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 bysorted bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort by
DVP-MVS++90.23 191.01 187.89 2494.34 2971.25 6395.06 194.23 578.38 3592.78 495.74 682.45 397.49 389.42 496.68 294.95 7
SED-MVS90.08 290.85 287.77 2695.30 270.98 7093.57 794.06 1277.24 5293.10 195.72 882.99 197.44 589.07 996.63 494.88 11
DVP-MVScopyleft89.60 390.35 387.33 4595.27 571.25 6393.49 992.73 6577.33 5092.12 995.78 480.98 997.40 789.08 796.41 1293.33 86
Zhenlong Yuan, Jinguo Luo, Fei Shen, Zhaoxin Li, Cong Liu, Tianlu Mao, Zhaoqi Wang: DVP-MVS: Synergize Depth-Edge and Visibility Prior for Multi-View Stereo. AAAI2025
DPE-MVScopyleft89.48 589.98 488.01 1494.80 1172.69 3291.59 4494.10 1075.90 8892.29 795.66 1081.67 697.38 987.44 2096.34 1593.95 54
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
MSP-MVS89.51 489.91 588.30 994.28 3273.46 1892.90 1694.11 880.27 1291.35 1494.16 4178.35 1396.77 2389.59 394.22 6594.67 24
Zhenlong Yuan, Cong Liu, Fei Shen, Zhaoxin Li, Jingguo luo, Tianlu Mao and Zhaoqi Wang: MSP-MVS: Multi-granularity Segmentation Prior Guided Multi-View Stereo. AAAI2025
APDe-MVS89.15 689.63 687.73 3094.49 2071.69 5893.83 493.96 1675.70 9291.06 1696.03 176.84 1597.03 1589.09 695.65 3294.47 31
SMA-MVScopyleft89.08 789.23 788.61 594.25 3373.73 1092.40 2393.63 2474.77 11292.29 795.97 274.28 3697.24 1188.58 1396.91 194.87 13
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
HPM-MVS++copyleft89.02 889.15 888.63 495.01 976.03 192.38 2692.85 6080.26 1387.78 3094.27 3675.89 2096.81 2287.45 1996.44 993.05 97
CNVR-MVS88.93 989.13 988.33 794.77 1273.82 990.51 6693.00 4780.90 988.06 2894.06 4676.43 1796.84 2088.48 1495.99 1994.34 37
SteuartSystems-ACMMP88.72 1088.86 1088.32 892.14 8072.96 2693.73 593.67 2380.19 1488.10 2794.80 1673.76 4197.11 1387.51 1895.82 2494.90 10
Skip Steuart: Steuart Systems R&D Blog.
SF-MVS88.46 1188.74 1187.64 3892.78 6971.95 5392.40 2394.74 275.71 9089.16 1995.10 1375.65 2296.19 4587.07 2196.01 1794.79 18
DeepPCF-MVS80.84 188.10 1288.56 1286.73 5692.24 7869.03 10989.57 9393.39 3477.53 4789.79 1894.12 4378.98 1296.58 3685.66 2795.72 2994.58 27
SD-MVS88.06 1488.50 1386.71 5792.60 7672.71 3091.81 4293.19 4077.87 3890.32 1794.00 4874.83 2893.78 14987.63 1794.27 6493.65 73
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
ETH3D-3000-0.188.09 1388.29 1487.50 4192.76 7071.89 5691.43 4894.70 374.47 12088.86 2294.61 2175.23 2595.84 5886.62 2695.92 2194.78 20
9.1488.26 1592.84 6891.52 4794.75 173.93 13388.57 2494.67 1975.57 2495.79 5986.77 2395.76 28
TSAR-MVS + MP.88.02 1788.11 1687.72 3293.68 4972.13 5091.41 4992.35 8074.62 11788.90 2193.85 5275.75 2196.00 5387.80 1594.63 5495.04 5
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
ACMMP_NAP88.05 1688.08 1787.94 1793.70 4773.05 2390.86 5993.59 2676.27 8288.14 2695.09 1571.06 6296.67 2887.67 1696.37 1494.09 46
NCCC88.06 1488.01 1888.24 1094.41 2473.62 1191.22 5492.83 6181.50 685.79 4693.47 5973.02 4797.00 1784.90 3394.94 4494.10 45
xxxxxxxxxxxxxcwj87.88 1987.92 1987.77 2693.80 4472.35 4590.47 6989.69 16874.31 12389.16 1995.10 1375.65 2296.19 4587.07 2196.01 1794.79 18
ZNCC-MVS87.94 1887.85 2088.20 1194.39 2673.33 2093.03 1493.81 2076.81 6685.24 5294.32 3571.76 5696.93 1885.53 2995.79 2594.32 38
testtj87.78 2087.78 2187.77 2694.55 1872.47 3992.23 3393.49 2974.75 11388.33 2594.43 3273.27 4497.02 1684.18 5094.84 4993.82 62
MP-MVS-pluss87.67 2287.72 2287.54 3993.64 5072.04 5289.80 8793.50 2875.17 10386.34 4195.29 1270.86 6396.00 5388.78 1296.04 1694.58 27
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
MP-MVScopyleft87.71 2187.64 2387.93 2094.36 2873.88 792.71 2292.65 7077.57 4383.84 8394.40 3472.24 5296.28 4185.65 2895.30 4093.62 76
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
APD-MVScopyleft87.44 2687.52 2487.19 4794.24 3472.39 4291.86 4192.83 6173.01 15488.58 2394.52 2373.36 4296.49 3784.26 4695.01 4292.70 108
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
HFP-MVS87.58 2387.47 2587.94 1794.58 1673.54 1593.04 1293.24 3776.78 6884.91 5894.44 3070.78 6496.61 3284.53 4194.89 4693.66 68
ETH3 D test640087.50 2587.44 2687.70 3593.71 4671.75 5790.62 6494.05 1570.80 18587.59 3393.51 5677.57 1496.63 3183.31 5795.77 2694.72 23
zzz-MVS87.53 2487.41 2787.90 2194.18 3774.25 590.23 7692.02 9479.45 2085.88 4394.80 1668.07 8896.21 4386.69 2495.34 3693.23 89
ETH3D cwj APD-0.1687.31 3287.27 2887.44 4391.60 8872.45 4190.02 8094.37 471.76 16687.28 3494.27 3675.18 2696.08 4985.16 3095.77 2693.80 65
GST-MVS87.42 2887.26 2987.89 2494.12 3972.97 2592.39 2593.43 3276.89 6484.68 6493.99 5070.67 6796.82 2184.18 5095.01 4293.90 57
MCST-MVS87.37 3087.25 3087.73 3094.53 1972.46 4089.82 8593.82 1973.07 15284.86 6392.89 7276.22 1896.33 3984.89 3595.13 4194.40 34
ACMMPR87.44 2687.23 3188.08 1394.64 1373.59 1293.04 1293.20 3976.78 6884.66 6794.52 2368.81 8696.65 2984.53 4194.90 4594.00 52
region2R87.42 2887.20 3288.09 1294.63 1473.55 1393.03 1493.12 4276.73 7184.45 7194.52 2369.09 8296.70 2684.37 4494.83 5194.03 49
#test#87.33 3187.13 3387.94 1794.58 1673.54 1592.34 2993.24 3775.23 10084.91 5894.44 3070.78 6496.61 3283.75 5594.89 4693.66 68
MTAPA87.23 3387.00 3487.90 2194.18 3774.25 586.58 18992.02 9479.45 2085.88 4394.80 1668.07 8896.21 4386.69 2495.34 3693.23 89
HPM-MVScopyleft87.11 3586.98 3587.50 4193.88 4372.16 4992.19 3493.33 3576.07 8583.81 8493.95 5169.77 7696.01 5285.15 3194.66 5394.32 38
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
CS-MVS86.69 4186.95 3685.90 7590.76 10267.57 14692.83 1793.30 3679.67 1984.57 7092.27 8371.47 5995.02 9684.24 4893.46 7095.13 4
CP-MVS87.11 3586.92 3787.68 3794.20 3673.86 893.98 392.82 6476.62 7383.68 8594.46 2767.93 9095.95 5684.20 4994.39 6093.23 89
XVS87.18 3486.91 3888.00 1594.42 2273.33 2092.78 1892.99 4979.14 2383.67 8694.17 4067.45 9596.60 3483.06 6294.50 5794.07 47
DeepC-MVS79.81 287.08 3786.88 3987.69 3691.16 9272.32 4790.31 7493.94 1777.12 5882.82 9794.23 3972.13 5497.09 1484.83 3695.37 3593.65 73
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
test_prior386.73 3986.86 4086.33 6392.61 7469.59 10088.85 11292.97 5475.41 9684.91 5893.54 5474.28 3695.48 7083.31 5795.86 2293.91 55
SR-MVS86.73 3986.67 4186.91 5294.11 4072.11 5192.37 2792.56 7374.50 11886.84 3794.65 2067.31 9795.77 6084.80 3792.85 7592.84 106
DeepC-MVS_fast79.65 386.91 3886.62 4287.76 2993.52 5272.37 4491.26 5093.04 4376.62 7384.22 7693.36 6171.44 6096.76 2480.82 8695.33 3894.16 43
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
Regformer-286.63 4486.53 4386.95 5189.33 13971.24 6788.43 12692.05 9382.50 186.88 3690.09 13474.45 3195.61 6384.38 4390.63 10394.01 51
CS-MVS-test86.29 5086.48 4485.71 7791.02 9567.21 15592.36 2893.78 2178.97 3083.51 8991.20 10970.65 6895.15 8881.96 7794.89 4694.77 21
DROMVSNet86.01 5386.38 4584.91 9789.31 14466.27 17092.32 3093.63 2479.37 2284.17 7891.88 9169.04 8595.43 7483.93 5393.77 6893.01 100
Regformer-186.41 4886.33 4686.64 5889.33 13970.93 7588.43 12691.39 12382.14 386.65 3890.09 13474.39 3495.01 9783.97 5290.63 10393.97 53
mPP-MVS86.67 4386.32 4787.72 3294.41 2473.55 1392.74 2092.22 8776.87 6582.81 9894.25 3866.44 10496.24 4282.88 6694.28 6393.38 83
