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

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

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

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

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




Method Infoallhigh-res
multi-view
indooroutdoorbotani.boulde.bridgedoorexhibi.lectur.living.loungeobserv.old co.statueterrac.
sort bysort bysort bysort bysort bysort bysort bysorted bysort bysort bysort bysort bysort bysort bysort bysort by
9.1488.26 1992.84 7091.52 5694.75 173.93 17188.57 3694.67 3075.57 2695.79 6486.77 5195.76 27
SF-MVS88.46 1588.74 1587.64 3892.78 7171.95 5292.40 2994.74 275.71 11389.16 2995.10 1875.65 2596.19 5287.07 4996.01 1794.79 23
MED-MVS test87.86 2694.57 1771.43 6193.28 1294.36 375.24 12792.25 995.03 2097.39 1188.15 3995.96 1994.75 30
MED-MVS89.59 490.16 487.86 2694.57 1771.43 6193.28 1294.36 376.30 9992.25 995.03 2081.59 797.39 1188.15 3995.96 1994.75 30
TestfortrainingZip a89.27 789.82 787.60 3994.57 1770.90 7893.28 1294.36 375.24 12792.25 995.03 2081.59 797.39 1186.12 5795.96 1994.52 54
ME-MVS88.98 1289.39 987.75 3094.54 2071.43 6191.61 4994.25 676.30 9990.62 2195.03 2078.06 1697.07 2088.15 3995.96 1994.75 30
DVP-MVS++90.23 191.01 187.89 2494.34 3171.25 6595.06 194.23 778.38 3892.78 495.74 682.45 397.49 489.42 1996.68 294.95 12
test_0728_SECOND87.71 3595.34 171.43 6193.49 1094.23 797.49 489.08 2296.41 1294.21 71
lecture88.09 1788.59 1686.58 6393.26 5669.77 9793.70 694.16 977.13 6689.76 2695.52 1472.26 5496.27 4986.87 5094.65 5293.70 102
test_one_060195.07 771.46 6094.14 1078.27 4192.05 1495.74 680.83 13
test072695.27 571.25 6593.60 794.11 1177.33 5892.81 395.79 380.98 11
MSP-MVS89.51 589.91 688.30 1094.28 3473.46 1792.90 2194.11 1180.27 1091.35 1794.16 5478.35 1596.77 2889.59 1794.22 6694.67 38
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
DPE-MVScopyleft89.48 689.98 588.01 1694.80 1172.69 3191.59 5194.10 1375.90 10892.29 795.66 1081.67 697.38 1487.44 4896.34 1593.95 86
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
PHI-MVS86.43 4986.17 5987.24 4790.88 10070.96 7492.27 3794.07 1472.45 20685.22 7991.90 12369.47 9696.42 4583.28 8695.94 2394.35 63
SED-MVS90.08 290.85 287.77 2895.30 270.98 7293.57 894.06 1577.24 6193.10 195.72 882.99 197.44 789.07 2596.63 494.88 16
test_241102_TWO94.06 1577.24 6192.78 495.72 881.26 1097.44 789.07 2596.58 694.26 70
test_241102_ONE95.30 270.98 7294.06 1577.17 6493.10 195.39 1682.99 197.27 15
APDe-MVScopyleft89.15 989.63 887.73 3194.49 2271.69 5593.83 493.96 1875.70 11591.06 1996.03 176.84 1897.03 2189.09 2195.65 3194.47 57
Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition
DeepC-MVS79.81 287.08 4086.88 4587.69 3691.16 9272.32 4590.31 7993.94 1977.12 6782.82 13694.23 5072.13 5797.09 1984.83 6795.37 3593.65 107
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
FOURS195.00 1072.39 4195.06 193.84 2074.49 15491.30 18
MCST-MVS87.37 3487.25 3587.73 3194.53 2172.46 4089.82 8893.82 2173.07 19884.86 8692.89 9676.22 2196.33 4684.89 6695.13 4094.40 60
ZNCC-MVS87.94 2287.85 2488.20 1294.39 2873.33 1993.03 1993.81 2276.81 7585.24 7894.32 4471.76 6196.93 2385.53 6195.79 2694.32 66
SPE-MVS-test86.29 5486.48 5185.71 8191.02 9667.21 18192.36 3493.78 2378.97 3383.51 12191.20 15470.65 7995.15 9281.96 10294.89 4694.77 25
3Dnovator+77.84 485.48 7384.47 9288.51 791.08 9473.49 1693.18 1693.78 2380.79 876.66 25693.37 8460.40 23796.75 3077.20 16293.73 7095.29 6
SteuartSystems-ACMMP88.72 1488.86 1488.32 992.14 7972.96 2593.73 593.67 2580.19 1288.10 4394.80 2773.76 3897.11 1887.51 4695.82 2594.90 15
Skip Steuart: Steuart Systems R&D Blog.
SMA-MVScopyleft89.08 1089.23 1088.61 694.25 3573.73 992.40 2993.63 2674.77 14892.29 795.97 274.28 3497.24 1688.58 3396.91 194.87 18
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
EC-MVSNet86.01 5886.38 5284.91 11489.31 14966.27 19592.32 3593.63 2679.37 2384.17 10391.88 12469.04 11095.43 7883.93 8193.77 6993.01 147
ACMMP_NAP88.05 2088.08 2187.94 1993.70 4573.05 2290.86 6593.59 2876.27 10188.14 4295.09 1971.06 7396.67 3387.67 4496.37 1494.09 78
CSCG86.41 5186.19 5887.07 5192.91 6772.48 3790.81 6693.56 2973.95 16983.16 12891.07 15975.94 2295.19 9079.94 12494.38 6293.55 115
MP-MVS-pluss87.67 2587.72 2587.54 4093.64 4872.04 5189.80 9093.50 3075.17 13586.34 6995.29 1770.86 7596.00 6088.78 3196.04 1694.58 47
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
FIs82.07 14982.42 13481.04 27688.80 17358.34 36688.26 16293.49 3176.93 7278.47 21391.04 16069.92 9092.34 24669.87 25384.97 22992.44 173
DELS-MVS85.41 7685.30 8085.77 8088.49 18467.93 15385.52 26993.44 3278.70 3483.63 11689.03 22074.57 2895.71 6780.26 12194.04 6793.66 103
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
GST-MVS87.42 3187.26 3487.89 2494.12 4072.97 2492.39 3193.43 3376.89 7384.68 8793.99 6570.67 7896.82 2684.18 7995.01 4193.90 89
FC-MVSNet-test81.52 16582.02 14680.03 30288.42 18955.97 40687.95 17393.42 3477.10 6877.38 23790.98 16569.96 8991.79 26668.46 26884.50 23692.33 176
DeepPCF-MVS80.84 188.10 1688.56 1786.73 6092.24 7869.03 11189.57 9993.39 3577.53 5389.79 2594.12 5678.98 1496.58 4085.66 5895.72 2894.58 47
HPM-MVScopyleft87.11 3886.98 4187.50 4393.88 4372.16 4792.19 3893.33 3676.07 10583.81 11193.95 6869.77 9396.01 5985.15 6294.66 5194.32 66
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
TestfortrainingZip87.28 4692.85 6872.05 5093.28 1293.32 3776.52 8588.91 3293.52 7777.30 1796.67 3391.98 9493.13 138
CS-MVS86.69 4486.95 4285.90 7990.76 10467.57 16592.83 2293.30 3879.67 1984.57 9492.27 10871.47 6695.02 10184.24 7793.46 7395.13 9
HFP-MVS87.58 2687.47 3187.94 1994.58 1673.54 1593.04 1793.24 3976.78 7784.91 8394.44 3970.78 7696.61 3784.53 7294.89 4693.66 103
ACMMPR87.44 2987.23 3688.08 1594.64 1373.59 1293.04 1793.20 4076.78 7784.66 9094.52 3268.81 11296.65 3584.53 7294.90 4594.00 83
reproduce_model87.28 3587.39 3386.95 5593.10 6271.24 6991.60 5093.19 4174.69 14988.80 3495.61 1170.29 8296.44 4486.20 5693.08 7593.16 134
reproduce-ours87.47 2787.61 2787.07 5193.27 5471.60 5691.56 5493.19 4174.98 13988.96 3095.54 1271.20 7196.54 4186.28 5493.49 7193.06 142
our_new_method87.47 2787.61 2787.07 5193.27 5471.60 5691.56 5493.19 4174.98 13988.96 3095.54 1271.20 7196.54 4186.28 5493.49 7193.06 142
SD-MVS88.06 1888.50 1886.71 6192.60 7672.71 2991.81 4693.19 4177.87 4290.32 2394.00 6374.83 2793.78 16087.63 4594.27 6593.65 107
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
ACMMPcopyleft85.89 6585.39 7687.38 4493.59 4972.63 3392.74 2593.18 4576.78 7780.73 17393.82 7264.33 16696.29 4782.67 9990.69 11893.23 127
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
region2R87.42 3187.20 3788.09 1494.63 1473.55 1393.03 1993.12 4676.73 8084.45 9594.52 3269.09 10696.70 3184.37 7494.83 4994.03 81
DPM-MVS84.93 8684.29 9386.84 5790.20 11473.04 2387.12 20593.04 4769.80 27582.85 13591.22 15373.06 4596.02 5876.72 17494.63 5491.46 212
PGM-MVS86.68 4586.27 5587.90 2294.22 3773.38 1890.22 8193.04 4775.53 11883.86 10994.42 4067.87 12696.64 3682.70 9894.57 5693.66 103
casdiffmvs_mvgpermissive85.99 5986.09 6285.70 8287.65 23167.22 18088.69 14293.04 4779.64 2185.33 7792.54 10573.30 4094.50 12683.49 8391.14 11095.37 2
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
DeepC-MVS_fast79.65 386.91 4186.62 5087.76 2993.52 5072.37 4391.26 5993.04 4776.62 8384.22 10193.36 8571.44 6796.76 2980.82 11395.33 3794.16 73
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
UniMVSNet (Re)81.60 16181.11 15783.09 20988.38 19064.41 25687.60 18493.02 5178.42 3778.56 20988.16 24969.78 9293.26 19569.58 25676.49 35091.60 203
sasdasda85.91 6385.87 6786.04 7589.84 12669.44 10690.45 7693.00 5276.70 8188.01 4691.23 15073.28 4193.91 15481.50 10588.80 15294.77 25
canonicalmvs85.91 6385.87 6786.04 7589.84 12669.44 10690.45 7693.00 5276.70 8188.01 4691.23 15073.28 4193.91 15481.50 10588.80 15294.77 25
CNVR-MVS88.93 1389.13 1388.33 894.77 1273.82 890.51 7093.00 5280.90 788.06 4494.06 5976.43 2096.84 2588.48 3695.99 1894.34 64
MSC_two_6792asdad89.16 194.34 3175.53 292.99 5597.53 289.67 1596.44 994.41 58
No_MVS89.16 194.34 3175.53 292.99 5597.53 289.67 1596.44 994.41 58
XVS87.18 3786.91 4488.00 1794.42 2473.33 1992.78 2392.99 5579.14 2683.67 11494.17 5367.45 12996.60 3883.06 8794.50 5794.07 79
X-MVStestdata80.37 20077.83 23988.00 1794.42 2473.33 1992.78 2392.99 5579.14 2683.67 11412.47 49767.45 12996.60 3883.06 8794.50 5794.07 79
APD-MVS_3200maxsize85.97 6185.88 6586.22 6892.69 7369.53 10091.93 4292.99 5573.54 18285.94 7094.51 3565.80 15495.61 6883.04 8992.51 8393.53 117
test_prior86.33 6592.61 7569.59 9992.97 6095.48 7593.91 87
IU-MVS95.30 271.25 6592.95 6166.81 32792.39 688.94 2896.63 494.85 21
balanced_conf0386.78 4286.99 4086.15 7191.24 9167.61 16390.51 7092.90 6277.26 6087.44 5791.63 13671.27 7096.06 5585.62 6095.01 4194.78 24
baseline84.93 8684.98 8384.80 11987.30 25165.39 21987.30 20192.88 6377.62 4784.04 10692.26 10971.81 6093.96 14681.31 10790.30 12495.03 11
MSLP-MVS++85.43 7585.76 6984.45 13491.93 8270.24 8690.71 6792.86 6477.46 5584.22 10192.81 10067.16 13392.94 21780.36 11994.35 6390.16 260
HPM-MVS++copyleft89.02 1189.15 1288.63 595.01 976.03 192.38 3292.85 6580.26 1187.78 4994.27 4775.89 2396.81 2787.45 4796.44 993.05 144
casdiffmvspermissive85.11 8385.14 8285.01 10787.20 25365.77 21187.75 18192.83 6677.84 4384.36 10092.38 10772.15 5693.93 15281.27 10990.48 12195.33 4
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
APD-MVScopyleft87.44 2987.52 3087.19 4894.24 3672.39 4191.86 4592.83 6673.01 20088.58 3594.52 3273.36 3996.49 4384.26 7595.01 4192.70 158
