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.
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MM89.16 689.23 788.97 490.79 9573.65 1092.66 2391.17 12986.57 187.39 4994.97 1971.70 5597.68 192.19 195.63 2895.57 1
casdiffmvs_mvgpermissive85.99 5186.09 5485.70 7487.65 21267.22 16488.69 13193.04 4179.64 2085.33 6792.54 9573.30 3594.50 11383.49 7491.14 9895.37 2
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
dcpmvs_285.63 6186.15 5284.06 13991.71 7864.94 21386.47 20891.87 10573.63 15386.60 5893.02 8476.57 1591.87 23383.36 7592.15 8195.35 3
casdiffmvspermissive85.11 7385.14 7385.01 9387.20 22765.77 19187.75 16592.83 6077.84 4084.36 8892.38 9772.15 4893.93 13781.27 9990.48 10895.33 4
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
3Dnovator+77.84 485.48 6484.47 8288.51 791.08 8673.49 1693.18 1193.78 1880.79 876.66 21793.37 7460.40 20596.75 2677.20 13893.73 6495.29 5
BP-MVS184.32 8183.71 9086.17 6187.84 20167.85 14189.38 9989.64 17977.73 4283.98 9592.12 10256.89 23095.43 7084.03 7191.75 8895.24 6
MVS_030487.69 2087.55 2488.12 1389.45 13071.76 5191.47 4989.54 18282.14 386.65 5794.28 3868.28 10197.46 690.81 595.31 3495.15 7
CS-MVS86.69 3986.95 3785.90 7190.76 9667.57 15092.83 1793.30 3279.67 1884.57 8492.27 9871.47 5895.02 9384.24 6893.46 6795.13 8
TSAR-MVS + MP.88.02 1788.11 1687.72 3093.68 4372.13 4691.41 5092.35 8274.62 12888.90 2493.85 6275.75 2096.00 5487.80 3694.63 4895.04 9
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
baseline84.93 7684.98 7484.80 10387.30 22565.39 20087.30 17992.88 5777.62 4484.04 9492.26 9971.81 5293.96 13181.31 9790.30 11195.03 10
DVP-MVS++90.23 191.01 187.89 2494.34 2771.25 5995.06 194.23 378.38 3592.78 495.74 682.45 397.49 489.42 1696.68 294.95 11
PC_three_145268.21 27292.02 1294.00 5482.09 595.98 5684.58 6296.68 294.95 11
IS-MVSNet83.15 10782.81 10584.18 12989.94 11663.30 25191.59 4388.46 22479.04 2779.49 15792.16 10065.10 13594.28 11867.71 23491.86 8794.95 11
SteuartSystems-ACMMP88.72 1188.86 1188.32 992.14 7272.96 2593.73 593.67 2080.19 1288.10 3494.80 2173.76 3397.11 1587.51 3995.82 2194.90 14
Skip Steuart: Steuart Systems R&D Blog.
SED-MVS90.08 290.85 287.77 2695.30 270.98 6693.57 794.06 1077.24 5793.10 195.72 882.99 197.44 789.07 2196.63 494.88 15
OPU-MVS89.06 394.62 1575.42 493.57 794.02 5282.45 396.87 2083.77 7396.48 894.88 15
SMA-MVScopyleft89.08 889.23 788.61 694.25 3173.73 992.40 2493.63 2174.77 12492.29 795.97 274.28 2997.24 1388.58 2996.91 194.87 17
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
test250677.30 24276.49 23979.74 26890.08 10952.02 38687.86 16463.10 42874.88 12080.16 15092.79 9138.29 39292.35 21468.74 22792.50 7894.86 18
ECVR-MVScopyleft79.61 17979.26 17280.67 24890.08 10954.69 36987.89 16277.44 38174.88 12080.27 14792.79 9148.96 31992.45 20868.55 22892.50 7894.86 18
IU-MVS95.30 271.25 5992.95 5566.81 28392.39 688.94 2496.63 494.85 20
test111179.43 18679.18 17580.15 26089.99 11453.31 38287.33 17877.05 38575.04 11480.23 14992.77 9348.97 31892.33 21668.87 22592.40 8094.81 21
SF-MVS88.46 1288.74 1287.64 3592.78 6471.95 4992.40 2494.74 275.71 9689.16 2195.10 1675.65 2196.19 4687.07 4296.01 1794.79 22
balanced_conf0386.78 3786.99 3586.15 6391.24 8367.61 14890.51 6292.90 5677.26 5687.44 4891.63 11571.27 6296.06 4985.62 5195.01 3794.78 23
sasdasda85.91 5585.87 5886.04 6789.84 11869.44 9890.45 6893.00 4676.70 7688.01 3791.23 12773.28 3693.91 13881.50 9588.80 13694.77 24
SPE-MVS-test86.29 4886.48 4385.71 7391.02 8867.21 16592.36 2993.78 1878.97 3083.51 10591.20 13070.65 7195.15 8481.96 9294.89 4294.77 24
canonicalmvs85.91 5585.87 5886.04 6789.84 11869.44 9890.45 6893.00 4676.70 7688.01 3791.23 12773.28 3693.91 13881.50 9588.80 13694.77 24
GDP-MVS83.52 9782.64 10886.16 6288.14 18568.45 12589.13 11192.69 6572.82 17683.71 10091.86 10855.69 23795.35 7980.03 11089.74 12394.69 27
test_0728_THIRD78.38 3592.12 995.78 481.46 797.40 989.42 1696.57 794.67 28
MSP-MVS89.51 489.91 588.30 1094.28 3073.46 1792.90 1694.11 680.27 1091.35 1494.16 4578.35 1396.77 2489.59 1494.22 6094.67 28
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
RRT-MVS82.60 11882.10 11784.10 13187.98 19562.94 26287.45 17491.27 12577.42 5379.85 15290.28 15156.62 23394.70 10879.87 11388.15 14994.67 28
MGCFI-Net85.06 7585.51 6583.70 15689.42 13163.01 25789.43 9492.62 7376.43 8087.53 4591.34 12572.82 4493.42 16481.28 9888.74 13994.66 31
alignmvs85.48 6485.32 7085.96 7089.51 12769.47 9589.74 8392.47 7676.17 8987.73 4491.46 12270.32 7393.78 14481.51 9488.95 13394.63 32
MP-MVS-pluss87.67 2187.72 2087.54 3693.64 4472.04 4889.80 8193.50 2575.17 11386.34 5995.29 1570.86 6796.00 5488.78 2796.04 1694.58 33
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
DeepPCF-MVS80.84 188.10 1388.56 1386.73 5392.24 7169.03 10389.57 9093.39 3077.53 5089.79 1994.12 4778.98 1296.58 3585.66 4995.72 2494.58 33
VDD-MVS83.01 11282.36 11384.96 9591.02 8866.40 17588.91 11888.11 22777.57 4684.39 8793.29 7652.19 27193.91 13877.05 14188.70 14094.57 35
KinetiMVS83.31 10582.61 10985.39 8187.08 23167.56 15188.06 15491.65 11377.80 4182.21 11991.79 10957.27 22594.07 12977.77 13289.89 12194.56 36
VDDNet81.52 13680.67 13884.05 14290.44 10164.13 23189.73 8485.91 27671.11 20483.18 10793.48 6950.54 29793.49 15873.40 18088.25 14794.54 37
MVSMamba_PlusPlus85.99 5185.96 5686.05 6691.09 8567.64 14789.63 8892.65 7072.89 17584.64 8191.71 11171.85 5196.03 5084.77 6094.45 5494.49 38
APDe-MVScopyleft89.15 789.63 687.73 2894.49 1871.69 5293.83 493.96 1375.70 9891.06 1696.03 176.84 1497.03 1789.09 1895.65 2794.47 39
Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition
MSC_two_6792asdad89.16 194.34 2775.53 292.99 4997.53 289.67 1296.44 994.41 40
No_MVS89.16 194.34 2775.53 292.99 4997.53 289.67 1296.44 994.41 40
MCST-MVS87.37 2987.25 3087.73 2894.53 1772.46 3889.82 7993.82 1673.07 17084.86 7692.89 8676.22 1796.33 4184.89 5795.13 3694.40 42
fmvsm_s_conf0.5_n_886.56 4287.17 3384.73 10587.76 20865.62 19489.20 10492.21 8979.94 1689.74 2094.86 2068.63 9694.20 12390.83 491.39 9494.38 43
CANet86.45 4386.10 5387.51 3790.09 10870.94 7089.70 8592.59 7481.78 481.32 13291.43 12370.34 7297.23 1484.26 6693.36 6894.37 44
PHI-MVS86.43 4486.17 5187.24 4190.88 9270.96 6892.27 3294.07 972.45 17885.22 6991.90 10569.47 8396.42 4083.28 7795.94 1994.35 45
CNVR-MVS88.93 1089.13 1088.33 894.77 1273.82 890.51 6293.00 4680.90 788.06 3594.06 5076.43 1696.84 2188.48 3295.99 1894.34 46
ZNCC-MVS87.94 1887.85 1988.20 1294.39 2473.33 1993.03 1493.81 1776.81 7085.24 6894.32 3771.76 5396.93 1985.53 5295.79 2294.32 47
HPM-MVScopyleft87.11 3386.98 3687.50 3893.88 3972.16 4592.19 3393.33 3176.07 9183.81 9993.95 5969.77 8096.01 5385.15 5394.66 4794.32 47
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
CDPH-MVS85.76 5985.29 7287.17 4393.49 4771.08 6488.58 13592.42 8068.32 27184.61 8293.48 6972.32 4696.15 4879.00 11795.43 3094.28 49
test_241102_TWO94.06 1077.24 5792.78 495.72 881.26 897.44 789.07 2196.58 694.26 50
test_0728_SECOND87.71 3295.34 171.43 5893.49 994.23 397.49 489.08 1996.41 1294.21 51
fmvsm_l_conf0.5_n_386.02 4986.32 4585.14 8787.20 22768.54 12389.57 9090.44 14975.31 10787.49 4694.39 3572.86 4292.72 19689.04 2390.56 10794.16 52
DeepC-MVS_fast79.65 386.91 3686.62 4287.76 2793.52 4672.37 4191.26 5193.04 4176.62 7884.22 8993.36 7571.44 5996.76 2580.82 10395.33 3394.16 52
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
EPP-MVSNet83.40 10183.02 10184.57 10890.13 10764.47 22492.32 3090.73 14174.45 13279.35 15991.10 13369.05 9195.12 8572.78 18787.22 16194.13 54
NCCC88.06 1488.01 1888.24 1194.41 2273.62 1191.22 5492.83 6081.50 585.79 6393.47 7173.02 4197.00 1884.90 5594.94 4094.10 55
ACMMP_NAP88.05 1688.08 1787.94 1993.70 4173.05 2290.86 5793.59 2376.27 8888.14 3395.09 1771.06 6596.67 2987.67 3796.37 1494.09 56
XVS87.18 3286.91 3988.00 1794.42 2073.33 1992.78 1892.99 4979.14 2383.67 10294.17 4467.45 10996.60 3383.06 7894.50 5194.07 57
X-MVStestdata80.37 16877.83 20588.00 1794.42 2073.33 1992.78 1892.99 4979.14 2383.67 10212.47 44267.45 10996.60 3383.06 7894.50 5194.07 57
region2R87.42 2787.20 3288.09 1494.63 1473.55 1393.03 1493.12 4076.73 7584.45 8594.52 2569.09 8896.70 2784.37 6594.83 4594.03 59
fmvsm_s_conf0.5_n_485.39 6885.75 6184.30 12086.70 24065.83 18788.77 12589.78 17275.46 10288.35 2893.73 6569.19 8793.06 18591.30 288.44 14594.02 60
ACMMPR87.44 2587.23 3188.08 1594.64 1373.59 1293.04 1293.20 3476.78 7284.66 8094.52 2568.81 9496.65 3084.53 6394.90 4194.00 61
fmvsm_s_conf0.1_n_283.80 8883.79 8983.83 15285.62 26364.94 21387.03 18686.62 26574.32 13487.97 3994.33 3660.67 19792.60 19989.72 1187.79 15293.96 62
