LCM-MVSNet | | | 99.95 1 | 99.95 1 | 99.95 1 | 99.99 1 | 99.99 1 | 99.95 2 | 99.97 3 | 99.99 1 | 100.00 1 | 99.98 8 | 99.78 8 | 100.00 1 | 99.92 3 | 100.00 1 | 99.87 10 |
|
ANet_high | | | 99.88 4 | 99.87 4 | 99.91 2 | 99.99 1 | 99.91 3 | 99.65 55 | 100.00 1 | 99.90 6 | 100.00 1 | 99.97 10 | 99.61 17 | 99.97 16 | 99.75 31 | 100.00 1 | 99.84 15 |
|
Gipuma | | | 99.57 48 | 99.59 44 | 99.49 162 | 99.98 3 | 99.71 53 | 99.72 26 | 99.84 37 | 99.81 28 | 99.94 20 | 99.78 80 | 98.91 83 | 99.71 300 | 98.41 154 | 99.95 67 | 99.05 280 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
Anonymous20231211 | | | 99.83 11 | 99.81 10 | 99.89 6 | 99.97 4 | 99.95 2 | 99.88 4 | 99.93 6 | 99.87 13 | 99.94 20 | 99.98 8 | 99.55 21 | 99.95 41 | 99.21 81 | 99.98 36 | 99.78 31 |
|
anonymousdsp | | | 99.80 13 | 99.77 14 | 99.90 4 | 99.96 5 | 99.88 8 | 99.73 22 | 99.85 29 | 99.70 50 | 99.92 31 | 99.93 14 | 99.45 23 | 99.97 16 | 99.36 63 | 100.00 1 | 99.85 14 |
|
v7n | | | 99.82 12 | 99.80 12 | 99.88 12 | 99.96 5 | 99.84 19 | 99.82 10 | 99.82 48 | 99.84 23 | 99.94 20 | 99.91 20 | 99.13 57 | 99.96 33 | 99.83 20 | 99.99 20 | 99.83 18 |
|
PS-MVSNAJss | | | 99.84 9 | 99.82 9 | 99.89 6 | 99.96 5 | 99.77 38 | 99.68 42 | 99.85 29 | 99.95 3 | 99.98 3 | 99.92 17 | 99.28 39 | 99.98 7 | 99.75 31 | 100.00 1 | 99.94 2 |
|
jajsoiax | | | 99.89 3 | 99.89 3 | 99.89 6 | 99.96 5 | 99.78 36 | 99.70 30 | 99.86 22 | 99.89 10 | 99.98 3 | 99.90 23 | 99.94 2 | 99.98 7 | 99.75 31 | 100.00 1 | 99.90 5 |
|
mvs_tets | | | 99.90 2 | 99.90 2 | 99.90 4 | 99.96 5 | 99.79 34 | 99.72 26 | 99.88 18 | 99.92 5 | 99.98 3 | 99.93 14 | 99.94 2 | 99.98 7 | 99.77 30 | 100.00 1 | 99.92 3 |
|
v52 | | | 99.85 7 | 99.84 7 | 99.89 6 | 99.96 5 | 99.89 6 | 99.87 5 | 99.81 56 | 99.85 19 | 99.96 8 | 99.90 23 | 99.27 42 | 99.95 41 | 99.93 1 | 99.99 20 | 99.82 23 |
|
V4 | | | 99.85 7 | 99.84 7 | 99.88 12 | 99.96 5 | 99.89 6 | 99.87 5 | 99.81 56 | 99.85 19 | 99.96 8 | 99.90 23 | 99.27 42 | 99.95 41 | 99.93 1 | 100.00 1 | 99.82 23 |
|
OurMVSNet-221017-0 | | | 99.75 19 | 99.71 25 | 99.84 21 | 99.96 5 | 99.83 23 | 99.83 8 | 99.85 29 | 99.80 31 | 99.93 26 | 99.93 14 | 98.54 141 | 99.93 66 | 99.59 39 | 99.98 36 | 99.76 38 |
|
pcd1.5k->3k | | | 49.97 335 | 55.52 336 | 33.31 348 | 99.95 13 | 0.00 366 | 0.00 357 | 99.81 56 | 0.00 361 | 0.00 362 | 100.00 1 | 99.96 1 | 0.00 364 | 0.00 361 | 100.00 1 | 99.92 3 |
|
v748 | | | 99.76 17 | 99.74 21 | 99.84 21 | 99.95 13 | 99.83 23 | 99.82 10 | 99.80 60 | 99.82 27 | 99.95 16 | 99.87 37 | 98.72 112 | 99.93 66 | 99.72 34 | 99.98 36 | 99.75 41 |
|
pmmvs6 | | | 99.86 6 | 99.86 6 | 99.83 25 | 99.94 15 | 99.90 4 | 99.83 8 | 99.91 11 | 99.85 19 | 99.94 20 | 99.95 12 | 99.73 10 | 99.90 110 | 99.65 35 | 99.97 47 | 99.69 57 |
|
test_djsdf | | | 99.84 9 | 99.81 10 | 99.91 2 | 99.94 15 | 99.84 19 | 99.77 14 | 99.80 60 | 99.73 42 | 99.97 6 | 99.92 17 | 99.77 9 | 99.98 7 | 99.43 54 | 100.00 1 | 99.90 5 |
|
MIMVSNet1 | | | 99.66 37 | 99.62 38 | 99.80 30 | 99.94 15 | 99.87 9 | 99.69 39 | 99.77 73 | 99.78 34 | 99.93 26 | 99.89 31 | 97.94 193 | 99.92 84 | 99.65 35 | 99.98 36 | 99.62 114 |
|
K. test v3 | | | 98.87 204 | 98.60 212 | 99.69 80 | 99.93 18 | 99.46 112 | 99.74 20 | 94.97 358 | 99.78 34 | 99.88 47 | 99.88 34 | 93.66 289 | 99.97 16 | 99.61 38 | 99.95 67 | 99.64 96 |
|
SixPastTwentyTwo | | | 99.42 85 | 99.30 102 | 99.76 43 | 99.92 19 | 99.67 69 | 99.70 30 | 99.14 284 | 99.65 67 | 99.89 39 | 99.90 23 | 96.20 266 | 99.94 55 | 99.42 58 | 99.92 91 | 99.67 70 |
|
wuykxyi23d | | | 99.65 42 | 99.64 36 | 99.69 80 | 99.92 19 | 99.20 188 | 98.89 216 | 99.99 2 | 98.73 200 | 99.95 16 | 99.80 64 | 99.84 4 | 99.99 4 | 99.64 37 | 99.98 36 | 99.89 9 |
|
Anonymous20240521 | | | 99.67 36 | 99.62 38 | 99.84 21 | 99.91 21 | 99.85 13 | 99.81 12 | 99.76 79 | 99.72 45 | 99.92 31 | 99.83 51 | 98.10 181 | 99.90 110 | 99.58 41 | 99.97 47 | 99.77 34 |
|
pm-mvs1 | | | 99.79 14 | 99.79 13 | 99.78 38 | 99.91 21 | 99.83 23 | 99.76 17 | 99.87 20 | 99.73 42 | 99.89 39 | 99.87 37 | 99.63 15 | 99.87 161 | 99.54 45 | 99.92 91 | 99.63 100 |
|
TransMVSNet (Re) | | | 99.78 15 | 99.77 14 | 99.81 28 | 99.91 21 | 99.85 13 | 99.75 18 | 99.86 22 | 99.70 50 | 99.91 34 | 99.89 31 | 99.60 19 | 99.87 161 | 99.59 39 | 99.74 193 | 99.71 50 |
|
Baseline_NR-MVSNet | | | 99.49 69 | 99.37 88 | 99.82 26 | 99.91 21 | 99.84 19 | 98.83 227 | 99.86 22 | 99.68 57 | 99.65 128 | 99.88 34 | 97.67 214 | 99.87 161 | 99.03 107 | 99.86 129 | 99.76 38 |
|
LTVRE_ROB | | 99.19 1 | 99.88 4 | 99.87 4 | 99.88 12 | 99.91 21 | 99.90 4 | 99.96 1 | 99.92 7 | 99.90 6 | 99.97 6 | 99.87 37 | 99.81 7 | 99.95 41 | 99.54 45 | 99.99 20 | 99.80 25 |
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 |
PVSNet_Blended_VisFu | | | 99.40 91 | 99.38 85 | 99.44 176 | 99.90 26 | 98.66 239 | 98.94 214 | 99.91 11 | 97.97 256 | 99.79 80 | 99.73 99 | 99.05 69 | 99.97 16 | 99.15 94 | 99.99 20 | 99.68 63 |
|
TDRefinement | | | 99.72 25 | 99.70 28 | 99.77 40 | 99.90 26 | 99.85 13 | 99.86 7 | 99.92 7 | 99.69 54 | 99.78 83 | 99.92 17 | 99.37 30 | 99.88 141 | 98.93 123 | 99.95 67 | 99.60 125 |
|
XXY-MVS | | | 99.71 27 | 99.67 32 | 99.81 28 | 99.89 28 | 99.72 52 | 99.59 66 | 99.82 48 | 99.39 113 | 99.82 66 | 99.84 50 | 99.38 28 | 99.91 93 | 99.38 60 | 99.93 88 | 99.80 25 |
|
FC-MVSNet-test | | | 99.70 28 | 99.65 34 | 99.86 18 | 99.88 29 | 99.86 12 | 99.72 26 | 99.78 70 | 99.90 6 | 99.82 66 | 99.83 51 | 98.45 154 | 99.87 161 | 99.51 48 | 99.97 47 | 99.86 12 |
|
EU-MVSNet | | | 99.39 94 | 99.62 38 | 98.72 277 | 99.88 29 | 96.44 309 | 99.56 71 | 99.85 29 | 99.90 6 | 99.90 36 | 99.85 45 | 98.09 182 | 99.83 230 | 99.58 41 | 99.95 67 | 99.90 5 |
|
CHOSEN 1792x2688 | | | 99.39 94 | 99.30 102 | 99.65 98 | 99.88 29 | 99.25 175 | 98.78 236 | 99.88 18 | 98.66 204 | 99.96 8 | 99.79 71 | 97.45 225 | 99.93 66 | 99.34 65 | 99.99 20 | 99.78 31 |
|
Vis-MVSNet | | | 99.75 19 | 99.74 21 | 99.79 35 | 99.88 29 | 99.66 72 | 99.69 39 | 99.92 7 | 99.67 59 | 99.77 88 | 99.75 93 | 99.61 17 | 99.98 7 | 99.35 64 | 99.98 36 | 99.72 47 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
tfpnnormal | | | 99.43 82 | 99.38 85 | 99.60 127 | 99.87 33 | 99.75 45 | 99.59 66 | 99.78 70 | 99.71 48 | 99.90 36 | 99.69 125 | 98.85 89 | 99.90 110 | 97.25 233 | 99.78 177 | 99.15 255 |
|
SteuartSystems-ACMMP | | | 99.30 115 | 99.14 126 | 99.76 43 | 99.87 33 | 99.66 72 | 99.18 155 | 99.60 163 | 98.55 213 | 99.57 152 | 99.67 143 | 99.03 71 | 99.94 55 | 97.01 245 | 99.80 169 | 99.69 57 |
Skip Steuart: Steuart Systems R&D Blog. |
no-one | | | 99.28 118 | 99.23 118 | 99.45 174 | 99.87 33 | 99.08 203 | 98.95 211 | 99.52 204 | 98.88 178 | 99.77 88 | 99.83 51 | 97.78 206 | 99.90 110 | 98.46 152 | 99.99 20 | 99.38 216 |
|
v13 | | | 99.76 17 | 99.77 14 | 99.73 64 | 99.86 36 | 99.55 98 | 99.77 14 | 99.86 22 | 99.79 33 | 99.96 8 | 99.91 20 | 98.90 84 | 99.87 161 | 99.91 5 | 100.00 1 | 99.78 31 |
|
lessismore_v0 | | | | | 99.64 105 | 99.86 36 | 99.38 143 | | 90.66 361 | | 99.89 39 | 99.83 51 | 94.56 283 | 99.97 16 | 99.56 44 | 99.92 91 | 99.57 144 |
|
ACMH+ | | 98.40 8 | 99.50 67 | 99.43 79 | 99.71 73 | 99.86 36 | 99.76 42 | 99.32 114 | 99.77 73 | 99.53 89 | 99.77 88 | 99.76 89 | 99.26 45 | 99.78 273 | 97.77 199 | 99.88 115 | 99.60 125 |
|
ACMH | | 98.42 6 | 99.59 46 | 99.54 54 | 99.72 69 | 99.86 36 | 99.62 85 | 99.56 71 | 99.79 68 | 98.77 192 | 99.80 75 | 99.85 45 | 99.64 14 | 99.85 197 | 98.70 139 | 99.89 109 | 99.70 54 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
v12 | | | 99.75 19 | 99.77 14 | 99.72 69 | 99.85 40 | 99.53 101 | 99.75 18 | 99.86 22 | 99.78 34 | 99.96 8 | 99.90 23 | 98.88 87 | 99.86 181 | 99.91 5 | 100.00 1 | 99.77 34 |
|
v11 | | | 99.75 19 | 99.76 18 | 99.71 73 | 99.85 40 | 99.49 104 | 99.73 22 | 99.84 37 | 99.75 39 | 99.95 16 | 99.90 23 | 98.93 80 | 99.86 181 | 99.92 3 | 100.00 1 | 99.77 34 |
|
HyFIR lowres test | | | 98.91 197 | 98.64 210 | 99.73 64 | 99.85 40 | 99.47 108 | 98.07 302 | 99.83 40 | 98.64 206 | 99.89 39 | 99.60 181 | 92.57 299 | 100.00 1 | 99.33 67 | 99.97 47 | 99.72 47 |
|
FIs | | | 99.65 42 | 99.58 46 | 99.84 21 | 99.84 43 | 99.85 13 | 99.66 50 | 99.75 85 | 99.86 16 | 99.74 100 | 99.79 71 | 98.27 169 | 99.85 197 | 99.37 62 | 99.93 88 | 99.83 18 |
|
V9 | | | 99.74 23 | 99.75 20 | 99.71 73 | 99.84 43 | 99.50 102 | 99.74 20 | 99.86 22 | 99.76 38 | 99.96 8 | 99.90 23 | 98.83 90 | 99.85 197 | 99.91 5 | 100.00 1 | 99.77 34 |
|
XVG-OURS-SEG-HR | | | 99.16 154 | 98.99 172 | 99.66 94 | 99.84 43 | 99.64 79 | 98.25 283 | 99.73 93 | 98.39 226 | 99.63 134 | 99.43 231 | 99.70 12 | 99.90 110 | 97.34 226 | 98.64 317 | 99.44 199 |
|
PMVS | | 92.94 21 | 98.82 210 | 98.81 198 | 98.85 262 | 99.84 43 | 97.99 279 | 99.20 153 | 99.47 218 | 99.71 48 | 99.42 187 | 99.82 59 | 98.09 182 | 99.47 349 | 93.88 335 | 99.85 132 | 99.07 278 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
MP-MVS-pluss | | | 99.14 157 | 98.92 182 | 99.80 30 | 99.83 47 | 99.83 23 | 98.61 245 | 99.63 142 | 96.84 302 | 99.44 181 | 99.58 189 | 98.81 91 | 99.91 93 | 97.70 203 | 99.82 155 | 99.67 70 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
V14 | | | 99.73 24 | 99.74 21 | 99.69 80 | 99.83 47 | 99.48 107 | 99.72 26 | 99.85 29 | 99.74 40 | 99.96 8 | 99.89 31 | 98.79 98 | 99.85 197 | 99.91 5 | 100.00 1 | 99.76 38 |
|
PM-MVS | | | 99.36 101 | 99.29 107 | 99.58 133 | 99.83 47 | 99.66 72 | 98.95 211 | 99.86 22 | 98.85 181 | 99.81 72 | 99.73 99 | 98.40 159 | 99.92 84 | 98.36 158 | 99.83 146 | 99.17 253 |
