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 bysorted bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort by
MCST-MVS91.08 191.46 289.94 497.66 273.37 997.13 295.58 889.33 185.77 3996.26 2472.84 2299.38 192.64 495.93 897.08 7
DPM-MVS90.70 290.52 591.24 189.68 15076.68 297.29 195.35 1082.87 1491.58 897.22 479.93 399.10 783.12 7297.64 297.94 1
MSP-MVS90.38 391.87 185.88 8292.83 7664.03 18793.06 9994.33 4882.19 1993.65 296.15 2785.89 197.19 7991.02 1597.75 196.43 22
CNVR-MVS90.32 490.89 488.61 1696.76 770.65 2296.47 1294.83 2384.83 889.07 1996.80 1270.86 2999.06 1192.64 495.71 996.12 30
ETH3 D test640090.27 590.44 689.75 696.82 674.33 795.89 1694.80 2677.13 7889.13 1897.38 274.49 1598.48 2492.32 995.98 696.46 21
DELS-MVS90.05 690.09 889.94 493.14 7073.88 897.01 394.40 4588.32 285.71 4194.91 6374.11 1698.91 1387.26 4495.94 797.03 8
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
SED-MVS89.94 790.36 788.70 1396.45 1169.38 4296.89 494.44 4071.65 18492.11 397.21 576.79 799.11 492.34 695.36 1297.62 2
DeepPCF-MVS81.17 189.72 891.38 384.72 12293.00 7358.16 27996.72 794.41 4386.50 590.25 1497.83 175.46 1298.67 1992.78 395.49 1197.32 4
CANet89.61 989.99 988.46 1794.39 3869.71 3896.53 1193.78 6086.89 489.68 1595.78 3165.94 6099.10 792.99 293.91 4096.58 15
DVP-MVS89.41 1089.73 1188.45 1896.40 1469.99 3096.64 894.52 3671.92 17090.55 1296.93 1073.77 1799.08 991.91 1094.90 1996.29 26
HPM-MVS++copyleft89.37 1189.95 1087.64 2695.10 2968.23 7095.24 3194.49 3882.43 1788.90 2096.35 2171.89 2898.63 2088.76 3096.40 496.06 31
NCCC89.07 1289.46 1287.91 2196.60 969.05 4996.38 1394.64 3384.42 986.74 3096.20 2566.56 5698.76 1889.03 2894.56 2995.92 37
DPE-MVS88.77 1389.21 1387.45 3396.26 1867.56 8594.17 5294.15 5368.77 23190.74 1197.27 376.09 1098.49 2390.58 1794.91 1896.30 25
SMA-MVScopyleft88.14 1488.29 1787.67 2593.21 6768.72 5793.85 7294.03 5674.18 11691.74 796.67 1365.61 6598.42 2889.24 2496.08 595.88 39
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
PS-MVSNAJ88.14 1487.61 2489.71 792.06 9476.72 195.75 1993.26 8683.86 1089.55 1696.06 2853.55 19397.89 4491.10 1393.31 5094.54 88
TSAR-MVS + MP.88.11 1688.64 1486.54 6191.73 10868.04 7390.36 20593.55 7382.89 1391.29 992.89 11372.27 2596.03 12887.99 3594.77 2395.54 46
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
TSAR-MVS + GP.87.96 1788.37 1686.70 5593.51 6065.32 14895.15 3493.84 5978.17 6685.93 3894.80 6775.80 1198.21 3189.38 2188.78 9896.59 13
DeepC-MVS_fast79.48 287.95 1888.00 1887.79 2495.86 2468.32 6595.74 2094.11 5583.82 1183.49 6396.19 2664.53 7698.44 2683.42 7194.88 2296.61 12
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
xiu_mvs_v2_base87.92 1987.38 2989.55 1091.41 12076.43 395.74 2093.12 9583.53 1289.55 1695.95 2953.45 19797.68 5091.07 1492.62 5994.54 88
EPNet87.84 2088.38 1586.23 7493.30 6366.05 12995.26 3094.84 2287.09 388.06 2294.53 7266.79 5397.34 7083.89 6891.68 7395.29 56
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
lupinMVS87.74 2187.77 2187.63 3089.24 16071.18 1796.57 1092.90 10382.70 1687.13 2695.27 4764.99 7095.80 13389.34 2291.80 7195.93 36
ETH3D-3000-0.187.61 2287.89 1986.75 5293.58 5767.21 9694.31 5094.14 5472.92 14587.13 2696.62 1467.81 4497.94 3990.13 1894.42 3295.09 68
APDe-MVS87.54 2387.84 2086.65 5696.07 2166.30 12494.84 4493.78 6069.35 22288.39 2196.34 2267.74 4597.66 5490.62 1693.44 4996.01 34
SD-MVS87.49 2487.49 2687.50 3293.60 5668.82 5593.90 6992.63 11476.86 8287.90 2395.76 3266.17 5797.63 5689.06 2691.48 7796.05 32
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
test_prior387.38 2587.70 2286.42 6694.71 3367.35 9295.10 3693.10 9675.40 9985.25 4895.61 3767.94 4096.84 10187.47 3994.77 2395.05 70
alignmvs87.28 2686.97 3488.24 2091.30 12171.14 1995.61 2493.56 7279.30 4787.07 2995.25 4968.43 3496.93 9987.87 3684.33 13796.65 11
Regformer-187.24 2787.60 2586.15 7695.14 2765.83 13793.95 6595.12 1582.11 2184.25 5495.73 3367.88 4398.35 2985.60 5488.64 10094.26 96
train_agg87.21 2887.42 2886.60 5794.18 4067.28 9494.16 5393.51 7471.87 17585.52 4395.33 4268.19 3697.27 7789.09 2594.90 1995.25 63
xxxxxxxxxxxxxcwj87.14 2987.19 3186.99 4593.84 4967.89 7795.05 3884.72 30278.19 6486.25 3196.44 1866.98 4997.79 4788.68 3194.56 2995.28 58
MG-MVS87.11 3086.27 4089.62 897.79 176.27 494.96 4294.49 3878.74 6083.87 6292.94 11064.34 7896.94 9775.19 13094.09 3695.66 42
ETH3D cwj APD-0.1687.06 3187.18 3286.71 5391.99 9867.48 9092.97 10494.21 5171.48 19585.72 4096.32 2368.13 3898.00 3889.06 2694.70 2794.65 84
SF-MVS87.03 3287.09 3386.84 4792.70 8267.45 9193.64 8093.76 6370.78 20786.25 3196.44 1866.98 4997.79 4788.68 3194.56 2995.28 58
agg_prior187.02 3387.26 3086.28 7394.16 4466.97 10594.08 5893.31 8471.85 17784.49 5295.39 4068.91 3396.75 10588.84 2994.32 3495.13 66
Regformer-287.00 3487.43 2785.71 9295.14 2764.73 16693.95 6594.95 2081.69 2684.03 6095.73 3367.35 4798.19 3385.40 5688.64 10094.20 98
CSCG86.87 3586.26 4188.72 1295.05 3070.79 2193.83 7695.33 1168.48 23577.63 11894.35 8173.04 2098.45 2584.92 6093.71 4596.92 9
canonicalmvs86.85 3686.25 4288.66 1591.80 10771.92 1393.54 8591.71 14880.26 3887.55 2495.25 4963.59 9096.93 9988.18 3484.34 13697.11 6
PHI-MVS86.83 3786.85 3786.78 5193.47 6165.55 14495.39 2995.10 1771.77 18185.69 4296.52 1562.07 10498.77 1786.06 5295.60 1096.03 33
SteuartSystems-ACMMP86.82 3886.90 3586.58 5990.42 13666.38 12196.09 1593.87 5877.73 7184.01 6195.66 3563.39 9297.94 3987.40 4193.55 4895.42 47
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PVSNet_Blended86.73 3986.86 3686.31 7293.76 5167.53 8796.33 1493.61 7082.34 1881.00 8193.08 10563.19 9597.29 7387.08 4591.38 7894.13 104
testtj86.62 4086.66 3986.50 6396.95 565.70 13994.41 4893.45 7867.74 23786.19 3496.39 2064.38 7797.91 4287.33 4293.14 5395.90 38
CS-MVS86.61 4186.85 3785.88 8291.52 11666.25 12695.42 2792.25 12480.36 3784.10 5994.82 6662.88 9996.08 12488.25 3392.07 6995.30 55
jason86.40 4286.17 4387.11 4186.16 21870.54 2495.71 2392.19 13182.00 2384.58 5194.34 8261.86 10695.53 15387.76 3790.89 8495.27 60
jason: jason.