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
NCCC88.06 1888.01 2288.24 1194.41 2673.62 1191.22 6292.83 6681.50 585.79 7393.47 8173.02 4697.00 2284.90 6494.94 4494.10 77
CP-MVS87.11 3886.92 4387.68 3794.20 3873.86 793.98 392.82 6976.62 8383.68 11394.46 3667.93 12495.95 6384.20 7894.39 6193.23 127
DVP-MVScopyleft89.60 390.35 387.33 4595.27 571.25 6593.49 1092.73 7077.33 5892.12 1295.78 480.98 1197.40 989.08 2296.41 1293.33 124
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
GDP-MVS83.52 11982.64 13186.16 7088.14 19968.45 13389.13 12192.69 7172.82 20483.71 11291.86 12655.69 27695.35 8780.03 12289.74 13694.69 33
EIA-MVS83.31 12882.80 12884.82 11789.59 13265.59 21488.21 16392.68 7274.66 15178.96 19986.42 30369.06 10895.26 8875.54 18890.09 12893.62 110
ZD-MVS94.38 2972.22 4692.67 7370.98 24187.75 5194.07 5874.01 3796.70 3184.66 7094.84 48
nrg03083.88 10583.53 11484.96 10986.77 27169.28 11090.46 7592.67 7374.79 14782.95 13191.33 14972.70 5193.09 21080.79 11579.28 31792.50 168
WR-MVS_H78.51 24778.49 22178.56 34188.02 20656.38 40088.43 15192.67 7377.14 6573.89 32187.55 26766.25 14589.24 34858.92 36473.55 39490.06 270
MVSMamba_PlusPlus85.99 5985.96 6486.05 7491.09 9367.64 16289.63 9792.65 7672.89 20384.64 9191.71 13171.85 5996.03 5684.77 6994.45 6094.49 56
MP-MVScopyleft87.71 2387.64 2687.93 2194.36 3073.88 692.71 2792.65 7677.57 4983.84 11094.40 4172.24 5596.28 4885.65 5995.30 3993.62 110
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
ETV-MVS84.90 8884.67 8885.59 8789.39 14468.66 12888.74 14092.64 7879.97 1684.10 10485.71 31669.32 9995.38 8380.82 11391.37 10692.72 157
MGCFI-Net85.06 8585.51 7483.70 18589.42 14163.01 29289.43 10492.62 7976.43 9087.53 5491.34 14872.82 5093.42 18981.28 10888.74 15594.66 41
CANet86.45 4886.10 6187.51 4290.09 11670.94 7689.70 9492.59 8081.78 481.32 15991.43 14670.34 8097.23 1784.26 7593.36 7494.37 62
SR-MVS86.73 4386.67 4886.91 5694.11 4172.11 4992.37 3392.56 8174.50 15386.84 6594.65 3167.31 13195.77 6584.80 6892.85 7892.84 156
alignmvs85.48 7385.32 7985.96 7889.51 13669.47 10389.74 9292.47 8276.17 10387.73 5391.46 14570.32 8193.78 16081.51 10488.95 14994.63 44
原ACMM184.35 14193.01 6668.79 11892.44 8363.96 37881.09 16491.57 14066.06 15095.45 7667.19 27994.82 5088.81 316
HQP_MVS83.64 11583.14 12085.14 9990.08 11768.71 12491.25 6092.44 8379.12 2878.92 20191.00 16360.42 23595.38 8378.71 14486.32 20491.33 213
plane_prior592.44 8395.38 8378.71 14486.32 20491.33 213
CDPH-MVS85.76 6885.29 8187.17 4993.49 5171.08 7088.58 14792.42 8668.32 31484.61 9293.48 7972.32 5396.15 5479.00 14095.43 3494.28 69
UniMVSNet_NR-MVSNet81.88 15381.54 15282.92 22088.46 18663.46 28287.13 20492.37 8780.19 1278.38 21489.14 21671.66 6593.05 21370.05 24976.46 35192.25 180
TSAR-MVS + MP.88.02 2188.11 2087.72 3393.68 4772.13 4891.41 5892.35 8874.62 15288.90 3393.85 7175.75 2496.00 6087.80 4394.63 5495.04 10
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
CLD-MVS82.31 14581.65 15184.29 14788.47 18567.73 15985.81 25992.35 8875.78 11178.33 21686.58 29864.01 16994.35 13076.05 18087.48 18490.79 232
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
E5new84.22 9284.12 9584.51 12987.60 23365.36 22187.45 19192.31 9076.51 8683.53 11792.26 10969.25 10393.50 17979.88 12588.26 16394.69 33
E584.22 9284.12 9584.51 12987.60 23365.36 22187.45 19192.31 9076.51 8683.53 11792.26 10969.25 10393.50 17979.88 12588.26 16394.69 33
E6new84.22 9284.12 9584.52 12787.60 23365.36 22187.45 19192.30 9276.51 8683.53 11792.26 10969.26 10193.49 18179.88 12588.26 16394.69 33
E684.22 9284.12 9584.52 12787.60 23365.36 22187.45 19192.30 9276.51 8683.53 11792.26 10969.26 10193.49 18179.88 12588.26 16394.69 33
SR-MVS-dyc-post85.77 6785.61 7286.23 6793.06 6470.63 8391.88 4392.27 9473.53 18385.69 7494.45 3765.00 16295.56 6982.75 9491.87 9692.50 168
RE-MVS-def85.48 7593.06 6470.63 8391.88 4392.27 9473.53 18385.69 7494.45 3763.87 17082.75 9491.87 9692.50 168
RPMNet73.51 33570.49 36582.58 23981.32 40365.19 22775.92 43192.27 9457.60 44172.73 33776.45 44852.30 30895.43 7848.14 44077.71 33387.11 372
E484.10 9883.99 10184.45 13487.58 24164.99 23586.54 23192.25 9776.38 9583.37 12292.09 12069.88 9193.58 16879.78 13088.03 17394.77 25
E284.00 10183.87 10284.39 13787.70 22864.95 23686.40 23892.23 9875.85 10983.21 12491.78 12870.09 8693.55 17379.52 13388.05 17194.66 41
E384.00 10183.87 10284.39 13787.70 22864.95 23686.40 23892.23 9875.85 10983.21 12491.78 12870.09 8693.55 17379.52 13388.05 17194.66 41
test1192.23 98
viewcassd2359sk1183.89 10483.74 10784.34 14287.76 22364.91 24286.30 24292.22 10175.47 12083.04 13091.52 14170.15 8493.53 17679.26 13587.96 17494.57 49
mPP-MVS86.67 4686.32 5387.72 3394.41 2673.55 1392.74 2592.22 10176.87 7482.81 13794.25 4966.44 14296.24 5082.88 9294.28 6493.38 120
fmvsm_s_conf0.5_n_886.56 4787.17 3884.73 12287.76 22365.62 21389.20 11492.21 10379.94 1789.74 2794.86 2668.63 11594.20 13890.83 591.39 10594.38 61
E3new83.78 10983.60 11284.31 14487.76 22364.89 24386.24 24592.20 10475.15 13682.87 13391.23 15070.11 8593.52 17879.05 13687.79 17794.51 55
DP-MVS Recon83.11 13382.09 14486.15 7194.44 2370.92 7788.79 13592.20 10470.53 25379.17 19791.03 16264.12 16896.03 5668.39 26990.14 12791.50 208
NormalMVS86.29 5485.88 6587.52 4193.26 5672.47 3891.65 4792.19 10679.31 2484.39 9792.18 11464.64 16495.53 7280.70 11694.65 5294.56 51
Elysia81.53 16380.16 17885.62 8585.51 30168.25 14088.84 13392.19 10671.31 22980.50 17689.83 19346.89 37694.82 11076.85 16789.57 13893.80 97
StellarMVS81.53 16380.16 17885.62 8585.51 30168.25 14088.84 13392.19 10671.31 22980.50 17689.83 19346.89 37694.82 11076.85 16789.57 13893.80 97
HQP3-MVS92.19 10685.99 213
HQP-MVS82.61 14182.02 14684.37 13989.33 14666.98 18489.17 11692.19 10676.41 9177.23 24290.23 18660.17 23895.11 9577.47 15985.99 21391.03 223
3Dnovator76.31 583.38 12482.31 13886.59 6287.94 21072.94 2890.64 6892.14 11177.21 6375.47 28292.83 9858.56 24994.72 11773.24 21392.71 8192.13 190
MTGPAbinary92.02 112
MTAPA87.23 3687.00 3987.90 2294.18 3974.25 586.58 22992.02 11279.45 2285.88 7194.80 2768.07 12396.21 5186.69 5295.34 3693.23 127
MVS_Test83.15 13083.06 12283.41 19686.86 26663.21 28886.11 24992.00 11474.31 16082.87 13389.44 21370.03 8893.21 19977.39 16188.50 16093.81 95
PVSNet_BlendedMVS80.60 19180.02 18282.36 24388.85 16565.40 21786.16 24892.00 11469.34 28678.11 22186.09 31166.02 15194.27 13371.52 23182.06 28087.39 356
PVSNet_Blended80.98 17480.34 17382.90 22188.85 16565.40 21784.43 29992.00 11467.62 32078.11 22185.05 33766.02 15194.27 13371.52 23189.50 14089.01 306
QAPM80.88 17679.50 19985.03 10588.01 20868.97 11591.59 5192.00 11466.63 33675.15 30092.16 11657.70 25695.45 7663.52 30588.76 15490.66 239
LPG-MVS_test82.08 14881.27 15484.50 13189.23 15468.76 12090.22 8191.94 11875.37 12476.64 25791.51 14254.29 28994.91 10378.44 14683.78 24989.83 281
LGP-MVS_train84.50 13189.23 15468.76 12091.94 11875.37 12476.64 25791.51 14254.29 28994.91 10378.44 14683.78 24989.83 281
TEST993.26 5672.96 2588.75 13891.89 12068.44 31285.00 8193.10 8974.36 3395.41 81
train_agg86.43 4986.20 5687.13 5093.26 5672.96 2588.75 13891.89 12068.69 30785.00 8193.10 8974.43 3195.41 8184.97 6395.71 2993.02 146
dcpmvs_285.63 7086.15 6084.06 16691.71 8564.94 23986.47 23391.87 12273.63 17886.60 6893.02 9476.57 1991.87 26583.36 8492.15 9095.35 3
DU-MVS81.12 17380.52 16982.90 22187.80 21763.46 28287.02 20991.87 12279.01 3178.38 21489.07 21865.02 16093.05 21370.05 24976.46 35192.20 183
test_893.13 6072.57 3588.68 14391.84 12468.69 30784.87 8593.10 8974.43 3195.16 91
viewmacassd2359aftdt83.76 11083.66 11084.07 16386.59 27764.56 24886.88 21691.82 12575.72 11283.34 12392.15 11868.24 12292.88 22079.05 13689.15 14794.77 25
PAPM_NR83.02 13482.41 13584.82 11792.47 7766.37 19387.93 17591.80 12673.82 17377.32 23990.66 17267.90 12594.90 10570.37 24489.48 14193.19 133
test1286.80 5992.63 7470.70 8291.79 12782.71 13871.67 6496.16 5394.50 5793.54 116
agg_prior92.85 6871.94 5391.78 12884.41 9694.93 102
PAPR81.66 16080.89 16283.99 17690.27 11264.00 26286.76 22391.77 12968.84 30577.13 24989.50 20667.63 12794.88 10867.55 27488.52 15993.09 140
viewmanbaseed2359cas83.66 11383.55 11384.00 17486.81 26964.53 24986.65 22691.75 13074.89 14383.15 12991.68 13268.74 11492.83 22479.02 13889.24 14494.63 44
balanced_ft_v183.98 10383.64 11185.03 10589.76 12965.86 20688.31 16091.71 13174.41 15780.41 17990.82 16862.90 18794.90 10583.04 8991.37 10694.32 66
PVSNet_Blended_VisFu82.62 14081.83 15084.96 10990.80 10269.76 9888.74 14091.70 13269.39 28478.96 19988.46 24065.47 15694.87 10974.42 19988.57 15790.24 258
viewdifsd2359ckpt0983.34 12582.55 13385.70 8287.64 23267.72 16088.43 15191.68 13371.91 21881.65 15590.68 17167.10 13494.75 11576.17 17787.70 18094.62 46
KinetiMVS83.31 12882.61 13285.39 9287.08 26267.56 16688.06 16991.65 13477.80 4482.21 14491.79 12757.27 26294.07 14477.77 15589.89 13494.56 51
fmvsm_s_conf0.5_n_685.55 7286.20 5683.60 18787.32 25065.13 22988.86 13091.63 13575.41 12288.23 4193.45 8268.56 11692.47 23889.52 1892.78 7993.20 132
viewdifsd2359ckpt1382.91 13682.29 13984.77 12086.96 26566.90 18887.47 18891.62 13672.19 21181.68 15490.71 17066.92 13593.28 19275.90 18287.15 19094.12 76
HPM-MVS_fast85.35 7984.95 8586.57 6493.69 4670.58 8592.15 4091.62 13673.89 17282.67 13994.09 5762.60 18995.54 7180.93 11192.93 7793.57 113
ACMM73.20 880.78 18679.84 18883.58 18989.31 14968.37 13589.99 8491.60 13870.28 26377.25 24089.66 20153.37 30093.53 17674.24 20282.85 27088.85 314
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
VPA-MVSNet80.60 19180.55 16880.76 28388.07 20460.80 33786.86 21791.58 13975.67 11680.24 18189.45 21263.34 17390.25 32970.51 24379.22 31891.23 216