|
PEN-MVS | | | 99.66 37 | 99.59 44 | 99.89 6 | 99.83 47 | 99.87 9 | 99.66 50 | 99.73 93 | 99.70 50 | 99.84 61 | 99.73 99 | 98.56 135 | 99.96 33 | 99.29 76 | 99.94 80 | 99.83 18 |
|
HPM-MVS_fast | | | 99.43 82 | 99.30 102 | 99.80 30 | 99.83 47 | 99.81 29 | 99.52 73 | 99.70 108 | 98.35 234 | 99.51 173 | 99.50 219 | 99.31 35 | 99.88 141 | 98.18 175 | 99.84 136 | 99.69 57 |
|
RPSCF | | | 99.18 149 | 99.02 164 | 99.64 105 | 99.83 47 | 99.85 13 | 99.44 84 | 99.82 48 | 98.33 239 | 99.50 175 | 99.78 80 | 97.90 195 | 99.65 332 | 96.78 256 | 99.83 146 | 99.44 199 |
|
COLMAP_ROB | | 98.06 12 | 99.45 80 | 99.37 88 | 99.70 79 | 99.83 47 | 99.70 60 | 99.38 95 | 99.78 70 | 99.53 89 | 99.67 118 | 99.78 80 | 99.19 49 | 99.86 181 | 97.32 227 | 99.87 122 | 99.55 148 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
TSAR-MVS + MP. | | | 99.34 108 | 99.24 116 | 99.63 109 | 99.82 54 | 99.37 146 | 99.26 137 | 99.35 250 | 98.77 192 | 99.57 152 | 99.70 119 | 99.27 42 | 99.88 141 | 97.71 202 | 99.75 186 | 99.65 90 |
|
new-patchmatchnet | | | 99.35 103 | 99.57 49 | 98.71 278 | 99.82 54 | 96.62 307 | 98.55 254 | 99.75 85 | 99.50 92 | 99.88 47 | 99.87 37 | 99.31 35 | 99.88 141 | 99.43 54 | 100.00 1 | 99.62 114 |
|
v15 | | | 99.72 25 | 99.73 24 | 99.68 83 | 99.82 54 | 99.44 119 | 99.70 30 | 99.85 29 | 99.72 45 | 99.95 16 | 99.88 34 | 98.76 105 | 99.84 213 | 99.90 9 | 100.00 1 | 99.75 41 |
|
VPNet | | | 99.46 78 | 99.37 88 | 99.71 73 | 99.82 54 | 99.59 90 | 99.48 79 | 99.70 108 | 99.81 28 | 99.69 112 | 99.58 189 | 97.66 218 | 99.86 181 | 99.17 90 | 99.44 254 | 99.67 70 |
|
XVG-OURS | | | 99.21 142 | 99.06 152 | 99.65 98 | 99.82 54 | 99.62 85 | 97.87 322 | 99.74 90 | 98.36 229 | 99.66 122 | 99.68 137 | 99.71 11 | 99.90 110 | 96.84 253 | 99.88 115 | 99.43 205 |
|
XVG-ACMP-BASELINE | | | 99.23 130 | 99.10 142 | 99.63 109 | 99.82 54 | 99.58 92 | 98.83 227 | 99.72 102 | 98.36 229 | 99.60 148 | 99.71 112 | 98.92 81 | 99.91 93 | 97.08 242 | 99.84 136 | 99.40 210 |
|
LPG-MVS_test | | | 99.22 139 | 99.05 157 | 99.74 56 | 99.82 54 | 99.63 83 | 99.16 168 | 99.73 93 | 97.56 279 | 99.64 130 | 99.69 125 | 99.37 30 | 99.89 126 | 96.66 263 | 99.87 122 | 99.69 57 |
|
LGP-MVS_train | | | | | 99.74 56 | 99.82 54 | 99.63 83 | | 99.73 93 | 97.56 279 | 99.64 130 | 99.69 125 | 99.37 30 | 99.89 126 | 96.66 263 | 99.87 122 | 99.69 57 |
|
zzz-MVS | | | 99.30 115 | 99.14 126 | 99.80 30 | 99.81 62 | 99.81 29 | 98.73 241 | 99.53 194 | 99.27 126 | 99.42 187 | 99.63 162 | 98.21 174 | 99.95 41 | 97.83 196 | 99.79 172 | 99.65 90 |
|
MTAPA | | | 99.35 103 | 99.20 122 | 99.80 30 | 99.81 62 | 99.81 29 | 99.33 111 | 99.53 194 | 99.27 126 | 99.42 187 | 99.63 162 | 98.21 174 | 99.95 41 | 97.83 196 | 99.79 172 | 99.65 90 |
|
testing_2 | | | 99.58 47 | 99.56 52 | 99.62 118 | 99.81 62 | 99.44 119 | 99.14 175 | 99.43 229 | 99.69 54 | 99.82 66 | 99.79 71 | 99.14 54 | 99.79 265 | 99.31 72 | 99.95 67 | 99.63 100 |
|
v17 | | | 99.70 28 | 99.71 25 | 99.67 86 | 99.81 62 | 99.44 119 | 99.70 30 | 99.83 40 | 99.69 54 | 99.94 20 | 99.87 37 | 98.70 113 | 99.84 213 | 99.88 14 | 99.99 20 | 99.73 44 |
|
v16 | | | 99.70 28 | 99.71 25 | 99.67 86 | 99.81 62 | 99.43 125 | 99.70 30 | 99.83 40 | 99.70 50 | 99.94 20 | 99.87 37 | 98.69 115 | 99.84 213 | 99.88 14 | 99.99 20 | 99.73 44 |
|
v10 | | | 99.69 32 | 99.69 29 | 99.66 94 | 99.81 62 | 99.39 137 | 99.66 50 | 99.75 85 | 99.60 82 | 99.92 31 | 99.87 37 | 98.75 108 | 99.86 181 | 99.90 9 | 99.99 20 | 99.73 44 |
|
HPM-MVS | | | 99.25 125 | 99.07 150 | 99.78 38 | 99.81 62 | 99.75 45 | 99.61 61 | 99.67 121 | 97.72 269 | 99.35 209 | 99.25 269 | 99.23 46 | 99.92 84 | 97.21 237 | 99.82 155 | 99.67 70 |
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
IterMVS-LS | | | 99.41 88 | 99.47 70 | 99.25 225 | 99.81 62 | 98.09 275 | 98.85 224 | 99.76 79 | 99.62 73 | 99.83 65 | 99.64 154 | 98.54 141 | 99.97 16 | 99.15 94 | 99.99 20 | 99.68 63 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
v1neww | | | 99.55 55 | 99.54 54 | 99.61 121 | 99.80 70 | 99.39 137 | 99.32 114 | 99.61 149 | 99.18 143 | 99.87 52 | 99.69 125 | 98.64 127 | 99.82 238 | 99.79 26 | 99.94 80 | 99.60 125 |
|
v7new | | | 99.55 55 | 99.54 54 | 99.61 121 | 99.80 70 | 99.39 137 | 99.32 114 | 99.61 149 | 99.18 143 | 99.87 52 | 99.69 125 | 98.64 127 | 99.82 238 | 99.79 26 | 99.94 80 | 99.60 125 |
|
v1240 | | | 99.56 51 | 99.58 46 | 99.51 158 | 99.80 70 | 99.00 208 | 99.00 201 | 99.65 134 | 99.15 150 | 99.90 36 | 99.75 93 | 99.09 61 | 99.88 141 | 99.90 9 | 99.96 60 | 99.67 70 |
|
v8 | | | 99.68 33 | 99.69 29 | 99.65 98 | 99.80 70 | 99.40 134 | 99.66 50 | 99.76 79 | 99.64 69 | 99.93 26 | 99.85 45 | 98.66 122 | 99.84 213 | 99.88 14 | 99.99 20 | 99.71 50 |
|
v7 | | | 99.56 51 | 99.54 54 | 99.61 121 | 99.80 70 | 99.39 137 | 99.30 124 | 99.59 167 | 99.14 152 | 99.82 66 | 99.72 105 | 98.75 108 | 99.84 213 | 99.83 20 | 99.94 80 | 99.61 119 |
|
v6 | | | 99.55 55 | 99.54 54 | 99.61 121 | 99.80 70 | 99.39 137 | 99.32 114 | 99.60 163 | 99.18 143 | 99.87 52 | 99.68 137 | 98.65 124 | 99.82 238 | 99.79 26 | 99.95 67 | 99.61 119 |
|
MDA-MVSNet-bldmvs | | | 99.06 168 | 99.05 157 | 99.07 244 | 99.80 70 | 97.83 285 | 98.89 216 | 99.72 102 | 99.29 122 | 99.63 134 | 99.70 119 | 96.47 259 | 99.89 126 | 98.17 177 | 99.82 155 | 99.50 176 |
|
PS-CasMVS | | | 99.66 37 | 99.58 46 | 99.89 6 | 99.80 70 | 99.85 13 | 99.66 50 | 99.73 93 | 99.62 73 | 99.84 61 | 99.71 112 | 98.62 129 | 99.96 33 | 99.30 73 | 99.96 60 | 99.86 12 |
|
DTE-MVSNet | | | 99.68 33 | 99.61 42 | 99.88 12 | 99.80 70 | 99.87 9 | 99.67 47 | 99.71 105 | 99.72 45 | 99.84 61 | 99.78 80 | 98.67 120 | 99.97 16 | 99.30 73 | 99.95 67 | 99.80 25 |
|
WR-MVS_H | | | 99.61 45 | 99.53 62 | 99.87 16 | 99.80 70 | 99.83 23 | 99.67 47 | 99.75 85 | 99.58 85 | 99.85 58 | 99.69 125 | 98.18 179 | 99.94 55 | 99.28 78 | 99.95 67 | 99.83 18 |
|
IS-MVSNet | | | 99.03 174 | 98.85 191 | 99.55 148 | 99.80 70 | 99.25 175 | 99.73 22 | 99.15 283 | 99.37 115 | 99.61 146 | 99.71 112 | 94.73 281 | 99.81 257 | 97.70 203 | 99.88 115 | 99.58 140 |
|
EPP-MVSNet | | | 99.17 152 | 99.00 169 | 99.66 94 | 99.80 70 | 99.43 125 | 99.70 30 | 99.24 275 | 99.48 94 | 99.56 159 | 99.77 86 | 94.89 279 | 99.93 66 | 98.72 138 | 99.89 109 | 99.63 100 |
|
ACMM | | 98.09 11 | 99.46 78 | 99.38 85 | 99.72 69 | 99.80 70 | 99.69 64 | 99.13 180 | 99.65 134 | 98.99 167 | 99.64 130 | 99.72 105 | 99.39 24 | 99.86 181 | 98.23 168 | 99.81 164 | 99.60 125 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
v1144 | | | 99.54 60 | 99.53 62 | 99.59 129 | 99.79 83 | 99.28 165 | 99.10 184 | 99.61 149 | 99.20 141 | 99.84 61 | 99.73 99 | 98.67 120 | 99.84 213 | 99.86 19 | 99.98 36 | 99.64 96 |
|
v18 | | | 99.68 33 | 99.69 29 | 99.65 98 | 99.79 83 | 99.40 134 | 99.68 42 | 99.83 40 | 99.66 64 | 99.93 26 | 99.85 45 | 98.65 124 | 99.84 213 | 99.87 18 | 99.99 20 | 99.71 50 |
|
V42 | | | 99.56 51 | 99.54 54 | 99.63 109 | 99.79 83 | 99.46 112 | 99.39 89 | 99.59 167 | 99.24 135 | 99.86 57 | 99.70 119 | 98.55 139 | 99.82 238 | 99.79 26 | 99.95 67 | 99.60 125 |
|
test20.03 | | | 99.55 55 | 99.54 54 | 99.58 133 | 99.79 83 | 99.37 146 | 99.02 197 | 99.89 15 | 99.60 82 | 99.82 66 | 99.62 169 | 98.81 91 | 99.89 126 | 99.43 54 | 99.86 129 | 99.47 188 |
|
test_0402 | | | 99.22 139 | 99.14 126 | 99.45 174 | 99.79 83 | 99.43 125 | 99.28 133 | 99.68 117 | 99.54 87 | 99.40 197 | 99.56 201 | 99.07 66 | 99.82 238 | 96.01 288 | 99.96 60 | 99.11 264 |
|
ACMMP | | | 99.25 125 | 99.08 146 | 99.74 56 | 99.79 83 | 99.68 67 | 99.50 75 | 99.65 134 | 98.07 250 | 99.52 171 | 99.69 125 | 98.57 134 | 99.92 84 | 97.18 239 | 99.79 172 | 99.63 100 |
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 |
HSP-MVS | | | 99.01 180 | 98.76 202 | 99.76 43 | 99.78 89 | 99.73 51 | 99.35 102 | 99.31 259 | 98.54 214 | 99.54 166 | 98.99 304 | 96.81 251 | 99.93 66 | 96.97 247 | 99.53 244 | 99.61 119 |
|
v144192 | | | 99.55 55 | 99.54 54 | 99.58 133 | 99.78 89 | 99.20 188 | 99.11 183 | 99.62 145 | 99.18 143 | 99.89 39 | 99.72 105 | 98.66 122 | 99.87 161 | 99.88 14 | 99.97 47 | 99.66 80 |
|
AllTest | | | 99.21 142 | 99.07 150 | 99.63 109 | 99.78 89 | 99.64 79 | 99.12 182 | 99.83 40 | 98.63 207 | 99.63 134 | 99.72 105 | 98.68 117 | 99.75 287 | 96.38 274 | 99.83 146 | 99.51 170 |
|
TestCases | | | | | 99.63 109 | 99.78 89 | 99.64 79 | | 99.83 40 | 98.63 207 | 99.63 134 | 99.72 105 | 98.68 117 | 99.75 287 | 96.38 274 | 99.83 146 | 99.51 170 |
|
v1141 | | | 99.54 60 | 99.52 64 | 99.57 139 | 99.78 89 | 99.27 169 | 99.15 170 | 99.61 149 | 99.26 130 | 99.89 39 | 99.69 125 | 98.56 135 | 99.82 238 | 99.82 23 | 99.97 47 | 99.63 100 |
|
divwei89l23v2f112 | | | 99.54 60 | 99.52 64 | 99.57 139 | 99.78 89 | 99.27 169 | 99.15 170 | 99.61 149 | 99.26 130 | 99.89 39 | 99.69 125 | 98.56 135 | 99.82 238 | 99.82 23 | 99.96 60 | 99.63 100 |
|
v2v482 | | | 99.50 67 | 99.47 70 | 99.58 133 | 99.78 89 | 99.25 175 | 99.14 175 | 99.58 175 | 99.25 133 | 99.81 72 | 99.62 169 | 98.24 171 | 99.84 213 | 99.83 20 | 99.97 47 | 99.64 96 |
|
FMVSNet1 | | | 99.66 37 | 99.63 37 | 99.73 64 | 99.78 89 | 99.77 38 | 99.68 42 | 99.70 108 | 99.67 59 | 99.82 66 | 99.83 51 | 98.98 74 | 99.90 110 | 99.24 80 | 99.97 47 | 99.53 159 |
|
Vis-MVSNet (Re-imp) | | | 98.77 216 | 98.58 215 | 99.34 203 | 99.78 89 | 98.88 225 | 99.61 61 | 99.56 182 | 99.11 155 | 99.24 230 | 99.56 201 | 93.00 297 | 99.78 273 | 97.43 222 | 99.89 109 | 99.35 225 |
|
