conf0.01 | | | 99.32 79 | 99.16 85 | 99.80 93 | 99.79 114 | 99.73 86 | 100.00 1 | 99.71 62 | 97.66 112 | 99.71 144 | 100.00 1 | 99.78 6 | 99.70 164 | 98.15 191 | 97.67 193 | 99.97 95 |
|
test_part3 | | | | | | | | 100.00 1 | | 98.23 64 | | 100.00 1 | | 100.00 1 | 100.00 1 | | |
|
conf0.002 | | | 99.32 79 | 99.16 85 | 99.80 93 | 99.79 114 | 99.73 86 | 100.00 1 | 99.71 62 | 97.66 112 | 99.71 144 | 100.00 1 | 99.78 6 | 99.70 164 | 98.15 191 | 97.67 193 | 99.97 95 |
|
thresconf0.02 | | | 99.32 79 | 99.16 85 | 99.79 97 | 99.79 114 | 99.73 86 | 100.00 1 | 99.71 62 | 97.66 112 | 99.71 144 | 100.00 1 | 99.78 6 | 99.70 164 | 98.15 191 | 97.67 193 | 99.94 114 |
|
tfpn_n400 | | | 99.32 79 | 99.16 85 | 99.79 97 | 99.79 114 | 99.73 86 | 100.00 1 | 99.71 62 | 97.66 112 | 99.71 144 | 100.00 1 | 99.78 6 | 99.70 164 | 98.15 191 | 97.67 193 | 99.94 114 |
|
tfpnconf | | | 99.32 79 | 99.16 85 | 99.79 97 | 99.79 114 | 99.73 86 | 100.00 1 | 99.71 62 | 97.66 112 | 99.71 144 | 100.00 1 | 99.78 6 | 99.70 164 | 98.15 191 | 97.67 193 | 99.94 114 |
|
tfpnview11 | | | 99.32 79 | 99.16 85 | 99.79 97 | 99.79 114 | 99.73 86 | 100.00 1 | 99.71 62 | 97.66 112 | 99.71 144 | 100.00 1 | 99.78 6 | 99.70 164 | 98.15 191 | 97.67 193 | 99.94 114 |
|
ESAPD | | | 99.76 15 | 99.69 18 | 100.00 1 | 100.00 1 | 99.99 1 | 100.00 1 | 99.42 120 | 98.23 64 | 100.00 1 | 100.00 1 | 99.53 25 | 100.00 1 | 100.00 1 | 100.00 1 | 100.00 1 |
|
CHOSEN 280x420 | | | 99.85 3 | 99.87 1 | 99.80 93 | 99.99 45 | 99.97 8 | 99.97 196 | 99.98 13 | 98.96 21 | 100.00 1 | 100.00 1 | 99.96 3 | 99.42 205 | 100.00 1 | 100.00 1 | 100.00 1 |
|
CANet | | | 99.40 71 | 99.24 76 | 99.89 73 | 99.99 45 | 99.76 81 | 100.00 1 | 99.73 54 | 98.40 52 | 99.78 136 | 100.00 1 | 95.28 180 | 99.96 112 | 100.00 1 | 99.99 87 | 99.96 105 |
|
CANet_DTU | | | 99.02 117 | 98.90 118 | 99.41 138 | 99.88 96 | 98.71 163 | 100.00 1 | 99.29 209 | 98.84 30 | 100.00 1 | 100.00 1 | 94.02 195 | 100.00 1 | 98.08 198 | 99.96 99 | 99.52 199 |
|
MVS_0304 | | | 98.98 123 | 98.66 134 | 99.94 57 | 99.95 81 | 99.86 65 | 100.00 1 | 99.29 209 | 98.38 55 | 99.81 134 | 100.00 1 | 90.60 247 | 100.00 1 | 100.00 1 | 99.91 104 | 99.95 110 |
|
MP-MVS-pluss | | | 99.61 54 | 99.50 56 | 99.97 23 | 99.98 71 | 99.92 35 | 100.00 1 | 99.42 120 | 97.53 130 | 99.77 137 | 100.00 1 | 98.77 104 | 100.00 1 | 99.99 44 | 100.00 1 | 99.99 88 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
HSP-MVS | | | 99.81 9 | 99.77 8 | 99.94 57 | 100.00 1 | 99.86 65 | 100.00 1 | 99.42 120 | 98.87 29 | 100.00 1 | 100.00 1 | 99.65 18 | 99.96 112 | 100.00 1 | 100.00 1 | 100.00 1 |
|
TSAR-MVS + MP. | | | 99.82 7 | 99.77 8 | 99.99 5 | 100.00 1 | 99.96 10 | 100.00 1 | 99.43 114 | 99.05 12 | 100.00 1 | 100.00 1 | 99.45 42 | 99.99 80 | 100.00 1 | 100.00 1 | 100.00 1 |
|
xiu_mvs_v1_base_debu | | | 99.35 75 | 99.21 79 | 99.79 97 | 99.67 134 | 99.71 94 | 99.78 240 | 99.36 180 | 98.13 71 | 100.00 1 | 100.00 1 | 97.00 146 | 100.00 1 | 99.83 85 | 99.07 124 | 99.66 193 |
|
ACMMP_Plus | | | 99.67 45 | 99.57 50 | 99.97 23 | 99.98 71 | 99.92 35 | 100.00 1 | 99.42 120 | 97.83 98 | 100.00 1 | 100.00 1 | 98.89 98 | 100.00 1 | 99.98 58 | 100.00 1 | 100.00 1 |
|
MPTG | | | 99.68 42 | 99.59 46 | 99.97 23 | 99.99 45 | 99.91 38 | 100.00 1 | 99.42 120 | 98.32 61 | 99.94 108 | 100.00 1 | 98.65 108 | 100.00 1 | 99.96 65 | 100.00 1 | 100.00 1 |
|
xiu_mvs_v2_base | | | 99.51 62 | 99.41 60 | 99.82 87 | 99.70 129 | 99.73 86 | 99.92 213 | 99.40 153 | 98.15 69 | 100.00 1 | 100.00 1 | 98.50 114 | 100.00 1 | 99.85 82 | 99.13 122 | 99.74 184 |
|
xiu_mvs_v1_base | | | 99.35 75 | 99.21 79 | 99.79 97 | 99.67 134 | 99.71 94 | 99.78 240 | 99.36 180 | 98.13 71 | 100.00 1 | 100.00 1 | 97.00 146 | 100.00 1 | 99.83 85 | 99.07 124 | 99.66 193 |
|
xiu_mvs_v1_base_debi | | | 99.35 75 | 99.21 79 | 99.79 97 | 99.67 134 | 99.71 94 | 99.78 240 | 99.36 180 | 98.13 71 | 100.00 1 | 100.00 1 | 97.00 146 | 100.00 1 | 99.83 85 | 99.07 124 | 99.66 193 |
|
MTAPA | | | 99.68 42 | 99.59 46 | 99.97 23 | 99.99 45 | 99.91 38 | 100.00 1 | 99.42 120 | 98.32 61 | 99.94 108 | 100.00 1 | 98.65 108 | 100.00 1 | 99.96 65 | 100.00 1 | 100.00 1 |
|
gm-plane-assit | | | | | | 99.52 169 | 97.26 243 | | | 95.86 210 | | 100.00 1 | | 99.43 203 | 98.76 165 | | |
|
TEST9 | | | | | | 100.00 1 | 99.95 19 | 100.00 1 | 99.42 120 | 97.65 119 | 100.00 1 | 100.00 1 | 99.53 25 | 99.97 97 | | | |
|
train_agg | | | 99.71 32 | 99.63 39 | 99.97 23 | 100.00 1 | 99.95 19 | 100.00 1 | 99.42 120 | 97.70 109 | 100.00 1 | 100.00 1 | 99.51 30 | 99.97 97 | 100.00 1 | 100.00 1 | 100.00 1 |
|
test_8 | | | | | | 100.00 1 | 99.91 38 | 100.00 1 | 99.42 120 | 97.70 109 | 100.00 1 | 100.00 1 | 99.51 30 | 99.98 93 | | | |
|
agg_prior3 | | | 99.71 32 | 99.63 39 | 99.97 23 | 100.00 1 | 99.95 19 | 100.00 1 | 99.42 120 | 97.71 108 | 100.00 1 | 100.00 1 | 99.51 30 | 99.97 97 | 100.00 1 | 100.00 1 | 100.00 1 |
|
cdsmvs_eth3d_5k | | | 24.41 331 | 32.55 331 | 0.00 344 | 0.00 358 | 0.00 359 | 0.00 350 | 99.39 167 | 0.00 354 | 0.00 355 | 100.00 1 | 93.55 200 | 0.00 357 | 0.00 354 | 0.00 355 | 0.00 355 |
|
agg_prior1 | | | 99.71 32 | 99.63 39 | 99.95 46 | 100.00 1 | 99.88 58 | 100.00 1 | 99.42 120 | 97.72 106 | 100.00 1 | 100.00 1 | 99.51 30 | 99.97 97 | 100.00 1 | 100.00 1 | 100.00 1 |
|
tmp_tt | | | 75.80 320 | 74.26 321 | 80.43 330 | 52.91 357 | 53.67 355 | 87.42 348 | 97.98 329 | 61.80 344 | 67.04 346 | 100.00 1 | 76.43 334 | 96.40 318 | 96.47 240 | 28.26 352 | 91.23 340 |
|
canonicalmvs | | | 99.03 113 | 98.73 130 | 99.94 57 | 99.75 126 | 99.95 19 | 100.00 1 | 99.30 205 | 97.64 121 | 100.00 1 | 100.00 1 | 95.22 182 | 99.97 97 | 99.76 96 | 96.90 208 | 99.91 126 |
|
alignmvs | | | 99.38 73 | 99.21 79 | 99.91 67 | 99.73 127 | 99.92 35 | 100.00 1 | 99.51 79 | 97.61 123 | 100.00 1 | 100.00 1 | 99.06 80 | 99.93 131 | 99.83 85 | 97.12 204 | 99.90 134 |
|
UA-Net | | | 99.06 110 | 98.83 121 | 99.74 108 | 99.52 169 | 99.40 121 | 99.08 322 | 99.45 96 | 97.64 121 | 99.83 124 | 100.00 1 | 95.80 171 | 99.94 129 | 98.35 183 | 99.80 113 | 99.88 151 |
|
HFP-MVS | | | 99.74 23 | 99.67 27 | 99.96 35 | 100.00 1 | 99.89 48 | 100.00 1 | 99.76 45 | 97.95 89 | 100.00 1 | 100.00 1 | 99.31 54 | 100.00 1 | 99.99 44 | 100.00 1 | 100.00 1 |
|
region2R | | | 99.72 29 | 99.64 35 | 99.97 23 | 100.00 1 | 99.90 44 | 100.00 1 | 99.74 52 | 97.86 97 | 100.00 1 | 100.00 1 | 99.19 72 | 100.00 1 | 99.99 44 | 100.00 1 | 100.00 1 |
|
PS-MVSNAJ | | | 99.64 49 | 99.57 50 | 99.85 83 | 99.78 120 | 99.81 76 | 99.95 205 | 99.42 120 | 98.38 55 | 100.00 1 | 100.00 1 | 98.75 105 | 100.00 1 | 99.88 78 | 99.99 87 | 99.74 184 |
|
#test# | | | 99.75 18 | 99.68 22 | 99.96 35 | 100.00 1 | 99.89 48 | 100.00 1 | 99.76 45 | 98.07 77 | 100.00 1 | 100.00 1 | 99.31 54 | 100.00 1 | 99.99 44 | 100.00 1 | 100.00 1 |
|
EI-MVSNet-UG-set | | | 99.69 39 | 99.63 39 | 99.87 79 | 99.99 45 | 99.64 103 | 99.95 205 | 99.44 105 | 98.35 59 | 100.00 1 | 100.00 1 | 98.98 87 | 99.97 97 | 99.98 58 | 100.00 1 | 100.00 1 |
|
EI-MVSNet-Vis-set | | | 99.70 36 | 99.64 35 | 99.87 79 | 100.00 1 | 99.64 103 | 99.98 190 | 99.44 105 | 98.35 59 | 99.99 75 | 100.00 1 | 99.04 82 | 99.96 112 | 99.98 58 | 100.00 1 | 100.00 1 |
|
Regformer-3 | | | 99.73 26 | 99.65 31 | 99.96 35 | 100.00 1 | 99.89 48 | 100.00 1 | 99.44 105 | 98.40 52 | 100.00 1 | 100.00 1 | 99.03 85 | 99.97 97 | 99.99 44 | 100.00 1 | 100.00 1 |
|
Regformer-4 | | | 99.73 26 | 99.65 31 | 99.95 46 | 100.00 1 | 99.89 48 | 100.00 1 | 99.44 105 | 98.40 52 | 100.00 1 | 100.00 1 | 99.03 85 | 99.97 97 | 99.99 44 | 100.00 1 | 100.00 1 |
|
Regformer-1 | | | 99.75 18 | 99.68 22 | 99.98 16 | 100.00 1 | 99.94 27 | 100.00 1 | 99.44 105 | 98.43 49 | 100.00 1 | 100.00 1 | 99.23 68 | 99.99 80 | 99.99 44 | 100.00 1 | 100.00 1 |
|
Regformer-2 | | | 99.75 18 | 99.68 22 | 99.97 23 | 100.00 1 | 99.94 27 | 100.00 1 | 99.44 105 | 98.42 51 | 100.00 1 | 100.00 1 | 99.22 69 | 99.99 80 | 99.99 44 | 100.00 1 | 100.00 1 |
|
HPM-MVS++ | | | 99.82 7 | 99.76 10 | 99.99 5 | 99.99 45 | 99.98 6 | 100.00 1 | 99.83 39 | 98.88 27 | 99.96 87 | 100.00 1 | 99.21 70 | 100.00 1 | 100.00 1 | 100.00 1 | 99.99 88 |
|
XVS | | | 99.79 12 | 99.73 14 | 99.98 16 | 100.00 1 | 99.94 27 | 100.00 1 | 99.75 49 | 98.67 40 | 100.00 1 | 100.00 1 | 99.16 75 | 100.00 1 | 100.00 1 | 100.00 1 | 100.00 1 |
|
test_prior3 | | | 99.81 9 | 99.78 6 | 99.90 70 | 100.00 1 | 99.75 83 | 100.00 1 | 99.73 54 | 98.82 33 | 100.00 1 | 100.00 1 | 99.47 39 | 99.97 97 | 100.00 1 | 100.00 1 | 100.00 1 |
|
test_prior2 | | | | | | | | 100.00 1 | | 98.82 33 | 100.00 1 | 100.00 1 | 99.47 39 | | 100.00 1 | 100.00 1 | |
|
æ–°å‡ ä½•1 | | | | | 99.99 5 | 100.00 1 | 99.96 10 | | 99.81 41 | 97.89 93 | 100.00 1 | 100.00 1 | 99.20 71 | 100.00 1 | 97.91 205 | 100.00 1 | 100.00 1 |
|
旧先验1 | | | | | | 99.99 45 | 99.88 58 | | 99.82 40 | | | 100.00 1 | 99.27 65 | | | 100.00 1 | 100.00 1 |
|
原ACMM1 | | | | | 99.93 60 | 100.00 1 | 99.80 78 | | 99.66 70 | 98.18 66 | 100.00 1 | 100.00 1 | 99.43 44 | 100.00 1 | 99.50 125 | 100.00 1 | 100.00 1 |
|
test222 | | | | | | 99.99 45 | 99.90 44 | 100.00 1 | 99.69 69 | 97.66 112 | 100.00 1 | 100.00 1 | 99.30 60 | | | 100.00 1 | 100.00 1 |
|
testdata | | | | | 99.66 114 | 99.99 45 | 98.97 155 | | 99.73 54 | 97.96 88 | 100.00 1 | 100.00 1 | 99.42 45 | 100.00 1 | 99.28 142 | 100.00 1 | 100.00 1 |
