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

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

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

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

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




Method Infoallhigh-res
multi-view
indooroutdoorbotani.boulde.bridgedoorexhibi.lectur.living.loungeobserv.old co.statueterrac.
sort bysort bysort bysort bysorted bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort by
HPM-MVS++89.02 289.15 288.63 195.01 176.03 192.38 1392.85 3180.26 1187.78 1094.27 1575.89 696.81 687.45 796.44 193.05 58
CNVR-MVS88.93 389.13 388.33 394.77 273.82 690.51 3893.00 2380.90 888.06 894.06 2276.43 396.84 588.48 295.99 394.34 13
ACMMPR87.44 1387.23 1588.08 794.64 373.59 893.04 593.20 1676.78 4984.66 3394.52 668.81 5396.65 1184.53 2094.90 2494.00 25
region2R87.42 1587.20 1688.09 694.63 473.55 993.03 793.12 1976.73 5284.45 3694.52 669.09 5196.70 984.37 2394.83 2794.03 22
HFP-MVS87.58 1187.47 1287.94 1094.58 573.54 1193.04 593.24 1476.78 4984.91 2794.44 1170.78 3696.61 1384.53 2094.89 2593.66 33
#test#87.33 1787.13 1787.94 1094.58 573.54 1192.34 1493.24 1475.23 7684.91 2794.44 1170.78 3696.61 1383.75 2794.89 2593.66 33
MCST-MVS87.37 1687.25 1487.73 1894.53 772.46 3089.82 5293.82 473.07 10984.86 3292.89 4376.22 496.33 2084.89 1795.13 2194.40 11
APDe-MVS89.15 189.63 187.73 1894.49 871.69 3893.83 293.96 275.70 6891.06 196.03 176.84 297.03 389.09 195.65 1294.47 10
DP-MVS Recon83.11 6382.09 6986.15 4694.44 970.92 4788.79 7792.20 4870.53 14779.17 8891.03 7564.12 8696.03 2868.39 15290.14 6991.50 96
XVS87.18 1986.91 2188.00 894.42 1073.33 1592.78 892.99 2579.14 1883.67 4894.17 1867.45 6296.60 1583.06 3294.50 3294.07 20
X-MVStestdata80.37 11177.83 14588.00 894.42 1073.33 1592.78 892.99 2579.14 1883.67 4812.47 32067.45 6296.60 1583.06 3294.50 3294.07 20
mPP-MVS86.67 2686.32 2787.72 2094.41 1273.55 992.74 1092.22 4776.87 4782.81 5894.25 1666.44 6996.24 2382.88 3694.28 3893.38 46
NCCC88.06 688.01 988.24 594.41 1273.62 791.22 2992.83 3281.50 585.79 1993.47 3173.02 2397.00 484.90 1594.94 2394.10 18
MP-MVScopyleft87.71 1087.64 1087.93 1394.36 1473.88 492.71 1292.65 3777.57 3283.84 4594.40 1472.24 2996.28 2285.65 1195.30 2093.62 40
APD-MVScopyleft87.44 1387.52 1187.19 2794.24 1572.39 3191.86 2192.83 3273.01 11088.58 594.52 673.36 2096.49 1884.26 2495.01 2292.70 65
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
PGM-MVS86.68 2586.27 2887.90 1494.22 1673.38 1490.22 4793.04 2075.53 7083.86 4494.42 1367.87 5996.64 1282.70 3794.57 3193.66 33
CP-MVS87.11 2086.92 2087.68 2394.20 1773.86 593.98 192.82 3476.62 5483.68 4794.46 1067.93 5795.95 3184.20 2594.39 3593.23 50
MPTG87.53 1287.41 1387.90 1494.18 1874.25 290.23 4692.02 5479.45 1685.88 1694.80 368.07 5596.21 2486.69 895.34 1693.23 50
MTAPA87.23 1887.00 1887.90 1494.18 1874.25 286.58 15392.02 5479.45 1685.88 1694.80 368.07 5596.21 2486.69 895.34 1693.23 50
114514_t80.68 10179.51 10784.20 8394.09 2067.27 11289.64 5791.11 9058.75 26274.08 17490.72 8058.10 16795.04 5969.70 14389.42 7690.30 137
HPM-MVS87.11 2086.98 1987.50 2493.88 2172.16 3492.19 1793.33 1376.07 6583.81 4693.95 2469.77 4596.01 2985.15 1294.66 2994.32 14
ACMMP_Plus88.05 888.08 887.94 1093.70 2273.05 1790.86 3293.59 776.27 6288.14 695.09 271.06 3596.67 1087.67 496.37 294.09 19
HPM-MVS_fast85.35 4484.95 4586.57 4093.69 2370.58 5292.15 1891.62 7473.89 9282.67 6094.09 2162.60 11795.54 3880.93 4592.93 4493.57 41
TSAR-MVS + MP.88.02 988.11 787.72 2093.68 2472.13 3591.41 2592.35 4474.62 8388.90 493.85 2575.75 796.00 3087.80 394.63 3095.04 2
ACMMPcopyleft85.89 3685.39 3887.38 2593.59 2572.63 2592.74 1093.18 1876.78 4980.73 7993.82 2664.33 8496.29 2182.67 3890.69 6393.23 50
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
DeepC-MVS_fast79.65 386.91 2386.62 2487.76 1793.52 2672.37 3291.26 2693.04 2076.62 5484.22 4193.36 3371.44 3396.76 780.82 4795.33 1894.16 16
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
CDPH-MVS85.76 3785.29 4287.17 2893.49 2771.08 4288.58 8592.42 4268.32 18284.61 3493.48 2972.32 2896.15 2779.00 5695.43 1494.28 15
agg_prior386.16 3385.85 3587.10 3093.31 2872.86 2288.77 7891.68 7368.29 18384.26 4092.83 4572.83 2495.42 4384.97 1395.71 993.02 59
DP-MVS76.78 18674.57 19383.42 10693.29 2969.46 7188.55 8683.70 22763.98 22170.20 20988.89 11454.01 19694.80 6946.66 27581.88 15486.01 241
CPTT-MVS83.73 5283.33 5384.92 6793.28 3070.86 4892.09 1990.38 10768.75 17679.57 8492.83 4560.60 15393.04 14480.92 4691.56 5590.86 110
TEST993.26 3172.96 1888.75 7991.89 6368.44 18185.00 2593.10 3774.36 1595.41 44
train_agg86.43 2886.20 2987.13 2993.26 3172.96 1888.75 7991.89 6368.69 17785.00 2593.10 3774.43 1295.41 4484.97 1395.71 993.02 59
test_893.13 3372.57 2788.68 8291.84 6668.69 17784.87 3193.10 3774.43 1295.16 52
新几何183.42 10693.13 3370.71 5085.48 21257.43 27181.80 6791.98 5363.28 9392.27 16564.60 18092.99 4387.27 218
112180.84 9279.77 9884.05 8893.11 3570.78 4984.66 19285.42 21357.37 27281.76 6892.02 5263.41 9194.12 8967.28 15792.93 4487.26 219
AdaColmapbinary80.58 10479.42 10984.06 8793.09 3668.91 7989.36 6088.97 16269.27 16575.70 15189.69 9657.20 17495.77 3363.06 18788.41 9187.50 214
原ACMM184.35 7993.01 3768.79 8092.44 3963.96 22281.09 7491.57 6366.06 7395.45 4167.19 15994.82 2888.81 180
CSCG86.41 3086.19 3087.07 3192.91 3872.48 2990.81 3393.56 873.95 9183.16 5391.07 7275.94 595.19 5179.94 5494.38 3693.55 42
agg_prior186.22 3286.09 3286.62 3892.85 3971.94 3688.59 8491.78 6968.96 17484.41 3793.18 3674.94 894.93 6184.75 1995.33 1893.01 61
agg_prior92.85 3971.94 3691.78 6984.41 3794.93 61
MG-MVS83.41 5883.45 5183.28 11192.74 4162.28 20788.17 10089.50 13975.22 7781.49 6992.74 4966.75 6695.11 5472.85 11591.58 5492.45 72
APD-MVS_3200maxsize85.97 3485.88 3386.22 4592.69 4269.53 6891.93 2092.99 2573.54 9885.94 1594.51 965.80 7695.61 3583.04 3492.51 4993.53 44
test1286.80 3492.63 4370.70 5191.79 6882.71 5971.67 3196.16 2694.50 3293.54 43
test_prior386.73 2486.86 2386.33 4292.61 4469.59 6688.85 7592.97 2875.41 7284.91 2793.54 2774.28 1695.48 3983.31 2895.86 593.91 27
test_prior86.33 4292.61 4469.59 6692.97 2895.48 3993.91 27
SD-MVS88.06 688.50 686.71 3692.60 4672.71 2391.81 2293.19 1777.87 2990.32 294.00 2374.83 993.78 10887.63 594.27 3993.65 38
PAPM_NR83.02 6482.41 6384.82 6992.47 4766.37 12387.93 10791.80 6773.82 9377.32 12890.66 8167.90 5894.90 6570.37 13889.48 7593.19 54
DeepPCF-MVS80.84 188.10 588.56 586.73 3592.24 4869.03 7489.57 5893.39 1277.53 3689.79 394.12 2078.98 196.58 1785.66 1095.72 894.58 7
abl_685.23 4584.95 4586.07 4892.23 4970.48 5390.80 3492.08 5273.51 9985.26 2294.16 1962.75 11095.92 3282.46 4091.30 5891.81 90
SteuartSystems-ACMMP88.72 488.86 488.32 492.14 5072.96 1893.73 393.67 680.19 1288.10 794.80 373.76 1997.11 187.51 695.82 794.90 4
Skip Steuart: Steuart Systems R&D Blog.
