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
ESAPD89.40 189.87 187.98 1295.06 172.65 2792.22 1994.09 175.63 7491.80 295.29 381.79 197.56 186.60 1396.38 393.74 37
HSP-MVS89.28 289.76 287.85 2094.28 1773.46 1592.90 892.73 4080.27 1391.35 494.16 2378.35 496.77 1289.59 194.22 4593.33 55
APDe-MVS89.15 389.63 387.73 2294.49 1071.69 4493.83 293.96 475.70 7291.06 596.03 176.84 597.03 889.09 295.65 1694.47 12
SMA-MVS89.03 489.17 488.60 294.25 1873.68 792.40 1493.59 974.72 9091.86 195.97 274.27 2197.24 488.58 496.91 194.87 5
HPM-MVS++copyleft89.02 589.15 588.63 195.01 376.03 192.38 1592.85 3580.26 1487.78 1494.27 1975.89 996.81 1187.45 1096.44 293.05 65
CNVR-MVS88.93 689.13 688.33 494.77 473.82 690.51 4293.00 2780.90 1088.06 1294.06 2776.43 696.84 1088.48 595.99 794.34 16
SteuartSystems-ACMMP88.72 788.86 788.32 592.14 5572.96 2093.73 393.67 880.19 1588.10 1194.80 773.76 2397.11 687.51 995.82 1194.90 4
Skip Steuart: Steuart Systems R&D Blog.
DeepPCF-MVS80.84 188.10 888.56 886.73 4192.24 5369.03 8289.57 6593.39 1677.53 3989.79 794.12 2578.98 396.58 2385.66 1595.72 1294.58 8
SD-MVS88.06 988.50 986.71 4292.60 5172.71 2591.81 2693.19 2177.87 3290.32 694.00 2874.83 1293.78 11587.63 894.27 4393.65 44
NCCC88.06 988.01 1288.24 694.41 1473.62 891.22 3392.83 3681.50 785.79 2493.47 3673.02 2797.00 984.90 2094.94 2794.10 22
ACMMP_Plus88.05 1188.08 1187.94 1393.70 2673.05 1990.86 3693.59 976.27 6688.14 1095.09 671.06 3996.67 1687.67 796.37 594.09 23
TSAR-MVS + MP.88.02 1288.11 1087.72 2493.68 2872.13 4091.41 2992.35 5174.62 9288.90 893.85 3075.75 1096.00 3687.80 694.63 3495.04 2
MP-MVScopyleft87.71 1387.64 1487.93 1694.36 1673.88 492.71 1392.65 4377.57 3583.84 5094.40 1872.24 3396.28 2885.65 1695.30 2493.62 46
MP-MVS-pluss87.67 1487.72 1387.54 2893.64 2972.04 4189.80 5893.50 1275.17 8586.34 1995.29 370.86 4096.00 3688.78 396.04 694.58 8
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
HFP-MVS87.58 1587.47 1687.94 1394.58 773.54 1293.04 593.24 1876.78 5284.91 3294.44 1570.78 4196.61 1984.53 2694.89 2993.66 39
zzz-MVS87.53 1687.41 1787.90 1794.18 2274.25 290.23 5092.02 6179.45 1985.88 2194.80 768.07 6096.21 3086.69 1195.34 2093.23 57
ACMMPR87.44 1787.23 1988.08 894.64 573.59 993.04 593.20 2076.78 5284.66 3894.52 1068.81 5896.65 1784.53 2694.90 2894.00 29
APD-MVScopyleft87.44 1787.52 1587.19 3394.24 1972.39 3591.86 2592.83 3673.01 12988.58 994.52 1073.36 2496.49 2484.26 3095.01 2692.70 72
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
region2R87.42 1987.20 2088.09 794.63 673.55 1093.03 793.12 2376.73 5584.45 4194.52 1069.09 5696.70 1584.37 2994.83 3194.03 26
MCST-MVS87.37 2087.25 1887.73 2294.53 972.46 3489.82 5693.82 673.07 12884.86 3792.89 4876.22 796.33 2684.89 2295.13 2594.40 13
#test#87.33 2187.13 2187.94 1394.58 773.54 1292.34 1693.24 1875.23 8284.91 3294.44 1570.78 4196.61 1983.75 3494.89 2993.66 39
MTAPA87.23 2287.00 2287.90 1794.18 2274.25 286.58 16392.02 6179.45 1985.88 2194.80 768.07 6096.21 3086.69 1195.34 2093.23 57
XVS87.18 2386.91 2588.00 1094.42 1273.33 1792.78 992.99 2979.14 2183.67 5394.17 2267.45 6796.60 2183.06 3994.50 3694.07 24
HPM-MVScopyleft87.11 2486.98 2387.50 3093.88 2572.16 3992.19 2193.33 1776.07 6983.81 5193.95 2969.77 5196.01 3585.15 1794.66 3394.32 18
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 2173.86 593.98 192.82 3876.62 5783.68 5294.46 1467.93 6295.95 3884.20 3294.39 3993.23 57
DeepC-MVS79.81 287.08 2686.88 2687.69 2691.16 6572.32 3890.31 4893.94 577.12 4482.82 6294.23 2172.13 3497.09 784.83 2395.37 1993.65 44
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 3172.37 3791.26 3093.04 2476.62 5784.22 4693.36 3871.44 3796.76 1380.82 5495.33 2294.16 20
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 4969.59 7488.85 8292.97 3275.41 7884.91 3293.54 3274.28 1995.48 4683.31 3595.86 993.91 31
PGM-MVS86.68 2986.27 3287.90 1794.22 2073.38 1690.22 5193.04 2475.53 7683.86 4994.42 1767.87 6496.64 1882.70 4494.57 3593.66 39
mPP-MVS86.67 3086.32 3187.72 2494.41 1473.55 1092.74 1192.22 5476.87 5082.81 6394.25 2066.44 7496.24 2982.88 4394.28 4293.38 52
Regformer-286.63 3186.53 2986.95 3889.33 10371.24 4788.43 9592.05 6082.50 186.88 1790.09 9774.45 1495.61 4284.38 2890.63 7194.01 28
CANet86.45 3286.10 3687.51 2990.09 8070.94 5289.70 6292.59 4481.78 481.32 7691.43 7470.34 4497.23 584.26 3093.36 4994.37 14
train_agg86.43 3386.20 3387.13 3593.26 3672.96 2088.75 8791.89 7068.69 20085.00 3093.10 4274.43 1595.41 5184.97 1895.71 1393.02 66
PHI-MVS86.43 3386.17 3587.24 3290.88 7070.96 5092.27 1894.07 372.45 14085.22 2891.90 6169.47 5396.42 2583.28 3795.94 894.35 15
Regformer-186.41 3586.33 3086.64 4389.33 10370.93 5388.43 9591.39 9082.14 386.65 1890.09 9774.39 1795.01 6783.97 3390.63 7193.97 30
CSCG86.41 3586.19 3487.07 3792.91 4372.48 3390.81 3793.56 1173.95 10083.16 5891.07 7975.94 895.19 5879.94 6194.38 4093.55 48
MVS_030486.37 3785.81 4188.02 990.13 7872.39 3589.66 6392.75 3981.64 682.66 6692.04 5764.44 8997.35 384.76 2494.25 4494.33 17
agg_prior186.22 3886.09 3786.62 4492.85 4471.94 4288.59 9291.78 7668.96 19784.41 4293.18 4174.94 1194.93 6884.75 2595.33 2293.01 68
agg_prior386.16 3985.85 4087.10 3693.31 3372.86 2488.77 8591.68 8068.29 21284.26 4592.83 5072.83 2895.42 5084.97 1895.71 1393.02 66
APD-MVS_3200maxsize85.97 4085.88 3886.22 5192.69 4769.53 7691.93 2492.99 2973.54 11585.94 2094.51 1365.80 8195.61 4283.04 4192.51 5693.53 50
canonicalmvs85.91 4185.87 3986.04 5589.84 8669.44 8090.45 4693.00 2776.70 5688.01 1391.23 7673.28 2593.91 10681.50 5088.80 8994.77 6
ACMMPcopyleft85.89 4285.39 4487.38 3193.59 3072.63 2992.74 1193.18 2276.78 5280.73 8593.82 3164.33 9096.29 2782.67 4590.69 7093.23 57
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 3271.08 4888.58 9392.42 4968.32 21184.61 3993.48 3472.32 3296.15 3379.00 6395.43 1894.28 19
TSAR-MVS + GP.85.71 4485.33 4586.84 3991.34 6372.50 3289.07 7787.28 20576.41 5985.80 2390.22 9574.15 2295.37 5581.82 4891.88 5892.65 75
Regformer-485.68 4585.45 4386.35 4788.95 11869.67 7388.29 10491.29 9281.73 585.36 2690.01 9972.62 3095.35 5683.28 3787.57 10494.03 26
alignmvs85.48 4685.32 4685.96 5689.51 9869.47 7889.74 6092.47 4576.17 6787.73 1591.46 7370.32 4593.78 11581.51 4988.95 8694.63 7
3Dnovator+77.84 485.48 4684.47 5488.51 391.08 6673.49 1493.18 493.78 780.79 1176.66 14593.37 3760.40 16396.75 1477.20 8193.73 4895.29 1
MSLP-MVS++85.43 4885.76 4284.45 8391.93 5870.24 6190.71 3992.86 3477.46 4184.22 4692.81 5367.16 7092.94 15580.36 5794.35 4190.16 150
