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 bysorted bysort bysort bysort bysort bysort bysort by
SED-MVS90.08 290.85 287.77 2695.30 270.98 7093.57 794.06 1277.24 5193.10 195.72 882.99 197.44 589.07 996.63 494.88 9
test_241102_ONE95.30 270.98 7094.06 1277.17 5593.10 195.39 1182.99 197.27 10
test072695.27 571.25 6393.60 694.11 877.33 4992.81 395.79 380.98 9
DVP-MVS++90.23 191.01 187.89 2494.34 2971.25 6395.06 194.23 578.38 3392.78 495.74 682.45 397.49 389.42 496.68 294.95 5
test_241102_TWO94.06 1277.24 5192.78 495.72 881.26 897.44 589.07 996.58 694.26 38
IU-MVS95.30 271.25 6392.95 5666.81 24292.39 688.94 1196.63 494.85 14
SMA-MVScopyleft89.08 789.23 788.61 594.25 3373.73 1092.40 2293.63 2374.77 11292.29 795.97 274.28 3497.24 1188.58 1396.91 194.87 11
Yufeng Yin; Xiaoyan Liu; Zichao Zhang: SMA-MVS: Segmentation-Guided Multi-Scale Anchor Deformation Patch Multi-View Stereo. IEEE Transactions on Circuits and Systems for Video Technology
DPE-MVScopyleft89.48 589.98 488.01 1494.80 1172.69 3291.59 4294.10 1075.90 8892.29 795.66 1081.67 697.38 987.44 2096.34 1593.95 51
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
DVP-MVScopyleft89.60 390.35 387.33 4595.27 571.25 6393.49 992.73 6577.33 4992.12 995.78 480.98 997.40 789.08 796.41 1293.33 82
Zhenlong Yuan, Jinguo Luo, Fei Shen, Zhaoxin Li, Cong Liu, Tianlu Mao, Zhaoqi Wang: DVP-MVS: Synergize Depth-Edge and Visibility Prior for Multi-View Stereo. AAAI2025
test_0728_THIRD78.38 3392.12 995.78 481.46 797.40 789.42 496.57 794.67 21
test_one_060195.07 771.46 6194.14 778.27 3592.05 1195.74 680.83 11
PC_three_145268.21 23492.02 1294.00 4882.09 595.98 5584.58 4096.68 294.95 5
test_part295.06 872.65 3391.80 13
MSP-MVS89.51 489.91 588.30 994.28 3273.46 1892.90 1694.11 880.27 1291.35 1494.16 4178.35 1396.77 2389.59 394.22 6494.67 21
Zhenlong Yuan, Cong Liu, Fei Shen, Zhaoxin Li, Jingguo luo, Tianlu Mao and Zhaoqi Wang: MSP-MVS: Multi-granularity Segmentation Prior Guided Multi-View Stereo. AAAI2025
FOURS195.00 1072.39 4295.06 193.84 1874.49 11891.30 15
APDe-MVS89.15 689.63 687.73 3094.49 2071.69 5893.83 493.96 1675.70 9291.06 1696.03 176.84 1597.03 1589.09 695.65 3294.47 28
SD-MVS88.06 1488.50 1386.71 5792.60 7672.71 3091.81 4093.19 4077.87 3690.32 1794.00 4874.83 2793.78 14587.63 1794.27 6393.65 70
Zhenlong Yuan, Jiakai Cao, Zhaoxin Li, Hao Jiang and Zhaoqi Wang: SD-MVS: Segmentation-driven Deformation Multi-View Stereo with Spherical Refinement and EM optimization. AAAI2024
DeepPCF-MVS80.84 188.10 1288.56 1286.73 5692.24 7869.03 11089.57 8993.39 3577.53 4689.79 1894.12 4378.98 1296.58 3685.66 2795.72 2994.58 24
xxxxxxxxxxxxxcwj87.88 1987.92 1987.77 2693.80 4472.35 4590.47 6689.69 16874.31 12289.16 1995.10 1375.65 2196.19 4587.07 2196.01 1794.79 16
SF-MVS88.46 1188.74 1187.64 3892.78 6971.95 5392.40 2294.74 275.71 9089.16 1995.10 1375.65 2196.19 4587.07 2196.01 1794.79 16
TSAR-MVS + MP.88.02 1788.11 1687.72 3293.68 4972.13 5091.41 4792.35 8074.62 11688.90 2193.85 5275.75 2096.00 5387.80 1594.63 5395.04 3
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
ETH3D-3000-0.188.09 1388.29 1487.50 4192.76 7071.89 5691.43 4694.70 374.47 11988.86 2294.61 2175.23 2495.84 5886.62 2695.92 2194.78 18
APD-MVScopyleft87.44 2687.52 2487.19 4794.24 3472.39 4291.86 3992.83 6173.01 15088.58 2394.52 2373.36 4096.49 3784.26 4695.01 4292.70 104
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
9.1488.26 1592.84 6891.52 4594.75 173.93 13288.57 2494.67 1975.57 2395.79 5986.77 2395.76 28
testtj87.78 2087.78 2187.77 2694.55 1872.47 3992.23 3193.49 3074.75 11388.33 2594.43 3273.27 4297.02 1684.18 4994.84 4893.82 59
ACMMP_NAP88.05 1688.08 1787.94 1793.70 4773.05 2390.86 5693.59 2576.27 8188.14 2695.09 1571.06 5996.67 2887.67 1696.37 1494.09 43
SteuartSystems-ACMMP88.72 1088.86 1088.32 892.14 8072.96 2693.73 593.67 2280.19 1488.10 2794.80 1673.76 3997.11 1387.51 1895.82 2494.90 8
Skip Steuart: Steuart Systems R&D Blog.
CNVR-MVS88.93 989.13 988.33 794.77 1273.82 990.51 6393.00 4780.90 988.06 2894.06 4676.43 1696.84 2088.48 1495.99 1994.34 34
canonicalmvs85.91 5385.87 5486.04 7289.84 12069.44 10890.45 6993.00 4776.70 7188.01 2991.23 10473.28 4193.91 14081.50 7788.80 12294.77 19
HPM-MVS++copyleft89.02 889.15 888.63 495.01 976.03 192.38 2592.85 6080.26 1387.78 3094.27 3675.89 1996.81 2287.45 1996.44 993.05 93
ZD-MVS94.38 2772.22 4892.67 6770.98 17987.75 3194.07 4574.01 3896.70 2684.66 3994.84 48
alignmvs85.48 5985.32 6185.96 7489.51 12769.47 10589.74 8592.47 7476.17 8287.73 3291.46 10070.32 6793.78 14581.51 7688.95 11994.63 23
ETH3 D test640087.50 2587.44 2687.70 3593.71 4671.75 5790.62 6194.05 1570.80 18187.59 3393.51 5677.57 1496.63 3183.31 5595.77 2694.72 20
ETH3D cwj APD-0.1687.31 3287.27 2887.44 4391.60 8772.45 4190.02 7794.37 471.76 16487.28 3494.27 3675.18 2596.08 4985.16 3095.77 2693.80 62
旧先验286.56 18658.10 32987.04 3588.98 27974.07 140
Regformer-286.63 4386.53 4286.95 5189.33 13471.24 6788.43 12392.05 9382.50 186.88 3690.09 12974.45 2995.61 6384.38 4390.63 10194.01 48
SR-MVS86.73 3986.67 4086.91 5294.11 4072.11 5192.37 2692.56 7374.50 11786.84 3794.65 2067.31 9595.77 6084.80 3792.85 7492.84 102
Regformer-186.41 4786.33 4486.64 5889.33 13470.93 7588.43 12391.39 12282.14 386.65 3890.09 12974.39 3295.01 9783.97 5190.63 10193.97 50
test117286.20 5086.22 4786.12 7093.95 4269.89 9691.79 4192.28 8275.07 10486.40 3994.58 2265.00 12095.56 6684.34 4592.60 7792.90 100
MP-MVS-pluss87.67 2287.72 2287.54 3993.64 5072.04 5289.80 8393.50 2875.17 10386.34 4095.29 1270.86 6096.00 5388.78 1296.04 1694.58 24
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
APD-MVS_3200maxsize85.97 5285.88 5386.22 6792.69 7269.53 10391.93 3692.99 4973.54 14085.94 4194.51 2665.80 11295.61 6383.04 6292.51 7993.53 77
zzz-MVS87.53 2487.41 2787.90 2194.18 3774.25 590.23 7392.02 9479.45 1985.88 4294.80 1668.07 8696.21 4386.69 2495.34 3693.23 85
MTAPA87.23 3387.00 3487.90 2194.18 3774.25 586.58 18592.02 9479.45 1985.88 4294.80 1668.07 8696.21 4386.69 2495.34 3693.23 85
TSAR-MVS + GP.85.71 5785.33 6086.84 5391.34 8972.50 3789.07 10187.28 23276.41 7485.80 4490.22 12774.15 3795.37 8381.82 7591.88 8592.65 108
NCCC88.06 1488.01 1888.24 1094.41 2473.62 1191.22 5192.83 6181.50 685.79 4593.47 5973.02 4597.00 1784.90 3394.94 4494.10 42
SR-MVS-dyc-post85.77 5585.61 5686.23 6693.06 6270.63 8291.88 3792.27 8373.53 14185.69 4694.45 2865.00 12095.56 6682.75 6591.87 8692.50 111
RE-MVS-def85.48 5793.06 6270.63 8291.88 3792.27 8373.53 14185.69 4694.45 2863.87 12782.75 6591.87 8692.50 111
testdata79.97 23790.90 9664.21 20784.71 26259.27 32185.40 4892.91 7062.02 15889.08 27768.95 18891.37 9386.63 290
Regformer-485.68 5885.45 5886.35 6288.95 15369.67 10088.29 13391.29 12481.73 585.36 4990.01 13272.62 4795.35 8483.28 5887.57 13494.03 46
abl_685.23 6484.95 7086.07 7192.23 7970.48 8690.80 5892.08 9273.51 14385.26 5094.16 4162.75 14495.92 5782.46 7291.30 9591.81 135
ZNCC-MVS87.94 1887.85 2088.20 1194.39 2673.33 2093.03 1493.81 2076.81 6585.24 5194.32 3571.76 5496.93 1885.53 2995.79 2594.32 35
PHI-MVS86.43 4586.17 5087.24 4690.88 9770.96 7292.27 3094.07 1172.45 15385.22 5291.90 8769.47 7696.42 3883.28 5895.94 2094.35 33
