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
LCM-MVSNet86.90 188.67 181.57 2091.50 163.30 10684.80 2787.77 786.18 196.26 296.06 190.32 184.49 5068.08 8497.05 396.93 1
TDRefinement86.32 286.33 286.29 188.64 3081.19 688.84 290.72 178.27 787.95 1792.53 1379.37 1184.79 4774.51 3796.15 492.88 9
abl_684.92 385.70 382.57 1486.72 4179.27 887.56 586.08 1677.48 988.12 1691.53 3081.18 684.31 5578.12 2394.47 3584.15 118
HPM-MVS_fast84.59 485.10 483.06 488.60 3175.83 2386.27 1986.89 1173.69 1786.17 3991.70 2578.23 1585.20 4079.45 1294.91 2688.15 62
ACMMPcopyleft84.22 584.84 682.35 1789.23 2276.66 2287.65 485.89 1871.03 3185.85 4490.58 5178.77 1385.78 3079.37 1595.17 1884.62 104
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
LTVRE_ROB75.46 184.22 584.98 581.94 1984.82 6375.40 2691.60 187.80 573.52 1888.90 1393.06 671.39 5981.53 9381.53 392.15 6988.91 48
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
HPM-MVScopyleft84.12 784.63 782.60 1288.21 3474.40 3185.24 2387.21 970.69 3485.14 5390.42 6078.99 1286.62 1180.83 694.93 2586.79 75
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
CP-MVS84.12 784.55 882.80 989.42 1879.74 788.19 384.43 4071.96 2884.70 6090.56 5277.12 1786.18 2179.24 1795.36 1482.49 153
mPP-MVS84.01 984.39 982.88 590.65 481.38 587.08 982.79 6872.41 2485.11 5590.85 4476.65 2084.89 4479.30 1694.63 3282.35 155
COLMAP_ROBcopyleft72.78 383.75 1084.11 1382.68 1182.97 8874.39 3287.18 788.18 478.98 586.11 4191.47 3279.70 1085.76 3166.91 10195.46 1387.89 64
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
ACMMPR83.62 1183.93 1582.69 1089.78 1177.51 1887.01 1184.19 4770.23 3584.49 6390.67 5075.15 3186.37 1579.58 1094.26 4284.18 117
APD-MVS_3200maxsize83.57 1284.33 1081.31 2782.83 9073.53 4085.50 2287.45 874.11 1586.45 3590.52 5580.02 984.48 5177.73 2594.34 4085.93 84
region2R83.54 1383.86 1782.58 1389.82 1077.53 1687.06 1084.23 4670.19 3783.86 7090.72 4975.20 3086.27 1879.41 1494.25 4383.95 122
XVS83.51 1483.73 1882.85 789.43 1677.61 1486.80 1384.66 3672.71 2282.87 7890.39 6273.86 4186.31 1678.84 1994.03 4684.64 102
LPG-MVS_test83.47 1584.33 1080.90 3387.00 3870.41 5782.04 4586.35 1269.77 3987.75 1891.13 3681.83 386.20 1977.13 2895.96 786.08 80
HFP-MVS83.39 1684.03 1481.48 2289.25 2075.69 2487.01 1184.27 4370.23 3584.47 6490.43 5776.79 1885.94 2779.58 1094.23 4482.82 144
MTAPA83.19 1783.87 1681.13 3091.16 278.16 1284.87 2580.63 11172.08 2584.93 5690.79 4574.65 3584.42 5280.98 494.75 2880.82 184
MP-MVScopyleft83.19 1783.54 2182.14 1890.54 579.00 986.42 1883.59 5771.31 2981.26 9790.96 4174.57 3784.69 4878.41 2194.78 2782.74 147
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
PGM-MVS83.07 1983.25 2782.54 1589.57 1477.21 2082.04 4585.40 2367.96 4884.91 5890.88 4275.59 2786.57 1278.16 2294.71 3083.82 123
SteuartSystems-ACMMP83.07 1983.64 1981.35 2585.14 5971.00 5185.53 2184.78 3370.91 3285.64 4590.41 6175.55 2887.69 379.75 795.08 2185.36 91
Skip Steuart: Steuart Systems R&D Blog.
