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 bysorted bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort by
ESAPD89.48 189.98 188.01 1094.80 472.69 2791.59 2694.10 175.90 7092.29 195.66 381.67 197.38 187.44 1196.34 493.95 32
HSP-MVS89.28 289.76 287.85 2094.28 1873.46 1592.90 892.73 4180.27 1391.35 594.16 2378.35 396.77 1189.59 194.22 4493.33 59
APDe-MVS89.15 389.63 387.73 2294.49 1171.69 4493.83 293.96 575.70 7391.06 696.03 176.84 497.03 789.09 295.65 1594.47 13
SMA-MVS89.08 489.23 488.61 294.25 1973.73 792.40 1493.63 1074.77 9292.29 195.97 274.28 1897.24 388.58 496.91 194.87 5
HPM-MVS++copyleft89.02 589.15 588.63 195.01 376.03 192.38 1592.85 3680.26 1487.78 1594.27 1975.89 896.81 1087.45 1096.44 293.05 69
CNVR-MVS88.93 689.13 688.33 494.77 573.82 690.51 4293.00 2880.90 1088.06 1394.06 2776.43 596.84 988.48 595.99 694.34 17
SteuartSystems-ACMMP88.72 788.86 788.32 592.14 5672.96 2093.73 393.67 980.19 1588.10 1294.80 773.76 2297.11 587.51 995.82 1094.90 4
Skip Steuart: Steuart Systems R&D Blog.
DeepPCF-MVS80.84 188.10 888.56 886.73 4192.24 5469.03 8389.57 6793.39 1777.53 3989.79 894.12 2578.98 296.58 2285.66 1495.72 1194.58 8
SD-MVS88.06 988.50 986.71 4292.60 5272.71 2591.81 2593.19 2277.87 3290.32 794.00 2874.83 1193.78 11887.63 894.27 4293.65 48
NCCC88.06 988.01 1288.24 694.41 1573.62 891.22 3392.83 3781.50 785.79 2593.47 3673.02 2697.00 884.90 1994.94 2694.10 23
ACMMP_Plus88.05 1188.08 1187.94 1393.70 2773.05 1990.86 3693.59 1176.27 6688.14 1195.09 671.06 3996.67 1587.67 796.37 394.09 24
TSAR-MVS + MP.88.02 1288.11 1087.72 2493.68 2972.13 4091.41 2992.35 5474.62 9488.90 993.85 3075.75 996.00 3587.80 694.63 3395.04 2
MP-MVScopyleft87.71 1387.64 1487.93 1694.36 1773.88 492.71 1392.65 4477.57 3583.84 5294.40 1872.24 3396.28 2785.65 1595.30 2393.62 50
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
MP-MVS-pluss87.67 1487.72 1387.54 2893.64 3072.04 4189.80 5993.50 1375.17 8686.34 2095.29 470.86 4096.00 3588.78 396.04 594.58 8
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
HFP-MVS87.58 1587.47 1687.94 1394.58 873.54 1293.04 593.24 1976.78 5284.91 3494.44 1570.78 4196.61 1884.53 2594.89 2893.66 43
zzz-MVS87.53 1687.41 1787.90 1794.18 2374.25 290.23 5092.02 6479.45 1985.88 2294.80 768.07 6196.21 2986.69 1295.34 1993.23 61
ACMMPR87.44 1787.23 1988.08 894.64 673.59 993.04 593.20 2176.78 5284.66 4094.52 1068.81 5996.65 1684.53 2594.90 2794.00 30
APD-MVScopyleft87.44 1787.52 1587.19 3394.24 2072.39 3591.86 2492.83 3773.01 13188.58 1094.52 1073.36 2396.49 2384.26 2995.01 2592.70 77
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
region2R87.42 1987.20 2088.09 794.63 773.55 1093.03 793.12 2476.73 5584.45 4394.52 1069.09 5796.70 1484.37 2894.83 3094.03 27
MCST-MVS87.37 2087.25 1887.73 2294.53 1072.46 3489.82 5793.82 773.07 13084.86 3992.89 4876.22 696.33 2584.89 2195.13 2494.40 14
#test#87.33 2187.13 2187.94 1394.58 873.54 1292.34 1693.24 1975.23 8384.91 3494.44 1570.78 4196.61 1883.75 3394.89 2893.66 43
MTAPA87.23 2287.00 2287.90 1794.18 2374.25 286.58 16992.02 6479.45 1985.88 2294.80 768.07 6196.21 2986.69 1295.34 1993.23 61
XVS87.18 2386.91 2588.00 1194.42 1373.33 1792.78 992.99 3079.14 2183.67 5594.17 2267.45 6896.60 2083.06 3894.50 3594.07 25
HPM-MVScopyleft87.11 2486.98 2387.50 3093.88 2672.16 3992.19 1993.33 1876.07 6983.81 5393.95 2969.77 5196.01 3485.15 1694.66 3294.32 19
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
CP-MVS87.11 2486.92 2487.68 2794.20 2273.86 593.98 192.82 3976.62 5783.68 5494.46 1467.93 6395.95 3784.20 3194.39 3893.23 61
DeepC-MVS79.81 287.08 2686.88 2687.69 2691.16 6672.32 3890.31 4893.94 677.12 4482.82 6494.23 2172.13 3497.09 684.83 2295.37 1893.65 48
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
DeepC-MVS_fast79.65 386.91 2786.62 2887.76 2193.52 3272.37 3791.26 3093.04 2576.62 5784.22 4893.36 3871.44 3796.76 1280.82 5695.33 2194.16 21
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
test_prior386.73 2886.86 2786.33 4892.61 5069.59 7588.85 8692.97 3375.41 7984.91 3493.54 3274.28 1895.48 4583.31 3495.86 893.91 33
PGM-MVS86.68 2986.27 3287.90 1794.22 2173.38 1690.22 5193.04 2575.53 7783.86 5194.42 1767.87 6596.64 1782.70 4394.57 3493.66 43
mPP-MVS86.67 3086.32 3187.72 2494.41 1573.55 1092.74 1192.22 5776.87 5082.81 6694.25 2066.44 7696.24 2882.88 4294.28 4193.38 56
Regformer-286.63 3186.53 2986.95 3889.33 10871.24 4788.43 9992.05 6382.50 186.88 1890.09 10074.45 1395.61 4184.38 2790.63 7094.01 29
CANet86.45 3286.10 3687.51 2990.09 8470.94 5289.70 6392.59 4581.78 481.32 8191.43 7470.34 4497.23 484.26 2993.36 4894.37 15
train_agg86.43 3386.20 3387.13 3593.26 3772.96 2088.75 9191.89 7368.69 20685.00 3293.10 4274.43 1495.41 5084.97 1795.71 1293.02 70
PHI-MVS86.43 3386.17 3587.24 3290.88 7270.96 5092.27 1894.07 472.45 14285.22 3091.90 6169.47 5496.42 2483.28 3695.94 794.35 16
Regformer-186.41 3586.33 3086.64 4389.33 10870.93 5388.43 9991.39 9482.14 386.65 1990.09 10074.39 1695.01 6683.97 3290.63 7093.97 31
CSCG86.41 3586.19 3487.07 3792.91 4472.48 3390.81 3793.56 1273.95 10283.16 6091.07 8175.94 795.19 5779.94 6394.38 3993.55 52
MVS_030486.37 3785.81 4188.02 990.13 8272.39 3589.66 6592.75 4081.64 682.66 6992.04 5764.44 9297.35 284.76 2394.25 4394.33 18
agg_prior186.22 3886.09 3786.62 4492.85 4571.94 4288.59 9691.78 7968.96 20384.41 4493.18 4174.94 1094.93 6784.75 2495.33 2193.01 72
agg_prior386.16 3985.85 4087.10 3693.31 3472.86 2488.77 8991.68 8368.29 21884.26 4792.83 5072.83 2895.42 4984.97 1795.71 1293.02 70
APD-MVS_3200maxsize85.97 4085.88 3886.22 5192.69 4869.53 7791.93 2392.99 3073.54 11785.94 2194.51 1365.80 8395.61 4183.04 4092.51 5593.53 54
canonicalmvs85.91 4185.87 3986.04 5689.84 9069.44 8190.45 4693.00 2876.70 5688.01 1491.23 7673.28 2493.91 10981.50 5188.80 9094.77 6
ACMMPcopyleft85.89 4285.39 4487.38 3193.59 3172.63 2992.74 1193.18 2376.78 5280.73 9093.82 3164.33 9396.29 2682.67 4490.69 6993.23 61
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
CDPH-MVS85.76 4385.29 4887.17 3493.49 3371.08 4888.58 9792.42 5168.32 21784.61 4193.48 3472.32 3296.15 3279.00 6695.43 1794.28 20
TSAR-MVS + GP.85.71 4485.33 4586.84 3991.34 6472.50 3289.07 8087.28 21376.41 5985.80 2490.22 9874.15 2195.37 5481.82 4791.88 5792.65 80
Regformer-485.68 4585.45 4386.35 4788.95 12469.67 7388.29 10991.29 9681.73 585.36 2890.01 10372.62 3095.35 5583.28 3687.57 10594.03 27
alignmvs85.48 4685.32 4685.96 5889.51 10269.47 7989.74 6192.47 4776.17 6787.73 1691.46 7370.32 4593.78 11881.51 5088.95 8694.63 7
3Dnovator+77.84 485.48 4684.47 5488.51 391.08 6773.49 1493.18 493.78 880.79 1176.66 15493.37 3760.40 16596.75 1377.20 8493.73 4795.29 1
MSLP-MVS++85.43 4885.76 4284.45 8591.93 5970.24 6190.71 3992.86 3577.46 4184.22 4892.81 5367.16 7292.94 16180.36 5994.35 4090.16 158
DELS-MVS85.41 4985.30 4785.77 5988.49 14067.93 11285.52 20793.44 1578.70 2883.63 5789.03 12774.57 1295.71 4080.26 6194.04 4593.66 43