UA-Net85.08 4884.96 4485.45 5392.07 5168.07 9989.78 5490.86 9582.48 284.60 3593.20 3569.35 4995.22 5071.39 13490.88 6293.07 57
旧先验191.96 5265.79 13486.37 20493.08 4169.31 5092.74 4688.74 183
MSLP-MVS++85.43 4285.76 3684.45 7691.93 5370.24 5490.71 3592.86 3077.46 3884.22 4192.81 4867.16 6592.94 14680.36 5094.35 3790.16 140
LFMVS81.82 7981.23 7983.57 10391.89 5463.43 18989.84 5181.85 24577.04 4483.21 5193.10 3752.26 20793.43 12871.98 12889.95 7293.85 30
PLCcopyleft70.83 1178.05 15776.37 16883.08 12091.88 5567.80 10388.19 9989.46 14164.33 21769.87 21988.38 12753.66 19893.58 11958.86 22282.73 14587.86 207
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
MVS_111021_HR85.14 4784.75 4786.32 4491.65 5672.70 2485.98 16890.33 11276.11 6482.08 6391.61 6271.36 3494.17 8881.02 4492.58 4892.08 84
test22291.50 5768.26 9584.16 20783.20 23154.63 28379.74 8291.63 6158.97 16291.42 5686.77 229
TSAR-MVS + GP.85.71 3885.33 3986.84 3391.34 5872.50 2889.07 6987.28 19476.41 5685.80 1890.22 8874.15 1895.37 4881.82 4191.88 5192.65 68
MAR-MVS81.84 7880.70 8585.27 5691.32 5971.53 4089.82 5290.92 9369.77 15678.50 9786.21 18762.36 12494.52 7665.36 17392.05 5089.77 159
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
DeepC-MVS79.81 287.08 2286.88 2287.69 2291.16 6072.32 3390.31 4493.94 377.12 4182.82 5794.23 1772.13 3097.09 284.83 1895.37 1593.65 38
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
3Dnovator+77.84 485.48 4084.47 4888.51 291.08 6173.49 1393.18 493.78 580.79 976.66 13993.37 3260.40 15796.75 877.20 7493.73 4295.29 1
VDD-MVS83.01 6582.36 6684.96 6491.02 6266.40 12288.91 7188.11 18177.57 3284.39 3993.29 3452.19 20893.91 9977.05 7788.70 8394.57 8
API-MVS81.99 7681.23 7984.26 8290.94 6370.18 6091.10 3089.32 14471.51 13578.66 9588.28 13065.26 7895.10 5764.74 17991.23 5987.51 213
testdata79.97 19790.90 6464.21 17484.71 21859.27 25885.40 2092.91 4262.02 13089.08 22568.95 14791.37 5786.63 233
PHI-MVS86.43 2886.17 3187.24 2690.88 6570.96 4492.27 1694.07 172.45 12185.22 2391.90 5569.47 4896.42 1983.28 3095.94 494.35 12
VNet82.21 7282.41 6381.62 16990.82 6660.93 21384.47 19789.78 13276.36 6084.07 4391.88 5664.71 8390.26 20770.68 13588.89 7993.66 33
PVSNet_Blended_VisFu82.62 6881.83 7484.96 6490.80 6769.76 6488.74 8191.70 7269.39 16178.96 9088.46 12665.47 7794.87 6774.42 10288.57 8690.24 138
LS3D76.95 18474.82 19183.37 10990.45 6867.36 11189.15 6786.94 19761.87 24069.52 22290.61 8251.71 21294.53 7446.38 27886.71 10988.21 202
VDDNet81.52 8480.67 8684.05 8890.44 6964.13 17689.73 5685.91 21071.11 13883.18 5293.48 2950.54 22093.49 12373.40 11288.25 9294.54 9
CNLPA78.08 15676.79 16381.97 15690.40 7071.07 4387.59 11384.55 22066.03 20272.38 19089.64 9857.56 17186.04 25159.61 21683.35 13888.79 181
PAPR81.66 8280.89 8483.99 9390.27 7164.00 18086.76 14991.77 7168.84 17577.13 13589.50 10067.63 6094.88 6667.55 15488.52 8993.09 56
Vis-MVSNetpermissive83.46 5782.80 6185.43 5490.25 7268.74 8490.30 4590.13 12176.33 6180.87 7792.89 4361.00 14694.20 8572.45 12290.97 6093.35 48
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
EPP-MVSNet83.40 5983.02 5784.57 7290.13 7364.47 17092.32 1590.73 9674.45 8579.35 8791.10 7069.05 5295.12 5372.78 11687.22 10394.13 17
HQP_MVS83.64 5483.14 5485.14 5990.08 7468.71 8591.25 2792.44 3979.12 2078.92 9191.00 7660.42 15595.38 4678.71 5986.32 11491.33 99
plane_prior790.08 7468.51 91
HyFIR77.63 17075.69 18383.44 10589.98 7668.58 9078.70 25287.50 19256.38 27775.80 15086.84 16158.67 16391.40 18561.58 20285.75 12290.34 136
IS-MVSNet83.15 6182.81 6084.18 8489.94 7763.30 19191.59 2388.46 17879.04 2279.49 8592.16 5065.10 8094.28 8167.71 15391.86 5294.95 3
plane_prior189.90 78
canonicalmvs85.91 3585.87 3486.04 4989.84 7969.44 7290.45 4293.00 2376.70 5388.01 991.23 6973.28 2193.91 9981.50 4388.80 8194.77 5
plane_prior689.84 7968.70 8760.42 155
NP-MVS89.62 8168.32 9390.24 86
HyFIR lowres test77.53 17175.40 18783.94 9689.59 8266.62 11980.36 23888.64 17556.29 27876.45 14285.17 20757.64 17093.28 13061.34 20583.10 14191.91 87
TAPA-MVS73.13 979.15 13777.94 14382.79 14189.59 8262.99 20088.16 10191.51 7965.77 20377.14 13491.09 7160.91 14793.21 13250.26 26487.05 10592.17 82
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
alignmvs85.48 4085.32 4085.96 5089.51 8469.47 7089.74 5592.47 3876.17 6387.73 1191.46 6770.32 3993.78 10881.51 4288.95 7894.63 6
PS-MVSNAJ81.69 8081.02 8383.70 9989.51 8468.21 9784.28 20590.09 12270.79 14281.26 7385.62 19963.15 9894.29 8075.62 9388.87 8088.59 192
ACMP74.13 681.51 8680.57 8784.36 7889.42 8668.69 8889.97 5091.50 8174.46 8475.04 16890.41 8453.82 19794.54 7377.56 7082.91 14289.86 155
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
BH-RMVSNet79.61 12678.44 13383.14 11789.38 8765.93 12984.95 18887.15 19573.56 9778.19 11289.79 9556.67 17793.36 12959.53 21886.74 10890.13 142
Regformer-186.41 3086.33 2686.64 3789.33 8870.93 4688.43 8791.39 8382.14 386.65 1490.09 9074.39 1495.01 6083.97 2690.63 6493.97 26
Regformer-286.63 2786.53 2586.95 3289.33 8871.24 4188.43 8792.05 5382.50 186.88 1390.09 9074.45 1195.61 3584.38 2290.63 6494.01 24
HQP-NCC89.33 8889.17 6376.41 5677.23 131
ACMP_Plane89.33 8889.17 6376.41 5677.23 131
