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 bysorted bysort bysort bysort bysort bysort bysort bysort bysort bysort by
DVP-MVS++90.23 191.01 187.89 2494.34 3171.25 6495.06 194.23 778.38 3892.78 495.74 682.45 397.49 489.42 1996.68 294.95 12
FOURS195.00 1072.39 4195.06 193.84 2074.49 14891.30 18
CP-MVS87.11 3886.92 4387.68 3794.20 3873.86 793.98 392.82 6876.62 8383.68 11294.46 3667.93 11995.95 6284.20 7894.39 6193.23 121
APDe-MVScopyleft89.15 989.63 887.73 3194.49 2271.69 5493.83 493.96 1875.70 10991.06 1996.03 176.84 1797.03 2189.09 2195.65 3194.47 52
Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition
SteuartSystems-ACMMP88.72 1488.86 1488.32 992.14 7872.96 2593.73 593.67 2580.19 1288.10 4294.80 2773.76 3797.11 1887.51 4695.82 2594.90 15
Skip Steuart: Steuart Systems R&D Blog.
lecture88.09 1788.59 1686.58 6293.26 5669.77 9693.70 694.16 977.13 6689.76 2695.52 1472.26 5396.27 4886.87 5094.65 5293.70 96
test072695.27 571.25 6493.60 794.11 1177.33 5892.81 395.79 380.98 11
SED-MVS90.08 290.85 287.77 2895.30 270.98 7193.57 894.06 1577.24 6193.10 195.72 882.99 197.44 789.07 2596.63 494.88 16
OPU-MVS89.06 394.62 1575.42 493.57 894.02 6182.45 396.87 2483.77 8296.48 894.88 16
DVP-MVScopyleft89.60 390.35 387.33 4595.27 571.25 6493.49 1092.73 6977.33 5892.12 1295.78 480.98 1197.40 989.08 2296.41 1293.33 118
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
test_0728_SECOND87.71 3595.34 171.43 6093.49 1094.23 797.49 489.08 2296.41 1294.21 65
MED-MVS test87.86 2694.57 1771.43 6093.28 1294.36 375.24 12192.25 995.03 2097.39 1188.15 3995.96 1994.75 29
MED-MVS89.59 490.16 487.86 2694.57 1771.43 6093.28 1294.36 376.30 9392.25 995.03 2081.59 797.39 1188.15 3995.96 1994.75 29
TestfortrainingZip a89.27 789.82 787.60 3994.57 1770.90 7793.28 1294.36 375.24 12192.25 995.03 2081.59 797.39 1186.12 5795.96 1994.52 49
TestfortrainingZip93.28 12
3Dnovator+77.84 485.48 7384.47 9288.51 791.08 9373.49 1693.18 1693.78 2380.79 876.66 24993.37 8360.40 23196.75 3077.20 15793.73 7095.29 6
HFP-MVS87.58 2687.47 3187.94 1994.58 1673.54 1593.04 1793.24 3876.78 7784.91 8294.44 3970.78 7596.61 3684.53 7294.89 4693.66 97
ACMMPR87.44 2987.23 3688.08 1594.64 1373.59 1293.04 1793.20 3976.78 7784.66 8994.52 3268.81 10696.65 3484.53 7294.90 4594.00 77
ZNCC-MVS87.94 2287.85 2488.20 1294.39 2873.33 1993.03 1993.81 2276.81 7585.24 7794.32 4471.76 6096.93 2385.53 6195.79 2694.32 61
region2R87.42 3187.20 3788.09 1494.63 1473.55 1393.03 1993.12 4576.73 8084.45 9494.52 3269.09 10096.70 3184.37 7494.83 4994.03 75
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 33
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
CS-MVS86.69 4486.95 4285.90 7890.76 10367.57 16492.83 2293.30 3779.67 1984.57 9392.27 10771.47 6595.02 10084.24 7793.46 7395.13 9
XVS87.18 3786.91 4488.00 1794.42 2473.33 1992.78 2392.99 5479.14 2683.67 11394.17 5367.45 12496.60 3783.06 8794.50 5794.07 73
X-MVStestdata80.37 19477.83 23488.00 1794.42 2473.33 1992.78 2392.99 5479.14 2683.67 11312.47 47967.45 12496.60 3783.06 8794.50 5794.07 73
mPP-MVS86.67 4686.32 5387.72 3394.41 2673.55 1392.74 2592.22 9576.87 7482.81 13194.25 4966.44 13796.24 4982.88 9294.28 6493.38 114
ACMMPcopyleft85.89 6585.39 7687.38 4493.59 4972.63 3392.74 2593.18 4476.78 7780.73 16793.82 7264.33 16196.29 4682.67 9990.69 11693.23 121
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
MP-MVScopyleft87.71 2387.64 2687.93 2194.36 3073.88 692.71 2792.65 7577.57 4983.84 10994.40 4172.24 5496.28 4785.65 5995.30 3993.62 104
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
MM89.16 889.23 1088.97 490.79 10273.65 1092.66 2891.17 14486.57 187.39 5794.97 2571.70 6297.68 192.19 195.63 3295.57 1
SF-MVS88.46 1588.74 1587.64 3892.78 7071.95 5192.40 2994.74 275.71 10789.16 2995.10 1875.65 2496.19 5187.07 4996.01 1794.79 23
SMA-MVScopyleft89.08 1089.23 1088.61 694.25 3573.73 992.40 2993.63 2674.77 14292.29 795.97 274.28 3397.24 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
GST-MVS87.42 3187.26 3487.89 2494.12 4072.97 2492.39 3193.43 3376.89 7384.68 8693.99 6570.67 7796.82 2684.18 7995.01 4193.90 83
HPM-MVS++copyleft89.02 1189.15 1288.63 595.01 976.03 192.38 3292.85 6480.26 1187.78 4894.27 4775.89 2296.81 2787.45 4796.44 993.05 137
SR-MVS86.73 4386.67 4886.91 5594.11 4172.11 4992.37 3392.56 8074.50 14786.84 6494.65 3167.31 12695.77 6484.80 6892.85 7892.84 149
SPE-MVS-test86.29 5486.48 5185.71 8091.02 9567.21 18092.36 3493.78 2378.97 3383.51 11691.20 14870.65 7895.15 9181.96 10294.89 4694.77 25
EC-MVSNet86.01 5886.38 5284.91 11289.31 14766.27 19492.32 3593.63 2679.37 2384.17 10291.88 11869.04 10495.43 7783.93 8193.77 6993.01 140
EPP-MVSNet83.40 11783.02 11784.57 12390.13 11464.47 24892.32 3590.73 15974.45 15079.35 18891.10 15169.05 10395.12 9272.78 21287.22 18194.13 69
PHI-MVS86.43 4986.17 5987.24 4690.88 9970.96 7392.27 3794.07 1472.45 19985.22 7891.90 11769.47 9496.42 4483.28 8695.94 2394.35 58
HPM-MVScopyleft87.11 3886.98 4187.50 4393.88 4372.16 4792.19 3893.33 3676.07 9983.81 11093.95 6869.77 9196.01 5885.15 6294.66 5194.32 61
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
MTMP92.18 3932.83 484
HPM-MVS_fast85.35 7984.95 8586.57 6393.69 4670.58 8492.15 4091.62 12973.89 16582.67 13394.09 5762.60 18395.54 7080.93 11192.93 7793.57 107
CPTT-MVS83.73 10583.33 11384.92 11193.28 5370.86 7892.09 4190.38 16968.75 29779.57 18292.83 9760.60 22793.04 20880.92 11291.56 10290.86 223
APD-MVS_3200maxsize85.97 6185.88 6586.22 6792.69 7269.53 9991.93 4292.99 5473.54 17585.94 6994.51 3565.80 14995.61 6783.04 8992.51 8393.53 111
SR-MVS-dyc-post85.77 6785.61 7286.23 6693.06 6470.63 8291.88 4392.27 8973.53 17685.69 7394.45 3765.00 15795.56 6882.75 9491.87 9592.50 161
RE-MVS-def85.48 7593.06 6470.63 8291.88 4392.27 8973.53 17685.69 7394.45 3763.87 16582.75 9491.87 9592.50 161
APD-MVScopyleft87.44 2987.52 3087.19 4794.24 3672.39 4191.86 4592.83 6573.01 19388.58 3494.52 3273.36 3896.49 4284.26 7595.01 4192.70 151
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
SD-MVS88.06 1888.50 1886.71 6092.60 7572.71 2991.81 4693.19 4077.87 4290.32 2394.00 6374.83 2693.78 15887.63 4594.27 6593.65 101
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
NormalMVS86.29 5485.88 6587.52 4193.26 5672.47 3891.65 4792.19 10079.31 2484.39 9692.18 10964.64 15995.53 7180.70 11694.65 5294.56 46
SymmetryMVS85.38 7884.81 8687.07 5091.47 8772.47 3891.65 4788.06 26279.31 2484.39 9692.18 10964.64 15995.53 7180.70 11690.91 11393.21 124
ME-MVS88.98 1289.39 987.75 3094.54 2071.43 6091.61 4994.25 676.30 9390.62 2195.03 2078.06 1697.07 2088.15 3995.96 1994.75 29
reproduce_model87.28 3587.39 3386.95 5493.10 6271.24 6891.60 5093.19 4074.69 14388.80 3395.61 1170.29 8196.44 4386.20 5693.08 7593.16 128
DPE-MVScopyleft89.48 689.98 588.01 1694.80 1172.69 3191.59 5194.10 1375.90 10292.29 795.66 1081.67 697.38 1487.44 4896.34 1593.95 80
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
QAPM80.88 17079.50 19385.03 10488.01 20668.97 11491.59 5192.00 10866.63 32875.15 29392.16 11157.70 25095.45 7563.52 30088.76 15290.66 232
IS-MVSNet83.15 12482.81 12184.18 14889.94 12363.30 28091.59 5188.46 25579.04 3079.49 18392.16 11165.10 15494.28 13067.71 26791.86 9794.95 12
reproduce-ours87.47 2787.61 2787.07 5093.27 5471.60 5591.56 5493.19 4074.98 13388.96 3095.54 1271.20 7096.54 4086.28 5493.49 7193.06 135
our_new_method87.47 2787.61 2787.07 5093.27 5471.60 5591.56 5493.19 4074.98 13388.96 3095.54 1271.20 7096.54 4086.28 5493.49 7193.06 135
9.1488.26 1992.84 6991.52 5694.75 173.93 16488.57 3594.67 3075.57 2595.79 6386.77 5195.76 27
MGCNet87.69 2487.55 2988.12 1389.45 13871.76 5391.47 5789.54 20182.14 386.65 6694.28 4668.28 11597.46 690.81 695.31 3895.15 8
TSAR-MVS + MP.88.02 2188.11 2087.72 3393.68 4772.13 4891.41 5892.35 8774.62 14688.90 3293.85 7175.75 2396.00 5987.80 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
DeepC-MVS_fast79.65 386.91 4186.62 5087.76 2993.52 5072.37 4391.26 5993.04 4676.62 8384.22 10093.36 8471.44 6696.76 2980.82 11395.33 3794.16 67
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
HQP_MVS83.64 10983.14 11485.14 9890.08 11668.71 12391.25 6092.44 8279.12 2878.92 19491.00 15860.42 22995.38 8278.71 13986.32 19791.33 206
plane_prior291.25 6079.12 28
NCCC88.06 1888.01 2288.24 1194.41 2673.62 1191.22 6292.83 6581.50 585.79 7293.47 8073.02 4597.00 2284.90 6494.94 4494.10 71
API-MVS81.99 14581.23 14984.26 14590.94 9770.18 9191.10 6389.32 21371.51 21978.66 19988.28 23965.26 15295.10 9764.74 29491.23 10787.51 341
EPNet83.72 10682.92 12086.14 7284.22 32769.48 10191.05 6485.27 31881.30 676.83 24491.65 12866.09 14495.56 6876.00 17693.85 6893.38 114
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