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
HPM-MVS_fast85.35 5084.95 5186.57 4693.69 2870.58 5992.15 2191.62 8473.89 10682.67 6894.09 2662.60 12595.54 4480.93 5492.93 5093.57 51
Regformer-385.23 5185.07 4985.70 6088.95 12469.01 8588.29 10989.91 14480.95 985.01 3190.01 10372.45 3194.19 9682.50 4587.57 10593.90 35
abl_685.23 5184.95 5186.07 5492.23 5570.48 6090.80 3892.08 6273.51 11885.26 2994.16 2362.75 11895.92 3882.46 4691.30 6491.81 105
MVS_111021_HR85.14 5384.75 5386.32 5091.65 6272.70 2685.98 18590.33 12576.11 6882.08 7291.61 6871.36 3894.17 9881.02 5292.58 5492.08 98
UA-Net85.08 5484.96 5085.45 6192.07 5768.07 11089.78 6090.86 10882.48 284.60 4293.20 4069.35 5595.22 5671.39 14590.88 6893.07 68
casdiffmvs184.76 5584.33 5586.04 5689.40 10568.78 9089.67 6492.54 4666.43 23585.41 2690.75 8972.88 2794.76 7881.64 4990.24 7594.57 10
EI-MVSNet-Vis-set84.19 5683.81 5685.31 6388.18 15067.85 11387.66 12489.73 14880.05 1782.95 6189.59 11270.74 4394.82 7680.66 5884.72 14093.28 60
casdiffmvs83.96 5783.25 6186.07 5488.48 14169.60 7489.26 7292.40 5268.07 21982.82 6490.03 10269.77 5194.86 7581.79 4886.64 12193.75 41
nrg03083.88 5883.53 5784.96 7386.77 19369.28 8290.46 4592.67 4274.79 9182.95 6191.33 7572.70 2993.09 15480.79 5779.28 21592.50 84
EI-MVSNet-UG-set83.81 5983.38 5985.09 7087.87 15867.53 11787.44 13689.66 14979.74 1882.23 7189.41 12170.24 4694.74 7979.95 6283.92 14692.99 73
CPTT-MVS83.73 6083.33 6084.92 7693.28 3670.86 5592.09 2290.38 12068.75 20579.57 9792.83 5060.60 16193.04 15880.92 5591.56 6190.86 128
EPNet83.72 6182.92 6786.14 5384.22 22769.48 7891.05 3585.27 23381.30 876.83 15091.65 6566.09 7995.56 4376.00 9593.85 4693.38 56
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
HQP_MVS83.64 6283.14 6285.14 6890.08 8568.71 9691.25 3192.44 4879.12 2378.92 10491.00 8560.42 16395.38 5278.71 6986.32 12691.33 115
Effi-MVS+83.62 6383.08 6385.24 6688.38 14667.45 11888.89 8489.15 16675.50 7882.27 7088.28 14669.61 5394.45 8677.81 7887.84 10393.84 38
OPM-MVS83.50 6482.95 6685.14 6888.79 13270.95 5189.13 7991.52 8877.55 3880.96 8891.75 6360.71 15794.50 8579.67 6486.51 12489.97 176
Vis-MVSNetpermissive83.46 6582.80 6985.43 6290.25 8168.74 9490.30 4990.13 13476.33 6580.87 8992.89 4861.00 15494.20 9572.45 13490.97 6693.35 58
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
MG-MVS83.41 6683.45 5883.28 12392.74 4762.28 22788.17 11389.50 15375.22 8481.49 7992.74 5466.75 7395.11 6072.85 12791.58 6092.45 85
EPP-MVSNet83.40 6783.02 6584.57 8190.13 8264.47 18392.32 1790.73 10974.45 9679.35 10091.10 7969.05 5895.12 5972.78 12887.22 11294.13 22
3Dnovator76.31 583.38 6882.31 7586.59 4587.94 15772.94 2390.64 4092.14 6177.21 4275.47 18192.83 5058.56 17294.72 8073.24 12592.71 5392.13 97
MVS_Test83.15 6983.06 6483.41 12086.86 19063.21 21386.11 18392.00 6774.31 9782.87 6389.44 12070.03 4793.21 14577.39 8388.50 9993.81 39
IS-MVSNet83.15 6982.81 6884.18 9489.94 8863.30 21091.59 2688.46 19479.04 2579.49 9892.16 5565.10 8894.28 8967.71 16991.86 5894.95 3
DP-MVS Recon83.11 7182.09 7786.15 5294.44 1270.92 5488.79 8892.20 5870.53 17479.17 10191.03 8464.12 9596.03 3368.39 16890.14 7691.50 111
PAPM_NR83.02 7282.41 7284.82 7892.47 5366.37 13587.93 12091.80 7773.82 11177.32 14290.66 9167.90 6494.90 7170.37 15089.48 8393.19 65
VDD-MVS83.01 7382.36 7484.96 7391.02 6966.40 13488.91 8388.11 19777.57 3584.39 4693.29 3952.19 22393.91 10977.05 8788.70 9294.57 10
MVSFormer82.85 7482.05 7885.24 6687.35 18070.21 6290.50 4390.38 12068.55 20881.32 8189.47 11561.68 13993.46 13678.98 6790.26 7392.05 99
OMC-MVS82.69 7581.97 8184.85 7788.75 13467.42 11987.98 11690.87 10774.92 9079.72 9691.65 6562.19 13693.96 10475.26 10786.42 12593.16 66
diffmvs182.63 7682.51 7082.96 14583.87 24663.47 20585.19 20989.42 15675.58 7681.38 8089.89 10567.42 7091.69 20381.01 5388.88 8893.71 42
PVSNet_Blended_VisFu82.62 7781.83 8284.96 7390.80 7469.76 7188.74 9391.70 8269.39 18978.96 10388.46 14165.47 8594.87 7474.42 11188.57 9590.24 156
MVS_111021_LR82.61 7882.11 7684.11 9588.82 12971.58 4585.15 21286.16 22674.69 9380.47 9291.04 8262.29 13390.55 23580.33 6090.08 7790.20 157
HQP-MVS82.61 7882.02 7984.37 8789.33 10866.98 12789.17 7492.19 5976.41 5977.23 14590.23 9760.17 16695.11 6077.47 8185.99 13191.03 122
CLD-MVS82.31 8081.65 8384.29 9188.47 14267.73 11685.81 19492.35 5475.78 7178.33 11886.58 20264.01 9694.35 8776.05 9487.48 11090.79 129
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
VNet82.21 8182.41 7281.62 18890.82 7360.93 23584.47 22789.78 14676.36 6484.07 5091.88 6264.71 9190.26 23770.68 14788.89 8793.66 43
LPG-MVS_test82.08 8281.27 8684.50 8389.23 11668.76 9290.22 5191.94 7175.37 8176.64 15591.51 7054.29 20694.91 6978.44 7183.78 14789.83 180
FIs82.07 8382.42 7181.04 20188.80 13158.34 25688.26 11193.49 1476.93 4978.47 11291.04 8269.92 4992.34 17969.87 15584.97 13792.44 86
PS-MVSNAJss82.07 8381.31 8584.34 9086.51 19667.27 12389.27 7191.51 8971.75 15479.37 9990.22 9863.15 10694.27 9077.69 7982.36 17691.49 112
API-MVS81.99 8581.23 8784.26 9290.94 7070.18 6791.10 3489.32 15971.51 16078.66 10888.28 14665.26 8695.10 6364.74 19891.23 6587.51 250
UniMVSNet_NR-MVSNet81.88 8681.54 8482.92 14688.46 14363.46 20687.13 14992.37 5380.19 1578.38 11689.14 12371.66 3693.05 15670.05 15276.46 25092.25 92
MAR-MVS81.84 8780.70 9485.27 6591.32 6571.53 4689.82 5790.92 10569.77 18478.50 11086.21 21562.36 13294.52 8465.36 19192.05 5689.77 187
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
LFMVS81.82 8881.23 8783.57 11591.89 6063.43 20889.84 5681.85 27977.04 4783.21 5893.10 4252.26 22293.43 14071.98 14089.95 7993.85 36
xiu_mvs_v2_base81.69 8981.05 9183.60 11389.15 11968.03 11184.46 22990.02 13970.67 17181.30 8486.53 20563.17 10594.19 9675.60 10388.54 9788.57 228
PS-MVSNAJ81.69 8981.02 9283.70 11189.51 10268.21 10884.28 23690.09 13570.79 16881.26 8585.62 23463.15 10694.29 8875.62 10288.87 8988.59 226
PAPR81.66 9180.89 9383.99 10490.27 8064.00 19486.76 16591.77 8168.84 20477.13 14989.50 11367.63 6694.88 7367.55 17188.52 9893.09 67
UniMVSNet (Re)81.60 9281.11 9083.09 13388.38 14664.41 18587.60 12593.02 2778.42 3178.56 10988.16 14869.78 5093.26 14469.58 15876.49 24991.60 107
FC-MVSNet-test81.52 9382.02 7980.03 21688.42 14555.97 29587.95 11893.42 1677.10 4577.38 14090.98 8769.96 4891.79 19368.46 16784.50 14192.33 88
VDDNet81.52 9380.67 9584.05 9990.44 7864.13 19089.73 6285.91 22971.11 16483.18 5993.48 3450.54 25993.49 13573.40 12388.25 10194.54 12
ACMP74.13 681.51 9580.57 9684.36 8889.42 10468.69 9989.97 5591.50 9274.46 9575.04 19790.41 9453.82 21194.54 8277.56 8082.91 16789.86 179
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
diffmvs81.48 9681.21 8982.31 16983.28 26162.72 22285.09 21388.63 19174.99 8778.31 11988.81 13165.80 8391.36 21579.03 6586.95 11692.84 76
jason81.39 9780.29 10284.70 8086.63 19469.90 6985.95 18686.77 21763.24 26681.07 8789.47 11561.08 15392.15 18378.33 7490.07 7892.05 99
jason: jason.