OPM-MVS83.50 12082.95 12585.14 9988.79 17470.95 7589.13 12191.52 14077.55 5280.96 16791.75 13060.71 22794.50 12679.67 13286.51 20289.97 276
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
Anonymous2023121178.97 23577.69 24782.81 22690.54 10764.29 25890.11 8391.51 14165.01 36276.16 27388.13 25450.56 34093.03 21669.68 25577.56 33791.11 219
PS-MVSNAJss82.07 14981.31 15384.34 14286.51 27967.27 17789.27 11291.51 14171.75 21979.37 19490.22 18763.15 18094.27 13377.69 15782.36 27791.49 209
TAPA-MVS73.13 979.15 22977.94 23482.79 23089.59 13262.99 29688.16 16691.51 14165.77 34677.14 24891.09 15860.91 22593.21 19950.26 42687.05 19292.17 188
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
ACMP74.13 681.51 16780.57 16784.36 14089.42 14168.69 12789.97 8591.50 14474.46 15575.04 30490.41 17953.82 29594.54 12377.56 15882.91 26989.86 280
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
PCF-MVS73.52 780.38 19878.84 21685.01 10787.71 22668.99 11483.65 31891.46 14563.00 38777.77 23190.28 18366.10 14895.09 9961.40 34188.22 16890.94 228
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
TranMVSNet+NR-MVSNet80.84 17780.31 17482.42 24187.85 21462.33 30787.74 18291.33 14680.55 977.99 22589.86 19165.23 15892.62 22867.05 28175.24 37892.30 178
RRT-MVS82.60 14382.10 14384.10 15787.98 20962.94 29787.45 19191.27 14777.42 5679.85 18590.28 18356.62 27094.70 11979.87 12988.15 16994.67 38
PS-CasMVS78.01 26178.09 23177.77 35987.71 22654.39 42588.02 17091.22 14877.50 5473.26 32988.64 23460.73 22688.41 36661.88 33573.88 39190.53 245
v7n78.97 23577.58 25083.14 20783.45 35365.51 21588.32 15991.21 14973.69 17772.41 34286.32 30657.93 25393.81 15969.18 25975.65 36490.11 264
PEN-MVS77.73 26777.69 24777.84 35787.07 26453.91 42887.91 17691.18 15077.56 5173.14 33188.82 22961.23 21989.17 35059.95 35272.37 40290.43 249
MM89.16 889.23 1088.97 490.79 10373.65 1092.66 2891.17 15186.57 187.39 5894.97 2571.70 6397.68 192.19 195.63 3295.57 1
save fliter93.80 4472.35 4490.47 7491.17 15174.31 160
CP-MVSNet78.22 25278.34 22677.84 35787.83 21654.54 42387.94 17491.17 15177.65 4673.48 32788.49 23962.24 19888.43 36562.19 33074.07 38790.55 244
114514_t80.68 18779.51 19884.20 15494.09 4267.27 17789.64 9691.11 15458.75 43274.08 31990.72 16958.10 25295.04 10069.70 25489.42 14290.30 256
NR-MVSNet80.23 20479.38 20182.78 23187.80 21763.34 28586.31 24191.09 15579.01 3172.17 34689.07 21867.20 13292.81 22566.08 28875.65 36492.20 183
fmvsm_s_conf0.5_n_1086.38 5286.76 4685.24 9687.33 24867.30 17589.50 10190.98 15676.25 10290.56 2294.75 2968.38 11894.24 13790.80 792.32 8994.19 72
OpenMVScopyleft72.83 1079.77 21178.33 22784.09 16185.17 31069.91 9490.57 6990.97 15766.70 33072.17 34691.91 12254.70 28693.96 14661.81 33790.95 11488.41 330
MAR-MVS81.84 15480.70 16485.27 9591.32 9071.53 5989.82 8890.92 15869.77 27778.50 21086.21 30762.36 19594.52 12565.36 29392.05 9389.77 284
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
tt080578.73 24077.83 23981.43 26285.17 31060.30 34889.41 10790.90 15971.21 23377.17 24788.73 23046.38 38293.21 19972.57 22078.96 31990.79 232
Anonymous2024052980.19 20678.89 21584.10 15790.60 10564.75 24688.95 12790.90 15965.97 34580.59 17591.17 15649.97 34893.73 16669.16 26082.70 27493.81 95
OMC-MVS82.69 13981.97 14884.85 11688.75 17667.42 16987.98 17190.87 16174.92 14279.72 18791.65 13462.19 19993.96 14675.26 19286.42 20393.16 134
UA-Net85.08 8484.96 8485.45 9092.07 8068.07 14689.78 9190.86 16282.48 284.60 9393.20 8869.35 9895.22 8971.39 23490.88 11693.07 141
viewdifsd2359ckpt0782.83 13882.78 13082.99 21686.51 27962.58 30085.09 27890.83 16375.22 12982.28 14191.63 13669.43 9792.03 25577.71 15686.32 20494.34 64
fmvsm_s_conf0.5_n_1186.06 5686.75 4784.00 17487.78 22066.09 19789.96 8690.80 16477.37 5786.72 6694.20 5272.51 5292.78 22689.08 2292.33 8793.13 138
test_fmvsm_n_192085.29 8085.34 7785.13 10286.12 28869.93 9388.65 14490.78 16569.97 27188.27 3993.98 6671.39 6891.54 28188.49 3590.45 12293.91 87
EPP-MVSNet83.40 12383.02 12384.57 12590.13 11564.47 25492.32 3590.73 16674.45 15679.35 19591.10 15769.05 10995.12 9372.78 21787.22 18894.13 75
DTE-MVSNet76.99 28376.80 26777.54 36686.24 28353.06 43887.52 18690.66 16777.08 6972.50 34088.67 23360.48 23489.52 34257.33 38170.74 41490.05 271
v1079.74 21278.67 21782.97 21984.06 33764.95 23687.88 17890.62 16873.11 19775.11 30186.56 29961.46 21394.05 14573.68 20575.55 36689.90 278
test_fmvsmconf_n85.92 6286.04 6385.57 8885.03 31769.51 10189.62 9890.58 16973.42 18687.75 5194.02 6172.85 4993.24 19690.37 890.75 11793.96 84
v119279.59 21578.43 22483.07 21283.55 35164.52 25086.93 21490.58 16970.83 24477.78 23085.90 31259.15 24493.94 14973.96 20477.19 34090.76 234
v114480.03 20879.03 21183.01 21583.78 34464.51 25187.11 20690.57 17171.96 21778.08 22386.20 30861.41 21493.94 14974.93 19477.23 33890.60 242
XVG-OURS-SEG-HR80.81 17979.76 19083.96 17885.60 29968.78 11983.54 32490.50 17270.66 25176.71 25591.66 13360.69 22891.26 29476.94 16681.58 28591.83 195
MVS78.19 25576.99 26381.78 25485.66 29666.99 18384.66 28890.47 17355.08 45472.02 34885.27 32963.83 17194.11 14366.10 28789.80 13584.24 424
fmvsm_l_conf0.5_n_386.02 5786.32 5385.14 9987.20 25368.54 13189.57 9990.44 17475.31 12687.49 5594.39 4272.86 4892.72 22789.04 2790.56 12094.16 73
XVG-OURS80.41 19679.23 20783.97 17785.64 29769.02 11383.03 33890.39 17571.09 23677.63 23391.49 14454.62 28891.35 29175.71 18483.47 26191.54 206
MVSFormer82.85 13782.05 14585.24 9687.35 24370.21 8790.50 7290.38 17668.55 30981.32 15989.47 20861.68 20793.46 18678.98 14190.26 12592.05 192
test_djsdf80.30 20379.32 20483.27 20083.98 33965.37 22090.50 7290.38 17668.55 30976.19 26988.70 23156.44 27193.46 18678.98 14180.14 30590.97 226
CPTT-MVS83.73 11183.33 11984.92 11393.28 5370.86 7992.09 4190.38 17668.75 30679.57 18992.83 9860.60 23393.04 21580.92 11291.56 10390.86 230
v14419279.47 21878.37 22582.78 23183.35 35463.96 26386.96 21190.36 17969.99 27077.50 23485.67 31960.66 23093.77 16274.27 20176.58 34890.62 240
v192192079.22 22778.03 23282.80 22783.30 35663.94 26586.80 21990.33 18069.91 27377.48 23585.53 32358.44 25093.75 16473.60 20676.85 34590.71 238
MVS_111021_HR85.14 8284.75 8786.32 6691.65 8672.70 3085.98 25190.33 18076.11 10482.08 14691.61 13971.36 6994.17 14181.02 11092.58 8292.08 191
v124078.99 23477.78 24282.64 23683.21 35963.54 27986.62 22890.30 18269.74 28077.33 23885.68 31857.04 26593.76 16373.13 21476.92 34290.62 240
test_fmvsmconf0.1_n85.61 7185.65 7185.50 8982.99 37169.39 10889.65 9590.29 18373.31 19087.77 5094.15 5571.72 6293.23 19790.31 990.67 11993.89 90
v879.97 21079.02 21282.80 22784.09 33664.50 25387.96 17290.29 18374.13 16775.24 29786.81 28562.88 18893.89 15774.39 20075.40 37390.00 272
fmvsm_s_conf0.5_n_386.36 5387.46 3283.09 20987.08 26265.21 22689.09 12390.21 18579.67 1989.98 2495.02 2473.17 4391.71 27191.30 391.60 10092.34 175
mvs_tets79.13 23077.77 24383.22 20484.70 32366.37 19389.17 11690.19 18669.38 28575.40 28789.46 21044.17 40593.15 20676.78 17380.70 29790.14 261
jajsoiax79.29 22677.96 23383.27 20084.68 32466.57 19189.25 11390.16 18769.20 29375.46 28489.49 20745.75 39393.13 20876.84 16980.80 29590.11 264
Vis-MVSNetpermissive83.46 12182.80 12885.43 9190.25 11368.74 12290.30 8090.13 18876.33 9880.87 17092.89 9661.00 22494.20 13872.45 22690.97 11393.35 123
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
PS-MVSNAJ81.69 15881.02 15983.70 18589.51 13668.21 14384.28 30490.09 18970.79 24581.26 16385.62 32163.15 18094.29 13175.62 18688.87 15188.59 325
xiu_mvs_v2_base81.69 15881.05 15883.60 18789.15 15768.03 14884.46 29690.02 19070.67 24881.30 16286.53 30163.17 17994.19 14075.60 18788.54 15888.57 326
FA-MVS(test-final)80.96 17579.91 18584.10 15788.30 19365.01 23384.55 29390.01 19173.25 19379.61 18887.57 26558.35 25194.72 11771.29 23586.25 20792.56 164
v2v48280.23 20479.29 20583.05 21383.62 34964.14 26087.04 20789.97 19273.61 17978.18 22087.22 27661.10 22293.82 15876.11 17876.78 34791.18 217
test_yl81.17 17080.47 17183.24 20289.13 15863.62 27186.21 24689.95 19372.43 20981.78 15289.61 20357.50 25993.58 16870.75 23986.90 19492.52 166
DCV-MVSNet81.17 17080.47 17183.24 20289.13 15863.62 27186.21 24689.95 19372.43 20981.78 15289.61 20357.50 25993.58 16870.75 23986.90 19492.52 166
fmvsm_s_conf0.5_n_783.34 12584.03 10081.28 26885.73 29565.13 22985.40 27089.90 19574.96 14182.13 14593.89 6966.65 13787.92 37186.56 5391.05 11190.80 231
V4279.38 22478.24 22982.83 22481.10 40565.50 21685.55 26589.82 19671.57 22578.21 21886.12 31060.66 23093.18 20575.64 18575.46 37089.81 283
fmvsm_s_conf0.5_n_485.39 7785.75 7084.30 14686.70 27365.83 20788.77 13689.78 19775.46 12188.35 3793.73 7469.19 10593.06 21291.30 388.44 16194.02 82
VNet82.21 14682.41 13581.62 25790.82 10160.93 33484.47 29489.78 19776.36 9784.07 10591.88 12464.71 16390.26 32870.68 24188.89 15093.66 103
diffmvs_AUTHOR82.38 14482.27 14082.73 23583.26 35763.80 26883.89 31289.76 19973.35 18982.37 14090.84 16666.25 14590.79 31882.77 9387.93 17593.59 112
diffmvspermissive82.10 14781.88 14982.76 23383.00 36763.78 27083.68 31789.76 19972.94 20182.02 14789.85 19265.96 15390.79 31882.38 10087.30 18793.71 101
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
XVG-ACMP-BASELINE76.11 30274.27 31481.62 25783.20 36064.67 24783.60 32189.75 20169.75 27871.85 34987.09 28132.78 46092.11 25369.99 25180.43 30188.09 338
EI-MVSNet-Vis-set84.19 9683.81 10585.31 9488.18 19667.85 15587.66 18389.73 20280.05 1582.95 13189.59 20570.74 7794.82 11080.66 11884.72 23393.28 126
EI-MVSNet-UG-set83.81 10683.38 11785.09 10487.87 21367.53 16787.44 19689.66 20379.74 1882.23 14389.41 21470.24 8394.74 11679.95 12383.92 24892.99 149
