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 bysort bysort bysort bysort bysorted bysort by
IterMVS-SCA-FT99.00 18299.16 11498.51 29899.75 9795.90 34098.07 30399.84 3299.84 2799.89 2699.73 9296.01 28099.99 599.33 58100.00 199.63 100
new-patchmatchnet99.35 9299.57 4098.71 29399.82 4696.62 33098.55 25999.75 7599.50 9399.88 3299.87 3299.31 3799.88 16599.43 41100.00 199.62 111
anonymousdsp99.80 1199.77 1299.90 499.96 499.88 999.73 2099.85 2699.70 5299.92 1899.93 1499.45 2399.97 1799.36 53100.00 199.85 13
UA-Net99.78 1399.76 1499.86 1699.72 11099.71 7199.91 399.95 599.96 299.71 10399.91 2099.15 5599.97 1799.50 35100.00 199.90 4
PS-MVSNAJss99.84 899.82 899.89 799.96 499.77 4499.68 3799.85 2699.95 399.98 399.92 1799.28 4199.98 799.75 13100.00 199.94 2
jajsoiax99.89 399.89 399.89 799.96 499.78 4199.70 2899.86 2299.89 1199.98 399.90 2299.94 199.98 799.75 13100.00 199.90 4
mvs_tets99.90 299.90 299.90 499.96 499.79 3899.72 2399.88 1899.92 699.98 399.93 1499.94 199.98 799.77 12100.00 199.92 3
LCM-MVSNet99.95 199.95 199.95 199.99 199.99 199.95 299.97 299.99 1100.00 199.98 999.78 6100.00 199.92 1100.00 199.87 9
test_djsdf99.84 899.81 999.91 299.94 1099.84 1999.77 1199.80 4999.73 4399.97 699.92 1799.77 799.98 799.43 41100.00 199.90 4
IterMVS98.97 18699.16 11498.42 30299.74 10395.64 34398.06 30599.83 3499.83 3099.85 4299.74 8896.10 27999.99 599.27 69100.00 199.63 100
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
ANet_high99.88 499.87 499.91 299.99 199.91 299.65 50100.00 199.90 7100.00 199.97 1099.61 1799.97 1799.75 13100.00 199.84 14
test250694.73 33894.59 34095.15 35499.59 15685.90 37999.75 1574.01 38099.89 1199.71 10399.86 3879.00 37899.90 13399.52 3299.99 1299.65 86
test111197.74 28798.16 26196.49 34899.60 15289.86 37799.71 2791.21 37499.89 1199.88 3299.87 3293.73 30499.90 13399.56 2699.99 1299.70 51
ECVR-MVScopyleft97.73 28898.04 26796.78 34199.59 15690.81 37399.72 2390.43 37699.89 1199.86 4099.86 3893.60 30699.89 15099.46 3899.99 1299.65 86
pmmvs-eth3d99.48 5499.47 5399.51 15999.77 8299.41 15498.81 23199.66 11899.42 11499.75 8399.66 13999.20 5099.76 29298.98 10699.99 1299.36 232
v7n99.82 1099.80 1099.88 1199.96 499.84 1999.82 899.82 3999.84 2799.94 1199.91 2099.13 6099.96 3599.83 999.99 1299.83 18
v899.68 2499.69 1899.65 10499.80 5899.40 15599.66 4599.76 6899.64 6999.93 1499.85 4198.66 12399.84 23499.88 699.99 1299.71 48
v1099.69 2199.69 1899.66 9999.81 5399.39 15799.66 4599.75 7599.60 8399.92 1899.87 3298.75 11299.86 19899.90 299.99 1299.73 44
CHOSEN 1792x268899.39 8299.30 9099.65 10499.88 2599.25 18998.78 23899.88 1898.66 21099.96 899.79 6597.45 23399.93 7199.34 5599.99 1299.78 32
PVSNet_Blended_VisFu99.40 7799.38 7199.44 18099.90 1998.66 25398.94 21499.91 1097.97 27299.79 6799.73 9299.05 7299.97 1799.15 8799.99 1299.68 61
IterMVS-LS99.41 7499.47 5399.25 23399.81 5398.09 28998.85 22399.76 6899.62 7399.83 5099.64 14698.54 13999.97 1799.15 8799.99 1299.68 61
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
DeepC-MVS98.90 499.62 3599.61 3199.67 9299.72 11099.44 14399.24 13699.71 9599.27 13099.93 1499.90 2299.70 1199.93 7198.99 10499.99 1299.64 95
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
LTVRE_ROB99.19 199.88 499.87 499.88 1199.91 1599.90 599.96 199.92 799.90 799.97 699.87 3299.81 599.95 4599.54 2899.99 1299.80 24
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
Anonymous2024052199.44 6599.42 6599.49 16599.89 2198.96 22999.62 5399.76 6899.85 2499.82 5299.88 2996.39 27199.97 1799.59 2199.98 2499.55 152
D2MVS99.22 12999.19 11199.29 22399.69 12498.74 24798.81 23199.41 24698.55 22199.68 11199.69 11898.13 18799.87 17898.82 12399.98 2499.24 253
CHOSEN 280x42098.41 25598.41 23598.40 30399.34 26595.89 34196.94 35999.44 23998.80 19899.25 23799.52 21693.51 30799.98 798.94 11599.98 2499.32 241
v119299.57 3999.57 4099.57 14199.77 8299.22 19899.04 19299.60 15999.18 14599.87 3999.72 9899.08 6799.85 21799.89 599.98 2499.66 78
v114499.54 4799.53 4999.59 13299.79 6899.28 18199.10 18099.61 14799.20 14399.84 4599.73 9298.67 12199.84 23499.86 899.98 2499.64 95
OurMVSNet-221017-099.75 1599.71 1699.84 1999.96 499.83 2499.83 699.85 2699.80 3699.93 1499.93 1498.54 13999.93 7199.59 2199.98 2499.76 39
UGNet99.38 8499.34 7999.49 16598.90 33198.90 23999.70 2899.35 26799.86 1998.57 31599.81 5798.50 14999.93 7199.38 5099.98 2499.66 78
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
MIMVSNet199.66 2699.62 2799.80 2999.94 1099.87 1099.69 3499.77 6399.78 3999.93 1499.89 2697.94 20199.92 9199.65 1699.98 2499.62 111
Vis-MVSNetpermissive99.75 1599.74 1599.79 3499.88 2599.66 8999.69 3499.92 799.67 6199.77 7599.75 8599.61 1799.98 799.35 5499.98 2499.72 45
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
UniMVSNet_ETH3D99.85 799.83 799.90 499.89 2199.91 299.89 499.71 9599.93 499.95 1099.89 2699.71 999.96 3599.51 3399.97 3399.84 14
test_part198.63 22798.26 25099.75 5799.40 24399.49 12999.67 4199.68 10999.86 1999.88 3299.86 3886.73 36099.93 7199.34 5599.97 3399.81 23
CANet99.11 16099.05 14999.28 22698.83 34098.56 25998.71 24799.41 24699.25 13499.23 24199.22 29497.66 22699.94 5799.19 7899.97 3399.33 238
pmmvs699.86 699.86 699.83 2199.94 1099.90 599.83 699.91 1099.85 2499.94 1199.95 1299.73 899.90 13399.65 1699.97 3399.69 55
v14419299.55 4599.54 4599.58 13699.78 7499.20 20499.11 17999.62 14099.18 14599.89 2699.72 9898.66 12399.87 17899.88 699.97 3399.66 78
v192192099.56 4299.57 4099.55 14899.75 9799.11 21299.05 19099.61 14799.15 15599.88 3299.71 10599.08 6799.87 17899.90 299.97 3399.66 78
FC-MVSNet-test99.70 1999.65 2499.86 1699.88 2599.86 1399.72 2399.78 6099.90 799.82 5299.83 4798.45 15499.87 17899.51 3399.97 3399.86 11
v2v48299.50 5099.47 5399.58 13699.78 7499.25 18999.14 16799.58 17599.25 13499.81 5999.62 16598.24 17699.84 23499.83 999.97 3399.64 95
Patchmtry98.78 21198.54 22399.49 16598.89 33499.19 20599.32 10899.67 11499.65 6799.72 9899.79 6591.87 32399.95 4598.00 18499.97 3399.33 238
PVSNet_BlendedMVS99.03 17499.01 16199.09 25299.54 18397.99 29398.58 25399.82 3997.62 29099.34 21999.71 10598.52 14699.77 29097.98 18599.97 3399.52 175
FMVSNet199.66 2699.63 2699.73 7399.78 7499.77 4499.68 3799.70 10099.67 6199.82 5299.83 4798.98 7899.90 13399.24 7099.97 3399.53 165
HyFIR lowres test98.91 19598.64 21099.73 7399.85 3499.47 13298.07 30399.83 3498.64 21299.89 2699.60 18392.57 314100.00 199.33 5899.97 3399.72 45
ppachtmachnet_test98.89 20099.12 12598.20 31299.66 13995.24 34797.63 33399.68 10999.08 16299.78 7099.62 16598.65 12599.88 16598.02 18099.96 4599.48 193
Anonymous2023121199.62 3599.57 4099.76 4799.61 15099.60 11099.81 999.73 8399.82 3299.90 2299.90 2297.97 20099.86 19899.42 4699.96 4599.80 24
nrg03099.70 1999.66 2299.82 2399.76 8699.84 1999.61 5899.70 10099.93 499.78 7099.68 12999.10 6199.78 28299.45 3999.96 4599.83 18
v124099.56 4299.58 3799.51 15999.80 5899.00 22399.00 19999.65 12999.15 15599.90 2299.75 8599.09 6399.88 16599.90 299.96 4599.67 68
PS-CasMVS99.66 2699.58 3799.89 799.80 5899.85 1499.66 4599.73 8399.62 7399.84 4599.71 10598.62 12799.96 3599.30 6399.96 4599.86 11
TAMVS99.49 5299.45 5799.63 11699.48 21699.42 15099.45 8299.57 17799.66 6599.78 7099.83 4797.85 21099.86 19899.44 4099.96 4599.61 122