Regformer-385.23 6485.07 6685.70 7688.95 15369.01 11288.29 13389.91 16280.95 885.01 5390.01 13272.45 4894.19 12682.50 7187.57 13493.90 54
TEST993.26 5672.96 2688.75 11391.89 10368.44 23285.00 5493.10 6574.36 3395.41 77
train_agg86.43 4586.20 4887.13 4993.26 5672.96 2688.75 11391.89 10368.69 22885.00 5493.10 6574.43 3095.41 7784.97 3295.71 3093.02 95
HFP-MVS87.58 2387.47 2587.94 1794.58 1673.54 1593.04 1293.24 3776.78 6784.91 5694.44 3070.78 6196.61 3284.53 4194.89 4693.66 65
#test#87.33 3187.13 3387.94 1794.58 1673.54 1592.34 2793.24 3775.23 10084.91 5694.44 3070.78 6196.61 3283.75 5494.89 4693.66 65
test_prior386.73 3986.86 3986.33 6392.61 7469.59 10188.85 10892.97 5475.41 9684.91 5693.54 5474.28 3495.48 7183.31 5595.86 2293.91 52
test_prior288.85 10875.41 9684.91 5693.54 5474.28 3483.31 5595.86 22
test_893.13 5872.57 3688.68 11891.84 10668.69 22884.87 6093.10 6574.43 3095.16 89
MCST-MVS87.37 3087.25 3087.73 3094.53 1972.46 4089.82 8193.82 1973.07 14884.86 6192.89 7176.22 1796.33 3984.89 3595.13 4194.40 31
GST-MVS87.42 2887.26 2987.89 2494.12 3972.97 2592.39 2493.43 3376.89 6384.68 6293.99 5070.67 6496.82 2184.18 4995.01 4293.90 54
h-mvs3383.15 8782.19 9586.02 7390.56 10270.85 7888.15 14089.16 18476.02 8584.67 6391.39 10261.54 16395.50 7082.71 6775.48 27991.72 137
hse-mvs281.72 10980.94 11584.07 12488.72 16467.68 14485.87 20487.26 23376.02 8584.67 6388.22 18361.54 16393.48 16182.71 6773.44 30691.06 155
ACMMPR87.44 2687.23 3188.08 1394.64 1373.59 1293.04 1293.20 3976.78 6784.66 6594.52 2368.81 8496.65 2984.53 4194.90 4594.00 49
CDPH-MVS85.76 5685.29 6387.17 4893.49 5371.08 6888.58 12192.42 7868.32 23384.61 6693.48 5772.32 4996.15 4879.00 9495.43 3494.28 37
UA-Net85.08 6884.96 6985.45 7892.07 8168.07 13789.78 8490.86 13782.48 284.60 6793.20 6369.35 7795.22 8771.39 16490.88 9993.07 92
region2R87.42 2887.20 3288.09 1294.63 1473.55 1393.03 1493.12 4276.73 7084.45 6894.52 2369.09 8096.70 2684.37 4494.83 5094.03 46
agg_prior186.22 4986.09 5286.62 5992.85 6671.94 5488.59 12091.78 10968.96 22384.41 6993.18 6474.94 2694.93 9884.75 3895.33 3893.01 96
agg_prior92.85 6671.94 5491.78 10984.41 6994.93 98
VDD-MVS83.01 9282.36 9384.96 9191.02 9466.40 16488.91 10588.11 21277.57 4284.39 7193.29 6252.19 24393.91 14077.05 11688.70 12494.57 26
casdiffmvs85.11 6785.14 6585.01 8987.20 21265.77 17887.75 15192.83 6177.84 3784.36 7292.38 8072.15 5193.93 13981.27 7990.48 10395.33 1
MSLP-MVS++85.43 6185.76 5584.45 10991.93 8370.24 8790.71 5992.86 5977.46 4884.22 7392.81 7567.16 9792.94 18680.36 8894.35 6190.16 187
DeepC-MVS_fast79.65 386.91 3886.62 4187.76 2993.52 5272.37 4491.26 4893.04 4376.62 7284.22 7393.36 6171.44 5796.76 2480.82 8395.33 3894.16 40
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
DROMVSNet86.01 5186.38 4384.91 9589.31 13966.27 16792.32 2893.63 2379.37 2184.17 7591.88 8869.04 8395.43 7583.93 5293.77 6793.01 96
ETV-MVS84.90 7284.67 7385.59 7789.39 13268.66 12688.74 11592.64 7179.97 1784.10 7685.71 24869.32 7895.38 8080.82 8391.37 9392.72 103
VNet82.21 10082.41 9181.62 19990.82 9860.93 25884.47 23689.78 16476.36 7984.07 7791.88 8864.71 12290.26 25770.68 16988.89 12093.66 65
baseline84.93 7084.98 6784.80 10087.30 21065.39 18687.30 16392.88 5877.62 4084.04 7892.26 8171.81 5393.96 13381.31 7890.30 10595.03 4
PGM-MVS86.68 4186.27 4687.90 2194.22 3573.38 1990.22 7493.04 4375.53 9483.86 7994.42 3367.87 9096.64 3082.70 6994.57 5593.66 65
MP-MVScopyleft87.71 2187.64 2387.93 2094.36 2873.88 792.71 2192.65 7077.57 4283.84 8094.40 3472.24 5096.28 4185.65 2895.30 4093.62 72
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
HPM-MVScopyleft87.11 3586.98 3587.50 4193.88 4372.16 4992.19 3293.33 3676.07 8483.81 8193.95 5169.77 7496.01 5285.15 3194.66 5294.32 35
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
CP-MVS87.11 3586.92 3687.68 3794.20 3673.86 893.98 392.82 6476.62 7283.68 8294.46 2767.93 8895.95 5684.20 4894.39 5993.23 85
XVS87.18 3486.91 3788.00 1594.42 2273.33 2092.78 1792.99 4979.14 2283.67 8394.17 4067.45 9396.60 3483.06 6094.50 5694.07 44
X-MVStestdata80.37 14377.83 17988.00 1594.42 2273.33 2092.78 1792.99 4979.14 2283.67 8312.47 37167.45 9396.60 3483.06 6094.50 5694.07 44
DELS-MVS85.41 6285.30 6285.77 7588.49 17167.93 13985.52 21793.44 3278.70 2983.63 8589.03 16174.57 2895.71 6280.26 9094.04 6593.66 65
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
LFMVS81.82 10881.23 10983.57 14191.89 8463.43 22589.84 8081.85 30377.04 6083.21 8693.10 6552.26 24293.43 16571.98 15989.95 11293.85 56
VDDNet81.52 11580.67 11884.05 12690.44 10564.13 20989.73 8685.91 25271.11 17683.18 8793.48 5750.54 26693.49 16073.40 14888.25 13094.54 27
CSCG86.41 4786.19 4987.07 5092.91 6572.48 3890.81 5793.56 2673.95 13083.16 8891.07 11075.94 1895.19 8879.94 9294.38 6093.55 75
CS-MVS84.53 7384.97 6883.23 15487.54 20463.27 22888.82 11093.50 2875.98 8783.07 8989.73 13970.29 6895.23 8682.07 7493.70 6991.18 151
nrg03083.88 7583.53 7784.96 9186.77 22069.28 10990.46 6892.67 6774.79 11182.95 9091.33 10372.70 4693.09 18080.79 8579.28 23692.50 111
EI-MVSNet-Vis-set84.19 7483.81 7685.31 8088.18 18067.85 14087.66 15389.73 16780.05 1682.95 9089.59 14570.74 6394.82 10680.66 8684.72 17093.28 84
MVS_Test83.15 8783.06 8383.41 14686.86 21663.21 23086.11 19892.00 9774.31 12282.87 9289.44 15370.03 7093.21 17077.39 11388.50 12893.81 60
DPM-MVS84.93 7084.29 7586.84 5390.20 10973.04 2487.12 16793.04 4369.80 20182.85 9391.22 10573.06 4496.02 5176.72 12194.63 5391.46 145
DeepC-MVS79.81 287.08 3786.88 3887.69 3691.16 9172.32 4790.31 7193.94 1777.12 5782.82 9494.23 3972.13 5297.09 1484.83 3695.37 3593.65 70
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
mPP-MVS86.67 4286.32 4587.72 3294.41 2473.55 1392.74 1992.22 8776.87 6482.81 9594.25 3866.44 10296.24 4282.88 6494.28 6293.38 79
test1286.80 5592.63 7370.70 8191.79 10882.71 9671.67 5596.16 4794.50 5693.54 76
HPM-MVS_fast85.35 6384.95 7086.57 6193.69 4870.58 8592.15 3491.62 11373.89 13382.67 9794.09 4462.60 14595.54 6980.93 8192.93 7293.57 74
Effi-MVS+83.62 8083.08 8285.24 8388.38 17667.45 14788.89 10689.15 18575.50 9582.27 9888.28 18069.61 7594.45 11677.81 10887.84 13293.84 58
EI-MVSNet-UG-set83.81 7683.38 7985.09 8787.87 18967.53 14687.44 15989.66 16979.74 1882.23 9989.41 15470.24 6994.74 10979.95 9183.92 17892.99 98
MVS_111021_HR85.14 6684.75 7286.32 6591.65 8672.70 3185.98 20090.33 15076.11 8382.08 10091.61 9571.36 5894.17 12881.02 8092.58 7892.08 127
diffmvs82.10 10181.88 10382.76 18083.00 28263.78 21583.68 25289.76 16572.94 15182.02 10189.85 13665.96 11190.79 25182.38 7387.30 14193.71 64
xiu_mvs_v1_base_debu80.80 13179.72 13584.03 12987.35 20570.19 9085.56 21088.77 19969.06 21981.83 10288.16 18450.91 26092.85 18878.29 10587.56 13689.06 225
xiu_mvs_v1_base80.80 13179.72 13584.03 12987.35 20570.19 9085.56 21088.77 19969.06 21981.83 10288.16 18450.91 26092.85 18878.29 10587.56 13689.06 225
xiu_mvs_v1_base_debi80.80 13179.72 13584.03 12987.35 20570.19 9085.56 21088.77 19969.06 21981.83 10288.16 18450.91 26092.85 18878.29 10587.56 13689.06 225
CS-MVS-test85.02 6985.21 6484.46 10889.28 14165.70 17991.16 5293.56 2677.83 3881.80 10589.89 13470.67 6495.61 6380.39 8792.34 8392.06 128
