This table lists the benchmark results for the high-res multi-view scenario. The following metrics are evaluated:

(*) For exact definitions, detailing how potentially incomplete ground truth is taken into account, see our paper.

The datasets are grouped into different categories, and result averages are computed for a category and method if results of the method are available for all datasets within the category. Note that the category "all" includes both the high-res multi-view and the low-res many-view scenarios.

Methods with suffix _ROB may participate in the Robust Vision Challenge.

Click a dataset result cell to show a visualization of the reconstruction. For training datasets, ground truth and accuracy / completeness visualizations are also available. The visualizations may not work with mobile browsers.




Method Infoallhigh-res
multi-view
indooroutdoorbotani.boulde.bridgedoorexhibi.lectur.living.loungeobserv.old co.statueterrac.
sort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysorted bysort bysort bysort bysort bysort by
LCM-MVSNet99.93 199.92 199.94 199.99 199.97 199.90 199.89 299.98 199.99 199.96 199.77 1100.00 199.81 1100.00 199.85 7
pmmvs699.67 399.70 399.60 1399.90 499.27 2199.53 799.76 899.64 1299.84 899.83 299.50 599.87 8799.36 1499.92 3799.64 41
UA-Net99.47 1199.40 1499.70 299.49 8699.29 1899.80 399.72 1099.82 399.04 11699.81 398.05 6999.96 898.85 4299.99 599.86 6
ANet_high99.57 799.67 599.28 8399.89 698.09 13499.14 4699.93 199.82 399.93 299.81 399.17 1299.94 2399.31 16100.00 199.82 9
UniMVSNet_ETH3D99.69 299.69 499.69 399.84 1499.34 1599.69 499.58 2899.90 299.86 799.78 599.58 399.95 1599.00 3499.95 1699.78 14
OurMVSNet-221017-099.37 2199.31 2299.53 3699.91 398.98 6599.63 699.58 2899.44 2999.78 1099.76 696.39 18299.92 3599.44 1399.92 3799.68 33
MVS-HIRNet94.32 30895.62 27990.42 35498.46 29075.36 37796.29 28289.13 37195.25 28095.38 34499.75 792.88 27499.19 35094.07 28999.39 22296.72 355
gg-mvs-nofinetune92.37 33291.20 33795.85 31895.80 37192.38 32599.31 2181.84 37799.75 591.83 36699.74 868.29 37199.02 35687.15 35797.12 34396.16 360
mvs_tets99.63 599.67 599.49 4999.88 798.61 9299.34 1599.71 1199.27 4499.90 499.74 899.68 299.97 399.55 899.99 599.88 3
test_djsdf99.52 999.51 999.53 3699.86 1198.74 8199.39 1399.56 4299.11 5799.70 1599.73 1099.00 1599.97 399.26 1899.98 999.89 2
anonymousdsp99.51 1099.47 1299.62 699.88 799.08 6399.34 1599.69 1598.93 8499.65 2299.72 1198.93 1999.95 1599.11 27100.00 199.82 9
PS-MVSNAJss99.46 1299.49 1099.35 7099.90 498.15 13099.20 3899.65 2099.48 2499.92 399.71 1298.07 6699.96 899.53 9100.00 199.93 1
JIA-IIPM95.52 29195.03 29897.00 28996.85 35694.03 29296.93 24695.82 34499.20 4994.63 35199.71 1283.09 34199.60 28494.42 27694.64 36397.36 346
Anonymous2023121199.27 2599.27 2499.26 8999.29 12898.18 12799.49 899.51 5899.70 899.80 999.68 1496.84 15599.83 14299.21 2399.91 4399.77 16
jajsoiax99.58 699.61 799.48 5199.87 1098.61 9299.28 3099.66 1999.09 6799.89 699.68 1499.53 499.97 399.50 1099.99 599.87 4
LTVRE_ROB98.40 199.67 399.71 299.56 2499.85 1399.11 5999.90 199.78 699.63 1499.78 1099.67 1699.48 699.81 16799.30 1799.97 1199.77 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
v7n99.53 899.57 899.41 6199.88 798.54 10099.45 999.61 2499.66 1199.68 1999.66 1798.44 4099.95 1599.73 299.96 1499.75 22
K. test v398.00 16597.66 18499.03 12899.79 1997.56 18699.19 4292.47 36299.62 1799.52 3599.66 1789.61 29699.96 899.25 2099.81 7299.56 74
SixPastTwentyTwo98.75 7398.62 7599.16 10299.83 1597.96 15599.28 3098.20 29899.37 3599.70 1599.65 1992.65 27899.93 2899.04 3299.84 5999.60 52
DSMNet-mixed97.42 21297.60 19096.87 29799.15 16591.46 33498.54 9399.12 20192.87 32197.58 26199.63 2096.21 18999.90 4995.74 23999.54 18999.27 201
TransMVSNet (Re)99.44 1399.47 1299.36 6599.80 1798.58 9599.27 3299.57 3599.39 3399.75 1299.62 2199.17 1299.83 14299.06 3099.62 15899.66 36
Gipumacopyleft99.03 3799.16 3098.64 17699.94 298.51 10299.32 1799.75 999.58 2298.60 18699.62 2198.22 5599.51 31397.70 11299.73 11097.89 324
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
Baseline_NR-MVSNet98.98 4498.86 4799.36 6599.82 1698.55 9797.47 20999.57 3599.37 3599.21 8999.61 2396.76 16499.83 14298.06 8999.83 6599.71 26
TDRefinement99.42 1699.38 1599.55 2699.76 2399.33 1699.68 599.71 1199.38 3499.53 3399.61 2398.64 2999.80 17698.24 7899.84 5999.52 98
pm-mvs199.44 1399.48 1199.33 7699.80 1798.63 8999.29 2699.63 2199.30 4299.65 2299.60 2599.16 1499.82 15399.07 2999.83 6599.56 74
v1098.97 4599.11 3398.55 19499.44 10296.21 23898.90 6699.55 4698.73 9399.48 4099.60 2596.63 17199.83 14299.70 399.99 599.61 51
test111196.49 26796.82 23895.52 32799.42 10787.08 35899.22 3587.14 37299.11 5799.46 4399.58 2788.69 30399.86 9498.80 4599.95 1699.62 46
test250692.39 33191.89 33493.89 34499.38 11282.28 37399.32 1766.03 38099.08 6998.77 16699.57 2866.26 37799.84 12798.71 5399.95 1699.54 86
ECVR-MVScopyleft96.42 27096.61 25195.85 31899.38 11288.18 35399.22 3586.00 37499.08 6999.36 6099.57 2888.47 30899.82 15398.52 6499.95 1699.54 86
v899.01 3899.16 3098.57 18999.47 9696.31 23698.90 6699.47 7699.03 7399.52 3599.57 2896.93 15199.81 16799.60 499.98 999.60 52
MIMVSNet199.38 2099.32 2199.55 2699.86 1199.19 3799.41 1299.59 2699.59 2099.71 1499.57 2897.12 14099.90 4999.21 2399.87 5599.54 86
Anonymous2024052198.69 8398.87 4598.16 22999.77 2095.11 26999.08 5099.44 8499.34 3899.33 6599.55 3294.10 25699.94 2399.25 2099.96 1499.42 145
GBi-Net98.65 9198.47 9899.17 9998.90 21698.24 12099.20 3899.44 8498.59 10198.95 13299.55 3294.14 25299.86 9497.77 10699.69 13399.41 148
test198.65 9198.47 9899.17 9998.90 21698.24 12099.20 3899.44 8498.59 10198.95 13299.55 3294.14 25299.86 9497.77 10699.69 13399.41 148
FMVSNet199.17 3099.17 2999.17 9999.55 6798.24 12099.20 3899.44 8499.21 4699.43 4899.55 3297.82 8699.86 9498.42 7099.89 5199.41 148
KD-MVS_self_test99.25 2799.18 2899.44 5799.63 5099.06 6498.69 8099.54 5099.31 4099.62 2799.53 3697.36 12799.86 9499.24 2299.71 12299.39 157
new-patchmatchnet98.35 13498.74 5797.18 28399.24 13692.23 32896.42 27699.48 7098.30 11699.69 1799.53 3697.44 12299.82 15398.84 4399.77 9399.49 109
lessismore_v098.97 13599.73 2597.53 18886.71 37399.37 5899.52 3889.93 29499.92 3598.99 3599.72 11799.44 138
FC-MVSNet-test99.27 2599.25 2599.34 7399.77 2098.37 11199.30 2599.57 3599.61 1999.40 5399.50 3997.12 14099.85 10999.02 3399.94 2499.80 12
VDDNet98.21 14997.95 16399.01 13299.58 5397.74 17799.01 5797.29 32499.67 1098.97 12999.50 3990.45 29199.80 17697.88 10099.20 25299.48 119
DeepC-MVS97.60 498.97 4598.93 4399.10 11199.35 12197.98 15098.01 15399.46 7897.56 17299.54 3099.50 3998.97 1699.84 12798.06 8999.92 3799.49 109
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
test_part197.91 17097.46 20099.27 8698.80 24098.18 12799.07 5399.36 10999.75 599.63 2599.49 4282.20 34899.89 5998.87 4199.95 1699.74 24
XXY-MVS99.14 3299.15 3299.10 11199.76 2397.74 17798.85 7199.62 2298.48 10899.37 5899.49 4298.75 2499.86 9498.20 8199.80 8099.71 26
Vis-MVSNetpermissive99.34 2299.36 1699.27 8699.73 2598.26 11899.17 4399.78 699.11 5799.27 7699.48 4498.82 2199.95 1598.94 3699.93 2899.59 58
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
UGNet98.53 11498.45 10298.79 16097.94 32296.96 21899.08 5098.54 28399.10 6496.82 30599.47 4596.55 17499.84 12798.56 6399.94 2499.55 82