DELS-MVS85.41 4985.30 4785.77 5788.49 13467.93 11085.52 20093.44 1478.70 2883.63 5589.03 12074.57 1395.71 4180.26 5994.04 4693.66 39
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 2770.58 5992.15 2291.62 8173.89 10482.67 6594.09 2662.60 12395.54 4580.93 5292.93 5193.57 47
Regformer-385.23 5185.07 4985.70 5888.95 11869.01 8488.29 10489.91 13780.95 985.01 2990.01 9972.45 3194.19 9382.50 4687.57 10493.90 33
abl_685.23 5184.95 5186.07 5492.23 5470.48 6090.80 3892.08 5973.51 11685.26 2794.16 2362.75 11695.92 3982.46 4791.30 6591.81 99
MVS_111021_HR85.14 5384.75 5386.32 5091.65 6172.70 2685.98 17890.33 11976.11 6882.08 6991.61 6871.36 3894.17 9581.02 5192.58 5592.08 92
UA-Net85.08 5484.96 5085.45 5992.07 5668.07 10889.78 5990.86 10282.48 284.60 4093.20 4069.35 5495.22 5771.39 14390.88 6993.07 64
EI-MVSNet-Vis-set84.19 5583.81 5585.31 6188.18 14367.85 11187.66 11989.73 14180.05 1782.95 5989.59 10670.74 4394.82 7580.66 5684.72 13593.28 56
nrg03083.88 5683.53 5684.96 7186.77 18569.28 8190.46 4592.67 4174.79 8982.95 5991.33 7572.70 2993.09 14980.79 5579.28 20892.50 78
EI-MVSNet-UG-set83.81 5783.38 5885.09 6887.87 15067.53 11587.44 13089.66 14279.74 1882.23 6889.41 11570.24 4694.74 7779.95 6083.92 14192.99 69
CPTT-MVS83.73 5883.33 5984.92 7493.28 3570.86 5592.09 2390.38 11468.75 19979.57 9092.83 5060.60 15993.04 15380.92 5391.56 6290.86 120
EPNet83.72 5982.92 6586.14 5384.22 21769.48 7791.05 3585.27 22581.30 876.83 14291.65 6566.09 7795.56 4476.00 9293.85 4793.38 52
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
HQP_MVS83.64 6083.14 6085.14 6690.08 8168.71 9491.25 3192.44 4679.12 2378.92 9791.00 8360.42 16195.38 5378.71 6686.32 12291.33 108
Effi-MVS+83.62 6183.08 6185.24 6488.38 13967.45 11688.89 8089.15 15875.50 7782.27 6788.28 13869.61 5294.45 8477.81 7587.84 10293.84 35
OPM-MVS83.50 6282.95 6485.14 6688.79 12670.95 5189.13 7691.52 8577.55 3880.96 8391.75 6360.71 15594.50 8379.67 6286.51 12089.97 168
Vis-MVSNetpermissive83.46 6382.80 6785.43 6090.25 7768.74 9290.30 4990.13 12876.33 6580.87 8492.89 4861.00 15294.20 9272.45 13190.97 6793.35 54
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
MG-MVS83.41 6483.45 5783.28 11992.74 4662.28 21988.17 10889.50 14675.22 8381.49 7592.74 5466.75 7195.11 6172.85 12491.58 6192.45 79
EPP-MVSNet83.40 6583.02 6384.57 7990.13 7864.47 18092.32 1790.73 10374.45 9479.35 9391.10 7769.05 5795.12 6072.78 12587.22 11194.13 21
3Dnovator76.31 583.38 6682.31 7286.59 4587.94 14972.94 2390.64 4092.14 5877.21 4275.47 17192.83 5058.56 17094.72 7873.24 12292.71 5492.13 91
MVS_Test83.15 6783.06 6283.41 11686.86 18263.21 20586.11 17692.00 6474.31 9582.87 6189.44 11470.03 4793.21 14077.39 8088.50 9893.81 36
IS-MVSNet83.15 6782.81 6684.18 9289.94 8463.30 20291.59 2788.46 18579.04 2579.49 9192.16 5565.10 8594.28 8767.71 16391.86 5994.95 3
DP-MVS Recon83.11 6982.09 7486.15 5294.44 1170.92 5488.79 8492.20 5570.53 16879.17 9491.03 8264.12 9296.03 3468.39 16290.14 7691.50 105
PAPM_NR83.02 7082.41 6984.82 7692.47 5266.37 13387.93 11591.80 7473.82 10977.32 13490.66 8867.90 6394.90 7270.37 14789.48 8393.19 61
VDD-MVS83.01 7182.36 7184.96 7191.02 6766.40 13288.91 7988.11 18877.57 3584.39 4493.29 3952.19 21993.91 10677.05 8488.70 9194.57 10
MVSFormer82.85 7282.05 7585.24 6487.35 17270.21 6290.50 4390.38 11468.55 20281.32 7689.47 10961.68 13793.46 13178.98 6490.26 7492.05 93
OMC-MVS82.69 7381.97 7884.85 7588.75 12867.42 11787.98 11190.87 10174.92 8879.72 8991.65 6562.19 13493.96 10175.26 10486.42 12193.16 62
PVSNet_Blended_VisFu82.62 7481.83 7984.96 7190.80 7269.76 7188.74 8991.70 7969.39 18378.96 9688.46 13365.47 8294.87 7474.42 10888.57 9490.24 148
MVS_111021_LR82.61 7582.11 7384.11 9388.82 12371.58 4585.15 20586.16 21874.69 9180.47 8691.04 8062.29 13190.55 22680.33 5890.08 7790.20 149
HQP-MVS82.61 7582.02 7684.37 8589.33 10366.98 12589.17 7192.19 5676.41 5977.23 13790.23 9460.17 16495.11 6177.47 7885.99 12691.03 114
CLD-MVS82.31 7781.65 8084.29 8988.47 13567.73 11485.81 18792.35 5175.78 7078.33 11186.58 19364.01 9394.35 8576.05 9187.48 10990.79 121
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
VNet82.21 7882.41 6981.62 17990.82 7160.93 22784.47 21889.78 13976.36 6484.07 4891.88 6264.71 8890.26 22870.68 14488.89 8793.66 39
LPG-MVS_test82.08 7981.27 8384.50 8189.23 11168.76 9090.22 5191.94 6875.37 8076.64 14691.51 7054.29 20294.91 7078.44 6883.78 14289.83 172
FIs82.07 8082.42 6881.04 19288.80 12558.34 24688.26 10693.49 1376.93 4978.47 10591.04 8069.92 4992.34 17369.87 15184.97 13192.44 80
PS-MVSNAJss82.07 8081.31 8284.34 8886.51 18767.27 12189.27 6991.51 8671.75 15079.37 9290.22 9563.15 10494.27 8877.69 7682.36 16991.49 106
API-MVS81.99 8281.23 8484.26 9090.94 6870.18 6791.10 3489.32 15171.51 15678.66 10188.28 13865.26 8395.10 6464.74 19091.23 6687.51 241
UniMVSNet_NR-MVSNet81.88 8381.54 8182.92 13988.46 13663.46 19887.13 14392.37 5080.19 1578.38 10989.14 11771.66 3693.05 15170.05 14876.46 24192.25 86
MAR-MVS81.84 8480.70 9085.27 6391.32 6471.53 4689.82 5690.92 10069.77 17878.50 10386.21 20662.36 13094.52 8265.36 18492.05 5789.77 179
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 8581.23 8483.57 11191.89 5963.43 20089.84 5581.85 26877.04 4783.21 5693.10 4252.26 21893.43 13571.98 13789.95 7993.85 34
xiu_mvs_v2_base81.69 8681.05 8783.60 10989.15 11468.03 10984.46 22090.02 13370.67 16681.30 7986.53 19663.17 10394.19 9375.60 10088.54 9688.57 219
PS-MVSNAJ81.69 8681.02 8883.70 10789.51 9868.21 10684.28 22790.09 12970.79 16381.26 8085.62 22563.15 10494.29 8675.62 9988.87 8888.59 217
PAPR81.66 8880.89 8983.99 10190.27 7664.00 19086.76 15991.77 7868.84 19877.13 14189.50 10767.63 6594.88 7367.55 16588.52 9793.09 63
UniMVSNet (Re)81.60 8981.11 8683.09 12788.38 13964.41 18287.60 12093.02 2678.42 3178.56 10288.16 14069.78 5093.26 13969.58 15376.49 24091.60 101
FC-MVSNet-test81.52 9082.02 7680.03 20788.42 13855.97 28487.95 11393.42 1577.10 4577.38 13290.98 8569.96 4891.79 18768.46 16184.50 13692.33 82
VDDNet81.52 9080.67 9184.05 9690.44 7464.13 18689.73 6185.91 22171.11 15983.18 5793.48 3450.54 25493.49 13073.40 12088.25 10094.54 11
ACMP74.13 681.51 9280.57 9284.36 8689.42 10068.69 9789.97 5491.50 8874.46 9375.04 18790.41 9153.82 20794.54 8077.56 7782.91 16189.86 171
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
jason81.39 9380.29 9784.70 7886.63 18669.90 6985.95 17986.77 20963.24 25681.07 8289.47 10961.08 15192.15 17778.33 7190.07 7892.05 93
jason: jason.
