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 bysorted bysort bysort bysort by
MPTG97.07 1696.77 2397.97 1099.37 1094.42 1597.15 10598.08 4795.07 1396.11 4998.59 590.88 4799.90 196.18 2699.50 1999.58 9
MTAPA97.08 1596.78 2297.97 1099.37 1094.42 1597.24 9398.08 4795.07 1396.11 4998.59 590.88 4799.90 196.18 2699.50 1999.58 9
MP-MVScopyleft96.77 2996.45 3497.72 2399.39 793.80 3398.41 1798.06 5493.37 5395.54 7298.34 2590.59 5099.88 394.83 5899.54 1399.49 24
mPP-MVS96.86 2596.60 2797.64 3099.40 593.44 4498.50 1398.09 4693.27 5795.95 5898.33 2891.04 4399.88 395.20 4599.57 1199.60 8
region2R97.07 1696.84 1797.77 2099.46 193.79 3498.52 1098.24 2693.19 6197.14 2198.34 2591.59 3799.87 595.46 4399.59 799.64 4
MP-MVS-pluss96.70 3196.27 3897.98 999.23 2194.71 1196.96 11698.06 5490.67 12295.55 7198.78 291.07 4299.86 696.58 1499.55 1299.38 37
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
ACMMP_Plus97.20 996.86 1698.23 399.09 2495.16 697.60 6698.19 3192.82 7697.93 898.74 391.60 3699.86 696.26 1999.52 1599.67 2
ACMMPR97.07 1696.84 1797.79 1799.44 293.88 3098.52 1098.31 2193.21 5897.15 2098.33 2891.35 3999.86 695.63 3899.59 799.62 5
PGM-MVS96.81 2796.53 3097.65 2899.35 1393.53 4297.65 6098.98 192.22 8697.14 2198.44 1491.17 4199.85 994.35 6599.46 2399.57 11
CP-MVS97.02 1996.81 2097.64 3099.33 1493.54 4198.80 398.28 2392.99 6796.45 4298.30 3391.90 3199.85 995.61 4099.68 299.54 17
ACMMPcopyleft96.27 4395.93 4397.28 4499.24 1992.62 6498.25 2598.81 392.99 6794.56 8398.39 2088.96 6399.85 994.57 6497.63 9399.36 39
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
HPM-MVS++97.34 796.97 1198.47 199.08 2596.16 197.55 7097.97 7595.59 496.61 3397.89 4992.57 1799.84 1295.95 3199.51 1799.40 33
MVS_030596.22 4595.84 4597.36 3997.72 8993.01 5396.93 12397.86 8295.55 594.80 8097.78 6086.05 10199.83 1396.71 1199.16 5099.25 46
HFP-MVS97.14 1396.92 1497.83 1399.42 394.12 2498.52 1098.32 1993.21 5897.18 1898.29 3492.08 2699.83 1395.63 3899.59 799.54 17
#test#97.02 1996.75 2497.83 1399.42 394.12 2498.15 2998.32 1992.57 8197.18 1898.29 3492.08 2699.83 1395.12 4899.59 799.54 17
QAPM93.45 11392.27 13196.98 5796.77 11992.62 6498.39 1898.12 3984.50 25888.27 21997.77 6182.39 16799.81 1685.40 22198.81 6698.51 97
XVS97.18 1096.96 1297.81 1599.38 894.03 2898.59 798.20 2994.85 1696.59 3598.29 3491.70 3499.80 1795.66 3699.40 3099.62 5
X-MVStestdata91.71 16089.67 21397.81 1599.38 894.03 2898.59 798.20 2994.85 1696.59 3532.69 32991.70 3499.80 1795.66 3699.40 3099.62 5
3Dnovator91.36 595.19 6694.44 7797.44 3696.56 12793.36 4798.65 698.36 1694.12 3689.25 20398.06 4382.20 17199.77 1993.41 8599.32 3999.18 49
CSCG96.05 4995.91 4496.46 7699.24 1990.47 12898.30 2198.57 1189.01 16593.97 9497.57 7892.62 1699.76 2094.66 6399.27 4399.15 52
OpenMVScopyleft89.19 1292.86 13391.68 14696.40 7895.34 17792.73 6198.27 2398.12 3984.86 25385.78 25197.75 6278.89 22899.74 2187.50 18698.65 7096.73 162
PVSNet_Blended_VisFu95.27 6294.91 6296.38 8098.20 7390.86 11897.27 9198.25 2590.21 13494.18 9097.27 8887.48 8599.73 2293.53 7997.77 9198.55 92
DeepC-MVS93.07 396.06 4895.66 4997.29 4397.96 8193.17 5097.30 9098.06 5493.92 4093.38 10198.66 486.83 9199.73 2295.60 4299.22 4698.96 68
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
LS3D93.57 11092.61 12196.47 7497.59 9591.61 9197.67 5797.72 9385.17 24890.29 15898.34 2584.60 11799.73 2283.85 24798.27 7798.06 123
abl_696.40 4096.21 4096.98 5798.89 3192.20 7597.89 3998.03 6393.34 5697.22 1798.42 1687.93 7799.72 2595.10 4999.07 5899.02 61
MCST-MVS97.18 1096.84 1798.20 499.30 1695.35 397.12 10798.07 5293.54 5196.08 5197.69 6593.86 599.71 2696.50 1699.39 3299.55 15
NCCC97.30 897.03 998.11 698.77 3395.06 897.34 8598.04 6195.96 297.09 2597.88 5193.18 999.71 2695.84 3499.17 4999.56 13
SteuartSystems-ACMMP97.62 397.53 297.87 1298.39 5794.25 1998.43 1698.27 2495.34 898.11 598.56 794.53 199.71 2696.57 1599.62 599.65 3
Skip Steuart: Steuart Systems R&D Blog.
3Dnovator+91.43 495.40 5894.48 7598.16 596.90 11395.34 498.48 1497.87 8094.65 2788.53 21398.02 4583.69 12599.71 2693.18 8898.96 6399.44 30
DELS-MVS96.61 3596.38 3697.30 4297.79 8793.19 4995.96 20698.18 3395.23 1095.87 5997.65 6991.45 3899.70 3095.87 3299.44 2799.00 66
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
DP-MVS92.76 13791.51 15096.52 6798.77 3390.99 11297.38 8396.08 22182.38 27689.29 20097.87 5283.77 12499.69 3181.37 26796.69 12098.89 77
PHI-MVS96.77 2996.46 3397.71 2598.40 5594.07 2698.21 2898.45 1589.86 14097.11 2498.01 4692.52 1999.69 3196.03 3099.53 1499.36 39
APDe-MVS97.82 197.73 198.08 799.15 2394.82 1098.81 298.30 2294.76 2398.30 498.90 193.77 699.68 3397.93 199.69 199.75 1
CNVR-MVS97.68 297.44 598.37 298.90 3095.86 297.27 9198.08 4795.81 397.87 998.31 3194.26 299.68 3397.02 399.49 2199.57 11
新几何197.32 4198.60 4593.59 4097.75 8881.58 28395.75 6597.85 5590.04 5699.67 3586.50 20299.13 5398.69 88
testdata299.67 3585.96 213
HSP-MVS97.53 497.49 497.63 3299.40 593.77 3798.53 997.85 8495.55 598.56 397.81 5893.90 499.65 3796.62 1299.21 4799.48 26
PS-MVSNAJ95.37 5995.33 5595.49 11997.35 9990.66 12495.31 23597.48 11593.85 4296.51 3895.70 16588.65 6899.65 3794.80 6098.27 7796.17 171
无先验95.79 21497.87 8083.87 26599.65 3787.68 17998.89 77
112194.71 7993.83 8297.34 4098.57 4993.64 3996.04 20197.73 9081.56 28595.68 6697.85 5590.23 5399.65 3787.68 17999.12 5698.73 84
EPNet95.20 6594.56 7097.14 5292.80 28392.68 6297.85 4394.87 27696.64 192.46 11497.80 5986.23 9699.65 3793.72 7798.62 7199.10 58
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
MVS_dtu94.12 8993.32 10096.52 6795.99 15692.02 8096.24 19296.49 20594.28 3492.95 11097.02 9979.10 22099.64 4290.61 12897.17 10797.90 127
DeepC-MVS_fast93.89 296.93 2496.64 2697.78 1898.64 4494.30 1797.41 7998.04 6194.81 2196.59 3598.37 2191.24 4099.64 4295.16 4699.52 1599.42 32
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
Regformer-496.97 2196.87 1597.25 4698.34 6092.66 6396.96 11698.01 6695.12 1297.14 2198.42 1691.82 3299.61 4496.90 599.13 5399.50 22
