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 6991.52 5694.75 173.93 16588.57 3594.67 3075.57 2595.79 6386.77 5195.76 27
SF-MVS88.46 1588.74 1587.64 3892.78 7071.95 5192.40 2994.74 275.71 10889.16 2995.10 1875.65 2496.19 5187.07 4996.01 1794.79 23
MED-MVS test87.86 2694.57 1771.43 6093.28 1294.36 375.24 12292.25 995.03 2097.39 1188.15 3995.96 1994.75 30
MED-MVS89.59 490.16 487.86 2694.57 1771.43 6093.28 1294.36 376.30 9492.25 995.03 2081.59 797.39 1188.15 3995.96 1994.75 30
TestfortrainingZip a89.27 789.82 787.60 3994.57 1770.90 7793.28 1294.36 375.24 12292.25 995.03 2081.59 797.39 1186.12 5795.96 1994.52 50
ME-MVS88.98 1289.39 987.75 3094.54 2071.43 6091.61 4994.25 676.30 9490.62 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 6495.06 194.23 778.38 3892.78 495.74 682.45 397.49 489.42 1996.68 294.95 12
test_0728_SECOND87.71 3595.34 171.43 6093.49 1094.23 797.49 489.08 2296.41 1294.21 66
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 97
test_one_060195.07 771.46 5994.14 1078.27 4192.05 1495.74 680.83 13
test072695.27 571.25 6493.60 794.11 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 34
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 10392.29 795.66 1081.67 697.38 1487.44 4896.34 1593.95 81
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 4690.88 9970.96 7392.27 3794.07 1472.45 20085.22 7891.90 11869.47 9596.42 4483.28 8695.94 2394.35 59
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
test_241102_TWO94.06 1577.24 6192.78 495.72 881.26 1097.44 789.07 2596.58 694.26 65
test_241102_ONE95.30 270.98 7194.06 1577.17 6493.10 195.39 1682.99 197.27 15
APDe-MVScopyleft89.15 989.63 887.73 3194.49 2271.69 5493.83 493.96 1875.70 11091.06 1996.03 176.84 1797.03 2189.09 2195.65 3194.47 53
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 9172.32 4590.31 7993.94 1977.12 6782.82 13194.23 5072.13 5697.09 1984.83 6795.37 3593.65 102
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 14991.30 18
MCST-MVS87.37 3487.25 3587.73 3194.53 2172.46 4089.82 8893.82 2173.07 19284.86 8592.89 9576.22 2096.33 4584.89 6695.13 4094.40 56
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 62
SPE-MVS-test86.29 5486.48 5185.71 8091.02 9567.21 18092.36 3493.78 2378.97 3383.51 11691.20 14970.65 7895.15 9181.96 10294.89 4694.77 25
3Dnovator+77.84 485.48 7384.47 9288.51 791.08 9373.49 1693.18 1693.78 2380.79 876.66 25093.37 8360.40 23296.75 3077.20 15893.73 7095.29 6
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.
SMA-MVScopyleft89.08 1089.23 1088.61 694.25 3573.73 992.40 2993.63 2674.77 14392.29 795.97 274.28 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
EC-MVSNet86.01 5886.38 5284.91 11289.31 14766.27 19492.32 3593.63 2679.37 2384.17 10291.88 11969.04 10595.43 7783.93 8193.77 6993.01 141
ACMMP_NAP88.05 2088.08 2187.94 1993.70 4573.05 2290.86 6593.59 2876.27 9688.14 4195.09 1971.06 7296.67 3387.67 4496.37 1494.09 73
CSCG86.41 5186.19 5887.07 5092.91 6772.48 3790.81 6693.56 2973.95 16383.16 12391.07 15475.94 2195.19 8979.94 12494.38 6293.55 110
MP-MVS-pluss87.67 2587.72 2587.54 4093.64 4872.04 5089.80 9093.50 3075.17 13086.34 6895.29 1770.86 7496.00 5988.78 3196.04 1694.58 43
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
FIs82.07 14482.42 12981.04 27088.80 17158.34 34988.26 16193.49 3176.93 7278.47 20791.04 15569.92 8992.34 24069.87 24984.97 22392.44 167
DELS-MVS85.41 7685.30 8085.77 7988.49 18267.93 15285.52 26493.44 3278.70 3483.63 11589.03 21574.57 2795.71 6680.26 12194.04 6793.66 98
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 8693.99 6570.67 7796.82 2684.18 7995.01 4193.90 84
FC-MVSNet-test81.52 16082.02 14180.03 29388.42 18755.97 38987.95 17293.42 3477.10 6877.38 23190.98 16169.96 8891.79 26068.46 26484.50 23092.33 170
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 43
HPM-MVScopyleft87.11 3886.98 4187.50 4393.88 4372.16 4792.19 3893.33 3676.07 10083.81 11093.95 6869.77 9296.01 5885.15 6294.66 5194.32 62
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
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
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 98
ACMMPR87.44 2987.23 3688.08 1594.64 1373.59 1293.04 1793.20 3976.78 7784.66 8994.52 3268.81 10796.65 3484.53 7294.90 4594.00 78
reproduce_model87.28 3587.39 3386.95 5493.10 6271.24 6891.60 5093.19 4074.69 14488.80 3395.61 1170.29 8196.44 4386.20 5693.08 7593.16 129
reproduce-ours87.47 2787.61 2787.07 5093.27 5471.60 5591.56 5493.19 4074.98 13488.96 3095.54 1271.20 7096.54 4086.28 5493.49 7193.06 136
our_new_method87.47 2787.61 2787.07 5093.27 5471.60 5591.56 5493.19 4074.98 13488.96 3095.54 1271.20 7096.54 4086.28 5493.49 7193.06 136
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 6593.65 102
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 4476.78 7780.73 16893.82 7264.33 16296.29 4682.67 9990.69 11693.23 122
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 4576.73 8084.45 9494.52 3269.09 10196.70 3184.37 7494.83 4994.03 76
DPM-MVS84.93 8684.29 9386.84 5690.20 11373.04 2387.12 20093.04 4669.80 26982.85 13091.22 14873.06 4496.02 5776.72 17094.63 5491.46 206
PGM-MVS86.68 4586.27 5587.90 2294.22 3773.38 1890.22 8193.04 4675.53 11383.86 10894.42 4067.87 12296.64 3582.70 9894.57 5693.66 98
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
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 68
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 15681.11 15283.09 20388.38 18864.41 25187.60 18393.02 5078.42 3778.56 20388.16 24469.78 9193.26 18969.58 25276.49 34391.60 197
sasdasda85.91 6385.87 6786.04 7489.84 12569.44 10590.45 7693.00 5176.70 8188.01 4591.23 14573.28 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 14573.28 4093.91 15281.50 10588.80 15094.77 25
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 60
MSC_two_6792asdad89.16 194.34 3175.53 292.99 5497.53 289.67 1596.44 994.41 54
No_MVS89.16 194.34 3175.53 292.99 5497.53 289.67 1596.44 994.41 54
XVS87.18 3786.91 4488.00 1794.42 2473.33 1992.78 2392.99 5479.14 2683.67 11394.17 5367.45 12596.60 3783.06 8794.50 5794.07 74
X-MVStestdata80.37 19577.83 23588.00 1794.42 2473.33 1992.78 2392.99 5479.14 2683.67 11312.47 47967.45 12596.60 3783.06 8794.50 5794.07 74
APD-MVS_3200maxsize85.97 6185.88 6586.22 6792.69 7269.53 9991.93 4292.99 5473.54 17685.94 6994.51 3565.80 15095.61 6783.04 8992.51 8393.53 112
test_prior86.33 6492.61 7469.59 9892.97 5995.48 7493.91 82
IU-MVS95.30 271.25 6492.95 6066.81 31992.39 688.94 2896.63 494.85 21
balanced_conf0386.78 4286.99 4086.15 7091.24 9067.61 16290.51 7092.90 6177.26 6087.44 5691.63 13171.27 6996.06 5485.62 6095.01 4194.78 24
baseline84.93 8684.98 8384.80 11787.30 24565.39 21887.30 19692.88 6277.62 4784.04 10592.26 10871.81 5993.96 14481.31 10790.30 12295.03 11
MSLP-MVS++85.43 7585.76 6984.45 12891.93 8170.24 8590.71 6792.86 6377.46 5584.22 10092.81 9967.16 12992.94 21180.36 11994.35 6390.16 254
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 4796.44 993.05 138
casdiffmvspermissive85.11 8385.14 8285.01 10587.20 24765.77 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
APD-MVScopyleft87.44 2987.52 3087.19 4794.24 3672.39 4191.86 4592.83 6573.01 19488.58 3494.52 3273.36 3896.49 4284.26 7595.01 4192.70 152
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 6581.50 585.79 7293.47 8073.02 4597.00 2284.90 6494.94 4494.10 72
CP-MVS87.11 3886.92 4387.68 3794.20 3873.86 793.98 392.82 6876.62 8383.68 11294.46 3667.93 12095.95 6284.20 7894.39 6193.23 122
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 1293.33 119
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 11482.64 12686.16 6988.14 19768.45 13289.13 12192.69 7072.82 19883.71 11191.86 12155.69 26995.35 8680.03 12289.74 13494.69 33
EIA-MVS83.31 12382.80 12384.82 11589.59 13065.59 21388.21 16292.68 7174.66 14678.96 19386.42 29869.06 10395.26 8775.54 18490.09 12693.62 105
ZD-MVS94.38 2972.22 4692.67 7270.98 23587.75 5094.07 5874.01 3696.70 3184.66 7094.84 48