test_fmvsmconf_n85.92 5486.04 5585.57 7785.03 28169.51 9389.62 8990.58 14473.42 16187.75 4294.02 5272.85 4393.24 16990.37 690.75 10493.96 62
DPE-MVScopyleft89.48 589.98 488.01 1694.80 1172.69 3191.59 4394.10 875.90 9492.29 795.66 1081.67 697.38 1187.44 4196.34 1593.95 64
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
test_fmvsm_n_192085.29 7085.34 6885.13 9086.12 25269.93 8688.65 13390.78 14069.97 23288.27 3093.98 5771.39 6091.54 24788.49 3190.45 10993.91 65
test_prior86.33 5792.61 6869.59 9192.97 5495.48 6793.91 65
GST-MVS87.42 2787.26 2987.89 2494.12 3672.97 2492.39 2693.43 2876.89 6884.68 7793.99 5670.67 7096.82 2284.18 7095.01 3793.90 67
test_fmvsmconf0.1_n85.61 6285.65 6285.50 7882.99 33069.39 10089.65 8690.29 15873.31 16487.77 4194.15 4671.72 5493.23 17090.31 790.67 10693.89 68
Anonymous20240521178.25 21577.01 22581.99 21491.03 8760.67 29184.77 25383.90 30270.65 21780.00 15191.20 13041.08 37791.43 25465.21 25685.26 19093.85 69
LFMVS81.82 12881.23 12983.57 16191.89 7663.43 24989.84 7881.85 33577.04 6583.21 10693.10 7952.26 27093.43 16371.98 19389.95 11993.85 69
fmvsm_s_conf0.5_n_284.04 8484.11 8583.81 15486.17 25065.00 21186.96 18987.28 24974.35 13388.25 3194.23 4261.82 17392.60 19989.85 988.09 15093.84 71
Effi-MVS+83.62 9583.08 9985.24 8588.38 17667.45 15388.89 11989.15 19975.50 10182.27 11788.28 20669.61 8294.45 11577.81 13187.84 15193.84 71
Anonymous2024052980.19 17278.89 18084.10 13190.60 9764.75 21888.95 11790.90 13665.97 30080.59 14491.17 13249.97 30393.73 15069.16 22282.70 23593.81 73
MVS_Test83.15 10783.06 10083.41 16686.86 23463.21 25386.11 22092.00 9774.31 13582.87 11189.44 17870.03 7693.21 17277.39 13788.50 14493.81 73
StellarMVS81.53 13580.16 15085.62 7585.51 26668.25 13188.84 12392.19 9171.31 19980.50 14589.83 16146.89 33094.82 10176.85 14389.57 12593.80 75
test_fmvsmconf0.01_n84.73 7984.52 8185.34 8280.25 37169.03 10389.47 9289.65 17873.24 16886.98 5494.27 3966.62 11693.23 17090.26 889.95 11993.78 76
GeoE81.71 13081.01 13483.80 15589.51 12764.45 22588.97 11688.73 21971.27 20178.63 17189.76 16366.32 12293.20 17569.89 21486.02 18293.74 77
diffmvspermissive82.10 12181.88 12382.76 20183.00 32863.78 23983.68 27989.76 17472.94 17382.02 12289.85 16065.96 12990.79 27282.38 9087.30 16093.71 78
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
HFP-MVS87.58 2287.47 2687.94 1994.58 1673.54 1593.04 1293.24 3376.78 7284.91 7394.44 3270.78 6896.61 3284.53 6394.89 4293.66 79
VNet82.21 12082.41 11181.62 22090.82 9360.93 28684.47 26289.78 17276.36 8684.07 9391.88 10664.71 13990.26 27970.68 20588.89 13493.66 79
PGM-MVS86.68 4086.27 4787.90 2294.22 3373.38 1890.22 7393.04 4175.53 10083.86 9794.42 3367.87 10696.64 3182.70 8894.57 5093.66 79
DELS-MVS85.41 6785.30 7185.77 7288.49 17067.93 14085.52 24093.44 2778.70 3183.63 10489.03 18574.57 2495.71 6180.26 10994.04 6193.66 79
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
SD-MVS88.06 1488.50 1486.71 5492.60 6972.71 2991.81 4193.19 3577.87 3990.32 1794.00 5474.83 2393.78 14487.63 3894.27 5993.65 83
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
DeepC-MVS79.81 287.08 3586.88 4087.69 3391.16 8472.32 4390.31 7193.94 1477.12 6282.82 11394.23 4272.13 4997.09 1684.83 5895.37 3193.65 83
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
patch_mono-283.65 9284.54 7980.99 24090.06 11365.83 18784.21 27188.74 21871.60 19485.01 7092.44 9674.51 2583.50 36582.15 9192.15 8193.64 85
EIA-MVS83.31 10582.80 10684.82 10189.59 12365.59 19588.21 14892.68 6674.66 12778.96 16386.42 26369.06 9095.26 8075.54 15990.09 11593.62 86
MP-MVScopyleft87.71 1987.64 2187.93 2194.36 2673.88 692.71 2292.65 7077.57 4683.84 9894.40 3472.24 4796.28 4385.65 5095.30 3593.62 86
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
HPM-MVS_fast85.35 6984.95 7686.57 5693.69 4270.58 7892.15 3591.62 11573.89 14782.67 11694.09 4862.60 15995.54 6580.93 10192.93 7193.57 88
fmvsm_s_conf0.1_n83.56 9683.38 9584.10 13184.86 28367.28 16089.40 9883.01 31970.67 21387.08 5293.96 5868.38 9991.45 25388.56 3084.50 19893.56 89
CSCG86.41 4686.19 5087.07 4592.91 6172.48 3790.81 5893.56 2473.95 14483.16 10891.07 13575.94 1895.19 8279.94 11294.38 5693.55 90
test1286.80 5292.63 6770.70 7591.79 10982.71 11571.67 5696.16 4794.50 5193.54 91
APD-MVS_3200maxsize85.97 5385.88 5786.22 6092.69 6669.53 9291.93 3792.99 4973.54 15785.94 6094.51 2865.80 13095.61 6283.04 8092.51 7793.53 92
mvs_anonymous79.42 18779.11 17680.34 25584.45 29457.97 32182.59 30087.62 24267.40 28176.17 23388.56 19968.47 9889.59 29270.65 20686.05 18193.47 93
fmvsm_s_conf0.5_n83.80 8883.71 9084.07 13786.69 24167.31 15989.46 9383.07 31871.09 20586.96 5593.70 6669.02 9391.47 25288.79 2684.62 19793.44 94
fmvsm_s_conf0.5_n_585.22 7185.55 6484.25 12786.26 24767.40 15689.18 10589.31 19072.50 17788.31 2993.86 6169.66 8191.96 22789.81 1091.05 9993.38 95
mPP-MVS86.67 4186.32 4587.72 3094.41 2273.55 1392.74 2092.22 8876.87 6982.81 11494.25 4166.44 12096.24 4482.88 8394.28 5893.38 95
EPNet83.72 9182.92 10486.14 6584.22 29769.48 9491.05 5685.27 28381.30 676.83 21291.65 11366.09 12595.56 6376.00 15393.85 6293.38 95
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
Vis-MVSNetpermissive83.46 9982.80 10685.43 8090.25 10568.74 11490.30 7290.13 16376.33 8780.87 14092.89 8661.00 19294.20 12372.45 19290.97 10193.35 98
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
DVP-MVScopyleft89.60 390.35 387.33 4095.27 571.25 5993.49 992.73 6477.33 5492.12 995.78 480.98 997.40 989.08 1996.41 1293.33 99
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
UniMVSNet_ETH3D79.10 19678.24 19481.70 21986.85 23560.24 29887.28 18088.79 21374.25 13876.84 21190.53 14949.48 30991.56 24567.98 23282.15 23993.29 100
EI-MVSNet-Vis-set84.19 8283.81 8885.31 8388.18 18267.85 14187.66 16789.73 17680.05 1482.95 10989.59 17070.74 6994.82 10180.66 10684.72 19593.28 101
MTAPA87.23 3187.00 3487.90 2294.18 3574.25 586.58 20592.02 9579.45 2185.88 6194.80 2168.07 10296.21 4586.69 4495.34 3293.23 102
CP-MVS87.11 3386.92 3887.68 3494.20 3473.86 793.98 392.82 6376.62 7883.68 10194.46 2967.93 10495.95 5784.20 6994.39 5593.23 102
ACMMPcopyleft85.89 5785.39 6787.38 3993.59 4572.63 3392.74 2093.18 3976.78 7280.73 14393.82 6364.33 14096.29 4282.67 8990.69 10593.23 102
Qingshan Xu, Weihang Kong, Wenbing Tao, Marc Pollefeys: Multi-Scale Geometric Consistency Guided and Planar Prior Assisted Multi-View Stereo. IEEE Transactions on Pattern Analysis and Machine Intelligence
fmvsm_s_conf0.1_n_a83.32 10482.99 10284.28 12283.79 30768.07 13689.34 10182.85 32469.80 23687.36 5094.06 5068.34 10091.56 24587.95 3583.46 22493.21 105
fmvsm_s_conf0.5_n_685.55 6386.20 4883.60 15887.32 22465.13 20688.86 12091.63 11475.41 10388.23 3293.45 7268.56 9792.47 20789.52 1592.78 7393.20 106
PAPM_NR83.02 11182.41 11184.82 10192.47 7066.37 17687.93 16091.80 10873.82 14877.32 20090.66 14567.90 10594.90 9770.37 20889.48 12793.19 107
reproduce_model87.28 3087.39 2886.95 4893.10 5671.24 6391.60 4293.19 3574.69 12588.80 2595.61 1170.29 7496.44 3986.20 4893.08 6993.16 108
OMC-MVS82.69 11481.97 12284.85 10088.75 16267.42 15487.98 15690.87 13874.92 11979.72 15491.65 11362.19 16993.96 13175.26 16386.42 17493.16 108
fmvsm_s_conf0.5_n_a83.63 9483.41 9484.28 12286.14 25168.12 13489.43 9482.87 32370.27 22587.27 5193.80 6469.09 8891.58 24288.21 3483.65 21893.14 110
PAPR81.66 13380.89 13683.99 14790.27 10464.00 23286.76 20091.77 11168.84 26277.13 21089.50 17167.63 10794.88 9967.55 23688.52 14393.09 111
UA-Net85.08 7484.96 7585.45 7992.07 7368.07 13689.78 8290.86 13982.48 284.60 8393.20 7869.35 8495.22 8171.39 19890.88 10393.07 112
reproduce-ours87.47 2387.61 2287.07 4593.27 5071.60 5391.56 4693.19 3574.98 11688.96 2295.54 1271.20 6396.54 3686.28 4693.49 6593.06 113
our_new_method87.47 2387.61 2287.07 4593.27 5071.60 5391.56 4693.19 3574.98 11688.96 2295.54 1271.20 6396.54 3686.28 4693.49 6593.06 113
HPM-MVS++copyleft89.02 989.15 988.63 595.01 976.03 192.38 2792.85 5980.26 1187.78 4094.27 3975.89 1996.81 2387.45 4096.44 993.05 115
thisisatest053079.40 18877.76 21084.31 11987.69 21165.10 20987.36 17684.26 29870.04 22877.42 19788.26 20849.94 30494.79 10470.20 20984.70 19693.03 116
train_agg86.43 4486.20 4887.13 4493.26 5272.96 2588.75 12791.89 10368.69 26485.00 7193.10 7974.43 2695.41 7384.97 5495.71 2593.02 117
EC-MVSNet86.01 5086.38 4484.91 9989.31 13966.27 17892.32 3093.63 2179.37 2284.17 9191.88 10669.04 9295.43 7083.93 7293.77 6393.01 118
mvsmamba80.60 16079.38 16784.27 12489.74 12167.24 16387.47 17286.95 25770.02 22975.38 24988.93 18651.24 28892.56 20275.47 16189.22 13093.00 119