Regformer-297.16 1296.99 1097.67 2798.32 6393.84 3296.83 12998.10 4495.24 997.49 1198.25 3792.57 1799.61 4496.80 799.29 4199.56 13
CHOSEN 1792x268894.15 8693.51 9296.06 9498.27 6689.38 15795.18 24198.48 1485.60 24393.76 9697.11 9683.15 13299.61 4491.33 12198.72 6999.19 48
CPTT-MVS95.57 5795.19 5896.70 6099.27 1791.48 9598.33 2098.11 4287.79 20395.17 7698.03 4487.09 8999.61 4493.51 8099.42 2899.02 61
UGNet94.04 9593.28 10396.31 8496.85 11491.19 10697.88 4097.68 9894.40 3093.00 10596.18 13873.39 26699.61 4491.72 11198.46 7498.13 118
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
MVS_test032694.10 9193.32 10096.44 7796.14 15091.94 8596.26 18797.05 16494.12 3692.25 12196.47 12779.44 21699.59 4990.37 13097.82 8897.80 134
TEST998.70 3694.19 2196.41 17098.02 6488.17 19696.03 5297.56 8092.74 1299.59 49
train_agg96.30 4295.83 4697.72 2398.70 3694.19 2196.41 17098.02 6488.58 18196.03 5297.56 8092.73 1399.59 4995.04 5099.37 3799.39 34
agg_prior396.16 4795.67 4897.62 3398.67 3893.88 3096.41 17098.00 6887.93 20095.81 6297.47 8492.33 2199.59 4995.04 5099.37 3799.39 34
test_898.67 3894.06 2796.37 17798.01 6688.58 18195.98 5797.55 8292.73 1399.58 53
EI-MVSNet-UG-set96.34 4196.30 3796.47 7498.20 7390.93 11696.86 12797.72 9394.67 2596.16 4898.46 1290.43 5199.58 5396.23 2097.96 8598.90 75
EI-MVSNet-Vis-set96.51 3796.47 3296.63 6398.24 6991.20 10596.89 12697.73 9094.74 2496.49 3998.49 1190.88 4799.58 5396.44 1798.32 7699.13 54
Regformer-197.10 1496.96 1297.54 3598.32 6393.48 4396.83 12997.99 7395.20 1197.46 1298.25 3792.48 2099.58 5396.79 999.29 4199.55 15
HPM-MVS96.69 3296.45 3497.40 3799.36 1293.11 5198.87 198.06 5491.17 11196.40 4397.99 4790.99 4499.58 5395.61 4099.61 699.49 24
APD-MVScopyleft96.95 2296.60 2798.01 899.03 2794.93 997.72 5498.10 4491.50 10098.01 698.32 3092.33 2199.58 5394.85 5799.51 1799.53 20
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
PVSNet_BlendedMVS94.06 9393.92 8094.47 15298.27 6689.46 15596.73 14198.36 1690.17 13594.36 8695.24 18388.02 7499.58 5393.44 8390.72 19894.36 262
PVSNet_Blended94.87 7694.56 7095.81 10398.27 6689.46 15595.47 22998.36 1688.84 17294.36 8696.09 14488.02 7499.58 5393.44 8398.18 7998.40 109
agg_prior196.22 4595.77 4797.56 3498.67 3893.79 3496.28 18698.00 6888.76 17895.68 6697.55 8292.70 1599.57 6195.01 5299.32 3999.32 41
agg_prior98.67 3893.79 3498.00 6895.68 6699.57 61
APD-MVS_3200maxsize96.81 2796.71 2597.12 5399.01 2892.31 7097.98 3698.06 5493.11 6497.44 1398.55 990.93 4599.55 6396.06 2899.25 4499.51 21
PCF-MVS89.48 1191.56 17289.95 20296.36 8296.60 12392.52 6792.51 28797.26 14379.41 29488.90 20596.56 12384.04 12299.55 6377.01 28797.30 10497.01 154
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
Regformer-396.85 2696.80 2197.01 5598.34 6092.02 8096.96 11697.76 8795.01 1597.08 2698.42 1691.71 3399.54 6596.80 799.13 5399.48 26
原ACMM196.38 8098.59 4691.09 11197.89 7787.41 21295.22 7597.68 6690.25 5299.54 6587.95 17299.12 5698.49 101
AdaColmapbinary94.34 8293.68 8796.31 8498.59 4691.68 9096.59 16197.81 8689.87 13992.15 12497.06 9883.62 12699.54 6589.34 14498.07 8297.70 138
xiu_mvs_v2_base95.32 6195.29 5695.40 12597.22 10190.50 12795.44 23097.44 12793.70 4796.46 4196.18 13888.59 7199.53 6894.79 6297.81 8996.17 171
VNet95.89 5395.45 5197.21 5098.07 7992.94 5797.50 7398.15 3593.87 4197.52 1097.61 7585.29 10899.53 6895.81 3595.27 14199.16 50
HPM-MVS_fast96.51 3796.27 3897.22 4999.32 1592.74 6098.74 498.06 5490.57 13196.77 2898.35 2290.21 5499.53 6894.80 6099.63 499.38 37
PLCcopyleft91.00 694.11 9093.43 9696.13 9398.58 4891.15 11096.69 15197.39 13287.29 21591.37 13696.71 10788.39 7299.52 7187.33 19097.13 10997.73 136
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
UA-Net95.95 5295.53 5097.20 5197.67 9192.98 5697.65 6098.13 3894.81 2196.61 3398.35 2288.87 6499.51 7290.36 13197.35 10399.11 57
MAR-MVS94.22 8493.46 9496.51 7198.00 8092.19 7697.67 5797.47 11888.13 19893.00 10595.84 15284.86 11599.51 7287.99 17198.17 8097.83 133
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
F-COLMAP93.58 10992.98 10795.37 12698.40 5588.98 16697.18 10297.29 14287.75 20590.49 15397.10 9785.21 10999.50 7486.70 19996.72 11997.63 139
DP-MVS Recon95.68 5595.12 6097.37 3899.19 2294.19 2197.03 11098.08 4788.35 18995.09 7797.65 6989.97 5799.48 7592.08 10398.59 7298.44 106
CDPH-MVS95.97 5195.38 5397.77 2098.93 2994.44 1496.35 17897.88 7886.98 22396.65 3297.89 4991.99 3099.47 7692.26 9499.46 2399.39 34
test1297.65 2898.46 5194.26 1897.66 9995.52 7390.89 4699.46 7799.25 4499.22 47
ab-mvs93.57 11092.55 12396.64 6197.28 10091.96 8495.40 23197.45 12489.81 14493.22 10296.28 13579.62 21499.46 7790.74 12693.11 16298.50 99
HY-MVS89.66 993.87 9992.95 10896.63 6397.10 10692.49 6895.64 22196.64 20089.05 16493.00 10595.79 15885.77 10599.45 7989.16 15194.35 15297.96 124
xiu_mvs_v1_base_debu95.01 6894.76 6495.75 10696.58 12491.71 8796.25 18997.35 13892.99 6796.70 2996.63 11882.67 15799.44 8096.22 2197.46 9696.11 176
xiu_mvs_v1_base95.01 6894.76 6495.75 10696.58 12491.71 8796.25 18997.35 13892.99 6796.70 2996.63 11882.67 15799.44 8096.22 2197.46 9696.11 176
xiu_mvs_v1_base_debi95.01 6894.76 6495.75 10696.58 12491.71 8796.25 18997.35 13892.99 6796.70 2996.63 11882.67 15799.44 8096.22 2197.46 9696.11 176
test_prior396.46 3996.20 4197.23 4798.67 3892.99 5496.35 17898.00 6892.80 7796.03 5297.59 7692.01 2899.41 8395.01 5299.38 3399.29 43
test_prior97.23 4798.67 3892.99 5498.00 6899.41 8399.29 43
TSAR-MVS + MP.97.42 597.33 697.69 2699.25 1894.24 2098.07 3497.85 8493.72 4598.57 298.35 2293.69 799.40 8597.06 299.46 2399.44 30
VDD-MVS93.82 10193.08 10596.02 9697.88 8689.96 13997.72 5495.85 23492.43 8395.86 6098.44 1468.42 28799.39 8696.31 1894.85 14598.71 87
WTY-MVS94.71 7994.02 7996.79 5997.71 9092.05 7896.59 16197.35 13890.61 12894.64 8296.93 10086.41 9599.39 8691.20 12594.71 15198.94 71