lupinMVS81.39 9780.27 10384.76 7987.35 18070.21 6285.55 20386.41 22162.85 27281.32 8188.61 13661.68 13992.24 18278.41 7390.26 7391.83 103
0601test81.17 9980.47 9983.24 12689.13 12063.62 19986.21 18089.95 14172.43 14581.78 7789.61 11157.50 18093.58 13070.75 14686.90 11792.52 83
DU-MVS81.12 10080.52 9882.90 14787.80 16863.46 20687.02 15491.87 7579.01 2678.38 11689.07 12565.02 8993.05 15670.05 15276.46 25092.20 94
PVSNet_Blended80.98 10180.34 10082.90 14788.85 12665.40 15184.43 23192.00 6767.62 22378.11 12885.05 24666.02 8194.27 9071.52 14389.50 8289.01 206
mvs-test180.88 10279.40 12185.29 6485.13 21469.75 7289.28 7088.10 19874.99 8776.44 16086.72 18957.27 18294.26 9473.53 12183.18 16491.87 102
QAPM80.88 10279.50 11985.03 7188.01 15668.97 8791.59 2692.00 6766.63 23375.15 19492.16 5557.70 17795.45 4763.52 20288.76 9190.66 137
112180.84 10479.77 10984.05 9993.11 4170.78 5684.66 22185.42 23257.37 31681.76 7892.02 5863.41 9994.12 9967.28 17492.93 5087.26 257
TranMVSNet+NR-MVSNet80.84 10480.31 10182.42 16687.85 15962.33 22587.74 12391.33 9580.55 1277.99 13189.86 10665.23 8792.62 16967.05 17975.24 26892.30 90
UGNet80.83 10679.59 11484.54 8288.04 15468.09 10989.42 6888.16 19676.95 4876.22 16689.46 11749.30 27293.94 10668.48 16690.31 7291.60 107
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
Fast-Effi-MVS+80.81 10779.92 10683.47 11688.85 12664.51 17785.53 20589.39 15770.79 16878.49 11185.06 24567.54 6793.58 13067.03 18086.58 12292.32 89
XVG-OURS-SEG-HR80.81 10779.76 11083.96 10685.60 20668.78 9083.54 24790.50 11770.66 17276.71 15391.66 6460.69 15891.26 21876.94 8881.58 18391.83 103
xiu_mvs_v1_base_debu80.80 10979.72 11184.03 10187.35 18070.19 6485.56 20088.77 18569.06 19881.83 7388.16 14850.91 24692.85 16378.29 7587.56 10789.06 199
xiu_mvs_v1_base80.80 10979.72 11184.03 10187.35 18070.19 6485.56 20088.77 18569.06 19881.83 7388.16 14850.91 24692.85 16378.29 7587.56 10789.06 199
xiu_mvs_v1_base_debi80.80 10979.72 11184.03 10187.35 18070.19 6485.56 20088.77 18569.06 19881.83 7388.16 14850.91 24692.85 16378.29 7587.56 10789.06 199
ACMM73.20 880.78 11279.84 10883.58 11489.31 11368.37 10389.99 5491.60 8570.28 17877.25 14389.66 10953.37 21493.53 13474.24 11482.85 16888.85 212
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
114514_t80.68 11379.51 11884.20 9394.09 2567.27 12389.64 6691.11 10158.75 30674.08 20490.72 9058.10 17595.04 6569.70 15689.42 8490.30 155
CANet_DTU80.61 11479.87 10782.83 15385.60 20663.17 21687.36 13788.65 18976.37 6375.88 17388.44 14253.51 21393.07 15573.30 12489.74 8192.25 92
VPA-MVSNet80.60 11580.55 9780.76 20588.07 15360.80 23886.86 15991.58 8675.67 7480.24 9389.45 11963.34 10090.25 23870.51 14979.22 21691.23 118
PVSNet_BlendedMVS80.60 11580.02 10482.36 16888.85 12665.40 15186.16 18192.00 6769.34 19278.11 12886.09 21866.02 8194.27 9071.52 14382.06 17787.39 252
AdaColmapbinary80.58 11779.42 12084.06 9893.09 4268.91 8889.36 6988.97 17669.27 19375.70 18089.69 10857.20 18595.77 3963.06 20688.41 10087.50 251
EI-MVSNet80.52 11879.98 10582.12 17084.28 22463.19 21586.41 17488.95 17874.18 9978.69 10687.54 16766.62 7492.43 17472.57 13380.57 19590.74 132
XVG-OURS80.41 11979.23 13083.97 10585.64 20569.02 8483.03 25790.39 11971.09 16577.63 13791.49 7254.62 20491.35 21675.71 10083.47 15691.54 109
v1neww80.40 12079.54 11582.98 14084.10 23564.51 17787.57 12790.22 12973.25 12378.47 11286.65 19762.83 11493.86 11275.72 9877.02 23590.58 143
v7new80.40 12079.54 11582.98 14084.10 23564.51 17787.57 12790.22 12973.25 12378.47 11286.65 19762.83 11493.86 11275.72 9877.02 23590.58 143
v680.40 12079.54 11582.98 14084.09 23764.50 18187.57 12790.22 12973.25 12378.47 11286.63 19962.84 11393.86 11275.73 9777.02 23590.58 143
PCF-MVS73.52 780.38 12378.84 13785.01 7287.71 17368.99 8683.65 24491.46 9363.00 26977.77 13590.28 9566.10 7895.09 6461.40 22288.22 10290.94 126
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
X-MVStestdata80.37 12477.83 15988.00 1194.42 1373.33 1792.78 992.99 3079.14 2183.67 5512.47 36367.45 6896.60 2083.06 3894.50 3594.07 25
test_djsdf80.30 12579.32 12483.27 12483.98 24465.37 15490.50 4390.38 12068.55 20876.19 16788.70 13256.44 18993.46 13678.98 6780.14 20290.97 125
v780.24 12679.26 12983.15 13084.07 24164.94 16587.56 13190.67 11072.26 14878.28 12086.51 20661.45 14494.03 10375.14 10877.41 22990.49 148
v2v48280.23 12779.29 12883.05 13683.62 25364.14 18987.04 15389.97 14073.61 11478.18 12787.22 17561.10 15293.82 11576.11 9376.78 24791.18 119
NR-MVSNet80.23 12779.38 12282.78 15987.80 16863.34 20986.31 17791.09 10279.01 2672.17 22989.07 12567.20 7192.81 16766.08 18675.65 25992.20 94
Anonymous2024052980.19 12978.89 13684.10 9690.60 7564.75 17088.95 8290.90 10665.97 24280.59 9191.17 7849.97 26493.73 12769.16 16282.70 17293.81 39
v114180.19 12979.31 12582.85 15083.84 24864.12 19187.14 14690.08 13673.13 12678.27 12186.39 20862.67 12393.75 12275.40 10576.83 24490.68 134
divwei89l23v2f11280.19 12979.31 12582.85 15083.84 24864.11 19387.13 14990.08 13673.13 12678.27 12186.39 20862.69 12193.75 12275.40 10576.82 24590.68 134
v180.19 12979.31 12582.85 15083.83 25064.12 19187.14 14690.07 13873.13 12678.27 12186.38 21262.72 12093.75 12275.41 10476.82 24590.68 134
IterMVS-LS80.06 13379.38 12282.11 17185.89 20163.20 21486.79 16289.34 15874.19 9875.45 18386.72 18966.62 7492.39 17672.58 13276.86 24190.75 131
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
Effi-MVS+-dtu80.03 13478.57 14284.42 8685.13 21468.74 9488.77 8988.10 19874.99 8774.97 19883.49 26557.27 18293.36 14173.53 12180.88 18991.18 119
v114480.03 13479.03 13383.01 13883.78 25164.51 17787.11 15190.57 11571.96 15378.08 13086.20 21661.41 14593.94 10674.93 10977.23 23190.60 140
v879.97 13679.02 13482.80 15684.09 23764.50 18187.96 11790.29 12874.13 10175.24 19286.81 18662.88 11193.89 11174.39 11275.40 26490.00 169
DI_MVS_plusplus_test79.89 13778.58 14183.85 11082.89 27365.32 15586.12 18289.55 15169.64 18870.55 24785.82 22957.24 18493.81 11676.85 8988.55 9692.41 87
test_normal79.81 13878.45 14483.89 10982.70 27765.40 15185.82 19389.48 15469.39 18970.12 25685.66 23257.15 18693.71 12877.08 8688.62 9492.56 82
OpenMVScopyleft72.83 1079.77 13978.33 15084.09 9785.17 21169.91 6890.57 4190.97 10466.70 22972.17 22991.91 6054.70 20293.96 10461.81 21990.95 6788.41 234
v1079.74 14078.67 13882.97 14484.06 24264.95 16487.88 12290.62 11373.11 12975.11 19586.56 20361.46 14394.05 10273.68 11775.55 26189.90 177
BH-RMVSNet79.61 14178.44 14683.14 13189.38 10765.93 14184.95 21687.15 21473.56 11678.19 12689.79 10756.67 18893.36 14159.53 23786.74 11990.13 160
v119279.59 14278.43 14783.07 13583.55 25564.52 17586.93 15790.58 11470.83 16777.78 13485.90 22559.15 16993.94 10673.96 11677.19 23390.76 130
ab-mvs79.51 14378.97 13581.14 19988.46 14360.91 23683.84 24289.24 16470.36 17679.03 10288.87 12963.23 10490.21 23965.12 19382.57 17492.28 91
WR-MVS79.49 14479.22 13180.27 21388.79 13258.35 25585.06 21488.61 19278.56 2977.65 13688.34 14463.81 9890.66 23464.98 19677.22 23291.80 106