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
EU-MVSNet97.66 19498.50 9195.13 33399.63 5085.84 36298.35 11698.21 29798.23 12499.54 3099.46 4695.02 22999.68 25498.24 7899.87 5599.87 4
LCM-MVSNet-Re98.64 9398.48 9699.11 10998.85 22798.51 10298.49 10199.83 498.37 11199.69 1799.46 4698.21 5799.92 3594.13 28799.30 23898.91 264
mvs_anonymous97.83 18598.16 14496.87 29798.18 31091.89 33097.31 22098.90 24097.37 19498.83 15699.46 4696.28 18899.79 19098.90 3898.16 31898.95 255
DTE-MVSNet99.43 1599.35 1799.66 499.71 3299.30 1799.31 2199.51 5899.64 1299.56 2899.46 4698.23 5299.97 398.78 4699.93 2899.72 25
ACMH96.65 799.25 2799.24 2699.26 8999.72 3198.38 11099.07 5399.55 4698.30 11699.65 2299.45 5099.22 999.76 21598.44 6899.77 9399.64 41
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
VPA-MVSNet99.30 2499.30 2399.28 8399.49 8698.36 11499.00 5999.45 8199.63 1499.52 3599.44 5198.25 5099.88 7099.09 2899.84 5999.62 46
EGC-MVSNET85.24 33880.54 34199.34 7399.77 2099.20 3399.08 5099.29 15112.08 37420.84 37599.42 5297.55 10899.85 10997.08 14399.72 11798.96 254
PEN-MVS99.41 1799.34 1999.62 699.73 2599.14 5299.29 2699.54 5099.62 1799.56 2899.42 5298.16 6299.96 898.78 4699.93 2899.77 16
PatchT96.65 26096.35 26297.54 26897.40 34595.32 26097.98 15696.64 33699.33 3996.89 30099.42 5284.32 33499.81 16797.69 11497.49 33297.48 344
FIs99.14 3299.09 3499.29 8199.70 3898.28 11799.13 4799.52 5799.48 2499.24 8599.41 5596.79 16199.82 15398.69 5599.88 5299.76 20
PS-CasMVS99.40 1899.33 2099.62 699.71 3299.10 6099.29 2699.53 5499.53 2399.46 4399.41 5598.23 5299.95 1598.89 4099.95 1699.81 11
ab-mvs98.41 12698.36 11798.59 18599.19 15097.23 20299.32 1798.81 26097.66 16298.62 18299.40 5796.82 15899.80 17695.88 23099.51 19998.75 286
Anonymous2024052998.93 5098.87 4599.12 10799.19 15098.22 12599.01 5798.99 22999.25 4599.54 3099.37 5897.04 14399.80 17697.89 9799.52 19699.35 177
CR-MVSNet96.28 27495.95 27197.28 28097.71 33294.22 28598.11 13598.92 23792.31 32796.91 29699.37 5885.44 32699.81 16797.39 12497.36 33997.81 330
Patchmtry97.35 21696.97 22798.50 20297.31 34996.47 23198.18 12898.92 23798.95 8398.78 16399.37 5885.44 32699.85 10995.96 22899.83 6599.17 225
EG-PatchMatch MVS98.99 4099.01 3998.94 13999.50 7997.47 19098.04 14799.59 2698.15 13499.40 5399.36 6198.58 3399.76 21598.78 4699.68 13899.59 58
IterMVS-SCA-FT97.85 18298.18 14096.87 29799.27 13191.16 34395.53 31499.25 16399.10 6499.41 5099.35 6293.10 26999.96 898.65 5699.94 2499.49 109
PMVScopyleft91.26 2097.86 17797.94 16597.65 25799.71 3297.94 15898.52 9598.68 27698.99 7697.52 26799.35 6297.41 12398.18 36791.59 33599.67 14496.82 353
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
WR-MVS_H99.33 2399.22 2799.65 599.71 3299.24 2499.32 1799.55 4699.46 2799.50 3999.34 6497.30 12999.93 2898.90 3899.93 2899.77 16
RPMNet97.02 24396.93 22897.30 27997.71 33294.22 28598.11 13599.30 14499.37 3596.91 29699.34 6486.72 31399.87 8797.53 11897.36 33997.81 330
IterMVS97.73 18998.11 15096.57 30499.24 13690.28 34495.52 31699.21 17298.86 8799.33 6599.33 6693.11 26899.94 2398.49 6599.94 2499.48 119
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
3Dnovator98.27 298.81 6398.73 5899.05 12598.76 24397.81 17199.25 3399.30 14498.57 10598.55 19699.33 6697.95 7899.90 4997.16 13499.67 14499.44 138
IterMVS-LS98.55 10998.70 6598.09 23199.48 9494.73 27597.22 22899.39 9998.97 7999.38 5699.31 6896.00 19699.93 2898.58 5899.97 1199.60 52
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
FMVSNet298.49 11898.40 11098.75 16898.90 21697.14 21398.61 8599.13 19998.59 10199.19 9199.28 6994.14 25299.82 15397.97 9599.80 8099.29 198
3Dnovator+97.89 398.69 8398.51 8999.24 9398.81 23898.40 10799.02 5699.19 17998.99 7698.07 23099.28 6997.11 14299.84 12796.84 16799.32 23399.47 127
VDD-MVS98.56 10598.39 11399.07 11899.13 16898.07 14098.59 8897.01 32899.59 2099.11 10099.27 7194.82 23599.79 19098.34 7599.63 15599.34 179
PVSNet_Blended_VisFu98.17 15498.15 14698.22 22599.73 2595.15 26697.36 21699.68 1694.45 29698.99 12499.27 7196.87 15499.94 2397.13 14099.91 4399.57 69
nrg03099.40 1899.35 1799.54 2999.58 5399.13 5598.98 6299.48 7099.68 999.46 4399.26 7398.62 3099.73 23099.17 2699.92 3799.76 20
CP-MVSNet99.21 2999.09 3499.56 2499.65 4598.96 6999.13 4799.34 12199.42 3199.33 6599.26 7397.01 14799.94 2398.74 5199.93 2899.79 13
RPSCF98.62 9798.36 11799.42 5899.65 4599.42 598.55 9299.57 3597.72 15998.90 14299.26 7396.12 19199.52 30995.72 24099.71 12299.32 187
tfpnnormal98.90 5498.90 4498.91 14399.67 4297.82 16999.00 5999.44 8499.45 2899.51 3899.24 7698.20 5899.86 9495.92 22999.69 13399.04 240
v124098.55 10998.62 7598.32 21699.22 14195.58 25197.51 20599.45 8197.16 21799.45 4699.24 7696.12 19199.85 10999.60 499.88 5299.55 82
APDe-MVS98.99 4098.79 5399.60 1399.21 14399.15 4898.87 6899.48 7097.57 17099.35 6299.24 7697.83 8399.89 5997.88 10099.70 12799.75 22
ambc98.24 22498.82 23695.97 24398.62 8499.00 22899.27 7699.21 7996.99 14899.50 31496.55 19599.50 20699.26 204
TAMVS98.24 14798.05 15698.80 15899.07 18097.18 20997.88 16498.81 26096.66 23899.17 9699.21 7994.81 23799.77 20896.96 15499.88 5299.44 138
v119298.60 10098.66 7198.41 20999.27 13195.88 24597.52 20399.36 10997.41 19099.33 6599.20 8196.37 18599.82 15399.57 699.92 3799.55 82
pmmvs-eth3d98.47 12098.34 12098.86 15099.30 12797.76 17497.16 23599.28 15495.54 27199.42 4999.19 8297.27 13299.63 27597.89 9799.97 1199.20 214
COLMAP_ROBcopyleft96.50 1098.99 4098.85 4899.41 6199.58 5399.10 6098.74 7499.56 4299.09 6799.33 6599.19 8298.40 4299.72 23895.98 22799.76 10399.42 145
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
v14419298.54 11298.57 8398.45 20699.21 14395.98 24297.63 19099.36 10997.15 21999.32 7199.18 8495.84 20799.84 12799.50 1099.91 4399.54 86
PM-MVS98.82 6198.72 6099.12 10799.64 4898.54 10097.98 15699.68 1697.62 16599.34 6499.18 8497.54 10999.77 20897.79 10499.74 10799.04 240
PVSNet_BlendedMVS97.55 20197.53 19297.60 26198.92 21293.77 30596.64 26499.43 9094.49 29297.62 25799.18 8496.82 15899.67 25794.73 26599.93 2899.36 173
ACMH+96.62 999.08 3599.00 4099.33 7699.71 3298.83 7598.60 8699.58 2899.11 5799.53 3399.18 8498.81 2299.67 25796.71 18099.77 9399.50 105
v192192098.54 11298.60 8098.38 21299.20 14795.76 25097.56 19999.36 10997.23 21299.38 5699.17 8896.02 19499.84 12799.57 699.90 4799.54 86
casdiffmvs98.95 4899.00 4098.81 15699.38 11297.33 19697.82 17199.57 3599.17 5499.35 6299.17 8898.35 4799.69 24598.46 6799.73 11099.41 148
Patchmatch-RL test97.26 22397.02 22497.99 24199.52 7495.53 25396.13 28999.71 1197.47 17999.27 7699.16 9084.30 33599.62 27797.89 9799.77 9398.81 275
V4298.78 6898.78 5498.76 16699.44 10297.04 21498.27 12099.19 17997.87 15099.25 8499.16 9096.84 15599.78 20299.21 2399.84 5999.46 129
QAPM97.31 21996.81 23998.82 15498.80 24097.49 18999.06 5599.19 17990.22 34797.69 25399.16 9096.91 15299.90 4990.89 34699.41 21999.07 234
wuyk23d96.06 27897.62 18891.38 35398.65 27198.57 9698.85 7196.95 33096.86 23099.90 499.16 9099.18 1198.40 36689.23 35299.77 9377.18 371
v114498.60 10098.66 7198.41 20999.36 11795.90 24497.58 19799.34 12197.51 17599.27 7699.15 9496.34 18799.80 17699.47 1299.93 2899.51 101
DP-MVS98.93 5098.81 5299.28 8399.21 14398.45 10698.46 10699.33 12699.63 1499.48 4099.15 9497.23 13799.75 22297.17 13399.66 14999.63 45