HQP-MVS82.61 6982.02 7184.37 7789.33 8866.98 11689.17 6392.19 4976.41 5677.23 13190.23 8760.17 15895.11 5477.47 7185.99 11991.03 104
ACMM73.20 880.78 10079.84 9783.58 10289.31 9368.37 9289.99 4991.60 7570.28 15077.25 12989.66 9753.37 19993.53 12274.24 10582.85 14388.85 178
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
Test_1112_low_res76.40 18975.44 18679.27 20589.28 9458.09 23581.69 22887.07 19659.53 25672.48 18886.67 17061.30 13989.33 22060.81 20980.15 17190.41 134
F-COLMAP76.38 19074.33 19782.50 14789.28 9466.95 11888.41 9089.03 15464.05 21966.83 25088.61 12146.78 23792.89 14757.48 23478.55 18087.67 209
LPG-MVS_test82.08 7381.27 7884.50 7489.23 9668.76 8290.22 4791.94 6175.37 7476.64 14091.51 6454.29 19294.91 6378.44 6183.78 13589.83 156
LGP-MVS_train84.50 7489.23 9668.76 8291.94 6175.37 7476.64 14091.51 6454.29 19294.91 6378.44 6183.78 13589.83 156
BH-untuned79.47 13178.60 12782.05 15489.19 9865.91 13086.07 16788.52 17772.18 12575.42 15587.69 14161.15 14393.54 12160.38 21086.83 10786.70 231
xiu_mvs_v2_base81.69 8081.05 8283.60 10189.15 9968.03 10084.46 19990.02 12670.67 14581.30 7286.53 18063.17 9794.19 8675.60 9488.54 8888.57 194
1112_ss77.40 18076.43 16680.32 19289.11 10060.41 21983.65 21387.72 18962.13 23873.05 18286.72 16562.58 11989.97 21162.11 19780.80 16290.59 124
Regformer-385.23 4585.07 4385.70 5288.95 10169.01 7688.29 9689.91 13080.95 785.01 2490.01 9272.45 2794.19 8682.50 3987.57 9693.90 29
Regformer-485.68 3985.45 3786.35 4188.95 10169.67 6588.29 9691.29 8581.73 485.36 2190.01 9272.62 2695.35 4983.28 3087.57 9694.03 22
Fast-Effi-MVS+80.81 9579.92 9683.47 10488.85 10364.51 16485.53 18189.39 14270.79 14278.49 9885.06 21067.54 6193.58 11967.03 16286.58 11092.32 76
PVSNet_BlendedMVS80.60 10280.02 9482.36 15088.85 10365.40 14086.16 16492.00 5769.34 16478.11 11486.09 19066.02 7494.27 8271.52 13282.06 15187.39 215
PVSNet_Blended80.98 9080.34 9082.90 13288.85 10365.40 14084.43 20192.00 5767.62 18778.11 11485.05 21166.02 7494.27 8271.52 13289.50 7489.01 174
MVS_111021_LR82.61 6982.11 6884.11 8588.82 10671.58 3985.15 18586.16 20774.69 8280.47 8091.04 7362.29 12590.55 20580.33 5190.08 7090.20 139
BH-w/o78.21 15277.33 15580.84 18488.81 10765.13 15084.87 18987.85 18769.75 15774.52 17284.74 21661.34 13893.11 14058.24 22985.84 12184.27 256
FIs82.07 7482.42 6281.04 18288.80 10858.34 23388.26 9893.49 976.93 4678.47 9991.04 7369.92 4392.34 16469.87 14284.97 12492.44 73
OPM-MVS83.50 5682.95 5885.14 5988.79 10970.95 4589.13 6891.52 7877.55 3580.96 7691.75 5760.71 14994.50 7779.67 5586.51 11289.97 152
WR-MVS79.49 13079.22 11980.27 19488.79 10958.35 23285.06 18688.61 17678.56 2677.65 12288.34 12863.81 9090.66 20464.98 17777.22 19391.80 91
OMC-MVS82.69 6781.97 7384.85 6888.75 11167.42 10887.98 10390.87 9474.92 8079.72 8391.65 5962.19 12893.96 9475.26 9886.42 11393.16 55
ACMH67.68 1675.89 19573.93 20081.77 16088.71 11266.61 12088.62 8389.01 15769.81 15566.78 25186.70 16941.95 26491.51 18455.64 24478.14 18687.17 221
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
Vis-MVSNet (Re-imp)78.36 15078.45 13178.07 22188.64 11351.78 28086.70 15079.63 26574.14 8975.11 16690.83 7961.29 14089.75 21358.10 23091.60 5392.69 67
PatchMatch-RL72.38 22470.90 22476.80 23588.60 11467.38 11079.53 24476.17 27962.75 23269.36 22582.00 24145.51 24584.89 25753.62 25180.58 16578.12 290
ACMH+68.96 1476.01 19474.01 19982.03 15588.60 11465.31 14588.86 7487.55 19170.25 15167.75 24187.47 14841.27 26593.19 13558.37 22775.94 21587.60 211
LTVRE_ROB69.57 1376.25 19174.54 19581.41 17488.60 11464.38 17379.24 24789.12 15370.76 14469.79 22187.86 13849.09 22893.20 13456.21 24380.16 17086.65 232
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
DELS-MVS85.41 4385.30 4185.77 5188.49 11767.93 10185.52 18293.44 1078.70 2583.63 5089.03 11374.57 1095.71 3480.26 5294.04 4093.66 33
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
CLD-MVS82.31 7181.65 7584.29 8188.47 11867.73 10585.81 17492.35 4475.78 6678.33 10586.58 17764.01 8794.35 7976.05 8487.48 10190.79 111
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
UniMVSNet_NR-MVSNet81.88 7781.54 7682.92 13188.46 11963.46 18787.13 13492.37 4380.19 1278.38 10389.14 11071.66 3293.05 14270.05 13976.46 21092.25 79
ab-mvs79.51 12878.97 12381.14 18088.46 11960.91 21483.84 21189.24 14970.36 14979.03 8988.87 11563.23 9690.21 20965.12 17482.57 14892.28 78
FC-MVSNet-test81.52 8482.02 7180.03 19688.42 12155.97 26387.95 10593.42 1177.10 4277.38 12690.98 7869.96 4291.79 17268.46 15184.50 12992.33 75
Effi-MVS+83.62 5583.08 5585.24 5788.38 12267.45 10788.89 7289.15 15175.50 7182.27 6188.28 13069.61 4694.45 7877.81 6887.84 9493.84 31
UniMVSNet (Re)81.60 8381.11 8183.09 11988.38 12264.41 17287.60 11293.02 2278.42 2878.56 9688.16 13369.78 4493.26 13169.58 14476.49 20991.60 92
VPNet78.69 14578.66 12678.76 21288.31 12455.72 26584.45 20086.63 20076.79 4878.26 11090.55 8359.30 16089.70 21566.63 16377.05 19590.88 109
TR-MVS77.44 17876.18 17481.20 17888.24 12563.24 19384.61 19586.40 20367.55 18877.81 11986.48 18254.10 19493.15 13757.75 23382.72 14687.20 220
EI-MVSNet-Vis-set84.19 4983.81 4985.31 5588.18 12667.85 10287.66 11189.73 13480.05 1482.95 5489.59 9970.74 3894.82 6880.66 4984.72 12893.28 49