v14419279.47 14578.37 14882.78 15983.35 25863.96 19586.96 15590.36 12369.99 18177.50 13885.67 23160.66 15993.77 12074.27 11376.58 24890.62 138
BH-untuned79.47 14578.60 14082.05 17289.19 11865.91 14286.07 18488.52 19372.18 15075.42 18487.69 16261.15 15193.54 13360.38 22986.83 11886.70 270
mvs_anonymous79.42 14779.11 13280.34 21084.45 22357.97 26282.59 25887.62 20767.40 22876.17 17088.56 13968.47 6089.59 24770.65 14886.05 13093.47 55
tttt051779.40 14877.91 15783.90 10888.10 15263.84 19788.37 10684.05 24471.45 16176.78 15189.12 12449.93 26794.89 7270.18 15183.18 16492.96 74
V4279.38 14978.24 15282.83 15381.10 29965.50 15085.55 20389.82 14571.57 15978.21 12586.12 21760.66 15993.18 14975.64 10175.46 26389.81 182
jajsoiax79.29 15077.96 15583.27 12484.68 22066.57 13389.25 7390.16 13369.20 19575.46 18289.49 11445.75 29493.13 15276.84 9080.80 19190.11 161
v192192079.22 15178.03 15482.80 15683.30 26063.94 19686.80 16190.33 12569.91 18277.48 13985.53 23658.44 17393.75 12273.60 12076.85 24290.71 133
TAPA-MVS73.13 979.15 15277.94 15682.79 15889.59 9762.99 22088.16 11491.51 8965.77 24377.14 14891.09 8060.91 15593.21 14550.26 28887.05 11492.17 96
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
mvs_tets79.13 15377.77 16283.22 12784.70 21966.37 13589.17 7490.19 13269.38 19175.40 18589.46 11744.17 30093.15 15076.78 9180.70 19390.14 159
CDS-MVSNet79.07 15477.70 16383.17 12987.60 17568.23 10784.40 23386.20 22567.49 22676.36 16186.54 20461.54 14290.79 23261.86 21887.33 11190.49 148
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
MVSTER79.01 15577.88 15882.38 16783.07 26764.80 16884.08 24088.95 17869.01 20278.69 10687.17 17854.70 20292.43 17474.69 11080.57 19589.89 178
v124078.99 15677.78 16182.64 16383.21 26263.54 20286.62 16890.30 12769.74 18777.33 14185.68 23057.04 18793.76 12173.13 12676.92 23890.62 138
Anonymous2023121178.97 15777.69 16482.81 15590.54 7664.29 18790.11 5391.51 8965.01 25276.16 17188.13 15250.56 25893.03 15969.68 15777.56 22791.11 121
v7n78.97 15777.58 16683.14 13183.45 25765.51 14988.32 10791.21 9873.69 11372.41 22686.32 21357.93 17693.81 11669.18 16175.65 25990.11 161
TAMVS78.89 15977.51 16783.03 13787.80 16867.79 11584.72 22085.05 23667.63 22276.75 15287.70 16162.25 13490.82 23158.53 24687.13 11390.49 148
v14878.72 16077.80 16081.47 19282.73 27661.96 23086.30 17888.08 20073.26 12276.18 16885.47 23862.46 13192.36 17871.92 14273.82 28190.09 163
VPNet78.69 16178.66 13978.76 24488.31 14855.72 30184.45 23086.63 21976.79 5178.26 12490.55 9359.30 16889.70 24666.63 18177.05 23490.88 127
anonymousdsp78.60 16277.15 17282.98 14080.51 30567.08 12587.24 14489.53 15265.66 24575.16 19387.19 17752.52 21692.25 18177.17 8579.34 21489.61 191
WR-MVS_H78.51 16378.49 14378.56 24788.02 15556.38 28988.43 9992.67 4277.14 4373.89 20587.55 16666.25 7789.24 25458.92 24173.55 28390.06 167
GBi-Net78.40 16477.40 16881.40 19487.60 17563.01 21788.39 10389.28 16071.63 15675.34 18787.28 17154.80 19891.11 22262.72 20779.57 21090.09 163
test178.40 16477.40 16881.40 19487.60 17563.01 21788.39 10389.28 16071.63 15675.34 18787.28 17154.80 19891.11 22262.72 20779.57 21090.09 163
Vis-MVSNet (Re-imp)78.36 16678.45 14478.07 25688.64 13651.78 32486.70 16679.63 30074.14 10075.11 19590.83 8861.29 14889.75 24458.10 25191.60 5992.69 79
Anonymous20240521178.25 16777.01 17481.99 17491.03 6860.67 23984.77 21983.90 24670.65 17380.00 9491.20 7741.08 31791.43 21365.21 19285.26 13593.85 36
CP-MVSNet78.22 16878.34 14977.84 25887.83 16654.54 30687.94 11991.17 10077.65 3373.48 20788.49 14062.24 13588.43 27462.19 21374.07 27690.55 146
BH-w/o78.21 16977.33 17080.84 20388.81 13065.13 16184.87 21787.85 20469.75 18574.52 20284.74 25261.34 14693.11 15358.24 25085.84 13384.27 303
FMVSNet278.20 17077.21 17181.20 19787.60 17562.89 22187.47 13589.02 16971.63 15675.29 19187.28 17154.80 19891.10 22562.38 21179.38 21389.61 191
MVS78.19 17176.99 17581.78 17885.66 20466.99 12684.66 22190.47 11855.08 32672.02 23485.27 24163.83 9794.11 10166.10 18589.80 8084.24 304
Baseline_NR-MVSNet78.15 17278.33 15077.61 26285.79 20256.21 29386.78 16385.76 23073.60 11577.93 13287.57 16565.02 8988.99 26567.14 17875.33 26587.63 247
CNLPA78.08 17376.79 17981.97 17590.40 7971.07 4987.59 12684.55 23966.03 24172.38 22789.64 11057.56 17986.04 29259.61 23583.35 16188.79 215
PLCcopyleft70.83 1178.05 17476.37 18583.08 13491.88 6167.80 11488.19 11289.46 15564.33 25969.87 26288.38 14353.66 21293.58 13058.86 24282.73 17087.86 243
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
Fast-Effi-MVS+-dtu78.02 17576.49 18282.62 16483.16 26666.96 12986.94 15687.45 21272.45 14271.49 24084.17 25554.79 20191.58 21167.61 17080.31 19989.30 195
PS-CasMVS78.01 17678.09 15377.77 26087.71 17354.39 30888.02 11591.22 9777.50 4073.26 20988.64 13560.73 15688.41 27561.88 21773.88 28090.53 147
v74877.97 17776.65 18181.92 17782.29 28363.28 21187.53 13290.35 12473.50 11970.76 24685.55 23558.28 17492.81 16768.81 16572.76 28889.67 189
V477.95 17876.37 18582.67 16179.40 31865.52 14786.43 17289.94 14272.28 14672.14 23284.95 24755.72 19293.44 13873.64 11872.86 28689.05 203
HY-MVS69.67 1277.95 17877.15 17280.36 20987.57 17960.21 24383.37 25587.78 20566.11 23875.37 18687.06 18463.27 10290.48 23661.38 22382.43 17590.40 153
v5277.94 18076.37 18582.67 16179.39 31965.52 14786.43 17289.94 14272.28 14672.15 23184.94 24855.70 19393.44 13873.64 11872.84 28789.06 199
FMVSNet377.88 18176.85 17780.97 20286.84 19162.36 22486.52 17188.77 18571.13 16375.34 18786.66 19654.07 20991.10 22562.72 20779.57 21089.45 193
Test477.83 18275.90 20083.62 11280.24 30765.25 15785.27 20890.67 11069.03 20166.48 29783.75 26143.07 30593.00 16075.93 9688.66 9392.62 81
PEN-MVS77.73 18377.69 16477.84 25887.07 18853.91 31087.91 12191.18 9977.56 3773.14 21188.82 13061.23 14989.17 26159.95 23272.37 28990.43 151
v1677.69 18476.36 18881.68 18584.15 23264.63 17487.33 13988.99 17372.69 14069.31 27082.08 27862.80 11791.79 19372.70 13067.23 31288.63 220
v1777.68 18576.35 18981.69 18484.15 23264.65 17287.33 13988.99 17372.70 13969.25 27182.07 27962.82 11691.79 19372.69 13167.15 31488.63 220
PAPM77.68 18576.40 18481.51 19187.29 18561.85 23183.78 24389.59 15064.74 25471.23 24188.70 13262.59 12693.66 12952.66 27887.03 11589.01 206
v1877.67 18776.35 18981.64 18784.09 23764.47 18387.27 14289.01 17172.59 14169.39 26782.04 28062.85 11291.80 19272.72 12967.20 31388.63 220
CHOSEN 1792x268877.63 18875.69 20183.44 11789.98 8768.58 10178.70 29487.50 21056.38 32175.80 17586.84 18558.67 17191.40 21461.58 22185.75 13490.34 154
HyFIR lowres test77.53 18975.40 20983.94 10789.59 9766.62 13180.36 27788.64 19056.29 32276.45 15785.17 24257.64 17893.28 14361.34 22483.10 16691.91 101
V1477.52 19076.12 19381.70 18384.15 23264.77 16987.21 14588.95 17872.80 13668.79 27381.94 28662.69 12191.72 19972.31 13666.27 32188.60 224
