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

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

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

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

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




Method Infoallhigh-res
multi-view
indooroutdoorbotani.boulde.bridgedoorexhibi.lectur.living.loungeobserv.old co.statueterrac.
sort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysorted bysort bysort bysort bysort bysort by
UA-Net99.42 2999.29 3699.80 2999.62 9199.55 5199.50 11699.70 1598.79 4099.77 2399.96 197.45 9199.96 1898.92 5499.90 2299.89 2
DeepC-MVS98.35 299.30 4499.19 4799.64 6199.82 2999.23 8799.62 7099.55 5398.94 2699.63 5099.95 295.82 13699.94 4099.37 1699.97 299.73 63
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
OurMVSNet-221017-097.88 18697.77 17698.19 24098.71 26896.53 25099.88 199.00 26597.79 11598.78 20199.94 391.68 26099.35 21397.21 20496.99 22298.69 209
SixPastTwentyTwo97.50 22897.33 22398.03 24698.65 27496.23 26099.77 2498.68 29697.14 17097.90 25899.93 490.45 27099.18 25097.00 21796.43 23098.67 225
SD-MVS99.41 3299.52 699.05 13699.74 5399.68 3099.46 13499.52 7599.11 899.88 399.91 599.43 197.70 30798.72 8099.93 899.77 49
ACMH97.28 898.10 15697.99 15498.44 21499.41 13196.96 23799.60 7799.56 4698.09 8998.15 24899.91 590.87 26899.70 16398.88 5697.45 20698.67 225
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
VDDNet97.55 22197.02 23699.16 12799.49 11698.12 19999.38 16799.30 21895.35 25999.68 3499.90 782.62 31799.93 5599.31 2498.13 17799.42 140
QAPM98.67 12298.30 13599.80 2999.20 17399.67 3299.77 2499.72 1194.74 26698.73 20599.90 795.78 13799.98 596.96 22199.88 3399.76 52
3Dnovator97.25 999.24 5299.05 5899.81 2799.12 19099.66 3499.84 999.74 1099.09 998.92 18499.90 795.94 13199.98 598.95 5299.92 999.79 43
CHOSEN 1792x268899.19 5599.10 5599.45 9399.89 898.52 17999.39 16299.94 198.73 4499.11 15199.89 1095.50 14399.94 4099.50 799.97 299.89 2
RPSCF98.22 14398.62 11396.99 28099.82 2991.58 30799.72 3999.44 15396.61 20499.66 4599.89 1095.92 13299.82 12097.46 19299.10 12699.57 108
3Dnovator+97.12 1399.18 5798.97 7199.82 2499.17 18299.68 3099.81 1599.51 8499.20 698.72 20699.89 1095.68 14099.97 1098.86 6399.86 4799.81 34
COLMAP_ROBcopyleft97.56 698.86 9898.75 9899.17 12699.88 1198.53 17699.34 17999.59 3797.55 13698.70 21399.89 1095.83 13599.90 8498.10 13399.90 2299.08 163
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
test_djsdf98.67 12298.57 12198.98 14398.70 26998.91 12899.88 199.46 13497.55 13699.22 13599.88 1495.73 13999.28 22999.03 4597.62 19198.75 193
DP-MVS99.16 6098.95 7599.78 3399.77 3899.53 5599.41 15599.50 9797.03 18299.04 16599.88 1497.39 9299.92 6398.66 8699.90 2299.87 4
TDRefinement95.42 27394.57 27897.97 25289.83 32396.11 26299.48 12798.75 28896.74 19596.68 27799.88 1488.65 29099.71 15798.37 11782.74 31998.09 282
EPP-MVSNet99.13 6298.99 6899.53 7899.65 8499.06 10299.81 1599.33 20997.43 14699.60 5699.88 1497.14 9999.84 10899.13 3898.94 13999.69 77
OpenMVScopyleft96.50 1698.47 12998.12 14399.52 8299.04 20599.53 5599.82 1399.72 1194.56 27298.08 25199.88 1494.73 18599.98 597.47 19199.76 7699.06 168
lessismore_v097.79 26598.69 27095.44 27594.75 32695.71 28699.87 1988.69 28899.32 22095.89 25294.93 25898.62 249
Vis-MVSNetpermissive99.12 6798.97 7199.56 7399.78 3499.10 9899.68 4999.66 2598.49 5699.86 799.87 1994.77 18299.84 10899.19 3299.41 10799.74 58
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
ACMH+97.24 1097.92 18397.78 17298.32 22299.46 12196.68 24799.56 9599.54 6198.41 6397.79 26399.87 1990.18 27599.66 17098.05 14297.18 21998.62 249
ACMMP_Plus99.47 2099.34 2499.88 499.87 1599.86 399.47 13199.48 11198.05 9899.76 2699.86 2298.82 3299.93 5598.82 7199.91 1599.84 12
PVSNet_Blended_VisFu99.36 3899.28 3899.61 6599.86 2099.07 10199.47 13199.93 297.66 12999.71 2999.86 2297.73 8699.96 1899.47 1299.82 6499.79 43
IS-MVSNet99.05 8098.87 8499.57 7099.73 5899.32 7699.75 3499.20 24298.02 10299.56 6399.86 2296.54 11699.67 16898.09 13499.13 12399.73 63
USDC97.34 23597.20 23197.75 26799.07 19995.20 27898.51 30299.04 26297.99 10398.31 24399.86 2289.02 28399.55 18795.67 25897.36 21398.49 269
TSAR-MVS + MP.99.58 399.50 799.81 2799.91 199.66 3499.63 6799.39 17598.91 3099.78 2299.85 2699.36 299.94 4098.84 6699.88 3399.82 30
tmp_tt82.80 29981.52 29986.66 31066.61 33468.44 33292.79 32797.92 31368.96 32580.04 32499.85 2685.77 30696.15 31697.86 15343.89 32995.39 315
AllTest98.87 9598.72 9999.31 10999.86 2098.48 18499.56 9599.61 3297.85 10999.36 10199.85 2695.95 12999.85 10396.66 23799.83 6099.59 105
TestCases99.31 10999.86 2098.48 18499.61 3297.85 10999.36 10199.85 2695.95 12999.85 10396.66 23799.83 6099.59 105
VDD-MVS97.73 20797.35 21898.88 16799.47 12097.12 22199.34 17998.85 28398.19 7699.67 4099.85 2682.98 31599.92 6399.49 1198.32 17199.60 101
APDe-MVS99.66 199.57 199.92 199.77 3899.89 199.75 3499.56 4699.02 1199.88 399.85 2699.18 599.96 1899.22 3099.92 999.90 1
DeepPCF-MVS98.18 398.81 10799.37 1797.12 27999.60 9791.75 30698.61 29799.44 15399.35 199.83 1199.85 2698.70 4899.81 12499.02 4799.91 1599.81 34
ACMM97.58 598.37 13798.34 13198.48 20799.41 13197.10 22299.56 9599.45 14598.53 5499.04 16599.85 2693.00 23199.71 15798.74 7597.45 20698.64 241
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
LS3D99.27 4999.12 5399.74 4399.18 17799.75 2199.56 9599.57 4398.45 5999.49 7599.85 2697.77 8599.94 4098.33 12199.84 5699.52 116
XVG-OURS98.73 11798.68 10498.88 16799.70 6897.73 20998.92 27799.55 5398.52 5599.45 8099.84 3595.27 14999.91 7298.08 13898.84 14899.00 173
ACMMPcopyleft99.45 2299.32 2699.82 2499.89 899.67 3299.62 7099.69 1898.12 8499.63 5099.84 3598.73 4699.96 1898.55 10399.83 6099.81 34
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
EI-MVSNet-UG-set99.58 399.57 199.64 6199.78 3499.14 9499.60 7799.45 14599.01 1499.90 199.83 3798.98 1899.93 5599.59 199.95 599.86 5
EI-MVSNet98.67 12298.67 10598.68 19199.35 14397.97 20299.50 11699.38 18196.93 18899.20 14099.83 3797.87 8199.36 21098.38 11697.56 19698.71 200
CVMVSNet98.57 12798.67 10598.30 22499.35 14395.59 26899.50 11699.55 5398.60 5199.39 9399.83 3794.48 19699.45 19398.75 7498.56 16199.85 8
LPG-MVS_test98.22 14398.13 14298.49 20599.33 14797.05 22899.58 8299.55 5397.46 14299.24 12899.83 3792.58 24699.72 15198.09 13497.51 19998.68 214
LGP-MVS_train98.49 20599.33 14797.05 22899.55 5397.46 14299.24 12899.83 3792.58 24699.72 15198.09 13497.51 19998.68 214