|
1314 | | | 99.38 73 | 99.19 83 | 99.96 35 | 98.88 229 | 99.89 48 | 99.24 301 | 99.93 31 | 98.88 27 | 98.79 201 | 100.00 1 | 97.02 141 | 100.00 1 | 100.00 1 | 100.00 1 | 100.00 1 |
|
1121 | | | 99.63 51 | 99.51 55 | 99.99 5 | 99.99 45 | 99.96 10 | 99.24 301 | 99.74 52 | 97.89 93 | 100.00 1 | 100.00 1 | 99.39 48 | 100.00 1 | 99.33 138 | 100.00 1 | 100.00 1 |
|
LFMVS | | | 97.42 186 | 96.62 204 | 99.81 90 | 99.80 112 | 99.50 109 | 99.16 316 | 99.56 73 | 94.48 245 | 100.00 1 | 100.00 1 | 79.35 327 | 100.00 1 | 99.89 77 | 97.37 202 | 99.94 114 |
|
VDD-MVS | | | 96.58 225 | 95.99 232 | 98.34 198 | 99.52 169 | 95.33 269 | 99.18 310 | 99.38 171 | 96.64 181 | 99.77 137 | 100.00 1 | 72.51 338 | 100.00 1 | 100.00 1 | 96.94 207 | 99.70 189 |
|
VDDNet | | | 96.39 234 | 95.55 250 | 98.90 173 | 99.27 197 | 97.45 232 | 99.15 317 | 99.92 35 | 91.28 297 | 99.98 80 | 100.00 1 | 73.55 336 | 100.00 1 | 99.85 82 | 96.98 206 | 99.24 203 |
|
MVS | | | 99.22 98 | 98.96 104 | 99.98 16 | 99.00 218 | 99.95 19 | 99.24 301 | 99.94 18 | 98.14 70 | 98.88 194 | 100.00 1 | 95.63 177 | 100.00 1 | 99.85 82 | 100.00 1 | 100.00 1 |
|
SD-MVS | | | 99.81 9 | 99.75 12 | 99.99 5 | 99.99 45 | 99.96 10 | 100.00 1 | 99.42 120 | 99.01 18 | 100.00 1 | 100.00 1 | 99.33 50 | 100.00 1 | 100.00 1 | 100.00 1 | 100.00 1 |
|
MSLP-MVS++ | | | 99.89 1 | 99.85 2 | 99.99 5 | 100.00 1 | 99.96 10 | 100.00 1 | 99.95 15 | 99.11 6 | 100.00 1 | 100.00 1 | 99.60 19 | 100.00 1 | 100.00 1 | 100.00 1 | 100.00 1 |
|
APDe-MVS | | | 99.84 6 | 99.78 6 | 99.99 5 | 100.00 1 | 99.98 6 | 100.00 1 | 99.44 105 | 99.06 10 | 100.00 1 | 100.00 1 | 99.56 23 | 99.99 80 | 100.00 1 | 100.00 1 | 100.00 1 |
|
APD-MVS_3200maxsize | | | 99.65 47 | 99.55 54 | 99.97 23 | 99.99 45 | 99.91 38 | 100.00 1 | 99.48 81 | 97.54 129 | 100.00 1 | 100.00 1 | 98.97 88 | 99.99 80 | 99.98 58 | 100.00 1 | 100.00 1 |
|
EI-MVSNet | | | 97.98 173 | 97.93 171 | 98.16 216 | 99.11 202 | 97.84 224 | 99.74 250 | 99.29 209 | 94.39 247 | 98.65 210 | 100.00 1 | 97.21 136 | 98.88 235 | 97.62 212 | 95.31 220 | 97.75 220 |
|
CVMVSNet | | | 98.56 149 | 98.47 150 | 98.82 177 | 99.11 202 | 97.67 228 | 99.74 250 | 99.47 82 | 97.57 128 | 99.06 186 | 100.00 1 | 95.72 175 | 98.97 226 | 98.21 189 | 97.33 203 | 99.83 164 |
|
TESTMET0.1,1 | | | 99.08 108 | 98.96 104 | 99.44 134 | 99.63 143 | 99.38 122 | 100.00 1 | 99.45 96 | 95.53 220 | 99.48 162 | 100.00 1 | 99.71 16 | 99.02 221 | 96.84 233 | 99.99 87 | 99.91 126 |
|
ACMMPR | | | 99.74 23 | 99.67 27 | 99.96 35 | 100.00 1 | 99.89 48 | 100.00 1 | 99.76 45 | 97.95 89 | 100.00 1 | 100.00 1 | 99.29 61 | 100.00 1 | 99.99 44 | 100.00 1 | 100.00 1 |
|
MP-MVS | | | 99.61 54 | 99.49 58 | 99.98 16 | 99.99 45 | 99.94 27 | 100.00 1 | 99.42 120 | 97.82 100 | 99.99 75 | 100.00 1 | 98.20 118 | 100.00 1 | 99.99 44 | 100.00 1 | 100.00 1 |
|
testmvs | | | 80.17 314 | 81.95 315 | 74.80 335 | 58.54 355 | 59.58 353 | 100.00 1 | 87.14 355 | 76.09 338 | 99.61 154 | 100.00 1 | 67.06 341 | 74.19 354 | 98.84 160 | 50.30 345 | 90.64 341 |
|
PGM-MVS | | | 99.69 39 | 99.61 44 | 99.95 46 | 99.99 45 | 99.85 68 | 100.00 1 | 99.58 72 | 97.69 111 | 100.00 1 | 100.00 1 | 99.44 43 | 100.00 1 | 99.79 90 | 100.00 1 | 100.00 1 |
|
MCST-MVS | | | 99.85 3 | 99.80 4 | 100.00 1 | 100.00 1 | 99.99 1 | 100.00 1 | 99.73 54 | 99.19 5 | 100.00 1 | 100.00 1 | 99.31 54 | 100.00 1 | 100.00 1 | 100.00 1 | 100.00 1 |
|
CDPH-MVS | | | 99.73 26 | 99.64 35 | 99.99 5 | 100.00 1 | 99.97 8 | 100.00 1 | 99.42 120 | 98.02 80 | 100.00 1 | 100.00 1 | 99.32 53 | 99.99 80 | 100.00 1 | 100.00 1 | 100.00 1 |
|
TSAR-MVS + GP. | | | 99.61 54 | 99.69 18 | 99.35 144 | 99.99 45 | 98.06 209 | 100.00 1 | 99.36 180 | 99.83 2 | 100.00 1 | 100.00 1 | 98.95 91 | 99.99 80 | 100.00 1 | 99.11 123 | 100.00 1 |
|
abl_6 | | | 99.53 60 | 99.40 61 | 99.92 66 | 100.00 1 | 99.76 81 | 100.00 1 | 99.42 120 | 97.21 148 | 100.00 1 | 100.00 1 | 98.12 120 | 100.00 1 | 99.82 89 | 100.00 1 | 100.00 1 |
|
mPP-MVS | | | 99.69 39 | 99.60 45 | 99.97 23 | 100.00 1 | 99.91 38 | 100.00 1 | 99.42 120 | 97.91 92 | 100.00 1 | 100.00 1 | 99.04 82 | 100.00 1 | 100.00 1 | 100.00 1 | 100.00 1 |
|
XVG-OURS-SEG-HR | | | 98.27 165 | 98.31 156 | 98.14 217 | 99.59 152 | 95.92 265 | 100.00 1 | 99.36 180 | 98.48 47 | 99.21 175 | 100.00 1 | 89.27 267 | 99.94 129 | 99.76 96 | 99.17 121 | 98.56 210 |
|
DWT-MVSNet_test | | | 99.22 98 | 99.22 78 | 99.22 155 | 99.56 160 | 97.98 213 | 99.89 219 | 99.39 167 | 97.20 149 | 99.96 87 | 100.00 1 | 99.52 28 | 99.82 150 | 99.11 151 | 98.34 151 | 99.87 158 |
|
MVSFormer | | | 98.94 127 | 98.82 122 | 99.28 150 | 99.45 179 | 99.49 112 | 100.00 1 | 99.13 261 | 95.46 227 | 99.97 84 | 100.00 1 | 96.76 156 | 98.59 266 | 98.63 172 | 100.00 1 | 99.74 184 |
|
jason | | | 99.11 106 | 98.96 104 | 99.59 122 | 99.17 200 | 99.31 127 | 100.00 1 | 99.13 261 | 97.38 137 | 99.83 124 | 100.00 1 | 95.54 178 | 99.72 162 | 99.57 117 | 99.97 97 | 99.74 184 |
jason: jason. |
lupinMVS | | | 99.29 88 | 99.16 85 | 99.69 112 | 99.45 179 | 99.49 112 | 100.00 1 | 99.15 252 | 97.45 133 | 99.97 84 | 100.00 1 | 96.76 156 | 99.76 157 | 99.67 106 | 100.00 1 | 99.81 169 |
|
HPM-MVS_fast | | | 99.60 57 | 99.49 58 | 99.91 67 | 99.99 45 | 99.78 80 | 100.00 1 | 99.42 120 | 97.09 155 | 100.00 1 | 100.00 1 | 98.95 91 | 99.96 112 | 99.98 58 | 100.00 1 | 100.00 1 |
|
PatchFormer-LS_test | | | 99.14 104 | 99.12 94 | 99.19 156 | 99.54 161 | 97.86 223 | 99.66 269 | 99.40 153 | 96.94 165 | 99.96 87 | 100.00 1 | 99.29 61 | 99.84 146 | 98.96 154 | 98.29 154 | 99.88 151 |
|
HPM-MVS | | | 99.59 58 | 99.50 56 | 99.89 73 | 100.00 1 | 99.70 98 | 100.00 1 | 99.42 120 | 97.46 132 | 100.00 1 | 100.00 1 | 98.60 110 | 99.96 112 | 99.99 44 | 100.00 1 | 100.00 1 |
|
XVG-OURS | | | 98.30 162 | 98.36 155 | 98.13 220 | 99.58 156 | 95.91 266 | 100.00 1 | 99.36 180 | 98.69 38 | 99.23 174 | 100.00 1 | 91.20 236 | 99.92 134 | 99.34 137 | 97.82 181 | 98.56 210 |
|
CHOSEN 1792x2688 | | | 99.00 119 | 98.91 115 | 99.25 153 | 99.90 93 | 97.79 225 | 100.00 1 | 99.99 10 | 98.79 36 | 98.28 234 | 100.00 1 | 93.63 199 | 99.95 118 | 99.66 108 | 99.95 101 | 100.00 1 |
|
EPNet | | | 99.62 52 | 99.69 18 | 99.42 137 | 99.99 45 | 98.37 178 | 100.00 1 | 99.89 37 | 98.83 31 | 100.00 1 | 100.00 1 | 98.97 88 | 100.00 1 | 99.90 75 | 99.61 118 | 99.89 139 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
APD-MVS | | | 99.68 42 | 99.58 48 | 99.97 23 | 99.99 45 | 99.96 10 | 100.00 1 | 99.42 120 | 97.53 130 | 100.00 1 | 100.00 1 | 99.27 65 | 99.97 97 | 100.00 1 | 100.00 1 | 100.00 1 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
CNVR-MVS | | | 99.85 3 | 99.80 4 | 100.00 1 | 100.00 1 | 99.99 1 | 100.00 1 | 99.77 44 | 99.07 8 | 100.00 1 | 100.00 1 | 99.39 48 | 100.00 1 | 100.00 1 | 100.00 1 | 100.00 1 |
|
NCCC | | | 99.86 2 | 99.82 3 | 100.00 1 | 100.00 1 | 99.99 1 | 100.00 1 | 99.71 62 | 99.07 8 | 100.00 1 | 100.00 1 | 99.59 21 | 100.00 1 | 100.00 1 | 100.00 1 | 100.00 1 |
|
114514_t | | | 99.39 72 | 99.25 74 | 99.81 90 | 99.97 75 | 99.48 116 | 100.00 1 | 99.42 120 | 95.53 220 | 100.00 1 | 100.00 1 | 98.37 117 | 99.95 118 | 99.97 63 | 100.00 1 | 100.00 1 |
|
CP-MVS | | | 99.67 45 | 99.58 48 | 99.95 46 | 100.00 1 | 99.84 69 | 100.00 1 | 99.42 120 | 97.77 103 | 100.00 1 | 100.00 1 | 99.07 79 | 100.00 1 | 100.00 1 | 100.00 1 | 100.00 1 |
|
SteuartSystems-ACMMP | | | 99.78 13 | 99.71 16 | 99.98 16 | 99.76 124 | 99.95 19 | 100.00 1 | 99.42 120 | 98.69 38 | 100.00 1 | 100.00 1 | 99.52 28 | 99.99 80 | 100.00 1 | 100.00 1 | 100.00 1 |
Skip Steuart: Steuart Systems R&D Blog. |
BH-w/o | | | 98.82 135 | 98.81 124 | 98.88 174 | 99.62 145 | 96.71 257 | 100.00 1 | 99.28 217 | 97.09 155 | 98.81 200 | 100.00 1 | 94.91 188 | 99.96 112 | 99.54 121 | 100.00 1 | 99.96 105 |
|
DELS-MVS | | | 99.62 52 | 99.56 53 | 99.82 87 | 99.92 90 | 99.45 118 | 100.00 1 | 99.78 43 | 98.92 25 | 99.73 141 | 100.00 1 | 97.70 128 | 100.00 1 | 99.93 72 | 100.00 1 | 100.00 1 |
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 |
BH-untuned | | | 98.64 144 | 98.65 137 | 98.60 186 | 99.59 152 | 96.17 262 | 100.00 1 | 99.28 217 | 96.67 180 | 98.41 227 | 100.00 1 | 94.52 191 | 99.83 148 | 99.41 133 | 100.00 1 | 99.81 169 |
|
CPTT-MVS | | | 99.49 65 | 99.38 65 | 99.85 83 | 100.00 1 | 99.54 107 | 100.00 1 | 99.42 120 | 97.58 127 | 99.98 80 | 100.00 1 | 97.43 135 | 100.00 1 | 99.99 44 | 100.00 1 | 100.00 1 |
|
PVSNet_Blended_VisFu | | | 99.33 78 | 99.18 84 | 99.78 105 | 99.82 98 | 99.49 112 | 100.00 1 | 99.95 15 | 97.36 138 | 99.63 153 | 100.00 1 | 96.45 164 | 99.95 118 | 99.79 90 | 99.65 117 | 99.89 139 |
|
PVSNet_Blended | | | 99.48 67 | 99.36 67 | 99.83 86 | 99.98 71 | 99.60 105 | 100.00 1 | 100.00 1 | 97.79 102 | 100.00 1 | 100.00 1 | 96.57 160 | 99.99 80 | 100.00 1 | 99.88 107 | 99.90 134 |
|
BH-RMVSNet | | | 98.46 156 | 98.08 165 | 99.59 122 | 99.61 147 | 99.19 139 | 100.00 1 | 99.28 217 | 97.06 159 | 98.95 190 | 100.00 1 | 88.99 270 | 99.82 150 | 98.83 162 | 100.00 1 | 99.77 177 |
|
WTY-MVS | | | 99.54 59 | 99.40 61 | 99.95 46 | 99.81 99 | 99.93 32 | 100.00 1 | 100.00 1 | 97.98 84 | 99.84 122 | 100.00 1 | 98.94 93 | 99.98 93 | 99.86 80 | 98.21 159 | 99.94 114 |
|