PGM-MVS86.68 4286.27 4887.90 2194.22 3573.38 1990.22 7793.04 4375.53 9483.86 8294.42 3367.87 9296.64 3082.70 7194.57 5693.66 68
test117286.20 5286.22 4986.12 7093.95 4269.89 9591.79 4392.28 8275.07 10486.40 4094.58 2265.00 12295.56 6584.34 4592.60 7892.90 104
train_agg86.43 4686.20 5087.13 4993.26 5672.96 2688.75 11791.89 10368.69 23285.00 5693.10 6574.43 3295.41 7684.97 3295.71 3093.02 99
CSCG86.41 4886.19 5187.07 5092.91 6572.48 3890.81 6093.56 2773.95 13183.16 9291.07 11475.94 1995.19 8679.94 9594.38 6193.55 79
PHI-MVS86.43 4686.17 5287.24 4690.88 9970.96 7292.27 3294.07 1172.45 15785.22 5391.90 9069.47 7896.42 3883.28 6095.94 2094.35 36
dcpmvs_285.63 6186.15 5384.06 12791.71 8664.94 19986.47 19291.87 10573.63 13986.60 3993.02 7076.57 1691.87 22583.36 5692.15 8495.35 1
CANet86.45 4586.10 5487.51 4090.09 11470.94 7489.70 9192.59 7281.78 481.32 11391.43 10470.34 6997.23 1284.26 4693.36 7194.37 35
agg_prior186.22 5186.09 5586.62 5992.85 6671.94 5488.59 12391.78 11068.96 22784.41 7293.18 6474.94 2794.93 9884.75 3895.33 3893.01 100
APD-MVS_3200maxsize85.97 5485.88 5686.22 6792.69 7269.53 10291.93 3892.99 4973.54 14385.94 4294.51 2665.80 11495.61 6383.04 6492.51 8093.53 81
canonicalmvs85.91 5585.87 5786.04 7289.84 12469.44 10790.45 7293.00 4776.70 7288.01 2991.23 10773.28 4393.91 14481.50 8088.80 12494.77 21
MSLP-MVS++85.43 6485.76 5884.45 11291.93 8370.24 8690.71 6292.86 5977.46 4984.22 7692.81 7667.16 9992.94 18980.36 9194.35 6290.16 191
SR-MVS-dyc-post85.77 5785.61 5986.23 6693.06 6270.63 8291.88 3992.27 8373.53 14485.69 4794.45 2865.00 12295.56 6582.75 6791.87 8892.50 115
RE-MVS-def85.48 6093.06 6270.63 8291.88 3992.27 8373.53 14485.69 4794.45 2863.87 12982.75 6791.87 8892.50 115
Regformer-485.68 6085.45 6186.35 6288.95 15769.67 9988.29 13691.29 12581.73 585.36 5090.01 13872.62 4995.35 8383.28 6087.57 13694.03 49
ACMMPcopyleft85.89 5685.39 6287.38 4493.59 5172.63 3492.74 2093.18 4176.78 6880.73 12293.82 5364.33 12596.29 4082.67 7290.69 10293.23 89
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
TSAR-MVS + GP.85.71 5985.33 6386.84 5391.34 9072.50 3789.07 10587.28 23376.41 7585.80 4590.22 13274.15 3995.37 8281.82 7891.88 8792.65 112
alignmvs85.48 6285.32 6485.96 7489.51 13169.47 10489.74 8992.47 7476.17 8387.73 3291.46 10370.32 7093.78 14981.51 7988.95 12194.63 26
DELS-MVS85.41 6585.30 6585.77 7688.49 17567.93 13885.52 22193.44 3178.70 3183.63 8889.03 16574.57 2995.71 6280.26 9394.04 6693.66 68
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
CDPH-MVS85.76 5885.29 6687.17 4893.49 5371.08 6888.58 12492.42 7868.32 23784.61 6893.48 5772.32 5196.15 4879.00 9995.43 3494.28 40
casdiffmvs85.11 7085.14 6785.01 9187.20 21865.77 18287.75 15592.83 6177.84 3984.36 7592.38 8272.15 5393.93 14381.27 8290.48 10595.33 2
Regformer-385.23 6785.07 6885.70 7888.95 15769.01 11188.29 13689.91 16280.95 885.01 5490.01 13872.45 5094.19 13082.50 7387.57 13693.90 57
baseline84.93 7284.98 6984.80 10287.30 21665.39 19187.30 16792.88 5877.62 4184.04 8192.26 8471.81 5593.96 13781.31 8190.30 10795.03 6
UA-Net85.08 7184.96 7085.45 8092.07 8168.07 13689.78 8890.86 13782.48 284.60 6993.20 6369.35 7995.22 8571.39 16890.88 10193.07 96
abl_685.23 6784.95 7186.07 7192.23 7970.48 8590.80 6192.08 9273.51 14685.26 5194.16 4162.75 14695.92 5782.46 7491.30 9791.81 139
HPM-MVS_fast85.35 6684.95 7186.57 6193.69 4870.58 8492.15 3691.62 11473.89 13482.67 10094.09 4462.60 14795.54 6880.93 8492.93 7393.57 78
MVS_111021_HR85.14 6984.75 7386.32 6591.65 8772.70 3185.98 20490.33 15076.11 8482.08 10391.61 9871.36 6194.17 13281.02 8392.58 7992.08 131
ETV-MVS84.90 7484.67 7485.59 7989.39 13668.66 12588.74 11992.64 7179.97 1784.10 7985.71 25369.32 8095.38 7980.82 8691.37 9592.72 107
patch_mono-283.65 8084.54 7580.99 22190.06 11965.83 17884.21 24988.74 20471.60 17385.01 5492.44 8174.51 3083.50 32682.15 7692.15 8493.64 75
3Dnovator+77.84 485.48 6284.47 7688.51 691.08 9373.49 1793.18 1193.78 2180.79 1076.66 19193.37 6060.40 19096.75 2577.20 11793.73 6995.29 3
DPM-MVS84.93 7284.29 7786.84 5390.20 11273.04 2487.12 17193.04 4369.80 20482.85 9691.22 10873.06 4696.02 5176.72 12594.63 5491.46 150
EI-MVSNet-Vis-set84.19 7583.81 7885.31 8288.18 18467.85 13987.66 15789.73 16780.05 1682.95 9389.59 14970.74 6694.82 10780.66 9084.72 17293.28 88
nrg03083.88 7683.53 7984.96 9386.77 22669.28 10890.46 7192.67 6774.79 11182.95 9391.33 10672.70 4893.09 18380.79 8879.28 24192.50 115
MG-MVS83.41 8583.45 8083.28 15492.74 7162.28 24988.17 14189.50 17275.22 10181.49 11292.74 8066.75 10095.11 9072.85 15891.58 9292.45 118
EI-MVSNet-UG-set83.81 7783.38 8185.09 8987.87 19367.53 14787.44 16389.66 16979.74 1882.23 10289.41 15870.24 7194.74 11079.95 9483.92 18292.99 102
CPTT-MVS83.73 7883.33 8284.92 9693.28 5570.86 7792.09 3790.38 14668.75 23179.57 13392.83 7460.60 18693.04 18780.92 8591.56 9390.86 168
HQP_MVS83.64 8183.14 8385.14 8790.08 11568.71 12191.25 5292.44 7579.12 2578.92 14191.00 11860.42 18895.38 7978.71 10286.32 15791.33 151
Effi-MVS+83.62 8283.08 8485.24 8588.38 18067.45 14888.89 11089.15 18575.50 9582.27 10188.28 18669.61 7794.45 11977.81 11187.84 13493.84 61
MVS_Test83.15 8983.06 8583.41 15186.86 22263.21 23586.11 20292.00 9774.31 12382.87 9589.44 15770.03 7293.21 17377.39 11688.50 13093.81 63
EPP-MVSNet83.40 8683.02 8684.57 10690.13 11364.47 20892.32 3090.73 13874.45 12279.35 13691.10 11269.05 8495.12 8972.78 15987.22 14494.13 44
OPM-MVS83.50 8382.95 8785.14 8788.79 16570.95 7389.13 10491.52 11777.55 4680.96 12091.75 9360.71 18294.50 11879.67 9686.51 15589.97 207
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
EPNet83.72 7982.92 8886.14 6984.22 26069.48 10391.05 5785.27 25981.30 776.83 18691.65 9566.09 10995.56 6576.00 13093.85 6793.38 83
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
IS-MVSNet83.15 8982.81 8984.18 12289.94 12263.30 23391.59 4488.46 21079.04 2779.49 13492.16 8565.10 11994.28 12267.71 20291.86 9094.95 7
EIA-MVS83.31 8882.80 9084.82 10089.59 12765.59 18488.21 13992.68 6674.66 11578.96 13986.42 24169.06 8395.26 8475.54 13590.09 11193.62 76
Vis-MVSNetpermissive83.46 8482.80 9085.43 8190.25 11168.74 11990.30 7590.13 15676.33 8180.87 12192.89 7261.00 17994.20 12972.45 16290.97 9993.35 85
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
FIs82.07 10582.42 9281.04 22088.80 16458.34 28688.26 13893.49 2976.93 6378.47 15191.04 11569.92 7492.34 20869.87 18384.97 16992.44 119
VNet82.21 10282.41 9381.62 20290.82 10060.93 26384.47 24089.78 16476.36 8084.07 8091.88 9164.71 12490.26 25970.68 17388.89 12293.66 68
PAPM_NR83.02 9382.41 9384.82 10092.47 7766.37 16887.93 15091.80 10873.82 13577.32 17690.66 12367.90 9194.90 10370.37 17689.48 11893.19 93
VDD-MVS83.01 9482.36 9584.96 9391.02 9566.40 16788.91 10988.11 21377.57 4384.39 7493.29 6252.19 24693.91 14477.05 11988.70 12694.57 29
3Dnovator76.31 583.38 8782.31 9686.59 6087.94 19272.94 2990.64 6392.14 9177.21 5475.47 21592.83 7458.56 19794.72 11173.24 15592.71 7792.13 130
h-mvs3383.15 8982.19 9786.02 7390.56 10570.85 7888.15 14389.16 18476.02 8684.67 6591.39 10561.54 16595.50 6982.71 6975.48 28391.72 141
MVS_111021_LR82.61 9982.11 9884.11 12388.82 16271.58 5985.15 22486.16 25074.69 11480.47 12591.04 11562.29 15490.55 25780.33 9290.08 11290.20 190