V977.52 19076.11 19681.73 18284.19 23164.89 16687.26 14388.94 18172.87 13568.65 27681.96 28562.65 12491.72 19972.27 13766.24 32288.60 224
v1577.51 19276.12 19381.66 18684.09 23764.65 17287.14 14688.96 17772.76 13768.90 27281.91 28762.74 11991.73 19772.32 13566.29 32088.61 223
v1277.51 19276.09 19781.76 18184.22 22764.99 16387.30 14188.93 18272.92 13268.48 28081.97 28362.54 12891.70 20272.24 13866.21 32488.58 227
v1377.50 19476.07 19881.77 17984.23 22665.07 16287.34 13888.91 18372.92 13268.35 28181.97 28362.53 12991.69 20372.20 13966.22 32388.56 229
v1177.45 19576.06 19981.59 19084.22 22764.52 17587.11 15189.02 16972.76 13768.76 27481.90 28862.09 13791.71 20171.98 14066.73 31588.56 229
FMVSNet177.44 19676.12 19381.40 19486.81 19263.01 21788.39 10389.28 16070.49 17574.39 20387.28 17149.06 27591.11 22260.91 22678.52 21890.09 163
TR-MVS77.44 19676.18 19281.20 19788.24 14963.24 21284.61 22586.40 22267.55 22577.81 13386.48 20754.10 20893.15 15057.75 25482.72 17187.20 258
1112_ss77.40 19876.43 18380.32 21189.11 12360.41 24283.65 24487.72 20662.13 28073.05 21286.72 18962.58 12789.97 24162.11 21680.80 19190.59 142
thisisatest051577.33 19975.38 21083.18 12885.27 21063.80 19882.11 26283.27 25665.06 25075.91 17283.84 25949.54 26994.27 9067.24 17686.19 12891.48 114
pm-mvs177.25 20076.68 18078.93 24184.22 22758.62 25386.41 17488.36 19571.37 16273.31 20888.01 15461.22 15089.15 26264.24 20073.01 28589.03 205
LCM-MVSNet-Re77.05 20176.94 17677.36 26787.20 18651.60 32580.06 27980.46 29175.20 8567.69 28586.72 18962.48 13088.98 26663.44 20389.25 8591.51 110
DTE-MVSNet76.99 20276.80 17877.54 26486.24 19853.06 32187.52 13390.66 11277.08 4672.50 21788.67 13460.48 16289.52 24857.33 25870.74 30090.05 168
Anonymous2024052176.96 20376.26 19179.07 23986.63 19456.37 29087.57 12791.09 10272.19 14971.23 24188.10 15354.30 20591.20 22158.34 24876.89 23989.65 190
LS3D76.95 20474.82 22083.37 12190.45 7767.36 12289.15 7886.94 21661.87 28269.52 26590.61 9251.71 23994.53 8346.38 31486.71 12088.21 236
GA-MVS76.87 20575.17 21881.97 17582.75 27562.58 22381.44 27186.35 22472.16 15274.74 20082.89 26846.20 28992.02 18668.85 16481.09 18791.30 117
DP-MVS76.78 20674.57 22283.42 11893.29 3569.46 8088.55 9883.70 24863.98 26370.20 25288.89 12854.01 21094.80 7746.66 31181.88 18086.01 286
cascas76.72 20774.64 22182.99 13985.78 20365.88 14382.33 26089.21 16560.85 28872.74 21481.02 29547.28 28293.75 12267.48 17285.02 13689.34 194
conf200view1176.55 20875.55 20479.57 22889.52 9956.99 27685.83 19083.23 25773.94 10376.32 16287.12 17951.89 23091.95 18748.33 29683.75 14989.78 183
tfpn11176.54 20975.51 20679.61 22589.52 9956.99 27685.83 19083.23 25773.94 10376.32 16287.12 17951.89 23092.06 18548.04 30383.73 15389.78 183
131476.53 21075.30 21380.21 21483.93 24562.32 22684.66 22188.81 18460.23 29270.16 25584.07 25755.30 19690.73 23367.37 17383.21 16387.59 249
thres100view90076.50 21175.55 20479.33 23089.52 9956.99 27685.83 19083.23 25773.94 10376.32 16287.12 17951.89 23091.95 18748.33 29683.75 14989.07 197
thres600view776.50 21175.44 20779.68 22289.40 10557.16 27385.53 20583.23 25773.79 11276.26 16587.09 18251.89 23091.89 19148.05 30283.72 15490.00 169
thres40076.50 21175.37 21179.86 21889.13 12057.65 26885.17 21083.60 24973.41 12076.45 15786.39 20852.12 22491.95 18748.33 29683.75 14990.00 169
tfpn200view976.42 21475.37 21179.55 22989.13 12057.65 26885.17 21083.60 24973.41 12076.45 15786.39 20852.12 22491.95 18748.33 29683.75 14989.07 197
Test_1112_low_res76.40 21575.44 20779.27 23189.28 11458.09 25881.69 26787.07 21559.53 29972.48 21986.67 19561.30 14789.33 25260.81 22880.15 20190.41 152
F-COLMAP76.38 21674.33 22782.50 16589.28 11466.95 13088.41 10289.03 16864.05 26166.83 29388.61 13646.78 28592.89 16257.48 25578.55 21787.67 246
LTVRE_ROB69.57 1376.25 21774.54 22481.41 19388.60 13764.38 18679.24 28789.12 16770.76 17069.79 26487.86 15549.09 27493.20 14756.21 26480.16 20086.65 271
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
view60076.20 21875.21 21479.16 23589.64 9255.82 29685.74 19582.06 27473.88 10775.74 17687.85 15651.84 23491.66 20546.75 30783.42 15790.00 169
view80076.20 21875.21 21479.16 23589.64 9255.82 29685.74 19582.06 27473.88 10775.74 17687.85 15651.84 23491.66 20546.75 30783.42 15790.00 169
conf0.05thres100076.20 21875.21 21479.16 23589.64 9255.82 29685.74 19582.06 27473.88 10775.74 17687.85 15651.84 23491.66 20546.75 30783.42 15790.00 169
tfpn76.20 21875.21 21479.16 23589.64 9255.82 29685.74 19582.06 27473.88 10775.74 17687.85 15651.84 23491.66 20546.75 30783.42 15790.00 169
MVP-Stereo76.12 22274.46 22681.13 20085.37 20969.79 7084.42 23287.95 20265.03 25167.46 28785.33 24053.28 21591.73 19758.01 25283.27 16281.85 323
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
XVG-ACMP-BASELINE76.11 22374.27 22881.62 18883.20 26364.67 17183.60 24689.75 14769.75 18571.85 23587.09 18232.78 33892.11 18469.99 15480.43 19888.09 238
ACMH+68.96 1476.01 22474.01 22982.03 17388.60 13765.31 15688.86 8587.55 20870.25 17967.75 28487.47 16941.27 31593.19 14858.37 24775.94 25587.60 248
ACMH67.68 1675.89 22573.93 23081.77 17988.71 13566.61 13288.62 9589.01 17169.81 18366.78 29486.70 19441.95 31491.51 21255.64 26578.14 22387.17 259
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
IB-MVS68.01 1575.85 22673.36 23483.31 12284.76 21866.03 13883.38 24885.06 23570.21 18069.40 26681.05 29445.76 29394.66 8165.10 19475.49 26289.25 196
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
testing_275.73 22773.34 23582.89 14977.37 32765.22 15884.10 23990.54 11669.09 19760.46 32381.15 29340.48 31992.84 16676.36 9280.54 19790.60 140
WTY-MVS75.65 22875.68 20275.57 28786.40 19756.82 28077.92 30182.40 26865.10 24976.18 16887.72 16063.13 10980.90 31560.31 23081.96 17889.00 208
thres20075.55 22974.47 22578.82 24387.78 17157.85 26583.07 25683.51 25272.44 14475.84 17484.42 25452.08 22691.75 19647.41 30583.64 15586.86 266
EPNet_dtu75.46 23074.86 21977.23 27082.57 28054.60 30586.89 15883.09 26271.64 15566.25 29985.86 22755.99 19188.04 27954.92 26886.55 12389.05 203
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
XXY-MVS75.41 23175.56 20374.96 29283.59 25457.82 26680.59 27683.87 24766.54 23474.93 19988.31 14563.24 10380.09 31962.16 21476.85 24286.97 264
TransMVSNet (Re)75.39 23274.56 22377.86 25785.50 20857.10 27586.78 16386.09 22872.17 15171.53 23987.34 17063.01 11089.31 25356.84 26161.83 33287.17 259
CostFormer75.24 23373.90 23179.27 23182.65 27958.27 25780.80 27282.73 26661.57 28375.33 19083.13 26755.52 19491.07 22864.98 19678.34 22288.45 232
pmmvs674.69 23473.39 23378.61 24681.38 29457.48 27186.64 16787.95 20264.99 25370.18 25386.61 20050.43 26089.52 24862.12 21570.18 30288.83 213
PatchFormer-LS_test74.50 23573.05 23778.86 24282.95 27159.55 24881.65 26882.30 27067.44 22771.62 23878.15 31652.34 22088.92 27065.05 19575.90 25688.12 237
tfpnnormal74.39 23673.16 23678.08 25586.10 20058.05 25984.65 22487.53 20970.32 17771.22 24385.63 23354.97 19789.86 24243.03 33175.02 26986.32 278