ACMMP_NAP88.05 2088.08 2187.94 1993.70 4573.05 2290.86 6593.59 2876.27 9588.14 4195.09 1971.06 7296.67 3387.67 4496.37 1494.09 72
CSCG86.41 5186.19 5887.07 5092.91 6772.48 3790.81 6693.56 2973.95 16283.16 12291.07 15375.94 2195.19 8979.94 12494.38 6293.55 109
MSLP-MVS++85.43 7585.76 6984.45 12891.93 8170.24 8590.71 6792.86 6377.46 5584.22 10092.81 9967.16 12892.94 21080.36 11994.35 6390.16 253
3Dnovator76.31 583.38 11882.31 13286.59 6187.94 20872.94 2890.64 6892.14 10577.21 6375.47 27592.83 9758.56 24394.72 11573.24 20892.71 8192.13 183
OpenMVScopyleft72.83 1079.77 20578.33 22184.09 15485.17 30469.91 9390.57 6990.97 15066.70 32272.17 33891.91 11654.70 27893.96 14461.81 32190.95 11288.41 323
balanced_conf0386.78 4286.99 4086.15 7091.24 9067.61 16290.51 7092.90 6177.26 6087.44 5691.63 13071.27 6996.06 5485.62 6095.01 4194.78 24
CNVR-MVS88.93 1389.13 1388.33 894.77 1273.82 890.51 7093.00 5180.90 788.06 4394.06 5976.43 1996.84 2588.48 3695.99 1894.34 59
MVSFormer82.85 13182.05 13985.24 9587.35 23670.21 8690.50 7290.38 16968.55 30181.32 15389.47 20261.68 20193.46 17978.98 13690.26 12392.05 185
test_djsdf80.30 19779.32 19883.27 19383.98 33365.37 21990.50 7290.38 16968.55 30176.19 26288.70 22556.44 26593.46 17978.98 13680.14 29890.97 219
save fliter93.80 4472.35 4490.47 7491.17 14474.31 153
nrg03083.88 9983.53 10884.96 10786.77 26469.28 10990.46 7592.67 7274.79 14182.95 12591.33 14372.70 5093.09 20380.79 11579.28 30892.50 161
sasdasda85.91 6385.87 6786.04 7489.84 12569.44 10590.45 7693.00 5176.70 8188.01 4591.23 14473.28 4093.91 15281.50 10588.80 15094.77 25
canonicalmvs85.91 6385.87 6786.04 7489.84 12569.44 10590.45 7693.00 5176.70 8188.01 4591.23 14473.28 4093.91 15281.50 10588.80 15094.77 25
plane_prior68.71 12390.38 7877.62 4786.16 202
DeepC-MVS79.81 287.08 4086.88 4587.69 3691.16 9172.32 4590.31 7993.94 1977.12 6782.82 13094.23 5072.13 5697.09 1984.83 6795.37 3593.65 101
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
Vis-MVSNetpermissive83.46 11582.80 12285.43 9090.25 11268.74 12190.30 8090.13 18176.33 9280.87 16492.89 9561.00 21894.20 13672.45 22190.97 11193.35 117
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
PGM-MVS86.68 4586.27 5587.90 2294.22 3773.38 1890.22 8193.04 4675.53 11283.86 10894.42 4067.87 12196.64 3582.70 9894.57 5693.66 97
LPG-MVS_test82.08 14281.27 14884.50 12589.23 15268.76 11990.22 8191.94 11275.37 11876.64 25091.51 13654.29 28194.91 10278.44 14183.78 24289.83 274
Anonymous2023121178.97 22977.69 24282.81 21990.54 10664.29 25290.11 8391.51 13465.01 34876.16 26688.13 24850.56 32793.03 20969.68 25077.56 32991.11 212
ACMM73.20 880.78 18079.84 18283.58 18289.31 14768.37 13489.99 8491.60 13170.28 25677.25 23389.66 19553.37 29293.53 17374.24 19782.85 26388.85 307
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ACMP74.13 681.51 16180.57 16184.36 13389.42 13968.69 12689.97 8591.50 13774.46 14975.04 29790.41 17353.82 28794.54 12177.56 15382.91 26289.86 273
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
fmvsm_s_conf0.5_n_1186.06 5686.75 4784.00 16787.78 21866.09 19689.96 8690.80 15777.37 5786.72 6594.20 5272.51 5192.78 21989.08 2292.33 8793.13 132
LFMVS81.82 14981.23 14983.57 18391.89 8263.43 27889.84 8781.85 37177.04 7083.21 11893.10 8852.26 30193.43 18171.98 22489.95 13093.85 85
MCST-MVS87.37 3487.25 3587.73 3194.53 2172.46 4089.82 8893.82 2173.07 19184.86 8592.89 9576.22 2096.33 4584.89 6695.13 4094.40 55
MAR-MVS81.84 14880.70 15885.27 9491.32 8971.53 5889.82 8890.92 15169.77 27078.50 20386.21 30162.36 18994.52 12365.36 28892.05 9389.77 277
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
MP-MVS-pluss87.67 2587.72 2587.54 4093.64 4872.04 5089.80 9093.50 3075.17 12986.34 6895.29 1770.86 7496.00 5988.78 3196.04 1694.58 42
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
UA-Net85.08 8484.96 8485.45 8992.07 7968.07 14589.78 9190.86 15582.48 284.60 9293.20 8769.35 9695.22 8871.39 22990.88 11493.07 134
alignmvs85.48 7385.32 7985.96 7789.51 13469.47 10289.74 9292.47 8176.17 9787.73 5291.46 13970.32 8093.78 15881.51 10488.95 14794.63 39
VDDNet81.52 15980.67 15984.05 16290.44 10864.13 25589.73 9385.91 31171.11 22883.18 12193.48 7850.54 32893.49 17673.40 20588.25 16194.54 48
CANet86.45 4886.10 6187.51 4290.09 11570.94 7589.70 9492.59 7981.78 481.32 15391.43 14070.34 7997.23 1784.26 7593.36 7494.37 57
test_fmvsmconf0.1_n85.61 7185.65 7185.50 8882.99 36369.39 10789.65 9590.29 17673.31 18387.77 4994.15 5571.72 6193.23 19090.31 990.67 11793.89 84
114514_t80.68 18179.51 19284.20 14794.09 4267.27 17689.64 9691.11 14758.75 41574.08 31290.72 16358.10 24695.04 9969.70 24989.42 14090.30 249
MVSMamba_PlusPlus85.99 5985.96 6486.05 7391.09 9267.64 16189.63 9792.65 7572.89 19684.64 9091.71 12571.85 5896.03 5584.77 6994.45 6094.49 51
test_fmvsmconf_n85.92 6286.04 6385.57 8785.03 31169.51 10089.62 9890.58 16273.42 17987.75 5094.02 6172.85 4893.24 18990.37 890.75 11593.96 78
fmvsm_l_conf0.5_n_386.02 5786.32 5385.14 9887.20 24668.54 13089.57 9990.44 16775.31 12087.49 5494.39 4272.86 4792.72 22089.04 2790.56 11894.16 67
DeepPCF-MVS80.84 188.10 1688.56 1786.73 5992.24 7769.03 11089.57 9993.39 3577.53 5389.79 2594.12 5678.98 1496.58 3985.66 5895.72 2894.58 42
fmvsm_s_conf0.5_n_1086.38 5286.76 4685.24 9587.33 24167.30 17489.50 10190.98 14976.25 9690.56 2294.75 2968.38 11294.24 13590.80 792.32 8994.19 66
test_fmvsmconf0.01_n84.73 8984.52 9185.34 9280.25 40569.03 11089.47 10289.65 19773.24 18786.98 6294.27 4766.62 13393.23 19090.26 1089.95 13093.78 93
fmvsm_s_conf0.5_n83.80 10183.71 10384.07 15686.69 26767.31 17389.46 10383.07 35471.09 22986.96 6393.70 7569.02 10591.47 27988.79 3084.62 22893.44 113
MGCFI-Net85.06 8585.51 7483.70 17889.42 13963.01 28689.43 10492.62 7876.43 8587.53 5391.34 14272.82 4993.42 18281.28 10888.74 15394.66 36
fmvsm_s_conf0.5_n_a83.63 11083.41 11084.28 14186.14 28068.12 14389.43 10482.87 35970.27 25787.27 5993.80 7369.09 10091.58 26788.21 3883.65 24993.14 131
UGNet80.83 17279.59 19184.54 12488.04 20368.09 14489.42 10688.16 25776.95 7176.22 26189.46 20449.30 34593.94 14768.48 26290.31 12191.60 196
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
tt080578.73 23477.83 23481.43 25585.17 30460.30 33089.41 10790.90 15271.21 22677.17 24088.73 22446.38 36893.21 19272.57 21578.96 31090.79 225
fmvsm_s_conf0.1_n83.56 11283.38 11184.10 15084.86 31367.28 17589.40 10883.01 35570.67 24187.08 6093.96 6768.38 11291.45 28088.56 3484.50 22993.56 108
BP-MVS184.32 9183.71 10386.17 6887.84 21367.85 15489.38 10989.64 19877.73 4583.98 10692.12 11456.89 26195.43 7784.03 8091.75 9895.24 7
AdaColmapbinary80.58 18879.42 19484.06 15993.09 6368.91 11589.36 11088.97 23569.27 28175.70 27189.69 19357.20 25895.77 6463.06 30588.41 16087.50 342
fmvsm_s_conf0.1_n_a83.32 12182.99 11884.28 14183.79 33768.07 14589.34 11182.85 36069.80 26887.36 5894.06 5968.34 11491.56 27087.95 4283.46 25593.21 124
PS-MVSNAJss82.07 14381.31 14784.34 13586.51 27267.27 17689.27 11291.51 13471.75 21279.37 18790.22 18163.15 17594.27 13177.69 15282.36 27091.49 202
jajsoiax79.29 22077.96 22883.27 19384.68 31866.57 19089.25 11390.16 18069.20 28675.46 27789.49 20145.75 37993.13 20176.84 16480.80 28890.11 257
fmvsm_s_conf0.5_n_886.56 4787.17 3884.73 12087.76 22165.62 21289.20 11492.21 9779.94 1789.74 2794.86 2668.63 10994.20 13690.83 591.39 10494.38 56
fmvsm_s_conf0.5_n_585.22 8185.55 7384.25 14686.26 27567.40 17089.18 11589.31 21472.50 19888.31 3793.86 7069.66 9291.96 25289.81 1391.05 10993.38 114
mvs_tets79.13 22477.77 23883.22 19784.70 31766.37 19289.17 11690.19 17969.38 27875.40 28089.46 20444.17 39193.15 19976.78 16880.70 29090.14 254
HQP-NCC89.33 14489.17 11676.41 8677.23 235
ACMP_Plane89.33 14489.17 11676.41 8677.23 235
HQP-MVS82.61 13582.02 14084.37 13289.33 14466.98 18389.17 11692.19 10076.41 8677.23 23590.23 18060.17 23295.11 9477.47 15485.99 20691.03 216
LS3D76.95 27974.82 29783.37 19090.45 10767.36 17289.15 12086.94 29161.87 38869.52 36890.61 16951.71 31594.53 12246.38 43286.71 19288.21 327
GDP-MVS83.52 11382.64 12586.16 6988.14 19768.45 13289.13 12192.69 7072.82 19783.71 11191.86 12055.69 26895.35 8680.03 12289.74 13494.69 32
OPM-MVS83.50 11482.95 11985.14 9888.79 17270.95 7489.13 12191.52 13377.55 5280.96 16191.75 12460.71 22194.50 12479.67 12786.51 19589.97 269
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
fmvsm_s_conf0.5_n_386.36 5387.46 3283.09 20287.08 25565.21 22189.09 12390.21 17879.67 1989.98 2495.02 2473.17 4291.71 26491.30 391.60 9992.34 168
TSAR-MVS + GP.85.71 6985.33 7886.84 5691.34 8872.50 3689.07 12487.28 28276.41 8685.80 7190.22 18174.15 3595.37 8581.82 10391.88 9492.65 155
test_prior472.60 3489.01 125
