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 bysorted bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort by
LCM-MVSNet99.95 199.95 199.95 199.99 199.99 199.95 299.97 299.99 1100.00 199.98 1099.78 6100.00 199.92 1100.00 199.87 9
mvs_tets99.90 299.90 299.90 499.96 499.79 3999.72 2499.88 1999.92 799.98 399.93 1599.94 199.98 899.77 12100.00 199.92 3
jajsoiax99.89 399.89 399.89 799.96 499.78 4299.70 2999.86 2499.89 1499.98 399.90 2399.94 199.98 899.75 13100.00 199.90 4
ANet_high99.88 499.87 499.91 299.99 199.91 299.65 51100.00 199.90 8100.00 199.97 1199.61 1799.97 1999.75 13100.00 199.84 14
LTVRE_ROB99.19 199.88 499.87 499.88 1199.91 1599.90 599.96 199.92 999.90 899.97 699.87 3399.81 599.95 4799.54 3099.99 1299.80 25
Andreas Kuhn, Heiko Hirschmüller, Daniel Scharstein, Helmut Mayer: A TV Prior for High-Quality Scalable Multi-View Stereo Reconstruction. International Journal of Computer Vision 2016
pmmvs699.86 699.86 699.83 2199.94 1099.90 599.83 699.91 1299.85 2799.94 1299.95 1399.73 899.90 13799.65 1799.97 3399.69 57
UniMVSNet_ETH3D99.85 799.83 799.90 499.89 2199.91 299.89 499.71 9799.93 599.95 1199.89 2799.71 999.96 3799.51 3599.97 3399.84 14
PS-MVSNAJss99.84 899.82 899.89 799.96 499.77 4599.68 3899.85 2899.95 399.98 399.92 1899.28 4299.98 899.75 13100.00 199.94 2
test_djsdf99.84 899.81 999.91 299.94 1099.84 2199.77 1299.80 5199.73 4699.97 699.92 1899.77 799.98 899.43 43100.00 199.90 4
v7n99.82 1099.80 1099.88 1199.96 499.84 2199.82 899.82 4199.84 3099.94 1299.91 2199.13 6099.96 3799.83 999.99 1299.83 18
anonymousdsp99.80 1199.77 1299.90 499.96 499.88 999.73 2199.85 2899.70 5599.92 1999.93 1599.45 2499.97 1999.36 55100.00 199.85 13
pm-mvs199.79 1299.79 1199.78 3799.91 1599.83 2599.76 1499.87 2199.73 4699.89 2799.87 3399.63 1499.87 18199.54 3099.92 7999.63 102
UA-Net99.78 1399.76 1499.86 1699.72 11199.71 7199.91 399.95 799.96 299.71 10499.91 2199.15 5599.97 1999.50 37100.00 199.90 4
TransMVSNet (Re)99.78 1399.77 1299.81 2699.91 1599.85 1699.75 1699.86 2499.70 5599.91 2199.89 2799.60 1999.87 18199.59 2399.74 19299.71 50
OurMVSNet-221017-099.75 1599.71 1699.84 1999.96 499.83 2599.83 699.85 2899.80 3999.93 1599.93 1598.54 13999.93 7599.59 2399.98 2499.76 41
Vis-MVSNetpermissive99.75 1599.74 1599.79 3499.88 2599.66 8999.69 3599.92 999.67 6499.77 7699.75 8899.61 1799.98 899.35 5699.98 2499.72 47
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
TDRefinement99.72 1799.70 1799.77 4099.90 1999.85 1699.86 599.92 999.69 5899.78 7199.92 1899.37 3299.88 16898.93 11899.95 5499.60 128
XXY-MVS99.71 1899.67 2299.81 2699.89 2199.72 6999.59 6699.82 4199.39 11799.82 5399.84 4799.38 3099.91 11799.38 5199.93 7599.80 25
nrg03099.70 1999.66 2399.82 2399.76 8799.84 2199.61 5999.70 10299.93 599.78 7199.68 13299.10 6199.78 28499.45 4199.96 4599.83 18
FC-MVSNet-test99.70 1999.65 2599.86 1699.88 2599.86 1399.72 2499.78 6299.90 899.82 5399.83 4898.45 15499.87 18199.51 3599.97 3399.86 11
GeoE99.69 2199.66 2399.78 3799.76 8799.76 5299.60 6499.82 4199.46 10699.75 8499.56 20599.63 1499.95 4799.43 4399.88 10799.62 113
v1099.69 2199.69 1999.66 9999.81 5399.39 15799.66 4699.75 7799.60 8699.92 1999.87 3398.75 11299.86 20199.90 299.99 1299.73 46
DROMVSNet99.69 2199.69 1999.68 8999.71 11499.91 299.76 1499.96 599.86 2299.51 18399.39 25799.57 2099.93 7599.64 2099.86 12399.20 266
v899.68 2499.69 1999.65 10499.80 5899.40 15599.66 4699.76 7099.64 7299.93 1599.85 4298.66 12399.84 23699.88 699.99 1299.71 50
DTE-MVSNet99.68 2499.61 3399.88 1199.80 5899.87 1099.67 4299.71 9799.72 4999.84 4699.78 7398.67 12199.97 1999.30 6699.95 5499.80 25
CS-MVS99.67 2699.70 1799.59 13499.54 18699.86 1399.80 1099.96 599.90 899.59 15099.41 24999.51 2399.95 4799.65 1799.90 8998.97 310
VPA-MVSNet99.66 2799.62 2999.79 3499.68 13599.75 5699.62 5499.69 10899.85 2799.80 6399.81 5898.81 9799.91 11799.47 3999.88 10799.70 53
PS-CasMVS99.66 2799.58 4099.89 799.80 5899.85 1699.66 4699.73 8599.62 7699.84 4699.71 10898.62 12799.96 3799.30 6699.96 4599.86 11
PEN-MVS99.66 2799.59 3699.89 799.83 3999.87 1099.66 4699.73 8599.70 5599.84 4699.73 9598.56 13699.96 3799.29 6999.94 6799.83 18
FMVSNet199.66 2799.63 2899.73 7399.78 7599.77 4599.68 3899.70 10299.67 6499.82 5399.83 4898.98 7899.90 13799.24 7399.97 3399.53 167
MIMVSNet199.66 2799.62 2999.80 2999.94 1099.87 1099.69 3599.77 6599.78 4299.93 1599.89 2797.94 20399.92 9599.65 1799.98 2499.62 113
FIs99.65 3299.58 4099.84 1999.84 3599.85 1699.66 4699.75 7799.86 2299.74 9399.79 6698.27 17599.85 21999.37 5499.93 7599.83 18
KD-MVS_self_test99.63 3399.59 3699.76 4799.84 3599.90 599.37 9999.79 5799.83 3399.88 3399.85 4298.42 15899.90 13799.60 2299.73 19999.49 190
casdiffmvs99.63 3399.61 3399.67 9299.79 6899.59 11399.13 17499.85 2899.79 4199.76 7899.72 10199.33 3799.82 25799.21 7699.94 6799.59 137
baseline99.63 3399.62 2999.66 9999.80 5899.62 10299.44 8799.80 5199.71 5099.72 9999.69 12199.15 5599.83 24799.32 6399.94 6799.53 167
Anonymous2023121199.62 3699.57 4399.76 4799.61 15299.60 11099.81 999.73 8599.82 3599.90 2399.90 2397.97 20299.86 20199.42 4899.96 4599.80 25
DeepC-MVS98.90 499.62 3699.61 3399.67 9299.72 11199.44 14399.24 13799.71 9799.27 13299.93 1599.90 2399.70 1199.93 7598.99 10699.99 1299.64 97
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
dcpmvs_299.61 3899.64 2799.53 15799.79 6898.82 24499.58 6899.97 299.95 399.96 899.76 8398.44 15599.99 599.34 5799.96 4599.78 33
WR-MVS_H99.61 3899.53 5299.87 1499.80 5899.83 2599.67 4299.75 7799.58 8999.85 4399.69 12198.18 18799.94 6199.28 7199.95 5499.83 18
CS-MVS-test99.59 4099.59 3699.60 13199.55 18499.86 1399.60 6499.94 899.90 899.59 15098.89 34399.24 4799.95 4799.66 1699.90 8998.98 309
ACMH98.42 699.59 4099.54 4899.72 7999.86 3199.62 10299.56 7299.79 5798.77 20499.80 6399.85 4299.64 1399.85 21998.70 13699.89 9999.70 53
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
v119299.57 4299.57 4399.57 14499.77 8399.22 19899.04 19399.60 16199.18 14799.87 4099.72 10199.08 6799.85 21999.89 599.98 2499.66 80
EG-PatchMatch MVS99.57 4299.56 4799.62 12699.77 8399.33 17399.26 12999.76 7099.32 12699.80 6399.78 7399.29 4099.87 18199.15 9099.91 8899.66 80
Gipumacopyleft99.57 4299.59 3699.49 16899.98 399.71 7199.72 2499.84 3499.81 3699.94 1299.78 7398.91 8799.71 30998.41 15099.95 5499.05 300
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
v192192099.56 4599.57 4399.55 15199.75 9899.11 21299.05 19199.61 14999.15 15799.88 3399.71 10899.08 6799.87 18199.90 299.97 3399.66 80
v124099.56 4599.58 4099.51 16299.80 5899.00 22499.00 20199.65 13199.15 15799.90 2399.75 8899.09 6399.88 16899.90 299.96 4599.67 70
V4299.56 4599.54 4899.63 11799.79 6899.46 13699.39 9399.59 16899.24 13899.86 4199.70 11598.55 13799.82 25799.79 1199.95 5499.60 128
v14419299.55 4899.54 4899.58 13999.78 7599.20 20499.11 18099.62 14299.18 14799.89 2799.72 10198.66 12399.87 18199.88 699.97 3399.66 80
test20.0399.55 4899.54 4899.58 13999.79 6899.37 16399.02 19799.89 1699.60 8699.82 5399.62 16898.81 9799.89 15399.43 4399.86 12399.47 200
v114499.54 5099.53 5299.59 13499.79 6899.28 18199.10 18199.61 14999.20 14599.84 4699.73 9598.67 12199.84 23699.86 899.98 2499.64 97
CP-MVSNet99.54 5099.43 6699.87 1499.76 8799.82 2999.57 7099.61 14999.54 9099.80 6399.64 14997.79 21699.95 4799.21 7699.94 6799.84 14
TranMVSNet+NR-MVSNet99.54 5099.47 5699.76 4799.58 16399.64 9699.30 11699.63 13999.61 8099.71 10499.56 20598.76 11099.96 3799.14 9699.92 7999.68 63
patch_mono-299.51 5399.46 6099.64 11199.70 12299.11 21299.04 19399.87 2199.71 5099.47 18999.79 6698.24 17799.98 899.38 5199.96 4599.83 18