OpenMVScopyleft96.65 797.09 23696.68 24698.32 21698.32 30197.16 21198.86 7099.37 10589.48 35196.29 32399.15 9496.56 17399.90 4992.90 31499.20 25297.89 324
EPP-MVSNet98.30 13898.04 15799.07 11899.56 6497.83 16699.29 2698.07 30499.03 7398.59 18899.13 9792.16 28299.90 4996.87 16499.68 13899.49 109
ACMMP_NAP98.75 7398.48 9699.57 1899.58 5399.29 1897.82 17199.25 16396.94 22698.78 16399.12 9898.02 7099.84 12797.13 14099.67 14499.59 58
RRT_MVS97.07 23896.57 25598.58 18695.89 37096.33 23497.36 21698.77 26697.85 15299.08 10699.12 9882.30 34599.96 898.82 4499.90 4799.45 133
MVS_Test98.18 15298.36 11797.67 25598.48 28894.73 27598.18 12899.02 22297.69 16098.04 23499.11 10097.22 13899.56 29798.57 6098.90 29098.71 289
MDA-MVSNet-bldmvs97.94 16997.91 16798.06 23699.44 10294.96 27196.63 26599.15 19898.35 11298.83 15699.11 10094.31 24999.85 10996.60 18698.72 29799.37 167
SMA-MVScopyleft98.40 12998.03 15899.51 4599.16 16199.21 2798.05 14599.22 17194.16 30398.98 12699.10 10297.52 11399.79 19096.45 20299.64 15299.53 94
Yufeng Yin; Xiaoyan Liu; Zichao Zhang: SMA-MVS: Segmentation-Guided Multi-Scale Anchor Deformation Patch Multi-View Stereo. IEEE Transactions on Circuits and Systems for Video Technology
MIMVSNet96.62 26296.25 26897.71 25499.04 18794.66 27899.16 4496.92 33297.23 21297.87 24199.10 10286.11 32099.65 27091.65 33399.21 25198.82 272
USDC97.41 21397.40 20197.44 27498.94 20693.67 30795.17 32499.53 5494.03 30698.97 12999.10 10295.29 22399.34 33595.84 23699.73 11099.30 194
test072699.50 7999.21 2798.17 13199.35 11597.97 14299.26 8099.06 10597.61 103
AllTest98.44 12398.20 13799.16 10299.50 7998.55 9798.25 12299.58 2896.80 23198.88 14999.06 10597.65 9799.57 29494.45 27499.61 16599.37 167
TestCases99.16 10299.50 7998.55 9799.58 2896.80 23198.88 14999.06 10597.65 9799.57 29494.45 27499.61 16599.37 167
TranMVSNet+NR-MVSNet99.17 3099.07 3699.46 5699.37 11698.87 7298.39 11299.42 9399.42 3199.36 6099.06 10598.38 4399.95 1598.34 7599.90 4799.57 69
LPG-MVS_test98.71 7898.46 10099.47 5499.57 5798.97 6698.23 12399.48 7096.60 23999.10 10399.06 10598.71 2799.83 14295.58 24999.78 8999.62 46
LGP-MVS_train99.47 5499.57 5798.97 6699.48 7096.60 23999.10 10399.06 10598.71 2799.83 14295.58 24999.78 8999.62 46
baseline98.96 4799.02 3898.76 16699.38 11297.26 20198.49 10199.50 6098.86 8799.19 9199.06 10598.23 5299.69 24598.71 5399.76 10399.33 185
VPNet98.87 5798.83 4999.01 13299.70 3897.62 18598.43 10999.35 11599.47 2699.28 7499.05 11296.72 16799.82 15398.09 8799.36 22799.59 58
RRT_test8_iter0595.24 29695.13 29695.57 32597.32 34887.02 35997.99 15499.41 9498.06 13799.12 9899.05 11266.85 37599.85 10998.93 3799.47 21099.84 8
MVSTER96.86 25196.55 25797.79 24997.91 32494.21 28797.56 19998.87 24597.49 17899.06 10999.05 11280.72 35099.80 17698.44 6899.82 6899.37 167
SD-MVS98.40 12998.68 6897.54 26898.96 20397.99 14697.88 16499.36 10998.20 12899.63 2599.04 11598.76 2395.33 37396.56 19299.74 10799.31 191
Zhenlong Yuan, Jiakai Cao, Zhaoxin Li, Hao Jiang and Zhaoqi Wang: SD-MVS: Segmentation-driven Deformation Multi-View Stereo with Spherical Refinement and EM optimization. AAAI2024
abl_698.99 4098.78 5499.61 999.45 10099.46 498.60 8699.50 6098.59 10199.24 8599.04 11598.54 3599.89 5996.45 20299.62 15899.50 105
FMVSNet596.01 27995.20 29498.41 20997.53 34096.10 23998.74 7499.50 6097.22 21598.03 23599.04 11569.80 37099.88 7097.27 12999.71 12299.25 205
IS-MVSNet98.19 15197.90 16899.08 11599.57 5797.97 15199.31 2198.32 29399.01 7598.98 12699.03 11891.59 28699.79 19095.49 25199.80 8099.48 119
DVP-MVS++98.90 5498.70 6599.51 4598.43 29399.15 4899.43 1099.32 12898.17 13199.26 8099.02 11998.18 5999.88 7097.07 14499.45 21499.49 109
test_one_060199.39 11199.20 3399.31 13498.49 10798.66 17799.02 11997.64 100
h-mvs3397.77 18897.33 20999.10 11199.21 14397.84 16598.35 11698.57 28299.11 5798.58 19099.02 11988.65 30699.96 898.11 8496.34 35299.49 109
SED-MVS98.91 5298.72 6099.49 4999.49 8699.17 3998.10 13799.31 13498.03 13899.66 2099.02 11998.36 4499.88 7096.91 15699.62 15899.41 148
test_241102_TWO99.30 14498.03 13899.26 8099.02 11997.51 11499.88 7096.91 15699.60 16799.66 36
DVP-MVScopyleft98.77 7098.52 8799.52 4199.50 7999.21 2798.02 15098.84 25497.97 14299.08 10699.02 11997.61 10399.88 7096.99 15099.63 15599.48 119
Zhenlong Yuan, Jinguo Luo, Fei Shen, Zhaoxin Li, Cong Liu, Tianlu Mao, Zhaoqi Wang: DVP-MVS: Synergize Depth-Edge and Visibility Prior for Multi-View Stereo. AAAI2025
test_0728_THIRD98.17 13199.08 10699.02 11997.89 7999.88 7097.07 14499.71 12299.70 31
EI-MVSNet98.40 12998.51 8998.04 23899.10 17394.73 27597.20 22998.87 24598.97 7999.06 10999.02 11996.00 19699.80 17698.58 5899.82 6899.60 52
CVMVSNet96.25 27597.21 21593.38 35099.10 17380.56 37697.20 22998.19 30096.94 22699.00 12399.02 11989.50 29899.80 17696.36 20999.59 17199.78 14
LFMVS97.20 22996.72 24398.64 17698.72 24996.95 21998.93 6594.14 35699.74 798.78 16399.01 12884.45 33299.73 23097.44 12199.27 24299.25 205
v2v48298.56 10598.62 7598.37 21399.42 10795.81 24897.58 19799.16 19297.90 14899.28 7499.01 12895.98 20099.79 19099.33 1599.90 4799.51 101
ACMMPcopyleft98.75 7398.50 9199.52 4199.56 6499.16 4398.87 6899.37 10597.16 21798.82 16099.01 12897.71 9399.87 8796.29 21399.69 13399.54 86
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
DPE-MVScopyleft98.59 10398.26 13099.57 1899.27 13199.15 4897.01 24099.39 9997.67 16199.44 4798.99 13197.53 11199.89 5995.40 25399.68 13899.66 36
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
MP-MVS-pluss98.57 10498.23 13499.60 1399.69 4099.35 1297.16 23599.38 10194.87 28798.97 12998.99 13198.01 7199.88 7097.29 12899.70 12799.58 64
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
EI-MVSNet-UG-set98.69 8398.71 6298.62 18199.10 17396.37 23397.23 22598.87 24599.20 4999.19 9198.99 13197.30 12999.85 10998.77 4999.79 8599.65 40
XVG-ACMP-BASELINE98.56 10598.34 12099.22 9599.54 7098.59 9497.71 18299.46 7897.25 20698.98 12698.99 13197.54 10999.84 12795.88 23099.74 10799.23 209
APD-MVS_3200maxsize98.84 6098.61 7899.53 3699.19 15099.27 2198.49 10199.33 12698.64 9599.03 11998.98 13597.89 7999.85 10996.54 19699.42 21899.46 129
XVG-OURS98.53 11498.34 12099.11 10999.50 7998.82 7795.97 29399.50 6097.30 20199.05 11498.98 13599.35 799.32 33895.72 24099.68 13899.18 221
v14898.45 12298.60 8098.00 24099.44 10294.98 27097.44 21299.06 20998.30 11699.32 7198.97 13796.65 17099.62 27798.37 7299.85 5799.39 157
EI-MVSNet-Vis-set98.68 8798.70 6598.63 17999.09 17696.40 23297.23 22598.86 25099.20 4999.18 9598.97 13797.29 13199.85 10998.72 5299.78 8999.64 41
CHOSEN 1792x268897.49 20597.14 22098.54 19799.68 4196.09 24196.50 27199.62 2291.58 33598.84 15598.97 13792.36 28099.88 7096.76 17399.95 1699.67 35
SR-MVS-dyc-post98.81 6398.55 8499.57 1899.20 14799.38 698.48 10499.30 14498.64 9598.95 13298.96 14097.49 11899.86 9496.56 19299.39 22299.45 133
RE-MVS-def98.58 8299.20 14799.38 698.48 10499.30 14498.64 9598.95 13298.96 14097.75 9096.56 19299.39 22299.45 133
D2MVS97.84 18397.84 17297.83 24799.14 16694.74 27496.94 24498.88 24395.84 26598.89 14598.96 14094.40 24799.69 24597.55 11599.95 1699.05 236
ACMM96.08 1298.91 5298.73 5899.48 5199.55 6799.14 5298.07 14199.37 10597.62 16599.04 11698.96 14098.84 2099.79 19097.43 12299.65 15099.49 109