GeoE81.71 15181.01 15483.80 17789.51 13464.45 24988.97 12688.73 24871.27 22578.63 20089.76 19266.32 13993.20 19569.89 24786.02 20593.74 94
Anonymous2024052980.19 20078.89 20984.10 15090.60 10464.75 24088.95 12790.90 15265.97 33680.59 16991.17 15049.97 33593.73 16469.16 25582.70 26793.81 89
VDD-MVS83.01 12982.36 13184.96 10791.02 9566.40 19188.91 12888.11 25877.57 4984.39 9693.29 8552.19 30293.91 15277.05 16088.70 15494.57 44
Effi-MVS+83.62 11183.08 11585.24 9588.38 18867.45 16788.89 12989.15 22575.50 11382.27 13688.28 23969.61 9394.45 12777.81 14987.84 16993.84 87
fmvsm_s_conf0.5_n_685.55 7286.20 5683.60 18087.32 24365.13 22488.86 13091.63 12875.41 11688.23 4093.45 8168.56 11092.47 23189.52 1892.78 7993.20 126
ACMH+68.96 1476.01 29774.01 30882.03 24388.60 17965.31 22088.86 13087.55 27670.25 25867.75 38387.47 26441.27 41093.19 19758.37 35475.94 35387.60 338
test_prior288.85 13275.41 11684.91 8293.54 7674.28 3383.31 8595.86 24
Elysia81.53 15780.16 17285.62 8485.51 29568.25 13988.84 13392.19 10071.31 22280.50 17089.83 18746.89 36294.82 10876.85 16289.57 13693.80 91
StellarMVS81.53 15780.16 17285.62 8485.51 29568.25 13988.84 13392.19 10071.31 22280.50 17089.83 18746.89 36294.82 10876.85 16289.57 13693.80 91
DP-MVS Recon83.11 12782.09 13886.15 7094.44 2370.92 7688.79 13592.20 9870.53 24679.17 19091.03 15664.12 16396.03 5568.39 26490.14 12591.50 201
fmvsm_s_conf0.5_n_485.39 7785.75 7084.30 13986.70 26665.83 20588.77 13689.78 19075.46 11588.35 3693.73 7469.19 9993.06 20591.30 388.44 15994.02 76
Effi-MVS+-dtu80.03 20278.57 21484.42 12985.13 30868.74 12188.77 13688.10 25974.99 13274.97 29983.49 36657.27 25693.36 18373.53 20280.88 28691.18 210
TEST993.26 5672.96 2588.75 13891.89 11468.44 30485.00 8093.10 8874.36 3295.41 80
train_agg86.43 4986.20 5687.13 4993.26 5672.96 2588.75 13891.89 11468.69 29885.00 8093.10 8874.43 3095.41 8084.97 6395.71 2993.02 139
ETV-MVS84.90 8884.67 8885.59 8689.39 14268.66 12788.74 14092.64 7779.97 1684.10 10385.71 31069.32 9795.38 8280.82 11391.37 10592.72 150
PVSNet_Blended_VisFu82.62 13481.83 14484.96 10790.80 10169.76 9788.74 14091.70 12569.39 27778.96 19288.46 23465.47 15194.87 10774.42 19488.57 15590.24 251
casdiffmvs_mvgpermissive85.99 5986.09 6285.70 8187.65 22967.22 17988.69 14293.04 4679.64 2185.33 7692.54 10473.30 3994.50 12483.49 8391.14 10895.37 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
test_893.13 6072.57 3588.68 14391.84 11868.69 29884.87 8493.10 8874.43 3095.16 90
test_fmvsm_n_192085.29 8085.34 7785.13 10186.12 28169.93 9288.65 14490.78 15869.97 26488.27 3893.98 6671.39 6791.54 27488.49 3590.45 12093.91 81
ACMH67.68 1675.89 29873.93 31081.77 24888.71 17666.61 18988.62 14589.01 23269.81 26766.78 39786.70 28641.95 40791.51 27755.64 37878.14 32187.17 350
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
fmvsm_s_conf0.5_n_987.39 3387.95 2385.70 8189.48 13767.88 15388.59 14689.05 22980.19 1290.70 2095.40 1574.56 2893.92 15191.54 292.07 9295.31 5
CDPH-MVS85.76 6885.29 8187.17 4893.49 5171.08 6988.58 14792.42 8568.32 30684.61 9193.48 7872.32 5296.15 5379.00 13595.43 3494.28 63
fmvsm_l_conf0.5_n_985.84 6686.63 4983.46 18587.12 25466.01 19988.56 14889.43 20575.59 11189.32 2894.32 4472.89 4691.21 28990.11 1192.33 8793.16 128
DP-MVS76.78 28274.57 30083.42 18793.29 5269.46 10488.55 14983.70 34063.98 36370.20 35688.89 22154.01 28694.80 11146.66 42981.88 27686.01 378
fmvsm_l_conf0.5_n84.47 9084.54 8984.27 14385.42 29868.81 11688.49 15087.26 28468.08 30888.03 4493.49 7772.04 5791.77 26088.90 2989.14 14692.24 175
viewdifsd2359ckpt0983.34 11982.55 12785.70 8187.64 23067.72 15988.43 15191.68 12671.91 21181.65 14990.68 16567.10 12994.75 11376.17 17287.70 17394.62 41
WR-MVS_H78.51 24178.49 21578.56 32288.02 20456.38 38388.43 15192.67 7277.14 6573.89 31487.55 26166.25 14089.24 32958.92 34773.55 38690.06 263
F-COLMAP76.38 29274.33 30682.50 23389.28 14966.95 18688.41 15389.03 23064.05 36166.83 39688.61 22946.78 36492.89 21257.48 36278.55 31287.67 336
GBi-Net78.40 24277.40 24981.40 25787.60 23163.01 28688.39 15489.28 21571.63 21475.34 28387.28 26654.80 27491.11 29062.72 30779.57 30290.09 259
test178.40 24277.40 24981.40 25787.60 23163.01 28688.39 15489.28 21571.63 21475.34 28387.28 26654.80 27491.11 29062.72 30779.57 30290.09 259
FMVSNet177.44 26976.12 27781.40 25786.81 26263.01 28688.39 15489.28 21570.49 25174.39 30987.28 26649.06 34991.11 29060.91 32878.52 31390.09 259
tttt051779.40 21677.91 23083.90 17388.10 20063.84 26188.37 15784.05 33671.45 22076.78 24689.12 21149.93 33894.89 10570.18 24383.18 26092.96 143
fmvsm_l_conf0.5_n_a84.13 9384.16 9484.06 15985.38 29968.40 13388.34 15886.85 29467.48 31587.48 5593.40 8270.89 7391.61 26588.38 3789.22 14392.16 182
v7n78.97 22977.58 24583.14 20083.45 34765.51 21488.32 15991.21 14273.69 17072.41 33486.32 30057.93 24793.81 15769.18 25475.65 35690.11 257
COLMAP_ROBcopyleft66.92 1773.01 33870.41 35480.81 27587.13 24965.63 21188.30 16084.19 33562.96 37363.80 42587.69 25638.04 42992.56 22646.66 42974.91 37384.24 405
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
FIs82.07 14382.42 12881.04 26988.80 17158.34 34888.26 16193.49 3176.93 7278.47 20691.04 15469.92 8992.34 23969.87 24884.97 22292.44 166
EIA-MVS83.31 12282.80 12284.82 11589.59 13065.59 21388.21 16292.68 7174.66 14578.96 19286.42 29769.06 10295.26 8775.54 18390.09 12693.62 104
PLCcopyleft70.83 1178.05 25376.37 27583.08 20491.88 8367.80 15688.19 16389.46 20464.33 35669.87 36588.38 23653.66 28893.58 16658.86 34882.73 26587.86 333
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
MG-MVS83.41 11683.45 10983.28 19292.74 7162.28 30388.17 16489.50 20375.22 12381.49 15192.74 10366.75 13195.11 9472.85 21191.58 10192.45 165
TAPA-MVS73.13 979.15 22377.94 22982.79 22389.59 13062.99 29088.16 16591.51 13465.77 33777.14 24191.09 15260.91 21993.21 19250.26 41087.05 18592.17 181
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
test_fmvsmvis_n_192084.02 9583.87 9784.49 12784.12 32969.37 10888.15 16687.96 26570.01 26283.95 10793.23 8668.80 10791.51 27788.61 3289.96 12992.57 156
h-mvs3383.15 12482.19 13586.02 7690.56 10570.85 7988.15 16689.16 22476.02 10084.67 8791.39 14161.54 20495.50 7382.71 9675.48 36091.72 195
KinetiMVS83.31 12282.61 12685.39 9187.08 25567.56 16588.06 16891.65 12777.80 4482.21 13891.79 12157.27 25694.07 14277.77 15089.89 13294.56 46
PS-CasMVS78.01 25578.09 22677.77 34187.71 22454.39 40888.02 16991.22 14177.50 5473.26 32288.64 22860.73 22088.41 34861.88 31973.88 38390.53 238
OMC-MVS82.69 13381.97 14284.85 11488.75 17467.42 16887.98 17090.87 15474.92 13679.72 18091.65 12862.19 19393.96 14475.26 18786.42 19693.16 128
v879.97 20479.02 20682.80 22084.09 33064.50 24787.96 17190.29 17674.13 16075.24 29086.81 27962.88 18293.89 15574.39 19575.40 36590.00 265
FC-MVSNet-test81.52 15982.02 14080.03 29288.42 18755.97 38987.95 17293.42 3477.10 6877.38 23090.98 16069.96 8891.79 25968.46 26384.50 22992.33 169
CP-MVSNet78.22 24678.34 22077.84 33987.83 21454.54 40687.94 17391.17 14477.65 4673.48 32088.49 23362.24 19288.43 34762.19 31574.07 37990.55 237
PAPM_NR83.02 12882.41 12984.82 11592.47 7666.37 19287.93 17491.80 12073.82 16677.32 23290.66 16667.90 12094.90 10470.37 23989.48 13993.19 127
PEN-MVS77.73 26177.69 24277.84 33987.07 25753.91 41187.91 17591.18 14377.56 5173.14 32488.82 22361.23 21389.17 33159.95 33572.37 39490.43 242
ECVR-MVScopyleft79.61 20779.26 20080.67 27890.08 11654.69 40487.89 17677.44 41874.88 13880.27 17392.79 10048.96 35192.45 23268.55 26192.50 8494.86 19
v1079.74 20678.67 21182.97 21284.06 33164.95 23087.88 17790.62 16173.11 19075.11 29486.56 29361.46 20794.05 14373.68 20075.55 35889.90 271
test250677.30 27376.49 27079.74 29890.08 11652.02 42287.86 17863.10 46574.88 13880.16 17692.79 10038.29 42892.35 23868.74 26092.50 8494.86 19
SSM_040481.91 14680.84 15785.13 10189.24 15168.26 13787.84 17989.25 21971.06 23180.62 16890.39 17459.57 23494.65 11972.45 22187.19 18292.47 164
casdiffmvspermissive85.11 8385.14 8285.01 10587.20 24665.77 20987.75 18092.83 6577.84 4384.36 9992.38 10672.15 5593.93 15081.27 10990.48 11995.33 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
TranMVSNet+NR-MVSNet80.84 17180.31 16882.42 23487.85 21262.33 30187.74 18191.33 13980.55 977.99 21889.86 18565.23 15392.62 22167.05 27675.24 37092.30 171
EI-MVSNet-Vis-set84.19 9283.81 10085.31 9388.18 19467.85 15487.66 18289.73 19580.05 1582.95 12589.59 19970.74 7694.82 10880.66 11884.72 22693.28 120
UniMVSNet (Re)81.60 15581.11 15183.09 20288.38 18864.41 25087.60 18393.02 5078.42 3778.56 20288.16 24369.78 9093.26 18869.58 25176.49 34291.60 196
CNLPA78.08 25176.79 26381.97 24590.40 10971.07 7087.59 18484.55 32866.03 33572.38 33589.64 19657.56 25286.04 37459.61 33983.35 25688.79 310