新几何183.42 14493.13 5870.71 8085.48 25557.43 33481.80 10591.98 8563.28 13392.27 20764.60 22792.99 7187.27 273
test_yl81.17 12080.47 12283.24 15289.13 14863.62 21686.21 19589.95 16072.43 15681.78 10789.61 14357.50 20493.58 15470.75 16786.90 14692.52 109
DCV-MVSNet81.17 12080.47 12283.24 15289.13 14863.62 21686.21 19589.95 16072.43 15681.78 10789.61 14357.50 20493.58 15470.75 16786.90 14692.52 109
112180.84 12679.77 13384.05 12693.11 6070.78 7984.66 23085.42 25657.37 33581.76 10992.02 8463.41 13194.12 12967.28 20392.93 7287.26 274
MG-MVS83.41 8383.45 7883.28 14992.74 7162.28 24488.17 13889.50 17275.22 10181.49 11092.74 7966.75 9895.11 9172.85 15491.58 9092.45 114
CANet86.45 4486.10 5187.51 4090.09 11170.94 7489.70 8792.59 7281.78 481.32 11191.43 10170.34 6697.23 1284.26 4693.36 7094.37 32
MVSFormer82.85 9382.05 9985.24 8387.35 20570.21 8890.50 6490.38 14668.55 23081.32 11189.47 14861.68 16093.46 16378.98 9590.26 10692.05 129
lupinMVS81.39 11880.27 12784.76 10187.35 20570.21 8885.55 21386.41 24462.85 29281.32 11188.61 17061.68 16092.24 21078.41 10390.26 10691.83 133
xiu_mvs_v2_base81.69 11181.05 11283.60 13989.15 14768.03 13884.46 23890.02 15870.67 18581.30 11486.53 23463.17 13794.19 12675.60 13088.54 12688.57 247
PS-MVSNAJ81.69 11181.02 11383.70 13889.51 12768.21 13584.28 24490.09 15770.79 18281.26 11585.62 25263.15 13894.29 11875.62 12988.87 12188.59 246
原ACMM184.35 11493.01 6468.79 11692.44 7563.96 28381.09 11691.57 9666.06 10895.45 7367.19 20694.82 5188.81 240
jason81.39 11880.29 12684.70 10286.63 22269.90 9585.95 20186.77 24063.24 28581.07 11789.47 14861.08 17692.15 21378.33 10490.07 11192.05 129
jason: jason.
OPM-MVS83.50 8182.95 8585.14 8588.79 16170.95 7389.13 10091.52 11677.55 4580.96 11891.75 9060.71 18094.50 11579.67 9386.51 15389.97 203
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
Vis-MVSNetpermissive83.46 8282.80 8885.43 7990.25 10868.74 12090.30 7290.13 15676.33 8080.87 11992.89 7161.00 17794.20 12572.45 15890.97 9793.35 81
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
ACMMPcopyleft85.89 5485.39 5987.38 4493.59 5172.63 3492.74 1993.18 4176.78 6780.73 12093.82 5364.33 12396.29 4082.67 7090.69 10093.23 85
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
Anonymous2024052980.19 14778.89 15584.10 12290.60 10164.75 19688.95 10490.90 13565.97 25780.59 12191.17 10749.97 27193.73 15169.16 18682.70 19893.81 60
test_part182.78 9482.08 9884.89 9690.66 10066.97 15890.96 5592.93 5777.19 5480.53 12290.04 13163.44 13095.39 7976.04 12576.90 25692.31 118
MVS_111021_LR82.61 9782.11 9684.11 12188.82 15871.58 5985.15 22086.16 24974.69 11480.47 12391.04 11162.29 15290.55 25580.33 8990.08 11090.20 186
ECVR-MVScopyleft79.61 15579.26 14780.67 22490.08 11254.69 32587.89 14877.44 33574.88 10980.27 12492.79 7648.96 28592.45 19868.55 19292.50 8094.86 12
VPA-MVSNet80.60 13780.55 12080.76 22288.07 18460.80 26186.86 17591.58 11575.67 9380.24 12589.45 15263.34 13290.25 25870.51 17179.22 23791.23 150
test111179.43 16279.18 15080.15 23489.99 11653.31 33887.33 16277.05 33875.04 10580.23 12692.77 7848.97 28492.33 20668.87 18992.40 8294.81 15
test250677.30 21576.49 21279.74 24290.08 11252.02 34187.86 15063.10 36874.88 10980.16 12792.79 7638.29 34192.35 20468.74 19192.50 8094.86 12
Anonymous20240521178.25 19077.01 19881.99 19391.03 9360.67 26384.77 22883.90 27570.65 18780.00 12891.20 10641.08 33191.43 23465.21 22185.26 16593.85 56
test22291.50 8868.26 13384.16 24583.20 28954.63 34679.74 12991.63 9458.97 19391.42 9286.77 286
OMC-MVS82.69 9581.97 10284.85 9788.75 16367.42 14887.98 14290.87 13674.92 10879.72 13091.65 9262.19 15593.96 13375.26 13386.42 15493.16 90
CPTT-MVS83.73 7783.33 8084.92 9493.28 5570.86 7792.09 3590.38 14668.75 22779.57 13192.83 7360.60 18493.04 18480.92 8291.56 9190.86 163
IS-MVSNet83.15 8782.81 8784.18 12089.94 11863.30 22791.59 4288.46 20979.04 2679.49 13292.16 8265.10 11794.28 11967.71 19891.86 8894.95 5
PS-MVSNAJss82.07 10381.31 10784.34 11586.51 22367.27 15289.27 9391.51 11771.75 16579.37 13390.22 12763.15 13894.27 12077.69 10982.36 20191.49 143
EPP-MVSNet83.40 8483.02 8484.57 10490.13 11064.47 20292.32 2890.73 13874.45 12179.35 13491.10 10869.05 8295.12 9072.78 15587.22 14294.13 41
DP-MVS Recon83.11 9082.09 9786.15 6894.44 2170.92 7688.79 11192.20 8870.53 18879.17 13591.03 11364.12 12596.03 5068.39 19590.14 10891.50 142
ab-mvs79.51 15878.97 15481.14 21488.46 17360.91 25983.84 25089.24 18170.36 19079.03 13688.87 16463.23 13690.21 25965.12 22282.57 19992.28 120
EIA-MVS83.31 8682.80 8884.82 9889.59 12365.59 18188.21 13692.68 6674.66 11578.96 13786.42 23669.06 8195.26 8575.54 13190.09 10993.62 72
PVSNet_Blended_VisFu82.62 9681.83 10484.96 9190.80 9969.76 9888.74 11591.70 11269.39 20878.96 13788.46 17565.47 11494.87 10574.42 13688.57 12590.24 185
HQP_MVS83.64 7983.14 8185.14 8590.08 11268.71 12291.25 4992.44 7579.12 2478.92 13991.00 11460.42 18695.38 8078.71 9786.32 15591.33 147
plane_prior368.60 12778.44 3178.92 139
RRT_MVS79.88 15278.38 16584.38 11185.42 23770.60 8488.71 11788.75 20372.30 15878.83 14189.14 15644.44 31292.18 21278.50 10079.33 23590.35 181
EI-MVSNet80.52 14079.98 12982.12 18884.28 25363.19 23286.41 18988.95 19574.18 12778.69 14287.54 19966.62 9992.43 19972.57 15780.57 22090.74 167
MVSTER79.01 17477.88 17882.38 18683.07 27964.80 19584.08 24988.95 19569.01 22278.69 14287.17 21154.70 22392.43 19974.69 13580.57 22089.89 206
API-MVS81.99 10581.23 10984.26 11890.94 9570.18 9391.10 5389.32 17671.51 17178.66 14488.28 18065.26 11595.10 9464.74 22691.23 9687.51 267
GeoE81.71 11081.01 11483.80 13789.51 12764.45 20388.97 10388.73 20471.27 17478.63 14589.76 13866.32 10493.20 17269.89 17886.02 16093.74 63
UniMVSNet (Re)81.60 11481.11 11183.09 16088.38 17664.41 20487.60 15493.02 4678.42 3278.56 14688.16 18469.78 7393.26 16969.58 18276.49 26391.60 138
MAR-MVS81.84 10780.70 11785.27 8291.32 9071.53 6089.82 8190.92 13469.77 20278.50 14786.21 24062.36 15194.52 11465.36 22092.05 8489.77 211
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
Fast-Effi-MVS+80.81 12979.92 13083.47 14288.85 15564.51 19985.53 21589.39 17470.79 18278.49 14885.06 26467.54 9293.58 15467.03 20986.58 15192.32 117
FIs82.07 10382.42 9081.04 21788.80 16058.34 28388.26 13593.49 3076.93 6278.47 14991.04 11169.92 7292.34 20569.87 17984.97 16792.44 115
UniMVSNet_NR-MVSNet81.88 10681.54 10682.92 16988.46 17363.46 22387.13 16692.37 7980.19 1478.38 15089.14 15671.66 5693.05 18270.05 17576.46 26492.25 121
DU-MVS81.12 12280.52 12182.90 17087.80 19263.46 22387.02 17091.87 10579.01 2778.38 15089.07 15965.02 11893.05 18270.05 17576.46 26492.20 123
CLD-MVS82.31 9981.65 10584.29 11788.47 17267.73 14385.81 20892.35 8075.78 8978.33 15286.58 23164.01 12694.35 11776.05 12487.48 13990.79 164
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
VPNet78.69 18178.66 15878.76 25888.31 17855.72 32184.45 23986.63 24276.79 6678.26 15390.55 12159.30 19189.70 26766.63 21077.05 25490.88 162
V4279.38 16678.24 17082.83 17281.10 31765.50 18385.55 21389.82 16371.57 17078.21 15486.12 24260.66 18293.18 17575.64 12875.46 28189.81 210
