v52 | | | 99.59 5 | 99.60 7 | 99.55 20 | 99.87 11 | 99.00 48 | 99.59 6 | 99.56 48 | 99.56 22 | 99.68 20 | 99.72 10 | 98.57 33 | 99.93 25 | 99.85 1 | 99.99 11 | 99.72 24 |
|
V4 | | | 99.59 5 | 99.60 7 | 99.55 20 | 99.87 11 | 99.00 48 | 99.59 6 | 99.56 48 | 99.56 22 | 99.68 20 | 99.72 10 | 98.57 33 | 99.93 25 | 99.85 1 | 99.99 11 | 99.72 24 |
|
v11 | | | 99.12 40 | 99.31 27 | 98.53 182 | 99.59 55 | 96.11 219 | 99.08 49 | 99.65 19 | 99.15 57 | 99.60 30 | 99.69 16 | 97.26 115 | 99.83 119 | 99.81 3 | 100.00 1 | 99.66 33 |
|
LCM-MVSNet | | | 99.93 1 | 99.92 1 | 99.94 1 | 99.99 1 | 99.97 1 | 99.90 1 | 99.89 2 | 99.98 1 | 99.99 1 | 99.96 1 | 99.77 1 | 100.00 1 | 99.81 3 | 100.00 1 | 99.85 9 |
|
v13 | | | 99.24 31 | 99.39 17 | 98.77 144 | 99.63 51 | 96.79 189 | 99.24 33 | 99.65 19 | 99.39 33 | 99.62 27 | 99.70 15 | 97.50 95 | 99.84 104 | 99.78 5 | 100.00 1 | 99.67 31 |
|
v12 | | | 99.21 32 | 99.37 19 | 98.74 152 | 99.60 54 | 96.72 194 | 99.19 39 | 99.65 19 | 99.35 39 | 99.62 27 | 99.69 16 | 97.43 102 | 99.83 119 | 99.76 6 | 100.00 1 | 99.66 33 |
|
V9 | | | 99.18 34 | 99.34 23 | 98.70 153 | 99.58 56 | 96.63 197 | 99.14 44 | 99.64 23 | 99.30 42 | 99.61 29 | 99.68 18 | 97.33 107 | 99.83 119 | 99.75 7 | 100.00 1 | 99.65 38 |
|
v7n | | | 99.53 9 | 99.57 9 | 99.41 53 | 99.88 7 | 98.54 80 | 99.45 10 | 99.61 29 | 99.66 9 | 99.68 20 | 99.66 22 | 98.44 41 | 99.95 13 | 99.73 8 | 99.96 28 | 99.75 22 |
|
V14 | | | 99.14 37 | 99.30 30 | 98.66 156 | 99.56 68 | 96.53 199 | 99.08 49 | 99.63 24 | 99.24 47 | 99.60 30 | 99.66 22 | 97.23 119 | 99.82 132 | 99.73 8 | 100.00 1 | 99.65 38 |
|
v15 | | | 99.11 41 | 99.27 32 | 98.62 162 | 99.52 80 | 96.43 203 | 99.01 55 | 99.63 24 | 99.18 56 | 99.59 32 | 99.64 26 | 97.13 123 | 99.81 145 | 99.71 10 | 100.00 1 | 99.64 41 |
|
v10 | | | 98.97 54 | 99.11 44 | 98.55 178 | 99.44 109 | 96.21 216 | 98.90 68 | 99.55 53 | 98.73 96 | 99.48 47 | 99.60 34 | 96.63 161 | 99.83 119 | 99.70 11 | 99.99 11 | 99.61 50 |
|
v17 | | | 99.07 43 | 99.22 36 | 98.61 165 | 99.50 86 | 96.42 204 | 99.01 55 | 99.60 31 | 99.15 57 | 99.48 47 | 99.61 30 | 97.05 127 | 99.81 145 | 99.64 12 | 99.98 19 | 99.61 50 |
|
v16 | | | 99.07 43 | 99.22 36 | 98.61 165 | 99.50 86 | 96.42 204 | 99.01 55 | 99.60 31 | 99.15 57 | 99.46 51 | 99.61 30 | 97.04 128 | 99.81 145 | 99.64 12 | 99.97 23 | 99.61 50 |
|
v748 | | | 99.44 14 | 99.48 12 | 99.33 67 | 99.88 7 | 98.43 87 | 99.42 11 | 99.53 58 | 99.63 12 | 99.69 17 | 99.60 34 | 97.99 68 | 99.91 43 | 99.60 14 | 99.96 28 | 99.66 33 |
|
v1240 | | | 98.55 116 | 98.62 87 | 98.32 208 | 99.22 147 | 95.58 237 | 97.51 213 | 99.45 85 | 97.16 212 | 99.45 54 | 99.24 83 | 96.12 186 | 99.85 88 | 99.60 14 | 99.88 64 | 99.55 84 |
|
v18 | | | 99.02 46 | 99.17 39 | 98.57 173 | 99.45 106 | 96.31 210 | 98.94 65 | 99.58 35 | 99.06 71 | 99.43 57 | 99.58 38 | 96.91 139 | 99.80 157 | 99.60 14 | 99.97 23 | 99.59 59 |
|
v8 | | | 99.01 47 | 99.16 41 | 98.57 173 | 99.47 99 | 96.31 210 | 98.90 68 | 99.47 80 | 99.03 73 | 99.52 40 | 99.57 39 | 96.93 138 | 99.81 145 | 99.60 14 | 99.98 19 | 99.60 53 |
|
v1921920 | | | 98.54 119 | 98.60 92 | 98.38 203 | 99.20 162 | 95.76 234 | 97.56 207 | 99.36 113 | 97.23 207 | 99.38 64 | 99.17 100 | 96.02 189 | 99.84 104 | 99.57 18 | 99.90 57 | 99.54 87 |
|
v1192 | | | 98.60 107 | 98.66 83 | 98.41 197 | 99.27 136 | 95.88 230 | 97.52 211 | 99.36 113 | 97.41 188 | 99.33 74 | 99.20 90 | 96.37 179 | 99.82 132 | 99.57 18 | 99.92 48 | 99.55 84 |
|
mvs_tets | | | 99.63 4 | 99.67 4 | 99.49 44 | 99.88 7 | 98.61 72 | 99.34 15 | 99.71 11 | 99.27 45 | 99.90 4 | 99.74 7 | 99.68 3 | 99.97 3 | 99.55 20 | 99.99 11 | 99.88 5 |
|
PS-MVSNAJss | | | 99.46 13 | 99.49 11 | 99.35 62 | 99.90 4 | 98.15 104 | 99.20 35 | 99.65 19 | 99.48 25 | 99.92 3 | 99.71 13 | 98.07 60 | 99.96 8 | 99.53 21 | 100.00 1 | 99.93 1 |
|
v144192 | | | 98.54 119 | 98.57 94 | 98.45 194 | 99.21 153 | 95.98 224 | 97.63 198 | 99.36 113 | 97.15 214 | 99.32 79 | 99.18 94 | 95.84 203 | 99.84 104 | 99.50 22 | 99.91 53 | 99.54 87 |
|
jajsoiax | | | 99.58 7 | 99.61 6 | 99.48 45 | 99.87 11 | 98.61 72 | 99.28 29 | 99.66 18 | 99.09 69 | 99.89 7 | 99.68 18 | 99.53 4 | 99.97 3 | 99.50 22 | 99.99 11 | 99.87 6 |
|
v1144 | | | 98.60 107 | 98.66 83 | 98.41 197 | 99.36 121 | 95.90 229 | 97.58 205 | 99.34 123 | 97.51 174 | 99.27 84 | 99.15 105 | 96.34 180 | 99.80 157 | 99.47 24 | 99.93 38 | 99.51 99 |
|
wuykxyi23d | | | 99.36 24 | 99.31 27 | 99.50 43 | 99.81 20 | 98.67 68 | 98.08 140 | 99.75 7 | 98.03 134 | 99.90 4 | 99.60 34 | 99.18 11 | 99.94 20 | 99.46 25 | 99.98 19 | 99.89 3 |
|
casdiffmvs1 | | | 98.49 125 | 98.45 111 | 98.61 165 | 98.99 207 | 97.15 177 | 98.70 80 | 99.25 153 | 97.42 187 | 97.87 223 | 99.20 90 | 96.29 181 | 99.66 262 | 99.44 26 | 98.91 270 | 99.03 231 |
|
OurMVSNet-221017-0 | | | 99.37 23 | 99.31 27 | 99.53 32 | 99.91 3 | 98.98 50 | 99.63 5 | 99.58 35 | 99.44 30 | 99.78 10 | 99.76 5 | 96.39 176 | 99.92 33 | 99.44 26 | 99.92 48 | 99.68 30 |
|
v7 | | | 98.67 93 | 98.73 68 | 98.50 188 | 99.43 113 | 96.21 216 | 98.00 157 | 99.31 133 | 97.58 167 | 99.17 102 | 99.18 94 | 96.63 161 | 99.80 157 | 99.42 28 | 99.88 64 | 99.48 117 |
|
pmmvs6 | | | 99.67 2 | 99.70 3 | 99.60 11 | 99.90 4 | 99.27 15 | 99.53 8 | 99.76 6 | 99.64 10 | 99.84 8 | 99.83 2 | 99.50 5 | 99.87 74 | 99.36 29 | 99.92 48 | 99.64 41 |
|
v2v482 | | | 98.56 112 | 98.62 87 | 98.37 204 | 99.42 114 | 95.81 233 | 97.58 205 | 99.16 186 | 97.90 146 | 99.28 82 | 99.01 136 | 95.98 195 | 99.79 179 | 99.33 30 | 99.90 57 | 99.51 99 |
|
ANet_high | | | 99.57 8 | 99.67 4 | 99.28 71 | 99.89 6 | 98.09 108 | 99.14 44 | 99.93 1 | 99.82 2 | 99.93 2 | 99.81 3 | 99.17 13 | 99.94 20 | 99.31 31 | 100.00 1 | 99.82 10 |
|
LTVRE_ROB | | 98.40 1 | 99.67 2 | 99.71 2 | 99.56 18 | 99.85 17 | 99.11 43 | 99.90 1 | 99.78 4 | 99.63 12 | 99.78 10 | 99.67 21 | 99.48 6 | 99.81 145 | 99.30 32 | 99.97 23 | 99.77 16 |
Andreas Kuhn, Heiko Hirschmüller, Daniel Scharstein, Helmut Mayer: A TV Prior for High-Quality Scalable Multi-View Stereo Reconstruction. International Journal of Computer Vision 2016 |
MVSFormer | | | 98.26 151 | 98.43 116 | 97.77 241 | 98.88 231 | 93.89 287 | 99.39 13 | 99.56 48 | 99.11 62 | 98.16 206 | 98.13 250 | 93.81 254 | 99.97 3 | 99.26 33 | 99.57 176 | 99.43 140 |
|
test_djsdf | | | 99.52 10 | 99.51 10 | 99.53 32 | 99.86 15 | 98.74 61 | 99.39 13 | 99.56 48 | 99.11 62 | 99.70 15 | 99.73 9 | 99.00 16 | 99.97 3 | 99.26 33 | 99.98 19 | 99.89 3 |
|
v1141 | | | 98.63 99 | 98.70 75 | 98.41 197 | 99.39 117 | 95.96 226 | 97.64 195 | 99.21 163 | 97.92 138 | 99.35 70 | 99.08 117 | 96.61 165 | 99.78 190 | 99.25 35 | 99.90 57 | 99.50 104 |
|
divwei89l23v2f112 | | | 98.63 99 | 98.70 75 | 98.41 197 | 99.39 117 | 95.96 226 | 97.64 195 | 99.21 163 | 97.92 138 | 99.35 70 | 99.08 117 | 96.61 165 | 99.78 190 | 99.25 35 | 99.90 57 | 99.50 104 |
|
v1 | | | 98.63 99 | 98.70 75 | 98.41 197 | 99.39 117 | 95.96 226 | 97.64 195 | 99.20 167 | 97.92 138 | 99.36 68 | 99.07 122 | 96.63 161 | 99.78 190 | 99.25 35 | 99.90 57 | 99.50 104 |
|
K. test v3 | | | 98.00 171 | 97.66 187 | 99.03 109 | 99.79 23 | 97.56 156 | 99.19 39 | 92.47 356 | 99.62 16 | 99.52 40 | 99.66 22 | 89.61 286 | 99.96 8 | 99.25 35 | 99.81 89 | 99.56 76 |
|
Anonymous20231211 | | | 99.27 28 | 99.27 32 | 99.26 76 | 99.29 134 | 98.18 102 | 99.49 9 | 99.51 63 | 99.70 6 | 99.80 9 | 99.68 18 | 96.84 146 | 99.83 119 | 99.21 39 | 99.91 53 | 99.77 16 |
|
V42 | | | 98.78 73 | 98.78 61 | 98.76 146 | 99.44 109 | 97.04 180 | 98.27 123 | 99.19 173 | 97.87 150 | 99.25 91 | 99.16 101 | 96.84 146 | 99.78 190 | 99.21 39 | 99.84 73 | 99.46 129 |
|
MIMVSNet1 | | | 99.38 22 | 99.32 26 | 99.55 20 | 99.86 15 | 99.19 25 | 99.41 12 | 99.59 33 | 99.59 19 | 99.71 14 | 99.57 39 | 97.12 124 | 99.90 47 | 99.21 39 | 99.87 68 | 99.54 87 |
|
v1neww | | | 98.70 83 | 98.76 64 | 98.52 183 | 99.47 99 | 96.30 212 | 98.03 148 | 99.18 177 | 97.92 138 | 99.26 89 | 99.08 117 | 96.91 139 | 99.78 190 | 99.19 42 | 99.82 82 | 99.47 125 |
|
v7new | | | 98.70 83 | 98.76 64 | 98.52 183 | 99.47 99 | 96.30 212 | 98.03 148 | 99.18 177 | 97.92 138 | 99.26 89 | 99.08 117 | 96.91 139 | 99.78 190 | 99.19 42 | 99.82 82 | 99.47 125 |
|
v6 | | | 98.70 83 | 98.76 64 | 98.52 183 | 99.47 99 | 96.30 212 | 98.03 148 | 99.18 177 | 97.92 138 | 99.27 84 | 99.08 117 | 96.91 139 | 99.78 190 | 99.19 42 | 99.82 82 | 99.48 117 |
|
nrg030 | | | 99.40 20 | 99.35 21 | 99.54 25 | 99.58 56 | 99.13 39 | 98.98 63 | 99.48 74 | 99.68 7 | 99.46 51 | 99.26 80 | 98.62 29 | 99.73 227 | 99.17 45 | 99.92 48 | 99.76 20 |
|
casdiffmvs | | | 98.22 155 | 98.17 144 | 98.35 205 | 98.75 251 | 96.62 198 | 98.62 84 | 99.12 192 | 98.04 133 | 96.46 313 | 99.12 110 | 95.81 204 | 99.63 271 | 99.17 45 | 98.45 294 | 98.80 263 |
|
anonymousdsp | | | 99.51 11 | 99.47 14 | 99.62 5 | 99.88 7 | 99.08 47 | 99.34 15 | 99.69 14 | 98.93 84 | 99.65 23 | 99.72 10 | 98.93 19 | 99.95 13 | 99.11 47 | 100.00 1 | 99.82 10 |
|
VPA-MVSNet | | | 99.30 27 | 99.30 30 | 99.28 71 | 99.49 92 | 98.36 92 | 99.00 60 | 99.45 85 | 99.63 12 | 99.52 40 | 99.44 57 | 98.25 47 | 99.88 65 | 99.09 48 | 99.84 73 | 99.62 46 |
|
pm-mvs1 | | | 99.44 14 | 99.48 12 | 99.33 67 | 99.80 21 | 98.63 69 | 99.29 25 | 99.63 24 | 99.30 42 | 99.65 23 | 99.60 34 | 99.16 15 | 99.82 132 | 99.07 49 | 99.83 79 | 99.56 76 |
|
TransMVSNet (Re) | | | 99.44 14 | 99.47 14 | 99.36 57 | 99.80 21 | 98.58 75 | 99.27 31 | 99.57 42 | 99.39 33 | 99.75 12 | 99.62 28 | 99.17 13 | 99.83 119 | 99.06 50 | 99.62 159 | 99.66 33 |
|
SixPastTwentyTwo | | | 98.75 76 | 98.62 87 | 99.16 86 | 99.83 18 | 97.96 125 | 99.28 29 | 98.20 281 | 99.37 36 | 99.70 15 | 99.65 25 | 92.65 270 | 99.93 25 | 99.04 51 | 99.84 73 | 99.60 53 |
|