DTE-MVSNet76.99 27776.80 26277.54 34886.24 27653.06 42087.52 18590.66 16077.08 6972.50 33288.67 22760.48 22889.52 32357.33 36570.74 40690.05 264
无先验87.48 18688.98 23360.00 40194.12 14067.28 27288.97 302
viewdifsd2359ckpt1382.91 13082.29 13384.77 11886.96 25866.90 18787.47 18791.62 12972.19 20481.68 14890.71 16466.92 13093.28 18575.90 17787.15 18394.12 70
mvsmamba80.60 18579.38 19584.27 14389.74 12867.24 17887.47 18786.95 29070.02 26175.38 28188.93 21951.24 31992.56 22675.47 18589.22 14393.00 141
FMVSNet278.20 24877.21 25381.20 26487.60 23162.89 29287.47 18789.02 23171.63 21475.29 28987.28 26654.80 27491.10 29362.38 31279.38 30689.61 281
RRT-MVS82.60 13782.10 13784.10 15087.98 20762.94 29187.45 19091.27 14077.42 5679.85 17890.28 17756.62 26494.70 11779.87 12588.15 16394.67 33
EI-MVSNet-UG-set83.81 10083.38 11185.09 10387.87 21167.53 16687.44 19189.66 19679.74 1882.23 13789.41 20870.24 8294.74 11479.95 12383.92 24192.99 142
SSM_040781.58 15680.48 16484.87 11388.81 16767.96 14987.37 19289.25 21971.06 23179.48 18490.39 17459.57 23494.48 12672.45 22185.93 20892.18 178
thisisatest053079.40 21677.76 23984.31 13787.69 22865.10 22787.36 19384.26 33470.04 26077.42 22988.26 24149.94 33694.79 11270.20 24284.70 22793.03 138
CANet_DTU80.61 18379.87 18182.83 21785.60 29363.17 28587.36 19388.65 25176.37 9075.88 26888.44 23553.51 29093.07 20473.30 20689.74 13492.25 173
test111179.43 21479.18 20380.15 29089.99 12153.31 41787.33 19577.05 42275.04 13180.23 17592.77 10248.97 35092.33 24068.87 25892.40 8694.81 22
baseline84.93 8684.98 8384.80 11787.30 24465.39 21887.30 19692.88 6277.62 4784.04 10592.26 10871.81 5993.96 14481.31 10790.30 12295.03 11
UniMVSNet_ETH3D79.10 22578.24 22381.70 24986.85 26060.24 33187.28 19788.79 24174.25 15676.84 24390.53 17249.48 34191.56 27067.98 26582.15 27193.29 119
anonymousdsp78.60 23877.15 25482.98 21180.51 40367.08 18187.24 19889.53 20265.66 33975.16 29287.19 27252.52 29692.25 24277.17 15879.34 30789.61 281
UniMVSNet_NR-MVSNet81.88 14781.54 14682.92 21388.46 18463.46 27687.13 19992.37 8680.19 1278.38 20789.14 21071.66 6493.05 20670.05 24476.46 34392.25 173
DPM-MVS84.93 8684.29 9386.84 5690.20 11373.04 2387.12 20093.04 4669.80 26882.85 12991.22 14773.06 4496.02 5776.72 16994.63 5491.46 205
v114480.03 20279.03 20583.01 20883.78 33864.51 24587.11 20190.57 16471.96 21078.08 21686.20 30261.41 20893.94 14774.93 18977.23 33090.60 235
v2v48280.23 19879.29 19983.05 20683.62 34364.14 25487.04 20289.97 18573.61 17278.18 21387.22 27061.10 21693.82 15676.11 17376.78 33991.18 210
fmvsm_s_conf0.1_n_283.80 10183.79 10183.83 17485.62 29264.94 23387.03 20386.62 30074.32 15287.97 4794.33 4360.67 22392.60 22389.72 1487.79 17093.96 78
DU-MVS81.12 16780.52 16382.90 21487.80 21563.46 27687.02 20491.87 11679.01 3178.38 20789.07 21265.02 15593.05 20670.05 24476.46 34392.20 176
LuminaMVS80.68 18179.62 19083.83 17485.07 31068.01 14886.99 20588.83 23970.36 25281.38 15287.99 25050.11 33392.51 23079.02 13386.89 18990.97 219
fmvsm_s_conf0.5_n_284.04 9484.11 9583.81 17686.17 27965.00 22986.96 20687.28 28274.35 15188.25 3994.23 5061.82 19992.60 22389.85 1288.09 16493.84 87
v14419279.47 21278.37 21982.78 22483.35 34863.96 25786.96 20690.36 17269.99 26377.50 22785.67 31360.66 22493.77 16074.27 19676.58 34090.62 233
Fast-Effi-MVS+-dtu78.02 25476.49 27082.62 23083.16 35766.96 18586.94 20887.45 28072.45 19971.49 34684.17 35054.79 27791.58 26767.61 26880.31 29589.30 290
v119279.59 20978.43 21883.07 20583.55 34564.52 24486.93 20990.58 16270.83 23777.78 22385.90 30659.15 23893.94 14773.96 19977.19 33290.76 227
EPNet_dtu75.46 30474.86 29677.23 35282.57 37354.60 40586.89 21083.09 35371.64 21366.25 40685.86 30855.99 26688.04 35254.92 38286.55 19489.05 297
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
viewmacassd2359aftdt83.76 10483.66 10584.07 15686.59 27064.56 24286.88 21191.82 11975.72 10683.34 11792.15 11368.24 11692.88 21379.05 13189.15 14594.77 25
原ACMM286.86 212
VPA-MVSNet80.60 18580.55 16280.76 27688.07 20260.80 32286.86 21291.58 13275.67 11080.24 17489.45 20663.34 16890.25 31070.51 23879.22 30991.23 209
v192192079.22 22178.03 22782.80 22083.30 35063.94 25986.80 21490.33 17369.91 26677.48 22885.53 31758.44 24493.75 16273.60 20176.85 33790.71 231
IterMVS-LS80.06 20179.38 19582.11 24185.89 28563.20 28386.79 21589.34 20874.19 15775.45 27886.72 28266.62 13392.39 23572.58 21476.86 33690.75 228
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
TransMVSNet (Re)75.39 30874.56 30177.86 33885.50 29757.10 37186.78 21686.09 31072.17 20671.53 34587.34 26563.01 17989.31 32756.84 37161.83 43887.17 350
Baseline_NR-MVSNet78.15 25078.33 22177.61 34585.79 28756.21 38786.78 21685.76 31473.60 17377.93 21987.57 25965.02 15588.99 33467.14 27575.33 36787.63 337
PAPR81.66 15480.89 15683.99 16990.27 11164.00 25686.76 21891.77 12368.84 29677.13 24289.50 20067.63 12294.88 10667.55 26988.52 15793.09 133
Vis-MVSNet (Re-imp)78.36 24478.45 21678.07 33488.64 17851.78 42886.70 21979.63 40074.14 15975.11 29490.83 16261.29 21289.75 31958.10 35791.60 9992.69 153
guyue81.13 16680.64 16082.60 23186.52 27163.92 26086.69 22087.73 27373.97 16180.83 16689.69 19356.70 26291.33 28578.26 14885.40 21992.54 158
viewmanbaseed2359cas83.66 10783.55 10784.00 16786.81 26264.53 24386.65 22191.75 12474.89 13783.15 12391.68 12668.74 10892.83 21779.02 13389.24 14294.63 39
pmmvs674.69 31373.39 31778.61 31981.38 39257.48 36686.64 22287.95 26664.99 34970.18 35786.61 28950.43 32989.52 32362.12 31770.18 40988.83 308
v124078.99 22877.78 23782.64 22983.21 35363.54 27386.62 22390.30 17569.74 27377.33 23185.68 31257.04 25993.76 16173.13 20976.92 33490.62 233
MTAPA87.23 3687.00 3987.90 2294.18 3974.25 586.58 22492.02 10679.45 2285.88 7094.80 2768.07 11796.21 5086.69 5295.34 3693.23 121
旧先验286.56 22558.10 42087.04 6188.98 33574.07 198
FMVSNet377.88 25876.85 26180.97 27286.84 26162.36 30086.52 22688.77 24371.13 22775.34 28386.66 28854.07 28491.10 29362.72 30779.57 30289.45 285
dcpmvs_285.63 7086.15 6084.06 15991.71 8464.94 23386.47 22791.87 11673.63 17186.60 6793.02 9376.57 1891.87 25883.36 8492.15 9095.35 3
AstraMVS80.81 17380.14 17482.80 22086.05 28463.96 25786.46 22885.90 31273.71 16980.85 16590.56 17054.06 28591.57 26979.72 12683.97 24092.86 147
pm-mvs177.25 27476.68 26878.93 31484.22 32758.62 34586.41 22988.36 25671.37 22173.31 32188.01 24961.22 21489.15 33264.24 29873.01 39189.03 298
EI-MVSNet80.52 18979.98 17782.12 23984.28 32563.19 28486.41 22988.95 23674.18 15878.69 19787.54 26266.62 13392.43 23372.57 21580.57 29290.74 229
CVMVSNet72.99 33972.58 32874.25 38484.28 32550.85 43686.41 22983.45 34644.56 45673.23 32387.54 26249.38 34385.70 37765.90 28478.44 31586.19 373
E284.00 9683.87 9784.39 13087.70 22664.95 23086.40 23292.23 9275.85 10383.21 11891.78 12270.09 8593.55 17079.52 12888.05 16594.66 36
E384.00 9683.87 9784.39 13087.70 22664.95 23086.40 23292.23 9275.85 10383.21 11891.78 12270.09 8593.55 17079.52 12888.05 16594.66 36
MonoMVSNet76.49 28975.80 27878.58 32181.55 38858.45 34686.36 23486.22 30674.87 14074.73 30383.73 35951.79 31488.73 34070.78 23372.15 39788.55 320
NR-MVSNet80.23 19879.38 19582.78 22487.80 21563.34 27986.31 23591.09 14879.01 3172.17 33889.07 21267.20 12792.81 21866.08 28375.65 35692.20 176
viewcassd2359sk1183.89 9883.74 10284.34 13587.76 22164.91 23686.30 23692.22 9575.47 11483.04 12491.52 13570.15 8393.53 17379.26 13087.96 16794.57 44
v14878.72 23577.80 23681.47 25482.73 36961.96 30786.30 23688.08 26073.26 18576.18 26385.47 31962.46 18792.36 23771.92 22573.82 38490.09 259
新几何286.29 238
E3new83.78 10383.60 10684.31 13787.76 22164.89 23786.24 23992.20 9875.15 13082.87 12791.23 14470.11 8493.52 17579.05 13187.79 17094.51 50
test_yl81.17 16480.47 16583.24 19589.13 15663.62 26586.21 24089.95 18672.43 20281.78 14689.61 19757.50 25393.58 16670.75 23486.90 18792.52 159
DCV-MVSNet81.17 16480.47 16583.24 19589.13 15663.62 26586.21 24089.95 18672.43 20281.78 14689.61 19757.50 25393.58 16670.75 23486.90 18792.52 159
PVSNet_BlendedMVS80.60 18580.02 17682.36 23688.85 16365.40 21686.16 24292.00 10869.34 27978.11 21486.09 30566.02 14694.27 13171.52 22682.06 27387.39 343
MVS_Test83.15 12483.06 11683.41 18986.86 25963.21 28286.11 24392.00 10874.31 15382.87 12789.44 20770.03 8793.21 19277.39 15688.50 15893.81 89
BH-untuned79.47 21278.60 21382.05 24289.19 15465.91 20386.07 24488.52 25472.18 20575.42 27987.69 25661.15 21593.54 17260.38 33286.83 19086.70 365
MVS_111021_HR85.14 8284.75 8786.32 6591.65 8572.70 3085.98 24590.33 17376.11 9882.08 14091.61 13371.36 6894.17 13981.02 11092.58 8292.08 184
jason81.39 16280.29 16984.70 12186.63 26969.90 9485.95 24686.77 29563.24 36881.07 15989.47 20261.08 21792.15 24578.33 14490.07 12892.05 185
jason: jason.