test_040272.79 22270.44 22679.84 19888.13 12765.99 12885.93 17084.29 22265.57 20667.40 24685.49 20246.92 23692.61 15535.88 29874.38 23480.94 280
VPA-MVSNet80.60 10280.55 8880.76 18688.07 12860.80 21686.86 14391.58 7675.67 6980.24 8189.45 10663.34 9290.25 20870.51 13779.22 17991.23 102
UGNet80.83 9479.59 10384.54 7388.04 12968.09 9889.42 5988.16 18076.95 4576.22 14489.46 10449.30 22693.94 9668.48 15090.31 6691.60 92
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
WR-MVS_H78.51 14778.49 13078.56 21588.02 13056.38 25888.43 8792.67 3577.14 4073.89 17587.55 14566.25 7089.24 22258.92 22173.55 24390.06 149
mvs-test182.41 6388.01 13165.80 13288.89 7289.15 15175.14 7980.77 7888.20 13269.61 4694.53 7475.75 8786.14 117
QAPM80.88 9179.50 10885.03 6288.01 13168.97 7891.59 2392.00 5766.63 19675.15 16592.16 5057.70 16995.45 4163.52 18388.76 8290.66 119
3Dnovator76.31 583.38 6082.31 6786.59 3987.94 13372.94 2190.64 3692.14 5177.21 3975.47 15292.83 4558.56 16494.72 7173.24 11392.71 4792.13 83
EI-MVSNet-UG-set83.81 5183.38 5285.09 6187.87 13467.53 10687.44 12289.66 13579.74 1582.23 6289.41 10870.24 4094.74 7079.95 5383.92 13492.99 62
TranMVSNet+NR-MVSNet80.84 9280.31 9182.42 14887.85 13562.33 20587.74 11091.33 8480.55 1077.99 11789.86 9465.23 7992.62 15467.05 16175.24 22892.30 77
CP-MVSNet78.22 15178.34 13677.84 22387.83 13654.54 26987.94 10691.17 8977.65 3073.48 17788.49 12562.24 12788.43 23462.19 19474.07 23590.55 128
DU-MVS81.12 8980.52 8982.90 13287.80 13763.46 18787.02 13991.87 6579.01 2378.38 10389.07 11165.02 8193.05 14270.05 13976.46 21092.20 80
NR-MVSNet80.23 11479.38 11082.78 14287.80 13763.34 19086.31 16191.09 9179.01 2372.17 19189.07 11167.20 6492.81 15266.08 16875.65 21992.20 80
TAMVS78.89 14377.51 15283.03 12387.80 13767.79 10484.72 19185.05 21767.63 18676.75 13787.70 14062.25 12690.82 20158.53 22687.13 10490.49 130
PS-CasMVS78.01 15878.09 14077.77 22587.71 14054.39 27188.02 10291.22 8677.50 3773.26 17988.64 12060.73 14888.41 23561.88 19873.88 23990.53 129
PCF-MVS73.52 780.38 11078.84 12485.01 6387.71 14068.99 7783.65 21391.46 8263.00 22777.77 12190.28 8566.10 7195.09 5861.40 20388.22 9390.94 108
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
GBi-Net78.40 14877.40 15381.40 17587.60 14263.01 19788.39 9189.28 14571.63 13175.34 15887.28 15154.80 18691.11 19262.72 18879.57 17390.09 145
test178.40 14877.40 15381.40 17587.60 14263.01 19788.39 9189.28 14571.63 13175.34 15887.28 15154.80 18691.11 19262.72 18879.57 17390.09 145
FMVSNet278.20 15377.21 15681.20 17887.60 14262.89 20187.47 12189.02 15571.63 13175.29 16287.28 15154.80 18691.10 19562.38 19279.38 17689.61 162
CDS-MVSNet79.07 13977.70 14983.17 11587.60 14268.23 9684.40 20386.20 20667.49 18976.36 14386.54 17961.54 13490.79 20261.86 19987.33 10290.49 130
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
HY-MVS69.67 1277.95 16077.15 15780.36 19087.57 14660.21 22083.37 21887.78 18866.11 19975.37 15787.06 16063.27 9490.48 20661.38 20482.43 14990.40 135
xiu_mvs_v1_base_debu80.80 9779.72 10084.03 9087.35 14770.19 5785.56 17688.77 17169.06 16981.83 6488.16 13350.91 21792.85 14878.29 6587.56 9889.06 167
xiu_mvs_v1_base80.80 9779.72 10084.03 9087.35 14770.19 5785.56 17688.77 17169.06 16981.83 6488.16 13350.91 21792.85 14878.29 6587.56 9889.06 167
xiu_mvs_v1_base_debi80.80 9779.72 10084.03 9087.35 14770.19 5785.56 17688.77 17169.06 16981.83 6488.16 13350.91 21792.85 14878.29 6587.56 9889.06 167
MVSFormer82.85 6682.05 7085.24 5787.35 14770.21 5590.50 3990.38 10768.55 17981.32 7089.47 10261.68 13193.46 12478.98 5790.26 6792.05 85
lupinMVS81.39 8780.27 9384.76 7087.35 14770.21 5585.55 17986.41 20262.85 23081.32 7088.61 12161.68 13192.24 16778.41 6390.26 6791.83 88
PAPM77.68 16776.40 16781.51 17287.29 15261.85 21083.78 21289.59 13664.74 21271.23 20188.70 11762.59 11893.66 11852.66 25587.03 10689.01 174
LCM-MVSNet-Re77.05 18276.94 16077.36 22987.20 15351.60 28180.06 24080.46 25775.20 7867.69 24286.72 16562.48 12288.98 22763.44 18489.25 7791.51 95
COLMAP_ROBcopyleft66.92 1773.01 21970.41 22780.81 18587.13 15465.63 13588.30 9584.19 22462.96 22863.80 27087.69 14138.04 27792.56 15746.66 27574.91 22984.24 257
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
PEN-MVS77.73 16577.69 15077.84 22387.07 15553.91 27387.91 10891.18 8877.56 3473.14 18188.82 11661.23 14189.17 22359.95 21372.37 24990.43 133
pcd1.5k->3k34.07 29435.26 29530.50 30886.92 1560.00 3290.00 32091.58 760.00 3240.00 3250.00 32656.23 1790.00 3240.00 32382.60 14791.49 97
MVS_Test83.15 6183.06 5683.41 10886.86 15763.21 19486.11 16692.00 5774.31 8682.87 5689.44 10770.03 4193.21 13277.39 7388.50 9093.81 32
FMVSNet377.88 16376.85 16180.97 18386.84 15862.36 20486.52 15588.77 17171.13 13775.34 15886.66 17154.07 19591.10 19562.72 18879.57 17389.45 164
FMVSNet177.44 17876.12 17581.40 17586.81 15963.01 19788.39 9189.28 14570.49 14874.39 17387.28 15149.06 22991.11 19260.91 20778.52 18190.09 145
nrg03083.88 5083.53 5084.96 6486.77 16069.28 7390.46 4192.67 3574.79 8182.95 5491.33 6872.70 2593.09 14180.79 4879.28 17892.50 71
jason81.39 8780.29 9284.70 7186.63 16169.90 6285.95 16986.77 19863.24 22481.07 7589.47 10261.08 14592.15 16878.33 6490.07 7192.05 85
jason: jason.