v2v48299.50 5499.47 5699.58 13999.78 7599.25 18999.14 16899.58 17799.25 13699.81 6099.62 16898.24 17799.84 23699.83 999.97 3399.64 97
ACMH+98.40 899.50 5499.43 6699.71 8399.86 3199.76 5299.32 10999.77 6599.53 9299.77 7699.76 8399.26 4699.78 28497.77 20699.88 10799.60 128
Baseline_NR-MVSNet99.49 5699.37 7699.82 2399.91 1599.84 2198.83 22899.86 2499.68 6099.65 12599.88 3097.67 22499.87 18199.03 10399.86 12399.76 41
TAMVS99.49 5699.45 6199.63 11799.48 21999.42 15099.45 8499.57 17999.66 6899.78 7199.83 4897.85 21299.86 20199.44 4299.96 4599.61 124
pmmvs-eth3d99.48 5899.47 5699.51 16299.77 8399.41 15498.81 23399.66 12099.42 11699.75 8499.66 14299.20 5099.76 29498.98 10899.99 1299.36 234
EI-MVSNet-UG-set99.48 5899.50 5499.42 18999.57 17398.65 25899.24 13799.46 23699.68 6099.80 6399.66 14298.99 7799.89 15399.19 8199.90 8999.72 47
APDe-MVS99.48 5899.36 7999.85 1899.55 18499.81 3299.50 7799.69 10898.99 17399.75 8499.71 10898.79 10499.93 7598.46 14899.85 12799.80 25
PMMVS299.48 5899.45 6199.57 14499.76 8798.99 22598.09 30299.90 1598.95 17999.78 7199.58 19499.57 2099.93 7599.48 3899.95 5499.79 31
DSMNet-mixed99.48 5899.65 2598.95 26699.71 11497.27 31899.50 7799.82 4199.59 8899.41 20999.85 4299.62 16100.00 199.53 3299.89 9999.59 137
DP-MVS99.48 5899.39 7199.74 6399.57 17399.62 10299.29 12399.61 14999.87 2099.74 9399.76 8398.69 11799.87 18198.20 16899.80 16499.75 44
EI-MVSNet-Vis-set99.47 6499.49 5599.42 18999.57 17398.66 25599.24 13799.46 23699.67 6499.79 6899.65 14798.97 8099.89 15399.15 9099.89 9999.71 50
VPNet99.46 6599.37 7699.71 8399.82 4699.59 11399.48 8199.70 10299.81 3699.69 11099.58 19497.66 22899.86 20199.17 8699.44 28099.67 70
ACMM98.09 1199.46 6599.38 7399.72 7999.80 5899.69 8299.13 17499.65 13198.99 17399.64 12799.72 10199.39 2699.86 20198.23 16599.81 15999.60 128
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
Regformer-499.45 6799.44 6399.50 16599.52 19798.94 23299.17 15899.53 20599.64 7299.76 7899.60 18698.96 8399.90 13798.91 11999.84 13299.67 70
COLMAP_ROBcopyleft98.06 1299.45 6799.37 7699.70 8799.83 3999.70 7899.38 9599.78 6299.53 9299.67 11799.78 7399.19 5199.86 20197.32 24399.87 11699.55 154
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
Anonymous2024052199.44 6999.42 6899.49 16899.89 2198.96 23099.62 5499.76 7099.85 2799.82 5399.88 3096.39 27399.97 1999.59 2399.98 2499.55 154
tfpnnormal99.43 7099.38 7399.60 13199.87 2999.75 5699.59 6699.78 6299.71 5099.90 2399.69 12198.85 9599.90 13797.25 25399.78 17599.15 277
HPM-MVS_fast99.43 7099.30 9299.80 2999.83 3999.81 3299.52 7599.70 10298.35 24899.51 18399.50 22699.31 3899.88 16898.18 17299.84 13299.69 57
3Dnovator99.15 299.43 7099.36 7999.65 10499.39 24799.42 15099.70 2999.56 18499.23 14099.35 22099.80 6099.17 5399.95 4798.21 16799.84 13299.59 137
Anonymous2024052999.42 7399.34 8199.65 10499.53 19299.60 11099.63 5399.39 25899.47 10299.76 7899.78 7398.13 18999.86 20198.70 13699.68 21999.49 190
SixPastTwentyTwo99.42 7399.30 9299.76 4799.92 1499.67 8799.70 2999.14 30999.65 7099.89 2799.90 2396.20 27899.94 6199.42 4899.92 7999.67 70
GBi-Net99.42 7399.31 8799.73 7399.49 21399.77 4599.68 3899.70 10299.44 10999.62 13999.83 4897.21 24799.90 13798.96 11299.90 8999.53 167
test199.42 7399.31 8799.73 7399.49 21399.77 4599.68 3899.70 10299.44 10999.62 13999.83 4897.21 24799.90 13798.96 11299.90 8999.53 167
Regformer-399.41 7799.41 6999.40 19999.52 19798.70 25199.17 15899.44 24199.62 7699.75 8499.60 18698.90 9099.85 21998.89 12099.84 13299.65 88
MVSFormer99.41 7799.44 6399.31 22399.57 17398.40 27299.77 1299.80 5199.73 4699.63 13199.30 27998.02 19799.98 899.43 4399.69 21499.55 154
IterMVS-LS99.41 7799.47 5699.25 23599.81 5398.09 29198.85 22599.76 7099.62 7699.83 5199.64 14998.54 13999.97 1999.15 9099.99 1299.68 63
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
SED-MVS99.40 8099.28 9999.77 4099.69 12699.82 2999.20 14799.54 19699.13 15999.82 5399.63 15998.91 8799.92 9597.85 20199.70 21199.58 142
v14899.40 8099.41 6999.39 20299.76 8798.94 23299.09 18599.59 16899.17 15199.81 6099.61 17798.41 15999.69 31799.32 6399.94 6799.53 167
NR-MVSNet99.40 8099.31 8799.68 8999.43 23699.55 12299.73 2199.50 22199.46 10699.88 3399.36 26597.54 23299.87 18198.97 11099.87 11699.63 102
PVSNet_Blended_VisFu99.40 8099.38 7399.44 18399.90 1998.66 25598.94 21699.91 1297.97 27499.79 6899.73 9599.05 7299.97 1999.15 9099.99 1299.68 63
EU-MVSNet99.39 8499.62 2998.72 29399.88 2596.44 33499.56 7299.85 2899.90 899.90 2399.85 4298.09 19199.83 24799.58 2699.95 5499.90 4
CHOSEN 1792x268899.39 8499.30 9299.65 10499.88 2599.25 18998.78 24099.88 1998.66 21299.96 899.79 6697.45 23599.93 7599.34 5799.99 1299.78 33
DVP-MVS++99.38 8699.25 10699.77 4099.03 32399.77 4599.74 1899.61 14999.18 14799.76 7899.61 17799.00 7599.92 9597.72 21299.60 24899.62 113
EI-MVSNet99.38 8699.44 6399.21 24099.58 16398.09 29199.26 12999.46 23699.62 7699.75 8499.67 13898.54 13999.85 21999.15 9099.92 7999.68 63
UGNet99.38 8699.34 8199.49 16898.90 33398.90 24099.70 2999.35 26999.86 2298.57 31799.81 5898.50 14999.93 7599.38 5199.98 2499.66 80
Wanjuan Su, Qingshan Xu, Wenbing Tao: Uncertainty-guided Multi-view Stereo Network for Depth Estimation. IEEE Transactions on Circuits and Systems for Video Technology, 2022
UniMVSNet_NR-MVSNet99.37 8999.25 10699.72 7999.47 22499.56 11998.97 21299.61 14999.43 11499.67 11799.28 28497.85 21299.95 4799.17 8699.81 15999.65 88
UniMVSNet (Re)99.37 8999.26 10499.68 8999.51 20299.58 11698.98 21099.60 16199.43 11499.70 10799.36 26597.70 21999.88 16899.20 7999.87 11699.59 137
CSCG99.37 8999.29 9799.60 13199.71 11499.46 13699.43 8999.85 2898.79 20199.41 20999.60 18698.92 8599.92 9598.02 18299.92 7999.43 217
PM-MVS99.36 9299.29 9799.58 13999.83 3999.66 8998.95 21499.86 2498.85 19399.81 6099.73 9598.40 16399.92 9598.36 15399.83 14299.17 273
abl_699.36 9299.23 11099.75 5799.71 11499.74 6299.33 10699.76 7099.07 16699.65 12599.63 15999.09 6399.92 9597.13 26199.76 18199.58 142
new-patchmatchnet99.35 9499.57 4398.71 29599.82 4696.62 33298.55 26199.75 7799.50 9599.88 3399.87 3399.31 3899.88 16899.43 43100.00 199.62 113
Anonymous2023120699.35 9499.31 8799.47 17499.74 10499.06 22399.28 12499.74 8299.23 14099.72 9999.53 21797.63 23099.88 16899.11 9899.84 13299.48 195
MTAPA99.35 9499.20 11299.80 2999.81 5399.81 3299.33 10699.53 20599.27 13299.42 20199.63 15998.21 18299.95 4797.83 20499.79 16999.65 88
FMVSNet299.35 9499.28 9999.55 15199.49 21399.35 17099.45 8499.57 17999.44 10999.70 10799.74 9197.21 24799.87 18199.03 10399.94 6799.44 211
3Dnovator+98.92 399.35 9499.24 10899.67 9299.35 25799.47 13299.62 5499.50 22199.44 10999.12 26499.78 7398.77 10999.94 6197.87 19899.72 20599.62 113
TSAR-MVS + MP.99.34 9999.24 10899.63 11799.82 4699.37 16399.26 12999.35 26998.77 20499.57 15799.70 11599.27 4599.88 16897.71 21499.75 18499.65 88
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
Regformer-299.34 9999.27 10299.53 15799.41 24299.10 21798.99 20699.53 20599.47 10299.66 12199.52 21998.80 10199.89 15398.31 15999.74 19299.60 128
diffmvs99.34 9999.32 8699.39 20299.67 14098.77 24898.57 25999.81 5099.61 8099.48 18799.41 24998.47 15099.86 20198.97 11099.90 8999.53 167
DELS-MVS99.34 9999.30 9299.48 17299.51 20299.36 16698.12 29899.53 20599.36 12199.41 20999.61 17799.22 4999.87 18199.21 7699.68 21999.20 266
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
DU-MVS99.33 10399.21 11199.71 8399.43 23699.56 11998.83 22899.53 20599.38 11899.67 11799.36 26597.67 22499.95 4799.17 8699.81 15999.63 102
ab-mvs99.33 10399.28 9999.47 17499.57 17399.39 15799.78 1199.43 24598.87 19199.57 15799.82 5598.06 19499.87 18198.69 13899.73 19999.15 277