test_040272.79 34270.44 35379.84 29688.13 19865.99 20185.93 24784.29 33265.57 34067.40 39085.49 31846.92 36192.61 22235.88 45874.38 37880.94 437
OurMVSNet-221017-074.26 31772.42 33079.80 29783.76 33959.59 33885.92 24886.64 29866.39 33066.96 39487.58 25839.46 41991.60 26665.76 28669.27 41288.22 326
hse-mvs281.72 15080.94 15584.07 15688.72 17567.68 16085.87 24987.26 28476.02 10084.67 8788.22 24261.54 20493.48 17782.71 9673.44 38891.06 214
EG-PatchMatch MVS74.04 32171.82 33580.71 27784.92 31267.42 16885.86 25088.08 26066.04 33464.22 42083.85 35435.10 43992.56 22657.44 36380.83 28782.16 430
AUN-MVS79.21 22277.60 24484.05 16288.71 17667.61 16285.84 25187.26 28469.08 28977.23 23588.14 24753.20 29493.47 17875.50 18473.45 38791.06 214
thres100view90076.50 28675.55 28579.33 30789.52 13356.99 37285.83 25283.23 34973.94 16376.32 25987.12 27451.89 31191.95 25348.33 42083.75 24589.07 292
CLD-MVS82.31 13981.65 14584.29 14088.47 18367.73 15885.81 25392.35 8775.78 10578.33 20986.58 29264.01 16494.35 12876.05 17587.48 17790.79 225
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
FE-MVSNET171.98 35170.01 35877.91 33677.16 43158.13 35085.61 25488.78 24268.62 30063.35 42681.28 39539.62 41888.61 34358.02 35867.67 41987.00 357
VortexMVS78.57 24077.89 23280.59 27985.89 28562.76 29385.61 25489.62 19972.06 20874.99 29885.38 32155.94 26790.77 30474.99 18876.58 34088.23 325
SixPastTwentyTwo73.37 33071.26 34579.70 29985.08 30957.89 35785.57 25683.56 34371.03 23365.66 40985.88 30742.10 40592.57 22559.11 34563.34 43388.65 316
xiu_mvs_v1_base_debu80.80 17679.72 18784.03 16487.35 23670.19 8885.56 25788.77 24369.06 29081.83 14288.16 24350.91 32292.85 21478.29 14587.56 17489.06 294
xiu_mvs_v1_base80.80 17679.72 18784.03 16487.35 23670.19 8885.56 25788.77 24369.06 29081.83 14288.16 24350.91 32292.85 21478.29 14587.56 17489.06 294
xiu_mvs_v1_base_debi80.80 17679.72 18784.03 16487.35 23670.19 8885.56 25788.77 24369.06 29081.83 14288.16 24350.91 32292.85 21478.29 14587.56 17489.06 294
V4279.38 21878.24 22382.83 21781.10 39765.50 21585.55 26089.82 18971.57 21878.21 21186.12 30460.66 22493.18 19875.64 18075.46 36289.81 276
lupinMVS81.39 16280.27 17084.76 11987.35 23670.21 8685.55 26086.41 30262.85 37581.32 15388.61 22961.68 20192.24 24378.41 14390.26 12391.83 188
Fast-Effi-MVS+80.81 17379.92 17883.47 18488.85 16364.51 24585.53 26289.39 20770.79 23878.49 20485.06 33067.54 12393.58 16667.03 27786.58 19392.32 170
thres600view776.50 28675.44 28679.68 30089.40 14157.16 36985.53 26283.23 34973.79 16776.26 26087.09 27551.89 31191.89 25648.05 42583.72 24890.00 265
DELS-MVS85.41 7685.30 8085.77 7988.49 18267.93 15285.52 26493.44 3278.70 3483.63 11589.03 21474.57 2795.71 6680.26 12194.04 6793.66 97
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
fmvsm_s_conf0.5_n_783.34 11984.03 9681.28 26185.73 28965.13 22485.40 26589.90 18874.96 13582.13 13993.89 6966.65 13287.92 35386.56 5391.05 10990.80 224
IMVS_040780.61 18379.90 18082.75 22787.13 24963.59 26985.33 26689.33 20970.51 24777.82 22089.03 21461.84 19792.91 21172.56 21785.56 21591.74 191
IMVS_040380.80 17680.12 17582.87 21687.13 24963.59 26985.19 26789.33 20970.51 24778.49 20489.03 21463.26 17193.27 18772.56 21785.56 21591.74 191
tfpn200view976.42 29075.37 29079.55 30589.13 15657.65 36385.17 26883.60 34173.41 18076.45 25586.39 29852.12 30391.95 25348.33 42083.75 24589.07 292
thres40076.50 28675.37 29079.86 29589.13 15657.65 36385.17 26883.60 34173.41 18076.45 25586.39 29852.12 30391.95 25348.33 42083.75 24590.00 265
MVS_111021_LR82.61 13582.11 13684.11 14988.82 16671.58 5785.15 27086.16 30874.69 14380.47 17291.04 15462.29 19090.55 30780.33 12090.08 12790.20 252
baseline176.98 27876.75 26677.66 34388.13 19855.66 39485.12 27181.89 36973.04 19276.79 24588.90 22062.43 18887.78 35663.30 30471.18 40489.55 283
mmtdpeth74.16 31973.01 32377.60 34783.72 34061.13 31585.10 27285.10 32172.06 20877.21 23980.33 40843.84 39385.75 37677.14 15952.61 45785.91 381
viewdifsd2359ckpt0782.83 13282.78 12482.99 20986.51 27262.58 29485.09 27390.83 15675.22 12382.28 13591.63 13069.43 9592.03 24877.71 15186.32 19794.34 59
WR-MVS79.49 21179.22 20280.27 28788.79 17258.35 34785.06 27488.61 25378.56 3577.65 22588.34 23763.81 16790.66 30664.98 29277.22 33191.80 190
ET-MVSNet_ETH3D78.63 23776.63 26984.64 12286.73 26569.47 10285.01 27584.61 32769.54 27566.51 40486.59 29050.16 33291.75 26176.26 17184.24 23792.69 153
OpenMVS_ROBcopyleft64.09 1970.56 36468.19 37077.65 34480.26 40459.41 34185.01 27582.96 35858.76 41465.43 41182.33 38537.63 43191.23 28845.34 43976.03 35282.32 427
BH-RMVSNet79.61 20778.44 21783.14 20089.38 14365.93 20284.95 27787.15 28773.56 17478.19 21289.79 19156.67 26393.36 18359.53 34086.74 19190.13 255
BH-w/o78.21 24777.33 25280.84 27488.81 16765.13 22484.87 27887.85 27069.75 27174.52 30784.74 33761.34 21093.11 20258.24 35685.84 21184.27 404
TDRefinement67.49 39064.34 40276.92 35473.47 45161.07 31884.86 27982.98 35759.77 40358.30 44685.13 32826.06 45487.89 35447.92 42660.59 44381.81 433
Anonymous20240521178.25 24577.01 25681.99 24491.03 9460.67 32484.77 28083.90 33870.65 24580.00 17791.20 14841.08 41291.43 28165.21 28985.26 22093.85 85
TAMVS78.89 23277.51 24883.03 20787.80 21567.79 15784.72 28185.05 32367.63 31176.75 24787.70 25562.25 19190.82 30058.53 35287.13 18490.49 240
sc_t172.19 34869.51 36080.23 28884.81 31461.09 31784.68 28280.22 39460.70 39571.27 34783.58 36436.59 43489.24 32960.41 33163.31 43490.37 245
131476.53 28575.30 29280.21 28983.93 33462.32 30284.66 28388.81 24060.23 39970.16 35984.07 35255.30 27190.73 30567.37 27183.21 25987.59 340
MVS78.19 24976.99 25881.78 24785.66 29066.99 18284.66 28390.47 16655.08 43672.02 34085.27 32363.83 16694.11 14166.10 28289.80 13384.24 405
tfpnnormal74.39 31573.16 32178.08 33386.10 28358.05 35284.65 28587.53 27770.32 25571.22 34985.63 31454.97 27289.86 31643.03 44475.02 37286.32 370
TR-MVS77.44 26976.18 27681.20 26488.24 19263.24 28184.61 28686.40 30367.55 31377.81 22286.48 29654.10 28393.15 19957.75 36182.72 26687.20 349
AllTest70.96 35868.09 37379.58 30385.15 30663.62 26584.58 28779.83 39762.31 38260.32 43986.73 28032.02 44488.96 33750.28 40871.57 40286.15 374
FA-MVS(test-final)80.96 16979.91 17984.10 15088.30 19165.01 22884.55 28890.01 18473.25 18679.61 18187.57 25958.35 24594.72 11571.29 23086.25 20092.56 157
EU-MVSNet68.53 38567.61 38471.31 41278.51 42547.01 45084.47 28984.27 33342.27 45966.44 40584.79 33640.44 41583.76 39558.76 35068.54 41783.17 417
VNet82.21 14082.41 12981.62 25090.82 10060.93 31984.47 28989.78 19076.36 9184.07 10491.88 11864.71 15890.26 30970.68 23688.89 14893.66 97
xiu_mvs_v2_base81.69 15281.05 15283.60 18089.15 15568.03 14784.46 29190.02 18370.67 24181.30 15686.53 29563.17 17494.19 13875.60 18288.54 15688.57 319
VPNet78.69 23678.66 21278.76 31788.31 19055.72 39384.45 29286.63 29976.79 7678.26 21090.55 17159.30 23789.70 32166.63 27877.05 33390.88 222
FE-MVSNET272.88 34171.28 34377.67 34278.30 42657.78 36184.43 29388.92 23869.56 27464.61 41781.67 39346.73 36688.54 34659.33 34167.99 41886.69 366
PVSNet_Blended80.98 16880.34 16782.90 21488.85 16365.40 21684.43 29392.00 10867.62 31278.11 21485.05 33166.02 14694.27 13171.52 22689.50 13889.01 299
MVP-Stereo76.12 29474.46 30481.13 26785.37 30069.79 9584.42 29587.95 26665.03 34767.46 38785.33 32253.28 29391.73 26358.01 35983.27 25881.85 432
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
CDS-MVSNet79.07 22677.70 24183.17 19987.60 23168.23 14184.40 29686.20 30767.49 31476.36 25886.54 29461.54 20490.79 30161.86 32087.33 17990.49 240
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
K. test v371.19 35568.51 36779.21 31083.04 36057.78 36184.35 29776.91 42372.90 19562.99 42982.86 37839.27 42091.09 29561.65 32252.66 45688.75 312
PS-MVSNAJ81.69 15281.02 15383.70 17889.51 13468.21 14284.28 29890.09 18270.79 23881.26 15785.62 31563.15 17594.29 12975.62 18188.87 14988.59 318
patch_mono-283.65 10884.54 8980.99 27090.06 12065.83 20584.21 29988.74 24771.60 21785.01 7992.44 10574.51 2983.50 39982.15 10192.15 9093.64 103
viewdifsd2359ckpt1180.37 19479.73 18582.30 23783.70 34162.39 29884.20 30086.67 29673.22 18880.90 16290.62 16763.00 18091.56 27076.81 16678.44 31592.95 144
viewmsd2359difaftdt80.37 19479.73 18582.30 23783.70 34162.39 29884.20 30086.67 29673.22 18880.90 16290.62 16763.00 18091.56 27076.81 16678.44 31592.95 144
test22291.50 8668.26 13784.16 30283.20 35254.63 43779.74 17991.63 13058.97 23991.42 10386.77 363
testdata184.14 30375.71 107
c3_l78.75 23377.91 23081.26 26282.89 36661.56 31284.09 30489.13 22769.97 26475.56 27384.29 34566.36 13892.09 24773.47 20475.48 36090.12 256
MVSTER79.01 22777.88 23382.38 23583.07 35864.80 23984.08 30588.95 23669.01 29378.69 19787.17 27354.70 27892.43 23374.69 19080.57 29289.89 272
diffmvs_AUTHOR82.38 13882.27 13482.73 22883.26 35163.80 26283.89 30689.76 19273.35 18282.37 13490.84 16166.25 14090.79 30182.77 9387.93 16893.59 106
ab-mvs79.51 21078.97 20781.14 26688.46 18460.91 32083.84 30789.24 22170.36 25279.03 19188.87 22263.23 17390.21 31165.12 29082.57 26892.28 172
reproduce_monomvs75.40 30774.38 30578.46 32783.92 33557.80 36083.78 30886.94 29173.47 17872.25 33784.47 33938.74 42489.27 32875.32 18670.53 40788.31 324
PAPM77.68 26576.40 27481.51 25387.29 24561.85 30883.78 30889.59 20064.74 35071.23 34888.70 22562.59 18493.66 16552.66 39487.03 18689.01 299
SD_040374.65 31474.77 29874.29 38386.20 27847.42 44783.71 31085.12 32069.30 28068.50 37987.95 25159.40 23686.05 37349.38 41483.35 25689.40 286
diffmvspermissive82.10 14181.88 14382.76 22683.00 36163.78 26483.68 31189.76 19272.94 19482.02 14189.85 18665.96 14890.79 30182.38 10087.30 18093.71 95
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