DP-MVS Recon83.11 9282.09 9986.15 6894.44 2170.92 7688.79 11592.20 8870.53 19279.17 13791.03 11764.12 12796.03 5068.39 19990.14 11091.50 147
test_part182.78 9682.08 10084.89 9890.66 10366.97 16090.96 5892.93 5777.19 5580.53 12490.04 13663.44 13295.39 7876.04 12976.90 26092.31 122
MVSFormer82.85 9582.05 10185.24 8587.35 21170.21 8790.50 6790.38 14668.55 23481.32 11389.47 15261.68 16293.46 16678.98 10090.26 10892.05 132
FC-MVSNet-test81.52 11882.02 10280.03 24088.42 17955.97 32287.95 14893.42 3377.10 5977.38 17490.98 12069.96 7391.79 22668.46 19884.50 17492.33 120
HQP-MVS82.61 9982.02 10284.37 11489.33 13966.98 15889.17 9992.19 8976.41 7577.23 17990.23 13160.17 19195.11 9077.47 11485.99 16391.03 162
OMC-MVS82.69 9781.97 10484.85 9988.75 16767.42 14987.98 14690.87 13674.92 10879.72 13291.65 9562.19 15793.96 13775.26 13786.42 15693.16 94
diffmvs82.10 10381.88 10582.76 18483.00 28763.78 22183.68 25789.76 16572.94 15582.02 10489.85 14165.96 11390.79 25382.38 7587.30 14393.71 67
PVSNet_Blended_VisFu82.62 9881.83 10684.96 9390.80 10169.76 9788.74 11991.70 11369.39 21178.96 13988.46 18165.47 11694.87 10674.42 14088.57 12790.24 189
CLD-MVS82.31 10181.65 10784.29 11988.47 17667.73 14285.81 21292.35 8075.78 8978.33 15486.58 23664.01 12894.35 12076.05 12887.48 14190.79 169
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 10881.54 10882.92 17388.46 17763.46 22987.13 17092.37 7980.19 1478.38 15289.14 16171.66 5893.05 18570.05 17976.46 26892.25 125
PS-MVSNAJss82.07 10581.31 10984.34 11786.51 22967.27 15389.27 9791.51 11871.75 16779.37 13590.22 13263.15 14094.27 12377.69 11282.36 20691.49 148
LPG-MVS_test82.08 10481.27 11084.50 10989.23 14868.76 11790.22 7791.94 10175.37 9876.64 19291.51 10054.29 22994.91 10078.44 10483.78 18389.83 212
LFMVS81.82 11081.23 11183.57 14691.89 8463.43 23189.84 8481.85 30577.04 6183.21 9093.10 6552.26 24593.43 16871.98 16389.95 11493.85 59
API-MVS81.99 10781.23 11184.26 12090.94 9770.18 9291.10 5589.32 17671.51 17578.66 14688.28 18665.26 11795.10 9364.74 23091.23 9887.51 270
UniMVSNet (Re)81.60 11781.11 11383.09 16488.38 18064.41 21087.60 15893.02 4678.42 3478.56 14888.16 19069.78 7593.26 17269.58 18676.49 26791.60 142
xiu_mvs_v2_base81.69 11381.05 11483.60 14489.15 15168.03 13784.46 24290.02 15870.67 18981.30 11686.53 23963.17 13994.19 13075.60 13488.54 12888.57 252
PS-MVSNAJ81.69 11381.02 11583.70 14389.51 13168.21 13484.28 24890.09 15770.79 18681.26 11785.62 25763.15 14094.29 12175.62 13388.87 12388.59 251
GeoE81.71 11281.01 11683.80 14189.51 13164.45 20988.97 10788.73 20571.27 17878.63 14789.76 14366.32 10693.20 17569.89 18286.02 16293.74 66
hse-mvs281.72 11180.94 11784.07 12688.72 16867.68 14485.87 20887.26 23476.02 8684.67 6588.22 18961.54 16593.48 16482.71 6973.44 30991.06 160
PAPR81.66 11680.89 11883.99 13590.27 11064.00 21686.76 18591.77 11268.84 23077.13 18489.50 15067.63 9394.88 10567.55 20488.52 12993.09 95
mvsmamba81.69 11380.74 11984.56 10787.45 21066.72 16391.26 5085.89 25474.66 11578.23 15790.56 12554.33 22894.91 10080.73 8983.54 19092.04 134
MAR-MVS81.84 10980.70 12085.27 8491.32 9171.53 6089.82 8590.92 13469.77 20578.50 14986.21 24562.36 15394.52 11765.36 22492.05 8689.77 215
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
VDDNet81.52 11880.67 12184.05 12990.44 10864.13 21589.73 9085.91 25371.11 18083.18 9193.48 5750.54 26993.49 16373.40 15288.25 13294.54 30
ACMP74.13 681.51 12080.57 12284.36 11589.42 13468.69 12489.97 8291.50 12174.46 12175.04 23390.41 12853.82 23494.54 11577.56 11382.91 19889.86 211
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
VPA-MVSNet80.60 14180.55 12380.76 22688.07 18860.80 26686.86 17991.58 11675.67 9380.24 12789.45 15663.34 13490.25 26070.51 17579.22 24291.23 155
DU-MVS81.12 12580.52 12482.90 17487.80 19763.46 22987.02 17491.87 10579.01 2878.38 15289.07 16365.02 12093.05 18570.05 17976.46 26892.20 127
test_yl81.17 12380.47 12583.24 15789.13 15263.62 22286.21 19989.95 16072.43 16081.78 10989.61 14757.50 20693.58 15770.75 17186.90 14892.52 113
DCV-MVSNet81.17 12380.47 12583.24 15789.13 15263.62 22286.21 19989.95 16072.43 16081.78 10989.61 14757.50 20693.58 15770.75 17186.90 14892.52 113
PVSNet_Blended80.98 12680.34 12782.90 17488.85 15965.40 18984.43 24492.00 9767.62 24178.11 16185.05 27066.02 11194.27 12371.52 16589.50 11789.01 235
TranMVSNet+NR-MVSNet80.84 12980.31 12882.42 18987.85 19462.33 24787.74 15691.33 12480.55 1177.99 16489.86 14065.23 11892.62 19567.05 21275.24 29292.30 123
jason81.39 12180.29 12984.70 10486.63 22869.90 9485.95 20586.77 24163.24 28881.07 11989.47 15261.08 17892.15 21478.33 10790.07 11392.05 132
jason: jason.
lupinMVS81.39 12180.27 13084.76 10387.35 21170.21 8785.55 21786.41 24562.85 29581.32 11388.61 17661.68 16292.24 21278.41 10690.26 10891.83 137
PVSNet_BlendedMVS80.60 14180.02 13182.36 19188.85 15965.40 18986.16 20192.00 9769.34 21378.11 16186.09 24866.02 11194.27 12371.52 16582.06 20887.39 272
EI-MVSNet80.52 14479.98 13282.12 19284.28 25863.19 23786.41 19388.95 19574.18 12878.69 14487.54 20566.62 10192.43 20272.57 16180.57 22690.74 172
Fast-Effi-MVS+80.81 13279.92 13383.47 14788.85 15964.51 20585.53 21989.39 17470.79 18678.49 15085.06 26967.54 9493.58 15767.03 21386.58 15392.32 121
CANet_DTU80.61 14079.87 13482.83 17685.60 23963.17 23887.36 16488.65 20676.37 7975.88 20988.44 18253.51 23693.07 18473.30 15389.74 11692.25 125
ACMM73.20 880.78 13779.84 13583.58 14589.31 14468.37 12989.99 8191.60 11570.28 19677.25 17789.66 14553.37 23793.53 16274.24 14382.85 19988.85 243
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
112180.84 12979.77 13684.05 12993.11 6070.78 7984.66 23485.42 25857.37 33881.76 11192.02 8763.41 13394.12 13367.28 20792.93 7387.26 277
XVG-OURS-SEG-HR80.81 13279.76 13783.96 13785.60 23968.78 11683.54 26390.50 14370.66 19076.71 19091.66 9460.69 18391.26 24076.94 12081.58 21491.83 137
xiu_mvs_v1_base_debu80.80 13479.72 13884.03 13287.35 21170.19 8985.56 21488.77 20069.06 22381.83 10588.16 19050.91 26392.85 19178.29 10887.56 13889.06 230
xiu_mvs_v1_base80.80 13479.72 13884.03 13287.35 21170.19 8985.56 21488.77 20069.06 22381.83 10588.16 19050.91 26392.85 19178.29 10887.56 13889.06 230
xiu_mvs_v1_base_debi80.80 13479.72 13884.03 13287.35 21170.19 8985.56 21488.77 20069.06 22381.83 10588.16 19050.91 26392.85 19178.29 10887.56 13889.06 230
UGNet80.83 13179.59 14184.54 10888.04 18968.09 13589.42 9488.16 21276.95 6276.22 20289.46 15449.30 28393.94 14068.48 19790.31 10691.60 142
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
114514_t80.68 13879.51 14284.20 12194.09 4167.27 15389.64 9291.11 13158.75 32974.08 24390.72 12258.10 19995.04 9569.70 18489.42 11990.30 187
QAPM80.88 12779.50 14385.03 9088.01 19168.97 11391.59 4492.00 9766.63 25375.15 22992.16 8557.70 20395.45 7263.52 23488.76 12590.66 174
AdaColmapbinary80.58 14379.42 14484.06 12793.09 6168.91 11489.36 9588.97 19469.27 21475.70 21289.69 14457.20 21195.77 6063.06 23988.41 13187.50 271
mvs-test180.88 12779.40 14585.29 8385.13 24769.75 9889.28 9688.10 21474.99 10676.44 19786.72 22557.27 20994.26 12773.53 14883.18 19591.87 136
NR-MVSNet80.23 15079.38 14682.78 18287.80 19763.34 23286.31 19691.09 13279.01 2872.17 26289.07 16367.20 9892.81 19466.08 21975.65 27992.20 127