DVP-MVScopyleft99.32 10599.17 11599.77 4099.69 12699.80 3799.14 16899.31 27899.16 15399.62 13999.61 17798.35 16799.91 11797.88 19599.72 20599.61 124
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
Regformer-199.32 10599.27 10299.47 17499.41 24298.95 23198.99 20699.48 22899.48 9799.66 12199.52 21998.78 10699.87 18198.36 15399.74 19299.60 128
APD-MVS_3200maxsize99.31 10799.16 11699.74 6399.53 19299.75 5699.27 12799.61 14999.19 14699.57 15799.64 14998.76 11099.90 13797.29 24599.62 23899.56 151
zzz-MVS99.30 10899.14 12099.80 2999.81 5399.81 3298.73 24699.53 20599.27 13299.42 20199.63 15998.21 18299.95 4797.83 20499.79 16999.65 88
SteuartSystems-ACMMP99.30 10899.14 12099.76 4799.87 2999.66 8999.18 15399.60 16198.55 22399.57 15799.67 13899.03 7499.94 6197.01 26599.80 16499.69 57
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testgi99.29 11099.26 10499.37 20999.75 9898.81 24598.84 22699.89 1698.38 24199.75 8499.04 32199.36 3599.86 20199.08 10099.25 30799.45 206
ACMMP_NAP99.28 11199.11 13099.79 3499.75 9899.81 3298.95 21499.53 20598.27 25799.53 17699.73 9598.75 11299.87 18197.70 21799.83 14299.68 63
LCM-MVSNet-Re99.28 11199.15 11999.67 9299.33 27299.76 5299.34 10499.97 298.93 18399.91 2199.79 6698.68 11899.93 7596.80 27899.56 25599.30 246
mvs_anonymous99.28 11199.39 7198.94 26799.19 29997.81 30399.02 19799.55 19099.78 4299.85 4399.80 6098.24 17799.86 20199.57 2799.50 27299.15 277
MVS_Test99.28 11199.31 8799.19 24399.35 25798.79 24799.36 10299.49 22699.17 15199.21 25099.67 13898.78 10699.66 33799.09 9999.66 23099.10 287
SR-MVS-dyc-post99.27 11599.11 13099.73 7399.54 18699.74 6299.26 12999.62 14299.16 15399.52 17899.64 14998.41 15999.91 11797.27 24899.61 24599.54 162
XVS99.27 11599.11 13099.75 5799.71 11499.71 7199.37 9999.61 14999.29 12898.76 30399.47 23998.47 15099.88 16897.62 22599.73 19999.67 70
OPM-MVS99.26 11799.13 12399.63 11799.70 12299.61 10898.58 25599.48 22898.50 22999.52 17899.63 15999.14 5899.76 29497.89 19499.77 17999.51 179
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
HFP-MVS99.25 11899.08 14199.76 4799.73 10799.70 7899.31 11399.59 16898.36 24399.36 21899.37 26098.80 10199.91 11797.43 23899.75 18499.68 63
HPM-MVScopyleft99.25 11899.07 14599.78 3799.81 5399.75 5699.61 5999.67 11697.72 28899.35 22099.25 29199.23 4899.92 9597.21 25699.82 15199.67 70
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
ACMMPcopyleft99.25 11899.08 14199.74 6399.79 6899.68 8599.50 7799.65 13198.07 26899.52 17899.69 12198.57 13499.92 9597.18 25899.79 16999.63 102
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
LS3D99.24 12199.11 13099.61 12998.38 36299.79 3999.57 7099.68 11199.61 8099.15 25999.71 10898.70 11699.91 11797.54 23199.68 21999.13 284
test117299.23 12299.05 15199.74 6399.52 19799.75 5699.20 14799.61 14998.97 17599.48 18799.58 19498.41 15999.91 11797.15 26099.55 25999.57 148
xiu_mvs_v1_base_debu99.23 12299.34 8198.91 27399.59 15898.23 28098.47 27099.66 12099.61 8099.68 11298.94 33899.39 2699.97 1999.18 8399.55 25998.51 338
xiu_mvs_v1_base99.23 12299.34 8198.91 27399.59 15898.23 28098.47 27099.66 12099.61 8099.68 11298.94 33899.39 2699.97 1999.18 8399.55 25998.51 338
xiu_mvs_v1_base_debi99.23 12299.34 8198.91 27399.59 15898.23 28098.47 27099.66 12099.61 8099.68 11298.94 33899.39 2699.97 1999.18 8399.55 25998.51 338
region2R99.23 12299.05 15199.77 4099.76 8799.70 7899.31 11399.59 16898.41 23799.32 22799.36 26598.73 11599.93 7597.29 24599.74 19299.67 70
ACMMPR99.23 12299.06 14799.76 4799.74 10499.69 8299.31 11399.59 16898.36 24399.35 22099.38 25998.61 12999.93 7597.43 23899.75 18499.67 70
XVG-ACMP-BASELINE99.23 12299.10 13899.63 11799.82 4699.58 11698.83 22899.72 9498.36 24399.60 14799.71 10898.92 8599.91 11797.08 26399.84 13299.40 223
CP-MVS99.23 12299.05 15199.75 5799.66 14199.66 8999.38 9599.62 14298.38 24199.06 27299.27 28698.79 10499.94 6197.51 23499.82 15199.66 80
DeepC-MVS_fast98.47 599.23 12299.12 12799.56 14899.28 28399.22 19898.99 20699.40 25599.08 16499.58 15499.64 14998.90 9099.83 24797.44 23799.75 18499.63 102
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
ZNCC-MVS99.22 13199.04 15799.77 4099.76 8799.73 6599.28 12499.56 18498.19 26299.14 26199.29 28298.84 9699.92 9597.53 23399.80 16499.64 97
D2MVS99.22 13199.19 11399.29 22699.69 12698.74 24998.81 23399.41 24898.55 22399.68 11299.69 12198.13 18999.87 18198.82 12599.98 2499.24 255
LPG-MVS_test99.22 13199.05 15199.74 6399.82 4699.63 10099.16 16499.73 8597.56 29499.64 12799.69 12199.37 3299.89 15396.66 28699.87 11699.69 57
CDS-MVSNet99.22 13199.13 12399.50 16599.35 25799.11 21298.96 21399.54 19699.46 10699.61 14599.70 11596.31 27599.83 24799.34 5799.88 10799.55 154
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
test_040299.22 13199.14 12099.45 18199.79 6899.43 14799.28 12499.68 11199.54 9099.40 21499.56 20599.07 6999.82 25796.01 31499.96 4599.11 285
AllTest99.21 13699.07 14599.63 11799.78 7599.64 9699.12 17899.83 3698.63 21599.63 13199.72 10198.68 11899.75 29896.38 30199.83 14299.51 179
XVG-OURS99.21 13699.06 14799.65 10499.82 4699.62 10297.87 32699.74 8298.36 24399.66 12199.68 13299.71 999.90 13796.84 27699.88 10799.43 217
Fast-Effi-MVS+-dtu99.20 13899.12 12799.43 18799.25 28899.69 8299.05 19199.82 4199.50 9598.97 27699.05 31898.98 7899.98 898.20 16899.24 30998.62 330
VDD-MVS99.20 13899.11 13099.44 18399.43 23698.98 22699.50 7798.32 34599.80 3999.56 16499.69 12196.99 25799.85 21998.99 10699.73 19999.50 185
PGM-MVS99.20 13899.01 16399.77 4099.75 9899.71 7199.16 16499.72 9497.99 27299.42 20199.60 18698.81 9799.93 7596.91 27099.74 19299.66 80
SR-MVS99.19 14199.00 16699.74 6399.51 20299.72 6999.18 15399.60 16198.85 19399.47 18999.58 19498.38 16499.92 9596.92 26999.54 26599.57 148
SMA-MVScopyleft99.19 14199.00 16699.73 7399.46 22999.73 6599.13 17499.52 21397.40 30599.57 15799.64 14998.93 8499.83 24797.61 22799.79 16999.63 102
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
pmmvs599.19 14199.11 13099.42 18999.76 8798.88 24198.55 26199.73 8598.82 19799.72 9999.62 16896.56 26499.82 25799.32 6399.95 5499.56 151
mPP-MVS99.19 14199.00 16699.76 4799.76 8799.68 8599.38 9599.54 19698.34 25299.01 27499.50 22698.53 14399.93 7597.18 25899.78 17599.66 80
ETV-MVS99.18 14599.18 11499.16 24699.34 26799.28 18199.12 17899.79 5799.48 9798.93 28098.55 35999.40 2599.93 7598.51 14699.52 26998.28 348
VNet99.18 14599.06 14799.56 14899.24 29099.36 16699.33 10699.31 27899.67 6499.47 18999.57 20296.48 26799.84 23699.15 9099.30 30199.47 200
RPSCF99.18 14599.02 16099.64 11199.83 3999.85 1699.44 8799.82 4198.33 25399.50 18599.78 7397.90 20699.65 34496.78 27999.83 14299.44 211
DeepPCF-MVS98.42 699.18 14599.02 16099.67 9299.22 29299.75 5697.25 35399.47 23298.72 20999.66 12199.70 11599.29 4099.63 34798.07 18199.81 15999.62 113
EPP-MVSNet99.17 14999.00 16699.66 9999.80 5899.43 14799.70 2999.24 29599.48 9799.56 16499.77 8094.89 29299.93 7598.72 13599.89 9999.63 102
GST-MVS99.16 15098.96 17799.75 5799.73 10799.73 6599.20 14799.55 19098.22 25999.32 22799.35 27098.65 12599.91 11796.86 27399.74 19299.62 113
MVP-Stereo99.16 15099.08 14199.43 18799.48 21999.07 22199.08 18899.55 19098.63 21599.31 23199.68 13298.19 18599.78 28498.18 17299.58 25399.45 206
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
XVG-OURS-SEG-HR99.16 15098.99 17199.66 9999.84 3599.64 9698.25 28899.73 8598.39 24099.63 13199.43 24799.70 1199.90 13797.34 24298.64 33999.44 211
jason99.16 15099.11 13099.32 22099.75 9898.44 26998.26 28799.39 25898.70 21099.74 9399.30 27998.54 13999.97 1998.48 14799.82 15199.55 154
jason: jason.