MVS_111021_HR96.68 3496.58 2996.99 5698.46 5192.31 7096.20 19498.90 294.30 3395.86 6097.74 6392.33 2199.38 8896.04 2999.42 2899.28 45
DeepPCF-MVS93.97 196.61 3597.09 795.15 12998.09 7886.63 23296.00 20598.15 3595.43 797.95 798.56 793.40 899.36 8996.77 1099.48 2299.45 28
TSAR-MVS + GP.96.69 3296.49 3197.27 4598.31 6593.39 4596.79 13696.72 19394.17 3597.44 1397.66 6892.76 1199.33 9096.86 697.76 9299.08 59
114514_t93.95 9793.06 10696.63 6399.07 2691.61 9197.46 7897.96 7677.99 30193.00 10597.57 7886.14 10099.33 9089.22 14899.15 5198.94 71
COLMAP_ROBcopyleft87.81 1590.40 21389.28 22093.79 18297.95 8287.13 22196.92 12495.89 23382.83 27386.88 24697.18 9273.77 26399.29 9278.44 28193.62 15894.95 233
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
sss94.51 8193.80 8396.64 6197.07 10791.97 8396.32 18298.06 5488.94 16994.50 8496.78 10484.60 11799.27 9391.90 10696.02 12998.68 89
MG-MVS95.61 5695.38 5396.31 8498.42 5490.53 12696.04 20197.48 11593.47 5295.67 6998.10 4089.17 6199.25 9491.27 12398.77 6799.13 54
MVS_111021_LR96.24 4496.19 4296.39 7998.23 7291.35 10096.24 19298.79 493.99 3995.80 6397.65 6989.92 5899.24 9595.87 3299.20 4898.58 91
alignmvs95.87 5495.23 5797.78 1897.56 9795.19 597.86 4197.17 14894.39 3196.47 4096.40 13185.89 10299.20 9696.21 2495.11 14398.95 70
VDDNet93.05 12592.07 13396.02 9696.84 11590.39 13098.08 3395.85 23486.22 23795.79 6498.46 1267.59 29099.19 9794.92 5694.85 14598.47 104
IB-MVS87.33 1789.91 22388.28 23394.79 14495.26 18587.70 21095.12 24293.95 29489.35 15187.03 24292.49 26270.74 27799.19 9789.18 15081.37 28497.49 148
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
canonicalmvs96.02 5095.45 5197.75 2297.59 9595.15 798.28 2297.60 10494.52 2896.27 4596.12 14187.65 8199.18 9996.20 2594.82 14798.91 74
API-MVS94.84 7794.49 7495.90 10097.90 8592.00 8297.80 4697.48 11589.19 15594.81 7996.71 10788.84 6599.17 10088.91 15798.76 6896.53 165
LFMVS93.60 10892.63 11996.52 6798.13 7791.27 10297.94 3793.39 30190.57 13196.29 4498.31 3169.00 28399.16 10194.18 6695.87 13399.12 56
AllTest90.23 21788.98 22493.98 17097.94 8386.64 22996.51 16595.54 24585.38 24485.49 25496.77 10570.28 27999.15 10280.02 27292.87 16396.15 173
TestCases93.98 17097.94 8386.64 22995.54 24585.38 24485.49 25496.77 10570.28 27999.15 10280.02 27292.87 16396.15 173
1112_ss93.37 11592.42 12996.21 9197.05 11090.99 11296.31 18396.72 19386.87 22989.83 17896.69 11186.51 9499.14 10488.12 16893.67 15698.50 99
PAPM_NR95.01 6894.59 6996.26 8998.89 3190.68 12397.24 9397.73 9091.80 9492.93 11196.62 12189.13 6299.14 10489.21 14997.78 9098.97 67
PAPR94.18 8593.42 9896.48 7397.64 9391.42 9995.55 22497.71 9688.99 16692.34 11995.82 15489.19 6099.11 10686.14 20797.38 10198.90 75
MVS91.71 16090.44 18395.51 11795.20 18991.59 9396.04 20197.45 12473.44 31387.36 23595.60 16985.42 10799.10 10785.97 21297.46 9695.83 186
Test_1112_low_res92.84 13591.84 14195.85 10297.04 11189.97 13795.53 22696.64 20085.38 24489.65 18895.18 18485.86 10399.10 10787.70 17793.58 16198.49 101
CNLPA94.28 8393.53 9196.52 6798.38 5892.55 6696.59 16196.88 18790.13 13691.91 12897.24 9085.21 10999.09 10987.64 18297.83 8797.92 126
OMC-MVS95.09 6794.70 6796.25 9098.46 5191.28 10196.43 16897.57 10792.04 8994.77 8197.96 4887.01 9099.09 10991.31 12296.77 11698.36 113
PVSNet86.66 1892.24 14991.74 14593.73 18997.77 8883.69 26392.88 28296.72 19387.91 20193.00 10594.86 19278.51 23199.05 11186.53 20097.45 10098.47 104
PatchMatch-RL92.90 13192.02 13695.56 11498.19 7590.80 12095.27 23897.18 14687.96 19991.86 13095.68 16680.44 20198.99 11284.01 24397.54 9596.89 158
MSDG91.42 17990.24 19194.96 13797.15 10588.91 16793.69 26796.32 21085.72 24286.93 24496.47 12780.24 20598.98 11380.57 26995.05 14496.98 155
MSLP-MVS++96.94 2397.06 896.59 6698.72 3591.86 8697.67 5798.49 1294.66 2697.24 1698.41 1992.31 2498.94 11496.61 1399.46 2398.96 68
Vis-MVSNetpermissive95.23 6394.81 6396.51 7197.18 10391.58 9498.26 2498.12 3994.38 3294.90 7898.15 3982.28 16898.92 11591.45 12098.58 7399.01 65
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
TAPA-MVS90.10 792.30 14691.22 15995.56 11498.33 6289.60 14796.79 13697.65 10181.83 28091.52 13397.23 9187.94 7698.91 11671.31 30198.37 7598.17 117
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
DI_MVS_plusplus_test92.01 15490.77 17395.73 10993.34 26889.78 14396.14 19696.18 21890.58 13081.80 27693.50 24574.95 25498.90 11793.51 8096.94 11298.51 97
XVG-OURS-SEG-HR93.86 10093.55 8994.81 14297.06 10988.53 17395.28 23697.45 12491.68 9794.08 9197.68 6682.41 16698.90 11793.84 7592.47 16896.98 155
mvs-test193.63 10793.69 8693.46 20596.02 15484.61 25497.24 9396.72 19393.85 4292.30 12095.76 16083.08 13898.89 11991.69 11496.54 12396.87 159
test_normal92.01 15490.75 17595.80 10493.24 27289.97 13795.93 20896.24 21590.62 12681.63 27793.45 24874.98 25398.89 11993.61 7897.04 11198.55 92
XVG-OURS93.72 10593.35 9994.80 14397.07 10788.61 17194.79 24597.46 12091.97 9293.99 9297.86 5481.74 18098.88 12192.64 9392.67 16796.92 157
testdata95.46 12398.18 7688.90 16897.66 9982.73 27497.03 2798.07 4290.06 5598.85 12289.67 13898.98 6298.64 90
lupinMVS94.99 7294.56 7096.29 8796.34 13891.21 10395.83 21296.27 21288.93 17096.22 4696.88 10286.20 9898.85 12295.27 4499.05 5998.82 82
旧先验295.94 20781.66 28197.34 1598.82 12492.26 94
EPP-MVSNet95.22 6495.04 6195.76 10597.49 9889.56 14998.67 597.00 17290.69 12194.24 8997.62 7489.79 5998.81 12593.39 8696.49 12498.92 73
131492.81 13692.03 13595.14 13095.33 18089.52 15396.04 20197.44 12787.72 20686.25 24995.33 17983.84 12398.79 12689.26 14697.05 11097.11 153
Effi-MVS+94.93 7394.45 7696.36 8296.61 12291.47 9696.41 17097.41 13191.02 11694.50 8495.92 14887.53 8498.78 12793.89 7396.81 11598.84 81
RPSCF90.75 20390.86 16990.42 27996.84 11576.29 30295.61 22396.34 20983.89 26391.38 13597.87 5276.45 24298.78 12787.16 19592.23 17196.20 170
jason94.84 7794.39 7896.18 9295.52 16990.93 11696.09 19896.52 20489.28 15296.01 5697.32 8684.70 11698.77 12995.15 4798.91 6598.85 79
jason: jason.
