive terms. copyleft](img/icon_copyleft.png) | 89.60 17 | 96.71 146 | 96.97 123 | 95.95 216 | 99.51 25 | 97.81 13 | 97.42 90 | 97.49 245 | 97.93 46 | 95.95 230 | 98.58 77 | 96.88 52 | 96.91 355 | 89.59 266 | 99.36 154 | 93.12 354 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
E-PMN | | | 89.52 320 | 89.78 314 | 88.73 342 | 93.14 357 | 77.61 350 | 83.26 361 | 92.02 326 | 94.82 176 | 93.71 297 | 93.11 320 | 75.31 321 | 96.81 356 | 85.81 313 | 96.81 316 | 91.77 358 |
|
GG-mvs-BLEND | | | | | 90.60 335 | 91.00 366 | 84.21 326 | 98.23 34 | 72.63 372 | | 82.76 364 | 84.11 364 | 56.14 366 | 96.79 357 | 72.20 359 | 92.09 349 | 90.78 360 |
|
new_pmnet | | | 92.34 279 | 91.69 280 | 94.32 276 | 96.23 313 | 89.16 239 | 92.27 319 | 92.88 319 | 84.39 332 | 95.29 247 | 96.35 257 | 85.66 278 | 96.74 358 | 84.53 325 | 97.56 297 | 97.05 298 |
|
PVSNet_0 | | 81.89 21 | 84.49 338 | 83.21 341 | 88.34 344 | 95.76 326 | 74.97 358 | 83.49 360 | 92.70 323 | 78.47 354 | 87.94 357 | 86.90 363 | 83.38 288 | 96.63 359 | 73.44 358 | 66.86 365 | 93.40 352 |
|
PNet_i23d | | | 83.82 339 | 83.39 339 | 85.10 350 | 96.07 319 | 65.16 365 | 81.87 363 | 94.37 303 | 90.87 269 | 93.92 291 | 92.89 328 | 52.80 370 | 96.44 360 | 77.52 354 | 70.22 364 | 93.70 350 |
|
SD-MVS | | | 97.37 100 | 97.70 66 | 96.35 184 | 98.14 198 | 95.13 96 | 96.54 132 | 98.92 74 | 95.94 127 | 99.19 30 | 98.08 131 | 97.74 21 | 95.06 361 | 95.24 130 | 99.54 103 | 98.87 186 |
|
test0.0.03 1 | | | 90.11 312 | 89.21 318 | 92.83 314 | 93.89 351 | 86.87 292 | 91.74 327 | 88.74 351 | 92.02 252 | 94.71 261 | 91.14 351 | 73.92 325 | 94.48 362 | 83.75 332 | 92.94 344 | 97.16 295 |
|
wuyk23d | | | 93.25 264 | 95.20 193 | 87.40 347 | 96.07 319 | 95.38 86 | 97.04 112 | 94.97 296 | 95.33 151 | 99.70 5 | 98.11 129 | 98.14 13 | 91.94 363 | 77.76 352 | 99.68 71 | 74.89 363 |
|
FPMVS | | | 89.92 317 | 88.63 324 | 93.82 291 | 98.37 160 | 96.94 41 | 91.58 328 | 93.34 314 | 88.00 297 | 90.32 346 | 97.10 209 | 70.87 343 | 91.13 364 | 71.91 360 | 96.16 327 | 93.39 353 |
|
testpf | | | 82.70 340 | 84.35 338 | 77.74 352 | 88.97 369 | 73.23 360 | 93.85 279 | 84.33 365 | 88.10 295 | 85.06 362 | 90.42 356 | 52.62 371 | 91.05 365 | 91.00 232 | 84.82 361 | 68.93 364 |
|
MVE | ![Method available under a permissive open source license. permissive](img/icon_permissive.png) | 73.61 22 | 86.48 336 | 85.92 336 | 88.18 345 | 96.23 313 | 85.28 306 | 81.78 364 | 75.79 368 | 86.01 313 | 82.53 365 | 91.88 339 | 92.74 192 | 87.47 366 | 71.42 361 | 94.86 338 | 91.78 357 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
DeepMVS_CX | ![Method available under an open source license with copyleft or other restrictive terms. copyleft](img/icon_copyleft.png) | | | | 77.17 353 | 90.94 367 | 85.28 306 | | 74.08 371 | 52.51 365 | 80.87 367 | 88.03 361 | 75.25 322 | 70.63 367 | 59.23 365 | 84.94 360 | 75.62 362 |
|
tmp_tt | | | 57.23 342 | 62.50 343 | 41.44 355 | 34.77 371 | 49.21 371 | 83.93 359 | 60.22 373 | 15.31 366 | 71.11 368 | 79.37 365 | 70.09 346 | 44.86 368 | 64.76 363 | 82.93 363 | 30.25 365 |
|
testmvs | | | 12.33 347 | 15.23 348 | 3.64 358 | 5.77 373 | 2.23 373 | 88.99 350 | 3.62 374 | 2.30 368 | 5.29 369 | 13.09 367 | 4.52 375 | 1.95 369 | 5.16 367 | 8.32 367 | 6.75 367 |
|
test123 | | | 12.59 346 | 15.49 347 | 3.87 357 | 6.07 372 | 2.55 372 | 90.75 337 | 2.59 375 | 2.52 367 | 5.20 370 | 13.02 368 | 4.96 374 | 1.85 370 | 5.20 366 | 9.09 366 | 7.23 366 |
|
test_part1 | | | | | 0.00 359 | | 0.00 374 | 0.00 365 | 98.84 88 | | | | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
v1.0 | | | 40.70 344 | 54.26 344 | 0.00 359 | 99.03 86 | 0.00 374 | 0.00 365 | 98.84 88 | 94.84 174 | 98.08 110 | 97.60 178 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
cdsmvs_eth3d_5k | | | 24.22 345 | 32.30 346 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 98.10 206 | 0.00 369 | 0.00 371 | 95.06 294 | 97.54 27 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
pcd_1.5k_mvsjas | | | 7.98 348 | 10.65 349 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 0.00 371 | 95.82 90 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