test_fmvsmconf0.01_n84.73 8984.52 9185.34 9380.25 41369.03 11189.47 10289.65 20473.24 19486.98 6394.27 4766.62 13893.23 19790.26 1089.95 13293.78 99
BP-MVS184.32 9183.71 10886.17 6987.84 21567.85 15589.38 10989.64 20577.73 4583.98 10792.12 11956.89 26795.43 7884.03 8091.75 9995.24 7
VortexMVS78.57 24677.89 23780.59 28685.89 29162.76 29985.61 26089.62 20672.06 21574.99 30585.38 32755.94 27590.77 32174.99 19376.58 34888.23 334
PAPM77.68 27176.40 27981.51 26087.29 25261.85 31683.78 31489.59 20764.74 36471.23 35688.70 23162.59 19093.66 16752.66 41087.03 19389.01 306
MGCNet87.69 2487.55 2988.12 1389.45 14071.76 5491.47 5789.54 20882.14 386.65 6794.28 4668.28 12197.46 690.81 695.31 3895.15 8
anonymousdsp78.60 24477.15 25982.98 21880.51 41167.08 18287.24 20389.53 20965.66 34875.16 29987.19 27852.52 30492.25 24977.17 16379.34 31689.61 288
MG-MVS83.41 12283.45 11583.28 19992.74 7262.28 30988.17 16589.50 21075.22 12981.49 15792.74 10466.75 13695.11 9572.85 21691.58 10292.45 172
PLCcopyleft70.83 1178.05 25976.37 28083.08 21191.88 8467.80 15788.19 16489.46 21164.33 37169.87 37388.38 24253.66 29693.58 16858.86 36582.73 27287.86 343
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
fmvsm_l_conf0.5_n_985.84 6686.63 4983.46 19287.12 26166.01 20088.56 14889.43 21275.59 11789.32 2894.32 4472.89 4791.21 29990.11 1192.33 8793.16 134
SDMVSNet80.38 19880.18 17780.99 27789.03 16364.94 23980.45 37889.40 21375.19 13376.61 25989.98 18960.61 23287.69 37576.83 17083.55 25890.33 254
Fast-Effi-MVS+80.81 17979.92 18483.47 19188.85 16564.51 25185.53 26789.39 21470.79 24578.49 21185.06 33667.54 12893.58 16867.03 28286.58 20092.32 177
IterMVS-LS80.06 20779.38 20182.11 24885.89 29163.20 28986.79 22089.34 21574.19 16475.45 28586.72 28866.62 13892.39 24272.58 21976.86 34490.75 235
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
icg_test_0407_278.92 23778.93 21478.90 33487.13 25663.59 27576.58 42789.33 21670.51 25477.82 22789.03 22061.84 20381.38 43372.56 22285.56 22291.74 198
IMVS_040780.61 18979.90 18682.75 23487.13 25663.59 27585.33 27189.33 21670.51 25477.82 22789.03 22061.84 20392.91 21872.56 22285.56 22291.74 198
IMVS_040477.16 28176.42 27879.37 32587.13 25663.59 27577.12 42489.33 21670.51 25466.22 42389.03 22050.36 34382.78 42372.56 22285.56 22291.74 198
IMVS_040380.80 18280.12 18182.87 22387.13 25663.59 27585.19 27289.33 21670.51 25478.49 21189.03 22063.26 17693.27 19472.56 22285.56 22291.74 198
API-MVS81.99 15181.23 15584.26 15290.94 9870.18 9291.10 6389.32 22071.51 22678.66 20688.28 24565.26 15795.10 9864.74 29991.23 10987.51 353
fmvsm_s_conf0.5_n_585.22 8185.55 7384.25 15386.26 28267.40 17189.18 11589.31 22172.50 20588.31 3893.86 7069.66 9491.96 25989.81 1391.05 11193.38 120
GBi-Net78.40 24877.40 25481.40 26487.60 23363.01 29288.39 15489.28 22271.63 22175.34 29087.28 27254.80 28291.11 30062.72 31979.57 30990.09 266
test178.40 24877.40 25481.40 26487.60 23363.01 29288.39 15489.28 22271.63 22175.34 29087.28 27254.80 28291.11 30062.72 31979.57 30990.09 266
FMVSNet177.44 27576.12 28281.40 26486.81 26963.01 29288.39 15489.28 22270.49 25874.39 31687.28 27249.06 36391.11 30060.91 34578.52 32290.09 266
cdsmvs_eth3d_5k19.96 46326.61 4650.00 4850.00 5080.00 5100.00 49689.26 2250.00 5030.00 50488.61 23561.62 2090.00 5040.00 5020.00 5020.00 500
SSM_040781.58 16280.48 17084.87 11588.81 16967.96 15087.37 19789.25 22671.06 23879.48 19190.39 18059.57 24094.48 12872.45 22685.93 21592.18 185
SSM_040481.91 15280.84 16385.13 10289.24 15368.26 13887.84 18089.25 22671.06 23880.62 17490.39 18059.57 24094.65 12172.45 22687.19 18992.47 171
ab-mvs79.51 21678.97 21381.14 27388.46 18660.91 33583.84 31389.24 22870.36 25979.03 19888.87 22863.23 17890.21 33065.12 29582.57 27592.28 179
cascas76.72 28874.64 30682.99 21685.78 29465.88 20582.33 34489.21 22960.85 41172.74 33681.02 40647.28 37293.75 16467.48 27585.02 22889.34 296
eth_miper_zixun_eth77.92 26376.69 27281.61 25983.00 36761.98 31483.15 33189.20 23069.52 28374.86 30884.35 35061.76 20692.56 23371.50 23372.89 40090.28 257
h-mvs3383.15 13082.19 14186.02 7790.56 10670.85 8088.15 16789.16 23176.02 10684.67 8891.39 14761.54 21095.50 7482.71 9675.48 36891.72 202
miper_ehance_all_eth78.59 24577.76 24481.08 27582.66 37961.56 32183.65 31889.15 23268.87 30475.55 28183.79 36566.49 14192.03 25573.25 21276.39 35389.64 287
Effi-MVS+83.62 11783.08 12185.24 9688.38 19067.45 16888.89 12989.15 23275.50 11982.27 14288.28 24569.61 9594.45 12977.81 15487.84 17693.84 93
c3_l78.75 23977.91 23581.26 26982.89 37461.56 32184.09 31089.13 23469.97 27175.56 28084.29 35166.36 14392.09 25473.47 20975.48 36890.12 263
LTVRE_ROB69.57 1376.25 30074.54 30981.41 26388.60 18164.38 25779.24 39489.12 23570.76 24769.79 37587.86 25849.09 36293.20 20256.21 39380.16 30386.65 385
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
fmvsm_s_conf0.5_n_987.39 3387.95 2385.70 8289.48 13967.88 15488.59 14689.05 23680.19 1290.70 2095.40 1574.56 2993.92 15391.54 292.07 9295.31 5
F-COLMAP76.38 29974.33 31382.50 24089.28 15166.95 18788.41 15389.03 23764.05 37566.83 41288.61 23546.78 37892.89 21957.48 37878.55 32187.67 346
FMVSNet278.20 25477.21 25881.20 27187.60 23362.89 29887.47 18889.02 23871.63 22175.29 29687.28 27254.80 28291.10 30362.38 32779.38 31589.61 288
ACMH67.68 1675.89 30573.93 31781.77 25588.71 17866.61 19088.62 14589.01 23969.81 27466.78 41386.70 29241.95 42191.51 28455.64 39478.14 33087.17 368
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
miper_enhance_ethall77.87 26576.86 26580.92 28081.65 39361.38 32582.68 33988.98 24065.52 35075.47 28282.30 39465.76 15592.00 25872.95 21576.39 35389.39 294
无先验87.48 18788.98 24060.00 41894.12 14267.28 27788.97 309
AdaColmapbinary80.58 19479.42 20084.06 16693.09 6368.91 11689.36 11088.97 24269.27 28875.70 27889.69 19957.20 26495.77 6563.06 31488.41 16287.50 354
EI-MVSNet80.52 19579.98 18382.12 24684.28 33163.19 29086.41 23588.95 24374.18 16578.69 20487.54 26866.62 13892.43 24072.57 22080.57 29990.74 236
MVSTER79.01 23377.88 23882.38 24283.07 36464.80 24584.08 31188.95 24369.01 30078.69 20487.17 27954.70 28692.43 24074.69 19580.57 29989.89 279
FE-MVSNET272.88 35471.28 35077.67 36078.30 43757.78 37884.43 29988.92 24569.56 28164.61 43581.67 40146.73 38088.54 36459.33 35867.99 42986.69 384
LuminaMVS80.68 18779.62 19683.83 18185.07 31668.01 14986.99 21088.83 24670.36 25981.38 15887.99 25650.11 34692.51 23779.02 13886.89 19690.97 226
131476.53 29075.30 29980.21 29883.93 34062.32 30884.66 28888.81 24760.23 41670.16 36784.07 36055.30 27990.73 32267.37 27683.21 26687.59 350
UniMVSNet_ETH3D79.10 23178.24 22981.70 25686.85 26760.24 34987.28 20288.79 24874.25 16376.84 25090.53 17849.48 35591.56 27767.98 27082.15 27893.29 125
xiu_mvs_v1_base_debu80.80 18279.72 19384.03 17187.35 24370.19 8985.56 26288.77 24969.06 29781.83 14888.16 24950.91 33592.85 22178.29 15087.56 18189.06 301
xiu_mvs_v1_base80.80 18279.72 19384.03 17187.35 24370.19 8985.56 26288.77 24969.06 29781.83 14888.16 24950.91 33592.85 22178.29 15087.56 18189.06 301
xiu_mvs_v1_base_debi80.80 18279.72 19384.03 17187.35 24370.19 8985.56 26288.77 24969.06 29781.83 14888.16 24950.91 33592.85 22178.29 15087.56 18189.06 301
FMVSNet377.88 26476.85 26680.97 27986.84 26862.36 30686.52 23288.77 24971.13 23475.34 29086.66 29454.07 29291.10 30362.72 31979.57 30989.45 292
usedtu_dtu_shiyan176.43 29575.32 29779.76 31383.00 36760.72 33881.74 35288.76 25368.99 30172.98 33384.19 35656.41 27290.27 32662.39 32579.40 31388.31 331
FE-MVSNET376.43 29575.32 29779.76 31383.00 36760.72 33881.74 35288.76 25368.99 30172.98 33384.19 35656.41 27290.27 32662.39 32579.40 31388.31 331
patch_mono-283.65 11484.54 8980.99 27790.06 12165.83 20784.21 30588.74 25571.60 22485.01 8092.44 10674.51 3083.50 41882.15 10192.15 9093.64 109
GeoE81.71 15781.01 16083.80 18489.51 13664.45 25588.97 12688.73 25671.27 23278.63 20789.76 19866.32 14493.20 20269.89 25286.02 21293.74 100
mamba_040879.37 22577.52 25184.93 11288.81 16967.96 15065.03 48088.66 25770.96 24279.48 19189.80 19558.69 24694.65 12170.35 24585.93 21592.18 185
SSM_0407277.67 27277.52 25178.12 35188.81 16967.96 15065.03 48088.66 25770.96 24279.48 19189.80 19558.69 24674.23 47470.35 24585.93 21592.18 185
CANet_DTU80.61 18979.87 18782.83 22485.60 29963.17 29187.36 19888.65 25976.37 9675.88 27588.44 24153.51 29893.07 21173.30 21189.74 13692.25 180
HyFIR lowres test77.53 27475.40 29383.94 17989.59 13266.62 18980.36 37988.64 26056.29 44976.45 26285.17 33357.64 25793.28 19261.34 34383.10 26891.91 194
WR-MVS79.49 21779.22 20880.27 29588.79 17458.35 36585.06 27988.61 26178.56 3577.65 23288.34 24363.81 17290.66 32364.98 29777.22 33991.80 197
BH-untuned79.47 21878.60 21982.05 24989.19 15665.91 20486.07 25088.52 26272.18 21275.42 28687.69 26261.15 22193.54 17560.38 34986.83 19786.70 383
IS-MVSNet83.15 13082.81 12784.18 15589.94 12463.30 28691.59 5188.46 26379.04 3079.49 19092.16 11665.10 15994.28 13267.71 27291.86 9894.95 12
pm-mvs177.25 28076.68 27378.93 33384.22 33358.62 36386.41 23588.36 26471.37 22873.31 32888.01 25561.22 22089.15 35164.24 30373.01 39989.03 305
UGNet80.83 17879.59 19784.54 12688.04 20568.09 14589.42 10688.16 26576.95 7176.22 26889.46 21049.30 35993.94 14968.48 26790.31 12391.60 203
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
VDD-MVS83.01 13582.36 13784.96 10991.02 9666.40 19288.91 12888.11 26677.57 4984.39 9793.29 8652.19 31093.91 15477.05 16588.70 15694.57 49
Effi-MVS+-dtu80.03 20878.57 22084.42 13685.13 31468.74 12288.77 13688.10 26774.99 13874.97 30683.49 37457.27 26293.36 19073.53 20780.88 29391.18 217