test_040299.22 12999.14 11899.45 17899.79 6899.43 14799.28 12399.68 10999.54 8799.40 21099.56 20299.07 6999.82 25596.01 31299.96 4599.11 283
our_test_398.85 20599.09 13798.13 31499.66 13994.90 35097.72 32999.58 17599.07 16499.64 12699.62 16598.19 18399.93 7198.41 14899.95 5299.55 152
CANet_DTU98.91 19598.85 19199.09 25298.79 34698.13 28498.18 28999.31 27699.48 9598.86 28999.51 22096.56 26299.95 4599.05 10099.95 5299.19 267
pmmvs599.19 13999.11 12899.42 18699.76 8698.88 24098.55 25999.73 8398.82 19599.72 9899.62 16596.56 26299.82 25599.32 6099.95 5299.56 149
bset_n11_16_dypcd98.69 22398.45 23099.42 18699.69 12498.52 26296.06 36596.80 36099.71 4799.73 9699.54 21195.14 28899.96 3599.39 4999.95 5299.79 30
RRT_MVS98.75 21598.54 22399.41 19498.14 36998.61 25798.98 20899.66 11899.31 12599.84 4599.75 8591.98 32099.98 799.20 7699.95 5299.62 111
V4299.56 4299.54 4599.63 11699.79 6899.46 13699.39 9199.59 16699.24 13699.86 4099.70 11298.55 13799.82 25599.79 1199.95 5299.60 126
EU-MVSNet99.39 8299.62 2798.72 29199.88 2596.44 33299.56 7099.85 2699.90 799.90 2299.85 4198.09 18999.83 24599.58 2499.95 5299.90 4
PMMVS299.48 5499.45 5799.57 14199.76 8698.99 22498.09 30099.90 1498.95 17799.78 7099.58 19199.57 2099.93 7199.48 3699.95 5299.79 30
DTE-MVSNet99.68 2499.61 3199.88 1199.80 5899.87 1099.67 4199.71 9599.72 4699.84 4599.78 7198.67 12199.97 1799.30 6399.95 5299.80 24
WR-MVS_H99.61 3799.53 4999.87 1499.80 5899.83 2499.67 4199.75 7599.58 8699.85 4299.69 11898.18 18599.94 5799.28 6899.95 5299.83 18
K. test v398.87 20398.60 21399.69 8899.93 1399.46 13699.74 1794.97 36799.78 3999.88 3299.88 2993.66 30599.97 1799.61 1999.95 5299.64 95
TDRefinement99.72 1799.70 1799.77 4099.90 1999.85 1499.86 599.92 799.69 5599.78 7099.92 1799.37 3199.88 16598.93 11699.95 5299.60 126
Gipumacopyleft99.57 3999.59 3499.49 16599.98 399.71 7199.72 2399.84 3299.81 3399.94 1199.78 7198.91 8799.71 30798.41 14899.95 5299.05 298
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
MVS_030498.88 20198.71 20499.39 19998.85 33898.91 23899.45 8299.30 27998.56 21997.26 35999.68 12996.18 27799.96 3599.17 8399.94 6599.29 247
v14899.40 7799.41 6699.39 19999.76 8698.94 23199.09 18499.59 16699.17 14999.81 5999.61 17498.41 15899.69 31599.32 6099.94 6599.53 165
casdiffmvs99.63 3299.61 3199.67 9299.79 6899.59 11399.13 17399.85 2699.79 3899.76 7799.72 9899.33 3699.82 25599.21 7399.94 6599.59 135
PEN-MVS99.66 2699.59 3499.89 799.83 3999.87 1099.66 4599.73 8399.70 5299.84 4599.73 9298.56 13699.96 3599.29 6699.94 6599.83 18
CP-MVSNet99.54 4799.43 6299.87 1499.76 8699.82 2899.57 6899.61 14799.54 8799.80 6299.64 14697.79 21499.95 4599.21 7399.94 6599.84 14
baseline99.63 3299.62 2799.66 9999.80 5899.62 10299.44 8599.80 4999.71 4799.72 9899.69 11899.15 5599.83 24599.32 6099.94 6599.53 165
FMVSNet299.35 9299.28 9799.55 14899.49 21099.35 17099.45 8299.57 17799.44 10799.70 10699.74 8897.21 24599.87 17899.03 10199.94 6599.44 209
ACMMP++_ref99.94 65
eth_miper_zixun_eth98.68 22498.71 20498.60 29599.10 31396.84 32797.52 34199.54 19498.94 17899.58 15199.48 23196.25 27599.76 29298.01 18399.93 7399.21 260
FIs99.65 3199.58 3799.84 1999.84 3599.85 1499.66 4599.75 7599.86 1999.74 9299.79 6598.27 17499.85 21799.37 5299.93 7399.83 18
pmmvs499.13 15499.06 14599.36 20999.57 17199.10 21698.01 30899.25 29098.78 20199.58 15199.44 24398.24 17699.76 29298.74 13199.93 7399.22 258
XXY-MVS99.71 1899.67 2199.81 2699.89 2199.72 6899.59 6599.82 3999.39 11599.82 5299.84 4699.38 2999.91 11399.38 5099.93 7399.80 24
pm-mvs199.79 1299.79 1199.78 3799.91 1599.83 2499.76 1399.87 2099.73 4399.89 2699.87 3299.63 1499.87 17899.54 2899.92 7799.63 100
EI-MVSNet99.38 8499.44 5999.21 23899.58 16198.09 28999.26 12899.46 23499.62 7399.75 8399.67 13598.54 13999.85 21799.15 8799.92 7799.68 61
TranMVSNet+NR-MVSNet99.54 4799.47 5399.76 4799.58 16199.64 9699.30 11599.63 13799.61 7799.71 10399.56 20298.76 11099.96 3599.14 9399.92 7799.68 61
lessismore_v099.64 11199.86 3199.38 16090.66 37599.89 2699.83 4794.56 29599.97 1799.56 2699.92 7799.57 146
SixPastTwentyTwo99.42 7099.30 9099.76 4799.92 1499.67 8799.70 2899.14 30799.65 6799.89 2699.90 2296.20 27699.94 5799.42 4699.92 7799.67 68
MVSTER98.47 25098.22 25399.24 23599.06 31798.35 27599.08 18799.46 23499.27 13099.75 8399.66 13988.61 35099.85 21799.14 9399.92 7799.52 175
N_pmnet98.73 21998.53 22599.35 21099.72 11098.67 25198.34 27794.65 36898.35 24699.79 6799.68 12998.03 19399.93 7198.28 15999.92 7799.44 209
CSCG99.37 8799.29 9599.60 13099.71 11399.46 13699.43 8799.85 2698.79 19999.41 20599.60 18398.92 8599.92 9198.02 18099.92 7799.43 215
CMPMVSbinary77.52 2398.50 24598.19 25899.41 19498.33 36299.56 11999.01 19799.59 16695.44 34499.57 15499.80 5995.64 28499.46 36496.47 29599.92 7799.21 260
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
EG-PatchMatch MVS99.57 3999.56 4499.62 12599.77 8299.33 17399.26 12899.76 6899.32 12499.80 6299.78 7199.29 3999.87 17899.15 8799.91 8699.66 78
miper_lstm_enhance98.65 22698.60 21398.82 28699.20 29597.33 31597.78 32799.66 11899.01 17099.59 14999.50 22394.62 29499.85 21798.12 17599.90 8799.26 250
EI-MVSNet-UG-set99.48 5499.50 5199.42 18699.57 17198.65 25699.24 13699.46 23499.68 5799.80 6299.66 13998.99 7799.89 15099.19 7899.90 8799.72 45
diffmvs99.34 9799.32 8499.39 19999.67 13898.77 24698.57 25799.81 4899.61 7799.48 18499.41 24698.47 15099.86 19898.97 10899.90 8799.53 165
YYNet198.95 19298.99 16998.84 28199.64 14397.14 32098.22 28899.32 27298.92 18399.59 14999.66 13997.40 23599.83 24598.27 16099.90 8799.55 152
GBi-Net99.42 7099.31 8599.73 7399.49 21099.77 4499.68 3799.70 10099.44 10799.62 13899.83 4797.21 24599.90 13398.96 11099.90 8799.53 165
FMVSNet597.80 28497.25 30099.42 18698.83 34098.97 22799.38 9399.80 4998.87 18999.25 23799.69 11880.60 37299.91 11398.96 11099.90 8799.38 226
test199.42 7099.31 8599.73 7399.49 21099.77 4499.68 3799.70 10099.44 10799.62 13899.83 4797.21 24599.90 13398.96 11099.90 8799.53 165
FMVSNet398.80 21098.63 21299.32 21799.13 30598.72 24899.10 18099.48 22699.23 13899.62 13899.64 14692.57 31499.86 19898.96 11099.90 8799.39 224
cl____98.54 24198.41 23598.92 26999.03 32197.80 30297.46 34399.59 16698.90 18599.60 14699.46 23993.85 30199.78 28297.97 18799.89 9599.17 271
DIV-MVS_self_test98.54 24198.42 23498.92 26999.03 32197.80 30297.46 34399.59 16698.90 18599.60 14699.46 23993.87 30099.78 28297.97 18799.89 9599.18 269
EI-MVSNet-Vis-set99.47 6099.49 5299.42 18699.57 17198.66 25399.24 13699.46 23499.67 6199.79 6799.65 14498.97 8099.89 15099.15 8799.89 9599.71 48
DSMNet-mixed99.48 5499.65 2498.95 26499.71 11397.27 31699.50 7599.82 3999.59 8599.41 20599.85 4199.62 16100.00 199.53 3099.89 9599.59 135
Vis-MVSNet (Re-imp)98.77 21298.58 21899.34 21199.78 7498.88 24099.61 5899.56 18299.11 16199.24 24099.56 20293.00 31299.78 28297.43 23699.89 9599.35 235
EPP-MVSNet99.17 14799.00 16499.66 9999.80 5899.43 14799.70 2899.24 29399.48 9599.56 16199.77 7894.89 29099.93 7198.72 13399.89 9599.63 100
CLD-MVS98.76 21498.57 21999.33 21399.57 17198.97 22797.53 33999.55 18896.41 33099.27 23599.13 30399.07 6999.78 28296.73 28099.89 9599.23 256
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