lupinMVS81.39 9380.27 9884.76 7787.35 17270.21 6285.55 19686.41 21362.85 26281.32 7688.61 12861.68 13792.24 17678.41 7090.26 7491.83 97
DU-MVS81.12 9580.52 9482.90 14087.80 16063.46 19887.02 14891.87 7279.01 2678.38 10989.07 11865.02 8693.05 15170.05 14876.46 24192.20 88
PVSNet_Blended80.98 9680.34 9582.90 14088.85 12065.40 14984.43 22292.00 6467.62 21778.11 12085.05 23766.02 7994.27 8871.52 14189.50 8289.01 197
mvs-test180.88 9779.40 11685.29 6285.13 20469.75 7289.28 6888.10 19074.99 8676.44 15186.72 18057.27 17994.26 9173.53 11883.18 15991.87 96
QAPM80.88 9779.50 11485.03 6988.01 14868.97 8691.59 2792.00 6466.63 22775.15 18492.16 5557.70 17595.45 4863.52 19488.76 9090.66 129
112180.84 9979.77 10484.05 9693.11 4070.78 5684.66 21285.42 22457.37 30581.76 7492.02 5863.41 9794.12 9667.28 16892.93 5187.26 248
TranMVSNet+NR-MVSNet80.84 9980.31 9682.42 15887.85 15162.33 21787.74 11891.33 9180.55 1277.99 12389.86 10165.23 8492.62 16367.05 17275.24 25992.30 84
UGNet80.83 10179.59 10984.54 8088.04 14668.09 10789.42 6688.16 18776.95 4876.22 15789.46 11149.30 26493.94 10368.48 16090.31 7391.60 101
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 10279.92 10183.47 11288.85 12064.51 17485.53 19889.39 14970.79 16378.49 10485.06 23667.54 6693.58 12667.03 17386.58 11892.32 83
XVG-OURS-SEG-HR80.81 10279.76 10583.96 10385.60 19768.78 8983.54 23990.50 11170.66 16776.71 14491.66 6460.69 15691.26 20976.94 8581.58 17691.83 97
xiu_mvs_v1_base_debu80.80 10479.72 10684.03 9887.35 17270.19 6485.56 19388.77 17769.06 19281.83 7088.16 14050.91 24292.85 15778.29 7287.56 10689.06 190
xiu_mvs_v1_base80.80 10479.72 10684.03 9887.35 17270.19 6485.56 19388.77 17769.06 19281.83 7088.16 14050.91 24292.85 15778.29 7287.56 10689.06 190
xiu_mvs_v1_base_debi80.80 10479.72 10684.03 9887.35 17270.19 6485.56 19388.77 17769.06 19281.83 7088.16 14050.91 24292.85 15778.29 7287.56 10689.06 190
ACMM73.20 880.78 10779.84 10383.58 11089.31 10868.37 10189.99 5391.60 8270.28 17277.25 13589.66 10453.37 21093.53 12974.24 11182.85 16288.85 203
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
114514_t80.68 10879.51 11384.20 9194.09 2467.27 12189.64 6491.11 9758.75 29574.08 19490.72 8758.10 17395.04 6669.70 15289.42 8490.30 147
CANet_DTU80.61 10979.87 10282.83 14685.60 19763.17 20887.36 13188.65 18176.37 6375.88 16388.44 13453.51 20993.07 15073.30 12189.74 8192.25 86
VPA-MVSNet80.60 11080.55 9380.76 19688.07 14560.80 23086.86 15391.58 8375.67 7380.24 8789.45 11363.34 9890.25 22970.51 14679.22 20991.23 111
PVSNet_BlendedMVS80.60 11080.02 9982.36 16088.85 12065.40 14986.16 17492.00 6469.34 18678.11 12086.09 20966.02 7994.27 8871.52 14182.06 17087.39 243
AdaColmapbinary80.58 11279.42 11584.06 9593.09 4168.91 8789.36 6788.97 16869.27 18775.70 17089.69 10357.20 18295.77 4063.06 19888.41 9987.50 242
EI-MVSNet80.52 11379.98 10082.12 16284.28 21463.19 20786.41 16888.95 17074.18 9778.69 9987.54 15766.62 7292.43 16872.57 13080.57 18890.74 124
XVG-OURS80.41 11479.23 12583.97 10285.64 19669.02 8383.03 24990.39 11371.09 16077.63 12991.49 7254.62 20191.35 20775.71 9783.47 15191.54 103
v1neww80.40 11579.54 11082.98 13484.10 22564.51 17487.57 12290.22 12373.25 12178.47 10586.65 18862.83 11293.86 10975.72 9577.02 22790.58 135
v7new80.40 11579.54 11082.98 13484.10 22564.51 17487.57 12290.22 12373.25 12178.47 10586.65 18862.83 11293.86 10975.72 9577.02 22790.58 135
v680.40 11579.54 11082.98 13484.09 22764.50 17887.57 12290.22 12373.25 12178.47 10586.63 19062.84 11193.86 10975.73 9477.02 22790.58 135
PCF-MVS73.52 780.38 11878.84 13185.01 7087.71 16568.99 8583.65 23691.46 8963.00 25977.77 12790.28 9266.10 7695.09 6561.40 21488.22 10190.94 118
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
X-MVStestdata80.37 11977.83 15388.00 1094.42 1273.33 1792.78 992.99 2979.14 2183.67 5312.47 35367.45 6796.60 2183.06 3994.50 3694.07 24
test_djsdf80.30 12079.32 11983.27 12083.98 23465.37 15290.50 4390.38 11468.55 20276.19 15888.70 12456.44 18693.46 13178.98 6480.14 19590.97 117
v780.24 12179.26 12483.15 12484.07 23164.94 16387.56 12590.67 10472.26 14578.28 11286.51 19761.45 14294.03 10075.14 10577.41 22190.49 140
v2v48280.23 12279.29 12383.05 13083.62 24264.14 18587.04 14789.97 13473.61 11278.18 11987.22 16661.10 15093.82 11276.11 9076.78 23891.18 112
NR-MVSNet80.23 12279.38 11782.78 15187.80 16063.34 20186.31 17191.09 9879.01 2672.17 21989.07 11867.20 6992.81 16166.08 17975.65 25092.20 88
v114180.19 12479.31 12082.85 14383.84 23764.12 18787.14 14090.08 13073.13 12478.27 11386.39 19962.67 12193.75 11975.40 10276.83 23590.68 126
divwei89l23v2f11280.19 12479.31 12082.85 14383.84 23764.11 18987.13 14390.08 13073.13 12478.27 11386.39 19962.69 11993.75 11975.40 10276.82 23690.68 126
v180.19 12479.31 12082.85 14383.83 23964.12 18787.14 14090.07 13273.13 12478.27 11386.38 20362.72 11893.75 11975.41 10176.82 23690.68 126
IterMVS-LS80.06 12779.38 11782.11 16385.89 19263.20 20686.79 15689.34 15074.19 9675.45 17386.72 18066.62 7292.39 17072.58 12976.86 23290.75 123
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
Effi-MVS+-dtu80.03 12878.57 13784.42 8485.13 20468.74 9288.77 8588.10 19074.99 8674.97 18883.49 25557.27 17993.36 13673.53 11880.88 18291.18 112
v114480.03 12879.03 12883.01 13283.78 24064.51 17487.11 14590.57 10971.96 14978.08 12286.20 20761.41 14393.94 10374.93 10677.23 22390.60 132
v879.97 13079.02 12982.80 14884.09 22764.50 17887.96 11290.29 12274.13 9975.24 18286.81 17762.88 10993.89 10874.39 10975.40 25590.00 161
DI_MVS_plusplus_test79.89 13178.58 13683.85 10682.89 26265.32 15386.12 17589.55 14469.64 18270.55 23685.82 22057.24 18193.81 11376.85 8688.55 9592.41 81
test_normal79.81 13278.45 13983.89 10582.70 26665.40 14985.82 18689.48 14769.39 18370.12 24585.66 22357.15 18393.71 12477.08 8388.62 9392.56 77
OpenMVScopyleft72.83 1079.77 13378.33 14584.09 9485.17 20169.91 6890.57 4190.97 9966.70 22372.17 21991.91 6054.70 19993.96 10161.81 21190.95 6888.41 225
v1079.74 13478.67 13282.97 13884.06 23264.95 16287.88 11790.62 10773.11 12775.11 18586.56 19461.46 14194.05 9973.68 11475.55 25289.90 169
BH-RMVSNet79.61 13578.44 14183.14 12589.38 10265.93 13984.95 20887.15 20673.56 11478.19 11889.79 10256.67 18593.36 13659.53 22986.74 11690.13 152
v119279.59 13678.43 14283.07 12983.55 24464.52 17286.93 15190.58 10870.83 16277.78 12685.90 21659.15 16793.94 10373.96 11377.19 22590.76 122
diffmvs79.51 13778.59 13582.25 16183.31 24962.66 21484.17 22888.11 18867.64 21576.09 16287.47 15964.01 9391.15 21271.71 14084.82 13492.94 70
ab-mvs79.51 13778.97 13081.14 19088.46 13660.91 22883.84 23489.24 15670.36 17079.03 9588.87 12263.23 10290.21 23065.12 18582.57 16792.28 85
WR-MVS79.49 13979.22 12680.27 20488.79 12658.35 24585.06 20688.61 18378.56 2977.65 12888.34 13663.81 9690.66 22564.98 18877.22 22491.80 100