PS-MVSNAJss82.07 7481.31 7784.34 8086.51 16267.27 11289.27 6191.51 7971.75 12979.37 8690.22 8863.15 9894.27 8277.69 6982.36 15091.49 97
WTY-MVS75.65 19875.68 18475.57 24386.40 16356.82 24977.92 25882.40 23865.10 20976.18 14687.72 13963.13 10180.90 27060.31 21181.96 15289.00 176
DTE-MVSNet76.99 18376.80 16277.54 22886.24 16453.06 27787.52 11990.66 9977.08 4372.50 18788.67 11960.48 15489.52 21757.33 23770.74 25990.05 150
PVSNet64.34 1872.08 22670.87 22575.69 24186.21 16556.44 25674.37 27680.73 25462.06 23970.17 21182.23 23542.86 25783.31 26354.77 24684.45 13187.32 217
IterMVS-LS80.06 11979.38 11082.11 15385.89 16663.20 19586.79 14689.34 14374.19 8775.45 15486.72 16566.62 6792.39 16172.58 12076.86 20190.75 113
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
Baseline_NR-MVSNet78.15 15578.33 13777.61 22785.79 16756.21 26186.78 14785.76 21173.60 9677.93 11887.57 14465.02 8188.99 22667.14 16075.33 22587.63 210
cascas76.72 18774.64 19282.99 12585.78 16865.88 13182.33 22289.21 15060.85 24672.74 18481.02 25447.28 23493.75 11267.48 15585.02 12389.34 165
MVS78.19 15476.99 15981.78 15985.66 16966.99 11584.66 19290.47 10555.08 28272.02 19585.27 20663.83 8994.11 9166.10 16789.80 7384.24 257
XVG-OURS80.41 10679.23 11883.97 9485.64 17069.02 7583.03 21990.39 10671.09 13977.63 12391.49 6654.62 19191.35 18675.71 9183.47 13791.54 94
XVG-OURS-SEG-HR80.81 9579.76 9983.96 9585.60 17168.78 8183.54 21690.50 10470.66 14676.71 13891.66 5860.69 15091.26 18876.94 7881.58 15691.83 88
TransMVSNet (Re)75.39 20174.56 19477.86 22285.50 17257.10 24786.78 14786.09 20972.17 12671.53 20087.34 15063.01 10289.31 22156.84 24061.83 28987.17 221
MVP-Stereo76.12 19274.46 19681.13 18185.37 17369.79 6384.42 20287.95 18565.03 21067.46 24485.33 20553.28 20091.73 17558.01 23183.27 13981.85 276
OpenMVScopyleft72.83 1079.77 12478.33 13784.09 8685.17 17469.91 6190.57 3790.97 9266.70 19272.17 19191.91 5454.70 18993.96 9461.81 20090.95 6188.41 200
AllTest70.96 23268.09 24379.58 20385.15 17563.62 18384.58 19679.83 26362.31 23660.32 27886.73 16332.02 29088.96 22950.28 26271.57 25586.15 237
TestCases79.58 20385.15 17563.62 18379.83 26362.31 23660.32 27886.73 16332.02 29088.96 22950.28 26271.57 25586.15 237
SixPastTwentyTwo73.37 21371.26 22179.70 20085.08 17757.89 24085.57 17583.56 22871.03 14065.66 25885.88 19242.10 26292.57 15659.11 22063.34 28688.65 185
EG-PatchMatch MVS74.04 20771.82 21580.71 18784.92 17867.42 10885.86 17288.08 18366.04 20164.22 26783.85 21935.10 28692.56 15757.44 23580.83 16182.16 275
IB-MVS68.01 1575.85 19673.36 20483.31 11084.76 17966.03 12683.38 21785.06 21670.21 15269.40 22381.05 25345.76 24394.66 7265.10 17575.49 22289.25 166
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
mvs_tets79.13 13877.77 14883.22 11484.70 18066.37 12389.17 6390.19 11969.38 16375.40 15689.46 10444.17 25093.15 13776.78 8180.70 16490.14 141
jajsoiax79.29 13577.96 14283.27 11284.68 18166.57 12189.25 6290.16 12069.20 16775.46 15389.49 10145.75 24493.13 13976.84 8080.80 16290.11 143
MIMVSNet70.69 23469.30 23174.88 24984.52 18256.35 25975.87 26879.42 26664.59 21367.76 24082.41 23241.10 26681.54 26946.64 27781.34 15786.75 230
MSDG73.36 21570.99 22380.49 18884.51 18365.80 13280.71 23586.13 20865.70 20465.46 25983.74 22244.60 24790.91 20051.13 25976.89 20084.74 253
mvs_anonymous79.42 13379.11 12080.34 19184.45 18457.97 23882.59 22087.62 19067.40 19176.17 14888.56 12468.47 5489.59 21670.65 13686.05 11893.47 45
EI-MVSNet80.52 10579.98 9582.12 15284.28 18563.19 19686.41 15888.95 16474.18 8878.69 9387.54 14666.62 6792.43 15972.57 12180.57 16690.74 114
CVMVSNet72.99 22072.58 20974.25 25584.28 18550.85 28786.41 15883.45 22944.56 30373.23 18087.54 14649.38 22485.70 25365.90 16978.44 18386.19 236
v1377.50 17676.07 18081.77 16084.23 18765.07 15187.34 12388.91 16972.92 11168.35 23881.97 24262.53 12191.69 18172.20 12766.22 28088.56 195
pm-mvs177.25 18176.68 16478.93 21084.22 18858.62 23086.41 15888.36 17971.37 13673.31 17888.01 13761.22 14289.15 22464.24 18173.01 24589.03 173
v1277.51 17476.09 17981.76 16284.22 18864.99 15287.30 12688.93 16872.92 11168.48 23781.97 24262.54 12091.70 18072.24 12666.21 28188.58 193
v1177.45 17776.06 18181.59 17184.22 18864.52 16287.11 13689.02 15572.76 11668.76 23181.90 24762.09 12991.71 17971.98 12866.73 27388.56 195
EPNet83.72 5382.92 5986.14 4784.22 18869.48 6991.05 3185.27 21481.30 676.83 13691.65 5966.09 7295.56 3776.00 8593.85 4193.38 46
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
V977.52 17276.11 17881.73 16384.19 19264.89 15587.26 12888.94 16772.87 11468.65 23381.96 24462.65 11691.72 17772.27 12566.24 27988.60 190
v1777.68 16776.35 17281.69 16584.15 19364.65 15987.33 12488.99 15972.70 11869.25 22882.07 23862.82 10891.79 17272.69 11967.15 27288.63 186
v1677.69 16676.36 17181.68 16684.15 19364.63 16187.33 12488.99 15972.69 11969.31 22782.08 23762.80 10991.79 17272.70 11867.23 27088.63 186
V1477.52 17276.12 17581.70 16484.15 19364.77 15787.21 13088.95 16472.80 11568.79 23081.94 24562.69 11391.72 17772.31 12466.27 27888.60 190
v1neww80.40 10779.54 10482.98 12684.10 19664.51 16487.57 11490.22 11673.25 10278.47 9986.65 17262.83 10693.86 10275.72 8977.02 19690.58 125
v7new80.40 10779.54 10482.98 12684.10 19664.51 16487.57 11490.22 11673.25 10278.47 9986.65 17262.83 10693.86 10275.72 8977.02 19690.58 125
v1877.67 16976.35 17281.64 16884.09 19864.47 17087.27 12789.01 15772.59 12069.39 22482.04 23962.85 10491.80 17172.72 11767.20 27188.63 186
v1577.51 17476.12 17581.66 16784.09 19864.65 15987.14 13188.96 16372.76 11668.90 22981.91 24662.74 11191.73 17572.32 12366.29 27788.61 189
v879.97 12179.02 12282.80 13984.09 19864.50 16887.96 10490.29 11574.13 9075.24 16386.81 16262.88 10393.89 10174.39 10375.40 22490.00 151
v680.40 10779.54 10482.98 12684.09 19864.50 16887.57 11490.22 11673.25 10278.47 9986.63 17462.84 10593.86 10275.73 8877.02 19690.58 125
v780.24 11379.26 11783.15 11684.07 20264.94 15487.56 11790.67 9772.26 12478.28 10686.51 18161.45 13694.03 9375.14 9977.41 19090.49 130
v1079.74 12578.67 12582.97 13084.06 20364.95 15387.88 10990.62 10073.11 10875.11 16686.56 17861.46 13594.05 9273.68 10875.55 22189.90 153