WTY-MVS86.32 4385.81 4887.85 2292.82 7869.37 4495.20 3295.25 1282.71 1581.91 7094.73 6867.93 4297.63 5679.55 10082.25 14896.54 16
MSLP-MVS++86.27 4485.91 4787.35 3692.01 9768.97 5295.04 4092.70 10879.04 5581.50 7496.50 1758.98 13496.78 10383.49 7093.93 3996.29 26
VNet86.20 4585.65 5287.84 2393.92 4769.99 3095.73 2295.94 678.43 6286.00 3793.07 10758.22 13797.00 8985.22 5784.33 13796.52 17
MVS_111021_HR86.19 4685.80 4987.37 3593.17 6969.79 3693.99 6393.76 6379.08 5478.88 10793.99 9162.25 10398.15 3485.93 5391.15 8294.15 103
ACMMP_NAP86.05 4785.80 4986.80 5091.58 11267.53 8791.79 14993.49 7774.93 10784.61 5095.30 4459.42 12797.92 4186.13 5194.92 1794.94 75
ETV-MVS86.01 4886.11 4485.70 9390.21 14167.02 10493.43 9091.92 13981.21 2984.13 5894.07 9060.93 11395.63 14389.28 2389.81 9294.46 94
APD-MVScopyleft85.93 4985.99 4585.76 8995.98 2365.21 15193.59 8392.58 11666.54 24886.17 3595.88 3063.83 8497.00 8986.39 5092.94 5595.06 69
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
PAPM85.89 5085.46 5387.18 3988.20 18472.42 1292.41 12592.77 10682.11 2180.34 8793.07 10768.27 3595.02 16278.39 11293.59 4794.09 106
Regformer-385.80 5185.92 4685.46 9994.17 4265.09 15892.95 10695.11 1681.13 3081.68 7295.04 5465.82 6298.32 3083.02 7384.36 13492.97 141
CDPH-MVS85.71 5285.46 5386.46 6494.75 3267.19 9793.89 7092.83 10570.90 20383.09 6595.28 4563.62 8897.36 6880.63 9494.18 3594.84 77
DeepC-MVS77.85 385.52 5385.24 5586.37 6988.80 16966.64 11492.15 13093.68 6781.07 3176.91 12893.64 9662.59 10198.44 2685.50 5592.84 5794.03 110
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
Regformer-485.45 5485.69 5184.73 12094.17 4263.23 20492.95 10694.83 2380.66 3481.29 7595.04 5465.12 6898.08 3682.74 7584.36 13492.88 145
casdiffmvs85.37 5584.87 6086.84 4788.25 18269.07 4893.04 10191.76 14581.27 2880.84 8392.07 13064.23 7996.06 12684.98 5987.43 11095.39 48
ZNCC-MVS85.33 5685.08 5786.06 7793.09 7265.65 14193.89 7093.41 8273.75 12779.94 9194.68 7060.61 11698.03 3782.63 7893.72 4494.52 90
MP-MVS-pluss85.24 5785.13 5685.56 9691.42 11865.59 14391.54 16192.51 11874.56 11080.62 8495.64 3659.15 13197.00 8986.94 4793.80 4194.07 108
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
PAPR85.15 5884.47 6287.18 3996.02 2268.29 6691.85 14793.00 10076.59 8679.03 10395.00 5661.59 10797.61 5878.16 11389.00 9795.63 43
MP-MVScopyleft85.02 5984.97 5885.17 11092.60 8464.27 18393.24 9492.27 12373.13 13979.63 9694.43 7561.90 10597.17 8085.00 5892.56 6094.06 109
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
baseline85.01 6084.44 6486.71 5388.33 17968.73 5690.24 20991.82 14481.05 3281.18 7792.50 12063.69 8796.08 12484.45 6386.71 11895.32 53
#test#84.98 6184.74 6185.72 9093.75 5365.01 16094.09 5793.19 9073.55 13379.22 10094.93 6059.04 13297.67 5182.66 7692.21 6494.49 92
CHOSEN 1792x268884.98 6183.45 7489.57 989.94 14575.14 592.07 13692.32 12181.87 2475.68 13588.27 17660.18 11998.60 2180.46 9690.27 9194.96 74
EIA-MVS84.84 6384.88 5984.69 12391.30 12162.36 22293.85 7292.04 13479.45 4579.33 9994.28 8562.42 10296.35 11480.05 9791.25 8195.38 49
zzz-MVS84.73 6484.47 6285.50 9791.89 10365.16 15391.55 16092.23 12575.32 10180.53 8595.21 5156.06 16697.16 8184.86 6192.55 6194.18 99
HFP-MVS84.73 6484.40 6585.72 9093.75 5365.01 16093.50 8793.19 9072.19 16479.22 10094.93 6059.04 13297.67 5181.55 8592.21 6494.49 92
MVS84.66 6682.86 8890.06 290.93 12774.56 687.91 25295.54 968.55 23372.35 17294.71 6959.78 12398.90 1481.29 9194.69 2896.74 10
GST-MVS84.63 6784.29 6685.66 9492.82 7865.27 14993.04 10193.13 9473.20 13778.89 10494.18 8759.41 12897.85 4681.45 8792.48 6393.86 117
ACMMPR84.37 6884.06 6785.28 10693.56 5864.37 17893.50 8793.15 9372.19 16478.85 10994.86 6456.69 15897.45 6281.55 8592.20 6694.02 111
region2R84.36 6984.03 6885.36 10493.54 5964.31 18093.43 9092.95 10172.16 16778.86 10894.84 6556.97 15397.53 6081.38 8992.11 6894.24 97
LFMVS84.34 7082.73 9189.18 1194.76 3173.25 1094.99 4191.89 14071.90 17282.16 6993.49 10047.98 24397.05 8482.55 7984.82 13097.25 5
test_yl84.28 7183.16 8287.64 2694.52 3669.24 4595.78 1795.09 1869.19 22581.09 7892.88 11457.00 15197.44 6381.11 9281.76 15296.23 28
DCV-MVSNet84.28 7183.16 8287.64 2694.52 3669.24 4595.78 1795.09 1869.19 22581.09 7892.88 11457.00 15197.44 6381.11 9281.76 15296.23 28
diffmvs84.28 7183.83 6985.61 9587.40 19968.02 7490.88 18989.24 23780.54 3581.64 7392.52 11959.83 12294.52 18187.32 4385.11 12894.29 95
HY-MVS76.49 584.28 7183.36 8087.02 4492.22 9167.74 8184.65 27594.50 3779.15 5182.23 6887.93 18366.88 5196.94 9780.53 9582.20 14996.39 24
MAR-MVS84.18 7583.43 7586.44 6596.25 1965.93 13494.28 5194.27 5074.41 11179.16 10295.61 3753.99 18898.88 1669.62 17493.26 5194.50 91
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
MVS_Test84.16 7683.20 8187.05 4391.56 11369.82 3589.99 21892.05 13377.77 7082.84 6686.57 19863.93 8396.09 12274.91 13689.18 9695.25 63
CANet_DTU84.09 7783.52 7185.81 8690.30 13966.82 10991.87 14589.01 25085.27 686.09 3693.74 9547.71 24696.98 9377.90 11689.78 9493.65 121
ET-MVSNet_ETH3D84.01 7883.15 8486.58 5990.78 13370.89 2094.74 4594.62 3481.44 2758.19 29393.64 9673.64 1992.35 25582.66 7678.66 17496.50 19
PVSNet_Blended_VisFu83.97 7983.50 7285.39 10390.02 14366.59 11793.77 7791.73 14677.43 7777.08 12789.81 16263.77 8696.97 9479.67 9988.21 10392.60 149
DWT-MVSNet_test83.95 8082.80 8987.41 3492.90 7570.07 2989.12 23594.42 4282.15 2077.64 11791.77 13470.81 3096.22 11765.03 22181.36 15695.94 35
MTAPA83.91 8183.38 7985.50 9791.89 10365.16 15381.75 29592.23 12575.32 10180.53 8595.21 5156.06 16697.16 8184.86 6192.55 6194.18 99
XVS83.87 8283.47 7385.05 11193.22 6563.78 19092.92 10892.66 11173.99 11978.18 11294.31 8455.25 17297.41 6579.16 10391.58 7593.95 113
Effi-MVS+83.82 8382.76 9086.99 4589.56 15369.40 4191.35 17186.12 29272.59 15083.22 6492.81 11759.60 12596.01 13081.76 8387.80 10795.56 45
EI-MVSNet-Vis-set83.77 8483.67 7084.06 13892.79 8163.56 20091.76 15294.81 2579.65 4477.87 11494.09 8863.35 9397.90 4379.35 10179.36 16690.74 182
MVSFormer83.75 8582.88 8786.37 6989.24 16071.18 1789.07 23690.69 18465.80 25387.13 2694.34 8264.99 7092.67 24272.83 14591.80 7195.27 60