MVS_Test94.89 7594.62 6895.68 11096.83 11789.55 15096.70 14997.17 14891.17 11195.60 7096.11 14387.87 7898.76 13093.01 9197.17 10798.72 85
ACMM89.79 892.96 12892.50 12794.35 15796.30 14088.71 16997.58 6997.36 13791.40 10690.53 15296.65 11379.77 21198.75 13191.24 12491.64 18295.59 198
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
LPG-MVS_test92.94 12992.56 12294.10 16496.16 14788.26 17997.65 6097.46 12091.29 10790.12 16697.16 9379.05 22298.73 13292.25 9691.89 17995.31 214
LGP-MVS_train94.10 16496.16 14788.26 17997.46 12091.29 10790.12 16697.16 9379.05 22298.73 13292.25 9691.89 17995.31 214
ACMP89.59 1092.62 13992.14 13294.05 16796.40 13688.20 18597.36 8497.25 14591.52 9988.30 21796.64 11478.46 23298.72 13491.86 10991.48 18695.23 221
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
HyFIR lowres test93.66 10692.92 10995.87 10198.24 6989.88 14094.58 24898.49 1285.06 25093.78 9595.78 15982.86 15398.67 13591.77 11095.71 13799.07 60
gm-plane-assit93.22 27478.89 29884.82 25493.52 24498.64 13687.72 176
OPM-MVS93.28 11892.76 11294.82 14094.63 21490.77 12296.65 15497.18 14693.72 4591.68 13197.26 8979.33 21898.63 13792.13 10092.28 17095.07 227
Fast-Effi-MVS+93.46 11292.75 11495.59 11396.77 11990.03 13196.81 13397.13 15488.19 19491.30 14194.27 22386.21 9798.63 13787.66 18196.46 12698.12 119
ACMH87.59 1690.53 21189.42 21893.87 17996.21 14287.92 20497.24 9396.94 18188.45 18583.91 26796.27 13671.92 26898.62 13984.43 23589.43 21195.05 232
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
HQP_MVS93.78 10393.43 9694.82 14096.21 14289.99 13497.74 5097.51 11394.85 1691.34 13896.64 11481.32 18598.60 14093.02 8992.23 17195.86 182
plane_prior597.51 11398.60 14093.02 8992.23 17195.86 182
XVG-ACMP-BASELINE90.93 19790.21 19493.09 21894.31 22585.89 23795.33 23397.26 14391.06 11589.38 19695.44 17668.61 28598.60 14089.46 14391.05 19394.79 249
BH-RMVSNet92.72 13891.97 13894.97 13697.16 10487.99 19996.15 19595.60 24290.62 12691.87 12997.15 9578.41 23398.57 14383.16 25297.60 9498.36 113
LTVRE_ROB88.41 1390.99 19589.92 20394.19 16196.18 14589.55 15096.31 18397.09 15887.88 20285.67 25295.91 14978.79 22998.57 14381.50 26589.98 20694.44 260
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
diffmvs93.43 11492.75 11495.48 12196.47 13489.61 14696.09 19897.14 15285.97 24093.09 10395.35 17884.87 11498.55 14589.51 14296.26 12898.28 115
ACMH+87.92 1490.20 21889.18 22293.25 21396.48 13386.45 23396.99 11496.68 19888.83 17384.79 25896.22 13770.16 28198.53 14684.42 23688.04 22394.77 251
tpmvs89.83 22789.15 22391.89 25294.92 20280.30 28793.11 27995.46 24786.28 23588.08 22192.65 25880.44 20198.52 14781.47 26689.92 20896.84 160
PatchFormer-LS_test91.68 16691.18 16193.19 21795.24 18683.63 26495.53 22695.44 24889.82 14391.37 13692.58 26180.85 19698.52 14789.65 14090.16 20597.42 150
DWT-MVSNet_test90.76 20189.89 20493.38 20895.04 19683.70 26295.85 21194.30 28688.19 19490.46 15492.80 25673.61 26498.50 14988.16 16790.58 19997.95 125
HQP4-MVS90.14 16098.50 14995.78 189
HQP-MVS93.19 12192.74 11694.54 15195.86 15889.33 15896.65 15497.39 13293.55 4890.14 16095.87 15080.95 18998.50 14992.13 10092.10 17695.78 189
IS-MVSNet94.90 7494.52 7396.05 9597.67 9190.56 12598.44 1596.22 21693.21 5893.99 9297.74 6385.55 10698.45 15289.98 13297.86 8699.14 53
CHOSEN 280x42093.12 12292.72 11794.34 15896.71 12187.27 21590.29 30397.72 9386.61 23391.34 13895.29 18084.29 12198.41 15393.25 8798.94 6497.35 151
VPA-MVSNet93.24 11992.48 12895.51 11795.70 16592.39 6997.86 4198.66 992.30 8592.09 12695.37 17780.49 20098.40 15493.95 7085.86 23895.75 193
PMMVS92.86 13392.34 13094.42 15594.92 20286.73 22894.53 25096.38 20884.78 25594.27 8895.12 18883.13 13498.40 15491.47 11996.49 12498.12 119
CLD-MVS92.98 12792.53 12594.32 15996.12 15289.20 16395.28 23697.47 11892.66 7989.90 17395.62 16880.58 19898.40 15492.73 9292.40 16995.38 210
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
cascas91.20 18890.08 19694.58 15094.97 19889.16 16593.65 26997.59 10679.90 29389.40 19592.92 25575.36 25098.36 15792.14 9994.75 14996.23 169
BH-untuned92.94 12992.62 12093.92 17897.22 10186.16 23696.40 17496.25 21490.06 13789.79 18096.17 14083.19 13098.35 15887.19 19397.27 10597.24 152
TR-MVS91.48 17690.59 18194.16 16396.40 13687.33 21395.67 21895.34 25587.68 20791.46 13495.52 17476.77 24198.35 15882.85 25693.61 15996.79 161
TDRefinement86.53 26484.76 26991.85 25382.23 31984.25 25596.38 17695.35 25284.97 25284.09 26594.94 18965.76 29898.34 16084.60 23474.52 30892.97 279
tpmp4_e2389.58 22888.59 22992.54 23395.16 19081.53 27694.11 26095.09 26681.66 28188.60 21193.44 24975.11 25198.33 16182.45 26191.72 18197.75 135
Effi-MVS+-dtu93.08 12393.21 10492.68 23196.02 15483.25 26697.14 10696.72 19393.85 4291.20 14793.44 24983.08 13898.30 16291.69 11495.73 13696.50 167
tpmrst91.44 17891.32 15391.79 25695.15 19179.20 29693.42 27295.37 25188.55 18393.49 9993.67 23982.49 16398.27 16390.41 12989.34 21297.90 127
XXY-MVS92.16 15191.23 15894.95 13894.75 21090.94 11597.47 7797.43 12989.14 16288.90 20596.43 13079.71 21298.24 16489.56 14187.68 22695.67 197
nrg03094.05 9493.31 10296.27 8895.22 18794.59 1298.34 1997.46 12092.93 7491.21 14696.64 11487.23 8898.22 16594.99 5585.80 23995.98 180
VPNet92.23 15091.31 15494.99 13495.56 16890.96 11497.22 9897.86 8292.96 7390.96 14896.62 12175.06 25298.20 16691.90 10683.65 27195.80 188
CostFormer91.18 19190.70 17792.62 23294.84 20681.76 27594.09 26194.43 28084.15 26092.72 11393.77 23679.43 21798.20 16690.70 12792.18 17497.90 127
USDC88.94 23487.83 23692.27 23694.66 21284.96 24993.86 26495.90 22887.34 21483.40 26995.56 17167.43 29198.19 16882.64 26089.67 21093.66 272
PS-MVSNAJss93.74 10493.51 9294.44 15393.91 25189.28 16197.75 4997.56 11092.50 8289.94 17296.54 12488.65 6898.18 16993.83 7690.90 19595.86 182
tpm cat188.36 25187.21 25091.81 25595.13 19280.55 28492.58 28695.70 23874.97 30987.45 23191.96 27278.01 23698.17 17080.39 27188.74 21896.72 163
PAPM91.52 17590.30 18795.20 12895.30 18189.83 14193.38 27396.85 18986.26 23688.59 21295.80 15584.88 11398.15 17175.67 29095.93 13297.63 139
PatchmatchNetpermissive91.91 15791.35 15193.59 19795.38 17584.11 25893.15 27895.39 24989.54 14692.10 12593.68 23882.82 15598.13 17284.81 22795.32 14098.52 95
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
TinyColmap86.82 26385.35 26591.21 26694.91 20482.99 26793.94 26394.02 29383.58 26781.56 27894.68 20062.34 30498.13 17275.78 28987.35 23292.52 286