nrg03083.88 10083.53 10984.96 10786.77 26569.28 10990.46 7592.67 7274.79 14282.95 12691.33 14472.70 5093.09 20480.79 11579.28 30992.50 162
WR-MVS_H78.51 24278.49 21678.56 32388.02 20456.38 38388.43 15192.67 7277.14 6573.89 31587.55 26266.25 14189.24 33058.92 34873.55 38790.06 264
MVSMamba_PlusPlus85.99 5985.96 6486.05 7391.09 9267.64 16189.63 9792.65 7572.89 19784.64 9091.71 12671.85 5896.03 5584.77 6994.45 6094.49 52
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 3993.62 105
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 8689.39 14268.66 12788.74 14092.64 7779.97 1684.10 10385.71 31169.32 9895.38 8280.82 11391.37 10592.72 151
MGCFI-Net85.06 8585.51 7483.70 17989.42 13963.01 28789.43 10492.62 7876.43 8587.53 5391.34 14372.82 4993.42 18381.28 10888.74 15394.66 37
CANet86.45 4886.10 6187.51 4290.09 11570.94 7589.70 9492.59 7981.78 481.32 15491.43 14170.34 7997.23 1784.26 7593.36 7494.37 58
SR-MVS86.73 4386.67 4886.91 5594.11 4172.11 4992.37 3392.56 8074.50 14886.84 6494.65 3167.31 12795.77 6484.80 6892.85 7892.84 150
alignmvs85.48 7385.32 7985.96 7789.51 13469.47 10289.74 9292.47 8176.17 9887.73 5291.46 14070.32 8093.78 15881.51 10488.95 14794.63 40
原ACMM184.35 13593.01 6668.79 11792.44 8263.96 36481.09 15991.57 13566.06 14695.45 7567.19 27594.82 5088.81 310
HQP_MVS83.64 11083.14 11585.14 9890.08 11668.71 12391.25 6092.44 8279.12 2878.92 19591.00 15960.42 23095.38 8278.71 14086.32 19891.33 207
plane_prior592.44 8295.38 8278.71 14086.32 19891.33 207
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 13695.43 3494.28 64
UniMVSNet_NR-MVSNet81.88 14881.54 14782.92 21488.46 18463.46 27787.13 19992.37 8680.19 1278.38 20889.14 21171.66 6493.05 20770.05 24576.46 34492.25 174
TSAR-MVS + MP.88.02 2188.11 2087.72 3393.68 4772.13 4891.41 5892.35 8774.62 14788.90 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
CLD-MVS82.31 14081.65 14684.29 14188.47 18367.73 15885.81 25492.35 8775.78 10678.33 21086.58 29364.01 16594.35 12876.05 17687.48 17890.79 226
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
SR-MVS-dyc-post85.77 6785.61 7286.23 6693.06 6470.63 8291.88 4392.27 8973.53 17785.69 7394.45 3765.00 15895.56 6882.75 9491.87 9592.50 162
RE-MVS-def85.48 7593.06 6470.63 8291.88 4392.27 8973.53 17785.69 7394.45 3763.87 16682.75 9491.87 9592.50 162
RPMNet73.51 32970.49 35382.58 23381.32 39665.19 22275.92 41492.27 8957.60 42472.73 33076.45 43952.30 30195.43 7748.14 42477.71 32687.11 355
E484.10 9483.99 9784.45 12887.58 23564.99 23086.54 22692.25 9276.38 9083.37 11792.09 11569.88 9093.58 16679.78 12688.03 16794.77 25
E284.00 9783.87 9884.39 13187.70 22664.95 23186.40 23392.23 9375.85 10483.21 11991.78 12370.09 8593.55 17179.52 12988.05 16594.66 37
E384.00 9783.87 9884.39 13187.70 22664.95 23186.40 23392.23 9375.85 10483.21 11991.78 12370.09 8593.55 17179.52 12988.05 16594.66 37
test1192.23 93
viewcassd2359sk1183.89 9983.74 10384.34 13687.76 22164.91 23786.30 23792.22 9675.47 11583.04 12591.52 13670.15 8393.53 17479.26 13187.96 16894.57 45
mPP-MVS86.67 4686.32 5387.72 3394.41 2673.55 1392.74 2592.22 9676.87 7482.81 13294.25 4966.44 13896.24 4982.88 9294.28 6493.38 115
fmvsm_s_conf0.5_n_886.56 4787.17 3884.73 12087.76 22165.62 21289.20 11492.21 9879.94 1789.74 2794.86 2668.63 11094.20 13690.83 591.39 10494.38 57
E3new83.78 10483.60 10784.31 13887.76 22164.89 23886.24 24092.20 9975.15 13182.87 12891.23 14570.11 8493.52 17679.05 13287.79 17194.51 51
DP-MVS Recon83.11 12882.09 13986.15 7094.44 2370.92 7688.79 13592.20 9970.53 24779.17 19191.03 15764.12 16496.03 5568.39 26590.14 12591.50 202
NormalMVS86.29 5485.88 6587.52 4193.26 5672.47 3891.65 4792.19 10179.31 2484.39 9692.18 10964.64 16095.53 7180.70 11694.65 5294.56 47
Elysia81.53 15880.16 17385.62 8485.51 29668.25 13988.84 13392.19 10171.31 22380.50 17189.83 18846.89 36394.82 10876.85 16389.57 13693.80 92
StellarMVS81.53 15880.16 17385.62 8485.51 29668.25 13988.84 13392.19 10171.31 22380.50 17189.83 18846.89 36394.82 10876.85 16389.57 13693.80 92
HQP3-MVS92.19 10185.99 207
HQP-MVS82.61 13682.02 14184.37 13389.33 14466.98 18389.17 11692.19 10176.41 8677.23 23690.23 18160.17 23395.11 9477.47 15585.99 20791.03 217
3Dnovator76.31 583.38 11982.31 13386.59 6187.94 20872.94 2890.64 6892.14 10677.21 6375.47 27692.83 9758.56 24494.72 11573.24 20992.71 8192.13 184
MTGPAbinary92.02 107
MTAPA87.23 3687.00 3987.90 2294.18 3974.25 586.58 22492.02 10779.45 2285.88 7094.80 2768.07 11896.21 5086.69 5295.34 3693.23 122
MVS_Test83.15 12583.06 11783.41 19086.86 26063.21 28386.11 24492.00 10974.31 15482.87 12889.44 20870.03 8793.21 19377.39 15788.50 15893.81 90
PVSNet_BlendedMVS80.60 18680.02 17782.36 23788.85 16365.40 21686.16 24392.00 10969.34 28078.11 21586.09 30666.02 14794.27 13171.52 22782.06 27487.39 344
PVSNet_Blended80.98 16980.34 16882.90 21588.85 16365.40 21684.43 29392.00 10967.62 31278.11 21585.05 33266.02 14794.27 13171.52 22789.50 13889.01 300
QAPM80.88 17179.50 19485.03 10488.01 20668.97 11491.59 5192.00 10966.63 32875.15 29492.16 11157.70 25195.45 7563.52 30188.76 15290.66 233
LPG-MVS_test82.08 14381.27 14984.50 12589.23 15268.76 11990.22 8191.94 11375.37 11976.64 25191.51 13754.29 28294.91 10278.44 14283.78 24389.83 275
LGP-MVS_train84.50 12589.23 15268.76 11991.94 11375.37 11976.64 25191.51 13754.29 28294.91 10278.44 14283.78 24389.83 275
TEST993.26 5672.96 2588.75 13891.89 11568.44 30485.00 8093.10 8874.36 3295.41 80
train_agg86.43 4986.20 5687.13 4993.26 5672.96 2588.75 13891.89 11568.69 29985.00 8093.10 8874.43 3095.41 8084.97 6395.71 2993.02 140
dcpmvs_285.63 7086.15 6084.06 16091.71 8464.94 23486.47 22891.87 11773.63 17286.60 6793.02 9376.57 1891.87 25983.36 8492.15 9095.35 3
DU-MVS81.12 16880.52 16482.90 21587.80 21563.46 27787.02 20491.87 11779.01 3178.38 20889.07 21365.02 15693.05 20770.05 24576.46 34492.20 177
test_893.13 6072.57 3588.68 14391.84 11968.69 29984.87 8493.10 8874.43 3095.16 90
viewmacassd2359aftdt83.76 10583.66 10684.07 15786.59 27164.56 24386.88 21191.82 12075.72 10783.34 11892.15 11368.24 11792.88 21479.05 13289.15 14594.77 25
PAPM_NR83.02 12982.41 13084.82 11592.47 7666.37 19287.93 17491.80 12173.82 16777.32 23390.66 16767.90 12194.90 10470.37 24089.48 13993.19 128
test1286.80 5892.63 7370.70 8191.79 12282.71 13371.67 6396.16 5294.50 5793.54 111
agg_prior92.85 6871.94 5291.78 12384.41 9594.93 101
PAPR81.66 15580.89 15783.99 17090.27 11164.00 25786.76 21891.77 12468.84 29777.13 24389.50 20167.63 12394.88 10667.55 27088.52 15793.09 134
viewmanbaseed2359cas83.66 10883.55 10884.00 16886.81 26364.53 24486.65 22191.75 12574.89 13883.15 12491.68 12768.74 10992.83 21879.02 13489.24 14294.63 40
PVSNet_Blended_VisFu82.62 13581.83 14584.96 10790.80 10169.76 9788.74 14091.70 12669.39 27878.96 19388.46 23565.47 15294.87 10774.42 19588.57 15590.24 252
viewdifsd2359ckpt0983.34 12082.55 12885.70 8187.64 23067.72 15988.43 15191.68 12771.91 21281.65 15090.68 16667.10 13094.75 11376.17 17387.70 17494.62 42
KinetiMVS83.31 12382.61 12785.39 9187.08 25667.56 16588.06 16891.65 12877.80 4482.21 13991.79 12257.27 25794.07 14277.77 15189.89 13294.56 47
fmvsm_s_conf0.5_n_685.55 7286.20 5683.60 18187.32 24465.13 22488.86 13091.63 12975.41 11788.23 4093.45 8168.56 11192.47 23289.52 1892.78 7993.20 127
viewdifsd2359ckpt1382.91 13182.29 13484.77 11886.96 25966.90 18787.47 18791.62 13072.19 20581.68 14990.71 16566.92 13193.28 18675.90 17887.15 18494.12 71
HPM-MVS_fast85.35 7984.95 8586.57 6393.69 4670.58 8492.15 4091.62 13073.89 16682.67 13494.09 5762.60 18495.54 7080.93 11192.93 7793.57 108
ACMM73.20 880.78 18179.84 18383.58 18389.31 14768.37 13489.99 8491.60 13270.28 25777.25 23489.66 19653.37 29393.53 17474.24 19882.85 26488.85 308
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
VPA-MVSNet80.60 18680.55 16380.76 27788.07 20260.80 32386.86 21291.58 13375.67 11180.24 17589.45 20763.34 16990.25 31170.51 23979.22 31091.23 210
OPM-MVS83.50 11582.95 12085.14 9888.79 17270.95 7489.13 12191.52 13477.55 5280.96 16291.75 12560.71 22294.50 12479.67 12886.51 19689.97 270