v14419279.47 14078.37 14382.78 15183.35 24763.96 19186.96 14990.36 11769.99 17577.50 13085.67 22260.66 15793.77 11774.27 11076.58 23990.62 130
BH-untuned79.47 14078.60 13482.05 16489.19 11365.91 14086.07 17788.52 18472.18 14675.42 17487.69 15261.15 14993.54 12860.38 22186.83 11586.70 261
mvs_anonymous79.42 14279.11 12780.34 20184.45 21357.97 25282.59 25087.62 19967.40 22276.17 16188.56 13168.47 5989.59 23870.65 14586.05 12593.47 51
V4279.38 14378.24 14782.83 14681.10 28865.50 14885.55 19689.82 13871.57 15578.21 11786.12 20860.66 15793.18 14475.64 9875.46 25489.81 174
jajsoiax79.29 14477.96 15083.27 12084.68 21066.57 13189.25 7090.16 12769.20 18975.46 17289.49 10845.75 28593.13 14776.84 8780.80 18490.11 153
v192192079.22 14578.03 14982.80 14883.30 25063.94 19286.80 15590.33 11969.91 17677.48 13185.53 22758.44 17193.75 11973.60 11776.85 23390.71 125
TAPA-MVS73.13 979.15 14677.94 15182.79 15089.59 9362.99 21288.16 10991.51 8665.77 23577.14 14091.09 7860.91 15393.21 14050.26 27887.05 11392.17 90
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
mvs_tets79.13 14777.77 15683.22 12284.70 20966.37 13389.17 7190.19 12669.38 18575.40 17589.46 11144.17 29193.15 14576.78 8880.70 18690.14 151
CDS-MVSNet79.07 14877.70 15783.17 12387.60 16768.23 10584.40 22486.20 21767.49 22076.36 15286.54 19561.54 14090.79 22361.86 21087.33 11090.49 140
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
MVSTER79.01 14977.88 15282.38 15983.07 25664.80 16684.08 23288.95 17069.01 19678.69 9987.17 16954.70 19992.43 16874.69 10780.57 18889.89 170
v124078.99 15077.78 15582.64 15583.21 25163.54 19586.62 16290.30 12169.74 18177.33 13385.68 22157.04 18493.76 11873.13 12376.92 23090.62 130
v7n78.97 15177.58 15983.14 12583.45 24665.51 14788.32 10291.21 9473.69 11172.41 21686.32 20457.93 17493.81 11369.18 15675.65 25090.11 153
TAMVS78.89 15277.51 16083.03 13187.80 16067.79 11384.72 21185.05 22867.63 21676.75 14387.70 15162.25 13290.82 22258.53 23887.13 11290.49 140
v14878.72 15377.80 15481.47 18382.73 26561.96 22286.30 17288.08 19273.26 12076.18 15985.47 22962.46 12992.36 17271.92 13973.82 27290.09 155
VPNet78.69 15478.66 13378.76 23488.31 14155.72 29084.45 22186.63 21176.79 5178.26 11690.55 9059.30 16689.70 23766.63 17477.05 22690.88 119
anonymousdsp78.60 15577.15 16582.98 13480.51 29467.08 12387.24 13889.53 14565.66 23775.16 18387.19 16852.52 21292.25 17577.17 8279.34 20789.61 182
WR-MVS_H78.51 15678.49 13878.56 23788.02 14756.38 27988.43 9592.67 4177.14 4373.89 19587.55 15666.25 7589.24 24558.92 23373.55 27490.06 159
GBi-Net78.40 15777.40 16181.40 18587.60 16763.01 20988.39 9989.28 15271.63 15275.34 17787.28 16254.80 19591.11 21362.72 19979.57 20390.09 155
test178.40 15777.40 16181.40 18587.60 16763.01 20988.39 9989.28 15271.63 15275.34 17787.28 16254.80 19591.11 21362.72 19979.57 20390.09 155
Vis-MVSNet (Re-imp)78.36 15978.45 13978.07 24688.64 13051.78 31386.70 16079.63 29074.14 9875.11 18590.83 8661.29 14689.75 23558.10 24291.60 6092.69 74
CP-MVSNet78.22 16078.34 14477.84 24887.83 15854.54 29587.94 11491.17 9677.65 3373.48 19788.49 13262.24 13388.43 26562.19 20574.07 26790.55 138
BH-w/o78.21 16177.33 16380.84 19488.81 12465.13 15984.87 20987.85 19669.75 17974.52 19284.74 24361.34 14493.11 14858.24 24185.84 12884.27 294
FMVSNet278.20 16277.21 16481.20 18887.60 16762.89 21387.47 12989.02 16171.63 15275.29 18187.28 16254.80 19591.10 21662.38 20379.38 20689.61 182
MVS78.19 16376.99 16781.78 16985.66 19566.99 12484.66 21290.47 11255.08 31572.02 22485.27 23263.83 9594.11 9866.10 17889.80 8084.24 295
Baseline_NR-MVSNet78.15 16478.33 14577.61 25285.79 19356.21 28286.78 15785.76 22273.60 11377.93 12487.57 15565.02 8688.99 25667.14 17175.33 25687.63 238
CNLPA78.08 16576.79 17181.97 16690.40 7571.07 4987.59 12184.55 23166.03 23472.38 21789.64 10557.56 17786.04 28459.61 22783.35 15688.79 206
PLCcopyleft70.83 1178.05 16676.37 17783.08 12891.88 6067.80 11288.19 10789.46 14864.33 24969.87 25188.38 13553.66 20893.58 12658.86 23482.73 16487.86 234
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
Fast-Effi-MVS+-dtu78.02 16776.49 17482.62 15683.16 25566.96 12786.94 15087.45 20472.45 14071.49 23084.17 24654.79 19891.58 20467.61 16480.31 19289.30 186
PS-CasMVS78.01 16878.09 14877.77 25087.71 16554.39 29788.02 11091.22 9377.50 4073.26 19988.64 12760.73 15488.41 26661.88 20973.88 27190.53 139
v74877.97 16976.65 17381.92 16882.29 27263.28 20387.53 12690.35 11873.50 11770.76 23585.55 22658.28 17292.81 16168.81 15972.76 27989.67 181
V477.95 17076.37 17782.67 15379.40 30665.52 14586.43 16689.94 13572.28 14372.14 22284.95 23855.72 18993.44 13373.64 11572.86 27789.05 194
HY-MVS69.67 1277.95 17077.15 16580.36 20087.57 17160.21 23483.37 24787.78 19766.11 23175.37 17687.06 17563.27 10090.48 22761.38 21582.43 16890.40 145
v5277.94 17276.37 17782.67 15379.39 30765.52 14586.43 16689.94 13572.28 14372.15 22184.94 23955.70 19093.44 13373.64 11572.84 27889.06 190
FMVSNet377.88 17376.85 16980.97 19386.84 18362.36 21686.52 16588.77 17771.13 15875.34 17786.66 18754.07 20591.10 21662.72 19979.57 20389.45 184
Test477.83 17475.90 19183.62 10880.24 29665.25 15585.27 20290.67 10469.03 19566.48 28683.75 25143.07 29693.00 15475.93 9388.66 9292.62 76
PEN-MVS77.73 17577.69 15877.84 24887.07 18053.91 29987.91 11691.18 9577.56 3773.14 20188.82 12361.23 14789.17 25259.95 22472.37 28090.43 143
v1677.69 17676.36 18081.68 17684.15 22264.63 17187.33 13388.99 16572.69 13869.31 25982.08 26862.80 11591.79 18772.70 12767.23 30288.63 211
v1777.68 17776.35 18181.69 17584.15 22264.65 16987.33 13388.99 16572.70 13769.25 26082.07 26962.82 11491.79 18772.69 12867.15 30488.63 211
PAPM77.68 17776.40 17681.51 18287.29 17761.85 22383.78 23589.59 14364.74 24471.23 23188.70 12462.59 12493.66 12552.66 26987.03 11489.01 197
v1877.67 17976.35 18181.64 17884.09 22764.47 18087.27 13689.01 16372.59 13969.39 25682.04 27062.85 11091.80 18672.72 12667.20 30388.63 211
CHOSEN 1792x268877.63 18075.69 19283.44 11389.98 8368.58 9978.70 28587.50 20256.38 31075.80 16586.84 17658.67 16991.40 20661.58 21385.75 12990.34 146
HyFIR lowres test77.53 18175.40 20083.94 10489.59 9366.62 12980.36 26888.64 18256.29 31176.45 14885.17 23357.64 17693.28 13861.34 21683.10 16091.91 95
V1477.52 18276.12 18481.70 17484.15 22264.77 16787.21 13988.95 17072.80 13468.79 26281.94 27662.69 11991.72 19372.31 13366.27 31188.60 215
V977.52 18276.11 18781.73 17384.19 22164.89 16487.26 13788.94 17372.87 13368.65 26581.96 27562.65 12291.72 19372.27 13466.24 31288.60 215
v1577.51 18476.12 18481.66 17784.09 22764.65 16987.14 14088.96 16972.76 13568.90 26181.91 27762.74 11791.73 19172.32 13266.29 31088.61 214