FC-MVSNet-test | | | 99.27 28 | 99.25 34 | 99.34 65 | 99.77 24 | 98.37 91 | 99.30 24 | 99.57 42 | 99.61 18 | 99.40 62 | 99.50 46 | 97.12 124 | 99.85 88 | 99.02 52 | 99.94 33 | 99.80 13 |
|
lessismore_v0 | | | | | 98.97 117 | 99.73 27 | 97.53 158 | | 86.71 368 | | 99.37 66 | 99.52 45 | 89.93 284 | 99.92 33 | 98.99 53 | 99.72 124 | 99.44 135 |
|
Vis-MVSNet | | | 99.34 25 | 99.36 20 | 99.27 74 | 99.73 27 | 98.26 94 | 99.17 41 | 99.78 4 | 99.11 62 | 99.27 84 | 99.48 50 | 98.82 21 | 99.95 13 | 98.94 54 | 99.93 38 | 99.59 59 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
mvs_anonymous | | | 97.83 188 | 98.16 148 | 96.87 283 | 98.18 312 | 91.89 313 | 97.31 223 | 98.90 234 | 97.37 191 | 98.83 153 | 99.46 52 | 96.28 182 | 99.79 179 | 98.90 55 | 98.16 305 | 98.95 240 |
|
WR-MVS_H | | | 99.33 26 | 99.22 36 | 99.65 4 | 99.71 33 | 99.24 18 | 99.32 17 | 99.55 53 | 99.46 28 | 99.50 45 | 99.34 71 | 97.30 109 | 99.93 25 | 98.90 55 | 99.93 38 | 99.77 16 |
|
PS-CasMVS | | | 99.40 20 | 99.33 25 | 99.62 5 | 99.71 33 | 99.10 44 | 99.29 25 | 99.53 58 | 99.53 24 | 99.46 51 | 99.41 61 | 98.23 49 | 99.95 13 | 98.89 57 | 99.95 30 | 99.81 12 |
|
UA-Net | | | 99.47 12 | 99.40 16 | 99.70 2 | 99.49 92 | 99.29 12 | 99.80 3 | 99.72 10 | 99.82 2 | 99.04 120 | 99.81 3 | 98.05 63 | 99.96 8 | 98.85 58 | 99.99 11 | 99.86 8 |
|
testing_2 | | | 98.93 57 | 98.99 50 | 98.76 146 | 99.57 61 | 97.03 181 | 97.85 175 | 99.13 190 | 98.46 111 | 99.44 55 | 99.44 57 | 98.22 51 | 99.74 222 | 98.85 58 | 99.94 33 | 99.51 99 |
|
new-patchmatchnet | | | 98.35 140 | 98.74 67 | 97.18 270 | 99.24 141 | 92.23 311 | 96.42 279 | 99.48 74 | 98.30 119 | 99.69 17 | 99.53 44 | 97.44 101 | 99.82 132 | 98.84 60 | 99.77 105 | 99.49 111 |
|
diffmvs1 | | | 98.39 139 | 98.43 116 | 98.27 214 | 98.53 288 | 96.18 218 | 97.91 168 | 99.37 108 | 98.73 96 | 97.22 279 | 99.15 105 | 96.97 137 | 99.77 201 | 98.80 61 | 99.18 240 | 98.86 254 |
|
PEN-MVS | | | 99.41 19 | 99.34 23 | 99.62 5 | 99.73 27 | 99.14 36 | 99.29 25 | 99.54 57 | 99.62 16 | 99.56 33 | 99.42 59 | 98.16 56 | 99.96 8 | 98.78 62 | 99.93 38 | 99.77 16 |
|
DTE-MVSNet | | | 99.43 17 | 99.35 21 | 99.66 3 | 99.71 33 | 99.30 11 | 99.31 20 | 99.51 63 | 99.64 10 | 99.56 33 | 99.46 52 | 98.23 49 | 99.97 3 | 98.78 62 | 99.93 38 | 99.72 24 |
|
EG-PatchMatch MVS | | | 98.99 49 | 99.01 48 | 98.94 121 | 99.50 86 | 97.47 160 | 98.04 147 | 99.59 33 | 98.15 131 | 99.40 62 | 99.36 68 | 98.58 32 | 99.76 207 | 98.78 62 | 99.68 143 | 99.59 59 |
|
EI-MVSNet-UG-set | | | 98.69 88 | 98.71 72 | 98.62 162 | 99.10 180 | 96.37 208 | 97.23 228 | 98.87 237 | 99.20 51 | 99.19 98 | 98.99 139 | 97.30 109 | 99.85 88 | 98.77 65 | 99.79 97 | 99.65 38 |
|
CP-MVSNet | | | 99.21 32 | 99.09 45 | 99.56 18 | 99.65 46 | 98.96 54 | 99.13 46 | 99.34 123 | 99.42 31 | 99.33 74 | 99.26 80 | 97.01 133 | 99.94 20 | 98.74 66 | 99.93 38 | 99.79 14 |
|
EI-MVSNet-Vis-set | | | 98.68 91 | 98.70 75 | 98.63 160 | 99.09 183 | 96.40 206 | 97.23 228 | 98.86 241 | 99.20 51 | 99.18 101 | 98.97 145 | 97.29 111 | 99.85 88 | 98.72 67 | 99.78 101 | 99.64 41 |
|
FIs | | | 99.14 37 | 99.09 45 | 99.29 70 | 99.70 39 | 98.28 93 | 99.13 46 | 99.52 62 | 99.48 25 | 99.24 92 | 99.41 61 | 96.79 152 | 99.82 132 | 98.69 68 | 99.88 64 | 99.76 20 |
|
semantic-postprocess | | | | | 96.87 283 | 99.27 136 | 91.16 332 | | 99.25 153 | 99.10 66 | 99.41 60 | 99.35 69 | 92.91 266 | 99.96 8 | 98.65 69 | 99.94 33 | 99.49 111 |
|
UniMVSNet (Re) | | | 98.87 63 | 98.71 72 | 99.35 62 | 99.24 141 | 98.73 64 | 97.73 186 | 99.38 104 | 98.93 84 | 99.12 105 | 98.73 186 | 96.77 153 | 99.86 79 | 98.63 70 | 99.80 93 | 99.46 129 |
|
EI-MVSNet | | | 98.40 135 | 98.51 98 | 98.04 230 | 99.10 180 | 94.73 258 | 97.20 232 | 98.87 237 | 98.97 79 | 99.06 112 | 99.02 134 | 96.00 191 | 99.80 157 | 98.58 71 | 99.82 82 | 99.60 53 |
|
IterMVS-LS | | | 98.55 116 | 98.70 75 | 98.09 223 | 99.48 97 | 94.73 258 | 97.22 231 | 99.39 100 | 98.97 79 | 99.38 64 | 99.31 75 | 96.00 191 | 99.93 25 | 98.58 71 | 99.97 23 | 99.60 53 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
MVS_Test | | | 98.18 159 | 98.36 126 | 97.67 247 | 98.48 290 | 94.73 258 | 98.18 130 | 99.02 213 | 97.69 158 | 98.04 215 | 99.11 112 | 97.22 121 | 99.56 295 | 98.57 73 | 98.90 271 | 98.71 272 |
|
UniMVSNet_NR-MVSNet | | | 98.86 65 | 98.68 80 | 99.40 55 | 99.17 170 | 98.74 61 | 97.68 190 | 99.40 98 | 99.14 60 | 99.06 112 | 98.59 211 | 96.71 158 | 99.93 25 | 98.57 73 | 99.77 105 | 99.53 92 |
|
DU-MVS | | | 98.82 67 | 98.63 86 | 99.39 56 | 99.16 172 | 98.74 61 | 97.54 210 | 99.25 153 | 98.84 89 | 99.06 112 | 98.76 184 | 96.76 155 | 99.93 25 | 98.57 73 | 99.77 105 | 99.50 104 |
|
UGNet | | | 98.53 121 | 98.45 111 | 98.79 139 | 97.94 320 | 96.96 184 | 99.08 49 | 98.54 269 | 99.10 66 | 96.82 299 | 99.47 51 | 96.55 168 | 99.84 104 | 98.56 76 | 99.94 33 | 99.55 84 |
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 |
IterMVS | | | 97.73 190 | 98.11 155 | 96.57 294 | 99.24 141 | 90.28 333 | 95.52 321 | 99.21 163 | 98.86 88 | 99.33 74 | 99.33 73 | 93.11 262 | 99.94 20 | 98.49 77 | 99.94 33 | 99.48 117 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
Regformer-4 | | | 98.73 79 | 98.68 80 | 98.89 128 | 99.02 202 | 97.22 171 | 97.17 236 | 99.06 200 | 99.21 48 | 99.17 102 | 98.85 169 | 97.45 100 | 99.86 79 | 98.48 78 | 99.70 131 | 99.60 53 |
|
diffmvs | | | 98.08 165 | 98.14 152 | 97.88 236 | 98.37 298 | 95.22 248 | 97.93 163 | 98.99 221 | 98.87 86 | 95.93 324 | 99.18 94 | 96.63 161 | 99.79 179 | 98.45 79 | 98.95 267 | 98.64 279 |
|
MVSTER | | | 96.86 244 | 96.55 247 | 97.79 240 | 97.91 322 | 94.21 276 | 97.56 207 | 98.87 237 | 97.49 177 | 99.06 112 | 99.05 128 | 80.72 330 | 99.80 157 | 98.44 80 | 99.82 82 | 99.37 159 |
|
ACMH | | 96.65 7 | 99.25 30 | 99.24 35 | 99.26 76 | 99.72 32 | 98.38 90 | 99.07 52 | 99.55 53 | 98.30 119 | 99.65 23 | 99.45 56 | 99.22 9 | 99.76 207 | 98.44 80 | 99.77 105 | 99.64 41 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
FMVSNet1 | | | 99.17 35 | 99.17 39 | 99.17 83 | 99.55 72 | 98.24 96 | 99.20 35 | 99.44 88 | 99.21 48 | 99.43 57 | 99.55 41 | 97.82 78 | 99.86 79 | 98.42 82 | 99.89 63 | 99.41 145 |
|
Regformer-3 | | | 98.61 105 | 98.61 90 | 98.63 160 | 99.02 202 | 96.53 199 | 97.17 236 | 98.84 243 | 99.13 61 | 99.10 109 | 98.85 169 | 97.24 117 | 99.79 179 | 98.41 83 | 99.70 131 | 99.57 71 |
|
v148 | | | 98.45 130 | 98.60 92 | 98.00 232 | 99.44 109 | 94.98 254 | 97.44 217 | 99.06 200 | 98.30 119 | 99.32 79 | 98.97 145 | 96.65 160 | 99.62 274 | 98.37 84 | 99.85 71 | 99.39 152 |
|
VDD-MVS | | | 98.56 112 | 98.39 122 | 99.07 100 | 99.13 178 | 98.07 113 | 98.59 89 | 97.01 308 | 99.59 19 | 99.11 106 | 99.27 78 | 94.82 230 | 99.79 179 | 98.34 85 | 99.63 158 | 99.34 172 |
|
TranMVSNet+NR-MVSNet | | | 99.17 35 | 99.07 47 | 99.46 50 | 99.37 120 | 98.87 56 | 98.39 119 | 99.42 96 | 99.42 31 | 99.36 68 | 99.06 123 | 98.38 43 | 99.95 13 | 98.34 85 | 99.90 57 | 99.57 71 |
|
pmmvs5 | | | 97.64 196 | 97.49 197 | 98.08 226 | 99.14 177 | 95.12 253 | 96.70 263 | 99.05 204 | 93.77 303 | 98.62 176 | 98.83 173 | 93.23 259 | 99.75 213 | 98.33 87 | 99.76 114 | 99.36 165 |
|
MVS_0304 | | | 98.02 168 | 97.88 176 | 98.46 192 | 98.22 310 | 96.39 207 | 96.50 273 | 99.49 71 | 98.03 134 | 97.24 278 | 98.33 239 | 94.80 233 | 99.90 47 | 98.31 88 | 99.95 30 | 99.08 223 |
|
EU-MVSNet | | | 97.66 195 | 98.50 100 | 95.13 327 | 99.63 51 | 85.84 349 | 98.35 120 | 98.21 280 | 98.23 124 | 99.54 35 | 99.46 52 | 95.02 224 | 99.68 248 | 98.24 89 | 99.87 68 | 99.87 6 |
|
TDRefinement | | | 99.42 18 | 99.38 18 | 99.55 20 | 99.76 25 | 99.33 10 | 99.68 4 | 99.71 11 | 99.38 35 | 99.53 38 | 99.61 30 | 98.64 28 | 99.80 157 | 98.24 89 | 99.84 73 | 99.52 96 |
|
DELS-MVS | | | 98.27 149 | 98.20 141 | 98.48 190 | 98.86 233 | 96.70 195 | 95.60 318 | 99.20 167 | 97.73 156 | 98.45 191 | 98.71 188 | 97.50 95 | 99.82 132 | 98.21 91 | 99.59 166 | 98.93 244 |
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 |
XXY-MVS | | | 99.14 37 | 99.15 43 | 99.10 95 | 99.76 25 | 97.74 147 | 98.85 73 | 99.62 27 | 98.48 110 | 99.37 66 | 99.49 49 | 98.75 24 | 99.86 79 | 98.20 92 | 99.80 93 | 99.71 27 |
|
alignmvs | | | 97.35 215 | 96.88 226 | 98.78 142 | 98.54 286 | 98.09 108 | 97.71 187 | 97.69 295 | 99.20 51 | 97.59 253 | 95.90 329 | 88.12 294 | 99.55 298 | 98.18 93 | 98.96 266 | 98.70 274 |
|
VNet | | | 98.42 132 | 98.30 134 | 98.79 139 | 98.79 249 | 97.29 166 | 98.23 126 | 98.66 264 | 99.31 41 | 98.85 150 | 98.80 178 | 94.80 233 | 99.78 190 | 98.13 94 | 99.13 249 | 99.31 182 |
|
VPNet | | | 98.87 63 | 98.83 56 | 99.01 113 | 99.70 39 | 97.62 155 | 98.43 116 | 99.35 119 | 99.47 27 | 99.28 82 | 99.05 128 | 96.72 157 | 99.82 132 | 98.09 95 | 99.36 209 | 99.59 59 |
|
canonicalmvs | | | 98.34 141 | 98.26 137 | 98.58 171 | 98.46 292 | 97.82 139 | 98.96 64 | 99.46 82 | 99.19 55 | 97.46 264 | 95.46 340 | 98.59 31 | 99.46 320 | 98.08 96 | 98.71 279 | 98.46 284 |
|
Baseline_NR-MVSNet | | | 98.98 53 | 98.86 54 | 99.36 57 | 99.82 19 | 98.55 77 | 97.47 216 | 99.57 42 | 99.37 36 | 99.21 96 | 99.61 30 | 96.76 155 | 99.83 119 | 98.06 97 | 99.83 79 | 99.71 27 |
|
DeepC-MVS | | 97.60 4 | 98.97 54 | 98.93 51 | 99.10 95 | 99.35 126 | 97.98 122 | 98.01 156 | 99.46 82 | 97.56 171 | 99.54 35 | 99.50 46 | 98.97 17 | 99.84 104 | 98.06 97 | 99.92 48 | 99.49 111 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
xiu_mvs_v1_base_debu | | | 97.86 182 | 98.17 144 | 96.92 280 | 98.98 209 | 93.91 284 | 96.45 276 | 99.17 183 | 97.85 152 | 98.41 195 | 97.14 307 | 98.47 38 | 99.92 33 | 98.02 99 | 99.05 255 | 96.92 333 |
|
xiu_mvs_v1_base | | | 97.86 182 | 98.17 144 | 96.92 280 | 98.98 209 | 93.91 284 | 96.45 276 | 99.17 183 | 97.85 152 | 98.41 195 | 97.14 307 | 98.47 38 | 99.92 33 | 98.02 99 | 99.05 255 | 96.92 333 |