CP-MVS83.71 8683.40 7884.65 12493.14 7063.84 18894.59 4692.28 12271.03 20177.41 12194.92 6255.21 17596.19 11881.32 9090.70 8693.91 115
baseline283.68 8783.42 7784.48 13087.37 20066.00 13190.06 21395.93 779.71 4369.08 20590.39 15277.92 496.28 11578.91 10781.38 15591.16 178
thisisatest051583.41 8882.49 9486.16 7589.46 15668.26 6893.54 8594.70 3074.31 11475.75 13490.92 14272.62 2396.52 11269.64 17281.50 15493.71 119
PVSNet_BlendedMVS83.38 8983.43 7583.22 15693.76 5167.53 8794.06 5993.61 7079.13 5281.00 8185.14 21263.19 9597.29 7387.08 4573.91 20584.83 272
PGM-MVS83.25 9082.70 9284.92 11492.81 8064.07 18690.44 20192.20 13071.28 19677.23 12494.43 7555.17 17697.31 7279.33 10291.38 7893.37 126
HPM-MVScopyleft83.25 9082.95 8684.17 13692.25 9062.88 21590.91 18691.86 14170.30 21277.12 12593.96 9256.75 15696.28 11582.04 8191.34 8093.34 127
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
EI-MVSNet-UG-set83.14 9282.96 8583.67 14892.28 8963.19 20691.38 16994.68 3179.22 4976.60 12993.75 9462.64 10097.76 4978.07 11478.01 17790.05 190
VDD-MVS83.06 9381.81 10386.81 4990.86 13167.70 8295.40 2891.50 15775.46 9681.78 7192.34 12740.09 27997.13 8386.85 4882.04 15095.60 44
PAPM_NR82.97 9481.84 10186.37 6994.10 4666.76 11287.66 25692.84 10469.96 21574.07 15193.57 9863.10 9797.50 6170.66 16790.58 8894.85 76
mPP-MVS82.96 9582.44 9584.52 12892.83 7662.92 21392.76 11191.85 14271.52 19275.61 13894.24 8653.48 19696.99 9278.97 10690.73 8593.64 122
SR-MVS82.81 9682.58 9383.50 15393.35 6261.16 23892.23 12991.28 16664.48 26181.27 7695.28 4553.71 19295.86 13282.87 7488.77 9993.49 125
DP-MVS Recon82.73 9781.65 10485.98 7997.31 467.06 10195.15 3491.99 13669.08 22876.50 13193.89 9354.48 18498.20 3270.76 16585.66 12592.69 146
CLD-MVS82.73 9782.35 9783.86 14187.90 19167.65 8495.45 2692.18 13285.06 772.58 16592.27 12852.46 20395.78 13484.18 6479.06 16988.16 213
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
sss82.71 9982.38 9683.73 14589.25 15959.58 26492.24 12894.89 2177.96 6879.86 9392.38 12556.70 15797.05 8477.26 11980.86 16094.55 86
3Dnovator73.91 682.69 10080.82 11388.31 1989.57 15271.26 1692.60 11994.39 4678.84 5767.89 22492.48 12348.42 23898.52 2268.80 18494.40 3395.15 65
MVSTER82.47 10182.05 9883.74 14392.68 8369.01 5091.90 14493.21 8779.83 3972.14 17385.71 20874.72 1394.72 17275.72 12672.49 21587.50 218
TESTMET0.1,182.41 10281.98 10083.72 14688.08 18563.74 19292.70 11493.77 6279.30 4777.61 11987.57 18858.19 13894.08 19573.91 14086.68 11993.33 129
CostFormer82.33 10381.15 10885.86 8589.01 16568.46 6282.39 29393.01 9875.59 9480.25 8881.57 25172.03 2794.96 16479.06 10577.48 18694.16 102
API-MVS82.28 10480.53 11987.54 3196.13 2070.59 2393.63 8191.04 17665.72 25575.45 14092.83 11656.11 16598.89 1564.10 22689.75 9593.15 135
IB-MVS77.80 482.18 10580.46 12187.35 3689.14 16270.28 2795.59 2595.17 1478.85 5670.19 19385.82 20670.66 3197.67 5172.19 15566.52 25594.09 106
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
xiu_mvs_v1_base_debu82.16 10681.12 10985.26 10786.42 21268.72 5792.59 12190.44 19273.12 14084.20 5594.36 7738.04 29095.73 13784.12 6586.81 11391.33 172
xiu_mvs_v1_base82.16 10681.12 10985.26 10786.42 21268.72 5792.59 12190.44 19273.12 14084.20 5594.36 7738.04 29095.73 13784.12 6586.81 11391.33 172
xiu_mvs_v1_base_debi82.16 10681.12 10985.26 10786.42 21268.72 5792.59 12190.44 19273.12 14084.20 5594.36 7738.04 29095.73 13784.12 6586.81 11391.33 172
3Dnovator+73.60 782.10 10980.60 11886.60 5790.89 13066.80 11195.20 3293.44 8074.05 11867.42 23092.49 12249.46 22897.65 5570.80 16491.68 7395.33 51
MVS_111021_LR82.02 11081.52 10583.51 15288.42 17762.88 21589.77 22188.93 25276.78 8475.55 13993.10 10350.31 22095.38 15683.82 6987.02 11292.26 161
PMMVS81.98 11182.04 9981.78 19289.76 14956.17 29691.13 18290.69 18477.96 6880.09 9093.57 9846.33 25494.99 16381.41 8887.46 10994.17 101
test117281.90 11281.83 10282.13 18493.23 6457.52 28791.61 15990.98 17864.32 26380.20 8995.00 5651.26 21395.61 14581.73 8488.13 10493.26 131
baseline181.84 11381.03 11284.28 13591.60 11166.62 11591.08 18391.66 15181.87 2474.86 14391.67 13869.98 3294.92 16771.76 15864.75 26791.29 177
EPP-MVSNet81.79 11481.52 10582.61 16788.77 17060.21 25693.02 10393.66 6968.52 23472.90 16090.39 15272.19 2694.96 16474.93 13579.29 16892.67 147
APD-MVS_3200maxsize81.64 11581.32 10782.59 16892.36 8658.74 27391.39 16791.01 17763.35 26979.72 9594.62 7151.82 20696.14 12079.71 9887.93 10692.89 144
ACMMPcopyleft81.49 11680.67 11683.93 14091.71 10962.90 21492.13 13192.22 12971.79 18071.68 18193.49 10050.32 21996.96 9578.47 11184.22 14191.93 164
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
CDS-MVSNet81.43 11780.74 11483.52 15186.26 21664.45 17292.09 13490.65 18775.83 9373.95 15389.81 16263.97 8292.91 23271.27 16182.82 14593.20 134
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
mvs_anonymous81.36 11879.99 12585.46 9990.39 13868.40 6386.88 26690.61 18874.41 11170.31 19284.67 21763.79 8592.32 25673.13 14285.70 12495.67 41
112181.25 11980.05 12384.87 11792.30 8864.31 18087.91 25291.39 16159.44 30079.94 9192.91 11157.09 14797.01 8766.63 20092.81 5893.29 130
thisisatest053081.15 12080.07 12284.39 13288.26 18165.63 14291.40 16594.62 3471.27 19770.93 18589.18 16572.47 2496.04 12765.62 21576.89 19291.49 169
Fast-Effi-MVS+81.14 12180.01 12484.51 12990.24 14065.86 13594.12 5689.15 24373.81 12675.37 14188.26 17757.26 14594.53 18066.97 19984.92 12993.15 135
HQP-MVS81.14 12180.64 11782.64 16687.54 19563.66 19794.06 5991.70 14979.80 4074.18 14790.30 15451.63 21095.61 14577.63 11778.90 17088.63 204
SR-MVS-dyc-post81.06 12380.70 11582.15 18292.02 9558.56 27590.90 18790.45 18962.76 27578.89 10494.46 7351.26 21395.61 14578.77 10986.77 11692.28 158
HyFIR lowres test81.03 12479.56 13385.43 10187.81 19268.11 7290.18 21090.01 21370.65 20972.95 15986.06 20463.61 8994.50 18275.01 13479.75 16493.67 120
nrg03080.93 12579.86 12784.13 13783.69 25668.83 5493.23 9591.20 16775.55 9575.06 14288.22 18063.04 9894.74 17181.88 8266.88 25288.82 202