1112_ss | | | 98.91 129 | 98.71 132 | 99.51 130 | 99.69 130 | 98.75 161 | 99.99 174 | 99.15 252 | 96.82 168 | 98.84 198 | 100.00 1 | 97.45 133 | 99.89 137 | 98.66 168 | 97.75 186 | 99.89 139 |
|
ab-mvs-re | | | 8.33 332 | 11.11 333 | 0.00 344 | 0.00 358 | 0.00 359 | 0.00 350 | 0.00 360 | 0.00 354 | 0.00 355 | 100.00 1 | 0.00 362 | 0.00 357 | 0.00 354 | 0.00 355 | 0.00 355 |
|
DP-MVS Recon | | | 99.76 15 | 99.69 18 | 99.98 16 | 100.00 1 | 99.95 19 | 100.00 1 | 99.52 75 | 97.99 82 | 99.99 75 | 100.00 1 | 99.72 15 | 100.00 1 | 99.96 65 | 100.00 1 | 100.00 1 |
|
MVS_111021_LR | | | 99.70 36 | 99.65 31 | 99.88 78 | 99.96 80 | 99.70 98 | 100.00 1 | 99.97 14 | 98.96 21 | 100.00 1 | 100.00 1 | 97.93 124 | 99.95 118 | 99.99 44 | 100.00 1 | 100.00 1 |
|
DP-MVS | | | 98.86 132 | 98.54 146 | 99.81 90 | 99.97 75 | 99.45 118 | 99.52 281 | 99.40 153 | 94.35 248 | 98.36 228 | 100.00 1 | 96.13 167 | 99.97 97 | 99.12 150 | 100.00 1 | 100.00 1 |
|
QAPM | | | 98.99 121 | 98.66 134 | 99.96 35 | 99.01 214 | 99.87 61 | 99.88 222 | 99.93 31 | 97.99 82 | 98.68 208 | 100.00 1 | 93.17 205 | 100.00 1 | 99.32 140 | 100.00 1 | 100.00 1 |
|
Vis-MVSNet | | | 98.52 153 | 98.25 157 | 99.34 145 | 99.68 133 | 98.55 170 | 99.68 266 | 99.41 151 | 97.34 141 | 99.94 108 | 100.00 1 | 90.38 252 | 99.70 164 | 99.03 153 | 98.84 129 | 99.76 179 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
IS-MVSNet | | | 99.08 108 | 98.91 115 | 99.59 122 | 99.65 138 | 99.38 122 | 99.78 240 | 99.24 231 | 96.70 176 | 99.51 160 | 100.00 1 | 98.44 116 | 99.52 194 | 98.47 179 | 98.39 146 | 99.88 151 |
|
PAPM_NR | | | 99.74 23 | 99.66 30 | 99.99 5 | 100.00 1 | 99.96 10 | 100.00 1 | 99.47 82 | 97.87 96 | 100.00 1 | 100.00 1 | 99.60 19 | 100.00 1 | 100.00 1 | 100.00 1 | 100.00 1 |
|
PAPR | | | 99.76 15 | 99.68 22 | 99.99 5 | 100.00 1 | 99.96 10 | 100.00 1 | 99.47 82 | 98.16 67 | 100.00 1 | 100.00 1 | 99.51 30 | 100.00 1 | 100.00 1 | 100.00 1 | 100.00 1 |
|
RPSCF | | | 97.37 187 | 98.24 158 | 94.76 303 | 99.80 112 | 84.57 328 | 99.99 174 | 99.05 292 | 94.95 234 | 99.82 132 | 100.00 1 | 94.03 194 | 100.00 1 | 98.15 191 | 98.38 149 | 99.70 189 |
|
Vis-MVSNet (Re-imp) | | | 98.99 121 | 98.89 119 | 99.29 149 | 99.64 142 | 98.89 157 | 99.98 190 | 99.31 203 | 96.74 172 | 99.48 162 | 100.00 1 | 98.11 121 | 99.10 217 | 98.39 181 | 98.34 151 | 99.89 139 |
|
MVS_111021_HR | | | 99.71 32 | 99.63 39 | 99.93 60 | 99.95 81 | 99.83 70 | 100.00 1 | 100.00 1 | 98.89 26 | 100.00 1 | 100.00 1 | 97.85 125 | 99.95 118 | 100.00 1 | 100.00 1 | 100.00 1 |
|
CSCG | | | 99.28 89 | 99.35 69 | 99.05 162 | 99.99 45 | 97.15 246 | 100.00 1 | 99.47 82 | 97.44 134 | 99.42 165 | 100.00 1 | 97.83 126 | 100.00 1 | 99.99 44 | 100.00 1 | 100.00 1 |
|
API-MVS | | | 99.72 29 | 99.70 17 | 99.79 97 | 99.97 75 | 99.37 124 | 99.96 199 | 99.94 18 | 98.48 47 | 100.00 1 | 100.00 1 | 98.92 95 | 100.00 1 | 100.00 1 | 100.00 1 | 100.00 1 |
|
EPP-MVSNet | | | 99.10 107 | 99.00 100 | 99.40 139 | 99.51 172 | 98.68 165 | 99.92 213 | 99.43 114 | 95.47 226 | 99.65 152 | 100.00 1 | 99.51 30 | 99.76 157 | 99.53 123 | 98.00 168 | 99.75 180 |
|
PMMVS | | | 99.12 105 | 98.97 103 | 99.58 126 | 99.57 158 | 98.98 153 | 100.00 1 | 99.30 205 | 97.14 151 | 99.96 87 | 100.00 1 | 96.53 163 | 99.82 150 | 99.70 102 | 98.49 137 | 99.94 114 |
|
PAPM | | | 99.78 13 | 99.76 10 | 99.85 83 | 99.01 214 | 99.95 19 | 100.00 1 | 99.75 49 | 99.37 3 | 99.99 75 | 100.00 1 | 99.76 14 | 99.60 172 | 100.00 1 | 100.00 1 | 100.00 1 |
|
ACMMP | | | 99.65 47 | 99.57 50 | 99.89 73 | 99.99 45 | 99.66 101 | 99.75 249 | 99.73 54 | 98.16 67 | 99.75 140 | 100.00 1 | 98.90 97 | 100.00 1 | 99.96 65 | 99.88 107 | 100.00 1 |
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 |
CNLPA | | | 99.72 29 | 99.65 31 | 99.91 67 | 99.97 75 | 99.72 93 | 100.00 1 | 99.47 82 | 98.43 49 | 99.88 120 | 100.00 1 | 99.14 77 | 100.00 1 | 99.97 63 | 100.00 1 | 100.00 1 |
|
PHI-MVS | | | 99.50 63 | 99.39 63 | 99.82 87 | 100.00 1 | 99.45 118 | 100.00 1 | 99.94 18 | 96.38 197 | 100.00 1 | 100.00 1 | 98.18 119 | 100.00 1 | 100.00 1 | 100.00 1 | 100.00 1 |
|
PVSNet | | 94.91 18 | 99.30 87 | 99.25 74 | 99.44 134 | 100.00 1 | 98.32 184 | 100.00 1 | 99.86 38 | 98.04 79 | 100.00 1 | 100.00 1 | 96.10 168 | 100.00 1 | 99.55 118 | 99.73 114 | 100.00 1 |
|
F-COLMAP | | | 99.64 49 | 99.64 35 | 99.67 113 | 99.99 45 | 99.07 144 | 100.00 1 | 99.44 105 | 98.30 63 | 99.90 116 | 100.00 1 | 99.18 73 | 99.99 80 | 99.91 74 | 100.00 1 | 99.94 114 |
|
DeepPCF-MVS | | 98.03 4 | 98.54 151 | 99.72 15 | 94.98 301 | 99.99 45 | 84.94 327 | 100.00 1 | 99.42 120 | 99.98 1 | 100.00 1 | 100.00 1 | 98.11 121 | 100.00 1 | 100.00 1 | 100.00 1 | 100.00 1 |
|
OMC-MVS | | | 99.27 90 | 99.38 65 | 98.96 169 | 99.95 81 | 97.06 250 | 100.00 1 | 99.40 153 | 98.83 31 | 99.88 120 | 100.00 1 | 97.01 142 | 99.86 141 | 99.47 126 | 99.84 110 | 99.97 95 |
|
DeepC-MVS | | 97.84 5 | 99.00 119 | 98.80 125 | 99.60 119 | 99.93 87 | 99.03 147 | 100.00 1 | 99.40 153 | 98.61 44 | 99.33 170 | 100.00 1 | 92.23 214 | 99.95 118 | 99.74 98 | 99.96 99 | 99.83 164 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
DeepC-MVS_fast | | 98.92 1 | 99.75 18 | 99.67 27 | 99.99 5 | 99.99 45 | 99.96 10 | 99.73 254 | 99.52 75 | 99.06 10 | 100.00 1 | 100.00 1 | 98.80 103 | 100.00 1 | 99.95 70 | 100.00 1 | 100.00 1 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
MG-MVS | | | 99.75 18 | 99.68 22 | 99.97 23 | 100.00 1 | 99.91 38 | 99.98 190 | 99.47 82 | 99.09 7 | 100.00 1 | 100.00 1 | 98.59 111 | 100.00 1 | 99.95 70 | 100.00 1 | 100.00 1 |
|
AdaColmap | | | 99.44 70 | 99.26 73 | 99.95 46 | 100.00 1 | 99.86 65 | 99.70 260 | 99.99 10 | 98.53 46 | 99.90 116 | 100.00 1 | 95.34 179 | 100.00 1 | 99.92 73 | 100.00 1 | 100.00 1 |
|
PLC | | 98.56 2 | 99.70 36 | 99.74 13 | 99.58 126 | 100.00 1 | 98.79 160 | 100.00 1 | 99.54 74 | 98.58 45 | 99.96 87 | 100.00 1 | 99.59 21 | 100.00 1 | 100.00 1 | 100.00 1 | 99.94 114 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
PCF-MVS | | 98.23 3 | 98.69 143 | 98.37 154 | 99.62 115 | 99.78 120 | 99.02 148 | 99.23 307 | 99.06 290 | 96.43 192 | 98.08 240 | 100.00 1 | 94.72 189 | 99.95 118 | 98.16 190 | 99.91 104 | 99.90 134 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
MAR-MVS | | | 99.49 65 | 99.36 67 | 99.89 73 | 99.97 75 | 99.66 101 | 99.74 250 | 99.95 15 | 97.89 93 | 100.00 1 | 100.00 1 | 96.71 158 | 100.00 1 | 100.00 1 | 100.00 1 | 100.00 1 |
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 |
3Dnovator+ | | 95.58 15 | 99.03 113 | 98.71 132 | 99.96 35 | 98.99 221 | 99.89 48 | 100.00 1 | 99.51 79 | 98.96 21 | 98.32 231 | 100.00 1 | 92.78 209 | 100.00 1 | 99.87 79 | 100.00 1 | 100.00 1 |
|
3Dnovator | | 95.63 14 | 99.06 110 | 98.76 128 | 99.96 35 | 98.86 232 | 99.90 44 | 99.98 190 | 99.93 31 | 98.95 24 | 98.49 224 | 100.00 1 | 92.91 208 | 100.00 1 | 99.71 100 | 100.00 1 | 100.00 1 |
|
TAPA-MVS | | 96.40 10 | 97.64 180 | 97.37 185 | 98.45 190 | 99.94 85 | 95.70 268 | 100.00 1 | 99.40 153 | 97.65 119 | 99.53 159 | 100.00 1 | 99.31 54 | 99.66 171 | 80.48 330 | 100.00 1 | 100.00 1 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
OpenMVS | | 95.20 17 | 98.76 137 | 98.41 151 | 99.78 105 | 98.89 228 | 99.81 76 | 99.99 174 | 99.76 45 | 98.02 80 | 98.02 245 | 100.00 1 | 91.44 232 | 100.00 1 | 99.63 110 | 99.97 97 | 99.55 197 |
|
MSDG | | | 98.90 130 | 98.63 139 | 99.70 111 | 99.92 90 | 99.25 133 | 100.00 1 | 99.37 174 | 95.71 214 | 99.40 169 | 100.00 1 | 96.58 159 | 99.95 118 | 96.80 236 | 99.94 102 | 99.91 126 |
|
LS3D | | | 99.31 86 | 99.13 92 | 99.87 79 | 99.99 45 | 99.71 94 | 99.55 278 | 99.46 94 | 97.32 142 | 99.82 132 | 100.00 1 | 96.85 155 | 99.97 97 | 99.14 148 | 100.00 1 | 99.92 125 |
|
COLMAP_ROB | | 97.10 7 | 98.29 163 | 98.17 162 | 98.65 184 | 99.94 85 | 97.39 235 | 99.30 297 | 99.40 153 | 95.64 215 | 97.75 256 | 100.00 1 | 92.69 211 | 99.95 118 | 98.89 157 | 99.92 103 | 98.62 209 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
VNet | | | 99.04 112 | 98.75 129 | 99.90 70 | 99.81 99 | 99.75 83 | 99.50 283 | 99.47 82 | 98.36 58 | 100.00 1 | 99.99 139 | 94.66 190 | 100.00 1 | 99.90 75 | 97.09 205 | 99.96 105 |
|
tfpn1000 | | | 99.47 68 | 99.34 71 | 99.87 79 | 99.89 95 | 99.80 78 | 100.00 1 | 99.72 60 | 97.83 98 | 99.96 87 | 99.98 140 | 99.94 4 | 99.82 150 | 98.87 159 | 97.87 175 | 100.00 1 |
|
tfpn_ndepth | | | 99.52 61 | 99.39 63 | 99.89 73 | 99.90 93 | 99.83 70 | 100.00 1 | 99.72 60 | 97.95 89 | 99.96 87 | 99.98 140 | 99.94 4 | 99.85 145 | 99.17 147 | 97.91 172 | 100.00 1 |
|
OPM-MVS | | | 97.21 192 | 97.18 190 | 97.32 255 | 98.08 271 | 94.66 287 | 100.00 1 | 99.28 217 | 98.65 42 | 98.92 191 | 99.98 140 | 86.03 296 | 99.56 181 | 98.28 187 | 95.41 217 | 97.72 257 |
|
AllTest | | | 98.55 150 | 98.40 152 | 98.99 166 | 99.93 87 | 97.35 238 | 100.00 1 | 99.40 153 | 97.08 157 | 99.09 182 | 99.98 140 | 93.37 201 | 99.95 118 | 96.94 229 | 99.84 110 | 99.68 191 |
|
TestCases | | | | | 98.99 166 | 99.93 87 | 97.35 238 | | 99.40 153 | 97.08 157 | 99.09 182 | 99.98 140 | 93.37 201 | 99.95 118 | 96.94 229 | 99.84 110 | 99.68 191 |
|
LPG-MVS_test | | | 97.31 189 | 97.32 186 | 97.28 257 | 98.85 233 | 94.60 290 | 100.00 1 | 99.37 174 | 97.35 139 | 98.85 196 | 99.98 140 | 86.66 290 | 99.56 181 | 99.55 118 | 95.26 222 | 97.70 265 |