v1277.51 18476.09 18881.76 17284.22 21764.99 16187.30 13588.93 17472.92 13068.48 26981.97 27362.54 12691.70 19672.24 13566.21 31488.58 218
v1377.50 18676.07 18981.77 17084.23 21665.07 16087.34 13288.91 17572.92 13068.35 27081.97 27362.53 12791.69 19772.20 13666.22 31388.56 220
v1177.45 18776.06 19081.59 18184.22 21764.52 17287.11 14589.02 16172.76 13568.76 26381.90 27862.09 13591.71 19571.98 13766.73 30588.56 220
FMVSNet177.44 18876.12 18481.40 18586.81 18463.01 20988.39 9989.28 15270.49 16974.39 19387.28 16249.06 26791.11 21360.91 21878.52 21190.09 155
TR-MVS77.44 18876.18 18381.20 18888.24 14263.24 20484.61 21686.40 21467.55 21977.81 12586.48 19854.10 20493.15 14557.75 24582.72 16587.20 249
1112_ss77.40 19076.43 17580.32 20289.11 11760.41 23383.65 23687.72 19862.13 27073.05 20286.72 18062.58 12589.97 23262.11 20880.80 18490.59 134
pm-mvs177.25 19176.68 17278.93 23184.22 21758.62 24386.41 16888.36 18671.37 15773.31 19888.01 14461.22 14889.15 25364.24 19273.01 27689.03 196
LCM-MVSNet-Re77.05 19276.94 16877.36 25787.20 17851.60 31480.06 27080.46 28175.20 8467.69 27486.72 18062.48 12888.98 25763.44 19589.25 8591.51 104
DTE-MVSNet76.99 19376.80 17077.54 25486.24 18953.06 31087.52 12790.66 10677.08 4672.50 20788.67 12660.48 16089.52 23957.33 24970.74 29190.05 160
LS3D76.95 19474.82 21083.37 11790.45 7367.36 12089.15 7586.94 20861.87 27269.52 25490.61 8951.71 23594.53 8146.38 30486.71 11788.21 227
GA-MVS76.87 19575.17 20881.97 16682.75 26462.58 21581.44 26286.35 21672.16 14874.74 19082.89 25846.20 28092.02 18068.85 15881.09 18091.30 110
DP-MVS76.78 19674.57 21283.42 11493.29 3469.46 7988.55 9483.70 23863.98 25370.20 24188.89 12154.01 20694.80 7646.66 30181.88 17386.01 277
cascas76.72 19774.64 21182.99 13385.78 19465.88 14182.33 25289.21 15760.85 27872.74 20481.02 28547.28 27393.75 11967.48 16685.02 13089.34 185
conf200view1176.55 19875.55 19579.57 21989.52 9556.99 26685.83 18383.23 24673.94 10176.32 15387.12 17051.89 22691.95 18148.33 28683.75 14489.78 175
tfpn11176.54 19975.51 19779.61 21689.52 9556.99 26685.83 18383.23 24673.94 10176.32 15387.12 17051.89 22692.06 17948.04 29383.73 14889.78 175
131476.53 20075.30 20380.21 20583.93 23562.32 21884.66 21288.81 17660.23 28270.16 24484.07 24855.30 19390.73 22467.37 16783.21 15887.59 240
thres100view90076.50 20175.55 19579.33 22189.52 9556.99 26685.83 18383.23 24673.94 10176.32 15387.12 17051.89 22691.95 18148.33 28683.75 14489.07 188
thres600view776.50 20175.44 19879.68 21389.40 10157.16 26385.53 19883.23 24673.79 11076.26 15687.09 17351.89 22691.89 18548.05 29283.72 14990.00 161
thres40076.50 20175.37 20179.86 20989.13 11557.65 25885.17 20383.60 23973.41 11876.45 14886.39 19952.12 22091.95 18148.33 28683.75 14490.00 161
tfpn200view976.42 20475.37 20179.55 22089.13 11557.65 25885.17 20383.60 23973.41 11876.45 14886.39 19952.12 22091.95 18148.33 28683.75 14489.07 188
Test_1112_low_res76.40 20575.44 19879.27 22289.28 10958.09 24881.69 25887.07 20759.53 28872.48 20986.67 18661.30 14589.33 24360.81 22080.15 19490.41 144
F-COLMAP76.38 20674.33 21782.50 15789.28 10966.95 12888.41 9889.03 16064.05 25166.83 28288.61 12846.78 27692.89 15657.48 24678.55 21087.67 237
LTVRE_ROB69.57 1376.25 20774.54 21481.41 18488.60 13164.38 18379.24 27889.12 15970.76 16569.79 25387.86 14549.09 26693.20 14256.21 25580.16 19386.65 262
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 20875.21 20479.16 22689.64 8855.82 28585.74 18882.06 26373.88 10575.74 16687.85 14651.84 23091.66 19846.75 29783.42 15290.00 161
view80076.20 20875.21 20479.16 22689.64 8855.82 28585.74 18882.06 26373.88 10575.74 16687.85 14651.84 23091.66 19846.75 29783.42 15290.00 161
conf0.05thres100076.20 20875.21 20479.16 22689.64 8855.82 28585.74 18882.06 26373.88 10575.74 16687.85 14651.84 23091.66 19846.75 29783.42 15290.00 161
tfpn76.20 20875.21 20479.16 22689.64 8855.82 28585.74 18882.06 26373.88 10575.74 16687.85 14651.84 23091.66 19846.75 29783.42 15290.00 161
MVP-Stereo76.12 21274.46 21681.13 19185.37 20069.79 7084.42 22387.95 19465.03 24267.46 27685.33 23153.28 21191.73 19158.01 24383.27 15781.85 314
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
XVG-ACMP-BASELINE76.11 21374.27 21881.62 17983.20 25264.67 16883.60 23889.75 14069.75 17971.85 22587.09 17332.78 32892.11 17869.99 15080.43 19188.09 229
ACMH+68.96 1476.01 21474.01 21982.03 16588.60 13165.31 15488.86 8187.55 20070.25 17367.75 27387.47 15941.27 30693.19 14358.37 23975.94 24687.60 239
ACMH67.68 1675.89 21573.93 22081.77 17088.71 12966.61 13088.62 9189.01 16369.81 17766.78 28386.70 18541.95 30591.51 20555.64 25678.14 21687.17 250
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
IB-MVS68.01 1575.85 21673.36 22483.31 11884.76 20866.03 13683.38 24085.06 22770.21 17469.40 25581.05 28445.76 28494.66 7965.10 18675.49 25389.25 187
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 21773.34 22582.89 14277.37 31565.22 15684.10 23190.54 11069.09 19160.46 31181.15 28340.48 30992.84 16076.36 8980.54 19090.60 132
WTY-MVS75.65 21875.68 19375.57 27786.40 18856.82 27077.92 29182.40 25765.10 24176.18 15987.72 15063.13 10780.90 30660.31 22281.96 17189.00 199
thres20075.55 21974.47 21578.82 23387.78 16357.85 25583.07 24883.51 24272.44 14275.84 16484.42 24552.08 22291.75 19047.41 29583.64 15086.86 257
EPNet_dtu75.46 22074.86 20977.23 26082.57 26954.60 29486.89 15283.09 25171.64 15166.25 28885.86 21855.99 18888.04 27054.92 25986.55 11989.05 194
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
XXY-MVS75.41 22175.56 19474.96 28183.59 24357.82 25680.59 26783.87 23766.54 22874.93 18988.31 13763.24 10180.09 31062.16 20676.85 23386.97 255
TransMVSNet (Re)75.39 22274.56 21377.86 24785.50 19957.10 26586.78 15786.09 22072.17 14771.53 22987.34 16163.01 10889.31 24456.84 25261.83 32287.17 250
CostFormer75.24 22373.90 22179.27 22282.65 26858.27 24780.80 26382.73 25561.57 27375.33 18083.13 25755.52 19191.07 21964.98 18878.34 21588.45 223
pmmvs674.69 22473.39 22378.61 23681.38 28357.48 26186.64 16187.95 19464.99 24370.18 24286.61 19150.43 25589.52 23962.12 20770.18 29388.83 204
PatchFormer-LS_test74.50 22573.05 22778.86 23282.95 26059.55 23981.65 25982.30 25967.44 22171.62 22878.15 30552.34 21688.92 26165.05 18775.90 24788.12 228
tfpnnormal74.39 22673.16 22678.08 24586.10 19158.05 24984.65 21587.53 20170.32 17171.22 23285.63 22454.97 19489.86 23343.03 32175.02 26086.32 269
IterMVS74.29 22772.94 22878.35 24281.53 28063.49 19781.58 26082.49 25668.06 21369.99 24883.69 25351.66 23685.54 28765.85 18171.64 28686.01 277
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
OurMVSNet-221017-074.26 22872.42 23479.80 21183.76 24159.59 23685.92 18186.64 21066.39 22966.96 28187.58 15439.46 31291.60 20365.76 18269.27 29588.22 226