Vis-MVSNetpermissive80.92 12679.98 12683.74 14388.48 17461.80 22893.44 8988.26 27273.96 12277.73 11591.76 13549.94 22494.76 16965.84 21290.37 9094.65 84
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
131480.70 12778.95 14585.94 8187.77 19367.56 8587.91 25292.55 11772.17 16667.44 22993.09 10450.27 22197.04 8671.68 16087.64 10893.23 133
RRT_test8_iter0580.61 12879.62 13183.60 15091.87 10666.90 10793.42 9293.68 6777.09 8068.83 21185.63 20966.82 5295.42 15476.46 12462.74 27988.48 207
tpmrst80.57 12979.14 14484.84 11890.10 14268.28 6781.70 29689.72 22477.63 7375.96 13379.54 28264.94 7292.71 23975.43 12877.28 18993.55 123
1112_ss80.56 13079.83 12882.77 16288.65 17160.78 24492.29 12688.36 26772.58 15172.46 16994.95 5865.09 6993.42 22066.38 20677.71 17994.10 105
VDDNet80.50 13178.26 15287.21 3886.19 21769.79 3694.48 4791.31 16360.42 29279.34 9890.91 14338.48 28696.56 11182.16 8081.05 15895.27 60
BH-w/o80.49 13279.30 14084.05 13990.83 13264.36 17993.60 8289.42 23274.35 11369.09 20490.15 15755.23 17495.61 14564.61 22386.43 12292.17 162
TAMVS80.37 13379.45 13683.13 15885.14 23363.37 20191.23 17690.76 18374.81 10972.65 16388.49 17160.63 11592.95 22769.41 17681.95 15193.08 138
HQP_MVS80.34 13479.75 12982.12 18586.94 20662.42 22093.13 9791.31 16378.81 5872.53 16689.14 16750.66 21795.55 15176.74 12078.53 17588.39 210
HPM-MVS_fast80.25 13579.55 13582.33 17591.55 11459.95 25991.32 17389.16 24265.23 25974.71 14493.07 10747.81 24595.74 13674.87 13888.23 10291.31 176
ab-mvs80.18 13678.31 15185.80 8788.44 17665.49 14783.00 29092.67 11071.82 17977.36 12285.01 21354.50 18196.59 10876.35 12575.63 19895.32 53
IS-MVSNet80.14 13779.41 13782.33 17587.91 19060.08 25891.97 14288.27 27072.90 14671.44 18391.73 13761.44 10893.66 21562.47 23886.53 12093.24 132
test-LLR80.10 13879.56 13381.72 19486.93 20861.17 23692.70 11491.54 15471.51 19375.62 13686.94 19553.83 18992.38 25272.21 15384.76 13291.60 167
PVSNet73.49 880.05 13978.63 14784.31 13390.92 12864.97 16292.47 12491.05 17579.18 5072.43 17090.51 15037.05 30294.06 19768.06 18786.00 12393.90 116
UA-Net80.02 14079.65 13081.11 20989.33 15757.72 28386.33 26989.00 25177.44 7681.01 8089.15 16659.33 12995.90 13161.01 24584.28 13989.73 194
test-mter79.96 14179.38 13981.72 19486.93 20861.17 23692.70 11491.54 15473.85 12475.62 13686.94 19549.84 22692.38 25272.21 15384.76 13291.60 167
QAPM79.95 14277.39 16987.64 2689.63 15171.41 1593.30 9393.70 6665.34 25867.39 23291.75 13647.83 24498.96 1257.71 26089.81 9292.54 151
UGNet79.87 14378.68 14683.45 15589.96 14461.51 23392.13 13190.79 18176.83 8378.85 10986.33 20138.16 28896.17 11967.93 18987.17 11192.67 147
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
abl_679.82 14479.20 14281.70 19689.85 14658.34 27788.47 24590.07 20862.56 27877.71 11693.08 10547.65 24796.78 10377.94 11585.45 12789.99 191
tpm279.80 14577.95 15885.34 10588.28 18068.26 6881.56 29891.42 16070.11 21377.59 12080.50 26967.40 4694.26 19067.34 19477.35 18793.51 124
thres20079.66 14678.33 15083.66 14992.54 8565.82 13893.06 9996.31 374.90 10873.30 15688.66 16959.67 12495.61 14547.84 29678.67 17389.56 197
CPTT-MVS79.59 14779.16 14380.89 21891.54 11559.80 26192.10 13388.54 26560.42 29272.96 15893.28 10248.27 23992.80 23678.89 10886.50 12190.06 189
Test_1112_low_res79.56 14878.60 14882.43 17088.24 18360.39 25392.09 13487.99 27672.10 16871.84 17787.42 19064.62 7593.04 22465.80 21377.30 18893.85 118
tttt051779.50 14978.53 14982.41 17387.22 20261.43 23589.75 22294.76 2769.29 22367.91 22388.06 18272.92 2195.63 14362.91 23473.90 20690.16 188
FIs79.47 15079.41 13779.67 24185.95 22159.40 26691.68 15693.94 5778.06 6768.96 20888.28 17566.61 5591.77 26766.20 20974.99 19987.82 215
BH-RMVSNet79.46 15177.65 16284.89 11591.68 11065.66 14093.55 8488.09 27472.93 14473.37 15591.12 14146.20 25696.12 12156.28 26585.61 12692.91 143
PCF-MVS73.15 979.29 15277.63 16384.29 13486.06 21965.96 13387.03 26291.10 17269.86 21769.79 20090.64 14657.54 14496.59 10864.37 22582.29 14790.32 186
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
Vis-MVSNet (Re-imp)79.24 15379.57 13278.24 26188.46 17552.29 31590.41 20389.12 24574.24 11569.13 20391.91 13265.77 6390.09 29159.00 25788.09 10592.33 155
114514_t79.17 15477.67 16183.68 14795.32 2665.53 14592.85 11091.60 15363.49 26867.92 22290.63 14846.65 25195.72 14167.01 19883.54 14289.79 192
VPA-MVSNet79.03 15578.00 15682.11 18885.95 22164.48 17193.22 9694.66 3275.05 10674.04 15284.95 21452.17 20593.52 21774.90 13767.04 25188.32 212
OPM-MVS79.00 15678.09 15481.73 19383.52 25963.83 18991.64 15890.30 19976.36 8971.97 17689.93 16146.30 25595.17 16175.10 13177.70 18086.19 245
EI-MVSNet78.97 15778.22 15381.25 20485.33 22962.73 21889.53 22693.21 8772.39 15772.14 17390.13 15860.99 11194.72 17267.73 19172.49 21586.29 242
AdaColmapbinary78.94 15877.00 17484.76 11996.34 1665.86 13592.66 11887.97 27762.18 28170.56 18692.37 12643.53 26897.35 6964.50 22482.86 14491.05 180
miper_enhance_ethall78.86 15977.97 15781.54 19988.00 18965.17 15291.41 16389.15 24375.19 10468.79 21283.98 22467.17 4892.82 23472.73 14765.30 25886.62 239
VPNet78.82 16077.53 16582.70 16484.52 24366.44 12093.93 6792.23 12580.46 3672.60 16488.38 17449.18 23293.13 22372.47 15163.97 27588.55 206
EPNet_dtu78.80 16179.26 14177.43 26988.06 18649.71 32891.96 14391.95 13877.67 7276.56 13091.28 14058.51 13690.20 28956.37 26480.95 15992.39 153
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
tfpn200view978.79 16277.43 16682.88 16092.21 9264.49 16992.05 13796.28 473.48 13471.75 17988.26 17760.07 12095.32 15745.16 30577.58 18288.83 200
TR-MVS78.77 16377.37 17082.95 15990.49 13560.88 24293.67 7990.07 20870.08 21474.51 14591.37 13945.69 25795.70 14260.12 25180.32 16192.29 157
mvs-test178.74 16477.95 15881.14 20783.22 26157.13 29193.96 6487.78 27875.42 9772.68 16290.80 14545.08 26194.54 17975.08 13277.49 18591.74 166
thres40078.68 16577.43 16682.43 17092.21 9264.49 16992.05 13796.28 473.48 13471.75 17988.26 17760.07 12095.32 15745.16 30577.58 18287.48 219
BH-untuned78.68 16577.08 17183.48 15489.84 14763.74 19292.70 11488.59 26371.57 19066.83 23888.65 17051.75 20895.39 15559.03 25684.77 13191.32 175