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
Anonymous2023121178.97 23077.69 24382.81 22090.54 10664.29 25390.11 8391.51 13565.01 34876.16 26788.13 24950.56 32893.03 21069.68 25177.56 33091.11 213
PS-MVSNAJss82.07 14481.31 14884.34 13686.51 27367.27 17689.27 11291.51 13571.75 21379.37 18890.22 18263.15 17694.27 13177.69 15382.36 27191.49 203
TAPA-MVS73.13 979.15 22477.94 23082.79 22489.59 13062.99 29188.16 16591.51 13565.77 33777.14 24291.09 15360.91 22093.21 19350.26 41087.05 18692.17 182
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
ACMP74.13 681.51 16280.57 16284.36 13489.42 13968.69 12689.97 8591.50 13874.46 15075.04 29890.41 17453.82 28894.54 12177.56 15482.91 26389.86 274
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
PCF-MVS73.52 780.38 19378.84 21185.01 10587.71 22468.99 11383.65 31291.46 13963.00 37277.77 22590.28 17866.10 14495.09 9861.40 32588.22 16290.94 222
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
TranMVSNet+NR-MVSNet80.84 17280.31 16982.42 23587.85 21262.33 30287.74 18191.33 14080.55 977.99 21989.86 18665.23 15492.62 22267.05 27775.24 37192.30 172
RRT-MVS82.60 13882.10 13884.10 15187.98 20762.94 29287.45 19091.27 14177.42 5679.85 17990.28 17856.62 26594.70 11779.87 12588.15 16394.67 34
PS-CasMVS78.01 25678.09 22777.77 34187.71 22454.39 40888.02 16991.22 14277.50 5473.26 32388.64 22960.73 22188.41 34861.88 32073.88 38490.53 239
v7n78.97 23077.58 24683.14 20183.45 34865.51 21488.32 15991.21 14373.69 17172.41 33586.32 30157.93 24893.81 15769.18 25575.65 35790.11 258
PEN-MVS77.73 26277.69 24377.84 33987.07 25853.91 41187.91 17591.18 14477.56 5173.14 32588.82 22461.23 21489.17 33259.95 33672.37 39590.43 243
MM89.16 889.23 1088.97 490.79 10273.65 1092.66 2891.17 14586.57 187.39 5794.97 2571.70 6297.68 192.19 195.63 3295.57 1
save fliter93.80 4472.35 4490.47 7491.17 14574.31 154
CP-MVSNet78.22 24778.34 22177.84 33987.83 21454.54 40687.94 17391.17 14577.65 4673.48 32188.49 23462.24 19388.43 34762.19 31674.07 38090.55 238
114514_t80.68 18279.51 19384.20 14894.09 4267.27 17689.64 9691.11 14858.75 41574.08 31390.72 16458.10 24795.04 9969.70 25089.42 14090.30 250
NR-MVSNet80.23 19979.38 19682.78 22587.80 21563.34 28086.31 23691.09 14979.01 3172.17 33989.07 21367.20 12892.81 21966.08 28475.65 35792.20 177
fmvsm_s_conf0.5_n_1086.38 5286.76 4685.24 9587.33 24267.30 17489.50 10190.98 15076.25 9790.56 2294.75 2968.38 11394.24 13590.80 792.32 8994.19 67
OpenMVScopyleft72.83 1079.77 20678.33 22284.09 15585.17 30569.91 9390.57 6990.97 15166.70 32272.17 33991.91 11754.70 27993.96 14461.81 32290.95 11288.41 324
MAR-MVS81.84 14980.70 15985.27 9491.32 8971.53 5889.82 8890.92 15269.77 27178.50 20486.21 30262.36 19094.52 12365.36 28992.05 9389.77 278
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 23577.83 23581.43 25685.17 30560.30 33189.41 10790.90 15371.21 22777.17 24188.73 22546.38 36993.21 19372.57 21678.96 31190.79 226
Anonymous2024052980.19 20178.89 21084.10 15190.60 10464.75 24188.95 12790.90 15365.97 33680.59 17091.17 15149.97 33693.73 16469.16 25682.70 26893.81 90
OMC-MVS82.69 13481.97 14384.85 11488.75 17467.42 16887.98 17090.87 15574.92 13779.72 18191.65 12962.19 19493.96 14475.26 18886.42 19793.16 129
UA-Net85.08 8484.96 8485.45 8992.07 7968.07 14589.78 9190.86 15682.48 284.60 9293.20 8769.35 9795.22 8871.39 23090.88 11493.07 135
viewdifsd2359ckpt0782.83 13382.78 12582.99 21086.51 27362.58 29585.09 27390.83 15775.22 12482.28 13691.63 13169.43 9692.03 24977.71 15286.32 19894.34 60
fmvsm_s_conf0.5_n_1186.06 5686.75 4784.00 16887.78 21866.09 19689.96 8690.80 15877.37 5786.72 6594.20 5272.51 5192.78 22089.08 2292.33 8793.13 133
test_fmvsm_n_192085.29 8085.34 7785.13 10186.12 28269.93 9288.65 14490.78 15969.97 26588.27 3893.98 6671.39 6791.54 27588.49 3590.45 12093.91 82
EPP-MVSNet83.40 11883.02 11884.57 12390.13 11464.47 24992.32 3590.73 16074.45 15179.35 18991.10 15269.05 10495.12 9272.78 21387.22 18294.13 70
DTE-MVSNet76.99 27876.80 26377.54 34886.24 27753.06 42087.52 18590.66 16177.08 6972.50 33388.67 22860.48 22989.52 32457.33 36570.74 40790.05 265
v1079.74 20778.67 21282.97 21384.06 33264.95 23187.88 17790.62 16273.11 19175.11 29586.56 29461.46 20894.05 14373.68 20175.55 35989.90 272
test_fmvsmconf_n85.92 6286.04 6385.57 8785.03 31269.51 10089.62 9890.58 16373.42 18087.75 5094.02 6172.85 4893.24 19090.37 890.75 11593.96 79
v119279.59 21078.43 21983.07 20683.55 34664.52 24586.93 20990.58 16370.83 23877.78 22485.90 30759.15 23993.94 14773.96 20077.19 33390.76 228
v114480.03 20379.03 20683.01 20983.78 33964.51 24687.11 20190.57 16571.96 21178.08 21786.20 30361.41 20993.94 14774.93 19077.23 33190.60 236
XVG-OURS-SEG-HR80.81 17479.76 18583.96 17285.60 29468.78 11883.54 31890.50 16670.66 24576.71 24991.66 12860.69 22391.26 28776.94 16281.58 27991.83 189
MVS78.19 25076.99 25981.78 24885.66 29166.99 18284.66 28390.47 16755.08 43672.02 34185.27 32463.83 16794.11 14166.10 28389.80 13384.24 405
fmvsm_l_conf0.5_n_386.02 5786.32 5385.14 9887.20 24768.54 13089.57 9990.44 16875.31 12187.49 5494.39 4272.86 4792.72 22189.04 2790.56 11894.16 68
XVG-OURS80.41 19179.23 20283.97 17185.64 29269.02 11283.03 33190.39 16971.09 23077.63 22791.49 13954.62 28191.35 28475.71 18083.47 25591.54 200
MVSFormer82.85 13282.05 14085.24 9587.35 23770.21 8690.50 7290.38 17068.55 30181.32 15489.47 20361.68 20293.46 18078.98 13790.26 12392.05 186
test_djsdf80.30 19879.32 19983.27 19483.98 33465.37 21990.50 7290.38 17068.55 30176.19 26388.70 22656.44 26693.46 18078.98 13780.14 29990.97 220
CPTT-MVS83.73 10683.33 11484.92 11193.28 5370.86 7892.09 4190.38 17068.75 29879.57 18392.83 9760.60 22893.04 20980.92 11291.56 10290.86 224
v14419279.47 21378.37 22082.78 22583.35 34963.96 25886.96 20690.36 17369.99 26477.50 22885.67 31460.66 22593.77 16074.27 19776.58 34190.62 234
v192192079.22 22278.03 22882.80 22183.30 35163.94 26086.80 21490.33 17469.91 26777.48 22985.53 31858.44 24593.75 16273.60 20276.85 33890.71 232
MVS_111021_HR85.14 8284.75 8786.32 6591.65 8572.70 3085.98 24690.33 17476.11 9982.08 14191.61 13471.36 6894.17 13981.02 11092.58 8292.08 185
v124078.99 22977.78 23882.64 23083.21 35463.54 27486.62 22390.30 17669.74 27477.33 23285.68 31357.04 26093.76 16173.13 21076.92 33590.62 234
test_fmvsmconf0.1_n85.61 7185.65 7185.50 8882.99 36469.39 10789.65 9590.29 17773.31 18487.77 4994.15 5571.72 6193.23 19190.31 990.67 11793.89 85
v879.97 20579.02 20782.80 22184.09 33164.50 24887.96 17190.29 17774.13 16175.24 29186.81 28062.88 18393.89 15574.39 19675.40 36690.00 266
fmvsm_s_conf0.5_n_386.36 5387.46 3283.09 20387.08 25665.21 22189.09 12390.21 17979.67 1989.98 2495.02 2473.17 4291.71 26591.30 391.60 9992.34 169
mvs_tets79.13 22577.77 23983.22 19884.70 31866.37 19289.17 11690.19 18069.38 27975.40 28189.46 20544.17 39293.15 20076.78 16980.70 29190.14 255
jajsoiax79.29 22177.96 22983.27 19484.68 31966.57 19089.25 11390.16 18169.20 28775.46 27889.49 20245.75 38093.13 20276.84 16580.80 28990.11 258
Vis-MVSNetpermissive83.46 11682.80 12385.43 9090.25 11268.74 12190.30 8090.13 18276.33 9380.87 16592.89 9561.00 21994.20 13672.45 22290.97 11193.35 118
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
PS-MVSNAJ81.69 15381.02 15483.70 17989.51 13468.21 14284.28 29890.09 18370.79 23981.26 15885.62 31663.15 17694.29 12975.62 18288.87 14988.59 319
xiu_mvs_v2_base81.69 15381.05 15383.60 18189.15 15568.03 14784.46 29190.02 18470.67 24281.30 15786.53 29663.17 17594.19 13875.60 18388.54 15688.57 320
FA-MVS(test-final)80.96 17079.91 18084.10 15188.30 19165.01 22884.55 28890.01 18573.25 18779.61 18287.57 26058.35 24694.72 11571.29 23186.25 20192.56 158
v2v48280.23 19979.29 20083.05 20783.62 34464.14 25587.04 20289.97 18673.61 17378.18 21487.22 27161.10 21793.82 15676.11 17476.78 34091.18 211
test_yl81.17 16580.47 16683.24 19689.13 15663.62 26686.21 24189.95 18772.43 20381.78 14789.61 19857.50 25493.58 16670.75 23586.90 18892.52 160