ACMP | | 97.51 14 | 99.05 171 | 98.84 193 | 99.67 86 | 99.78 89 | 99.55 98 | 98.88 218 | 99.66 125 | 97.11 298 | 99.47 178 | 99.60 181 | 99.07 66 | 99.89 126 | 96.18 280 | 99.85 132 | 99.58 140 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
pmmvs-eth3d | | | 99.48 71 | 99.47 70 | 99.51 158 | 99.77 99 | 99.41 133 | 98.81 231 | 99.66 125 | 99.42 110 | 99.75 92 | 99.66 148 | 99.20 48 | 99.76 281 | 98.98 112 | 99.99 20 | 99.36 223 |
|
Patchmatch-RL test | | | 98.60 227 | 98.36 236 | 99.33 205 | 99.77 99 | 99.07 205 | 98.27 281 | 99.87 20 | 98.91 176 | 99.74 100 | 99.72 105 | 90.57 319 | 99.79 265 | 98.55 148 | 99.85 132 | 99.11 264 |
|
v1192 | | | 99.57 48 | 99.57 49 | 99.57 139 | 99.77 99 | 99.22 182 | 99.04 194 | 99.60 163 | 99.18 143 | 99.87 52 | 99.72 105 | 99.08 64 | 99.85 197 | 99.89 13 | 99.98 36 | 99.66 80 |
|
v1 | | | 99.54 60 | 99.52 64 | 99.58 133 | 99.77 99 | 99.28 165 | 99.15 170 | 99.61 149 | 99.26 130 | 99.88 47 | 99.68 137 | 98.56 135 | 99.82 238 | 99.82 23 | 99.97 47 | 99.63 100 |
|
EG-PatchMatch MVS | | | 99.57 48 | 99.56 52 | 99.62 118 | 99.77 99 | 99.33 156 | 99.26 137 | 99.76 79 | 99.32 121 | 99.80 75 | 99.78 80 | 99.29 37 | 99.87 161 | 99.15 94 | 99.91 101 | 99.66 80 |
|
pmmvs5 | | | 99.19 147 | 99.11 135 | 99.42 181 | 99.76 104 | 98.88 225 | 98.55 254 | 99.73 93 | 98.82 185 | 99.72 104 | 99.62 169 | 96.56 255 | 99.82 238 | 99.32 70 | 99.95 67 | 99.56 145 |
|
nrg030 | | | 99.70 28 | 99.66 33 | 99.82 26 | 99.76 104 | 99.84 19 | 99.61 61 | 99.70 108 | 99.93 4 | 99.78 83 | 99.68 137 | 99.10 59 | 99.78 273 | 99.45 52 | 99.96 60 | 99.83 18 |
|
v148 | | | 99.40 91 | 99.41 81 | 99.39 192 | 99.76 104 | 98.94 215 | 99.09 188 | 99.59 167 | 99.17 148 | 99.81 72 | 99.61 178 | 98.41 157 | 99.69 307 | 99.32 70 | 99.94 80 | 99.53 159 |
|
region2R | | | 99.23 130 | 99.05 157 | 99.77 40 | 99.76 104 | 99.70 60 | 99.31 121 | 99.59 167 | 98.41 224 | 99.32 217 | 99.36 246 | 98.73 111 | 99.93 66 | 97.29 229 | 99.74 193 | 99.67 70 |
|
MP-MVS | | | 99.06 168 | 98.83 196 | 99.76 43 | 99.76 104 | 99.71 53 | 99.32 114 | 99.50 209 | 98.35 234 | 98.97 259 | 99.48 222 | 98.37 162 | 99.92 84 | 95.95 294 | 99.75 186 | 99.63 100 |
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
PMMVS2 | | | 99.48 71 | 99.45 74 | 99.57 139 | 99.76 104 | 98.99 209 | 98.09 298 | 99.90 14 | 98.95 170 | 99.78 83 | 99.58 189 | 99.57 20 | 99.93 66 | 99.48 50 | 99.95 67 | 99.79 30 |
|
CP-MVSNet | | | 99.54 60 | 99.43 79 | 99.87 16 | 99.76 104 | 99.82 28 | 99.57 69 | 99.61 149 | 99.54 87 | 99.80 75 | 99.64 154 | 97.79 205 | 99.95 41 | 99.21 81 | 99.94 80 | 99.84 15 |
|
mPP-MVS | | | 99.19 147 | 99.00 169 | 99.76 43 | 99.76 104 | 99.68 67 | 99.38 95 | 99.54 189 | 98.34 238 | 99.01 256 | 99.50 219 | 98.53 145 | 99.93 66 | 97.18 239 | 99.78 177 | 99.66 80 |
|
semantic-postprocess | | | | | 98.51 282 | 99.75 112 | 95.90 320 | | 99.84 37 | 99.84 23 | 99.89 39 | 99.73 99 | 95.96 271 | 99.99 4 | 99.33 67 | 100.00 1 | 99.63 100 |
|
ACMMP_Plus | | | 99.28 118 | 99.11 135 | 99.79 35 | 99.75 112 | 99.81 29 | 98.95 211 | 99.53 194 | 98.27 243 | 99.53 169 | 99.73 99 | 98.75 108 | 99.87 161 | 97.70 203 | 99.83 146 | 99.68 63 |
|
v1921920 | | | 99.56 51 | 99.57 49 | 99.55 148 | 99.75 112 | 99.11 197 | 99.05 192 | 99.61 149 | 99.15 150 | 99.88 47 | 99.71 112 | 99.08 64 | 99.87 161 | 99.90 9 | 99.97 47 | 99.66 80 |
|
testgi | | | 99.29 117 | 99.26 113 | 99.37 198 | 99.75 112 | 98.81 232 | 98.84 225 | 99.89 15 | 98.38 227 | 99.75 92 | 99.04 303 | 99.36 33 | 99.86 181 | 99.08 104 | 99.25 282 | 99.45 194 |
|
PGM-MVS | | | 99.20 144 | 99.01 167 | 99.77 40 | 99.75 112 | 99.71 53 | 99.16 168 | 99.72 102 | 97.99 254 | 99.42 187 | 99.60 181 | 98.81 91 | 99.93 66 | 96.91 249 | 99.74 193 | 99.66 80 |
|
jason | | | 99.16 154 | 99.11 135 | 99.32 209 | 99.75 112 | 98.44 247 | 98.26 282 | 99.39 241 | 98.70 202 | 99.74 100 | 99.30 259 | 98.54 141 | 99.97 16 | 98.48 151 | 99.82 155 | 99.55 148 |
jason: jason. |
Anonymous20231206 | | | 99.35 103 | 99.31 97 | 99.47 167 | 99.74 118 | 99.06 207 | 99.28 133 | 99.74 90 | 99.23 137 | 99.72 104 | 99.53 210 | 97.63 220 | 99.88 141 | 99.11 102 | 99.84 136 | 99.48 183 |
|
ACMMPR | | | 99.23 130 | 99.06 152 | 99.76 43 | 99.74 118 | 99.69 64 | 99.31 121 | 99.59 167 | 98.36 229 | 99.35 209 | 99.38 240 | 98.61 131 | 99.93 66 | 97.43 222 | 99.75 186 | 99.67 70 |
|
IterMVS | | | 98.97 186 | 99.16 123 | 98.42 287 | 99.74 118 | 95.64 327 | 98.06 303 | 99.83 40 | 99.83 26 | 99.85 58 | 99.74 95 | 96.10 269 | 99.99 4 | 99.27 79 | 100.00 1 | 99.63 100 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
conf0.01 | | | 97.19 292 | 96.74 298 | 98.51 282 | 99.73 121 | 98.35 255 | 99.35 102 | 95.78 349 | 96.54 306 | 99.39 198 | 99.08 291 | 86.57 344 | 99.88 141 | 95.69 302 | 98.57 320 | 97.30 347 |
|
conf0.002 | | | 97.19 292 | 96.74 298 | 98.51 282 | 99.73 121 | 98.35 255 | 99.35 102 | 95.78 349 | 96.54 306 | 99.39 198 | 99.08 291 | 86.57 344 | 99.88 141 | 95.69 302 | 98.57 320 | 97.30 347 |
|
thresconf0.02 | | | 97.25 287 | 96.74 298 | 98.75 272 | 99.73 121 | 98.35 255 | 99.35 102 | 95.78 349 | 96.54 306 | 99.39 198 | 99.08 291 | 86.57 344 | 99.88 141 | 95.69 302 | 98.57 320 | 98.02 330 |
|
tfpn_n400 | | | 97.25 287 | 96.74 298 | 98.75 272 | 99.73 121 | 98.35 255 | 99.35 102 | 95.78 349 | 96.54 306 | 99.39 198 | 99.08 291 | 86.57 344 | 99.88 141 | 95.69 302 | 98.57 320 | 98.02 330 |
|
tfpnconf | | | 97.25 287 | 96.74 298 | 98.75 272 | 99.73 121 | 98.35 255 | 99.35 102 | 95.78 349 | 96.54 306 | 99.39 198 | 99.08 291 | 86.57 344 | 99.88 141 | 95.69 302 | 98.57 320 | 98.02 330 |
|
tfpnview11 | | | 97.25 287 | 96.74 298 | 98.75 272 | 99.73 121 | 98.35 255 | 99.35 102 | 95.78 349 | 96.54 306 | 99.39 198 | 99.08 291 | 86.57 344 | 99.88 141 | 95.69 302 | 98.57 320 | 98.02 330 |
|
HFP-MVS | | | 99.25 125 | 99.08 146 | 99.76 43 | 99.73 121 | 99.70 60 | 99.31 121 | 99.59 167 | 98.36 229 | 99.36 207 | 99.37 241 | 98.80 95 | 99.91 93 | 97.43 222 | 99.75 186 | 99.68 63 |
|
#test# | | | 99.12 160 | 98.90 185 | 99.76 43 | 99.73 121 | 99.70 60 | 99.10 184 | 99.59 167 | 97.60 277 | 99.36 207 | 99.37 241 | 98.80 95 | 99.91 93 | 96.84 253 | 99.75 186 | 99.68 63 |
|
testmv | | | 99.53 66 | 99.51 67 | 99.59 129 | 99.73 121 | 99.31 159 | 98.48 263 | 99.92 7 | 99.57 86 | 99.87 52 | 99.79 71 | 99.12 58 | 99.91 93 | 99.16 93 | 99.99 20 | 99.55 148 |
|
114514_t | | | 98.49 238 | 98.11 253 | 99.64 105 | 99.73 121 | 99.58 92 | 99.24 143 | 99.76 79 | 89.94 352 | 99.42 187 | 99.56 201 | 97.76 207 | 99.86 181 | 97.74 201 | 99.82 155 | 99.47 188 |
|
UA-Net | | | 99.78 15 | 99.76 18 | 99.86 18 | 99.72 131 | 99.71 53 | 99.91 3 | 99.95 5 | 99.96 2 | 99.71 108 | 99.91 20 | 99.15 53 | 99.97 16 | 99.50 49 | 100.00 1 | 99.90 5 |
|
N_pmnet | | | 98.73 221 | 98.53 221 | 99.35 202 | 99.72 131 | 98.67 238 | 98.34 277 | 94.65 359 | 98.35 234 | 99.79 80 | 99.68 137 | 98.03 186 | 99.93 66 | 98.28 166 | 99.92 91 | 99.44 199 |
|
DeepC-MVS | | 98.90 4 | 99.62 44 | 99.61 42 | 99.67 86 | 99.72 131 | 99.44 119 | 99.24 143 | 99.71 105 | 99.27 126 | 99.93 26 | 99.90 23 | 99.70 12 | 99.93 66 | 98.99 110 | 99.99 20 | 99.64 96 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
XVS | | | 99.27 123 | 99.11 135 | 99.75 52 | 99.71 134 | 99.71 53 | 99.37 99 | 99.61 149 | 99.29 122 | 98.76 284 | 99.47 225 | 98.47 151 | 99.88 141 | 97.62 210 | 99.73 199 | 99.67 70 |
|
X-MVStestdata | | | 96.09 323 | 94.87 331 | 99.75 52 | 99.71 134 | 99.71 53 | 99.37 99 | 99.61 149 | 99.29 122 | 98.76 284 | 61.30 365 | 98.47 151 | 99.88 141 | 97.62 210 | 99.73 199 | 99.67 70 |
|
VDDNet | | | 98.97 186 | 98.82 197 | 99.42 181 | 99.71 134 | 98.81 232 | 99.62 57 | 98.68 305 | 99.81 28 | 99.38 205 | 99.80 64 | 94.25 285 | 99.85 197 | 98.79 131 | 99.32 273 | 99.59 136 |
|
abl_6 | | | 99.36 101 | 99.23 118 | 99.75 52 | 99.71 134 | 99.74 50 | 99.33 111 | 99.76 79 | 99.07 162 | 99.65 128 | 99.63 162 | 99.09 61 | 99.92 84 | 97.13 241 | 99.76 183 | 99.58 140 |
|
DSMNet-mixed | | | 99.48 71 | 99.65 34 | 98.95 252 | 99.71 134 | 97.27 298 | 99.50 75 | 99.82 48 | 99.59 84 | 99.41 193 | 99.85 45 | 99.62 16 | 100.00 1 | 99.53 47 | 99.89 109 | 99.59 136 |
|
CSCG | | | 99.37 98 | 99.29 107 | 99.60 127 | 99.71 134 | 99.46 112 | 99.43 85 | 99.85 29 | 98.79 189 | 99.41 193 | 99.60 181 | 98.92 81 | 99.92 84 | 98.02 184 | 99.92 91 | 99.43 205 |
|
LF4IMVS | | | 99.01 180 | 98.92 182 | 99.27 216 | 99.71 134 | 99.28 165 | 98.59 248 | 99.77 73 | 98.32 240 | 99.39 198 | 99.41 235 | 98.62 129 | 99.84 213 | 96.62 266 | 99.84 136 | 98.69 301 |
|
OPM-MVS | | | 99.26 124 | 99.13 129 | 99.63 109 | 99.70 141 | 99.61 89 | 98.58 249 | 99.48 214 | 98.50 217 | 99.52 171 | 99.63 162 | 99.14 54 | 99.76 281 | 97.89 192 | 99.77 181 | 99.51 170 |
|
new_pmnet | | | 98.88 203 | 98.89 186 | 98.84 264 | 99.70 141 | 97.62 292 | 98.15 290 | 99.50 209 | 97.98 255 | 99.62 141 | 99.54 208 | 98.15 180 | 99.94 55 | 97.55 215 | 99.84 136 | 98.95 286 |
|
view600 | | | 96.86 302 | 96.52 305 | 97.88 307 | 99.69 143 | 95.87 322 | 99.39 89 | 97.68 330 | 99.11 155 | 98.96 261 | 97.82 347 | 87.40 330 | 99.79 265 | 89.78 343 | 98.83 301 | 97.98 334 |
|
view800 | | | 96.86 302 | 96.52 305 | 97.88 307 | 99.69 143 | 95.87 322 | 99.39 89 | 97.68 330 | 99.11 155 | 98.96 261 | 97.82 347 | 87.40 330 | 99.79 265 | 89.78 343 | 98.83 301 | 97.98 334 |
|
conf0.05thres1000 | | | 96.86 302 | 96.52 305 | 97.88 307 | 99.69 143 | 95.87 322 | 99.39 89 | 97.68 330 | 99.11 155 | 98.96 261 | 97.82 347 | 87.40 330 | 99.79 265 | 89.78 343 | 98.83 301 | 97.98 334 |