v14878.72 24177.80 24181.47 26182.73 37761.96 31586.30 24288.08 26873.26 19276.18 27085.47 32562.46 19392.36 24471.92 23073.82 39290.09 266
EG-PatchMatch MVS74.04 32871.82 34280.71 28484.92 31867.42 16985.86 25688.08 26866.04 34264.22 43883.85 36235.10 45692.56 23357.44 37980.83 29482.16 448
viewmambaseed2359dif80.41 19679.84 18882.12 24682.95 37362.50 30383.39 32588.06 27067.11 32580.98 16690.31 18266.20 14791.01 30874.62 19684.90 23092.86 154
SymmetryMVS85.38 7884.81 8687.07 5191.47 8872.47 3891.65 4788.06 27079.31 2484.39 9792.18 11464.64 16495.53 7280.70 11690.91 11593.21 130
cl2278.07 25877.01 26181.23 27082.37 38661.83 31783.55 32287.98 27268.96 30375.06 30383.87 36161.40 21591.88 26473.53 20776.39 35389.98 275
test_fmvsmvis_n_192084.02 10083.87 10284.49 13384.12 33569.37 10988.15 16787.96 27370.01 26983.95 10893.23 8768.80 11391.51 28488.61 3289.96 13192.57 163
pmmvs674.69 32073.39 32478.61 33881.38 40057.48 38386.64 22787.95 27464.99 36370.18 36586.61 29550.43 34289.52 34262.12 33270.18 41788.83 315
MVP-Stereo76.12 30174.46 31181.13 27485.37 30669.79 9684.42 30187.95 27465.03 36167.46 40385.33 32853.28 30191.73 27058.01 37583.27 26581.85 450
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
cl____77.72 26876.76 26980.58 28782.49 38360.48 34583.09 33487.87 27669.22 29174.38 31785.22 33262.10 20091.53 28271.09 23675.41 37289.73 286
DIV-MVS_self_test77.72 26876.76 26980.58 28782.48 38460.48 34583.09 33487.86 27769.22 29174.38 31785.24 33062.10 20091.53 28271.09 23675.40 37389.74 285
BH-w/o78.21 25377.33 25780.84 28188.81 16965.13 22984.87 28387.85 27869.75 27874.52 31484.74 34361.34 21693.11 20958.24 37385.84 21884.27 423
FE-MVS77.78 26675.68 28684.08 16288.09 20366.00 20183.13 33287.79 27968.42 31378.01 22485.23 33145.50 39695.12 9359.11 36285.83 21991.11 219
HY-MVS69.67 1277.95 26277.15 25980.36 29287.57 24260.21 35083.37 32787.78 28066.11 34075.37 28987.06 28363.27 17590.48 32561.38 34282.43 27690.40 251
guyue81.13 17280.64 16682.60 23886.52 27863.92 26686.69 22587.73 28173.97 16880.83 17289.69 19956.70 26891.33 29378.26 15385.40 22692.54 165
1112_ss77.40 27776.43 27780.32 29489.11 16260.41 34783.65 31887.72 28262.13 40273.05 33286.72 28862.58 19189.97 33462.11 33380.80 29590.59 243
mvs_anonymous79.42 22179.11 21080.34 29384.45 33057.97 37282.59 34087.62 28367.40 32476.17 27288.56 23868.47 11789.59 34170.65 24286.05 21193.47 118
ACMH+68.96 1476.01 30474.01 31582.03 25088.60 18165.31 22588.86 13087.55 28470.25 26567.75 39887.47 27041.27 42493.19 20458.37 37175.94 36187.60 348
tfpnnormal74.39 32273.16 32878.08 35286.10 28958.05 36984.65 29087.53 28570.32 26271.22 35785.63 32054.97 28089.86 33543.03 46075.02 38086.32 388
CHOSEN 1792x268877.63 27375.69 28583.44 19389.98 12368.58 13078.70 40487.50 28656.38 44875.80 27786.84 28458.67 24891.40 29061.58 34085.75 22090.34 253
ambc75.24 39073.16 47050.51 45663.05 48587.47 28764.28 43777.81 44017.80 48689.73 33957.88 37660.64 46085.49 405
Fast-Effi-MVS+-dtu78.02 26076.49 27582.62 23783.16 36366.96 18686.94 21387.45 28872.45 20671.49 35484.17 35854.79 28591.58 27467.61 27380.31 30289.30 297
usedtu_blend_shiyan573.29 34370.96 35780.25 29677.80 44262.16 31184.44 29887.38 28964.41 36868.09 39376.28 45151.32 32891.23 29663.21 31265.76 43987.35 358
D2MVS74.82 31973.21 32779.64 32079.81 42062.56 30280.34 38087.35 29064.37 37068.86 38382.66 38946.37 38390.10 33167.91 27181.24 28886.25 389
blended_shiyan873.38 33771.17 35380.02 30378.36 43561.51 32382.43 34287.28 29165.40 35468.61 38677.53 44351.91 32091.00 31163.28 31065.76 43987.53 352
fmvsm_s_conf0.5_n_284.04 9984.11 9983.81 18386.17 28665.00 23486.96 21187.28 29174.35 15888.25 4094.23 5061.82 20592.60 23089.85 1288.09 17093.84 93
TSAR-MVS + GP.85.71 6985.33 7886.84 5791.34 8972.50 3689.07 12487.28 29176.41 9185.80 7290.22 18774.15 3695.37 8681.82 10391.88 9592.65 162
blended_shiyan673.38 33771.17 35380.01 30478.36 43561.48 32482.43 34287.27 29465.40 35468.56 38877.55 44251.94 31991.01 30863.27 31165.76 43987.55 351
blend_shiyan472.29 36069.65 37280.21 29878.24 43862.16 31182.29 34587.27 29465.41 35368.43 39276.42 45039.91 43391.23 29663.21 31265.66 44487.22 365
fmvsm_l_conf0.5_n84.47 9084.54 8984.27 15085.42 30468.81 11788.49 15087.26 29668.08 31688.03 4593.49 7872.04 5891.77 26788.90 2989.14 14892.24 182
hse-mvs281.72 15680.94 16184.07 16388.72 17767.68 16185.87 25587.26 29676.02 10684.67 8888.22 24861.54 21093.48 18482.71 9673.44 39691.06 221
AUN-MVS79.21 22877.60 24984.05 16988.71 17867.61 16385.84 25787.26 29669.08 29677.23 24288.14 25353.20 30293.47 18575.50 18973.45 39591.06 221
wanda-best-256-51272.94 35170.66 36179.79 31177.80 44261.03 33281.31 36287.15 29965.18 35768.09 39376.28 45151.32 32890.97 31263.06 31465.76 43987.35 358
FE-blended-shiyan772.94 35170.66 36179.79 31177.80 44261.03 33281.31 36287.15 29965.18 35768.09 39376.28 45151.32 32890.97 31263.06 31465.76 43987.35 358
BH-RMVSNet79.61 21378.44 22383.14 20789.38 14565.93 20384.95 28287.15 29973.56 18178.19 21989.79 19756.67 26993.36 19059.53 35786.74 19890.13 262
Test_1112_low_res76.40 29875.44 29179.27 32789.28 15158.09 36881.69 35587.07 30259.53 42372.48 34186.67 29361.30 21789.33 34560.81 34780.15 30490.41 250
KD-MVS_self_test68.81 39667.59 39972.46 42174.29 46145.45 47177.93 41687.00 30363.12 38463.99 44178.99 43242.32 41684.77 40756.55 39164.09 44987.16 370
mvsmamba80.60 19179.38 20184.27 15089.74 13067.24 17987.47 18886.95 30470.02 26875.38 28888.93 22551.24 33292.56 23375.47 19089.22 14593.00 148
reproduce_monomvs75.40 31474.38 31278.46 34683.92 34157.80 37783.78 31486.94 30573.47 18572.25 34584.47 34538.74 44089.27 34775.32 19170.53 41588.31 331
LS3D76.95 28574.82 30483.37 19790.45 10867.36 17389.15 12086.94 30561.87 40569.52 37690.61 17551.71 32594.53 12446.38 44886.71 19988.21 336
miper_lstm_enhance74.11 32773.11 32977.13 37180.11 41559.62 35572.23 45186.92 30766.76 32970.40 36282.92 38456.93 26682.92 42269.06 26172.63 40188.87 313
fmvsm_l_conf0.5_n_a84.13 9784.16 9484.06 16685.38 30568.40 13488.34 15886.85 30867.48 32387.48 5693.40 8370.89 7491.61 27288.38 3789.22 14592.16 189
jason81.39 16880.29 17584.70 12386.63 27669.90 9585.95 25286.77 30963.24 38381.07 16589.47 20861.08 22392.15 25278.33 14990.07 13092.05 192
jason: jason.
gbinet_0.2-2-1-0.0273.24 34570.86 36080.39 29078.03 44061.62 32083.10 33386.69 31065.98 34469.29 38076.15 45449.77 35291.51 28462.75 31866.00 43788.03 339
viewdifsd2359ckpt1180.37 20079.73 19182.30 24483.70 34762.39 30484.20 30686.67 31173.22 19580.90 16890.62 17363.00 18591.56 27776.81 17178.44 32492.95 151
viewmsd2359difaftdt80.37 20079.73 19182.30 24483.70 34762.39 30484.20 30686.67 31173.22 19580.90 16890.62 17363.00 18591.56 27776.81 17178.44 32492.95 151
OurMVSNet-221017-074.26 32472.42 33779.80 31083.76 34559.59 35685.92 25486.64 31366.39 33866.96 41087.58 26439.46 43591.60 27365.76 29169.27 42088.22 335
VPNet78.69 24278.66 21878.76 33688.31 19255.72 41084.45 29786.63 31476.79 7678.26 21790.55 17759.30 24389.70 34066.63 28377.05 34190.88 229
fmvsm_s_conf0.1_n_283.80 10783.79 10683.83 18185.62 29864.94 23987.03 20886.62 31574.32 15987.97 4894.33 4360.67 22992.60 23089.72 1487.79 17793.96 84
USDC70.33 38168.37 38176.21 37780.60 40956.23 40379.19 39686.49 31660.89 41061.29 45185.47 32531.78 46389.47 34453.37 40776.21 35982.94 441
lupinMVS81.39 16880.27 17684.76 12187.35 24370.21 8785.55 26586.41 31762.85 39081.32 15988.61 23561.68 20792.24 25078.41 14890.26 12591.83 195
TR-MVS77.44 27576.18 28181.20 27188.24 19463.24 28784.61 29186.40 31867.55 32177.81 22986.48 30254.10 29193.15 20657.75 37782.72 27387.20 366
旧先验191.96 8165.79 21086.37 31993.08 9369.31 10092.74 8088.74 321
GA-MVS76.87 28675.17 30181.97 25282.75 37662.58 30081.44 36086.35 32072.16 21474.74 30982.89 38546.20 38792.02 25768.85 26481.09 29091.30 215
MonoMVSNet76.49 29475.80 28378.58 34081.55 39658.45 36486.36 24086.22 32174.87 14674.73 31083.73 36751.79 32488.73 35970.78 23872.15 40588.55 327
CDS-MVSNet79.07 23277.70 24683.17 20687.60 23368.23 14284.40 30286.20 32267.49 32276.36 26586.54 30061.54 21090.79 31861.86 33687.33 18690.49 247
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
MVS_111021_LR82.61 14182.11 14284.11 15688.82 16871.58 5885.15 27586.16 32374.69 14980.47 17891.04 16062.29 19690.55 32480.33 12090.08 12990.20 259
MSDG73.36 34170.99 35680.49 28984.51 32965.80 20980.71 37386.13 32465.70 34765.46 42883.74 36644.60 40090.91 31451.13 41976.89 34384.74 419
TransMVSNet (Re)75.39 31574.56 30877.86 35685.50 30357.10 38886.78 22186.09 32572.17 21371.53 35387.34 27163.01 18489.31 34656.84 38761.83 45687.17 368
VDDNet81.52 16580.67 16584.05 16990.44 10964.13 26189.73 9385.91 32671.11 23583.18 12793.48 7950.54 34193.49 18173.40 21088.25 16794.54 53
AstraMVS80.81 17980.14 18082.80 22786.05 29063.96 26386.46 23485.90 32773.71 17680.85 17190.56 17654.06 29391.57 27679.72 13183.97 24792.86 154
sd_testset77.70 27077.40 25478.60 33989.03 16360.02 35179.00 39985.83 32875.19 13376.61 25989.98 18954.81 28185.46 40062.63 32383.55 25890.33 254
Baseline_NR-MVSNet78.15 25678.33 22777.61 36385.79 29356.21 40486.78 22185.76 32973.60 18077.93 22687.57 26565.02 16088.99 35367.14 28075.33 37587.63 347
Anonymous2024052168.80 39767.22 40473.55 40974.33 46054.11 42683.18 33085.61 33058.15 43561.68 45080.94 40830.71 46681.27 43457.00 38573.34 39885.28 409
test_vis1_n_192075.52 31075.78 28474.75 39779.84 41957.44 38483.26 32985.52 33162.83 39179.34 19686.17 30945.10 39879.71 44078.75 14381.21 28987.10 374
新几何183.42 19493.13 6070.71 8185.48 33257.43 44381.80 15191.98 12163.28 17492.27 24864.60 30092.99 7687.27 364