DCV-MVSNet81.17 16580.47 16683.24 19689.13 15663.62 26686.21 24189.95 18772.43 20381.78 14789.61 19857.50 25493.58 16670.75 23586.90 18892.52 160
fmvsm_s_conf0.5_n_783.34 12084.03 9681.28 26285.73 29065.13 22485.40 26589.90 18974.96 13682.13 14093.89 6966.65 13387.92 35386.56 5391.05 10990.80 225
V4279.38 21978.24 22482.83 21881.10 39865.50 21585.55 26089.82 19071.57 21978.21 21286.12 30560.66 22593.18 19975.64 18175.46 36389.81 277
fmvsm_s_conf0.5_n_485.39 7785.75 7084.30 14086.70 26765.83 20588.77 13689.78 19175.46 11688.35 3693.73 7469.19 10093.06 20691.30 388.44 15994.02 77
VNet82.21 14182.41 13081.62 25190.82 10060.93 32084.47 28989.78 19176.36 9284.07 10491.88 11964.71 15990.26 31070.68 23788.89 14893.66 98
diffmvs_AUTHOR82.38 13982.27 13582.73 22983.26 35263.80 26383.89 30689.76 19373.35 18382.37 13590.84 16266.25 14190.79 30282.77 9387.93 16993.59 107
diffmvspermissive82.10 14281.88 14482.76 22783.00 36263.78 26583.68 31189.76 19372.94 19582.02 14289.85 18765.96 14990.79 30282.38 10087.30 18193.71 96
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 29674.27 30881.62 25183.20 35564.67 24283.60 31589.75 19569.75 27271.85 34287.09 27632.78 44392.11 24769.99 24780.43 29588.09 330
EI-MVSNet-Vis-set84.19 9283.81 10185.31 9388.18 19467.85 15487.66 18289.73 19680.05 1582.95 12689.59 20070.74 7694.82 10880.66 11884.72 22793.28 121
EI-MVSNet-UG-set83.81 10183.38 11285.09 10387.87 21167.53 16687.44 19189.66 19779.74 1882.23 13889.41 20970.24 8294.74 11479.95 12383.92 24292.99 143
test_fmvsmconf0.01_n84.73 8984.52 9185.34 9280.25 40669.03 11089.47 10289.65 19873.24 18886.98 6294.27 4766.62 13493.23 19190.26 1089.95 13093.78 94
BP-MVS184.32 9183.71 10486.17 6887.84 21367.85 15489.38 10989.64 19977.73 4583.98 10692.12 11456.89 26295.43 7784.03 8091.75 9895.24 7
VortexMVS78.57 24177.89 23380.59 28085.89 28662.76 29485.61 25589.62 20072.06 20974.99 29985.38 32255.94 26890.77 30574.99 18976.58 34188.23 326
PAPM77.68 26676.40 27581.51 25487.29 24661.85 30983.78 30889.59 20164.74 35071.23 34988.70 22662.59 18593.66 16552.66 39487.03 18789.01 300
MGCNet87.69 2487.55 2988.12 1389.45 13871.76 5391.47 5789.54 20282.14 386.65 6694.28 4668.28 11697.46 690.81 695.31 3895.15 8
anonymousdsp78.60 23977.15 25582.98 21280.51 40467.08 18187.24 19889.53 20365.66 33975.16 29387.19 27352.52 29792.25 24377.17 15979.34 30889.61 282
MG-MVS83.41 11783.45 11083.28 19392.74 7162.28 30488.17 16489.50 20475.22 12481.49 15292.74 10366.75 13295.11 9472.85 21291.58 10192.45 166
PLCcopyleft70.83 1178.05 25476.37 27683.08 20591.88 8367.80 15688.19 16389.46 20564.33 35669.87 36688.38 23753.66 28993.58 16658.86 34982.73 26687.86 334
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 18687.12 25566.01 19988.56 14889.43 20675.59 11289.32 2894.32 4472.89 4691.21 29090.11 1192.33 8793.16 129
SDMVSNet80.38 19380.18 17280.99 27189.03 16164.94 23480.45 36389.40 20775.19 12876.61 25389.98 18460.61 22787.69 35776.83 16683.55 25290.33 248
Fast-Effi-MVS+80.81 17479.92 17983.47 18588.85 16364.51 24685.53 26289.39 20870.79 23978.49 20585.06 33167.54 12493.58 16667.03 27886.58 19492.32 171
IterMVS-LS80.06 20279.38 19682.11 24285.89 28663.20 28486.79 21589.34 20974.19 15875.45 27986.72 28366.62 13492.39 23672.58 21576.86 33790.75 229
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
icg_test_0407_278.92 23278.93 20978.90 31687.13 25063.59 27076.58 41089.33 21070.51 24877.82 22189.03 21561.84 19881.38 41472.56 21885.56 21691.74 192
IMVS_040780.61 18479.90 18182.75 22887.13 25063.59 27085.33 26689.33 21070.51 24877.82 22189.03 21561.84 19892.91 21272.56 21885.56 21691.74 192
IMVS_040477.16 27676.42 27479.37 30787.13 25063.59 27077.12 40889.33 21070.51 24866.22 40889.03 21550.36 33182.78 40472.56 21885.56 21691.74 192
IMVS_040380.80 17780.12 17682.87 21787.13 25063.59 27085.19 26789.33 21070.51 24878.49 20589.03 21563.26 17293.27 18872.56 21885.56 21691.74 192
API-MVS81.99 14681.23 15084.26 14690.94 9770.18 9191.10 6389.32 21471.51 22078.66 20088.28 24065.26 15395.10 9764.74 29591.23 10787.51 342
fmvsm_s_conf0.5_n_585.22 8185.55 7384.25 14786.26 27667.40 17089.18 11589.31 21572.50 19988.31 3793.86 7069.66 9391.96 25389.81 1391.05 10993.38 115
GBi-Net78.40 24377.40 25081.40 25887.60 23163.01 28788.39 15489.28 21671.63 21575.34 28487.28 26754.80 27591.11 29162.72 30879.57 30390.09 260
test178.40 24377.40 25081.40 25887.60 23163.01 28788.39 15489.28 21671.63 21575.34 28487.28 26754.80 27591.11 29162.72 30879.57 30390.09 260
FMVSNet177.44 27076.12 27881.40 25886.81 26363.01 28788.39 15489.28 21670.49 25274.39 31087.28 26749.06 35091.11 29160.91 32978.52 31490.09 260
cdsmvs_eth3d_5k19.96 44626.61 4480.00 4670.00 4900.00 4920.00 47989.26 2190.00 4850.00 48688.61 23061.62 2040.00 4860.00 4850.00 4840.00 482
SSM_040781.58 15780.48 16584.87 11388.81 16767.96 14987.37 19289.25 22071.06 23279.48 18590.39 17559.57 23594.48 12672.45 22285.93 20992.18 179
SSM_040481.91 14780.84 15885.13 10189.24 15168.26 13787.84 17989.25 22071.06 23280.62 16990.39 17559.57 23594.65 11972.45 22287.19 18392.47 165
ab-mvs79.51 21178.97 20881.14 26788.46 18460.91 32183.84 30789.24 22270.36 25379.03 19288.87 22363.23 17490.21 31265.12 29182.57 26992.28 173
cascas76.72 28474.64 30082.99 21085.78 28965.88 20482.33 33589.21 22360.85 39472.74 32981.02 39947.28 35993.75 16267.48 27185.02 22289.34 290
eth_miper_zixun_eth77.92 25876.69 26881.61 25383.00 36261.98 30783.15 32589.20 22469.52 27774.86 30284.35 34561.76 20192.56 22771.50 22972.89 39390.28 251
h-mvs3383.15 12582.19 13686.02 7690.56 10570.85 7988.15 16689.16 22576.02 10184.67 8791.39 14261.54 20595.50 7382.71 9675.48 36191.72 196
miper_ehance_all_eth78.59 24077.76 24081.08 26982.66 37261.56 31383.65 31289.15 22668.87 29675.55 27583.79 35866.49 13792.03 24973.25 20876.39 34689.64 281
Effi-MVS+83.62 11283.08 11685.24 9588.38 18867.45 16788.89 12989.15 22675.50 11482.27 13788.28 24069.61 9494.45 12777.81 15087.84 17093.84 88
c3_l78.75 23477.91 23181.26 26382.89 36761.56 31384.09 30489.13 22869.97 26575.56 27484.29 34666.36 13992.09 24873.47 20575.48 36190.12 257
LTVRE_ROB69.57 1376.25 29474.54 30381.41 25788.60 17964.38 25279.24 37989.12 22970.76 24169.79 36887.86 25349.09 34993.20 19656.21 37780.16 29786.65 367
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
fmvsm_s_conf0.5_n_987.39 3387.95 2385.70 8189.48 13767.88 15388.59 14689.05 23080.19 1290.70 2095.40 1574.56 2893.92 15191.54 292.07 9295.31 5
F-COLMAP76.38 29374.33 30782.50 23489.28 14966.95 18688.41 15389.03 23164.05 36166.83 39788.61 23046.78 36592.89 21357.48 36278.55 31387.67 337
FMVSNet278.20 24977.21 25481.20 26587.60 23162.89 29387.47 18789.02 23271.63 21575.29 29087.28 26754.80 27591.10 29462.38 31379.38 30789.61 282
ACMH67.68 1675.89 29973.93 31181.77 24988.71 17666.61 18988.62 14589.01 23369.81 26866.78 39886.70 28741.95 40891.51 27855.64 37878.14 32287.17 351
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
miper_enhance_ethall77.87 26076.86 26180.92 27481.65 38661.38 31582.68 33288.98 23465.52 34175.47 27682.30 38765.76 15192.00 25272.95 21176.39 34689.39 288
无先验87.48 18688.98 23460.00 40194.12 14067.28 27388.97 303
AdaColmapbinary80.58 18979.42 19584.06 16093.09 6368.91 11589.36 11088.97 23669.27 28275.70 27289.69 19457.20 25995.77 6463.06 30688.41 16087.50 343
EI-MVSNet80.52 19079.98 17882.12 24084.28 32663.19 28586.41 23088.95 23774.18 15978.69 19887.54 26366.62 13492.43 23472.57 21680.57 29390.74 230
MVSTER79.01 22877.88 23482.38 23683.07 35964.80 24084.08 30588.95 23769.01 29478.69 19887.17 27454.70 27992.43 23474.69 19180.57 29389.89 273
FE-MVSNET272.88 34271.28 34477.67 34278.30 42757.78 36184.43 29388.92 23969.56 27564.61 41881.67 39446.73 36788.54 34659.33 34267.99 41986.69 366
LuminaMVS80.68 18279.62 19183.83 17585.07 31168.01 14886.99 20588.83 24070.36 25381.38 15387.99 25150.11 33492.51 23179.02 13486.89 19090.97 220
131476.53 28675.30 29380.21 29083.93 33562.32 30384.66 28388.81 24160.23 39970.16 36084.07 35355.30 27290.73 30667.37 27283.21 26087.59 341