SteuartSystems-ACMMP99.54 799.42 1199.87 699.82 2999.81 1199.59 7999.51 8498.62 4999.79 1899.83 3799.28 399.97 1098.48 10899.90 2299.84 12
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XXY-MVS98.38 13698.09 14699.24 12199.26 16599.32 7699.56 9599.55 5397.45 14598.71 20799.83 3793.23 22899.63 17998.88 5696.32 23398.76 192
nrg03098.64 12598.42 12799.28 11899.05 20499.69 2999.81 1599.46 13498.04 9999.01 16899.82 4496.69 11399.38 20399.34 2194.59 26898.78 187
FC-MVSNet-test98.75 11698.62 11399.15 12999.08 19899.45 6699.86 899.60 3498.23 7598.70 21399.82 4496.80 10799.22 24499.07 4396.38 23198.79 186
EI-MVSNet-Vis-set99.58 399.56 399.64 6199.78 3499.15 9399.61 7699.45 14599.01 1499.89 299.82 4499.01 1199.92 6399.56 499.95 599.85 8
APD-MVS_3200maxsize99.48 1799.35 2299.85 1799.76 4199.83 799.63 6799.54 6198.36 6599.79 1899.82 4498.86 2999.95 3398.62 9199.81 6599.78 47
EU-MVSNet97.98 17598.03 15197.81 26498.72 26696.65 24899.66 5499.66 2598.09 8998.35 24199.82 4495.25 15198.01 29997.41 19695.30 24898.78 187
APD-MVScopyleft99.27 4999.08 5699.84 2199.75 4799.79 1699.50 11699.50 9797.16 16999.77 2399.82 4498.78 3699.94 4097.56 18199.86 4799.80 39
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
TAMVS99.12 6799.08 5699.24 12199.46 12198.55 17499.51 11199.46 13498.09 8999.45 8099.82 4498.34 6899.51 18998.70 8198.93 14099.67 84
DeepC-MVS_fast98.69 199.49 1399.39 1599.77 3599.63 8799.59 4699.36 17399.46 13499.07 1099.79 1899.82 4498.85 3099.92 6398.68 8599.87 3799.82 30
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
MG-MVS99.13 6299.02 6699.45 9399.57 10298.63 16799.07 23999.34 20198.99 1999.61 5599.82 4497.98 8099.87 9797.00 21799.80 6799.85 8
OPM-MVS98.19 14798.10 14498.45 21198.88 24297.07 22699.28 19499.38 18198.57 5299.22 13599.81 5392.12 25699.66 17098.08 13897.54 19898.61 258
MPTG99.49 1399.36 1999.89 299.90 399.86 399.36 17399.47 12598.79 4099.68 3499.81 5398.43 6199.97 1098.88 5699.90 2299.83 23
MTAPA99.52 1199.39 1599.89 299.90 399.86 399.66 5499.47 12598.79 4099.68 3499.81 5398.43 6199.97 1098.88 5699.90 2299.83 23
FIs98.78 11298.63 11099.23 12399.18 17799.54 5299.83 1299.59 3798.28 7098.79 20099.81 5396.75 11199.37 20699.08 4296.38 23198.78 187
mvs_tets98.40 13598.23 13898.91 15898.67 27398.51 18199.66 5499.53 7198.19 7698.65 22399.81 5392.75 23799.44 19899.31 2497.48 20598.77 190
mvs_anonymous99.03 8398.99 6899.16 12799.38 13898.52 17999.51 11199.38 18197.79 11599.38 9599.81 5397.30 9699.45 19399.35 1798.99 13499.51 119
TSAR-MVS + GP.99.36 3899.36 1999.36 10399.67 7298.61 17299.07 23999.33 20999.00 1899.82 1499.81 5399.06 899.84 10899.09 4199.42 10699.65 88
abl_699.44 2599.31 3199.83 2299.85 2399.75 2199.66 5499.59 3798.13 8299.82 1499.81 5398.60 5499.96 1898.46 11199.88 3399.79 43
EPNet98.86 9898.71 10199.30 11297.20 30498.18 19599.62 7098.91 27799.28 298.63 22599.81 5395.96 12899.99 199.24 2999.72 8399.73 63
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
ab-mvs98.86 9898.63 11099.54 7499.64 8599.19 8899.44 13999.54 6197.77 11799.30 11199.81 5394.20 20699.93 5599.17 3598.82 14999.49 123
OMC-MVS99.08 7799.04 6199.20 12599.67 7298.22 19499.28 19499.52 7598.07 9399.66 4599.81 5397.79 8499.78 13297.79 15899.81 6599.60 101
jajsoiax98.43 13298.28 13698.88 16798.60 27898.43 18799.82 1399.53 7198.19 7698.63 22599.80 6493.22 22999.44 19899.22 3097.50 20198.77 190
Regformer-399.57 699.53 599.68 5099.76 4199.29 8099.58 8299.44 15399.01 1499.87 699.80 6498.97 1999.91 7299.44 1599.92 999.83 23
Regformer-499.59 299.54 499.73 4599.76 4199.41 7099.58 8299.49 10299.02 1199.88 399.80 6499.00 1799.94 4099.45 1499.92 999.84 12
PGM-MVS99.45 2299.31 3199.86 1299.87 1599.78 2099.58 8299.65 3097.84 11199.71 2999.80 6499.12 799.97 1098.33 12199.87 3799.83 23
TransMVSNet (Re)97.15 24096.58 24398.86 17599.12 19098.85 13499.49 12298.91 27795.48 25897.16 27199.80 6493.38 22799.11 25794.16 28791.73 29698.62 249
K. test v397.10 24296.79 24098.01 24998.72 26696.33 25799.87 497.05 32297.59 13196.16 28299.80 6488.71 28799.04 26396.69 23596.55 22898.65 239
DELS-MVS99.48 1799.42 1199.65 5699.72 6199.40 7299.05 24599.66 2599.14 799.57 6299.80 6498.46 5999.94 4099.57 299.84 5699.60 101
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
CSCG99.32 4299.32 2699.32 10899.85 2398.29 19199.71 4199.66 2598.11 8699.41 8899.80 6498.37 6799.96 1898.99 4999.96 499.72 69
MP-MVS-pluss99.37 3799.20 4699.88 499.90 399.87 299.30 18699.52 7597.18 16799.60 5699.79 7298.79 3599.95 3398.83 6899.91 1599.83 23
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
pm-mvs197.68 21497.28 22898.88 16799.06 20198.62 16999.50 11699.45 14596.32 22797.87 25999.79 7292.47 25099.35 21397.54 18393.54 28498.67 225
LFMVS97.90 18597.35 21899.54 7499.52 10899.01 10899.39 16298.24 30897.10 17799.65 4899.79 7284.79 31199.91 7299.28 2698.38 16999.69 77
TinyColmap97.12 24196.89 23897.83 26299.07 19995.52 27298.57 29998.74 29197.58 13397.81 26299.79 7288.16 29799.56 18595.10 26797.21 21798.39 277
ACMP97.20 1198.06 15997.94 15898.45 21199.37 14097.01 23199.44 13999.49 10297.54 13998.45 23599.79 7291.95 25799.72 15197.91 14997.49 20498.62 249
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
pmmvs696.53 24996.09 25097.82 26398.69 27095.47 27399.37 16999.47 12593.46 29197.41 26699.78 7787.06 30399.33 21796.92 22592.70 29398.65 239
MSLP-MVS++99.46 2199.47 899.44 9699.60 9799.16 9199.41 15599.71 1398.98 2099.45 8099.78 7799.19 499.54 18899.28 2699.84 5699.63 96
VNet99.11 7198.90 8099.73 4599.52 10899.56 4999.41 15599.39 17599.01 1499.74 2899.78 7795.56 14199.92 6399.52 698.18 17499.72 69
114514_t98.93 9298.67 10599.72 4799.85 2399.53 5599.62 7099.59 3792.65 29799.71 2999.78 7798.06 7899.90 8498.84 6699.91 1599.74 58
Vis-MVSNet (Re-imp)98.87 9598.72 9999.31 10999.71 6398.88 13099.80 1999.44 15397.91 10599.36 10199.78 7795.49 14499.43 20197.91 14999.11 12499.62 99
anonymousdsp98.44 13198.28 13698.94 14898.50 28398.96 11999.77 2499.50 9797.07 17898.87 19099.77 8294.76 18399.28 22998.66 8697.60 19298.57 265
CDS-MVSNet99.09 7599.03 6399.25 12099.42 12898.73 15899.45 13599.46 13498.11 8699.46 7999.77 8298.01 7999.37 20698.70 8198.92 14299.66 85
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
MSDG98.98 8998.80 9299.53 7899.76 4199.19 8898.75 28999.55 5397.25 16199.47 7799.77 8297.82 8399.87 9796.93 22499.90 2299.54 111
CHOSEN 280x42099.12 6799.13 5199.08 13299.66 8297.89 20398.43 30499.71 1398.88 3199.62 5399.76 8596.63 11499.70 16399.46 1399.99 199.66 85