EPNet83.72 11282.92 12686.14 7384.22 33369.48 10291.05 6485.27 33381.30 676.83 25191.65 13466.09 14995.56 6976.00 18193.85 6893.38 120
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
UnsupCasMVSNet_eth67.33 40865.99 41271.37 42773.48 46751.47 44975.16 43885.19 33465.20 35660.78 45380.93 41042.35 41577.20 45157.12 38253.69 47385.44 407
SD_040374.65 32174.77 30574.29 40186.20 28547.42 46583.71 31685.12 33569.30 28768.50 39087.95 25759.40 24286.05 39149.38 43083.35 26389.40 293
mmtdpeth74.16 32673.01 33077.60 36583.72 34661.13 32785.10 27785.10 33672.06 21577.21 24680.33 41543.84 40785.75 39477.14 16452.61 47585.91 399
IB-MVS68.01 1575.85 30673.36 32683.31 19884.76 32266.03 19883.38 32685.06 33770.21 26669.40 37781.05 40545.76 39294.66 12065.10 29675.49 36789.25 298
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
TAMVS78.89 23877.51 25383.03 21487.80 21767.79 15884.72 28685.05 33867.63 31976.75 25487.70 26162.25 19790.82 31758.53 36987.13 19190.49 247
CL-MVSNet_self_test72.37 35871.46 34675.09 39179.49 42653.53 43080.76 37185.01 33969.12 29570.51 36082.05 39857.92 25484.13 41152.27 41266.00 43787.60 348
testdata79.97 30590.90 9964.21 25984.71 34059.27 42585.40 7692.91 9562.02 20289.08 35268.95 26291.37 10686.63 386
MS-PatchMatch73.83 33172.67 33377.30 36983.87 34266.02 19981.82 35084.66 34161.37 40968.61 38682.82 38747.29 37188.21 36759.27 35984.32 24377.68 465
ET-MVSNet_ETH3D78.63 24376.63 27484.64 12486.73 27269.47 10385.01 28084.61 34269.54 28266.51 42086.59 29650.16 34591.75 26876.26 17684.24 24492.69 160
CNLPA78.08 25776.79 26881.97 25290.40 11071.07 7187.59 18584.55 34366.03 34372.38 34389.64 20257.56 25886.04 39259.61 35683.35 26388.79 317
MIMVSNet168.58 39966.78 40973.98 40680.07 41651.82 44580.77 37084.37 34464.40 36959.75 45982.16 39736.47 45283.63 41542.73 46170.33 41686.48 387
KD-MVS_2432*160066.22 41863.89 42173.21 41275.47 45853.42 43270.76 45884.35 34564.10 37366.52 41878.52 43434.55 45784.98 40450.40 42250.33 47881.23 453
miper_refine_blended66.22 41863.89 42173.21 41275.47 45853.42 43270.76 45884.35 34564.10 37366.52 41878.52 43434.55 45784.98 40450.40 42250.33 47881.23 453
test_040272.79 35570.44 36679.84 30988.13 20065.99 20285.93 25384.29 34765.57 34967.40 40685.49 32446.92 37592.61 22935.88 47574.38 38680.94 455
EU-MVSNet68.53 40167.61 39871.31 43078.51 43447.01 46884.47 29484.27 34842.27 47766.44 42184.79 34240.44 42983.76 41358.76 36768.54 42583.17 435
thisisatest053079.40 22277.76 24484.31 14487.69 23065.10 23287.36 19884.26 34970.04 26777.42 23688.26 24749.94 34994.79 11470.20 24784.70 23493.03 145
COLMAP_ROBcopyleft66.92 1773.01 34970.41 36780.81 28287.13 25665.63 21288.30 16184.19 35062.96 38863.80 44387.69 26238.04 44592.56 23346.66 44574.91 38184.24 424
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
tttt051779.40 22277.91 23583.90 18088.10 20263.84 26788.37 15784.05 35171.45 22776.78 25389.12 21749.93 35194.89 10770.18 24883.18 26792.96 150
CMPMVSbinary51.72 2170.19 38368.16 38476.28 37673.15 47157.55 38279.47 39183.92 35248.02 47056.48 46984.81 34143.13 41186.42 38862.67 32281.81 28484.89 417
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
Anonymous20240521178.25 25177.01 26181.99 25191.03 9560.67 34184.77 28583.90 35370.65 25280.00 18491.20 15441.08 42691.43 28965.21 29485.26 22793.85 91
XXY-MVS75.41 31375.56 28974.96 39283.59 35057.82 37680.59 37583.87 35466.54 33774.93 30788.31 24463.24 17780.09 43962.16 33176.85 34586.97 376
DP-MVS76.78 28774.57 30783.42 19493.29 5269.46 10588.55 14983.70 35563.98 37770.20 36488.89 22754.01 29494.80 11346.66 44581.88 28386.01 396
tfpn200view976.42 29775.37 29579.55 32389.13 15857.65 38085.17 27383.60 35673.41 18776.45 26286.39 30452.12 31191.95 26048.33 43683.75 25289.07 299
thres40076.50 29175.37 29579.86 30889.13 15857.65 38085.17 27383.60 35673.41 18776.45 26286.39 30452.12 31191.95 26048.33 43683.75 25290.00 272
SixPastTwentyTwo73.37 33971.26 35279.70 31785.08 31557.89 37485.57 26183.56 35871.03 24065.66 42685.88 31342.10 41992.57 23259.11 36263.34 45088.65 323
thres20075.55 30974.47 31078.82 33587.78 22057.85 37583.07 33683.51 35972.44 20875.84 27684.42 34652.08 31491.75 26847.41 44383.64 25786.86 378
IterMVS-SCA-FT75.43 31273.87 31980.11 30182.69 37864.85 24481.57 35783.47 36069.16 29470.49 36184.15 35951.95 31788.15 36869.23 25872.14 40687.34 361
CVMVSNet72.99 35072.58 33574.25 40284.28 33150.85 45486.41 23583.45 36144.56 47473.23 33087.54 26849.38 35785.70 39565.90 28978.44 32486.19 391
ITE_SJBPF78.22 34881.77 39260.57 34383.30 36269.25 29067.54 40087.20 27736.33 45387.28 38054.34 40174.62 38486.80 380
thisisatest051577.33 27875.38 29483.18 20585.27 30963.80 26882.11 34883.27 36365.06 36075.91 27483.84 36349.54 35494.27 13367.24 27886.19 20891.48 210
mvs5depth69.45 39267.45 40175.46 38773.93 46255.83 40879.19 39683.23 36466.89 32671.63 35283.32 37633.69 45985.09 40359.81 35455.34 47185.46 406
thres100view90076.50 29175.55 29079.33 32689.52 13556.99 38985.83 25883.23 36473.94 17076.32 26687.12 28051.89 32191.95 26048.33 43683.75 25289.07 299
thres600view776.50 29175.44 29179.68 31889.40 14357.16 38685.53 26783.23 36473.79 17476.26 26787.09 28151.89 32191.89 26348.05 44183.72 25590.00 272
test22291.50 8768.26 13884.16 30883.20 36754.63 45579.74 18691.63 13658.97 24591.42 10486.77 381
EPNet_dtu75.46 31174.86 30377.23 37082.57 38154.60 42286.89 21583.09 36871.64 22066.25 42285.86 31455.99 27488.04 37054.92 39886.55 20189.05 304
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
fmvsm_s_conf0.5_n83.80 10783.71 10884.07 16386.69 27467.31 17489.46 10383.07 36971.09 23686.96 6493.70 7569.02 11191.47 28788.79 3084.62 23593.44 119
fmvsm_s_conf0.1_n83.56 11883.38 11784.10 15784.86 31967.28 17689.40 10883.01 37070.67 24887.08 6193.96 6768.38 11891.45 28888.56 3484.50 23693.56 114
testing9176.54 28975.66 28879.18 33088.43 18855.89 40781.08 36583.00 37173.76 17575.34 29084.29 35146.20 38790.07 33264.33 30184.50 23691.58 205
TDRefinement67.49 40664.34 41876.92 37273.47 46861.07 33084.86 28482.98 37259.77 42058.30 46385.13 33426.06 47287.89 37247.92 44260.59 46181.81 451
OpenMVS_ROBcopyleft64.09 1970.56 37868.19 38377.65 36280.26 41259.41 35985.01 28082.96 37358.76 43165.43 42982.33 39337.63 44791.23 29645.34 45576.03 36082.32 445
fmvsm_s_conf0.5_n_a83.63 11683.41 11684.28 14886.14 28768.12 14489.43 10482.87 37470.27 26487.27 6093.80 7369.09 10691.58 27488.21 3883.65 25693.14 137
fmvsm_s_conf0.1_n_a83.32 12782.99 12484.28 14883.79 34368.07 14689.34 11182.85 37569.80 27587.36 5994.06 5968.34 12091.56 27787.95 4283.46 26293.21 130
RPSCF73.23 34671.46 34678.54 34282.50 38259.85 35282.18 34782.84 37658.96 42871.15 35889.41 21445.48 39784.77 40758.82 36671.83 40891.02 225
CostFormer75.24 31673.90 31879.27 32782.65 38058.27 36780.80 36882.73 37761.57 40675.33 29483.13 38055.52 27791.07 30664.98 29778.34 32988.45 328
IterMVS74.29 32372.94 33178.35 34781.53 39763.49 28181.58 35682.49 37868.06 31769.99 37083.69 36951.66 32685.54 39865.85 29071.64 40986.01 396
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
test_cas_vis1_n_192073.76 33273.74 32173.81 40875.90 45259.77 35380.51 37682.40 37958.30 43481.62 15685.69 31744.35 40476.41 45876.29 17578.61 32085.23 410
WTY-MVS75.65 30875.68 28675.57 38386.40 28156.82 39177.92 41782.40 37965.10 35976.18 27087.72 26063.13 18380.90 43660.31 35081.96 28189.00 308
0.4-1-1-0.270.01 38766.86 40779.44 32477.61 44560.64 34276.77 42682.34 38162.40 39865.91 42566.65 47540.05 43190.83 31661.77 33868.24 42786.86 378
0.3-1-1-0.01570.03 38666.80 40879.72 31678.18 43961.07 33077.63 41982.32 38262.65 39565.50 42767.29 47437.62 44890.91 31461.99 33468.04 42887.19 367
0.4-1-1-0.170.93 37267.94 39079.91 30679.35 42861.27 32678.95 40182.19 38363.36 38267.50 40169.40 47339.83 43491.04 30762.44 32468.40 42687.40 355
pmmvs474.03 33071.91 34180.39 29081.96 38968.32 13681.45 35982.14 38459.32 42469.87 37385.13 33452.40 30788.13 36960.21 35174.74 38384.73 420
FMVSNet569.50 39167.96 38874.15 40382.97 37255.35 41580.01 38682.12 38562.56 39663.02 44481.53 40236.92 44981.92 42948.42 43574.06 38885.17 413
baseline176.98 28476.75 27177.66 36188.13 20055.66 41185.12 27681.89 38673.04 19976.79 25288.90 22662.43 19487.78 37463.30 30971.18 41289.55 290
UnsupCasMVSNet_bld63.70 42861.53 43470.21 43673.69 46551.39 45072.82 44981.89 38655.63 45257.81 46571.80 46838.67 44178.61 44449.26 43252.21 47680.63 457
LFMVS81.82 15581.23 15583.57 19091.89 8363.43 28489.84 8781.85 38877.04 7083.21 12493.10 8952.26 30993.43 18871.98 22989.95 13293.85 91
sss73.60 33473.64 32273.51 41082.80 37555.01 41976.12 42981.69 38962.47 39774.68 31185.85 31557.32 26178.11 44760.86 34680.93 29187.39 356
SSC-MVS3.273.35 34273.39 32473.23 41185.30 30849.01 46174.58 44481.57 39075.21 13173.68 32485.58 32252.53 30382.05 42854.33 40277.69 33588.63 324
pmmvs-eth3d70.50 37967.83 39378.52 34477.37 44866.18 19681.82 35081.51 39158.90 42963.90 44280.42 41342.69 41486.28 38958.56 36865.30 44683.11 437
TinyColmap67.30 40964.81 41674.76 39681.92 39156.68 39580.29 38181.49 39260.33 41456.27 47183.22 37724.77 47687.66 37645.52 45369.47 41979.95 460
testing9976.09 30375.12 30279.00 33188.16 19755.50 41380.79 36981.40 39373.30 19175.17 29884.27 35444.48 40290.02 33364.28 30284.22 24591.48 210
tpmvs71.09 37069.29 37576.49 37582.04 38856.04 40578.92 40281.37 39464.05 37567.18 40878.28 43649.74 35389.77 33749.67 42972.37 40283.67 431
WBMVS73.43 33672.81 33275.28 38987.91 21150.99 45378.59 40781.31 39565.51 35274.47 31584.83 34046.39 38186.68 38458.41 37077.86 33188.17 337
usedtu_dtu_shiyan264.75 42561.63 43374.10 40470.64 47753.18 43782.10 34981.27 39656.22 45056.39 47074.67 46127.94 47083.56 41642.71 46262.73 45385.57 404