|
LGP-MVS_train | | | | | 97.28 257 | 98.85 233 | 94.60 290 | | 99.37 174 | 97.35 139 | 98.85 196 | 99.98 140 | 86.66 290 | 99.56 181 | 99.55 118 | 95.26 222 | 97.70 265 |
|
cascas | | | 98.43 157 | 98.07 166 | 99.50 132 | 99.65 138 | 99.02 148 | 100.00 1 | 99.22 236 | 94.21 252 | 99.72 142 | 99.98 140 | 92.03 217 | 99.93 131 | 99.68 104 | 98.12 164 | 99.54 198 |
|
ACMP | | 97.00 8 | 97.19 193 | 97.16 191 | 97.27 259 | 98.97 223 | 94.58 292 | 100.00 1 | 99.32 198 | 97.97 86 | 97.45 264 | 99.98 140 | 85.79 298 | 99.56 181 | 99.70 102 | 95.24 225 | 97.67 276 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
ACMM | | 97.17 6 | 97.37 187 | 97.40 183 | 97.29 256 | 99.01 214 | 94.64 289 | 100.00 1 | 99.25 228 | 98.07 77 | 98.44 226 | 99.98 140 | 87.38 284 | 99.55 186 | 99.25 143 | 95.19 227 | 97.69 270 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
HQP_MVS | | | 97.71 179 | 97.82 174 | 97.37 253 | 99.00 218 | 94.80 280 | 100.00 1 | 99.40 153 | 99.00 19 | 99.08 184 | 99.97 150 | 88.58 276 | 99.55 186 | 99.79 90 | 95.57 215 | 97.76 216 |
|
plane_prior4 | | | | | | | | | | | | 99.97 150 | | | | | |
|
SixPastTwentyTwo | | | 95.71 262 | 95.49 253 | 96.38 290 | 97.42 305 | 93.01 305 | 99.84 227 | 98.23 318 | 94.75 236 | 95.98 288 | 99.97 150 | 85.35 300 | 98.43 278 | 94.71 264 | 93.17 250 | 97.69 270 |
|
NP-MVS | | | | | | 99.07 206 | 94.81 279 | | | | | 99.97 150 | | | | | |
|
HQP-MVS | | | 97.73 177 | 97.85 173 | 97.39 252 | 99.07 206 | 94.82 277 | 100.00 1 | 99.40 153 | 99.04 13 | 99.17 176 | 99.97 150 | 88.61 274 | 99.57 177 | 99.79 90 | 95.58 211 | 97.77 214 |
|
ITE_SJBPF | | | | | 96.84 279 | 98.96 224 | 93.49 301 | | 98.12 323 | 98.12 74 | 98.35 229 | 99.97 150 | 84.45 302 | 99.56 181 | 95.63 250 | 95.25 224 | 97.49 296 |
|
ACMH+ | | 96.20 13 | 96.49 229 | 96.33 214 | 97.00 265 | 99.06 210 | 93.80 299 | 99.81 235 | 99.31 203 | 97.32 142 | 95.89 290 | 99.97 150 | 82.62 313 | 99.54 189 | 98.34 184 | 94.63 239 | 97.65 282 |
|
CLD-MVS | | | 97.64 180 | 97.74 176 | 97.36 254 | 99.01 214 | 94.76 285 | 100.00 1 | 99.34 193 | 99.30 4 | 99.00 188 | 99.97 150 | 87.49 283 | 99.57 177 | 99.96 65 | 95.58 211 | 97.75 220 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
ACMH | | 96.25 11 | 96.77 209 | 96.62 204 | 97.21 260 | 98.96 224 | 94.43 294 | 99.64 271 | 99.33 195 | 97.43 135 | 96.55 283 | 99.97 150 | 83.52 309 | 99.54 189 | 99.07 152 | 95.13 230 | 97.66 278 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
conf200view11 | | | 99.25 94 | 99.01 98 | 99.95 46 | 99.81 99 | 99.87 61 | 100.00 1 | 99.94 18 | 97.13 152 | 99.83 124 | 99.96 159 | 97.01 142 | 100.00 1 | 99.59 112 | 97.85 177 | 99.97 95 |
|
thres100view900 | | | 99.25 94 | 99.01 98 | 99.95 46 | 99.81 99 | 99.87 61 | 100.00 1 | 99.94 18 | 97.13 152 | 99.83 124 | 99.96 159 | 97.01 142 | 100.00 1 | 99.59 112 | 97.85 177 | 99.98 90 |
|
tfpn200view9 | | | 99.26 92 | 99.03 96 | 99.96 35 | 99.81 99 | 99.89 48 | 100.00 1 | 99.94 18 | 97.23 145 | 99.83 124 | 99.96 159 | 97.04 138 | 100.00 1 | 99.59 112 | 97.85 177 | 99.98 90 |
|
view600 | | | 99.18 100 | 98.93 110 | 99.93 60 | 99.81 99 | 99.83 70 | 100.00 1 | 99.94 18 | 96.96 161 | 99.54 155 | 99.96 159 | 96.99 149 | 100.00 1 | 99.43 127 | 97.75 186 | 99.97 95 |
|
view800 | | | 99.18 100 | 98.93 110 | 99.93 60 | 99.81 99 | 99.83 70 | 100.00 1 | 99.94 18 | 96.96 161 | 99.54 155 | 99.96 159 | 96.99 149 | 100.00 1 | 99.43 127 | 97.75 186 | 99.97 95 |
|
conf0.05thres1000 | | | 99.18 100 | 98.93 110 | 99.93 60 | 99.81 99 | 99.83 70 | 100.00 1 | 99.94 18 | 96.96 161 | 99.54 155 | 99.96 159 | 96.99 149 | 100.00 1 | 99.43 127 | 97.75 186 | 99.97 95 |
|
tfpn | | | 99.18 100 | 98.93 110 | 99.93 60 | 99.81 99 | 99.83 70 | 100.00 1 | 99.94 18 | 96.96 161 | 99.54 155 | 99.96 159 | 96.99 149 | 100.00 1 | 99.43 127 | 97.75 186 | 99.97 95 |
|
thres600view7 | | | 99.24 97 | 99.00 100 | 99.95 46 | 99.81 99 | 99.87 61 | 100.00 1 | 99.94 18 | 97.13 152 | 99.83 124 | 99.96 159 | 97.01 142 | 100.00 1 | 99.54 121 | 97.77 185 | 99.97 95 |
|
thres400 | | | 99.26 92 | 99.03 96 | 99.95 46 | 99.81 99 | 99.89 48 | 100.00 1 | 99.94 18 | 97.23 145 | 99.83 124 | 99.96 159 | 97.04 138 | 100.00 1 | 99.59 112 | 97.85 177 | 99.97 95 |
|
thres200 | | | 99.27 90 | 99.04 95 | 99.96 35 | 99.81 99 | 99.90 44 | 100.00 1 | 99.94 18 | 97.31 144 | 99.83 124 | 99.96 159 | 97.04 138 | 100.00 1 | 99.62 111 | 97.88 174 | 99.98 90 |
|
EPNet_dtu | | | 98.53 152 | 98.23 160 | 99.43 136 | 99.92 90 | 99.01 151 | 99.96 199 | 99.47 82 | 98.80 35 | 99.96 87 | 99.96 159 | 98.56 112 | 99.30 212 | 87.78 318 | 99.68 115 | 100.00 1 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
Fast-Effi-MVS+ | | | 98.40 160 | 98.02 169 | 99.55 129 | 99.63 143 | 99.06 145 | 100.00 1 | 99.15 252 | 95.07 231 | 99.42 165 | 99.95 170 | 93.26 204 | 99.73 160 | 97.44 218 | 98.24 157 | 99.87 158 |
|
nrg030 | | | 97.64 180 | 97.27 187 | 98.75 181 | 98.34 247 | 99.53 108 | 100.00 1 | 99.22 236 | 96.21 203 | 98.27 235 | 99.95 170 | 94.40 192 | 98.98 225 | 99.23 144 | 89.78 289 | 97.75 220 |
|
test0.0.03 1 | | | 98.12 169 | 98.03 168 | 98.39 193 | 99.11 202 | 98.07 208 | 100.00 1 | 99.93 31 | 96.70 176 | 96.91 277 | 99.95 170 | 99.31 54 | 98.19 284 | 91.93 293 | 98.44 141 | 98.91 204 |
|
OurMVSNet-221017-0 | | | 96.14 248 | 95.98 233 | 96.62 286 | 97.49 301 | 93.44 302 | 99.92 213 | 98.16 321 | 95.86 210 | 97.65 257 | 99.95 170 | 85.71 299 | 98.78 244 | 94.93 263 | 94.18 243 | 97.64 285 |
|
sss | | | 99.45 69 | 99.34 71 | 99.80 93 | 99.76 124 | 99.50 109 | 100.00 1 | 99.91 36 | 97.72 106 | 99.98 80 | 99.94 174 | 98.45 115 | 100.00 1 | 99.53 123 | 98.75 131 | 99.89 139 |
|
TR-MVS | | | 98.14 168 | 97.74 176 | 99.33 146 | 99.59 152 | 98.28 186 | 99.27 298 | 99.21 240 | 96.42 194 | 99.15 180 | 99.94 174 | 88.87 272 | 99.79 155 | 98.88 158 | 98.29 154 | 99.93 123 |
|
USDC | | | 95.90 256 | 95.70 245 | 96.50 288 | 98.60 239 | 92.56 311 | 100.00 1 | 98.30 317 | 97.77 103 | 96.92 275 | 99.94 174 | 81.25 321 | 99.45 202 | 93.54 283 | 94.96 235 | 97.49 296 |
|
mvs-test1 | | | 98.89 131 | 98.99 102 | 98.60 186 | 99.77 122 | 95.96 263 | 100.00 1 | 98.94 299 | 97.61 123 | 99.93 113 | 99.92 177 | 95.89 169 | 99.93 131 | 99.36 135 | 99.50 119 | 99.90 134 |
|
lessismore_v0 | | | | | 96.05 294 | 97.55 297 | 91.80 315 | | 99.22 236 | | 91.87 309 | 99.91 178 | 83.50 310 | 98.68 257 | 92.48 290 | 90.42 279 | 97.68 272 |
|
HyFIR lowres test | | | 99.32 79 | 99.24 76 | 99.58 126 | 99.95 81 | 99.26 131 | 100.00 1 | 99.99 10 | 96.72 175 | 99.29 172 | 99.91 178 | 99.49 36 | 99.47 200 | 99.74 98 | 98.08 166 | 100.00 1 |
|
Effi-MVS+ | | | 98.58 147 | 98.24 158 | 99.61 116 | 99.60 149 | 99.26 131 | 97.85 338 | 99.10 269 | 96.22 202 | 99.97 84 | 99.89 180 | 93.75 197 | 99.77 156 | 99.43 127 | 98.34 151 | 99.81 169 |
|
VPNet | | | 96.41 231 | 95.76 242 | 98.33 199 | 98.61 238 | 98.30 185 | 99.48 284 | 99.45 96 | 96.98 160 | 98.87 195 | 99.88 181 | 81.57 317 | 98.93 227 | 99.22 146 | 87.82 306 | 97.76 216 |
|
TinyColmap | | | 95.50 265 | 95.12 265 | 96.64 285 | 98.69 235 | 93.00 306 | 99.40 289 | 97.75 333 | 96.40 196 | 96.14 286 | 99.87 182 | 79.47 326 | 99.50 197 | 93.62 280 | 94.72 238 | 97.40 301 |
|
LF4IMVS | | | 96.19 243 | 96.18 220 | 96.23 293 | 98.26 253 | 92.09 313 | 100.00 1 | 97.89 331 | 97.82 100 | 97.94 248 | 99.87 182 | 82.71 312 | 99.38 207 | 97.41 220 | 93.71 244 | 97.20 307 |
|
testgi | | | 96.18 244 | 95.93 235 | 96.93 269 | 98.98 222 | 94.20 297 | 100.00 1 | 99.07 282 | 97.16 150 | 96.06 287 | 99.86 184 | 84.08 308 | 97.79 303 | 90.38 304 | 97.80 183 | 98.81 205 |
|
MVS_Test | | | 98.93 128 | 98.65 137 | 99.77 107 | 99.62 145 | 99.50 109 | 99.99 174 | 99.19 243 | 95.52 222 | 99.96 87 | 99.86 184 | 96.54 162 | 99.98 93 | 98.65 170 | 98.48 138 | 99.82 167 |
|
test_djsdf | | | 97.55 184 | 97.38 184 | 98.07 224 | 97.50 299 | 97.99 212 | 100.00 1 | 99.13 261 | 95.46 227 | 98.47 225 | 99.85 186 | 92.01 219 | 98.59 266 | 98.63 172 | 95.36 218 | 97.62 288 |
|
HY-MVS | | 96.53 9 | 99.50 63 | 99.35 69 | 99.96 35 | 99.81 99 | 99.93 32 | 99.64 271 | 100.00 1 | 97.97 86 | 99.84 122 | 99.85 186 | 98.94 93 | 99.99 80 | 99.86 80 | 98.23 158 | 99.95 110 |
|
TDRefinement | | | 91.93 296 | 90.48 301 | 96.27 292 | 81.60 344 | 92.65 310 | 99.10 320 | 97.61 336 | 93.96 255 | 93.77 303 | 99.85 186 | 80.03 324 | 99.53 193 | 97.82 207 | 70.59 341 | 96.63 313 |
|
XXY-MVS | | | 97.14 197 | 96.63 203 | 98.67 183 | 98.65 236 | 98.92 156 | 99.54 279 | 99.29 209 | 95.57 219 | 97.63 258 | 99.83 189 | 87.79 281 | 99.35 210 | 98.39 181 | 92.95 253 | 97.75 220 |
|
CDS-MVSNet | | | 98.96 125 | 98.95 108 | 99.01 165 | 99.48 178 | 98.36 179 | 99.93 211 | 99.37 174 | 96.79 170 | 99.31 171 | 99.83 189 | 99.77 13 | 98.91 229 | 98.07 199 | 97.98 169 | 99.77 177 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
DeepMVS_CX | | | | | 89.98 316 | 98.90 227 | 71.46 342 | | 99.18 247 | 97.61 123 | 96.92 275 | 99.83 189 | 86.07 294 | 99.83 148 | 96.02 242 | 97.65 199 | 98.65 208 |
|
FIs | | | 97.95 174 | 97.73 178 | 98.62 185 | 98.53 242 | 99.24 135 | 100.00 1 | 99.43 114 | 96.74 172 | 97.87 251 | 99.82 192 | 95.27 181 | 98.89 232 | 98.78 163 | 93.07 251 | 97.74 242 |
|