IterMVS74.29 23772.94 23878.35 25281.53 29163.49 20481.58 26982.49 26768.06 22069.99 25983.69 26351.66 24085.54 29565.85 18871.64 29586.01 286
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
OurMVSNet-221017-074.26 23872.42 24479.80 22083.76 25259.59 24585.92 18886.64 21866.39 23666.96 29287.58 16439.46 32291.60 21065.76 18969.27 30488.22 235
EG-PatchMatch MVS74.04 23971.82 25580.71 20684.92 21767.42 11985.86 18988.08 20066.04 24064.22 31183.85 25835.10 33792.56 17257.44 25680.83 19082.16 322
pmmvs474.03 24071.91 25280.39 20881.96 28668.32 10481.45 27082.14 27259.32 30069.87 26285.13 24352.40 21988.13 27860.21 23174.74 27284.73 301
MS-PatchMatch73.83 24172.67 24077.30 26983.87 24666.02 13981.82 26484.66 23861.37 28668.61 27882.82 27047.29 28188.21 27659.27 23884.32 14477.68 336
tfpn_ndepth73.70 24272.75 23976.52 27487.78 17154.92 30484.32 23580.28 29567.57 22472.50 21784.82 24950.12 26289.44 25145.73 31781.66 18285.20 293
DWT-MVSNet_test73.70 24271.86 25379.21 23382.91 27258.94 25082.34 25982.17 27165.21 24771.05 24578.31 31344.21 29990.17 24063.29 20577.28 23088.53 231
conf0.0173.67 24472.42 24477.42 26587.85 15953.28 31583.38 24879.08 30368.40 21172.45 22086.08 21950.60 25289.19 25544.25 32279.66 20489.78 183
conf0.00273.67 24472.42 24477.42 26587.85 15953.28 31583.38 24879.08 30368.40 21172.45 22086.08 21950.60 25289.19 25544.25 32279.66 20489.78 183
sss73.60 24673.64 23273.51 30282.80 27455.01 30376.12 30781.69 28062.47 27774.68 20185.85 22857.32 18178.11 32760.86 22780.93 18887.39 252
Patchmatch-test173.49 24771.85 25478.41 25184.05 24362.17 22879.96 28179.29 30266.30 23772.38 22779.58 30751.95 22985.08 29955.46 26677.67 22687.99 239
tpmp4_e2373.45 24871.17 26280.31 21283.55 25559.56 24781.88 26382.33 26957.94 31170.51 24981.62 28951.19 24491.63 20953.96 27277.51 22889.75 188
tfpn100073.44 24972.49 24276.29 28087.81 16753.69 31284.05 24178.81 31067.99 22172.09 23386.27 21449.95 26589.04 26444.09 32881.38 18486.15 281
thresconf0.0273.39 25072.42 24476.31 27687.85 15953.28 31583.38 24879.08 30368.40 21172.45 22086.08 21950.60 25289.19 25544.25 32279.66 20486.48 273
tfpn_n40073.39 25072.42 24476.31 27687.85 15953.28 31583.38 24879.08 30368.40 21172.45 22086.08 21950.60 25289.19 25544.25 32279.66 20486.48 273
tfpnconf73.39 25072.42 24476.31 27687.85 15953.28 31583.38 24879.08 30368.40 21172.45 22086.08 21950.60 25289.19 25544.25 32279.66 20486.48 273
tfpnview1173.39 25072.42 24476.31 27687.85 15953.28 31583.38 24879.08 30368.40 21172.45 22086.08 21950.60 25289.19 25544.25 32279.66 20486.48 273
SixPastTwentyTwo73.37 25471.26 26179.70 22185.08 21657.89 26485.57 19983.56 25171.03 16665.66 30185.88 22642.10 31292.57 17159.11 24063.34 32988.65 219
CR-MVSNet73.37 25471.27 26079.67 22381.32 29765.19 15975.92 30980.30 29359.92 29572.73 21581.19 29152.50 21786.69 28659.84 23377.71 22487.11 262
MSDG73.36 25670.99 26380.49 20784.51 22265.80 14480.71 27486.13 22765.70 24465.46 30283.74 26244.60 29790.91 23051.13 28376.89 23984.74 300
tpm273.26 25771.46 25778.63 24583.34 25956.71 28380.65 27580.40 29256.63 32073.55 20682.02 28151.80 23891.24 21956.35 26378.42 22187.95 240
RPSCF73.23 25871.46 25778.54 24882.50 28159.85 24482.18 26182.84 26558.96 30371.15 24489.41 12145.48 29684.77 30158.82 24371.83 29491.02 124
PatchmatchNetpermissive73.12 25971.33 25978.49 25083.18 26460.85 23779.63 28378.57 31164.13 26071.73 23679.81 30651.20 24385.97 29357.40 25776.36 25288.66 218
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
COLMAP_ROBcopyleft66.92 1773.01 26070.41 26780.81 20487.13 18765.63 14688.30 10884.19 24362.96 27063.80 31487.69 16238.04 32892.56 17246.66 31174.91 27084.24 304
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
CVMVSNet72.99 26172.58 24174.25 29984.28 22450.85 33086.41 17483.45 25444.56 34673.23 21087.54 16749.38 27085.70 29465.90 18778.44 22086.19 280
test-LLR72.94 26272.43 24374.48 29681.35 29558.04 26078.38 29577.46 31766.66 23069.95 26079.00 31148.06 27879.24 32166.13 18384.83 13886.15 281
test_040272.79 26370.44 26679.84 21988.13 15165.99 14085.93 18784.29 24165.57 24667.40 28985.49 23746.92 28492.61 17035.88 34174.38 27580.94 326
tpmrst72.39 26472.13 25173.18 30480.54 30449.91 33479.91 28279.08 30363.11 26771.69 23779.95 30355.32 19582.77 31065.66 19073.89 27986.87 265
PatchMatch-RL72.38 26570.90 26476.80 27388.60 13767.38 12179.53 28476.17 32362.75 27469.36 26882.00 28245.51 29584.89 30053.62 27480.58 19478.12 334
tpm72.37 26671.71 25674.35 29882.19 28452.00 32279.22 28877.29 31964.56 25672.95 21383.68 26451.35 24183.26 30958.33 24975.80 25787.81 244
PVSNet64.34 1872.08 26770.87 26575.69 28586.21 19956.44 28774.37 31980.73 28762.06 28170.17 25482.23 27642.86 30783.31 30854.77 26984.45 14387.32 255
RPMNet71.62 26868.94 27579.67 22381.32 29765.19 15975.92 30978.30 31357.60 31472.73 21576.45 32552.30 22186.69 28648.14 30177.71 22487.11 262
pmmvs571.55 26970.20 26975.61 28677.83 32456.39 28881.74 26680.89 28457.76 31267.46 28784.49 25349.26 27385.32 29857.08 26075.29 26685.11 297
test-mter71.41 27070.39 26874.48 29681.35 29558.04 26078.38 29577.46 31760.32 29169.95 26079.00 31136.08 33579.24 32166.13 18384.83 13886.15 281
K. test v371.19 27168.51 27779.21 23383.04 26957.78 26784.35 23476.91 32172.90 13462.99 31782.86 26939.27 32391.09 22761.65 22052.66 34688.75 216
tpmvs71.09 27269.29 27276.49 27582.04 28556.04 29478.92 29281.37 28364.05 26167.18 29178.28 31449.74 26889.77 24349.67 29172.37 28983.67 309
AllTest70.96 27368.09 28379.58 22685.15 21263.62 19984.58 22679.83 29862.31 27860.32 32486.73 18732.02 33988.96 26850.28 28671.57 29686.15 281
Patchmtry70.74 27469.16 27375.49 28980.72 30154.07 30974.94 31880.30 29358.34 30770.01 25781.19 29152.50 21786.54 28853.37 27571.09 29885.87 289
MIMVSNet70.69 27569.30 27174.88 29384.52 22156.35 29175.87 31179.42 30164.59 25567.76 28382.41 27341.10 31681.54 31446.64 31381.34 18586.75 269
tpm cat170.57 27668.31 27977.35 26882.41 28257.95 26378.08 29980.22 29652.04 33768.54 27977.66 32052.00 22887.84 28151.77 27972.07 29386.25 279
OpenMVS_ROBcopyleft64.09 1970.56 27768.19 28077.65 26180.26 30659.41 24985.01 21582.96 26458.76 30565.43 30382.33 27437.63 33191.23 22045.34 32076.03 25482.32 320
pmmvs-eth3d70.50 27867.83 28778.52 24977.37 32766.18 13781.82 26481.51 28158.90 30463.90 31380.42 30042.69 30886.28 29158.56 24565.30 32683.11 315
USDC70.33 27968.37 27876.21 28280.60 30356.23 29279.19 28986.49 22060.89 28761.29 32085.47 23831.78 34189.47 25053.37 27576.21 25382.94 319
Patchmatch-RL test70.24 28067.78 28977.61 26277.43 32659.57 24671.16 32470.33 34462.94 27168.65 27672.77 33550.62 25185.49 29669.58 15866.58 31887.77 245
CMPMVSbinary51.72 2170.19 28168.16 28176.28 28173.15 34257.55 27079.47 28583.92 24548.02 34456.48 33784.81 25043.13 30486.42 29062.67 21081.81 18184.89 298
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