BH-RMVSNet79.61 15578.44 16383.14 15889.38 13365.93 17384.95 22587.15 23573.56 13978.19 15589.79 13756.67 21293.36 16659.53 26686.74 14990.13 189
v2v48280.23 14579.29 14683.05 16383.62 26564.14 20887.04 16989.97 15973.61 13778.18 15687.22 20861.10 17593.82 14376.11 12376.78 26191.18 151
PVSNet_BlendedMVS80.60 13780.02 12882.36 18788.85 15565.40 18486.16 19792.00 9769.34 21078.11 15786.09 24366.02 10994.27 12071.52 16182.06 20387.39 269
PVSNet_Blended80.98 12380.34 12482.90 17088.85 15565.40 18484.43 24092.00 9767.62 23778.11 15785.05 26566.02 10994.27 12071.52 16189.50 11589.01 230
v114480.03 14979.03 15283.01 16583.78 26364.51 19987.11 16890.57 14271.96 16378.08 15986.20 24161.41 16793.94 13674.93 13477.23 25190.60 172
TranMVSNet+NR-MVSNet80.84 12680.31 12582.42 18587.85 19062.33 24287.74 15291.33 12380.55 1177.99 16089.86 13565.23 11692.62 19267.05 20875.24 28992.30 119
Baseline_NR-MVSNet78.15 19578.33 16877.61 27685.79 23056.21 31786.78 17985.76 25373.60 13877.93 16187.57 19765.02 11888.99 27867.14 20775.33 28587.63 263
TR-MVS77.44 21176.18 21781.20 21288.24 17963.24 22984.61 23486.40 24567.55 23877.81 16286.48 23554.10 22893.15 17657.75 28482.72 19787.20 275
v119279.59 15778.43 16483.07 16283.55 26764.52 19886.93 17390.58 14170.83 18077.78 16385.90 24459.15 19293.94 13673.96 14177.19 25390.76 165
PCF-MVS73.52 780.38 14278.84 15685.01 8987.71 19668.99 11383.65 25391.46 12163.00 28977.77 16490.28 12466.10 10695.09 9561.40 25288.22 13190.94 161
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
WR-MVS79.49 15979.22 14980.27 23288.79 16158.35 28285.06 22288.61 20778.56 3077.65 16588.34 17863.81 12990.66 25464.98 22477.22 25291.80 136
XVG-OURS80.41 14179.23 14883.97 13385.64 23369.02 11183.03 26690.39 14571.09 17777.63 16691.49 9954.62 22591.35 23675.71 12783.47 18691.54 140
v14419279.47 16078.37 16682.78 17883.35 27063.96 21186.96 17190.36 14969.99 19677.50 16785.67 25060.66 18293.77 14774.27 13876.58 26290.62 170
v192192079.22 16878.03 17382.80 17583.30 27263.94 21286.80 17790.33 15069.91 19977.48 16885.53 25358.44 19693.75 14973.60 14376.85 25990.71 168
thisisatest053079.40 16477.76 18384.31 11687.69 19865.10 19287.36 16084.26 27170.04 19577.42 16988.26 18249.94 27294.79 10870.20 17384.70 17193.03 94
FC-MVSNet-test81.52 11582.02 10080.03 23688.42 17555.97 31987.95 14493.42 3477.10 5877.38 17090.98 11669.96 7191.79 22468.46 19484.50 17292.33 116
v124078.99 17577.78 18182.64 18183.21 27463.54 22086.62 18490.30 15269.74 20577.33 17185.68 24957.04 21093.76 14873.13 15276.92 25590.62 170
PAPM_NR83.02 9182.41 9184.82 9892.47 7766.37 16587.93 14691.80 10773.82 13477.32 17290.66 11967.90 8994.90 10270.37 17289.48 11693.19 89
ACMM73.20 880.78 13479.84 13283.58 14089.31 13968.37 13089.99 7891.60 11470.28 19277.25 17389.66 14153.37 23493.53 15974.24 13982.85 19488.85 238
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
HQP4-MVS77.24 17495.11 9191.03 157
AUN-MVS79.21 16977.60 18884.05 12688.71 16567.61 14585.84 20687.26 23369.08 21877.23 17588.14 18853.20 23693.47 16275.50 13273.45 30591.06 155
HQP-NCC89.33 13489.17 9576.41 7477.23 175
ACMP_Plane89.33 13489.17 9576.41 7477.23 175
HQP-MVS82.61 9782.02 10084.37 11289.33 13466.98 15689.17 9592.19 8976.41 7477.23 17590.23 12660.17 18995.11 9177.47 11185.99 16191.03 157
TAPA-MVS73.13 979.15 17077.94 17582.79 17789.59 12362.99 23788.16 13991.51 11765.77 25877.14 17991.09 10960.91 17893.21 17050.26 32187.05 14492.17 125
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
PAPR81.66 11380.89 11683.99 13290.27 10764.00 21086.76 18191.77 11168.84 22677.13 18089.50 14667.63 9194.88 10467.55 20088.52 12793.09 91
UniMVSNet_ETH3D79.10 17278.24 17081.70 19886.85 21760.24 26987.28 16488.79 19874.25 12576.84 18190.53 12249.48 27791.56 23067.98 19682.15 20293.29 83
EPNet83.72 7882.92 8686.14 6984.22 25569.48 10491.05 5485.27 25781.30 776.83 18291.65 9266.09 10795.56 6676.00 12693.85 6693.38 79
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
baseline176.98 22076.75 20877.66 27488.13 18155.66 32285.12 22181.89 30173.04 14976.79 18388.90 16262.43 15087.78 29563.30 23471.18 32189.55 217
tttt051779.40 16477.91 17683.90 13688.10 18363.84 21388.37 13084.05 27371.45 17276.78 18489.12 15849.93 27494.89 10370.18 17483.18 19092.96 99
TAMVS78.89 17877.51 19083.03 16487.80 19267.79 14284.72 22985.05 26067.63 23676.75 18587.70 19362.25 15390.82 25058.53 27787.13 14390.49 176
XVG-OURS-SEG-HR80.81 12979.76 13483.96 13485.60 23468.78 11783.54 25890.50 14370.66 18676.71 18691.66 9160.69 18191.26 23876.94 11881.58 20891.83 133
3Dnovator+77.84 485.48 5984.47 7488.51 691.08 9273.49 1793.18 1193.78 2180.79 1076.66 18793.37 6060.40 18896.75 2577.20 11493.73 6895.29 2
LPG-MVS_test82.08 10281.27 10884.50 10689.23 14468.76 11890.22 7491.94 10175.37 9876.64 18891.51 9754.29 22694.91 10078.44 10183.78 17989.83 208
LGP-MVS_train84.50 10689.23 14468.76 11891.94 10175.37 9876.64 18891.51 9754.29 22694.91 10078.44 10183.78 17989.83 208
tfpn200view976.42 22975.37 22879.55 24989.13 14857.65 29585.17 21883.60 27873.41 14476.45 19086.39 23752.12 24491.95 21948.33 32983.75 18189.07 223
thres40076.50 22675.37 22879.86 23989.13 14857.65 29585.17 21883.60 27873.41 14476.45 19086.39 23752.12 24491.95 21948.33 32983.75 18190.00 199
HyFIR lowres test77.53 21075.40 22683.94 13589.59 12366.62 16180.36 29088.64 20656.29 34176.45 19085.17 26157.64 20293.28 16861.34 25483.10 19291.91 131
mvs-test180.88 12479.40 14285.29 8185.13 24369.75 9989.28 9288.10 21374.99 10676.44 19386.72 22057.27 20794.26 12473.53 14483.18 19091.87 132
CDS-MVSNet79.07 17377.70 18583.17 15787.60 19968.23 13484.40 24286.20 24867.49 23976.36 19486.54 23361.54 16390.79 25161.86 24887.33 14090.49 176
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
thres100view90076.50 22675.55 22279.33 25089.52 12656.99 30385.83 20783.23 28773.94 13176.32 19587.12 21251.89 25191.95 21948.33 32983.75 18189.07 223
thres600view776.50 22675.44 22479.68 24489.40 13157.16 30085.53 21583.23 28773.79 13576.26 19687.09 21351.89 25191.89 22248.05 33483.72 18490.00 199
UGNet80.83 12879.59 13884.54 10588.04 18568.09 13689.42 9088.16 21176.95 6176.22 19789.46 15049.30 28093.94 13668.48 19390.31 10491.60 138
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
test_djsdf80.30 14479.32 14583.27 15083.98 26065.37 18790.50 6490.38 14668.55 23076.19 19888.70 16656.44 21393.46 16378.98 9580.14 22690.97 160
v14878.72 18077.80 18081.47 20382.73 28961.96 24886.30 19388.08 21573.26 14676.18 19985.47 25562.46 14992.36 20371.92 16073.82 30290.09 193
WTY-MVS75.65 23975.68 22075.57 29586.40 22456.82 30577.92 31682.40 29765.10 26576.18 19987.72 19263.13 14180.90 33560.31 26081.96 20489.00 232
mvs_anonymous79.42 16379.11 15180.34 23084.45 25257.97 28982.59 26887.62 22567.40 24076.17 20188.56 17368.47 8589.59 26870.65 17086.05 15993.47 78
Anonymous2023121178.97 17677.69 18682.81 17490.54 10364.29 20690.11 7691.51 11765.01 26876.16 20288.13 18950.56 26593.03 18569.68 18177.56 24991.11 154
bset_n11_16_dypcd77.12 21775.47 22382.06 19081.12 31665.99 17181.37 28283.20 28969.94 19876.09 20383.38 28647.75 29092.26 20878.51 9977.91 24587.95 255