test_djsdf80.30 11279.32 11283.27 11283.98 20465.37 14390.50 3990.38 10768.55 17976.19 14588.70 11756.44 17893.46 12478.98 5780.14 17290.97 107
131476.53 18875.30 18880.21 19583.93 20562.32 20684.66 19288.81 17060.23 25070.16 21284.07 21855.30 18590.73 20367.37 15683.21 14087.59 212
MS-PatchMatch73.83 20972.67 20877.30 23183.87 20666.02 12781.82 22584.66 21961.37 24468.61 23582.82 22947.29 23388.21 23659.27 21984.32 13277.68 292
v114180.19 11679.31 11382.85 13583.84 20764.12 17787.14 13190.08 12373.13 10578.27 10786.39 18362.67 11593.75 11275.40 9676.83 20490.68 116
divwei89l23v2f11280.19 11679.31 11382.85 13583.84 20764.11 17987.13 13490.08 12373.13 10578.27 10786.39 18362.69 11393.75 11275.40 9676.82 20590.68 116
v180.19 11679.31 11382.85 13583.83 20964.12 17787.14 13190.07 12573.13 10578.27 10786.38 18562.72 11293.75 11275.41 9576.82 20590.68 116
v114480.03 12079.03 12183.01 12483.78 21064.51 16487.11 13690.57 10271.96 12878.08 11686.20 18861.41 13793.94 9674.93 10077.23 19290.60 122
OurMVSNet-221017-074.26 20672.42 21179.80 19983.76 21159.59 22285.92 17186.64 19966.39 19866.96 24987.58 14339.46 27191.60 18365.76 17169.27 26388.22 201
v2v48280.23 11479.29 11683.05 12283.62 21264.14 17587.04 13889.97 12773.61 9578.18 11387.22 15561.10 14493.82 10576.11 8376.78 20791.18 103
XXY-MVS75.41 20075.56 18574.96 24883.59 21357.82 24180.59 23783.87 22666.54 19774.93 16988.31 12963.24 9580.09 27462.16 19576.85 20286.97 226
v119279.59 12778.43 13483.07 12183.55 21464.52 16286.93 14190.58 10170.83 14177.78 12085.90 19159.15 16193.94 9673.96 10777.19 19490.76 112
tpmp4_e2373.45 21271.17 22280.31 19383.55 21459.56 22581.88 22482.33 23957.94 26770.51 20781.62 24851.19 21691.63 18253.96 24977.51 18989.75 160
v7n78.97 14277.58 15183.14 11783.45 21665.51 13888.32 9491.21 8773.69 9472.41 18986.32 18657.93 16893.81 10669.18 14675.65 21990.11 143
v14419279.47 13178.37 13582.78 14283.35 21763.96 18186.96 14090.36 11069.99 15377.50 12485.67 19760.66 15193.77 11074.27 10476.58 20890.62 120
tpm273.26 21671.46 21778.63 21383.34 21856.71 25280.65 23680.40 25856.63 27673.55 17682.02 24051.80 21191.24 18956.35 24278.42 18487.95 205
diffmvs79.51 12878.59 12882.25 15183.31 21962.66 20284.17 20688.11 18167.64 18576.09 14987.47 14864.01 8791.15 19171.71 13184.82 12792.94 63
v192192079.22 13678.03 14182.80 13983.30 22063.94 18286.80 14590.33 11269.91 15477.48 12585.53 20158.44 16593.75 11273.60 11176.85 20290.71 115
v124078.99 14177.78 14782.64 14683.21 22163.54 18586.62 15290.30 11469.74 15977.33 12785.68 19657.04 17693.76 11173.13 11476.92 19990.62 120
XVG-ACMP-BASELINE76.11 19374.27 19881.62 16983.20 22264.67 15883.60 21589.75 13369.75 15771.85 19687.09 15932.78 28992.11 16969.99 14180.43 16988.09 204
MDTV_nov1_ep1369.97 23083.18 22353.48 27577.10 26280.18 26260.45 24769.33 22680.44 25848.89 23086.90 24451.60 25778.51 182
PatchmatchNetpermissive73.12 21871.33 21978.49 21883.18 22360.85 21579.63 24378.57 26864.13 21871.73 19779.81 26451.20 21585.97 25257.40 23676.36 21288.66 184
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
gg-mvs-nofinetune69.95 24067.96 24475.94 23983.07 22554.51 27077.23 26170.29 30263.11 22570.32 20862.33 30443.62 25288.69 23353.88 25087.76 9584.62 255
MVSTER79.01 14077.88 14482.38 14983.07 22564.80 15684.08 21088.95 16469.01 17378.69 9387.17 15854.70 18992.43 15974.69 10180.57 16689.89 154
K. test v371.19 23068.51 23779.21 20783.04 22757.78 24284.35 20476.91 27772.90 11362.99 27382.86 22839.27 27291.09 19761.65 20152.66 30488.75 182
FMVSNet569.50 24267.96 24474.15 25682.97 22855.35 26680.01 24182.12 24362.56 23463.02 27181.53 24936.92 28181.92 26748.42 27074.06 23685.17 249
PatchFormer-LS_test74.50 20473.05 20678.86 21182.95 22959.55 22681.65 22982.30 24067.44 19071.62 19978.15 27152.34 20588.92 23165.05 17675.90 21688.12 203
DWT-MVSNet_test73.70 21071.86 21479.21 20782.91 23058.94 22882.34 22182.17 24165.21 20771.05 20378.31 26944.21 24990.17 21063.29 18677.28 19188.53 197
DI_MVS_plusplus_test79.89 12278.58 12983.85 9882.89 23165.32 14486.12 16589.55 13769.64 16070.55 20585.82 19557.24 17393.81 10676.85 7988.55 8792.41 74
sss73.60 21173.64 20273.51 25982.80 23255.01 26776.12 26481.69 24662.47 23574.68 17185.85 19457.32 17278.11 28260.86 20880.93 16087.39 215
GA-MVS76.87 18575.17 18981.97 15682.75 23362.58 20381.44 23286.35 20572.16 12774.74 17082.89 22746.20 23992.02 17068.85 14881.09 15991.30 101
v14878.72 14477.80 14681.47 17382.73 23461.96 20986.30 16288.08 18373.26 10176.18 14685.47 20362.46 12392.36 16371.92 13073.82 24090.09 145
test_normal79.81 12378.45 13183.89 9782.70 23565.40 14085.82 17389.48 14069.39 16170.12 21385.66 19857.15 17593.71 11777.08 7688.62 8592.56 70
CostFormer75.24 20273.90 20179.27 20582.65 23658.27 23480.80 23382.73 23661.57 24175.33 16183.13 22655.52 18391.07 19864.98 17778.34 18588.45 198
EPNet_dtu75.46 19974.86 19077.23 23282.57 23754.60 26886.89 14283.09 23271.64 13066.25 25685.86 19355.99 18088.04 23854.92 24586.55 11189.05 171
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
RPSCF73.23 21771.46 21778.54 21682.50 23859.85 22182.18 22382.84 23558.96 25971.15 20289.41 10845.48 24684.77 25858.82 22371.83 25391.02 106
tpm cat170.57 23568.31 23977.35 23082.41 23957.95 23978.08 25780.22 26152.04 29368.54 23677.66 27652.00 21087.84 24051.77 25672.07 25286.25 235
v74877.97 15976.65 16581.92 15882.29 24063.28 19287.53 11890.35 11173.50 10070.76 20485.55 20058.28 16692.81 15268.81 14972.76 24889.67 161
tpm72.37 22571.71 21674.35 25482.19 24152.00 27879.22 24877.29 27564.56 21472.95 18383.68 22451.35 21483.26 26458.33 22875.80 21787.81 208
tpmvs71.09 23169.29 23276.49 23682.04 24256.04 26278.92 25181.37 25064.05 21967.18 24878.28 27049.74 22389.77 21249.67 26772.37 24983.67 261
pmmvs474.03 20871.91 21380.39 18981.96 24368.32 9381.45 23182.14 24259.32 25769.87 21985.13 20852.40 20488.13 23760.21 21274.74 23184.73 254
TinyColmap67.30 25464.81 25774.76 25181.92 24456.68 25380.29 23981.49 24960.33 24856.27 29483.22 22524.77 30087.66 24245.52 28169.47 26279.95 284
ITE_SJBPF78.22 22081.77 24560.57 21783.30 23069.25 16667.54 24387.20 15636.33 28387.28 24354.34 24774.62 23286.80 228