ACMH98.42 699.59 3899.54 4599.72 7999.86 3199.62 10299.56 7099.79 5598.77 20299.80 6299.85 4199.64 1399.85 21798.70 13499.89 9599.70 51
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
GeoE99.69 2199.66 2299.78 3799.76 8699.76 5199.60 6399.82 3999.46 10499.75 8399.56 20299.63 1499.95 4599.43 4199.88 10399.62 111
c3_l98.72 22098.71 20498.72 29199.12 30797.22 31897.68 33299.56 18298.90 18599.54 16899.48 23196.37 27299.73 30197.88 19399.88 10399.21 260
VPA-MVSNet99.66 2699.62 2799.79 3499.68 13399.75 5599.62 5399.69 10699.85 2499.80 6299.81 5798.81 9799.91 11399.47 3799.88 10399.70 51
MDA-MVSNet_test_wron98.95 19298.99 16998.85 27999.64 14397.16 31998.23 28799.33 27098.93 18199.56 16199.66 13997.39 23799.83 24598.29 15899.88 10399.55 152
XVG-OURS99.21 13499.06 14599.65 10499.82 4699.62 10297.87 32499.74 8098.36 24199.66 12099.68 12999.71 999.90 13396.84 27499.88 10399.43 215
CDS-MVSNet99.22 12999.13 12199.50 16299.35 25599.11 21298.96 21199.54 19499.46 10499.61 14499.70 11296.31 27399.83 24599.34 5599.88 10399.55 152
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
IS-MVSNet99.03 17498.85 19199.55 14899.80 5899.25 18999.73 2099.15 30699.37 11799.61 14499.71 10594.73 29399.81 27197.70 21599.88 10399.58 140
USDC98.96 18998.93 17899.05 25899.54 18397.99 29397.07 35799.80 4998.21 25899.75 8399.77 7898.43 15599.64 34497.90 19199.88 10399.51 177
ACMH+98.40 899.50 5099.43 6299.71 8399.86 3199.76 5199.32 10899.77 6399.53 8999.77 7599.76 8199.26 4599.78 28297.77 20499.88 10399.60 126
SD-MVS99.01 18099.30 9098.15 31399.50 20599.40 15598.94 21499.61 14799.22 14299.75 8399.82 5499.54 2295.51 37597.48 23399.87 11299.54 160
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
UniMVSNet (Re)99.37 8799.26 10299.68 8999.51 19899.58 11698.98 20899.60 15999.43 11299.70 10699.36 26197.70 21799.88 16599.20 7699.87 11299.59 135
WR-MVS99.11 16098.93 17899.66 9999.30 27699.42 15098.42 27499.37 26399.04 16999.57 15499.20 29896.89 25799.86 19898.66 13899.87 11299.70 51
NR-MVSNet99.40 7799.31 8599.68 8999.43 23499.55 12299.73 2099.50 21999.46 10499.88 3299.36 26197.54 23099.87 17898.97 10899.87 11299.63 100
LPG-MVS_test99.22 12999.05 14999.74 6399.82 4699.63 10099.16 16399.73 8397.56 29299.64 12699.69 11899.37 3199.89 15096.66 28499.87 11299.69 55
LGP-MVS_train99.74 6399.82 4699.63 10099.73 8397.56 29299.64 12699.69 11899.37 3199.89 15096.66 28499.87 11299.69 55
COLMAP_ROBcopyleft98.06 1299.45 6399.37 7499.70 8799.83 3999.70 7899.38 9399.78 6099.53 8999.67 11699.78 7199.19 5199.86 19897.32 24199.87 11299.55 152
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
test20.0399.55 4599.54 4599.58 13699.79 6899.37 16399.02 19599.89 1599.60 8399.82 5299.62 16598.81 9799.89 15099.43 4199.86 11999.47 198
Baseline_NR-MVSNet99.49 5299.37 7499.82 2399.91 1599.84 1998.83 22699.86 2299.68 5799.65 12499.88 2997.67 22299.87 17899.03 10199.86 11999.76 39
DROMVSNet99.69 2199.69 1899.68 8999.71 11399.91 299.76 1399.96 499.86 1999.51 18099.39 25399.57 2099.93 7199.64 1899.86 11999.20 264
MSDG99.08 16598.98 17299.37 20699.60 15299.13 21097.54 33799.74 8098.84 19499.53 17399.55 20999.10 6199.79 27997.07 26299.86 11999.18 269
EGC-MVSNET89.05 34085.52 34399.64 11199.89 2199.78 4199.56 7099.52 21124.19 37449.96 37599.83 4799.15 5599.92 9197.71 21299.85 12399.21 260
Patchmatch-RL test98.60 23198.36 24099.33 21399.77 8299.07 22098.27 28499.87 2098.91 18499.74 9299.72 9890.57 34099.79 27998.55 14299.85 12399.11 283
APDe-MVS99.48 5499.36 7799.85 1899.55 18299.81 3199.50 7599.69 10698.99 17199.75 8399.71 10598.79 10499.93 7198.46 14699.85 12399.80 24
ACMP97.51 1499.05 17098.84 19399.67 9299.78 7499.55 12298.88 21799.66 11897.11 31899.47 18699.60 18399.07 6999.89 15096.18 30799.85 12399.58 140
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
PMVScopyleft92.94 2198.82 20898.81 19798.85 27999.84 3597.99 29399.20 14699.47 23099.71 4799.42 19799.82 5498.09 18999.47 36293.88 35499.85 12399.07 296
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
Anonymous2023120699.35 9299.31 8599.47 17199.74 10399.06 22299.28 12399.74 8099.23 13899.72 9899.53 21497.63 22899.88 16599.11 9599.84 12899.48 193
Regformer-399.41 7499.41 6699.40 19699.52 19398.70 24999.17 15799.44 23999.62 7399.75 8399.60 18398.90 9099.85 21798.89 11899.84 12899.65 86
Regformer-499.45 6399.44 5999.50 16299.52 19398.94 23199.17 15799.53 20399.64 6999.76 7799.60 18398.96 8399.90 13398.91 11799.84 12899.67 68
HPM-MVS_fast99.43 6699.30 9099.80 2999.83 3999.81 3199.52 7399.70 10098.35 24699.51 18099.50 22399.31 3799.88 16598.18 17099.84 12899.69 55
XVG-ACMP-BASELINE99.23 12099.10 13699.63 11699.82 4699.58 11698.83 22699.72 9298.36 24199.60 14699.71 10598.92 8599.91 11397.08 26199.84 12899.40 221
new_pmnet98.88 20198.89 18798.84 28199.70 12197.62 30798.15 29299.50 21997.98 27199.62 13899.54 21198.15 18699.94 5797.55 22899.84 12898.95 308
Test_1112_low_res98.95 19298.73 20299.63 11699.68 13399.15 20998.09 30099.80 4997.14 31699.46 18999.40 24996.11 27899.89 15099.01 10399.84 12899.84 14
1112_ss99.05 17098.84 19399.67 9299.66 13999.29 17998.52 26499.82 3997.65 28999.43 19599.16 30196.42 26899.91 11399.07 9999.84 12899.80 24
3Dnovator99.15 299.43 6699.36 7799.65 10499.39 24599.42 15099.70 2899.56 18299.23 13899.35 21699.80 5999.17 5399.95 4598.21 16599.84 12899.59 135
LF4IMVS99.01 18098.92 18299.27 22899.71 11399.28 18198.59 25299.77 6398.32 25299.39 21199.41 24698.62 12799.84 23496.62 28899.84 12898.69 325
ACMMP_NAP99.28 10999.11 12899.79 3499.75 9799.81 3198.95 21299.53 20398.27 25599.53 17399.73 9298.75 11299.87 17897.70 21599.83 13899.68 61
AllTest99.21 13499.07 14399.63 11699.78 7499.64 9699.12 17799.83 3498.63 21399.63 13099.72 9898.68 11899.75 29696.38 29999.83 13899.51 177
TestCases99.63 11699.78 7499.64 9699.83 3498.63 21399.63 13099.72 9898.68 11899.75 29696.38 29999.83 13899.51 177
PM-MVS99.36 9099.29 9599.58 13699.83 3999.66 8998.95 21299.86 2298.85 19199.81 5999.73 9298.40 16299.92 9198.36 15199.83 13899.17 271
EPNet98.13 27397.77 28899.18 24394.57 37797.99 29399.24 13697.96 34799.74 4297.29 35899.62 16593.13 31099.97 1798.59 14099.83 13899.58 140
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
PVSNet_Blended98.70 22298.59 21599.02 26099.54 18397.99 29397.58 33699.82 3995.70 34299.34 21998.98 32798.52 14699.77 29097.98 18599.83 13899.30 244
MVS-HIRNet97.86 28298.22 25396.76 34299.28 28191.53 36998.38 27692.60 37399.13 15799.31 22799.96 1197.18 24999.68 32698.34 15499.83 13899.07 296
RPSCF99.18 14399.02 15899.64 11199.83 3999.85 1499.44 8599.82 3998.33 25199.50 18299.78 7197.90 20499.65 34296.78 27799.83 13899.44 209
TinyColmap98.97 18698.93 17899.07 25699.46 22698.19 28197.75 32899.75 7598.79 19999.54 16899.70 11298.97 8099.62 34696.63 28799.83 13899.41 219
MP-MVS-pluss99.14 15298.92 18299.80 2999.83 3999.83 2498.61 24999.63 13796.84 32499.44 19199.58 19198.81 9799.91 11397.70 21599.82 14799.67 68
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
MDA-MVSNet-bldmvs99.06 16799.05 14999.07 25699.80 5897.83 30098.89 21699.72 9299.29 12699.63 13099.70 11296.47 26699.89 15098.17 17299.82 14799.50 183
jason99.16 14899.11 12899.32 21799.75 9798.44 26798.26 28599.39 25698.70 20899.74 9299.30 27598.54 13999.97 1798.48 14599.82 14799.55 152
jason: jason.