miper_ehance_all_eth78.59 23977.76 23981.08 26882.66 37161.56 31283.65 31289.15 22568.87 29575.55 27483.79 35766.49 13692.03 24873.25 20776.39 34589.64 280
1112_ss77.40 27176.43 27280.32 28689.11 16060.41 32983.65 31287.72 27462.13 38573.05 32586.72 28262.58 18589.97 31562.11 31880.80 28890.59 236
PCF-MVS73.52 780.38 19278.84 21085.01 10587.71 22468.99 11383.65 31291.46 13863.00 37277.77 22490.28 17766.10 14395.09 9861.40 32488.22 16290.94 221
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
XVG-ACMP-BASELINE76.11 29574.27 30781.62 25083.20 35464.67 24183.60 31589.75 19469.75 27171.85 34187.09 27532.78 44392.11 24669.99 24680.43 29488.09 329
tt032070.49 36668.03 37477.89 33784.78 31559.12 34283.55 31680.44 38958.13 41967.43 38980.41 40739.26 42187.54 35955.12 38063.18 43586.99 358
cl2278.07 25277.01 25681.23 26382.37 37861.83 30983.55 31687.98 26468.96 29475.06 29683.87 35361.40 20991.88 25773.53 20276.39 34589.98 268
XVG-OURS-SEG-HR80.81 17379.76 18483.96 17185.60 29368.78 11883.54 31890.50 16570.66 24476.71 24891.66 12760.69 22291.26 28676.94 16181.58 27891.83 188
viewmambaseed2359dif80.41 19079.84 18282.12 23982.95 36562.50 29783.39 31988.06 26267.11 31780.98 16090.31 17666.20 14291.01 29774.62 19184.90 22392.86 147
IB-MVS68.01 1575.85 29973.36 31983.31 19184.76 31666.03 19783.38 32085.06 32270.21 25969.40 36981.05 39845.76 37894.66 11865.10 29175.49 35989.25 291
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
HY-MVS69.67 1277.95 25677.15 25480.36 28487.57 23560.21 33283.37 32187.78 27266.11 33275.37 28287.06 27763.27 17090.48 30861.38 32582.43 26990.40 244
tt0320-xc70.11 37067.45 38778.07 33485.33 30159.51 34083.28 32278.96 40758.77 41367.10 39380.28 40936.73 43387.42 36056.83 37259.77 44587.29 347
test_vis1_n_192075.52 30375.78 27974.75 37979.84 41157.44 36783.26 32385.52 31662.83 37679.34 18986.17 30345.10 38479.71 42178.75 13881.21 28287.10 356
Anonymous2024052168.80 38167.22 39073.55 39074.33 44354.11 40983.18 32485.61 31558.15 41861.68 43380.94 40130.71 44981.27 41557.00 36973.34 39085.28 390
eth_miper_zixun_eth77.92 25776.69 26781.61 25283.00 36161.98 30683.15 32589.20 22369.52 27674.86 30184.35 34461.76 20092.56 22671.50 22872.89 39290.28 250
FE-MVS77.78 26075.68 28184.08 15588.09 20166.00 20083.13 32687.79 27168.42 30578.01 21785.23 32545.50 38295.12 9259.11 34585.83 21291.11 212
cl____77.72 26276.76 26480.58 28082.49 37560.48 32783.09 32787.87 26869.22 28474.38 31085.22 32662.10 19491.53 27571.09 23175.41 36489.73 279
DIV-MVS_self_test77.72 26276.76 26480.58 28082.48 37660.48 32783.09 32787.86 26969.22 28474.38 31085.24 32462.10 19491.53 27571.09 23175.40 36589.74 278
thres20075.55 30274.47 30378.82 31687.78 21857.85 35883.07 32983.51 34472.44 20175.84 26984.42 34052.08 30691.75 26147.41 42783.64 25086.86 361
testing368.56 38467.67 38371.22 41387.33 24142.87 46383.06 33071.54 44370.36 25269.08 37384.38 34230.33 45085.69 37837.50 45675.45 36385.09 396
XVG-OURS80.41 19079.23 20183.97 17085.64 29169.02 11283.03 33190.39 16871.09 22977.63 22691.49 13854.62 28091.35 28375.71 17983.47 25491.54 199
miper_enhance_ethall77.87 25976.86 26080.92 27381.65 38561.38 31482.68 33288.98 23365.52 34175.47 27582.30 38665.76 15092.00 25172.95 21076.39 34589.39 287
mvs_anonymous79.42 21579.11 20480.34 28584.45 32457.97 35582.59 33387.62 27567.40 31676.17 26588.56 23268.47 11189.59 32270.65 23786.05 20493.47 112
baseline275.70 30073.83 31381.30 26083.26 35161.79 31082.57 33480.65 38366.81 31966.88 39583.42 36757.86 24992.19 24463.47 30179.57 30289.91 270
cascas76.72 28374.64 29982.99 20985.78 28865.88 20482.33 33589.21 22260.85 39472.74 32881.02 39947.28 35893.75 16267.48 27085.02 22189.34 289
WB-MVSnew71.96 35271.65 33772.89 39884.67 32151.88 42682.29 33677.57 41562.31 38273.67 31883.00 37453.49 29181.10 41645.75 43682.13 27285.70 384
RPSCF73.23 33571.46 33978.54 32382.50 37459.85 33482.18 33782.84 36158.96 41171.15 35089.41 20845.48 38384.77 38958.82 34971.83 40091.02 218
thisisatest051577.33 27275.38 28983.18 19885.27 30363.80 26282.11 33883.27 34865.06 34675.91 26783.84 35549.54 34094.27 13167.24 27386.19 20191.48 203
pmmvs-eth3d70.50 36567.83 37978.52 32577.37 43066.18 19581.82 33981.51 37458.90 41263.90 42480.42 40642.69 40086.28 37158.56 35165.30 42983.11 419
MS-PatchMatch73.83 32472.67 32677.30 35183.87 33666.02 19881.82 33984.66 32661.37 39268.61 37782.82 37947.29 35788.21 34959.27 34284.32 23677.68 447
pmmvs571.55 35370.20 35775.61 36477.83 42756.39 38281.74 34180.89 37957.76 42267.46 38784.49 33849.26 34685.32 38457.08 36775.29 36885.11 395
Test_1112_low_res76.40 29175.44 28679.27 30889.28 14958.09 35181.69 34287.07 28859.53 40672.48 33386.67 28761.30 21189.33 32660.81 33080.15 29790.41 243
IterMVS74.29 31672.94 32478.35 32881.53 38963.49 27581.58 34382.49 36368.06 30969.99 36283.69 36151.66 31685.54 38065.85 28571.64 40186.01 378
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
IterMVS-SCA-FT75.43 30573.87 31280.11 29182.69 37064.85 23881.57 34483.47 34569.16 28770.49 35384.15 35151.95 30988.15 35069.23 25372.14 39887.34 345
test_vis1_n69.85 37469.21 36371.77 40672.66 45755.27 40081.48 34576.21 42752.03 44475.30 28883.20 37128.97 45176.22 44174.60 19278.41 31983.81 411
pmmvs474.03 32371.91 33480.39 28381.96 38168.32 13581.45 34682.14 36659.32 40769.87 36585.13 32852.40 29988.13 35160.21 33474.74 37584.73 401
GA-MVS76.87 28075.17 29481.97 24582.75 36862.58 29481.44 34786.35 30572.16 20774.74 30282.89 37746.20 37392.02 25068.85 25981.09 28391.30 208
UWE-MVS72.13 34971.49 33874.03 38686.66 26847.70 44581.40 34876.89 42463.60 36775.59 27284.22 34939.94 41785.62 37948.98 41786.13 20388.77 311
test_fmvs1_n70.86 36070.24 35672.73 40072.51 45855.28 39981.27 34979.71 39951.49 44778.73 19684.87 33327.54 45377.02 43376.06 17479.97 30085.88 382
testing9176.54 28475.66 28379.18 31188.43 18655.89 39081.08 35083.00 35673.76 16875.34 28384.29 34546.20 37390.07 31364.33 29684.50 22991.58 198
testing22274.04 32172.66 32778.19 33087.89 21055.36 39781.06 35179.20 40571.30 22474.65 30583.57 36539.11 42388.67 34251.43 40285.75 21390.53 238
test_fmvs170.93 35970.52 35172.16 40473.71 44755.05 40180.82 35278.77 40851.21 44878.58 20184.41 34131.20 44876.94 43475.88 17880.12 29984.47 403
CostFormer75.24 30973.90 31179.27 30882.65 37258.27 34980.80 35382.73 36261.57 38975.33 28783.13 37255.52 26991.07 29664.98 29278.34 32088.45 321
testing9976.09 29675.12 29579.00 31288.16 19555.50 39680.79 35481.40 37673.30 18475.17 29184.27 34844.48 38890.02 31464.28 29784.22 23891.48 203
MIMVSNet168.58 38366.78 39373.98 38780.07 40851.82 42780.77 35584.37 32964.40 35459.75 44282.16 38936.47 43583.63 39742.73 44570.33 40886.48 369
CL-MVSNet_self_test72.37 34571.46 33975.09 37379.49 41853.53 41380.76 35685.01 32469.12 28870.51 35282.05 39057.92 24884.13 39352.27 39666.00 42787.60 338
testing1175.14 31074.01 30878.53 32488.16 19556.38 38380.74 35780.42 39070.67 24172.69 33183.72 36043.61 39589.86 31662.29 31483.76 24489.36 288
MSDG73.36 33270.99 34780.49 28284.51 32365.80 20780.71 35886.13 30965.70 33865.46 41083.74 35844.60 38690.91 29951.13 40376.89 33584.74 400
tpm273.26 33471.46 33978.63 31883.34 34956.71 37780.65 35980.40 39156.63 43073.55 31982.02 39151.80 31391.24 28756.35 37678.42 31887.95 330
XXY-MVS75.41 30675.56 28474.96 37483.59 34457.82 35980.59 36083.87 33966.54 32974.93 30088.31 23863.24 17280.09 42062.16 31676.85 33786.97 359
test_cas_vis1_n_192073.76 32573.74 31473.81 38975.90 43559.77 33580.51 36182.40 36458.30 41781.62 15085.69 31144.35 39076.41 43976.29 17078.61 31185.23 391
EGC-MVSNET52.07 43147.05 43567.14 43283.51 34660.71 32380.50 36267.75 4540.07 4820.43 48375.85 44424.26 45981.54 41228.82 46562.25 43759.16 465
SDMVSNet80.38 19280.18 17180.99 27089.03 16164.94 23380.45 36389.40 20675.19 12776.61 25289.98 18360.61 22687.69 35776.83 16583.55 25190.33 247
HyFIR lowres test77.53 26875.40 28883.94 17289.59 13066.62 18880.36 36488.64 25256.29 43276.45 25585.17 32757.64 25193.28 18561.34 32683.10 26191.91 187
D2MVS74.82 31273.21 32079.64 30279.81 41262.56 29680.34 36587.35 28164.37 35568.86 37482.66 38146.37 36990.10 31267.91 26681.24 28186.25 371
testing3-275.12 31175.19 29374.91 37590.40 10945.09 45880.29 36678.42 41078.37 4076.54 25487.75 25344.36 38987.28 36257.04 36883.49 25392.37 167
TinyColmap67.30 39364.81 40074.76 37881.92 38356.68 37880.29 36681.49 37560.33 39756.27 45383.22 36924.77 45887.66 35845.52 43769.47 41179.95 442
FE-MVSNET67.25 39465.33 39873.02 39775.86 43652.54 42180.26 36880.56 38563.80 36660.39 43779.70 41741.41 40984.66 39143.34 44362.62 43681.86 431
LCM-MVSNet-Re77.05 27676.94 25977.36 34987.20 24651.60 42980.06 36980.46 38875.20 12667.69 38486.72 28262.48 18688.98 33563.44 30289.25 14191.51 200
test_fmvs268.35 38767.48 38670.98 41569.50 46151.95 42480.05 37076.38 42649.33 45074.65 30584.38 34223.30 46275.40 45074.51 19375.17 37185.60 385
FMVSNet569.50 37567.96 37574.15 38582.97 36455.35 39880.01 37182.12 36762.56 38063.02 42781.53 39436.92 43281.92 41048.42 41974.06 38085.17 394
SCA74.22 31872.33 33179.91 29484.05 33262.17 30479.96 37279.29 40466.30 33172.38 33580.13 41151.95 30988.60 34459.25 34377.67 32888.96 303
tpmrst72.39 34372.13 33373.18 39680.54 40249.91 44079.91 37379.08 40663.11 37071.69 34379.95 41355.32 27082.77 40565.66 28773.89 38286.87 360
PatchmatchNetpermissive73.12 33671.33 34278.49 32683.18 35560.85 32179.63 37478.57 40964.13 35771.73 34279.81 41651.20 32085.97 37557.40 36476.36 35088.66 315
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PatchMatch-RL72.38 34470.90 34876.80 35688.60 17967.38 17179.53 37576.17 42862.75 37869.36 37082.00 39245.51 38184.89 38853.62 38980.58 29178.12 446
CMPMVSbinary51.72 2170.19 36968.16 37176.28 35873.15 45457.55 36579.47 37683.92 33748.02 45256.48 45284.81 33543.13 39786.42 37062.67 31081.81 27784.89 398