FC-MVSNet-test | | | 97.84 175 | 97.63 180 | 98.45 190 | 98.30 251 | 99.05 146 | 100.00 1 | 99.43 114 | 96.63 183 | 97.61 260 | 99.82 192 | 95.19 183 | 98.57 269 | 98.64 171 | 93.05 252 | 97.73 252 |
|
mvs_anonymous | | | 98.80 136 | 98.60 142 | 99.38 142 | 99.57 158 | 99.24 135 | 100.00 1 | 99.21 240 | 95.87 208 | 98.92 191 | 99.82 192 | 96.39 165 | 99.03 220 | 99.13 149 | 98.50 136 | 99.88 151 |
|
ab-mvs | | | 98.42 158 | 98.02 169 | 99.61 116 | 99.71 128 | 99.00 152 | 99.10 320 | 99.64 71 | 96.70 176 | 99.04 187 | 99.81 195 | 90.64 246 | 99.98 93 | 99.64 109 | 97.93 171 | 99.84 161 |
|
TAMVS | | | 98.76 137 | 98.73 130 | 98.86 175 | 99.44 181 | 97.69 227 | 99.57 276 | 99.34 193 | 96.57 185 | 99.12 181 | 99.81 195 | 98.83 100 | 99.16 215 | 97.97 204 | 97.91 172 | 99.73 188 |
|
PatchMatch-RL | | | 99.02 117 | 98.78 126 | 99.74 108 | 99.99 45 | 99.29 128 | 100.00 1 | 100.00 1 | 98.38 55 | 99.89 119 | 99.81 195 | 93.14 206 | 99.99 80 | 97.85 206 | 99.98 94 | 99.95 110 |
|
MVSTER | | | 98.58 147 | 98.52 147 | 98.77 180 | 99.65 138 | 99.68 100 | 100.00 1 | 99.29 209 | 95.63 216 | 98.65 210 | 99.80 198 | 99.78 6 | 98.88 235 | 98.59 175 | 95.31 220 | 97.73 252 |
|
EU-MVSNet | | | 96.63 222 | 96.53 206 | 96.94 268 | 97.59 295 | 96.87 254 | 99.76 247 | 99.47 82 | 96.35 198 | 96.85 279 | 99.78 199 | 92.57 212 | 96.27 323 | 95.33 254 | 91.08 270 | 97.68 272 |
|
PVSNet_0 | | 93.57 19 | 96.41 231 | 95.74 243 | 98.41 192 | 99.84 97 | 95.22 270 | 100.00 1 | 100.00 1 | 98.08 76 | 97.55 262 | 99.78 199 | 84.40 303 | 100.00 1 | 100.00 1 | 81.99 321 | 100.00 1 |
|
diffmvs | | | 98.52 153 | 98.11 163 | 99.73 110 | 99.59 152 | 99.47 117 | 100.00 1 | 99.19 243 | 93.68 267 | 99.70 150 | 99.75 201 | 95.07 184 | 99.84 146 | 97.57 213 | 98.48 138 | 99.89 139 |
|
K. test v3 | | | 95.46 267 | 95.14 264 | 96.40 289 | 97.53 298 | 93.40 303 | 99.99 174 | 99.23 234 | 95.49 225 | 92.70 308 | 99.73 202 | 84.26 304 | 98.12 288 | 93.94 278 | 93.38 249 | 97.68 272 |
|
semantic-postprocess | | | | | 97.62 243 | 99.40 187 | 96.83 255 | | 99.14 256 | 94.65 240 | 97.55 262 | 99.72 203 | 89.64 263 | 98.31 282 | 95.62 251 | 92.05 260 | 97.73 252 |
|
pm-mvs1 | | | 95.76 261 | 95.01 267 | 98.00 230 | 98.23 255 | 97.45 232 | 99.24 301 | 99.04 295 | 93.13 283 | 95.93 289 | 99.72 203 | 86.28 293 | 98.84 238 | 95.62 251 | 87.92 305 | 97.72 257 |
|
tfpnnormal | | | 96.36 235 | 95.69 247 | 98.37 195 | 98.55 240 | 98.71 163 | 99.69 264 | 99.45 96 | 93.16 282 | 96.69 282 | 99.71 205 | 88.44 278 | 98.99 224 | 94.17 272 | 91.38 267 | 97.41 300 |
|
pmmvs4 | | | 97.17 194 | 96.80 197 | 98.27 204 | 97.68 290 | 98.64 167 | 100.00 1 | 99.18 247 | 94.22 251 | 98.55 218 | 99.71 205 | 93.67 198 | 98.47 276 | 95.66 249 | 92.57 256 | 97.71 264 |
|
TransMVSNet (Re) | | | 94.78 271 | 93.72 274 | 97.93 236 | 98.34 247 | 97.88 220 | 99.23 307 | 97.98 329 | 91.60 294 | 94.55 297 | 99.71 205 | 87.89 279 | 98.36 280 | 89.30 315 | 84.92 317 | 97.56 294 |
|
ADS-MVSNet2 | | | 98.28 164 | 98.51 148 | 97.62 243 | 99.51 172 | 95.03 273 | 99.24 301 | 99.41 151 | 95.52 222 | 99.96 87 | 99.70 208 | 97.57 131 | 97.94 301 | 97.11 226 | 98.54 134 | 99.88 151 |
|
ADS-MVSNet | | | 98.70 142 | 98.51 148 | 99.28 150 | 99.51 172 | 98.39 175 | 99.24 301 | 99.44 105 | 95.52 222 | 99.96 87 | 99.70 208 | 97.57 131 | 99.58 176 | 97.11 226 | 98.54 134 | 99.88 151 |
|
Patchmatch-test1 | | | 98.23 167 | 97.91 172 | 99.17 157 | 99.41 183 | 98.25 192 | 99.99 174 | 99.45 96 | 96.91 167 | 99.76 139 | 99.69 210 | 89.65 262 | 99.37 208 | 97.55 214 | 98.79 130 | 99.89 139 |
|
jajsoiax | | | 97.07 200 | 96.79 199 | 97.89 238 | 97.28 308 | 97.12 247 | 99.95 205 | 99.19 243 | 96.55 186 | 97.31 267 | 99.69 210 | 87.35 286 | 98.91 229 | 98.70 167 | 95.12 231 | 97.66 278 |
|
mvs_tets | | | 97.00 205 | 96.69 201 | 97.94 234 | 97.41 307 | 97.27 242 | 99.60 274 | 99.18 247 | 96.51 190 | 97.35 266 | 99.69 210 | 86.53 292 | 98.91 229 | 98.84 160 | 95.09 232 | 97.65 282 |
|
test123 | | | 79.44 316 | 79.23 318 | 80.05 331 | 80.03 346 | 71.72 340 | 100.00 1 | 77.93 358 | 62.52 343 | 94.81 295 | 99.69 210 | 78.21 330 | 74.53 353 | 92.57 288 | 27.33 353 | 93.90 334 |
|
IB-MVS | | 96.24 12 | 97.54 185 | 96.95 192 | 99.33 146 | 99.67 134 | 98.10 206 | 100.00 1 | 99.47 82 | 97.42 136 | 99.26 173 | 99.69 210 | 98.83 100 | 99.89 137 | 99.43 127 | 78.77 329 | 100.00 1 |
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 |
GG-mvs-BLEND | | | | | 99.59 122 | 99.54 161 | 99.49 112 | 99.17 315 | 99.52 75 | | 99.96 87 | 99.68 215 | 100.00 1 | 99.33 211 | 99.71 100 | 99.99 87 | 99.96 105 |
|
WR-MVS | | | 97.09 198 | 96.64 202 | 98.46 189 | 98.43 244 | 99.09 143 | 99.97 196 | 99.33 195 | 95.62 217 | 97.76 253 | 99.67 216 | 91.17 237 | 98.56 270 | 98.49 178 | 89.28 293 | 97.74 242 |
|
tpm2 | | | 98.64 144 | 98.58 144 | 98.81 179 | 99.42 182 | 97.12 247 | 99.69 264 | 99.37 174 | 93.63 270 | 99.94 108 | 99.67 216 | 98.96 90 | 99.47 200 | 98.62 174 | 97.95 170 | 99.83 164 |
|
IterMVS | | | 96.76 213 | 96.46 210 | 97.63 241 | 99.41 183 | 96.89 253 | 99.99 174 | 99.13 261 | 94.74 238 | 97.59 261 | 99.66 218 | 89.63 264 | 98.28 283 | 95.71 247 | 92.31 258 | 97.72 257 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
PS-CasMVS | | | 96.34 237 | 95.78 241 | 98.03 229 | 98.18 258 | 98.27 188 | 99.71 258 | 99.32 198 | 94.75 236 | 96.82 280 | 99.65 219 | 86.98 289 | 98.15 286 | 97.74 208 | 88.85 298 | 97.66 278 |
|
DU-MVS | | | 96.93 207 | 96.49 208 | 98.22 211 | 98.31 249 | 98.41 173 | 100.00 1 | 99.37 174 | 96.41 195 | 97.76 253 | 99.65 219 | 92.14 215 | 98.50 273 | 97.98 201 | 86.84 310 | 97.75 220 |
|
CP-MVSNet | | | 96.73 214 | 96.25 219 | 98.18 214 | 98.21 256 | 98.67 166 | 99.77 244 | 99.32 198 | 95.06 232 | 97.20 271 | 99.65 219 | 90.10 254 | 98.19 284 | 98.06 200 | 88.90 297 | 97.66 278 |
|
NR-MVSNet | | | 96.63 222 | 96.04 230 | 98.38 194 | 98.31 249 | 98.98 153 | 99.22 309 | 99.35 188 | 95.87 208 | 94.43 299 | 99.65 219 | 92.73 210 | 98.40 279 | 96.78 237 | 88.05 304 | 97.75 220 |
|
GA-MVS | | | 97.72 178 | 97.27 187 | 99.06 160 | 99.24 199 | 97.93 217 | 100.00 1 | 99.24 231 | 95.80 213 | 98.99 189 | 99.64 223 | 89.77 260 | 99.36 209 | 95.12 259 | 97.62 200 | 99.89 139 |
|
UniMVSNet_NR-MVSNet | | | 97.16 195 | 96.80 197 | 98.22 211 | 98.38 246 | 98.41 173 | 100.00 1 | 99.45 96 | 96.14 204 | 97.76 253 | 99.64 223 | 95.05 185 | 98.50 273 | 97.98 201 | 86.84 310 | 97.75 220 |
|
TranMVSNet+NR-MVSNet | | | 96.45 230 | 96.01 231 | 97.79 240 | 98.00 280 | 97.62 230 | 100.00 1 | 99.35 188 | 95.98 206 | 97.31 267 | 99.64 223 | 90.09 255 | 98.00 300 | 96.89 232 | 86.80 313 | 97.75 220 |
|
tpmrst | | | 98.98 123 | 98.93 110 | 99.14 159 | 99.61 147 | 97.74 226 | 99.52 281 | 99.36 180 | 96.05 205 | 99.98 80 | 99.64 223 | 99.04 82 | 99.86 141 | 98.94 155 | 98.19 161 | 99.82 167 |
|
Fast-Effi-MVS+-dtu | | | 98.38 161 | 98.56 145 | 97.82 239 | 99.58 156 | 94.44 293 | 100.00 1 | 99.16 251 | 96.75 171 | 99.51 160 | 99.63 227 | 95.03 186 | 99.60 172 | 97.71 209 | 99.67 116 | 99.42 201 |
|
MDTV_nov1_ep13 | | | | 98.94 109 | | 99.53 164 | 98.36 179 | 99.39 290 | 99.46 94 | 96.54 187 | 99.99 75 | 99.63 227 | 98.92 95 | 99.86 141 | 98.30 186 | 98.71 132 | |
|
anonymousdsp | | | 97.16 195 | 96.88 194 | 98.00 230 | 97.08 310 | 98.06 209 | 99.81 235 | 99.15 252 | 94.58 241 | 97.84 252 | 99.62 229 | 90.49 249 | 98.60 264 | 97.98 201 | 95.32 219 | 97.33 305 |
|
pmmvs6 | | | 93.64 277 | 92.87 282 | 95.94 296 | 97.47 303 | 91.41 318 | 98.92 326 | 99.02 296 | 87.84 322 | 95.01 294 | 99.61 230 | 77.24 332 | 98.77 247 | 94.33 270 | 86.41 314 | 97.63 286 |
|
PS-MVSNAJss | | | 98.03 171 | 98.06 167 | 97.94 234 | 97.63 293 | 97.33 241 | 99.89 219 | 99.23 234 | 96.27 201 | 98.03 243 | 99.59 231 | 98.75 105 | 98.78 244 | 98.52 177 | 94.61 240 | 97.70 265 |
|
Patchmatch-test | | | 97.83 176 | 97.42 182 | 99.06 160 | 99.08 205 | 97.66 229 | 98.66 331 | 99.21 240 | 93.65 269 | 98.25 237 | 99.58 232 | 99.47 39 | 99.57 177 | 90.25 307 | 98.59 133 | 99.95 110 |
|
PatchmatchNet | | | 99.03 113 | 98.96 104 | 99.26 152 | 99.49 177 | 98.33 181 | 99.38 291 | 99.45 96 | 96.64 181 | 99.96 87 | 99.58 232 | 99.49 36 | 99.50 197 | 97.63 211 | 99.00 127 | 99.93 123 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
DTE-MVSNet | | | 95.52 264 | 94.99 268 | 97.08 262 | 97.49 301 | 96.45 261 | 100.00 1 | 99.25 228 | 93.82 259 | 96.17 285 | 99.57 234 | 87.81 280 | 97.18 307 | 94.57 265 | 86.26 315 | 97.62 288 |
|
PEN-MVS | | | 96.01 253 | 95.48 255 | 97.58 245 | 97.74 288 | 97.26 243 | 99.90 216 | 99.29 209 | 94.55 242 | 96.79 281 | 99.55 235 | 87.38 284 | 97.84 302 | 96.92 231 | 87.24 308 | 97.65 282 |
|
CMPMVS | | 66.12 22 | 90.65 303 | 92.04 290 | 86.46 323 | 96.18 315 | 66.87 345 | 98.03 337 | 99.38 171 | 83.38 333 | 85.49 332 | 99.55 235 | 77.59 331 | 98.80 243 | 94.44 267 | 94.31 242 | 93.72 336 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
IterMVS-LS | | | 97.56 183 | 97.44 181 | 97.92 237 | 99.38 191 | 97.90 218 | 99.89 219 | 99.10 269 | 94.41 246 | 98.32 231 | 99.54 237 | 97.21 136 | 98.11 290 | 97.50 217 | 91.62 264 | 97.75 220 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
dp | | | 98.72 139 | 98.61 141 | 99.03 164 | 99.53 164 | 97.39 235 | 99.45 285 | 99.39 167 | 95.62 217 | 99.94 108 | 99.52 238 | 98.83 100 | 99.82 150 | 96.77 238 | 98.42 143 | 99.89 139 |