DPE-MVScopyleft99.14 15498.92 18499.82 2399.57 17399.77 4598.74 24499.60 16198.55 22399.76 7899.69 12198.23 18199.92 9596.39 30099.75 18499.76 41
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
MP-MVS-pluss99.14 15498.92 18499.80 2999.83 3999.83 2598.61 25199.63 13996.84 32699.44 19599.58 19498.81 9799.91 11797.70 21799.82 15199.67 70
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
pmmvs499.13 15699.06 14799.36 21299.57 17399.10 21798.01 31099.25 29298.78 20399.58 15499.44 24698.24 17799.76 29498.74 13399.93 7599.22 260
MVS_111021_LR99.13 15699.03 15999.42 18999.58 16399.32 17597.91 32599.73 8598.68 21199.31 23199.48 23499.09 6399.66 33797.70 21799.77 17999.29 249
EIA-MVS99.12 15899.01 16399.45 18199.36 25599.62 10299.34 10499.79 5798.41 23798.84 29398.89 34398.75 11299.84 23698.15 17699.51 27098.89 317
#test#99.12 15898.90 18899.76 4799.73 10799.70 7899.10 18199.59 16897.60 29399.36 21899.37 26098.80 10199.91 11796.84 27699.75 18499.68 63
TSAR-MVS + GP.99.12 15899.04 15799.38 20699.34 26799.16 20798.15 29499.29 28398.18 26399.63 13199.62 16899.18 5299.68 32898.20 16899.74 19299.30 246
MVS_111021_HR99.12 15899.02 16099.40 19999.50 20899.11 21297.92 32399.71 9798.76 20799.08 26899.47 23999.17 5399.54 35797.85 20199.76 18199.54 162
xxxxxxxxxxxxxcwj99.11 16298.96 17799.54 15599.53 19299.25 18998.29 28499.76 7099.07 16699.42 20199.61 17798.86 9399.87 18196.45 29899.68 21999.49 190
CANet99.11 16299.05 15199.28 22898.83 34298.56 26198.71 24999.41 24899.25 13699.23 24499.22 29897.66 22899.94 6199.19 8199.97 3399.33 240
WR-MVS99.11 16298.93 18099.66 9999.30 27899.42 15098.42 27699.37 26599.04 17199.57 15799.20 30296.89 25999.86 20198.66 14099.87 11699.70 53
PHI-MVS99.11 16298.95 17999.59 13499.13 30799.59 11399.17 15899.65 13197.88 28099.25 24099.46 24298.97 8099.80 27897.26 25099.82 15199.37 231
SF-MVS99.10 16698.93 18099.62 12699.58 16399.51 12799.13 17499.65 13197.97 27499.42 20199.61 17798.86 9399.87 18196.45 29899.68 21999.49 190
MSDG99.08 16798.98 17499.37 20999.60 15499.13 21097.54 33999.74 8298.84 19699.53 17699.55 21299.10 6199.79 28197.07 26499.86 12399.18 271
Effi-MVS+-dtu99.07 16898.92 18499.52 15998.89 33699.78 4299.15 16699.66 12099.34 12298.92 28399.24 29697.69 22199.98 898.11 17899.28 30398.81 324
Effi-MVS+99.06 16998.97 17599.34 21499.31 27498.98 22698.31 28399.91 1298.81 19898.79 29998.94 33899.14 5899.84 23698.79 12798.74 33599.20 266
MP-MVScopyleft99.06 16998.83 19799.76 4799.76 8799.71 7199.32 10999.50 22198.35 24898.97 27699.48 23498.37 16599.92 9595.95 32099.75 18499.63 102
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
MDA-MVSNet-bldmvs99.06 16999.05 15199.07 25899.80 5897.83 30298.89 21899.72 9499.29 12899.63 13199.70 11596.47 26899.89 15398.17 17499.82 15199.50 185
MSLP-MVS++99.05 17299.09 13998.91 27399.21 29498.36 27698.82 23299.47 23298.85 19398.90 28699.56 20598.78 10699.09 37098.57 14399.68 21999.26 252
1112_ss99.05 17298.84 19599.67 9299.66 14199.29 17998.52 26699.82 4197.65 29199.43 19999.16 30596.42 27099.91 11799.07 10199.84 13299.80 25
ACMP97.51 1499.05 17298.84 19599.67 9299.78 7599.55 12298.88 21999.66 12097.11 32099.47 18999.60 18699.07 6999.89 15396.18 30999.85 12799.58 142
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
MSP-MVS99.04 17598.79 20299.81 2699.78 7599.73 6599.35 10399.57 17998.54 22699.54 17198.99 32896.81 26199.93 7596.97 26799.53 26799.77 37
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
PVSNet_BlendedMVS99.03 17699.01 16399.09 25499.54 18697.99 29598.58 25599.82 4197.62 29299.34 22399.71 10898.52 14699.77 29297.98 18799.97 3399.52 177
IS-MVSNet99.03 17698.85 19399.55 15199.80 5899.25 18999.73 2199.15 30899.37 11999.61 14599.71 10894.73 29599.81 27397.70 21799.88 10799.58 142
xiu_mvs_v2_base99.02 17899.11 13098.77 29099.37 25398.09 29198.13 29799.51 21799.47 10299.42 20198.54 36099.38 3099.97 1998.83 12399.33 29898.24 350
Fast-Effi-MVS+99.02 17898.87 19199.46 17799.38 25099.50 12899.04 19399.79 5797.17 31698.62 31298.74 35299.34 3699.95 4798.32 15899.41 28698.92 315
canonicalmvs99.02 17899.00 16699.09 25499.10 31598.70 25199.61 5999.66 12099.63 7598.64 31197.65 37399.04 7399.54 35798.79 12798.92 32499.04 301
MCST-MVS99.02 17898.81 19999.65 10499.58 16399.49 12998.58 25599.07 31298.40 23999.04 27399.25 29198.51 14899.80 27897.31 24499.51 27099.65 88
SD-MVS99.01 18299.30 9298.15 31599.50 20899.40 15598.94 21699.61 14999.22 14499.75 8499.82 5599.54 2295.51 37797.48 23599.87 11699.54 162
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
LF4IMVS99.01 18298.92 18499.27 23099.71 11499.28 18198.59 25499.77 6598.32 25499.39 21599.41 24998.62 12799.84 23696.62 29099.84 13298.69 328
IterMVS-SCA-FT99.00 18499.16 11698.51 30099.75 9895.90 34298.07 30599.84 3499.84 3099.89 2799.73 9596.01 28299.99 599.33 61100.00 199.63 102
MS-PatchMatch99.00 18498.97 17599.09 25499.11 31498.19 28398.76 24399.33 27298.49 23199.44 19599.58 19498.21 18299.69 31798.20 16899.62 23899.39 226
PS-MVSNAJ99.00 18499.08 14198.76 29199.37 25398.10 29098.00 31299.51 21799.47 10299.41 20998.50 36299.28 4299.97 1998.83 12399.34 29698.20 354
CNVR-MVS98.99 18798.80 20199.56 14899.25 28899.43 14798.54 26499.27 28798.58 22098.80 29899.43 24798.53 14399.70 31197.22 25599.59 25299.54 162
VDDNet98.97 18898.82 19899.42 18999.71 11498.81 24599.62 5498.68 32999.81 3699.38 21699.80 6094.25 29999.85 21998.79 12799.32 29999.59 137
IterMVS98.97 18899.16 11698.42 30499.74 10495.64 34598.06 30799.83 3699.83 3399.85 4399.74 9196.10 28199.99 599.27 72100.00 199.63 102
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
TinyColmap98.97 18898.93 18099.07 25899.46 22998.19 28397.75 33099.75 7798.79 20199.54 17199.70 11598.97 8099.62 34896.63 28999.83 14299.41 221
HPM-MVS++copyleft98.96 19198.70 20999.74 6399.52 19799.71 7198.86 22399.19 30498.47 23398.59 31599.06 31798.08 19399.91 11796.94 26899.60 24899.60 128
lupinMVS98.96 19198.87 19199.24 23799.57 17398.40 27298.12 29899.18 30598.28 25699.63 13199.13 30798.02 19799.97 1998.22 16699.69 21499.35 237
USDC98.96 19198.93 18099.05 26099.54 18697.99 29597.07 35999.80 5198.21 26099.75 8499.77 8098.43 15699.64 34697.90 19399.88 10799.51 179
YYNet198.95 19498.99 17198.84 28399.64 14597.14 32298.22 29099.32 27498.92 18599.59 15099.66 14297.40 23799.83 24798.27 16299.90 8999.55 154
MDA-MVSNet_test_wron98.95 19498.99 17198.85 28199.64 14597.16 32198.23 28999.33 27298.93 18399.56 16499.66 14297.39 23999.83 24798.29 16099.88 10799.55 154
Test_1112_low_res98.95 19498.73 20499.63 11799.68 13599.15 20998.09 30299.80 5197.14 31899.46 19399.40 25396.11 28099.89 15399.01 10599.84 13299.84 14
CANet_DTU98.91 19798.85 19399.09 25498.79 34898.13 28698.18 29199.31 27899.48 9798.86 29199.51 22396.56 26499.95 4799.05 10299.95 5499.19 269
HyFIR lowres test98.91 19798.64 21299.73 7399.85 3499.47 13298.07 30599.83 3698.64 21499.89 2799.60 18692.57 316100.00 199.33 6199.97 3399.72 47
HQP_MVS98.90 19998.68 21199.55 15199.58 16399.24 19498.80 23699.54 19698.94 18099.14 26199.25 29197.24 24599.82 25795.84 32399.78 17599.60 128