dp88.90 23688.26 23490.81 27294.58 21776.62 30192.85 28394.93 27385.12 24990.07 17193.07 25375.81 24598.12 17480.53 27087.42 23097.71 137
jajsoiax92.42 14291.89 14094.03 16893.33 27088.50 17497.73 5297.53 11192.00 9188.85 20796.50 12675.62 24998.11 17593.88 7491.56 18595.48 199
patchmatchnet-post90.45 28082.65 16098.10 176
v7n90.76 20189.86 20593.45 20693.54 26187.60 21297.70 5697.37 13588.85 17187.65 22994.08 22981.08 18798.10 17684.68 23083.79 27094.66 254
mvs_tets92.31 14591.76 14293.94 17793.41 26688.29 17797.63 6497.53 11192.04 8988.76 20896.45 12974.62 25698.09 17893.91 7291.48 18695.45 203
Fast-Effi-MVS+-dtu92.29 14791.99 13793.21 21695.27 18285.52 24397.03 11096.63 20292.09 8889.11 20495.14 18680.33 20498.08 17987.54 18594.74 15096.03 179
test_post17.58 33281.76 17998.08 179
Test489.48 22987.50 23995.44 12490.76 29789.72 14495.78 21697.09 15890.28 13377.67 30291.74 27655.42 31598.08 17991.92 10596.83 11498.52 95
MDTV_nov1_ep1390.76 17495.22 18780.33 28693.03 28195.28 25688.14 19792.84 11293.83 23481.34 18498.08 17982.86 25594.34 153
v691.69 16591.00 16493.75 18694.14 23388.12 19297.20 9996.98 17389.19 15589.90 17394.42 21183.04 14298.07 18389.07 15285.10 24895.07 227
v5290.70 20790.00 20092.82 22393.24 27287.03 22297.60 6697.14 15288.21 19287.69 22793.94 23180.91 19298.07 18387.39 18783.87 26993.36 278
test-LLR91.42 17991.19 16092.12 24694.59 21580.66 28194.29 25592.98 30391.11 11390.76 15092.37 26479.02 22498.07 18388.81 16196.74 11797.63 139
test-mter90.19 21989.54 21692.12 24694.59 21580.66 28194.29 25592.98 30387.68 20790.76 15092.37 26467.67 28998.07 18388.81 16196.74 11797.63 139
BH-w/o92.14 15391.75 14393.31 21196.99 11285.73 23995.67 21895.69 23988.73 17989.26 20294.82 19582.97 14898.07 18385.26 22396.32 12796.13 175
v1neww91.70 16391.01 16293.75 18694.19 22888.14 19097.20 9996.98 17389.18 15789.87 17694.44 20983.10 13698.06 18889.06 15385.09 24995.06 230
v7new91.70 16391.01 16293.75 18694.19 22888.14 19097.20 9996.98 17389.18 15789.87 17694.44 20983.10 13698.06 18889.06 15385.09 24995.06 230
V490.71 20690.00 20092.82 22393.21 27587.03 22297.59 6897.16 15188.21 19287.69 22793.92 23380.93 19198.06 18887.39 18783.90 26893.39 276
v191.61 16790.89 16593.78 18394.01 24688.21 18496.96 11696.96 17789.17 15989.78 18194.29 21982.97 14898.05 19188.85 15984.99 25595.08 225
V4291.58 17190.87 16893.73 18994.05 24588.50 17497.32 8896.97 17688.80 17789.71 18494.33 21682.54 16198.05 19189.01 15585.07 25194.64 255
EI-MVSNet93.03 12692.88 11093.48 20395.77 16386.98 22496.44 16697.12 15590.66 12491.30 14197.64 7286.56 9398.05 19189.91 13390.55 20095.41 204
MVSTER93.20 12092.81 11194.37 15696.56 12789.59 14897.06 10997.12 15591.24 11091.30 14195.96 14682.02 17498.05 19193.48 8290.55 20095.47 201
v114191.61 16790.89 16593.78 18394.01 24688.24 18196.96 11696.96 17789.17 15989.75 18294.29 21982.99 14698.03 19588.85 15985.00 25495.07 227
divwei89l23v2f11291.61 16790.89 16593.78 18394.01 24688.22 18396.96 11696.96 17789.17 15989.75 18294.28 22183.02 14498.03 19588.86 15884.98 25695.08 225
UniMVSNet (Re)93.31 11792.55 12395.61 11295.39 17493.34 4897.39 8198.71 593.14 6390.10 16894.83 19487.71 7998.03 19591.67 11683.99 26495.46 202
v2v48291.59 17090.85 17093.80 18193.87 25388.17 18796.94 12296.88 18789.54 14689.53 19294.90 19181.70 18198.02 19889.25 14785.04 25395.20 222
v74890.34 21489.54 21692.75 22893.25 27185.71 24097.61 6597.17 14888.54 18487.20 23893.54 24381.02 18898.01 19985.73 21781.80 28094.52 257
v891.29 18690.53 18293.57 20094.15 23288.12 19297.34 8597.06 16388.99 16688.32 21694.26 22583.08 13898.01 19987.62 18383.92 26794.57 256
v791.47 17790.73 17693.68 19494.13 23488.16 18897.09 10897.05 16488.38 18789.80 17994.52 20482.21 17098.01 19988.00 17085.42 24294.87 239
v14419291.06 19390.28 18893.39 20793.66 25987.23 21896.83 12997.07 16187.43 21189.69 18694.28 22181.48 18298.00 20287.18 19484.92 25794.93 237
v114491.37 18290.60 18093.68 19493.89 25288.23 18296.84 12897.03 17088.37 18889.69 18694.39 21282.04 17397.98 20387.80 17585.37 24394.84 241
v124090.70 20789.85 20693.23 21493.51 26386.80 22796.61 15997.02 17187.16 21789.58 18994.31 21879.55 21597.98 20385.52 21985.44 24194.90 238
OurMVSNet-221017-090.51 21290.19 19591.44 26493.41 26681.25 27896.98 11596.28 21191.68 9786.55 24796.30 13474.20 25997.98 20388.96 15687.40 23195.09 224
v192192090.85 19990.03 19993.29 21293.55 26086.96 22696.74 14097.04 16887.36 21389.52 19394.34 21580.23 20697.97 20686.27 20485.21 24694.94 235
v119291.07 19290.23 19293.58 19993.70 25787.82 20796.73 14197.07 16187.77 20489.58 18994.32 21780.90 19597.97 20686.52 20185.48 24094.95 233
v1091.04 19490.23 19293.49 20294.12 23688.16 18897.32 8897.08 16088.26 19188.29 21894.22 22682.17 17297.97 20686.45 20384.12 26394.33 263
PVSNet_082.17 1985.46 27383.64 27490.92 27095.27 18279.49 29390.55 30295.60 24283.76 26683.00 27089.95 28171.09 27497.97 20682.75 25860.79 32095.31 214
GA-MVS91.38 18190.31 18694.59 14694.65 21387.62 21194.34 25396.19 21790.73 12090.35 15793.83 23471.84 26997.96 21087.22 19293.61 15998.21 116
ITE_SJBPF92.43 23595.34 17785.37 24595.92 22691.47 10187.75 22696.39 13271.00 27597.96 21082.36 26289.86 20993.97 269
FIs94.09 9293.70 8595.27 12795.70 16592.03 7998.10 3198.68 793.36 5590.39 15696.70 10987.63 8297.94 21292.25 9690.50 20295.84 185
testing_287.33 25985.03 26694.22 16087.77 30989.32 16094.97 24397.11 15789.22 15471.64 31188.73 29755.16 31697.94 21291.95 10488.73 21995.41 204
tpm289.96 22289.21 22192.23 24094.91 20481.25 27893.78 26594.42 28180.62 29191.56 13293.44 24976.44 24397.94 21285.60 21892.08 17897.49 148
TAMVS94.01 9693.46 9495.64 11196.16 14790.45 12996.71 14696.89 18689.27 15393.46 10096.92 10187.29 8797.94 21288.70 16395.74 13598.53 94
MVSFormer95.37 5995.16 5995.99 9896.34 13891.21 10398.22 2697.57 10791.42 10496.22 4697.32 8686.20 9897.92 21694.07 6799.05 5998.85 79
test_djsdf93.07 12492.76 11294.00 16993.49 26488.70 17098.22 2697.57 10791.42 10490.08 17095.55 17282.85 15497.92 21694.07 6791.58 18495.40 208
JIA-IIPM88.26 25287.04 25391.91 25193.52 26281.42 27789.38 30994.38 28280.84 28990.93 14980.74 31579.22 21997.92 21682.76 25791.62 18396.38 168
Vis-MVSNet (Re-imp)94.15 8693.88 8194.95 13897.61 9487.92 20498.10 3195.80 23792.22 8693.02 10497.45 8584.53 11997.91 21988.24 16697.97 8499.02 61
CDS-MVSNet94.14 8893.54 9095.93 9996.18 14591.46 9796.33 18197.04 16888.97 16893.56 9796.51 12587.55 8397.89 22089.80 13595.95 13198.44 106