pmmvs571.55 36670.20 37075.61 38277.83 44156.39 39981.74 35280.89 39757.76 43967.46 40384.49 34449.26 36085.32 40257.08 38375.29 37685.11 414
ANet_high50.57 45046.10 45463.99 45548.67 50039.13 48870.99 45780.85 39861.39 40831.18 48957.70 48517.02 48773.65 47731.22 48115.89 49779.18 462
LCM-MVSNet54.25 44149.68 45167.97 44953.73 49745.28 47466.85 47380.78 39935.96 48639.45 48762.23 4808.70 49678.06 44848.24 43951.20 47780.57 458
PVSNet64.34 1872.08 36470.87 35975.69 38186.21 28456.44 39874.37 44580.73 40062.06 40370.17 36682.23 39642.86 41383.31 42054.77 39984.45 24087.32 362
baseline275.70 30773.83 32081.30 26783.26 35761.79 31882.57 34180.65 40166.81 32766.88 41183.42 37557.86 25592.19 25163.47 30679.57 30989.91 277
ppachtmachnet_test70.04 38567.34 40378.14 35079.80 42161.13 32779.19 39680.59 40259.16 42665.27 43079.29 42746.75 37987.29 37949.33 43166.72 43286.00 398
FE-MVSNET67.25 41065.33 41473.02 41675.86 45352.54 43980.26 38380.56 40363.80 38060.39 45479.70 42441.41 42384.66 40943.34 45962.62 45481.86 449
Gipumacopyleft45.18 45541.86 45855.16 46977.03 45051.52 44832.50 49380.52 40432.46 48927.12 49235.02 4939.52 49575.50 46622.31 48960.21 46238.45 492
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
Anonymous2023120668.60 39867.80 39471.02 43280.23 41450.75 45578.30 41280.47 40556.79 44666.11 42482.63 39046.35 38478.95 44343.62 45875.70 36383.36 434
LCM-MVSNet-Re77.05 28276.94 26477.36 36787.20 25351.60 44780.06 38480.46 40675.20 13267.69 39986.72 28862.48 19288.98 35463.44 30789.25 14391.51 207
tt032070.49 38068.03 38777.89 35584.78 32159.12 36083.55 32280.44 40758.13 43667.43 40580.41 41439.26 43787.54 37755.12 39663.18 45286.99 375
testing1175.14 31774.01 31578.53 34388.16 19756.38 40080.74 37280.42 40870.67 24872.69 33983.72 36843.61 40989.86 33562.29 32983.76 25189.36 295
tpm273.26 34471.46 34678.63 33783.34 35556.71 39480.65 37480.40 40956.63 44773.55 32682.02 39951.80 32391.24 29556.35 39278.42 32787.95 340
CR-MVSNet73.37 33971.27 35179.67 31981.32 40365.19 22775.92 43180.30 41059.92 41972.73 33781.19 40352.50 30586.69 38359.84 35377.71 33387.11 372
Patchmtry70.74 37569.16 37775.49 38680.72 40754.07 42774.94 44280.30 41058.34 43370.01 36881.19 40352.50 30586.54 38553.37 40771.09 41385.87 401
sc_t172.19 36269.51 37380.23 29784.81 32061.09 32984.68 28780.22 41260.70 41271.27 35583.58 37236.59 45189.24 34860.41 34863.31 45190.37 252
tpm cat170.57 37768.31 38277.35 36882.41 38557.95 37378.08 41380.22 41252.04 46168.54 38977.66 44152.00 31687.84 37351.77 41372.07 40786.25 389
MDTV_nov1_ep1369.97 37183.18 36153.48 43177.10 42580.18 41460.45 41369.33 37980.44 41248.89 36686.90 38251.60 41578.51 323
AllTest70.96 37168.09 38679.58 32185.15 31263.62 27184.58 29279.83 41562.31 39960.32 45686.73 28632.02 46188.96 35650.28 42471.57 41086.15 392
TestCases79.58 32185.15 31263.62 27179.83 41562.31 39960.32 45686.73 28632.02 46188.96 35650.28 42471.57 41086.15 392
test_fmvs1_n70.86 37470.24 36972.73 41972.51 47555.28 41681.27 36479.71 41751.49 46578.73 20384.87 33927.54 47177.02 45276.06 17979.97 30785.88 400
Vis-MVSNet (Re-imp)78.36 25078.45 22278.07 35388.64 18051.78 44686.70 22479.63 41874.14 16675.11 30190.83 16761.29 21889.75 33858.10 37491.60 10092.69 160
MIMVSNet70.69 37669.30 37474.88 39484.52 32856.35 40275.87 43379.42 41964.59 36567.76 39782.41 39141.10 42581.54 43146.64 44781.34 28686.75 382
myMVS_eth3d2873.62 33373.53 32373.90 40788.20 19547.41 46678.06 41479.37 42074.29 16273.98 32084.29 35144.67 39983.54 41751.47 41687.39 18590.74 236
dmvs_re71.14 36970.58 36372.80 41881.96 38959.68 35475.60 43579.34 42168.55 30969.27 38180.72 41149.42 35676.54 45552.56 41177.79 33282.19 447
SCA74.22 32572.33 33879.91 30684.05 33862.17 31079.96 38779.29 42266.30 33972.38 34380.13 41851.95 31788.60 36259.25 36077.67 33688.96 310
testing22274.04 32872.66 33478.19 34987.89 21255.36 41481.06 36679.20 42371.30 23174.65 31283.57 37339.11 43988.67 36151.43 41885.75 22090.53 245
tpmrst72.39 35672.13 34073.18 41580.54 41049.91 45879.91 38879.08 42463.11 38571.69 35179.95 42055.32 27882.77 42465.66 29273.89 39086.87 377
tt0320-xc70.11 38467.45 40178.07 35385.33 30759.51 35883.28 32878.96 42558.77 43067.10 40980.28 41636.73 45087.42 37856.83 38859.77 46387.29 363
test_fmvs170.93 37270.52 36472.16 42273.71 46455.05 41880.82 36778.77 42651.21 46678.58 20884.41 34731.20 46576.94 45375.88 18380.12 30684.47 422
PatchmatchNetpermissive73.12 34771.33 34978.49 34583.18 36160.85 33679.63 38978.57 42764.13 37271.73 35079.81 42351.20 33385.97 39357.40 38076.36 35888.66 322
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
testing3-275.12 31875.19 30074.91 39390.40 11045.09 47680.29 38178.42 42878.37 4076.54 26187.75 25944.36 40387.28 38057.04 38483.49 26092.37 174
MDA-MVSNet-bldmvs66.68 41363.66 42375.75 38079.28 42960.56 34473.92 44778.35 42964.43 36750.13 47979.87 42244.02 40683.67 41446.10 45056.86 46583.03 439
new-patchmatchnet61.73 43261.73 43261.70 45872.74 47324.50 50169.16 46578.03 43061.40 40756.72 46875.53 45938.42 44276.48 45745.95 45157.67 46484.13 426
our_test_369.14 39467.00 40575.57 38379.80 42158.80 36177.96 41577.81 43159.55 42262.90 44778.25 43747.43 37083.97 41251.71 41467.58 43183.93 429
test20.0367.45 40766.95 40668.94 44075.48 45744.84 47777.50 42077.67 43266.66 33163.01 44583.80 36447.02 37478.40 44542.53 46468.86 42483.58 432
WB-MVSnew71.96 36571.65 34472.89 41784.67 32751.88 44482.29 34577.57 43362.31 39973.67 32583.00 38253.49 29981.10 43545.75 45282.13 27985.70 402
test-LLR72.94 35172.43 33674.48 39881.35 40158.04 37078.38 40877.46 43466.66 33169.95 37179.00 43048.06 36879.24 44166.13 28584.83 23186.15 392
test-mter71.41 36770.39 36874.48 39881.35 40158.04 37078.38 40877.46 43460.32 41569.95 37179.00 43036.08 45479.24 44166.13 28584.83 23186.15 392
ECVR-MVScopyleft79.61 21379.26 20680.67 28590.08 11754.69 42187.89 17777.44 43674.88 14480.27 18092.79 10148.96 36592.45 23968.55 26692.50 8494.86 19
UBG73.08 34872.27 33975.51 38588.02 20651.29 45178.35 41177.38 43765.52 35073.87 32282.36 39245.55 39486.48 38755.02 39784.39 24288.75 319
tpm72.37 35871.71 34374.35 40082.19 38752.00 44179.22 39577.29 43864.56 36672.95 33583.68 37051.35 32783.26 42158.33 37275.80 36287.81 344
LF4IMVS64.02 42762.19 43069.50 43870.90 47653.29 43576.13 42877.18 43952.65 46058.59 46180.98 40723.55 47976.52 45653.06 40966.66 43378.68 463
test111179.43 22079.18 20980.15 30089.99 12253.31 43487.33 20077.05 44075.04 13780.23 18292.77 10348.97 36492.33 24768.87 26392.40 8694.81 22
K. test v371.19 36868.51 38079.21 32983.04 36657.78 37884.35 30376.91 44172.90 20262.99 44682.86 38639.27 43691.09 30561.65 33952.66 47488.75 319
UWE-MVS72.13 36371.49 34574.03 40586.66 27547.70 46381.40 36176.89 44263.60 38175.59 27984.22 35539.94 43285.62 39748.98 43386.13 21088.77 318
testgi66.67 41466.53 41067.08 45175.62 45641.69 48675.93 43076.50 44366.11 34065.20 43386.59 29635.72 45574.71 47143.71 45773.38 39784.84 418
test_fmvs268.35 40367.48 40070.98 43369.50 47951.95 44280.05 38576.38 44449.33 46874.65 31284.38 34823.30 48075.40 46974.51 19875.17 37985.60 403
test_vis1_n69.85 39069.21 37671.77 42472.66 47455.27 41781.48 35876.21 44552.03 46275.30 29583.20 37928.97 46876.22 46074.60 19778.41 32883.81 430
PatchMatch-RL72.38 35770.90 35876.80 37488.60 18167.38 17279.53 39076.17 44662.75 39369.36 37882.00 40045.51 39584.89 40653.62 40580.58 29878.12 464
JIA-IIPM66.32 41762.82 42976.82 37377.09 44961.72 31965.34 47875.38 44758.04 43864.51 43662.32 47942.05 42086.51 38651.45 41769.22 42182.21 446
ADS-MVSNet266.20 42063.33 42474.82 39579.92 41758.75 36267.55 47075.19 44853.37 45865.25 43175.86 45642.32 41680.53 43841.57 46568.91 42285.18 411
ETVMVS72.25 36171.05 35575.84 37987.77 22251.91 44379.39 39274.98 44969.26 28973.71 32382.95 38340.82 42886.14 39046.17 44984.43 24189.47 291
PatchT68.46 40267.85 39170.29 43580.70 40843.93 47972.47 45074.88 45060.15 41770.55 35976.57 44749.94 34981.59 43050.58 42074.83 38285.34 408
dp66.80 41265.43 41370.90 43479.74 42348.82 46275.12 44074.77 45159.61 42164.08 44077.23 44442.89 41280.72 43748.86 43466.58 43483.16 436
MDA-MVSNet_test_wron65.03 42262.92 42671.37 42775.93 45156.73 39269.09 46774.73 45257.28 44454.03 47477.89 43845.88 38974.39 47349.89 42861.55 45782.99 440
TESTMET0.1,169.89 38969.00 37872.55 42079.27 43056.85 39078.38 40874.71 45357.64 44068.09 39377.19 44537.75 44676.70 45463.92 30484.09 24684.10 427
YYNet165.03 42262.91 42771.38 42675.85 45456.60 39669.12 46674.66 45457.28 44454.12 47377.87 43945.85 39074.48 47249.95 42761.52 45883.05 438
test_fmvs363.36 42961.82 43167.98 44862.51 48846.96 46977.37 42274.03 45545.24 47367.50 40178.79 43312.16 49272.98 47872.77 21866.02 43683.99 428
PMMVS69.34 39368.67 37971.35 42975.67 45562.03 31375.17 43773.46 45650.00 46768.68 38479.05 42852.07 31578.13 44661.16 34482.77 27173.90 471
PVSNet_057.27 2061.67 43359.27 43668.85 44279.61 42457.44 38468.01 46873.44 45755.93 45158.54 46270.41 47144.58 40177.55 45047.01 44435.91 48671.55 474
Syy-MVS68.05 40467.85 39168.67 44484.68 32440.97 48778.62 40573.08 45866.65 33466.74 41479.46 42552.11 31382.30 42632.89 47876.38 35682.75 442
myMVS_eth3d67.02 41166.29 41169.21 43984.68 32442.58 48278.62 40573.08 45866.65 33466.74 41479.46 42531.53 46482.30 42639.43 47076.38 35682.75 442
test0.0.03 168.00 40567.69 39668.90 44177.55 44647.43 46475.70 43472.95 46066.66 33166.56 41682.29 39548.06 36875.87 46444.97 45674.51 38583.41 433
testing368.56 40067.67 39771.22 43187.33 24842.87 48183.06 33771.54 46170.36 25969.08 38284.38 34830.33 46785.69 39637.50 47375.45 37185.09 415