thisisatest051577.33 21475.38 22783.18 15685.27 23963.80 21482.11 27383.27 28665.06 26675.91 20483.84 27849.54 27694.27 12067.24 20586.19 15791.48 144
RRT_test8_iter0578.38 18877.40 19181.34 20886.00 22858.86 27886.55 18791.26 12572.13 16275.91 20487.42 20244.97 30993.73 15177.02 11775.30 28691.45 146
CANet_DTU80.61 13679.87 13182.83 17285.60 23463.17 23387.36 16088.65 20576.37 7875.88 20688.44 17653.51 23393.07 18173.30 14989.74 11492.25 121
thres20075.55 24074.47 23878.82 25787.78 19557.85 29283.07 26583.51 28172.44 15575.84 20784.42 27052.08 24691.75 22547.41 33683.64 18586.86 284
CHOSEN 1792x268877.63 20975.69 21983.44 14389.98 11768.58 12878.70 30887.50 22856.38 34075.80 20886.84 21658.67 19491.40 23561.58 25185.75 16490.34 182
AdaColmapbinary80.58 13979.42 14184.06 12593.09 6168.91 11589.36 9188.97 19469.27 21175.70 20989.69 14057.20 20995.77 6063.06 23688.41 12987.50 268
c3_l78.75 17977.91 17681.26 21082.89 28661.56 25384.09 24889.13 18769.97 19775.56 21084.29 27266.36 10392.09 21573.47 14775.48 27990.12 190
miper_ehance_all_eth78.59 18477.76 18381.08 21682.66 29161.56 25383.65 25389.15 18568.87 22575.55 21183.79 28066.49 10192.03 21673.25 15076.39 26689.64 214
miper_enhance_ethall77.87 20476.86 20280.92 21981.65 30561.38 25582.68 26788.98 19265.52 26275.47 21282.30 29865.76 11392.00 21872.95 15376.39 26689.39 219
3Dnovator76.31 583.38 8582.31 9486.59 6087.94 18872.94 2990.64 6092.14 9177.21 5375.47 21292.83 7358.56 19594.72 11073.24 15192.71 7692.13 126
jajsoiax79.29 16777.96 17483.27 15084.68 24966.57 16389.25 9490.16 15569.20 21575.46 21489.49 14745.75 30693.13 17876.84 11980.80 21690.11 191
IterMVS-LS80.06 14879.38 14382.11 18985.89 22963.20 23186.79 17889.34 17574.19 12675.45 21586.72 22066.62 9992.39 20172.58 15676.86 25890.75 166
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
BH-untuned79.47 16078.60 15982.05 19189.19 14665.91 17486.07 19988.52 20872.18 15975.42 21687.69 19461.15 17493.54 15860.38 25986.83 14886.70 288
mvs_tets79.13 17177.77 18283.22 15584.70 24866.37 16589.17 9590.19 15469.38 20975.40 21789.46 15044.17 31493.15 17676.78 12080.70 21890.14 188
HY-MVS69.67 1277.95 20177.15 19680.36 22987.57 20360.21 27083.37 26087.78 22366.11 25375.37 21887.06 21563.27 13490.48 25661.38 25382.43 20090.40 180
GBi-Net78.40 18677.40 19181.40 20587.60 19963.01 23488.39 12789.28 17771.63 16775.34 21987.28 20454.80 21991.11 24162.72 23779.57 22990.09 193
test178.40 18677.40 19181.40 20587.60 19963.01 23488.39 12789.28 17771.63 16775.34 21987.28 20454.80 21991.11 24162.72 23779.57 22990.09 193
FMVSNet377.88 20376.85 20380.97 21886.84 21862.36 24186.52 18888.77 19971.13 17575.34 21986.66 22754.07 22991.10 24462.72 23779.57 22989.45 218
CostFormer75.24 24573.90 24479.27 25182.65 29258.27 28480.80 28382.73 29561.57 30375.33 22283.13 28855.52 21591.07 24764.98 22478.34 24388.45 249
FMVSNet278.20 19377.21 19581.20 21287.60 19962.89 23887.47 15889.02 19071.63 16775.29 22387.28 20454.80 21991.10 24462.38 24179.38 23389.61 215
v879.97 15179.02 15382.80 17584.09 25764.50 20187.96 14390.29 15374.13 12975.24 22486.81 21762.88 14393.89 14274.39 13775.40 28390.00 199
anonymousdsp78.60 18377.15 19682.98 16780.51 32367.08 15487.24 16589.53 17165.66 26075.16 22587.19 21052.52 23792.25 20977.17 11579.34 23489.61 215
QAPM80.88 12479.50 14085.03 8888.01 18768.97 11491.59 4292.00 9766.63 24975.15 22692.16 8257.70 20195.45 7363.52 23088.76 12390.66 169
v1079.74 15478.67 15782.97 16884.06 25864.95 19387.88 14990.62 14073.11 14775.11 22786.56 23261.46 16694.05 13273.68 14275.55 27789.90 205
Vis-MVSNet (Re-imp)78.36 18978.45 16278.07 26988.64 16751.78 34486.70 18279.63 32474.14 12875.11 22790.83 11761.29 17189.75 26558.10 28191.60 8992.69 106
cl2278.07 19777.01 19881.23 21182.37 29861.83 25083.55 25787.98 21768.96 22375.06 22983.87 27661.40 16891.88 22373.53 14476.39 26689.98 202
ACMP74.13 681.51 11780.57 11984.36 11389.42 13068.69 12589.97 7991.50 12074.46 12075.04 23090.41 12353.82 23194.54 11277.56 11082.91 19389.86 207
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
Effi-MVS+-dtu80.03 14978.57 16084.42 11085.13 24368.74 12088.77 11288.10 21374.99 10674.97 23183.49 28457.27 20793.36 16673.53 14480.88 21491.18 151
XXY-MVS75.41 24375.56 22174.96 30183.59 26657.82 29380.59 28883.87 27666.54 25074.93 23288.31 17963.24 13580.09 33862.16 24476.85 25986.97 282
eth_miper_zixun_eth77.92 20276.69 20981.61 20183.00 28261.98 24783.15 26289.20 18369.52 20774.86 23384.35 27161.76 15992.56 19571.50 16372.89 31090.28 184
GA-MVS76.87 22275.17 23181.97 19482.75 28862.58 23981.44 28186.35 24772.16 16174.74 23482.89 29046.20 30192.02 21768.85 19081.09 21291.30 149
sss73.60 25773.64 24773.51 31282.80 28755.01 32476.12 32281.69 30462.47 29774.68 23585.85 24757.32 20678.11 34560.86 25780.93 21387.39 269
BH-w/o78.21 19277.33 19480.84 22088.81 15965.13 19184.87 22687.85 22269.75 20374.52 23684.74 26861.34 16993.11 17958.24 28085.84 16384.27 318
FMVSNet177.44 21176.12 21881.40 20586.81 21963.01 23488.39 12789.28 17770.49 18974.39 23787.28 20449.06 28391.11 24160.91 25678.52 23990.09 193
cl____77.72 20676.76 20680.58 22582.49 29560.48 26683.09 26387.87 22069.22 21374.38 23885.22 26062.10 15691.53 23171.09 16575.41 28289.73 213
DIV-MVS_self_test77.72 20676.76 20680.58 22582.48 29660.48 26683.09 26387.86 22169.22 21374.38 23885.24 25962.10 15691.53 23171.09 16575.40 28389.74 212
114514_t80.68 13579.51 13984.20 11994.09 4167.27 15289.64 8891.11 13158.75 32674.08 24090.72 11858.10 19795.04 9669.70 18089.42 11790.30 183
WR-MVS_H78.51 18578.49 16178.56 26188.02 18656.38 31488.43 12392.67 6777.14 5673.89 24187.55 19866.25 10589.24 27458.92 27273.55 30490.06 197
tpm273.26 26271.46 26478.63 25983.34 27156.71 30880.65 28780.40 31756.63 33973.55 24282.02 30351.80 25391.24 23956.35 29578.42 24287.95 255
CP-MVSNet78.22 19178.34 16777.84 27187.83 19154.54 32787.94 14591.17 12977.65 3973.48 24388.49 17462.24 15488.43 28762.19 24374.07 29790.55 174
pm-mvs177.25 21676.68 21078.93 25684.22 25558.62 28186.41 18988.36 21071.37 17373.31 24488.01 19061.22 17389.15 27664.24 22873.01 30989.03 229
PS-CasMVS78.01 20078.09 17277.77 27387.71 19654.39 32988.02 14191.22 12677.50 4773.26 24588.64 16960.73 17988.41 28861.88 24773.88 30190.53 175
CVMVSNet72.99 26672.58 25574.25 30884.28 25350.85 35086.41 18983.45 28444.56 35673.23 24687.54 19949.38 27885.70 30865.90 21678.44 24186.19 295
PEN-MVS77.73 20577.69 18677.84 27187.07 21553.91 33287.91 14791.18 12877.56 4473.14 24788.82 16561.23 17289.17 27559.95 26272.37 31290.43 178
1112_ss77.40 21376.43 21480.32 23189.11 15260.41 26883.65 25387.72 22462.13 30073.05 24886.72 22062.58 14789.97 26262.11 24680.80 21690.59 173
tpm72.37 27271.71 26374.35 30782.19 30052.00 34279.22 30277.29 33664.56 27272.95 24983.68 28351.35 25683.26 32658.33 27975.80 27387.81 260
cascas76.72 22474.64 23482.99 16685.78 23165.88 17582.33 27189.21 18260.85 30872.74 25081.02 30947.28 29393.75 14967.48 20185.02 16689.34 220
CR-MVSNet73.37 25971.27 26879.67 24581.32 31465.19 18975.92 32480.30 31859.92 31572.73 25181.19 30652.50 23886.69 30159.84 26377.71 24687.11 280