|
xiu_mvs_v1_base_debi | | | 97.86 182 | 98.17 144 | 96.92 280 | 98.98 209 | 93.91 284 | 96.45 276 | 99.17 183 | 97.85 152 | 98.41 195 | 97.14 307 | 98.47 38 | 99.92 33 | 98.02 99 | 99.05 255 | 96.92 333 |
|
NR-MVSNet | | | 98.95 56 | 98.82 57 | 99.36 57 | 99.16 172 | 98.72 66 | 99.22 34 | 99.20 167 | 99.10 66 | 99.72 13 | 98.76 184 | 96.38 178 | 99.86 79 | 98.00 102 | 99.82 82 | 99.50 104 |
|
FMVSNet2 | | | 98.49 125 | 98.40 120 | 98.75 148 | 98.90 225 | 97.14 179 | 98.61 86 | 99.13 190 | 98.59 103 | 99.19 98 | 99.28 76 | 94.14 247 | 99.82 132 | 97.97 103 | 99.80 93 | 99.29 188 |
|
Anonymous20240529 | | | 98.93 57 | 98.87 53 | 99.12 91 | 99.19 163 | 98.22 101 | 99.01 55 | 98.99 221 | 99.25 46 | 99.54 35 | 99.37 65 | 97.04 128 | 99.80 157 | 97.89 104 | 99.52 191 | 99.35 170 |
|
pmmvs-eth3d | | | 98.47 128 | 98.34 129 | 98.86 132 | 99.30 133 | 97.76 144 | 97.16 238 | 99.28 142 | 95.54 270 | 99.42 59 | 99.19 92 | 97.27 112 | 99.63 271 | 97.89 104 | 99.97 23 | 99.20 205 |
|
Patchmatch-RL test | | | 97.26 222 | 97.02 219 | 97.99 233 | 99.52 80 | 95.53 239 | 96.13 292 | 99.71 11 | 97.47 178 | 99.27 84 | 99.16 101 | 84.30 318 | 99.62 274 | 97.89 104 | 99.77 105 | 98.81 260 |
|
VDDNet | | | 98.21 156 | 97.95 168 | 99.01 113 | 99.58 56 | 97.74 147 | 99.01 55 | 97.29 303 | 99.67 8 | 98.97 132 | 99.50 46 | 90.45 282 | 99.80 157 | 97.88 107 | 99.20 234 | 99.48 117 |
|
APDe-MVS | | | 98.99 49 | 98.79 60 | 99.60 11 | 99.21 153 | 99.15 34 | 98.87 70 | 99.48 74 | 97.57 169 | 99.35 70 | 99.24 83 | 97.83 75 | 99.89 57 | 97.88 107 | 99.70 131 | 99.75 22 |
|
CANet | | | 97.87 181 | 97.76 179 | 98.19 219 | 97.75 325 | 95.51 240 | 96.76 259 | 99.05 204 | 97.74 155 | 96.93 288 | 98.21 248 | 95.59 210 | 99.89 57 | 97.86 109 | 99.93 38 | 99.19 211 |
|
Regformer-1 | | | 98.55 116 | 98.44 114 | 98.87 130 | 98.85 236 | 97.29 166 | 96.91 251 | 98.99 221 | 98.97 79 | 98.99 127 | 98.64 201 | 97.26 115 | 99.81 145 | 97.79 110 | 99.57 176 | 99.51 99 |
|
PM-MVS | | | 98.82 67 | 98.72 71 | 99.12 91 | 99.64 49 | 98.54 80 | 97.98 159 | 99.68 15 | 97.62 163 | 99.34 73 | 99.18 94 | 97.54 91 | 99.77 201 | 97.79 110 | 99.74 116 | 99.04 228 |
|
tttt0517 | | | 95.64 275 | 94.98 285 | 97.64 251 | 99.36 121 | 93.81 290 | 98.72 78 | 90.47 365 | 98.08 132 | 98.67 168 | 98.34 236 | 73.88 361 | 99.92 33 | 97.77 112 | 99.51 192 | 99.20 205 |
|
GBi-Net | | | 98.65 95 | 98.47 106 | 99.17 83 | 98.90 225 | 98.24 96 | 99.20 35 | 99.44 88 | 98.59 103 | 98.95 135 | 99.55 41 | 94.14 247 | 99.86 79 | 97.77 112 | 99.69 138 | 99.41 145 |
|
test1 | | | 98.65 95 | 98.47 106 | 99.17 83 | 98.90 225 | 98.24 96 | 99.20 35 | 99.44 88 | 98.59 103 | 98.95 135 | 99.55 41 | 94.14 247 | 99.86 79 | 97.77 112 | 99.69 138 | 99.41 145 |
|
FMVSNet3 | | | 97.50 204 | 97.24 211 | 98.29 212 | 98.08 315 | 95.83 232 | 97.86 173 | 98.91 233 | 97.89 147 | 98.95 135 | 98.95 149 | 87.06 295 | 99.81 145 | 97.77 112 | 99.69 138 | 99.23 199 |
|
UnsupCasMVSNet_eth | | | 97.89 178 | 97.60 192 | 98.75 148 | 99.31 131 | 97.17 175 | 97.62 199 | 99.35 119 | 98.72 98 | 98.76 162 | 98.68 192 | 92.57 271 | 99.74 222 | 97.76 116 | 95.60 350 | 99.34 172 |
|
Regformer-2 | | | 98.60 107 | 98.46 109 | 99.02 112 | 98.85 236 | 97.71 149 | 96.91 251 | 99.09 197 | 98.98 78 | 99.01 124 | 98.64 201 | 97.37 106 | 99.84 104 | 97.75 117 | 99.57 176 | 99.52 96 |
|
test20.03 | | | 98.78 73 | 98.77 63 | 98.78 142 | 99.46 103 | 97.20 172 | 97.78 179 | 99.24 159 | 99.04 72 | 99.41 60 | 98.90 157 | 97.65 84 | 99.76 207 | 97.70 118 | 99.79 97 | 99.39 152 |
|
Gipuma | | | 99.03 45 | 99.16 41 | 98.64 158 | 99.94 2 | 98.51 82 | 99.32 17 | 99.75 7 | 99.58 21 | 98.60 180 | 99.62 28 | 98.22 51 | 99.51 312 | 97.70 118 | 99.73 119 | 97.89 303 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
PatchT | | | 96.65 254 | 96.35 252 | 97.54 258 | 97.40 341 | 95.32 245 | 97.98 159 | 96.64 320 | 99.33 40 | 96.89 295 | 99.42 59 | 84.32 317 | 99.81 145 | 97.69 120 | 97.49 327 | 97.48 327 |
|
test_normal | | | 97.58 200 | 97.41 202 | 98.10 222 | 99.03 200 | 95.72 235 | 96.21 288 | 97.05 307 | 96.71 229 | 98.65 170 | 98.12 254 | 93.87 251 | 99.69 243 | 97.68 121 | 99.35 211 | 98.88 252 |
|
MSLP-MVS++ | | | 98.02 168 | 98.14 152 | 97.64 251 | 98.58 281 | 95.19 250 | 97.48 214 | 99.23 161 | 97.47 178 | 97.90 221 | 98.62 207 | 97.04 128 | 98.81 358 | 97.55 122 | 99.41 205 | 98.94 243 |
|
WR-MVS | | | 98.40 135 | 98.19 143 | 99.03 109 | 99.00 205 | 97.65 152 | 96.85 255 | 98.94 225 | 98.57 107 | 98.89 144 | 98.50 224 | 95.60 209 | 99.85 88 | 97.54 123 | 99.85 71 | 99.59 59 |
|
HPM-MVS_fast | | | 99.01 47 | 98.82 57 | 99.57 15 | 99.71 33 | 99.35 8 | 99.00 60 | 99.50 65 | 97.33 194 | 98.94 139 | 98.86 166 | 98.75 24 | 99.82 132 | 97.53 124 | 99.71 128 | 99.56 76 |
|
RPMNet | | | 96.82 247 | 96.66 241 | 97.28 267 | 97.71 327 | 94.22 274 | 98.11 137 | 96.90 314 | 99.37 36 | 96.91 291 | 99.34 71 | 86.72 296 | 99.81 145 | 97.53 124 | 97.36 332 | 97.81 309 |
|
PMMVS2 | | | 98.07 167 | 98.08 160 | 98.04 230 | 99.41 115 | 94.59 264 | 94.59 341 | 99.40 98 | 97.50 175 | 98.82 156 | 98.83 173 | 96.83 148 | 99.84 104 | 97.50 126 | 99.81 89 | 99.71 27 |
|
Test4 | | | 97.43 211 | 97.18 213 | 98.18 220 | 99.05 195 | 96.02 223 | 96.62 269 | 99.09 197 | 96.25 246 | 98.63 175 | 97.70 278 | 90.49 281 | 99.68 248 | 97.50 126 | 99.30 221 | 98.83 257 |
|
DI_MVS_plusplus_test | | | 97.57 202 | 97.40 203 | 98.07 227 | 99.06 190 | 95.71 236 | 96.58 271 | 96.96 309 | 96.71 229 | 98.69 166 | 98.13 250 | 93.81 254 | 99.68 248 | 97.45 128 | 99.19 238 | 98.80 263 |
|
LFMVS | | | 97.20 227 | 96.72 234 | 98.64 158 | 98.72 255 | 96.95 185 | 98.93 67 | 94.14 346 | 99.74 5 | 98.78 159 | 99.01 136 | 84.45 315 | 99.73 227 | 97.44 129 | 99.27 226 | 99.25 195 |
|
ACMM | | 96.08 12 | 98.91 60 | 98.73 68 | 99.48 45 | 99.55 72 | 99.14 36 | 98.07 142 | 99.37 108 | 97.62 163 | 99.04 120 | 98.96 148 | 98.84 20 | 99.79 179 | 97.43 130 | 99.65 155 | 99.49 111 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
CHOSEN 280x420 | | | 95.51 280 | 95.47 271 | 95.65 321 | 98.25 305 | 88.27 341 | 93.25 354 | 98.88 236 | 93.53 306 | 94.65 345 | 97.15 306 | 86.17 301 | 99.93 25 | 97.41 131 | 99.93 38 | 98.73 271 |
|
CR-MVSNet | | | 96.28 265 | 95.95 262 | 97.28 267 | 97.71 327 | 94.22 274 | 98.11 137 | 98.92 231 | 92.31 320 | 96.91 291 | 99.37 65 | 85.44 310 | 99.81 145 | 97.39 132 | 97.36 332 | 97.81 309 |
|
Anonymous202405211 | | | 97.90 176 | 97.50 196 | 99.08 98 | 98.90 225 | 98.25 95 | 98.53 95 | 96.16 325 | 98.87 86 | 99.11 106 | 98.86 166 | 90.40 283 | 99.78 190 | 97.36 133 | 99.31 219 | 99.19 211 |
|
CANet_DTU | | | 97.26 222 | 97.06 218 | 97.84 238 | 97.57 332 | 94.65 262 | 96.19 291 | 98.79 252 | 97.23 207 | 95.14 342 | 98.24 245 | 93.22 260 | 99.84 104 | 97.34 134 | 99.84 73 | 99.04 228 |
|
Anonymous20231206 | | | 98.21 156 | 98.21 140 | 98.20 218 | 99.51 83 | 95.43 243 | 98.13 134 | 99.32 131 | 96.16 251 | 98.93 140 | 98.82 176 | 96.00 191 | 99.83 119 | 97.32 135 | 99.73 119 | 99.36 165 |
|
MP-MVS-pluss | | | 98.57 111 | 98.23 139 | 99.60 11 | 99.69 41 | 99.35 8 | 97.16 238 | 99.38 104 | 94.87 283 | 98.97 132 | 98.99 139 | 98.01 65 | 99.88 65 | 97.29 136 | 99.70 131 | 99.58 66 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
FMVSNet5 | | | 96.01 269 | 95.20 280 | 98.41 197 | 97.53 335 | 96.10 220 | 98.74 76 | 99.50 65 | 97.22 210 | 98.03 216 | 99.04 130 | 69.80 364 | 99.88 65 | 97.27 137 | 99.71 128 | 99.25 195 |
|
our_test_3 | | | 97.39 214 | 97.73 182 | 96.34 298 | 98.70 261 | 89.78 335 | 94.61 340 | 98.97 224 | 96.50 236 | 99.04 120 | 98.85 169 | 95.98 195 | 99.84 104 | 97.26 138 | 99.67 149 | 99.41 145 |
|
jason | | | 97.45 210 | 97.35 208 | 97.76 242 | 99.24 141 | 93.93 283 | 95.86 307 | 98.42 274 | 94.24 296 | 98.50 189 | 98.13 250 | 94.82 230 | 99.91 43 | 97.22 139 | 99.73 119 | 99.43 140 |
jason: jason. |
DP-MVS | | | 98.93 57 | 98.81 59 | 99.28 71 | 99.21 153 | 98.45 86 | 98.46 114 | 99.33 128 | 99.63 12 | 99.48 47 | 99.15 105 | 97.23 119 | 99.75 213 | 97.17 140 | 99.66 154 | 99.63 45 |
|
zzz-MVS | | | 98.79 70 | 98.52 97 | 99.61 8 | 99.67 43 | 99.36 6 | 97.33 221 | 99.20 167 | 98.83 90 | 98.89 144 | 98.90 157 | 96.98 135 | 99.92 33 | 97.16 141 | 99.70 131 | 99.56 76 |
|
MTAPA | | | 98.88 62 | 98.64 85 | 99.61 8 | 99.67 43 | 99.36 6 | 98.43 116 | 99.20 167 | 98.83 90 | 98.89 144 | 98.90 157 | 96.98 135 | 99.92 33 | 97.16 141 | 99.70 131 | 99.56 76 |
|
TSAR-MVS + GP. | | | 98.18 159 | 97.98 166 | 98.77 144 | 98.71 257 | 97.88 132 | 96.32 283 | 98.66 264 | 96.33 242 | 99.23 95 | 98.51 221 | 97.48 99 | 99.40 325 | 97.16 141 | 99.46 201 | 99.02 232 |
|
3Dnovator | | 98.27 2 | 98.81 69 | 98.73 68 | 99.05 106 | 98.76 250 | 97.81 141 | 99.25 32 | 99.30 139 | 98.57 107 | 98.55 186 | 99.33 73 | 97.95 72 | 99.90 47 | 97.16 141 | 99.67 149 | 99.44 135 |
|
ACMMP_Plus | | | 98.75 76 | 98.48 104 | 99.57 15 | 99.58 56 | 99.29 12 | 97.82 178 | 99.25 153 | 96.94 218 | 98.78 159 | 99.12 110 | 98.02 64 | 99.84 104 | 97.13 145 | 99.67 149 | 99.59 59 |
|
PVSNet_Blended_VisFu | | | 98.17 161 | 98.15 150 | 98.22 217 | 99.73 27 | 95.15 251 | 97.36 220 | 99.68 15 | 94.45 291 | 98.99 127 | 99.27 78 | 96.87 145 | 99.94 20 | 97.13 145 | 99.91 53 | 99.57 71 |
|
LP | | | 96.60 257 | 96.57 246 | 96.68 289 | 97.64 331 | 91.70 315 | 98.11 137 | 97.74 292 | 97.29 200 | 97.91 220 | 99.24 83 | 88.35 292 | 99.85 88 | 97.11 147 | 95.76 349 | 98.49 283 |
|
HyFIR lowres test | | | 97.19 228 | 96.60 244 | 98.96 118 | 99.62 53 | 97.28 168 | 95.17 329 | 99.50 65 | 94.21 297 | 99.01 124 | 98.32 240 | 86.61 297 | 99.99 2 | 97.10 148 | 99.84 73 | 99.60 53 |