HPM-MVScopyleft99.25 11699.07 14399.78 3799.81 5399.75 5599.61 5899.67 11497.72 28699.35 21699.25 28799.23 4799.92 9197.21 25499.82 14799.67 68
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
114514_t98.49 24898.11 26499.64 11199.73 10699.58 11699.24 13699.76 6889.94 36699.42 19799.56 20297.76 21699.86 19897.74 20999.82 14799.47 198
CP-MVS99.23 12099.05 14999.75 5799.66 13999.66 8999.38 9399.62 14098.38 23999.06 27099.27 28298.79 10499.94 5797.51 23299.82 14799.66 78
PHI-MVS99.11 16098.95 17799.59 13299.13 30599.59 11399.17 15799.65 12997.88 27899.25 23799.46 23998.97 8099.80 27697.26 24899.82 14799.37 229
wuyk23d97.58 29599.13 12192.93 35599.69 12499.49 12999.52 7399.77 6397.97 27299.96 899.79 6599.84 399.94 5795.85 32099.82 14779.36 371
CVMVSNet98.61 22998.88 18897.80 32299.58 16193.60 35799.26 12899.64 13599.66 6599.72 9899.67 13593.26 30899.93 7199.30 6399.81 15599.87 9
UniMVSNet_NR-MVSNet99.37 8799.25 10499.72 7999.47 22199.56 11998.97 21099.61 14799.43 11299.67 11699.28 28097.85 21099.95 4599.17 8399.81 15599.65 86
DU-MVS99.33 10199.21 10999.71 8399.43 23499.56 11998.83 22699.53 20399.38 11699.67 11699.36 26197.67 22299.95 4599.17 8399.81 15599.63 100
DeepPCF-MVS98.42 699.18 14399.02 15899.67 9299.22 29099.75 5597.25 35199.47 23098.72 20799.66 12099.70 11299.29 3999.63 34598.07 17999.81 15599.62 111
ACMM98.09 1199.46 6199.38 7199.72 7999.80 5899.69 8299.13 17399.65 12998.99 17199.64 12699.72 9899.39 2599.86 19898.23 16399.81 15599.60 126
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ZNCC-MVS99.22 12999.04 15599.77 4099.76 8699.73 6499.28 12399.56 18298.19 26099.14 25899.29 27898.84 9699.92 9197.53 23199.80 16099.64 95
test_0728_THIRD99.18 14599.62 13899.61 17498.58 13399.91 11397.72 21099.80 16099.77 35
SteuartSystems-ACMMP99.30 10699.14 11899.76 4799.87 2999.66 8999.18 15299.60 15998.55 22199.57 15499.67 13599.03 7499.94 5797.01 26399.80 16099.69 55
Skip Steuart: Steuart Systems R&D Blog.
DP-MVS99.48 5499.39 6999.74 6399.57 17199.62 10299.29 12299.61 14799.87 1799.74 9299.76 8198.69 11799.87 17898.20 16699.80 16099.75 42
PCF-MVS96.03 1896.73 31595.86 32699.33 21399.44 23199.16 20796.87 36099.44 23986.58 36898.95 27699.40 24994.38 29699.88 16587.93 36799.80 16098.95 308
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
SMA-MVScopyleft99.19 13999.00 16499.73 7399.46 22699.73 6499.13 17399.52 21197.40 30399.57 15499.64 14698.93 8499.83 24597.61 22599.79 16599.63 100
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
zzz-MVS99.30 10699.14 11899.80 2999.81 5399.81 3198.73 24499.53 20399.27 13099.42 19799.63 15698.21 18099.95 4597.83 20299.79 16599.65 86
MTAPA99.35 9299.20 11099.80 2999.81 5399.81 3199.33 10599.53 20399.27 13099.42 19799.63 15698.21 18099.95 4597.83 20299.79 16599.65 86
ACMMP++99.79 165
ACMMPcopyleft99.25 11699.08 13999.74 6399.79 6899.68 8599.50 7599.65 12998.07 26699.52 17599.69 11898.57 13499.92 9197.18 25699.79 16599.63 100
Qingshan Xu, Weihang Kong, Wenbing Tao, Marc Pollefeys: Multi-Scale Geometric Consistency Guided and Planar Prior Assisted Multi-View Stereo. IEEE Transactions on Pattern Analysis and Machine Intelligence
OMC-MVS98.90 19798.72 20399.44 18099.39 24599.42 15098.58 25399.64 13597.31 30899.44 19199.62 16598.59 13199.69 31596.17 30899.79 16599.22 258
tfpnnormal99.43 6699.38 7199.60 13099.87 2999.75 5599.59 6599.78 6099.71 4799.90 2299.69 11898.85 9599.90 13397.25 25199.78 17199.15 275
HQP_MVS98.90 19798.68 20999.55 14899.58 16199.24 19498.80 23499.54 19498.94 17899.14 25899.25 28797.24 24399.82 25595.84 32199.78 17199.60 126
plane_prior599.54 19499.82 25595.84 32199.78 17199.60 126
mPP-MVS99.19 13999.00 16499.76 4799.76 8699.68 8599.38 9399.54 19498.34 25099.01 27299.50 22398.53 14399.93 7197.18 25699.78 17199.66 78
CS-MVS99.40 7799.43 6299.29 22399.44 23199.72 6899.36 10099.91 1099.71 4799.28 23398.83 34399.22 4899.86 19899.40 4899.77 17598.29 345
OPM-MVS99.26 11599.13 12199.63 11699.70 12199.61 10898.58 25399.48 22698.50 22799.52 17599.63 15699.14 5899.76 29297.89 19299.77 17599.51 177
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
MVS_111021_LR99.13 15499.03 15799.42 18699.58 16199.32 17597.91 32399.73 8398.68 20999.31 22799.48 23199.09 6399.66 33597.70 21599.77 17599.29 247
abl_699.36 9099.23 10899.75 5799.71 11399.74 6199.33 10599.76 6899.07 16499.65 12499.63 15699.09 6399.92 9197.13 25999.76 17899.58 140
MIMVSNet98.43 25398.20 25599.11 25099.53 18898.38 27399.58 6798.61 33198.96 17699.33 22199.76 8190.92 33399.81 27197.38 23999.76 17899.15 275
MVS_111021_HR99.12 15699.02 15899.40 19699.50 20599.11 21297.92 32199.71 9598.76 20599.08 26699.47 23699.17 5399.54 35597.85 19999.76 17899.54 160
DPE-MVScopyleft99.14 15298.92 18299.82 2399.57 17199.77 4498.74 24299.60 15998.55 22199.76 7799.69 11898.23 17999.92 9196.39 29899.75 18199.76 39
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
TSAR-MVS + MP.99.34 9799.24 10699.63 11699.82 4699.37 16399.26 12899.35 26798.77 20299.57 15499.70 11299.27 4499.88 16597.71 21299.75 18199.65 86
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
HFP-MVS99.25 11699.08 13999.76 4799.73 10699.70 7899.31 11299.59 16698.36 24199.36 21499.37 25698.80 10199.91 11397.43 23699.75 18199.68 61
#test#99.12 15698.90 18699.76 4799.73 10699.70 7899.10 18099.59 16697.60 29199.36 21499.37 25698.80 10199.91 11396.84 27499.75 18199.68 61
ACMMPR99.23 12099.06 14599.76 4799.74 10399.69 8299.31 11299.59 16698.36 24199.35 21699.38 25598.61 12999.93 7197.43 23699.75 18199.67 68
MP-MVScopyleft99.06 16798.83 19599.76 4799.76 8699.71 7199.32 10899.50 21998.35 24698.97 27499.48 23198.37 16499.92 9195.95 31899.75 18199.63 100
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
QAPM98.40 25797.99 27099.65 10499.39 24599.47 13299.67 4199.52 21191.70 36398.78 29999.80 5998.55 13799.95 4594.71 34399.75 18199.53 165
DeepC-MVS_fast98.47 599.23 12099.12 12599.56 14599.28 28199.22 19898.99 20499.40 25399.08 16299.58 15199.64 14698.90 9099.83 24597.44 23599.75 18199.63 100
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
GST-MVS99.16 14898.96 17599.75 5799.73 10699.73 6499.20 14699.55 18898.22 25799.32 22399.35 26698.65 12599.91 11396.86 27199.74 18999.62 111
region2R99.23 12099.05 14999.77 4099.76 8699.70 7899.31 11299.59 16698.41 23599.32 22399.36 26198.73 11599.93 7197.29 24399.74 18999.67 68
Regformer-199.32 10399.27 10099.47 17199.41 24098.95 23098.99 20499.48 22699.48 9599.66 12099.52 21698.78 10699.87 17898.36 15199.74 18999.60 126
Regformer-299.34 9799.27 10099.53 15499.41 24099.10 21698.99 20499.53 20399.47 10099.66 12099.52 21698.80 10199.89 15098.31 15799.74 18999.60 126
PGM-MVS99.20 13699.01 16199.77 4099.75 9799.71 7199.16 16399.72 9297.99 27099.42 19799.60 18398.81 9799.93 7196.91 26899.74 18999.66 78
TransMVSNet (Re)99.78 1399.77 1299.81 2699.91 1599.85 1499.75 1599.86 2299.70 5299.91 2099.89 2699.60 1999.87 17899.59 2199.74 18999.71 48
TSAR-MVS + GP.99.12 15699.04 15599.38 20399.34 26599.16 20798.15 29299.29 28198.18 26199.63 13099.62 16599.18 5299.68 32698.20 16699.74 18999.30 244
KD-MVS_self_test99.63 3299.59 3499.76 4799.84 3599.90 599.37 9799.79 5599.83 3099.88 3299.85 4198.42 15799.90 13399.60 2099.73 19699.49 188