RPMNet73.51 25870.49 27482.58 18381.32 31465.19 18975.92 32492.27 8357.60 33372.73 25176.45 34352.30 24195.43 7548.14 33377.71 24687.11 280
DTE-MVSNet76.99 21976.80 20477.54 27886.24 22553.06 34087.52 15690.66 13977.08 5972.50 25388.67 16860.48 18589.52 26957.33 28870.74 32390.05 198
Test_1112_low_res76.40 23075.44 22479.27 25189.28 14158.09 28581.69 27787.07 23659.53 31972.48 25486.67 22661.30 17089.33 27260.81 25880.15 22590.41 179
v7n78.97 17677.58 18983.14 15883.45 26965.51 18288.32 13191.21 12773.69 13672.41 25586.32 23957.93 19893.81 14469.18 18575.65 27590.11 191
SCA74.22 25172.33 25879.91 23884.05 25962.17 24579.96 29579.29 32666.30 25272.38 25680.13 31851.95 24988.60 28559.25 26877.67 24888.96 234
CNLPA78.08 19676.79 20581.97 19490.40 10671.07 6987.59 15584.55 26566.03 25672.38 25689.64 14257.56 20386.04 30659.61 26583.35 18788.79 241
NR-MVSNet80.23 14579.38 14382.78 17887.80 19263.34 22686.31 19291.09 13279.01 2772.17 25889.07 15967.20 9692.81 19166.08 21575.65 27592.20 123
OpenMVScopyleft72.83 1079.77 15378.33 16884.09 12385.17 24069.91 9490.57 6290.97 13366.70 24572.17 25891.91 8654.70 22393.96 13361.81 24990.95 9888.41 251
MVS78.19 19476.99 20081.78 19685.66 23266.99 15584.66 23090.47 14455.08 34572.02 26085.27 25863.83 12894.11 13166.10 21489.80 11384.24 319
XVG-ACMP-BASELINE76.11 23474.27 24181.62 19983.20 27564.67 19783.60 25689.75 16669.75 20371.85 26187.09 21332.78 35492.11 21469.99 17780.43 22288.09 254
PatchmatchNetpermissive73.12 26471.33 26778.49 26483.18 27660.85 26079.63 29778.57 32864.13 27771.73 26279.81 32351.20 25885.97 30757.40 28776.36 26988.66 244
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
tpmrst72.39 27072.13 25973.18 31680.54 32249.91 35379.91 29679.08 32763.11 28771.69 26379.95 32055.32 21682.77 32865.66 21973.89 30086.87 283
TransMVSNet (Re)75.39 24474.56 23677.86 27085.50 23657.10 30286.78 17986.09 25172.17 16071.53 26487.34 20363.01 14289.31 27356.84 29261.83 34687.17 276
Fast-Effi-MVS+-dtu78.02 19976.49 21282.62 18283.16 27866.96 15986.94 17287.45 23072.45 15371.49 26584.17 27354.79 22291.58 22967.61 19980.31 22389.30 221
PAPM77.68 20876.40 21581.51 20287.29 21161.85 24983.78 25189.59 17064.74 27071.23 26688.70 16662.59 14693.66 15352.66 30887.03 14589.01 230
tfpnnormal74.39 24873.16 25178.08 26886.10 22758.05 28684.65 23387.53 22770.32 19171.22 26785.63 25154.97 21889.86 26343.03 35075.02 29086.32 292
RPSCF73.23 26371.46 26478.54 26282.50 29459.85 27182.18 27282.84 29458.96 32371.15 26889.41 15445.48 30884.77 31658.82 27471.83 31791.02 159
DWT-MVSNet_test73.70 25671.86 26179.21 25382.91 28558.94 27782.34 27082.17 29865.21 26371.05 26978.31 33244.21 31390.17 26063.29 23577.28 25088.53 248
PatchT68.46 30067.85 29470.29 32880.70 32043.93 36372.47 33774.88 34460.15 31370.55 27076.57 34249.94 27281.59 33150.58 31574.83 29285.34 306
CL-MVSNet_self_test72.37 27271.46 26475.09 30079.49 33653.53 33480.76 28585.01 26169.12 21770.51 27182.05 30257.92 19984.13 31952.27 30966.00 33887.60 264
IterMVS-SCA-FT75.43 24273.87 24580.11 23582.69 29064.85 19481.57 27983.47 28369.16 21670.49 27284.15 27451.95 24988.15 29069.23 18472.14 31587.34 271
miper_lstm_enhance74.11 25273.11 25277.13 28480.11 32659.62 27372.23 33886.92 23966.76 24470.40 27382.92 28956.93 21182.92 32769.06 18772.63 31188.87 237
gg-mvs-nofinetune69.95 28967.96 29275.94 29183.07 27954.51 32877.23 31970.29 35463.11 28770.32 27462.33 35743.62 31688.69 28453.88 30387.76 13384.62 317
DP-MVS76.78 22374.57 23583.42 14493.29 5469.46 10788.55 12283.70 27763.98 28270.20 27588.89 16354.01 23094.80 10746.66 33881.88 20686.01 300
pmmvs674.69 24773.39 24878.61 26081.38 31157.48 29886.64 18387.95 21864.99 26970.18 27686.61 22850.43 26789.52 26962.12 24570.18 32588.83 239
PVSNet64.34 1872.08 27470.87 27375.69 29386.21 22656.44 31274.37 33480.73 31162.06 30170.17 27782.23 30042.86 32083.31 32554.77 30084.45 17487.32 272
131476.53 22575.30 23080.21 23383.93 26162.32 24384.66 23088.81 19760.23 31270.16 27884.07 27555.30 21790.73 25367.37 20283.21 18987.59 266
Patchmtry70.74 28069.16 28275.49 29780.72 31954.07 33174.94 33380.30 31858.34 32770.01 27981.19 30652.50 23886.54 30253.37 30571.09 32285.87 303
EPMVS69.02 29468.16 28971.59 32079.61 33449.80 35577.40 31866.93 36262.82 29370.01 27979.05 32545.79 30477.86 34756.58 29375.26 28887.13 279
IterMVS74.29 24972.94 25378.35 26581.53 30863.49 22281.58 27882.49 29668.06 23569.99 28183.69 28251.66 25585.54 30965.85 21771.64 31886.01 300
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
test-LLR72.94 26772.43 25674.48 30581.35 31258.04 28778.38 30977.46 33366.66 24669.95 28279.00 32748.06 28879.24 33966.13 21284.83 16886.15 296
test-mter71.41 27670.39 27774.48 30581.35 31258.04 28778.38 30977.46 33360.32 31169.95 28279.00 32736.08 34879.24 33966.13 21284.83 16886.15 296
pmmvs474.03 25471.91 26080.39 22881.96 30268.32 13181.45 28082.14 29959.32 32069.87 28485.13 26252.40 24088.13 29160.21 26174.74 29384.73 315
PLCcopyleft70.83 1178.05 19876.37 21683.08 16191.88 8567.80 14188.19 13789.46 17364.33 27669.87 28488.38 17753.66 23293.58 15458.86 27382.73 19687.86 259
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
LTVRE_ROB69.57 1376.25 23274.54 23781.41 20488.60 16864.38 20579.24 30189.12 18870.76 18469.79 28687.86 19149.09 28293.20 17256.21 29680.16 22486.65 289
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
LS3D76.95 22174.82 23383.37 14790.45 10467.36 15189.15 9986.94 23861.87 30269.52 28790.61 12051.71 25494.53 11346.38 34186.71 15088.21 253
IB-MVS68.01 1575.85 23773.36 24983.31 14884.76 24766.03 16983.38 25985.06 25970.21 19469.40 28881.05 30845.76 30594.66 11165.10 22375.49 27889.25 222
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
PatchMatch-RL72.38 27170.90 27176.80 28788.60 16867.38 15079.53 29876.17 34162.75 29469.36 28982.00 30445.51 30784.89 31553.62 30480.58 21978.12 351
MDTV_nov1_ep1369.97 27983.18 27653.48 33577.10 32080.18 32160.45 30969.33 29080.44 31548.89 28686.90 30051.60 31278.51 240
D2MVS74.82 24673.21 25079.64 24679.81 33062.56 24080.34 29187.35 23164.37 27568.86 29182.66 29446.37 29890.10 26167.91 19781.24 21186.25 293
PMMVS69.34 29268.67 28471.35 32475.67 35062.03 24675.17 32873.46 34950.00 35468.68 29279.05 32552.07 24778.13 34461.16 25582.77 19573.90 355
Patchmatch-RL test70.24 28667.78 29777.61 27677.43 34459.57 27571.16 34070.33 35362.94 29168.65 29372.77 35150.62 26485.49 31069.58 18266.58 33687.77 261
MS-PatchMatch73.83 25572.67 25477.30 28183.87 26266.02 17081.82 27484.66 26361.37 30668.61 29482.82 29247.29 29288.21 28959.27 26784.32 17577.68 352
tpm cat170.57 28268.31 28777.35 28082.41 29757.95 29078.08 31380.22 32052.04 35168.54 29577.66 33852.00 24887.84 29451.77 31072.07 31686.25 293
TESTMET0.1,169.89 29069.00 28372.55 31779.27 33956.85 30478.38 30974.71 34757.64 33268.09 29677.19 34037.75 34376.70 35063.92 22984.09 17784.10 322
MIMVSNet70.69 28169.30 28074.88 30284.52 25056.35 31575.87 32679.42 32564.59 27167.76 29782.41 29641.10 33081.54 33246.64 34081.34 20986.75 287
ACMH+68.96 1476.01 23574.01 24282.03 19288.60 16865.31 18888.86 10787.55 22670.25 19367.75 29887.47 20141.27 32993.19 17458.37 27875.94 27287.60 264