|
LTVRE_ROB | | 95.29 16 | 96.32 238 | 96.10 227 | 96.99 266 | 98.55 240 | 93.88 298 | 99.45 285 | 99.28 217 | 94.50 244 | 96.46 284 | 99.52 238 | 84.86 301 | 99.48 199 | 97.26 223 | 95.03 233 | 97.59 292 |
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 |
tpmp4_e23 | | | 98.71 140 | 98.66 134 | 98.84 176 | 99.60 149 | 96.98 252 | 99.83 228 | 99.35 188 | 94.29 249 | 99.90 116 | 99.50 240 | 99.17 74 | 99.73 160 | 98.22 188 | 98.13 163 | 99.81 169 |
|
v7n | | | 96.06 252 | 95.42 257 | 97.99 232 | 97.58 296 | 97.35 238 | 99.86 225 | 99.11 268 | 92.81 285 | 97.91 250 | 99.49 241 | 90.99 244 | 98.92 228 | 92.51 289 | 88.49 302 | 97.70 265 |
|
test_0402 | | | 94.35 273 | 93.70 275 | 96.32 291 | 97.92 283 | 93.60 300 | 99.61 273 | 98.85 304 | 88.19 321 | 94.68 296 | 99.48 242 | 80.01 325 | 98.58 268 | 89.39 313 | 95.15 229 | 96.77 311 |
|
Baseline_NR-MVSNet | | | 96.16 246 | 95.70 245 | 97.56 246 | 98.28 252 | 96.79 256 | 100.00 1 | 97.86 332 | 91.93 292 | 97.63 258 | 99.47 243 | 92.14 215 | 98.35 281 | 97.13 225 | 86.83 312 | 97.54 295 |
|
pmmvs5 | | | 95.94 255 | 95.61 248 | 96.95 267 | 97.42 305 | 94.66 287 | 100.00 1 | 98.08 325 | 93.60 272 | 97.05 273 | 99.43 244 | 87.02 287 | 98.46 277 | 95.76 244 | 92.12 259 | 97.72 257 |
|
v148 | | | 96.29 239 | 95.84 237 | 97.63 241 | 97.74 288 | 96.53 260 | 100.00 1 | 99.07 282 | 93.52 273 | 98.01 246 | 99.42 245 | 91.22 235 | 98.60 264 | 96.37 241 | 87.22 309 | 97.75 220 |
|
CostFormer | | | 98.84 133 | 98.77 127 | 99.04 163 | 99.41 183 | 97.58 231 | 99.67 267 | 99.35 188 | 94.66 239 | 99.96 87 | 99.36 246 | 99.28 64 | 99.74 159 | 99.41 133 | 97.81 182 | 99.81 169 |
|
tpm | | | 98.24 166 | 98.22 161 | 98.32 200 | 99.13 201 | 95.79 267 | 99.53 280 | 99.12 267 | 95.20 230 | 99.96 87 | 99.36 246 | 97.58 130 | 99.28 213 | 97.41 220 | 96.67 209 | 99.88 151 |
|
EPMVS | | | 99.25 94 | 99.13 92 | 99.60 119 | 99.60 149 | 99.20 138 | 99.60 274 | 100.00 1 | 96.93 166 | 99.92 114 | 99.36 246 | 99.05 81 | 99.71 163 | 98.77 164 | 98.94 128 | 99.90 134 |
|
v7 | | | 96.64 221 | 96.14 224 | 98.13 220 | 98.18 258 | 97.97 214 | 99.99 174 | 99.09 272 | 93.62 271 | 98.76 202 | 99.30 249 | 91.13 239 | 98.70 256 | 94.37 269 | 90.80 273 | 97.74 242 |
|
XVG-ACMP-BASELINE | | | 96.60 224 | 96.52 207 | 96.84 279 | 98.41 245 | 93.29 304 | 99.99 174 | 99.32 198 | 97.76 105 | 98.51 223 | 99.29 250 | 81.95 315 | 99.54 189 | 98.40 180 | 95.03 233 | 97.68 272 |
|
tpmvs | | | 98.59 146 | 98.38 153 | 99.23 154 | 99.69 130 | 97.90 218 | 99.31 296 | 99.47 82 | 94.52 243 | 99.68 151 | 99.28 251 | 97.64 129 | 99.89 137 | 97.71 209 | 98.17 162 | 99.89 139 |
|
v1921920 | | | 96.16 246 | 95.50 251 | 98.14 217 | 97.88 286 | 97.96 215 | 99.99 174 | 99.07 282 | 93.33 278 | 98.60 214 | 99.24 252 | 89.37 266 | 98.71 255 | 91.28 295 | 90.74 275 | 97.75 220 |
|
testpf | | | 97.02 204 | 96.87 195 | 97.44 251 | 99.50 175 | 95.18 271 | 95.70 343 | 99.33 195 | 91.35 296 | 98.00 247 | 99.22 253 | 96.29 166 | 98.49 275 | 94.42 268 | 98.07 167 | 98.67 207 |
|
v748 | | | 95.47 266 | 94.95 269 | 97.04 263 | 97.46 304 | 94.76 285 | 99.93 211 | 99.10 269 | 91.95 291 | 97.11 272 | 99.18 254 | 89.94 259 | 98.68 257 | 94.01 276 | 85.88 316 | 97.67 276 |
|
test-LLR | | | 99.03 113 | 98.91 115 | 99.40 139 | 99.40 187 | 99.28 129 | 100.00 1 | 99.45 96 | 96.70 176 | 99.42 165 | 99.12 255 | 99.31 54 | 99.01 222 | 96.82 234 | 99.99 87 | 99.91 126 |
|
test-mter | | | 98.96 125 | 98.82 122 | 99.40 139 | 99.40 187 | 99.28 129 | 100.00 1 | 99.45 96 | 95.44 229 | 99.42 165 | 99.12 255 | 99.70 17 | 99.01 222 | 96.82 234 | 99.99 87 | 99.91 126 |
|
v144192 | | | 96.40 233 | 95.81 238 | 98.17 215 | 97.89 285 | 98.11 205 | 99.99 174 | 99.06 290 | 93.39 276 | 98.75 203 | 99.09 257 | 90.43 251 | 98.66 260 | 93.10 285 | 90.55 277 | 97.75 220 |
|
v2v482 | | | 96.70 216 | 96.18 220 | 98.27 204 | 98.04 276 | 98.39 175 | 100.00 1 | 99.13 261 | 94.19 253 | 98.58 217 | 99.08 258 | 90.48 250 | 98.67 259 | 95.69 248 | 90.44 278 | 97.75 220 |
|
v6 | | | 96.77 209 | 96.26 218 | 98.29 202 | 98.10 267 | 98.27 188 | 100.00 1 | 99.09 272 | 93.95 256 | 98.73 205 | 99.06 259 | 91.51 229 | 98.86 237 | 95.83 243 | 90.04 280 | 97.74 242 |
|
Test_1112_low_res | | | 98.83 134 | 98.60 142 | 99.51 130 | 99.69 130 | 98.75 161 | 99.99 174 | 99.14 256 | 96.81 169 | 98.84 198 | 99.06 259 | 97.45 133 | 99.89 137 | 98.66 168 | 97.75 186 | 99.89 139 |
|
v1neww | | | 96.77 209 | 96.27 216 | 98.26 206 | 98.16 261 | 98.23 193 | 100.00 1 | 99.09 272 | 93.94 257 | 98.73 205 | 99.05 261 | 91.65 222 | 98.82 240 | 95.75 245 | 90.04 280 | 97.74 242 |
|
v7new | | | 96.77 209 | 96.27 216 | 98.26 206 | 98.16 261 | 98.23 193 | 100.00 1 | 99.09 272 | 93.94 257 | 98.73 205 | 99.05 261 | 91.65 222 | 98.82 240 | 95.75 245 | 90.04 280 | 97.74 242 |
|
V42 | | | 96.65 220 | 96.16 222 | 98.11 223 | 98.17 260 | 98.23 193 | 99.99 174 | 99.09 272 | 93.97 254 | 98.74 204 | 99.05 261 | 91.09 242 | 98.82 240 | 95.46 253 | 89.90 287 | 97.27 306 |
|
MVP-Stereo | | | 96.51 227 | 96.48 209 | 96.60 287 | 95.65 320 | 94.25 295 | 98.84 329 | 98.16 321 | 95.85 212 | 95.23 293 | 99.04 264 | 92.54 213 | 99.13 216 | 92.98 286 | 99.98 94 | 96.43 315 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
v1141 | | | 96.66 218 | 96.12 225 | 98.26 206 | 98.05 274 | 98.28 186 | 100.00 1 | 99.09 272 | 93.71 261 | 98.59 215 | 99.04 264 | 91.57 226 | 98.73 251 | 95.05 260 | 90.00 283 | 97.75 220 |
|
divwei89l23v2f112 | | | 96.68 217 | 96.15 223 | 98.25 210 | 98.03 277 | 98.27 188 | 100.00 1 | 99.09 272 | 93.79 260 | 98.59 215 | 99.04 264 | 91.54 228 | 98.73 251 | 95.29 258 | 89.99 284 | 97.75 220 |
|
v1 | | | 96.66 218 | 96.12 225 | 98.30 201 | 98.09 268 | 98.33 181 | 100.00 1 | 99.09 272 | 93.69 266 | 98.68 208 | 99.04 264 | 91.42 233 | 98.83 239 | 95.05 260 | 89.99 284 | 97.75 220 |
|
UGNet | | | 98.41 159 | 98.11 163 | 99.31 148 | 99.54 161 | 98.55 170 | 99.18 310 | 100.00 1 | 98.64 43 | 99.79 135 | 99.04 264 | 87.61 282 | 100.00 1 | 99.30 141 | 99.89 106 | 99.40 202 |
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 |
LP | | | 95.89 258 | 95.35 259 | 97.51 247 | 98.92 226 | 95.15 272 | 98.66 331 | 99.39 167 | 89.43 315 | 97.22 270 | 99.03 269 | 94.37 193 | 97.74 304 | 83.71 325 | 97.44 201 | 99.63 196 |
|
PVSNet_BlendedMVS | | | 98.71 140 | 98.62 140 | 98.98 168 | 99.98 71 | 99.60 105 | 100.00 1 | 100.00 1 | 97.23 145 | 100.00 1 | 99.03 269 | 96.57 160 | 99.99 80 | 100.00 1 | 94.75 236 | 97.35 303 |
|
v52 | | | 95.88 260 | 95.35 259 | 97.48 249 | 97.66 291 | 97.38 237 | 99.88 222 | 99.07 282 | 92.19 288 | 98.09 239 | 99.02 271 | 90.06 256 | 98.72 253 | 93.58 281 | 88.61 301 | 96.34 316 |
|
MS-PatchMatch | | | 95.66 263 | 95.87 236 | 95.05 299 | 97.80 287 | 89.25 321 | 98.88 328 | 99.30 205 | 96.35 198 | 96.86 278 | 99.01 272 | 81.35 320 | 99.43 203 | 93.30 284 | 99.98 94 | 96.46 314 |
|
V4 | | | 95.89 258 | 95.36 258 | 97.49 248 | 97.65 292 | 97.40 234 | 99.88 222 | 99.07 282 | 92.19 288 | 98.08 240 | 99.01 272 | 90.20 253 | 98.72 253 | 93.57 282 | 88.63 300 | 96.34 316 |
|
v8 | | | 96.35 236 | 95.73 244 | 98.21 213 | 98.11 266 | 98.23 193 | 99.94 209 | 99.07 282 | 92.66 286 | 98.29 233 | 99.00 274 | 91.46 231 | 98.77 247 | 94.17 272 | 88.83 299 | 97.62 288 |
|
v1144 | | | 96.51 227 | 95.97 234 | 98.13 220 | 97.98 281 | 98.04 211 | 99.99 174 | 99.08 280 | 93.51 274 | 98.62 213 | 98.98 275 | 90.98 245 | 98.62 261 | 93.79 279 | 90.79 274 | 97.74 242 |
|
CR-MVSNet | | | 98.02 172 | 97.71 179 | 98.93 170 | 99.31 194 | 98.86 158 | 99.13 318 | 99.00 297 | 96.53 188 | 99.96 87 | 98.98 275 | 96.94 153 | 98.10 293 | 91.18 296 | 98.40 144 | 99.84 161 |
|
Patchmtry | | | 96.81 208 | 96.37 212 | 98.14 217 | 99.31 194 | 98.55 170 | 98.91 327 | 99.00 297 | 90.45 301 | 97.92 249 | 98.98 275 | 96.94 153 | 98.12 288 | 94.27 271 | 91.53 265 | 97.75 220 |
|
v1192 | | | 96.18 244 | 95.49 253 | 98.26 206 | 98.01 278 | 98.15 203 | 99.99 174 | 99.08 280 | 93.36 277 | 98.54 219 | 98.97 278 | 89.47 265 | 98.89 232 | 91.15 297 | 90.82 272 | 97.75 220 |
|
v1240 | | | 95.96 254 | 95.25 261 | 98.07 224 | 97.91 284 | 97.87 222 | 99.96 199 | 99.07 282 | 93.24 280 | 98.64 212 | 98.96 279 | 88.98 271 | 98.61 262 | 89.58 310 | 90.92 271 | 97.75 220 |
|
v10 | | | 96.14 248 | 95.50 251 | 98.07 224 | 98.19 257 | 97.96 215 | 99.83 228 | 99.07 282 | 92.10 290 | 98.07 242 | 98.94 280 | 91.07 243 | 98.61 262 | 92.41 292 | 89.82 288 | 97.63 286 |
|
VPA-MVSNet | | | 97.03 203 | 96.43 211 | 98.82 177 | 98.64 237 | 99.32 126 | 99.38 291 | 99.47 82 | 96.73 174 | 98.91 193 | 98.94 280 | 87.00 288 | 99.40 206 | 99.23 144 | 89.59 290 | 97.76 216 |
|
FMVSNet3 | | | 97.30 190 | 96.95 192 | 98.37 195 | 99.65 138 | 99.25 133 | 99.71 258 | 99.28 217 | 94.23 250 | 98.53 220 | 98.91 282 | 93.30 203 | 98.11 290 | 95.31 255 | 93.60 245 | 97.73 252 |
|
UniMVSNet (Re) | | | 97.29 191 | 96.85 196 | 98.59 188 | 98.49 243 | 99.13 142 | 100.00 1 | 99.42 120 | 96.52 189 | 98.24 238 | 98.90 283 | 94.93 187 | 98.89 232 | 97.54 216 | 87.61 307 | 97.75 220 |
|
test20.03 | | | 93.11 289 | 92.85 283 | 93.88 311 | 95.19 323 | 91.83 314 | 100.00 1 | 98.87 303 | 93.68 267 | 92.76 306 | 98.88 284 | 89.20 268 | 92.71 337 | 77.88 336 | 89.19 294 | 97.09 309 |