|
tfpn | | | 96.86 302 | 96.52 305 | 97.88 307 | 99.69 143 | 95.87 322 | 99.39 89 | 97.68 330 | 99.11 155 | 98.96 261 | 97.82 347 | 87.40 330 | 99.79 265 | 89.78 343 | 98.83 301 | 97.98 334 |
|
PNet_i23d | | | 97.02 297 | 97.87 270 | 94.49 344 | 99.69 143 | 84.81 363 | 95.18 356 | 99.85 29 | 97.83 266 | 99.32 217 | 99.57 196 | 95.53 276 | 99.47 349 | 96.09 282 | 97.74 348 | 99.18 251 |
|
wuyk23d | | | 97.58 279 | 99.13 129 | 92.93 345 | 99.69 143 | 99.49 104 | 99.52 73 | 99.77 73 | 97.97 256 | 99.96 8 | 99.79 71 | 99.84 4 | 99.94 55 | 95.85 296 | 99.82 155 | 79.36 358 |
|
DeepMVS_CX | | | | | 97.98 303 | 99.69 143 | 96.95 303 | | 99.26 269 | 75.51 357 | 95.74 356 | 98.28 340 | 96.47 259 | 99.62 337 | 91.23 341 | 97.89 346 | 97.38 345 |
|
VPA-MVSNet | | | 99.66 37 | 99.62 38 | 99.79 35 | 99.68 150 | 99.75 45 | 99.62 57 | 99.69 114 | 99.85 19 | 99.80 75 | 99.81 62 | 98.81 91 | 99.91 93 | 99.47 51 | 99.88 115 | 99.70 54 |
|
UnsupCasMVSNet_eth | | | 98.83 208 | 98.57 217 | 99.59 129 | 99.68 150 | 99.45 117 | 98.99 204 | 99.67 121 | 99.48 94 | 99.55 163 | 99.36 246 | 94.92 278 | 99.86 181 | 98.95 121 | 96.57 353 | 99.45 194 |
|
Test_1112_low_res | | | 98.95 192 | 98.73 203 | 99.63 109 | 99.68 150 | 99.15 194 | 98.09 298 | 99.80 60 | 97.14 295 | 99.46 180 | 99.40 236 | 96.11 268 | 99.89 126 | 99.01 109 | 99.84 136 | 99.84 15 |
|
MVE | | 92.54 22 | 96.66 310 | 96.11 314 | 98.31 294 | 99.68 150 | 97.55 294 | 97.94 317 | 95.60 355 | 99.37 115 | 90.68 359 | 98.70 329 | 96.56 255 | 98.61 359 | 86.94 357 | 99.55 239 | 98.77 299 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
tfpn1000 | | | 97.28 286 | 96.83 295 | 98.64 279 | 99.67 154 | 97.68 291 | 99.41 86 | 95.47 356 | 97.14 295 | 99.43 185 | 99.07 298 | 85.87 351 | 99.88 141 | 96.78 256 | 98.67 316 | 98.34 316 |
|
our_test_3 | | | 98.85 207 | 99.09 144 | 98.13 300 | 99.66 155 | 94.90 336 | 97.72 326 | 99.58 175 | 99.07 162 | 99.64 130 | 99.62 169 | 98.19 177 | 99.93 66 | 98.41 154 | 99.95 67 | 99.55 148 |
|
ppachtmachnet_test | | | 98.89 202 | 99.12 132 | 98.20 297 | 99.66 155 | 95.24 333 | 97.63 328 | 99.68 117 | 99.08 160 | 99.78 83 | 99.62 169 | 98.65 124 | 99.88 141 | 98.02 184 | 99.96 60 | 99.48 183 |
|
CP-MVS | | | 99.23 130 | 99.05 157 | 99.75 52 | 99.66 155 | 99.66 72 | 99.38 95 | 99.62 145 | 98.38 227 | 99.06 253 | 99.27 265 | 98.79 98 | 99.94 55 | 97.51 218 | 99.82 155 | 99.66 80 |
|
1112_ss | | | 99.05 171 | 98.84 193 | 99.67 86 | 99.66 155 | 99.29 163 | 98.52 259 | 99.82 48 | 97.65 274 | 99.43 185 | 99.16 282 | 96.42 261 | 99.91 93 | 99.07 105 | 99.84 136 | 99.80 25 |
|
1111 | | | 97.29 285 | 96.71 304 | 99.04 247 | 99.65 159 | 97.72 287 | 98.35 275 | 99.80 60 | 99.40 111 | 99.66 122 | 99.43 231 | 75.10 365 | 99.87 161 | 98.98 112 | 99.98 36 | 99.52 167 |
|
.test1245 | | | 85.84 334 | 89.27 335 | 75.54 347 | 99.65 159 | 97.72 287 | 98.35 275 | 99.80 60 | 99.40 111 | 99.66 122 | 99.43 231 | 75.10 365 | 99.87 161 | 98.98 112 | 33.07 359 | 29.03 360 |
|
YYNet1 | | | 98.95 192 | 98.99 172 | 98.84 264 | 99.64 161 | 97.14 301 | 98.22 285 | 99.32 255 | 98.92 175 | 99.59 149 | 99.66 148 | 97.40 227 | 99.83 230 | 98.27 167 | 99.90 103 | 99.55 148 |
|
MDA-MVSNet_test_wron | | | 98.95 192 | 98.99 172 | 98.85 262 | 99.64 161 | 97.16 300 | 98.23 284 | 99.33 253 | 98.93 173 | 99.56 159 | 99.66 148 | 97.39 229 | 99.83 230 | 98.29 165 | 99.88 115 | 99.55 148 |
|
tfpn111 | | | 96.50 313 | 96.12 313 | 97.65 318 | 99.63 163 | 95.93 317 | 99.18 155 | 97.57 335 | 98.75 197 | 98.70 289 | 97.31 357 | 87.04 335 | 99.72 294 | 88.27 350 | 98.61 319 | 97.30 347 |
|
conf200view11 | | | 96.43 314 | 96.03 316 | 97.63 319 | 99.63 163 | 95.93 317 | 99.18 155 | 97.57 335 | 98.75 197 | 98.70 289 | 97.31 357 | 87.04 335 | 99.67 320 | 87.62 352 | 98.51 329 | 97.30 347 |
|
thres100view900 | | | 96.39 316 | 96.03 316 | 97.47 322 | 99.63 163 | 95.93 317 | 99.18 155 | 97.57 335 | 98.75 197 | 98.70 289 | 97.31 357 | 87.04 335 | 99.67 320 | 87.62 352 | 98.51 329 | 96.81 352 |
|
thres600view7 | | | 96.60 311 | 96.16 312 | 97.93 305 | 99.63 163 | 96.09 315 | 99.18 155 | 97.57 335 | 98.77 192 | 98.72 287 | 97.32 356 | 87.04 335 | 99.72 294 | 88.57 348 | 98.62 318 | 97.98 334 |
|
ITE_SJBPF | | | | | 99.38 194 | 99.63 163 | 99.44 119 | | 99.73 93 | 98.56 212 | 99.33 215 | 99.53 210 | 98.88 87 | 99.68 315 | 96.01 288 | 99.65 221 | 99.02 283 |
|
test_part2 | | | | | | 99.62 168 | 99.67 69 | | | | 99.55 163 | | | | | | |
|
ESAPD | | | 98.87 204 | 98.58 215 | 99.74 56 | 99.62 168 | 99.67 69 | 98.74 238 | 99.53 194 | 97.71 270 | 99.55 163 | 99.57 196 | 98.40 159 | 99.90 110 | 94.47 327 | 99.68 210 | 99.66 80 |
|
CPTT-MVS | | | 98.74 219 | 98.44 225 | 99.64 105 | 99.61 170 | 99.38 143 | 99.18 155 | 99.55 185 | 96.49 312 | 99.27 224 | 99.37 241 | 97.11 244 | 99.92 84 | 95.74 301 | 99.67 216 | 99.62 114 |
|
tfpn_ndepth | | | 96.93 301 | 96.43 309 | 98.42 287 | 99.60 171 | 97.72 287 | 99.22 149 | 95.16 357 | 95.91 319 | 99.26 226 | 98.79 324 | 85.56 352 | 99.87 161 | 96.03 287 | 98.35 333 | 97.68 342 |
|
MSDG | | | 99.08 166 | 98.98 175 | 99.37 198 | 99.60 171 | 99.13 195 | 97.54 332 | 99.74 90 | 98.84 184 | 99.53 169 | 99.55 206 | 99.10 59 | 99.79 265 | 97.07 243 | 99.86 129 | 99.18 251 |
|
FPMVS | | | 96.32 318 | 95.50 325 | 98.79 269 | 99.60 171 | 98.17 269 | 98.46 268 | 98.80 299 | 97.16 294 | 96.28 351 | 99.63 162 | 82.19 356 | 99.09 355 | 88.45 349 | 98.89 300 | 99.10 268 |
|
xiu_mvs_v1_base_debu | | | 99.23 130 | 99.34 93 | 98.91 256 | 99.59 174 | 98.23 264 | 98.47 264 | 99.66 125 | 99.61 77 | 99.68 114 | 98.94 315 | 99.39 24 | 99.97 16 | 99.18 87 | 99.55 239 | 98.51 309 |
|
xiu_mvs_v1_base | | | 99.23 130 | 99.34 93 | 98.91 256 | 99.59 174 | 98.23 264 | 98.47 264 | 99.66 125 | 99.61 77 | 99.68 114 | 98.94 315 | 99.39 24 | 99.97 16 | 99.18 87 | 99.55 239 | 98.51 309 |
|
xiu_mvs_v1_base_debi | | | 99.23 130 | 99.34 93 | 98.91 256 | 99.59 174 | 98.23 264 | 98.47 264 | 99.66 125 | 99.61 77 | 99.68 114 | 98.94 315 | 99.39 24 | 99.97 16 | 99.18 87 | 99.55 239 | 98.51 309 |
|
tfpn200view9 | | | 96.30 319 | 95.89 318 | 97.53 320 | 99.58 177 | 96.11 313 | 99.00 201 | 97.54 340 | 98.43 221 | 98.52 303 | 96.98 362 | 86.85 339 | 99.67 320 | 87.62 352 | 98.51 329 | 96.81 352 |
|
EI-MVSNet | | | 99.38 96 | 99.44 76 | 99.21 230 | 99.58 177 | 98.09 275 | 99.26 137 | 99.46 221 | 99.62 73 | 99.75 92 | 99.67 143 | 98.54 141 | 99.85 197 | 99.15 94 | 99.92 91 | 99.68 63 |
|
CVMVSNet | | | 98.61 226 | 98.88 187 | 97.80 313 | 99.58 177 | 93.60 341 | 99.26 137 | 99.64 139 | 99.66 64 | 99.72 104 | 99.67 143 | 93.26 292 | 99.93 66 | 99.30 73 | 99.81 164 | 99.87 10 |
|
thres400 | | | 96.40 315 | 95.89 318 | 97.92 306 | 99.58 177 | 96.11 313 | 99.00 201 | 97.54 340 | 98.43 221 | 98.52 303 | 96.98 362 | 86.85 339 | 99.67 320 | 87.62 352 | 98.51 329 | 97.98 334 |
|
MCST-MVS | | | 99.02 176 | 98.81 198 | 99.65 98 | 99.58 177 | 99.49 104 | 98.58 249 | 99.07 287 | 98.40 225 | 99.04 254 | 99.25 269 | 98.51 149 | 99.80 262 | 97.31 228 | 99.51 246 | 99.65 90 |
|
HQP_MVS | | | 98.90 199 | 98.68 207 | 99.55 148 | 99.58 177 | 99.24 178 | 98.80 232 | 99.54 189 | 98.94 171 | 99.14 244 | 99.25 269 | 97.24 235 | 99.82 238 | 95.84 297 | 99.78 177 | 99.60 125 |
|
plane_prior7 | | | | | | 99.58 177 | 99.38 143 | | | | | | | | | | |
|
TranMVSNet+NR-MVSNet | | | 99.54 60 | 99.47 70 | 99.76 43 | 99.58 177 | 99.64 79 | 99.30 124 | 99.63 142 | 99.61 77 | 99.71 108 | 99.56 201 | 98.76 105 | 99.96 33 | 99.14 100 | 99.92 91 | 99.68 63 |
|
MVS_111021_LR | | | 99.13 158 | 99.03 163 | 99.42 181 | 99.58 177 | 99.32 158 | 97.91 321 | 99.73 93 | 98.68 203 | 99.31 219 | 99.48 222 | 99.09 61 | 99.66 325 | 97.70 203 | 99.77 181 | 99.29 237 |
|
EI-MVSNet-UG-set | | | 99.48 71 | 99.50 68 | 99.42 181 | 99.57 186 | 98.65 241 | 99.24 143 | 99.46 221 | 99.68 57 | 99.80 75 | 99.66 148 | 98.99 73 | 99.89 126 | 99.19 85 | 99.90 103 | 99.72 47 |
|
EI-MVSNet-Vis-set | | | 99.47 77 | 99.49 69 | 99.42 181 | 99.57 186 | 98.66 239 | 99.24 143 | 99.46 221 | 99.67 59 | 99.79 80 | 99.65 153 | 98.97 76 | 99.89 126 | 99.15 94 | 99.89 109 | 99.71 50 |
|
pmmvs4 | | | 99.13 158 | 99.06 152 | 99.36 201 | 99.57 186 | 99.10 200 | 98.01 306 | 99.25 272 | 98.78 191 | 99.58 150 | 99.44 230 | 98.24 171 | 99.76 281 | 98.74 136 | 99.93 88 | 99.22 241 |
|
DI_MVS_plusplus_test | | | 98.80 213 | 98.65 209 | 99.27 216 | 99.57 186 | 98.90 222 | 98.44 270 | 97.95 326 | 99.02 166 | 99.51 173 | 99.23 277 | 96.18 267 | 99.76 281 | 98.52 150 | 99.42 261 | 99.14 259 |
|
MVSFormer | | | 99.41 88 | 99.44 76 | 99.31 211 | 99.57 186 | 98.40 250 | 99.77 14 | 99.80 60 | 99.73 42 | 99.63 134 | 99.30 259 | 98.02 188 | 99.98 7 | 99.43 54 | 99.69 208 | 99.55 148 |
|
lupinMVS | | | 98.96 189 | 98.87 188 | 99.24 227 | 99.57 186 | 98.40 250 | 98.12 294 | 99.18 280 | 98.28 242 | 99.63 134 | 99.13 284 | 98.02 188 | 99.97 16 | 98.22 169 | 99.69 208 | 99.35 225 |
|
Test4 | | | 98.65 224 | 98.44 225 | 99.27 216 | 99.57 186 | 98.86 228 | 98.43 271 | 99.41 232 | 98.85 181 | 99.57 152 | 98.95 314 | 93.05 295 | 99.75 287 | 98.57 146 | 99.56 233 | 99.19 248 |
|
ab-mvs | | | 99.33 111 | 99.28 109 | 99.47 167 | 99.57 186 | 99.39 137 | 99.78 13 | 99.43 229 | 98.87 179 | 99.57 152 | 99.82 59 | 98.06 185 | 99.87 161 | 98.69 140 | 99.73 199 | 99.15 255 |
|