EI-MVSNet-UG-set83.81 8783.38 9585.09 9187.87 19967.53 15287.44 17589.66 17779.74 1782.23 11889.41 17970.24 7594.74 10579.95 11183.92 21092.99 120
tttt051779.40 18877.91 20183.90 15188.10 18863.84 23788.37 14384.05 30071.45 19776.78 21489.12 18249.93 30694.89 9870.18 21083.18 22892.96 121
test9_res84.90 5595.70 2692.87 122
AstraMVS80.81 15080.14 15182.80 19586.05 25563.96 23386.46 20985.90 27773.71 15180.85 14190.56 14754.06 25491.57 24479.72 11483.97 20992.86 123
SR-MVS86.73 3886.67 4186.91 4994.11 3772.11 4792.37 2892.56 7574.50 12986.84 5694.65 2467.31 11195.77 5984.80 5992.85 7292.84 124
ETV-MVS84.90 7884.67 7885.59 7689.39 13468.66 12088.74 12992.64 7279.97 1584.10 9285.71 27669.32 8595.38 7580.82 10391.37 9592.72 125
agg_prior282.91 8295.45 2992.70 126
APD-MVScopyleft87.44 2587.52 2587.19 4294.24 3272.39 3991.86 4092.83 6073.01 17288.58 2694.52 2573.36 3496.49 3884.26 6695.01 3792.70 126
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
ET-MVSNet_ETH3D78.63 20776.63 23884.64 10786.73 23969.47 9585.01 24884.61 29169.54 24266.51 37186.59 25650.16 30091.75 23676.26 14984.24 20692.69 128
Vis-MVSNet (Re-imp)78.36 21478.45 18778.07 30188.64 16651.78 39286.70 20179.63 36374.14 14175.11 26290.83 14361.29 18689.75 28958.10 32391.60 8992.69 128
TSAR-MVS + GP.85.71 6085.33 6986.84 5091.34 8172.50 3689.07 11487.28 24976.41 8185.80 6290.22 15574.15 3195.37 7881.82 9391.88 8492.65 130
test_fmvsmvis_n_192084.02 8583.87 8784.49 11284.12 29969.37 10188.15 15287.96 23270.01 23083.95 9693.23 7768.80 9591.51 25088.61 2889.96 11892.57 131
FA-MVS(test-final)80.96 14679.91 15584.10 13188.30 17965.01 21084.55 26190.01 16673.25 16779.61 15587.57 22558.35 21494.72 10671.29 19986.25 17792.56 132
guyue81.13 14380.64 13982.60 20486.52 24463.92 23686.69 20287.73 24073.97 14380.83 14289.69 16456.70 23191.33 25878.26 13085.40 18992.54 133
test_yl81.17 14180.47 14383.24 17289.13 14763.62 24086.21 21789.95 16872.43 18181.78 12789.61 16857.50 22293.58 15270.75 20386.90 16592.52 134
DCV-MVSNet81.17 14180.47 14383.24 17289.13 14763.62 24086.21 21789.95 16872.43 18181.78 12789.61 16857.50 22293.58 15270.75 20386.90 16592.52 134
SR-MVS-dyc-post85.77 5885.61 6386.23 5993.06 5870.63 7691.88 3892.27 8473.53 15885.69 6494.45 3065.00 13895.56 6382.75 8491.87 8592.50 136
RE-MVS-def85.48 6693.06 5870.63 7691.88 3892.27 8473.53 15885.69 6494.45 3063.87 14482.75 8491.87 8592.50 136
nrg03083.88 8683.53 9284.96 9586.77 23869.28 10290.46 6792.67 6774.79 12382.95 10991.33 12672.70 4593.09 18380.79 10579.28 27692.50 136
MG-MVS83.41 10083.45 9383.28 16992.74 6562.28 27088.17 15089.50 18475.22 10881.49 13092.74 9466.75 11495.11 8772.85 18691.58 9192.45 139
FIs82.07 12382.42 11081.04 23988.80 15958.34 31588.26 14793.49 2676.93 6778.47 17691.04 13669.92 7892.34 21569.87 21584.97 19292.44 140
testing3-275.12 27975.19 26174.91 34090.40 10245.09 42180.29 33378.42 37378.37 3776.54 22287.75 21944.36 35587.28 33057.04 33383.49 22292.37 141
fmvsm_s_conf0.5_n_386.36 4787.46 2783.09 17987.08 23165.21 20389.09 11390.21 16079.67 1889.98 1895.02 1873.17 3891.71 23991.30 291.60 8992.34 142
FC-MVSNet-test81.52 13682.02 12080.03 26288.42 17555.97 35487.95 15893.42 2977.10 6377.38 19890.98 14269.96 7791.79 23468.46 23084.50 19892.33 143
Fast-Effi-MVS+80.81 15079.92 15483.47 16288.85 15464.51 22185.53 23889.39 18770.79 21078.49 17585.06 29667.54 10893.58 15267.03 24486.58 17192.32 144
TranMVSNet+NR-MVSNet80.84 14880.31 14682.42 20787.85 20062.33 26887.74 16691.33 12480.55 977.99 18889.86 15965.23 13492.62 19767.05 24375.24 33692.30 145
ab-mvs79.51 18278.97 17981.14 23688.46 17260.91 28783.84 27689.24 19570.36 22079.03 16288.87 18963.23 15190.21 28165.12 25782.57 23692.28 146
CANet_DTU80.61 15979.87 15682.83 19285.60 26463.17 25687.36 17688.65 22076.37 8575.88 23688.44 20253.51 25993.07 18473.30 18189.74 12392.25 147
UniMVSNet_NR-MVSNet81.88 12681.54 12682.92 18988.46 17263.46 24787.13 18292.37 8180.19 1278.38 17789.14 18171.66 5793.05 18670.05 21176.46 30992.25 147
fmvsm_l_conf0.5_n84.47 8084.54 7984.27 12485.42 26868.81 10988.49 13787.26 25168.08 27388.03 3693.49 6872.04 5091.77 23588.90 2589.14 13292.24 149
DU-MVS81.12 14480.52 14282.90 19087.80 20363.46 24787.02 18791.87 10579.01 2878.38 17789.07 18365.02 13693.05 18670.05 21176.46 30992.20 150
NR-MVSNet80.23 17079.38 16782.78 19987.80 20363.34 25086.31 21491.09 13379.01 2872.17 30689.07 18367.20 11292.81 19566.08 25075.65 32292.20 150
TAPA-MVS73.13 979.15 19477.94 20082.79 19889.59 12362.99 26188.16 15191.51 11965.77 30177.14 20991.09 13460.91 19393.21 17250.26 37587.05 16392.17 152
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
fmvsm_l_conf0.5_n_a84.13 8384.16 8484.06 13985.38 26968.40 12688.34 14486.85 26167.48 28087.48 4793.40 7370.89 6691.61 24088.38 3389.22 13092.16 153
3Dnovator76.31 583.38 10282.31 11486.59 5587.94 19672.94 2890.64 6092.14 9477.21 5975.47 24392.83 8858.56 21294.72 10673.24 18392.71 7592.13 154
MVS_111021_HR85.14 7284.75 7786.32 5891.65 7972.70 3085.98 22290.33 15576.11 9082.08 12191.61 11771.36 6194.17 12681.02 10092.58 7692.08 155
MVSFormer82.85 11382.05 11985.24 8587.35 21870.21 8090.50 6490.38 15168.55 26681.32 13289.47 17361.68 17593.46 16178.98 11890.26 11292.05 156
jason81.39 13980.29 14784.70 10686.63 24369.90 8885.95 22386.77 26263.24 33181.07 13889.47 17361.08 19192.15 22178.33 12690.07 11792.05 156
jason: jason.
HyFIR lowres test77.53 23775.40 25683.94 15089.59 12366.62 17280.36 33188.64 22156.29 39576.45 22385.17 29357.64 22093.28 16761.34 29383.10 22991.91 158
XVG-OURS-SEG-HR80.81 15079.76 15883.96 14985.60 26468.78 11183.54 28690.50 14770.66 21676.71 21691.66 11260.69 19691.26 25976.94 14281.58 24691.83 159
lupinMVS81.39 13980.27 14884.76 10487.35 21870.21 8085.55 23686.41 26762.85 33881.32 13288.61 19661.68 17592.24 21978.41 12590.26 11291.83 159
WR-MVS79.49 18379.22 17480.27 25788.79 16058.35 31485.06 24788.61 22278.56 3277.65 19388.34 20463.81 14690.66 27664.98 25977.22 29791.80 161
h-mvs3383.15 10782.19 11586.02 6990.56 9870.85 7388.15 15289.16 19876.02 9284.67 7891.39 12461.54 17895.50 6682.71 8675.48 32691.72 162
UniMVSNet (Re)81.60 13481.11 13183.09 17988.38 17664.41 22687.60 16893.02 4578.42 3478.56 17388.16 21069.78 7993.26 16869.58 21876.49 30891.60 163
UGNet80.83 14979.59 16384.54 10988.04 19168.09 13589.42 9688.16 22676.95 6676.22 22989.46 17549.30 31393.94 13468.48 22990.31 11091.60 163
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
testing9176.54 25275.66 25179.18 28088.43 17455.89 35581.08 31783.00 32073.76 15075.34 25184.29 31146.20 33990.07 28364.33 26384.50 19891.58 165
XVG-OURS80.41 16579.23 17383.97 14885.64 26269.02 10583.03 29890.39 15071.09 20577.63 19491.49 12154.62 24991.35 25675.71 15583.47 22391.54 166
LCM-MVSNet-Re77.05 24476.94 22877.36 31487.20 22751.60 39380.06 33580.46 35175.20 11067.69 35186.72 24862.48 16288.98 30563.44 26989.25 12991.51 167
DP-MVS Recon83.11 11082.09 11886.15 6394.44 1970.92 7188.79 12492.20 9070.53 21879.17 16191.03 13864.12 14296.03 5068.39 23190.14 11491.50 168
PS-MVSNAJss82.07 12381.31 12784.34 11886.51 24567.27 16189.27 10291.51 11971.75 18979.37 15890.22 15563.15 15394.27 11977.69 13382.36 23891.49 169
testing9976.09 26475.12 26379.00 28188.16 18355.50 36180.79 32181.40 34073.30 16575.17 25984.27 31444.48 35490.02 28464.28 26484.22 20791.48 170
thisisatest051577.33 24175.38 25783.18 17585.27 27363.80 23882.11 30583.27 31265.06 31075.91 23583.84 32149.54 30894.27 11967.24 24086.19 17891.48 170
DPM-MVS84.93 7684.29 8386.84 5090.20 10673.04 2387.12 18393.04 4169.80 23682.85 11291.22 12973.06 4096.02 5276.72 14794.63 4891.46 172
HQP_MVS83.64 9383.14 9885.14 8790.08 10968.71 11691.25 5292.44 7779.12 2578.92 16591.00 14060.42 20395.38 7578.71 12186.32 17591.33 173
plane_prior592.44 7795.38 7578.71 12186.32 17591.33 173
GA-MVS76.87 24875.17 26281.97 21582.75 33462.58 26581.44 31486.35 27072.16 18574.74 27082.89 34346.20 33992.02 22568.85 22681.09 25191.30 175
VPA-MVSNet80.60 16080.55 14180.76 24688.07 19060.80 28986.86 19491.58 11775.67 9980.24 14889.45 17763.34 14790.25 28070.51 20779.22 27791.23 176
Effi-MVS+-dtu80.03 17478.57 18584.42 11485.13 27868.74 11488.77 12588.10 22874.99 11574.97 26783.49 33257.27 22593.36 16573.53 17780.88 25491.18 177
v2v48280.23 17079.29 17183.05 18383.62 31164.14 23087.04 18589.97 16773.61 15478.18 18387.22 23661.10 19093.82 14276.11 15076.78 30591.18 177
FE-MVS77.78 23075.68 24984.08 13688.09 18966.00 18283.13 29387.79 23868.42 27078.01 18785.23 29145.50 34895.12 8559.11 31185.83 18691.11 179