MVS-HIRNet59.14 27357.67 27663.57 28881.65 24643.50 30271.73 28065.06 31339.59 30851.43 30257.73 30838.34 27682.58 26639.53 29373.95 23764.62 306
GG-mvs-BLEND75.38 24681.59 24755.80 26479.32 24669.63 30467.19 24773.67 29143.24 25388.90 23250.41 26184.50 12981.45 278
IterMVS74.29 20572.94 20778.35 21981.53 24863.49 18681.58 23082.49 23768.06 18469.99 21683.69 22351.66 21385.54 25465.85 17071.64 25486.01 241
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
gm-plane-assit81.40 24953.83 27462.72 23380.94 25692.39 16163.40 185
pmmvs674.69 20373.39 20378.61 21481.38 25057.48 24486.64 15187.95 18564.99 21170.18 21086.61 17550.43 22189.52 21762.12 19670.18 26188.83 179
test-LLR72.94 22172.43 21074.48 25281.35 25158.04 23678.38 25377.46 27366.66 19369.95 21779.00 26748.06 23179.24 27666.13 16584.83 12586.15 237
test-mter71.41 22970.39 22874.48 25281.35 25158.04 23678.38 25377.46 27360.32 24969.95 21779.00 26736.08 28479.24 27666.13 16584.83 12586.15 237
CR-MVSNet73.37 21371.27 22079.67 20181.32 25365.19 14875.92 26680.30 25959.92 25372.73 18581.19 25052.50 20286.69 24559.84 21477.71 18787.11 224
RPMNet71.62 22768.94 23579.67 20181.32 25365.19 14875.92 26678.30 27057.60 27072.73 18576.45 28052.30 20686.69 24548.14 27277.71 18787.11 224
V4279.38 13478.24 13982.83 13881.10 25565.50 13985.55 17989.82 13171.57 13478.21 11186.12 18960.66 15193.18 13675.64 9275.46 22389.81 158
lessismore_v078.97 20981.01 25657.15 24665.99 31161.16 27582.82 22939.12 27391.34 18759.67 21546.92 30888.43 199
Patchmtry70.74 23369.16 23375.49 24480.72 25754.07 27274.94 27580.30 25958.34 26370.01 21481.19 25052.50 20286.54 24753.37 25271.09 25785.87 243
PatchT68.46 24867.85 24670.29 27280.70 25843.93 30172.47 27974.88 28560.15 25170.55 20576.57 27949.94 22281.59 26850.58 26074.83 23085.34 246
USDC70.33 23868.37 23876.21 23880.60 25956.23 26079.19 24986.49 20160.89 24561.29 27485.47 20331.78 29289.47 21953.37 25276.21 21382.94 272
tpmrst72.39 22372.13 21273.18 26180.54 26049.91 29179.91 24279.08 26763.11 22571.69 19879.95 26155.32 18482.77 26565.66 17273.89 23886.87 227
anonymousdsp78.60 14677.15 15782.98 12680.51 26167.08 11487.24 12989.53 13865.66 20575.16 16487.19 15752.52 20192.25 16677.17 7579.34 17789.61 162
Patchmatch-test163.30 26761.13 27069.83 27480.26 26259.58 22364.06 30472.27 29951.98 29459.95 28074.19 28733.22 28770.98 30440.66 29173.57 24178.94 287
OpenMVS_ROBcopyleft64.09 1970.56 23668.19 24077.65 22680.26 26259.41 22785.01 18782.96 23458.76 26165.43 26082.33 23337.63 28091.23 19045.34 28376.03 21482.32 273
Test477.83 16475.90 18283.62 10080.24 26465.25 14685.27 18490.67 9769.03 17266.48 25483.75 22143.07 25593.00 14575.93 8688.66 8492.62 69
Anonymous2023120668.60 24567.80 24871.02 27080.23 26550.75 28878.30 25680.47 25656.79 27566.11 25782.63 23146.35 23878.95 27843.62 28675.70 21883.36 264
MIMVSNet168.58 24666.78 25273.98 25780.07 26651.82 27980.77 23484.37 22164.40 21659.75 28282.16 23636.47 28283.63 26142.73 28770.33 26086.48 234
ADS-MVSNet266.20 26063.33 26174.82 25079.92 26758.75 22967.55 29875.19 28353.37 28965.25 26175.86 28142.32 26080.53 27241.57 28968.91 26585.18 247
ADS-MVSNet64.36 26462.88 26468.78 27979.92 26747.17 29667.55 29871.18 30053.37 28965.25 26175.86 28142.32 26073.99 29841.57 28968.91 26585.18 247
dp66.80 25565.43 25670.90 27179.74 26948.82 29475.12 27374.77 28759.61 25564.08 26877.23 27742.89 25680.72 27148.86 26966.58 27583.16 266
EPMVS69.02 24468.16 24171.59 26479.61 27049.80 29377.40 26066.93 31062.82 23170.01 21479.05 26545.79 24277.86 28456.58 24175.26 22787.13 223
PVSNet_057.27 2061.67 27059.27 27268.85 27879.61 27057.44 24568.01 29673.44 29555.93 27958.54 28470.41 29744.58 24877.55 28547.01 27435.91 31071.55 301
Patchmatch-test62.11 26860.61 27166.58 28479.42 27249.82 29263.49 30669.05 30851.98 29459.95 28074.19 28733.22 28770.98 30440.66 29173.57 24178.94 287
V477.95 16076.37 16882.67 14479.40 27365.52 13686.43 15689.94 12872.28 12272.14 19484.95 21255.72 18193.44 12673.64 10972.86 24689.05 171
v5277.94 16276.37 16882.67 14479.39 27465.52 13686.43 15689.94 12872.28 12272.15 19384.94 21355.70 18293.44 12673.64 10972.84 24789.06 167
MDA-MVSNet-bldmvs66.68 25663.66 26075.75 24079.28 27560.56 21873.92 27778.35 26964.43 21550.13 30479.87 26344.02 25183.67 26046.10 27956.86 29883.03 269
TESTMET0.1,169.89 24169.00 23472.55 26279.27 27656.85 24878.38 25374.71 28957.64 26968.09 23977.19 27837.75 27876.70 28763.92 18284.09 13384.10 260
N_pmnet52.79 28353.26 28251.40 30178.99 2777.68 32669.52 2883.89 32651.63 29757.01 29174.98 28440.83 26765.96 31237.78 29664.67 28480.56 283
EU-MVSNet68.53 24767.61 25071.31 26978.51 27847.01 29784.47 19784.27 22342.27 30466.44 25584.79 21540.44 26983.76 25958.76 22468.54 26983.17 265
pmmvs571.55 22870.20 22975.61 24277.83 27956.39 25781.74 22780.89 25157.76 26867.46 24484.49 21749.26 22785.32 25657.08 23975.29 22685.11 250
test0.0.03 168.00 25067.69 24968.90 27777.55 28047.43 29575.70 26972.95 29666.66 19366.56 25282.29 23448.06 23175.87 29144.97 28474.51 23383.41 263
Patchmatch-RL test68.08 24965.61 25575.47 24577.43 28159.57 22471.16 28170.33 30162.94 22968.65 23372.77 29231.06 29385.49 25569.58 14466.58 27581.34 279
pmmvs-eth3d70.50 23767.83 24778.52 21777.37 28266.18 12581.82 22581.51 24858.90 26063.90 26980.42 25942.69 25886.28 25058.56 22565.30 28383.11 267
testing_275.73 19773.34 20582.89 13477.37 28265.22 14784.10 20990.54 10369.09 16860.46 27781.15 25240.48 26892.84 15176.36 8280.54 16890.60 122
Anonymous2023121164.82 26361.79 26773.91 25877.11 28450.92 28685.29 18381.53 24754.19 28457.98 28678.03 27226.90 29687.83 24137.92 29557.12 29782.99 270
JIA-IIPM66.32 25962.82 26576.82 23477.09 28561.72 21165.34 30275.38 28158.04 26664.51 26562.32 30542.05 26386.51 24851.45 25869.22 26482.21 274
Gipumacopyleft45.18 28941.86 29155.16 29777.03 28651.52 28232.50 31880.52 25532.46 31227.12 31335.02 3159.52 31775.50 29222.31 31460.21 29538.45 313
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
MDA-MVSNet_test_wron65.03 26162.92 26271.37 26675.93 28756.73 25069.09 29374.73 28857.28 27354.03 29777.89 27345.88 24074.39 29649.89 26661.55 29082.99 270