PS-MVSNAJss98.92 9398.92 7798.90 16298.78 25898.53 17699.78 2299.54 6198.07 9399.00 17599.76 8599.01 1199.37 20699.13 3897.23 21698.81 184
Regformer-199.53 999.47 899.72 4799.71 6399.44 6799.49 12299.46 13498.95 2599.83 1199.76 8599.01 1199.93 5599.17 3599.87 3799.80 39
Regformer-299.54 799.47 899.75 3899.71 6399.52 5899.49 12299.49 10298.94 2699.83 1199.76 8599.01 1199.94 4099.15 3799.87 3799.80 39
MVS_Test99.10 7498.97 7199.48 8799.49 11699.14 9499.67 5199.34 20197.31 15699.58 6099.76 8597.65 8899.82 12098.87 6099.07 12999.46 132
mPP-MVS99.44 2599.30 3399.86 1299.88 1199.79 1699.69 4499.48 11198.12 8499.50 7299.75 9098.78 3699.97 1098.57 9899.89 3099.83 23
HPM-MVS_fast99.51 1299.40 1499.85 1799.91 199.79 1699.76 2799.56 4697.72 12399.76 2699.75 9099.13 699.92 6399.07 4399.92 999.85 8
HyFIR lowres test99.11 7198.92 7799.65 5699.90 399.37 7399.02 25499.91 397.67 12899.59 5999.75 9095.90 13399.73 14799.53 599.02 13299.86 5
ITE_SJBPF98.08 24499.29 15896.37 25598.92 27498.34 6698.83 19799.75 9091.09 26599.62 18095.82 25397.40 21098.25 280
XVS99.53 999.42 1199.87 699.85 2399.83 799.69 4499.68 1998.98 2099.37 9799.74 9498.81 3399.94 4098.79 7299.86 4799.84 12
MP-MVScopyleft99.33 4199.15 5099.87 699.88 1199.82 1099.66 5499.46 13498.09 8999.48 7699.74 9498.29 7099.96 1897.93 14899.87 3799.82 30
MVS_111021_LR99.41 3299.33 2599.65 5699.77 3899.51 6098.94 27699.85 698.82 3699.65 4899.74 9498.51 5699.80 12798.83 6899.89 3099.64 93
VPNet97.84 19097.44 20899.01 13999.21 17198.94 12399.48 12799.57 4398.38 6499.28 11999.73 9788.89 28599.39 20299.19 3293.27 28698.71 200
MVSTER98.49 12898.32 13399.00 14199.35 14399.02 10699.54 10399.38 18197.41 14999.20 14099.73 9793.86 22099.36 21098.87 6097.56 19698.62 249
MVS_111021_HR99.41 3299.32 2699.66 5399.72 6199.47 6498.95 27499.85 698.82 3699.54 6699.73 9798.51 5699.74 13998.91 5599.88 3399.77 49
PHI-MVS99.30 4499.17 4999.70 4999.56 10599.52 5899.58 8299.80 897.12 17399.62 5399.73 9798.58 5599.90 8498.61 9399.91 1599.68 81
semantic-postprocess98.06 24599.57 10296.36 25699.49 10297.18 16798.71 20799.72 10192.70 24399.14 25197.44 19495.86 24098.67 225
MVS_dtu98.77 11498.60 11999.30 11298.95 22498.47 18699.08 23899.27 23399.26 398.94 18199.71 10293.54 22699.96 1898.86 6399.79 7199.45 136
XVG-OURS-SEG-HR98.69 12098.62 11398.89 16499.71 6397.74 20899.12 22899.54 6198.44 6299.42 8699.71 10294.20 20699.92 6398.54 10598.90 14499.00 173
EPNet_dtu98.03 16897.96 15698.23 23598.27 28895.54 27199.23 20998.75 28899.02 1197.82 26199.71 10296.11 12799.48 19093.04 29299.65 9799.69 77
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CNVR-MVS99.42 2999.30 3399.78 3399.62 9199.71 2699.26 20599.52 7598.82 3699.39 9399.71 10298.96 2099.85 10398.59 9599.80 6799.77 49
v7n97.87 18797.52 19698.92 15698.76 26298.58 17399.84 999.46 13496.20 23798.91 18599.70 10694.89 17199.44 19896.03 25093.89 28198.75 193
testdata99.54 7499.75 4798.95 12099.51 8497.07 17899.43 8499.70 10698.87 2899.94 4097.76 16299.64 9899.72 69
IterMVS97.83 19197.77 17698.02 24899.58 10096.27 25999.02 25499.48 11197.22 16598.71 20799.70 10692.75 23799.13 25497.46 19296.00 23898.67 225
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
PCF-MVS97.08 1497.66 21897.06 23599.47 9099.61 9599.09 9998.04 31599.25 23791.24 30498.51 23199.70 10694.55 19399.91 7292.76 29499.85 5199.42 140
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
LTVRE_ROB97.16 1298.02 17097.90 16098.40 21799.23 16896.80 24399.70 4299.60 3497.12 17398.18 24799.70 10691.73 25999.72 15198.39 11497.45 20698.68 214
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
HFP-MVS99.49 1399.37 1799.86 1299.87 1599.80 1299.66 5499.67 2298.15 8099.68 3499.69 11199.06 899.96 1898.69 8399.87 3799.84 12
#test#99.43 2799.29 3699.86 1299.87 1599.80 1299.55 10099.67 2297.83 11299.68 3499.69 11199.06 899.96 1898.39 11499.87 3799.84 12
旧先验199.74 5399.59 4699.54 6199.69 11198.47 5899.68 9399.73 63
ACMMPR99.49 1399.36 1999.86 1299.87 1599.79 1699.66 5499.67 2298.15 8099.67 4099.69 11198.95 2399.96 1898.69 8399.87 3799.84 12
CPTT-MVS99.11 7198.90 8099.74 4399.80 3299.46 6599.59 7999.49 10297.03 18299.63 5099.69 11197.27 9799.96 1897.82 15699.84 5699.81 34
MVS_test032698.79 11198.62 11399.28 11899.00 21098.41 18999.01 25899.09 25499.23 598.67 21699.68 11694.31 20399.95 3398.74 7599.89 3099.46 132
region2R99.48 1799.35 2299.87 699.88 1199.80 1299.65 6499.66 2598.13 8299.66 4599.68 11698.96 2099.96 1898.62 9199.87 3799.84 12
PS-CasMVS97.93 18097.59 19398.95 14798.99 21299.06 10299.68 4999.52 7597.13 17198.31 24399.68 11692.44 25499.05 26298.51 10694.08 27798.75 193
HY-MVS97.30 798.85 10498.64 10999.47 9099.42 12899.08 10099.62 7099.36 18997.39 15199.28 11999.68 11696.44 11799.92 6398.37 11798.22 17299.40 142
DP-MVS Recon99.12 6798.95 7599.65 5699.74 5399.70 2899.27 19799.57 4396.40 22499.42 8699.68 11698.75 4499.80 12797.98 14499.72 8399.44 137
ADS-MVSNet298.02 17098.07 14997.87 25899.33 14795.19 27999.23 20999.08 25596.24 23499.10 15499.67 12194.11 21198.93 27896.81 22899.05 13099.48 125
ADS-MVSNet98.20 14698.08 14798.56 20099.33 14796.48 25299.23 20999.15 24796.24 23499.10 15499.67 12194.11 21199.71 15796.81 22899.05 13099.48 125
diffmvs98.72 11898.49 12499.43 9999.48 11999.19 8899.62 7099.42 16295.58 25799.37 9799.67 12196.14 12699.74 13998.14 13198.96 13799.37 144
DTE-MVSNet97.51 22797.19 23298.46 21098.63 27698.13 19899.84 999.48 11196.68 19997.97 25799.67 12192.92 23398.56 28596.88 22792.60 29498.70 204
Baseline_NR-MVSNet97.76 20197.45 20598.68 19199.09 19798.29 19199.41 15598.85 28395.65 25698.63 22599.67 12194.82 17599.10 25998.07 14092.89 29098.64 241
CMPMVSbinary69.68 2394.13 28394.90 27591.84 30397.24 30380.01 32398.52 30199.48 11189.01 31191.99 30999.67 12185.67 30799.13 25495.44 26197.03 22196.39 311
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
原ACMM199.65 5699.73 5899.33 7599.47 12597.46 14299.12 14999.66 12798.67 5199.91 7297.70 17199.69 9099.71 76
test22299.75 4799.49 6198.91 27999.49 10296.42 22199.34 10799.65 12898.28 7199.69 9099.72 69
112199.09 7598.87 8499.75 3899.74 5399.60 4499.27 19799.48 11196.82 19399.25 12799.65 12898.38 6599.93 5597.53 18499.67 9499.73 63
MVSFormer99.17 5899.12 5399.29 11699.51 11098.94 12399.88 199.46 13497.55 13699.80 1699.65 12897.39 9299.28 22999.03 4599.85 5199.65 88
jason99.13 6299.03 6399.45 9399.46 12198.87 13199.12 22899.26 23598.03 10199.79 1899.65 12897.02 10299.85 10399.02 4799.90 2299.65 88
jason: jason.