Anonymous2023121178.97 20077.69 21382.81 19490.54 9964.29 22890.11 7591.51 11965.01 31276.16 23488.13 21550.56 29693.03 18969.68 21777.56 29591.11 179
hse-mvs281.72 12980.94 13584.07 13788.72 16367.68 14685.87 22687.26 25176.02 9284.67 7888.22 20961.54 17893.48 15982.71 8673.44 35491.06 181
AUN-MVS79.21 19377.60 21584.05 14288.71 16467.61 14885.84 22887.26 25169.08 25577.23 20388.14 21453.20 26393.47 16075.50 16073.45 35391.06 181
HQP4-MVS77.24 20295.11 8791.03 183
HQP-MVS82.61 11682.02 12084.37 11589.33 13666.98 16889.17 10692.19 9176.41 8177.23 20390.23 15460.17 20695.11 8777.47 13585.99 18391.03 183
RPSCF73.23 30271.46 30678.54 29182.50 34059.85 30182.18 30482.84 32558.96 37471.15 31889.41 17945.48 34984.77 35658.82 31571.83 36691.02 185
LuminaMVS80.68 15779.62 16283.83 15285.07 28068.01 13986.99 18888.83 21170.36 22081.38 13187.99 21750.11 30192.51 20679.02 11686.89 16790.97 186
test_djsdf80.30 16979.32 17083.27 17083.98 30365.37 20190.50 6490.38 15168.55 26676.19 23088.70 19256.44 23493.46 16178.98 11880.14 26690.97 186
PCF-MVS73.52 780.38 16678.84 18185.01 9387.71 20968.99 10683.65 28091.46 12363.00 33577.77 19290.28 15166.10 12495.09 9161.40 29188.22 14890.94 188
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
VPNet78.69 20678.66 18378.76 28588.31 17855.72 35884.45 26586.63 26476.79 7178.26 18090.55 14859.30 20889.70 29166.63 24577.05 29990.88 189
CPTT-MVS83.73 9083.33 9784.92 9893.28 4970.86 7292.09 3690.38 15168.75 26379.57 15692.83 8860.60 20193.04 18880.92 10291.56 9290.86 190
fmvsm_s_conf0.5_n_783.34 10384.03 8681.28 23185.73 26065.13 20685.40 24189.90 17074.96 11882.13 12093.89 6066.65 11587.92 32186.56 4591.05 9990.80 191
tt080578.73 20477.83 20581.43 22585.17 27460.30 29789.41 9790.90 13671.21 20277.17 20888.73 19146.38 33493.21 17272.57 19078.96 27890.79 192
CLD-MVS82.31 11981.65 12584.29 12188.47 17167.73 14585.81 23092.35 8275.78 9578.33 17986.58 25864.01 14394.35 11676.05 15287.48 15790.79 192
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
v119279.59 18178.43 18983.07 18283.55 31364.52 22086.93 19290.58 14470.83 20977.78 19185.90 27259.15 20993.94 13473.96 17477.19 29890.76 194
IterMVS-LS80.06 17379.38 16782.11 21185.89 25663.20 25486.79 19789.34 18874.19 13975.45 24686.72 24866.62 11692.39 21172.58 18976.86 30290.75 195
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
myMVS_eth3d2873.62 29373.53 28373.90 35288.20 18147.41 41178.06 36579.37 36574.29 13773.98 28184.29 31144.67 35183.54 36451.47 36587.39 15890.74 196
EI-MVSNet80.52 16479.98 15382.12 21084.28 29563.19 25586.41 21088.95 20974.18 14078.69 16887.54 22866.62 11692.43 20972.57 19080.57 26090.74 196
v192192079.22 19278.03 19882.80 19583.30 31863.94 23586.80 19690.33 15569.91 23477.48 19685.53 28358.44 21393.75 14873.60 17676.85 30390.71 198
QAPM80.88 14779.50 16585.03 9288.01 19468.97 10791.59 4392.00 9766.63 29275.15 26192.16 10057.70 21995.45 6863.52 26788.76 13890.66 199
v14419279.47 18478.37 19082.78 19983.35 31663.96 23386.96 18990.36 15469.99 23177.50 19585.67 27960.66 19893.77 14674.27 17176.58 30690.62 200
v124078.99 19977.78 20882.64 20283.21 32063.54 24486.62 20490.30 15769.74 24177.33 19985.68 27857.04 22893.76 14773.13 18476.92 30090.62 200
v114480.03 17479.03 17783.01 18583.78 30864.51 22187.11 18490.57 14671.96 18878.08 18686.20 26861.41 18293.94 13474.93 16577.23 29690.60 202
1112_ss77.40 24076.43 24180.32 25689.11 15160.41 29683.65 28087.72 24162.13 34873.05 29386.72 24862.58 16189.97 28562.11 28580.80 25690.59 203
CP-MVSNet78.22 21678.34 19177.84 30587.83 20254.54 37187.94 15991.17 12977.65 4373.48 28888.49 20062.24 16888.43 31562.19 28274.07 34590.55 204
testing22274.04 28872.66 29478.19 29887.89 19855.36 36281.06 31879.20 36871.30 20074.65 27383.57 33139.11 38788.67 31251.43 36785.75 18790.53 205
PS-CasMVS78.01 22578.09 19777.77 30787.71 20954.39 37388.02 15591.22 12677.50 5173.26 29088.64 19560.73 19488.41 31661.88 28673.88 34990.53 205
CDS-MVSNet79.07 19777.70 21283.17 17687.60 21368.23 13284.40 26886.20 27267.49 27976.36 22686.54 26061.54 17890.79 27261.86 28787.33 15990.49 207
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
TAMVS78.89 20277.51 21783.03 18487.80 20367.79 14484.72 25485.05 28767.63 27676.75 21587.70 22162.25 16790.82 27158.53 31887.13 16290.49 207
PEN-MVS77.73 23177.69 21377.84 30587.07 23353.91 37687.91 16191.18 12877.56 4873.14 29288.82 19061.23 18789.17 30159.95 30272.37 36090.43 209
Test_1112_low_res76.40 25975.44 25479.27 27789.28 14158.09 31781.69 30987.07 25559.53 36972.48 30186.67 25361.30 18589.33 29660.81 29780.15 26590.41 210
HY-MVS69.67 1277.95 22677.15 22380.36 25487.57 21760.21 29983.37 28887.78 23966.11 29675.37 25087.06 24363.27 14990.48 27861.38 29282.43 23790.40 211
sc_t172.19 31469.51 32580.23 25884.81 28461.09 28484.68 25580.22 35760.70 35871.27 31583.58 33036.59 39889.24 29960.41 29863.31 39890.37 212
CHOSEN 1792x268877.63 23675.69 24883.44 16389.98 11568.58 12278.70 35587.50 24556.38 39475.80 23886.84 24458.67 21191.40 25561.58 29085.75 18790.34 213
SDMVSNet80.38 16680.18 14980.99 24089.03 15264.94 21380.45 33089.40 18675.19 11176.61 22089.98 15760.61 20087.69 32576.83 14583.55 22090.33 214
sd_testset77.70 23477.40 21878.60 28889.03 15260.02 30079.00 35085.83 27875.19 11176.61 22089.98 15754.81 24285.46 34962.63 27883.55 22090.33 214
114514_t80.68 15779.51 16484.20 12894.09 3867.27 16189.64 8791.11 13258.75 37874.08 28090.72 14458.10 21595.04 9269.70 21689.42 12890.30 216
eth_miper_zixun_eth77.92 22776.69 23681.61 22283.00 32861.98 27383.15 29289.20 19769.52 24374.86 26984.35 31061.76 17492.56 20271.50 19772.89 35890.28 217
PVSNet_Blended_VisFu82.62 11581.83 12484.96 9590.80 9469.76 9088.74 12991.70 11269.39 24478.96 16388.46 20165.47 13294.87 10074.42 16988.57 14190.24 218
MVS_111021_LR82.61 11682.11 11684.11 13088.82 15771.58 5585.15 24486.16 27374.69 12580.47 14691.04 13662.29 16690.55 27780.33 10890.08 11690.20 219
MSLP-MVS++85.43 6685.76 6084.45 11391.93 7570.24 7990.71 5992.86 5877.46 5284.22 8992.81 9067.16 11392.94 19080.36 10794.35 5790.16 220
mvs_tets79.13 19577.77 20983.22 17484.70 28766.37 17689.17 10690.19 16169.38 24575.40 24889.46 17544.17 35793.15 17976.78 14680.70 25890.14 221
BH-RMVSNet79.61 17978.44 18883.14 17789.38 13565.93 18484.95 25087.15 25473.56 15678.19 18289.79 16256.67 23293.36 16559.53 30786.74 16990.13 222
c3_l78.75 20377.91 20181.26 23282.89 33261.56 27984.09 27489.13 20169.97 23275.56 24184.29 31166.36 12192.09 22373.47 17975.48 32690.12 223
v7n78.97 20077.58 21683.14 17783.45 31565.51 19688.32 14591.21 12773.69 15272.41 30286.32 26657.93 21693.81 14369.18 22175.65 32290.11 224
jajsoiax79.29 19177.96 19983.27 17084.68 28866.57 17489.25 10390.16 16269.20 25275.46 24589.49 17245.75 34593.13 18176.84 14480.80 25690.11 224
v14878.72 20577.80 20781.47 22482.73 33561.96 27486.30 21588.08 22973.26 16676.18 23185.47 28562.46 16392.36 21371.92 19473.82 35090.09 226
GBi-Net78.40 21277.40 21881.40 22787.60 21363.01 25788.39 14089.28 19171.63 19175.34 25187.28 23254.80 24391.11 26262.72 27479.57 27090.09 226
test178.40 21277.40 21881.40 22787.60 21363.01 25788.39 14089.28 19171.63 19175.34 25187.28 23254.80 24391.11 26262.72 27479.57 27090.09 226
FMVSNet177.44 23876.12 24581.40 22786.81 23763.01 25788.39 14089.28 19170.49 21974.39 27787.28 23249.06 31791.11 26260.91 29578.52 28190.09 226
WR-MVS_H78.51 21178.49 18678.56 29088.02 19256.38 34888.43 13892.67 6777.14 6173.89 28287.55 22766.25 12389.24 29958.92 31373.55 35290.06 230
DTE-MVSNet76.99 24576.80 23177.54 31386.24 24853.06 38587.52 17090.66 14277.08 6472.50 30088.67 19460.48 20289.52 29357.33 33070.74 37290.05 231
v879.97 17679.02 17882.80 19584.09 30064.50 22387.96 15790.29 15874.13 14275.24 25886.81 24562.88 15893.89 14174.39 17075.40 33190.00 232
thres600view776.50 25475.44 25479.68 27089.40 13357.16 33485.53 23883.23 31373.79 14976.26 22887.09 24151.89 28091.89 23148.05 38983.72 21790.00 232
thres40076.50 25475.37 25879.86 26589.13 14757.65 32885.17 24283.60 30573.41 16276.45 22386.39 26452.12 27291.95 22848.33 38483.75 21490.00 232
cl2278.07 22277.01 22581.23 23382.37 34461.83 27683.55 28487.98 23168.96 26075.06 26483.87 31961.40 18391.88 23273.53 17776.39 31189.98 235
OPM-MVS83.50 9882.95 10385.14 8788.79 16070.95 6989.13 11191.52 11877.55 4980.96 13991.75 11060.71 19594.50 11379.67 11586.51 17389.97 236
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
baseline275.70 26873.83 28081.30 23083.26 31961.79 27782.57 30180.65 34766.81 28366.88 36283.42 33357.86 21892.19 22063.47 26879.57 27089.91 237