YYNet165.03 26162.91 26371.38 26575.85 28856.60 25469.12 29274.66 29157.28 27354.12 29677.87 27445.85 24174.48 29549.95 26561.52 29183.05 268
PMMVS69.34 24368.67 23671.35 26875.67 28962.03 20875.17 27073.46 29450.00 29968.68 23279.05 26552.07 20978.13 28161.16 20682.77 14473.90 299
testgi66.67 25766.53 25367.08 28275.62 29041.69 30675.93 26576.50 27866.11 19965.20 26386.59 17635.72 28574.71 29443.71 28573.38 24484.84 252
LP61.36 27157.78 27572.09 26375.54 29158.53 23167.16 30075.22 28251.90 29654.13 29569.97 29837.73 27980.45 27332.74 30255.63 30077.29 294
test20.0367.45 25266.95 25168.94 27675.48 29244.84 29977.50 25977.67 27266.66 19363.01 27283.80 22047.02 23578.40 28042.53 28868.86 26783.58 262
PM-MVS66.41 25864.14 25973.20 26073.92 29356.45 25578.97 25064.96 31463.88 22364.72 26480.24 26019.84 30683.44 26266.24 16464.52 28579.71 285
UnsupCasMVSNet_bld63.70 26661.53 26970.21 27373.69 29451.39 28472.82 27881.89 24455.63 28057.81 28771.80 29438.67 27478.61 27949.26 26852.21 30580.63 281
UnsupCasMVSNet_eth67.33 25365.99 25471.37 26673.48 29551.47 28375.16 27185.19 21565.20 20860.78 27680.93 25742.35 25977.20 28657.12 23853.69 30385.44 245
TDRefinement67.49 25164.34 25876.92 23373.47 29661.07 21284.86 19082.98 23359.77 25458.30 28585.13 20826.06 29887.89 23947.92 27360.59 29481.81 277
ambc75.24 24773.16 29750.51 28963.05 30787.47 19364.28 26677.81 27517.80 30989.73 21457.88 23260.64 29385.49 244
CMPMVSbinary51.72 2170.19 23968.16 24176.28 23773.15 29857.55 24379.47 24583.92 22548.02 30156.48 29384.81 21443.13 25486.42 24962.67 19181.81 15584.89 251
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
new-patchmatchnet61.73 26961.73 26861.70 29172.74 29924.50 32269.16 29178.03 27161.40 24256.72 29275.53 28338.42 27576.48 28945.95 28057.67 29684.13 259
testus59.00 27457.91 27462.25 29072.25 30039.09 30969.74 28675.02 28453.04 29157.21 29073.72 29018.76 30870.33 30632.86 30168.57 26877.35 293
testpf56.51 27957.58 27753.30 29871.99 30141.19 30746.89 31569.32 30758.06 26552.87 30169.45 30027.99 29572.73 30059.59 21762.07 28845.98 311
test235659.50 27258.08 27363.74 28771.23 30241.88 30467.59 29772.42 29853.72 28857.65 28870.74 29626.31 29772.40 30132.03 30571.06 25876.93 296
LF4IMVS64.02 26562.19 26669.50 27570.90 30353.29 27676.13 26377.18 27652.65 29258.59 28380.98 25523.55 30176.52 28853.06 25466.66 27478.68 289
test123567858.74 27556.89 27964.30 28569.70 30441.87 30571.05 28274.87 28654.06 28550.63 30371.53 29525.30 29974.10 29731.80 30663.10 28776.93 296
111157.11 27856.82 28057.97 29569.10 30528.28 31768.90 29474.54 29254.01 28653.71 29874.51 28523.09 30267.90 31032.28 30361.26 29277.73 291
.test124545.55 28850.02 28632.14 30769.10 30528.28 31768.90 29474.54 29254.01 28653.71 29874.51 28523.09 30267.90 31032.28 3030.02 3220.25 320
new_pmnet50.91 28550.29 28552.78 29968.58 30734.94 31563.71 30556.63 31639.73 30744.95 30565.47 30321.93 30458.48 31434.98 29956.62 29964.92 305
DSMNet-mixed57.77 27756.90 27860.38 29267.70 30835.61 31269.18 29053.97 31732.30 31457.49 28979.88 26240.39 27068.57 30938.78 29472.37 24976.97 295
FPMVS53.68 28251.64 28359.81 29365.08 30951.03 28569.48 28969.58 30541.46 30540.67 30772.32 29316.46 31170.00 30724.24 31365.42 28258.40 308
pmmvs357.79 27654.26 28168.37 28064.02 31056.72 25175.12 27365.17 31240.20 30652.93 30069.86 29920.36 30575.48 29345.45 28255.25 30272.90 300
test1235649.28 28748.51 28851.59 30062.06 31119.11 32360.40 30872.45 29747.60 30240.64 30865.68 30213.84 31368.72 30827.29 31046.67 30966.94 304
testmv53.85 28151.03 28462.31 28961.46 31238.88 31070.95 28574.69 29051.11 29841.26 30666.85 30114.28 31272.13 30229.19 30849.51 30775.93 298
PNet_i23d38.26 29335.42 29446.79 30258.74 31335.48 31359.65 30951.25 31832.45 31323.44 31747.53 3132.04 32258.96 31325.60 31218.09 31745.92 312
wuyk23d16.82 30015.94 30219.46 31058.74 31331.45 31639.22 3163.74 3276.84 3206.04 3222.70 3231.27 32324.29 32010.54 32014.40 3212.63 318
no-one51.08 28445.79 29066.95 28357.92 31550.49 29059.63 31076.04 28048.04 30031.85 31056.10 31119.12 30780.08 27536.89 29726.52 31270.29 302
PMMVS240.82 29138.86 29346.69 30353.84 31616.45 32448.61 31449.92 31937.49 30931.67 31160.97 3078.14 31956.42 31528.42 30930.72 31167.19 303
LCM-MVSNet54.25 28049.68 28767.97 28153.73 31745.28 29866.85 30180.78 25335.96 31039.45 30962.23 3068.70 31878.06 28348.24 27151.20 30680.57 282
E-PMN31.77 29530.64 29735.15 30552.87 31827.67 31957.09 31247.86 32024.64 31516.40 31933.05 31711.23 31554.90 31614.46 31818.15 31622.87 315
EMVS30.81 29629.65 29834.27 30650.96 31925.95 32156.58 31346.80 32124.01 31715.53 32030.68 31812.47 31454.43 31712.81 31917.05 31822.43 316
ANet_high50.57 28646.10 28963.99 28648.67 32039.13 30870.99 28480.85 25261.39 24331.18 31257.70 30917.02 31073.65 29931.22 30715.89 31979.18 286
wuykxyi23d39.76 29233.18 29659.51 29446.98 32144.01 30057.70 31167.74 30924.13 31613.98 32134.33 3161.27 32371.33 30334.23 30018.23 31563.18 307
MVEpermissive26.22 2330.37 29725.89 30043.81 30444.55 32235.46 31428.87 31939.07 32218.20 31818.58 31840.18 3142.68 32147.37 31817.07 31723.78 31448.60 310
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
PMVScopyleft37.38 2244.16 29040.28 29255.82 29640.82 32342.54 30365.12 30363.99 31534.43 31124.48 31457.12 3103.92 32076.17 29017.10 31655.52 30148.75 309
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
DeepMVS_CXcopyleft27.40 30940.17 32426.90 32024.59 32517.44 31923.95 31548.61 3129.77 31626.48 31918.06 31524.47 31328.83 314
tmp_tt18.61 29921.40 30110.23 3114.82 32510.11 32534.70 31730.74 3241.48 32123.91 31626.07 31928.42 29413.41 32127.12 31115.35 3207.17 317
testmvs6.04 3038.02 3050.10 3130.08 3260.03 32869.74 2860.04 3280.05 3220.31 3231.68 3240.02 3260.04 3220.24 3210.02 3220.25 320
test1236.12 3028.11 3040.14 3120.06 3270.09 32771.05 2820.03 3290.04 3230.25 3241.30 3250.05 3250.03 3230.21 3220.01 3240.29 319
cdsmvs_eth3d_5k19.96 29826.61 2990.00 3140.00 3280.00 3290.00 32089.26 1480.00 3240.00 32588.61 12161.62 1330.00 3240.00 3230.00 3250.00 322
pcd_1.5k_mvsjas5.26 3047.02 3060.00 3140.00 3280.00 3290.00 3200.00 3300.00 3240.00 3250.00 32663.15 980.00 3240.00 3230.00 3250.00 322
sosnet-low-res0.00 3050.00 307