XVS99.27 11399.11 12899.75 5799.71 11399.71 7199.37 9799.61 14799.29 12698.76 30199.47 23698.47 15099.88 16597.62 22399.73 19699.67 68
X-MVStestdata96.09 32794.87 33799.75 5799.71 11399.71 7199.37 9799.61 14799.29 12698.76 30161.30 38098.47 15099.88 16597.62 22399.73 19699.67 68
VDD-MVS99.20 13699.11 12899.44 18099.43 23498.98 22599.50 7598.32 34399.80 3699.56 16199.69 11896.99 25599.85 21798.99 10499.73 19699.50 183
ab-mvs99.33 10199.28 9799.47 17199.57 17199.39 15799.78 1099.43 24398.87 18999.57 15499.82 5498.06 19299.87 17898.69 13699.73 19699.15 275
TAPA-MVS97.92 1398.03 27897.55 29499.46 17499.47 22199.44 14398.50 26699.62 14086.79 36799.07 26999.26 28598.26 17599.62 34697.28 24599.73 19699.31 243
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
DVP-MVScopyleft99.32 10399.17 11399.77 4099.69 12499.80 3699.14 16799.31 27699.16 15199.62 13899.61 17498.35 16699.91 11397.88 19399.72 20299.61 122
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_SECOND99.83 2199.70 12199.79 3899.14 16799.61 14799.92 9197.88 19399.72 20299.77 35
RRT_test8_iter0597.35 30397.25 30097.63 32798.81 34493.13 35999.26 12899.89 1599.51 9299.83 5099.68 12979.03 37799.88 16599.53 3099.72 20299.89 8
3Dnovator+98.92 399.35 9299.24 10699.67 9299.35 25599.47 13299.62 5399.50 21999.44 10799.12 26199.78 7198.77 10999.94 5797.87 19699.72 20299.62 111
plane_prior99.24 19498.42 27497.87 27999.71 206
APD-MVScopyleft98.87 20398.59 21599.71 8399.50 20599.62 10299.01 19799.57 17796.80 32699.54 16899.63 15698.29 17299.91 11395.24 33599.71 20699.61 122
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
SED-MVS99.40 7799.28 9799.77 4099.69 12499.82 2899.20 14699.54 19499.13 15799.82 5299.63 15698.91 8799.92 9197.85 19999.70 20899.58 140
IU-MVS99.69 12499.77 4499.22 29797.50 29899.69 10997.75 20899.70 20899.77 35
ambc99.20 24099.35 25598.53 26099.17 15799.46 23499.67 11699.80 5998.46 15399.70 30997.92 19099.70 20899.38 226
MSC_two_6792asdad99.74 6399.03 32199.53 12499.23 29499.92 9197.77 20499.69 21199.78 32
No_MVS99.74 6399.03 32199.53 12499.23 29499.92 9197.77 20499.69 21199.78 32
test_241102_TWO99.54 19499.13 15799.76 7799.63 15698.32 17199.92 9197.85 19999.69 21199.75 42
MVSFormer99.41 7499.44 5999.31 22099.57 17198.40 27099.77 1199.80 4999.73 4399.63 13099.30 27598.02 19599.98 799.43 4199.69 21199.55 152
lupinMVS98.96 18998.87 18999.24 23599.57 17198.40 27098.12 29699.18 30398.28 25499.63 13099.13 30398.02 19599.97 1798.22 16499.69 21199.35 235
xxxxxxxxxxxxxcwj99.11 16098.96 17599.54 15299.53 18899.25 18998.29 28299.76 6899.07 16499.42 19799.61 17498.86 9399.87 17896.45 29699.68 21699.49 188
SF-MVS99.10 16498.93 17899.62 12599.58 16199.51 12799.13 17399.65 12997.97 27299.42 19799.61 17498.86 9399.87 17896.45 29699.68 21699.49 188
Anonymous2024052999.42 7099.34 7999.65 10499.53 18899.60 11099.63 5299.39 25699.47 10099.76 7799.78 7198.13 18799.86 19898.70 13499.68 21699.49 188
MSLP-MVS++99.05 17099.09 13798.91 27199.21 29298.36 27498.82 23099.47 23098.85 19198.90 28499.56 20298.78 10699.09 36898.57 14199.68 21699.26 250
DELS-MVS99.34 9799.30 9099.48 16999.51 19899.36 16698.12 29699.53 20399.36 11999.41 20599.61 17499.22 4899.87 17899.21 7399.68 21699.20 264
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
PVSNet97.47 1598.42 25498.44 23298.35 30599.46 22696.26 33496.70 36299.34 26997.68 28899.00 27399.13 30397.40 23599.72 30397.59 22799.68 21699.08 291
LS3D99.24 11999.11 12899.61 12898.38 36099.79 3899.57 6899.68 10999.61 7799.15 25699.71 10598.70 11699.91 11397.54 22999.68 21699.13 282
ETH3D-3000-0.198.77 21298.50 22799.59 13299.47 22199.53 12498.77 23999.60 15997.33 30799.23 24199.50 22397.91 20399.83 24595.02 33999.67 22399.41 219
HQP3-MVS99.37 26399.67 223
CPTT-MVS98.74 21798.44 23299.64 11199.61 15099.38 16099.18 15299.55 18896.49 32999.27 23599.37 25697.11 25199.92 9195.74 32599.67 22399.62 111
HQP-MVS98.36 25998.02 26999.39 19999.31 27298.94 23197.98 31399.37 26397.45 30098.15 33398.83 34396.67 26099.70 30994.73 34199.67 22399.53 165
ETH3 D test640097.76 28697.19 30399.50 16299.38 24899.26 18598.34 27799.49 22492.99 36098.54 31799.20 29895.92 28299.82 25591.14 36299.66 22799.40 221
CS-MVS-test99.43 6699.40 6899.53 15499.51 19899.84 1999.60 6399.94 699.52 9199.10 26498.89 33999.24 4699.90 13399.11 9599.66 22798.84 319
MVS_Test99.28 10999.31 8599.19 24199.35 25598.79 24599.36 10099.49 22499.17 14999.21 24799.67 13598.78 10699.66 33599.09 9799.66 22799.10 285
CDPH-MVS98.56 23798.20 25599.61 12899.50 20599.46 13698.32 28099.41 24695.22 34799.21 24799.10 31098.34 16899.82 25595.09 33899.66 22799.56 149
tttt051797.62 29397.20 30298.90 27799.76 8697.40 31399.48 7994.36 36999.06 16899.70 10699.49 22884.55 36699.94 5798.73 13299.65 23199.36 232
ITE_SJBPF99.38 20399.63 14599.44 14399.73 8398.56 21999.33 22199.53 21498.88 9299.68 32696.01 31299.65 23199.02 304
9.1498.64 21099.45 22998.81 23199.60 15997.52 29799.28 23399.56 20298.53 14399.83 24595.36 33499.64 233
Patchmatch-test98.10 27597.98 27298.48 30099.27 28396.48 33199.40 8999.07 31098.81 19699.23 24199.57 19990.11 34499.87 17896.69 28199.64 23399.09 288
sss98.90 19798.77 20199.27 22899.48 21698.44 26798.72 24599.32 27297.94 27699.37 21399.35 26696.31 27399.91 11398.85 12099.63 23599.47 198
cl2297.56 29697.28 29898.40 30398.37 36196.75 32897.24 35299.37 26397.31 30899.41 20599.22 29487.30 35299.37 36697.70 21599.62 23699.08 291
miper_ehance_all_eth98.59 23498.59 21598.59 29698.98 32797.07 32197.49 34299.52 21198.50 22799.52 17599.37 25696.41 27099.71 30797.86 19799.62 23699.00 306
miper_enhance_ethall98.03 27897.94 27898.32 30798.27 36396.43 33396.95 35899.41 24696.37 33299.43 19598.96 33294.74 29299.69 31597.71 21299.62 23698.83 320
SCA98.11 27498.36 24097.36 33399.20 29592.99 36098.17 29198.49 33798.24 25699.10 26499.57 19996.01 28099.94 5796.86 27199.62 23699.14 279
MS-PatchMatch99.00 18298.97 17399.09 25299.11 31298.19 28198.76 24199.33 27098.49 22999.44 19199.58 19198.21 18099.69 31598.20 16699.62 23699.39 224
APD-MVS_3200maxsize99.31 10599.16 11499.74 6399.53 18899.75 5599.27 12699.61 14799.19 14499.57 15499.64 14698.76 11099.90 13397.29 24399.62 23699.56 149
EPNet_dtu97.62 29397.79 28797.11 34096.67 37492.31 36398.51 26598.04 34599.24 13695.77 36899.47 23693.78 30399.66 33598.98 10699.62 23699.37 229
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
SR-MVS-dyc-post99.27 11399.11 12899.73 7399.54 18399.74 6199.26 12899.62 14099.16 15199.52 17599.64 14698.41 15899.91 11397.27 24699.61 24399.54 160
RE-MVS-def99.13 12199.54 18399.74 6199.26 12899.62 14099.16 15199.52 17599.64 14698.57 13497.27 24699.61 24399.54 160
MG-MVS98.52 24398.39 23798.94 26599.15 30297.39 31498.18 28999.21 30198.89 18899.23 24199.63 15697.37 23999.74 29894.22 34899.61 24399.69 55
DVP-MVS++99.38 8499.25 10499.77 4099.03 32199.77 4499.74 1799.61 14799.18 14599.76 7799.61 17499.00 7599.92 9197.72 21099.60 24699.62 111
PC_three_145297.56 29299.68 11199.41 24699.09 6397.09 37396.66 28499.60 24699.62 111
OPU-MVS99.29 22399.12 30799.44 14399.20 14699.40 24999.00 7598.84 37096.54 29099.60 24699.58 140