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
MVP-Stereo98.08 15997.92 16698.57 18998.96 20396.79 22397.90 16399.18 18396.41 24698.46 20298.95 14495.93 20399.60 28496.51 19898.98 28699.31 191
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
YYNet197.60 19897.67 18197.39 27799.04 18793.04 31595.27 32198.38 29297.25 20698.92 14098.95 14495.48 22099.73 23096.99 15098.74 29599.41 148
MDA-MVSNet_test_wron97.60 19897.66 18497.41 27699.04 18793.09 31195.27 32198.42 28997.26 20598.88 14998.95 14495.43 22199.73 23097.02 14798.72 29799.41 148
FMVSNet397.50 20397.24 21398.29 22098.08 31695.83 24797.86 16798.91 23997.89 14998.95 13298.95 14487.06 31199.81 16797.77 10699.69 13399.23 209
OPM-MVS98.56 10598.32 12499.25 9199.41 10998.73 8497.13 23799.18 18397.10 22098.75 16998.92 14898.18 5999.65 27096.68 18299.56 18699.37 167
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
ADS-MVSNet295.43 29394.98 29996.76 30398.14 31291.74 33197.92 16097.76 31190.23 34596.51 31698.91 14985.61 32399.85 10992.88 31596.90 34598.69 292
ADS-MVSNet95.24 29694.93 30196.18 31298.14 31290.10 34597.92 16097.32 32390.23 34596.51 31698.91 14985.61 32399.74 22692.88 31596.90 34598.69 292
test_040298.76 7198.71 6298.93 14099.56 6498.14 13298.45 10899.34 12199.28 4398.95 13298.91 14998.34 4899.79 19095.63 24699.91 4398.86 269
test_241102_ONE99.49 8699.17 3999.31 13497.98 14099.66 2098.90 15298.36 4499.48 318
xxxxxxxxxxxxxcwj98.44 12398.24 13299.06 12399.11 16997.97 15196.53 26899.54 5098.24 12298.83 15698.90 15297.80 8799.82 15395.68 24399.52 19699.38 164
SF-MVS98.53 11498.27 12999.32 7899.31 12498.75 8098.19 12799.41 9496.77 23398.83 15698.90 15297.80 8799.82 15395.68 24399.52 19699.38 164
zzz-MVS98.79 6598.52 8799.61 999.67 4299.36 1097.33 21899.20 17498.83 9098.89 14598.90 15296.98 14999.92 3597.16 13499.70 12799.56 74
MTAPA98.88 5698.64 7399.61 999.67 4299.36 1098.43 10999.20 17498.83 9098.89 14598.90 15296.98 14999.92 3597.16 13499.70 12799.56 74
test20.0398.78 6898.77 5698.78 16399.46 9797.20 20797.78 17399.24 16899.04 7299.41 5098.90 15297.65 9799.76 21597.70 11299.79 8599.39 157
SteuartSystems-ACMMP98.79 6598.54 8599.54 2999.73 2599.16 4398.23 12399.31 13497.92 14698.90 14298.90 15298.00 7299.88 7096.15 22199.72 11799.58 64
Skip Steuart: Steuart Systems R&D Blog.
N_pmnet97.63 19797.17 21698.99 13499.27 13197.86 16395.98 29293.41 35995.25 28099.47 4298.90 15295.63 21299.85 10996.91 15699.73 11099.27 201
TSAR-MVS + MP.98.63 9598.49 9499.06 12399.64 4897.90 16098.51 9998.94 23296.96 22599.24 8598.89 16097.83 8399.81 16796.88 16399.49 20799.48 119
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
test117298.76 7198.49 9499.57 1899.18 15799.37 998.39 11299.31 13498.43 10998.90 14298.88 16197.49 11899.86 9496.43 20499.37 22699.48 119
PGM-MVS98.66 9098.37 11699.55 2699.53 7299.18 3898.23 12399.49 6897.01 22498.69 17398.88 16198.00 7299.89 5995.87 23399.59 17199.58 64
TinyColmap97.89 17397.98 16197.60 26198.86 22594.35 28496.21 28699.44 8497.45 18699.06 10998.88 16197.99 7599.28 34494.38 28099.58 17799.18 221
LS3D98.63 9598.38 11599.36 6597.25 35099.38 699.12 4999.32 12899.21 4698.44 20498.88 16197.31 12899.80 17696.58 18799.34 23198.92 261
Anonymous20240521197.90 17197.50 19499.08 11598.90 21698.25 11998.53 9496.16 34098.87 8699.11 10098.86 16590.40 29299.78 20297.36 12599.31 23599.19 219
HPM-MVS_fast99.01 3898.82 5099.57 1899.71 3299.35 1299.00 5999.50 6097.33 19798.94 13898.86 16598.75 2499.82 15397.53 11899.71 12299.56 74
CMPMVSbinary75.91 2396.29 27395.44 28698.84 15296.25 36698.69 8797.02 23999.12 20188.90 35497.83 24498.86 16589.51 29798.90 36191.92 32999.51 19998.92 261
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
SR-MVS98.71 7898.43 10699.57 1899.18 15799.35 1298.36 11599.29 15198.29 11998.88 14998.85 16897.53 11199.87 8796.14 22299.31 23599.48 119
our_test_397.39 21497.73 17996.34 30898.70 25689.78 34694.61 34198.97 23196.50 24299.04 11698.85 16895.98 20099.84 12797.26 13099.67 14499.41 148
MVS_030497.64 19597.35 20698.52 19897.87 32696.69 22898.59 8898.05 30697.44 18893.74 36198.85 16893.69 26399.88 7098.11 8499.81 7298.98 249
Regformer-398.61 9898.61 7898.63 17999.02 19296.53 23097.17 23398.84 25499.13 5699.10 10398.85 16897.24 13699.79 19098.41 7199.70 12799.57 69
Regformer-498.73 7698.68 6898.89 14699.02 19297.22 20497.17 23399.06 20999.21 4699.17 9698.85 16897.45 12199.86 9498.48 6699.70 12799.60 52
EPNet96.14 27795.44 28698.25 22390.76 37795.50 25597.92 16094.65 34998.97 7992.98 36298.85 16889.12 30099.87 8795.99 22699.68 13899.39 157
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
pmmvs597.64 19597.49 19598.08 23499.14 16695.12 26896.70 26299.05 21393.77 30998.62 18298.83 17493.23 26599.75 22298.33 7799.76 10399.36 173
PMMVS298.07 16098.08 15498.04 23899.41 10994.59 28194.59 34299.40 9797.50 17698.82 16098.83 17496.83 15799.84 12797.50 12099.81 7299.71 26
MDTV_nov1_ep1395.22 29397.06 35383.20 37197.74 18096.16 34094.37 29896.99 29298.83 17483.95 33799.53 30593.90 29397.95 327
Anonymous2023120698.21 14998.21 13698.20 22699.51 7695.43 25898.13 13299.32 12896.16 25498.93 13998.82 17796.00 19699.83 14297.32 12799.73 11099.36 173
ACMP95.32 1598.41 12698.09 15199.36 6599.51 7698.79 7997.68 18599.38 10195.76 26898.81 16298.82 17798.36 4499.82 15394.75 26499.77 9399.48 119
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
GeoE99.05 3698.99 4299.25 9199.44 10298.35 11598.73 7699.56 4298.42 11098.91 14198.81 17998.94 1899.91 4598.35 7499.73 11099.49 109
VNet98.42 12598.30 12598.79 16098.79 24297.29 19898.23 12398.66 27799.31 4098.85 15398.80 18094.80 23899.78 20298.13 8399.13 26699.31 191
tpmrst95.07 29995.46 28493.91 34397.11 35284.36 36997.62 19196.96 32994.98 28396.35 32298.80 18085.46 32599.59 28895.60 24796.23 35497.79 333
ppachtmachnet_test97.50 20397.74 17796.78 30298.70 25691.23 34294.55 34399.05 21396.36 24799.21 8998.79 18296.39 18299.78 20296.74 17599.82 6899.34 179
miper_lstm_enhance97.18 23197.16 21797.25 28298.16 31192.85 31795.15 32699.31 13497.25 20698.74 17198.78 18390.07 29399.78 20297.19 13299.80 8099.11 232
DeepPCF-MVS96.93 598.32 13698.01 15999.23 9498.39 29898.97 6695.03 32899.18 18396.88 22999.33 6598.78 18398.16 6299.28 34496.74 17599.62 15899.44 138
patchmatchnet-post98.77 18584.37 33399.85 109
APD-MVScopyleft98.10 15797.67 18199.42 5899.11 16998.93 7097.76 17899.28 15494.97 28498.72 17298.77 18597.04 14399.85 10993.79 29899.54 18999.49 109
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
DU-MVS98.82 6198.63 7499.39 6499.16 16198.74 8197.54 20199.25 16398.84 8999.06 10998.76 18796.76 16499.93 2898.57 6099.77 9399.50 105
NR-MVSNet98.95 4898.82 5099.36 6599.16 16198.72 8699.22 3599.20 17499.10 6499.72 1398.76 18796.38 18499.86 9498.00 9499.82 6899.50 105
eth_miper_zixun_eth97.23 22797.25 21197.17 28498.00 32092.77 31994.71 33599.18 18397.27 20498.56 19498.74 18991.89 28599.69 24597.06 14699.81 7299.05 236
UniMVSNet (Re)98.87 5798.71 6299.35 7099.24 13698.73 8497.73 18199.38 10198.93 8499.12 9898.73 19096.77 16299.86 9498.63 5799.80 8099.46 129
MG-MVS96.77 25596.61 25197.26 28198.31 30293.06 31295.93 29898.12 30396.45 24597.92 23798.73 19093.77 26199.39 33091.19 34299.04 27699.33 185