UniMVSNet_ETH3D79.10 22678.24 22481.70 25086.85 26160.24 33287.28 19788.79 24274.25 15776.84 24490.53 17349.48 34291.56 27167.98 26682.15 27293.29 120
xiu_mvs_v1_base_debu80.80 17779.72 18884.03 16587.35 23770.19 8885.56 25788.77 24369.06 29181.83 14388.16 24450.91 32392.85 21578.29 14687.56 17589.06 295
xiu_mvs_v1_base80.80 17779.72 18884.03 16587.35 23770.19 8885.56 25788.77 24369.06 29181.83 14388.16 24450.91 32392.85 21578.29 14687.56 17589.06 295
xiu_mvs_v1_base_debi80.80 17779.72 18884.03 16587.35 23770.19 8885.56 25788.77 24369.06 29181.83 14388.16 24450.91 32392.85 21578.29 14687.56 17589.06 295
FMVSNet377.88 25976.85 26280.97 27386.84 26262.36 30186.52 22788.77 24371.13 22875.34 28486.66 28954.07 28591.10 29462.72 30879.57 30389.45 286
patch_mono-283.65 10984.54 8980.99 27190.06 12065.83 20584.21 29988.74 24771.60 21885.01 7992.44 10574.51 2983.50 39982.15 10192.15 9093.64 104
GeoE81.71 15281.01 15583.80 17889.51 13464.45 25088.97 12688.73 24871.27 22678.63 20189.76 19366.32 14093.20 19669.89 24886.02 20693.74 95
mamba_040879.37 22077.52 24784.93 11088.81 16767.96 14965.03 46388.66 24970.96 23679.48 18589.80 19058.69 24194.65 11970.35 24185.93 20992.18 179
SSM_0407277.67 26777.52 24778.12 33388.81 16767.96 14965.03 46388.66 24970.96 23679.48 18589.80 19058.69 24174.23 45570.35 24185.93 20992.18 179
CANet_DTU80.61 18479.87 18282.83 21885.60 29463.17 28687.36 19388.65 25176.37 9175.88 26988.44 23653.51 29193.07 20573.30 20789.74 13492.25 174
HyFIR lowres test77.53 26975.40 28983.94 17389.59 13066.62 18880.36 36488.64 25256.29 43276.45 25685.17 32857.64 25293.28 18661.34 32783.10 26291.91 188
WR-MVS79.49 21279.22 20380.27 28888.79 17258.35 34885.06 27488.61 25378.56 3577.65 22688.34 23863.81 16890.66 30764.98 29377.22 33291.80 191
BH-untuned79.47 21378.60 21482.05 24389.19 15465.91 20386.07 24588.52 25472.18 20675.42 28087.69 25761.15 21693.54 17360.38 33386.83 19186.70 365
IS-MVSNet83.15 12582.81 12284.18 14989.94 12363.30 28191.59 5188.46 25579.04 3079.49 18492.16 11165.10 15594.28 13067.71 26891.86 9794.95 12
pm-mvs177.25 27576.68 26978.93 31584.22 32858.62 34686.41 23088.36 25671.37 22273.31 32288.01 25061.22 21589.15 33364.24 29973.01 39289.03 299
UGNet80.83 17379.59 19284.54 12488.04 20368.09 14489.42 10688.16 25776.95 7176.22 26289.46 20549.30 34693.94 14768.48 26390.31 12191.60 197
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 13082.36 13284.96 10791.02 9566.40 19188.91 12888.11 25877.57 4984.39 9693.29 8552.19 30393.91 15277.05 16188.70 15494.57 45
Effi-MVS+-dtu80.03 20378.57 21584.42 13085.13 30968.74 12188.77 13688.10 25974.99 13374.97 30083.49 36757.27 25793.36 18473.53 20380.88 28791.18 211
v14878.72 23677.80 23781.47 25582.73 37061.96 30886.30 23788.08 26073.26 18676.18 26485.47 32062.46 18892.36 23871.92 22673.82 38590.09 260
EG-PatchMatch MVS74.04 32271.82 33680.71 27884.92 31367.42 16885.86 25188.08 26066.04 33464.22 42183.85 35535.10 43992.56 22757.44 36380.83 28882.16 430
viewmambaseed2359dif80.41 19179.84 18382.12 24082.95 36662.50 29883.39 31988.06 26267.11 31780.98 16190.31 17766.20 14391.01 29874.62 19284.90 22492.86 148
SymmetryMVS85.38 7884.81 8687.07 5091.47 8772.47 3891.65 4788.06 26279.31 2484.39 9692.18 10964.64 16095.53 7180.70 11690.91 11393.21 125
cl2278.07 25377.01 25781.23 26482.37 37961.83 31083.55 31687.98 26468.96 29575.06 29783.87 35461.40 21091.88 25873.53 20376.39 34689.98 269
test_fmvsmvis_n_192084.02 9683.87 9884.49 12784.12 33069.37 10888.15 16687.96 26570.01 26383.95 10793.23 8668.80 10891.51 27888.61 3289.96 12992.57 157
pmmvs674.69 31473.39 31878.61 32081.38 39357.48 36686.64 22287.95 26664.99 34970.18 35886.61 29050.43 33089.52 32462.12 31870.18 41088.83 309
MVP-Stereo76.12 29574.46 30581.13 26885.37 30169.79 9584.42 29587.95 26665.03 34767.46 38885.33 32353.28 29491.73 26458.01 35983.27 25981.85 432
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
cl____77.72 26376.76 26580.58 28182.49 37660.48 32883.09 32787.87 26869.22 28574.38 31185.22 32762.10 19591.53 27671.09 23275.41 36589.73 280
DIV-MVS_self_test77.72 26376.76 26580.58 28182.48 37760.48 32883.09 32787.86 26969.22 28574.38 31185.24 32562.10 19591.53 27671.09 23275.40 36689.74 279
BH-w/o78.21 24877.33 25380.84 27588.81 16765.13 22484.87 27887.85 27069.75 27274.52 30884.74 33861.34 21193.11 20358.24 35785.84 21284.27 404
FE-MVS77.78 26175.68 28284.08 15688.09 20166.00 20083.13 32687.79 27168.42 30578.01 21885.23 32645.50 38395.12 9259.11 34685.83 21391.11 213
HY-MVS69.67 1277.95 25777.15 25580.36 28587.57 23660.21 33383.37 32187.78 27266.11 33275.37 28387.06 27863.27 17190.48 30961.38 32682.43 27090.40 245
guyue81.13 16780.64 16182.60 23286.52 27263.92 26186.69 22087.73 27373.97 16280.83 16789.69 19456.70 26391.33 28678.26 14985.40 22092.54 159
1112_ss77.40 27276.43 27380.32 28789.11 16060.41 33083.65 31287.72 27462.13 38573.05 32686.72 28362.58 18689.97 31662.11 31980.80 28990.59 237
mvs_anonymous79.42 21679.11 20580.34 28684.45 32557.97 35582.59 33387.62 27567.40 31676.17 26688.56 23368.47 11289.59 32370.65 23886.05 20593.47 113
ACMH+68.96 1476.01 29874.01 30982.03 24488.60 17965.31 22088.86 13087.55 27670.25 25967.75 38487.47 26541.27 41193.19 19858.37 35575.94 35487.60 339
tfpnnormal74.39 31673.16 32278.08 33486.10 28458.05 35284.65 28587.53 27770.32 25671.22 35085.63 31554.97 27389.86 31743.03 44475.02 37386.32 370
CHOSEN 1792x268877.63 26875.69 28183.44 18789.98 12268.58 12978.70 38987.50 27856.38 43175.80 27186.84 27958.67 24391.40 28361.58 32485.75 21490.34 247
ambc75.24 37273.16 45350.51 43863.05 46887.47 27964.28 42077.81 43317.80 46889.73 32157.88 36060.64 44285.49 386
Fast-Effi-MVS+-dtu78.02 25576.49 27182.62 23183.16 35866.96 18586.94 20887.45 28072.45 20071.49 34784.17 35154.79 27891.58 26867.61 26980.31 29689.30 291
D2MVS74.82 31373.21 32179.64 30379.81 41362.56 29780.34 36587.35 28164.37 35568.86 37582.66 38246.37 37090.10 31367.91 26781.24 28286.25 371
fmvsm_s_conf0.5_n_284.04 9584.11 9583.81 17786.17 28065.00 22986.96 20687.28 28274.35 15288.25 3994.23 5061.82 20092.60 22489.85 1288.09 16493.84 88
TSAR-MVS + GP.85.71 6985.33 7886.84 5691.34 8872.50 3689.07 12487.28 28276.41 8685.80 7190.22 18274.15 3595.37 8581.82 10391.88 9492.65 156
fmvsm_l_conf0.5_n84.47 9084.54 8984.27 14485.42 29968.81 11688.49 15087.26 28468.08 30888.03 4493.49 7772.04 5791.77 26188.90 2989.14 14692.24 176
hse-mvs281.72 15180.94 15684.07 15788.72 17567.68 16085.87 25087.26 28476.02 10184.67 8788.22 24361.54 20593.48 17882.71 9673.44 38991.06 215
AUN-MVS79.21 22377.60 24584.05 16388.71 17667.61 16285.84 25287.26 28469.08 29077.23 23688.14 24853.20 29593.47 17975.50 18573.45 38891.06 215
BH-RMVSNet79.61 20878.44 21883.14 20189.38 14365.93 20284.95 27787.15 28773.56 17578.19 21389.79 19256.67 26493.36 18459.53 34186.74 19290.13 256
Test_1112_low_res76.40 29275.44 28779.27 30989.28 14958.09 35181.69 34287.07 28859.53 40672.48 33486.67 28861.30 21289.33 32760.81 33180.15 29890.41 244
KD-MVS_self_test68.81 38067.59 38572.46 40374.29 44445.45 45377.93 40187.00 28963.12 36963.99 42478.99 42542.32 40384.77 38956.55 37564.09 43287.16 353
mvsmamba80.60 18679.38 19684.27 14489.74 12867.24 17887.47 18786.95 29070.02 26275.38 28288.93 22051.24 32092.56 22775.47 18689.22 14393.00 142
reproduce_monomvs75.40 30874.38 30678.46 32883.92 33657.80 36083.78 30886.94 29173.47 17972.25 33884.47 34038.74 42489.27 32975.32 18770.53 40888.31 325
LS3D76.95 28074.82 29883.37 19190.45 10767.36 17289.15 12086.94 29161.87 38869.52 36990.61 17051.71 31694.53 12246.38 43286.71 19388.21 328
miper_lstm_enhance74.11 32173.11 32377.13 35380.11 40859.62 33872.23 43486.92 29366.76 32170.40 35582.92 37756.93 26182.92 40369.06 25772.63 39488.87 307
fmvsm_l_conf0.5_n_a84.13 9384.16 9484.06 16085.38 30068.40 13388.34 15886.85 29467.48 31587.48 5593.40 8270.89 7391.61 26688.38 3789.22 14392.16 183
jason81.39 16380.29 17084.70 12186.63 27069.90 9485.95 24786.77 29563.24 36881.07 16089.47 20361.08 21892.15 24678.33 14590.07 12892.05 186
jason: jason.