|
MDA-MVSNet_test_wron | | | 97.60 198 | 97.66 187 | 97.41 265 | 99.04 197 | 93.09 299 | 95.27 326 | 98.42 274 | 97.26 201 | 98.88 147 | 98.95 149 | 95.43 216 | 99.73 227 | 97.02 149 | 98.72 276 | 99.41 145 |
|
YYNet1 | | | 97.60 198 | 97.67 184 | 97.39 266 | 99.04 197 | 93.04 302 | 95.27 326 | 98.38 276 | 97.25 202 | 98.92 141 | 98.95 149 | 95.48 215 | 99.73 227 | 96.99 150 | 98.74 275 | 99.41 145 |
|
pmmvs4 | | | 97.58 200 | 97.28 210 | 98.51 187 | 98.84 239 | 96.93 186 | 95.40 325 | 98.52 270 | 93.60 305 | 98.61 178 | 98.65 198 | 95.10 223 | 99.60 281 | 96.97 151 | 99.79 97 | 98.99 235 |
|
TAMVS | | | 98.24 154 | 98.05 162 | 98.80 138 | 99.07 187 | 97.18 174 | 97.88 170 | 98.81 249 | 96.66 232 | 99.17 102 | 99.21 88 | 94.81 232 | 99.77 201 | 96.96 152 | 99.88 64 | 99.44 135 |
|
N_pmnet | | | 97.63 197 | 97.17 214 | 98.99 116 | 99.27 136 | 97.86 134 | 95.98 295 | 93.41 348 | 95.25 275 | 99.47 50 | 98.90 157 | 95.63 208 | 99.85 88 | 96.91 153 | 99.73 119 | 99.27 190 |
|
1112_ss | | | 97.29 221 | 96.86 227 | 98.58 171 | 99.34 128 | 96.32 209 | 96.75 260 | 99.58 35 | 93.14 310 | 96.89 295 | 97.48 292 | 92.11 275 | 99.86 79 | 96.91 153 | 99.54 184 | 99.57 71 |
|
thisisatest0530 | | | 95.27 283 | 94.45 291 | 97.74 244 | 99.19 163 | 94.37 272 | 97.86 173 | 90.20 366 | 97.17 211 | 98.22 203 | 97.65 281 | 73.53 362 | 99.90 47 | 96.90 155 | 99.35 211 | 98.95 240 |
|
Fast-Effi-MVS+-dtu | | | 98.27 149 | 98.09 157 | 98.81 137 | 98.43 295 | 98.11 107 | 97.61 201 | 99.50 65 | 98.64 99 | 97.39 272 | 97.52 289 | 98.12 59 | 99.95 13 | 96.90 155 | 98.71 279 | 98.38 290 |
|
TSAR-MVS + MP. | | | 98.63 99 | 98.49 103 | 99.06 105 | 99.64 49 | 97.90 131 | 98.51 100 | 98.94 225 | 96.96 217 | 99.24 92 | 98.89 162 | 97.83 75 | 99.81 145 | 96.88 157 | 99.49 200 | 99.48 117 |
|
MVS_111021_HR | | | 98.25 153 | 98.08 160 | 98.75 148 | 99.09 183 | 97.46 161 | 95.97 296 | 99.27 147 | 97.60 166 | 97.99 217 | 98.25 244 | 98.15 58 | 99.38 329 | 96.87 158 | 99.57 176 | 99.42 143 |
|
EPP-MVSNet | | | 98.30 145 | 98.04 163 | 99.07 100 | 99.56 68 | 97.83 136 | 99.29 25 | 98.07 285 | 99.03 73 | 98.59 181 | 99.13 109 | 92.16 274 | 99.90 47 | 96.87 158 | 99.68 143 | 99.49 111 |
|
MS-PatchMatch | | | 97.68 193 | 97.75 180 | 97.45 262 | 98.23 309 | 93.78 291 | 97.29 224 | 98.84 243 | 96.10 253 | 98.64 172 | 98.65 198 | 96.04 188 | 99.36 330 | 96.84 160 | 99.14 246 | 99.20 205 |
|
3Dnovator+ | | 97.89 3 | 98.69 88 | 98.51 98 | 99.24 79 | 98.81 246 | 98.40 88 | 99.02 54 | 99.19 173 | 98.99 76 | 98.07 212 | 99.28 76 | 97.11 126 | 99.84 104 | 96.84 160 | 99.32 217 | 99.47 125 |
|
XVS | | | 98.72 80 | 98.45 111 | 99.53 32 | 99.46 103 | 99.21 20 | 98.65 81 | 99.34 123 | 98.62 101 | 97.54 258 | 98.63 205 | 97.50 95 | 99.83 119 | 96.79 162 | 99.53 188 | 99.56 76 |
|
X-MVStestdata | | | 94.32 308 | 92.59 326 | 99.53 32 | 99.46 103 | 99.21 20 | 98.65 81 | 99.34 123 | 98.62 101 | 97.54 258 | 45.85 366 | 97.50 95 | 99.83 119 | 96.79 162 | 99.53 188 | 99.56 76 |
|
lupinMVS | | | 97.06 235 | 96.86 227 | 97.65 249 | 98.88 231 | 93.89 287 | 95.48 322 | 97.97 287 | 93.53 306 | 98.16 206 | 97.58 285 | 93.81 254 | 99.91 43 | 96.77 164 | 99.57 176 | 99.17 217 |
|
CHOSEN 1792x2688 | | | 97.49 206 | 97.14 217 | 98.54 181 | 99.68 42 | 96.09 222 | 96.50 273 | 99.62 27 | 91.58 329 | 98.84 152 | 98.97 145 | 92.36 272 | 99.88 65 | 96.76 165 | 99.95 30 | 99.67 31 |
|
ppachtmachnet_test | | | 97.50 204 | 97.74 181 | 96.78 287 | 98.70 261 | 91.23 331 | 94.55 342 | 99.05 204 | 96.36 241 | 99.21 96 | 98.79 180 | 96.39 176 | 99.78 190 | 96.74 166 | 99.82 82 | 99.34 172 |
|
DeepPCF-MVS | | 96.93 5 | 98.32 143 | 98.01 165 | 99.23 80 | 98.39 297 | 98.97 51 | 95.03 332 | 99.18 177 | 96.88 221 | 99.33 74 | 98.78 181 | 98.16 56 | 99.28 341 | 96.74 166 | 99.62 159 | 99.44 135 |
|
no-one | | | 97.98 174 | 98.10 156 | 97.61 253 | 99.55 72 | 93.82 289 | 96.70 263 | 98.94 225 | 96.18 247 | 99.52 40 | 99.41 61 | 95.90 201 | 99.81 145 | 96.72 168 | 99.99 11 | 99.20 205 |
|
CDS-MVSNet | | | 97.69 192 | 97.35 208 | 98.69 154 | 98.73 254 | 97.02 183 | 96.92 250 | 98.75 257 | 95.89 259 | 98.59 181 | 98.67 194 | 92.08 276 | 99.74 222 | 96.72 168 | 99.81 89 | 99.32 178 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
CSCG | | | 98.68 91 | 98.50 100 | 99.20 82 | 99.45 106 | 98.63 69 | 98.56 91 | 99.57 42 | 97.87 150 | 98.85 150 | 98.04 261 | 97.66 83 | 99.84 104 | 96.72 168 | 99.81 89 | 99.13 221 |
|
ACMH+ | | 96.62 9 | 99.08 42 | 99.00 49 | 99.33 67 | 99.71 33 | 98.83 57 | 98.60 87 | 99.58 35 | 99.11 62 | 99.53 38 | 99.18 94 | 98.81 22 | 99.67 254 | 96.71 171 | 99.77 105 | 99.50 104 |
|
MVS_111021_LR | | | 98.30 145 | 98.12 154 | 98.83 135 | 99.16 172 | 98.03 116 | 96.09 293 | 99.30 139 | 97.58 167 | 98.10 210 | 98.24 245 | 98.25 47 | 99.34 332 | 96.69 172 | 99.65 155 | 99.12 222 |
|
OPM-MVS | | | 98.56 112 | 98.32 133 | 99.25 78 | 99.41 115 | 98.73 64 | 97.13 240 | 99.18 177 | 97.10 215 | 98.75 163 | 98.92 153 | 98.18 55 | 99.65 268 | 96.68 173 | 99.56 181 | 99.37 159 |
|
Effi-MVS+-dtu | | | 98.26 151 | 97.90 174 | 99.35 62 | 98.02 317 | 99.49 2 | 98.02 155 | 99.16 186 | 98.29 122 | 97.64 249 | 97.99 263 | 96.44 174 | 99.95 13 | 96.66 174 | 98.93 269 | 98.60 280 |
|
mvs-test1 | | | 97.83 188 | 97.48 200 | 98.89 128 | 98.02 317 | 99.20 23 | 97.20 232 | 99.16 186 | 98.29 122 | 96.46 313 | 97.17 304 | 96.44 174 | 99.92 33 | 96.66 174 | 97.90 322 | 97.54 326 |
|
Effi-MVS+ | | | 98.02 168 | 97.82 178 | 98.62 162 | 98.53 288 | 97.19 173 | 97.33 221 | 99.68 15 | 97.30 198 | 96.68 302 | 97.46 294 | 98.56 35 | 99.80 157 | 96.63 176 | 98.20 302 | 98.86 254 |
|
MDA-MVSNet-bldmvs | | | 97.94 175 | 97.91 173 | 98.06 228 | 99.44 109 | 94.96 255 | 96.63 268 | 99.15 189 | 98.35 113 | 98.83 153 | 99.11 112 | 94.31 244 | 99.85 88 | 96.60 177 | 98.72 276 | 99.37 159 |
|
Test_1112_low_res | | | 96.99 240 | 96.55 247 | 98.31 210 | 99.35 126 | 95.47 242 | 95.84 310 | 99.53 58 | 91.51 331 | 96.80 300 | 98.48 227 | 91.36 278 | 99.83 119 | 96.58 178 | 99.53 188 | 99.62 46 |
|
LS3D | | | 98.63 99 | 98.38 124 | 99.36 57 | 97.25 345 | 99.38 5 | 99.12 48 | 99.32 131 | 99.21 48 | 98.44 192 | 98.88 163 | 97.31 108 | 99.80 157 | 96.58 178 | 99.34 214 | 98.92 245 |
|
HFP-MVS | | | 98.71 81 | 98.44 114 | 99.51 40 | 99.49 92 | 99.16 29 | 98.52 96 | 99.31 133 | 97.47 178 | 98.58 183 | 98.50 224 | 97.97 70 | 99.85 88 | 96.57 180 | 99.59 166 | 99.53 92 |
|
ACMMPR | | | 98.70 83 | 98.42 118 | 99.54 25 | 99.52 80 | 99.14 36 | 98.52 96 | 99.31 133 | 97.47 178 | 98.56 185 | 98.54 219 | 97.75 80 | 99.88 65 | 96.57 180 | 99.59 166 | 99.58 66 |
|
sss | | | 97.21 226 | 96.93 222 | 98.06 228 | 98.83 241 | 95.22 248 | 96.75 260 | 98.48 272 | 94.49 287 | 97.27 277 | 97.90 268 | 92.77 268 | 99.80 157 | 96.57 180 | 99.32 217 | 99.16 220 |
|
SD-MVS | | | 98.40 135 | 98.68 80 | 97.54 258 | 98.96 212 | 97.99 118 | 97.88 170 | 99.36 113 | 98.20 127 | 99.63 26 | 99.04 130 | 98.76 23 | 95.33 366 | 96.56 183 | 99.74 116 | 99.31 182 |
|
ambc | | | | | 98.24 216 | 98.82 244 | 95.97 225 | 98.62 84 | 99.00 220 | | 99.27 84 | 99.21 88 | 96.99 134 | 99.50 313 | 96.55 184 | 99.50 199 | 99.26 193 |
|
APD-MVS_3200maxsize | | | 98.84 66 | 98.61 90 | 99.53 32 | 99.19 163 | 99.27 15 | 98.49 102 | 99.33 128 | 98.64 99 | 99.03 123 | 98.98 143 | 97.89 73 | 99.85 88 | 96.54 185 | 99.42 204 | 99.46 129 |
|
CP-MVS | | | 98.70 83 | 98.42 118 | 99.52 37 | 99.36 121 | 99.12 41 | 98.72 78 | 99.36 113 | 97.54 173 | 98.30 200 | 98.40 230 | 97.86 74 | 99.89 57 | 96.53 186 | 99.72 124 | 99.56 76 |
|
MVP-Stereo | | | 98.08 165 | 97.92 172 | 98.57 173 | 98.96 212 | 96.79 189 | 97.90 169 | 99.18 177 | 96.41 240 | 98.46 190 | 98.95 149 | 95.93 198 | 99.60 281 | 96.51 187 | 98.98 265 | 99.31 182 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
testgi | | | 98.32 143 | 98.39 122 | 98.13 221 | 99.57 61 | 95.54 238 | 97.78 179 | 99.49 71 | 97.37 191 | 99.19 98 | 97.65 281 | 98.96 18 | 99.49 314 | 96.50 188 | 98.99 263 | 99.34 172 |
|
HPM-MVS | | | 98.79 70 | 98.53 96 | 99.59 14 | 99.65 46 | 99.29 12 | 99.16 42 | 99.43 93 | 96.74 226 | 98.61 178 | 98.38 232 | 98.62 29 | 99.87 74 | 96.47 189 | 99.67 149 | 99.59 59 |
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
region2R | | | 98.69 88 | 98.40 120 | 99.54 25 | 99.53 78 | 99.17 27 | 98.52 96 | 99.31 133 | 97.46 183 | 98.44 192 | 98.51 221 | 97.83 75 | 99.88 65 | 96.46 190 | 99.58 172 | 99.58 66 |
|
SMA-MVS | | | 98.40 135 | 98.03 164 | 99.51 40 | 99.16 172 | 99.21 20 | 98.05 146 | 99.22 162 | 94.16 299 | 98.98 129 | 99.10 114 | 97.52 94 | 99.79 179 | 96.45 191 | 99.64 157 | 99.53 92 |
|
abl_6 | | | 98.99 49 | 98.78 61 | 99.61 8 | 99.45 106 | 99.46 3 | 98.60 87 | 99.50 65 | 98.59 103 | 99.24 92 | 99.04 130 | 98.54 36 | 99.89 57 | 96.45 191 | 99.62 159 | 99.50 104 |
|
PatchFormer-LS_test | | | 94.08 316 | 93.91 308 | 94.59 333 | 96.93 349 | 86.86 346 | 97.55 209 | 96.57 321 | 94.27 295 | 94.38 348 | 93.64 362 | 80.96 329 | 99.59 285 | 96.44 193 | 94.48 357 | 97.31 330 |
|
CNVR-MVS | | | 98.17 161 | 97.87 177 | 99.07 100 | 98.67 269 | 98.24 96 | 97.01 243 | 98.93 228 | 97.25 202 | 97.62 250 | 98.34 236 | 97.27 112 | 99.57 292 | 96.42 194 | 99.33 215 | 99.39 152 |
|
PS-MVSNAJ | | | 97.08 234 | 97.39 205 | 96.16 309 | 98.56 283 | 92.46 307 | 95.24 328 | 98.85 242 | 97.25 202 | 97.49 262 | 95.99 324 | 98.07 60 | 99.90 47 | 96.37 195 | 98.67 282 | 96.12 350 |
|
CVMVSNet | | | 96.25 266 | 97.21 212 | 93.38 347 | 99.10 180 | 80.56 367 | 97.20 232 | 98.19 283 | 96.94 218 | 99.00 126 | 99.02 134 | 89.50 288 | 99.80 157 | 96.36 196 | 99.59 166 | 99.78 15 |
|