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
anonymousdsp92.16 15191.55 14893.97 17292.58 28789.55 15097.51 7297.42 13089.42 15088.40 21494.84 19380.66 19797.88 22191.87 10891.28 19094.48 258
FC-MVSNet-test93.94 9893.57 8895.04 13295.48 17191.45 9898.12 3098.71 593.37 5390.23 15996.70 10987.66 8097.85 22291.49 11890.39 20395.83 186
ADS-MVSNet89.89 22488.68 22893.53 20195.86 15884.89 25190.93 29995.07 26783.23 27191.28 14491.81 27479.01 22697.85 22279.52 27491.39 18897.84 131
UniMVSNet_NR-MVSNet93.37 11592.67 11895.47 12295.34 17792.83 5897.17 10398.58 1092.98 7290.13 16495.80 15588.37 7397.85 22291.71 11283.93 26595.73 195
DU-MVS92.90 13192.04 13495.49 11994.95 20092.83 5897.16 10498.24 2693.02 6690.13 16495.71 16383.47 12797.85 22291.71 11283.93 26595.78 189
v14890.99 19590.38 18592.81 22693.83 25485.80 23896.78 13896.68 19889.45 14988.75 20993.93 23282.96 15097.82 22687.83 17483.25 27394.80 247
MS-PatchMatch90.27 21589.77 20991.78 25794.33 22484.72 25395.55 22496.73 19286.17 23886.36 24895.28 18271.28 27397.80 22784.09 24098.14 8192.81 283
WR-MVS92.34 14391.53 14994.77 14595.13 19290.83 11996.40 17497.98 7491.88 9389.29 20095.54 17382.50 16297.80 22789.79 13685.27 24595.69 196
pm-mvs190.72 20589.65 21593.96 17394.29 22689.63 14597.79 4796.82 19089.07 16386.12 25095.48 17578.61 23097.78 22986.97 19781.67 28294.46 259
EPMVS90.70 20789.81 20893.37 20994.73 21184.21 25693.67 26888.02 32089.50 14892.38 11793.49 24677.82 23897.78 22986.03 21192.68 16698.11 122
NR-MVSNet92.34 14391.27 15695.53 11694.95 20093.05 5297.39 8198.07 5292.65 8084.46 25995.71 16385.00 11297.77 23189.71 13783.52 27295.78 189
MVP-Stereo90.74 20490.08 19692.71 22993.19 27788.20 18595.86 21096.27 21286.07 23984.86 25794.76 19777.84 23797.75 23283.88 24698.01 8392.17 300
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
mvs_anonymous93.82 10193.74 8494.06 16696.44 13585.41 24495.81 21397.05 16489.85 14290.09 16996.36 13387.44 8697.75 23293.97 6996.69 12099.02 61
EG-PatchMatch MVS87.02 26285.44 26391.76 25992.67 28585.00 24896.08 20096.45 20683.41 27079.52 29893.49 24657.10 31197.72 23479.34 27890.87 19692.56 285
SixPastTwentyTwo89.15 23388.54 23190.98 26893.49 26480.28 28896.70 14994.70 27790.78 11884.15 26495.57 17071.78 27097.71 23584.63 23185.07 25194.94 235
test_post192.81 28416.58 33380.53 19997.68 23686.20 206
pmmvs687.81 25686.19 25892.69 23091.32 29486.30 23497.34 8596.41 20780.59 29284.05 26694.37 21467.37 29297.67 23784.75 22879.51 29094.09 268
TESTMET0.1,190.06 22189.42 21891.97 25094.41 22280.62 28394.29 25591.97 31087.28 21690.44 15592.47 26368.79 28497.67 23788.50 16596.60 12297.61 143
LF4IMVS87.94 25487.25 24689.98 28392.38 28980.05 29194.38 25295.25 25987.59 20984.34 26094.74 19964.31 30097.66 23984.83 22687.45 22892.23 298
IterMVS-LS92.29 14791.94 13993.34 21096.25 14186.97 22596.57 16497.05 16490.67 12289.50 19494.80 19686.59 9297.64 24089.91 13386.11 23795.40 208
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
OpenMVS_ROBcopyleft81.14 2084.42 27682.28 27790.83 27190.06 29984.05 25995.73 21794.04 29273.89 31280.17 29791.53 27859.15 30897.64 24066.92 30789.05 21490.80 307
CMPMVSbinary62.92 2185.62 27284.92 26787.74 29089.14 30473.12 30894.17 25896.80 19173.98 31173.65 30794.93 19066.36 29497.61 24283.95 24591.28 19092.48 289
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
TranMVSNet+NR-MVSNet92.50 14091.63 14795.14 13094.76 20992.07 7797.53 7198.11 4292.90 7589.56 19196.12 14183.16 13197.60 24389.30 14583.20 27595.75 193
WR-MVS_H92.00 15691.35 15193.95 17495.09 19489.47 15498.04 3598.68 791.46 10288.34 21594.68 20085.86 10397.56 24485.77 21584.24 26294.82 245
lessismore_v090.45 27891.96 29279.09 29787.19 32380.32 29494.39 21266.31 29597.55 24584.00 24476.84 29594.70 252
gg-mvs-nofinetune87.82 25585.61 26294.44 15394.46 21989.27 16291.21 29884.61 32680.88 28889.89 17574.98 31871.50 27197.53 24685.75 21697.21 10696.51 166
CP-MVSNet91.89 15891.24 15793.82 18095.05 19588.57 17297.82 4598.19 3191.70 9688.21 22095.76 16081.96 17597.52 24787.86 17384.65 25995.37 211
Patchmatch-test89.42 23187.99 23593.70 19295.27 18285.11 24688.98 31094.37 28381.11 28687.10 24193.69 23782.28 16897.50 24874.37 29294.76 14898.48 103
PS-CasMVS91.55 17390.84 17293.69 19394.96 19988.28 17897.84 4498.24 2691.46 10288.04 22295.80 15579.67 21397.48 24987.02 19684.54 26095.31 214
FMVSNet391.78 15990.69 17895.03 13396.53 12992.27 7297.02 11296.93 18289.79 14589.35 19794.65 20277.01 24097.47 25086.12 20888.82 21595.35 212
pmmvs490.93 19789.85 20694.17 16293.34 26890.79 12194.60 24796.02 22284.62 25687.45 23195.15 18581.88 17897.45 25187.70 17787.87 22594.27 266
Baseline_NR-MVSNet91.20 18890.62 17992.95 22293.83 25488.03 19897.01 11395.12 26588.42 18689.70 18595.13 18783.47 12797.44 25289.66 13983.24 27493.37 277
tpm90.25 21689.74 21291.76 25993.92 25079.73 29293.98 26293.54 30088.28 19091.99 12793.25 25277.51 23997.44 25287.30 19187.94 22498.12 119
FMVSNet291.31 18590.08 19694.99 13496.51 13092.21 7397.41 7996.95 18088.82 17488.62 21094.75 19873.87 26097.42 25485.20 22488.55 22195.35 212
Patchmatch-test191.54 17490.85 17093.59 19795.59 16784.95 25094.72 24695.58 24490.82 11792.25 12193.58 24275.80 24697.41 25583.35 24995.98 13098.40 109
SD-MVS97.41 697.53 297.06 5498.57 4994.46 1397.92 3898.14 3794.82 2099.01 198.55 994.18 397.41 25596.94 499.64 399.32 41
MVS-HIRNet82.47 28381.21 28486.26 29695.38 17569.21 31588.96 31189.49 31966.28 31780.79 28274.08 32068.48 28697.39 25771.93 29995.47 13892.18 299
EPNet_dtu91.71 16091.28 15592.99 22193.76 25683.71 26196.69 15195.28 25693.15 6287.02 24395.95 14783.37 12997.38 25879.46 27696.84 11397.88 130
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
pmmvs589.86 22688.87 22692.82 22392.86 28186.23 23596.26 18795.39 24984.24 25987.12 23994.51 20574.27 25897.36 25987.61 18487.57 22794.86 240
PEN-MVS91.20 18890.44 18393.48 20394.49 21887.91 20697.76 4898.18 3391.29 10787.78 22595.74 16280.35 20397.33 26085.46 22082.96 27695.19 223
TransMVSNet (Re)88.94 23487.56 23793.08 21994.35 22388.45 17697.73 5295.23 26087.47 21084.26 26295.29 18079.86 21097.33 26079.44 27774.44 31093.45 275
GBi-Net91.35 18390.27 18994.59 14696.51 13091.18 10797.50 7396.93 18288.82 17489.35 19794.51 20573.87 26097.29 26286.12 20888.82 21595.31 214
test191.35 18390.27 18994.59 14696.51 13091.18 10797.50 7396.93 18288.82 17489.35 19794.51 20573.87 26097.29 26286.12 20888.82 21595.31 214