zzz-MVS83.01 2183.63 2081.13 3091.16 278.16 1282.72 4180.63 11172.08 2584.93 5690.79 4574.65 3584.42 5280.98 494.75 2880.82 184
APDe-MVS82.88 2284.14 1279.08 5184.80 6566.72 8086.54 1685.11 2772.00 2786.65 3391.75 2478.20 1687.04 877.93 2494.32 4183.47 131
GST-MVS82.79 2383.27 2681.34 2688.99 2573.29 4185.94 2085.13 2668.58 4684.14 6890.21 6973.37 4486.41 1379.09 1893.98 4984.30 116
ACMP69.50 882.64 2483.38 2380.40 3886.50 4369.44 6482.30 4286.08 1666.80 5486.70 3289.99 7381.64 585.95 2674.35 3896.11 585.81 86
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
MP-MVS-pluss82.54 2583.46 2279.76 4288.88 2968.44 7281.57 4886.33 1463.17 9685.38 5291.26 3576.33 2284.67 4983.30 194.96 2486.17 79
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
#test#82.40 2682.71 3381.48 2289.25 2075.69 2484.47 2984.27 4364.45 7884.47 6490.43 5776.79 1885.94 2776.01 3294.23 4482.82 144
ACMMP_Plus82.33 2783.28 2579.46 4789.28 1969.09 7083.62 3484.98 2864.77 7583.97 6991.02 3975.53 2985.93 2982.00 294.36 3883.35 137
SMA-MVS82.12 2882.68 3480.43 3788.90 2869.52 6285.12 2484.76 3463.53 9184.23 6791.47 3272.02 5387.16 679.74 994.36 3884.61 105
ACMM69.25 982.11 2983.31 2478.49 5988.17 3573.96 3483.11 3784.52 3966.40 5887.45 2389.16 8781.02 780.52 13374.27 3995.73 980.98 181
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ESAPD82.00 3083.02 2978.95 5485.36 5667.25 7982.91 3884.98 2873.52 1885.43 5190.03 7276.37 2186.97 1074.56 3694.02 4882.62 149
PMVScopyleft70.70 681.70 3183.15 2877.36 7190.35 682.82 382.15 4379.22 13574.08 1687.16 2791.97 1984.80 276.97 18664.98 11893.61 5172.28 265
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
UA-Net81.56 3282.28 3679.40 4888.91 2769.16 6884.67 2880.01 12775.34 1279.80 11794.91 269.79 6980.25 13772.63 4694.46 3688.78 52
CPTT-MVS81.51 3381.76 3880.76 3589.20 2378.75 1086.48 1782.03 7868.80 4280.92 10588.52 10072.00 5482.39 8074.80 3393.04 5781.14 177
ACMH+66.64 1081.20 3482.48 3577.35 7281.16 11062.39 11080.51 5487.80 573.02 2187.57 2191.08 3880.28 882.44 7964.82 11996.10 687.21 72
APD-MVScopyleft81.13 3581.73 3979.36 4984.47 7170.53 5683.85 3383.70 5469.43 4183.67 7288.96 9575.89 2686.41 1372.62 4792.95 5881.14 177
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
3Dnovator+73.19 281.08 3680.48 4682.87 681.41 10772.03 4384.38 3086.23 1577.28 1180.65 10890.18 7059.80 15687.58 473.06 4491.34 8189.01 43
DeepC-MVS72.44 481.00 3780.83 4581.50 2186.70 4270.03 6182.06 4487.00 1059.89 12480.91 10690.53 5372.19 4988.56 173.67 4294.52 3485.92 85
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
OPM-MVS80.99 3881.63 4179.07 5286.86 4069.39 6579.41 6984.00 5265.64 6285.54 4989.28 8176.32 2383.47 6574.03 4093.57 5284.35 115
LS3D80.99 3880.85 4481.41 2478.37 13871.37 4787.45 685.87 1977.48 981.98 8589.95 7469.14 7285.26 3766.15 10891.24 8387.61 67