c3_l97.36 21597.37 20497.31 27898.09 31593.25 31095.01 32999.16 19297.05 22198.77 16698.72 19292.88 27499.64 27296.93 15599.76 10399.05 236
cl____97.02 24396.83 23797.58 26397.82 32894.04 29194.66 33899.16 19297.04 22298.63 18098.71 19388.68 30599.69 24597.00 14899.81 7299.00 247
DIV-MVS_self_test97.02 24396.84 23697.58 26397.82 32894.03 29294.66 33899.16 19297.04 22298.63 18098.71 19388.69 30399.69 24597.00 14899.81 7299.01 244
DELS-MVS98.27 14298.20 13798.48 20398.86 22596.70 22795.60 31299.20 17497.73 15898.45 20398.71 19397.50 11599.82 15398.21 8099.59 17198.93 260
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
9.1497.78 17499.07 18097.53 20299.32 12895.53 27398.54 19898.70 19697.58 10599.76 21594.32 28199.46 211
tpmvs95.02 30195.25 29294.33 33996.39 36585.87 36198.08 14096.83 33495.46 27595.51 34398.69 19785.91 32199.53 30594.16 28296.23 35497.58 341
PatchmatchNetpermissive95.58 28995.67 27895.30 33297.34 34787.32 35697.65 18996.65 33595.30 27997.07 28898.69 19784.77 32999.75 22294.97 26098.64 30398.83 271
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
mPP-MVS98.64 9398.34 12099.54 2999.54 7099.17 3998.63 8399.24 16897.47 17998.09 22998.68 19997.62 10299.89 5996.22 21699.62 15899.57 69
UnsupCasMVSNet_eth97.89 17397.60 19098.75 16899.31 12497.17 21097.62 19199.35 11598.72 9498.76 16898.68 19992.57 27999.74 22697.76 11095.60 35999.34 179
SCA96.41 27196.66 24995.67 32298.24 30688.35 35195.85 30396.88 33396.11 25597.67 25498.67 20193.10 26999.85 10994.16 28299.22 24998.81 275
Patchmatch-test96.55 26396.34 26397.17 28498.35 29993.06 31298.40 11197.79 31097.33 19798.41 20898.67 20183.68 33999.69 24595.16 25699.31 23598.77 283
CDS-MVSNet97.69 19197.35 20698.69 17398.73 24797.02 21696.92 24898.75 27095.89 26498.59 18898.67 20192.08 28499.74 22696.72 17899.81 7299.32 187
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
MP-MVScopyleft98.46 12198.09 15199.54 2999.57 5799.22 2698.50 10099.19 17997.61 16797.58 26198.66 20497.40 12499.88 7094.72 26799.60 16799.54 86
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
DeepC-MVS_fast96.85 698.30 13898.15 14698.75 16898.61 27297.23 20297.76 17899.09 20597.31 20098.75 16998.66 20497.56 10799.64 27296.10 22499.55 18899.39 157
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
MS-PatchMatch97.68 19297.75 17697.45 27398.23 30893.78 30497.29 22198.84 25496.10 25698.64 17998.65 20696.04 19399.36 33396.84 16799.14 26399.20 214
pmmvs497.58 20097.28 21098.51 20098.84 23096.93 22095.40 32098.52 28593.60 31198.61 18498.65 20695.10 22899.60 28496.97 15399.79 8598.99 248
FPMVS93.44 32392.23 32897.08 28799.25 13597.86 16395.61 31197.16 32692.90 32093.76 36098.65 20675.94 36595.66 37179.30 37197.49 33297.73 335
Regformer-198.55 10998.44 10498.87 14898.85 22797.29 19896.91 24998.99 22998.97 7998.99 12498.64 20997.26 13599.81 16797.79 10499.57 18199.51 101
Regformer-298.60 10098.46 10099.02 13198.85 22797.71 17996.91 24999.09 20598.98 7899.01 12098.64 20997.37 12699.84 12797.75 11199.57 18199.52 98
dp93.47 32293.59 31693.13 35296.64 35981.62 37597.66 18796.42 33892.80 32296.11 32598.64 20978.55 36299.59 28893.31 31092.18 37098.16 314
EPMVS93.72 32093.27 31995.09 33496.04 36887.76 35498.13 13285.01 37594.69 29096.92 29498.64 20978.47 36399.31 33995.04 25796.46 35198.20 312
XVS98.72 7798.45 10299.53 3699.46 9799.21 2798.65 8199.34 12198.62 9997.54 26598.63 21397.50 11599.83 14296.79 16999.53 19399.56 74
CostFormer93.97 31693.78 31394.51 33897.53 34085.83 36397.98 15695.96 34389.29 35394.99 34998.63 21378.63 36099.62 27794.54 27096.50 35098.09 317
ETH3D-3000-0.198.03 16197.62 18899.29 8199.11 16998.80 7897.47 20999.32 12895.54 27198.43 20798.62 21596.61 17299.77 20893.95 29299.49 20799.30 194
MSLP-MVS++98.02 16398.14 14897.64 25998.58 27795.19 26597.48 20799.23 17097.47 17997.90 23998.62 21597.04 14398.81 36397.55 11599.41 21998.94 259
Vis-MVSNet (Re-imp)97.46 20897.16 21798.34 21599.55 6796.10 23998.94 6498.44 28898.32 11598.16 22198.62 21588.76 30299.73 23093.88 29599.79 8599.18 221
XVG-OURS-SEG-HR98.49 11898.28 12899.14 10599.49 8698.83 7596.54 26799.48 7097.32 19999.11 10098.61 21899.33 899.30 34196.23 21598.38 31099.28 199
ITE_SJBPF98.87 14899.22 14198.48 10499.35 11597.50 17698.28 21698.60 21997.64 10099.35 33493.86 29699.27 24298.79 281
UniMVSNet_NR-MVSNet98.86 5998.68 6899.40 6399.17 15998.74 8197.68 18599.40 9799.14 5599.06 10998.59 22096.71 16899.93 2898.57 6099.77 9399.53 94
114514_t96.50 26695.77 27398.69 17399.48 9497.43 19397.84 16999.55 4681.42 36896.51 31698.58 22195.53 21599.67 25793.41 30899.58 17798.98 249
HY-MVS95.94 1395.90 28295.35 29097.55 26797.95 32194.79 27398.81 7396.94 33192.28 32895.17 34698.57 22289.90 29599.75 22291.20 34197.33 34198.10 316
tpm94.67 30494.34 30895.66 32397.68 33688.42 35097.88 16494.90 34894.46 29496.03 33098.56 22378.66 35999.79 19095.88 23095.01 36298.78 282
PC_three_145293.27 31599.40 5398.54 22498.22 5597.00 37095.17 25599.45 21499.49 109
ACMMPR98.70 8198.42 10899.54 2999.52 7499.14 5298.52 9599.31 13497.47 17998.56 19498.54 22497.75 9099.88 7096.57 18999.59 17199.58 64
new_pmnet96.99 24796.76 24197.67 25598.72 24994.89 27295.95 29798.20 29892.62 32498.55 19698.54 22494.88 23499.52 30993.96 29199.44 21798.59 298
OPU-MVS98.82 15498.59 27698.30 11698.10 13798.52 22798.18 5998.75 36494.62 26899.48 20999.41 148
region2R98.69 8398.40 11099.54 2999.53 7299.17 3998.52 9599.31 13497.46 18498.44 20498.51 22897.83 8399.88 7096.46 20199.58 17799.58 64
TSAR-MVS + GP.98.18 15297.98 16198.77 16598.71 25297.88 16196.32 28198.66 27796.33 24899.23 8898.51 22897.48 12099.40 32897.16 13499.46 21199.02 243
OMC-MVS97.88 17597.49 19599.04 12798.89 22198.63 8996.94 24499.25 16395.02 28298.53 19998.51 22897.27 13299.47 32093.50 30699.51 19999.01 244
testtj97.79 18797.25 21199.42 5899.03 19098.85 7397.78 17399.18 18395.83 26698.12 22598.50 23195.50 21899.86 9492.23 32899.07 27299.54 86
HFP-MVS98.71 7898.44 10499.51 4599.49 8699.16 4398.52 9599.31 13497.47 17998.58 19098.50 23197.97 7699.85 10996.57 18999.59 17199.53 94
#test#98.50 11798.16 14499.51 4599.49 8699.16 4398.03 14899.31 13496.30 25198.58 19098.50 23197.97 7699.85 10995.68 24399.59 17199.53 94
diffmvs98.22 14898.24 13298.17 22899.00 19595.44 25796.38 27899.58 2897.79 15698.53 19998.50 23196.76 16499.74 22697.95 9699.64 15299.34 179
WR-MVS98.40 12998.19 13999.03 12899.00 19597.65 18296.85 25298.94 23298.57 10598.89 14598.50 23195.60 21399.85 10997.54 11799.85 5799.59 58
Test_1112_low_res96.99 24796.55 25798.31 21899.35 12195.47 25695.84 30499.53 5491.51 33796.80 30698.48 23691.36 28799.83 14296.58 18799.53 19399.62 46
miper_ehance_all_eth97.06 23997.03 22397.16 28697.83 32793.06 31294.66 33899.09 20595.99 26198.69 17398.45 23792.73 27799.61 28396.79 16999.03 27798.82 272
PHI-MVS98.29 14197.95 16399.34 7398.44 29299.16 4398.12 13499.38 10196.01 26098.06 23198.43 23897.80 8799.67 25795.69 24299.58 17799.20 214
tpm cat193.29 32493.13 32393.75 34597.39 34684.74 36697.39 21397.65 31583.39 36794.16 35498.41 23982.86 34399.39 33091.56 33695.35 36197.14 348
ETH3D cwj APD-0.1697.55 20197.00 22599.19 9898.51 28698.64 8896.85 25299.13 19994.19 30297.65 25598.40 24095.78 20899.81 16793.37 30999.16 25999.12 230
CP-MVS98.70 8198.42 10899.52 4199.36 11799.12 5798.72 7799.36 10997.54 17498.30 21498.40 24097.86 8199.89 5996.53 19799.72 11799.56 74