v1079.74 17878.67 18282.97 18884.06 30164.95 21287.88 16390.62 14373.11 16975.11 26286.56 25961.46 18194.05 13073.68 17575.55 32489.90 238
MVSTER79.01 19877.88 20482.38 20883.07 32564.80 21784.08 27588.95 20969.01 25978.69 16887.17 23954.70 24792.43 20974.69 16680.57 26089.89 239
ACMP74.13 681.51 13880.57 14084.36 11689.42 13168.69 11989.97 7791.50 12274.46 13175.04 26590.41 15053.82 25694.54 11077.56 13482.91 23089.86 240
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
LPG-MVS_test82.08 12281.27 12884.50 11089.23 14368.76 11290.22 7391.94 10175.37 10576.64 21891.51 11954.29 25094.91 9578.44 12383.78 21189.83 241
LGP-MVS_train84.50 11089.23 14368.76 11291.94 10175.37 10576.64 21891.51 11954.29 25094.91 9578.44 12383.78 21189.83 241
V4279.38 19078.24 19482.83 19281.10 36365.50 19785.55 23689.82 17171.57 19578.21 18186.12 27060.66 19893.18 17875.64 15675.46 32889.81 243
MAR-MVS81.84 12780.70 13785.27 8491.32 8271.53 5689.82 7990.92 13569.77 23878.50 17486.21 26762.36 16594.52 11265.36 25592.05 8389.77 244
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
DIV-MVS_self_test77.72 23276.76 23380.58 25082.48 34260.48 29483.09 29487.86 23669.22 25074.38 27885.24 29062.10 17091.53 24871.09 20075.40 33189.74 245
cl____77.72 23276.76 23380.58 25082.49 34160.48 29483.09 29487.87 23569.22 25074.38 27885.22 29262.10 17091.53 24871.09 20075.41 33089.73 246
miper_ehance_all_eth78.59 20977.76 21081.08 23882.66 33761.56 27983.65 28089.15 19968.87 26175.55 24283.79 32366.49 11992.03 22473.25 18276.39 31189.64 247
anonymousdsp78.60 20877.15 22382.98 18780.51 36967.08 16687.24 18189.53 18365.66 30375.16 26087.19 23852.52 26592.25 21877.17 13979.34 27589.61 248
FMVSNet278.20 21877.21 22281.20 23487.60 21362.89 26387.47 17289.02 20471.63 19175.29 25787.28 23254.80 24391.10 26562.38 27979.38 27489.61 248
baseline176.98 24676.75 23577.66 30888.13 18655.66 35985.12 24581.89 33373.04 17176.79 21388.90 18762.43 16487.78 32463.30 27171.18 37089.55 250
ETVMVS72.25 31371.05 31275.84 32687.77 20751.91 38979.39 34374.98 39469.26 24873.71 28482.95 34140.82 37986.14 34046.17 39784.43 20389.47 251
FMVSNet377.88 22876.85 23080.97 24286.84 23662.36 26786.52 20788.77 21471.13 20375.34 25186.66 25454.07 25391.10 26562.72 27479.57 27089.45 252
miper_enhance_ethall77.87 22976.86 22980.92 24381.65 35161.38 28182.68 29988.98 20665.52 30575.47 24382.30 35265.76 13192.00 22672.95 18576.39 31189.39 253
testing1175.14 27874.01 27578.53 29288.16 18356.38 34880.74 32480.42 35370.67 21372.69 29983.72 32643.61 36189.86 28662.29 28183.76 21389.36 254
cascas76.72 25174.64 26682.99 18685.78 25965.88 18682.33 30289.21 19660.85 35772.74 29681.02 36347.28 32693.75 14867.48 23785.02 19189.34 255
Fast-Effi-MVS+-dtu78.02 22476.49 23982.62 20383.16 32466.96 17086.94 19187.45 24772.45 17871.49 31484.17 31654.79 24691.58 24267.61 23580.31 26389.30 256
IB-MVS68.01 1575.85 26773.36 28683.31 16884.76 28666.03 18083.38 28785.06 28670.21 22769.40 33781.05 36245.76 34494.66 10965.10 25875.49 32589.25 257
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
thres100view90076.50 25475.55 25379.33 27689.52 12656.99 33785.83 22983.23 31373.94 14576.32 22787.12 24051.89 28091.95 22848.33 38483.75 21489.07 258
tfpn200view976.42 25875.37 25879.55 27589.13 14757.65 32885.17 24283.60 30573.41 16276.45 22386.39 26452.12 27291.95 22848.33 38483.75 21489.07 258
xiu_mvs_v1_base_debu80.80 15379.72 15984.03 14487.35 21870.19 8285.56 23388.77 21469.06 25681.83 12388.16 21050.91 29192.85 19278.29 12787.56 15489.06 260
xiu_mvs_v1_base80.80 15379.72 15984.03 14487.35 21870.19 8285.56 23388.77 21469.06 25681.83 12388.16 21050.91 29192.85 19278.29 12787.56 15489.06 260
xiu_mvs_v1_base_debi80.80 15379.72 15984.03 14487.35 21870.19 8285.56 23388.77 21469.06 25681.83 12388.16 21050.91 29192.85 19278.29 12787.56 15489.06 260
EPNet_dtu75.46 27274.86 26477.23 31782.57 33954.60 37086.89 19383.09 31771.64 19066.25 37385.86 27455.99 23588.04 32054.92 34786.55 17289.05 263
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
pm-mvs177.25 24376.68 23778.93 28384.22 29758.62 31286.41 21088.36 22571.37 19873.31 28988.01 21661.22 18889.15 30264.24 26573.01 35789.03 264
PVSNet_Blended80.98 14580.34 14582.90 19088.85 15465.40 19884.43 26692.00 9767.62 27778.11 18485.05 29766.02 12794.27 11971.52 19589.50 12689.01 265
PAPM77.68 23576.40 24281.51 22387.29 22661.85 27583.78 27789.59 18164.74 31471.23 31688.70 19262.59 16093.66 15152.66 35987.03 16489.01 265
WTY-MVS75.65 26975.68 24975.57 33086.40 24656.82 33977.92 36882.40 32865.10 30976.18 23187.72 22063.13 15680.90 38160.31 30081.96 24289.00 267
无先验87.48 17188.98 20660.00 36494.12 12767.28 23988.97 268
GSMVS88.96 269
sam_mvs151.32 28788.96 269
SCA74.22 28572.33 29879.91 26484.05 30262.17 27179.96 33879.29 36766.30 29572.38 30380.13 37551.95 27888.60 31359.25 30977.67 29488.96 269
miper_lstm_enhance74.11 28773.11 28977.13 31880.11 37359.62 30472.23 39886.92 26066.76 28570.40 32282.92 34256.93 22982.92 36969.06 22372.63 35988.87 272
ACMM73.20 880.78 15679.84 15783.58 16089.31 13968.37 12789.99 7691.60 11670.28 22477.25 20189.66 16653.37 26193.53 15774.24 17282.85 23188.85 273
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
pmmvs674.69 28173.39 28478.61 28781.38 35857.48 33186.64 20387.95 23364.99 31370.18 32586.61 25550.43 29889.52 29362.12 28470.18 37588.83 274
原ACMM184.35 11793.01 6068.79 11092.44 7763.96 32881.09 13791.57 11866.06 12695.45 6867.19 24194.82 4688.81 275
CNLPA78.08 22176.79 23281.97 21590.40 10271.07 6587.59 16984.55 29266.03 29972.38 30389.64 16757.56 22186.04 34159.61 30683.35 22588.79 276
UWE-MVS72.13 31571.49 30574.03 35086.66 24247.70 40981.40 31576.89 38763.60 33075.59 24084.22 31539.94 38285.62 34648.98 38186.13 18088.77 277
UBG73.08 30472.27 29975.51 33288.02 19251.29 39778.35 36277.38 38265.52 30573.87 28382.36 35045.55 34686.48 33755.02 34684.39 20488.75 278
K. test v371.19 32068.51 33279.21 27983.04 32757.78 32784.35 26976.91 38672.90 17462.99 39382.86 34439.27 38491.09 26761.65 28952.66 41988.75 278
旧先验191.96 7465.79 19086.37 26993.08 8369.31 8692.74 7488.74 280
PatchmatchNetpermissive73.12 30371.33 30978.49 29483.18 32260.85 28879.63 34078.57 37264.13 32171.73 31079.81 38051.20 28985.97 34257.40 32976.36 31688.66 281
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
SixPastTwentyTwo73.37 29771.26 31179.70 26985.08 27957.89 32385.57 23283.56 30771.03 20765.66 37585.88 27342.10 37192.57 20159.11 31163.34 39788.65 282
SSC-MVS3.273.35 30073.39 28473.23 35685.30 27249.01 40774.58 39181.57 33775.21 10973.68 28585.58 28252.53 26482.05 37454.33 35177.69 29388.63 283
PS-MVSNAJ81.69 13181.02 13383.70 15689.51 12768.21 13384.28 27090.09 16470.79 21081.26 13685.62 28163.15 15394.29 11775.62 15788.87 13588.59 284
xiu_mvs_v2_base81.69 13181.05 13283.60 15889.15 14668.03 13884.46 26490.02 16570.67 21381.30 13586.53 26163.17 15294.19 12575.60 15888.54 14288.57 285
MonoMVSNet76.49 25775.80 24678.58 28981.55 35458.45 31386.36 21386.22 27174.87 12274.73 27183.73 32551.79 28388.73 31070.78 20272.15 36388.55 286
CostFormer75.24 27773.90 27879.27 27782.65 33858.27 31680.80 32082.73 32661.57 35275.33 25583.13 33855.52 23891.07 26864.98 25978.34 28688.45 287
lessismore_v078.97 28281.01 36457.15 33565.99 42161.16 39982.82 34539.12 38691.34 25759.67 30546.92 42688.43 288
OpenMVScopyleft72.83 1079.77 17778.33 19284.09 13585.17 27469.91 8790.57 6190.97 13466.70 28672.17 30691.91 10454.70 24793.96 13161.81 28890.95 10288.41 289
reproduce_monomvs75.40 27574.38 27278.46 29583.92 30557.80 32683.78 27786.94 25873.47 16072.25 30584.47 30538.74 38889.27 29875.32 16270.53 37388.31 290
VortexMVS78.57 21077.89 20380.59 24985.89 25662.76 26485.61 23189.62 18072.06 18674.99 26685.38 28755.94 23690.77 27474.99 16476.58 30688.23 291
OurMVSNet-221017-074.26 28472.42 29779.80 26783.76 30959.59 30585.92 22586.64 26366.39 29466.96 36187.58 22439.46 38391.60 24165.76 25369.27 37888.22 292
LS3D76.95 24774.82 26583.37 16790.45 10067.36 15889.15 11086.94 25861.87 35169.52 33690.61 14651.71 28494.53 11146.38 39686.71 17088.21 293
WBMVS73.43 29672.81 29275.28 33687.91 19750.99 39978.59 35881.31 34265.51 30774.47 27684.83 30046.39 33386.68 33458.41 31977.86 28988.17 294
XVG-ACMP-BASELINE76.11 26374.27 27481.62 22083.20 32164.67 21983.60 28389.75 17569.75 23971.85 30987.09 24132.78 40792.11 22269.99 21380.43 26288.09 295
tpm273.26 30171.46 30678.63 28683.34 31756.71 34280.65 32680.40 35456.63 39373.55 28782.02 35751.80 28291.24 26056.35 34178.42 28487.95 296