LCM-MVSNet-Re77.05 21876.94 20177.36 27987.20 21251.60 34580.06 29380.46 31675.20 10267.69 29986.72 22062.48 14888.98 27963.44 23289.25 11891.51 141
ITE_SJBPF78.22 26681.77 30460.57 26483.30 28569.25 21267.54 30087.20 20936.33 34787.28 29954.34 30174.62 29486.80 285
pmmvs571.55 27570.20 27875.61 29477.83 34256.39 31381.74 27680.89 30857.76 33167.46 30184.49 26949.26 28185.32 31257.08 29075.29 28785.11 311
MVP-Stereo76.12 23374.46 23981.13 21585.37 23869.79 9784.42 24187.95 21865.03 26767.46 30185.33 25753.28 23591.73 22758.01 28283.27 18881.85 338
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
test_040272.79 26870.44 27579.84 24088.13 18165.99 17185.93 20284.29 26965.57 26167.40 30385.49 25446.92 29592.61 19335.88 35974.38 29680.94 343
GG-mvs-BLEND75.38 29881.59 30755.80 32079.32 30069.63 35667.19 30473.67 35043.24 31788.90 28350.41 31684.50 17281.45 340
tpmvs71.09 27869.29 28176.49 28882.04 30156.04 31878.92 30681.37 30764.05 28067.18 30578.28 33349.74 27589.77 26449.67 32472.37 31283.67 324
OurMVSNet-221017-074.26 25072.42 25779.80 24183.76 26459.59 27485.92 20386.64 24166.39 25166.96 30687.58 19639.46 33591.60 22865.76 21869.27 32788.22 252
baseline275.70 23873.83 24681.30 20983.26 27361.79 25182.57 26980.65 31266.81 24266.88 30783.42 28557.86 20092.19 21163.47 23179.57 22989.91 204
MVS_030472.48 26970.89 27277.24 28282.20 29959.68 27284.11 24783.49 28267.10 24166.87 30880.59 31435.00 35187.40 29759.07 27179.58 22884.63 316
F-COLMAP76.38 23174.33 24082.50 18489.28 14166.95 16088.41 12689.03 18964.05 28066.83 30988.61 17046.78 29692.89 18757.48 28578.55 23887.67 262
ACMH67.68 1675.89 23673.93 24381.77 19788.71 16566.61 16288.62 11989.01 19169.81 20066.78 31086.70 22541.95 32891.51 23355.64 29778.14 24487.17 276
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
test0.0.03 168.00 30167.69 29868.90 33377.55 34347.43 35775.70 32772.95 35166.66 24666.56 31182.29 29948.06 28875.87 35444.97 34774.51 29583.41 326
MDTV_nov1_ep13_2view37.79 36875.16 32955.10 34466.53 31249.34 27953.98 30287.94 257
KD-MVS_2432*160066.22 31263.89 31373.21 31375.47 35353.42 33670.76 34384.35 26764.10 27866.52 31378.52 33034.55 35284.98 31350.40 31750.33 36181.23 341
miper_refine_blended66.22 31263.89 31373.21 31375.47 35353.42 33670.76 34384.35 26764.10 27866.52 31378.52 33034.55 35284.98 31350.40 31750.33 36181.23 341
ET-MVSNet_ETH3D78.63 18276.63 21184.64 10386.73 22169.47 10585.01 22384.61 26469.54 20666.51 31586.59 22950.16 26991.75 22576.26 12284.24 17692.69 106
EU-MVSNet68.53 29967.61 29971.31 32578.51 34147.01 35984.47 23684.27 27042.27 35766.44 31684.79 26740.44 33383.76 32158.76 27568.54 33283.17 328
EPNet_dtu75.46 24174.86 23277.23 28382.57 29354.60 32686.89 17483.09 29171.64 16666.25 31785.86 24655.99 21488.04 29254.92 29986.55 15289.05 228
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
Anonymous2023120668.60 29767.80 29671.02 32680.23 32550.75 35178.30 31280.47 31556.79 33866.11 31882.63 29546.35 29978.95 34143.62 34975.70 27483.36 327
SixPastTwentyTwo73.37 25971.26 26979.70 24385.08 24557.89 29185.57 20983.56 28071.03 17865.66 31985.88 24542.10 32692.57 19459.11 27063.34 34488.65 245
MSDG73.36 26170.99 27080.49 22784.51 25165.80 17680.71 28686.13 25065.70 25965.46 32083.74 28144.60 31090.91 24951.13 31476.89 25784.74 314
OpenMVS_ROBcopyleft64.09 1970.56 28368.19 28877.65 27580.26 32459.41 27685.01 22382.96 29358.76 32565.43 32182.33 29737.63 34491.23 24045.34 34676.03 27182.32 335
ppachtmachnet_test70.04 28867.34 30178.14 26779.80 33161.13 25679.19 30380.59 31359.16 32265.27 32279.29 32446.75 29787.29 29849.33 32566.72 33486.00 302
ADS-MVSNet266.20 31463.33 31674.82 30379.92 32858.75 28067.55 35375.19 34353.37 34865.25 32375.86 34442.32 32380.53 33741.57 35368.91 32985.18 308
ADS-MVSNet64.36 31862.88 32068.78 33579.92 32847.17 35867.55 35371.18 35253.37 34865.25 32375.86 34442.32 32373.99 36141.57 35368.91 32985.18 308
testgi66.67 30866.53 30667.08 33975.62 35141.69 36675.93 32376.50 34066.11 25365.20 32586.59 22935.72 34974.71 35843.71 34873.38 30784.84 313
PM-MVS66.41 31064.14 31273.20 31573.92 35756.45 31178.97 30564.96 36663.88 28464.72 32680.24 31719.84 36683.44 32466.24 21164.52 34279.71 348
JIA-IIPM66.32 31162.82 32176.82 28677.09 34661.72 25265.34 35675.38 34258.04 33064.51 32762.32 35842.05 32786.51 30351.45 31369.22 32882.21 336
ambc75.24 29973.16 36150.51 35263.05 36087.47 22964.28 32877.81 33717.80 36789.73 26657.88 28360.64 34985.49 304
EG-PatchMatch MVS74.04 25371.82 26280.71 22384.92 24667.42 14885.86 20588.08 21566.04 25564.22 32983.85 27735.10 35092.56 19557.44 28680.83 21582.16 337
dp66.80 30665.43 30870.90 32779.74 33348.82 35675.12 33174.77 34559.61 31764.08 33077.23 33942.89 31980.72 33648.86 32766.58 33683.16 329
KD-MVS_self_test68.81 29567.59 30072.46 31874.29 35645.45 36077.93 31587.00 23763.12 28663.99 33178.99 32942.32 32384.77 31656.55 29464.09 34387.16 278
pmmvs-eth3d70.50 28467.83 29578.52 26377.37 34566.18 16881.82 27481.51 30558.90 32463.90 33280.42 31642.69 32186.28 30558.56 27665.30 34083.11 330
COLMAP_ROBcopyleft66.92 1773.01 26570.41 27680.81 22187.13 21465.63 18088.30 13284.19 27262.96 29063.80 33387.69 19438.04 34292.56 19546.66 33874.91 29184.24 319
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
FMVSNet569.50 29167.96 29274.15 30982.97 28455.35 32380.01 29482.12 30062.56 29663.02 33481.53 30536.92 34581.92 33048.42 32874.06 29885.17 310
test20.0367.45 30366.95 30468.94 33275.48 35244.84 36277.50 31777.67 33266.66 24663.01 33583.80 27947.02 29478.40 34342.53 35268.86 33183.58 325
K. test v371.19 27768.51 28579.21 25383.04 28157.78 29484.35 24376.91 33972.90 15262.99 33682.86 29139.27 33691.09 24661.65 25052.66 35888.75 242
our_test_369.14 29367.00 30375.57 29579.80 33158.80 27977.96 31477.81 33159.55 31862.90 33778.25 33447.43 29183.97 32051.71 31167.58 33383.93 323
CHOSEN 280x42066.51 30964.71 31071.90 31981.45 30963.52 22157.98 36168.95 36053.57 34762.59 33876.70 34146.22 30075.29 35755.25 29879.68 22776.88 354
Anonymous2024052168.80 29667.22 30273.55 31174.33 35554.11 33083.18 26185.61 25458.15 32861.68 33980.94 31130.71 35881.27 33457.00 29173.34 30885.28 307
USDC70.33 28568.37 28676.21 29080.60 32156.23 31679.19 30386.49 24360.89 30761.29 34085.47 25531.78 35789.47 27153.37 30576.21 27082.94 334
lessismore_v078.97 25581.01 31857.15 30165.99 36361.16 34182.82 29239.12 33791.34 23759.67 26446.92 36388.43 250
UnsupCasMVSNet_eth67.33 30465.99 30771.37 32273.48 35951.47 34775.16 32985.19 25865.20 26460.78 34280.93 31342.35 32277.20 34957.12 28953.69 35785.44 305
AllTest70.96 27968.09 29179.58 24785.15 24163.62 21684.58 23579.83 32262.31 29860.32 34386.73 21832.02 35588.96 28150.28 31971.57 31986.15 296
TestCases79.58 24785.15 24163.62 21679.83 32262.31 29860.32 34386.73 21832.02 35588.96 28150.28 31971.57 31986.15 296
Patchmatch-test64.82 31763.24 31769.57 33079.42 33749.82 35463.49 35969.05 35951.98 35259.95 34580.13 31850.91 26070.98 36340.66 35573.57 30387.90 258
MIMVSNet168.58 29866.78 30573.98 31080.07 32751.82 34380.77 28484.37 26664.40 27459.75 34682.16 30136.47 34683.63 32342.73 35170.33 32486.48 291