ZNCC-MVS98.68 8798.40 11099.54 2999.57 5799.21 2798.46 10699.29 15197.28 20398.11 22798.39 24298.00 7299.87 8796.86 16699.64 15299.55 82
GST-MVS98.61 9898.30 12599.52 4199.51 7699.20 3398.26 12199.25 16397.44 18898.67 17598.39 24297.68 9499.85 10996.00 22599.51 19999.52 98
bset_n11_16_dypcd96.99 24796.56 25698.27 22299.00 19595.25 26192.18 36594.05 35798.75 9299.01 12098.38 24488.98 30199.93 2898.77 4999.92 3799.64 41
HPM-MVScopyleft98.79 6598.53 8699.59 1799.65 4599.29 1899.16 4499.43 9096.74 23498.61 18498.38 24498.62 3099.87 8796.47 20099.67 14499.59 58
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
testdata98.09 23198.93 20895.40 25998.80 26290.08 34997.45 27398.37 24695.26 22499.70 24193.58 30398.95 28899.17 225
CPTT-MVS97.84 18397.36 20599.27 8699.31 12498.46 10598.29 11899.27 15794.90 28697.83 24498.37 24694.90 23199.84 12793.85 29799.54 18999.51 101
DROMVSNet99.09 3499.05 3799.20 9699.28 12998.93 7099.24 3499.84 399.08 6998.12 22598.37 24698.72 2699.90 4999.05 3199.77 9398.77 283
OpenMVS_ROBcopyleft95.38 1495.84 28495.18 29597.81 24898.41 29797.15 21297.37 21598.62 28083.86 36598.65 17898.37 24694.29 25099.68 25488.41 35498.62 30596.60 356
tttt051795.64 28894.98 29997.64 25999.36 11793.81 30398.72 7790.47 36898.08 13698.67 17598.34 25073.88 36799.92 3597.77 10699.51 19999.20 214
旧先验198.82 23697.45 19298.76 26798.34 25095.50 21899.01 28299.23 209
CNVR-MVS98.17 15497.87 17099.07 11898.67 26598.24 12097.01 24098.93 23497.25 20697.62 25798.34 25097.27 13299.57 29496.42 20599.33 23299.39 157
HyFIR lowres test97.19 23096.60 25398.96 13699.62 5297.28 20095.17 32499.50 6094.21 30199.01 12098.32 25386.61 31499.99 297.10 14299.84 5999.60 52
UnsupCasMVSNet_bld97.30 22096.92 23098.45 20699.28 12996.78 22696.20 28799.27 15795.42 27698.28 21698.30 25493.16 26799.71 23994.99 25997.37 33798.87 268
MSDG97.71 19097.52 19398.28 22198.91 21596.82 22294.42 34599.37 10597.65 16398.37 21398.29 25597.40 12499.33 33794.09 28899.22 24998.68 295
MVS_111021_HR98.25 14698.08 15498.75 16899.09 17697.46 19195.97 29399.27 15797.60 16897.99 23698.25 25698.15 6499.38 33296.87 16499.57 18199.42 145
CANet_DTU97.26 22397.06 22297.84 24697.57 33794.65 27996.19 28898.79 26397.23 21295.14 34798.24 25793.22 26699.84 12797.34 12699.84 5999.04 240
MVS_111021_LR98.30 13898.12 14998.83 15399.16 16198.03 14496.09 29099.30 14497.58 16998.10 22898.24 25798.25 5099.34 33596.69 18199.65 15099.12 230
tpm293.09 32692.58 32794.62 33797.56 33886.53 36097.66 18795.79 34586.15 36294.07 35798.23 25975.95 36499.53 30590.91 34596.86 34897.81 330
CANet97.87 17697.76 17598.19 22797.75 33095.51 25496.76 25899.05 21397.74 15796.93 29398.21 26095.59 21499.89 5997.86 10299.93 2899.19 219
LF4IMVS97.90 17197.69 18098.52 19899.17 15997.66 18197.19 23299.47 7696.31 25097.85 24398.20 26196.71 16899.52 30994.62 26899.72 11798.38 307
CL-MVSNet_self_test97.44 21197.22 21498.08 23498.57 27995.78 24994.30 34898.79 26396.58 24198.60 18698.19 26294.74 24199.64 27296.41 20698.84 29198.82 272
cl2295.79 28595.39 28996.98 29196.77 35892.79 31894.40 34698.53 28494.59 29197.89 24098.17 26382.82 34499.24 34696.37 20799.03 27798.92 261
112196.73 25696.00 26998.91 14398.95 20597.76 17498.07 14198.73 27387.65 35996.54 31398.13 26494.52 24499.73 23092.38 32699.02 28099.24 208
MVSFormer98.26 14498.43 10697.77 25098.88 22293.89 30199.39 1399.56 4299.11 5798.16 22198.13 26493.81 25999.97 399.26 1899.57 18199.43 142
jason97.45 21097.35 20697.76 25199.24 13693.93 29795.86 30198.42 28994.24 30098.50 20198.13 26494.82 23599.91 4597.22 13199.73 11099.43 142
jason: jason.
ZD-MVS99.01 19498.84 7499.07 20894.10 30498.05 23398.12 26796.36 18699.86 9492.70 32299.19 256
test22298.92 21296.93 22095.54 31398.78 26585.72 36396.86 30298.11 26894.43 24599.10 27199.23 209
新几何198.91 14398.94 20697.76 17498.76 26787.58 36096.75 30798.10 26994.80 23899.78 20292.73 32199.00 28399.20 214
原ACMM198.35 21498.90 21696.25 23798.83 25992.48 32596.07 32898.10 26995.39 22299.71 23992.61 32498.99 28499.08 233
EPNet_dtu94.93 30294.78 30395.38 33193.58 37487.68 35596.78 25695.69 34697.35 19689.14 37098.09 27188.15 30999.49 31594.95 26199.30 23898.98 249
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
pmmvs395.03 30094.40 30696.93 29397.70 33492.53 32295.08 32797.71 31388.57 35697.71 25198.08 27279.39 35799.82 15396.19 21899.11 27098.43 305
DP-MVS Recon97.33 21896.92 23098.57 18999.09 17697.99 14696.79 25599.35 11593.18 31697.71 25198.07 27395.00 23099.31 33993.97 29099.13 26698.42 306
CSCG98.68 8798.50 9199.20 9699.45 10098.63 8998.56 9199.57 3597.87 15098.85 15398.04 27497.66 9699.84 12796.72 17899.81 7299.13 229
F-COLMAP97.30 22096.68 24699.14 10599.19 15098.39 10897.27 22499.30 14492.93 31996.62 31198.00 27595.73 21099.68 25492.62 32398.46 30999.35 177
Effi-MVS+-dtu98.26 14497.90 16899.35 7098.02 31899.49 398.02 15099.16 19298.29 11997.64 25697.99 27696.44 18099.95 1596.66 18398.93 28998.60 296
hse-mvs297.46 20897.07 22198.64 17698.73 24797.33 19697.45 21197.64 31799.11 5798.58 19097.98 27788.65 30699.79 19098.11 8497.39 33698.81 275
HQP_MVS97.99 16897.67 18198.93 14099.19 15097.65 18297.77 17699.27 15798.20 12897.79 24797.98 27794.90 23199.70 24194.42 27699.51 19999.45 133
plane_prior497.98 277
BH-RMVSNet96.83 25296.58 25497.58 26398.47 28994.05 29096.67 26397.36 32096.70 23797.87 24197.98 27795.14 22799.44 32590.47 34898.58 30799.25 205
AUN-MVS96.24 27695.45 28598.60 18498.70 25697.22 20497.38 21497.65 31595.95 26295.53 34297.96 28182.11 34999.79 19096.31 21197.44 33498.80 280
NCCC97.86 17797.47 19999.05 12598.61 27298.07 14096.98 24298.90 24097.63 16497.04 29097.93 28295.99 19999.66 26595.31 25498.82 29399.43 142
sss97.21 22896.93 22898.06 23698.83 23395.22 26496.75 25998.48 28794.49 29297.27 28197.90 28392.77 27699.80 17696.57 18999.32 23399.16 228
test_yl96.69 25796.29 26597.90 24398.28 30395.24 26297.29 22197.36 32098.21 12598.17 21997.86 28486.27 31699.55 30094.87 26298.32 31198.89 265
DCV-MVSNet96.69 25796.29 26597.90 24398.28 30395.24 26297.29 22197.36 32098.21 12598.17 21997.86 28486.27 31699.55 30094.87 26298.32 31198.89 265
CDPH-MVS97.26 22396.66 24999.07 11899.00 19598.15 13096.03 29199.01 22591.21 34197.79 24797.85 28696.89 15399.69 24592.75 32099.38 22599.39 157
HPM-MVS++copyleft98.10 15797.64 18699.48 5199.09 17699.13 5597.52 20398.75 27097.46 18496.90 29997.83 28796.01 19599.84 12795.82 23799.35 22999.46 129
ETH3 D test640096.46 26995.59 28199.08 11598.88 22298.21 12696.53 26899.18 18388.87 35597.08 28797.79 28893.64 26499.77 20888.92 35399.40 22199.28 199
PatchMatch-RL97.24 22696.78 24098.61 18399.03 19097.83 16696.36 27999.06 20993.49 31497.36 27997.78 28995.75 20999.49 31593.44 30798.77 29498.52 299
TAPA-MVS96.21 1196.63 26195.95 27198.65 17598.93 20898.09 13496.93 24699.28 15483.58 36698.13 22497.78 28996.13 19099.40 32893.52 30499.29 24098.45 303
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
baseline195.96 28195.44 28697.52 27098.51 28693.99 29598.39 11296.09 34298.21 12598.40 21297.76 29186.88 31299.63 27595.42 25289.27 37198.95 255
WTY-MVS96.67 25996.27 26797.87 24598.81 23894.61 28096.77 25797.92 30994.94 28597.12 28497.74 29291.11 28899.82 15393.89 29498.15 31999.18 221