BH-RMVSNet98.41 13498.08 14799.40 10199.41 13198.83 13899.30 18698.77 28797.70 12698.94 18199.65 12892.91 23599.74 13996.52 24199.55 10299.64 93
sss99.17 5899.05 5899.53 7899.62 9198.97 11599.36 17399.62 3197.83 11299.67 4099.65 12897.37 9599.95 3399.19 3299.19 12099.68 81
新几何199.75 3899.75 4799.59 4699.54 6196.76 19499.29 11599.64 13498.43 6199.94 4096.92 22599.66 9599.72 69
PEN-MVS97.76 20197.44 20898.72 19098.77 26198.54 17599.78 2299.51 8497.06 18098.29 24599.64 13492.63 24598.89 27998.09 13493.16 28798.72 198
CP-MVSNet98.09 15797.78 17299.01 13998.97 21999.24 8699.67 5199.46 13497.25 16198.48 23499.64 13493.79 22199.06 26198.63 8994.10 27698.74 196
LF4IMVS97.52 22497.46 20497.70 27098.98 21695.55 26999.29 19098.82 28698.07 9398.66 21799.64 13489.97 27699.61 18197.01 21696.68 22397.94 290
HPM-MVS99.42 2999.28 3899.83 2299.90 399.72 2599.81 1599.54 6197.59 13199.68 3499.63 13898.91 2699.94 4098.58 9699.91 1599.84 12
NCCC99.34 4099.19 4799.79 3299.61 9599.65 3799.30 18699.48 11198.86 3299.21 13799.63 13898.72 4799.90 8498.25 12599.63 10099.80 39
CP-MVS99.45 2299.32 2699.85 1799.83 2899.75 2199.69 4499.52 7598.07 9399.53 6799.63 13898.93 2599.97 1098.74 7599.91 1599.83 23
AdaColmapbinary99.01 8798.80 9299.66 5399.56 10599.54 5299.18 21999.70 1598.18 7999.35 10499.63 13896.32 12199.90 8497.48 18999.77 7499.55 109
TAPA-MVS97.07 1597.74 20697.34 22198.94 14899.70 6897.53 21199.25 20699.51 8491.90 30199.30 11199.63 13898.78 3699.64 17488.09 30899.87 3799.65 88
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
MCST-MVS99.43 2799.30 3399.82 2499.79 3399.74 2499.29 19099.40 17298.79 4099.52 6999.62 14398.91 2699.90 8498.64 8899.75 7799.82 30
WTY-MVS99.06 7998.88 8399.61 6599.62 9199.16 9199.37 16999.56 4698.04 9999.53 6799.62 14396.84 10699.94 4098.85 6598.49 16599.72 69
MDTV_nov1_ep1398.32 13399.11 19294.44 28899.27 19798.74 29197.51 14099.40 9299.62 14394.78 17899.76 13797.59 17798.81 151
MVS_030599.24 5299.13 5199.57 7099.44 12699.12 9699.29 19099.55 5398.93 2899.52 6999.61 14696.36 12099.97 1099.57 299.92 999.63 96
HQP_MVS98.27 14298.22 13998.44 21499.29 15896.97 23599.39 16299.47 12598.97 2399.11 15199.61 14692.71 24199.69 16697.78 15997.63 18998.67 225
plane_prior499.61 146
Patchmatch-test198.16 14998.14 14198.22 23799.30 15595.55 26999.07 23998.97 26897.57 13499.43 8499.60 14992.72 24099.60 18297.38 19799.20 11999.50 122
TranMVSNet+NR-MVSNet97.93 18097.66 18798.76 18898.78 25898.62 16999.65 6499.49 10297.76 11898.49 23399.60 14994.23 20598.97 27798.00 14392.90 28998.70 204
tpmrst98.33 13898.48 12597.90 25799.16 18494.78 28499.31 18499.11 25197.27 15999.45 8099.59 15195.33 14699.84 10898.48 10898.61 15599.09 162
IterMVS-LS98.46 13098.42 12798.58 19799.59 9998.00 20099.37 16999.43 16196.94 18799.07 15999.59 15197.87 8199.03 26598.32 12395.62 24498.71 200
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
F-COLMAP99.19 5599.04 6199.64 6199.78 3499.27 8399.42 15199.54 6197.29 15899.41 8899.59 15198.42 6499.93 5598.19 12799.69 9099.73 63
pmmvs498.13 15197.90 16098.81 18298.61 27798.87 13198.99 26199.21 24196.44 21999.06 16399.58 15495.90 13399.11 25797.18 20896.11 23698.46 273
1112_ss98.98 8998.77 9599.59 6799.68 7199.02 10699.25 20699.48 11197.23 16499.13 14799.58 15496.93 10599.90 8498.87 6098.78 15299.84 12
ab-mvs-re8.30 31211.06 3130.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 33499.58 1540.00 3410.00 3360.00 3330.00 3340.00 332
PatchmatchNetpermissive98.31 13998.36 12998.19 24099.16 18495.32 27699.27 19798.92 27497.37 15299.37 9799.58 15494.90 17099.70 16397.43 19599.21 11899.54 111
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
Patchmatch-test97.93 18097.65 18898.77 18799.18 17797.07 22699.03 25199.14 24996.16 24198.74 20499.57 15894.56 19299.72 15193.36 29199.11 12499.52 116
PVSNet96.02 1798.85 10498.84 8898.89 16499.73 5897.28 21498.32 30899.60 3497.86 10799.50 7299.57 15896.75 11199.86 10098.56 10199.70 8999.54 111
cdsmvs_eth3d_5k24.64 31132.85 3120.00 3240.00 3370.00 3380.00 32999.51 840.00 3330.00 33499.56 16096.58 1150.00 3360.00 3330.00 3340.00 332
131498.68 12198.54 12399.11 13198.89 24198.65 16599.27 19799.49 10296.89 18997.99 25699.56 16097.72 8799.83 11597.74 16599.27 11698.84 183
lupinMVS99.13 6299.01 6799.46 9299.51 11098.94 12399.05 24599.16 24697.86 10799.80 1699.56 16097.39 9299.86 10098.94 5399.85 5199.58 107
CDPH-MVS99.13 6298.91 7999.80 2999.75 4799.71 2699.15 22499.41 16596.60 20699.60 5699.55 16398.83 3199.90 8497.48 18999.83 6099.78 47
dp97.75 20497.80 16997.59 27199.10 19593.71 29699.32 18198.88 28196.48 21799.08 15899.55 16392.67 24499.82 12096.52 24198.58 15899.24 152
CLD-MVS98.16 14998.10 14498.33 22199.29 15896.82 24298.75 28999.44 15397.83 11299.13 14799.55 16392.92 23399.67 16898.32 12397.69 18898.48 270
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
MVS97.28 23796.55 24499.48 8798.78 25898.95 12099.27 19799.39 17583.53 31798.08 25199.54 16696.97 10399.87 9794.23 28599.16 12199.63 96
pmmvs597.52 22497.30 22698.16 24298.57 28096.73 24499.27 19798.90 27996.14 24498.37 23999.53 16791.54 26299.14 25197.51 18695.87 23998.63 247
v74897.52 22497.23 23098.41 21698.69 27097.23 21999.87 499.45 14595.72 25498.51 23199.53 16794.13 21099.30 22696.78 23092.39 29598.70 204
HPM-MVS++99.39 3699.23 4599.87 699.75 4799.84 699.43 14499.51 8498.68 4799.27 12399.53 16798.64 5299.96 1898.44 11399.80 6799.79 43
PatchMatch-RL98.84 10698.62 11399.52 8299.71 6399.28 8199.06 24399.77 997.74 12199.50 7299.53 16795.41 14599.84 10897.17 20999.64 9899.44 137
test_prior399.21 5499.05 5899.68 5099.67 7299.48 6298.96 27099.56 4698.34 6699.01 16899.52 17198.68 4999.83 11597.96 14599.74 7999.74 58
test_prior298.96 27098.34 6699.01 16899.52 17198.68 4997.96 14599.74 79
test_040296.64 24696.24 24797.85 26098.85 24996.43 25499.44 13999.26 23593.52 28996.98 27599.52 17188.52 29299.20 24992.58 29697.50 20197.93 291
v14897.79 19997.55 19498.50 20498.74 26397.72 21099.54 10399.33 20996.26 23298.90 18799.51 17494.68 18799.14 25197.83 15593.15 28898.63 247
v798.05 16597.78 17298.87 17198.99 21298.67 16299.64 6699.34 20196.31 22899.29 11599.51 17494.78 17899.27 23297.03 21595.15 25298.66 236
DU-MVS98.08 15897.79 17098.96 14598.87 24598.98 11299.41 15599.45 14597.87 10698.71 20799.50 17694.82 17599.22 24498.57 9892.87 29198.68 214