xiu_mvs_v2_base | | | 97.16 230 | 97.49 197 | 96.17 307 | 98.54 286 | 92.46 307 | 95.45 323 | 98.84 243 | 97.25 202 | 97.48 263 | 96.49 316 | 98.31 46 | 99.90 47 | 96.34 197 | 98.68 281 | 96.15 349 |
|
ACMMP | | | 98.75 76 | 98.50 100 | 99.52 37 | 99.56 68 | 99.16 29 | 98.87 70 | 99.37 108 | 97.16 212 | 98.82 156 | 99.01 136 | 97.71 81 | 99.87 74 | 96.29 198 | 99.69 138 | 99.54 87 |
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 |
XVG-OURS-SEG-HR | | | 98.49 125 | 98.28 136 | 99.14 89 | 99.49 92 | 98.83 57 | 96.54 272 | 99.48 74 | 97.32 196 | 99.11 106 | 98.61 209 | 99.33 8 | 99.30 338 | 96.23 199 | 98.38 295 | 99.28 189 |
|
GA-MVS | | | 95.86 271 | 95.32 276 | 97.49 260 | 98.60 279 | 94.15 278 | 93.83 350 | 97.93 288 | 95.49 271 | 96.68 302 | 97.42 297 | 83.21 323 | 99.30 338 | 96.22 200 | 98.55 288 | 99.01 233 |
|
mPP-MVS | | | 98.64 97 | 98.34 129 | 99.54 25 | 99.54 76 | 99.17 27 | 98.63 83 | 99.24 159 | 97.47 178 | 98.09 211 | 98.68 192 | 97.62 88 | 99.89 57 | 96.22 200 | 99.62 159 | 99.57 71 |
|
Fast-Effi-MVS+ | | | 97.67 194 | 97.38 206 | 98.57 173 | 98.71 257 | 97.43 163 | 97.23 228 | 99.45 85 | 94.82 284 | 96.13 317 | 96.51 315 | 98.52 37 | 99.91 43 | 96.19 202 | 98.83 272 | 98.37 292 |
|
pmmvs3 | | | 95.03 287 | 94.40 296 | 96.93 279 | 97.70 329 | 92.53 306 | 95.08 331 | 97.71 294 | 88.57 349 | 97.71 245 | 98.08 259 | 79.39 343 | 99.82 132 | 96.19 202 | 99.11 253 | 98.43 287 |
|
MCST-MVS | | | 98.00 171 | 97.63 190 | 99.10 95 | 99.24 141 | 98.17 103 | 96.89 253 | 98.73 260 | 95.66 262 | 97.92 218 | 97.70 278 | 97.17 122 | 99.66 262 | 96.18 204 | 99.23 230 | 99.47 125 |
|
testmv | | | 98.51 123 | 98.47 106 | 98.61 165 | 99.24 141 | 96.53 199 | 96.66 266 | 99.73 9 | 98.56 109 | 99.50 45 | 99.23 87 | 97.24 117 | 99.87 74 | 96.16 205 | 99.93 38 | 99.44 135 |
|
SteuartSystems-ACMMP | | | 98.79 70 | 98.54 95 | 99.54 25 | 99.73 27 | 99.16 29 | 98.23 126 | 99.31 133 | 97.92 138 | 98.90 142 | 98.90 157 | 98.00 66 | 99.88 65 | 96.15 206 | 99.72 124 | 99.58 66 |
Skip Steuart: Steuart Systems R&D Blog. |
HSP-MVS | | | 98.34 141 | 97.94 170 | 99.54 25 | 99.57 61 | 99.25 17 | 98.57 90 | 98.84 243 | 97.55 172 | 99.31 81 | 97.71 277 | 94.61 238 | 99.88 65 | 96.14 207 | 99.19 238 | 99.48 117 |
|
DeepC-MVS_fast | | 96.85 6 | 98.30 145 | 98.15 150 | 98.75 148 | 98.61 277 | 97.23 169 | 97.76 183 | 99.09 197 | 97.31 197 | 98.75 163 | 98.66 196 | 97.56 90 | 99.64 270 | 96.10 208 | 99.55 183 | 99.39 152 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
1111 | | | 93.99 318 | 93.72 313 | 94.80 330 | 99.33 129 | 85.20 353 | 95.97 296 | 99.39 100 | 97.88 148 | 98.64 172 | 98.56 216 | 57.79 372 | 99.80 157 | 96.02 209 | 99.87 68 | 99.40 151 |
|
.test1245 | | | 79.71 341 | 84.30 342 | 65.96 355 | 99.33 129 | 85.20 353 | 95.97 296 | 99.39 100 | 97.88 148 | 98.64 172 | 98.56 216 | 57.79 372 | 99.80 157 | 96.02 209 | 15.07 366 | 12.86 367 |
|
GST-MVS | | | 98.61 105 | 98.30 134 | 99.52 37 | 99.51 83 | 99.20 23 | 98.26 124 | 99.25 153 | 97.44 186 | 98.67 168 | 98.39 231 | 97.68 82 | 99.85 88 | 96.00 211 | 99.51 192 | 99.52 96 |
|
EPNet | | | 96.14 267 | 95.44 273 | 98.25 215 | 90.76 370 | 95.50 241 | 97.92 165 | 94.65 333 | 98.97 79 | 92.98 357 | 98.85 169 | 89.12 290 | 99.87 74 | 95.99 212 | 99.68 143 | 99.39 152 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
COLMAP_ROB | | 96.50 10 | 98.99 49 | 98.85 55 | 99.41 53 | 99.58 56 | 99.10 44 | 98.74 76 | 99.56 48 | 99.09 69 | 99.33 74 | 99.19 92 | 98.40 42 | 99.72 236 | 95.98 213 | 99.76 114 | 99.42 143 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
Patchmtry | | | 97.35 215 | 96.97 221 | 98.50 188 | 97.31 344 | 96.47 202 | 98.18 130 | 98.92 231 | 98.95 83 | 98.78 159 | 99.37 65 | 85.44 310 | 99.85 88 | 95.96 214 | 99.83 79 | 99.17 217 |
|
tfpnnormal | | | 98.90 61 | 98.90 52 | 98.91 125 | 99.67 43 | 97.82 139 | 99.00 60 | 99.44 88 | 99.45 29 | 99.51 44 | 99.24 83 | 98.20 54 | 99.86 79 | 95.92 215 | 99.69 138 | 99.04 228 |
|
XVG-ACMP-BASELINE | | | 98.56 112 | 98.34 129 | 99.22 81 | 99.54 76 | 98.59 74 | 97.71 187 | 99.46 82 | 97.25 202 | 98.98 129 | 98.99 139 | 97.54 91 | 99.84 104 | 95.88 216 | 99.74 116 | 99.23 199 |
|
tpm | | | 94.67 303 | 94.34 298 | 95.66 320 | 97.68 330 | 88.42 339 | 97.88 170 | 94.90 332 | 94.46 289 | 96.03 323 | 98.56 216 | 78.66 344 | 99.79 179 | 95.88 216 | 95.01 353 | 98.78 266 |
|
ab-mvs | | | 98.41 133 | 98.36 126 | 98.59 170 | 99.19 163 | 97.23 169 | 99.32 17 | 98.81 249 | 97.66 160 | 98.62 176 | 99.40 64 | 96.82 149 | 99.80 157 | 95.88 216 | 99.51 192 | 98.75 270 |
|
test-LLR | | | 93.90 320 | 93.85 309 | 94.04 338 | 96.53 355 | 84.62 357 | 94.05 346 | 92.39 357 | 96.17 248 | 94.12 351 | 95.07 344 | 82.30 327 | 99.67 254 | 95.87 219 | 98.18 303 | 97.82 307 |
|
test-mter | | | 92.33 333 | 91.76 335 | 94.04 338 | 96.53 355 | 84.62 357 | 94.05 346 | 92.39 357 | 94.00 302 | 94.12 351 | 95.07 344 | 65.63 371 | 99.67 254 | 95.87 219 | 98.18 303 | 97.82 307 |
|
PGM-MVS | | | 98.66 94 | 98.37 125 | 99.55 20 | 99.53 78 | 99.18 26 | 98.23 126 | 99.49 71 | 97.01 216 | 98.69 166 | 98.88 163 | 98.00 66 | 99.89 57 | 95.87 219 | 99.59 166 | 99.58 66 |
|
USDC | | | 97.41 213 | 97.40 203 | 97.44 263 | 98.94 215 | 93.67 294 | 95.17 329 | 99.53 58 | 94.03 301 | 98.97 132 | 99.10 114 | 95.29 218 | 99.34 332 | 95.84 222 | 99.73 119 | 99.30 185 |
|
HPM-MVS++ | | | 98.10 163 | 97.64 189 | 99.48 45 | 99.09 183 | 99.13 39 | 97.52 211 | 98.75 257 | 97.46 183 | 96.90 294 | 97.83 272 | 96.01 190 | 99.84 104 | 95.82 223 | 99.35 211 | 99.46 129 |
|
TESTMET0.1,1 | | | 92.19 335 | 91.77 334 | 93.46 345 | 96.48 357 | 82.80 364 | 94.05 346 | 91.52 362 | 94.45 291 | 94.00 354 | 94.88 352 | 66.65 368 | 99.56 295 | 95.78 224 | 98.11 308 | 98.02 301 |
|
DSMNet-mixed | | | 97.42 212 | 97.60 192 | 96.87 283 | 99.15 176 | 91.46 318 | 98.54 94 | 99.12 192 | 92.87 313 | 97.58 254 | 99.63 27 | 96.21 183 | 99.90 47 | 95.74 225 | 99.54 184 | 99.27 190 |
|
XVG-OURS | | | 98.53 121 | 98.34 129 | 99.11 93 | 99.50 86 | 98.82 59 | 95.97 296 | 99.50 65 | 97.30 198 | 99.05 117 | 98.98 143 | 99.35 7 | 99.32 335 | 95.72 226 | 99.68 143 | 99.18 213 |
|
RPSCF | | | 98.62 104 | 98.36 126 | 99.42 51 | 99.65 46 | 99.42 4 | 98.55 93 | 99.57 42 | 97.72 157 | 98.90 142 | 99.26 80 | 96.12 186 | 99.52 307 | 95.72 226 | 99.71 128 | 99.32 178 |
|
PHI-MVS | | | 98.29 148 | 97.95 168 | 99.34 65 | 98.44 294 | 99.16 29 | 98.12 136 | 99.38 104 | 96.01 257 | 98.06 213 | 98.43 228 | 97.80 79 | 99.67 254 | 95.69 228 | 99.58 172 | 99.20 205 |
|
#test# | | | 98.50 124 | 98.16 148 | 99.51 40 | 99.49 92 | 99.16 29 | 98.03 148 | 99.31 133 | 96.30 245 | 98.58 183 | 98.50 224 | 97.97 70 | 99.85 88 | 95.68 229 | 99.59 166 | 99.53 92 |
|
test_0402 | | | 98.76 75 | 98.71 72 | 98.93 122 | 99.56 68 | 98.14 106 | 98.45 115 | 99.34 123 | 99.28 44 | 98.95 135 | 98.91 154 | 98.34 45 | 99.79 179 | 95.63 230 | 99.91 53 | 98.86 254 |
|
tpmrst | | | 95.07 286 | 95.46 272 | 93.91 341 | 97.11 347 | 84.36 359 | 97.62 199 | 96.96 309 | 94.98 279 | 96.35 315 | 98.80 178 | 85.46 309 | 99.59 285 | 95.60 231 | 96.23 346 | 97.79 312 |
|
PMMVS | | | 96.51 259 | 95.98 261 | 98.09 223 | 97.53 335 | 95.84 231 | 94.92 334 | 98.84 243 | 91.58 329 | 96.05 322 | 95.58 332 | 95.68 207 | 99.66 262 | 95.59 232 | 98.09 315 | 98.76 269 |
|
LPG-MVS_test | | | 98.71 81 | 98.46 109 | 99.47 48 | 99.57 61 | 98.97 51 | 98.23 126 | 99.48 74 | 96.60 234 | 99.10 109 | 99.06 123 | 98.71 26 | 99.83 119 | 95.58 233 | 99.78 101 | 99.62 46 |
|
LGP-MVS_train | | | | | 99.47 48 | 99.57 61 | 98.97 51 | | 99.48 74 | 96.60 234 | 99.10 109 | 99.06 123 | 98.71 26 | 99.83 119 | 95.58 233 | 99.78 101 | 99.62 46 |
|
IS-MVSNet | | | 98.19 158 | 97.90 174 | 99.08 98 | 99.57 61 | 97.97 123 | 99.31 20 | 98.32 277 | 99.01 75 | 98.98 129 | 99.03 133 | 91.59 277 | 99.79 179 | 95.49 235 | 99.80 93 | 99.48 117 |
|
ESAPD | | | 98.59 110 | 98.26 137 | 99.57 15 | 99.27 136 | 99.15 34 | 97.01 243 | 99.39 100 | 97.67 159 | 99.44 55 | 98.99 139 | 97.53 93 | 99.89 57 | 95.40 236 | 99.68 143 | 99.66 33 |
|
NCCC | | | 97.86 182 | 97.47 201 | 99.05 106 | 98.61 277 | 98.07 113 | 96.98 245 | 98.90 234 | 97.63 162 | 97.04 285 | 97.93 267 | 95.99 194 | 99.66 262 | 95.31 237 | 98.82 273 | 99.43 140 |
|
Patchmatch-test | | | 96.55 258 | 96.34 253 | 97.17 271 | 98.35 299 | 93.06 300 | 98.40 118 | 97.79 290 | 97.33 194 | 98.41 195 | 98.67 194 | 83.68 322 | 99.69 243 | 95.16 238 | 99.31 219 | 98.77 267 |
|
EPMVS | | | 93.72 322 | 93.27 321 | 95.09 328 | 96.04 362 | 87.76 342 | 98.13 134 | 85.01 369 | 94.69 285 | 96.92 289 | 98.64 201 | 78.47 347 | 99.31 336 | 95.04 239 | 96.46 344 | 98.20 294 |
|
DWT-MVSNet_test | | | 92.75 330 | 92.05 332 | 94.85 329 | 96.48 357 | 87.21 345 | 97.83 177 | 94.99 331 | 92.22 322 | 92.72 358 | 94.11 359 | 70.75 363 | 99.46 320 | 95.01 240 | 94.33 358 | 97.87 305 |
|
UnsupCasMVSNet_bld | | | 97.30 219 | 96.92 223 | 98.45 194 | 99.28 135 | 96.78 193 | 96.20 290 | 99.27 147 | 95.42 273 | 98.28 201 | 98.30 241 | 93.16 261 | 99.71 237 | 94.99 241 | 97.37 330 | 98.87 253 |
|
PatchmatchNet | | | 95.58 276 | 95.67 268 | 95.30 326 | 97.34 343 | 87.32 344 | 97.65 194 | 96.65 319 | 95.30 274 | 97.07 283 | 98.69 190 | 84.77 312 | 99.75 213 | 94.97 242 | 98.64 283 | 98.83 257 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
EPNet_dtu | | | 94.93 289 | 94.78 289 | 95.38 325 | 93.58 369 | 87.68 343 | 96.78 257 | 95.69 330 | 97.35 193 | 89.14 365 | 98.09 258 | 88.15 293 | 99.49 314 | 94.95 243 | 99.30 221 | 98.98 236 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
0601test | | | 96.69 251 | 96.29 255 | 97.90 234 | 98.28 303 | 95.24 246 | 97.29 224 | 97.36 299 | 98.21 125 | 98.17 204 | 97.86 269 | 86.27 299 | 99.55 298 | 94.87 244 | 98.32 296 | 98.89 250 |