test_method79.78 33979.50 34280.62 35580.21 37845.76 38070.82 36998.41 29131.08 37380.89 37497.71 29384.85 32897.37 36991.51 33780.03 37298.75 286
MSP-MVS98.40 12998.00 16099.61 999.57 5799.25 2398.57 9099.35 11597.55 17399.31 7397.71 29394.61 24299.88 7096.14 22299.19 25699.70 31
Zhenlong Yuan, Cong Liu, Fei Shen, Zhaoxin Li, Jingguo luo, Tianlu Mao and Zhaoqi Wang: MSP-MVS: Multi-granularity Segmentation Prior Guided Multi-View Stereo. AAAI2025
MCST-MVS98.00 16597.63 18799.10 11199.24 13698.17 12996.89 25198.73 27395.66 26997.92 23797.70 29597.17 13999.66 26596.18 22099.23 24899.47 127
AdaColmapbinary97.14 23496.71 24498.46 20598.34 30097.80 17296.95 24398.93 23495.58 27096.92 29497.66 29695.87 20699.53 30590.97 34399.14 26398.04 318
thisisatest053095.27 29594.45 30597.74 25399.19 15094.37 28397.86 16790.20 36997.17 21698.22 21897.65 29773.53 36899.90 4996.90 16199.35 22998.95 255
testgi98.32 13698.39 11398.13 23099.57 5795.54 25297.78 17399.49 6897.37 19499.19 9197.65 29798.96 1799.49 31596.50 19998.99 28499.34 179
test_prior397.48 20797.00 22598.95 13798.69 26097.95 15695.74 30799.03 21896.48 24396.11 32597.63 29995.92 20499.59 28894.16 28299.20 25299.30 194
test_prior295.74 30796.48 24396.11 32597.63 29995.92 20494.16 28299.20 252
cdsmvs_eth3d_5k24.66 34132.88 3440.00 3590.00 3820.00 3830.00 37099.10 2040.00 3770.00 37897.58 30199.21 100.00 3780.00 3760.00 3760.00 374
lupinMVS97.06 23996.86 23497.65 25798.88 22293.89 30195.48 31797.97 30793.53 31298.16 22197.58 30193.81 25999.91 4596.77 17299.57 18199.17 225
TEST998.71 25298.08 13895.96 29599.03 21891.40 33895.85 33197.53 30396.52 17599.76 215
train_agg97.10 23596.45 26099.07 11898.71 25298.08 13895.96 29599.03 21891.64 33395.85 33197.53 30396.47 17899.76 21593.67 30099.16 25999.36 173
Fast-Effi-MVS+-dtu98.27 14298.09 15198.81 15698.43 29398.11 13397.61 19399.50 6098.64 9597.39 27797.52 30598.12 6599.95 1596.90 16198.71 29998.38 307
test_898.67 26598.01 14595.91 30099.02 22291.64 33395.79 33397.50 30696.47 17899.76 215
agg_prior197.06 23996.40 26199.03 12898.68 26397.99 14695.76 30599.01 22591.73 33295.59 33497.50 30696.49 17799.77 20893.71 29999.14 26399.34 179
1112_ss97.29 22296.86 23498.58 18699.34 12396.32 23596.75 25999.58 2893.14 31796.89 30097.48 30892.11 28399.86 9496.91 15699.54 18999.57 69
ab-mvs-re8.12 34510.83 3480.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 37897.48 3080.00 3820.00 3780.00 3760.00 3760.00 374
Effi-MVS+98.02 16397.82 17398.62 18198.53 28597.19 20897.33 21899.68 1697.30 20196.68 30897.46 31098.56 3499.80 17696.63 18598.20 31598.86 269
PCF-MVS92.86 1894.36 30793.00 32498.42 20898.70 25697.56 18693.16 36099.11 20379.59 36997.55 26497.43 31192.19 28199.73 23079.85 37099.45 21497.97 322
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
GA-MVS95.86 28395.32 29197.49 27198.60 27494.15 28993.83 35597.93 30895.49 27496.68 30897.42 31283.21 34099.30 34196.22 21698.55 30899.01 244
CNLPA97.17 23296.71 24498.55 19498.56 28098.05 14396.33 28098.93 23496.91 22897.06 28997.39 31394.38 24899.45 32491.66 33299.18 25898.14 315
CS-MVS-test98.41 12698.30 12598.73 17298.84 23098.39 10898.71 7999.79 597.98 14096.86 30297.38 31497.86 8199.83 14297.81 10399.46 21197.97 322
PLCcopyleft94.65 1696.51 26495.73 27598.85 15198.75 24597.91 15996.42 27699.06 20990.94 34495.59 33497.38 31494.41 24699.59 28890.93 34498.04 32699.05 236
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
BH-untuned96.83 25296.75 24297.08 28798.74 24693.33 30996.71 26198.26 29596.72 23598.44 20497.37 31695.20 22599.47 32091.89 33097.43 33598.44 304
PVSNet_Blended96.88 25096.68 24697.47 27298.92 21293.77 30594.71 33599.43 9090.98 34397.62 25797.36 31796.82 15899.67 25794.73 26599.56 18698.98 249
miper_enhance_ethall96.01 27995.74 27496.81 30196.41 36492.27 32793.69 35798.89 24291.14 34298.30 21497.35 31890.58 29099.58 29396.31 21199.03 27798.60 296
DPM-MVS96.32 27295.59 28198.51 20098.76 24397.21 20694.54 34498.26 29591.94 33196.37 32197.25 31993.06 27199.43 32691.42 33898.74 29598.89 265
CS-MVS98.16 15698.22 13597.97 24298.56 28097.01 21798.10 13799.70 1497.45 18697.29 28097.19 32097.72 9299.80 17698.37 7299.62 15897.11 349
E-PMN94.17 31294.37 30793.58 34796.86 35585.71 36490.11 36797.07 32798.17 13197.82 24697.19 32084.62 33198.94 35989.77 35097.68 33196.09 363
mvs-test197.83 18597.48 19898.89 14698.02 31899.20 3397.20 22999.16 19298.29 11996.46 32097.17 32296.44 18099.92 3596.66 18397.90 32897.54 343
CLD-MVS97.49 20597.16 21798.48 20399.07 18097.03 21594.71 33599.21 17294.46 29498.06 23197.16 32397.57 10699.48 31894.46 27399.78 8998.95 255
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
CHOSEN 280x42095.51 29295.47 28395.65 32498.25 30588.27 35293.25 35998.88 24393.53 31294.65 35097.15 32486.17 31899.93 2897.41 12399.93 2898.73 288
xiu_mvs_v1_base_debu97.86 17798.17 14196.92 29498.98 20093.91 29896.45 27399.17 18997.85 15298.41 20897.14 32598.47 3799.92 3598.02 9199.05 27396.92 350
xiu_mvs_v1_base97.86 17798.17 14196.92 29498.98 20093.91 29896.45 27399.17 18997.85 15298.41 20897.14 32598.47 3799.92 3598.02 9199.05 27396.92 350
xiu_mvs_v1_base_debi97.86 17798.17 14196.92 29498.98 20093.91 29896.45 27399.17 18997.85 15298.41 20897.14 32598.47 3799.92 3598.02 9199.05 27396.92 350
NP-MVS98.84 23097.39 19596.84 328
HQP-MVS97.00 24696.49 25998.55 19498.67 26596.79 22396.29 28299.04 21696.05 25795.55 33896.84 32893.84 25799.54 30392.82 31799.26 24599.32 187
API-MVS97.04 24296.91 23297.42 27597.88 32598.23 12498.18 12898.50 28697.57 17097.39 27796.75 33096.77 16299.15 35390.16 34999.02 28094.88 367
131495.74 28695.60 28096.17 31397.53 34092.75 32098.07 14198.31 29491.22 34094.25 35396.68 33195.53 21599.03 35591.64 33497.18 34296.74 354
TR-MVS95.55 29095.12 29796.86 30097.54 33993.94 29696.49 27296.53 33794.36 29997.03 29196.61 33294.26 25199.16 35286.91 35896.31 35397.47 345
Fast-Effi-MVS+97.67 19397.38 20398.57 18998.71 25297.43 19397.23 22599.45 8194.82 28896.13 32496.51 33398.52 3699.91 4596.19 21898.83 29298.37 309
xiu_mvs_v2_base97.16 23397.49 19596.17 31398.54 28392.46 32395.45 31898.84 25497.25 20697.48 27196.49 33498.31 4999.90 4996.34 21098.68 30196.15 361
MVS93.19 32592.09 32996.50 30696.91 35494.03 29298.07 14198.06 30568.01 37094.56 35296.48 33595.96 20299.30 34183.84 36396.89 34796.17 359
PAPM_NR96.82 25496.32 26498.30 21999.07 18096.69 22897.48 20798.76 26795.81 26796.61 31296.47 33694.12 25599.17 35190.82 34797.78 32999.06 235
KD-MVS_2432*160092.87 32791.99 33195.51 32891.37 37589.27 34794.07 35098.14 30195.42 27697.25 28296.44 33767.86 37299.24 34691.28 33996.08 35698.02 319
miper_refine_blended92.87 32791.99 33195.51 32891.37 37589.27 34794.07 35098.14 30195.42 27697.25 28296.44 33767.86 37299.24 34691.28 33996.08 35698.02 319
PVSNet93.40 1795.67 28795.70 27695.57 32598.83 23388.57 34992.50 36297.72 31292.69 32396.49 31996.44 33793.72 26299.43 32693.61 30199.28 24198.71 289
EMVS93.83 31894.02 31093.23 35196.83 35784.96 36589.77 36896.32 33997.92 14697.43 27596.36 34086.17 31898.93 36087.68 35697.73 33095.81 364
MAR-MVS96.47 26895.70 27698.79 16097.92 32399.12 5798.28 11998.60 28192.16 33095.54 34196.17 34194.77 24099.52 30989.62 35198.23 31397.72 336
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