EG-PatchMatch MVS74.04 22971.82 24580.71 19784.92 20767.42 11785.86 18288.08 19266.04 23364.22 30083.85 24935.10 32792.56 16657.44 24780.83 18382.16 313
pmmvs474.03 23071.91 24280.39 19981.96 27568.32 10281.45 26182.14 26159.32 28969.87 25185.13 23452.40 21588.13 26960.21 22374.74 26384.73 292
MS-PatchMatch73.83 23172.67 23077.30 25983.87 23666.02 13781.82 25584.66 23061.37 27668.61 26782.82 26047.29 27288.21 26759.27 23084.32 13977.68 327
tfpn_ndepth73.70 23272.75 22976.52 26487.78 16354.92 29384.32 22680.28 28567.57 21872.50 20784.82 24050.12 25789.44 24245.73 30781.66 17585.20 284
DWT-MVSNet_test73.70 23271.86 24379.21 22482.91 26158.94 24182.34 25182.17 26065.21 23971.05 23478.31 30344.21 29090.17 23163.29 19777.28 22288.53 222
conf0.0173.67 23472.42 23477.42 25587.85 15153.28 30483.38 24079.08 29368.40 20572.45 21086.08 21050.60 24889.19 24644.25 31279.66 19789.78 175
conf0.00273.67 23472.42 23477.42 25587.85 15153.28 30483.38 24079.08 29368.40 20572.45 21086.08 21050.60 24889.19 24644.25 31279.66 19789.78 175
sss73.60 23673.64 22273.51 29282.80 26355.01 29276.12 29781.69 26962.47 26774.68 19185.85 21957.32 17878.11 31860.86 21980.93 18187.39 243
Patchmatch-test173.49 23771.85 24478.41 24184.05 23362.17 22079.96 27279.29 29266.30 23072.38 21779.58 29751.95 22585.08 29155.46 25777.67 21987.99 230
tpmp4_e2373.45 23871.17 25280.31 20383.55 24459.56 23881.88 25482.33 25857.94 30070.51 23881.62 27951.19 24091.63 20253.96 26377.51 22089.75 180
tfpn100073.44 23972.49 23276.29 27087.81 15953.69 30184.05 23378.81 30067.99 21472.09 22386.27 20549.95 25989.04 25544.09 31881.38 17786.15 272
thresconf0.0273.39 24072.42 23476.31 26687.85 15153.28 30483.38 24079.08 29368.40 20572.45 21086.08 21050.60 24889.19 24644.25 31279.66 19786.48 264
tfpn_n40073.39 24072.42 23476.31 26687.85 15153.28 30483.38 24079.08 29368.40 20572.45 21086.08 21050.60 24889.19 24644.25 31279.66 19786.48 264
tfpnconf73.39 24072.42 23476.31 26687.85 15153.28 30483.38 24079.08 29368.40 20572.45 21086.08 21050.60 24889.19 24644.25 31279.66 19786.48 264
tfpnview1173.39 24072.42 23476.31 26687.85 15153.28 30483.38 24079.08 29368.40 20572.45 21086.08 21050.60 24889.19 24644.25 31279.66 19786.48 264
SixPastTwentyTwo73.37 24471.26 25179.70 21285.08 20657.89 25485.57 19283.56 24171.03 16165.66 29085.88 21742.10 30392.57 16559.11 23263.34 31988.65 210
CR-MVSNet73.37 24471.27 25079.67 21481.32 28665.19 15775.92 29980.30 28359.92 28572.73 20581.19 28152.50 21386.69 27859.84 22577.71 21787.11 253
MSDG73.36 24670.99 25380.49 19884.51 21265.80 14280.71 26586.13 21965.70 23665.46 29183.74 25244.60 28890.91 22151.13 27376.89 23184.74 291
tpm273.26 24771.46 24778.63 23583.34 24856.71 27380.65 26680.40 28256.63 30973.55 19682.02 27151.80 23491.24 21056.35 25478.42 21487.95 231
RPSCF73.23 24871.46 24778.54 23882.50 27059.85 23582.18 25382.84 25458.96 29271.15 23389.41 11545.48 28784.77 29358.82 23571.83 28591.02 116
PatchmatchNetpermissive73.12 24971.33 24978.49 24083.18 25360.85 22979.63 27478.57 30164.13 25071.73 22679.81 29651.20 23985.97 28557.40 24876.36 24388.66 209
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
COLMAP_ROBcopyleft66.92 1773.01 25070.41 25780.81 19587.13 17965.63 14488.30 10384.19 23562.96 26063.80 30387.69 15238.04 31892.56 16646.66 30174.91 26184.24 295
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
CVMVSNet72.99 25172.58 23174.25 28884.28 21450.85 32086.41 16883.45 24444.56 33673.23 20087.54 15749.38 26285.70 28665.90 18078.44 21386.19 271
test-LLR72.94 25272.43 23374.48 28581.35 28458.04 25078.38 28677.46 30666.66 22469.95 24979.00 30148.06 27079.24 31266.13 17684.83 13286.15 272
test_040272.79 25370.44 25679.84 21088.13 14465.99 13885.93 18084.29 23365.57 23867.40 27885.49 22846.92 27592.61 16435.88 33274.38 26680.94 317
tpmrst72.39 25472.13 24173.18 29480.54 29349.91 32479.91 27379.08 29363.11 25771.69 22779.95 29355.32 19282.77 30165.66 18373.89 27086.87 256
PatchMatch-RL72.38 25570.90 25476.80 26388.60 13167.38 11979.53 27576.17 31262.75 26469.36 25782.00 27245.51 28684.89 29253.62 26580.58 18778.12 325
tpm72.37 25671.71 24674.35 28782.19 27352.00 31179.22 27977.29 30864.56 24672.95 20383.68 25451.35 23783.26 30058.33 24075.80 24887.81 235
PVSNet64.34 1872.08 25770.87 25575.69 27586.21 19056.44 27774.37 30980.73 27762.06 27170.17 24382.23 26642.86 29883.31 29954.77 26084.45 13887.32 246
RPMNet71.62 25868.94 26579.67 21481.32 28665.19 15775.92 29978.30 30357.60 30372.73 20576.45 31552.30 21786.69 27848.14 29177.71 21787.11 253
pmmvs571.55 25970.20 25975.61 27677.83 31256.39 27881.74 25780.89 27457.76 30167.46 27684.49 24449.26 26585.32 29057.08 25175.29 25785.11 288
test-mter71.41 26070.39 25874.48 28581.35 28458.04 25078.38 28677.46 30660.32 28169.95 24979.00 30136.08 32579.24 31266.13 17684.83 13286.15 272
K. test v371.19 26168.51 26779.21 22483.04 25857.78 25784.35 22576.91 31072.90 13262.99 30682.86 25939.27 31391.09 21861.65 21252.66 33788.75 207
tpmvs71.09 26269.29 26276.49 26582.04 27456.04 28378.92 28381.37 27364.05 25167.18 28078.28 30449.74 26189.77 23449.67 28172.37 28083.67 299
AllTest70.96 26368.09 27379.58 21785.15 20263.62 19384.58 21779.83 28862.31 26860.32 31286.73 17832.02 32988.96 25950.28 27671.57 28786.15 272
Patchmtry70.74 26469.16 26375.49 27880.72 29054.07 29874.94 30880.30 28358.34 29670.01 24681.19 28152.50 21386.54 28053.37 26671.09 28985.87 280
MIMVSNet70.69 26569.30 26174.88 28284.52 21156.35 28075.87 30179.42 29164.59 24567.76 27282.41 26341.10 30781.54 30546.64 30381.34 17886.75 260
tpm cat170.57 26668.31 26977.35 25882.41 27157.95 25378.08 29080.22 28652.04 32768.54 26877.66 31052.00 22487.84 27251.77 27072.07 28486.25 270
OpenMVS_ROBcopyleft64.09 1970.56 26768.19 27077.65 25180.26 29559.41 24085.01 20782.96 25358.76 29465.43 29282.33 26437.63 32191.23 21145.34 31076.03 24582.32 311
pmmvs-eth3d70.50 26867.83 27778.52 23977.37 31566.18 13581.82 25581.51 27158.90 29363.90 30280.42 29042.69 29986.28 28358.56 23765.30 31683.11 305
USDC70.33 26968.37 26876.21 27280.60 29256.23 28179.19 28086.49 21260.89 27761.29 30885.47 22931.78 33189.47 24153.37 26676.21 24482.94 310
Patchmatch-RL test70.24 27067.78 27977.61 25277.43 31459.57 23771.16 31470.33 33362.94 26168.65 26572.77 32550.62 24785.49 28869.58 15366.58 30887.77 236
CMPMVSbinary51.72 2170.19 27168.16 27176.28 27173.15 33157.55 26079.47 27683.92 23648.02 33456.48 32684.81 24143.13 29586.42 28262.67 20281.81 17484.89 289
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
ppachtmachnet_test70.04 27267.34 28278.14 24479.80 30161.13 22579.19 28080.59 27859.16 29165.27 29379.29 29846.75 27787.29 27549.33 28266.72 30686.00 279
gg-mvs-nofinetune69.95 27367.96 27475.94 27383.07 25654.51 29677.23 29470.29 33463.11 25770.32 24062.33 33743.62 29388.69 26353.88 26487.76 10384.62 293