ppachtmachnet_test70.04 28267.34 29278.14 25479.80 31261.13 23379.19 28980.59 28859.16 30265.27 30479.29 30846.75 28687.29 28349.33 29266.72 31686.00 288
gg-mvs-nofinetune69.95 28367.96 28475.94 28383.07 26754.51 30777.23 30470.29 34563.11 26770.32 25162.33 34743.62 30288.69 27253.88 27387.76 10484.62 302
TESTMET0.1,169.89 28469.00 27472.55 30579.27 32156.85 27978.38 29574.71 33357.64 31368.09 28277.19 32237.75 32976.70 33263.92 20184.09 14584.10 307
FMVSNet569.50 28567.96 28474.15 30082.97 27055.35 30280.01 28082.12 27362.56 27663.02 31581.53 29036.92 33281.92 31248.42 29574.06 27785.17 296
PMMVS69.34 28668.67 27671.35 31275.67 33362.03 22975.17 31373.46 33850.00 34268.68 27579.05 30952.07 22778.13 32661.16 22582.77 16973.90 344
our_test_369.14 28767.00 29375.57 28779.80 31258.80 25177.96 30077.81 31559.55 29862.90 31878.25 31547.43 28083.97 30351.71 28067.58 31183.93 308
EPMVS69.02 28868.16 28171.59 30879.61 31549.80 33677.40 30366.93 35462.82 27370.01 25779.05 30945.79 29277.86 32956.58 26275.26 26787.13 261
Anonymous2023120668.60 28967.80 28871.02 31480.23 30850.75 33178.30 29880.47 29056.79 31966.11 30082.63 27246.35 28778.95 32343.62 33075.70 25883.36 312
MIMVSNet168.58 29066.78 29573.98 30180.07 30951.82 32380.77 27384.37 24064.40 25859.75 32782.16 27736.47 33383.63 30642.73 33270.33 30186.48 273
EU-MVSNet68.53 29167.61 29171.31 31378.51 32347.01 34084.47 22784.27 24242.27 34766.44 29884.79 25140.44 32083.76 30458.76 24468.54 31083.17 313
PatchT68.46 29267.85 28670.29 31680.70 30243.93 34472.47 32274.88 32960.15 29370.55 24776.57 32449.94 26681.59 31350.58 28474.83 27185.34 292
test0.0.03 168.00 29367.69 29068.90 32177.55 32547.43 33875.70 31272.95 34066.66 23066.56 29582.29 27548.06 27875.87 33644.97 32174.51 27483.41 311
TDRefinement67.49 29464.34 30176.92 27173.47 34061.07 23484.86 21882.98 26359.77 29658.30 33085.13 24326.06 34587.89 28047.92 30460.59 33781.81 324
test20.0367.45 29566.95 29468.94 32075.48 33644.84 34277.50 30277.67 31666.66 23063.01 31683.80 26047.02 28378.40 32542.53 33368.86 30883.58 310
UnsupCasMVSNet_eth67.33 29665.99 29771.37 31073.48 33951.47 32775.16 31485.19 23465.20 24860.78 32280.93 29842.35 30977.20 33157.12 25953.69 34585.44 291
TinyColmap67.30 29764.81 29974.76 29581.92 28756.68 28480.29 27881.49 28260.33 29056.27 33883.22 26624.77 34787.66 28245.52 31869.47 30379.95 330
dp66.80 29865.43 29870.90 31579.74 31448.82 33775.12 31674.77 33159.61 29764.08 31277.23 32142.89 30680.72 31648.86 29466.58 31883.16 314
MDA-MVSNet-bldmvs66.68 29963.66 30375.75 28479.28 32060.56 24173.92 32078.35 31264.43 25750.13 34879.87 30544.02 30183.67 30546.10 31556.86 34083.03 317
testgi66.67 30066.53 29667.08 32675.62 33441.69 34975.93 30876.50 32266.11 23865.20 30786.59 20135.72 33674.71 34043.71 32973.38 28484.84 299
CHOSEN 280x42066.51 30164.71 30071.90 30781.45 29263.52 20357.98 35368.95 35253.57 33262.59 31976.70 32346.22 28875.29 33955.25 26779.68 20376.88 342
PM-MVS66.41 30264.14 30273.20 30373.92 33756.45 28678.97 29164.96 35863.88 26564.72 30880.24 30119.84 35383.44 30766.24 18264.52 32879.71 331
JIA-IIPM66.32 30362.82 30976.82 27277.09 32961.72 23265.34 34575.38 32558.04 31064.51 30962.32 34842.05 31386.51 28951.45 28269.22 30582.21 321
ADS-MVSNet266.20 30463.33 30474.82 29479.92 31058.75 25267.55 34175.19 32753.37 33365.25 30575.86 32642.32 31080.53 31741.57 33468.91 30685.18 294
YYNet165.03 30562.91 30771.38 30975.85 33256.60 28569.12 33574.66 33557.28 31754.12 34077.87 31845.85 29174.48 34149.95 28961.52 33483.05 316
MDA-MVSNet_test_wron65.03 30562.92 30671.37 31075.93 33156.73 28169.09 33674.73 33257.28 31754.03 34177.89 31745.88 29074.39 34249.89 29061.55 33382.99 318
Patchmatch-test64.82 30763.24 30569.57 31879.42 31749.82 33563.49 34869.05 35151.98 33859.95 32680.13 30250.91 24670.98 35040.66 33673.57 28287.90 242
ADS-MVSNet64.36 30862.88 30868.78 32379.92 31047.17 33967.55 34171.18 34353.37 33365.25 30575.86 32642.32 31073.99 34441.57 33468.91 30685.18 294
LF4IMVS64.02 30962.19 31069.50 31970.90 34753.29 31476.13 30677.18 32052.65 33658.59 32880.98 29623.55 34876.52 33353.06 27766.66 31778.68 333
UnsupCasMVSNet_bld63.70 31061.53 31270.21 31773.69 33851.39 32872.82 32181.89 27855.63 32457.81 33171.80 33738.67 32578.61 32449.26 29352.21 34780.63 327
new-patchmatchnet61.73 31161.73 31161.70 33472.74 34324.50 36569.16 33478.03 31461.40 28456.72 33675.53 32838.42 32676.48 33445.95 31657.67 33984.13 306
PVSNet_057.27 2061.67 31259.27 31368.85 32279.61 31557.44 27268.01 33973.44 33955.93 32358.54 32970.41 34044.58 29877.55 33047.01 30635.91 35271.55 346
LP61.36 31357.78 31672.09 30675.54 33558.53 25467.16 34375.22 32651.90 33954.13 33969.97 34137.73 33080.45 31832.74 34555.63 34277.29 338
test235659.50 31458.08 31463.74 33071.23 34641.88 34767.59 34072.42 34253.72 33157.65 33270.74 33926.31 34472.40 34732.03 34871.06 29976.93 340
MVS-HIRNet59.14 31557.67 31763.57 33181.65 28943.50 34571.73 32365.06 35739.59 35151.43 34657.73 35138.34 32782.58 31139.53 33773.95 27864.62 351
testus59.00 31657.91 31562.25 33372.25 34439.09 35269.74 32975.02 32853.04 33557.21 33473.72 33318.76 35570.33 35132.86 34468.57 30977.35 337
test123567858.74 31756.89 32064.30 32869.70 34841.87 34871.05 32574.87 33054.06 32850.63 34771.53 33825.30 34674.10 34331.80 34963.10 33076.93 340
pmmvs357.79 31854.26 32268.37 32464.02 35456.72 28275.12 31665.17 35640.20 34952.93 34469.86 34220.36 35275.48 33845.45 31955.25 34472.90 345
DSMNet-mixed57.77 31956.90 31960.38 33567.70 35235.61 35569.18 33353.97 36132.30 35757.49 33379.88 30440.39 32168.57 35438.78 33872.37 28976.97 339
111157.11 32056.82 32157.97 33869.10 34928.28 36068.90 33774.54 33654.01 32953.71 34274.51 33023.09 34967.90 35532.28 34661.26 33577.73 335
testpf56.51 32157.58 31853.30 34171.99 34541.19 35046.89 35869.32 35058.06 30952.87 34569.45 34327.99 34372.73 34659.59 23662.07 33145.98 356
LCM-MVSNet54.25 32249.68 32967.97 32553.73 36145.28 34166.85 34480.78 28635.96 35339.45 35362.23 3498.70 36578.06 32848.24 30051.20 34880.57 328
testmv53.85 32351.03 32562.31 33261.46 35638.88 35370.95 32874.69 33451.11 34141.26 35066.85 34414.28 35972.13 34829.19 35149.51 34975.93 343
FPMVS53.68 32451.64 32459.81 33665.08 35351.03 32969.48 33269.58 34841.46 34840.67 35172.32 33616.46 35870.00 35224.24 35665.42 32558.40 353
N_pmnet52.79 32553.26 32351.40 34478.99 3227.68 36969.52 3313.89 37051.63 34057.01 33574.98 32940.83 31865.96 35737.78 33964.67 32780.56 329
no-one51.08 32645.79 33266.95 32757.92 35950.49 33359.63 35276.04 32448.04 34331.85 35456.10 35419.12 35480.08 32036.89 34026.52 35470.29 347
new_pmnet50.91 32750.29 32652.78 34268.58 35134.94 35863.71 34756.63 36039.73 35044.95 34965.47 34621.93 35158.48 35934.98 34256.62 34164.92 350
ANet_high50.57 32846.10 33163.99 32948.67 36439.13 35170.99 32780.85 28561.39 28531.18 35657.70 35217.02 35773.65 34531.22 35015.89 36179.18 332