DP-MVS | | | 99.48 71 | 99.39 83 | 99.74 56 | 99.57 186 | 99.62 85 | 99.29 132 | 99.61 149 | 99.87 13 | 99.74 100 | 99.76 89 | 98.69 115 | 99.87 161 | 98.20 171 | 99.80 169 | 99.75 41 |
|
F-COLMAP | | | 98.74 219 | 98.45 224 | 99.62 118 | 99.57 186 | 99.47 108 | 98.84 225 | 99.65 134 | 96.31 314 | 98.93 267 | 99.19 281 | 97.68 213 | 99.87 161 | 96.52 269 | 99.37 268 | 99.53 159 |
|
CLD-MVS | | | 98.76 217 | 98.57 217 | 99.33 205 | 99.57 186 | 98.97 212 | 97.53 334 | 99.55 185 | 96.41 313 | 99.27 224 | 99.13 284 | 99.07 66 | 99.78 273 | 96.73 260 | 99.89 109 | 99.23 240 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
test_normal | | | 98.82 210 | 98.67 208 | 99.27 216 | 99.56 197 | 98.83 231 | 98.22 285 | 98.01 323 | 99.03 165 | 99.49 177 | 99.24 274 | 96.21 265 | 99.76 281 | 98.69 140 | 99.56 233 | 99.22 241 |
|
UnsupCasMVSNet_bld | | | 98.55 233 | 98.27 242 | 99.40 189 | 99.56 197 | 99.37 146 | 97.97 314 | 99.68 117 | 97.49 284 | 99.08 249 | 99.35 251 | 95.41 277 | 99.82 238 | 97.70 203 | 98.19 339 | 99.01 284 |
|
APDe-MVS | | | 99.48 71 | 99.36 91 | 99.85 20 | 99.55 199 | 99.81 29 | 99.50 75 | 99.69 114 | 98.99 167 | 99.75 92 | 99.71 112 | 98.79 98 | 99.93 66 | 98.46 152 | 99.85 132 | 99.80 25 |
|
PVSNet_BlendedMVS | | | 99.03 174 | 99.01 167 | 99.09 240 | 99.54 200 | 97.99 279 | 98.58 249 | 99.82 48 | 97.62 275 | 99.34 213 | 99.71 112 | 98.52 147 | 99.77 279 | 97.98 188 | 99.97 47 | 99.52 167 |
|
PVSNet_Blended | | | 98.70 222 | 98.59 213 | 99.02 249 | 99.54 200 | 97.99 279 | 97.58 331 | 99.82 48 | 95.70 325 | 99.34 213 | 98.98 307 | 98.52 147 | 99.77 279 | 97.98 188 | 99.83 146 | 99.30 234 |
|
USDC | | | 98.96 189 | 98.93 179 | 99.05 246 | 99.54 200 | 97.99 279 | 97.07 344 | 99.80 60 | 98.21 245 | 99.75 92 | 99.77 86 | 98.43 155 | 99.64 334 | 97.90 191 | 99.88 115 | 99.51 170 |
|
APD-MVS_3200maxsize | | | 99.31 114 | 99.16 123 | 99.74 56 | 99.53 203 | 99.75 45 | 99.27 136 | 99.61 149 | 99.19 142 | 99.57 152 | 99.64 154 | 98.76 105 | 99.90 110 | 97.29 229 | 99.62 224 | 99.56 145 |
|
MIMVSNet | | | 98.43 243 | 98.20 247 | 99.11 238 | 99.53 203 | 98.38 253 | 99.58 68 | 98.61 307 | 98.96 169 | 99.33 215 | 99.76 89 | 90.92 312 | 99.81 257 | 97.38 225 | 99.76 183 | 99.15 255 |
|
Regformer-3 | | | 99.41 88 | 99.41 81 | 99.40 189 | 99.52 205 | 98.70 236 | 99.17 162 | 99.44 226 | 99.62 73 | 99.75 92 | 99.60 181 | 98.90 84 | 99.85 197 | 98.89 125 | 99.84 136 | 99.65 90 |
|
Regformer-4 | | | 99.45 80 | 99.44 76 | 99.50 160 | 99.52 205 | 98.94 215 | 99.17 162 | 99.53 194 | 99.64 69 | 99.76 91 | 99.60 181 | 98.96 79 | 99.90 110 | 98.91 124 | 99.84 136 | 99.67 70 |
|
HPM-MVS++ | | | 98.96 189 | 98.70 205 | 99.74 56 | 99.52 205 | 99.71 53 | 98.86 221 | 99.19 279 | 98.47 220 | 98.59 299 | 99.06 299 | 98.08 184 | 99.91 93 | 96.94 248 | 99.60 229 | 99.60 125 |
|
GA-MVS | | | 97.99 271 | 97.68 278 | 98.93 255 | 99.52 205 | 98.04 278 | 97.19 343 | 99.05 290 | 98.32 240 | 98.81 278 | 98.97 310 | 89.89 326 | 99.41 353 | 98.33 161 | 99.05 292 | 99.34 227 |
|
test222 | | | | | | 99.51 209 | 99.08 203 | 97.83 324 | 99.29 263 | 95.21 332 | 98.68 293 | 99.31 256 | 97.28 234 | | | 99.38 266 | 99.43 205 |
|
testdata | | | | | 99.42 181 | 99.51 209 | 98.93 219 | | 99.30 262 | 96.20 315 | 98.87 274 | 99.40 236 | 98.33 166 | 99.89 126 | 96.29 277 | 99.28 277 | 99.44 199 |
|
plane_prior1 | | | | | | 99.51 209 | | | | | | | | | | | |
|
UniMVSNet (Re) | | | 99.37 98 | 99.26 113 | 99.68 83 | 99.51 209 | 99.58 92 | 98.98 208 | 99.60 163 | 99.43 108 | 99.70 110 | 99.36 246 | 97.70 209 | 99.88 141 | 99.20 84 | 99.87 122 | 99.59 136 |
|
DELS-MVS | | | 99.34 108 | 99.30 102 | 99.48 165 | 99.51 209 | 99.36 149 | 98.12 294 | 99.53 194 | 99.36 117 | 99.41 193 | 99.61 178 | 99.22 47 | 99.87 161 | 99.21 81 | 99.68 210 | 99.20 245 |
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 |
新几何1 | | | | | 99.52 155 | 99.50 214 | 99.22 182 | | 99.26 269 | 95.66 327 | 98.60 298 | 99.28 263 | 97.67 214 | 99.89 126 | 95.95 294 | 99.32 273 | 99.45 194 |
|
SD-MVS | | | 99.01 180 | 99.30 102 | 98.15 299 | 99.50 214 | 99.40 134 | 98.94 214 | 99.61 149 | 99.22 140 | 99.75 92 | 99.82 59 | 99.54 22 | 95.51 361 | 97.48 219 | 99.87 122 | 99.54 156 |
|
CDPH-MVS | | | 98.56 231 | 98.20 247 | 99.61 121 | 99.50 214 | 99.46 112 | 98.32 279 | 99.41 232 | 95.22 331 | 99.21 235 | 99.10 290 | 98.34 164 | 99.82 238 | 95.09 321 | 99.66 219 | 99.56 145 |
|
APD-MVS | | | 98.87 204 | 98.59 213 | 99.71 73 | 99.50 214 | 99.62 85 | 99.01 199 | 99.57 179 | 96.80 304 | 99.54 166 | 99.63 162 | 98.29 167 | 99.91 93 | 95.24 318 | 99.71 205 | 99.61 119 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
MVS_111021_HR | | | 99.12 160 | 99.02 164 | 99.40 189 | 99.50 214 | 99.11 197 | 97.92 319 | 99.71 105 | 98.76 195 | 99.08 249 | 99.47 225 | 99.17 51 | 99.54 345 | 97.85 195 | 99.76 183 | 99.54 156 |
|
旧先验1 | | | | | | 99.49 219 | 99.29 163 | | 99.26 269 | | | 99.39 239 | 97.67 214 | | | 99.36 269 | 99.46 192 |
|
1121 | | | 98.56 231 | 98.24 243 | 99.52 155 | 99.49 219 | 99.24 178 | 99.30 124 | 99.22 277 | 95.77 323 | 98.52 303 | 99.29 262 | 97.39 229 | 99.85 197 | 95.79 299 | 99.34 270 | 99.46 192 |
|
GBi-Net | | | 99.42 85 | 99.31 97 | 99.73 64 | 99.49 219 | 99.77 38 | 99.68 42 | 99.70 108 | 99.44 103 | 99.62 141 | 99.83 51 | 97.21 238 | 99.90 110 | 98.96 117 | 99.90 103 | 99.53 159 |
|
test1 | | | 99.42 85 | 99.31 97 | 99.73 64 | 99.49 219 | 99.77 38 | 99.68 42 | 99.70 108 | 99.44 103 | 99.62 141 | 99.83 51 | 97.21 238 | 99.90 110 | 98.96 117 | 99.90 103 | 99.53 159 |
|
FMVSNet2 | | | 99.35 103 | 99.28 109 | 99.55 148 | 99.49 219 | 99.35 153 | 99.45 82 | 99.57 179 | 99.44 103 | 99.70 110 | 99.74 95 | 97.21 238 | 99.87 161 | 99.03 107 | 99.94 80 | 99.44 199 |
|
DP-MVS Recon | | | 98.50 236 | 98.23 244 | 99.31 211 | 99.49 219 | 99.46 112 | 98.56 253 | 99.63 142 | 94.86 337 | 98.85 276 | 99.37 241 | 97.81 203 | 99.59 342 | 96.08 283 | 99.44 254 | 98.88 291 |
|
MVP-Stereo | | | 99.16 154 | 99.08 146 | 99.43 179 | 99.48 225 | 99.07 205 | 99.08 189 | 99.55 185 | 98.63 207 | 99.31 219 | 99.68 137 | 98.19 177 | 99.78 273 | 98.18 175 | 99.58 231 | 99.45 194 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
thres200 | | | 96.09 323 | 95.68 324 | 97.33 326 | 99.48 225 | 96.22 312 | 98.53 258 | 97.57 335 | 98.06 251 | 98.37 311 | 96.73 364 | 86.84 341 | 99.61 341 | 86.99 356 | 98.57 320 | 96.16 355 |
|
sss | | | 98.90 199 | 98.77 201 | 99.27 216 | 99.48 225 | 98.44 247 | 98.72 242 | 99.32 255 | 97.94 258 | 99.37 206 | 99.35 251 | 96.31 263 | 99.91 93 | 98.85 127 | 99.63 223 | 99.47 188 |
|
PAPM_NR | | | 98.36 250 | 98.04 257 | 99.33 205 | 99.48 225 | 98.93 219 | 98.79 235 | 99.28 266 | 97.54 282 | 98.56 302 | 98.57 333 | 97.12 243 | 99.69 307 | 94.09 333 | 98.90 299 | 99.38 216 |
|
TAMVS | | | 99.49 69 | 99.45 74 | 99.63 109 | 99.48 225 | 99.42 129 | 99.45 82 | 99.57 179 | 99.66 64 | 99.78 83 | 99.83 51 | 97.85 200 | 99.86 181 | 99.44 53 | 99.96 60 | 99.61 119 |
|
原ACMM1 | | | | | 99.37 198 | 99.47 230 | 98.87 227 | | 99.27 267 | 96.74 305 | 98.26 314 | 99.32 254 | 97.93 194 | 99.82 238 | 95.96 293 | 99.38 266 | 99.43 205 |
|
plane_prior6 | | | | | | 99.47 230 | 99.26 171 | | | | | | 97.24 235 | | | | |
|
UniMVSNet_NR-MVSNet | | | 99.37 98 | 99.25 115 | 99.72 69 | 99.47 230 | 99.56 95 | 98.97 209 | 99.61 149 | 99.43 108 | 99.67 118 | 99.28 263 | 97.85 200 | 99.95 41 | 99.17 90 | 99.81 164 | 99.65 90 |
|
TAPA-MVS | | 97.92 13 | 98.03 269 | 97.55 281 | 99.46 170 | 99.47 230 | 99.44 119 | 98.50 261 | 99.62 145 | 86.79 353 | 99.07 252 | 99.26 267 | 98.26 170 | 99.62 337 | 97.28 231 | 99.73 199 | 99.31 233 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
SMA-MVS | | | 99.23 130 | 99.06 152 | 99.74 56 | 99.46 234 | 99.76 42 | 99.13 180 | 99.58 175 | 97.62 275 | 99.68 114 | 99.64 154 | 99.02 72 | 99.83 230 | 97.61 212 | 99.82 155 | 99.63 100 |
|
test12356 | | | 98.43 243 | 98.39 232 | 98.55 281 | 99.46 234 | 96.36 310 | 97.32 341 | 99.81 56 | 97.60 277 | 99.62 141 | 99.37 241 | 94.57 282 | 99.89 126 | 97.80 198 | 99.92 91 | 99.40 210 |
|
test1235678 | | | 98.93 196 | 98.84 193 | 99.19 233 | 99.46 234 | 98.55 243 | 97.53 334 | 99.77 73 | 98.76 195 | 99.69 112 | 99.48 222 | 96.69 252 | 99.90 110 | 98.30 164 | 99.91 101 | 99.11 264 |
|
PVSNet | | 97.47 15 | 98.42 245 | 98.44 225 | 98.35 291 | 99.46 234 | 96.26 311 | 96.70 349 | 99.34 252 | 97.68 273 | 99.00 257 | 99.13 284 | 97.40 227 | 99.72 294 | 97.59 214 | 99.68 210 | 99.08 274 |
|
TinyColmap | | | 98.97 186 | 98.93 179 | 99.07 244 | 99.46 234 | 98.19 267 | 97.75 325 | 99.75 85 | 98.79 189 | 99.54 166 | 99.70 119 | 98.97 76 | 99.62 337 | 96.63 265 | 99.83 146 | 99.41 209 |
|
PatchMatch-RL | | | 98.68 223 | 98.47 222 | 99.30 213 | 99.44 239 | 99.28 165 | 98.14 292 | 99.54 189 | 97.12 297 | 99.11 247 | 99.25 269 | 97.80 204 | 99.70 301 | 96.51 270 | 99.30 275 | 98.93 288 |
|
PCF-MVS | | 96.03 18 | 96.73 308 | 95.86 320 | 99.33 205 | 99.44 239 | 99.16 192 | 96.87 346 | 99.44 226 | 86.58 354 | 98.95 265 | 99.40 236 | 94.38 284 | 99.88 141 | 87.93 351 | 99.80 169 | 98.95 286 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
VDD-MVS | | | 99.20 144 | 99.11 135 | 99.44 176 | 99.43 241 | 98.98 210 | 99.50 75 | 98.32 319 | 99.80 31 | 99.56 159 | 99.69 125 | 96.99 248 | 99.85 197 | 98.99 110 | 99.73 199 | 99.50 176 |
|
DU-MVS | | | 99.33 111 | 99.21 121 | 99.71 73 | 99.43 241 | 99.56 95 | 98.83 227 | 99.53 194 | 99.38 114 | 99.67 118 | 99.36 246 | 97.67 214 | 99.95 41 | 99.17 90 | 99.81 164 | 99.63 100 |