IterMVS-LS80.06 15379.38 14682.11 19385.89 23463.20 23686.79 18289.34 17574.19 12775.45 21886.72 22566.62 10192.39 20472.58 16076.86 26290.75 171
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
iter_conf_final80.63 13979.35 14884.46 11189.36 13867.70 14389.85 8384.49 26973.19 15078.30 15588.94 16645.98 30594.56 11379.59 9784.48 17691.11 158
test_djsdf80.30 14979.32 14983.27 15583.98 26565.37 19290.50 6790.38 14668.55 23476.19 20388.70 17256.44 21593.46 16678.98 10080.14 23290.97 165
v2v48280.23 15079.29 15083.05 16783.62 27064.14 21487.04 17389.97 15973.61 14078.18 16087.22 21361.10 17793.82 14776.11 12776.78 26591.18 156
ECVR-MVScopyleft79.61 16079.26 15180.67 22890.08 11554.69 32887.89 15277.44 33874.88 10980.27 12692.79 7748.96 28992.45 20168.55 19692.50 8194.86 14
XVG-OURS80.41 14579.23 15283.97 13685.64 23869.02 11083.03 27190.39 14571.09 18177.63 17091.49 10254.62 22791.35 23875.71 13183.47 19191.54 144
RRT_MVS80.35 14879.22 15383.74 14287.63 20465.46 18891.08 5688.92 19773.82 13576.44 19790.03 13749.05 28794.25 12876.84 12179.20 24391.51 145
WR-MVS79.49 16479.22 15380.27 23688.79 16558.35 28585.06 22688.61 20878.56 3277.65 16988.34 18463.81 13190.66 25664.98 22877.22 25691.80 140
test111179.43 16779.18 15580.15 23889.99 12053.31 34187.33 16677.05 34175.04 10580.23 12892.77 7948.97 28892.33 20968.87 19392.40 8394.81 17
mvs_anonymous79.42 16879.11 15680.34 23484.45 25757.97 29282.59 27387.62 22667.40 24476.17 20688.56 17968.47 8789.59 26970.65 17486.05 16193.47 82
v114480.03 15479.03 15783.01 16983.78 26864.51 20587.11 17290.57 14271.96 16578.08 16386.20 24661.41 16993.94 14074.93 13877.23 25590.60 177
v879.97 15779.02 15882.80 17984.09 26264.50 20787.96 14790.29 15374.13 13075.24 22786.81 22262.88 14593.89 14674.39 14175.40 28790.00 203
ab-mvs79.51 16378.97 15981.14 21788.46 17760.91 26483.84 25589.24 18170.36 19479.03 13888.87 17063.23 13890.21 26165.12 22682.57 20492.28 124
Anonymous2024052980.19 15278.89 16084.10 12490.60 10464.75 20288.95 10890.90 13565.97 26180.59 12391.17 11149.97 27493.73 15569.16 19082.70 20393.81 63
PCF-MVS73.52 780.38 14678.84 16185.01 9187.71 20168.99 11283.65 25891.46 12263.00 29277.77 16890.28 12966.10 10895.09 9461.40 25588.22 13390.94 166
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
iter_conf0580.00 15678.70 16283.91 13987.84 19565.83 17888.84 11484.92 26471.61 17278.70 14388.94 16643.88 31794.56 11379.28 9884.28 17991.33 151
v1079.74 15978.67 16382.97 17284.06 26364.95 19887.88 15390.62 14073.11 15175.11 23086.56 23761.46 16894.05 13673.68 14675.55 28189.90 209
VPNet78.69 18678.66 16478.76 26188.31 18255.72 32484.45 24386.63 24376.79 6778.26 15690.55 12659.30 19389.70 26866.63 21477.05 25890.88 167
BH-untuned79.47 16578.60 16582.05 19489.19 15065.91 17686.07 20388.52 20972.18 16275.42 21987.69 20061.15 17693.54 16160.38 26286.83 15086.70 291
Effi-MVS+-dtu80.03 15478.57 16684.42 11385.13 24768.74 11988.77 11688.10 21474.99 10674.97 23483.49 28957.27 20993.36 16973.53 14880.88 22091.18 156
WR-MVS_H78.51 19078.49 16778.56 26488.02 19056.38 31788.43 12692.67 6777.14 5773.89 24487.55 20466.25 10789.24 27558.92 27573.55 30790.06 201
Vis-MVSNet (Re-imp)78.36 19378.45 16878.07 27288.64 17151.78 34786.70 18679.63 32674.14 12975.11 23090.83 12161.29 17389.75 26658.10 28491.60 9192.69 110
BH-RMVSNet79.61 16078.44 16983.14 16289.38 13765.93 17584.95 22987.15 23673.56 14278.19 15989.79 14256.67 21493.36 16959.53 26986.74 15190.13 193
v119279.59 16278.43 17083.07 16683.55 27264.52 20486.93 17790.58 14170.83 18477.78 16785.90 24959.15 19493.94 14073.96 14577.19 25790.76 170
v14419279.47 16578.37 17182.78 18283.35 27563.96 21786.96 17590.36 14969.99 20077.50 17185.67 25560.66 18493.77 15174.27 14276.58 26690.62 175
CP-MVSNet78.22 19578.34 17277.84 27487.83 19654.54 33087.94 14991.17 12977.65 4073.48 24788.49 18062.24 15688.43 28962.19 24674.07 30090.55 179
Baseline_NR-MVSNet78.15 19978.33 17377.61 27985.79 23556.21 32086.78 18385.76 25573.60 14177.93 16587.57 20365.02 12088.99 27967.14 21175.33 28987.63 266
OpenMVScopyleft72.83 1079.77 15878.33 17384.09 12585.17 24469.91 9390.57 6590.97 13366.70 24972.17 26291.91 8954.70 22593.96 13761.81 25290.95 10088.41 255
UniMVSNet_ETH3D79.10 17778.24 17581.70 20186.85 22360.24 27487.28 16888.79 19974.25 12676.84 18590.53 12749.48 28091.56 23267.98 20082.15 20793.29 87
V4279.38 17178.24 17582.83 17681.10 32065.50 18685.55 21789.82 16371.57 17478.21 15886.12 24760.66 18493.18 17875.64 13275.46 28589.81 214
PS-CasMVS78.01 20478.09 17777.77 27687.71 20154.39 33288.02 14591.22 12677.50 4873.26 24988.64 17560.73 18188.41 29061.88 25073.88 30490.53 180
v192192079.22 17378.03 17882.80 17983.30 27763.94 21886.80 18190.33 15069.91 20277.48 17285.53 25858.44 19893.75 15373.60 14776.85 26390.71 173
jajsoiax79.29 17277.96 17983.27 15584.68 25466.57 16689.25 9890.16 15569.20 21875.46 21789.49 15145.75 31093.13 18176.84 12180.80 22290.11 195
TAPA-MVS73.13 979.15 17577.94 18082.79 18189.59 12762.99 24288.16 14291.51 11865.77 26277.14 18391.09 11360.91 18093.21 17350.26 32487.05 14692.17 129
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
tttt051779.40 16977.91 18183.90 14088.10 18763.84 21988.37 13384.05 27771.45 17676.78 18889.12 16249.93 27794.89 10470.18 17883.18 19592.96 103
c3_l78.75 18477.91 18181.26 21282.89 29061.56 25884.09 25389.13 18769.97 20175.56 21384.29 27766.36 10592.09 21673.47 15175.48 28390.12 194
MVSTER79.01 17977.88 18382.38 19083.07 28464.80 20184.08 25488.95 19569.01 22678.69 14487.17 21654.70 22592.43 20274.69 13980.57 22689.89 210
X-MVStestdata80.37 14777.83 18488.00 1594.42 2273.33 2092.78 1892.99 4979.14 2383.67 8612.47 37467.45 9596.60 3483.06 6294.50 5794.07 47
v14878.72 18577.80 18581.47 20682.73 29361.96 25386.30 19788.08 21673.26 14976.18 20485.47 26062.46 15192.36 20671.92 16473.82 30590.09 197
v124078.99 18077.78 18682.64 18583.21 27963.54 22686.62 18890.30 15269.74 20877.33 17585.68 25457.04 21293.76 15273.13 15676.92 25990.62 175
mvs_tets79.13 17677.77 18783.22 15984.70 25366.37 16889.17 9990.19 15469.38 21275.40 22089.46 15444.17 31593.15 17976.78 12380.70 22490.14 192
miper_ehance_all_eth78.59 18977.76 18881.08 21982.66 29561.56 25883.65 25889.15 18568.87 22975.55 21483.79 28566.49 10392.03 21773.25 15476.39 27089.64 218
thisisatest053079.40 16977.76 18884.31 11887.69 20365.10 19787.36 16484.26 27570.04 19977.42 17388.26 18849.94 27594.79 10970.20 17784.70 17393.03 98
CDS-MVSNet79.07 17877.70 19083.17 16187.60 20568.23 13384.40 24686.20 24967.49 24376.36 19986.54 23861.54 16590.79 25361.86 25187.33 14290.49 181
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
Anonymous2023121178.97 18177.69 19182.81 17890.54 10664.29 21290.11 7991.51 11865.01 27176.16 20788.13 19550.56 26893.03 18869.68 18577.56 25491.11 158
PEN-MVS77.73 20977.69 19177.84 27487.07 22153.91 33587.91 15191.18 12877.56 4573.14 25188.82 17161.23 17489.17 27659.95 26572.37 31590.43 183
AUN-MVS79.21 17477.60 19384.05 12988.71 16967.61 14585.84 21087.26 23469.08 22277.23 17988.14 19453.20 23993.47 16575.50 13673.45 30891.06 160
v7n78.97 18177.58 19483.14 16283.45 27465.51 18588.32 13491.21 12773.69 13872.41 25986.32 24457.93 20093.81 14869.18 18975.65 27990.11 195
TAMVS78.89 18377.51 19583.03 16887.80 19767.79 14184.72 23385.05 26267.63 24076.75 18987.70 19962.25 15590.82 25258.53 28087.13 14590.49 181