MDTV_nov1_ep13_2view37.79 43575.16 38555.10 39866.53 36849.34 31253.98 35287.94 297
Patchmatch-test64.82 37263.24 37369.57 38279.42 38549.82 40563.49 42969.05 41451.98 40859.95 40480.13 37550.91 29170.98 42340.66 41373.57 35187.90 298
PLCcopyleft70.83 1178.05 22376.37 24383.08 18191.88 7767.80 14388.19 14989.46 18564.33 32069.87 33388.38 20353.66 25793.58 15258.86 31482.73 23387.86 299
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
tpm72.37 31171.71 30374.35 34782.19 34552.00 38779.22 34677.29 38364.56 31672.95 29583.68 32851.35 28683.26 36858.33 32175.80 32087.81 300
Patchmatch-RL test70.24 33367.78 34677.61 31077.43 39459.57 30671.16 40270.33 40862.94 33768.65 34472.77 41450.62 29585.49 34869.58 21866.58 38887.77 301
F-COLMAP76.38 26074.33 27382.50 20689.28 14166.95 17188.41 13989.03 20364.05 32566.83 36388.61 19646.78 33192.89 19157.48 32778.55 28087.67 302
Baseline_NR-MVSNet78.15 22078.33 19277.61 31085.79 25856.21 35286.78 19885.76 27973.60 15577.93 18987.57 22565.02 13688.99 30467.14 24275.33 33387.63 303
CL-MVSNet_self_test72.37 31171.46 30675.09 33879.49 38453.53 37880.76 32385.01 28869.12 25470.51 32082.05 35657.92 21784.13 35952.27 36166.00 39187.60 304
ACMH+68.96 1476.01 26574.01 27582.03 21388.60 16765.31 20288.86 12087.55 24370.25 22667.75 35087.47 23041.27 37593.19 17758.37 32075.94 31987.60 304
131476.53 25375.30 26080.21 25983.93 30462.32 26984.66 25688.81 21260.23 36270.16 32784.07 31855.30 24090.73 27567.37 23883.21 22787.59 306
API-MVS81.99 12581.23 12984.26 12690.94 9070.18 8591.10 5589.32 18971.51 19678.66 17088.28 20665.26 13395.10 9064.74 26191.23 9787.51 307
AdaColmapbinary80.58 16379.42 16684.06 13993.09 5768.91 10889.36 10088.97 20869.27 24775.70 23989.69 16457.20 22795.77 5963.06 27288.41 14687.50 308
PVSNet_BlendedMVS80.60 16080.02 15282.36 20988.85 15465.40 19886.16 21992.00 9769.34 24678.11 18486.09 27166.02 12794.27 11971.52 19582.06 24187.39 309
sss73.60 29473.64 28273.51 35582.80 33355.01 36776.12 37681.69 33662.47 34474.68 27285.85 27557.32 22478.11 39260.86 29680.93 25287.39 309
IterMVS-SCA-FT75.43 27373.87 27980.11 26182.69 33664.85 21681.57 31183.47 30969.16 25370.49 32184.15 31751.95 27888.15 31869.23 22072.14 36487.34 311
PVSNet64.34 1872.08 31670.87 31575.69 32886.21 24956.44 34674.37 39280.73 34662.06 34970.17 32682.23 35442.86 36583.31 36754.77 34884.45 20287.32 312
tt0320-xc70.11 33567.45 35278.07 30185.33 27159.51 30783.28 28978.96 37058.77 37667.10 36080.28 37336.73 39787.42 32856.83 33759.77 40887.29 313
新几何183.42 16493.13 5470.71 7485.48 28257.43 38981.80 12691.98 10363.28 14892.27 21764.60 26292.99 7087.27 314
TR-MVS77.44 23876.18 24481.20 23488.24 18063.24 25284.61 25986.40 26867.55 27877.81 19086.48 26254.10 25293.15 17957.75 32682.72 23487.20 315
TransMVSNet (Re)75.39 27674.56 26877.86 30485.50 26757.10 33686.78 19886.09 27572.17 18471.53 31387.34 23163.01 15789.31 29756.84 33661.83 40187.17 316
ACMH67.68 1675.89 26673.93 27781.77 21888.71 16466.61 17388.62 13489.01 20569.81 23566.78 36486.70 25241.95 37391.51 25055.64 34378.14 28787.17 316
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
KD-MVS_self_test68.81 34567.59 35072.46 36674.29 40745.45 41677.93 36787.00 25663.12 33263.99 38878.99 38842.32 36884.77 35656.55 34064.09 39687.16 318
EPMVS69.02 34468.16 33671.59 37079.61 38249.80 40677.40 37166.93 41962.82 34070.01 32879.05 38445.79 34377.86 39456.58 33975.26 33587.13 319
CR-MVSNet73.37 29771.27 31079.67 27181.32 36165.19 20475.92 37880.30 35559.92 36572.73 29781.19 36052.50 26686.69 33359.84 30377.71 29187.11 320
RPMNet73.51 29570.49 31882.58 20581.32 36165.19 20475.92 37892.27 8457.60 38772.73 29776.45 40252.30 26995.43 7048.14 38877.71 29187.11 320
test_vis1_n_192075.52 27175.78 24774.75 34479.84 37757.44 33283.26 29085.52 28162.83 33979.34 16086.17 26945.10 35079.71 38578.75 12081.21 25087.10 322
tt032070.49 33168.03 33977.89 30384.78 28559.12 30983.55 28480.44 35258.13 38267.43 35680.41 37139.26 38587.54 32755.12 34563.18 39986.99 323
XXY-MVS75.41 27475.56 25274.96 33983.59 31257.82 32580.59 32783.87 30366.54 29374.93 26888.31 20563.24 15080.09 38462.16 28376.85 30386.97 324
tpmrst72.39 30972.13 30073.18 36080.54 36849.91 40479.91 33979.08 36963.11 33371.69 31179.95 37755.32 23982.77 37065.66 25473.89 34886.87 325
thres20075.55 27074.47 27078.82 28487.78 20657.85 32483.07 29683.51 30872.44 18075.84 23784.42 30652.08 27591.75 23647.41 39183.64 21986.86 326
ITE_SJBPF78.22 29781.77 35060.57 29283.30 31169.25 24967.54 35287.20 23736.33 40087.28 33054.34 35074.62 34286.80 327
test22291.50 8068.26 13084.16 27283.20 31654.63 40079.74 15391.63 11558.97 21091.42 9386.77 328
MIMVSNet70.69 32769.30 32674.88 34184.52 29256.35 35075.87 38079.42 36464.59 31567.76 34982.41 34941.10 37681.54 37746.64 39581.34 24786.75 329
BH-untuned79.47 18478.60 18482.05 21289.19 14565.91 18586.07 22188.52 22372.18 18375.42 24787.69 22261.15 18993.54 15660.38 29986.83 16886.70 330
LTVRE_ROB69.57 1376.25 26174.54 26981.41 22688.60 16764.38 22779.24 34589.12 20270.76 21269.79 33587.86 21849.09 31693.20 17556.21 34280.16 26486.65 331
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
testdata79.97 26390.90 9164.21 22984.71 28959.27 37185.40 6692.91 8562.02 17289.08 30368.95 22491.37 9586.63 332
MIMVSNet168.58 34866.78 35873.98 35180.07 37451.82 39180.77 32284.37 29364.40 31859.75 40582.16 35536.47 39983.63 36342.73 40870.33 37486.48 333
tfpnnormal74.39 28273.16 28878.08 30086.10 25458.05 31884.65 25887.53 24470.32 22371.22 31785.63 28054.97 24189.86 28643.03 40775.02 33886.32 334
D2MVS74.82 28073.21 28779.64 27279.81 37862.56 26680.34 33287.35 24864.37 31968.86 34282.66 34746.37 33590.10 28267.91 23381.24 24986.25 335
tpm cat170.57 32868.31 33477.35 31582.41 34357.95 32278.08 36480.22 35752.04 40668.54 34677.66 39752.00 27787.84 32351.77 36272.07 36586.25 335
CVMVSNet72.99 30672.58 29574.25 34884.28 29550.85 40086.41 21083.45 31044.56 41973.23 29187.54 22849.38 31185.70 34465.90 25178.44 28386.19 337
AllTest70.96 32368.09 33879.58 27385.15 27663.62 24084.58 26079.83 36062.31 34560.32 40286.73 24632.02 40888.96 30750.28 37371.57 36886.15 338
TestCases79.58 27385.15 27663.62 24079.83 36062.31 34560.32 40286.73 24632.02 40888.96 30750.28 37371.57 36886.15 338
test-LLR72.94 30772.43 29674.48 34581.35 35958.04 31978.38 35977.46 37966.66 28769.95 33179.00 38648.06 32279.24 38666.13 24784.83 19386.15 338
test-mter71.41 31970.39 32174.48 34581.35 35958.04 31978.38 35977.46 37960.32 36169.95 33179.00 38636.08 40179.24 38666.13 24784.83 19386.15 338
IterMVS74.29 28372.94 29178.35 29681.53 35563.49 24681.58 31082.49 32768.06 27469.99 33083.69 32751.66 28585.54 34765.85 25271.64 36786.01 342
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
DP-MVS76.78 25074.57 26783.42 16493.29 4869.46 9788.55 13683.70 30463.98 32770.20 32488.89 18854.01 25594.80 10346.66 39381.88 24486.01 342
ppachtmachnet_test70.04 33667.34 35478.14 29979.80 37961.13 28279.19 34780.59 34859.16 37265.27 37879.29 38346.75 33287.29 32949.33 37966.72 38686.00 344
mmtdpeth74.16 28673.01 29077.60 31283.72 31061.13 28285.10 24685.10 28572.06 18677.21 20780.33 37243.84 35985.75 34377.14 14052.61 42085.91 345
test_fmvs1_n70.86 32570.24 32272.73 36372.51 42155.28 36481.27 31679.71 36251.49 41078.73 16784.87 29927.54 41777.02 39776.06 15179.97 26885.88 346
Patchmtry70.74 32669.16 32975.49 33380.72 36554.07 37574.94 38980.30 35558.34 37970.01 32881.19 36052.50 26686.54 33553.37 35671.09 37185.87 347
WB-MVSnew71.96 31771.65 30472.89 36184.67 29151.88 39082.29 30377.57 37862.31 34573.67 28683.00 34053.49 26081.10 38045.75 40082.13 24085.70 348
test_fmvs268.35 35267.48 35170.98 37869.50 42451.95 38880.05 33676.38 38949.33 41374.65 27384.38 30823.30 42675.40 41474.51 16875.17 33785.60 349
ambc75.24 33773.16 41650.51 40263.05 43087.47 24664.28 38477.81 39617.80 43289.73 29057.88 32560.64 40585.49 350
mvs5depth69.45 34167.45 35275.46 33473.93 40855.83 35679.19 34783.23 31366.89 28271.63 31283.32 33433.69 40685.09 35259.81 30455.34 41685.46 351
UnsupCasMVSNet_eth67.33 35765.99 36171.37 37273.48 41351.47 39575.16 38585.19 28465.20 30860.78 40080.93 36742.35 36777.20 39657.12 33153.69 41885.44 352
PatchT68.46 35167.85 34270.29 38080.70 36643.93 42472.47 39774.88 39560.15 36370.55 31976.57 40149.94 30481.59 37650.58 36974.83 34085.34 353
Anonymous2024052168.80 34667.22 35573.55 35474.33 40654.11 37483.18 29185.61 28058.15 38161.68 39780.94 36530.71 41381.27 37957.00 33473.34 35685.28 354
test_cas_vis1_n_192073.76 29273.74 28173.81 35375.90 39959.77 30280.51 32882.40 32858.30 38081.62 12985.69 27744.35 35676.41 40376.29 14878.61 27985.23 355