|
Anonymous20240521 | | | 96.69 251 | 96.29 255 | 97.90 234 | 98.28 303 | 95.24 246 | 97.29 224 | 97.36 299 | 98.21 125 | 98.17 204 | 97.86 269 | 86.27 299 | 99.55 298 | 94.87 244 | 98.32 296 | 98.89 250 |
|
Patchmatch-test1 | | | 96.44 263 | 96.72 234 | 95.60 322 | 98.24 307 | 88.35 340 | 95.85 309 | 96.88 315 | 96.11 252 | 97.67 248 | 98.57 213 | 93.10 263 | 99.69 243 | 94.79 246 | 99.22 231 | 98.77 267 |
|
ACMP | | 95.32 15 | 98.41 133 | 98.09 157 | 99.36 57 | 99.51 83 | 98.79 60 | 97.68 190 | 99.38 104 | 95.76 261 | 98.81 158 | 98.82 176 | 98.36 44 | 99.82 132 | 94.75 247 | 99.77 105 | 99.48 117 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
PVSNet_BlendedMVS | | | 97.55 203 | 97.53 194 | 97.60 254 | 98.92 221 | 93.77 292 | 96.64 267 | 99.43 93 | 94.49 287 | 97.62 250 | 99.18 94 | 96.82 149 | 99.67 254 | 94.73 248 | 99.93 38 | 99.36 165 |
|
PVSNet_Blended | | | 96.88 243 | 96.68 238 | 97.47 261 | 98.92 221 | 93.77 292 | 94.71 338 | 99.43 93 | 90.98 336 | 97.62 250 | 97.36 301 | 96.82 149 | 99.67 254 | 94.73 248 | 99.56 181 | 98.98 236 |
|
MP-MVS | | | 98.46 129 | 98.09 157 | 99.54 25 | 99.57 61 | 99.22 19 | 98.50 101 | 99.19 173 | 97.61 165 | 97.58 254 | 98.66 196 | 97.40 104 | 99.88 65 | 94.72 250 | 99.60 165 | 99.54 87 |
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
LF4IMVS | | | 97.90 176 | 97.69 183 | 98.52 183 | 99.17 170 | 97.66 151 | 97.19 235 | 99.47 80 | 96.31 244 | 97.85 227 | 98.20 249 | 96.71 158 | 99.52 307 | 94.62 251 | 99.72 124 | 98.38 290 |
|
testpf | | | 89.08 340 | 90.27 340 | 85.50 353 | 94.03 368 | 82.85 363 | 96.87 254 | 91.09 363 | 91.61 328 | 90.96 363 | 94.86 355 | 66.15 370 | 95.83 363 | 94.58 252 | 92.27 362 | 77.82 364 |
|
CostFormer | | | 93.97 319 | 93.78 311 | 94.51 334 | 97.53 335 | 85.83 350 | 97.98 159 | 95.96 327 | 89.29 347 | 94.99 344 | 98.63 205 | 78.63 345 | 99.62 274 | 94.54 253 | 96.50 343 | 98.09 299 |
|
thisisatest0515 | | | 94.12 314 | 93.16 322 | 96.97 278 | 98.60 279 | 92.90 303 | 93.77 351 | 90.61 364 | 94.10 300 | 96.91 291 | 95.87 330 | 74.99 359 | 99.80 157 | 94.52 254 | 99.12 252 | 98.20 294 |
|
旧先验2 | | | | | | | | 95.76 311 | | 88.56 350 | 97.52 260 | | | 99.66 262 | 94.48 255 | | |
|
CLD-MVS | | | 97.49 206 | 97.16 215 | 98.48 190 | 99.07 187 | 97.03 181 | 94.71 338 | 99.21 163 | 94.46 289 | 98.06 213 | 97.16 305 | 97.57 89 | 99.48 317 | 94.46 256 | 99.78 101 | 98.95 240 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
AllTest | | | 98.44 131 | 98.20 141 | 99.16 86 | 99.50 86 | 98.55 77 | 98.25 125 | 99.58 35 | 96.80 224 | 98.88 147 | 99.06 123 | 97.65 84 | 99.57 292 | 94.45 257 | 99.61 163 | 99.37 159 |
|
TestCases | | | | | 99.16 86 | 99.50 86 | 98.55 77 | | 99.58 35 | 96.80 224 | 98.88 147 | 99.06 123 | 97.65 84 | 99.57 292 | 94.45 257 | 99.61 163 | 99.37 159 |
|
HQP_MVS | | | 97.99 173 | 97.67 184 | 98.93 122 | 99.19 163 | 97.65 152 | 97.77 181 | 99.27 147 | 98.20 127 | 97.79 241 | 97.98 264 | 94.90 226 | 99.70 239 | 94.42 259 | 99.51 192 | 99.45 133 |
|
plane_prior5 | | | | | | | | | 99.27 147 | | | | | 99.70 239 | 94.42 259 | 99.51 192 | 99.45 133 |
|
JIA-IIPM | | | 95.52 278 | 95.03 284 | 97.00 276 | 96.85 352 | 94.03 280 | 96.93 248 | 95.82 328 | 99.20 51 | 94.63 346 | 99.71 13 | 83.09 324 | 99.60 281 | 94.42 259 | 94.64 354 | 97.36 329 |
|
cascas | | | 94.79 298 | 94.33 299 | 96.15 310 | 96.02 363 | 92.36 310 | 92.34 359 | 99.26 152 | 85.34 358 | 95.08 343 | 94.96 351 | 92.96 265 | 98.53 359 | 94.41 262 | 98.59 286 | 97.56 325 |
|
TinyColmap | | | 97.89 178 | 97.98 166 | 97.60 254 | 98.86 233 | 94.35 273 | 96.21 288 | 99.44 88 | 97.45 185 | 99.06 112 | 98.88 163 | 97.99 68 | 99.28 341 | 94.38 263 | 99.58 172 | 99.18 213 |
|
test_post1 | | | | | | | | 97.59 204 | | | | 20.48 370 | 83.07 325 | 99.66 262 | 94.16 264 | | |
|
test_prior3 | | | 97.48 208 | 97.00 220 | 98.95 119 | 98.69 264 | 97.95 126 | 95.74 313 | 99.03 209 | 96.48 237 | 96.11 318 | 97.63 283 | 95.92 199 | 99.59 285 | 94.16 264 | 99.20 234 | 99.30 185 |
|
test_prior2 | | | | | | | | 95.74 313 | | 96.48 237 | 96.11 318 | 97.63 283 | 95.92 199 | | 94.16 264 | 99.20 234 | |
|
tpmvs | | | 95.02 288 | 95.25 278 | 94.33 335 | 96.39 359 | 85.87 348 | 98.08 140 | 96.83 316 | 95.46 272 | 95.51 337 | 98.69 190 | 85.91 304 | 99.53 303 | 94.16 264 | 96.23 346 | 97.58 324 |
|
LCM-MVSNet-Re | | | 98.64 97 | 98.48 104 | 99.11 93 | 98.85 236 | 98.51 82 | 98.49 102 | 99.83 3 | 98.37 112 | 99.69 17 | 99.46 52 | 98.21 53 | 99.92 33 | 94.13 268 | 99.30 221 | 98.91 247 |
|
MSDG | | | 97.71 191 | 97.52 195 | 98.28 213 | 98.91 224 | 96.82 188 | 94.42 343 | 99.37 108 | 97.65 161 | 98.37 199 | 98.29 242 | 97.40 104 | 99.33 334 | 94.09 269 | 99.22 231 | 98.68 278 |
|
MVS-HIRNet | | | 94.32 308 | 95.62 269 | 90.42 351 | 98.46 292 | 75.36 368 | 96.29 284 | 89.13 367 | 95.25 275 | 95.38 339 | 99.75 6 | 92.88 267 | 99.19 344 | 94.07 270 | 99.39 207 | 96.72 342 |
|
DP-MVS Recon | | | 97.33 217 | 96.92 223 | 98.57 173 | 99.09 183 | 97.99 118 | 96.79 256 | 99.35 119 | 93.18 309 | 97.71 245 | 98.07 260 | 95.00 225 | 99.31 336 | 93.97 271 | 99.13 249 | 98.42 288 |
|
new_pmnet | | | 96.99 240 | 96.76 232 | 97.67 247 | 98.72 255 | 94.89 256 | 95.95 303 | 98.20 281 | 92.62 316 | 98.55 186 | 98.54 219 | 94.88 229 | 99.52 307 | 93.96 272 | 99.44 203 | 98.59 281 |
|
MDTV_nov1_ep13 | | | | 95.22 279 | | 97.06 348 | 83.20 361 | 97.74 185 | 96.16 325 | 94.37 293 | 96.99 287 | 98.83 173 | 83.95 320 | 99.53 303 | 93.90 273 | 97.95 321 | |
|
WTY-MVS | | | 96.67 253 | 96.27 257 | 97.87 237 | 98.81 246 | 94.61 263 | 96.77 258 | 97.92 289 | 94.94 281 | 97.12 280 | 97.74 276 | 91.11 279 | 99.82 132 | 93.89 274 | 98.15 306 | 99.18 213 |
|
Vis-MVSNet (Re-imp) | | | 97.46 209 | 97.16 215 | 98.34 207 | 99.55 72 | 96.10 220 | 98.94 65 | 98.44 273 | 98.32 118 | 98.16 206 | 98.62 207 | 88.76 291 | 99.73 227 | 93.88 275 | 99.79 97 | 99.18 213 |
|
ITE_SJBPF | | | | | 98.87 130 | 99.22 147 | 98.48 84 | | 99.35 119 | 97.50 175 | 98.28 201 | 98.60 210 | 97.64 87 | 99.35 331 | 93.86 276 | 99.27 226 | 98.79 265 |
|
CPTT-MVS | | | 97.84 187 | 97.36 207 | 99.27 74 | 99.31 131 | 98.46 85 | 98.29 121 | 99.27 147 | 94.90 282 | 97.83 232 | 98.37 233 | 94.90 226 | 99.84 104 | 93.85 277 | 99.54 184 | 99.51 99 |
|
APD-MVS | | | 98.10 163 | 97.67 184 | 99.42 51 | 99.11 179 | 98.93 55 | 97.76 183 | 99.28 142 | 94.97 280 | 98.72 165 | 98.77 182 | 97.04 128 | 99.85 88 | 93.79 278 | 99.54 184 | 99.49 111 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
agg_prior1 | | | 97.06 235 | 96.40 251 | 99.03 109 | 98.68 266 | 97.99 118 | 95.76 311 | 99.01 216 | 91.73 325 | 95.59 329 | 97.50 290 | 96.49 171 | 99.77 201 | 93.71 279 | 99.14 246 | 99.34 172 |
|
train_agg | | | 97.10 232 | 96.45 250 | 99.07 100 | 98.71 257 | 98.08 111 | 95.96 300 | 99.03 209 | 91.64 326 | 95.85 325 | 97.53 287 | 96.47 172 | 99.76 207 | 93.67 280 | 99.16 242 | 99.36 165 |
|
agg_prior3 | | | 96.95 242 | 96.27 257 | 99.00 115 | 98.68 266 | 97.91 129 | 95.96 300 | 99.01 216 | 90.74 338 | 95.60 328 | 97.45 295 | 96.14 184 | 99.74 222 | 93.67 280 | 99.16 242 | 99.36 165 |
|
PVSNet | | 93.40 17 | 95.67 274 | 95.70 266 | 95.57 323 | 98.83 241 | 88.57 338 | 92.50 357 | 97.72 293 | 92.69 315 | 96.49 312 | 96.44 319 | 93.72 258 | 99.43 324 | 93.61 282 | 99.28 225 | 98.71 272 |
|
test0.0.03 1 | | | 94.51 304 | 93.69 314 | 96.99 277 | 96.05 361 | 93.61 295 | 94.97 333 | 93.49 347 | 96.17 248 | 97.57 256 | 94.88 352 | 82.30 327 | 99.01 352 | 93.60 283 | 94.17 359 | 98.37 292 |
|
testdata | | | | | 98.09 223 | 98.93 217 | 95.40 244 | | 98.80 251 | 90.08 343 | 97.45 265 | 98.37 233 | 95.26 219 | 99.70 239 | 93.58 284 | 98.95 267 | 99.17 217 |
|
MDTV_nov1_ep13_2view | | | | | | | 74.92 369 | 97.69 189 | | 90.06 344 | 97.75 244 | | 85.78 306 | | 93.52 285 | | 98.69 275 |
|
TAPA-MVS | | 96.21 11 | 96.63 255 | 95.95 262 | 98.65 157 | 98.93 217 | 98.09 108 | 96.93 248 | 99.28 142 | 83.58 360 | 98.13 209 | 97.78 274 | 96.13 185 | 99.40 325 | 93.52 285 | 99.29 224 | 98.45 285 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
OMC-MVS | | | 97.88 180 | 97.49 197 | 99.04 108 | 98.89 230 | 98.63 69 | 96.94 247 | 99.25 153 | 95.02 278 | 98.53 188 | 98.51 221 | 97.27 112 | 99.47 318 | 93.50 287 | 99.51 192 | 99.01 233 |
|
PatchMatch-RL | | | 97.24 225 | 96.78 231 | 98.61 165 | 99.03 200 | 97.83 136 | 96.36 281 | 99.06 200 | 93.49 308 | 97.36 275 | 97.78 274 | 95.75 205 | 99.49 314 | 93.44 288 | 98.77 274 | 98.52 282 |
|
114514_t | | | 96.50 261 | 95.77 264 | 98.69 154 | 99.48 97 | 97.43 163 | 97.84 176 | 99.55 53 | 81.42 362 | 96.51 309 | 98.58 212 | 95.53 211 | 99.67 254 | 93.41 289 | 99.58 172 | 98.98 236 |
|
dp | | | 93.47 324 | 93.59 317 | 93.13 349 | 96.64 354 | 81.62 366 | 97.66 192 | 96.42 323 | 92.80 314 | 96.11 318 | 98.64 201 | 78.55 346 | 99.59 285 | 93.31 290 | 92.18 363 | 98.16 296 |
|
test9_res | | | | | | | | | | | | | | | 93.28 291 | 99.15 245 | 99.38 158 |
|
IB-MVS | | 91.63 19 | 92.24 334 | 90.90 337 | 96.27 300 | 97.22 346 | 91.24 330 | 94.36 344 | 93.33 349 | 92.37 319 | 92.24 359 | 94.58 356 | 66.20 369 | 99.89 57 | 93.16 292 | 94.63 355 | 97.66 316 |
Christian Sormann, Mattia Rossi, Andreas Kuhn and Friedrich Fraundorfer: IB-MVS: An Iterative Algorithm for Deep Multi-View Stereo based on Binary Decisions. BMVC 2021 |
tfpn1000 | | | 94.81 297 | 94.25 300 | 96.47 297 | 99.01 204 | 93.47 297 | 98.56 91 | 92.30 359 | 96.17 248 | 97.90 221 | 96.29 321 | 76.70 355 | 99.77 201 | 93.02 293 | 98.29 298 | 96.16 347 |
|