PAPM91.88 33690.34 33996.51 30598.06 31792.56 32192.44 36397.17 32586.35 36190.38 36896.01 34286.61 31499.21 34970.65 37395.43 36097.75 334
PS-MVSNAJ97.08 23797.39 20296.16 31598.56 28092.46 32395.24 32398.85 25397.25 20697.49 27095.99 34398.07 6699.90 4996.37 20798.67 30296.12 362
baseline293.73 31992.83 32596.42 30797.70 33491.28 34096.84 25489.77 37093.96 30892.44 36495.93 34479.14 35899.77 20892.94 31396.76 34998.21 311
alignmvs97.35 21696.88 23398.78 16398.54 28398.09 13497.71 18297.69 31499.20 4997.59 26095.90 34588.12 31099.55 30098.18 8298.96 28798.70 291
ET-MVSNet_ETH3D94.30 31093.21 32097.58 26398.14 31294.47 28294.78 33493.24 36194.72 28989.56 36995.87 34678.57 36199.81 16796.91 15697.11 34498.46 301
thisisatest051594.12 31493.16 32196.97 29298.60 27492.90 31693.77 35690.61 36794.10 30496.91 29695.87 34674.99 36699.80 17694.52 27199.12 26998.20 312
BH-w/o95.13 29894.89 30295.86 31798.20 30991.31 33895.65 31097.37 31993.64 31096.52 31595.70 34893.04 27299.02 35688.10 35595.82 35897.24 347
PMMVS96.51 26495.98 27098.09 23197.53 34095.84 24694.92 33198.84 25491.58 33596.05 32995.58 34995.68 21199.66 26595.59 24898.09 32298.76 285
EIA-MVS98.00 16597.74 17798.80 15898.72 24998.09 13498.05 14599.60 2597.39 19296.63 31095.55 35097.68 9499.80 17696.73 17799.27 24298.52 299
ETV-MVS98.03 16197.86 17198.56 19398.69 26098.07 14097.51 20599.50 6098.10 13597.50 26995.51 35198.41 4199.88 7096.27 21499.24 24797.71 337
PAPR95.29 29494.47 30497.75 25297.50 34495.14 26794.89 33298.71 27591.39 33995.35 34595.48 35294.57 24399.14 35484.95 36197.37 33798.97 253
canonicalmvs98.34 13598.26 13098.58 18698.46 29097.82 16998.96 6399.46 7899.19 5397.46 27295.46 35398.59 3299.46 32298.08 8898.71 29998.46 301
MVEpermissive83.40 2292.50 33091.92 33394.25 34098.83 23391.64 33292.71 36183.52 37695.92 26386.46 37395.46 35395.20 22595.40 37280.51 36998.64 30395.73 365
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
test-LLR93.90 31793.85 31194.04 34196.53 36084.62 36794.05 35292.39 36396.17 25294.12 35595.07 35582.30 34599.67 25795.87 23398.18 31697.82 328
test-mter92.33 33391.76 33694.04 34196.53 36084.62 36794.05 35292.39 36394.00 30794.12 35595.07 35565.63 37999.67 25795.87 23398.18 31697.82 328
thres600view794.45 30693.83 31296.29 30999.06 18491.53 33397.99 15494.24 35498.34 11397.44 27495.01 35779.84 35399.67 25784.33 36298.23 31397.66 338
gm-plane-assit94.83 37281.97 37488.07 35894.99 35899.60 28491.76 331
thres100view90094.19 31193.67 31595.75 32199.06 18491.35 33798.03 14894.24 35498.33 11497.40 27694.98 35979.84 35399.62 27783.05 36498.08 32396.29 357
cascas94.79 30394.33 30996.15 31696.02 36992.36 32692.34 36499.26 16285.34 36495.08 34894.96 36092.96 27398.53 36594.41 27998.59 30697.56 342
TESTMET0.1,192.19 33591.77 33593.46 34896.48 36282.80 37294.05 35291.52 36694.45 29694.00 35894.88 36166.65 37699.56 29795.78 23898.11 32198.02 319
test0.0.03 194.51 30593.69 31496.99 29096.05 36793.61 30894.97 33093.49 35896.17 25297.57 26394.88 36182.30 34599.01 35893.60 30294.17 36798.37 309
DeepMVS_CXcopyleft93.44 34998.24 30694.21 28794.34 35164.28 37191.34 36794.87 36389.45 29992.77 37477.54 37293.14 36893.35 369
IB-MVS91.63 1992.24 33490.90 33896.27 31097.22 35191.24 34194.36 34793.33 36092.37 32692.24 36594.58 36466.20 37899.89 5993.16 31294.63 36497.66 338
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
tfpn200view994.03 31593.44 31795.78 32098.93 20891.44 33597.60 19494.29 35297.94 14497.10 28594.31 36579.67 35599.62 27783.05 36498.08 32396.29 357
thres40094.14 31393.44 31796.24 31198.93 20891.44 33597.60 19494.29 35297.94 14497.10 28594.31 36579.67 35599.62 27783.05 36498.08 32397.66 338
DWT-MVSNet_test92.75 32992.05 33094.85 33596.48 36287.21 35797.83 17094.99 34792.22 32992.72 36394.11 36770.75 36999.46 32295.01 25894.33 36697.87 326
thres20093.72 32093.14 32295.46 33098.66 27091.29 33996.61 26694.63 35097.39 19296.83 30493.71 36879.88 35299.56 29782.40 36798.13 32095.54 366
PVSNet_089.98 2191.15 33790.30 34093.70 34697.72 33184.34 37090.24 36697.42 31890.20 34893.79 35993.09 36990.90 28998.89 36286.57 35972.76 37397.87 326
tmp_tt78.77 34078.73 34378.90 35658.45 37974.76 37994.20 34978.26 37939.16 37286.71 37292.82 37080.50 35175.19 37586.16 36092.29 36986.74 370
GG-mvs-BLEND94.76 33694.54 37392.13 32999.31 2180.47 37888.73 37191.01 37167.59 37498.16 36882.30 36894.53 36593.98 368
X-MVStestdata94.32 30892.59 32699.53 3699.46 9799.21 2798.65 8199.34 12198.62 9997.54 26545.85 37297.50 11599.83 14296.79 16999.53 19399.56 74
testmvs17.12 34220.53 3456.87 35812.05 3804.20 38293.62 3586.73 3814.62 37610.41 37624.33 3738.28 3813.56 3779.69 37515.07 37412.86 373
test12317.04 34320.11 3467.82 35710.25 3814.91 38194.80 3334.47 3824.93 37510.00 37724.28 3749.69 3803.64 37610.14 37412.43 37514.92 372
test_post21.25 37583.86 33899.70 241
test_post197.59 19620.48 37683.07 34299.66 26594.16 282
test_blank0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
uanet_test0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
pcd_1.5k_mvsjas8.17 34410.90 3470.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 37798.07 660.00 3780.00 3760.00 3760.00 374
sosnet-low-res0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
sosnet0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
uncertanet0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
Regformer0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
uanet0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
FOURS199.73 2599.67 299.43 1099.54 5099.43 3099.26 80
MSC_two_6792asdad99.32 7898.43 29398.37 11198.86 25099.89 5997.14 13899.60 16799.71 26
No_MVS99.32 7898.43 29398.37 11198.86 25099.89 5997.14 13899.60 16799.71 26
eth-test20.00 382
eth-test0.00 382
IU-MVS99.49 8699.15 4898.87 24592.97 31899.41 5096.76 17399.62 15899.66 36
save fliter99.11 16997.97 15196.53 26899.02 22298.24 122
test_0728_SECOND99.60 1399.50 7999.23 2598.02 15099.32 12899.88 7096.99 15099.63 15599.68 33
GSMVS98.81 275
test_part299.36 11799.10 6099.05 114
sam_mvs184.74 33098.81 275
sam_mvs84.29 336
MTGPAbinary99.20 174
MTMP97.93 15991.91 365
test9_res93.28 31199.15 26299.38 164
agg_prior292.50 32599.16 25999.37 167
agg_prior98.68 26397.99 14699.01 22595.59 33499.77 208
test_prior497.97 15195.86 301
test_prior98.95 13798.69 26097.95 15699.03 21899.59 28899.30 194
旧先验295.76 30588.56 35797.52 26799.66 26594.48 272
新几何295.93 298
无先验95.74 30798.74 27289.38 35299.73 23092.38 32699.22 213
原ACMM295.53 314
testdata299.79 19092.80 319
segment_acmp97.02 146
testdata195.44 31996.32 249
test1298.93 14098.58 27797.83 16698.66 27796.53 31495.51 21799.69 24599.13 26699.27 201
plane_prior799.19 15097.87 162
plane_prior698.99 19997.70 18094.90 231
plane_prior599.27 15799.70 24194.42 27699.51 19999.45 133
plane_prior397.78 17397.41 19097.79 247
plane_prior297.77 17698.20 128
plane_prior199.05 186
plane_prior97.65 18297.07 23896.72 23599.36 227
n20.00 383
nn0.00 383
door-mid99.57 35
test1198.87 245
door99.41 94
HQP5-MVS96.79 223
HQP-NCC98.67 26596.29 28296.05 25795.55 338
ACMP_Plane98.67 26596.29 28296.05 25795.55 338
BP-MVS92.82 317
HQP4-MVS95.56 33799.54 30399.32 187
HQP3-MVS99.04 21699.26 245
HQP2-MVS93.84 257
MDTV_nov1_ep13_2view74.92 37897.69 18490.06 35097.75 25085.78 32293.52 30498.69 292
ACMMP++_ref99.77 93
ACMMP++99.68 138
Test By Simon96.52 175