HPM-MVS++copyleft98.96 18998.70 20799.74 6399.52 19399.71 7198.86 22199.19 30298.47 23198.59 31399.06 31398.08 19199.91 11396.94 26699.60 24699.60 126
CNVR-MVS98.99 18598.80 19999.56 14599.25 28699.43 14798.54 26299.27 28598.58 21898.80 29699.43 24498.53 14399.70 30997.22 25399.59 25099.54 160
Anonymous20240521198.75 21598.46 22999.63 11699.34 26599.66 8999.47 8197.65 35299.28 12999.56 16199.50 22393.15 30999.84 23498.62 13999.58 25199.40 221
MVP-Stereo99.16 14899.08 13999.43 18499.48 21699.07 22099.08 18799.55 18898.63 21399.31 22799.68 12998.19 18399.78 28298.18 17099.58 25199.45 204
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
ADS-MVSNet297.78 28597.66 29398.12 31599.14 30395.36 34599.22 14398.75 32596.97 31998.25 32999.64 14690.90 33499.94 5796.51 29299.56 25399.08 291
ADS-MVSNet97.72 29197.67 29297.86 32099.14 30394.65 35199.22 14398.86 31996.97 31998.25 32999.64 14690.90 33499.84 23496.51 29299.56 25399.08 291
LCM-MVSNet-Re99.28 10999.15 11799.67 9299.33 27099.76 5199.34 10399.97 298.93 18199.91 2099.79 6598.68 11899.93 7196.80 27699.56 25399.30 244
API-MVS98.38 25898.39 23798.35 30598.83 34099.26 18599.14 16799.18 30398.59 21798.66 30898.78 34798.61 12999.57 35494.14 34999.56 25396.21 368
test117299.23 12099.05 14999.74 6399.52 19399.75 5599.20 14699.61 14798.97 17399.48 18499.58 19198.41 15899.91 11397.15 25899.55 25799.57 146
xiu_mvs_v1_base_debu99.23 12099.34 7998.91 27199.59 15698.23 27898.47 26899.66 11899.61 7799.68 11198.94 33499.39 2599.97 1799.18 8099.55 25798.51 335
xiu_mvs_v1_base99.23 12099.34 7998.91 27199.59 15698.23 27898.47 26899.66 11899.61 7799.68 11198.94 33499.39 2599.97 1799.18 8099.55 25798.51 335
xiu_mvs_v1_base_debi99.23 12099.34 7998.91 27199.59 15698.23 27898.47 26899.66 11899.61 7799.68 11198.94 33499.39 2599.97 1799.18 8099.55 25798.51 335
OpenMVScopyleft98.12 1098.23 27097.89 28499.26 23099.19 29799.26 18599.65 5099.69 10691.33 36498.14 33799.77 7898.28 17399.96 3595.41 33299.55 25798.58 331
MVEpermissive92.54 2296.66 31796.11 32198.31 30999.68 13397.55 30997.94 31995.60 36699.37 11790.68 37498.70 35096.56 26298.61 37286.94 37299.55 25798.77 323
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
SR-MVS99.19 13999.00 16499.74 6399.51 19899.72 6899.18 15299.60 15998.85 19199.47 18699.58 19198.38 16399.92 9196.92 26799.54 26399.57 146
thisisatest053097.45 29896.95 30998.94 26599.68 13397.73 30499.09 18494.19 37198.61 21699.56 16199.30 27584.30 36799.93 7198.27 16099.54 26399.16 273
MSP-MVS99.04 17398.79 20099.81 2699.78 7499.73 6499.35 10299.57 17798.54 22499.54 16898.99 32496.81 25999.93 7196.97 26599.53 26599.77 35
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
AdaColmapbinary98.60 23198.35 24299.38 20399.12 30799.22 19898.67 24899.42 24597.84 28398.81 29499.27 28297.32 24199.81 27195.14 33699.53 26599.10 285
ETV-MVS99.18 14399.18 11299.16 24499.34 26599.28 18199.12 17799.79 5599.48 9598.93 27898.55 35699.40 2499.93 7198.51 14499.52 26798.28 346
EIA-MVS99.12 15699.01 16199.45 17899.36 25399.62 10299.34 10399.79 5598.41 23598.84 29198.89 33998.75 11299.84 23498.15 17499.51 26898.89 313
MCST-MVS99.02 17698.81 19799.65 10499.58 16199.49 12998.58 25399.07 31098.40 23799.04 27199.25 28798.51 14899.80 27697.31 24299.51 26899.65 86
mvs_anonymous99.28 10999.39 6998.94 26599.19 29797.81 30199.02 19599.55 18899.78 3999.85 4299.80 5998.24 17699.86 19899.57 2599.50 27099.15 275
CNLPA98.57 23698.34 24399.28 22699.18 29999.10 21698.34 27799.41 24698.48 23098.52 31898.98 32797.05 25399.78 28295.59 32799.50 27098.96 307
ZD-MVS99.43 23499.61 10899.43 24396.38 33199.11 26299.07 31297.86 20899.92 9194.04 35199.49 272
test_prior398.62 22898.34 24399.46 17499.35 25599.22 19897.95 31799.39 25697.87 27998.05 33999.05 31497.90 20499.69 31595.99 31499.49 27299.48 193
test_prior297.95 31797.87 27998.05 33999.05 31497.90 20495.99 31499.49 272
pmmvs398.08 27697.80 28598.91 27199.41 24097.69 30697.87 32499.66 11895.87 33899.50 18299.51 22090.35 34299.97 1798.55 14299.47 27599.08 291
test1299.54 15299.29 27899.33 17399.16 30598.43 32397.54 23099.82 25599.47 27599.48 193
agg_prior294.58 34599.46 27799.50 183
test9_res95.10 33799.44 27899.50 183
train_agg98.35 26297.95 27499.57 14199.35 25599.35 17098.11 29899.41 24694.90 35197.92 34498.99 32498.02 19599.85 21795.38 33399.44 27899.50 183
agg_prior198.33 26497.92 28099.57 14199.35 25599.36 16697.99 31299.39 25694.85 35497.76 35398.98 32798.03 19399.85 21795.49 32999.44 27899.51 177
VPNet99.46 6199.37 7499.71 8399.82 4699.59 11399.48 7999.70 10099.81 3399.69 10999.58 19197.66 22699.86 19899.17 8399.44 27899.67 68
DP-MVS Recon98.50 24598.23 25299.31 22099.49 21099.46 13698.56 25899.63 13794.86 35398.85 29099.37 25697.81 21299.59 35296.08 30999.44 27898.88 314
LFMVS98.46 25198.19 25899.26 23099.24 28898.52 26299.62 5396.94 35999.87 1799.31 22799.58 19191.04 33199.81 27198.68 13799.42 28399.45 204
Fast-Effi-MVS+99.02 17698.87 18999.46 17499.38 24899.50 12899.04 19299.79 5597.17 31498.62 31098.74 34999.34 3599.95 4598.32 15699.41 28498.92 311
PatchmatchNetpermissive97.65 29297.80 28597.18 33898.82 34392.49 36299.17 15798.39 34198.12 26298.79 29799.58 19190.71 33899.89 15097.23 25299.41 28499.16 273
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
thisisatest051596.98 30996.42 31698.66 29499.42 23997.47 31097.27 35094.30 37097.24 31099.15 25698.86 34285.01 36499.87 17897.10 26099.39 28698.63 326
ETH3D cwj APD-0.1698.50 24598.16 26199.51 15999.04 32099.39 15798.47 26899.47 23096.70 32898.78 29999.33 27097.62 22999.86 19894.69 34499.38 28799.28 249
testtj98.56 23798.17 26099.72 7999.45 22999.60 11098.88 21799.50 21996.88 32199.18 25399.48 23197.08 25299.92 9193.69 35599.38 28799.63 100
原ACMM199.37 20699.47 22198.87 24299.27 28596.74 32798.26 32899.32 27197.93 20299.82 25595.96 31799.38 28799.43 215
test22299.51 19899.08 21997.83 32699.29 28195.21 34898.68 30799.31 27397.28 24299.38 28799.43 215
F-COLMAP98.74 21798.45 23099.62 12599.57 17199.47 13298.84 22499.65 12996.31 33398.93 27899.19 30097.68 22199.87 17896.52 29199.37 29199.53 165
DPM-MVS98.28 26597.94 27899.32 21799.36 25399.11 21297.31 34998.78 32496.88 32198.84 29199.11 30997.77 21599.61 35094.03 35299.36 29299.23 256
旧先验199.49 21099.29 17999.26 28799.39 25397.67 22299.36 29299.46 202
PS-MVSNAJ99.00 18299.08 13998.76 28999.37 25198.10 28898.00 31099.51 21599.47 10099.41 20598.50 35999.28 4199.97 1798.83 12199.34 29498.20 352
112198.56 23798.24 25199.52 15699.49 21099.24 19499.30 11599.22 29795.77 34098.52 31899.29 27897.39 23799.85 21795.79 32399.34 29499.46 202
xiu_mvs_v2_base99.02 17699.11 12898.77 28899.37 25198.09 28998.13 29599.51 21599.47 10099.42 19798.54 35799.38 2999.97 1798.83 12199.33 29698.24 348
新几何199.52 15699.50 20599.22 19899.26 28795.66 34398.60 31299.28 28097.67 22299.89 15095.95 31899.32 29799.45 204
VDDNet98.97 18698.82 19699.42 18699.71 11398.81 24399.62 5398.68 32799.81 3399.38 21299.80 5994.25 29799.85 21798.79 12599.32 29799.59 135
VNet99.18 14399.06 14599.56 14599.24 28899.36 16699.33 10599.31 27699.67 6199.47 18699.57 19996.48 26599.84 23499.15 8799.30 29999.47 198