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
ETVMVS72.25 34771.05 34675.84 36187.77 22051.91 42579.39 37774.98 43169.26 28273.71 31682.95 37540.82 41486.14 37246.17 43384.43 23489.47 284
GG-mvs-BLEND75.38 37081.59 38755.80 39279.32 37869.63 44867.19 39173.67 44943.24 39688.90 33950.41 40584.50 22981.45 434
LTVRE_ROB69.57 1376.25 29374.54 30281.41 25688.60 17964.38 25179.24 37989.12 22870.76 24069.79 36787.86 25249.09 34893.20 19556.21 37780.16 29686.65 367
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
tpm72.37 34571.71 33674.35 38282.19 37952.00 42379.22 38077.29 42064.56 35272.95 32783.68 36251.35 31783.26 40258.33 35575.80 35487.81 334
mvs5depth69.45 37667.45 38775.46 36973.93 44555.83 39179.19 38183.23 34966.89 31871.63 34483.32 36833.69 44285.09 38559.81 33755.34 45385.46 387
ppachtmachnet_test70.04 37167.34 38978.14 33179.80 41361.13 31579.19 38180.59 38459.16 40965.27 41279.29 42046.75 36587.29 36149.33 41566.72 42286.00 380
USDC70.33 36768.37 36876.21 35980.60 40156.23 38679.19 38186.49 30160.89 39361.29 43485.47 31931.78 44689.47 32553.37 39176.21 35182.94 423
sd_testset77.70 26477.40 24978.60 32089.03 16160.02 33379.00 38485.83 31375.19 12776.61 25289.98 18354.81 27385.46 38262.63 31183.55 25190.33 247
PM-MVS66.41 40064.14 40373.20 39573.92 44656.45 38078.97 38564.96 46263.88 36564.72 41680.24 41019.84 46683.44 40066.24 27964.52 43179.71 443
tpmvs71.09 35769.29 36276.49 35782.04 38056.04 38878.92 38681.37 37764.05 36167.18 39278.28 42949.74 33989.77 31849.67 41372.37 39483.67 413
test_post178.90 3875.43 48148.81 35385.44 38359.25 343
mamv476.81 28178.23 22572.54 40286.12 28165.75 21078.76 38882.07 36864.12 35872.97 32691.02 15767.97 11868.08 46783.04 8978.02 32283.80 412
CHOSEN 1792x268877.63 26775.69 28083.44 18689.98 12268.58 12978.70 38987.50 27856.38 43175.80 27086.84 27858.67 24291.40 28261.58 32385.75 21390.34 246
Syy-MVS68.05 38867.85 37768.67 42684.68 31840.97 46978.62 39073.08 44066.65 32666.74 39879.46 41852.11 30582.30 40732.89 46176.38 34882.75 424
myMVS_eth3d67.02 39566.29 39569.21 42184.68 31842.58 46478.62 39073.08 44066.65 32666.74 39879.46 41831.53 44782.30 40739.43 45376.38 34882.75 424
WBMVS73.43 32972.81 32575.28 37187.91 20950.99 43578.59 39281.31 37865.51 34374.47 30884.83 33446.39 36786.68 36658.41 35377.86 32388.17 328
test-LLR72.94 34072.43 32974.48 38081.35 39358.04 35378.38 39377.46 41666.66 32369.95 36379.00 42348.06 35479.24 42266.13 28084.83 22486.15 374
TESTMET0.1,169.89 37369.00 36572.55 40179.27 42156.85 37378.38 39374.71 43557.64 42368.09 38177.19 43637.75 43076.70 43563.92 29984.09 23984.10 408
test-mter71.41 35470.39 35574.48 38081.35 39358.04 35378.38 39377.46 41660.32 39869.95 36379.00 42336.08 43779.24 42266.13 28084.83 22486.15 374
UBG73.08 33772.27 33275.51 36788.02 20451.29 43378.35 39677.38 41965.52 34173.87 31582.36 38445.55 38086.48 36955.02 38184.39 23588.75 312
Anonymous2023120668.60 38267.80 38071.02 41480.23 40650.75 43778.30 39780.47 38756.79 42966.11 40882.63 38246.35 37078.95 42443.62 44275.70 35583.36 416
tpm cat170.57 36368.31 36977.35 35082.41 37757.95 35678.08 39880.22 39452.04 44368.54 37877.66 43452.00 30887.84 35551.77 39772.07 39986.25 371
myMVS_eth3d2873.62 32673.53 31673.90 38888.20 19347.41 44878.06 39979.37 40274.29 15573.98 31384.29 34544.67 38583.54 39851.47 40087.39 17890.74 229
our_test_369.14 37867.00 39175.57 36579.80 41358.80 34377.96 40077.81 41359.55 40562.90 43078.25 43047.43 35683.97 39451.71 39867.58 42183.93 410
KD-MVS_self_test68.81 38067.59 38572.46 40374.29 44445.45 45377.93 40187.00 28963.12 36963.99 42378.99 42542.32 40284.77 38956.55 37564.09 43287.16 352
WTY-MVS75.65 30175.68 28175.57 36586.40 27456.82 37477.92 40282.40 36465.10 34576.18 26387.72 25463.13 17880.90 41760.31 33381.96 27489.00 301
UWE-MVS-2865.32 40564.93 39966.49 43478.70 42338.55 47177.86 40364.39 46362.00 38764.13 42183.60 36341.44 40876.00 44331.39 46380.89 28584.92 397
test20.0367.45 39166.95 39268.94 42275.48 44044.84 45977.50 40477.67 41466.66 32363.01 42883.80 35647.02 36078.40 42642.53 44768.86 41683.58 414
EPMVS69.02 37968.16 37171.59 40779.61 41649.80 44277.40 40566.93 45662.82 37770.01 36079.05 42145.79 37777.86 43056.58 37475.26 36987.13 353
test_fmvs363.36 41261.82 41567.98 43062.51 47046.96 45177.37 40674.03 43745.24 45567.50 38678.79 42612.16 47472.98 45972.77 21366.02 42683.99 409
gg-mvs-nofinetune69.95 37267.96 37575.94 36083.07 35854.51 40777.23 40770.29 44663.11 37070.32 35562.33 46043.62 39488.69 34153.88 38887.76 17284.62 402
IMVS_040477.16 27576.42 27379.37 30687.13 24963.59 26977.12 40889.33 20970.51 24766.22 40789.03 21450.36 33082.78 40472.56 21785.56 21591.74 191
MDTV_nov1_ep1369.97 35983.18 35553.48 41477.10 40980.18 39660.45 39669.33 37180.44 40548.89 35286.90 36451.60 39978.51 314
icg_test_0407_278.92 23178.93 20878.90 31587.13 24963.59 26976.58 41089.33 20970.51 24777.82 22089.03 21461.84 19781.38 41472.56 21785.56 21591.74 191
LF4IMVS64.02 41062.19 41469.50 42070.90 45953.29 41876.13 41177.18 42152.65 44258.59 44480.98 40023.55 46176.52 43753.06 39366.66 42378.68 445
sss73.60 32773.64 31573.51 39182.80 36755.01 40276.12 41281.69 37262.47 38174.68 30485.85 30957.32 25578.11 42860.86 32980.93 28487.39 343
testgi66.67 39866.53 39467.08 43375.62 43941.69 46875.93 41376.50 42566.11 33265.20 41586.59 29035.72 43874.71 45243.71 44173.38 38984.84 399
CR-MVSNet73.37 33071.27 34479.67 30181.32 39565.19 22275.92 41480.30 39259.92 40272.73 32981.19 39652.50 29786.69 36559.84 33677.71 32587.11 354
RPMNet73.51 32870.49 35282.58 23281.32 39565.19 22275.92 41492.27 8957.60 42472.73 32976.45 43952.30 30095.43 7748.14 42477.71 32587.11 354
MIMVSNet70.69 36269.30 36174.88 37684.52 32256.35 38575.87 41679.42 40164.59 35167.76 38282.41 38341.10 41181.54 41246.64 43181.34 27986.75 364
test0.0.03 168.00 38967.69 38268.90 42377.55 42847.43 44675.70 41772.95 44266.66 32366.56 40082.29 38748.06 35475.87 44544.97 44074.51 37783.41 415
dmvs_re71.14 35670.58 35072.80 39981.96 38159.68 33675.60 41879.34 40368.55 30169.27 37280.72 40449.42 34276.54 43652.56 39577.79 32482.19 429
dmvs_testset62.63 41364.11 40458.19 44478.55 42424.76 48275.28 41965.94 45967.91 31060.34 43876.01 44153.56 28973.94 45731.79 46267.65 42075.88 451
PMMVS69.34 37768.67 36671.35 41175.67 43862.03 30575.17 42073.46 43850.00 44968.68 37579.05 42152.07 30778.13 42761.16 32782.77 26473.90 453
UnsupCasMVSNet_eth67.33 39265.99 39671.37 40973.48 45051.47 43175.16 42185.19 31965.20 34460.78 43680.93 40342.35 40177.20 43257.12 36653.69 45585.44 388
MDTV_nov1_ep13_2view37.79 47275.16 42155.10 43566.53 40149.34 34453.98 38787.94 331
pmmvs357.79 42054.26 42568.37 42764.02 46956.72 37675.12 42365.17 46040.20 46152.93 45769.86 45720.36 46575.48 44845.45 43855.25 45472.90 455
dp66.80 39665.43 39770.90 41679.74 41548.82 44475.12 42374.77 43359.61 40464.08 42277.23 43542.89 39880.72 41848.86 41866.58 42483.16 418
Patchmtry70.74 36169.16 36475.49 36880.72 39954.07 41074.94 42580.30 39258.34 41670.01 36081.19 39652.50 29786.54 36753.37 39171.09 40585.87 383
ttmdpeth59.91 41857.10 42268.34 42867.13 46546.65 45274.64 42667.41 45548.30 45162.52 43285.04 33220.40 46475.93 44442.55 44645.90 46682.44 426
SSC-MVS3.273.35 33373.39 31773.23 39285.30 30249.01 44374.58 42781.57 37375.21 12573.68 31785.58 31652.53 29582.05 40954.33 38677.69 32788.63 317
PVSNet64.34 1872.08 35070.87 34975.69 36386.21 27756.44 38174.37 42880.73 38262.06 38670.17 35882.23 38842.86 39983.31 40154.77 38384.45 23387.32 346
WB-MVS54.94 42354.72 42455.60 45073.50 44920.90 48474.27 42961.19 46759.16 40950.61 45974.15 44747.19 35975.78 44617.31 47535.07 46970.12 457
MDA-MVSNet-bldmvs66.68 39763.66 40775.75 36279.28 42060.56 32673.92 43078.35 41164.43 35350.13 46179.87 41544.02 39283.67 39646.10 43456.86 44783.03 421
SSC-MVS53.88 42653.59 42654.75 45272.87 45519.59 48573.84 43160.53 46957.58 42549.18 46373.45 45046.34 37175.47 44916.20 47832.28 47169.20 458
UnsupCasMVSNet_bld63.70 41161.53 41770.21 41873.69 44851.39 43272.82 43281.89 36955.63 43457.81 44871.80 45338.67 42578.61 42549.26 41652.21 45880.63 439
PatchT68.46 38667.85 37770.29 41780.70 40043.93 46172.47 43374.88 43260.15 40070.55 35176.57 43849.94 33681.59 41150.58 40474.83 37485.34 389
miper_lstm_enhance74.11 32073.11 32277.13 35380.11 40759.62 33772.23 43486.92 29366.76 32170.40 35482.92 37656.93 26082.92 40369.06 25672.63 39388.87 306
MVS-HIRNet59.14 41957.67 42163.57 43881.65 38543.50 46271.73 43565.06 46139.59 46351.43 45857.73 46638.34 42782.58 40639.53 45173.95 38164.62 462
MVStest156.63 42252.76 42868.25 42961.67 47153.25 41971.67 43668.90 45338.59 46450.59 46083.05 37325.08 45670.66 46136.76 45738.56 46780.83 438
APD_test153.31 42849.93 43363.42 43965.68 46650.13 43971.59 43766.90 45734.43 46940.58 46871.56 4548.65 47976.27 44034.64 46055.36 45263.86 463
Patchmatch-RL test70.24 36867.78 38177.61 34577.43 42959.57 33971.16 43870.33 44562.94 37468.65 37672.77 45150.62 32685.49 38169.58 25166.58 42487.77 335
test1236.12 4508.11 4530.14 4650.06 4890.09 49071.05 4390.03 4900.04 4840.25 4851.30 4840.05 4870.03 4850.21 4840.01 4830.29 480
ANet_high50.57 43346.10 43763.99 43748.67 48239.13 47070.99 44080.85 38061.39 39131.18 47157.70 46717.02 46973.65 45831.22 46415.89 47979.18 444
KD-MVS_2432*160066.22 40263.89 40573.21 39375.47 44153.42 41570.76 44184.35 33064.10 35966.52 40278.52 42734.55 44084.98 38650.40 40650.33 46081.23 435
miper_refine_blended66.22 40263.89 40573.21 39375.47 44153.42 41570.76 44184.35 33064.10 35966.52 40278.52 42734.55 44084.98 38650.40 40650.33 46081.23 435
test_vis1_rt60.28 41758.42 42065.84 43567.25 46455.60 39570.44 44360.94 46844.33 45759.00 44366.64 45824.91 45768.67 46562.80 30669.48 41073.25 454