NR-MVSNet97.97 17897.61 19199.02 13898.87 24599.26 8499.47 13199.42 16297.63 13097.08 27299.50 17695.07 15899.13 25497.86 15393.59 28398.68 214
XVG-ACMP-BASELINE97.83 19197.71 18598.20 23999.11 19296.33 25799.41 15599.52 7598.06 9799.05 16499.50 17689.64 27999.73 14797.73 16697.38 21298.53 267
HSP-MVS99.41 3299.26 4399.85 1799.89 899.80 1299.67 5199.37 18898.70 4599.77 2399.49 17998.21 7399.95 3398.46 11199.77 7499.81 34
TEST999.67 7299.65 3799.05 24599.41 16596.22 23698.95 17999.49 17998.77 3999.91 72
train_agg99.02 8498.77 9599.77 3599.67 7299.65 3799.05 24599.41 16596.28 22998.95 17999.49 17998.76 4199.91 7297.63 17599.72 8399.75 53
agg_prior199.01 8798.76 9799.76 3799.67 7299.62 4098.99 26199.40 17296.26 23298.87 19099.49 17998.77 3999.91 7297.69 17299.72 8399.75 53
PVSNet_Blended99.08 7798.97 7199.42 10099.76 4198.79 15498.78 28699.91 396.74 19599.67 4099.49 17997.53 8999.88 9598.98 5099.85 5199.60 101
CNLPA99.14 6198.99 6899.59 6799.58 10099.41 7099.16 22199.44 15398.45 5999.19 14399.49 17998.08 7799.89 9297.73 16699.75 7799.48 125
test_899.67 7299.61 4299.03 25199.41 16596.28 22998.93 18399.48 18598.76 4199.91 72
agg_prior398.97 9198.71 10199.75 3899.67 7299.60 4499.04 25099.41 16595.93 25198.87 19099.48 18598.61 5399.91 7297.63 17599.72 8399.75 53
EPMVS97.82 19497.65 18898.35 22098.88 24295.98 26399.49 12294.71 32797.57 13499.26 12699.48 18592.46 25399.71 15797.87 15299.08 12899.35 145
PLCcopyleft97.94 499.02 8498.85 8799.53 7899.66 8299.01 10899.24 20899.52 7596.85 19199.27 12399.48 18598.25 7299.91 7297.76 16299.62 10199.65 88
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
xiu_mvs_v1_base_debu99.29 4699.27 4099.34 10499.63 8798.97 11599.12 22899.51 8498.86 3299.84 899.47 18998.18 7499.99 199.50 799.31 11399.08 163
xiu_mvs_v1_base99.29 4699.27 4099.34 10499.63 8798.97 11599.12 22899.51 8498.86 3299.84 899.47 18998.18 7499.99 199.50 799.31 11399.08 163
xiu_mvs_v1_base_debi99.29 4699.27 4099.34 10499.63 8798.97 11599.12 22899.51 8498.86 3299.84 899.47 18998.18 7499.99 199.50 799.31 11399.08 163
v192192097.80 19797.45 20598.84 17998.80 25298.53 17699.52 10799.34 20196.15 24399.24 12899.47 18993.98 21599.29 22895.40 26395.13 25398.69 209
v5297.79 19997.50 19998.66 19498.80 25298.62 16999.87 499.44 15395.87 25299.01 16899.46 19394.44 19999.33 21796.65 23993.96 28098.05 284
V497.80 19797.51 19898.67 19398.79 25498.63 16799.87 499.44 15395.87 25299.01 16899.46 19394.52 19599.33 21796.64 24093.97 27998.05 284
UniMVSNet_NR-MVSNet98.22 14397.97 15598.96 14598.92 23598.98 11299.48 12799.53 7197.76 11898.71 20799.46 19396.43 11899.22 24498.57 9892.87 29198.69 209
testgi97.65 21997.50 19998.13 24399.36 14296.45 25399.42 15199.48 11197.76 11897.87 25999.45 19691.09 26598.81 28194.53 27698.52 16399.13 157
tpm297.44 23297.34 22197.74 26899.15 18794.36 28999.45 13598.94 27193.45 29298.90 18799.44 19791.35 26399.59 18497.31 20098.07 17999.29 149
mvs-test198.86 9898.84 8898.89 16499.33 14797.77 20799.44 13999.30 21898.47 5799.10 15499.43 19896.78 10899.95 3398.73 7899.02 13298.96 179
WR-MVS98.06 15997.73 18399.06 13498.86 24899.25 8599.19 21899.35 19397.30 15798.66 21799.43 19893.94 21699.21 24898.58 9694.28 27298.71 200
v897.95 17997.63 19098.93 15198.95 22498.81 14799.80 1999.41 16596.03 25099.10 15499.42 20094.92 16899.30 22696.94 22394.08 27798.66 236
tpmvs97.98 17598.02 15297.84 26199.04 20594.73 28699.31 18499.20 24296.10 24998.76 20399.42 20094.94 16599.81 12496.97 22098.45 16698.97 177
UGNet98.87 9598.69 10399.40 10199.22 17098.72 15999.44 13999.68 1999.24 499.18 14599.42 20092.74 23999.96 1899.34 2199.94 799.53 115
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
Effi-MVS+98.81 10798.59 12099.48 8799.46 12199.12 9698.08 31499.50 9797.50 14199.38 9599.41 20396.37 11999.81 12499.11 4098.54 16299.51 119
v1097.85 18897.52 19698.86 17598.99 21298.67 16299.75 3499.41 16595.70 25598.98 17799.41 20394.75 18499.23 24196.01 25194.63 26798.67 225
LP97.04 24396.80 23997.77 26698.90 23895.23 27798.97 26899.06 26094.02 28298.09 25099.41 20393.88 21898.82 28090.46 30098.42 16899.26 151
tpmp4_e2397.34 23597.29 22797.52 27299.25 16793.73 29499.58 8299.19 24594.00 28398.20 24699.41 20390.74 26999.74 13997.13 21098.07 17999.07 167
v14419297.92 18397.60 19298.87 17198.83 25198.65 16599.55 10099.34 20196.20 23799.32 10999.40 20794.36 20099.26 23796.37 24695.03 25598.70 204
NP-MVS99.23 16896.92 23899.40 207
HQP-MVS98.02 17097.90 16098.37 21999.19 17496.83 24098.98 26599.39 17598.24 7298.66 21799.40 20792.47 25099.64 17497.19 20697.58 19498.64 241
MAR-MVS98.86 9898.63 11099.54 7499.37 14099.66 3499.45 13599.54 6196.61 20499.01 16899.40 20797.09 10099.86 10097.68 17499.53 10399.10 158
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
API-MVS99.04 8199.03 6399.06 13499.40 13599.31 7999.55 10099.56 4698.54 5399.33 10899.39 21198.76 4199.78 13296.98 21999.78 7298.07 283
CR-MVSNet98.17 14897.93 15998.87 17199.18 17798.49 18299.22 21399.33 20996.96 18599.56 6399.38 21294.33 20199.00 26894.83 27298.58 15899.14 155
Patchmtry97.75 20497.40 21498.81 18299.10 19598.87 13199.11 23499.33 20994.83 26498.81 19899.38 21294.33 20199.02 26696.10 24895.57 24598.53 267
BH-untuned98.42 13398.36 12998.59 19699.49 11696.70 24599.27 19799.13 25097.24 16398.80 19999.38 21295.75 13899.74 13997.07 21499.16 12199.33 147
v1neww98.12 15397.84 16698.93 15198.97 21998.81 14799.66 5499.35 19396.49 21199.29 11599.37 21595.02 16099.32 22097.73 16694.73 26098.67 225
v7new98.12 15397.84 16698.93 15198.97 21998.81 14799.66 5499.35 19396.49 21199.29 11599.37 21595.02 16099.32 22097.73 16694.73 26098.67 225
divwei89l23v2f11298.06 15997.78 17298.91 15898.90 23898.77 15799.57 8899.35 19396.45 21899.24 12899.37 21594.92 16899.27 23297.50 18794.71 26498.68 214
v698.12 15397.84 16698.94 14898.94 22898.83 13899.66 5499.34 20196.49 21199.30 11199.37 21594.95 16499.34 21697.77 16194.74 25998.67 225
V4298.06 15997.79 17098.86 17598.98 21698.84 13599.69 4499.34 20196.53 21099.30 11199.37 21594.67 18899.32 22097.57 18094.66 26598.42 274
VPA-MVSNet98.29 14097.95 15799.30 11299.16 18499.54 5299.50 11699.58 4298.27 7199.35 10499.37 21592.53 24899.65 17299.35 1794.46 26998.72 198