|
FMVSNet2 | | | 96.22 242 | 95.60 249 | 98.06 227 | 99.53 164 | 98.33 181 | 99.45 285 | 99.27 224 | 93.71 261 | 98.03 243 | 98.84 285 | 84.23 305 | 98.10 293 | 93.97 277 | 93.40 248 | 97.73 252 |
|
GBi-Net | | | 96.07 250 | 95.80 239 | 96.89 271 | 99.53 164 | 94.87 274 | 99.18 310 | 99.27 224 | 93.71 261 | 98.53 220 | 98.81 286 | 84.23 305 | 98.07 296 | 95.31 255 | 93.60 245 | 97.72 257 |
|
test1 | | | 96.07 250 | 95.80 239 | 96.89 271 | 99.53 164 | 94.87 274 | 99.18 310 | 99.27 224 | 93.71 261 | 98.53 220 | 98.81 286 | 84.23 305 | 98.07 296 | 95.31 255 | 93.60 245 | 97.72 257 |
|
FMVSNet1 | | | 94.45 272 | 93.63 276 | 96.89 271 | 98.87 231 | 94.87 274 | 99.18 310 | 99.27 224 | 90.95 300 | 97.31 267 | 98.81 286 | 72.89 337 | 98.07 296 | 92.61 287 | 92.81 254 | 97.72 257 |
|
Effi-MVS+-dtu | | | 98.51 155 | 98.86 120 | 97.47 250 | 99.77 122 | 94.21 296 | 100.00 1 | 98.94 299 | 97.61 123 | 99.91 115 | 98.75 289 | 95.89 169 | 99.51 196 | 99.36 135 | 99.48 120 | 98.68 206 |
|
test2356 | | | 92.55 293 | 93.94 271 | 88.39 319 | 93.49 327 | 78.42 333 | 100.00 1 | 99.40 153 | 91.64 293 | 93.93 301 | 98.74 290 | 91.11 240 | 88.67 342 | 79.37 333 | 97.79 184 | 98.08 212 |
|
tpm cat1 | | | 98.05 170 | 97.76 175 | 98.92 172 | 99.50 175 | 97.10 249 | 99.77 244 | 99.30 205 | 90.20 304 | 99.72 142 | 98.71 291 | 97.71 127 | 99.86 141 | 96.75 239 | 98.20 160 | 99.81 169 |
|
testus | | | 91.61 301 | 92.92 281 | 87.70 320 | 93.91 326 | 74.98 337 | 100.00 1 | 98.19 320 | 92.59 287 | 93.90 302 | 98.68 292 | 81.43 318 | 90.77 340 | 79.82 332 | 97.71 192 | 97.34 304 |
|
WR-MVS_H | | | 96.73 214 | 96.32 215 | 97.95 233 | 98.26 253 | 97.88 220 | 99.72 256 | 99.43 114 | 95.06 232 | 96.99 274 | 98.68 292 | 93.02 207 | 98.53 271 | 97.43 219 | 88.33 303 | 97.43 299 |
|
EG-PatchMatch MVS | | | 92.94 290 | 92.49 285 | 94.29 307 | 95.87 319 | 87.07 325 | 99.07 324 | 98.11 324 | 93.19 281 | 88.98 316 | 98.66 294 | 70.89 339 | 99.08 218 | 92.43 291 | 95.21 226 | 96.72 312 |
|
UnsupCasMVSNet_eth | | | 94.25 274 | 93.89 272 | 95.34 297 | 97.63 293 | 92.13 312 | 99.73 254 | 99.36 180 | 94.88 235 | 92.78 305 | 98.63 295 | 82.72 311 | 96.53 313 | 94.57 265 | 84.73 318 | 97.36 302 |
|
Anonymous20231206 | | | 93.45 282 | 93.17 280 | 94.30 306 | 95.00 324 | 89.69 320 | 99.98 190 | 98.43 316 | 93.30 279 | 94.50 298 | 98.59 296 | 90.52 248 | 95.73 328 | 77.46 338 | 90.73 276 | 97.48 298 |
|
N_pmnet | | | 91.88 298 | 93.37 279 | 87.40 321 | 97.24 309 | 66.33 346 | 99.90 216 | 91.05 351 | 89.77 310 | 95.65 291 | 98.58 297 | 90.05 257 | 98.11 290 | 85.39 322 | 92.72 255 | 97.75 220 |
|
MIMVSNet | | | 97.06 201 | 96.73 200 | 98.05 228 | 99.38 191 | 96.64 259 | 98.47 334 | 99.35 188 | 93.41 275 | 99.48 162 | 98.53 298 | 89.66 261 | 97.70 305 | 94.16 274 | 98.11 165 | 99.80 176 |
|
LCM-MVSNet-Re | | | 96.52 226 | 97.21 189 | 94.44 304 | 99.27 197 | 85.80 326 | 99.85 226 | 96.61 344 | 95.98 206 | 92.75 307 | 98.48 299 | 93.97 196 | 97.55 306 | 99.58 116 | 98.43 142 | 99.98 90 |
|
FMVSNet5 | | | 95.32 268 | 95.43 256 | 94.99 300 | 99.39 190 | 92.99 307 | 99.25 300 | 99.24 231 | 90.45 301 | 97.44 265 | 98.45 300 | 95.78 172 | 94.39 332 | 87.02 319 | 91.88 262 | 97.59 292 |
|
MIMVSNet1 | | | 91.96 295 | 91.20 296 | 94.23 308 | 94.94 325 | 91.69 316 | 99.34 294 | 99.22 236 | 88.23 319 | 94.18 300 | 98.45 300 | 75.52 335 | 93.41 336 | 79.37 333 | 91.49 266 | 97.60 291 |
|
YYNet1 | | | 92.44 294 | 90.92 299 | 97.03 264 | 96.20 314 | 97.06 250 | 99.99 174 | 99.14 256 | 88.21 320 | 67.93 344 | 98.43 302 | 88.63 273 | 96.28 322 | 90.64 299 | 89.08 296 | 97.74 242 |
|
DI_MVS_plusplus_test | | | 96.28 240 | 95.16 263 | 99.61 116 | 96.01 317 | 99.18 140 | 100.00 1 | 99.29 209 | 96.49 191 | 89.08 314 | 98.42 303 | 80.06 322 | 99.90 135 | 98.74 166 | 98.39 146 | 99.75 180 |
|
test_normal | | | 96.24 241 | 95.12 265 | 99.60 119 | 96.00 318 | 99.16 141 | 100.00 1 | 99.29 209 | 96.43 192 | 88.96 317 | 98.40 304 | 80.06 322 | 99.90 135 | 98.53 176 | 98.39 146 | 99.75 180 |
|
MDA-MVSNet-bldmvs | | | 91.65 300 | 89.94 303 | 96.79 283 | 96.72 311 | 96.70 258 | 99.42 288 | 98.94 299 | 88.89 317 | 66.97 347 | 98.37 305 | 81.43 318 | 95.91 326 | 89.24 316 | 89.46 292 | 97.75 220 |
|
FPMVS | | | 77.92 319 | 79.45 317 | 73.34 337 | 76.87 349 | 46.81 356 | 98.24 335 | 99.05 292 | 59.89 346 | 73.55 341 | 98.34 306 | 36.81 352 | 86.55 344 | 80.96 329 | 91.35 268 | 86.65 346 |
|
MDA-MVSNet_test_wron | | | 92.61 292 | 91.09 298 | 97.19 261 | 96.71 312 | 97.26 243 | 100.00 1 | 99.14 256 | 88.61 318 | 67.90 345 | 98.32 307 | 89.03 269 | 96.57 309 | 90.47 303 | 89.59 290 | 97.74 242 |
|
new_pmnet | | | 94.11 276 | 93.47 278 | 96.04 295 | 96.60 313 | 92.82 308 | 99.97 196 | 98.91 302 | 90.21 303 | 95.26 292 | 98.05 308 | 85.89 297 | 98.14 287 | 84.28 324 | 92.01 261 | 97.16 308 |
|
patchmatchnet-post | | | | | | | | | | | | 97.79 309 | 99.41 46 | 99.54 189 | | | |
|
Patchmatch-RL test | | | 93.49 280 | 93.63 276 | 93.05 312 | 91.78 329 | 83.41 329 | 98.21 336 | 96.95 340 | 91.58 295 | 91.05 310 | 97.64 310 | 99.40 47 | 95.83 327 | 94.11 275 | 81.95 322 | 99.91 126 |
|
DSMNet-mixed | | | 95.18 269 | 95.21 262 | 95.08 298 | 96.03 316 | 90.21 319 | 99.65 270 | 93.64 349 | 92.91 284 | 98.34 230 | 97.40 311 | 90.05 257 | 95.51 330 | 91.02 298 | 97.86 176 | 99.51 200 |
|
OpenMVS_ROB | | 88.34 20 | 91.89 297 | 91.12 297 | 94.19 309 | 95.55 321 | 87.63 324 | 99.26 299 | 98.03 326 | 86.61 324 | 90.65 313 | 96.82 312 | 70.14 340 | 98.78 244 | 86.54 321 | 96.50 210 | 96.15 318 |
|
pmmvs3 | | | 90.62 304 | 89.36 305 | 94.40 305 | 90.53 333 | 91.49 317 | 100.00 1 | 96.73 342 | 84.21 331 | 93.65 304 | 96.65 313 | 82.56 314 | 94.83 331 | 82.28 327 | 77.62 333 | 96.89 310 |
|
test12356 | | | 86.30 310 | 87.15 311 | 83.77 329 | 84.24 341 | 72.00 339 | 99.94 209 | 96.80 341 | 84.63 330 | 85.16 333 | 96.51 314 | 77.02 333 | 86.31 346 | 70.06 342 | 89.93 286 | 93.00 338 |
|
test1235678 | | | 88.02 309 | 88.73 307 | 85.90 325 | 87.57 338 | 71.70 341 | 100.00 1 | 97.42 337 | 87.52 323 | 86.19 330 | 96.39 315 | 81.60 316 | 87.93 343 | 70.72 341 | 91.18 269 | 98.08 212 |
|
Test4 | | | 92.63 291 | 90.45 302 | 99.17 157 | 92.81 328 | 99.02 148 | 99.98 190 | 99.13 261 | 96.60 184 | 82.04 337 | 96.27 316 | 51.35 346 | 98.75 250 | 97.55 214 | 98.36 150 | 99.75 180 |
|
1111 | | | 88.62 307 | 89.13 306 | 87.08 322 | 87.71 336 | 77.22 334 | 99.96 199 | 97.71 334 | 85.51 326 | 83.47 335 | 96.26 317 | 95.76 173 | 90.96 338 | 66.63 344 | 89.17 295 | 93.07 337 |
|
.test1245 | | | 85.18 311 | 84.81 312 | 86.28 324 | 87.71 336 | 77.22 334 | 99.96 199 | 97.71 334 | 85.51 326 | 83.47 335 | 96.26 317 | 95.76 173 | 90.96 338 | 66.63 344 | 50.30 345 | 90.64 341 |
|
PM-MVS | | | 88.39 308 | 87.41 310 | 91.31 314 | 91.73 330 | 82.02 331 | 99.79 239 | 96.62 343 | 91.06 299 | 90.71 312 | 95.73 319 | 48.60 348 | 95.96 325 | 90.56 301 | 81.91 323 | 95.97 321 |
|
v17 | | | 93.53 279 | 92.42 286 | 96.88 275 | 98.09 268 | 98.16 201 | 99.83 228 | 98.74 306 | 89.95 307 | 89.05 315 | 95.65 320 | 91.99 220 | 96.54 310 | 90.31 305 | 78.15 332 | 95.95 322 |
|
v18 | | | 93.55 278 | 92.42 286 | 96.91 270 | 98.12 264 | 98.26 191 | 99.83 228 | 98.74 306 | 89.99 306 | 88.94 318 | 95.64 321 | 92.02 218 | 96.54 310 | 90.27 306 | 78.26 330 | 95.94 324 |
|
v16 | | | 93.48 281 | 92.34 288 | 96.89 271 | 98.13 263 | 98.19 199 | 99.82 233 | 98.74 306 | 89.94 308 | 88.90 319 | 95.62 322 | 91.65 222 | 96.54 310 | 90.03 308 | 78.22 331 | 95.95 322 |
|
V14 | | | 93.24 284 | 92.04 290 | 96.87 276 | 98.07 272 | 98.20 198 | 99.80 238 | 98.74 306 | 89.76 311 | 88.64 322 | 95.53 323 | 91.47 230 | 96.47 314 | 89.49 311 | 76.84 335 | 95.92 326 |
|
pmmvs-eth3d | | | 91.73 299 | 90.67 300 | 94.92 302 | 91.63 331 | 92.71 309 | 99.90 216 | 98.54 315 | 91.19 298 | 88.08 326 | 95.50 324 | 79.31 328 | 96.13 324 | 90.55 302 | 81.32 324 | 95.91 329 |
|
v11 | | | 93.14 288 | 91.93 295 | 96.77 284 | 98.01 278 | 98.17 200 | 99.72 256 | 98.74 306 | 89.39 316 | 88.81 320 | 95.49 325 | 91.15 238 | 96.29 321 | 86.78 320 | 79.25 327 | 95.86 331 |
|
Anonymous20231211 | | | 84.35 313 | 82.41 314 | 90.15 315 | 89.14 334 | 78.88 332 | 98.71 330 | 98.22 319 | 70.20 341 | 86.88 329 | 95.44 326 | 47.11 350 | 95.72 329 | 81.14 328 | 74.88 339 | 95.84 332 |
|
v15 | | | 93.28 283 | 92.08 289 | 96.87 276 | 98.07 272 | 98.22 197 | 99.82 233 | 98.74 306 | 89.83 309 | 88.74 321 | 95.44 326 | 91.55 227 | 96.47 314 | 89.70 309 | 76.87 334 | 95.93 325 |
|
V9 | | | 93.20 285 | 91.99 292 | 96.85 278 | 98.05 274 | 98.16 201 | 99.77 244 | 98.73 312 | 89.67 312 | 88.64 322 | 95.44 326 | 91.34 234 | 96.47 314 | 89.46 312 | 76.79 336 | 95.92 326 |
|
v12 | | | 93.18 286 | 91.97 293 | 96.80 282 | 98.09 268 | 98.10 206 | 99.76 247 | 98.73 312 | 89.61 313 | 88.45 325 | 95.41 329 | 91.63 225 | 96.39 319 | 89.32 314 | 76.76 338 | 95.91 329 |
|
v13 | | | 93.18 286 | 91.97 293 | 96.81 281 | 98.12 264 | 98.12 204 | 99.74 250 | 98.73 312 | 89.47 314 | 88.52 324 | 95.40 330 | 91.72 221 | 96.41 317 | 89.23 317 | 76.77 337 | 95.92 326 |
|