testmvs6.04 4518.02 4540.10 4660.08 4880.03 49169.74 4440.04 4890.05 4830.31 4841.68 4830.02 4880.04 4840.24 4830.02 4820.25 481
N_pmnet52.79 42953.26 42751.40 45478.99 4227.68 48869.52 4453.89 48751.63 44657.01 45074.98 44640.83 41365.96 46937.78 45564.67 43080.56 441
FPMVS53.68 42751.64 42959.81 44365.08 46751.03 43469.48 44669.58 44941.46 46040.67 46772.32 45216.46 47070.00 46424.24 47165.42 42858.40 467
DSMNet-mixed57.77 42156.90 42360.38 44267.70 46335.61 47369.18 44753.97 47432.30 47257.49 44979.88 41440.39 41668.57 46638.78 45472.37 39476.97 448
new-patchmatchnet61.73 41561.73 41661.70 44072.74 45624.50 48369.16 44878.03 41261.40 39056.72 45175.53 44538.42 42676.48 43845.95 43557.67 44684.13 407
YYNet165.03 40662.91 41171.38 40875.85 43756.60 37969.12 44974.66 43657.28 42754.12 45577.87 43245.85 37674.48 45349.95 41161.52 44083.05 420
MDA-MVSNet_test_wron65.03 40662.92 41071.37 40975.93 43456.73 37569.09 45074.73 43457.28 42754.03 45677.89 43145.88 37574.39 45449.89 41261.55 43982.99 422
PVSNet_057.27 2061.67 41659.27 41968.85 42479.61 41657.44 36768.01 45173.44 43955.93 43358.54 44570.41 45644.58 38777.55 43147.01 42835.91 46871.55 456
dongtai45.42 43745.38 43845.55 45673.36 45226.85 48067.72 45234.19 48254.15 43849.65 46256.41 46925.43 45562.94 47219.45 47328.09 47346.86 472
ADS-MVSNet266.20 40463.33 40874.82 37779.92 40958.75 34467.55 45375.19 43053.37 44065.25 41375.86 44242.32 40280.53 41941.57 44868.91 41485.18 392
ADS-MVSNet64.36 40962.88 41268.78 42579.92 40947.17 44967.55 45371.18 44453.37 44065.25 41375.86 44242.32 40273.99 45641.57 44868.91 41485.18 392
mvsany_test162.30 41461.26 41865.41 43669.52 46054.86 40366.86 45549.78 47646.65 45368.50 37983.21 37049.15 34766.28 46856.93 37060.77 44175.11 452
LCM-MVSNet54.25 42449.68 43467.97 43153.73 47945.28 45666.85 45680.78 38135.96 46839.45 46962.23 4628.70 47878.06 42948.24 42351.20 45980.57 440
test_vis3_rt49.26 43447.02 43656.00 44754.30 47645.27 45766.76 45748.08 47736.83 46644.38 46553.20 4707.17 48164.07 47056.77 37355.66 45058.65 466
testf145.72 43541.96 43957.00 44556.90 47345.32 45466.14 45859.26 47026.19 47330.89 47260.96 4644.14 48270.64 46226.39 46946.73 46455.04 468
APD_test245.72 43541.96 43957.00 44556.90 47345.32 45466.14 45859.26 47026.19 47330.89 47260.96 4644.14 48270.64 46226.39 46946.73 46455.04 468
kuosan39.70 44140.40 44237.58 45964.52 46826.98 47865.62 46033.02 48346.12 45442.79 46648.99 47224.10 46046.56 48012.16 48126.30 47439.20 473
JIA-IIPM66.32 40162.82 41376.82 35577.09 43261.72 31165.34 46175.38 42958.04 42164.51 41862.32 46142.05 40686.51 36851.45 40169.22 41382.21 428
PMVScopyleft37.38 2244.16 43940.28 44355.82 44940.82 48442.54 46665.12 46263.99 46434.43 46924.48 47557.12 4683.92 48476.17 44217.10 47655.52 45148.75 470
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
mamba_040879.37 21977.52 24684.93 11088.81 16767.96 14965.03 46388.66 24970.96 23579.48 18489.80 18958.69 24094.65 11970.35 24085.93 20892.18 178
SSM_0407277.67 26677.52 24678.12 33288.81 16767.96 14965.03 46388.66 24970.96 23579.48 18489.80 18958.69 24074.23 45570.35 24085.93 20892.18 178
new_pmnet50.91 43250.29 43252.78 45368.58 46234.94 47563.71 46556.63 47339.73 46244.95 46465.47 45921.93 46358.48 47334.98 45956.62 44864.92 461
mvsany_test353.99 42551.45 43061.61 44155.51 47544.74 46063.52 46645.41 48043.69 45858.11 44776.45 43917.99 46763.76 47154.77 38347.59 46276.34 450
Patchmatch-test64.82 40863.24 40969.57 41979.42 41949.82 44163.49 46769.05 45151.98 44559.95 44180.13 41150.91 32270.98 46040.66 45073.57 38587.90 332
ambc75.24 37273.16 45350.51 43863.05 46887.47 27964.28 41977.81 43317.80 46889.73 32057.88 36060.64 44285.49 386
test_f52.09 43050.82 43155.90 44853.82 47842.31 46759.42 46958.31 47236.45 46756.12 45470.96 45512.18 47357.79 47453.51 39056.57 44967.60 459
CHOSEN 280x42066.51 39964.71 40171.90 40581.45 39063.52 27457.98 47068.95 45253.57 43962.59 43176.70 43746.22 37275.29 45155.25 37979.68 30176.88 449
E-PMN31.77 44230.64 44535.15 46052.87 48027.67 47757.09 47147.86 47824.64 47516.40 48033.05 47611.23 47554.90 47614.46 47918.15 47722.87 476
EMVS30.81 44429.65 44634.27 46150.96 48125.95 48156.58 47246.80 47924.01 47615.53 48130.68 47712.47 47254.43 47712.81 48017.05 47822.43 477
PMMVS240.82 44038.86 44446.69 45553.84 47716.45 48648.61 47349.92 47537.49 46531.67 47060.97 4638.14 48056.42 47528.42 46630.72 47267.19 460
wuyk23d16.82 44815.94 45119.46 46358.74 47231.45 47639.22 4743.74 4886.84 4796.04 4822.70 4821.27 48624.29 48210.54 48214.40 4812.63 479
tmp_tt18.61 44721.40 45010.23 4644.82 48710.11 48734.70 47530.74 4851.48 48123.91 47726.07 47828.42 45213.41 48327.12 46715.35 4807.17 478
Gipumacopyleft45.18 43841.86 44155.16 45177.03 43351.52 43032.50 47680.52 38632.46 47127.12 47435.02 4759.52 47775.50 44722.31 47260.21 44438.45 474
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
MVEpermissive26.22 2330.37 44525.89 44943.81 45744.55 48335.46 47428.87 47739.07 48118.20 47718.58 47940.18 4742.68 48547.37 47917.07 47723.78 47648.60 471
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
test_method31.52 44329.28 44738.23 45827.03 4866.50 48920.94 47862.21 4664.05 48022.35 47852.50 47113.33 47147.58 47827.04 46834.04 47060.62 464
mmdepth0.00 4530.00 4560.00 4670.00 4900.00 4920.00 4790.00 4910.00 4850.00 4860.00 4850.00 4890.00 4860.00 4850.00 4840.00 482
monomultidepth0.00 4530.00 4560.00 4670.00 4900.00 4920.00 4790.00 4910.00 4850.00 4860.00 4850.00 4890.00 4860.00 4850.00 4840.00 482
test_blank0.00 4530.00 4560.00 4670.00 4900.00 4920.00 4790.00 4910.00 4850.00 4860.00 4850.00 4890.00 4860.00 4850.00 4840.00 482
uanet_test0.00 4530.00 4560.00 4670.00 4900.00 4920.00 4790.00 4910.00 4850.00 4860.00 4850.00 4890.00 4860.00 4850.00 4840.00 482
DCPMVS0.00 4530.00 4560.00 4670.00 4900.00 4920.00 4790.00 4910.00 4850.00 4860.00 4850.00 4890.00 4860.00 4850.00 4840.00 482
cdsmvs_eth3d_5k19.96 44626.61 4480.00 4670.00 4900.00 4920.00 47989.26 2180.00 4850.00 48688.61 22961.62 2030.00 4860.00 4850.00 4840.00 482
pcd_1.5k_mvsjas5.26 4527.02 4550.00 4670.00 4900.00 4920.00 4790.00 4910.00 4850.00 4860.00 48563.15 1750.00 4860.00 4850.00 4840.00 482
sosnet-low-res0.00 4530.00 4560.00 4670.00 4900.00 4920.00 4790.00 4910.00 4850.00 4860.00 4850.00 4890.00 4860.00 4850.00 4840.00 482
sosnet0.00 4530.00 4560.00 4670.00 4900.00 4920.00 4790.00 4910.00 4850.00 4860.00 4850.00 4890.00 4860.00 4850.00 4840.00 482
uncertanet0.00 4530.00 4560.00 4670.00 4900.00 4920.00 4790.00 4910.00 4850.00 4860.00 4850.00 4890.00 4860.00 4850.00 4840.00 482
Regformer0.00 4530.00 4560.00 4670.00 4900.00 4920.00 4790.00 4910.00 4850.00 4860.00 4850.00 4890.00 4860.00 4850.00 4840.00 482
ab-mvs-re7.23 4499.64 4520.00 4670.00 4900.00 4920.00 4790.00 4910.00 4850.00 48686.72 2820.00 4890.00 4860.00 4850.00 4840.00 482
uanet0.00 4530.00 4560.00 4670.00 4900.00 4920.00 4790.00 4910.00 4850.00 4860.00 4850.00 4890.00 4860.00 4850.00 4840.00 482
WAC-MVS42.58 46439.46 452
MSC_two_6792asdad89.16 194.34 3175.53 292.99 5497.53 289.67 1596.44 994.41 53
PC_three_145268.21 30792.02 1594.00 6382.09 595.98 6184.58 7196.68 294.95 12
No_MVS89.16 194.34 3175.53 292.99 5497.53 289.67 1596.44 994.41 53
test_one_060195.07 771.46 5994.14 1078.27 4192.05 1495.74 680.83 13
eth-test20.00 490
eth-test0.00 490
ZD-MVS94.38 2972.22 4692.67 7270.98 23487.75 5094.07 5874.01 3696.70 3184.66 7094.84 48
IU-MVS95.30 271.25 6492.95 6066.81 31992.39 688.94 2896.63 494.85 21
test_241102_TWO94.06 1577.24 6192.78 495.72 881.26 1097.44 789.07 2596.58 694.26 64
test_241102_ONE95.30 270.98 7194.06 1577.17 6493.10 195.39 1682.99 197.27 15
test_0728_THIRD78.38 3892.12 1295.78 481.46 997.40 989.42 1996.57 794.67 33
GSMVS88.96 303
test_part295.06 872.65 3291.80 16
sam_mvs151.32 31888.96 303
sam_mvs50.01 334
MTGPAbinary92.02 106
test_post5.46 48050.36 33084.24 392
patchmatchnet-post74.00 44851.12 32188.60 344
gm-plane-assit81.40 39153.83 41262.72 37980.94 40192.39 23563.40 303
test9_res84.90 6495.70 3092.87 146
agg_prior282.91 9195.45 3392.70 151
agg_prior92.85 6871.94 5291.78 12284.41 9594.93 101
TestCases79.58 30385.15 30663.62 26579.83 39762.31 38260.32 43986.73 28032.02 44488.96 33750.28 40871.57 40286.15 374
test_prior86.33 6492.61 7469.59 9892.97 5995.48 7493.91 81
新几何183.42 18793.13 6070.71 8085.48 31757.43 42681.80 14591.98 11563.28 16992.27 24164.60 29592.99 7687.27 348
旧先验191.96 8065.79 20886.37 30493.08 9269.31 9892.74 8088.74 314
原ACMM184.35 13493.01 6668.79 11792.44 8263.96 36481.09 15891.57 13466.06 14595.45 7567.19 27494.82 5088.81 309
testdata291.01 29762.37 313
segment_acmp73.08 43
testdata79.97 29390.90 9864.21 25384.71 32559.27 40885.40 7592.91 9462.02 19689.08 33368.95 25791.37 10586.63 368
test1286.80 5892.63 7370.70 8191.79 12182.71 13271.67 6396.16 5294.50 5793.54 110
plane_prior790.08 11668.51 131
plane_prior689.84 12568.70 12560.42 229
plane_prior592.44 8295.38 8278.71 13986.32 19791.33 206
plane_prior491.00 158
plane_prior368.60 12878.44 3678.92 194
plane_prior189.90 124
n20.00 491
nn0.00 491
door-mid69.98 447
lessismore_v078.97 31381.01 39857.15 37065.99 45861.16 43582.82 37939.12 42291.34 28459.67 33846.92 46388.43 322
LGP-MVS_train84.50 12589.23 15268.76 11991.94 11275.37 11876.64 25091.51 13654.29 28194.91 10278.44 14183.78 24289.83 274
test1192.23 92
door69.44 450
HQP5-MVS66.98 183
BP-MVS77.47 154
HQP4-MVS77.24 23495.11 9491.03 216
HQP3-MVS92.19 10085.99 206
HQP2-MVS60.17 232
NP-MVS89.62 12968.32 13590.24 179
ACMMP++_ref81.95 275
ACMMP++81.25 280
Test By Simon64.33 161
ITE_SJBPF78.22 32981.77 38460.57 32583.30 34769.25 28367.54 38587.20 27136.33 43687.28 36254.34 38574.62 37686.80 362
DeepMVS_CXcopyleft27.40 46240.17 48526.90 47924.59 48617.44 47823.95 47648.61 4739.77 47626.48 48118.06 47424.47 47528.83 475