XVG-ACMP-BASELINE80.54 4081.06 4378.98 5387.01 3772.91 4280.23 6085.56 2066.56 5785.64 4589.57 7869.12 7380.55 13272.51 4893.37 5383.48 130
PEN-MVS80.46 4182.91 3073.11 13089.83 939.02 28077.06 9682.61 7180.04 390.60 892.85 974.93 3485.21 3963.15 12995.15 1995.09 2
PS-CasMVS80.41 4282.86 3273.07 13189.93 739.21 27777.15 9481.28 9479.74 490.87 692.73 1175.03 3384.93 4363.83 12695.19 1795.07 3
DTE-MVSNet80.35 4382.89 3172.74 14289.84 837.34 29577.16 9381.81 8280.45 290.92 592.95 774.57 3786.12 2563.65 12794.68 3194.76 6
SD-MVS80.28 4481.55 4276.47 7683.57 8067.83 7683.39 3685.35 2564.42 8186.14 4087.07 11874.02 4080.97 11977.70 2692.32 6880.62 189
WR-MVS_H80.22 4582.17 3774.39 9989.46 1542.69 25378.24 8182.24 7578.21 889.57 1192.10 1868.05 8385.59 3266.04 11095.62 1194.88 5
HPM-MVS++copyleft79.89 4679.80 5180.18 4089.02 2478.44 1183.49 3580.18 12464.71 7778.11 13888.39 10365.46 10683.14 7077.64 2791.20 8478.94 212
HSP-MVS79.69 4779.17 5681.27 2989.70 1277.46 1987.16 880.58 11464.94 7481.05 10288.38 10457.10 20187.10 779.75 783.87 20379.24 209
XVG-OURS-SEG-HR79.62 4879.99 4978.49 5986.46 4474.79 3077.15 9485.39 2466.73 5580.39 11288.85 9774.43 3978.33 17374.73 3585.79 16982.35 155
XVG-OURS79.51 4979.82 5078.58 5886.11 4674.96 2976.33 10684.95 3066.89 5182.75 8088.99 9366.82 9378.37 17174.80 3390.76 9882.40 154
CP-MVSNet79.48 5081.65 4072.98 13589.66 1339.06 27976.76 9880.46 11678.91 690.32 991.70 2568.49 7884.89 4463.40 12895.12 2095.01 4
OMC-MVS79.41 5178.79 5881.28 2880.62 11270.71 5580.91 5184.76 3462.54 10181.77 8786.65 13571.46 5783.53 6467.95 9192.44 6589.60 34
v7n79.37 5280.41 4776.28 8078.67 13755.81 14879.22 7082.51 7470.72 3387.54 2292.44 1468.00 8581.34 10372.84 4591.72 7191.69 12
TSAR-MVS + MP.79.05 5378.81 5779.74 4388.94 2667.52 7786.61 1581.38 9351.71 21777.15 14591.42 3465.49 10587.20 579.44 1387.17 15684.51 110
v5278.96 5479.79 5276.46 7773.03 23454.90 15178.48 7683.48 5864.43 7991.19 491.54 2872.08 5081.11 11276.45 3087.47 14593.38 7
V478.96 5479.79 5276.46 7773.02 23554.90 15178.48 7683.47 5964.43 7991.20 391.54 2872.08 5081.11 11276.45 3087.46 14793.38 7
mvs_tets78.93 5678.67 6079.72 4484.81 6473.93 3580.65 5376.50 17651.98 21587.40 2491.86 2176.09 2578.53 16268.58 7990.20 10586.69 77
test_djsdf78.88 5778.27 6380.70 3681.42 10671.24 4983.98 3175.72 18252.27 21087.37 2592.25 1668.04 8480.56 13072.28 5291.15 8590.32 32
HQP_MVS78.77 5878.78 5978.72 5685.18 5765.18 9182.74 3985.49 2165.45 6478.23 13689.11 8960.83 14786.15 2271.09 5690.94 9084.82 99
anonymousdsp78.60 5977.80 6781.00 3278.01 14374.34 3380.09 6176.12 17850.51 23589.19 1290.88 4271.45 5877.78 18173.38 4390.60 10090.90 26
OurMVSNet-221017-078.57 6078.53 6278.67 5780.48 11364.16 9880.24 5982.06 7761.89 10588.77 1493.32 457.15 19982.60 7870.08 6892.80 5989.25 38
jajsoiax78.51 6178.16 6479.59 4684.65 6773.83 3780.42 5676.12 17851.33 22287.19 2691.51 3173.79 4378.44 16668.27 8290.13 10986.49 78