ADS-MVSNet266.20 36863.33 37274.82 34279.92 37558.75 31167.55 41775.19 39353.37 40365.25 37975.86 40542.32 36880.53 38341.57 41168.91 38085.18 356
ADS-MVSNet64.36 37362.88 37668.78 38879.92 37547.17 41267.55 41771.18 40753.37 40365.25 37975.86 40542.32 36873.99 41941.57 41168.91 38085.18 356
FMVSNet569.50 34067.96 34074.15 34982.97 33155.35 36380.01 33782.12 33162.56 34363.02 39181.53 35936.92 39681.92 37548.42 38374.06 34685.17 358
pmmvs571.55 31870.20 32375.61 32977.83 39256.39 34781.74 30880.89 34357.76 38567.46 35484.49 30449.26 31485.32 35157.08 33275.29 33485.11 359
testing368.56 34967.67 34871.22 37687.33 22342.87 42683.06 29771.54 40670.36 22069.08 34184.38 30830.33 41485.69 34537.50 41975.45 32985.09 360
UWE-MVS-2865.32 36964.93 36366.49 39778.70 38938.55 43477.86 36964.39 42662.00 35064.13 38683.60 32941.44 37476.00 40731.39 42680.89 25384.92 361
CMPMVSbinary51.72 2170.19 33468.16 33676.28 32373.15 41757.55 33079.47 34283.92 30148.02 41556.48 41584.81 30143.13 36386.42 33862.67 27781.81 24584.89 362
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
testgi66.67 36266.53 35967.08 39675.62 40241.69 43175.93 37776.50 38866.11 29665.20 38186.59 25635.72 40274.71 41643.71 40573.38 35584.84 363
MSDG73.36 29970.99 31380.49 25284.51 29365.80 18980.71 32586.13 27465.70 30265.46 37683.74 32444.60 35290.91 27051.13 36876.89 30184.74 364
pmmvs474.03 29071.91 30180.39 25381.96 34768.32 12881.45 31382.14 33059.32 37069.87 33385.13 29452.40 26888.13 31960.21 30174.74 34184.73 365
gg-mvs-nofinetune69.95 33767.96 34075.94 32583.07 32554.51 37277.23 37370.29 40963.11 33370.32 32362.33 42343.62 36088.69 31153.88 35387.76 15384.62 366
test_fmvs170.93 32470.52 31772.16 36773.71 41055.05 36680.82 31978.77 37151.21 41178.58 17284.41 30731.20 41276.94 39875.88 15480.12 26784.47 367
BH-w/o78.21 21777.33 22180.84 24488.81 15865.13 20684.87 25187.85 23769.75 23974.52 27584.74 30361.34 18493.11 18258.24 32285.84 18584.27 368
MVS78.19 21976.99 22781.78 21785.66 26166.99 16784.66 25690.47 14855.08 39972.02 30885.27 28963.83 14594.11 12866.10 24989.80 12284.24 369
COLMAP_ROBcopyleft66.92 1773.01 30570.41 32080.81 24587.13 23065.63 19388.30 14684.19 29962.96 33663.80 39087.69 22238.04 39392.56 20246.66 39374.91 33984.24 369
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
new-patchmatchnet61.73 37961.73 38061.70 40372.74 41924.50 44669.16 41278.03 37561.40 35356.72 41475.53 40838.42 39076.48 40245.95 39957.67 40984.13 371
TESTMET0.1,169.89 33869.00 33072.55 36479.27 38756.85 33878.38 35974.71 39857.64 38668.09 34877.19 39937.75 39476.70 39963.92 26684.09 20884.10 372
test_fmvs363.36 37661.82 37967.98 39362.51 43346.96 41477.37 37274.03 40045.24 41867.50 35378.79 38912.16 43872.98 42272.77 18866.02 39083.99 373
our_test_369.14 34367.00 35675.57 33079.80 37958.80 31077.96 36677.81 37659.55 36862.90 39478.25 39347.43 32483.97 36051.71 36367.58 38583.93 374
test_vis1_n69.85 33969.21 32871.77 36972.66 42055.27 36581.48 31276.21 39052.03 40775.30 25683.20 33728.97 41576.22 40574.60 16778.41 28583.81 375
mamv476.81 24978.23 19672.54 36586.12 25265.75 19278.76 35482.07 33264.12 32272.97 29491.02 13967.97 10368.08 43083.04 8078.02 28883.80 376
tpmvs71.09 32269.29 32776.49 32282.04 34656.04 35378.92 35281.37 34164.05 32567.18 35978.28 39249.74 30789.77 28849.67 37872.37 36083.67 377
test20.0367.45 35666.95 35768.94 38575.48 40344.84 42277.50 37077.67 37766.66 28763.01 39283.80 32247.02 32878.40 39042.53 41068.86 38283.58 378
test0.0.03 168.00 35467.69 34768.90 38677.55 39347.43 41075.70 38172.95 40566.66 28766.56 36782.29 35348.06 32275.87 40944.97 40474.51 34383.41 379
Anonymous2023120668.60 34767.80 34571.02 37780.23 37250.75 40178.30 36380.47 35056.79 39266.11 37482.63 34846.35 33678.95 38843.62 40675.70 32183.36 380
EU-MVSNet68.53 35067.61 34971.31 37578.51 39147.01 41384.47 26284.27 29742.27 42266.44 37284.79 30240.44 38083.76 36158.76 31668.54 38383.17 381
dp66.80 36065.43 36270.90 37979.74 38148.82 40875.12 38774.77 39659.61 36764.08 38777.23 39842.89 36480.72 38248.86 38266.58 38883.16 382
pmmvs-eth3d70.50 33067.83 34478.52 29377.37 39566.18 17981.82 30681.51 33858.90 37563.90 38980.42 37042.69 36686.28 33958.56 31765.30 39383.11 383
YYNet165.03 37062.91 37571.38 37175.85 40056.60 34469.12 41374.66 39957.28 39054.12 41877.87 39545.85 34274.48 41749.95 37661.52 40383.05 384
MDA-MVSNet-bldmvs66.68 36163.66 37175.75 32779.28 38660.56 29373.92 39478.35 37464.43 31750.13 42479.87 37944.02 35883.67 36246.10 39856.86 41083.03 385
MDA-MVSNet_test_wron65.03 37062.92 37471.37 37275.93 39856.73 34069.09 41474.73 39757.28 39054.03 41977.89 39445.88 34174.39 41849.89 37761.55 40282.99 386
USDC70.33 33268.37 33376.21 32480.60 36756.23 35179.19 34786.49 26660.89 35661.29 39885.47 28531.78 41089.47 29553.37 35676.21 31782.94 387
Syy-MVS68.05 35367.85 34268.67 38984.68 28840.97 43278.62 35673.08 40366.65 29066.74 36579.46 38152.11 27482.30 37232.89 42476.38 31482.75 388
myMVS_eth3d67.02 35966.29 36069.21 38484.68 28842.58 42778.62 35673.08 40366.65 29066.74 36579.46 38131.53 41182.30 37239.43 41676.38 31482.75 388
ttmdpeth59.91 38257.10 38668.34 39167.13 42846.65 41574.64 39067.41 41848.30 41462.52 39685.04 29820.40 42875.93 40842.55 40945.90 42982.44 390
OpenMVS_ROBcopyleft64.09 1970.56 32968.19 33577.65 30980.26 37059.41 30885.01 24882.96 32258.76 37765.43 37782.33 35137.63 39591.23 26145.34 40376.03 31882.32 391
JIA-IIPM66.32 36562.82 37776.82 32077.09 39661.72 27865.34 42575.38 39258.04 38464.51 38362.32 42442.05 37286.51 33651.45 36669.22 37982.21 392
dmvs_re71.14 32170.58 31672.80 36281.96 34759.68 30375.60 38279.34 36668.55 26669.27 34080.72 36849.42 31076.54 40052.56 36077.79 29082.19 393
EG-PatchMatch MVS74.04 28871.82 30280.71 24784.92 28267.42 15485.86 22788.08 22966.04 29864.22 38583.85 32035.10 40392.56 20257.44 32880.83 25582.16 394
MVP-Stereo76.12 26274.46 27181.13 23785.37 27069.79 8984.42 26787.95 23365.03 31167.46 35485.33 28853.28 26291.73 23858.01 32483.27 22681.85 395
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
TDRefinement67.49 35564.34 36676.92 31973.47 41461.07 28584.86 25282.98 32159.77 36658.30 40985.13 29426.06 41887.89 32247.92 39060.59 40681.81 396
GG-mvs-BLEND75.38 33581.59 35355.80 35779.32 34469.63 41167.19 35873.67 41243.24 36288.90 30950.41 37084.50 19881.45 397
KD-MVS_2432*160066.22 36663.89 36973.21 35775.47 40453.42 38070.76 40584.35 29464.10 32366.52 36978.52 39034.55 40484.98 35350.40 37150.33 42381.23 398
miper_refine_blended66.22 36663.89 36973.21 35775.47 40453.42 38070.76 40584.35 29464.10 32366.52 36978.52 39034.55 40484.98 35350.40 37150.33 42381.23 398
test_040272.79 30870.44 31979.84 26688.13 18665.99 18385.93 22484.29 29665.57 30467.40 35785.49 28446.92 32992.61 19835.88 42174.38 34480.94 400
MVStest156.63 38652.76 39268.25 39261.67 43453.25 38471.67 40068.90 41638.59 42750.59 42383.05 33925.08 42070.66 42436.76 42038.56 43080.83 401
UnsupCasMVSNet_bld63.70 37561.53 38170.21 38173.69 41151.39 39672.82 39681.89 33355.63 39757.81 41171.80 41638.67 38978.61 38949.26 38052.21 42180.63 402
LCM-MVSNet54.25 38849.68 39867.97 39453.73 44245.28 41966.85 42080.78 34535.96 43139.45 43262.23 4258.70 44278.06 39348.24 38751.20 42280.57 403
N_pmnet52.79 39353.26 39151.40 41778.99 3887.68 45169.52 4093.89 45051.63 40957.01 41374.98 40940.83 37865.96 43237.78 41864.67 39480.56 404
TinyColmap67.30 35864.81 36474.76 34381.92 34956.68 34380.29 33381.49 33960.33 36056.27 41683.22 33524.77 42287.66 32645.52 40169.47 37779.95 405
PM-MVS66.41 36464.14 36773.20 35973.92 40956.45 34578.97 35164.96 42563.88 32964.72 38280.24 37419.84 43083.44 36666.24 24664.52 39579.71 406
ANet_high50.57 39746.10 40163.99 40048.67 44539.13 43370.99 40480.85 34461.39 35431.18 43457.70 43017.02 43373.65 42131.22 42715.89 44279.18 407
LF4IMVS64.02 37462.19 37869.50 38370.90 42253.29 38376.13 37577.18 38452.65 40558.59 40780.98 36423.55 42576.52 40153.06 35866.66 38778.68 408
PatchMatch-RL72.38 31070.90 31476.80 32188.60 16767.38 15779.53 34176.17 39162.75 34169.36 33882.00 35845.51 34784.89 35553.62 35480.58 25978.12 409
MS-PatchMatch73.83 29172.67 29377.30 31683.87 30666.02 18181.82 30684.66 29061.37 35568.61 34582.82 34547.29 32588.21 31759.27 30884.32 20577.68 410
DSMNet-mixed57.77 38556.90 38760.38 40567.70 42635.61 43669.18 41153.97 43732.30 43557.49 41279.88 37840.39 38168.57 42938.78 41772.37 36076.97 411
CHOSEN 280x42066.51 36364.71 36571.90 36881.45 35663.52 24557.98 43268.95 41553.57 40262.59 39576.70 40046.22 33875.29 41555.25 34479.68 26976.88 412