viewdifsd2359ckpt1180.37 19579.73 18682.30 23883.70 34262.39 29984.20 30086.67 29673.22 18980.90 16390.62 16863.00 18191.56 27176.81 16778.44 31692.95 145
viewmsd2359difaftdt80.37 19579.73 18682.30 23883.70 34262.39 29984.20 30086.67 29673.22 18980.90 16390.62 16863.00 18191.56 27176.81 16778.44 31692.95 145
OurMVSNet-221017-074.26 31872.42 33179.80 29883.76 34059.59 33985.92 24986.64 29866.39 33066.96 39587.58 25939.46 41991.60 26765.76 28769.27 41388.22 327
VPNet78.69 23778.66 21378.76 31888.31 19055.72 39384.45 29286.63 29976.79 7678.26 21190.55 17259.30 23889.70 32266.63 27977.05 33490.88 223
fmvsm_s_conf0.1_n_283.80 10283.79 10283.83 17585.62 29364.94 23487.03 20386.62 30074.32 15387.97 4794.33 4360.67 22492.60 22489.72 1487.79 17193.96 79
USDC70.33 36768.37 36876.21 35980.60 40256.23 38679.19 38186.49 30160.89 39361.29 43485.47 32031.78 44689.47 32653.37 39176.21 35282.94 423
lupinMVS81.39 16380.27 17184.76 11987.35 23770.21 8685.55 26086.41 30262.85 37581.32 15488.61 23061.68 20292.24 24478.41 14490.26 12391.83 189
TR-MVS77.44 27076.18 27781.20 26588.24 19263.24 28284.61 28686.40 30367.55 31377.81 22386.48 29754.10 28493.15 20057.75 36182.72 26787.20 350
旧先验191.96 8065.79 20886.37 30493.08 9269.31 9992.74 8088.74 315
GA-MVS76.87 28175.17 29581.97 24682.75 36962.58 29581.44 34786.35 30572.16 20874.74 30382.89 37846.20 37492.02 25168.85 26081.09 28491.30 209
MonoMVSNet76.49 29075.80 27978.58 32281.55 38958.45 34786.36 23586.22 30674.87 14174.73 30483.73 36051.79 31588.73 34170.78 23472.15 39888.55 321
CDS-MVSNet79.07 22777.70 24283.17 20087.60 23168.23 14184.40 29686.20 30767.49 31476.36 25986.54 29561.54 20590.79 30261.86 32187.33 18090.49 241
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
MVS_111021_LR82.61 13682.11 13784.11 15088.82 16671.58 5785.15 27086.16 30874.69 14480.47 17391.04 15562.29 19190.55 30880.33 12090.08 12790.20 253
MSDG73.36 33370.99 34880.49 28384.51 32465.80 20780.71 35886.13 30965.70 33865.46 41183.74 35944.60 38790.91 30051.13 40376.89 33684.74 400
TransMVSNet (Re)75.39 30974.56 30277.86 33885.50 29857.10 37186.78 21686.09 31072.17 20771.53 34687.34 26663.01 18089.31 32856.84 37161.83 43887.17 351
VDDNet81.52 16080.67 16084.05 16390.44 10864.13 25689.73 9385.91 31171.11 22983.18 12293.48 7850.54 32993.49 17773.40 20688.25 16194.54 49
AstraMVS80.81 17480.14 17582.80 22186.05 28563.96 25886.46 22985.90 31273.71 17080.85 16690.56 17154.06 28691.57 27079.72 12783.97 24192.86 148
sd_testset77.70 26577.40 25078.60 32189.03 16160.02 33479.00 38485.83 31375.19 12876.61 25389.98 18454.81 27485.46 38262.63 31283.55 25290.33 248
Baseline_NR-MVSNet78.15 25178.33 22277.61 34585.79 28856.21 38786.78 21685.76 31473.60 17477.93 22087.57 26065.02 15688.99 33567.14 27675.33 36887.63 338
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 39185.28 390
test_vis1_n_192075.52 30475.78 28074.75 37979.84 41257.44 36783.26 32385.52 31662.83 37679.34 19086.17 30445.10 38579.71 42178.75 13981.21 28387.10 357
新几何183.42 18893.13 6070.71 8085.48 31757.43 42681.80 14691.98 11663.28 17092.27 24264.60 29692.99 7687.27 349
EPNet83.72 10782.92 12186.14 7284.22 32869.48 10191.05 6485.27 31881.30 676.83 24591.65 12966.09 14595.56 6876.00 17793.85 6893.38 115
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
UnsupCasMVSNet_eth67.33 39265.99 39671.37 40973.48 45051.47 43175.16 42185.19 31965.20 34460.78 43680.93 40342.35 40277.20 43257.12 36653.69 45585.44 388
SD_040374.65 31574.77 29974.29 38386.20 27947.42 44783.71 31085.12 32069.30 28168.50 38087.95 25259.40 23786.05 37349.38 41483.35 25789.40 287
mmtdpeth74.16 32073.01 32477.60 34783.72 34161.13 31685.10 27285.10 32172.06 20977.21 24080.33 40843.84 39485.75 37677.14 16052.61 45785.91 381
IB-MVS68.01 1575.85 30073.36 32083.31 19284.76 31766.03 19783.38 32085.06 32270.21 26069.40 37081.05 39845.76 37994.66 11865.10 29275.49 36089.25 292
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 23377.51 24983.03 20887.80 21567.79 15784.72 28185.05 32367.63 31176.75 24887.70 25662.25 19290.82 30158.53 35387.13 18590.49 241
CL-MVSNet_self_test72.37 34671.46 34075.09 37379.49 41953.53 41380.76 35685.01 32469.12 28970.51 35382.05 39157.92 24984.13 39352.27 39666.00 42787.60 339
testdata79.97 29490.90 9864.21 25484.71 32559.27 40885.40 7592.91 9462.02 19789.08 33468.95 25891.37 10586.63 368
MS-PatchMatch73.83 32572.67 32777.30 35183.87 33766.02 19881.82 33984.66 32661.37 39268.61 37882.82 38047.29 35888.21 34959.27 34384.32 23777.68 447
ET-MVSNet_ETH3D78.63 23876.63 27084.64 12286.73 26669.47 10285.01 27584.61 32769.54 27666.51 40586.59 29150.16 33391.75 26276.26 17284.24 23892.69 154
CNLPA78.08 25276.79 26481.97 24690.40 10971.07 7087.59 18484.55 32866.03 33572.38 33689.64 19757.56 25386.04 37459.61 34083.35 25788.79 311
MIMVSNet168.58 38366.78 39373.98 38780.07 40951.82 42780.77 35584.37 32964.40 35459.75 44282.16 39036.47 43583.63 39742.73 44570.33 40986.48 369
KD-MVS_2432*160066.22 40263.89 40573.21 39375.47 44153.42 41570.76 44184.35 33064.10 35966.52 40378.52 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 40378.52 42734.55 44084.98 38650.40 40650.33 46081.23 435
test_040272.79 34370.44 35479.84 29788.13 19865.99 20185.93 24884.29 33265.57 34067.40 39185.49 31946.92 36292.61 22335.88 45874.38 37980.94 437
EU-MVSNet68.53 38567.61 38471.31 41278.51 42647.01 45084.47 28984.27 33342.27 45966.44 40684.79 33740.44 41683.76 39558.76 35168.54 41883.17 417
thisisatest053079.40 21777.76 24084.31 13887.69 22865.10 22787.36 19384.26 33470.04 26177.42 23088.26 24249.94 33794.79 11270.20 24384.70 22893.03 139
COLMAP_ROBcopyleft66.92 1773.01 33970.41 35580.81 27687.13 25065.63 21188.30 16084.19 33562.96 37363.80 42687.69 25738.04 42992.56 22746.66 42974.91 37484.24 405
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
tttt051779.40 21777.91 23183.90 17488.10 20063.84 26288.37 15784.05 33671.45 22176.78 24789.12 21249.93 33994.89 10570.18 24483.18 26192.96 144
CMPMVSbinary51.72 2170.19 36968.16 37176.28 35873.15 45457.55 36579.47 37683.92 33748.02 45256.48 45284.81 33643.13 39886.42 37062.67 31181.81 27884.89 398
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
Anonymous20240521178.25 24677.01 25781.99 24591.03 9460.67 32584.77 28083.90 33870.65 24680.00 17891.20 14941.08 41391.43 28265.21 29085.26 22193.85 86
XXY-MVS75.41 30775.56 28574.96 37483.59 34557.82 35980.59 36083.87 33966.54 32974.93 30188.31 23963.24 17380.09 42062.16 31776.85 33886.97 359
DP-MVS76.78 28374.57 30183.42 18893.29 5269.46 10488.55 14983.70 34063.98 36370.20 35788.89 22254.01 28794.80 11146.66 42981.88 27786.01 378
tfpn200view976.42 29175.37 29179.55 30689.13 15657.65 36385.17 26883.60 34173.41 18176.45 25686.39 29952.12 30491.95 25448.33 42083.75 24689.07 293
thres40076.50 28775.37 29179.86 29689.13 15657.65 36385.17 26883.60 34173.41 18176.45 25686.39 29952.12 30491.95 25448.33 42083.75 24690.00 266
SixPastTwentyTwo73.37 33171.26 34679.70 30085.08 31057.89 35785.57 25683.56 34371.03 23465.66 41085.88 30842.10 40692.57 22659.11 34663.34 43388.65 317
thres20075.55 30374.47 30478.82 31787.78 21857.85 35883.07 32983.51 34472.44 20275.84 27084.42 34152.08 30791.75 26247.41 42783.64 25186.86 361
IterMVS-SCA-FT75.43 30673.87 31380.11 29282.69 37164.85 23981.57 34483.47 34569.16 28870.49 35484.15 35251.95 31088.15 35069.23 25472.14 39987.34 346
CVMVSNet72.99 34072.58 32974.25 38484.28 32650.85 43686.41 23083.45 34644.56 45673.23 32487.54 26349.38 34485.70 37765.90 28578.44 31686.19 373
ITE_SJBPF78.22 33081.77 38560.57 32683.30 34769.25 28467.54 38687.20 27236.33 43687.28 36254.34 38574.62 37786.80 362
thisisatest051577.33 27375.38 29083.18 19985.27 30463.80 26382.11 33883.27 34865.06 34675.91 26883.84 35649.54 34194.27 13167.24 27486.19 20291.48 204
mvs5depth69.45 37667.45 38775.46 36973.93 44555.83 39179.19 38183.23 34966.89 31871.63 34583.32 36933.69 44285.09 38559.81 33855.34 45385.46 387
thres100view90076.50 28775.55 28679.33 30889.52 13356.99 37285.83 25383.23 34973.94 16476.32 26087.12 27551.89 31291.95 25448.33 42083.75 24689.07 293
thres600view776.50 28775.44 28779.68 30189.40 14157.16 36985.53 26283.23 34973.79 16876.26 26187.09 27651.89 31291.89 25748.05 42583.72 24990.00 266
test22291.50 8668.26 13784.16 30283.20 35254.63 43779.74 18091.63 13158.97 24091.42 10386.77 363
EPNet_dtu75.46 30574.86 29777.23 35282.57 37454.60 40586.89 21083.09 35371.64 21466.25 40785.86 30955.99 26788.04 35254.92 38286.55 19589.05 298
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
fmvsm_s_conf0.5_n83.80 10283.71 10484.07 15786.69 26867.31 17389.46 10383.07 35471.09 23086.96 6393.70 7569.02 10691.47 28088.79 3084.62 22993.44 114
fmvsm_s_conf0.1_n83.56 11383.38 11284.10 15184.86 31467.28 17589.40 10883.01 35570.67 24287.08 6093.96 6768.38 11391.45 28188.56 3484.50 23093.56 109
testing9176.54 28575.66 28479.18 31288.43 18655.89 39081.08 35083.00 35673.76 16975.34 28484.29 34646.20 37490.07 31464.33 29784.50 23091.58 199
TDRefinement67.49 39064.34 40276.92 35473.47 45161.07 31984.86 27982.98 35759.77 40358.30 44685.13 32926.06 45487.89 35447.92 42660.59 44381.81 433