TESTMET0.1,169.89 27469.00 26472.55 29579.27 30956.85 26978.38 28674.71 32257.64 30268.09 27177.19 31237.75 31976.70 32363.92 19384.09 14084.10 298
FMVSNet569.50 27567.96 27474.15 28982.97 25955.35 29180.01 27182.12 26262.56 26663.02 30481.53 28036.92 32281.92 30348.42 28574.06 26885.17 287
PMMVS69.34 27668.67 26671.35 30275.67 32262.03 22175.17 30373.46 32750.00 33268.68 26479.05 29952.07 22378.13 31761.16 21782.77 16373.90 335
EPMVS69.02 27768.16 27171.59 29879.61 30349.80 32677.40 29366.93 34362.82 26370.01 24679.05 29945.79 28377.86 32056.58 25375.26 25887.13 252
Anonymous2023120668.60 27867.80 27871.02 30480.23 29750.75 32178.30 28980.47 28056.79 30866.11 28982.63 26246.35 27878.95 31443.62 32075.70 24983.36 302
MIMVSNet168.58 27966.78 28473.98 29080.07 29851.82 31280.77 26484.37 23264.40 24859.75 31582.16 26736.47 32383.63 29742.73 32270.33 29286.48 264
EU-MVSNet68.53 28067.61 28171.31 30378.51 31147.01 33084.47 21884.27 23442.27 33766.44 28784.79 24240.44 31083.76 29558.76 23668.54 30183.17 303
PatchT68.46 28167.85 27670.29 30680.70 29143.93 33472.47 31274.88 31860.15 28370.55 23676.57 31449.94 26081.59 30450.58 27474.83 26285.34 283
test0.0.03 168.00 28267.69 28068.90 31177.55 31347.43 32875.70 30272.95 32966.66 22466.56 28482.29 26548.06 27075.87 32744.97 31174.51 26583.41 301
TDRefinement67.49 28364.34 29076.92 26173.47 32961.07 22684.86 21082.98 25259.77 28658.30 31885.13 23426.06 33687.89 27147.92 29460.59 32781.81 315
test20.0367.45 28466.95 28368.94 31075.48 32544.84 33277.50 29277.67 30566.66 22463.01 30583.80 25047.02 27478.40 31642.53 32368.86 29983.58 300
UnsupCasMVSNet_eth67.33 28565.99 28671.37 30073.48 32851.47 31675.16 30485.19 22665.20 24060.78 31080.93 28842.35 30077.20 32257.12 25053.69 33685.44 282
TinyColmap67.30 28664.81 28874.76 28481.92 27656.68 27480.29 26981.49 27260.33 28056.27 32783.22 25624.77 33887.66 27445.52 30869.47 29479.95 321
dp66.80 28765.43 28770.90 30579.74 30248.82 32775.12 30674.77 32059.61 28764.08 30177.23 31142.89 29780.72 30748.86 28466.58 30883.16 304
MDA-MVSNet-bldmvs66.68 28863.66 29275.75 27479.28 30860.56 23273.92 31078.35 30264.43 24750.13 33779.87 29544.02 29283.67 29646.10 30556.86 33183.03 307
testgi66.67 28966.53 28567.08 31675.62 32341.69 33975.93 29876.50 31166.11 23165.20 29686.59 19235.72 32674.71 33143.71 31973.38 27584.84 290
CHOSEN 280x42066.51 29064.71 28971.90 29781.45 28163.52 19657.98 34368.95 34153.57 32262.59 30776.70 31346.22 27975.29 33055.25 25879.68 19676.88 333
PM-MVS66.41 29164.14 29173.20 29373.92 32656.45 27678.97 28264.96 34763.88 25564.72 29780.24 29119.84 34483.44 29866.24 17564.52 31879.71 322
JIA-IIPM66.32 29262.82 29876.82 26277.09 31861.72 22465.34 33575.38 31458.04 29964.51 29862.32 33842.05 30486.51 28151.45 27269.22 29682.21 312
ADS-MVSNet266.20 29363.33 29374.82 28379.92 29958.75 24267.55 33175.19 31653.37 32365.25 29475.86 31642.32 30180.53 30841.57 32468.91 29785.18 285
YYNet165.03 29462.91 29671.38 29975.85 32156.60 27569.12 32574.66 32457.28 30654.12 32977.87 30845.85 28274.48 33249.95 27961.52 32483.05 306
MDA-MVSNet_test_wron65.03 29462.92 29571.37 30075.93 32056.73 27169.09 32674.73 32157.28 30654.03 33077.89 30745.88 28174.39 33349.89 28061.55 32382.99 308
Anonymous2023121164.82 29661.79 30073.91 29177.11 31750.92 31985.29 20181.53 27054.19 31757.98 31978.03 30626.90 33487.83 27337.92 32957.12 33082.99 308
Patchmatch-test64.82 29663.24 29469.57 30879.42 30549.82 32563.49 33869.05 34051.98 32859.95 31480.13 29250.91 24270.98 34140.66 32673.57 27387.90 233
ADS-MVSNet64.36 29862.88 29768.78 31379.92 29947.17 32967.55 33171.18 33253.37 32365.25 29475.86 31642.32 30173.99 33541.57 32468.91 29785.18 285
LF4IMVS64.02 29962.19 29969.50 30970.90 33653.29 30376.13 29677.18 30952.65 32658.59 31680.98 28623.55 33976.52 32453.06 26866.66 30778.68 324
UnsupCasMVSNet_bld63.70 30061.53 30270.21 30773.69 32751.39 31772.82 31181.89 26755.63 31357.81 32071.80 32738.67 31578.61 31549.26 28352.21 33880.63 318
new-patchmatchnet61.73 30161.73 30161.70 32472.74 33224.50 35569.16 32478.03 30461.40 27456.72 32575.53 31838.42 31676.48 32545.95 30657.67 32984.13 297
PVSNet_057.27 2061.67 30259.27 30368.85 31279.61 30357.44 26268.01 32973.44 32855.93 31258.54 31770.41 33044.58 28977.55 32147.01 29635.91 34371.55 337
LP61.36 30357.78 30672.09 29675.54 32458.53 24467.16 33375.22 31551.90 32954.13 32869.97 33137.73 32080.45 30932.74 33655.63 33377.29 329
test235659.50 30458.08 30463.74 32071.23 33541.88 33767.59 33072.42 33153.72 32157.65 32170.74 32926.31 33572.40 33832.03 33971.06 29076.93 331
MVS-HIRNet59.14 30557.67 30763.57 32181.65 27843.50 33571.73 31365.06 34639.59 34151.43 33557.73 34138.34 31782.58 30239.53 32773.95 26964.62 342
testus59.00 30657.91 30562.25 32372.25 33339.09 34269.74 31975.02 31753.04 32557.21 32373.72 32318.76 34670.33 34232.86 33568.57 30077.35 328
test123567858.74 30756.89 31064.30 31869.70 33741.87 33871.05 31574.87 31954.06 31850.63 33671.53 32825.30 33774.10 33431.80 34063.10 32076.93 331
pmmvs357.79 30854.26 31268.37 31464.02 34356.72 27275.12 30665.17 34540.20 33952.93 33369.86 33220.36 34375.48 32945.45 30955.25 33572.90 336
DSMNet-mixed57.77 30956.90 30960.38 32567.70 34135.61 34569.18 32353.97 35032.30 34757.49 32279.88 29440.39 31168.57 34538.78 32872.37 28076.97 330
111157.11 31056.82 31157.97 32869.10 33828.28 35068.90 32774.54 32554.01 31953.71 33174.51 32023.09 34067.90 34632.28 33761.26 32577.73 326
testpf56.51 31157.58 30853.30 33171.99 33441.19 34046.89 34869.32 33958.06 29852.87 33469.45 33327.99 33372.73 33759.59 22862.07 32145.98 347
LCM-MVSNet54.25 31249.68 31867.97 31553.73 35045.28 33166.85 33480.78 27635.96 34339.45 34262.23 3398.70 35678.06 31948.24 29051.20 33980.57 319
testmv53.85 31351.03 31562.31 32261.46 34538.88 34370.95 31874.69 32351.11 33141.26 33966.85 33414.28 35072.13 33929.19 34249.51 34075.93 334
FPMVS53.68 31451.64 31459.81 32665.08 34251.03 31869.48 32269.58 33741.46 33840.67 34072.32 32616.46 34970.00 34324.24 34765.42 31558.40 344
N_pmnet52.79 31553.26 31351.40 33478.99 3107.68 35969.52 3213.89 35951.63 33057.01 32474.98 31940.83 30865.96 34837.78 33064.67 31780.56 320
no-one51.08 31645.79 32166.95 31757.92 34850.49 32359.63 34276.04 31348.04 33331.85 34356.10 34419.12 34580.08 31136.89 33126.52 34570.29 338
new_pmnet50.91 31750.29 31652.78 33268.58 34034.94 34863.71 33756.63 34939.73 34044.95 33865.47 33621.93 34258.48 35034.98 33356.62 33264.92 341
ANet_high50.57 31846.10 32063.99 31948.67 35339.13 34170.99 31780.85 27561.39 27531.18 34557.70 34217.02 34873.65 33631.22 34115.89 35279.18 323
test1235649.28 31948.51 31951.59 33362.06 34419.11 35660.40 34072.45 33047.60 33540.64 34165.68 33513.84 35168.72 34427.29 34446.67 34266.94 340