sss98.90 19998.77 20399.27 23099.48 21998.44 26998.72 24799.32 27497.94 27899.37 21799.35 27096.31 27599.91 11798.85 12299.63 23799.47 200
OMC-MVS98.90 19998.72 20599.44 18399.39 24799.42 15098.58 25599.64 13797.31 31099.44 19599.62 16898.59 13199.69 31796.17 31099.79 16999.22 260
ppachtmachnet_test98.89 20299.12 12798.20 31499.66 14195.24 34997.63 33599.68 11199.08 16499.78 7199.62 16898.65 12599.88 16898.02 18299.96 4599.48 195
MVS_030498.88 20398.71 20699.39 20298.85 34098.91 23999.45 8499.30 28198.56 22197.26 36199.68 13296.18 27999.96 3799.17 8699.94 6799.29 249
new_pmnet98.88 20398.89 18998.84 28399.70 12297.62 30998.15 29499.50 22197.98 27399.62 13999.54 21498.15 18899.94 6197.55 23099.84 13298.95 312
K. test v398.87 20598.60 21599.69 8899.93 1399.46 13699.74 1894.97 36999.78 4299.88 3399.88 3093.66 30799.97 1999.61 2199.95 5499.64 97
APD-MVScopyleft98.87 20598.59 21799.71 8399.50 20899.62 10299.01 19999.57 17996.80 32899.54 17199.63 15998.29 17399.91 11795.24 33799.71 20999.61 124
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
our_test_398.85 20799.09 13998.13 31699.66 14194.90 35297.72 33199.58 17799.07 16699.64 12799.62 16898.19 18599.93 7598.41 15099.95 5499.55 154
mvs-test198.83 20898.70 20999.22 23998.89 33699.65 9498.88 21999.66 12099.34 12298.29 32898.94 33897.69 22199.96 3798.11 17898.54 34398.04 358
UnsupCasMVSNet_eth98.83 20898.57 22199.59 13499.68 13599.45 14198.99 20699.67 11699.48 9799.55 16999.36 26594.92 29199.86 20198.95 11696.57 36899.45 206
NCCC98.82 21098.57 22199.58 13999.21 29499.31 17698.61 25199.25 29298.65 21398.43 32599.26 28997.86 21099.81 27396.55 29199.27 30699.61 124
PMVScopyleft92.94 2198.82 21098.81 19998.85 28199.84 3597.99 29599.20 14799.47 23299.71 5099.42 20199.82 5598.09 19199.47 36493.88 35699.85 12799.07 298
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
FMVSNet398.80 21298.63 21499.32 22099.13 30798.72 25099.10 18199.48 22899.23 14099.62 13999.64 14992.57 31699.86 20198.96 11299.90 8999.39 226
Patchmtry98.78 21398.54 22599.49 16898.89 33699.19 20599.32 10999.67 11699.65 7099.72 9999.79 6691.87 32599.95 4798.00 18699.97 3399.33 240
ETH3D-3000-0.198.77 21498.50 22999.59 13499.47 22499.53 12498.77 24199.60 16197.33 30999.23 24499.50 22697.91 20599.83 24795.02 34199.67 22699.41 221
Vis-MVSNet (Re-imp)98.77 21498.58 22099.34 21499.78 7598.88 24199.61 5999.56 18499.11 16399.24 24399.56 20593.00 31499.78 28497.43 23899.89 9999.35 237
CLD-MVS98.76 21698.57 22199.33 21699.57 17398.97 22897.53 34199.55 19096.41 33299.27 23899.13 30799.07 6999.78 28496.73 28299.89 9999.23 258
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
Anonymous20240521198.75 21798.46 23199.63 11799.34 26799.66 8999.47 8397.65 35499.28 13199.56 16499.50 22693.15 31199.84 23698.62 14199.58 25399.40 223
RRT_MVS98.75 21798.54 22599.41 19798.14 37198.61 25998.98 21099.66 12099.31 12799.84 4699.75 8891.98 32299.98 899.20 7999.95 5499.62 113
CPTT-MVS98.74 21998.44 23499.64 11199.61 15299.38 16099.18 15399.55 19096.49 33199.27 23899.37 26097.11 25399.92 9595.74 32799.67 22699.62 113
F-COLMAP98.74 21998.45 23299.62 12699.57 17399.47 13298.84 22699.65 13196.31 33598.93 28099.19 30497.68 22399.87 18196.52 29399.37 29399.53 167
N_pmnet98.73 22198.53 22799.35 21399.72 11198.67 25398.34 27994.65 37098.35 24899.79 6899.68 13298.03 19599.93 7598.28 16199.92 7999.44 211
c3_l98.72 22298.71 20698.72 29399.12 30997.22 32097.68 33499.56 18498.90 18799.54 17199.48 23496.37 27499.73 30397.88 19599.88 10799.21 262
CL-MVSNet_self_test98.71 22398.56 22499.15 24899.22 29298.66 25597.14 35699.51 21798.09 26799.54 17199.27 28696.87 26099.74 30098.43 14998.96 32199.03 302
PVSNet_Blended98.70 22498.59 21799.02 26299.54 18697.99 29597.58 33899.82 4195.70 34499.34 22398.98 33198.52 14699.77 29297.98 18799.83 14299.30 246
bset_n11_16_dypcd98.69 22598.45 23299.42 18999.69 12698.52 26496.06 36796.80 36299.71 5099.73 9799.54 21495.14 29099.96 3799.39 5099.95 5499.79 31
eth_miper_zixun_eth98.68 22698.71 20698.60 29799.10 31596.84 32997.52 34399.54 19698.94 18099.58 15499.48 23496.25 27799.76 29498.01 18599.93 7599.21 262
PatchMatch-RL98.68 22698.47 23099.30 22599.44 23499.28 18198.14 29699.54 19697.12 31999.11 26599.25 29197.80 21599.70 31196.51 29499.30 30198.93 314
miper_lstm_enhance98.65 22898.60 21598.82 28899.20 29797.33 31797.78 32999.66 12099.01 17299.59 15099.50 22694.62 29699.85 21998.12 17799.90 8999.26 252
test_part198.63 22998.26 25299.75 5799.40 24599.49 12999.67 4299.68 11199.86 2299.88 3399.86 3986.73 36299.93 7599.34 5799.97 3399.81 24
test_prior398.62 23098.34 24599.46 17799.35 25799.22 19897.95 31999.39 25897.87 28198.05 34199.05 31897.90 20699.69 31795.99 31699.49 27499.48 195
h-mvs3398.61 23198.34 24599.44 18399.60 15498.67 25399.27 12799.44 24199.68 6099.32 22799.49 23192.50 319100.00 199.24 7396.51 36999.65 88
CVMVSNet98.61 23198.88 19097.80 32499.58 16393.60 35999.26 12999.64 13799.66 6899.72 9999.67 13893.26 31099.93 7599.30 6699.81 15999.87 9
Patchmatch-RL test98.60 23398.36 24299.33 21699.77 8399.07 22198.27 28699.87 2198.91 18699.74 9399.72 10190.57 34299.79 28198.55 14499.85 12799.11 285
RPMNet98.60 23398.53 22798.83 28599.05 32098.12 28799.30 11699.62 14299.86 2299.16 25799.74 9192.53 31899.92 9598.75 13298.77 33198.44 343
AdaColmapbinary98.60 23398.35 24499.38 20699.12 30999.22 19898.67 25099.42 24797.84 28598.81 29699.27 28697.32 24399.81 27395.14 33899.53 26799.10 287
miper_ehance_all_eth98.59 23698.59 21798.59 29898.98 32997.07 32397.49 34499.52 21398.50 22999.52 17899.37 26096.41 27299.71 30997.86 19999.62 23899.00 308
WTY-MVS98.59 23698.37 24199.26 23299.43 23698.40 27298.74 24499.13 31198.10 26599.21 25099.24 29694.82 29399.90 13797.86 19998.77 33199.49 190
CNLPA98.57 23898.34 24599.28 22899.18 30199.10 21798.34 27999.41 24898.48 23298.52 32098.98 33197.05 25599.78 28495.59 32999.50 27298.96 311
testtj98.56 23998.17 26299.72 7999.45 23299.60 11098.88 21999.50 22196.88 32399.18 25699.48 23497.08 25499.92 9593.69 35799.38 28999.63 102
112198.56 23998.24 25399.52 15999.49 21399.24 19499.30 11699.22 29995.77 34298.52 32099.29 28297.39 23999.85 21995.79 32599.34 29699.46 204
CDPH-MVS98.56 23998.20 25799.61 12999.50 20899.46 13698.32 28299.41 24895.22 34999.21 25099.10 31498.34 16999.82 25795.09 34099.66 23099.56 151
UnsupCasMVSNet_bld98.55 24298.27 25199.40 19999.56 18399.37 16397.97 31899.68 11197.49 30199.08 26899.35 27095.41 28999.82 25797.70 21798.19 35299.01 307
cl____98.54 24398.41 23798.92 27199.03 32397.80 30497.46 34599.59 16898.90 18799.60 14799.46 24293.85 30399.78 28497.97 18999.89 9999.17 273
DIV-MVS_self_test98.54 24398.42 23698.92 27199.03 32397.80 30497.46 34599.59 16898.90 18799.60 14799.46 24293.87 30299.78 28497.97 18999.89 9999.18 271
hse-mvs298.52 24598.30 24999.16 24699.29 28098.60 26098.77 24199.02 31699.68 6099.32 22799.04 32192.50 31999.85 21999.24 7397.87 36099.03 302
MG-MVS98.52 24598.39 23998.94 26799.15 30497.39 31698.18 29199.21 30398.89 19099.23 24499.63 15997.37 24199.74 30094.22 35099.61 24599.69 57