GBi-Net78.40 19177.40 19681.40 20887.60 20563.01 23988.39 13089.28 17771.63 16975.34 22287.28 20954.80 22191.11 24362.72 24079.57 23590.09 197
test178.40 19177.40 19681.40 20887.60 20563.01 23988.39 13089.28 17771.63 16975.34 22287.28 20954.80 22191.11 24362.72 24079.57 23590.09 197
BH-w/o78.21 19677.33 19880.84 22488.81 16365.13 19684.87 23087.85 22369.75 20674.52 23984.74 27361.34 17193.11 18258.24 28385.84 16584.27 321
FMVSNet278.20 19777.21 19981.20 21587.60 20562.89 24387.47 16289.02 19071.63 16975.29 22687.28 20954.80 22191.10 24662.38 24479.38 23989.61 219
anonymousdsp78.60 18877.15 20082.98 17180.51 32667.08 15687.24 16989.53 17165.66 26475.16 22887.19 21552.52 24092.25 21177.17 11879.34 24089.61 219
HY-MVS69.67 1277.95 20577.15 20080.36 23387.57 20960.21 27583.37 26587.78 22466.11 25775.37 22187.06 22063.27 13690.48 25861.38 25682.43 20590.40 185
cl2278.07 20177.01 20281.23 21382.37 30261.83 25583.55 26287.98 21868.96 22775.06 23283.87 28161.40 17091.88 22473.53 14876.39 27089.98 206
Anonymous20240521178.25 19477.01 20281.99 19691.03 9460.67 26884.77 23283.90 27970.65 19180.00 13091.20 10941.08 33491.43 23665.21 22585.26 16793.85 59
MVS78.19 19876.99 20481.78 19985.66 23766.99 15784.66 23490.47 14455.08 34872.02 26485.27 26363.83 13094.11 13566.10 21889.80 11584.24 322
LCM-MVSNet-Re77.05 22276.94 20577.36 28287.20 21851.60 34880.06 29680.46 31875.20 10267.69 30286.72 22562.48 15088.98 28063.44 23689.25 12091.51 145
miper_enhance_ethall77.87 20876.86 20680.92 22381.65 30961.38 26082.68 27288.98 19265.52 26675.47 21582.30 30265.76 11592.00 21972.95 15776.39 27089.39 223
FMVSNet377.88 20776.85 20780.97 22286.84 22462.36 24686.52 19188.77 20071.13 17975.34 22286.66 23254.07 23291.10 24662.72 24079.57 23589.45 222
DTE-MVSNet76.99 22376.80 20877.54 28186.24 23153.06 34387.52 16090.66 13977.08 6072.50 25788.67 17460.48 18789.52 27057.33 29170.74 32690.05 202
CNLPA78.08 20076.79 20981.97 19790.40 10971.07 6987.59 15984.55 26866.03 26072.38 26089.64 14657.56 20586.04 30859.61 26883.35 19288.79 246
cl____77.72 21076.76 21080.58 22982.49 29960.48 27183.09 26887.87 22169.22 21674.38 24185.22 26562.10 15891.53 23371.09 16975.41 28689.73 217
DIV-MVS_self_test77.72 21076.76 21080.58 22982.48 30060.48 27183.09 26887.86 22269.22 21674.38 24185.24 26462.10 15891.53 23371.09 16975.40 28789.74 216
baseline176.98 22476.75 21277.66 27788.13 18555.66 32585.12 22581.89 30373.04 15376.79 18788.90 16862.43 15287.78 29763.30 23871.18 32489.55 221
eth_miper_zixun_eth77.92 20676.69 21381.61 20483.00 28761.98 25283.15 26789.20 18369.52 21074.86 23684.35 27661.76 16192.56 19871.50 16772.89 31390.28 188
pm-mvs177.25 22176.68 21478.93 25984.22 26058.62 28486.41 19388.36 21171.37 17773.31 24888.01 19661.22 17589.15 27764.24 23273.01 31289.03 234
ET-MVSNet_ETH3D78.63 18776.63 21584.64 10586.73 22769.47 10485.01 22784.61 26769.54 20966.51 31886.59 23450.16 27291.75 22776.26 12684.24 18092.69 110
test250677.30 21976.49 21679.74 24690.08 11552.02 34487.86 15463.10 37174.88 10980.16 12992.79 7738.29 34492.35 20768.74 19592.50 8194.86 14
Fast-Effi-MVS+-dtu78.02 20376.49 21682.62 18683.16 28366.96 16186.94 17687.45 23172.45 15771.49 26984.17 27854.79 22491.58 23167.61 20380.31 22989.30 226
1112_ss77.40 21776.43 21880.32 23589.11 15660.41 27383.65 25887.72 22562.13 30373.05 25286.72 22562.58 14989.97 26362.11 24980.80 22290.59 178
PAPM77.68 21276.40 21981.51 20587.29 21761.85 25483.78 25689.59 17064.74 27371.23 27088.70 17262.59 14893.66 15652.66 31187.03 14789.01 235
PLCcopyleft70.83 1178.05 20276.37 22083.08 16591.88 8567.80 14088.19 14089.46 17364.33 27969.87 28788.38 18353.66 23593.58 15758.86 27682.73 20187.86 262
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
TR-MVS77.44 21576.18 22181.20 21588.24 18363.24 23484.61 23886.40 24667.55 24277.81 16686.48 24054.10 23193.15 17957.75 28782.72 20287.20 278
FMVSNet177.44 21576.12 22281.40 20886.81 22563.01 23988.39 13089.28 17770.49 19374.39 24087.28 20949.06 28691.11 24360.91 25978.52 24590.09 197
bld_raw_dy_0_6477.29 22075.98 22381.22 21485.04 25065.47 18788.14 14477.56 33569.20 21873.77 24589.40 16042.24 32888.85 28576.78 12381.64 21389.33 225
CHOSEN 1792x268877.63 21375.69 22483.44 14889.98 12168.58 12778.70 31187.50 22956.38 34375.80 21186.84 22158.67 19691.40 23761.58 25485.75 16690.34 186
WTY-MVS75.65 24375.68 22575.57 29886.40 23056.82 30877.92 31982.40 30065.10 26876.18 20487.72 19863.13 14380.90 33860.31 26381.96 20989.00 237
XXY-MVS75.41 24775.56 22674.96 30483.59 27157.82 29680.59 29183.87 28066.54 25474.93 23588.31 18563.24 13780.09 34162.16 24776.85 26386.97 285
thres100view90076.50 23075.55 22779.33 25489.52 13056.99 30685.83 21183.23 29173.94 13276.32 20087.12 21751.89 25491.95 22048.33 33283.75 18589.07 228
thres600view776.50 23075.44 22879.68 24889.40 13557.16 30385.53 21983.23 29173.79 13776.26 20187.09 21851.89 25491.89 22348.05 33783.72 18890.00 203
Test_1112_low_res76.40 23475.44 22879.27 25589.28 14658.09 28881.69 28187.07 23759.53 32272.48 25886.67 23161.30 17289.33 27360.81 26180.15 23190.41 184
HyFIR lowres test77.53 21475.40 23083.94 13889.59 12766.62 16480.36 29388.64 20756.29 34476.45 19485.17 26657.64 20493.28 17161.34 25783.10 19791.91 135
thisisatest051577.33 21875.38 23183.18 16085.27 24363.80 22082.11 27783.27 29065.06 26975.91 20883.84 28349.54 27994.27 12367.24 20986.19 15991.48 149
tfpn200view976.42 23375.37 23279.55 25389.13 15257.65 29885.17 22283.60 28273.41 14776.45 19486.39 24252.12 24791.95 22048.33 33283.75 18589.07 228
thres40076.50 23075.37 23279.86 24389.13 15257.65 29885.17 22283.60 28273.41 14776.45 19486.39 24252.12 24791.95 22048.33 33283.75 18590.00 203
131476.53 22975.30 23480.21 23783.93 26662.32 24884.66 23488.81 19860.23 31570.16 28184.07 28055.30 21990.73 25567.37 20683.21 19487.59 269
GA-MVS76.87 22675.17 23581.97 19782.75 29262.58 24481.44 28586.35 24872.16 16474.74 23782.89 29446.20 30492.02 21868.85 19481.09 21891.30 154
EPNet_dtu75.46 24574.86 23677.23 28682.57 29754.60 32986.89 17883.09 29471.64 16866.25 32085.86 25155.99 21688.04 29454.92 30286.55 15489.05 233
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
LS3D76.95 22574.82 23783.37 15290.45 10767.36 15289.15 10386.94 23961.87 30569.52 29090.61 12451.71 25794.53 11646.38 34486.71 15288.21 257
cascas76.72 22874.64 23882.99 17085.78 23665.88 17782.33 27589.21 18260.85 31172.74 25481.02 31347.28 29693.75 15367.48 20585.02 16889.34 224
DP-MVS76.78 22774.57 23983.42 14993.29 5469.46 10688.55 12583.70 28163.98 28570.20 27888.89 16954.01 23394.80 10846.66 34181.88 21186.01 303
TransMVSNet (Re)75.39 24874.56 24077.86 27385.50 24157.10 30586.78 18386.09 25272.17 16371.53 26887.34 20863.01 14489.31 27456.84 29561.83 34987.17 279
LTVRE_ROB69.57 1376.25 23674.54 24181.41 20788.60 17264.38 21179.24 30489.12 18870.76 18869.79 28987.86 19749.09 28593.20 17556.21 29980.16 23086.65 292
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
thres20075.55 24474.47 24278.82 26087.78 20057.85 29583.07 27083.51 28572.44 15975.84 21084.42 27552.08 24991.75 22747.41 33983.64 18986.86 287
MVP-Stereo76.12 23774.46 24381.13 21885.37 24269.79 9684.42 24587.95 21965.03 27067.46 30485.33 26253.28 23891.73 22958.01 28583.27 19381.85 341