PatchMatch-RL98.68 22498.47 22899.30 22299.44 23199.28 18198.14 29499.54 19497.12 31799.11 26299.25 28797.80 21399.70 30996.51 29299.30 29998.93 310
Effi-MVS+-dtu99.07 16698.92 18299.52 15698.89 33499.78 4199.15 16599.66 11899.34 12098.92 28199.24 29297.69 21999.98 798.11 17699.28 30198.81 321
testdata99.42 18699.51 19898.93 23599.30 27996.20 33498.87 28899.40 24998.33 17099.89 15096.29 30299.28 30199.44 209
OpenMVS_ROBcopyleft97.31 1797.36 30296.84 31398.89 27899.29 27899.45 14198.87 22099.48 22686.54 36999.44 19199.74 8897.34 24099.86 19891.61 35999.28 30197.37 364
NCCC98.82 20898.57 21999.58 13699.21 29299.31 17698.61 24999.25 29098.65 21198.43 32399.26 28597.86 20899.81 27196.55 28999.27 30499.61 122
testgi99.29 10899.26 10299.37 20699.75 9798.81 24398.84 22499.89 1598.38 23999.75 8399.04 31799.36 3499.86 19899.08 9899.25 30599.45 204
PLCcopyleft97.35 1698.36 25997.99 27099.48 16999.32 27199.24 19498.50 26699.51 21595.19 34998.58 31498.96 33296.95 25699.83 24595.63 32699.25 30599.37 229
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
Fast-Effi-MVS+-dtu99.20 13699.12 12599.43 18499.25 28699.69 8299.05 19099.82 3999.50 9398.97 27499.05 31498.98 7899.98 798.20 16699.24 30798.62 327
PMMVS98.49 24898.29 24899.11 25098.96 32898.42 26997.54 33799.32 27297.53 29698.47 32298.15 36597.88 20799.82 25597.46 23499.24 30799.09 288
EPMVS96.53 31996.32 31797.17 33998.18 36692.97 36199.39 9189.95 37798.21 25898.61 31199.59 18986.69 36299.72 30396.99 26499.23 30998.81 321
alignmvs98.28 26597.96 27399.25 23399.12 30798.93 23599.03 19498.42 33999.64 6998.72 30497.85 36890.86 33699.62 34698.88 11999.13 31099.19 267
cascas96.99 30896.82 31497.48 32997.57 37395.64 34396.43 36499.56 18291.75 36297.13 36297.61 37195.58 28698.63 37196.68 28299.11 31198.18 353
BH-RMVSNet98.41 25598.14 26399.21 23899.21 29298.47 26498.60 25198.26 34498.35 24698.93 27899.31 27397.20 24899.66 33594.32 34699.10 31299.51 177
MAR-MVS98.24 26997.92 28099.19 24198.78 34899.65 9499.17 15799.14 30795.36 34598.04 34198.81 34697.47 23299.72 30395.47 33199.06 31398.21 350
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
GA-MVS97.99 28197.68 29198.93 26899.52 19398.04 29297.19 35399.05 31398.32 25298.81 29498.97 33089.89 34799.41 36598.33 15599.05 31499.34 237
EMVS96.96 31097.28 29895.99 35398.76 35091.03 37195.26 36898.61 33199.34 12098.92 28198.88 34193.79 30299.66 33592.87 35699.05 31497.30 365
E-PMN97.14 30797.43 29596.27 35098.79 34691.62 36895.54 36799.01 31699.44 10798.88 28599.12 30792.78 31399.68 32694.30 34799.03 31697.50 361
tpmrst97.73 28898.07 26696.73 34498.71 35292.00 36499.10 18098.86 31998.52 22598.92 28199.54 21191.90 32199.82 25598.02 18099.03 31698.37 342
PatchT98.45 25298.32 24698.83 28398.94 32998.29 27699.24 13698.82 32299.84 2799.08 26699.76 8191.37 32699.94 5798.82 12399.00 31898.26 347
CL-MVSNet_self_test98.71 22198.56 22299.15 24699.22 29098.66 25397.14 35499.51 21598.09 26599.54 16899.27 28296.87 25899.74 29898.43 14798.96 31999.03 300
test_yl98.25 26797.95 27499.13 24899.17 30098.47 26499.00 19998.67 32998.97 17399.22 24599.02 32291.31 32799.69 31597.26 24898.93 32099.24 253
DCV-MVSNet98.25 26797.95 27499.13 24899.17 30098.47 26499.00 19998.67 32998.97 17399.22 24599.02 32291.31 32799.69 31597.26 24898.93 32099.24 253
canonicalmvs99.02 17699.00 16499.09 25299.10 31398.70 24999.61 5899.66 11899.63 7298.64 30997.65 37099.04 7399.54 35598.79 12598.92 32299.04 299
MDTV_nov1_ep1397.73 28998.70 35390.83 37299.15 16598.02 34698.51 22698.82 29399.61 17490.98 33299.66 33596.89 27098.92 322
PAPM_NR98.36 25998.04 26799.33 21399.48 21698.93 23598.79 23799.28 28497.54 29598.56 31698.57 35497.12 25099.69 31594.09 35098.90 32499.38 226
FPMVS96.32 32395.50 33198.79 28799.60 15298.17 28398.46 27398.80 32397.16 31596.28 36499.63 15682.19 36899.09 36888.45 36698.89 32599.10 285
tpm cat196.78 31396.98 30896.16 35298.85 33890.59 37599.08 18799.32 27292.37 36197.73 35599.46 23991.15 33099.69 31596.07 31098.80 32698.21 350
test-LLR97.15 30596.95 30997.74 32598.18 36695.02 34897.38 34596.10 36198.00 26897.81 35098.58 35290.04 34599.91 11397.69 22198.78 32798.31 343
test-mter96.23 32695.73 32997.74 32598.18 36695.02 34897.38 34596.10 36197.90 27797.81 35098.58 35279.12 37699.91 11397.69 22198.78 32798.31 343
TESTMET0.1,196.24 32595.84 32797.41 33298.24 36493.84 35697.38 34595.84 36598.43 23297.81 35098.56 35579.77 37399.89 15097.77 20498.77 32998.52 334
CR-MVSNet98.35 26298.20 25598.83 28399.05 31898.12 28599.30 11599.67 11497.39 30499.16 25499.79 6591.87 32399.91 11398.78 12898.77 32998.44 340
RPMNet98.60 23198.53 22598.83 28399.05 31898.12 28599.30 11599.62 14099.86 1999.16 25499.74 8892.53 31699.92 9198.75 13098.77 32998.44 340
WTY-MVS98.59 23498.37 23999.26 23099.43 23498.40 27098.74 24299.13 30998.10 26399.21 24799.24 29294.82 29199.90 13397.86 19798.77 32999.49 188
Effi-MVS+99.06 16798.97 17399.34 21199.31 27298.98 22598.31 28199.91 1098.81 19698.79 29798.94 33499.14 5899.84 23498.79 12598.74 33399.20 264
PAPR97.56 29697.07 30599.04 25998.80 34598.11 28797.63 33399.25 29094.56 35798.02 34298.25 36497.43 23499.68 32690.90 36398.74 33399.33 238
tpmvs97.39 30097.69 29096.52 34798.41 35991.76 36699.30 11598.94 31897.74 28597.85 34999.55 20992.40 31999.73 30196.25 30498.73 33598.06 355
dp96.86 31197.07 30596.24 35198.68 35490.30 37699.19 15198.38 34297.35 30698.23 33199.59 18987.23 35399.82 25596.27 30398.73 33598.59 329
XVG-OURS-SEG-HR99.16 14898.99 16999.66 9999.84 3599.64 9698.25 28699.73 8398.39 23899.63 13099.43 24499.70 1199.90 13397.34 24098.64 33799.44 209
thres600view796.60 31896.16 32097.93 31899.63 14596.09 33899.18 15297.57 35398.77 20298.72 30497.32 37487.04 35599.72 30388.57 36598.62 33897.98 357
thres20096.09 32795.68 33097.33 33599.48 21696.22 33598.53 26397.57 35398.06 26798.37 32596.73 37986.84 35999.61 35086.99 37198.57 33996.16 369
131498.00 28097.90 28398.27 31198.90 33197.45 31299.30 11599.06 31294.98 35097.21 36099.12 30798.43 15599.67 33195.58 32898.56 34097.71 360
mvs-test198.83 20698.70 20799.22 23798.89 33499.65 9498.88 21799.66 11899.34 12098.29 32698.94 33497.69 21999.96 3598.11 17698.54 34198.04 356
thres100view90096.39 32196.03 32397.47 33099.63 14595.93 33999.18 15297.57 35398.75 20698.70 30697.31 37587.04 35599.67 33187.62 36898.51 34296.81 366
tfpn200view996.30 32495.89 32497.53 32899.58 16196.11 33699.00 19997.54 35698.43 23298.52 31896.98 37786.85 35799.67 33187.62 36898.51 34296.81 366
thres40096.40 32095.89 32497.92 31999.58 16196.11 33699.00 19997.54 35698.43 23298.52 31896.98 37786.85 35799.67 33187.62 36898.51 34297.98 357
MVS95.72 33594.63 33998.99 26198.56 35697.98 29899.30 11598.86 31972.71 37297.30 35799.08 31198.34 16899.74 29889.21 36498.33 34599.26 250
BH-untuned98.22 27198.09 26598.58 29799.38 24897.24 31798.55 25998.98 31797.81 28499.20 25298.76 34897.01 25499.65 34294.83 34098.33 34598.86 316
test_method91.72 33992.32 34289.91 35693.49 37870.18 38090.28 36999.56 18261.71 37395.39 37099.52 21693.90 29999.94 5798.76 12998.27 34799.62 111
gg-mvs-nofinetune95.87 33295.17 33697.97 31798.19 36596.95 32399.69 3489.23 37899.89 1196.24 36699.94 1381.19 36999.51 36093.99 35398.20 34897.44 362