LF4IMVS64.02 31962.19 32269.50 33170.90 36453.29 33976.13 32177.18 33752.65 35058.59 34780.98 31023.55 36376.52 35153.06 30766.66 33578.68 350
PVSNet_057.27 2061.67 32259.27 32568.85 33479.61 33457.44 29968.01 35273.44 35055.93 34258.54 34870.41 35444.58 31177.55 34847.01 33735.91 36471.55 357
TDRefinement67.49 30264.34 31176.92 28573.47 36061.07 25784.86 22782.98 29259.77 31658.30 34985.13 26226.06 36087.89 29347.92 33560.59 35081.81 339
UnsupCasMVSNet_bld63.70 32061.53 32470.21 32973.69 35851.39 34872.82 33681.89 30155.63 34357.81 35071.80 35338.67 33878.61 34249.26 32652.21 35980.63 344
DSMNet-mixed57.77 32556.90 32760.38 34367.70 36635.61 36969.18 34853.97 37132.30 36657.49 35179.88 32140.39 33468.57 36538.78 35772.37 31276.97 353
N_pmnet52.79 32853.26 32951.40 34878.99 3407.68 37969.52 3463.89 37951.63 35357.01 35274.98 34840.83 33265.96 36637.78 35864.67 34180.56 346
new-patchmatchnet61.73 32161.73 32361.70 34272.74 36324.50 37669.16 34978.03 33061.40 30456.72 35375.53 34738.42 33976.48 35245.95 34357.67 35284.13 321
CMPMVSbinary51.72 2170.19 28768.16 28976.28 28973.15 36257.55 29779.47 29983.92 27448.02 35556.48 35484.81 26643.13 31886.42 30462.67 24081.81 20784.89 312
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
TinyColmap67.30 30564.81 30974.76 30481.92 30356.68 30980.29 29281.49 30660.33 31056.27 35583.22 28724.77 36187.66 29645.52 34469.47 32679.95 347
YYNet165.03 31562.91 31971.38 32175.85 34956.60 31069.12 35074.66 34857.28 33654.12 35677.87 33645.85 30374.48 35949.95 32261.52 34883.05 331
MDA-MVSNet_test_wron65.03 31562.92 31871.37 32275.93 34856.73 30669.09 35174.73 34657.28 33654.03 35777.89 33545.88 30274.39 36049.89 32361.55 34782.99 333
pmmvs357.79 32454.26 32868.37 33664.02 36856.72 30775.12 33165.17 36440.20 35952.93 35869.86 35520.36 36575.48 35645.45 34555.25 35672.90 356
MVS-HIRNet59.14 32357.67 32663.57 34181.65 30543.50 36471.73 33965.06 36539.59 36151.43 35957.73 36138.34 34082.58 32939.53 35673.95 29964.62 360
MDA-MVSNet-bldmvs66.68 30763.66 31575.75 29279.28 33860.56 26573.92 33578.35 32964.43 27350.13 36079.87 32244.02 31583.67 32246.10 34256.86 35383.03 332
new_pmnet50.91 33050.29 33152.78 34768.58 36534.94 37163.71 35856.63 37039.73 36044.95 36165.47 35621.93 36458.48 36734.98 36056.62 35464.92 359
FPMVS53.68 32751.64 33059.81 34465.08 36751.03 34969.48 34769.58 35741.46 35840.67 36272.32 35216.46 36970.00 36424.24 36665.42 33958.40 363
LCM-MVSNet54.25 32649.68 33267.97 33753.73 37145.28 36166.85 35580.78 31035.96 36339.45 36362.23 3598.70 37578.06 34648.24 33251.20 36080.57 345
PMMVS240.82 33438.86 33746.69 34953.84 37016.45 37748.61 36449.92 37237.49 36231.67 36460.97 3608.14 37656.42 36828.42 36330.72 36667.19 358
ANet_high50.57 33146.10 33463.99 34048.67 37439.13 36770.99 34280.85 30961.39 30531.18 36557.70 36217.02 36873.65 36231.22 36115.89 37179.18 349
Gipumacopyleft45.18 33241.86 33555.16 34677.03 34751.52 34632.50 36780.52 31432.46 36527.12 36635.02 3679.52 37475.50 35522.31 36760.21 35138.45 366
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
PMVScopyleft37.38 2244.16 33340.28 33655.82 34540.82 37642.54 36565.12 35763.99 36734.43 36424.48 36757.12 3633.92 37776.17 35317.10 36955.52 35548.75 364
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
DeepMVS_CXcopyleft27.40 35440.17 37726.90 37424.59 37817.44 37023.95 36848.61 3659.77 37326.48 37318.06 36824.47 36728.83 367
tmp_tt18.61 34021.40 34310.23 3564.82 37910.11 37834.70 36630.74 3771.48 37323.91 36926.07 37028.42 35913.41 37527.12 36415.35 3727.17 370
test_method31.52 33629.28 34038.23 35127.03 3786.50 38020.94 36962.21 3694.05 37222.35 37052.50 36413.33 37047.58 37127.04 36534.04 36560.62 361
MVEpermissive26.22 2330.37 33825.89 34243.81 35044.55 37535.46 37028.87 36839.07 37518.20 36918.58 37140.18 3662.68 37847.37 37217.07 37023.78 36848.60 365
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
E-PMN31.77 33530.64 33835.15 35252.87 37227.67 37357.09 36247.86 37324.64 36716.40 37233.05 36811.23 37254.90 36914.46 37118.15 36922.87 368
EMVS30.81 33729.65 33934.27 35350.96 37325.95 37556.58 36346.80 37424.01 36815.53 37330.68 36912.47 37154.43 37012.81 37217.05 37022.43 369
wuyk23d16.82 34115.94 34419.46 35558.74 36931.45 37239.22 3653.74 3806.84 3716.04 3742.70 3741.27 37924.29 37410.54 37314.40 3732.63 371
EGC-MVSNET52.07 32947.05 33367.14 33883.51 26860.71 26280.50 28967.75 3610.07 3740.43 37575.85 34624.26 36281.54 33228.82 36262.25 34559.16 362
testmvs6.04 3448.02 3470.10 3580.08 3800.03 38269.74 3450.04 3810.05 3750.31 3761.68 3750.02 3810.04 3760.24 3740.02 3740.25 373
test1236.12 3438.11 3460.14 3570.06 3810.09 38171.05 3410.03 3820.04 3760.25 3771.30 3760.05 3800.03 3770.21 3750.01 3750.29 372
test_blank0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
uanet_test0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
cdsmvs_eth3d_5k19.96 33926.61 3410.00 3590.00 3820.00 3830.00 37089.26 1800.00 3770.00 37888.61 17061.62 1620.00 3780.00 3760.00 3760.00 374
pcd_1.5k_mvsjas5.26 3457.02 3480.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 37763.15 1380.00 3780.00 3760.00 3760.00 374
sosnet-low-res0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
sosnet0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
uncertanet0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
Regformer0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
ab-mvs-re7.23 3429.64 3450.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 37886.72 2200.00 3820.00 3780.00 3760.00 3760.00 374
uanet0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
MSC_two_6792asdad89.16 194.34 2975.53 292.99 4997.53 189.67 196.44 994.41 29
No_MVS89.16 194.34 2975.53 292.99 4997.53 189.67 196.44 994.41 29
eth-test20.00 382
eth-test0.00 382
OPU-MVS89.06 394.62 1575.42 493.57 794.02 4782.45 396.87 1983.77 5396.48 894.88 9
save fliter93.80 4472.35 4590.47 6691.17 12974.31 122
test_0728_SECOND87.71 3495.34 171.43 6293.49 994.23 597.49 389.08 796.41 1294.21 39
GSMVS88.96 234
sam_mvs151.32 25788.96 234
sam_mvs50.01 270
MTGPAbinary92.02 94
test_post178.90 3075.43 37348.81 28785.44 31159.25 268
test_post5.46 37250.36 26884.24 318
patchmatchnet-post74.00 34951.12 25988.60 285
MTMP92.18 3332.83 376
gm-plane-assit81.40 31053.83 33362.72 29580.94 31192.39 20163.40 233
test9_res84.90 3395.70 3192.87 101
agg_prior282.91 6395.45 3392.70 104
test_prior472.60 3589.01 102
test_prior86.33 6392.61 7469.59 10192.97 5495.48 7193.91 52
新几何286.29 194
旧先验191.96 8265.79 17786.37 24693.08 6969.31 7992.74 7588.74 243
无先验87.48 15788.98 19260.00 31494.12 12967.28 20388.97 233
原ACMM286.86 175
testdata291.01 24862.37 242
segment_acmp73.08 43
testdata184.14 24675.71 90
plane_prior790.08 11268.51 129
plane_prior689.84 12068.70 12460.42 186
plane_prior592.44 7595.38 8078.71 9786.32 15591.33 147
plane_prior491.00 114
plane_prior291.25 4979.12 24
plane_prior189.90 119
plane_prior68.71 12290.38 7077.62 4086.16 158
n20.00 383
nn0.00 383
door-mid69.98 355
test1192.23 86
door69.44 358
HQP5-MVS66.98 156
BP-MVS77.47 111
HQP3-MVS92.19 8985.99 161
HQP2-MVS60.17 189
NP-MVS89.62 12268.32 13190.24 125
ACMMP++_ref81.95 205
ACMMP++81.25 210
Test By Simon64.33 123