|
NR-MVSNet | | | 99.40 91 | 99.31 97 | 99.68 83 | 99.43 241 | 99.55 98 | 99.73 22 | 99.50 209 | 99.46 101 | 99.88 47 | 99.36 246 | 97.54 221 | 99.87 161 | 98.97 116 | 99.87 122 | 99.63 100 |
|
WTY-MVS | | | 98.59 229 | 98.37 235 | 99.26 221 | 99.43 241 | 98.40 250 | 98.74 238 | 99.13 286 | 98.10 249 | 99.21 235 | 99.24 274 | 94.82 280 | 99.90 110 | 97.86 194 | 98.77 308 | 99.49 182 |
|
casdiffmvs | | | 99.24 128 | 99.23 118 | 99.26 221 | 99.42 245 | 98.85 230 | 99.48 79 | 99.58 175 | 99.67 59 | 98.70 289 | 99.67 143 | 97.85 200 | 99.72 294 | 99.41 59 | 99.28 277 | 99.20 245 |
|
Regformer-1 | | | 99.32 113 | 99.27 111 | 99.47 167 | 99.41 246 | 98.95 214 | 98.99 204 | 99.48 214 | 99.48 94 | 99.66 122 | 99.52 212 | 98.78 101 | 99.87 161 | 98.36 158 | 99.74 193 | 99.60 125 |
|
Regformer-2 | | | 99.34 108 | 99.27 111 | 99.53 153 | 99.41 246 | 99.10 200 | 98.99 204 | 99.53 194 | 99.47 98 | 99.66 122 | 99.52 212 | 98.80 95 | 99.89 126 | 98.31 163 | 99.74 193 | 99.60 125 |
|
pmmvs3 | | | 98.08 267 | 97.80 272 | 98.91 256 | 99.41 246 | 97.69 290 | 97.87 322 | 99.66 125 | 95.87 320 | 99.50 175 | 99.51 216 | 90.35 321 | 99.97 16 | 98.55 148 | 99.47 251 | 99.08 274 |
|
NP-MVS | | | | | | 99.40 249 | 99.13 195 | | | | | 98.83 321 | | | | | |
|
QAPM | | | 98.40 248 | 97.99 259 | 99.65 98 | 99.39 250 | 99.47 108 | 99.67 47 | 99.52 204 | 91.70 349 | 98.78 283 | 99.80 64 | 98.55 139 | 99.95 41 | 94.71 325 | 99.75 186 | 99.53 159 |
|
OMC-MVS | | | 98.90 199 | 98.72 204 | 99.44 176 | 99.39 250 | 99.42 129 | 98.58 249 | 99.64 139 | 97.31 291 | 99.44 181 | 99.62 169 | 98.59 133 | 99.69 307 | 96.17 281 | 99.79 172 | 99.22 241 |
|
3Dnovator | | 99.15 2 | 99.43 82 | 99.36 91 | 99.65 98 | 99.39 250 | 99.42 129 | 99.70 30 | 99.56 182 | 99.23 137 | 99.35 209 | 99.80 64 | 99.17 51 | 99.95 41 | 98.21 170 | 99.84 136 | 99.59 136 |
|
Fast-Effi-MVS+ | | | 99.02 176 | 98.87 188 | 99.46 170 | 99.38 253 | 99.50 102 | 99.04 194 | 99.79 68 | 97.17 293 | 98.62 296 | 98.74 328 | 99.34 34 | 99.95 41 | 98.32 162 | 99.41 263 | 98.92 289 |
|
BH-untuned | | | 98.22 261 | 98.09 254 | 98.58 280 | 99.38 253 | 97.24 299 | 98.55 254 | 98.98 293 | 97.81 267 | 99.20 240 | 98.76 326 | 97.01 247 | 99.65 332 | 94.83 322 | 98.33 334 | 98.86 293 |
|
xiu_mvs_v2_base | | | 99.02 176 | 99.11 135 | 98.77 270 | 99.37 255 | 98.09 275 | 98.13 293 | 99.51 206 | 99.47 98 | 99.42 187 | 98.54 335 | 99.38 28 | 99.97 16 | 98.83 128 | 99.33 272 | 98.24 321 |
|
PS-MVSNAJ | | | 99.00 183 | 99.08 146 | 98.76 271 | 99.37 255 | 98.10 274 | 98.00 308 | 99.51 206 | 99.47 98 | 99.41 193 | 98.50 337 | 99.28 39 | 99.97 16 | 98.83 128 | 99.34 270 | 98.20 325 |
|
diffmvs | | | 98.94 195 | 98.87 188 | 99.13 237 | 99.37 255 | 98.90 222 | 99.25 141 | 99.64 139 | 97.55 281 | 99.04 254 | 99.58 189 | 97.23 237 | 99.64 334 | 98.73 137 | 99.44 254 | 98.86 293 |
|
ambc | | | | | 99.20 232 | 99.35 258 | 98.53 244 | 99.17 162 | 99.46 221 | | 99.67 118 | 99.80 64 | 98.46 153 | 99.70 301 | 97.92 190 | 99.70 207 | 99.38 216 |
|
TEST9 | | | | | | 99.35 258 | 99.35 153 | 98.11 296 | 99.41 232 | 94.83 339 | 97.92 330 | 98.99 304 | 98.02 188 | 99.85 197 | | | |
|
train_agg | | | 98.35 253 | 97.95 263 | 99.57 139 | 99.35 258 | 99.35 153 | 98.11 296 | 99.41 232 | 94.90 335 | 97.92 330 | 98.99 304 | 98.02 188 | 99.85 197 | 95.38 316 | 99.44 254 | 99.50 176 |
|
agg_prior1 | | | 98.33 256 | 97.92 265 | 99.57 139 | 99.35 258 | 99.36 149 | 97.99 310 | 99.39 241 | 94.85 338 | 97.76 340 | 98.98 307 | 98.03 186 | 99.85 197 | 95.49 311 | 99.44 254 | 99.51 170 |
|
agg_prior | | | | | | 99.35 258 | 99.36 149 | | 99.39 241 | | 97.76 340 | | | 99.85 197 | | | |
|
test_prior3 | | | 98.62 225 | 98.34 238 | 99.46 170 | 99.35 258 | 99.22 182 | 97.95 315 | 99.39 241 | 97.87 261 | 98.05 325 | 99.05 300 | 97.90 195 | 99.69 307 | 95.99 290 | 99.49 249 | 99.48 183 |
|
test_prior | | | | | 99.46 170 | 99.35 258 | 99.22 182 | | 99.39 241 | | | | | 99.69 307 | | | 99.48 183 |
|
MVS_Test | | | 99.28 118 | 99.31 97 | 99.19 233 | 99.35 258 | 98.79 234 | 99.36 101 | 99.49 213 | 99.17 148 | 99.21 235 | 99.67 143 | 98.78 101 | 99.66 325 | 99.09 103 | 99.66 219 | 99.10 268 |
|
CDS-MVSNet | | | 99.22 139 | 99.13 129 | 99.50 160 | 99.35 258 | 99.11 197 | 98.96 210 | 99.54 189 | 99.46 101 | 99.61 146 | 99.70 119 | 96.31 263 | 99.83 230 | 99.34 65 | 99.88 115 | 99.55 148 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
3Dnovator+ | | 98.92 3 | 99.35 103 | 99.24 116 | 99.67 86 | 99.35 258 | 99.47 108 | 99.62 57 | 99.50 209 | 99.44 103 | 99.12 246 | 99.78 80 | 98.77 104 | 99.94 55 | 97.87 193 | 99.72 204 | 99.62 114 |
|
Anonymous202405211 | | | 98.75 218 | 98.46 223 | 99.63 109 | 99.34 268 | 99.66 72 | 99.47 81 | 97.65 334 | 99.28 125 | 99.56 159 | 99.50 219 | 93.15 293 | 99.84 213 | 98.62 144 | 99.58 231 | 99.40 210 |
|
CHOSEN 280x420 | | | 98.41 246 | 98.41 230 | 98.40 289 | 99.34 268 | 95.89 321 | 96.94 345 | 99.44 226 | 98.80 188 | 99.25 227 | 99.52 212 | 93.51 290 | 99.98 7 | 98.94 122 | 99.98 36 | 99.32 232 |
|
test_8 | | | | | | 99.34 268 | 99.31 159 | 98.08 301 | 99.40 238 | 94.90 335 | 97.87 334 | 98.97 310 | 98.02 188 | 99.84 213 | | | |
|
agg_prior3 | | | 98.24 258 | 97.81 271 | 99.53 153 | 99.34 268 | 99.26 171 | 98.09 298 | 99.39 241 | 94.21 343 | 97.77 339 | 98.96 312 | 97.74 208 | 99.84 213 | 95.38 316 | 99.44 254 | 99.50 176 |
|
TSAR-MVS + GP. | | | 99.12 160 | 99.04 162 | 99.38 194 | 99.34 268 | 99.16 192 | 98.15 290 | 99.29 263 | 98.18 247 | 99.63 134 | 99.62 169 | 99.18 50 | 99.68 315 | 98.20 171 | 99.74 193 | 99.30 234 |
|
LCM-MVSNet-Re | | | 99.28 118 | 99.15 125 | 99.67 86 | 99.33 273 | 99.76 42 | 99.34 109 | 99.97 3 | 98.93 173 | 99.91 34 | 99.79 71 | 98.68 117 | 99.93 66 | 96.80 255 | 99.56 233 | 99.30 234 |
|
PLC | | 97.35 16 | 98.36 250 | 97.99 259 | 99.48 165 | 99.32 274 | 99.24 178 | 98.50 261 | 99.51 206 | 95.19 333 | 98.58 300 | 98.96 312 | 96.95 249 | 99.83 230 | 95.63 308 | 99.25 282 | 99.37 220 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
Effi-MVS+ | | | 99.06 168 | 98.97 176 | 99.34 203 | 99.31 275 | 98.98 210 | 98.31 280 | 99.91 11 | 98.81 186 | 98.79 281 | 98.94 315 | 99.14 54 | 99.84 213 | 98.79 131 | 98.74 312 | 99.20 245 |
|
HQP-NCC | | | | | | 99.31 275 | | 97.98 311 | | 97.45 285 | 98.15 319 | | | | | | |
|
ACMP_Plane | | | | | | 99.31 275 | | 97.98 311 | | 97.45 285 | 98.15 319 | | | | | | |
|
HQP-MVS | | | 98.36 250 | 98.02 258 | 99.39 192 | 99.31 275 | 98.94 215 | 97.98 311 | 99.37 247 | 97.45 285 | 98.15 319 | 98.83 321 | 96.67 253 | 99.70 301 | 94.73 323 | 99.67 216 | 99.53 159 |
|
WR-MVS | | | 99.11 163 | 98.93 179 | 99.66 94 | 99.30 279 | 99.42 129 | 98.42 272 | 99.37 247 | 99.04 164 | 99.57 152 | 99.20 280 | 96.89 250 | 99.86 181 | 98.66 143 | 99.87 122 | 99.70 54 |
|
test12 | | | | | 99.54 152 | 99.29 280 | 99.33 156 | | 99.16 282 | | 98.43 309 | | 97.54 221 | 99.82 238 | | 99.47 251 | 99.48 183 |
|
OpenMVS_ROB | | 97.31 17 | 97.36 284 | 96.84 294 | 98.89 261 | 99.29 280 | 99.45 117 | 98.87 220 | 99.48 214 | 86.54 355 | 99.44 181 | 99.74 95 | 97.34 232 | 99.86 181 | 91.61 339 | 99.28 277 | 97.37 346 |
|
MVS-HIRNet | | | 97.86 272 | 98.22 245 | 96.76 331 | 99.28 282 | 91.53 353 | 98.38 274 | 92.60 360 | 99.13 153 | 99.31 219 | 99.96 11 | 97.18 242 | 99.68 315 | 98.34 160 | 99.83 146 | 99.07 278 |
|
DeepC-MVS_fast | | 98.47 5 | 99.23 130 | 99.12 132 | 99.56 145 | 99.28 282 | 99.22 182 | 98.99 204 | 99.40 238 | 99.08 160 | 99.58 150 | 99.64 154 | 98.90 84 | 99.83 230 | 97.44 221 | 99.75 186 | 99.63 100 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
Patchmatch-test | | | 98.10 266 | 97.98 261 | 98.48 286 | 99.27 284 | 96.48 308 | 99.40 88 | 99.07 287 | 98.81 186 | 99.23 231 | 99.57 196 | 90.11 323 | 99.87 161 | 96.69 261 | 99.64 222 | 99.09 271 |
|
Fast-Effi-MVS+-dtu | | | 99.20 144 | 99.12 132 | 99.43 179 | 99.25 285 | 99.69 64 | 99.05 192 | 99.82 48 | 99.50 92 | 98.97 259 | 99.05 300 | 98.98 74 | 99.98 7 | 98.20 171 | 99.24 284 | 98.62 302 |
|
CNVR-MVS | | | 98.99 185 | 98.80 200 | 99.56 145 | 99.25 285 | 99.43 125 | 98.54 257 | 99.27 267 | 98.58 211 | 98.80 280 | 99.43 231 | 98.53 145 | 99.70 301 | 97.22 235 | 99.59 230 | 99.54 156 |
|
LFMVS | | | 98.46 241 | 98.19 250 | 99.26 221 | 99.24 287 | 98.52 245 | 99.62 57 | 96.94 343 | 99.87 13 | 99.31 219 | 99.58 189 | 91.04 310 | 99.81 257 | 98.68 142 | 99.42 261 | 99.45 194 |
|
VNet | | | 99.18 149 | 99.06 152 | 99.56 145 | 99.24 287 | 99.36 149 | 99.33 111 | 99.31 259 | 99.67 59 | 99.47 178 | 99.57 196 | 96.48 258 | 99.84 213 | 99.15 94 | 99.30 275 | 99.47 188 |
|
DeepPCF-MVS | | 98.42 6 | 99.18 149 | 99.02 164 | 99.67 86 | 99.22 289 | 99.75 45 | 97.25 342 | 99.47 218 | 98.72 201 | 99.66 122 | 99.70 119 | 99.29 37 | 99.63 336 | 98.07 183 | 99.81 164 | 99.62 114 |
|
MSLP-MVS++ | | | 99.05 171 | 99.09 144 | 98.91 256 | 99.21 290 | 98.36 254 | 98.82 230 | 99.47 218 | 98.85 181 | 98.90 272 | 99.56 201 | 98.78 101 | 99.09 355 | 98.57 146 | 99.68 210 | 99.26 238 |
|
NCCC | | | 98.82 210 | 98.57 217 | 99.58 133 | 99.21 290 | 99.31 159 | 98.61 245 | 99.25 272 | 98.65 205 | 98.43 309 | 99.26 267 | 97.86 199 | 99.81 257 | 96.55 268 | 99.27 281 | 99.61 119 |
|
BH-RMVSNet | | | 98.41 246 | 98.14 252 | 99.21 230 | 99.21 290 | 98.47 246 | 98.60 247 | 98.26 320 | 98.35 234 | 98.93 267 | 99.31 256 | 97.20 241 | 99.66 325 | 94.32 329 | 99.10 290 | 99.51 170 |
|