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
F-COLMAP76.38 23574.33 24482.50 18889.28 14666.95 16288.41 12989.03 18964.05 28366.83 31288.61 17646.78 29992.89 19057.48 28878.55 24487.67 265
XVG-ACMP-BASELINE76.11 23874.27 24581.62 20283.20 28064.67 20383.60 26189.75 16669.75 20671.85 26587.09 21832.78 35792.11 21569.99 18180.43 22888.09 258
ACMH+68.96 1476.01 23974.01 24682.03 19588.60 17265.31 19388.86 11187.55 22770.25 19767.75 30187.47 20741.27 33293.19 17758.37 28175.94 27687.60 267
ACMH67.68 1675.89 24073.93 24781.77 20088.71 16966.61 16588.62 12289.01 19169.81 20366.78 31386.70 23041.95 33191.51 23555.64 30078.14 25087.17 279
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
CostFormer75.24 24973.90 24879.27 25582.65 29658.27 28780.80 28682.73 29861.57 30675.33 22583.13 29255.52 21791.07 24964.98 22878.34 24988.45 253
IterMVS-SCA-FT75.43 24673.87 24980.11 23982.69 29464.85 20081.57 28383.47 28769.16 22070.49 27584.15 27951.95 25288.15 29269.23 18872.14 31887.34 274
baseline275.70 24273.83 25081.30 21183.26 27861.79 25682.57 27480.65 31466.81 24666.88 31083.42 29057.86 20292.19 21363.47 23579.57 23589.91 208
sss73.60 26073.64 25173.51 31582.80 29155.01 32776.12 32581.69 30662.47 30074.68 23885.85 25257.32 20878.11 34860.86 26080.93 21987.39 272
pmmvs674.69 25173.39 25278.61 26381.38 31557.48 30186.64 18787.95 21964.99 27270.18 27986.61 23350.43 27089.52 27062.12 24870.18 32888.83 244
IB-MVS68.01 1575.85 24173.36 25383.31 15384.76 25266.03 17283.38 26485.06 26170.21 19869.40 29181.05 31245.76 30994.66 11265.10 22775.49 28289.25 227
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
D2MVS74.82 25073.21 25479.64 25079.81 33362.56 24580.34 29487.35 23264.37 27868.86 29482.66 29846.37 30190.10 26267.91 20181.24 21786.25 296
tfpnnormal74.39 25273.16 25578.08 27186.10 23358.05 28984.65 23787.53 22870.32 19571.22 27185.63 25654.97 22089.86 26443.03 35375.02 29386.32 295
miper_lstm_enhance74.11 25673.11 25677.13 28780.11 32959.62 27872.23 34186.92 24066.76 24870.40 27682.92 29356.93 21382.92 33069.06 19172.63 31488.87 242
IterMVS74.29 25372.94 25778.35 26881.53 31263.49 22881.58 28282.49 29968.06 23969.99 28483.69 28751.66 25885.54 31165.85 22171.64 32186.01 303
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
MS-PatchMatch73.83 25972.67 25877.30 28483.87 26766.02 17381.82 27884.66 26661.37 30968.61 29782.82 29647.29 29588.21 29159.27 27084.32 17877.68 355
CVMVSNet72.99 26972.58 25974.25 31184.28 25850.85 35386.41 19383.45 28844.56 35973.23 25087.54 20549.38 28185.70 31065.90 22078.44 24786.19 298
test-LLR72.94 27072.43 26074.48 30881.35 31658.04 29078.38 31277.46 33666.66 25069.95 28579.00 33148.06 29279.24 34266.13 21684.83 17086.15 299
OurMVSNet-221017-074.26 25472.42 26179.80 24583.76 26959.59 27985.92 20786.64 24266.39 25566.96 30987.58 20239.46 33891.60 23065.76 22269.27 33088.22 256
SCA74.22 25572.33 26279.91 24284.05 26462.17 25079.96 29879.29 32866.30 25672.38 26080.13 32251.95 25288.60 28759.25 27177.67 25388.96 239
tpmrst72.39 27372.13 26373.18 31980.54 32549.91 35679.91 29979.08 32963.11 29071.69 26779.95 32455.32 21882.77 33165.66 22373.89 30386.87 286
pmmvs474.03 25871.91 26480.39 23281.96 30668.32 13081.45 28482.14 30159.32 32369.87 28785.13 26752.40 24388.13 29360.21 26474.74 29684.73 318
EG-PatchMatch MVS74.04 25771.82 26580.71 22784.92 25167.42 14985.86 20988.08 21666.04 25964.22 33283.85 28235.10 35392.56 19857.44 28980.83 22182.16 340
tpm72.37 27571.71 26674.35 31082.19 30452.00 34579.22 30577.29 33964.56 27572.95 25383.68 28851.35 25983.26 32958.33 28275.80 27787.81 263
CL-MVSNet_self_test72.37 27571.46 26775.09 30379.49 33953.53 33780.76 28885.01 26369.12 22170.51 27482.05 30657.92 20184.13 32152.27 31266.00 34187.60 267
tpm273.26 26571.46 26778.63 26283.34 27656.71 31180.65 29080.40 31956.63 34273.55 24682.02 30751.80 25691.24 24156.35 29878.42 24887.95 259
RPSCF73.23 26671.46 26778.54 26582.50 29859.85 27682.18 27682.84 29758.96 32671.15 27289.41 15845.48 31284.77 31858.82 27771.83 32091.02 164
PatchmatchNetpermissive73.12 26771.33 27078.49 26783.18 28160.85 26579.63 30078.57 33064.13 28071.73 26679.81 32751.20 26185.97 30957.40 29076.36 27388.66 249
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
CR-MVSNet73.37 26271.27 27179.67 24981.32 31865.19 19475.92 32780.30 32059.92 31872.73 25581.19 31052.50 24186.69 30359.84 26677.71 25187.11 283
SixPastTwentyTwo73.37 26271.26 27279.70 24785.08 24957.89 29485.57 21383.56 28471.03 18265.66 32285.88 25042.10 32992.57 19759.11 27363.34 34788.65 250
MSDG73.36 26470.99 27380.49 23184.51 25665.80 18080.71 28986.13 25165.70 26365.46 32383.74 28644.60 31390.91 25151.13 31776.89 26184.74 317
PatchMatch-RL72.38 27470.90 27476.80 29088.60 17267.38 15179.53 30176.17 34462.75 29769.36 29282.00 30845.51 31184.89 31753.62 30780.58 22578.12 354
MVS_030472.48 27270.89 27577.24 28582.20 30359.68 27784.11 25283.49 28667.10 24566.87 31180.59 31835.00 35487.40 29959.07 27479.58 23484.63 319
PVSNet64.34 1872.08 27770.87 27675.69 29686.21 23256.44 31574.37 33780.73 31362.06 30470.17 28082.23 30442.86 32283.31 32854.77 30384.45 17787.32 275
RPMNet73.51 26170.49 27782.58 18781.32 31865.19 19475.92 32792.27 8357.60 33672.73 25576.45 34652.30 24495.43 7448.14 33677.71 25187.11 283
test_040272.79 27170.44 27879.84 24488.13 18565.99 17485.93 20684.29 27365.57 26567.40 30685.49 25946.92 29892.61 19635.88 36274.38 29980.94 346
COLMAP_ROBcopyleft66.92 1773.01 26870.41 27980.81 22587.13 22065.63 18388.30 13584.19 27662.96 29363.80 33687.69 20038.04 34592.56 19846.66 34174.91 29484.24 322
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
test-mter71.41 27970.39 28074.48 30881.35 31658.04 29078.38 31277.46 33660.32 31469.95 28579.00 33136.08 35179.24 34266.13 21684.83 17086.15 299
pmmvs571.55 27870.20 28175.61 29777.83 34556.39 31681.74 28080.89 31057.76 33467.46 30484.49 27449.26 28485.32 31457.08 29375.29 29085.11 314
MDTV_nov1_ep1369.97 28283.18 28153.48 33877.10 32380.18 32360.45 31269.33 29380.44 31948.89 29086.90 30251.60 31578.51 246
MIMVSNet70.69 28469.30 28374.88 30584.52 25556.35 31875.87 32979.42 32764.59 27467.76 30082.41 30041.10 33381.54 33546.64 34381.34 21586.75 290
tpmvs71.09 28169.29 28476.49 29182.04 30556.04 32178.92 30981.37 30964.05 28367.18 30878.28 33649.74 27889.77 26549.67 32772.37 31583.67 327
Patchmtry70.74 28369.16 28575.49 30080.72 32254.07 33474.94 33680.30 32058.34 33070.01 28281.19 31052.50 24186.54 30453.37 30871.09 32585.87 306
TESTMET0.1,169.89 29369.00 28672.55 32079.27 34256.85 30778.38 31274.71 35057.64 33568.09 29977.19 34337.75 34676.70 35363.92 23384.09 18184.10 325
PMMVS69.34 29568.67 28771.35 32775.67 35362.03 25175.17 33173.46 35250.00 35768.68 29579.05 32952.07 25078.13 34761.16 25882.77 20073.90 358
K. test v371.19 28068.51 28879.21 25783.04 28657.78 29784.35 24776.91 34272.90 15662.99 33982.86 29539.27 33991.09 24861.65 25352.66 36188.75 247
USDC70.33 28868.37 28976.21 29380.60 32456.23 31979.19 30686.49 24460.89 31061.29 34385.47 26031.78 36089.47 27253.37 30876.21 27482.94 337
tpm cat170.57 28568.31 29077.35 28382.41 30157.95 29378.08 31680.22 32252.04 35468.54 29877.66 34152.00 25187.84 29651.77 31372.07 31986.25 296