OMC-MVS78.67 16777.91 16080.95 21685.76 22557.40 28988.49 24488.67 26073.85 12472.43 17092.10 12949.29 23194.55 17872.73 14777.89 17890.91 181
tpm78.58 16877.03 17283.22 15685.94 22364.56 16783.21 28891.14 17178.31 6373.67 15479.68 28064.01 8192.09 26166.07 21071.26 22593.03 139
OpenMVScopyleft70.45 1178.54 16975.92 18886.41 6885.93 22471.68 1492.74 11292.51 11866.49 24964.56 25391.96 13143.88 26798.10 3554.61 26990.65 8789.44 198
EPMVS78.49 17075.98 18786.02 7891.21 12369.68 3980.23 30891.20 16775.25 10372.48 16878.11 29154.65 18093.69 21457.66 26183.04 14394.69 80
AUN-MVS78.37 17177.43 16681.17 20686.60 21157.45 28889.46 22891.16 16974.11 11774.40 14690.49 15155.52 17194.57 17574.73 13960.43 30391.48 170
thres100view90078.37 17177.01 17382.46 16991.89 10363.21 20591.19 18096.33 172.28 16070.45 18987.89 18460.31 11795.32 15745.16 30577.58 18288.83 200
GA-MVS78.33 17376.23 18484.65 12483.65 25766.30 12491.44 16290.14 20676.01 9170.32 19184.02 22342.50 27194.72 17270.98 16277.00 19192.94 142
cascas78.18 17475.77 19085.41 10287.14 20469.11 4792.96 10591.15 17066.71 24770.47 18786.07 20337.49 29696.48 11370.15 17079.80 16390.65 183
UniMVSNet_NR-MVSNet78.15 17577.55 16479.98 23284.46 24560.26 25492.25 12793.20 8977.50 7568.88 20986.61 19766.10 5892.13 25966.38 20662.55 28087.54 217
thres600view778.00 17676.66 17882.03 19091.93 10063.69 19591.30 17496.33 172.43 15570.46 18887.89 18460.31 11794.92 16742.64 31776.64 19387.48 219
FC-MVSNet-test77.99 17778.08 15577.70 26484.89 23855.51 30190.27 20793.75 6576.87 8166.80 23987.59 18765.71 6490.23 28862.89 23573.94 20487.37 222
Anonymous20240521177.96 17875.33 19485.87 8493.73 5564.52 16894.85 4385.36 29862.52 27976.11 13290.18 15629.43 32797.29 7368.51 18577.24 19095.81 40
cl-mvsnet277.94 17976.78 17681.42 20187.57 19464.93 16490.67 19688.86 25572.45 15467.63 22882.68 23664.07 8092.91 23271.79 15665.30 25886.44 240
XXY-MVS77.94 17976.44 18182.43 17082.60 26764.44 17392.01 13991.83 14373.59 13270.00 19685.82 20654.43 18594.76 16969.63 17368.02 24588.10 214
MS-PatchMatch77.90 18176.50 18082.12 18585.99 22069.95 3391.75 15492.70 10873.97 12162.58 27384.44 22041.11 27595.78 13463.76 22992.17 6780.62 316
FMVSNet377.73 18276.04 18682.80 16191.20 12468.99 5191.87 14591.99 13673.35 13667.04 23583.19 23256.62 15992.14 25859.80 25369.34 23487.28 225
miper_ehance_all_eth77.60 18376.44 18181.09 21385.70 22664.41 17690.65 19788.64 26272.31 15867.37 23382.52 23764.77 7492.64 24570.67 16665.30 25886.24 244
UniMVSNet (Re)77.58 18476.78 17679.98 23284.11 25160.80 24391.76 15293.17 9276.56 8769.93 19984.78 21663.32 9492.36 25464.89 22262.51 28286.78 233
PatchmatchNetpermissive77.46 18574.63 20085.96 8089.55 15470.35 2679.97 31289.55 22772.23 16270.94 18476.91 30257.03 14992.79 23754.27 27181.17 15794.74 79
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
v2v48277.42 18675.65 19282.73 16380.38 28467.13 10091.85 14790.23 20375.09 10569.37 20183.39 23053.79 19194.44 18371.77 15765.00 26486.63 238
RRT_MVS77.38 18776.59 17979.77 23990.91 12963.61 19991.15 18190.91 17972.28 16072.06 17587.28 19343.92 26689.04 29873.32 14167.47 24986.67 234
CHOSEN 280x42077.35 18876.95 17578.55 25687.07 20562.68 21969.71 33482.95 31868.80 23071.48 18287.27 19466.03 5984.00 32776.47 12382.81 14688.95 199
PS-MVSNAJss77.26 18976.31 18380.13 22980.64 28259.16 27090.63 20091.06 17472.80 14768.58 21684.57 21953.55 19393.96 20572.97 14371.96 21987.27 226
gg-mvs-nofinetune77.18 19074.31 20785.80 8791.42 11868.36 6471.78 32994.72 2949.61 33177.12 12545.92 34777.41 693.98 20467.62 19293.16 5295.05 70
MVP-Stereo77.12 19176.23 18479.79 23881.72 27366.34 12389.29 22990.88 18070.56 21062.01 27682.88 23349.34 22994.13 19265.55 21793.80 4178.88 328
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
X-MVStestdata76.86 19274.13 21185.05 11193.22 6563.78 19092.92 10892.66 11173.99 11978.18 11210.19 35955.25 17297.41 6579.16 10391.58 7593.95 113
DU-MVS76.86 19275.84 18979.91 23482.96 26560.26 25491.26 17591.54 15476.46 8868.88 20986.35 19956.16 16392.13 25966.38 20662.55 28087.35 223
Anonymous2024052976.84 19474.15 21084.88 11691.02 12564.95 16393.84 7591.09 17353.57 32173.00 15787.42 19035.91 30697.32 7169.14 18072.41 21792.36 154
cl_fuxian76.83 19575.47 19380.93 21785.02 23664.18 18590.39 20488.11 27371.66 18366.65 24081.64 24963.58 9192.56 24669.31 17862.86 27886.04 250
WR-MVS76.76 19675.74 19179.82 23784.60 24162.27 22592.60 11992.51 11876.06 9067.87 22585.34 21056.76 15590.24 28762.20 23963.69 27786.94 231
v114476.73 19774.88 19782.27 17780.23 28966.60 11691.68 15690.21 20573.69 12969.06 20681.89 24452.73 20194.40 18469.21 17965.23 26185.80 257
IterMVS-LS76.49 19875.18 19680.43 22284.49 24462.74 21790.64 19888.80 25672.40 15665.16 24881.72 24760.98 11292.27 25767.74 19064.65 26986.29 242
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
V4276.46 19974.55 20382.19 18179.14 30267.82 7990.26 20889.42 23273.75 12768.63 21581.89 24451.31 21294.09 19471.69 15964.84 26584.66 273
v14876.19 20074.47 20581.36 20280.05 29064.44 17391.75 15490.23 20373.68 13067.13 23480.84 26455.92 16993.86 21168.95 18261.73 29185.76 260
Effi-MVS+-dtu76.14 20175.28 19578.72 25583.22 26155.17 30389.87 21987.78 27875.42 9767.98 22181.43 25345.08 26192.52 24875.08 13271.63 22088.48 207
cl-mvsnet_76.07 20274.67 19880.28 22585.15 23261.76 22990.12 21188.73 25871.16 19865.43 24581.57 25161.15 10992.95 22766.54 20362.17 28486.13 248
cl-mvsnet176.07 20274.67 19880.28 22585.14 23361.75 23090.12 21188.73 25871.16 19865.42 24681.60 25061.15 10992.94 23166.54 20362.16 28686.14 246
FMVSNet276.07 20274.01 21382.26 17988.85 16667.66 8391.33 17291.61 15270.84 20465.98 24282.25 24048.03 24092.00 26358.46 25868.73 24087.10 227
v14419276.05 20574.03 21282.12 18579.50 29666.55 11891.39 16789.71 22572.30 15968.17 21981.33 25651.75 20894.03 20167.94 18864.19 27185.77 258
NR-MVSNet76.05 20574.59 20180.44 22182.96 26562.18 22690.83 19191.73 14677.12 7960.96 27986.35 19959.28 13091.80 26660.74 24661.34 29587.35 223