pcd1.5k->3k | | | 41.47 343 | 44.19 345 | 33.29 356 | 99.65 10 | 0.00 374 | 0.00 365 | 99.07 34 | 0.00 369 | 0.00 371 | 0.00 371 | 99.04 3 | 0.00 371 | 0.00 368 | 99.96 11 | 99.87 2 |
|
sosnet-low-res | | | 0.00 350 | 0.00 351 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 0.00 371 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
sosnet | | | 0.00 350 | 0.00 351 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 0.00 371 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
uncertanet | | | 0.00 350 | 0.00 351 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 0.00 371 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
Regformer | | | 0.00 350 | 0.00 351 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 0.00 371 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
ab-mvs-re | | | 7.91 349 | 10.55 350 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 94.94 296 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
uanet | | | 0.00 350 | 0.00 351 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 0.00 371 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
GSMVS | | | | | | | | | | | | | | | | | 98.06 259 |
|
test_part2 | | | | | | 99.03 86 | 96.07 66 | | | | 98.08 110 | | | | | | |
|
sam_mvs1 | | | | | | | | | | | | | 77.80 306 | | | | 98.06 259 |
|
sam_mvs | | | | | | | | | | | | | 77.38 310 | | | | |
|
MTGPA | ![Method available as binary. binary](img/icon_binary.png) | | | | | | | | 98.73 114 | | | | | | | | |
|
MTMP | | | | | | | | 96.55 131 | 74.60 369 | | | | | | | | |
|
test9_res | | | | | | | | | | | | | | | 91.29 226 | 98.89 216 | 99.00 160 |
|
agg_prior2 | | | | | | | | | | | | | | | 90.34 258 | 98.90 212 | 99.10 150 |
|
test_prior4 | | | | | | | 95.38 86 | 93.61 290 | | | | | | | | | |
|
test_prior2 | | | | | | | | 93.33 299 | | 94.21 198 | 94.02 286 | 96.25 260 | 93.64 169 | | 91.90 213 | 98.96 206 | |
|
æ–°å‡ ä½•2 | | | | | | | | 93.43 294 | | | | | | | | | |
|
旧先验1 | | | | | | 97.80 234 | 93.87 137 | | 97.75 227 | | | 97.04 212 | 93.57 171 | | | 98.68 234 | 98.72 201 |
|
原ACMM2 | | | | | | | | 92.82 307 | | | | | | | | | |
|
test222 | | | | | | 98.17 193 | 93.24 159 | 92.74 311 | 97.61 243 | 75.17 360 | 94.65 262 | 96.69 237 | 90.96 233 | | | 98.66 236 | 97.66 278 |
|
segment_acmp | | | | | | | | | | | | | 95.34 110 | | | | |
|
testdata1 | | | | | | | | 92.77 308 | | 93.78 214 | | | | | | | |
|
plane_prior7 | | | | | | 98.70 119 | 94.67 111 | | | | | | | | | | |
|
plane_prior6 | | | | | | 98.38 159 | 94.37 120 | | | | | | 91.91 220 | | | | |
|
plane_prior4 | | | | | | | | | | | | 96.77 231 | | | | | |
|
plane_prior3 | | | | | | | 94.51 114 | | | 95.29 153 | 96.16 224 | | | | | | |
|
plane_prior2 | | | | | | | | 96.50 134 | | 96.36 107 | | | | | | | |
|
plane_prior1 | | | | | | 98.49 149 | | | | | | | | | | | |
|
plane_prior | | | | | | | 94.29 122 | 95.42 200 | | 94.31 195 | | | | | | 98.93 211 | |
|
n2 | | | | | | | | | 0.00 376 | | | | | | | | |
|
nn | | | | | | | | | 0.00 376 | | | | | | | | |
|
door-mid | | | | | | | | | 98.17 199 | | | | | | | | |
|
test11 | | | | | | | | | 98.08 209 | | | | | | | | |
|
door | | | | | | | | | 97.81 225 | | | | | | | | |
|
HQP5-MVS | | | | | | | 92.47 168 | | | | | | | | | | |
|
HQP-NCC | | | | | | 97.85 223 | | 94.26 254 | | 93.18 226 | 92.86 321 | | | | | | |
|
ACMP_Plane | | | | | | 97.85 223 | | 94.26 254 | | 93.18 226 | 92.86 321 | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 90.51 252 | | |
|
HQP3-MVS | | | | | | | | | 98.43 160 | | | | | | | 98.74 227 | |
|
HQP2-MVS | | | | | | | | | | | | | 90.33 239 | | | | |
|
NP-MVS | | | | | | 98.14 198 | 93.72 144 | | | | | 95.08 292 | | | | | |
|
MDTV_nov1_ep13_2view | | | | | | | 57.28 370 | 94.89 235 | | 80.59 345 | 94.02 286 | | 78.66 304 | | 85.50 318 | | 97.82 273 |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 99.52 110 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 99.55 101 | |
|
Test By Simon | | | | | | | | | | | | | 94.51 139 | | | | |
|