mvsany_test353.99 38951.45 39461.61 40455.51 43844.74 42363.52 42845.41 44343.69 42158.11 41076.45 40217.99 43163.76 43454.77 34847.59 42576.34 413
dmvs_testset62.63 37764.11 36858.19 40778.55 39024.76 44575.28 38365.94 42267.91 27560.34 40176.01 40453.56 25873.94 42031.79 42567.65 38475.88 414
mvsany_test162.30 37861.26 38265.41 39969.52 42354.86 36866.86 41949.78 43946.65 41668.50 34783.21 33649.15 31566.28 43156.93 33560.77 40475.11 415
PMMVS69.34 34268.67 33171.35 37475.67 40162.03 27275.17 38473.46 40150.00 41268.68 34379.05 38452.07 27678.13 39161.16 29482.77 23273.90 416
test_vis1_rt60.28 38158.42 38465.84 39867.25 42755.60 36070.44 40760.94 43144.33 42059.00 40666.64 42124.91 42168.67 42862.80 27369.48 37673.25 417
pmmvs357.79 38454.26 38968.37 39064.02 43256.72 34175.12 38765.17 42340.20 42452.93 42069.86 42020.36 42975.48 41245.45 40255.25 41772.90 418
PVSNet_057.27 2061.67 38059.27 38368.85 38779.61 38257.44 33268.01 41573.44 40255.93 39658.54 40870.41 41944.58 35377.55 39547.01 39235.91 43171.55 419
WB-MVS54.94 38754.72 38855.60 41373.50 41220.90 44774.27 39361.19 43059.16 37250.61 42274.15 41047.19 32775.78 41017.31 43835.07 43270.12 420
SSC-MVS53.88 39053.59 39054.75 41572.87 41819.59 44873.84 39560.53 43257.58 38849.18 42673.45 41346.34 33775.47 41316.20 44132.28 43469.20 421
test_f52.09 39450.82 39555.90 41153.82 44142.31 43059.42 43158.31 43536.45 43056.12 41770.96 41812.18 43757.79 43753.51 35556.57 41267.60 422
PMMVS240.82 40438.86 40846.69 41853.84 44016.45 44948.61 43549.92 43837.49 42831.67 43360.97 4268.14 44456.42 43828.42 42930.72 43567.19 423
new_pmnet50.91 39650.29 39652.78 41668.58 42534.94 43863.71 42756.63 43639.73 42544.95 42765.47 42221.93 42758.48 43634.98 42256.62 41164.92 424
MVS-HIRNet59.14 38357.67 38563.57 40181.65 35143.50 42571.73 39965.06 42439.59 42651.43 42157.73 42938.34 39182.58 37139.53 41473.95 34764.62 425
APD_test153.31 39249.93 39763.42 40265.68 42950.13 40371.59 40166.90 42034.43 43240.58 43171.56 4178.65 44376.27 40434.64 42355.36 41563.86 426
test_method31.52 40729.28 41138.23 42127.03 4496.50 45220.94 44062.21 4294.05 44322.35 44152.50 43413.33 43547.58 44127.04 43134.04 43360.62 427
EGC-MVSNET52.07 39547.05 39967.14 39583.51 31460.71 29080.50 32967.75 4170.07 4450.43 44675.85 40724.26 42381.54 37728.82 42862.25 40059.16 428
test_vis3_rt49.26 39847.02 40056.00 41054.30 43945.27 42066.76 42148.08 44036.83 42944.38 42853.20 4337.17 44564.07 43356.77 33855.66 41358.65 429
FPMVS53.68 39151.64 39359.81 40665.08 43051.03 39869.48 41069.58 41241.46 42340.67 43072.32 41516.46 43470.00 42724.24 43465.42 39258.40 430
testf145.72 39941.96 40357.00 40856.90 43645.32 41766.14 42259.26 43326.19 43630.89 43560.96 4274.14 44670.64 42526.39 43246.73 42755.04 431
APD_test245.72 39941.96 40357.00 40856.90 43645.32 41766.14 42259.26 43326.19 43630.89 43560.96 4274.14 44670.64 42526.39 43246.73 42755.04 431
PMVScopyleft37.38 2244.16 40340.28 40755.82 41240.82 44742.54 42965.12 42663.99 42734.43 43224.48 43857.12 4313.92 44876.17 40617.10 43955.52 41448.75 433
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
MVEpermissive26.22 2330.37 40925.89 41343.81 42044.55 44635.46 43728.87 43939.07 44418.20 44018.58 44240.18 4372.68 44947.37 44217.07 44023.78 43948.60 434
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
dongtai45.42 40145.38 40245.55 41973.36 41526.85 44367.72 41634.19 44554.15 40149.65 42556.41 43225.43 41962.94 43519.45 43628.09 43646.86 435
kuosan39.70 40540.40 40637.58 42264.52 43126.98 44165.62 42433.02 44646.12 41742.79 42948.99 43524.10 42446.56 44312.16 44426.30 43739.20 436
Gipumacopyleft45.18 40241.86 40555.16 41477.03 39751.52 39432.50 43880.52 34932.46 43427.12 43735.02 4389.52 44175.50 41122.31 43560.21 40738.45 437
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
DeepMVS_CXcopyleft27.40 42540.17 44826.90 44224.59 44917.44 44123.95 43948.61 4369.77 44026.48 44418.06 43724.47 43828.83 438
E-PMN31.77 40630.64 40935.15 42352.87 44327.67 44057.09 43347.86 44124.64 43816.40 44333.05 43911.23 43954.90 43914.46 44218.15 44022.87 439
EMVS30.81 40829.65 41034.27 42450.96 44425.95 44456.58 43446.80 44224.01 43915.53 44430.68 44012.47 43654.43 44012.81 44317.05 44122.43 440
tmp_tt18.61 41121.40 41410.23 4274.82 45010.11 45034.70 43730.74 4481.48 44423.91 44026.07 44128.42 41613.41 44627.12 43015.35 4437.17 441
wuyk23d16.82 41215.94 41519.46 42658.74 43531.45 43939.22 4363.74 4516.84 4426.04 4452.70 4451.27 45024.29 44510.54 44514.40 4442.63 442
test1236.12 4148.11 4170.14 4280.06 4520.09 45371.05 4030.03 4530.04 4470.25 4481.30 4470.05 4510.03 4480.21 4470.01 4460.29 443
testmvs6.04 4158.02 4180.10 4290.08 4510.03 45469.74 4080.04 4520.05 4460.31 4471.68 4460.02 4520.04 4470.24 4460.02 4450.25 444
mmdepth0.00 4170.00 4200.00 4300.00 4530.00 4550.00 4410.00 4540.00 4480.00 4490.00 4480.00 4530.00 4490.00 4480.00 4470.00 445
monomultidepth0.00 4170.00 4200.00 4300.00 4530.00 4550.00 4410.00 4540.00 4480.00 4490.00 4480.00 4530.00 4490.00 4480.00 4470.00 445
test_blank0.00 4170.00 4200.00 4300.00 4530.00 4550.00 4410.00 4540.00 4480.00 4490.00 4480.00 4530.00 4490.00 4480.00 4470.00 445
uanet_test0.00 4170.00 4200.00 4300.00 4530.00 4550.00 4410.00 4540.00 4480.00 4490.00 4480.00 4530.00 4490.00 4480.00 4470.00 445
DCPMVS0.00 4170.00 4200.00 4300.00 4530.00 4550.00 4410.00 4540.00 4480.00 4490.00 4480.00 4530.00 4490.00 4480.00 4470.00 445
cdsmvs_eth3d_5k19.96 41026.61 4120.00 4300.00 4530.00 4550.00 44189.26 1940.00 4480.00 44988.61 19661.62 1770.00 4490.00 4480.00 4470.00 445
pcd_1.5k_mvsjas5.26 4167.02 4190.00 4300.00 4530.00 4550.00 4410.00 4540.00 4480.00 4490.00 44863.15 1530.00 4490.00 4480.00 4470.00 445
sosnet-low-res0.00 4170.00 4200.00 4300.00 4530.00 4550.00 4410.00 4540.00 4480.00 4490.00 4480.00 4530.00 4490.00 4480.00 4470.00 445
sosnet0.00 4170.00 4200.00 4300.00 4530.00 4550.00 4410.00 4540.00 4480.00 4490.00 4480.00 4530.00 4490.00 4480.00 4470.00 445
uncertanet0.00 4170.00 4200.00 4300.00 4530.00 4550.00 4410.00 4540.00 4480.00 4490.00 4480.00 4530.00 4490.00 4480.00 4470.00 445
Regformer0.00 4170.00 4200.00 4300.00 4530.00 4550.00 4410.00 4540.00 4480.00 4490.00 4480.00 4530.00 4490.00 4480.00 4470.00 445
ab-mvs-re7.23 4139.64 4160.00 4300.00 4530.00 4550.00 4410.00 4540.00 4480.00 44986.72 2480.00 4530.00 4490.00 4480.00 4470.00 445
uanet0.00 4170.00 4200.00 4300.00 4530.00 4550.00 4410.00 4540.00 4480.00 4490.00 4480.00 4530.00 4490.00 4480.00 4470.00 445
WAC-MVS42.58 42739.46 415
FOURS195.00 1072.39 3995.06 193.84 1574.49 13091.30 15
test_one_060195.07 771.46 5794.14 578.27 3892.05 1195.74 680.83 11
eth-test20.00 453
eth-test0.00 453
ZD-MVS94.38 2572.22 4492.67 6770.98 20887.75 4294.07 4974.01 3296.70 2784.66 6194.84 44
test_241102_ONE95.30 270.98 6694.06 1077.17 6093.10 195.39 1482.99 197.27 12
9.1488.26 1592.84 6391.52 4894.75 173.93 14688.57 2794.67 2375.57 2295.79 5886.77 4395.76 23
save fliter93.80 4072.35 4290.47 6691.17 12974.31 135
test072695.27 571.25 5993.60 694.11 677.33 5492.81 395.79 380.98 9
test_part295.06 872.65 3291.80 13
sam_mvs50.01 302
MTGPAbinary92.02 95
test_post178.90 3535.43 44448.81 32185.44 35059.25 309
test_post5.46 44350.36 29984.24 358
patchmatchnet-post74.00 41151.12 29088.60 313
MTMP92.18 3432.83 447
gm-plane-assit81.40 35753.83 37762.72 34280.94 36592.39 21163.40 270
TEST993.26 5272.96 2588.75 12791.89 10368.44 26985.00 7193.10 7974.36 2895.41 73
test_893.13 5472.57 3588.68 13291.84 10768.69 26484.87 7593.10 7974.43 2695.16 83
agg_prior92.85 6271.94 5091.78 11084.41 8694.93 94
test_prior472.60 3489.01 115
test_prior288.85 12275.41 10384.91 7393.54 6774.28 2983.31 7695.86 20
旧先验286.56 20658.10 38387.04 5388.98 30574.07 173
新几何286.29 216
原ACMM286.86 194
testdata291.01 26962.37 280
segment_acmp73.08 39
testdata184.14 27375.71 96
plane_prior790.08 10968.51 124
plane_prior689.84 11868.70 11860.42 203
plane_prior491.00 140
plane_prior368.60 12178.44 3378.92 165
plane_prior291.25 5279.12 25
plane_prior189.90 117
plane_prior68.71 11690.38 7077.62 4486.16 179
n20.00 454
nn0.00 454
door-mid69.98 410
test1192.23 87
door69.44 413
HQP5-MVS66.98 168
HQP-NCC89.33 13689.17 10676.41 8177.23 203
ACMP_Plane89.33 13689.17 10676.41 8177.23 203
BP-MVS77.47 135
HQP3-MVS92.19 9185.99 183
HQP2-MVS60.17 206
NP-MVS89.62 12268.32 12890.24 153
MDTV_nov1_ep1369.97 32483.18 32253.48 37977.10 37480.18 35960.45 35969.33 33980.44 36948.89 32086.90 33251.60 36478.51 282
ACMMP++_ref81.95 243
ACMMP++81.25 248
Test By Simon64.33 140