v119275.98 20773.92 21482.15 18279.73 29266.24 12791.22 17789.75 21972.67 14968.49 21781.42 25449.86 22594.27 18867.08 19765.02 26385.95 254
eth_miper_zixun_eth75.96 20874.40 20680.66 21984.66 24063.02 20889.28 23088.27 27071.88 17465.73 24381.65 24859.45 12692.81 23568.13 18660.53 30186.14 246
TranMVSNet+NR-MVSNet75.86 20974.52 20479.89 23582.44 26860.64 25091.37 17091.37 16276.63 8567.65 22786.21 20252.37 20491.55 27161.84 24160.81 29887.48 219
SCA75.82 21072.76 22585.01 11386.63 21070.08 2881.06 30289.19 24071.60 18970.01 19577.09 30045.53 25890.25 28460.43 24873.27 20894.68 81
LPG-MVS_test75.82 21074.58 20279.56 24584.31 24859.37 26790.44 20189.73 22269.49 22064.86 24988.42 17238.65 28494.30 18672.56 14972.76 21285.01 270
GBi-Net75.65 21273.83 21581.10 21088.85 16665.11 15590.01 21590.32 19570.84 20467.04 23580.25 27448.03 24091.54 27259.80 25369.34 23486.64 235
test175.65 21273.83 21581.10 21088.85 16665.11 15590.01 21590.32 19570.84 20467.04 23580.25 27448.03 24091.54 27259.80 25369.34 23486.64 235
v192192075.63 21473.49 21982.06 18979.38 29766.35 12291.07 18589.48 22971.98 16967.99 22081.22 25949.16 23493.90 20866.56 20264.56 27085.92 256
ACMP71.68 1075.58 21574.23 20979.62 24384.97 23759.64 26290.80 19289.07 24870.39 21162.95 26987.30 19238.28 28793.87 20972.89 14471.45 22385.36 266
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
v875.35 21673.26 22181.61 19880.67 28166.82 10989.54 22589.27 23671.65 18463.30 26780.30 27354.99 17894.06 19767.33 19562.33 28383.94 278
tpm cat175.30 21772.21 23384.58 12788.52 17267.77 8078.16 32188.02 27561.88 28568.45 21876.37 30660.65 11494.03 20153.77 27474.11 20291.93 164
PLCcopyleft68.80 1475.23 21873.68 21779.86 23692.93 7458.68 27490.64 19888.30 26860.90 28964.43 25790.53 14942.38 27294.57 17556.52 26376.54 19486.33 241
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
v124075.21 21972.98 22381.88 19179.20 29966.00 13190.75 19489.11 24671.63 18867.41 23181.22 25947.36 24893.87 20965.46 21864.72 26885.77 258
Fast-Effi-MVS+-dtu75.04 22073.37 22080.07 23080.86 27859.52 26591.20 17985.38 29771.90 17265.20 24784.84 21541.46 27492.97 22666.50 20572.96 21187.73 216
dp75.01 22172.09 23483.76 14289.28 15866.22 12879.96 31389.75 21971.16 19867.80 22677.19 29951.81 20792.54 24750.39 28271.44 22492.51 152
TAPA-MVS70.22 1274.94 22273.53 21879.17 25090.40 13752.07 31689.19 23389.61 22662.69 27770.07 19492.67 11848.89 23794.32 18538.26 33179.97 16291.12 179
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
v1074.77 22372.54 23081.46 20080.33 28766.71 11389.15 23489.08 24770.94 20263.08 26879.86 27852.52 20294.04 20065.70 21462.17 28483.64 280
XVG-OURS-SEG-HR74.70 22473.08 22279.57 24478.25 31257.33 29080.49 30487.32 28263.22 27168.76 21390.12 16044.89 26391.59 27070.55 16874.09 20389.79 192
ACMM69.62 1374.34 22572.73 22679.17 25084.25 25057.87 28190.36 20589.93 21463.17 27265.64 24486.04 20537.79 29494.10 19365.89 21171.52 22285.55 263
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
CNLPA74.31 22672.30 23280.32 22391.49 11761.66 23190.85 19080.72 32456.67 31463.85 26190.64 14646.75 25090.84 27953.79 27375.99 19788.47 209
XVG-OURS74.25 22772.46 23179.63 24278.45 31157.59 28680.33 30687.39 28163.86 26668.76 21389.62 16440.50 27791.72 26869.00 18174.25 20189.58 195
CVMVSNet74.04 22874.27 20873.33 30085.33 22943.94 34289.53 22688.39 26654.33 32070.37 19090.13 15849.17 23384.05 32561.83 24279.36 16691.99 163
Baseline_NR-MVSNet73.99 22972.83 22477.48 26880.78 27959.29 26991.79 14984.55 30568.85 22968.99 20780.70 26556.16 16392.04 26262.67 23660.98 29781.11 310
pmmvs473.92 23071.81 23780.25 22779.17 30065.24 15087.43 25987.26 28467.64 24163.46 26483.91 22548.96 23691.53 27562.94 23365.49 25783.96 277
D2MVS73.80 23172.02 23579.15 25279.15 30162.97 20988.58 24390.07 20872.94 14359.22 28778.30 28842.31 27392.70 24165.59 21672.00 21881.79 307
CR-MVSNet73.79 23270.82 24482.70 16483.15 26367.96 7570.25 33184.00 31073.67 13169.97 19772.41 32157.82 14189.48 29552.99 27773.13 20990.64 184
test_djsdf73.76 23372.56 22977.39 27077.00 32053.93 30889.07 23690.69 18465.80 25363.92 25982.03 24343.14 27092.67 24272.83 14568.53 24185.57 262
pmmvs573.35 23471.52 23978.86 25478.64 30960.61 25191.08 18386.90 28567.69 23863.32 26683.64 22644.33 26590.53 28162.04 24066.02 25685.46 264
Anonymous2023121173.08 23570.39 24681.13 20890.62 13463.33 20291.40 16590.06 21151.84 32664.46 25680.67 26736.49 30494.07 19663.83 22864.17 27285.98 252
miper_lstm_enhance73.05 23671.73 23877.03 27483.80 25458.32 27881.76 29488.88 25369.80 21861.01 27878.23 29057.19 14687.51 31365.34 21959.53 30585.27 269
jajsoiax73.05 23671.51 24077.67 26577.46 31754.83 30488.81 23990.04 21269.13 22762.85 27183.51 22831.16 32292.75 23870.83 16369.80 23085.43 265
LCM-MVSNet-Re72.93 23871.84 23676.18 28388.49 17348.02 33280.07 31170.17 34473.96 12252.25 31580.09 27749.98 22388.24 30467.35 19384.23 14092.28 158
pm-mvs172.89 23971.09 24278.26 26079.10 30357.62 28590.80 19289.30 23567.66 23962.91 27081.78 24649.11 23592.95 22760.29 25058.89 30884.22 276
tpmvs72.88 24069.76 25282.22 18090.98 12667.05 10278.22 32088.30 26863.10 27364.35 25874.98 31355.09 17794.27 18843.25 31169.57 23385.34 267
test0.0.03 172.76 24172.71 22772.88 30480.25 28847.99 33391.22 17789.45 23071.51 19362.51 27487.66 18653.83 18985.06 32250.16 28367.84 24885.58 261
UniMVSNet_ETH3D72.74 24270.53 24579.36 24778.62 31056.64 29485.01 27389.20 23963.77 26764.84 25184.44 22034.05 31191.86 26563.94 22770.89 22789.57 196
mvs_tets72.71 24371.11 24177.52 26677.41 31854.52 30688.45 24689.76 21868.76 23262.70 27283.26 23129.49 32692.71 23970.51 16969.62 23285.34 267
FMVSNet172.71 24369.91 25081.10 21083.60 25865.11 15590.01 21590.32 19563.92 26563.56 26380.25 27436.35 30591.54 27254.46 27066.75 25386.64 235
IterMVS72.65 24570.83 24378.09 26282.17 26962.96 21087.64 25786.28 28971.56 19160.44 28178.85 28645.42 26086.66 31763.30 23161.83 28884.65 274
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
test_part172.36 24669.25 25481.68 19779.94 29165.07 15990.68 19589.53 22852.32 32363.42 26579.21 28440.43 27894.01 20367.14 19660.59 30085.96 253