OpenMVS_ROBcopyleft64.09 1970.56 36468.19 37077.65 34480.26 40559.41 34285.01 27582.96 35858.76 41465.43 41282.33 38637.63 43191.23 28945.34 43976.03 35382.32 427
fmvsm_s_conf0.5_n_a83.63 11183.41 11184.28 14286.14 28168.12 14389.43 10482.87 35970.27 25887.27 5993.80 7369.09 10191.58 26888.21 3883.65 25093.14 132
fmvsm_s_conf0.1_n_a83.32 12282.99 11984.28 14283.79 33868.07 14589.34 11182.85 36069.80 26987.36 5894.06 5968.34 11591.56 27187.95 4283.46 25693.21 125
RPSCF73.23 33671.46 34078.54 32482.50 37559.85 33582.18 33782.84 36158.96 41171.15 35189.41 20945.48 38484.77 38958.82 35071.83 40191.02 219
CostFormer75.24 31073.90 31279.27 30982.65 37358.27 35080.80 35382.73 36261.57 38975.33 28883.13 37355.52 27091.07 29764.98 29378.34 32188.45 322
IterMVS74.29 31772.94 32578.35 32981.53 39063.49 27681.58 34382.49 36368.06 30969.99 36383.69 36251.66 31785.54 38065.85 28671.64 40286.01 378
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
test_cas_vis1_n_192073.76 32673.74 31573.81 38975.90 43559.77 33680.51 36182.40 36458.30 41781.62 15185.69 31244.35 39176.41 43976.29 17178.61 31285.23 391
WTY-MVS75.65 30275.68 28275.57 36586.40 27556.82 37477.92 40282.40 36465.10 34576.18 26487.72 25563.13 17980.90 41760.31 33481.96 27589.00 302
pmmvs474.03 32471.91 33580.39 28481.96 38268.32 13581.45 34682.14 36659.32 40769.87 36685.13 32952.40 30088.13 35160.21 33574.74 37684.73 401
FMVSNet569.50 37567.96 37574.15 38582.97 36555.35 39880.01 37182.12 36762.56 38063.02 42781.53 39536.92 43281.92 41048.42 41974.06 38185.17 394
mamv476.81 28278.23 22672.54 40286.12 28265.75 21078.76 38882.07 36864.12 35872.97 32791.02 15867.97 11968.08 46783.04 8978.02 32383.80 412
baseline176.98 27976.75 26777.66 34388.13 19855.66 39485.12 27181.89 36973.04 19376.79 24688.90 22162.43 18987.78 35663.30 30571.18 40589.55 284
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
LFMVS81.82 15081.23 15083.57 18491.89 8263.43 27989.84 8781.85 37177.04 7083.21 11993.10 8852.26 30293.43 18271.98 22589.95 13093.85 86
sss73.60 32873.64 31673.51 39182.80 36855.01 40276.12 41281.69 37262.47 38174.68 30585.85 31057.32 25678.11 42860.86 33080.93 28587.39 344
SSC-MVS3.273.35 33473.39 31873.23 39285.30 30349.01 44374.58 42781.57 37375.21 12673.68 31885.58 31752.53 29682.05 40954.33 38677.69 32888.63 318
pmmvs-eth3d70.50 36567.83 37978.52 32677.37 43166.18 19581.82 33981.51 37458.90 41263.90 42580.42 40642.69 40186.28 37158.56 35265.30 42983.11 419
TinyColmap67.30 39364.81 40074.76 37881.92 38456.68 37880.29 36681.49 37560.33 39756.27 45383.22 37024.77 45887.66 35845.52 43769.47 41279.95 442
testing9976.09 29775.12 29679.00 31388.16 19555.50 39680.79 35481.40 37673.30 18575.17 29284.27 34944.48 38990.02 31564.28 29884.22 23991.48 204
tpmvs71.09 35769.29 36276.49 35782.04 38156.04 38878.92 38681.37 37764.05 36167.18 39378.28 42949.74 34089.77 31949.67 41372.37 39583.67 413
WBMVS73.43 33072.81 32675.28 37187.91 20950.99 43578.59 39281.31 37865.51 34374.47 30984.83 33546.39 36886.68 36658.41 35477.86 32488.17 329
pmmvs571.55 35370.20 35875.61 36477.83 42856.39 38281.74 34180.89 37957.76 42267.46 38884.49 33949.26 34785.32 38457.08 36775.29 36985.11 395
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
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
PVSNet64.34 1872.08 35170.87 35075.69 36386.21 27856.44 38174.37 42880.73 38262.06 38670.17 35982.23 38942.86 40083.31 40154.77 38384.45 23487.32 347
baseline275.70 30173.83 31481.30 26183.26 35261.79 31182.57 33480.65 38366.81 31966.88 39683.42 36857.86 25092.19 24563.47 30279.57 30389.91 271
ppachtmachnet_test70.04 37167.34 38978.14 33279.80 41461.13 31679.19 38180.59 38459.16 40965.27 41379.29 42046.75 36687.29 36149.33 41566.72 42286.00 380
FE-MVSNET67.25 39465.33 39873.02 39775.86 43652.54 42180.26 36880.56 38563.80 36660.39 43779.70 41741.41 41084.66 39143.34 44362.62 43681.86 431
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
Anonymous2023120668.60 38267.80 38071.02 41480.23 40750.75 43778.30 39780.47 38756.79 42966.11 40982.63 38346.35 37178.95 42443.62 44275.70 35683.36 416
LCM-MVSNet-Re77.05 27776.94 26077.36 34987.20 24751.60 42980.06 36980.46 38875.20 12767.69 38586.72 28362.48 18788.98 33663.44 30389.25 14191.51 201
tt032070.49 36668.03 37477.89 33784.78 31659.12 34383.55 31680.44 38958.13 41967.43 39080.41 40739.26 42187.54 35955.12 38063.18 43586.99 358
testing1175.14 31174.01 30978.53 32588.16 19556.38 38380.74 35780.42 39070.67 24272.69 33283.72 36143.61 39689.86 31762.29 31583.76 24589.36 289
tpm273.26 33571.46 34078.63 31983.34 35056.71 37780.65 35980.40 39156.63 43073.55 32082.02 39251.80 31491.24 28856.35 37678.42 31987.95 331
CR-MVSNet73.37 33171.27 34579.67 30281.32 39665.19 22275.92 41480.30 39259.92 40272.73 33081.19 39652.50 29886.69 36559.84 33777.71 32687.11 355
Patchmtry70.74 36169.16 36475.49 36880.72 40054.07 41074.94 42580.30 39258.34 41670.01 36181.19 39652.50 29886.54 36753.37 39171.09 40685.87 383
sc_t172.19 34969.51 36080.23 28984.81 31561.09 31884.68 28280.22 39460.70 39571.27 34883.58 36536.59 43489.24 33060.41 33263.31 43490.37 246
tpm cat170.57 36368.31 36977.35 35082.41 37857.95 35678.08 39880.22 39452.04 44368.54 37977.66 43452.00 30987.84 35551.77 39772.07 40086.25 371
MDTV_nov1_ep1369.97 35983.18 35653.48 41477.10 40980.18 39660.45 39669.33 37280.44 40548.89 35386.90 36451.60 39978.51 315
AllTest70.96 35868.09 37379.58 30485.15 30763.62 26684.58 28779.83 39762.31 38260.32 43986.73 28132.02 44488.96 33850.28 40871.57 40386.15 374
TestCases79.58 30485.15 30763.62 26679.83 39762.31 38260.32 43986.73 28132.02 44488.96 33850.28 40871.57 40386.15 374
test_fmvs1_n70.86 36070.24 35772.73 40072.51 45855.28 39981.27 34979.71 39951.49 44778.73 19784.87 33427.54 45377.02 43376.06 17579.97 30185.88 382
Vis-MVSNet (Re-imp)78.36 24578.45 21778.07 33588.64 17851.78 42886.70 21979.63 40074.14 16075.11 29590.83 16361.29 21389.75 32058.10 35891.60 9992.69 154
MIMVSNet70.69 36269.30 36174.88 37684.52 32356.35 38575.87 41679.42 40164.59 35167.76 38382.41 38441.10 41281.54 41246.64 43181.34 28086.75 364
myMVS_eth3d2873.62 32773.53 31773.90 38888.20 19347.41 44878.06 39979.37 40274.29 15673.98 31484.29 34644.67 38683.54 39851.47 40087.39 17990.74 230
dmvs_re71.14 35670.58 35172.80 39981.96 38259.68 33775.60 41879.34 40368.55 30169.27 37380.72 40449.42 34376.54 43652.56 39577.79 32582.19 429
SCA74.22 31972.33 33279.91 29584.05 33362.17 30579.96 37279.29 40466.30 33172.38 33680.13 41151.95 31088.60 34459.25 34477.67 32988.96 304
testing22274.04 32272.66 32878.19 33187.89 21055.36 39781.06 35179.20 40571.30 22574.65 30683.57 36639.11 42388.67 34351.43 40285.75 21490.53 239
tpmrst72.39 34472.13 33473.18 39680.54 40349.91 44079.91 37379.08 40663.11 37071.69 34479.95 41355.32 27182.77 40565.66 28873.89 38386.87 360
tt0320-xc70.11 37067.45 38778.07 33585.33 30259.51 34183.28 32278.96 40758.77 41367.10 39480.28 40936.73 43387.42 36056.83 37259.77 44587.29 348
test_fmvs170.93 35970.52 35272.16 40473.71 44755.05 40180.82 35278.77 40851.21 44878.58 20284.41 34231.20 44876.94 43475.88 17980.12 30084.47 403
PatchmatchNetpermissive73.12 33771.33 34378.49 32783.18 35660.85 32279.63 37478.57 40964.13 35771.73 34379.81 41651.20 32185.97 37557.40 36476.36 35188.66 316
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
testing3-275.12 31275.19 29474.91 37590.40 10945.09 45880.29 36678.42 41078.37 4076.54 25587.75 25444.36 39087.28 36257.04 36883.49 25492.37 168
MDA-MVSNet-bldmvs66.68 39763.66 40775.75 36279.28 42160.56 32773.92 43078.35 41164.43 35350.13 46179.87 41544.02 39383.67 39646.10 43456.86 44783.03 421
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
our_test_369.14 37867.00 39175.57 36579.80 41458.80 34477.96 40077.81 41359.55 40562.90 43078.25 43047.43 35783.97 39451.71 39867.58 42183.93 410
test20.0367.45 39166.95 39268.94 42275.48 44044.84 45977.50 40477.67 41466.66 32363.01 42883.80 35747.02 36178.40 42642.53 44768.86 41783.58 414
WB-MVSnew71.96 35271.65 33872.89 39884.67 32251.88 42682.29 33677.57 41562.31 38273.67 31983.00 37553.49 29281.10 41645.75 43682.13 27385.70 384
test-LLR72.94 34172.43 33074.48 38081.35 39458.04 35378.38 39377.46 41666.66 32369.95 36479.00 42348.06 35579.24 42266.13 28184.83 22586.15 374
test-mter71.41 35470.39 35674.48 38081.35 39458.04 35378.38 39377.46 41660.32 39869.95 36479.00 42336.08 43779.24 42266.13 28184.83 22586.15 374
ECVR-MVScopyleft79.61 20879.26 20180.67 27990.08 11654.69 40487.89 17677.44 41874.88 13980.27 17492.79 10048.96 35292.45 23368.55 26292.50 8494.86 19
UBG73.08 33872.27 33375.51 36788.02 20451.29 43378.35 39677.38 41965.52 34173.87 31682.36 38545.55 38186.48 36955.02 38184.39 23688.75 313
tpm72.37 34671.71 33774.35 38282.19 38052.00 42379.22 38077.29 42064.56 35272.95 32883.68 36351.35 31883.26 40258.33 35675.80 35587.81 335
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
test111179.43 21579.18 20480.15 29189.99 12153.31 41787.33 19577.05 42275.04 13280.23 17692.77 10248.97 35192.33 24168.87 25992.40 8694.81 22