PVSNet_BlendedMVS98.86 9898.80 9299.03 13799.76 4198.79 15499.28 19499.91 397.42 14899.67 4099.37 21597.53 8999.88 9598.98 5097.29 21598.42 274
MVP-Stereo97.81 19597.75 18297.99 25197.53 29796.60 24998.96 27098.85 28397.22 16597.23 26999.36 22295.28 14899.46 19295.51 26099.78 7297.92 292
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
v114198.05 16597.76 17998.91 15898.91 23798.78 15699.57 8899.35 19396.41 22399.23 13399.36 22294.93 16799.27 23297.38 19794.72 26298.68 214
v124097.69 21297.32 22498.79 18598.85 24998.43 18799.48 12799.36 18996.11 24699.27 12399.36 22293.76 22399.24 24094.46 27895.23 24998.70 204
v198.05 16597.76 17998.93 15198.92 23598.80 15299.57 8899.35 19396.39 22599.28 11999.36 22294.86 17399.32 22097.38 19794.72 26298.68 214
v114497.98 17597.69 18698.85 17898.87 24598.66 16499.54 10399.35 19396.27 23199.23 13399.35 22694.67 18899.23 24196.73 23295.16 25198.68 214
v2v48298.06 15997.77 17698.92 15698.90 23898.82 14599.57 8899.36 18996.65 20199.19 14399.35 22694.20 20699.25 23897.72 17094.97 25698.69 209
CostFormer97.72 20997.73 18397.71 26999.15 18794.02 29299.54 10399.02 26494.67 26799.04 16599.35 22692.35 25599.77 13498.50 10797.94 18399.34 146
Fast-Effi-MVS+-dtu98.77 11498.83 9198.60 19599.41 13196.99 23399.52 10799.49 10298.11 8699.24 12899.34 22996.96 10499.79 13097.95 14799.45 10499.02 172
Fast-Effi-MVS+98.70 11998.43 12699.51 8499.51 11099.28 8199.52 10799.47 12596.11 24699.01 16899.34 22996.20 12599.84 10897.88 15198.82 14999.39 143
v119297.81 19597.44 20898.91 15898.88 24298.68 16199.51 11199.34 20196.18 23999.20 14099.34 22994.03 21499.36 21095.32 26595.18 25098.69 209
tpm97.67 21797.55 19498.03 24699.02 20895.01 28299.43 14498.54 30396.44 21999.12 14999.34 22991.83 25899.60 18297.75 16496.46 22999.48 125
PAPM97.59 22097.09 23499.07 13399.06 20198.26 19398.30 30999.10 25294.88 26398.08 25199.34 22996.27 12399.64 17489.87 30298.92 14299.31 148
GBi-Net97.68 21497.48 20198.29 22599.51 11097.26 21699.43 14499.48 11196.49 21199.07 15999.32 23490.26 27298.98 27097.10 21196.65 22498.62 249
test197.68 21497.48 20198.29 22599.51 11097.26 21699.43 14499.48 11196.49 21199.07 15999.32 23490.26 27298.98 27097.10 21196.65 22498.62 249
FMVSNet196.84 24596.36 24698.29 22599.32 15397.26 21699.43 14499.48 11195.11 26198.55 23099.32 23483.95 31498.98 27095.81 25496.26 23498.62 249
MS-PatchMatch97.24 23997.32 22496.99 28098.45 28593.51 29998.82 28499.32 21597.41 14998.13 24999.30 23788.99 28499.56 18595.68 25799.80 6797.90 293
GA-MVS97.85 18897.47 20399.00 14199.38 13897.99 20198.57 29999.15 24797.04 18198.90 18799.30 23789.83 27799.38 20396.70 23498.33 17099.62 99
FMVSNet297.72 20997.36 21698.80 18499.51 11098.84 13599.45 13599.42 16296.49 21198.86 19599.29 23990.26 27298.98 27096.44 24396.56 22798.58 264
TESTMET0.1,197.55 22197.27 22998.40 21798.93 23396.53 25098.67 29397.61 32096.96 18598.64 22499.28 24088.63 29199.45 19397.30 20199.38 10899.21 153
FMVSNet398.03 16897.76 17998.84 17999.39 13798.98 11299.40 16199.38 18196.67 20099.07 15999.28 24092.93 23298.98 27097.10 21196.65 22498.56 266
PAPM_NR99.04 8198.84 8899.66 5399.74 5399.44 6799.39 16299.38 18197.70 12699.28 11999.28 24098.34 6899.85 10396.96 22199.45 10499.69 77
xiu_mvs_v2_base99.26 5199.25 4499.29 11699.53 10798.91 12899.02 25499.45 14598.80 3999.71 2999.26 24398.94 2499.98 599.34 2199.23 11798.98 176
test20.0396.12 26595.96 25496.63 28797.44 29895.45 27499.51 11199.38 18196.55 20996.16 28299.25 24493.76 22396.17 31587.35 31194.22 27498.27 279
PS-MVSNAJ99.32 4299.32 2699.30 11299.57 10298.94 12398.97 26899.46 13498.92 2999.71 2999.24 24599.01 1199.98 599.35 1799.66 9598.97 177
Test_1112_low_res98.89 9498.66 10899.57 7099.69 7098.95 12099.03 25199.47 12596.98 18499.15 14699.23 24696.77 11099.89 9298.83 6898.78 15299.86 5
EG-PatchMatch MVS95.97 26795.69 26196.81 28597.78 29492.79 30299.16 22198.93 27296.16 24194.08 29499.22 24782.72 31699.47 19195.67 25897.50 20198.17 281
TR-MVS97.76 20197.41 21398.82 18199.06 20197.87 20498.87 28298.56 30296.63 20398.68 21599.22 24792.49 24999.65 17295.40 26397.79 18698.95 180
WR-MVS_H98.13 15197.87 16598.90 16299.02 20898.84 13599.70 4299.59 3797.27 15998.40 23799.19 24995.53 14299.23 24198.34 12093.78 28298.61 258
MIMVSNet195.51 27195.04 27496.92 28397.38 29995.60 26799.52 10799.50 9793.65 28796.97 27699.17 25085.28 30996.56 31488.36 30795.55 24698.60 260
gm-plane-assit98.54 28292.96 30194.65 26899.15 25199.64 17497.56 181
MIMVSNet97.73 20797.45 20598.57 19899.45 12597.50 21299.02 25498.98 26796.11 24699.41 8899.14 25290.28 27198.74 28295.74 25598.93 14099.47 129
LCM-MVSNet-Re97.83 19198.15 14096.87 28499.30 15592.25 30599.59 7998.26 30797.43 14696.20 28199.13 25396.27 12398.73 28398.17 12998.99 13499.64 93
UniMVSNet (Re)98.29 14098.00 15399.13 13099.00 21099.36 7499.49 12299.51 8497.95 10498.97 17899.13 25396.30 12299.38 20398.36 11993.34 28598.66 236
N_pmnet94.95 27895.83 25692.31 30298.47 28479.33 32499.12 22892.81 33393.87 28597.68 26499.13 25393.87 21999.01 26791.38 29896.19 23598.59 261
PAPR98.63 12698.34 13199.51 8499.40 13599.03 10598.80 28599.36 18996.33 22699.00 17599.12 25698.46 5999.84 10895.23 26699.37 11299.66 85
tpm cat197.39 23497.36 21697.50 27499.17 18293.73 29499.43 14499.31 21691.27 30398.71 20799.08 25794.31 20399.77 13496.41 24598.50 16499.00 173
FMVSNet596.43 25196.19 24897.15 27799.11 19295.89 26599.32 18199.52 7594.47 27698.34 24299.07 25887.54 30097.07 31092.61 29595.72 24298.47 271
PMMVS98.80 11098.62 11399.34 10499.27 16398.70 16098.76 28899.31 21697.34 15399.21 13799.07 25897.20 9899.82 12098.56 10198.87 14699.52 116
Anonymous2023120696.22 26296.03 25196.79 28697.31 30294.14 29199.63 6799.08 25596.17 24097.04 27399.06 26093.94 21697.76 30686.96 31295.06 25498.47 271
DeepMVS_CXcopyleft93.34 29799.29 15882.27 32199.22 24085.15 31596.33 28099.05 26190.97 26799.73 14793.57 28997.77 18798.01 287
YYNet195.36 27494.51 27997.92 25597.89 29297.10 22299.10 23699.23 23993.26 29380.77 32199.04 26292.81 23698.02 29894.30 28294.18 27598.64 241
MDA-MVSNet-bldmvs94.96 27793.98 28297.92 25598.24 28997.27 21599.15 22499.33 20993.80 28680.09 32399.03 26388.31 29597.86 30393.49 29094.36 27198.62 249