FMVSNet189.88 22588.31 23294.59 14695.41 17391.18 10797.50 7396.93 18286.62 23287.41 23394.51 20565.94 29797.29 26283.04 25487.43 22995.31 214
test_040286.46 26584.79 26891.45 26395.02 19785.55 24296.29 18594.89 27480.90 28782.21 27193.97 23068.21 28897.29 26262.98 31188.68 22091.51 304
CR-MVSNet90.82 20089.77 20993.95 17494.45 22087.19 21990.23 30495.68 24086.89 22892.40 11592.36 26780.91 19297.05 26681.09 26893.95 15497.60 144
RPMNet88.52 24486.72 25693.95 17494.45 22087.19 21990.23 30494.99 27077.87 30392.40 11587.55 30880.17 20797.05 26668.84 30593.95 15497.60 144
LCM-MVSNet-Re92.50 14092.52 12692.44 23496.82 11881.89 27496.92 12493.71 29692.41 8484.30 26194.60 20385.08 11197.03 26891.51 11797.36 10298.40 109
Patchmtry88.64 24287.25 24692.78 22794.09 24086.64 22989.82 30795.68 24080.81 29087.63 23092.36 26780.91 19297.03 26878.86 27985.12 24794.67 253
PatchT88.87 23787.42 24293.22 21594.08 24285.10 24789.51 30894.64 27881.92 27992.36 11888.15 30380.05 20897.01 27072.43 29793.65 15797.54 147
DTE-MVSNet90.56 21089.75 21193.01 22093.95 24987.25 21697.64 6397.65 10190.74 11987.12 23995.68 16679.97 20997.00 27183.33 25181.66 28394.78 250
GG-mvs-BLEND93.62 19693.69 25889.20 16392.39 29083.33 32787.98 22489.84 28371.00 27596.87 27282.08 26495.40 13994.80 247
ambc86.56 29583.60 31670.00 31485.69 31794.97 27180.60 28788.45 29937.42 32496.84 27382.69 25975.44 29992.86 280
K. test v387.64 25786.75 25590.32 28093.02 28079.48 29496.61 15992.08 30990.66 12480.25 29694.09 22867.21 29396.65 27485.96 21380.83 28794.83 243
semantic-postprocess91.82 25495.52 16984.20 25796.15 21990.61 12887.39 23494.27 22375.63 24896.44 27587.34 18986.88 23494.82 245
N_pmnet78.73 28878.71 28778.79 30692.80 28346.50 33294.14 25943.71 33578.61 29980.83 28091.66 27774.94 25596.36 27667.24 30684.45 26193.50 273
UnsupCasMVSNet_bld82.13 28479.46 28690.14 28288.00 30782.47 26990.89 30196.62 20378.94 29775.61 30484.40 31356.63 31296.31 27777.30 28666.77 31991.63 303
IterMVS90.15 22089.67 21391.61 26195.48 17183.72 26094.33 25496.12 22089.99 13887.31 23794.15 22775.78 24796.27 27886.97 19786.89 23394.83 243
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
v1888.71 23987.52 23892.27 23694.16 23188.11 19496.82 13295.96 22387.03 21980.76 28389.81 28483.15 13296.22 27984.69 22975.31 30192.49 287
v1788.67 24187.47 24192.26 23894.13 23488.09 19696.81 13395.95 22487.02 22080.72 28489.75 28683.11 13596.20 28084.61 23275.15 30392.49 287
v1688.69 24087.50 23992.26 23894.19 22888.11 19496.81 13395.95 22487.01 22180.71 28589.80 28583.08 13896.20 28084.61 23275.34 30092.48 289
v1588.53 24387.31 24392.20 24194.09 24088.05 19796.72 14495.90 22887.01 22180.53 28889.60 29083.02 14496.13 28284.29 23774.64 30492.41 293
V988.49 24787.26 24592.18 24294.12 23687.97 20296.73 14195.90 22886.95 22580.40 29189.61 28882.98 14796.13 28284.14 23974.55 30792.44 291
v1388.45 24987.22 24992.16 24594.08 24287.95 20396.71 14695.90 22886.86 23080.27 29589.55 29282.92 15196.12 28484.02 24274.63 30592.40 294
V1488.52 24487.30 24492.17 24394.12 23687.99 19996.72 14495.91 22786.98 22380.50 28989.63 28783.03 14396.12 28484.23 23874.60 30692.40 294
v1288.46 24887.23 24892.17 24394.10 23987.99 19996.71 14695.90 22886.91 22680.34 29389.58 29182.92 15196.11 28684.09 24074.50 30992.42 292
v1188.41 25087.19 25292.08 24894.08 24287.77 20896.75 13995.85 23486.74 23180.50 28989.50 29382.49 16396.08 28783.55 24875.20 30292.38 296
ADS-MVSNet289.45 23088.59 22992.03 24995.86 15882.26 27290.93 29994.32 28583.23 27191.28 14491.81 27479.01 22695.99 28879.52 27491.39 18897.84 131
LP84.13 27781.85 28290.97 26993.20 27682.12 27387.68 31494.27 28876.80 30481.93 27488.52 29872.97 26795.95 28959.53 31681.73 28194.84 241
MDA-MVSNet-bldmvs85.00 27482.95 27691.17 26793.13 27983.33 26594.56 24995.00 26984.57 25765.13 31792.65 25870.45 27895.85 29073.57 29577.49 29394.33 263
PM-MVS83.48 27881.86 28188.31 28787.83 30877.59 30093.43 27191.75 31186.91 22680.63 28689.91 28244.42 32295.84 29185.17 22576.73 29691.50 305
MIMVSNet88.50 24686.76 25493.72 19194.84 20687.77 20891.39 29494.05 29186.41 23487.99 22392.59 26063.27 30195.82 29277.44 28392.84 16597.57 146
pmmvs-eth3d86.22 26784.45 27091.53 26288.34 30687.25 21694.47 25195.01 26883.47 26979.51 29989.61 28869.75 28295.71 29383.13 25376.73 29691.64 302
Anonymous2023120687.09 26186.14 25989.93 28491.22 29580.35 28596.11 19795.35 25283.57 26884.16 26393.02 25473.54 26595.61 29472.16 29886.14 23693.84 271
Patchmatch-RL test87.38 25886.24 25790.81 27288.74 30578.40 29988.12 31393.17 30287.11 21882.17 27289.29 29481.95 17695.60 29588.64 16477.02 29498.41 108
CVMVSNet91.23 18791.75 14389.67 28595.77 16374.69 30496.44 16694.88 27585.81 24192.18 12397.64 7279.07 22195.58 29688.06 16995.86 13498.74 83
MDA-MVSNet_test_wron85.87 27084.23 27290.80 27492.38 28982.57 26893.17 27695.15 26382.15 27767.65 31392.33 27078.20 23495.51 29777.33 28479.74 28894.31 265
YYNet185.87 27084.23 27290.78 27592.38 28982.46 27093.17 27695.14 26482.12 27867.69 31292.36 26778.16 23595.50 29877.31 28579.73 28994.39 261
UnsupCasMVSNet_eth85.99 26984.45 27090.62 27689.97 30082.40 27193.62 27097.37 13589.86 14078.59 30192.37 26465.25 29995.35 29982.27 26370.75 31394.10 267
Anonymous2023121178.22 29075.30 29186.99 29486.14 31274.16 30695.62 22293.88 29566.43 31674.44 30687.86 30541.39 32395.11 30062.49 31269.46 31691.71 301
EU-MVSNet88.72 23888.90 22588.20 28893.15 27874.21 30596.63 15894.22 28985.18 24787.32 23695.97 14576.16 24494.98 30185.27 22286.17 23595.41 204
new_pmnet82.89 28081.12 28588.18 28989.63 30280.18 28991.77 29392.57 30776.79 30575.56 30588.23 30261.22 30694.48 30271.43 30082.92 27789.87 309
testgi87.97 25387.21 25090.24 28192.86 28180.76 28096.67 15394.97 27191.74 9585.52 25395.83 15362.66 30394.47 30376.25 28888.36 22295.48 199
FMVSNet587.29 26085.79 26191.78 25794.80 20887.28 21495.49 22895.28 25684.09 26183.85 26891.82 27362.95 30294.17 30478.48 28085.34 24493.91 270
DSMNet-mixed86.34 26686.12 26087.00 29389.88 30170.43 31094.93 24490.08 31777.97 30285.42 25692.78 25774.44 25793.96 30574.43 29195.14 14296.62 164
new-patchmatchnet83.18 27981.87 28087.11 29286.88 31175.99 30393.70 26695.18 26285.02 25177.30 30388.40 30065.99 29693.88 30674.19 29470.18 31491.47 306
pmmvs379.97 28677.50 29087.39 29182.80 31779.38 29592.70 28590.75 31570.69 31578.66 30087.47 30951.34 31993.40 30773.39 29669.65 31589.38 310
MIMVSNet184.93 27583.05 27590.56 27789.56 30384.84 25295.40 23195.35 25283.91 26280.38 29292.21 27157.23 31093.34 30870.69 30482.75 27993.50 273