K. test v371.19 35568.51 36779.21 31183.04 36157.78 36184.35 29776.91 42372.90 19662.99 42982.86 37939.27 42091.09 29661.65 32352.66 45688.75 313
UWE-MVS72.13 35071.49 33974.03 38686.66 26947.70 44581.40 34876.89 42463.60 36775.59 27384.22 35039.94 41885.62 37948.98 41786.13 20488.77 312
testgi66.67 39866.53 39467.08 43375.62 43941.69 46875.93 41376.50 42566.11 33265.20 41686.59 29135.72 43874.71 45243.71 44173.38 39084.84 399
test_fmvs268.35 38767.48 38670.98 41569.50 46151.95 42480.05 37076.38 42649.33 45074.65 30684.38 34323.30 46275.40 45074.51 19475.17 37285.60 385
test_vis1_n69.85 37469.21 36371.77 40672.66 45755.27 40081.48 34576.21 42752.03 44475.30 28983.20 37228.97 45176.22 44174.60 19378.41 32083.81 411
PatchMatch-RL72.38 34570.90 34976.80 35688.60 17967.38 17179.53 37576.17 42862.75 37869.36 37182.00 39345.51 38284.89 38853.62 38980.58 29278.12 446
JIA-IIPM66.32 40162.82 41376.82 35577.09 43261.72 31265.34 46175.38 42958.04 42164.51 41962.32 46142.05 40786.51 36851.45 40169.22 41482.21 428
ADS-MVSNet266.20 40463.33 40874.82 37779.92 41058.75 34567.55 45375.19 43053.37 44065.25 41475.86 44242.32 40380.53 41941.57 44868.91 41585.18 392
ETVMVS72.25 34871.05 34775.84 36187.77 22051.91 42579.39 37774.98 43169.26 28373.71 31782.95 37640.82 41586.14 37246.17 43384.43 23589.47 285
PatchT68.46 38667.85 37770.29 41780.70 40143.93 46172.47 43374.88 43260.15 40070.55 35276.57 43849.94 33781.59 41150.58 40474.83 37585.34 389
dp66.80 39665.43 39770.90 41679.74 41648.82 44475.12 42374.77 43359.61 40464.08 42377.23 43542.89 39980.72 41848.86 41866.58 42483.16 418
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 37674.39 45449.89 41261.55 43982.99 422
TESTMET0.1,169.89 37369.00 36572.55 40179.27 42256.85 37378.38 39374.71 43557.64 42368.09 38277.19 43637.75 43076.70 43563.92 30084.09 24084.10 408
YYNet165.03 40662.91 41171.38 40875.85 43756.60 37969.12 44974.66 43657.28 42754.12 45577.87 43245.85 37774.48 45349.95 41161.52 44083.05 420
test_fmvs363.36 41261.82 41567.98 43062.51 47046.96 45177.37 40674.03 43745.24 45567.50 38778.79 42612.16 47472.98 45972.77 21466.02 42683.99 409
PMMVS69.34 37768.67 36671.35 41175.67 43862.03 30675.17 42073.46 43850.00 44968.68 37679.05 42152.07 30878.13 42761.16 32882.77 26573.90 453
PVSNet_057.27 2061.67 41659.27 41968.85 42479.61 41757.44 36768.01 45173.44 43955.93 43358.54 44570.41 45644.58 38877.55 43147.01 42835.91 46871.55 456
Syy-MVS68.05 38867.85 37768.67 42684.68 31940.97 46978.62 39073.08 44066.65 32666.74 39979.46 41852.11 30682.30 40732.89 46176.38 34982.75 424
myMVS_eth3d67.02 39566.29 39569.21 42184.68 31942.58 46478.62 39073.08 44066.65 32666.74 39979.46 41831.53 44782.30 40739.43 45376.38 34982.75 424
test0.0.03 168.00 38967.69 38268.90 42377.55 42947.43 44675.70 41772.95 44266.66 32366.56 40182.29 38848.06 35575.87 44544.97 44074.51 37883.41 415
testing368.56 38467.67 38371.22 41387.33 24242.87 46383.06 33071.54 44370.36 25369.08 37484.38 34330.33 45085.69 37837.50 45675.45 36485.09 396
ADS-MVSNet64.36 40962.88 41268.78 42579.92 41047.17 44967.55 45371.18 44453.37 44065.25 41475.86 44242.32 40373.99 45641.57 44868.91 41585.18 392
Patchmatch-RL test70.24 36867.78 38177.61 34577.43 43059.57 34071.16 43870.33 44562.94 37468.65 37772.77 45150.62 32785.49 38169.58 25266.58 42487.77 336
gg-mvs-nofinetune69.95 37267.96 37575.94 36083.07 35954.51 40777.23 40770.29 44663.11 37070.32 35662.33 46043.62 39588.69 34253.88 38887.76 17384.62 402
door-mid69.98 447
GG-mvs-BLEND75.38 37081.59 38855.80 39279.32 37869.63 44867.19 39273.67 44943.24 39788.90 34050.41 40584.50 23081.45 434
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
door69.44 450
Patchmatch-test64.82 40863.24 40969.57 41979.42 42049.82 44163.49 46769.05 45151.98 44559.95 44180.13 41150.91 32370.98 46040.66 45073.57 38687.90 333
CHOSEN 280x42066.51 39964.71 40171.90 40581.45 39163.52 27557.98 47068.95 45253.57 43962.59 43176.70 43746.22 37375.29 45155.25 37979.68 30276.88 449
MVStest156.63 42252.76 42868.25 42961.67 47153.25 41971.67 43668.90 45338.59 46450.59 46083.05 37425.08 45670.66 46136.76 45738.56 46780.83 438
EGC-MVSNET52.07 43147.05 43567.14 43283.51 34760.71 32480.50 36267.75 4540.07 4820.43 48375.85 44424.26 45981.54 41228.82 46562.25 43759.16 465
ttmdpeth59.91 41857.10 42268.34 42867.13 46546.65 45274.64 42667.41 45548.30 45162.52 43285.04 33320.40 46475.93 44442.55 44645.90 46682.44 426
EPMVS69.02 37968.16 37171.59 40779.61 41749.80 44277.40 40566.93 45662.82 37770.01 36179.05 42145.79 37877.86 43056.58 37475.26 37087.13 354
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
lessismore_v078.97 31481.01 39957.15 37065.99 45861.16 43582.82 38039.12 42291.34 28559.67 33946.92 46388.43 323
dmvs_testset62.63 41364.11 40458.19 44478.55 42524.76 48275.28 41965.94 45967.91 31060.34 43876.01 44153.56 29073.94 45731.79 46267.65 42075.88 451
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
MVS-HIRNet59.14 41957.67 42163.57 43881.65 38643.50 46271.73 43565.06 46139.59 46351.43 45857.73 46638.34 42782.58 40639.53 45173.95 38264.62 462
PM-MVS66.41 40064.14 40373.20 39573.92 44656.45 38078.97 38564.96 46263.88 36564.72 41780.24 41019.84 46683.44 40066.24 28064.52 43179.71 443
UWE-MVS-2865.32 40564.93 39966.49 43478.70 42438.55 47177.86 40364.39 46362.00 38764.13 42283.60 36441.44 40976.00 44331.39 46380.89 28684.92 397
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)
test250677.30 27476.49 27179.74 29990.08 11652.02 42287.86 17863.10 46574.88 13980.16 17792.79 10038.29 42892.35 23968.74 26192.50 8494.86 19
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
WB-MVS54.94 42354.72 42455.60 45073.50 44920.90 48474.27 42961.19 46759.16 40950.61 45974.15 44747.19 36075.78 44617.31 47535.07 46970.12 457
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 30769.48 41173.25 454
SSC-MVS53.88 42653.59 42654.75 45272.87 45519.59 48573.84 43160.53 46957.58 42549.18 46373.45 45046.34 37275.47 44916.20 47832.28 47169.20 458
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
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
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
DSMNet-mixed57.77 42156.90 42360.38 44267.70 46335.61 47369.18 44753.97 47432.30 47257.49 44979.88 41440.39 41768.57 46638.78 45472.37 39576.97 448
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
mvsany_test162.30 41461.26 41865.41 43669.52 46054.86 40366.86 45549.78 47646.65 45368.50 38083.21 37149.15 34866.28 46856.93 37060.77 44175.11 452
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
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
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
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)
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
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
MTMP92.18 3932.83 484
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
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
N_pmnet52.79 42953.26 42751.40 45478.99 4237.68 48869.52 4453.89 48751.63 44657.01 45074.98 44640.83 41465.96 46937.78 45564.67 43080.56 441
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
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
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
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
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 1760.00 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
n20.00 491
nn0.00 491
ab-mvs-re7.23 4499.64 4520.00 4670.00 4900.00 4920.00 4790.00 4910.00 4850.00 48686.72 2830.00 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
TestfortrainingZip93.28 12
WAC-MVS42.58 46439.46 452
PC_three_145268.21 30792.02 1594.00 6382.09 595.98 6184.58 7196.68 294.95 12
eth-test20.00 490
eth-test0.00 490
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 34
GSMVS88.96 304
test_part295.06 872.65 3291.80 16
sam_mvs151.32 31988.96 304
sam_mvs50.01 335
test_post178.90 3875.43 48148.81 35485.44 38359.25 344
test_post5.46 48050.36 33184.24 392
patchmatchnet-post74.00 44851.12 32288.60 344
gm-plane-assit81.40 39253.83 41262.72 37980.94 40192.39 23663.40 304
test9_res84.90 6495.70 3092.87 147
agg_prior282.91 9195.45 3392.70 152
test_prior472.60 3489.01 125
test_prior288.85 13275.41 11784.91 8293.54 7674.28 3383.31 8595.86 24
旧先验286.56 22558.10 42087.04 6188.98 33674.07 199
新几何286.29 239
原ACMM286.86 212
testdata291.01 29862.37 314
segment_acmp73.08 43
testdata184.14 30375.71 108
plane_prior790.08 11668.51 131
plane_prior689.84 12568.70 12560.42 230
plane_prior491.00 159
plane_prior368.60 12878.44 3678.92 195
plane_prior291.25 6079.12 28
plane_prior189.90 124
plane_prior68.71 12390.38 7877.62 4786.16 203
HQP5-MVS66.98 183
HQP-NCC89.33 14489.17 11676.41 8677.23 236
ACMP_Plane89.33 14489.17 11676.41 8677.23 236
BP-MVS77.47 155
HQP4-MVS77.24 23595.11 9491.03 217
HQP2-MVS60.17 233
NP-MVS89.62 12968.32 13590.24 180
MDTV_nov1_ep13_2view37.79 47275.16 42155.10 43566.53 40249.34 34553.98 38787.94 332
ACMMP++_ref81.95 276
ACMMP++81.25 281
Test By Simon64.33 162