PatchMatch-RL72.06 24769.98 24778.28 25989.51 15555.70 30083.49 28283.39 31661.24 28863.72 26282.76 23434.77 30993.03 22553.37 27677.59 18186.12 249
PVSNet_068.08 1571.81 24868.32 26082.27 17784.68 23962.31 22488.68 24190.31 19875.84 9257.93 29880.65 26837.85 29394.19 19169.94 17129.05 35090.31 187
MIMVSNet71.64 24968.44 25881.23 20581.97 27264.44 17373.05 32888.80 25669.67 21964.59 25274.79 31432.79 31487.82 30853.99 27276.35 19591.42 171
IterMVS-SCA-FT71.55 25069.97 24876.32 28181.48 27460.67 24987.64 25785.99 29366.17 25159.50 28578.88 28545.53 25883.65 32962.58 23761.93 28784.63 275
v7n71.31 25168.65 25679.28 24876.40 32260.77 24586.71 26789.45 23064.17 26458.77 29278.24 28944.59 26493.54 21657.76 25961.75 29083.52 283
anonymousdsp71.14 25269.37 25376.45 28072.95 33154.71 30584.19 27788.88 25361.92 28462.15 27579.77 27938.14 28991.44 27768.90 18367.45 25083.21 289
testing_271.09 25367.32 26582.40 17469.82 34066.52 11983.64 28090.77 18272.21 16345.12 33771.07 32927.60 33293.74 21275.71 12769.96 22986.95 230
F-COLMAP70.66 25468.44 25877.32 27186.37 21555.91 29888.00 25086.32 28856.94 31257.28 30188.07 18133.58 31292.49 24951.02 28068.37 24283.55 281
WR-MVS_H70.59 25569.94 24972.53 30681.03 27751.43 31987.35 26092.03 13567.38 24260.23 28280.70 26555.84 17083.45 33146.33 30158.58 30982.72 295
CP-MVSNet70.50 25669.91 25072.26 30980.71 28051.00 32287.23 26190.30 19967.84 23659.64 28482.69 23550.23 22282.30 33951.28 27959.28 30683.46 285
RPMNet70.42 25765.68 27384.63 12683.15 26367.96 7570.25 33190.45 18946.83 33969.97 19765.10 33856.48 16295.30 16035.79 33673.13 20990.64 184
tfpnnormal70.10 25867.36 26378.32 25883.45 26060.97 24188.85 23892.77 10664.85 26060.83 28078.53 28743.52 26993.48 21831.73 34661.70 29280.52 317
TransMVSNet (Re)70.07 25967.66 26277.31 27280.62 28359.13 27191.78 15184.94 30165.97 25260.08 28380.44 27050.78 21691.87 26448.84 28945.46 33580.94 312
CL-MVSNet_2432*160069.92 26068.09 26175.41 28673.25 33055.90 29990.05 21489.90 21569.96 21561.96 27776.54 30351.05 21587.64 31049.51 28750.59 32882.70 297
DP-MVS69.90 26166.48 26780.14 22895.36 2562.93 21189.56 22376.11 33150.27 33057.69 29985.23 21139.68 28095.73 13733.35 34071.05 22681.78 308
PS-CasMVS69.86 26269.13 25572.07 31280.35 28650.57 32487.02 26389.75 21967.27 24359.19 28882.28 23946.58 25282.24 34050.69 28159.02 30783.39 287
MSDG69.54 26365.73 27280.96 21585.11 23563.71 19484.19 27783.28 31756.95 31154.50 30684.03 22231.50 32096.03 12842.87 31569.13 23783.14 291
PEN-MVS69.46 26468.56 25772.17 31179.27 29849.71 32886.90 26589.24 23767.24 24659.08 28982.51 23847.23 24983.54 33048.42 29157.12 31083.25 288
LS3D69.17 26566.40 26877.50 26791.92 10156.12 29785.12 27280.37 32546.96 33756.50 30387.51 18937.25 29793.71 21332.52 34579.40 16582.68 298
PatchT69.11 26665.37 27780.32 22382.07 27163.68 19667.96 34087.62 28050.86 32969.37 20165.18 33757.09 14788.53 30241.59 32066.60 25488.74 203
KD-MVS_2432*160069.03 26766.37 26977.01 27585.56 22761.06 23981.44 29990.25 20167.27 24358.00 29676.53 30454.49 18287.63 31148.04 29335.77 34682.34 301
miper_refine_blended69.03 26766.37 26977.01 27585.56 22761.06 23981.44 29990.25 20167.27 24358.00 29676.53 30454.49 18287.63 31148.04 29335.77 34682.34 301
MVS_030468.99 26967.23 26674.28 29580.36 28552.54 31387.01 26486.36 28759.89 29866.22 24173.56 31724.25 33788.03 30657.34 26270.11 22882.27 303
ACMH63.93 1768.62 27064.81 27880.03 23185.22 23163.25 20387.72 25584.66 30460.83 29051.57 31879.43 28327.29 33394.96 16441.76 31864.84 26581.88 306
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
EG-PatchMatch MVS68.55 27165.41 27677.96 26378.69 30862.93 21189.86 22089.17 24160.55 29150.27 32377.73 29422.60 34294.06 19747.18 29972.65 21476.88 335
ADS-MVSNet68.54 27264.38 28581.03 21488.06 18666.90 10768.01 33884.02 30957.57 30664.48 25469.87 33038.68 28289.21 29740.87 32267.89 24686.97 228
DTE-MVSNet68.46 27367.33 26471.87 31477.94 31549.00 33186.16 27088.58 26466.36 25058.19 29382.21 24146.36 25383.87 32844.97 30855.17 31782.73 294
our_test_368.29 27464.69 28079.11 25378.92 30464.85 16588.40 24785.06 29960.32 29452.68 31376.12 30840.81 27689.80 29444.25 31055.65 31582.67 299
Patchmatch-RL test68.17 27564.49 28379.19 24971.22 33553.93 30870.07 33371.54 34369.22 22456.79 30262.89 34056.58 16088.61 29969.53 17552.61 32395.03 73
XVG-ACMP-BASELINE68.04 27665.53 27575.56 28574.06 32952.37 31478.43 31785.88 29462.03 28258.91 29181.21 26120.38 34591.15 27860.69 24768.18 24383.16 290
FMVSNet568.04 27665.66 27475.18 28884.43 24657.89 28083.54 28186.26 29061.83 28653.64 31173.30 31837.15 30085.08 32148.99 28861.77 28982.56 300
ppachtmachnet_test67.72 27863.70 28779.77 23978.92 30466.04 13088.68 24182.90 31960.11 29655.45 30475.96 30939.19 28190.55 28039.53 32652.55 32482.71 296
ACMH+65.35 1667.65 27964.55 28176.96 27784.59 24257.10 29288.08 24980.79 32358.59 30553.00 31281.09 26326.63 33592.95 22746.51 30061.69 29380.82 313
pmmvs667.57 28064.76 27976.00 28472.82 33353.37 31088.71 24086.78 28653.19 32257.58 30078.03 29235.33 30892.41 25155.56 26754.88 31982.21 304
Anonymous2023120667.53 28165.78 27172.79 30574.95 32647.59 33588.23 24887.32 28261.75 28758.07 29577.29 29737.79 29487.29 31542.91 31363.71 27683.48 284
Patchmtry67.53 28163.93 28678.34 25782.12 27064.38 17768.72 33584.00 31048.23 33659.24 28672.41 32157.82 14189.27 29646.10 30256.68 31481.36 309
USDC67.43 28364.51 28276.19 28277.94 31555.29 30278.38 31885.00 30073.17 13848.36 32980.37 27121.23 34492.48 25052.15 27864.02 27480.81 314
ADS-MVSNet266.90 28463.44 28977.26 27388.06 18660.70 24868.01 33875.56 33457.57 30664.48 25469.87 33038.68 28284.10 32440.87 32267.89 24686.97 228
CMPMVSbinary48.56 2166.77 28564.41 28473.84 29770.65 33850.31 32577.79 32285.73 29645.54 34044.76 33882.14 24235.40 30790.14 29063.18 23274.54 20081.07 311
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
OpenMVS_ROBcopyleft61.12 1866.39 28662.92 29276.80 27976.51 32157.77 28289.22 23183.41 31555.48 31853.86 31077.84 29326.28 33693.95 20634.90 33868.76 23978.68 330