test0.0.03 189.37 23288.70 22791.41 26592.47 28885.63 24195.22 24092.70 30691.11 11386.91 24593.65 24079.02 22493.19 30978.00 28289.18 21395.41 204
test20.0386.14 26885.40 26488.35 28690.12 29880.06 29095.90 20995.20 26188.59 18081.29 27993.62 24171.43 27292.65 31071.26 30281.17 28592.34 297
111178.29 28977.55 28980.50 30283.89 31459.98 32491.89 29193.71 29675.06 30773.60 30887.67 30655.66 31392.60 31158.54 31877.92 29288.93 311
.test124565.38 29869.22 29653.86 31883.89 31459.98 32491.89 29193.71 29675.06 30773.60 30887.67 30655.66 31392.60 31158.54 3182.96 3319.00 329
testus82.63 28282.15 27884.07 29887.31 31067.67 31693.18 27494.29 28782.47 27582.14 27390.69 27953.01 31791.94 31366.30 30889.96 20792.62 284
no-one68.12 29663.78 29981.13 30174.01 32470.22 31387.61 31590.71 31672.63 31453.13 32271.89 32130.29 32791.45 31461.53 31532.21 32581.72 317
testpf80.97 28581.40 28379.65 30491.53 29372.43 30973.47 32589.55 31878.63 29880.81 28189.06 29561.36 30591.36 31583.34 25084.89 25875.15 320
test235682.77 28182.14 27984.65 29785.77 31370.36 31191.22 29793.69 29981.58 28381.82 27589.00 29660.63 30790.77 31664.74 30990.80 19792.82 281
test123567879.82 28778.53 28883.69 29982.55 31867.55 31792.50 28894.13 29079.28 29572.10 31086.45 31157.27 30990.68 31761.60 31480.90 28692.82 281
test1235674.97 29174.13 29277.49 30778.81 32056.23 32888.53 31292.75 30575.14 30667.50 31485.07 31244.88 32189.96 31858.71 31775.75 29886.26 312
LCM-MVSNet72.55 29269.39 29582.03 30070.81 32965.42 32090.12 30694.36 28455.02 32165.88 31681.72 31424.16 33389.96 31874.32 29368.10 31790.71 308
Gipumacopyleft67.86 29765.41 29875.18 31092.66 28673.45 30766.50 32794.52 27953.33 32257.80 32166.07 32430.81 32689.20 32048.15 32578.88 29162.90 324
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
testmv72.22 29370.02 29378.82 30573.06 32761.75 32291.24 29692.31 30874.45 31061.06 31980.51 31634.21 32588.63 32155.31 32168.07 31886.06 313
PMMVS270.19 29566.92 29780.01 30376.35 32165.67 31986.22 31687.58 32264.83 31962.38 31880.29 31726.78 33188.49 32263.79 31054.07 32185.88 314
PMVScopyleft53.92 2258.58 30155.40 30268.12 31451.00 33348.64 33078.86 32387.10 32446.77 32535.84 32974.28 3198.76 33586.34 32342.07 32673.91 31169.38 322
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
FPMVS71.27 29469.85 29475.50 30974.64 32259.03 32691.30 29591.50 31258.80 32057.92 32088.28 30129.98 32985.53 32453.43 32282.84 27881.95 316
wuykxyi23d56.92 30251.11 30674.38 31262.30 33161.47 32380.09 32284.87 32549.62 32430.80 33057.20 3287.03 33682.94 32555.69 32032.36 32478.72 319
ANet_high63.94 29959.58 30077.02 30861.24 33266.06 31885.66 31887.93 32178.53 30042.94 32471.04 32225.42 33280.71 32652.60 32330.83 32784.28 315
DeepMVS_CXcopyleft74.68 31190.84 29664.34 32181.61 33065.34 31867.47 31588.01 30448.60 32080.13 32762.33 31373.68 31279.58 318
PNet_i23d59.01 30055.87 30168.44 31373.98 32551.37 32981.36 32182.41 32852.37 32342.49 32670.39 32311.39 33479.99 32849.77 32438.71 32373.97 321
E-PMN53.28 30352.56 30455.43 31674.43 32347.13 33183.63 32076.30 33142.23 32642.59 32562.22 32628.57 33074.40 32931.53 32831.51 32644.78 325
EMVS52.08 30551.31 30554.39 31772.62 32845.39 33383.84 31975.51 33241.13 32740.77 32759.65 32730.08 32873.60 33028.31 32929.90 32844.18 326
MVEpermissive50.73 2353.25 30448.81 30766.58 31565.34 33057.50 32772.49 32670.94 33340.15 32839.28 32863.51 3256.89 33873.48 33138.29 32742.38 32268.76 323
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
tmp_tt51.94 30653.82 30346.29 31933.73 33445.30 33478.32 32467.24 33418.02 32950.93 32387.05 31052.99 31853.11 33270.76 30325.29 32940.46 327
wuyk23d25.11 30824.57 31026.74 32173.98 32539.89 33557.88 3289.80 33612.27 33010.39 3316.97 3347.03 33636.44 33325.43 33017.39 3303.89 331
testmvs13.36 31016.33 3114.48 3235.04 3352.26 33793.18 2743.28 3372.70 3318.24 33221.66 3302.29 3402.19 3347.58 3312.96 3319.00 329
test12313.04 31115.66 3125.18 3224.51 3363.45 33692.50 2881.81 3382.50 3327.58 33320.15 3313.67 3392.18 3357.13 3321.07 3339.90 328
cdsmvs_eth3d_5k23.24 30930.99 3090.00 3240.00 3370.00 3380.00 32997.63 1030.00 3330.00 33496.88 10284.38 1200.00 3360.00 3330.00 3340.00 332
pcd_1.5k_mvsjas7.39 3139.85 3140.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 3340.00 33588.65 680.00 3360.00 3330.00 3340.00 332
pcd1.5k->3k38.37 30740.51 30831.96 32094.29 2260.00 3380.00 32997.69 970.00 3330.00 3340.00 33581.45 1830.00 3360.00 33391.11 19295.89 181
sosnet-low-res0.00 3140.00 3150.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 3340.00 3350.00 3410.00 3360.00 3330.00 3340.00 332
sosnet0.00 3140.00 3150.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 3340.00 3350.00 3410.00 3360.00 3330.00 3340.00 332
uncertanet0.00 3140.00 3150.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 3340.00 3350.00 3410.00 3360.00 3330.00 3340.00 332
Regformer0.00 3140.00 3150.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 3340.00 3350.00 3410.00 3360.00 3330.00 3340.00 332
ab-mvs-re8.06 31210.74 3130.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 33496.69 1110.00 3410.00 3360.00 3330.00 3340.00 332
uanet0.00 3140.00 3150.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 3340.00 3350.00 3410.00 3360.00 3330.00 3340.00 332
sam_mvs182.76 156
sam_mvs81.94 177
MTGPAbinary98.08 47
MTMP82.03 329
test9_res94.81 5999.38 3399.45 28
agg_prior293.94 7199.38 3399.50 22
test_prior493.66 3896.42 169
test_prior296.35 17892.80 7796.03 5297.59 7692.01 2895.01 5299.38 33
新几何295.79 214
旧先验198.38 5893.38 4697.75 8898.09 4192.30 2599.01 6199.16 50
原ACMM295.67 218
test22298.24 6992.21 7395.33 23397.60 10479.22 29695.25 7497.84 5788.80 6699.15 5198.72 85
segment_acmp92.89 10
testdata195.26 23993.10 65
plane_prior796.21 14289.98 136
plane_prior696.10 15390.00 13281.32 185
plane_prior496.64 114
plane_prior390.00 13294.46 2991.34 138
plane_prior297.74 5094.85 16
plane_prior196.14 150
plane_prior89.99 13497.24 9394.06 3892.16 175
n20.00 339
nn0.00 339
door-mid91.06 314
test1197.88 78
door91.13 313
HQP5-MVS89.33 158
HQP-NCC95.86 15896.65 15493.55 4890.14 160
ACMP_Plane95.86 15896.65 15493.55 4890.14 160
BP-MVS92.13 100
HQP3-MVS97.39 13292.10 176
HQP2-MVS80.95 189
NP-MVS95.99 15689.81 14295.87 150
MDTV_nov1_ep13_2view70.35 31293.10 28083.88 26493.55 9882.47 16586.25 20598.38 112
ACMMP++_ref90.30 204
ACMMP++91.02 194
Test By Simon88.73 67