OpenMVS_ROBcopyleft64.09 1970.56 28668.19 29177.65 27880.26 32759.41 28185.01 22782.96 29658.76 32865.43 32482.33 30137.63 34791.23 24245.34 34976.03 27582.32 338
EPMVS69.02 29768.16 29271.59 32379.61 33749.80 35877.40 32166.93 36562.82 29670.01 28279.05 32945.79 30877.86 35056.58 29675.26 29187.13 282
CMPMVSbinary51.72 2170.19 29068.16 29276.28 29273.15 36557.55 30079.47 30283.92 27848.02 35856.48 35784.81 27143.13 32086.42 30662.67 24381.81 21284.89 315
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
AllTest70.96 28268.09 29479.58 25185.15 24563.62 22284.58 23979.83 32462.31 30160.32 34686.73 22332.02 35888.96 28250.28 32271.57 32286.15 299
gg-mvs-nofinetune69.95 29267.96 29575.94 29483.07 28454.51 33177.23 32270.29 35763.11 29070.32 27762.33 36043.62 31888.69 28653.88 30687.76 13584.62 320
FMVSNet569.50 29467.96 29574.15 31282.97 28955.35 32680.01 29782.12 30262.56 29963.02 33781.53 30936.92 34881.92 33348.42 33174.06 30185.17 313
PatchT68.46 30367.85 29770.29 33180.70 32343.93 36672.47 34074.88 34760.15 31670.55 27376.57 34549.94 27581.59 33450.58 31874.83 29585.34 309
pmmvs-eth3d70.50 28767.83 29878.52 26677.37 34866.18 17181.82 27881.51 30758.90 32763.90 33580.42 32042.69 32386.28 30758.56 27965.30 34383.11 333
Anonymous2023120668.60 30067.80 29971.02 32980.23 32850.75 35478.30 31580.47 31756.79 34166.11 32182.63 29946.35 30278.95 34443.62 35275.70 27883.36 330
Patchmatch-RL test70.24 28967.78 30077.61 27977.43 34759.57 28071.16 34370.33 35662.94 29468.65 29672.77 35450.62 26785.49 31269.58 18666.58 33987.77 264
test0.0.03 168.00 30467.69 30168.90 33677.55 34647.43 36075.70 33072.95 35466.66 25066.56 31482.29 30348.06 29275.87 35744.97 35074.51 29883.41 329
EU-MVSNet68.53 30267.61 30271.31 32878.51 34447.01 36284.47 24084.27 27442.27 36066.44 31984.79 27240.44 33683.76 32358.76 27868.54 33583.17 331
KD-MVS_self_test68.81 29867.59 30372.46 32174.29 35945.45 36377.93 31887.00 23863.12 28963.99 33478.99 33342.32 32584.77 31856.55 29764.09 34687.16 281
ppachtmachnet_test70.04 29167.34 30478.14 27079.80 33461.13 26179.19 30680.59 31559.16 32565.27 32579.29 32846.75 30087.29 30049.33 32866.72 33786.00 305
Anonymous2024052168.80 29967.22 30573.55 31474.33 35854.11 33383.18 26685.61 25658.15 33161.68 34280.94 31530.71 36181.27 33757.00 29473.34 31185.28 310
our_test_369.14 29667.00 30675.57 29879.80 33458.80 28277.96 31777.81 33359.55 32162.90 34078.25 33747.43 29483.97 32251.71 31467.58 33683.93 326
test20.0367.45 30666.95 30768.94 33575.48 35544.84 36577.50 32077.67 33466.66 25063.01 33883.80 28447.02 29778.40 34642.53 35568.86 33483.58 328
MIMVSNet168.58 30166.78 30873.98 31380.07 33051.82 34680.77 28784.37 27064.40 27759.75 34982.16 30536.47 34983.63 32542.73 35470.33 32786.48 294
testgi66.67 31166.53 30967.08 34275.62 35441.69 36975.93 32676.50 34366.11 25765.20 32886.59 23435.72 35274.71 36143.71 35173.38 31084.84 316
UnsupCasMVSNet_eth67.33 30765.99 31071.37 32573.48 36251.47 35075.16 33285.19 26065.20 26760.78 34580.93 31742.35 32477.20 35257.12 29253.69 36085.44 308
dp66.80 30965.43 31170.90 33079.74 33648.82 35975.12 33474.77 34859.61 32064.08 33377.23 34242.89 32180.72 33948.86 33066.58 33983.16 332
TinyColmap67.30 30864.81 31274.76 30781.92 30756.68 31280.29 29581.49 30860.33 31356.27 35883.22 29124.77 36487.66 29845.52 34769.47 32979.95 350
CHOSEN 280x42066.51 31264.71 31371.90 32281.45 31363.52 22757.98 36468.95 36353.57 35062.59 34176.70 34446.22 30375.29 36055.25 30179.68 23376.88 357
TDRefinement67.49 30564.34 31476.92 28873.47 36361.07 26284.86 23182.98 29559.77 31958.30 35285.13 26726.06 36387.89 29547.92 33860.59 35381.81 342
PM-MVS66.41 31364.14 31573.20 31873.92 36056.45 31478.97 30864.96 36963.88 28764.72 32980.24 32119.84 36983.44 32766.24 21564.52 34579.71 351
KD-MVS_2432*160066.22 31563.89 31673.21 31675.47 35653.42 33970.76 34684.35 27164.10 28166.52 31678.52 33434.55 35584.98 31550.40 32050.33 36481.23 344
miper_refine_blended66.22 31563.89 31673.21 31675.47 35653.42 33970.76 34684.35 27164.10 28166.52 31678.52 33434.55 35584.98 31550.40 32050.33 36481.23 344
MDA-MVSNet-bldmvs66.68 31063.66 31875.75 29579.28 34160.56 27073.92 33878.35 33164.43 27650.13 36379.87 32644.02 31683.67 32446.10 34556.86 35683.03 335
ADS-MVSNet266.20 31763.33 31974.82 30679.92 33158.75 28367.55 35675.19 34653.37 35165.25 32675.86 34742.32 32580.53 34041.57 35668.91 33285.18 311
Patchmatch-test64.82 32063.24 32069.57 33379.42 34049.82 35763.49 36269.05 36251.98 35559.95 34880.13 32250.91 26370.98 36640.66 35873.57 30687.90 261
MDA-MVSNet_test_wron65.03 31862.92 32171.37 32575.93 35156.73 30969.09 35474.73 34957.28 33954.03 36077.89 33845.88 30674.39 36349.89 32661.55 35082.99 336
YYNet165.03 31862.91 32271.38 32475.85 35256.60 31369.12 35374.66 35157.28 33954.12 35977.87 33945.85 30774.48 36249.95 32561.52 35183.05 334
ADS-MVSNet64.36 32162.88 32368.78 33879.92 33147.17 36167.55 35671.18 35553.37 35165.25 32675.86 34742.32 32573.99 36441.57 35668.91 33285.18 311
JIA-IIPM66.32 31462.82 32476.82 28977.09 34961.72 25765.34 35975.38 34558.04 33364.51 33062.32 36142.05 33086.51 30551.45 31669.22 33182.21 339
LF4IMVS64.02 32262.19 32569.50 33470.90 36753.29 34276.13 32477.18 34052.65 35358.59 35080.98 31423.55 36676.52 35453.06 31066.66 33878.68 353
new-patchmatchnet61.73 32461.73 32661.70 34572.74 36624.50 37969.16 35278.03 33261.40 30756.72 35675.53 35038.42 34276.48 35545.95 34657.67 35584.13 324
UnsupCasMVSNet_bld63.70 32361.53 32770.21 33273.69 36151.39 35172.82 33981.89 30355.63 34657.81 35371.80 35638.67 34178.61 34549.26 32952.21 36280.63 347
PVSNet_057.27 2061.67 32559.27 32868.85 33779.61 33757.44 30268.01 35573.44 35355.93 34558.54 35170.41 35744.58 31477.55 35147.01 34035.91 36771.55 360
MVS-HIRNet59.14 32657.67 32963.57 34481.65 30943.50 36771.73 34265.06 36839.59 36451.43 36257.73 36438.34 34382.58 33239.53 35973.95 30264.62 363
DSMNet-mixed57.77 32856.90 33060.38 34667.70 36935.61 37269.18 35153.97 37432.30 36957.49 35479.88 32540.39 33768.57 36838.78 36072.37 31576.97 356
pmmvs357.79 32754.26 33168.37 33964.02 37156.72 31075.12 33465.17 36740.20 36252.93 36169.86 35820.36 36875.48 35945.45 34855.25 35972.90 359
N_pmnet52.79 33153.26 33251.40 35178.99 3437.68 38269.52 3493.89 38251.63 35657.01 35574.98 35140.83 33565.96 36937.78 36164.67 34480.56 349
FPMVS53.68 33051.64 33359.81 34765.08 37051.03 35269.48 35069.58 36041.46 36140.67 36572.32 35516.46 37270.00 36724.24 36965.42 34258.40 366
new_pmnet50.91 33350.29 33452.78 35068.58 36834.94 37463.71 36156.63 37339.73 36344.95 36465.47 35921.93 36758.48 37034.98 36356.62 35764.92 362
LCM-MVSNet54.25 32949.68 33567.97 34053.73 37445.28 36466.85 35880.78 31235.96 36639.45 36662.23 3628.70 37878.06 34948.24 33551.20 36380.57 348
EGC-MVSNET52.07 33247.05 33667.14 34183.51 27360.71 26780.50 29267.75 3640.07 3770.43 37875.85 34924.26 36581.54 33528.82 36562.25 34859.16 365
ANet_high50.57 33446.10 33763.99 34348.67 37739.13 37070.99 34580.85 31161.39 30831.18 36857.70 36517.02 37173.65 36531.22 36415.89 37479.18 352
Gipumacopyleft45.18 33541.86 33855.16 34977.03 35051.52 34932.50 37080.52 31632.46 36827.12 36935.02 3709.52 37775.50 35822.31 37060.21 35438.45 369