CNVR-MVS78.49 6278.59 6178.16 6385.86 5167.40 7878.12 8481.50 8663.92 8577.51 14386.56 13968.43 8084.82 4673.83 4191.61 7482.26 158
DeepPCF-MVS71.07 578.48 6377.14 7382.52 1684.39 7577.04 2176.35 10484.05 5056.66 15780.27 11385.31 16268.56 7787.03 967.39 9691.26 8283.50 129
DP-MVS78.44 6479.29 5575.90 8581.86 10265.33 8979.05 7184.63 3874.83 1480.41 11186.27 14671.68 5583.45 6662.45 13392.40 6678.92 213
NCCC78.25 6578.04 6578.89 5585.61 5369.45 6379.80 6580.99 10765.77 6175.55 16986.25 14867.42 8885.42 3370.10 6790.88 9681.81 167
test_040278.17 6679.48 5474.24 10183.50 8159.15 13472.52 15174.60 19275.34 1288.69 1591.81 2275.06 3282.37 8165.10 11688.68 12881.20 174
AllTest77.66 6777.43 6978.35 6179.19 12870.81 5278.60 7488.64 265.37 6780.09 11588.17 10770.33 6478.43 16755.60 17790.90 9485.81 86
PS-MVSNAJss77.54 6877.35 7078.13 6584.88 6266.37 8378.55 7579.59 13253.48 20186.29 3892.43 1562.39 12780.25 13767.90 9290.61 9987.77 65
ACMH63.62 1477.50 6980.11 4869.68 18179.61 11956.28 14678.81 7283.62 5663.41 9487.14 2890.23 6876.11 2473.32 22167.58 9394.44 3779.44 207
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
CDPH-MVS77.33 7077.06 7478.14 6484.21 7663.98 10076.07 11183.45 6054.20 19077.68 14287.18 11569.98 6785.37 3468.01 8792.72 6385.08 96
DeepC-MVS_fast69.89 777.17 7176.33 8379.70 4583.90 7967.94 7480.06 6383.75 5356.73 15674.88 17785.32 16165.54 10487.79 265.61 11491.14 8683.35 137
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
v74876.93 7277.95 6673.87 10673.94 20752.44 17075.90 11479.98 12865.34 6986.97 3091.77 2367.40 8978.40 16970.23 6590.01 11090.76 30
X-MVStestdata76.81 7374.79 9982.85 789.43 1677.61 1486.80 1384.66 3672.71 2282.87 789.95 36573.86 4186.31 1678.84 1994.03 4684.64 102
test_prior376.71 7477.19 7175.27 9282.15 9859.85 12775.57 11884.33 4158.92 13176.53 15986.78 12667.83 8683.39 6769.81 7092.76 6182.58 150
train_agg76.38 7576.55 7875.86 8685.47 5469.32 6676.42 10278.69 14654.00 19476.97 14686.74 12966.60 9481.10 11472.50 4991.56 7577.15 229
agg_prior376.32 7676.33 8376.28 8085.86 5170.13 6076.50 10078.26 15653.41 20375.78 16586.49 14166.58 9681.57 9272.50 4991.56 7577.15 229
v1376.23 7777.02 7573.86 10874.61 19248.80 19076.91 9781.10 10162.66 9987.02 2991.01 4059.76 15781.41 9871.29 5588.78 12791.38 13
TranMVSNet+NR-MVSNet76.13 7877.66 6871.56 16184.61 6942.57 25470.98 18578.29 15568.67 4583.04 7689.26 8272.99 4780.75 12955.58 18095.47 1291.35 14
v1276.03 7976.79 7673.76 11074.45 19448.60 19676.59 9981.11 9862.22 10486.79 3190.74 4859.51 15881.40 10071.01 5888.67 12991.29 15
agg_prior175.89 8076.41 8174.31 10084.44 7366.02 8576.12 11078.62 14954.40 18876.95 14886.85 12366.44 9880.34 13572.45 5191.42 7976.57 234
V975.82 8176.53 7973.66 11174.28 19848.37 19776.26 10781.10 10161.73 10786.59 3490.43 5759.16 16481.42 9770.71 6188.56 13091.21 18
SixPastTwentyTwo75.77 8276.34 8274.06 10481.69 10454.84 15376.47 10175.49 18464.10 8487.73 2092.24 1750.45 23081.30 10567.41 9591.46 7886.04 82