Patchmatch-test1 | | | 98.13 264 | 98.40 231 | 97.31 327 | 99.20 293 | 92.99 343 | 98.17 289 | 98.49 313 | 98.24 244 | 99.10 248 | 99.52 212 | 96.01 270 | 99.83 230 | 97.22 235 | 99.62 224 | 99.12 263 |
|
mvs_anonymous | | | 99.28 118 | 99.39 83 | 98.94 253 | 99.19 294 | 97.81 286 | 99.02 197 | 99.55 185 | 99.78 34 | 99.85 58 | 99.80 64 | 98.24 171 | 99.86 181 | 99.57 43 | 99.50 247 | 99.15 255 |
|
OpenMVS | | 98.12 10 | 98.23 260 | 97.89 269 | 99.26 221 | 99.19 294 | 99.26 171 | 99.65 55 | 99.69 114 | 91.33 350 | 98.14 323 | 99.77 86 | 98.28 168 | 99.96 33 | 95.41 315 | 99.55 239 | 98.58 306 |
|
CNLPA | | | 98.57 230 | 98.34 238 | 99.28 214 | 99.18 296 | 99.10 200 | 98.34 277 | 99.41 232 | 98.48 219 | 98.52 303 | 98.98 307 | 97.05 246 | 99.78 273 | 95.59 309 | 99.50 247 | 98.96 285 |
|
MG-MVS | | | 98.52 235 | 98.39 232 | 98.94 253 | 99.15 297 | 97.39 297 | 98.18 287 | 99.21 278 | 98.89 177 | 99.23 231 | 99.63 162 | 97.37 231 | 99.74 291 | 94.22 331 | 99.61 228 | 99.69 57 |
|
ADS-MVSNet2 | | | 97.78 274 | 97.66 280 | 98.12 301 | 99.14 298 | 95.36 330 | 99.22 149 | 98.75 301 | 96.97 299 | 98.25 315 | 99.64 154 | 90.90 313 | 99.94 55 | 96.51 270 | 99.56 233 | 99.08 274 |
|
ADS-MVSNet | | | 97.72 276 | 97.67 279 | 97.86 311 | 99.14 298 | 94.65 337 | 99.22 149 | 98.86 295 | 96.97 299 | 98.25 315 | 99.64 154 | 90.90 313 | 99.84 213 | 96.51 270 | 99.56 233 | 99.08 274 |
|
FMVSNet3 | | | 98.80 213 | 98.63 211 | 99.32 209 | 99.13 300 | 98.72 235 | 99.10 184 | 99.48 214 | 99.23 137 | 99.62 141 | 99.64 154 | 92.57 299 | 99.86 181 | 98.96 117 | 99.90 103 | 99.39 213 |
|
PHI-MVS | | | 99.11 163 | 98.95 178 | 99.59 129 | 99.13 300 | 99.59 90 | 99.17 162 | 99.65 134 | 97.88 260 | 99.25 227 | 99.46 228 | 98.97 76 | 99.80 262 | 97.26 232 | 99.82 155 | 99.37 220 |
|
alignmvs | | | 98.28 257 | 97.96 262 | 99.25 225 | 99.12 302 | 98.93 219 | 99.03 196 | 98.42 316 | 99.64 69 | 98.72 287 | 97.85 345 | 90.86 315 | 99.62 337 | 98.88 126 | 99.13 288 | 99.19 248 |
|
PAPM | | | 95.61 331 | 94.71 332 | 98.31 294 | 99.12 302 | 96.63 306 | 96.66 350 | 98.46 314 | 90.77 351 | 96.25 352 | 98.68 330 | 93.01 296 | 99.69 307 | 81.60 358 | 97.86 347 | 98.62 302 |
|
AdaColmap | | | 98.60 227 | 98.35 237 | 99.38 194 | 99.12 302 | 99.22 182 | 98.67 244 | 99.42 231 | 97.84 265 | 98.81 278 | 99.27 265 | 97.32 233 | 99.81 257 | 95.14 319 | 99.53 244 | 99.10 268 |
|
MS-PatchMatch | | | 99.00 183 | 98.97 176 | 99.09 240 | 99.11 305 | 98.19 267 | 98.76 237 | 99.33 253 | 98.49 218 | 99.44 181 | 99.58 189 | 98.21 174 | 99.69 307 | 98.20 171 | 99.62 224 | 99.39 213 |
|
testus | | | 98.15 263 | 98.06 256 | 98.40 289 | 99.11 305 | 95.95 316 | 96.77 347 | 99.89 15 | 95.83 321 | 99.23 231 | 98.47 338 | 97.50 223 | 99.84 213 | 96.58 267 | 99.20 287 | 99.39 213 |
|
canonicalmvs | | | 99.02 176 | 99.00 169 | 99.09 240 | 99.10 307 | 98.70 236 | 99.61 61 | 99.66 125 | 99.63 72 | 98.64 295 | 97.65 352 | 99.04 70 | 99.54 345 | 98.79 131 | 98.92 297 | 99.04 281 |
|
MVS_0304 | | | 99.17 152 | 99.10 142 | 99.38 194 | 99.08 308 | 98.86 228 | 98.46 268 | 99.73 93 | 99.53 89 | 99.35 209 | 99.30 259 | 97.11 244 | 99.96 33 | 99.33 67 | 99.99 20 | 99.33 228 |
|
BH-w/o | | | 97.20 291 | 97.01 289 | 97.76 314 | 99.08 308 | 95.69 326 | 98.03 305 | 98.52 310 | 95.76 324 | 97.96 329 | 98.02 343 | 95.62 274 | 99.47 349 | 92.82 337 | 97.25 351 | 98.12 327 |
|
MVSTER | | | 98.47 240 | 98.22 245 | 99.24 227 | 99.06 310 | 98.35 255 | 99.08 189 | 99.46 221 | 99.27 126 | 99.75 92 | 99.66 148 | 88.61 329 | 99.85 197 | 99.14 100 | 99.92 91 | 99.52 167 |
|
CR-MVSNet | | | 98.35 253 | 98.20 247 | 98.83 266 | 99.05 311 | 98.12 271 | 99.30 124 | 99.67 121 | 97.39 288 | 99.16 241 | 99.79 71 | 91.87 305 | 99.91 93 | 98.78 134 | 98.77 308 | 98.44 312 |
|
RPMNet | | | 98.53 234 | 98.44 225 | 98.83 266 | 99.05 311 | 98.12 271 | 99.30 124 | 98.78 300 | 99.86 16 | 99.16 241 | 99.74 95 | 92.53 301 | 99.91 93 | 98.75 135 | 98.77 308 | 98.44 312 |
|
HY-MVS | | 98.23 9 | 98.21 262 | 97.95 263 | 98.99 250 | 99.03 313 | 98.24 263 | 99.61 61 | 98.72 303 | 96.81 303 | 98.73 286 | 99.51 216 | 94.06 286 | 99.86 181 | 96.91 249 | 98.20 337 | 98.86 293 |
|
PMMVS | | | 98.49 238 | 98.29 241 | 99.11 238 | 98.96 314 | 98.42 249 | 97.54 332 | 99.32 255 | 97.53 283 | 98.47 308 | 98.15 342 | 97.88 198 | 99.82 238 | 97.46 220 | 99.24 284 | 99.09 271 |
|
PatchT | | | 98.45 242 | 98.32 240 | 98.83 266 | 98.94 315 | 98.29 262 | 99.24 143 | 98.82 298 | 99.84 23 | 99.08 249 | 99.76 89 | 91.37 308 | 99.94 55 | 98.82 130 | 99.00 296 | 98.26 319 |
|
tpm | | | 97.15 294 | 96.95 291 | 97.75 315 | 98.91 316 | 94.24 339 | 99.32 114 | 97.96 324 | 97.71 270 | 98.29 312 | 99.32 254 | 86.72 342 | 99.92 84 | 98.10 182 | 96.24 355 | 99.09 271 |
|
1314 | | | 98.00 270 | 97.90 268 | 98.27 296 | 98.90 317 | 97.45 296 | 99.30 124 | 99.06 289 | 94.98 334 | 97.21 347 | 99.12 288 | 98.43 155 | 99.67 320 | 95.58 310 | 98.56 327 | 97.71 341 |
|
tpmp4_e23 | | | 96.11 322 | 96.06 315 | 96.27 339 | 98.90 317 | 90.70 358 | 99.34 109 | 99.03 291 | 93.72 344 | 96.56 350 | 99.31 256 | 83.63 354 | 99.75 287 | 96.06 285 | 98.02 344 | 98.35 315 |
|
CostFormer | | | 96.71 309 | 96.79 297 | 96.46 338 | 98.90 317 | 90.71 357 | 99.41 86 | 98.68 305 | 94.69 340 | 98.14 323 | 99.34 253 | 86.32 350 | 99.80 262 | 97.60 213 | 98.07 342 | 98.88 291 |
|
UGNet | | | 99.38 96 | 99.34 93 | 99.49 162 | 98.90 317 | 98.90 222 | 99.70 30 | 99.35 250 | 99.86 16 | 98.57 301 | 99.81 62 | 98.50 150 | 99.93 66 | 99.38 60 | 99.98 36 | 99.66 80 |
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 |
Effi-MVS+-dtu | | | 99.07 167 | 98.92 182 | 99.52 155 | 98.89 321 | 99.78 36 | 99.15 170 | 99.66 125 | 99.34 118 | 98.92 269 | 99.24 274 | 97.69 211 | 99.98 7 | 98.11 180 | 99.28 277 | 98.81 297 |
|
mvs-test1 | | | 98.83 208 | 98.70 205 | 99.22 229 | 98.89 321 | 99.65 77 | 98.88 218 | 99.66 125 | 99.34 118 | 98.29 312 | 98.94 315 | 97.69 211 | 99.96 33 | 98.11 180 | 98.54 328 | 98.04 329 |
|
Patchmtry | | | 98.78 215 | 98.54 220 | 99.49 162 | 98.89 321 | 99.19 190 | 99.32 114 | 99.67 121 | 99.65 67 | 99.72 104 | 99.79 71 | 91.87 305 | 99.95 41 | 98.00 187 | 99.97 47 | 99.33 228 |
|
LP | | | 98.34 255 | 98.44 225 | 98.05 302 | 98.88 324 | 95.31 332 | 99.28 133 | 98.74 302 | 99.12 154 | 98.98 258 | 99.79 71 | 93.40 291 | 99.93 66 | 98.38 156 | 99.41 263 | 98.90 290 |
|
tpm2 | | | 96.35 317 | 96.22 311 | 96.73 333 | 98.88 324 | 91.75 351 | 99.21 152 | 98.51 311 | 93.27 346 | 97.89 332 | 99.21 279 | 84.83 353 | 99.70 301 | 96.04 286 | 98.18 340 | 98.75 300 |
|
tpm cat1 | | | 96.78 307 | 96.98 290 | 96.16 342 | 98.85 326 | 90.59 359 | 99.08 189 | 99.32 255 | 92.37 347 | 97.73 342 | 99.46 228 | 91.15 309 | 99.69 307 | 96.07 284 | 98.80 305 | 98.21 323 |
|
CANet | | | 99.11 163 | 99.05 157 | 99.28 214 | 98.83 327 | 98.56 242 | 98.71 243 | 99.41 232 | 99.25 133 | 99.23 231 | 99.22 278 | 97.66 218 | 99.94 55 | 99.19 85 | 99.97 47 | 99.33 228 |
|
FMVSNet5 | | | 97.80 273 | 97.25 284 | 99.42 181 | 98.83 327 | 98.97 212 | 99.38 95 | 99.80 60 | 98.87 179 | 99.25 227 | 99.69 125 | 80.60 361 | 99.91 93 | 98.96 117 | 99.90 103 | 99.38 216 |
|
API-MVS | | | 98.38 249 | 98.39 232 | 98.35 291 | 98.83 327 | 99.26 171 | 99.14 175 | 99.18 280 | 98.59 210 | 98.66 294 | 98.78 325 | 98.61 131 | 99.57 344 | 94.14 332 | 99.56 233 | 96.21 354 |
|
PatchmatchNet | | | 97.65 277 | 97.80 272 | 97.18 328 | 98.82 330 | 92.49 345 | 99.17 162 | 98.39 317 | 98.12 248 | 98.79 281 | 99.58 189 | 90.71 317 | 99.89 126 | 97.23 234 | 99.41 263 | 99.16 254 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
PAPR | | | 97.56 280 | 97.07 286 | 99.04 247 | 98.80 331 | 98.11 273 | 97.63 328 | 99.25 272 | 94.56 341 | 98.02 328 | 98.25 341 | 97.43 226 | 99.68 315 | 90.90 342 | 98.74 312 | 99.33 228 |
|
CANet_DTU | | | 98.91 197 | 98.85 191 | 99.09 240 | 98.79 332 | 98.13 270 | 98.18 287 | 99.31 259 | 99.48 94 | 98.86 275 | 99.51 216 | 96.56 255 | 99.95 41 | 99.05 106 | 99.95 67 | 99.19 248 |
|
E-PMN | | | 97.14 296 | 97.43 282 | 96.27 339 | 98.79 332 | 91.62 352 | 95.54 353 | 99.01 292 | 99.44 103 | 98.88 273 | 99.12 288 | 92.78 298 | 99.68 315 | 94.30 330 | 99.03 294 | 97.50 343 |
|
PVSNet_0 | | 95.53 19 | 95.85 328 | 95.31 327 | 97.47 322 | 98.78 334 | 93.48 342 | 95.72 352 | 99.40 238 | 96.18 316 | 97.37 344 | 97.73 351 | 95.73 272 | 99.58 343 | 95.49 311 | 81.40 358 | 99.36 223 |
|
MAR-MVS | | | 98.24 258 | 97.92 265 | 99.19 233 | 98.78 334 | 99.65 77 | 99.17 162 | 99.14 284 | 95.36 329 | 98.04 327 | 98.81 323 | 97.47 224 | 99.72 294 | 95.47 313 | 99.06 291 | 98.21 323 |
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 |
EMVS | | | 96.96 299 | 97.28 283 | 95.99 343 | 98.76 336 | 91.03 355 | 95.26 355 | 98.61 307 | 99.34 118 | 98.92 269 | 98.88 320 | 93.79 287 | 99.66 325 | 92.87 336 | 99.05 292 | 97.30 347 |
|
PatchFormer-LS_test | | | 96.95 300 | 97.07 286 | 96.62 336 | 98.76 336 | 91.85 349 | 99.18 155 | 98.45 315 | 97.29 292 | 97.73 342 | 97.22 361 | 88.77 328 | 99.76 281 | 98.13 179 | 98.04 343 | 98.25 320 |
|
IB-MVS | | 95.41 20 | 95.30 332 | 94.46 334 | 97.84 312 | 98.76 336 | 95.33 331 | 97.33 340 | 96.07 347 | 96.02 317 | 95.37 357 | 97.41 355 | 76.17 364 | 99.96 33 | 97.54 216 | 95.44 357 | 98.22 322 |
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 |
tpmrst | | | 97.73 275 | 98.07 255 | 96.73 333 | 98.71 339 | 92.00 347 | 99.10 184 | 98.86 295 | 98.52 215 | 98.92 269 | 99.54 208 | 91.90 303 | 99.82 238 | 98.02 184 | 99.03 294 | 98.37 314 |