BH-w/o98.00 17497.89 16498.32 22299.35 14396.20 26199.01 25898.90 27996.42 22198.38 23899.00 26495.26 15099.72 15196.06 24998.61 15599.03 170
Effi-MVS+-dtu98.78 11298.89 8298.47 20999.33 14796.91 23999.57 8899.30 21898.47 5799.41 8898.99 26596.78 10899.74 13998.73 7899.38 10898.74 196
testpf95.66 27096.02 25394.58 29498.35 28792.32 30497.25 32197.91 31592.83 29597.03 27498.99 26588.69 28898.61 28495.72 25697.40 21092.80 318
UnsupCasMVSNet_eth96.44 25096.12 24997.40 27698.65 27495.65 26699.36 17399.51 8497.13 17196.04 28598.99 26588.40 29498.17 28896.71 23390.27 29998.40 276
test0.0.03 197.71 21197.42 21298.56 20098.41 28697.82 20598.78 28698.63 29897.34 15398.05 25598.98 26894.45 19798.98 27095.04 26997.15 22098.89 181
MDA-MVSNet_test_wron95.45 27294.60 27798.01 24998.16 29097.21 22099.11 23499.24 23893.49 29080.73 32298.98 26893.02 23098.18 28794.22 28694.45 27098.64 241
FPMVS84.93 29685.65 29682.75 31686.77 32763.39 33398.35 30798.92 27474.11 32283.39 31998.98 26850.85 32992.40 32684.54 31694.97 25692.46 319
alignmvs98.81 10798.56 12299.58 6999.43 12799.42 6999.51 11198.96 27098.61 5099.35 10498.92 27194.78 17899.77 13499.35 1798.11 17899.54 111
test-LLR98.06 15997.90 16098.55 20298.79 25497.10 22298.67 29397.75 31697.34 15398.61 22898.85 27294.45 19799.45 19397.25 20299.38 10899.10 158
test-mter97.49 23097.13 23398.55 20298.79 25497.10 22298.67 29397.75 31696.65 20198.61 22898.85 27288.23 29699.45 19397.25 20299.38 10899.10 158
DI_MVS_plusplus_test97.45 23196.79 24099.44 9697.76 29599.04 10499.21 21598.61 30097.74 12194.01 29798.83 27487.38 30299.83 11598.63 8998.90 14499.44 137
test_normal97.44 23296.77 24299.44 9697.75 29699.00 11099.10 23698.64 29797.71 12493.93 30098.82 27587.39 30199.83 11598.61 9398.97 13699.49 123
canonicalmvs99.02 8498.86 8699.51 8499.42 12899.32 7699.80 1999.48 11198.63 4899.31 11098.81 27697.09 10099.75 13899.27 2897.90 18499.47 129
DWT-MVSNet_test97.53 22397.40 21497.93 25499.03 20794.86 28399.57 8898.63 29896.59 20898.36 24098.79 27789.32 28199.74 13998.14 13198.16 17699.20 154
new_pmnet96.38 25596.03 25197.41 27598.13 29195.16 28199.05 24599.20 24293.94 28497.39 26798.79 27791.61 26199.04 26390.43 30195.77 24198.05 284
cascas97.69 21297.43 21198.48 20798.60 27897.30 21398.18 31399.39 17592.96 29498.41 23698.78 27993.77 22299.27 23298.16 13098.61 15598.86 182
PVSNet_094.43 1996.09 26695.47 26897.94 25399.31 15494.34 29097.81 31699.70 1597.12 17397.46 26598.75 28089.71 27899.79 13097.69 17281.69 32099.68 81
patchmatchnet-post98.70 28194.79 17799.74 139
Patchmatch-RL test95.84 26895.81 25795.95 29195.61 30790.57 30898.24 31098.39 30495.10 26295.20 28798.67 28294.78 17897.77 30596.28 24790.02 30099.51 119
DSMNet-mixed97.25 23897.35 21896.95 28297.84 29393.61 29899.57 8896.63 32396.13 24598.87 19098.61 28394.59 19197.70 30795.08 26898.86 14799.55 109
PatchFormer-LS_test98.01 17398.05 15097.87 25899.15 18794.76 28599.42 15198.93 27297.12 17398.84 19698.59 28493.74 22599.80 12798.55 10398.17 17599.06 168
testus94.61 27995.30 27292.54 30196.44 30584.18 31698.36 30599.03 26394.18 28196.49 27898.57 28588.74 28695.09 31987.41 31098.45 16698.36 278
IB-MVS95.67 1896.22 26295.44 27098.57 19899.21 17196.70 24598.65 29697.74 31896.71 19797.27 26898.54 28686.03 30599.92 6398.47 11086.30 31699.10 158
Christian Sormann, Mattia Rossi, Andreas Kuhn and Friedrich Fraundorfer: IB-MVS: An Iterative Algorithm for Deep Multi-View Stereo based on Binary Decisions. BMVC 2021
GG-mvs-BLEND98.45 21198.55 28198.16 19699.43 14493.68 32997.23 26998.46 28789.30 28299.22 24495.43 26298.22 17297.98 288
test235694.07 28594.46 28092.89 29995.18 31086.13 31497.60 31999.06 26093.61 28896.15 28498.28 28885.60 30893.95 32186.68 31498.00 18198.59 261
OpenMVS_ROBcopyleft92.34 2094.38 28293.70 28396.41 29097.38 29993.17 30099.06 24398.75 28886.58 31494.84 29098.26 28981.53 31899.32 22089.01 30597.87 18596.76 309
pmmvs394.09 28493.25 28696.60 28894.76 31294.49 28798.92 27798.18 31189.66 30896.48 27998.06 29086.28 30497.33 30989.68 30387.20 31097.97 289
test1235691.74 29092.19 29190.37 30891.22 31982.41 31998.61 29798.28 30690.66 30791.82 31097.92 29184.90 31092.61 32381.64 31994.66 26596.09 313
test123567892.91 28893.30 28591.71 30593.14 31783.01 31898.75 28998.58 30192.80 29692.45 30797.91 29288.51 29393.54 32282.26 31895.35 24798.59 261
111192.30 28992.21 29092.55 30093.30 31586.27 31299.15 22498.74 29191.94 29990.85 31297.82 29384.18 31295.21 31779.65 32094.27 27396.19 312
.test124583.42 29786.17 29575.15 31993.30 31586.27 31299.15 22498.74 29191.94 29990.85 31297.82 29384.18 31295.21 31779.65 32039.90 33043.98 329
v1796.42 25295.81 25798.25 23298.94 22898.80 15299.76 2799.28 22894.57 27094.18 29197.71 29595.23 15298.16 28994.86 27087.73 30897.80 296
v1896.42 25295.80 25998.26 22898.95 22498.82 14599.76 2799.28 22894.58 26994.12 29297.70 29695.22 15398.16 28994.83 27287.80 30697.79 301
v1696.39 25495.76 26098.26 22898.96 22298.81 14799.76 2799.28 22894.57 27094.10 29397.70 29695.04 15998.16 28994.70 27487.77 30797.80 296
PM-MVS92.96 28792.23 28995.14 29395.61 30789.98 31099.37 16998.21 30994.80 26595.04 28997.69 29865.06 32497.90 30294.30 28289.98 30197.54 308
V1496.26 25795.60 26398.26 22898.94 22898.83 13899.76 2799.29 22194.49 27593.96 29897.66 29994.99 16398.13 29394.41 27986.90 31297.80 296
Anonymous2023121190.69 29289.39 29394.58 29494.25 31388.18 31199.29 19099.07 25882.45 31992.95 30697.65 30063.96 32697.79 30489.27 30485.63 31797.77 302
v1196.23 26195.57 26798.21 23898.93 23398.83 13899.72 3999.29 22194.29 28094.05 29597.64 30194.88 17298.04 29792.89 29388.43 30497.77 302
V996.25 25895.58 26498.26 22898.94 22898.83 13899.75 3499.29 22194.45 27793.96 29897.62 30294.94 16598.14 29294.40 28086.87 31397.81 294
v1596.28 25695.62 26298.25 23298.94 22898.83 13899.76 2799.29 22194.52 27494.02 29697.61 30395.02 16098.13 29394.53 27686.92 31197.80 296
v1396.24 25995.58 26498.25 23298.98 21698.83 13899.75 3499.29 22194.35 27993.89 30197.60 30495.17 15598.11 29594.27 28486.86 31497.81 294
v1296.24 25995.58 26498.23 23598.96 22298.81 14799.76 2799.29 22194.42 27893.85 30297.60 30495.12 15698.09 29694.32 28186.85 31597.80 296
Test495.05 27693.67 28499.22 12496.07 30698.94 12399.20 21799.27 23397.71 12489.96 31597.59 30666.18 32399.25 23898.06 14198.96 13799.47 129