v1175.76 8376.51 8073.48 11874.28 19847.81 20976.16 10981.28 9461.56 10886.39 3690.38 6359.32 16281.41 9870.85 5988.41 13291.23 16
RPSCF75.76 8374.37 10579.93 4174.81 18377.53 1677.53 8879.30 13459.44 12678.88 12689.80 7671.26 6073.09 22357.45 16080.89 24689.17 41
v1075.69 8576.20 8674.16 10274.44 19648.69 19275.84 11682.93 6759.02 13085.92 4389.17 8658.56 17382.74 7670.73 6089.14 12391.05 20
V1475.58 8676.26 8573.55 11674.10 20648.13 20275.91 11381.07 10461.19 11186.34 3790.11 7158.80 16881.40 10070.40 6388.43 13191.12 19
Anonymous2023121175.54 8777.19 7170.59 16877.67 15045.70 23974.73 13580.19 12368.80 4282.95 7792.91 866.26 9976.76 19158.41 15692.77 6089.30 37
Effi-MVS+-dtu75.43 8872.28 14784.91 277.05 15483.58 278.47 7877.70 16457.68 14074.89 17678.13 25164.80 11184.26 5656.46 17085.32 18486.88 74
v1575.37 8976.01 8773.44 12073.91 21047.87 20875.55 12081.04 10560.76 11686.11 4189.76 7758.53 17481.40 10070.11 6688.32 13391.04 22
wuykxyi23d75.33 9076.75 7771.04 16478.83 13585.01 171.78 16761.00 26953.47 20296.33 193.38 373.07 4568.04 27565.65 11397.28 260.07 336
Regformer-275.32 9174.47 10377.88 6674.22 20166.65 8172.77 14877.54 16668.47 4780.44 11072.08 30470.60 6380.97 11970.08 6884.02 20186.01 83
F-COLMAP75.29 9273.99 11079.18 5081.73 10371.90 4481.86 4782.98 6559.86 12572.27 21184.00 18164.56 11483.07 7251.48 20287.19 15582.56 152
HQP-MVS75.24 9375.01 9875.94 8482.37 9358.80 13677.32 9084.12 4859.08 12771.58 21685.96 15758.09 18185.30 3667.38 9789.16 12183.73 126
TAPA-MVS65.27 1275.16 9474.29 10777.77 6874.86 18268.08 7377.89 8584.04 5155.15 17276.19 16483.39 18666.91 9180.11 14260.04 14590.14 10885.13 94
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
IS-MVSNet75.10 9575.42 9574.15 10379.23 12648.05 20579.43 6778.04 16170.09 3879.17 12488.02 11153.04 21683.60 6258.05 15793.76 5090.79 28
v875.07 9675.64 9173.35 12273.42 21647.46 21875.20 12581.45 8960.05 12285.64 4589.26 8258.08 18381.80 9069.71 7287.97 13990.79 28
v1775.03 9775.59 9273.36 12173.56 21247.66 21375.48 12181.45 8960.58 11885.55 4889.02 9158.36 17681.47 9469.69 7386.59 16290.96 23
UniMVSNet (Re)75.00 9875.48 9473.56 11583.14 8547.92 20770.41 19181.04 10563.67 8879.54 11986.37 14562.83 12181.82 8957.10 16495.25 1690.94 25
PHI-MVS74.92 9974.36 10676.61 7376.40 16362.32 11180.38 5783.15 6354.16 19273.23 19880.75 21962.19 13083.86 5868.02 8690.92 9383.65 127
DU-MVS74.91 10075.57 9372.93 13783.50 8145.79 23769.47 20180.14 12565.22 7081.74 8987.08 11661.82 13381.07 11656.21 17394.98 2291.93 10
UniMVSNet_NR-MVSNet74.90 10175.65 9072.64 14583.04 8645.79 23769.26 20378.81 14466.66 5681.74 8986.88 12263.26 11981.07 11656.21 17394.98 2291.05 20
v1674.89 10275.41 9673.35 12273.54 21347.62 21475.47 12281.45 8960.58 11885.46 5088.97 9458.27 17781.47 9469.66 7485.25 18590.95 24