.test124545.55 32050.02 31732.14 34069.10 33828.28 35068.90 32774.54 32554.01 31953.71 33174.51 32023.09 34067.90 34632.28 3370.02 3550.25 356
Gipumacopyleft45.18 32141.86 32255.16 33077.03 31951.52 31532.50 35180.52 27932.46 34527.12 34635.02 3489.52 35575.50 32822.31 34860.21 32838.45 349
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
PMVScopyleft37.38 2244.16 32240.28 32355.82 32940.82 35642.54 33665.12 33663.99 34834.43 34424.48 34757.12 3433.92 35876.17 32617.10 35055.52 33448.75 345
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
PMMVS240.82 32338.86 32446.69 33653.84 34916.45 35748.61 34749.92 35237.49 34231.67 34460.97 3408.14 35756.42 35128.42 34330.72 34467.19 339
wuykxyi23d39.76 32433.18 32759.51 32746.98 35444.01 33357.70 34467.74 34224.13 34913.98 35434.33 3491.27 36171.33 34034.23 33418.23 34863.18 343
PNet_i23d38.26 32535.42 32546.79 33558.74 34635.48 34659.65 34151.25 35132.45 34623.44 35047.53 3462.04 36058.96 34925.60 34618.09 35045.92 348
pcd1.5k->3k34.07 32635.26 32630.50 34186.92 1810.00 3620.00 35391.58 830.00 3570.00 3580.00 35956.23 1870.00 3600.00 35782.60 16691.49 106
E-PMN31.77 32730.64 32835.15 33852.87 35127.67 35257.09 34547.86 35324.64 34816.40 35233.05 35011.23 35354.90 35214.46 35218.15 34922.87 351
EMVS30.81 32829.65 32934.27 33950.96 35225.95 35456.58 34646.80 35424.01 35015.53 35330.68 35112.47 35254.43 35312.81 35317.05 35122.43 352
MVEpermissive26.22 2330.37 32925.89 33143.81 33744.55 35535.46 34728.87 35239.07 35518.20 35118.58 35140.18 3472.68 35947.37 35417.07 35123.78 34748.60 346
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
cdsmvs_eth3d_5k19.96 33026.61 3300.00 3470.00 3610.00 3620.00 35389.26 1550.00 3570.00 35888.61 12861.62 1390.00 3600.00 3570.00 3580.00 358
tmp_tt18.61 33121.40 33210.23 3444.82 35810.11 35834.70 35030.74 3571.48 35423.91 34926.07 35228.42 33213.41 35727.12 34515.35 3537.17 353
wuyk23d16.82 33215.94 33319.46 34358.74 34631.45 34939.22 3493.74 3606.84 3536.04 3552.70 3561.27 36124.29 35610.54 35414.40 3542.63 354
ab-mvs-re7.23 3339.64 3340.00 3470.00 3610.00 3620.00 3530.00 3630.00 3570.00 35886.72 1800.00 3650.00 3600.00 3570.00 3580.00 358
test1236.12 3348.11 3350.14 3450.06 3600.09 36071.05 3150.03 3620.04 3560.25 3571.30 3580.05 3630.03 3590.21 3560.01 3570.29 355
testmvs6.04 3358.02 3360.10 3460.08 3590.03 36169.74 3190.04 3610.05 3550.31 3561.68 3570.02 3640.04 3580.24 3550.02 3550.25 356
pcd_1.5k_mvsjas5.26 3367.02 3370.00 3470.00 3610.00 3620.00 3530.00 3630.00 3570.00 3580.00 35963.15 1040.00 3600.00 3570.00 3580.00 358
sosnet-low-res0.00 3370.00 3380.00 3470.00 3610.00 3620.00 3530.00 3630.00 3570.00 3580.00 3590.00 3650.00 3600.00 3570.00 3580.00 358
sosnet0.00 3370.00 3380.00 3470.00 3610.00 3620.00 3530.00 3630.00 3570.00 3580.00 3590.00 3650.00 3600.00 3570.00 3580.00 358
uncertanet0.00 3370.00 3380.00 3470.00 3610.00 3620.00 3530.00 3630.00 3570.00 3580.00 3590.00 3650.00 3600.00 3570.00 3580.00 358
Regformer0.00 3370.00 3380.00 3470.00 3610.00 3620.00 3530.00 3630.00 3570.00 3580.00 3590.00 3650.00 3600.00 3570.00 3580.00 358
uanet0.00 3370.00 3380.00 3470.00 3610.00 3620.00 3530.00 3630.00 3570.00 3580.00 3590.00 3650.00 3600.00 3570.00 3580.00 358
GSMVS88.96 201
test_part392.22 1975.63 7495.29 397.56 186.60 13
test_part295.06 172.65 2791.80 2
test_part194.09 181.79 196.38 393.74 37
sam_mvs151.32 23888.96 201
sam_mvs50.01 258
semantic-postprocess80.11 20682.69 26764.85 16583.47 24369.16 19070.49 23984.15 24750.83 24688.15 26869.23 15572.14 28387.34 245
ambc75.24 28073.16 33050.51 32263.05 33987.47 20364.28 29977.81 30917.80 34789.73 23657.88 24460.64 32685.49 281
MTGPAbinary92.02 61
test_post178.90 2845.43 35548.81 26985.44 28959.25 231
test_post5.46 35450.36 25684.24 294
patchmatchnet-post74.00 32251.12 24188.60 264
GG-mvs-BLEND75.38 27981.59 27955.80 28979.32 27769.63 33667.19 27973.67 32443.24 29488.90 26250.41 27584.50 13681.45 316
MTMP32.83 356
gm-plane-assit81.40 28253.83 30062.72 26580.94 28792.39 17063.40 196
test9_res84.90 2095.70 1592.87 71
TEST993.26 3672.96 2088.75 8791.89 7068.44 20485.00 3093.10 4274.36 1895.41 51
test_893.13 3872.57 3188.68 9091.84 7368.69 20084.87 3693.10 4274.43 1595.16 59
agg_prior282.91 4295.45 1792.70 72
agg_prior92.85 4471.94 4291.78 7684.41 4294.93 68
TestCases79.58 21785.15 20263.62 19379.83 28862.31 26860.32 31286.73 17832.02 32988.96 25950.28 27671.57 28786.15 272
test_prior472.60 3089.01 78
test_prior288.85 8275.41 7884.91 3293.54 3274.28 1983.31 3595.86 9
test_prior86.33 4892.61 4969.59 7492.97 3295.48 4693.91 31
旧先验286.56 16458.10 29787.04 1688.98 25774.07 112
新几何286.29 173
新几何183.42 11493.13 3870.71 5785.48 22357.43 30481.80 7391.98 5963.28 9992.27 17464.60 19192.99 5087.27 247
旧先验191.96 5765.79 14386.37 21593.08 4669.31 5592.74 5388.74 208
无先验87.48 12888.98 16760.00 28494.12 9667.28 16888.97 200
原ACMM286.86 153
原ACMM184.35 8793.01 4268.79 8892.44 4663.96 25481.09 8191.57 6966.06 7895.45 4867.19 17094.82 3288.81 205
test22291.50 6268.26 10484.16 22983.20 25054.63 31679.74 8891.63 6758.97 16891.42 6386.77 259
testdata291.01 22062.37 204
segment_acmp73.08 26
testdata79.97 20890.90 6964.21 18484.71 22959.27 29085.40 2592.91 4762.02 13689.08 25468.95 15791.37 6486.63 263
testdata184.14 23075.71 71
test1286.80 4092.63 4870.70 5891.79 7582.71 6471.67 3596.16 3294.50 3693.54 49
plane_prior790.08 8168.51 100
plane_prior689.84 8668.70 9660.42 161
plane_prior592.44 4695.38 5378.71 6686.32 12291.33 108
plane_prior491.00 83
plane_prior368.60 9878.44 3078.92 97
plane_prior291.25 3179.12 23
plane_prior189.90 85
plane_prior68.71 9490.38 4777.62 3486.16 124
n20.00 363
nn0.00 363
door-mid69.98 335
lessismore_v078.97 23081.01 28957.15 26465.99 34461.16 30982.82 26039.12 31491.34 20859.67 22646.92 34188.43 224
LGP-MVS_train84.50 8189.23 11168.76 9091.94 6875.37 8076.64 14691.51 7054.29 20294.91 7078.44 6883.78 14289.83 172
test1192.23 53
door69.44 338
HQP5-MVS66.98 125
HQP-NCC89.33 10389.17 7176.41 5977.23 137
ACMP_Plane89.33 10389.17 7176.41 5977.23 137
BP-MVS77.47 78
HQP4-MVS77.24 13695.11 6191.03 114
HQP3-MVS92.19 5685.99 126
HQP2-MVS60.17 164
NP-MVS89.62 9268.32 10290.24 93
MDTV_nov1_ep13_2view37.79 34475.16 30455.10 31466.53 28549.34 26353.98 26287.94 232
MDTV_nov1_ep1369.97 26083.18 25353.48 30277.10 29580.18 28760.45 27969.33 25880.44 28948.89 26886.90 27751.60 27178.51 212
ACMMP++_ref81.95 172
ACMMP++81.25 179
Test By Simon64.33 90
ITE_SJBPF78.22 24381.77 27760.57 23183.30 24569.25 18867.54 27587.20 16736.33 32487.28 27654.34 26174.62 26486.80 258
DeepMVS_CXcopyleft27.40 34240.17 35726.90 35324.59 35817.44 35223.95 34848.61 3459.77 35426.48 35518.06 34924.47 34628.83 350