|
MDTV_nov1_ep13 | | | | 97.73 276 | | 98.70 340 | 90.83 356 | 99.15 170 | 98.02 322 | 98.51 216 | 98.82 277 | 99.61 178 | 90.98 311 | 99.66 325 | 96.89 251 | 98.92 297 | |
|
dp | | | 96.86 302 | 97.07 286 | 96.24 341 | 98.68 341 | 90.30 360 | 99.19 154 | 98.38 318 | 97.35 290 | 98.23 317 | 99.59 187 | 87.23 334 | 99.82 238 | 96.27 278 | 98.73 314 | 98.59 304 |
|
JIA-IIPM | | | 98.06 268 | 97.92 265 | 98.50 285 | 98.59 342 | 97.02 302 | 98.80 232 | 98.51 311 | 99.88 12 | 97.89 332 | 99.87 37 | 91.89 304 | 99.90 110 | 98.16 178 | 97.68 349 | 98.59 304 |
|
MVS | | | 95.72 330 | 94.63 333 | 98.99 250 | 98.56 343 | 97.98 284 | 99.30 124 | 98.86 295 | 72.71 358 | 97.30 345 | 99.08 291 | 98.34 164 | 99.74 291 | 89.21 347 | 98.33 334 | 99.26 238 |
|
TR-MVS | | | 97.44 281 | 97.15 285 | 98.32 293 | 98.53 344 | 97.46 295 | 98.47 264 | 97.91 327 | 96.85 301 | 98.21 318 | 98.51 336 | 96.42 261 | 99.51 347 | 92.16 338 | 97.29 350 | 97.98 334 |
|
DWT-MVSNet_test | | | 96.03 325 | 95.80 322 | 96.71 335 | 98.50 345 | 91.93 348 | 99.25 141 | 97.87 328 | 95.99 318 | 96.81 349 | 97.61 353 | 81.02 358 | 99.66 325 | 97.20 238 | 97.98 345 | 98.54 307 |
|
tpmvs | | | 97.39 282 | 97.69 277 | 96.52 337 | 98.41 346 | 91.76 350 | 99.30 124 | 98.94 294 | 97.74 268 | 97.85 335 | 99.55 206 | 92.40 302 | 99.73 293 | 96.25 279 | 98.73 314 | 98.06 328 |
|
LS3D | | | 99.24 128 | 99.11 135 | 99.61 121 | 98.38 347 | 99.79 34 | 99.57 69 | 99.68 117 | 99.61 77 | 99.15 243 | 99.71 112 | 98.70 113 | 99.91 93 | 97.54 216 | 99.68 210 | 99.13 262 |
|
CMPMVS | | 77.52 23 | 98.50 236 | 98.19 250 | 99.41 188 | 98.33 348 | 99.56 95 | 99.01 199 | 99.59 167 | 95.44 328 | 99.57 152 | 99.80 64 | 95.64 273 | 99.46 352 | 96.47 273 | 99.92 91 | 99.21 244 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
TESTMET0.1,1 | | | 96.24 320 | 95.84 321 | 97.41 324 | 98.24 349 | 93.84 340 | 97.38 337 | 95.84 348 | 98.43 221 | 97.81 336 | 98.56 334 | 79.77 362 | 99.89 126 | 97.77 199 | 98.77 308 | 98.52 308 |
|
gg-mvs-nofinetune | | | 95.87 327 | 95.17 330 | 97.97 304 | 98.19 350 | 96.95 303 | 99.69 39 | 89.23 363 | 99.89 10 | 96.24 353 | 99.94 13 | 81.19 357 | 99.51 347 | 93.99 334 | 98.20 337 | 97.44 344 |
|
test-LLR | | | 97.15 294 | 96.95 291 | 97.74 316 | 98.18 351 | 95.02 334 | 97.38 337 | 96.10 345 | 98.00 252 | 97.81 336 | 98.58 331 | 90.04 324 | 99.91 93 | 97.69 208 | 98.78 306 | 98.31 317 |
|
test-mter | | | 96.23 321 | 95.73 323 | 97.74 316 | 98.18 351 | 95.02 334 | 97.38 337 | 96.10 345 | 97.90 259 | 97.81 336 | 98.58 331 | 79.12 363 | 99.91 93 | 97.69 208 | 98.78 306 | 98.31 317 |
|
EPMVS | | | 96.53 312 | 96.32 310 | 97.17 329 | 98.18 351 | 92.97 344 | 99.39 89 | 89.95 362 | 98.21 245 | 98.61 297 | 99.59 187 | 86.69 343 | 99.72 294 | 96.99 246 | 99.23 286 | 98.81 297 |
|
test0.0.03 1 | | | 97.37 283 | 96.91 293 | 98.74 276 | 97.72 354 | 97.57 293 | 97.60 330 | 97.36 342 | 98.00 252 | 99.21 235 | 98.02 343 | 90.04 324 | 99.79 265 | 98.37 157 | 95.89 356 | 98.86 293 |
|
GG-mvs-BLEND | | | | | 97.36 325 | 97.59 355 | 96.87 305 | 99.70 30 | 88.49 364 | | 94.64 358 | 97.26 360 | 80.66 360 | 99.12 354 | 91.50 340 | 96.50 354 | 96.08 356 |
|
gm-plane-assit | | | | | | 97.59 355 | 89.02 362 | | | 93.47 345 | | 98.30 339 | | 99.84 213 | 96.38 274 | | |
|
cascas | | | 96.99 298 | 96.82 296 | 97.48 321 | 97.57 357 | 95.64 327 | 96.43 351 | 99.56 182 | 91.75 348 | 97.13 348 | 97.61 353 | 95.58 275 | 98.63 358 | 96.68 262 | 99.11 289 | 98.18 326 |
|
testpf | | | 94.48 333 | 95.31 327 | 91.99 346 | 97.22 358 | 89.64 361 | 98.86 221 | 96.52 344 | 94.36 342 | 96.09 354 | 98.76 326 | 82.21 355 | 98.73 357 | 97.05 244 | 96.74 352 | 87.60 357 |
|
test2356 | | | 95.99 326 | 95.26 329 | 98.18 298 | 96.93 359 | 95.53 329 | 95.31 354 | 98.71 304 | 95.67 326 | 98.48 307 | 97.83 346 | 80.72 359 | 99.88 141 | 95.47 313 | 98.21 336 | 99.11 264 |
|
EPNet_dtu | | | 97.62 278 | 97.79 274 | 97.11 330 | 96.67 360 | 92.31 346 | 98.51 260 | 98.04 321 | 99.24 135 | 95.77 355 | 99.47 225 | 93.78 288 | 99.66 325 | 98.98 112 | 99.62 224 | 99.37 220 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
EPNet | | | 98.13 264 | 97.77 275 | 99.18 236 | 94.57 361 | 97.99 279 | 99.24 143 | 97.96 324 | 99.74 40 | 97.29 346 | 99.62 169 | 93.13 294 | 99.97 16 | 98.59 145 | 99.83 146 | 99.58 140 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
tmp_tt | | | 95.75 329 | 95.42 326 | 96.76 331 | 89.90 362 | 94.42 338 | 98.86 221 | 97.87 328 | 78.01 356 | 99.30 223 | 99.69 125 | 97.70 209 | 95.89 360 | 99.29 76 | 98.14 341 | 99.95 1 |
|
testmvs | | | 28.94 337 | 33.33 337 | 15.79 350 | 26.03 363 | 9.81 365 | 96.77 347 | 15.67 365 | 11.55 360 | 23.87 361 | 50.74 368 | 19.03 368 | 8.53 363 | 23.21 360 | 33.07 359 | 29.03 360 |
|
test123 | | | 29.31 336 | 33.05 339 | 18.08 349 | 25.93 364 | 12.24 364 | 97.53 334 | 10.93 366 | 11.78 359 | 24.21 360 | 50.08 369 | 21.04 367 | 8.60 362 | 23.51 359 | 32.43 361 | 33.39 359 |
|
cdsmvs_eth3d_5k | | | 24.88 338 | 33.17 338 | 0.00 351 | 0.00 365 | 0.00 366 | 0.00 357 | 99.62 145 | 0.00 361 | 0.00 362 | 99.13 284 | 99.82 6 | 0.00 364 | 0.00 361 | 0.00 362 | 0.00 362 |
|
pcd_1.5k_mvsjas | | | 16.61 339 | 22.14 340 | 0.00 351 | 0.00 365 | 0.00 366 | 0.00 357 | 0.00 367 | 0.00 361 | 0.00 362 | 100.00 1 | 99.28 39 | 0.00 364 | 0.00 361 | 0.00 362 | 0.00 362 |
|
sosnet-low-res | | | 8.33 340 | 11.11 341 | 0.00 351 | 0.00 365 | 0.00 366 | 0.00 357 | 0.00 367 | 0.00 361 | 0.00 362 | 100.00 1 | 0.00 369 | 0.00 364 | 0.00 361 | 0.00 362 | 0.00 362 |
|
sosnet | | | 8.33 340 | 11.11 341 | 0.00 351 | 0.00 365 | 0.00 366 | 0.00 357 | 0.00 367 | 0.00 361 | 0.00 362 | 100.00 1 | 0.00 369 | 0.00 364 | 0.00 361 | 0.00 362 | 0.00 362 |
|
uncertanet | | | 8.33 340 | 11.11 341 | 0.00 351 | 0.00 365 | 0.00 366 | 0.00 357 | 0.00 367 | 0.00 361 | 0.00 362 | 100.00 1 | 0.00 369 | 0.00 364 | 0.00 361 | 0.00 362 | 0.00 362 |
|
Regformer | | | 8.33 340 | 11.11 341 | 0.00 351 | 0.00 365 | 0.00 366 | 0.00 357 | 0.00 367 | 0.00 361 | 0.00 362 | 100.00 1 | 0.00 369 | 0.00 364 | 0.00 361 | 0.00 362 | 0.00 362 |
|
ab-mvs-re | | | 8.26 345 | 11.02 346 | 0.00 351 | 0.00 365 | 0.00 366 | 0.00 357 | 0.00 367 | 0.00 361 | 0.00 362 | 99.16 282 | 0.00 369 | 0.00 364 | 0.00 361 | 0.00 362 | 0.00 362 |
|
uanet | | | 8.33 340 | 11.11 341 | 0.00 351 | 0.00 365 | 0.00 366 | 0.00 357 | 0.00 367 | 0.00 361 | 0.00 362 | 100.00 1 | 0.00 369 | 0.00 364 | 0.00 361 | 0.00 362 | 0.00 362 |
|
GSMVS | | | | | | | | | | | | | | | | | 99.14 259 |
|
test_part3 | | | | | | | | 98.74 238 | | 97.71 270 | | 99.57 196 | | 99.90 110 | 94.47 327 | | |
|
test_part1 | | | | | | | | | 99.53 194 | | | | 98.40 159 | | | 99.68 210 | 99.66 80 |
|
sam_mvs1 | | | | | | | | | | | | | 90.81 316 | | | | 99.14 259 |
|
sam_mvs | | | | | | | | | | | | | 90.52 320 | | | | |
|
MTGPA | | | | | | | | | 99.53 194 | | | | | | | | |
|
test_post1 | | | | | | | | 99.14 175 | | | | 51.63 367 | 89.54 327 | 99.82 238 | 96.86 252 | | |
|
test_post | | | | | | | | | | | | 52.41 366 | 90.25 322 | 99.86 181 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 99.62 169 | 90.58 318 | 99.94 55 | | | |
|
MTMP | | | | | | | | | 98.59 309 | | | | | | | | |
|
test9_res | | | | | | | | | | | | | | | 95.10 320 | 99.44 254 | 99.50 176 |
|
agg_prior2 | | | | | | | | | | | | | | | 94.58 326 | 99.46 253 | 99.50 176 |
|
test_prior4 | | | | | | | 99.19 190 | 98.00 308 | | | | | | | | | |
|
test_prior2 | | | | | | | | 97.95 315 | | 97.87 261 | 98.05 325 | 99.05 300 | 97.90 195 | | 95.99 290 | 99.49 249 | |
|
旧先验2 | | | | | | | | 97.94 317 | | 95.33 330 | 98.94 266 | | | 99.88 141 | 96.75 258 | | |
|
新几何2 | | | | | | | | 98.04 304 | | | | | | | | | |
|
无先验 | | | | | | | | 98.01 306 | 99.23 276 | 95.83 321 | | | | 99.85 197 | 95.79 299 | | 99.44 199 |
|
原ACMM2 | | | | | | | | 97.92 319 | | | | | | | | | |
|
testdata2 | | | | | | | | | | | | | | 99.89 126 | 95.99 290 | | |
|
segment_acmp | | | | | | | | | | | | | 98.37 162 | | | | |
|
testdata1 | | | | | | | | 97.72 326 | | 97.86 264 | | | | | | | |
|
plane_prior5 | | | | | | | | | 99.54 189 | | | | | 99.82 238 | 95.84 297 | 99.78 177 | 99.60 125 |
|
plane_prior4 | | | | | | | | | | | | 99.25 269 | | | | | |
|
plane_prior3 | | | | | | | 99.31 159 | | | 98.36 229 | 99.14 244 | | | | | | |
|
plane_prior2 | | | | | | | | 98.80 232 | | 98.94 171 | | | | | | | |
|
plane_prior | | | | | | | 99.24 178 | 98.42 272 | | 97.87 261 | | | | | | 99.71 205 | |
|
n2 | | | | | | | | | 0.00 367 | | | | | | | | |
|
nn | | | | | | | | | 0.00 367 | | | | | | | | |
|
door-mid | | | | | | | | | 99.83 40 | | | | | | | | |
|
test11 | | | | | | | | | 99.29 263 | | | | | | | | |
|
door | | | | | | | | | 99.77 73 | | | | | | | | |
|
HQP5-MVS | | | | | | | 98.94 215 | | | | | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 94.73 323 | | |
|
HQP4-MVS | | | | | | | | | | | 98.15 319 | | | 99.70 301 | | | 99.53 159 |
|
HQP3-MVS | | | | | | | | | 99.37 247 | | | | | | | 99.67 216 | |
|
HQP2-MVS | | | | | | | | | | | | | 96.67 253 | | | | |
|
MDTV_nov1_ep13_2view | | | | | | | 91.44 354 | 99.14 175 | | 97.37 289 | 99.21 235 | | 91.78 307 | | 96.75 258 | | 99.03 282 |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 99.94 80 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 99.79 172 | |
|
Test By Simon | | | | | | | | | | | | | 98.41 157 | | | | |
|