ambc | | | | | 88.45 317 | 86.84 339 | 70.76 343 | 97.79 340 | 98.02 328 | | 90.91 311 | 95.14 331 | 38.69 351 | 98.51 272 | 94.97 262 | 84.23 319 | 96.09 320 |
|
RPMNet | | | 95.10 270 | 93.82 273 | 98.93 170 | 99.31 194 | 98.86 158 | 99.13 318 | 99.38 171 | 79.82 337 | 99.96 87 | 95.13 332 | 95.69 176 | 98.10 293 | 77.54 337 | 98.40 144 | 99.84 161 |
|
new-patchmatchnet | | | 90.30 305 | 89.46 304 | 92.84 313 | 90.77 332 | 88.55 323 | 99.83 228 | 98.80 305 | 90.07 305 | 87.86 327 | 95.00 333 | 78.77 329 | 94.30 333 | 84.86 323 | 79.15 328 | 95.68 333 |
|
PatchT | | | 95.90 256 | 94.95 269 | 98.75 181 | 99.03 212 | 98.39 175 | 99.08 322 | 99.32 198 | 85.52 325 | 99.96 87 | 94.99 334 | 97.94 123 | 98.05 299 | 80.20 331 | 98.47 140 | 99.81 169 |
|
UnsupCasMVSNet_bld | | | 89.50 306 | 88.00 309 | 93.99 310 | 95.30 322 | 88.86 322 | 98.52 333 | 99.28 217 | 85.50 328 | 87.80 328 | 94.11 335 | 61.63 342 | 96.96 308 | 90.63 300 | 79.26 326 | 96.15 318 |
|
testing_2 | | | 90.79 302 | 88.26 308 | 98.35 197 | 89.11 335 | 98.56 169 | 99.70 260 | 99.14 256 | 93.70 265 | 73.80 340 | 94.06 336 | 55.19 343 | 98.76 249 | 97.17 224 | 92.50 257 | 97.74 242 |
|
LCM-MVSNet | | | 79.01 318 | 76.93 320 | 85.27 327 | 78.28 347 | 68.01 344 | 96.57 341 | 98.03 326 | 55.10 347 | 82.03 338 | 93.27 337 | 31.99 354 | 93.95 334 | 82.72 326 | 74.37 340 | 93.84 335 |
|
testmv | | | 79.83 315 | 79.77 316 | 79.99 332 | 78.22 348 | 63.55 349 | 99.67 267 | 95.51 347 | 80.89 335 | 76.24 339 | 92.90 338 | 52.16 345 | 86.10 347 | 62.45 347 | 79.90 325 | 90.33 343 |
|
PMMVS2 | | | 79.15 317 | 77.28 319 | 84.76 328 | 82.34 343 | 72.66 338 | 99.70 260 | 95.11 348 | 71.68 340 | 84.78 334 | 90.87 339 | 32.05 353 | 89.99 341 | 75.53 339 | 63.45 342 | 91.64 339 |
|
Gipuma | | | 84.73 312 | 83.50 313 | 88.40 318 | 97.50 299 | 82.21 330 | 88.87 346 | 99.05 292 | 65.81 342 | 85.71 331 | 90.49 340 | 53.70 344 | 96.31 320 | 78.64 335 | 91.74 263 | 86.67 345 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
JIA-IIPM | | | 97.09 198 | 96.34 213 | 99.36 143 | 98.88 229 | 98.59 168 | 99.81 235 | 99.43 114 | 84.81 329 | 99.96 87 | 90.34 341 | 98.55 113 | 99.52 194 | 97.00 228 | 98.28 156 | 99.98 90 |
|
test_post | | | | | | | | | | | | 89.05 342 | 99.49 36 | 99.59 174 | | | |
|
PMVS | | 60.66 23 | 65.98 327 | 65.05 326 | 68.75 341 | 55.06 356 | 38.40 357 | 88.19 347 | 96.98 339 | 48.30 352 | 44.82 353 | 88.52 343 | 12.22 360 | 86.49 345 | 67.58 343 | 83.79 320 | 81.35 350 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
test_post1 | | | | | | | | 99.32 295 | | | | 88.24 344 | 99.33 50 | 99.59 174 | 98.31 185 | | |
|
MVS-HIRNet | | | 94.12 275 | 92.73 284 | 98.29 202 | 99.33 193 | 95.95 264 | 99.38 291 | 99.19 243 | 74.54 339 | 98.26 236 | 86.34 345 | 86.07 294 | 99.06 219 | 91.60 294 | 99.87 109 | 99.85 160 |
|
E-PMN | | | 70.72 322 | 70.06 323 | 72.69 339 | 83.92 342 | 65.48 348 | 99.95 205 | 92.72 350 | 49.88 350 | 72.30 342 | 86.26 346 | 47.17 349 | 77.43 351 | 53.83 351 | 44.49 347 | 75.17 353 |
|
EMVS | | | 69.88 324 | 69.09 324 | 72.24 340 | 84.70 340 | 65.82 347 | 99.96 199 | 87.08 356 | 49.82 351 | 71.51 343 | 84.74 347 | 49.30 347 | 75.32 352 | 50.97 352 | 43.71 348 | 75.59 352 |
|
PNet_i23d | | | 69.93 323 | 67.61 325 | 76.86 333 | 75.89 350 | 62.08 352 | 97.85 338 | 88.23 353 | 61.04 345 | 55.65 350 | 84.10 348 | 19.35 357 | 83.21 348 | 66.45 346 | 59.98 343 | 85.29 348 |
|
gg-mvs-nofinetune | | | 96.95 206 | 96.10 227 | 99.50 132 | 99.41 183 | 99.36 125 | 99.07 324 | 99.52 75 | 83.69 332 | 99.96 87 | 83.60 349 | 100.00 1 | 99.20 214 | 99.68 104 | 99.99 87 | 99.96 105 |
|
MVE | | 68.59 21 | 67.22 325 | 64.68 327 | 74.84 334 | 74.67 352 | 62.32 351 | 95.84 342 | 90.87 352 | 50.98 349 | 58.72 349 | 81.05 350 | 12.20 361 | 78.95 350 | 61.06 349 | 56.75 344 | 83.24 349 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
ANet_high | | | 66.05 326 | 63.44 328 | 73.88 336 | 61.14 354 | 63.45 350 | 95.68 344 | 87.18 354 | 79.93 336 | 47.35 351 | 80.68 351 | 22.35 356 | 72.33 355 | 61.24 348 | 35.42 350 | 85.88 347 |
|
no-one | | | 74.65 321 | 71.03 322 | 85.51 326 | 80.99 345 | 75.42 336 | 99.70 260 | 97.15 338 | 81.02 334 | 66.48 348 | 80.55 352 | 29.10 355 | 93.65 335 | 73.74 340 | 30.53 351 | 87.47 344 |
|
wuykxyi23d | | | 62.75 328 | 59.23 329 | 73.34 337 | 61.53 353 | 59.39 354 | 93.28 345 | 86.17 357 | 53.70 348 | 46.89 352 | 77.89 353 | 12.35 358 | 79.96 349 | 60.86 350 | 40.35 349 | 80.68 351 |
|
X-MVStestdata | | | 97.04 202 | 96.06 229 | 99.98 16 | 100.00 1 | 99.94 27 | 100.00 1 | 99.75 49 | 98.67 40 | 100.00 1 | 66.97 354 | 99.16 75 | 100.00 1 | 100.00 1 | 100.00 1 | 100.00 1 |
|
wuyk23d | | | 28.28 330 | 29.73 332 | 23.92 343 | 75.89 350 | 32.61 358 | 66.50 349 | 12.88 359 | 16.09 353 | 14.59 354 | 16.59 355 | 12.35 358 | 32.36 356 | 39.36 353 | 13.36 354 | 6.79 354 |
|
pcd_1.5k_mvsjas | | | 8.24 333 | 10.99 334 | 0.00 344 | 0.00 358 | 0.00 359 | 0.00 350 | 0.00 360 | 0.00 354 | 0.00 355 | 0.14 356 | 98.75 105 | 0.00 357 | 0.00 354 | 0.00 355 | 0.00 355 |
|
pcd1.5k->3k | | | 40.07 329 | 42.58 330 | 32.57 342 | 97.97 282 | 0.00 359 | 0.00 350 | 99.25 228 | 0.00 354 | 0.00 355 | 0.14 356 | 91.10 241 | 0.00 357 | 0.00 354 | 94.75 236 | 97.70 265 |
|
sosnet-low-res | | | 0.01 334 | 0.02 335 | 0.00 344 | 0.00 358 | 0.00 359 | 0.00 350 | 0.00 360 | 0.00 354 | 0.00 355 | 0.14 356 | 0.00 362 | 0.00 357 | 0.00 354 | 0.00 355 | 0.00 355 |
|
sosnet | | | 0.01 334 | 0.02 335 | 0.00 344 | 0.00 358 | 0.00 359 | 0.00 350 | 0.00 360 | 0.00 354 | 0.00 355 | 0.14 356 | 0.00 362 | 0.00 357 | 0.00 354 | 0.00 355 | 0.00 355 |
|
uncertanet | | | 0.01 334 | 0.02 335 | 0.00 344 | 0.00 358 | 0.00 359 | 0.00 350 | 0.00 360 | 0.00 354 | 0.00 355 | 0.14 356 | 0.00 362 | 0.00 357 | 0.00 354 | 0.00 355 | 0.00 355 |
|
Regformer | | | 0.01 334 | 0.02 335 | 0.00 344 | 0.00 358 | 0.00 359 | 0.00 350 | 0.00 360 | 0.00 354 | 0.00 355 | 0.14 356 | 0.00 362 | 0.00 357 | 0.00 354 | 0.00 355 | 0.00 355 |
|
uanet | | | 0.01 334 | 0.02 335 | 0.00 344 | 0.00 358 | 0.00 359 | 0.00 350 | 0.00 360 | 0.00 354 | 0.00 355 | 0.14 356 | 0.00 362 | 0.00 357 | 0.00 354 | 0.00 355 | 0.00 355 |
|
GSMVS | | | | | | | | | | | | | | | | | 99.91 126 |
|
test_part2 | | | | | | 100.00 1 | 99.99 1 | | | | 100.00 1 | | | | | | |
|
test_part1 | | | | | | | | | 99.42 120 | | | | 99.53 25 | | | 100.00 1 | 100.00 1 |
|
sam_mvs1 | | | | | | | | | | | | | 99.29 61 | | | | 99.91 126 |
|
sam_mvs | | | | | | | | | | | | | 99.33 50 | | | | |
|
MTGPA | | | | | | | | | 99.42 120 | | | | | | | | |
|
MTMP | | | | | | | | | 99.18 247 | | | | | | | | |
|
test9_res | | | | | | | | | | | | | | | 100.00 1 | 100.00 1 | 100.00 1 |
|
agg_prior2 | | | | | | | | | | | | | | | 100.00 1 | 100.00 1 | 100.00 1 |
|
agg_prior | | | | | | 100.00 1 | 99.88 58 | | 99.42 120 | | 100.00 1 | | | 99.97 97 | | | |
|
test_prior4 | | | | | | | 99.93 32 | 100.00 1 | | | | | | | | | |
|
test_prior | | | | | 99.90 70 | 100.00 1 | 99.75 83 | | 99.73 54 | | | | | 99.97 97 | | | 100.00 1 |
|
旧先验2 | | | | | | | | 100.00 1 | | 98.11 75 | 100.00 1 | | | 100.00 1 | 99.67 106 | | |
|
æ–°å‡ ä½•2 | | | | | | | | 100.00 1 | | | | | | | | | |
|
æ— å…ˆéªŒ | | | | | | | | 100.00 1 | 99.80 42 | 97.98 84 | | | | 100.00 1 | 99.33 138 | | 100.00 1 |
|
原ACMM2 | | | | | | | | 100.00 1 | | | | | | | | | |
|
testdata2 | | | | | | | | | | | | | | 100.00 1 | 97.36 222 | | |
|
segment_acmp | | | | | | | | | | | | | 99.55 24 | | | | |
|
testdata1 | | | | | | | | 100.00 1 | | 98.77 37 | | | | | | | |
|
test12 | | | | | 99.95 46 | 99.99 45 | 99.89 48 | | 99.42 120 | | 100.00 1 | | 99.24 67 | 99.97 97 | | 100.00 1 | 100.00 1 |
|
plane_prior7 | | | | | | 99.00 218 | 94.78 284 | | | | | | | | | | |
|
plane_prior6 | | | | | | 99.06 210 | 94.80 280 | | | | | | 88.58 276 | | | | |
|
plane_prior5 | | | | | | | | | 99.40 153 | | | | | 99.55 186 | 99.79 90 | 95.57 215 | 97.76 216 |
|
plane_prior3 | | | | | | | 94.79 283 | | | 99.03 16 | 99.08 184 | | | | | | |
|
plane_prior2 | | | | | | | | 100.00 1 | | 99.00 19 | | | | | | | |
|
plane_prior1 | | | | | | 99.02 213 | | | | | | | | | | | |
|
plane_prior | | | | | | | 94.80 280 | 100.00 1 | | 99.03 16 | | | | | | 95.58 211 | |
|
n2 | | | | | | | | | 0.00 360 | | | | | | | | |
|
nn | | | | | | | | | 0.00 360 | | | | | | | | |
|
door-mid | | | | | | | | | 96.32 345 | | | | | | | | |
|
test11 | | | | | | | | | 99.42 120 | | | | | | | | |
|
door | | | | | | | | | 96.13 346 | | | | | | | | |
|
HQP5-MVS | | | | | | | 94.82 277 | | | | | | | | | | |
|
HQP-NCC | | | | | | 99.07 206 | | 100.00 1 | | 99.04 13 | 99.17 176 | | | | | | |
|
ACMP_Plane | | | | | | 99.07 206 | | 100.00 1 | | 99.04 13 | 99.17 176 | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 99.79 90 | | |
|
HQP4-MVS | | | | | | | | | | | 99.17 176 | | | 99.57 177 | | | 97.77 214 |
|
HQP3-MVS | | | | | | | | | 99.40 153 | | | | | | | 95.58 211 | |
|
HQP2-MVS | | | | | | | | | | | | | 88.61 274 | | | | |
|
MDTV_nov1_ep13_2view | | | | | | | 99.24 135 | 99.56 277 | | 96.31 200 | 99.96 87 | | 98.86 99 | | 98.92 156 | | 99.89 139 |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 94.58 241 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 95.17 228 | |
|
Test By Simon | | | | | | | | | | | | | 99.10 78 | | | | |
|