ETH3D cwj APD-0.1698.50 24798.16 26399.51 16299.04 32299.39 15798.47 27099.47 23296.70 33098.78 30199.33 27497.62 23199.86 20194.69 34699.38 28999.28 251
DP-MVS Recon98.50 24798.23 25499.31 22399.49 21399.46 13698.56 26099.63 13994.86 35598.85 29299.37 26097.81 21499.59 35496.08 31199.44 28098.88 318
CMPMVSbinary77.52 2398.50 24798.19 26099.41 19798.33 36499.56 11999.01 19999.59 16895.44 34699.57 15799.80 6095.64 28699.46 36696.47 29799.92 7999.21 262
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
114514_t98.49 25098.11 26699.64 11199.73 10799.58 11699.24 13799.76 7089.94 36899.42 20199.56 20597.76 21899.86 20197.74 21199.82 15199.47 200
PMMVS98.49 25098.29 25099.11 25298.96 33098.42 27197.54 33999.32 27497.53 29898.47 32498.15 36897.88 20999.82 25797.46 23699.24 30999.09 290
MVSTER98.47 25298.22 25599.24 23799.06 31998.35 27799.08 18899.46 23699.27 13299.75 8499.66 14288.61 35299.85 21999.14 9699.92 7999.52 177
LFMVS98.46 25398.19 26099.26 23299.24 29098.52 26499.62 5496.94 36199.87 2099.31 23199.58 19491.04 33399.81 27398.68 13999.42 28599.45 206
PatchT98.45 25498.32 24898.83 28598.94 33198.29 27899.24 13798.82 32499.84 3099.08 26899.76 8391.37 32899.94 6198.82 12599.00 32098.26 349
MIMVSNet98.43 25598.20 25799.11 25299.53 19298.38 27599.58 6898.61 33398.96 17899.33 22599.76 8390.92 33599.81 27397.38 24199.76 18199.15 277
PVSNet97.47 1598.42 25698.44 23498.35 30799.46 22996.26 33696.70 36499.34 27197.68 29099.00 27599.13 30797.40 23799.72 30597.59 22999.68 21999.08 293
CHOSEN 280x42098.41 25798.41 23798.40 30599.34 26795.89 34396.94 36199.44 24198.80 20099.25 24099.52 21993.51 30999.98 898.94 11799.98 2499.32 243
BH-RMVSNet98.41 25798.14 26599.21 24099.21 29498.47 26698.60 25398.26 34698.35 24898.93 28099.31 27797.20 25099.66 33794.32 34899.10 31499.51 179
QAPM98.40 25997.99 27299.65 10499.39 24799.47 13299.67 4299.52 21391.70 36598.78 30199.80 6098.55 13799.95 4794.71 34599.75 18499.53 167
API-MVS98.38 26098.39 23998.35 30798.83 34299.26 18599.14 16899.18 30598.59 21998.66 31098.78 35098.61 12999.57 35694.14 35199.56 25596.21 370
HQP-MVS98.36 26198.02 27199.39 20299.31 27498.94 23297.98 31599.37 26597.45 30298.15 33598.83 34796.67 26299.70 31194.73 34399.67 22699.53 167
PAPM_NR98.36 26198.04 26999.33 21699.48 21998.93 23698.79 23999.28 28697.54 29798.56 31898.57 35797.12 25299.69 31794.09 35298.90 32699.38 228
PLCcopyleft97.35 1698.36 26197.99 27299.48 17299.32 27399.24 19498.50 26899.51 21795.19 35198.58 31698.96 33696.95 25899.83 24795.63 32899.25 30799.37 231
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
train_agg98.35 26497.95 27699.57 14499.35 25799.35 17098.11 30099.41 24894.90 35397.92 34698.99 32898.02 19799.85 21995.38 33599.44 28099.50 185
CR-MVSNet98.35 26498.20 25798.83 28599.05 32098.12 28799.30 11699.67 11697.39 30699.16 25799.79 6691.87 32599.91 11798.78 13098.77 33198.44 343
agg_prior198.33 26697.92 28299.57 14499.35 25799.36 16697.99 31499.39 25894.85 35697.76 35598.98 33198.03 19599.85 21995.49 33199.44 28099.51 179
DPM-MVS98.28 26797.94 28099.32 22099.36 25599.11 21297.31 35198.78 32696.88 32398.84 29399.11 31397.77 21799.61 35294.03 35499.36 29499.23 258
alignmvs98.28 26797.96 27599.25 23599.12 30998.93 23699.03 19698.42 34199.64 7298.72 30697.85 37190.86 33899.62 34898.88 12199.13 31299.19 269
test_yl98.25 26997.95 27699.13 25099.17 30298.47 26699.00 20198.67 33198.97 17599.22 24899.02 32691.31 32999.69 31797.26 25098.93 32299.24 255
DCV-MVSNet98.25 26997.95 27699.13 25099.17 30298.47 26699.00 20198.67 33198.97 17599.22 24899.02 32691.31 32999.69 31797.26 25098.93 32299.24 255
MAR-MVS98.24 27197.92 28299.19 24398.78 35099.65 9499.17 15899.14 30995.36 34798.04 34398.81 34997.47 23499.72 30595.47 33399.06 31598.21 352
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
OpenMVScopyleft98.12 1098.23 27297.89 28699.26 23299.19 29999.26 18599.65 5199.69 10891.33 36698.14 33999.77 8098.28 17499.96 3795.41 33499.55 25998.58 334
BH-untuned98.22 27398.09 26798.58 29999.38 25097.24 31998.55 26198.98 31997.81 28699.20 25598.76 35197.01 25699.65 34494.83 34298.33 34798.86 320
HY-MVS98.23 998.21 27497.95 27698.99 26399.03 32398.24 27999.61 5998.72 32896.81 32798.73 30599.51 22394.06 30099.86 20196.91 27098.20 35098.86 320
EPNet98.13 27597.77 29099.18 24594.57 37997.99 29599.24 13797.96 34999.74 4597.29 36099.62 16893.13 31299.97 1998.59 14299.83 14299.58 142
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
SCA98.11 27698.36 24297.36 33599.20 29792.99 36298.17 29398.49 33998.24 25899.10 26799.57 20296.01 28299.94 6196.86 27399.62 23899.14 281
Patchmatch-test98.10 27797.98 27498.48 30299.27 28596.48 33399.40 9199.07 31298.81 19899.23 24499.57 20290.11 34699.87 18196.69 28399.64 23599.09 290
pmmvs398.08 27897.80 28798.91 27399.41 24297.69 30897.87 32699.66 12095.87 34099.50 18599.51 22390.35 34499.97 1998.55 14499.47 27799.08 293
JIA-IIPM98.06 27997.92 28298.50 30198.59 35797.02 32498.80 23698.51 33799.88 1997.89 34899.87 3391.89 32499.90 13798.16 17597.68 36298.59 332
miper_enhance_ethall98.03 28097.94 28098.32 30998.27 36596.43 33596.95 36099.41 24896.37 33499.43 19998.96 33694.74 29499.69 31797.71 21499.62 23898.83 323
TAPA-MVS97.92 1398.03 28097.55 29699.46 17799.47 22499.44 14398.50 26899.62 14286.79 36999.07 27199.26 28998.26 17699.62 34897.28 24799.73 19999.31 245
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
131498.00 28297.90 28598.27 31398.90 33397.45 31499.30 11699.06 31494.98 35297.21 36299.12 31198.43 15699.67 33395.58 33098.56 34297.71 362
GA-MVS97.99 28397.68 29398.93 27099.52 19798.04 29497.19 35599.05 31598.32 25498.81 29698.97 33489.89 34999.41 36798.33 15799.05 31699.34 239
MVS-HIRNet97.86 28498.22 25596.76 34499.28 28391.53 37198.38 27892.60 37599.13 15999.31 23199.96 1297.18 25199.68 32898.34 15699.83 14299.07 298
AUN-MVS97.82 28597.38 29899.14 24999.27 28598.53 26298.72 24799.02 31698.10 26597.18 36399.03 32589.26 35199.85 21997.94 19197.91 35899.03 302
FMVSNet597.80 28697.25 30299.42 18998.83 34298.97 22899.38 9599.80 5198.87 19199.25 24099.69 12180.60 37499.91 11798.96 11299.90 8999.38 228
ADS-MVSNet297.78 28797.66 29598.12 31799.14 30595.36 34799.22 14498.75 32796.97 32198.25 33199.64 14990.90 33699.94 6196.51 29499.56 25599.08 293
ETH3 D test640097.76 28897.19 30599.50 16599.38 25099.26 18598.34 27999.49 22692.99 36298.54 31999.20 30295.92 28499.82 25791.14 36499.66 23099.40 223
test111197.74 28998.16 26396.49 35099.60 15489.86 37999.71 2891.21 37699.89 1499.88 3399.87 3393.73 30699.90 13799.56 2899.99 1299.70 53
ECVR-MVScopyleft97.73 29098.04 26996.78 34399.59 15890.81 37599.72 2490.43 37899.89 1499.86 4199.86 3993.60 30899.89 15399.46 4099.99 1299.65 88
baseline197.73 29097.33 29998.96 26599.30 27897.73 30699.40 9198.42 34199.33 12599.46 19399.21 30091.18 33199.82 25798.35 15591.26 37499.32 243
tpmrst97.73 29098.07 26896.73 34698.71 35492.00 36699.10 18198.86 32198.52 22798.92 28399.54 21491.90 32399.82 25798.02 18299.03 31898.37 345