HY-MVS98.23 998.21 27297.95 27498.99 26199.03 32198.24 27799.61 5898.72 32696.81 32598.73 30399.51 22094.06 29899.86 19896.91 26898.20 34898.86 316
UnsupCasMVSNet_bld98.55 24098.27 24999.40 19699.56 18199.37 16397.97 31699.68 10997.49 29999.08 26699.35 26695.41 28799.82 25597.70 21598.19 35099.01 305
tpm296.35 32296.22 31996.73 34498.88 33791.75 36799.21 14598.51 33593.27 35997.89 34699.21 29684.83 36599.70 30996.04 31198.18 35198.75 324
tmp_tt95.75 33495.42 33296.76 34289.90 37994.42 35298.86 22197.87 35078.01 37099.30 23299.69 11897.70 21795.89 37499.29 6698.14 35299.95 1
baseline296.83 31296.28 31898.46 30199.09 31596.91 32598.83 22693.87 37297.23 31196.23 36798.36 36188.12 35199.90 13396.68 28298.14 35298.57 332
CostFormer96.71 31696.79 31596.46 34998.90 33190.71 37499.41 8898.68 32794.69 35698.14 33799.34 26986.32 36399.80 27697.60 22698.07 35498.88 314
DWT-MVSNet_test96.03 32995.80 32896.71 34698.50 35891.93 36599.25 13597.87 35095.99 33796.81 36397.61 37181.02 37099.66 33597.20 25597.98 35598.54 333
AUN-MVS97.82 28397.38 29699.14 24799.27 28398.53 26098.72 24599.02 31498.10 26397.18 36199.03 32189.26 34999.85 21797.94 18997.91 35699.03 300
DeepMVS_CXcopyleft97.98 31699.69 12496.95 32399.26 28775.51 37195.74 36998.28 36396.47 26699.62 34691.23 36197.89 35797.38 363
hse-mvs298.52 24398.30 24799.16 24499.29 27898.60 25898.77 23999.02 31499.68 5799.32 22399.04 31792.50 31799.85 21799.24 7097.87 35899.03 300
PAPM95.61 33694.71 33898.31 30999.12 30796.63 32996.66 36398.46 33890.77 36596.25 36598.68 35193.01 31199.69 31581.60 37397.86 35998.62 327
JIA-IIPM98.06 27797.92 28098.50 29998.59 35597.02 32298.80 23498.51 33599.88 1697.89 34699.87 3291.89 32299.90 13398.16 17397.68 36098.59 329
ET-MVSNet_ETH3D96.78 31396.07 32298.91 27199.26 28597.92 29997.70 33196.05 36497.96 27592.37 37398.43 36087.06 35499.90 13398.27 16097.56 36198.91 312
TR-MVS97.44 29997.15 30498.32 30798.53 35797.46 31198.47 26897.91 34996.85 32398.21 33298.51 35896.42 26899.51 36092.16 35897.29 36297.98 357
BH-w/o97.20 30497.01 30797.76 32399.08 31695.69 34298.03 30798.52 33495.76 34197.96 34398.02 36695.62 28599.47 36292.82 35797.25 36398.12 354
KD-MVS_2432*160095.89 33095.41 33397.31 33694.96 37593.89 35497.09 35599.22 29797.23 31198.88 28599.04 31779.23 37499.54 35596.24 30596.81 36498.50 338
miper_refine_blended95.89 33095.41 33397.31 33694.96 37593.89 35497.09 35599.22 29797.23 31198.88 28599.04 31779.23 37499.54 35596.24 30596.81 36498.50 338
UnsupCasMVSNet_eth98.83 20698.57 21999.59 13299.68 13399.45 14198.99 20499.67 11499.48 9599.55 16699.36 26194.92 28999.86 19898.95 11496.57 36699.45 204
h-mvs3398.61 22998.34 24399.44 18099.60 15298.67 25199.27 12699.44 23999.68 5799.32 22399.49 22892.50 317100.00 199.24 7096.51 36799.65 86
GG-mvs-BLEND97.36 33397.59 37196.87 32699.70 2888.49 37994.64 37297.26 37680.66 37199.12 36791.50 36096.50 36896.08 370
tpm97.15 30596.95 30997.75 32498.91 33094.24 35399.32 10897.96 34797.71 28798.29 32699.32 27186.72 36199.92 9198.10 17896.24 36999.09 288
test0.0.03 197.37 30196.91 31298.74 29097.72 37097.57 30897.60 33597.36 35898.00 26899.21 24798.02 36690.04 34599.79 27998.37 15095.89 37098.86 316
IB-MVS95.41 2095.30 33794.46 34197.84 32198.76 35095.33 34697.33 34896.07 36396.02 33695.37 37197.41 37376.17 37999.96 3597.54 22995.44 37198.22 349
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
baseline197.73 28897.33 29798.96 26399.30 27697.73 30499.40 8998.42 33999.33 12399.46 18999.21 29691.18 32999.82 25598.35 15391.26 37299.32 241
PVSNet_095.53 1995.85 33395.31 33597.47 33098.78 34893.48 35895.72 36699.40 25396.18 33597.37 35697.73 36995.73 28399.58 35395.49 32981.40 37399.36 232
testmvs28.94 34233.33 34415.79 35826.03 3809.81 38296.77 36115.67 38111.55 37623.87 37750.74 38319.03 3818.53 37723.21 37533.07 37429.03 373
test12329.31 34133.05 34618.08 35725.93 38112.24 38197.53 33910.93 38211.78 37524.21 37650.08 38421.04 3808.60 37623.51 37432.43 37533.39 372
test_blank8.33 34511.11 3480.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 378100.00 10.00 3820.00 3780.00 3760.00 3760.00 374
uanet_test8.33 34511.11 3480.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 378100.00 10.00 3820.00 3780.00 3760.00 3760.00 374
cdsmvs_eth3d_5k24.88 34333.17 3450.00 3590.00 3820.00 3830.00 37099.62 1400.00 3770.00 37899.13 30399.82 40.00 3780.00 3760.00 3760.00 374
pcd_1.5k_mvsjas16.61 34422.14 3470.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 378100.00 199.28 410.00 3780.00 3760.00 3760.00 374
sosnet-low-res8.33 34511.11 3480.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 378100.00 10.00 3820.00 3780.00 3760.00 3760.00 374
sosnet8.33 34511.11 3480.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 378100.00 10.00 3820.00 3780.00 3760.00 3760.00 374
uncertanet8.33 34511.11 3480.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 378100.00 10.00 3820.00 3780.00 3760.00 3760.00 374
Regformer8.33 34511.11 3480.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 378100.00 10.00 3820.00 3780.00 3760.00 3760.00 374
ab-mvs-re8.26 35211.02 3550.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 37899.16 3010.00 3820.00 3780.00 3760.00 3760.00 374
uanet8.33 34511.11 3480.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 378100.00 10.00 3820.00 3780.00 3760.00 3760.00 374
FOURS199.83 3999.89 899.74 1799.71 9599.69 5599.63 130
test_one_060199.63 14599.76 5199.55 18899.23 13899.31 22799.61 17498.59 131
eth-test20.00 382
eth-test0.00 382
test_241102_ONE99.69 12499.82 2899.54 19499.12 16099.82 5299.49 22898.91 8799.52 359
save fliter99.53 18899.25 18998.29 28299.38 26299.07 164
test072699.69 12499.80 3699.24 13699.57 17799.16 15199.73 9699.65 14498.35 166
GSMVS99.14 279
test_part299.62 14999.67 8799.55 166
sam_mvs190.81 33799.14 279
sam_mvs90.52 341
MTGPAbinary99.53 203
test_post199.14 16751.63 38289.54 34899.82 25596.86 271
test_post52.41 38190.25 34399.86 198
patchmatchnet-post99.62 16590.58 33999.94 57
MTMP99.09 18498.59 333
gm-plane-assit97.59 37189.02 37893.47 35898.30 36299.84 23496.38 299
TEST999.35 25599.35 17098.11 29899.41 24694.83 35597.92 34498.99 32498.02 19599.85 217
test_899.34 26599.31 17698.08 30299.40 25394.90 35197.87 34898.97 33098.02 19599.84 234
agg_prior99.35 25599.36 16699.39 25697.76 35399.85 217
test_prior499.19 20598.00 310
test_prior99.46 17499.35 25599.22 19899.39 25699.69 31599.48 193
旧先验297.94 31995.33 34698.94 27799.88 16596.75 278
新几何298.04 306
无先验98.01 30899.23 29495.83 33999.85 21795.79 32399.44 209
原ACMM297.92 321
testdata299.89 15095.99 314
segment_acmp98.37 164
testdata197.72 32997.86 282
plane_prior799.58 16199.38 160
plane_prior699.47 22199.26 18597.24 243
plane_prior499.25 287
plane_prior399.31 17698.36 24199.14 258
plane_prior298.80 23498.94 178
plane_prior199.51 198
n20.00 383
nn0.00 383
door-mid99.83 34
test1199.29 281
door99.77 63
HQP5-MVS98.94 231
HQP-NCC99.31 27297.98 31397.45 30098.15 333
ACMP_Plane99.31 27297.98 31397.45 30098.15 333
BP-MVS94.73 341
HQP4-MVS98.15 33399.70 30999.53 165
HQP2-MVS96.67 260
NP-MVS99.40 24399.13 21098.83 343
MDTV_nov1_ep13_2view91.44 37099.14 16797.37 30599.21 24791.78 32596.75 27899.03 300
Test By Simon98.41 158