OpenMVS | | 96.65 7 | 97.09 233 | 96.68 238 | 98.32 208 | 98.32 301 | 97.16 176 | 98.86 72 | 99.37 108 | 89.48 345 | 96.29 316 | 99.15 105 | 96.56 167 | 99.90 47 | 92.90 294 | 99.20 234 | 97.89 303 |
|
ADS-MVSNet2 | | | 95.43 281 | 94.98 285 | 96.76 288 | 98.14 313 | 91.74 314 | 97.92 165 | 97.76 291 | 90.23 339 | 96.51 309 | 98.91 154 | 85.61 307 | 99.85 88 | 92.88 295 | 96.90 338 | 98.69 275 |
|
ADS-MVSNet | | | 95.24 284 | 94.93 287 | 96.18 306 | 98.14 313 | 90.10 334 | 97.92 165 | 97.32 302 | 90.23 339 | 96.51 309 | 98.91 154 | 85.61 307 | 99.74 222 | 92.88 295 | 96.90 338 | 98.69 275 |
|
BP-MVS | | | | | | | | | | | | | | | 92.82 297 | | |
|
HQP-MVS | | | 97.00 239 | 96.49 249 | 98.55 178 | 98.67 269 | 96.79 189 | 96.29 284 | 99.04 207 | 96.05 254 | 95.55 333 | 96.84 310 | 93.84 252 | 99.54 301 | 92.82 297 | 99.26 228 | 99.32 178 |
|
testdata2 | | | | | | | | | | | | | | 99.79 179 | 92.80 299 | | |
|
CDPH-MVS | | | 97.26 222 | 96.66 241 | 99.07 100 | 99.00 205 | 98.15 104 | 96.03 294 | 99.01 216 | 91.21 335 | 97.79 241 | 97.85 271 | 96.89 144 | 99.69 243 | 92.75 300 | 99.38 208 | 99.39 152 |
|
æ–°å‡ ä½•1 | | | | | 98.91 125 | 98.94 215 | 97.76 144 | | 98.76 254 | 87.58 353 | 96.75 301 | 98.10 256 | 94.80 233 | 99.78 190 | 92.73 301 | 99.00 262 | 99.20 205 |
|
F-COLMAP | | | 97.30 219 | 96.68 238 | 99.14 89 | 99.19 163 | 98.39 89 | 97.27 227 | 99.30 139 | 92.93 311 | 96.62 304 | 98.00 262 | 95.73 206 | 99.68 248 | 92.62 302 | 98.46 293 | 99.35 170 |
|
原ACMM1 | | | | | 98.35 205 | 98.90 225 | 96.25 215 | | 98.83 248 | 92.48 317 | 96.07 321 | 98.10 256 | 95.39 217 | 99.71 237 | 92.61 303 | 98.99 263 | 99.08 223 |
|
agg_prior2 | | | | | | | | | | | | | | | 92.50 304 | 99.16 242 | 99.37 159 |
|
test1235678 | | | 97.06 235 | 96.84 229 | 97.73 245 | 98.55 285 | 94.46 271 | 94.80 336 | 99.36 113 | 96.85 223 | 98.83 153 | 98.26 243 | 92.72 269 | 99.82 132 | 92.49 305 | 99.70 131 | 98.91 247 |
|
æ— å…ˆéªŒ | | | | | | | | 95.74 313 | 98.74 259 | 89.38 346 | | | | 99.73 227 | 92.38 306 | | 99.22 203 |
|
1121 | | | 96.73 250 | 96.00 260 | 98.91 125 | 98.95 214 | 97.76 144 | 98.07 142 | 98.73 260 | 87.65 352 | 96.54 306 | 98.13 250 | 94.52 240 | 99.73 227 | 92.38 306 | 99.02 259 | 99.24 198 |
|
CMPMVS | | 75.91 23 | 96.29 264 | 95.44 273 | 98.84 134 | 96.25 360 | 98.69 67 | 97.02 242 | 99.12 192 | 88.90 348 | 97.83 232 | 98.86 166 | 89.51 287 | 98.90 355 | 91.92 308 | 99.51 192 | 98.92 245 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
BH-untuned | | | 96.83 245 | 96.75 233 | 97.08 272 | 98.74 253 | 93.33 298 | 96.71 262 | 98.26 279 | 96.72 227 | 98.44 192 | 97.37 300 | 95.20 220 | 99.47 318 | 91.89 309 | 97.43 329 | 98.44 286 |
|
gm-plane-assit | | | | | | 94.83 365 | 81.97 365 | | | 88.07 351 | | 94.99 347 | | 99.60 281 | 91.76 310 | | |
|
CNLPA | | | 97.17 229 | 96.71 236 | 98.55 178 | 98.56 283 | 98.05 115 | 96.33 282 | 98.93 228 | 96.91 220 | 97.06 284 | 97.39 298 | 94.38 243 | 99.45 322 | 91.66 311 | 99.18 240 | 98.14 297 |
|
MIMVSNet | | | 96.62 256 | 96.25 259 | 97.71 246 | 99.04 197 | 94.66 261 | 99.16 42 | 96.92 313 | 97.23 207 | 97.87 223 | 99.10 114 | 86.11 303 | 99.65 268 | 91.65 312 | 99.21 233 | 98.82 259 |
|
1314 | | | 95.74 273 | 95.60 270 | 96.17 307 | 97.53 335 | 92.75 304 | 98.07 142 | 98.31 278 | 91.22 334 | 94.25 349 | 96.68 313 | 95.53 211 | 99.03 349 | 91.64 313 | 97.18 335 | 96.74 341 |
|
tpmp4_e23 | | | 92.91 329 | 92.45 328 | 94.29 336 | 97.41 340 | 85.62 352 | 97.95 162 | 96.77 317 | 87.55 354 | 91.33 362 | 98.57 213 | 74.21 360 | 99.59 285 | 91.62 314 | 96.64 342 | 97.65 323 |
|
PMVS | | 91.26 20 | 97.86 182 | 97.94 170 | 97.65 249 | 99.71 33 | 97.94 128 | 98.52 96 | 98.68 263 | 98.99 76 | 97.52 260 | 99.35 69 | 97.41 103 | 98.18 361 | 91.59 315 | 99.67 149 | 96.82 340 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
tpm cat1 | | | 93.29 326 | 93.13 324 | 93.75 342 | 97.39 342 | 84.74 356 | 97.39 218 | 97.65 296 | 83.39 361 | 94.16 350 | 98.41 229 | 82.86 326 | 99.39 327 | 91.56 316 | 95.35 352 | 97.14 332 |
|
conf0.01 | | | 94.82 295 | 94.07 301 | 97.06 274 | 99.21 153 | 94.53 265 | 98.47 108 | 92.69 350 | 95.61 263 | 97.81 235 | 95.54 333 | 77.71 349 | 99.80 157 | 91.49 317 | 98.11 308 | 96.86 336 |
|
conf0.002 | | | 94.82 295 | 94.07 301 | 97.06 274 | 99.21 153 | 94.53 265 | 98.47 108 | 92.69 350 | 95.61 263 | 97.81 235 | 95.54 333 | 77.71 349 | 99.80 157 | 91.49 317 | 98.11 308 | 96.86 336 |
|
thresconf0.02 | | | 94.70 299 | 94.07 301 | 96.58 290 | 99.21 153 | 94.53 265 | 98.47 108 | 92.69 350 | 95.61 263 | 97.81 235 | 95.54 333 | 77.71 349 | 99.80 157 | 91.49 317 | 98.11 308 | 95.42 355 |
|
tfpn_n400 | | | 94.70 299 | 94.07 301 | 96.58 290 | 99.21 153 | 94.53 265 | 98.47 108 | 92.69 350 | 95.61 263 | 97.81 235 | 95.54 333 | 77.71 349 | 99.80 157 | 91.49 317 | 98.11 308 | 95.42 355 |
|
tfpnconf | | | 94.70 299 | 94.07 301 | 96.58 290 | 99.21 153 | 94.53 265 | 98.47 108 | 92.69 350 | 95.61 263 | 97.81 235 | 95.54 333 | 77.71 349 | 99.80 157 | 91.49 317 | 98.11 308 | 95.42 355 |
|
tfpnview11 | | | 94.70 299 | 94.07 301 | 96.58 290 | 99.21 153 | 94.53 265 | 98.47 108 | 92.69 350 | 95.61 263 | 97.81 235 | 95.54 333 | 77.71 349 | 99.80 157 | 91.49 317 | 98.11 308 | 95.42 355 |
|
tfpn_ndepth | | | 94.12 314 | 93.51 318 | 95.94 314 | 98.86 233 | 93.60 296 | 98.16 133 | 91.90 361 | 94.66 286 | 97.41 268 | 95.24 343 | 76.24 356 | 99.73 227 | 91.21 323 | 97.88 323 | 94.50 360 |
|
HY-MVS | | 95.94 13 | 95.90 270 | 95.35 275 | 97.55 257 | 97.95 319 | 94.79 257 | 98.81 75 | 96.94 312 | 92.28 321 | 95.17 341 | 98.57 213 | 89.90 285 | 99.75 213 | 91.20 324 | 97.33 334 | 98.10 298 |
|
MG-MVS | | | 96.77 249 | 96.61 243 | 97.26 269 | 98.31 302 | 93.06 300 | 95.93 304 | 98.12 284 | 96.45 239 | 97.92 218 | 98.73 186 | 93.77 257 | 99.39 327 | 91.19 325 | 99.04 258 | 99.33 177 |
|
AdaColmap | | | 97.14 231 | 96.71 236 | 98.46 192 | 98.34 300 | 97.80 142 | 96.95 246 | 98.93 228 | 95.58 269 | 96.92 289 | 97.66 280 | 95.87 202 | 99.53 303 | 90.97 326 | 99.14 246 | 98.04 300 |
|
PLC | | 94.65 16 | 96.51 259 | 95.73 265 | 98.85 133 | 98.75 251 | 97.91 129 | 96.42 279 | 99.06 200 | 90.94 337 | 95.59 329 | 97.38 299 | 94.41 242 | 99.59 285 | 90.93 327 | 98.04 320 | 99.05 227 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
tpm2 | | | 93.09 328 | 92.58 327 | 94.62 332 | 97.56 333 | 86.53 347 | 97.66 192 | 95.79 329 | 86.15 356 | 94.07 353 | 98.23 247 | 75.95 357 | 99.53 303 | 90.91 328 | 96.86 341 | 97.81 309 |
|
QAPM | | | 97.31 218 | 96.81 230 | 98.82 136 | 98.80 248 | 97.49 159 | 99.06 53 | 99.19 173 | 90.22 341 | 97.69 247 | 99.16 101 | 96.91 139 | 99.90 47 | 90.89 329 | 99.41 205 | 99.07 225 |
|
test12356 | | | 94.85 294 | 95.12 282 | 94.03 340 | 98.25 305 | 83.12 362 | 93.85 349 | 99.33 128 | 94.17 298 | 97.28 276 | 97.20 302 | 85.83 305 | 99.75 213 | 90.85 330 | 99.33 215 | 99.22 203 |
|
PAPM_NR | | | 96.82 247 | 96.32 254 | 98.30 211 | 99.07 187 | 96.69 196 | 97.48 214 | 98.76 254 | 95.81 260 | 96.61 305 | 96.47 318 | 94.12 250 | 99.17 345 | 90.82 331 | 97.78 324 | 99.06 226 |
|
BH-RMVSNet | | | 96.83 245 | 96.58 245 | 97.58 256 | 98.47 291 | 94.05 279 | 96.67 265 | 97.36 299 | 96.70 231 | 97.87 223 | 97.98 264 | 95.14 222 | 99.44 323 | 90.47 332 | 98.58 287 | 99.25 195 |
|
API-MVS | | | 97.04 238 | 96.91 225 | 97.42 264 | 97.88 324 | 98.23 100 | 98.18 130 | 98.50 271 | 97.57 169 | 97.39 272 | 96.75 312 | 96.77 153 | 99.15 347 | 90.16 333 | 99.02 259 | 94.88 359 |
|
E-PMN | | | 94.17 312 | 94.37 297 | 93.58 344 | 96.86 351 | 85.71 351 | 90.11 362 | 97.07 306 | 98.17 130 | 97.82 234 | 97.19 303 | 84.62 314 | 98.94 353 | 89.77 334 | 97.68 326 | 96.09 351 |
|
MAR-MVS | | | 96.47 262 | 95.70 266 | 98.79 139 | 97.92 321 | 99.12 41 | 98.28 122 | 98.60 268 | 92.16 323 | 95.54 336 | 96.17 322 | 94.77 236 | 99.52 307 | 89.62 335 | 98.23 299 | 97.72 315 |
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 |
wuyk23d | | | 96.06 268 | 97.62 191 | 91.38 350 | 98.65 275 | 98.57 76 | 98.85 73 | 96.95 311 | 96.86 222 | 99.90 4 | 99.16 101 | 99.18 11 | 98.40 360 | 89.23 336 | 99.77 105 | 77.18 365 |
|
PNet_i23d | | | 91.80 337 | 92.35 329 | 90.14 352 | 98.65 275 | 73.10 371 | 89.22 364 | 99.02 213 | 95.23 277 | 97.87 223 | 97.82 273 | 78.45 348 | 98.89 356 | 88.73 337 | 86.14 364 | 98.42 288 |
|
OpenMVS_ROB | | 95.38 14 | 95.84 272 | 95.18 281 | 97.81 239 | 98.41 296 | 97.15 177 | 97.37 219 | 98.62 267 | 83.86 359 | 98.65 170 | 98.37 233 | 94.29 245 | 99.68 248 | 88.41 338 | 98.62 285 | 96.60 343 |
|
BH-w/o | | | 95.13 285 | 94.89 288 | 95.86 316 | 98.20 311 | 91.31 328 | 95.65 316 | 97.37 298 | 93.64 304 | 96.52 308 | 95.70 331 | 93.04 264 | 99.02 350 | 88.10 339 | 95.82 348 | 97.24 331 |
|
testus | | | 95.52 278 | 95.32 276 | 96.13 311 | 97.91 322 | 89.49 337 | 93.62 352 | 99.61 29 | 92.41 318 | 97.38 274 | 95.42 342 | 94.72 237 | 99.63 271 | 88.06 340 | 98.72 276 | 99.26 193 |
|
EMVS | | | 93.83 321 | 94.02 307 | 93.23 348 | 96.83 353 | 84.96 355 | 89.77 363 | 96.32 324 | 97.92 138 | 97.43 267 | 96.36 320 | 86.17 301 | 98.93 354 | 87.68 341 | 97.73 325 | 95.81 352 |
|
gg-mvs-nofinetune | | | 92.37 332 | 91.20 336 | 95.85 317 | 95.80 364 | 92.38 309 | 99.31 20 | 81.84 371 | 99.75 4 | 91.83 360 | 99.74 7 | 68.29 365 | 99.02 350 | 87.15 342 | 97.12 336 | 96.16 347 |
|
TR-MVS | | | 95.55 277 | 95.12 282 | 96.86 286 | 97.54 334 | 93.94 282 | 96.49 275 | 96.53 322 | 94.36 294 | 97.03 286 | 96.61 314 | 94.26 246 | 99.16 346 | 86.91 343 | 96.31 345 | 97.47 328 |
|
PVSNet_0 | | 89.98 21 | 91.15 339 | 90.30 339 | 93.70 343 | 97.72 326 | 84.34 360 | 90.24 361 | 97.42 297 | 90.20 342 | 93.79 355 | 93.09 363 | 90.90 280 | 98.89 356 | 86.57 344 | 72.76 365 | 97.87 305 |