ADS-MVSNet97.72 29397.67 29497.86 32299.14 30594.65 35399.22 14498.86 32196.97 32198.25 33199.64 14990.90 33699.84 23696.51 29499.56 25599.08 293
PatchmatchNetpermissive97.65 29497.80 28797.18 34098.82 34592.49 36499.17 15898.39 34398.12 26498.79 29999.58 19490.71 34099.89 15397.23 25499.41 28699.16 275
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
tttt051797.62 29597.20 30498.90 27999.76 8797.40 31599.48 8194.36 37199.06 17099.70 10799.49 23184.55 36899.94 6198.73 13499.65 23399.36 234
EPNet_dtu97.62 29597.79 28997.11 34296.67 37692.31 36598.51 26798.04 34799.24 13895.77 37099.47 23993.78 30599.66 33798.98 10899.62 23899.37 231
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
wuyk23d97.58 29799.13 12392.93 35799.69 12699.49 12999.52 7599.77 6597.97 27499.96 899.79 6699.84 399.94 6195.85 32299.82 15179.36 373
cl2297.56 29897.28 30098.40 30598.37 36396.75 33097.24 35499.37 26597.31 31099.41 20999.22 29887.30 35499.37 36897.70 21799.62 23899.08 293
PAPR97.56 29897.07 30799.04 26198.80 34798.11 28997.63 33599.25 29294.56 35998.02 34498.25 36797.43 23699.68 32890.90 36598.74 33599.33 240
thisisatest053097.45 30096.95 31198.94 26799.68 13597.73 30699.09 18594.19 37398.61 21899.56 16499.30 27984.30 36999.93 7598.27 16299.54 26599.16 275
TR-MVS97.44 30197.15 30698.32 30998.53 35997.46 31398.47 27097.91 35196.85 32598.21 33498.51 36196.42 27099.51 36292.16 36097.29 36497.98 359
tpmvs97.39 30297.69 29296.52 34998.41 36191.76 36899.30 11698.94 32097.74 28797.85 35199.55 21292.40 32199.73 30396.25 30698.73 33798.06 357
test0.0.03 197.37 30396.91 31498.74 29297.72 37297.57 31097.60 33797.36 36098.00 27099.21 25098.02 36990.04 34799.79 28198.37 15295.89 37298.86 320
OpenMVS_ROBcopyleft97.31 1797.36 30496.84 31598.89 28099.29 28099.45 14198.87 22299.48 22886.54 37199.44 19599.74 9197.34 24299.86 20191.61 36199.28 30397.37 366
RRT_test8_iter0597.35 30597.25 30297.63 32998.81 34693.13 36199.26 12999.89 1699.51 9499.83 5199.68 13279.03 37999.88 16899.53 3299.72 20599.89 8
BH-w/o97.20 30697.01 30997.76 32599.08 31895.69 34498.03 30998.52 33695.76 34397.96 34598.02 36995.62 28799.47 36492.82 35997.25 36598.12 356
test-LLR97.15 30796.95 31197.74 32798.18 36895.02 35097.38 34796.10 36398.00 27097.81 35298.58 35590.04 34799.91 11797.69 22398.78 32998.31 346
tpm97.15 30796.95 31197.75 32698.91 33294.24 35599.32 10997.96 34997.71 28998.29 32899.32 27586.72 36399.92 9598.10 18096.24 37199.09 290
E-PMN97.14 30997.43 29796.27 35298.79 34891.62 37095.54 36999.01 31899.44 10998.88 28799.12 31192.78 31599.68 32894.30 34999.03 31897.50 363
cascas96.99 31096.82 31697.48 33197.57 37595.64 34596.43 36699.56 18491.75 36497.13 36497.61 37495.58 28898.63 37396.68 28499.11 31398.18 355
thisisatest051596.98 31196.42 31898.66 29699.42 24197.47 31297.27 35294.30 37297.24 31299.15 25998.86 34685.01 36699.87 18197.10 26299.39 28898.63 329
EMVS96.96 31297.28 30095.99 35598.76 35291.03 37395.26 37098.61 33399.34 12298.92 28398.88 34593.79 30499.66 33792.87 35899.05 31697.30 367
dp96.86 31397.07 30796.24 35398.68 35690.30 37899.19 15298.38 34497.35 30898.23 33399.59 19287.23 35599.82 25796.27 30598.73 33798.59 332
baseline296.83 31496.28 32098.46 30399.09 31796.91 32798.83 22893.87 37497.23 31396.23 36998.36 36488.12 35399.90 13796.68 28498.14 35498.57 335
ET-MVSNet_ETH3D96.78 31596.07 32498.91 27399.26 28797.92 30197.70 33396.05 36697.96 27792.37 37598.43 36387.06 35699.90 13798.27 16297.56 36398.91 316
tpm cat196.78 31596.98 31096.16 35498.85 34090.59 37799.08 18899.32 27492.37 36397.73 35799.46 24291.15 33299.69 31796.07 31298.80 32898.21 352
PCF-MVS96.03 1896.73 31795.86 32899.33 21699.44 23499.16 20796.87 36299.44 24186.58 37098.95 27899.40 25394.38 29899.88 16887.93 36999.80 16498.95 312
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
CostFormer96.71 31896.79 31796.46 35198.90 33390.71 37699.41 9098.68 32994.69 35898.14 33999.34 27386.32 36599.80 27897.60 22898.07 35698.88 318
MVEpermissive92.54 2296.66 31996.11 32398.31 31199.68 13597.55 31197.94 32195.60 36899.37 11990.68 37698.70 35396.56 26498.61 37486.94 37499.55 25998.77 326
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
thres600view796.60 32096.16 32297.93 32099.63 14796.09 34099.18 15397.57 35598.77 20498.72 30697.32 37787.04 35799.72 30588.57 36798.62 34097.98 359
EPMVS96.53 32196.32 31997.17 34198.18 36892.97 36399.39 9389.95 37998.21 26098.61 31399.59 19286.69 36499.72 30596.99 26699.23 31198.81 324
thres40096.40 32295.89 32697.92 32199.58 16396.11 33899.00 20197.54 35898.43 23498.52 32096.98 38086.85 35999.67 33387.62 37098.51 34497.98 359
thres100view90096.39 32396.03 32597.47 33299.63 14795.93 34199.18 15397.57 35598.75 20898.70 30897.31 37887.04 35799.67 33387.62 37098.51 34496.81 368
tpm296.35 32496.22 32196.73 34698.88 33991.75 36999.21 14698.51 33793.27 36197.89 34899.21 30084.83 36799.70 31196.04 31398.18 35398.75 327
FPMVS96.32 32595.50 33398.79 28999.60 15498.17 28598.46 27598.80 32597.16 31796.28 36699.63 15982.19 37099.09 37088.45 36898.89 32799.10 287
tfpn200view996.30 32695.89 32697.53 33099.58 16396.11 33899.00 20197.54 35898.43 23498.52 32096.98 38086.85 35999.67 33387.62 37098.51 34496.81 368
TESTMET0.1,196.24 32795.84 32997.41 33498.24 36693.84 35897.38 34795.84 36798.43 23497.81 35298.56 35879.77 37599.89 15397.77 20698.77 33198.52 337
test-mter96.23 32895.73 33197.74 32798.18 36895.02 35097.38 34796.10 36397.90 27997.81 35298.58 35579.12 37899.91 11797.69 22398.78 32998.31 346
X-MVStestdata96.09 32994.87 33999.75 5799.71 11499.71 7199.37 9999.61 14999.29 12898.76 30361.30 38398.47 15099.88 16897.62 22599.73 19999.67 70
thres20096.09 32995.68 33297.33 33799.48 21996.22 33798.53 26597.57 35598.06 26998.37 32796.73 38286.84 36199.61 35286.99 37398.57 34196.16 371
DWT-MVSNet_test96.03 33195.80 33096.71 34898.50 36091.93 36799.25 13697.87 35295.99 33996.81 36597.61 37481.02 37299.66 33797.20 25797.98 35798.54 336
KD-MVS_2432*160095.89 33295.41 33597.31 33894.96 37793.89 35697.09 35799.22 29997.23 31398.88 28799.04 32179.23 37699.54 35796.24 30796.81 36698.50 341
miper_refine_blended95.89 33295.41 33597.31 33894.96 37793.89 35697.09 35799.22 29997.23 31398.88 28799.04 32179.23 37699.54 35796.24 30796.81 36698.50 341
gg-mvs-nofinetune95.87 33495.17 33897.97 31998.19 36796.95 32599.69 3589.23 38099.89 1496.24 36899.94 1481.19 37199.51 36293.99 35598.20 35097.44 364
PVSNet_095.53 1995.85 33595.31 33797.47 33298.78 35093.48 36095.72 36899.40 25596.18 33797.37 35897.73 37295.73 28599.58 35595.49 33181.40 37599.36 234
tmp_tt95.75 33695.42 33496.76 34489.90 38194.42 35498.86 22397.87 35278.01 37299.30 23699.69 12197.70 21995.89 37699.29 6998.14 35499.95 1
MVS95.72 33794.63 34198.99 26398.56 35897.98 30099.30 11698.86 32172.71 37497.30 35999.08 31598.34 16999.74 30089.21 36698.33 34799.26 252
PAPM95.61 33894.71 34098.31 31199.12 30996.63 33196.66 36598.46 34090.77 36796.25 36798.68 35493.01 31399.69 31781.60 37597.86 36198.62 330
IB-MVS95.41 2095.30 33994.46 34397.84 32398.76 35295.33 34897.33 35096.07 36596.02 33895.37 37397.41 37676.17 38199.96 3797.54 23195.44 37398.22 351