test1235649.28 32948.51 33051.59 34362.06 35519.11 36660.40 35072.45 34147.60 34540.64 35265.68 34513.84 36068.72 35327.29 35346.67 35166.94 349
.test124545.55 33050.02 32832.14 35069.10 34928.28 36068.90 33774.54 33654.01 32953.71 34274.51 33023.09 34967.90 35532.28 3460.02 3640.25 365
Gipumacopyleft45.18 33141.86 33355.16 34077.03 33051.52 32632.50 36180.52 28932.46 35527.12 35735.02 3589.52 36475.50 33722.31 35760.21 33838.45 358
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
PMVScopyleft37.38 2244.16 33240.28 33455.82 33940.82 36742.54 34665.12 34663.99 35934.43 35424.48 35857.12 3533.92 36776.17 33517.10 35955.52 34348.75 354
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
PMMVS240.82 33338.86 33546.69 34653.84 36016.45 36748.61 35749.92 36337.49 35231.67 35560.97 3508.14 36656.42 36028.42 35230.72 35367.19 348
wuykxyi23d39.76 33433.18 33859.51 33746.98 36544.01 34357.70 35467.74 35324.13 35913.98 36534.33 3591.27 37071.33 34934.23 34318.23 35763.18 352
PNet_i23d38.26 33535.42 33646.79 34558.74 35735.48 35659.65 35151.25 36232.45 35623.44 36147.53 3562.04 36958.96 35825.60 35518.09 35945.92 357
v1.037.66 33650.21 3270.00 35795.06 10.00 3720.00 36394.09 275.63 7591.80 395.29 40.00 3740.00 3690.00 3660.00 3670.00 367
pcd1.5k->3k34.07 33735.26 33730.50 35186.92 1890.00 3720.00 36391.58 860.00 3670.00 3690.00 36956.23 1900.00 3690.00 36682.60 17391.49 112
E-PMN31.77 33830.64 33935.15 34852.87 36227.67 36257.09 35547.86 36424.64 35816.40 36333.05 36011.23 36254.90 36114.46 36118.15 35822.87 360
EMVS30.81 33929.65 34034.27 34950.96 36325.95 36456.58 35646.80 36524.01 36015.53 36430.68 36112.47 36154.43 36212.81 36217.05 36022.43 361
MVEpermissive26.22 2330.37 34025.89 34243.81 34744.55 36635.46 35728.87 36239.07 36618.20 36118.58 36240.18 3572.68 36847.37 36317.07 36023.78 35648.60 355
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
cdsmvs_eth3d_5k19.96 34126.61 3410.00 3570.00 3720.00 3720.00 36389.26 1630.00 3670.00 36988.61 13661.62 1410.00 3690.00 3660.00 3670.00 367
tmp_tt18.61 34221.40 34310.23 3544.82 36910.11 36834.70 36030.74 3681.48 36423.91 36026.07 36228.42 34213.41 36627.12 35415.35 3627.17 362
wuyk23d16.82 34315.94 34419.46 35358.74 35731.45 35939.22 3593.74 3716.84 3636.04 3662.70 3661.27 37024.29 36510.54 36314.40 3632.63 363
ab-mvs-re7.23 3449.64 3450.00 3570.00 3720.00 3720.00 3630.00 3740.00 3670.00 36986.72 1890.00 3740.00 3690.00 3660.00 3670.00 367
test1236.12 3458.11 3460.14 3550.06 3710.09 37071.05 3250.03 3730.04 3660.25 3681.30 3680.05 3720.03 3680.21 3650.01 3660.29 364
testmvs6.04 3468.02 3470.10 3560.08 3700.03 37169.74 3290.04 3720.05 3650.31 3671.68 3670.02 3730.04 3670.24 3640.02 3640.25 365
pcd_1.5k_mvsjas5.26 3477.02 3480.00 3570.00 3720.00 3720.00 3630.00 3740.00 3670.00 3690.00 36963.15 1060.00 3690.00 3660.00 3670.00 367
sosnet-low-res0.00 3480.00 3490.00 3570.00 3720.00 3720.00 3630.00 3740.00 3670.00 3690.00 3690.00 3740.00 3690.00 3660.00 3670.00 367
sosnet0.00 3480.00 3490.00 3570.00 3720.00 3720.00 3630.00 3740.00 3670.00 3690.00 3690.00 3740.00 3690.00 3660.00 3670.00 367
uncertanet0.00 3480.00 3490.00 3570.00 3720.00 3720.00 3630.00 3740.00 3670.00 3690.00 3690.00 3740.00 3690.00 3660.00 3670.00 367
Regformer0.00 3480.00 3490.00 3570.00 3720.00 3720.00 3630.00 3740.00 3670.00 3690.00 3690.00 3740.00 3690.00 3660.00 3670.00 367
uanet0.00 3480.00 3490.00 3570.00 3720.00 3720.00 3630.00 3740.00 3670.00 3690.00 3690.00 3740.00 3690.00 3660.00 3670.00 367
GSMVS88.96 210
test_part295.06 172.65 2891.80 3
test_part10.00 3570.00 3720.00 36394.09 20.00 3740.00 3690.00 3660.00 3670.00 367
sam_mvs151.32 24288.96 210
sam_mvs50.01 263
semantic-postprocess80.11 21582.69 27864.85 16783.47 25369.16 19670.49 25084.15 25650.83 25088.15 27769.23 16072.14 29287.34 254
ambc75.24 29173.16 34150.51 33263.05 34987.47 21164.28 31077.81 31917.80 35689.73 24557.88 25360.64 33685.49 290
MTGPAbinary92.02 64
test_post178.90 2935.43 36548.81 27785.44 29759.25 239
test_post5.46 36450.36 26184.24 302
patchmatchnet-post74.00 33251.12 24588.60 273
GG-mvs-BLEND75.38 29081.59 29055.80 30079.32 28669.63 34767.19 29073.67 33443.24 30388.90 27150.41 28584.50 14181.45 325
MTMP92.18 2032.83 367
gm-plane-assit81.40 29353.83 31162.72 27580.94 29792.39 17663.40 204
test9_res84.90 1995.70 1492.87 75
TEST993.26 3772.96 2088.75 9191.89 7368.44 21085.00 3293.10 4274.36 1795.41 50
test_893.13 3972.57 3188.68 9491.84 7668.69 20684.87 3893.10 4274.43 1495.16 58
agg_prior282.91 4195.45 1692.70 77
agg_prior92.85 4571.94 4291.78 7984.41 4494.93 67
TestCases79.58 22685.15 21263.62 19979.83 29862.31 27860.32 32486.73 18732.02 33988.96 26850.28 28671.57 29686.15 281
test_prior472.60 3089.01 81
test_prior288.85 8675.41 7984.91 3493.54 3274.28 1883.31 3495.86 8
test_prior86.33 4892.61 5069.59 7592.97 3395.48 4593.91 33
旧先验286.56 17058.10 30887.04 1788.98 26674.07 115
新几何286.29 179
新几何183.42 11893.13 3970.71 5785.48 23157.43 31581.80 7691.98 5963.28 10192.27 18064.60 19992.99 4987.27 256
旧先验191.96 5865.79 14586.37 22393.08 4669.31 5692.74 5288.74 217
无先验87.48 13488.98 17560.00 29494.12 9967.28 17488.97 209
原ACMM286.86 159
原ACMM184.35 8993.01 4368.79 8992.44 4863.96 26481.09 8691.57 6966.06 8095.45 4767.19 17794.82 3188.81 214
test22291.50 6368.26 10684.16 23783.20 26154.63 32779.74 9591.63 6758.97 17091.42 6286.77 268
testdata291.01 22962.37 212
segment_acmp73.08 25
testdata79.97 21790.90 7164.21 18884.71 23759.27 30185.40 2792.91 4762.02 13889.08 26368.95 16391.37 6386.63 272
testdata184.14 23875.71 72
test1286.80 4092.63 4970.70 5891.79 7882.71 6771.67 3596.16 3194.50 3593.54 53
plane_prior790.08 8568.51 102
plane_prior689.84 9068.70 9860.42 163
plane_prior592.44 4895.38 5278.71 6986.32 12691.33 115
plane_prior491.00 85
plane_prior368.60 10078.44 3078.92 104
plane_prior291.25 3179.12 23
plane_prior189.90 89
plane_prior68.71 9690.38 4777.62 3486.16 129
n20.00 374
nn0.00 374
door-mid69.98 346
lessismore_v078.97 24081.01 30057.15 27465.99 35561.16 32182.82 27039.12 32491.34 21759.67 23446.92 35088.43 233
LGP-MVS_train84.50 8389.23 11668.76 9291.94 7175.37 8176.64 15591.51 7054.29 20694.91 6978.44 7183.78 14789.83 180
test1192.23 56
door69.44 349
HQP5-MVS66.98 127
HQP-NCC89.33 10889.17 7476.41 5977.23 145
ACMP_Plane89.33 10889.17 7476.41 5977.23 145
BP-MVS77.47 81
HQP4-MVS77.24 14495.11 6091.03 122
HQP3-MVS92.19 5985.99 131
HQP2-MVS60.17 166
NP-MVS89.62 9668.32 10490.24 96
MDTV_nov1_ep13_2view37.79 35475.16 31455.10 32566.53 29649.34 27153.98 27187.94 241
MDTV_nov1_ep1369.97 27083.18 26453.48 31377.10 30580.18 29760.45 28969.33 26980.44 29948.89 27686.90 28551.60 28178.51 219
ACMMP++_ref81.95 179
ACMMP++81.25 186
Test By Simon64.33 93
ITE_SJBPF78.22 25381.77 28860.57 24083.30 25569.25 19467.54 28687.20 17636.33 33487.28 28454.34 27074.62 27386.80 267
DeepMVS_CXcopyleft27.40 35240.17 36826.90 36324.59 36917.44 36223.95 35948.61 3559.77 36326.48 36418.06 35824.47 35528.83 359