pmmvs-eth3d95.34 27594.73 27697.15 27795.53 30995.94 26499.35 17799.10 25295.13 26093.55 30397.54 30788.15 29897.91 30194.58 27589.69 30297.61 305
ambc93.06 29892.68 31882.36 32098.47 30398.73 29595.09 28897.41 30855.55 32899.10 25996.42 24491.32 29797.71 304
RPMNet96.61 24795.85 25598.87 17199.18 17798.49 18299.22 21399.08 25588.72 31399.56 6397.38 30994.08 21399.00 26886.87 31398.58 15899.14 155
new-patchmatchnet94.48 28094.08 28195.67 29295.08 31192.41 30399.18 21999.28 22894.55 27393.49 30497.37 31087.86 29997.01 31191.57 29788.36 30597.61 305
PatchT97.03 24496.44 24598.79 18598.99 21298.34 19099.16 22199.07 25892.13 29899.52 6997.31 31194.54 19498.98 27088.54 30698.73 15499.03 170
testing_294.44 28192.93 28798.98 14394.16 31499.00 11099.42 15199.28 22896.60 20684.86 31796.84 31270.91 32099.27 23298.23 12696.08 23798.68 214
UnsupCasMVSNet_bld93.53 28692.51 28896.58 28997.38 29993.82 29398.24 31099.48 11191.10 30593.10 30596.66 31374.89 31998.37 28694.03 28887.71 30997.56 307
LCM-MVSNet86.80 29585.22 29891.53 30687.81 32580.96 32298.23 31298.99 26671.05 32390.13 31496.51 31448.45 33196.88 31290.51 29985.30 31896.76 309
testmv87.91 29387.80 29488.24 30987.68 32677.50 32699.07 23997.66 31989.27 30986.47 31696.22 31568.35 32292.49 32576.63 32488.82 30394.72 316
PMMVS286.87 29485.37 29791.35 30790.21 32283.80 31798.89 28097.45 32183.13 31891.67 31195.03 31648.49 33094.70 32085.86 31577.62 32195.54 314
Gipumacopyleft90.99 29190.15 29293.51 29698.73 26490.12 30993.98 32599.45 14579.32 32092.28 30894.91 31769.61 32197.98 30087.42 30995.67 24392.45 320
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
JIA-IIPM97.50 22897.02 23698.93 15198.73 26497.80 20699.30 18698.97 26891.73 30298.91 18594.86 31895.10 15799.71 15797.58 17897.98 18299.28 150
PMVScopyleft70.75 2275.98 30574.97 30479.01 31870.98 33355.18 33493.37 32698.21 30965.08 32961.78 33093.83 31921.74 33992.53 32478.59 32291.12 29889.34 324
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
MVS-HIRNet95.75 26995.16 27397.51 27399.30 15593.69 29798.88 28195.78 32485.09 31698.78 20192.65 32091.29 26499.37 20694.85 27199.85 5199.46 132
E-PMN80.61 30079.88 30182.81 31590.75 32176.38 32897.69 31795.76 32566.44 32783.52 31892.25 32162.54 32787.16 33068.53 32861.40 32484.89 327
EMVS80.02 30179.22 30282.43 31791.19 32076.40 32797.55 32092.49 33566.36 32883.01 32091.27 32264.63 32585.79 33165.82 32960.65 32585.08 326
PNet_i23d79.43 30277.68 30384.67 31286.18 32871.69 33196.50 32393.68 32975.17 32171.33 32691.18 32332.18 33590.62 32778.57 32374.34 32291.71 322
gg-mvs-nofinetune96.17 26495.32 27198.73 18998.79 25498.14 19799.38 16794.09 32891.07 30698.07 25491.04 32489.62 28099.35 21396.75 23199.09 12798.68 214
ANet_high77.30 30374.86 30584.62 31375.88 33277.61 32597.63 31893.15 33288.81 31264.27 32889.29 32536.51 33383.93 33275.89 32552.31 32792.33 321
no-one83.04 29880.12 30091.79 30489.44 32485.65 31599.32 18198.32 30589.06 31079.79 32589.16 32644.86 33296.67 31384.33 31746.78 32893.05 317
MVEpermissive76.82 2176.91 30474.31 30684.70 31185.38 33076.05 32996.88 32293.17 33167.39 32671.28 32789.01 32721.66 34087.69 32971.74 32772.29 32390.35 323
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
wuykxyi23d74.42 30671.19 30784.14 31476.16 33174.29 33096.00 32492.57 33469.57 32463.84 32987.49 32821.98 33788.86 32875.56 32657.50 32689.26 325
testmvs39.17 30943.78 30825.37 32336.04 33616.84 33798.36 30526.56 33620.06 33138.51 33267.32 32929.64 33615.30 33537.59 33139.90 33043.98 329
test12339.01 31042.50 31028.53 32239.17 33520.91 33698.75 28919.17 33819.83 33238.57 33166.67 33033.16 33415.42 33437.50 33229.66 33249.26 328
test_post65.99 33194.65 19099.73 147
test_post199.23 20965.14 33294.18 20999.71 15797.58 178
X-MVStestdata96.55 24895.45 26999.87 699.85 2399.83 799.69 4499.68 1998.98 2099.37 9764.01 33398.81 3399.94 4098.79 7299.86 4799.84 12
wuyk23d40.18 30841.29 31136.84 32086.18 32849.12 33579.73 32822.81 33727.64 33025.46 33328.45 33421.98 33748.89 33355.80 33023.56 33312.51 331
pcd_1.5k_mvsjas8.27 31311.03 3140.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 3340.27 33599.01 110.00 3360.00 3330.00 3340.00 332
pcd1.5k->3k40.85 30743.49 30932.93 32198.95 2240.00 3380.00 32999.53 710.00 3330.00 3340.27 33595.32 1470.00 3360.00 33397.30 21498.80 185
sosnet-low-res0.02 3140.03 3150.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 3340.27 3350.00 3410.00 3360.00 3330.00 3340.00 332
sosnet0.02 3140.03 3150.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 3340.27 3350.00 3410.00 3360.00 3330.00 3340.00 332
uncertanet0.02 3140.03 3150.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 3340.27 3350.00 3410.00 3360.00 3330.00 3340.00 332
Regformer0.02 3140.03 3150.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 3340.27 3350.00 3410.00 3360.00 3330.00 3340.00 332
uanet0.02 3140.03 3150.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 3340.27 3350.00 3410.00 3360.00 3330.00 3340.00 332
sam_mvs194.86 173
sam_mvs94.72 186
MTGPAbinary99.47 125
MTMP98.88 281
test9_res97.49 18899.72 8399.75 53
agg_prior297.21 20499.73 8299.75 53
agg_prior99.67 7299.62 4099.40 17298.87 19099.91 72
test_prior499.56 4998.99 261
test_prior99.68 5099.67 7299.48 6299.56 4699.83 11599.74 58
旧先验298.96 27096.70 19899.47 7799.94 4098.19 127
新几何299.01 258
无先验98.99 26199.51 8496.89 18999.93 5597.53 18499.72 69
原ACMM298.95 274
testdata299.95 3396.67 236
segment_acmp98.96 20
testdata198.85 28398.32 69
test1299.75 3899.64 8599.61 4299.29 22199.21 13798.38 6599.89 9299.74 7999.74 58
plane_prior799.29 15897.03 230
plane_prior699.27 16396.98 23492.71 241
plane_prior599.47 12599.69 16697.78 15997.63 18998.67 225
plane_prior397.00 23298.69 4699.11 151
plane_prior299.39 16298.97 23
plane_prior199.26 165
plane_prior96.97 23599.21 21598.45 5997.60 192
n20.00 339
nn0.00 339
door-mid98.05 312
test1199.35 193
door97.92 313
HQP5-MVS96.83 240
HQP-NCC99.19 17498.98 26598.24 7298.66 217
ACMP_Plane99.19 17498.98 26598.24 7298.66 217
BP-MVS97.19 206
HQP4-MVS98.66 21799.64 17498.64 241
HQP3-MVS99.39 17597.58 194
HQP2-MVS92.47 250
MDTV_nov1_ep13_2view95.18 28099.35 17796.84 19299.58 6095.19 15497.82 15699.46 132
ACMMP++_ref97.19 218
ACMMP++97.43 209
Test By Simon98.75 44