LTVRE_ROB59.60 1966.27 28763.54 28874.45 29284.00 25351.55 31867.08 34183.53 31358.78 30354.94 30580.31 27234.54 31093.23 22240.64 32468.03 24478.58 331
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
JIA-IIPM66.06 28862.45 29576.88 27881.42 27654.45 30757.49 34988.67 26049.36 33263.86 26046.86 34656.06 16690.25 28449.53 28668.83 23885.95 254
Patchmatch-test65.86 28960.94 30180.62 22083.75 25558.83 27258.91 34875.26 33644.50 34350.95 32277.09 30058.81 13587.90 30735.13 33764.03 27395.12 67
UnsupCasMVSNet_eth65.79 29063.10 29073.88 29670.71 33750.29 32681.09 30189.88 21672.58 15149.25 32774.77 31532.57 31687.43 31455.96 26641.04 34183.90 279
pmmvs-eth3d65.53 29162.32 29675.19 28769.39 34259.59 26382.80 29183.43 31462.52 27951.30 32072.49 31932.86 31387.16 31655.32 26850.73 32778.83 329
SixPastTwentyTwo64.92 29261.78 29974.34 29478.74 30749.76 32783.42 28579.51 32862.86 27450.27 32377.35 29530.92 32490.49 28245.89 30347.06 33382.78 292
OurMVSNet-221017-064.68 29362.17 29772.21 31076.08 32547.35 33680.67 30381.02 32256.19 31551.60 31779.66 28127.05 33488.56 30153.60 27553.63 32280.71 315
test_040264.54 29461.09 30074.92 28984.10 25260.75 24687.95 25179.71 32752.03 32552.41 31477.20 29832.21 31891.64 26923.14 34961.03 29672.36 341
testgi64.48 29562.87 29369.31 31871.24 33440.62 34685.49 27179.92 32665.36 25754.18 30883.49 22923.74 34084.55 32341.60 31960.79 29982.77 293
RPSCF64.24 29661.98 29871.01 31576.10 32445.00 33975.83 32575.94 33246.94 33858.96 29084.59 21831.40 32182.00 34147.76 29760.33 30486.04 250
EU-MVSNet64.01 29763.01 29167.02 32574.40 32838.86 35183.27 28686.19 29145.11 34154.27 30781.15 26236.91 30380.01 34448.79 29057.02 31182.19 305
test20.0363.83 29862.65 29467.38 32470.58 33939.94 34786.57 26884.17 30763.29 27051.86 31677.30 29637.09 30182.47 33738.87 33054.13 32179.73 323
MDA-MVSNet_test_wron63.78 29960.16 30274.64 29078.15 31360.41 25283.49 28284.03 30856.17 31739.17 34671.59 32737.22 29883.24 33442.87 31548.73 33080.26 320
YYNet163.76 30060.14 30374.62 29178.06 31460.19 25783.46 28483.99 31256.18 31639.25 34571.56 32837.18 29983.34 33242.90 31448.70 33180.32 319
K. test v363.09 30159.61 30573.53 29976.26 32349.38 33083.27 28677.15 33064.35 26247.77 33072.32 32328.73 32887.79 30949.93 28536.69 34583.41 286
COLMAP_ROBcopyleft57.96 2062.98 30259.65 30472.98 30381.44 27553.00 31283.75 27975.53 33548.34 33548.81 32881.40 25524.14 33890.30 28332.95 34260.52 30275.65 338
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
AllTest61.66 30358.06 30772.46 30779.57 29351.42 32080.17 30968.61 34651.25 32745.88 33281.23 25719.86 34686.58 31838.98 32857.01 31279.39 325
UnsupCasMVSNet_bld61.60 30457.71 30873.29 30168.73 34351.64 31778.61 31689.05 24957.20 31046.11 33161.96 34128.70 32988.60 30050.08 28438.90 34379.63 324
MDA-MVSNet-bldmvs61.54 30557.70 30973.05 30279.53 29557.00 29383.08 28981.23 32157.57 30634.91 34872.45 32032.79 31486.26 32035.81 33541.95 33975.89 337
DIV-MVS_2432*160060.87 30658.60 30667.68 32266.13 34439.93 34875.63 32684.70 30357.32 30949.57 32668.45 33329.55 32582.87 33548.09 29247.94 33280.25 321
TinyColmap60.32 30756.42 31372.00 31378.78 30653.18 31178.36 31975.64 33352.30 32441.59 34475.82 31114.76 35188.35 30335.84 33454.71 32074.46 339
MVS-HIRNet60.25 30855.55 31474.35 29384.37 24756.57 29571.64 33074.11 33734.44 34845.54 33642.24 35031.11 32389.81 29240.36 32576.10 19676.67 336
MIMVSNet160.16 30957.33 31068.67 31969.71 34144.13 34178.92 31584.21 30655.05 31944.63 33971.85 32523.91 33981.54 34332.63 34455.03 31880.35 318
PM-MVS59.40 31056.59 31167.84 32063.63 34641.86 34376.76 32363.22 35259.01 30251.07 32172.27 32411.72 35383.25 33361.34 24350.28 32978.39 332
new-patchmatchnet59.30 31156.48 31267.79 32165.86 34544.19 34082.47 29281.77 32059.94 29743.65 34266.20 33627.67 33181.68 34239.34 32741.40 34077.50 334
DSMNet-mixed56.78 31254.44 31563.79 32763.21 34729.44 35564.43 34364.10 35142.12 34551.32 31971.60 32631.76 31975.04 34636.23 33365.20 26286.87 232
pmmvs355.51 31351.50 31867.53 32357.90 35250.93 32380.37 30573.66 33840.63 34644.15 34164.75 33916.30 34878.97 34544.77 30940.98 34272.69 340
TDRefinement55.28 31451.58 31766.39 32659.53 35146.15 33876.23 32472.80 33944.60 34242.49 34376.28 30715.29 34982.39 33833.20 34143.75 33770.62 343
LF4IMVS54.01 31552.12 31659.69 32862.41 34939.91 34968.59 33668.28 34842.96 34444.55 34075.18 31214.09 35268.39 34941.36 32151.68 32570.78 342
N_pmnet50.55 31649.11 31954.88 33177.17 3194.02 36484.36 2762.00 36348.59 33345.86 33468.82 33232.22 31782.80 33631.58 34751.38 32677.81 333
new_pmnet49.31 31746.44 32057.93 32962.84 34840.74 34568.47 33762.96 35336.48 34735.09 34757.81 34314.97 35072.18 34732.86 34346.44 33460.88 347
FPMVS45.64 31843.10 32153.23 33351.42 35436.46 35264.97 34271.91 34129.13 35027.53 34961.55 3429.83 35565.01 35316.00 35255.58 31658.22 348
LCM-MVSNet40.54 31935.79 32254.76 33236.92 35930.81 35451.41 35069.02 34522.07 35224.63 35045.37 3484.56 36165.81 35133.67 33934.50 34867.67 344
ANet_high40.27 32035.20 32355.47 33034.74 36034.47 35363.84 34471.56 34248.42 33418.80 35341.08 3519.52 35664.45 35420.18 3508.66 35767.49 345
PMMVS237.93 32133.61 32450.92 33446.31 35624.76 35860.55 34750.05 35528.94 35120.93 35147.59 3454.41 36265.13 35225.14 34818.55 35262.87 346
Gipumacopyleft34.91 32231.44 32545.30 33570.99 33639.64 35019.85 35672.56 34020.10 35416.16 35521.47 3565.08 36071.16 34813.07 35343.70 33825.08 352
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
PMVScopyleft26.43 2231.84 32328.16 32642.89 33625.87 36227.58 35650.92 35149.78 35621.37 35314.17 35640.81 3522.01 36366.62 3509.61 35538.88 34434.49 351
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
E-PMN24.61 32424.00 32826.45 33943.74 35718.44 36160.86 34539.66 35715.11 3559.53 35822.10 3556.52 35846.94 3568.31 35610.14 35413.98 354
MVEpermissive24.84 2324.35 32519.77 33138.09 33734.56 36126.92 35726.57 35438.87 35911.73 35711.37 35727.44 3531.37 36450.42 35511.41 35414.60 35336.93 349
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
EMVS23.76 32623.20 33025.46