|
tmp_tt | | | 78.77 342 | 78.73 343 | 78.90 354 | 58.45 371 | 74.76 370 | 94.20 345 | 78.26 373 | 39.16 366 | 86.71 367 | 92.82 364 | 80.50 331 | 75.19 368 | 86.16 345 | 92.29 361 | 86.74 363 |
|
view600 | | | 94.87 290 | 94.41 292 | 96.26 301 | 99.22 147 | 91.37 321 | 98.49 102 | 94.45 335 | 98.75 92 | 97.85 227 | 95.98 325 | 80.38 332 | 99.75 213 | 86.06 346 | 98.49 289 | 97.66 316 |
|
view800 | | | 94.87 290 | 94.41 292 | 96.26 301 | 99.22 147 | 91.37 321 | 98.49 102 | 94.45 335 | 98.75 92 | 97.85 227 | 95.98 325 | 80.38 332 | 99.75 213 | 86.06 346 | 98.49 289 | 97.66 316 |
|
conf0.05thres1000 | | | 94.87 290 | 94.41 292 | 96.26 301 | 99.22 147 | 91.37 321 | 98.49 102 | 94.45 335 | 98.75 92 | 97.85 227 | 95.98 325 | 80.38 332 | 99.75 213 | 86.06 346 | 98.49 289 | 97.66 316 |
|
tfpn | | | 94.87 290 | 94.41 292 | 96.26 301 | 99.22 147 | 91.37 321 | 98.49 102 | 94.45 335 | 98.75 92 | 97.85 227 | 95.98 325 | 80.38 332 | 99.75 213 | 86.06 346 | 98.49 289 | 97.66 316 |
|
PAPR | | | 95.29 282 | 94.47 290 | 97.75 243 | 97.50 339 | 95.14 252 | 94.89 335 | 98.71 262 | 91.39 333 | 95.35 340 | 95.48 339 | 94.57 239 | 99.14 348 | 84.95 350 | 97.37 330 | 98.97 239 |
|
test2356 | | | 91.64 338 | 90.19 341 | 96.00 312 | 94.30 367 | 89.58 336 | 90.84 360 | 96.68 318 | 91.76 324 | 95.48 338 | 93.69 361 | 67.05 367 | 99.52 307 | 84.83 351 | 97.08 337 | 98.91 247 |
|
thres600view7 | | | 94.45 305 | 93.83 310 | 96.29 299 | 99.06 190 | 91.53 317 | 97.99 158 | 94.24 342 | 98.34 114 | 97.44 266 | 95.01 346 | 79.84 337 | 99.67 254 | 84.33 352 | 98.23 299 | 97.66 316 |
|
tfpn111 | | | 94.33 307 | 93.78 311 | 95.96 313 | 99.06 190 | 91.35 325 | 98.03 148 | 94.24 342 | 98.33 115 | 97.40 269 | 94.98 348 | 79.84 337 | 99.68 248 | 83.94 353 | 98.22 301 | 96.86 336 |
|
MVS | | | 93.19 327 | 92.09 331 | 96.50 296 | 96.91 350 | 94.03 280 | 98.07 142 | 98.06 286 | 68.01 364 | 94.56 347 | 96.48 317 | 95.96 197 | 99.30 338 | 83.84 354 | 96.89 340 | 96.17 346 |
|
conf200view11 | | | 94.24 310 | 93.67 315 | 95.94 314 | 99.06 190 | 91.35 325 | 98.03 148 | 94.24 342 | 98.33 115 | 97.40 269 | 94.98 348 | 79.84 337 | 99.62 274 | 83.05 355 | 98.08 316 | 96.86 336 |
|
thres100view900 | | | 94.19 311 | 93.67 315 | 95.75 319 | 99.06 190 | 91.35 325 | 98.03 148 | 94.24 342 | 98.33 115 | 97.40 269 | 94.98 348 | 79.84 337 | 99.62 274 | 83.05 355 | 98.08 316 | 96.29 344 |
|
tfpn200view9 | | | 94.03 317 | 93.44 319 | 95.78 318 | 98.93 217 | 91.44 319 | 97.60 202 | 94.29 340 | 97.94 136 | 97.10 281 | 94.31 357 | 79.67 341 | 99.62 274 | 83.05 355 | 98.08 316 | 96.29 344 |
|
thres400 | | | 94.14 313 | 93.44 319 | 96.24 305 | 98.93 217 | 91.44 319 | 97.60 202 | 94.29 340 | 97.94 136 | 97.10 281 | 94.31 357 | 79.67 341 | 99.62 274 | 83.05 355 | 98.08 316 | 97.66 316 |
|
thres200 | | | 93.72 322 | 93.14 323 | 95.46 324 | 98.66 274 | 91.29 329 | 96.61 270 | 94.63 334 | 97.39 190 | 96.83 298 | 93.71 360 | 79.88 336 | 99.56 295 | 82.40 359 | 98.13 307 | 95.54 354 |
|
GG-mvs-BLEND | | | | | 94.76 331 | 94.54 366 | 92.13 312 | 99.31 20 | 80.47 372 | | 88.73 366 | 91.01 365 | 67.59 366 | 98.16 362 | 82.30 360 | 94.53 356 | 93.98 361 |
|
MVE | | 83.40 22 | 92.50 331 | 91.92 333 | 94.25 337 | 98.83 241 | 91.64 316 | 92.71 356 | 83.52 370 | 95.92 258 | 86.46 368 | 95.46 340 | 95.20 220 | 95.40 365 | 80.51 361 | 98.64 283 | 95.73 353 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
PCF-MVS | | 92.86 18 | 94.36 306 | 93.00 325 | 98.42 196 | 98.70 261 | 97.56 156 | 93.16 355 | 99.11 195 | 79.59 363 | 97.55 257 | 97.43 296 | 92.19 273 | 99.73 227 | 79.85 362 | 99.45 202 | 97.97 302 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
FPMVS | | | 93.44 325 | 92.23 330 | 97.08 272 | 99.25 140 | 97.86 134 | 95.61 317 | 97.16 305 | 92.90 312 | 93.76 356 | 98.65 198 | 75.94 358 | 95.66 364 | 79.30 363 | 97.49 327 | 97.73 314 |
|
DeepMVS_CX | | | | | 93.44 346 | 98.24 307 | 94.21 276 | | 94.34 339 | 64.28 365 | 91.34 361 | 94.87 354 | 89.45 289 | 92.77 367 | 77.54 364 | 93.14 360 | 93.35 362 |
|
PAPM | | | 91.88 336 | 90.34 338 | 96.51 295 | 98.06 316 | 92.56 305 | 92.44 358 | 97.17 304 | 86.35 355 | 90.38 364 | 96.01 323 | 86.61 297 | 99.21 343 | 70.65 365 | 95.43 351 | 97.75 313 |
|
test123 | | | 17.04 347 | 20.11 348 | 7.82 357 | 10.25 373 | 4.91 372 | 94.80 336 | 4.47 375 | 4.93 367 | 10.00 370 | 24.28 368 | 9.69 374 | 3.64 369 | 10.14 366 | 12.43 368 | 14.92 366 |
|
testmvs | | | 17.12 346 | 20.53 347 | 6.87 358 | 12.05 372 | 4.20 373 | 93.62 352 | 6.73 374 | 4.62 368 | 10.41 369 | 24.33 367 | 8.28 375 | 3.56 370 | 9.69 367 | 15.07 366 | 12.86 367 |
|
test_part1 | | | | | 0.00 359 | | 0.00 374 | 0.00 365 | 99.28 142 | | | | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
v1.0 | | | 41.09 344 | 54.78 344 | 0.00 359 | 99.36 121 | 0.00 374 | 0.00 365 | 99.28 142 | 96.66 232 | 99.05 117 | 98.71 188 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
cdsmvs_eth3d_5k | | | 24.66 345 | 32.88 346 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 99.10 196 | 0.00 369 | 0.00 371 | 97.58 285 | 99.21 10 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
pcd_1.5k_mvsjas | | | 8.17 348 | 10.90 349 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 0.00 371 | 98.07 60 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
pcd1.5k->3k | | | 41.59 343 | 44.35 345 | 33.30 356 | 99.87 11 | 0.00 374 | 0.00 365 | 99.58 35 | 0.00 369 | 0.00 371 | 0.00 371 | 99.70 2 | 0.00 371 | 0.00 368 | 99.99 11 | 99.91 2 |
|
sosnet-low-res | | | 0.00 350 | 0.00 351 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 0.00 371 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
sosnet | | | 0.00 350 | 0.00 351 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 0.00 371 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
uncertanet | | | 0.00 350 | 0.00 351 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 0.00 371 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
Regformer | | | 0.00 350 | 0.00 351 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 0.00 371 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
ab-mvs-re | | | 8.12 349 | 10.83 350 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 97.48 292 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
uanet | | | 0.00 350 | 0.00 351 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 0.00 371 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
GSMVS | | | | | | | | | | | | | | | | | 98.81 260 |
|
test_part2 | | | | | | 99.36 121 | 99.10 44 | | | | 99.05 117 | | | | | | |
|
sam_mvs1 | | | | | | | | | | | | | 84.74 313 | | | | 98.81 260 |
|
sam_mvs | | | | | | | | | | | | | 84.29 319 | | | | |
|
MTGPA | | | | | | | | | 99.20 167 | | | | | | | | |
|
test_post | | | | | | | | | | | | 21.25 369 | 83.86 321 | 99.70 239 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 98.77 182 | 84.37 316 | 99.85 88 | | | |
|
MTMP | | | | | | | | 97.93 163 | 91.91 360 | | | | | | | | |
|
TEST9 | | | | | | 98.71 257 | 98.08 111 | 95.96 300 | 99.03 209 | 91.40 332 | 95.85 325 | 97.53 287 | 96.52 169 | 99.76 207 | | | |
|
test_8 | | | | | | 98.67 269 | 98.01 117 | 95.91 306 | 99.02 213 | 91.64 326 | 95.79 327 | 97.50 290 | 96.47 172 | 99.76 207 | | | |
|
agg_prior | | | | | | 98.68 266 | 97.99 118 | | 99.01 216 | | 95.59 329 | | | 99.77 201 | | | |
|
test_prior4 | | | | | | | 97.97 123 | 95.86 307 | | | | | | | | | |
|
test_prior | | | | | 98.95 119 | 98.69 264 | 97.95 126 | | 99.03 209 | | | | | 99.59 285 | | | 99.30 185 |
|
æ–°å‡ ä½•2 | | | | | | | | 95.93 304 | | | | | | | | | |
|
旧先验1 | | | | | | 98.82 244 | 97.45 162 | | 98.76 254 | | | 98.34 236 | 95.50 214 | | | 99.01 261 | 99.23 199 |
|
原ACMM2 | | | | | | | | 95.53 320 | | | | | | | | | |
|
test222 | | | | | | 98.92 221 | 96.93 186 | 95.54 319 | 98.78 253 | 85.72 357 | 96.86 297 | 98.11 255 | 94.43 241 | | | 99.10 254 | 99.23 199 |
|
segment_acmp | | | | | | | | | | | | | 97.02 132 | | | | |
|
testdata1 | | | | | | | | 95.44 324 | | 96.32 243 | | | | | | | |
|
test12 | | | | | 98.93 122 | 98.58 281 | 97.83 136 | | 98.66 264 | | 96.53 307 | | 95.51 213 | 99.69 243 | | 99.13 249 | 99.27 190 |
|
plane_prior7 | | | | | | 99.19 163 | 97.87 133 | | | | | | | | | | |
|
plane_prior6 | | | | | | 98.99 207 | 97.70 150 | | | | | | 94.90 226 | | | | |
|
plane_prior4 | | | | | | | | | | | | 97.98 264 | | | | | |
|
plane_prior3 | | | | | | | 97.78 143 | | | 97.41 188 | 97.79 241 | | | | | | |
|
plane_prior2 | | | | | | | | 97.77 181 | | 98.20 127 | | | | | | | |
|
plane_prior1 | | | | | | 99.05 195 | | | | | | | | | | | |
|
plane_prior | | | | | | | 97.65 152 | 97.07 241 | | 96.72 227 | | | | | | 99.36 209 | |
|
n2 | | | | | | | | | 0.00 376 | | | | | | | | |
|
nn | | | | | | | | | 0.00 376 | | | | | | | | |
|
door-mid | | | | | | | | | 99.57 42 | | | | | | | | |
|
test11 | | | | | | | | | 98.87 237 | | | | | | | | |
|
door | | | | | | | | | 99.41 97 | | | | | | | | |
|
HQP5-MVS | | | | | | | 96.79 189 | | | | | | | | | | |
|
HQP-NCC | | | | | | 98.67 269 | | 96.29 284 | | 96.05 254 | 95.55 333 | | | | | | |
|
ACMP_Plane | | | | | | 98.67 269 | | 96.29 284 | | 96.05 254 | 95.55 333 | | | | | | |
|
HQP4-MVS | | | | | | | | | | | 95.56 332 | | | 99.54 301 | | | 99.32 178 |
|
HQP3-MVS | | | | | | | | | 99.04 207 | | | | | | | 99.26 228 | |
|
HQP2-MVS | | | | | | | | | | | | | 93.84 252 | | | | |
|
NP-MVS | | | | | | 98.84 239 | 97.39 165 | | | | | 96.84 310 | | | | | |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 99.77 105 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 99.68 143 | |
|
Test By Simon | | | | | | | | | | | | | 96.52 169 | | | | |
|