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
PMVScopyleft37.38 2244.16 33640.28 33955.82 34840.82 37942.54 36865.12 36063.99 37034.43 36724.48 37057.12 3663.92 38076.17 35617.10 37255.52 35848.75 367
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
PMMVS240.82 33738.86 34046.69 35253.84 37316.45 38048.61 36749.92 37537.49 36531.67 36760.97 3638.14 37956.42 37128.42 36630.72 36967.19 361
E-PMN31.77 33830.64 34135.15 35552.87 37527.67 37657.09 36547.86 37624.64 37016.40 37533.05 37111.23 37554.90 37214.46 37418.15 37222.87 371
EMVS30.81 34029.65 34234.27 35650.96 37625.95 37856.58 36646.80 37724.01 37115.53 37630.68 37212.47 37454.43 37312.81 37517.05 37322.43 372
test_method31.52 33929.28 34338.23 35427.03 3816.50 38320.94 37262.21 3724.05 37522.35 37352.50 36713.33 37347.58 37427.04 36834.04 36860.62 364
cdsmvs_eth3d_5k19.96 34226.61 3440.00 3620.00 3850.00 3860.00 37389.26 1800.00 3800.00 38188.61 17661.62 1640.00 3810.00 3790.00 3790.00 377
MVEpermissive26.22 2330.37 34125.89 34543.81 35344.55 37835.46 37328.87 37139.07 37818.20 37218.58 37440.18 3692.68 38147.37 37517.07 37323.78 37148.60 368
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
tmp_tt18.61 34321.40 34610.23 3594.82 38210.11 38134.70 36930.74 3801.48 37623.91 37226.07 37328.42 36213.41 37827.12 36715.35 3757.17 373
wuyk23d16.82 34415.94 34719.46 35858.74 37231.45 37539.22 3683.74 3836.84 3746.04 3772.70 3771.27 38224.29 37710.54 37614.40 3762.63 374
ab-mvs-re7.23 3459.64 3480.00 3620.00 3850.00 3860.00 3730.00 3860.00 3800.00 38186.72 2250.00 3850.00 3810.00 3790.00 3790.00 377
test1236.12 3468.11 3490.14 3600.06 3840.09 38471.05 3440.03 3850.04 3790.25 3801.30 3790.05 3830.03 3800.21 3780.01 3780.29 375
testmvs6.04 3478.02 3500.10 3610.08 3830.03 38569.74 3480.04 3840.05 3780.31 3791.68 3780.02 3840.04 3790.24 3770.02 3770.25 376
pcd_1.5k_mvsjas5.26 3487.02 3510.00 3620.00 3850.00 3860.00 3730.00 3860.00 3800.00 3810.00 38063.15 1400.00 3810.00 3790.00 3790.00 377
test_blank0.00 3490.00 3520.00 3620.00 3850.00 3860.00 3730.00 3860.00 3800.00 3810.00 3800.00 3850.00 3810.00 3790.00 3790.00 377
uanet_test0.00 3490.00 3520.00 3620.00 3850.00 3860.00 3730.00 3860.00 3800.00 3810.00 3800.00 3850.00 3810.00 3790.00 3790.00 377
DCPMVS0.00 3490.00 3520.00 3620.00 3850.00 3860.00 3730.00 3860.00 3800.00 3810.00 3800.00 3850.00 3810.00 3790.00 3790.00 377
sosnet-low-res0.00 3490.00 3520.00 3620.00 3850.00 3860.00 3730.00 3860.00 3800.00 3810.00 3800.00 3850.00 3810.00 3790.00 3790.00 377
sosnet0.00 3490.00 3520.00 3620.00 3850.00 3860.00 3730.00 3860.00 3800.00 3810.00 3800.00 3850.00 3810.00 3790.00 3790.00 377
uncertanet0.00 3490.00 3520.00 3620.00 3850.00 3860.00 3730.00 3860.00 3800.00 3810.00 3800.00 3850.00 3810.00 3790.00 3790.00 377
Regformer0.00 3490.00 3520.00 3620.00 3850.00 3860.00 3730.00 3860.00 3800.00 3810.00 3800.00 3850.00 3810.00 3790.00 3790.00 377
uanet0.00 3490.00 3520.00 3620.00 3850.00 3860.00 3730.00 3860.00 3800.00 3810.00 3800.00 3850.00 3810.00 3790.00 3790.00 377
FOURS195.00 1072.39 4295.06 193.84 1874.49 11991.30 15
MSC_two_6792asdad89.16 194.34 2975.53 292.99 4997.53 189.67 196.44 994.41 32
PC_three_145268.21 23892.02 1294.00 4882.09 595.98 5584.58 4096.68 294.95 7
No_MVS89.16 194.34 2975.53 292.99 4997.53 189.67 196.44 994.41 32
test_one_060195.07 771.46 6194.14 778.27 3792.05 1195.74 680.83 11
eth-test20.00 385
eth-test0.00 385
ZD-MVS94.38 2772.22 4892.67 6770.98 18387.75 3194.07 4574.01 4096.70 2684.66 3994.84 49
IU-MVS95.30 271.25 6392.95 5666.81 24692.39 688.94 1196.63 494.85 16
OPU-MVS89.06 394.62 1575.42 493.57 794.02 4782.45 396.87 1983.77 5496.48 894.88 11
test_241102_TWO94.06 1277.24 5292.78 495.72 881.26 897.44 589.07 996.58 694.26 41
test_241102_ONE95.30 270.98 7094.06 1277.17 5693.10 195.39 1182.99 197.27 10
save fliter93.80 4472.35 4590.47 6991.17 12974.31 123
test_0728_THIRD78.38 3592.12 995.78 481.46 797.40 789.42 496.57 794.67 24
test_0728_SECOND87.71 3495.34 171.43 6293.49 994.23 597.49 389.08 796.41 1294.21 42
test072695.27 571.25 6393.60 694.11 877.33 5092.81 395.79 380.98 9
GSMVS88.96 239
test_part295.06 872.65 3391.80 13
sam_mvs151.32 26088.96 239
sam_mvs50.01 273
ambc75.24 30273.16 36450.51 35563.05 36387.47 23064.28 33177.81 34017.80 37089.73 26757.88 28660.64 35285.49 307
MTGPAbinary92.02 94
test_post178.90 3105.43 37648.81 29185.44 31359.25 271
test_post5.46 37550.36 27184.24 320
patchmatchnet-post74.00 35251.12 26288.60 287
GG-mvs-BLEND75.38 30181.59 31155.80 32379.32 30369.63 35967.19 30773.67 35343.24 31988.90 28450.41 31984.50 17481.45 343
MTMP92.18 3532.83 379
gm-plane-assit81.40 31453.83 33662.72 29880.94 31592.39 20463.40 237
test9_res84.90 3395.70 3192.87 105
TEST993.26 5672.96 2688.75 11791.89 10368.44 23685.00 5693.10 6574.36 3595.41 76
test_893.13 5872.57 3688.68 12191.84 10768.69 23284.87 6293.10 6574.43 3295.16 87
agg_prior282.91 6595.45 3392.70 108
agg_prior92.85 6671.94 5491.78 11084.41 7294.93 98
TestCases79.58 25185.15 24563.62 22279.83 32462.31 30160.32 34686.73 22332.02 35888.96 28250.28 32271.57 32286.15 299
test_prior472.60 3589.01 106
test_prior288.85 11275.41 9684.91 5893.54 5474.28 3683.31 5795.86 22
test_prior86.33 6392.61 7469.59 10092.97 5495.48 7093.91 55
旧先验286.56 19058.10 33287.04 3588.98 28074.07 144
新几何286.29 198
新几何183.42 14993.13 5870.71 8085.48 25757.43 33781.80 10891.98 8863.28 13592.27 21064.60 23192.99 7287.27 276
旧先验191.96 8265.79 18186.37 24793.08 6969.31 8192.74 7688.74 248
无先验87.48 16188.98 19260.00 31794.12 13367.28 20788.97 238
原ACMM286.86 179
原ACMM184.35 11693.01 6468.79 11592.44 7563.96 28681.09 11891.57 9966.06 11095.45 7267.19 21094.82 5288.81 245
test22291.50 8968.26 13284.16 25083.20 29354.63 34979.74 13191.63 9758.97 19591.42 9486.77 289
testdata291.01 25062.37 245
segment_acmp73.08 45
testdata79.97 24190.90 9864.21 21384.71 26559.27 32485.40 4992.91 7162.02 16089.08 27868.95 19291.37 9586.63 293
testdata184.14 25175.71 90
test1286.80 5592.63 7370.70 8191.79 10982.71 9971.67 5796.16 4794.50 5793.54 80
plane_prior790.08 11568.51 128
plane_prior689.84 12468.70 12360.42 188
plane_prior592.44 7595.38 7978.71 10286.32 15791.33 151
plane_prior491.00 118
plane_prior368.60 12678.44 3378.92 141
plane_prior291.25 5279.12 25
plane_prior189.90 123
plane_prior68.71 12190.38 7377.62 4186.16 160
n20.00 386
nn0.00 386
door-mid69.98 358
lessismore_v078.97 25881.01 32157.15 30465.99 36661.16 34482.82 29639.12 34091.34 23959.67 26746.92 36688.43 254
LGP-MVS_train84.50 10989.23 14868.76 11791.94 10175.37 9876.64 19291.51 10054.29 22994.91 10078.44 10483.78 18389.83 212
test1192.23 86
door69.44 361
HQP5-MVS66.98 158
HQP-NCC89.33 13989.17 9976.41 7577.23 179
ACMP_Plane89.33 13989.17 9976.41 7577.23 179
BP-MVS77.47 114
HQP4-MVS77.24 17895.11 9091.03 162
HQP3-MVS92.19 8985.99 163
HQP2-MVS60.17 191
NP-MVS89.62 12668.32 13090.24 130
MDTV_nov1_ep13_2view37.79 37175.16 33255.10 34766.53 31549.34 28253.98 30587.94 260
ACMMP++_ref81.95 210
ACMMP++81.25 216
Test By Simon64.33 125
ITE_SJBPF78.22 26981.77 30860.57 26983.30 28969.25 21567.54 30387.20 21436.33 35087.28 30154.34 30474.62 29786.80 288
DeepMVS_CXcopyleft27.40 35740.17 38026.90 37724.59 38117.44 37323.95 37148.61 3689.77 37626.48 37618.06 37124.47 37028.83 370