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
test250694.73 34094.59 34295.15 35699.59 15885.90 38199.75 1674.01 38299.89 1499.71 10499.86 3979.00 38099.90 13799.52 3499.99 1299.65 88
test_method91.72 34192.32 34489.91 35893.49 38070.18 38290.28 37199.56 18461.71 37595.39 37299.52 21993.90 30199.94 6198.76 13198.27 34999.62 113
EGC-MVSNET89.05 34285.52 34599.64 11199.89 2199.78 4299.56 7299.52 21324.19 37649.96 37799.83 4899.15 5599.92 9597.71 21499.85 12799.21 262
test12329.31 34333.05 34818.08 35925.93 38312.24 38397.53 34110.93 38411.78 37724.21 37850.08 38721.04 3828.60 37823.51 37632.43 37733.39 374
testmvs28.94 34433.33 34615.79 36026.03 3829.81 38496.77 36315.67 38311.55 37823.87 37950.74 38619.03 3838.53 37923.21 37733.07 37629.03 375
cdsmvs_eth3d_5k24.88 34533.17 3470.00 3610.00 3840.00 3850.00 37299.62 1420.00 3790.00 38099.13 30799.82 40.00 3800.00 3780.00 3780.00 376
pcd_1.5k_mvsjas16.61 34622.14 3490.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 380100.00 199.28 420.00 3800.00 3780.00 3780.00 376
test_blank8.33 34711.11 3500.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 380100.00 10.00 3840.00 3800.00 3780.00 3780.00 376
uanet_test8.33 34711.11 3500.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 380100.00 10.00 3840.00 3800.00 3780.00 3780.00 376
DCPMVS8.33 34711.11 3500.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 380100.00 10.00 3840.00 3800.00 3780.00 3780.00 376
sosnet-low-res8.33 34711.11 3500.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 380100.00 10.00 3840.00 3800.00 3780.00 3780.00 376
sosnet8.33 34711.11 3500.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 380100.00 10.00 3840.00 3800.00 3780.00 3780.00 376
uncertanet8.33 34711.11 3500.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 380100.00 10.00 3840.00 3800.00 3780.00 3780.00 376
Regformer8.33 34711.11 3500.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 380100.00 10.00 3840.00 3800.00 3780.00 3780.00 376
uanet8.33 34711.11 3500.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 380100.00 10.00 3840.00 3800.00 3780.00 3780.00 376
ab-mvs-re8.26 35511.02 3580.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 38099.16 3050.00 3840.00 3800.00 3780.00 3780.00 376
FOURS199.83 3999.89 899.74 1899.71 9799.69 5899.63 131
MSC_two_6792asdad99.74 6399.03 32399.53 12499.23 29699.92 9597.77 20699.69 21499.78 33
PC_three_145297.56 29499.68 11299.41 24999.09 6397.09 37596.66 28699.60 24899.62 113
No_MVS99.74 6399.03 32399.53 12499.23 29699.92 9597.77 20699.69 21499.78 33
test_one_060199.63 14799.76 5299.55 19099.23 14099.31 23199.61 17798.59 131
eth-test20.00 384
eth-test0.00 384
ZD-MVS99.43 23699.61 10899.43 24596.38 33399.11 26599.07 31697.86 21099.92 9594.04 35399.49 274
RE-MVS-def99.13 12399.54 18699.74 6299.26 12999.62 14299.16 15399.52 17899.64 14998.57 13497.27 24899.61 24599.54 162
IU-MVS99.69 12699.77 4599.22 29997.50 30099.69 11097.75 21099.70 21199.77 37
OPU-MVS99.29 22699.12 30999.44 14399.20 14799.40 25399.00 7598.84 37296.54 29299.60 24899.58 142
test_241102_TWO99.54 19699.13 15999.76 7899.63 15998.32 17299.92 9597.85 20199.69 21499.75 44
test_241102_ONE99.69 12699.82 2999.54 19699.12 16299.82 5399.49 23198.91 8799.52 361
9.1498.64 21299.45 23298.81 23399.60 16197.52 29999.28 23799.56 20598.53 14399.83 24795.36 33699.64 235
save fliter99.53 19299.25 18998.29 28499.38 26499.07 166
test_0728_THIRD99.18 14799.62 13999.61 17798.58 13399.91 11797.72 21299.80 16499.77 37
test_0728_SECOND99.83 2199.70 12299.79 3999.14 16899.61 14999.92 9597.88 19599.72 20599.77 37
test072699.69 12699.80 3799.24 13799.57 17999.16 15399.73 9799.65 14798.35 167
GSMVS99.14 281
test_part299.62 15199.67 8799.55 169
sam_mvs190.81 33999.14 281
sam_mvs90.52 343
ambc99.20 24299.35 25798.53 26299.17 15899.46 23699.67 11799.80 6098.46 15399.70 31197.92 19299.70 21199.38 228
MTGPAbinary99.53 205
test_post199.14 16851.63 38589.54 35099.82 25796.86 273
test_post52.41 38490.25 34599.86 201
patchmatchnet-post99.62 16890.58 34199.94 61
GG-mvs-BLEND97.36 33597.59 37396.87 32899.70 2988.49 38194.64 37497.26 37980.66 37399.12 36991.50 36296.50 37096.08 372
MTMP99.09 18598.59 335
gm-plane-assit97.59 37389.02 38093.47 36098.30 36599.84 23696.38 301
test9_res95.10 33999.44 28099.50 185
TEST999.35 25799.35 17098.11 30099.41 24894.83 35797.92 34698.99 32898.02 19799.85 219
test_899.34 26799.31 17698.08 30499.40 25594.90 35397.87 35098.97 33498.02 19799.84 236
agg_prior294.58 34799.46 27999.50 185
agg_prior99.35 25799.36 16699.39 25897.76 35599.85 219
TestCases99.63 11799.78 7599.64 9699.83 3698.63 21599.63 13199.72 10198.68 11899.75 29896.38 30199.83 14299.51 179
test_prior499.19 20598.00 312
test_prior297.95 31997.87 28198.05 34199.05 31897.90 20695.99 31699.49 274
test_prior99.46 17799.35 25799.22 19899.39 25899.69 31799.48 195
旧先验297.94 32195.33 34898.94 27999.88 16896.75 280
新几何298.04 308
新几何199.52 15999.50 20899.22 19899.26 28995.66 34598.60 31499.28 28497.67 22499.89 15395.95 32099.32 29999.45 206
旧先验199.49 21399.29 17999.26 28999.39 25797.67 22499.36 29499.46 204
无先验98.01 31099.23 29695.83 34199.85 21995.79 32599.44 211
原ACMM297.92 323
原ACMM199.37 20999.47 22498.87 24399.27 28796.74 32998.26 33099.32 27597.93 20499.82 25795.96 31999.38 28999.43 217
test22299.51 20299.08 22097.83 32899.29 28395.21 35098.68 30999.31 27797.28 24499.38 28999.43 217
testdata299.89 15395.99 316
segment_acmp98.37 165
testdata99.42 18999.51 20298.93 23699.30 28196.20 33698.87 29099.40 25398.33 17199.89 15396.29 30499.28 30399.44 211
testdata197.72 33197.86 284
test1299.54 15599.29 28099.33 17399.16 30798.43 32597.54 23299.82 25799.47 27799.48 195
plane_prior799.58 16399.38 160
plane_prior699.47 22499.26 18597.24 245
plane_prior599.54 19699.82 25795.84 32399.78 17599.60 128
plane_prior499.25 291
plane_prior399.31 17698.36 24399.14 261
plane_prior298.80 23698.94 180
plane_prior199.51 202
plane_prior99.24 19498.42 27697.87 28199.71 209
n20.00 385
nn0.00 385
door-mid99.83 36
lessismore_v099.64 11199.86 3199.38 16090.66 37799.89 2799.83 4894.56 29799.97 1999.56 2899.92 7999.57 148
LGP-MVS_train99.74 6399.82 4699.63 10099.73 8597.56 29499.64 12799.69 12199.37 3299.89 15396.66 28699.87 11699.69 57
test1199.29 283
door99.77 65
HQP5-MVS98.94 232
HQP-NCC99.31 27497.98 31597.45 30298.15 335
ACMP_Plane99.31 27497.98 31597.45 30298.15 335
BP-MVS94.73 343
HQP4-MVS98.15 33599.70 31199.53 167
HQP3-MVS99.37 26599.67 226
HQP2-MVS96.67 262
NP-MVS99.40 24599.13 21098.83 347
MDTV_nov1_ep13_2view91.44 37299.14 16897.37 30799.21 25091.78 32796.75 28099.03 302
MDTV_nov1_ep1397.73 29198.70 35590.83 37499.15 16698.02 34898.51 22898.82 29599.61 17790.98 33499.66 33796.89 27298.92 324
ACMMP++_ref99.94 67
ACMMP++99.79 169
Test By Simon98.41 159
ITE_SJBPF99.38 20699.63 14799.44 14399.73 8598.56 22199.33 22599.53 21798.88 9299.68 32896.01 31499.65 23399.02 306
DeepMVS_CXcopyleft97.98 31899.69 12696.95 32599.26 28975.51 37395.74 37198.28 36696.47 26899.62 34891.23 36397.89 35997.38 365