ADS-MVSNet64.36 42662.88 42868.78 44379.92 41747.17 46767.55 47071.18 46253.37 45865.25 43175.86 45642.32 41673.99 47541.57 46568.91 42285.18 411
Patchmatch-RL test70.24 38267.78 39577.61 36377.43 44759.57 35771.16 45570.33 46362.94 38968.65 38572.77 46650.62 33985.49 39969.58 25666.58 43487.77 345
gg-mvs-nofinetune69.95 38867.96 38875.94 37883.07 36454.51 42477.23 42370.29 46463.11 38570.32 36362.33 47843.62 40888.69 36053.88 40487.76 17984.62 421
door-mid69.98 465
GG-mvs-BLEND75.38 38881.59 39555.80 40979.32 39369.63 46667.19 40773.67 46443.24 41088.90 35850.41 42184.50 23681.45 452
FPMVS53.68 44451.64 44659.81 46165.08 48551.03 45269.48 46369.58 46741.46 47840.67 48572.32 46716.46 48870.00 48324.24 48865.42 44558.40 485
door69.44 468
Patchmatch-test64.82 42463.24 42569.57 43779.42 42749.82 45963.49 48469.05 46951.98 46359.95 45880.13 41850.91 33570.98 47940.66 46773.57 39387.90 342
CHOSEN 280x42066.51 41564.71 41771.90 42381.45 39863.52 28057.98 48768.95 47053.57 45762.59 44876.70 44646.22 38675.29 47055.25 39579.68 30876.88 467
MVStest156.63 43952.76 44568.25 44761.67 48953.25 43671.67 45368.90 47138.59 48250.59 47883.05 38125.08 47470.66 48036.76 47438.56 48580.83 456
EGC-MVSNET52.07 44847.05 45267.14 45083.51 35260.71 34080.50 37767.75 4720.07 5000.43 50175.85 45824.26 47781.54 43128.82 48262.25 45559.16 483
ttmdpeth59.91 43557.10 43968.34 44667.13 48346.65 47074.64 44367.41 47348.30 46962.52 44985.04 33820.40 48275.93 46342.55 46345.90 48482.44 444
EPMVS69.02 39568.16 38471.59 42579.61 42449.80 46077.40 42166.93 47462.82 39270.01 36879.05 42845.79 39177.86 44956.58 39075.26 37787.13 371
APD_test153.31 44549.93 45063.42 45765.68 48450.13 45771.59 45466.90 47534.43 48740.58 48671.56 4698.65 49776.27 45934.64 47755.36 47063.86 481
lessismore_v078.97 33281.01 40657.15 38765.99 47661.16 45282.82 38739.12 43891.34 29259.67 35546.92 48188.43 329
dmvs_testset62.63 43064.11 42058.19 46278.55 43324.76 50075.28 43665.94 47767.91 31860.34 45576.01 45553.56 29773.94 47631.79 47967.65 43075.88 469
pmmvs357.79 43754.26 44268.37 44564.02 48756.72 39375.12 44065.17 47840.20 47952.93 47569.86 47220.36 48375.48 46745.45 45455.25 47272.90 473
MVS-HIRNet59.14 43657.67 43863.57 45681.65 39343.50 48071.73 45265.06 47939.59 48151.43 47657.73 48438.34 44382.58 42539.53 46873.95 38964.62 480
PM-MVS66.41 41664.14 41973.20 41473.92 46356.45 39778.97 40064.96 48063.88 37964.72 43480.24 41719.84 48483.44 41966.24 28464.52 44879.71 461
UWE-MVS-2865.32 42164.93 41566.49 45278.70 43238.55 48977.86 41864.39 48162.00 40464.13 43983.60 37141.44 42276.00 46231.39 48080.89 29284.92 416
PMVScopyleft37.38 2244.16 45640.28 46055.82 46740.82 50242.54 48465.12 47963.99 48234.43 48724.48 49357.12 4863.92 50276.17 46117.10 49355.52 46948.75 488
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
test250677.30 27976.49 27579.74 31590.08 11752.02 44087.86 17963.10 48374.88 14480.16 18392.79 10138.29 44492.35 24568.74 26592.50 8494.86 19
test_method31.52 46029.28 46438.23 47627.03 5046.50 50720.94 49562.21 4844.05 49822.35 49652.50 48913.33 48947.58 49627.04 48534.04 48860.62 482
WB-MVS54.94 44054.72 44155.60 46873.50 46620.90 50274.27 44661.19 48559.16 42650.61 47774.15 46247.19 37375.78 46517.31 49235.07 48770.12 475
test_vis1_rt60.28 43458.42 43765.84 45367.25 48255.60 41270.44 46060.94 48644.33 47559.00 46066.64 47624.91 47568.67 48462.80 31769.48 41873.25 472
SSC-MVS53.88 44353.59 44354.75 47072.87 47219.59 50373.84 44860.53 48757.58 44249.18 48173.45 46546.34 38575.47 46816.20 49532.28 48969.20 476
testf145.72 45241.96 45657.00 46356.90 49145.32 47266.14 47559.26 48826.19 49130.89 49060.96 4824.14 50070.64 48126.39 48646.73 48255.04 486
APD_test245.72 45241.96 45657.00 46356.90 49145.32 47266.14 47559.26 48826.19 49130.89 49060.96 4824.14 50070.64 48126.39 48646.73 48255.04 486
test_f52.09 44750.82 44855.90 46653.82 49642.31 48559.42 48658.31 49036.45 48556.12 47270.96 47012.18 49157.79 49253.51 40656.57 46767.60 477
new_pmnet50.91 44950.29 44952.78 47168.58 48034.94 49363.71 48256.63 49139.73 48044.95 48265.47 47721.93 48158.48 49134.98 47656.62 46664.92 479
DSMNet-mixed57.77 43856.90 44060.38 46067.70 48135.61 49169.18 46453.97 49232.30 49057.49 46679.88 42140.39 43068.57 48538.78 47172.37 40276.97 466
PMMVS240.82 45738.86 46146.69 47353.84 49516.45 50448.61 49049.92 49337.49 48331.67 48860.97 4818.14 49856.42 49328.42 48330.72 49067.19 478
mvsany_test162.30 43161.26 43565.41 45469.52 47854.86 42066.86 47249.78 49446.65 47168.50 39083.21 37849.15 36166.28 48656.93 38660.77 45975.11 470
test_vis3_rt49.26 45147.02 45356.00 46554.30 49445.27 47566.76 47448.08 49536.83 48444.38 48353.20 4887.17 49964.07 48856.77 38955.66 46858.65 484
E-PMN31.77 45930.64 46235.15 47852.87 49827.67 49557.09 48847.86 49624.64 49316.40 49833.05 49411.23 49354.90 49414.46 49618.15 49522.87 494
EMVS30.81 46129.65 46334.27 47950.96 49925.95 49956.58 48946.80 49724.01 49415.53 49930.68 49512.47 49054.43 49512.81 49717.05 49622.43 495
mvsany_test353.99 44251.45 44761.61 45955.51 49344.74 47863.52 48345.41 49843.69 47658.11 46476.45 44817.99 48563.76 48954.77 39947.59 48076.34 468
MVEpermissive26.22 2330.37 46225.89 46643.81 47544.55 50135.46 49228.87 49439.07 49918.20 49518.58 49740.18 4922.68 50347.37 49717.07 49423.78 49448.60 489
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
dongtai45.42 45445.38 45545.55 47473.36 46926.85 49867.72 46934.19 50054.15 45649.65 48056.41 48725.43 47362.94 49019.45 49028.09 49146.86 490
kuosan39.70 45840.40 45937.58 47764.52 48626.98 49665.62 47733.02 50146.12 47242.79 48448.99 49024.10 47846.56 49812.16 49826.30 49239.20 491
MTMP92.18 3932.83 502
tmp_tt18.61 46421.40 46710.23 4824.82 50510.11 50534.70 49230.74 5031.48 49923.91 49526.07 49628.42 46913.41 50127.12 48415.35 4987.17 496
DeepMVS_CXcopyleft27.40 48040.17 50326.90 49724.59 50417.44 49623.95 49448.61 4919.77 49426.48 49918.06 49124.47 49328.83 493
N_pmnet52.79 44653.26 44451.40 47278.99 4317.68 50669.52 4623.89 50551.63 46457.01 46774.98 46040.83 42765.96 48737.78 47264.67 44780.56 459
wuyk23d16.82 46515.94 46819.46 48158.74 49031.45 49439.22 4913.74 5066.84 4976.04 5002.70 5001.27 50424.29 50010.54 49914.40 4992.63 497
testmvs6.04 4688.02 4710.10 4840.08 5060.03 50969.74 4610.04 5070.05 5010.31 5021.68 5010.02 5060.04 5020.24 5000.02 5000.25 499
test1236.12 4678.11 4700.14 4830.06 5070.09 50871.05 4560.03 5080.04 5020.25 5031.30 5020.05 5050.03 5030.21 5010.01 5010.29 498
mmdepth0.00 4700.00 4730.00 4850.00 5080.00 5100.00 4960.00 5090.00 5030.00 5040.00 5030.00 5070.00 5040.00 5020.00 5020.00 500
monomultidepth0.00 4700.00 4730.00 4850.00 5080.00 5100.00 4960.00 5090.00 5030.00 5040.00 5030.00 5070.00 5040.00 5020.00 5020.00 500
test_blank0.00 4700.00 4730.00 4850.00 5080.00 5100.00 4960.00 5090.00 5030.00 5040.00 5030.00 5070.00 5040.00 5020.00 5020.00 500
uanet_test0.00 4700.00 4730.00 4850.00 5080.00 5100.00 4960.00 5090.00 5030.00 5040.00 5030.00 5070.00 5040.00 5020.00 5020.00 500
DCPMVS0.00 4700.00 4730.00 4850.00 5080.00 5100.00 4960.00 5090.00 5030.00 5040.00 5030.00 5070.00 5040.00 5020.00 5020.00 500
pcd_1.5k_mvsjas5.26 4697.02 4720.00 4850.00 5080.00 5100.00 4960.00 5090.00 5030.00 5040.00 50363.15 1800.00 5040.00 5020.00 5020.00 500
sosnet-low-res0.00 4700.00 4730.00 4850.00 5080.00 5100.00 4960.00 5090.00 5030.00 5040.00 5030.00 5070.00 5040.00 5020.00 5020.00 500
sosnet0.00 4700.00 4730.00 4850.00 5080.00 5100.00 4960.00 5090.00 5030.00 5040.00 5030.00 5070.00 5040.00 5020.00 5020.00 500
uncertanet0.00 4700.00 4730.00 4850.00 5080.00 5100.00 4960.00 5090.00 5030.00 5040.00 5030.00 5070.00 5040.00 5020.00 5020.00 500
Regformer0.00 4700.00 4730.00 4850.00 5080.00 5100.00 4960.00 5090.00 5030.00 5040.00 5030.00 5070.00 5040.00 5020.00 5020.00 500
n20.00 509
nn0.00 509
ab-mvs-re7.23 4669.64 4690.00 4850.00 5080.00 5100.00 4960.00 5090.00 5030.00 50486.72 2880.00 5070.00 5040.00 5020.00 5020.00 500
uanet0.00 4700.00 4730.00 4850.00 5080.00 5100.00 4960.00 5090.00 5030.00 5040.00 5030.00 5070.00 5040.00 5020.00 5020.00 500
WAC-MVS42.58 48239.46 469
PC_three_145268.21 31592.02 1594.00 6382.09 595.98 6284.58 7196.68 294.95 12
eth-test20.00 508
eth-test0.00 508
OPU-MVS89.06 394.62 1575.42 493.57 894.02 6182.45 396.87 2483.77 8296.48 894.88 16
test_0728_THIRD78.38 3892.12 1295.78 481.46 997.40 989.42 1996.57 794.67 38
GSMVS88.96 310
test_part295.06 872.65 3291.80 16
sam_mvs151.32 32888.96 310
sam_mvs50.01 347
test_post178.90 4035.43 49948.81 36785.44 40159.25 360
test_post5.46 49850.36 34384.24 410
patchmatchnet-post74.00 46351.12 33488.60 362
gm-plane-assit81.40 39953.83 42962.72 39480.94 40892.39 24263.40 308
test9_res84.90 6495.70 3092.87 153
agg_prior282.91 9195.45 3392.70 158
test_prior472.60 3489.01 125
test_prior288.85 13275.41 12284.91 8393.54 7674.28 3483.31 8595.86 24
旧先验286.56 23058.10 43787.04 6288.98 35474.07 203
新几何286.29 244
原ACMM286.86 217
testdata291.01 30862.37 328
segment_acmp73.08 44
testdata184.14 30975.71 113
plane_prior790.08 11768.51 132
plane_prior689.84 12668.70 12660.42 235
plane_prior491.00 163
plane_prior368.60 12978.44 3678.92 201
plane_prior291.25 6079.12 28
plane_prior189.90 125
plane_prior68.71 12490.38 7877.62 4786.16 209
HQP5-MVS66.98 184
HQP-NCC89.33 14689.17 11676.41 9177.23 242
ACMP_Plane89.33 14689.17 11676.41 9177.23 242
BP-MVS77.47 159
HQP4-MVS77.24 24195.11 9591.03 223
HQP2-MVS60.17 238
NP-MVS89.62 13168.32 13690.24 185
MDTV_nov1_ep13_2view37.79 49075.16 43855.10 45366.53 41749.34 35853.98 40387.94 341
ACMMP++_ref81.95 282
ACMMP++81.25 287
Test By Simon64.33 166