nrg03074.87 10375.99 8871.52 16274.90 18149.88 18574.10 14182.58 7354.55 18783.50 7489.21 8571.51 5675.74 20061.24 13892.34 6788.94 47
Vis-MVSNetpermissive74.85 10474.56 10175.72 8781.63 10564.64 9576.35 10479.06 14062.85 9873.33 19688.41 10262.54 12579.59 14863.94 12582.92 21282.94 141
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
Regformer-474.64 10573.67 11477.55 6974.74 18564.49 9772.91 14575.42 18767.45 4980.24 11472.07 30768.98 7480.19 14170.29 6480.91 24487.98 63
v1874.60 10675.06 9773.22 12773.29 22247.36 22275.02 12781.47 8860.01 12385.13 5488.44 10157.93 19081.47 9469.26 7685.02 18990.84 27
MVS_030474.55 10773.47 11877.80 6777.41 15363.88 10175.75 11783.67 5563.55 9066.12 26982.16 20660.20 15186.15 2265.37 11586.98 15883.38 134
MSLP-MVS++74.48 10875.78 8970.59 16884.66 6662.40 10978.65 7384.24 4560.55 12077.71 14181.98 20863.12 12077.64 18262.95 13088.14 13571.73 270
Regformer-174.28 10973.63 11676.21 8374.22 20164.12 9972.77 14875.46 18666.86 5379.27 12272.08 30469.29 7178.74 15868.73 7884.02 20185.77 89
AdaColmapbinary74.22 11074.56 10173.20 12881.95 10060.97 11979.43 6780.90 10865.57 6372.54 20881.76 21270.98 6285.26 3747.88 23290.00 11173.37 253
CSCG74.12 11174.39 10473.33 12479.35 12361.66 11677.45 8981.98 7962.47 10379.06 12580.19 22661.83 13278.79 15759.83 14787.35 15079.54 206
PAPM_NR73.91 11274.16 10873.16 12981.90 10153.50 16381.28 4981.40 9266.17 5973.30 19783.31 19059.96 15283.10 7158.45 15581.66 23182.87 142
EPP-MVSNet73.86 11373.38 12175.31 9178.19 14053.35 16680.45 5577.32 17065.11 7276.47 16186.80 12449.47 23283.77 5953.89 19292.72 6388.81 51
mvs-test173.81 11470.69 16883.18 377.05 15481.39 475.39 12377.70 16457.68 14071.19 22574.72 28364.80 11183.66 6156.46 17081.19 24284.50 111
K. test v373.67 11573.61 11773.87 10679.78 11755.62 14974.69 13762.04 26666.16 6084.76 5993.23 549.47 23280.97 11965.66 11286.67 16185.02 97
NR-MVSNet73.62 11674.05 10972.33 15483.50 8143.71 24765.65 25077.32 17064.32 8275.59 16887.08 11662.45 12681.34 10354.90 18395.63 1091.93 10
v773.59 11773.69 11373.28 12674.42 19748.68 19372.74 15081.98 7954.76 18282.07 8485.05 16758.53 17482.22 8667.99 8885.66 17388.95 46
DP-MVS Recon73.57 11872.69 14176.23 8282.85 8963.39 10474.32 13982.96 6657.75 13970.35 23581.98 20864.34 11584.41 5449.69 21689.95 11380.89 182
CNLPA73.44 11973.03 13374.66 9478.27 13975.29 2775.99 11278.49 15165.39 6675.67 16783.22 19561.23 14266.77 28753.70 19485.33 18381.92 166
MCST-MVS73.42 12073.34 12373.63 11481.28 10859.17 13374.80 13383.13 6445.50 27072.84 20183.78 18465.15 10880.99 11864.54 12089.09 12480.73 187
v119273.40 12173.42 11973.32 12574.65 19148.67 19472.21 15481.73 8352.76 20881.85 8684.56 17457.12 20082.24 8568.58 7987.33 15189.06 42
114514_t73.40 12173.33 12473.64 11384.15 7857.11 14378.20 8280.02 12643.76 28472.55 20786.07 15564.00 11683.35 6960.14 14491.03 8980.45 192
FC-MVSNet-test73.32 12374.78 10068.93 19279.21 12736.57 29771.82 16679.54 13357.63 14482.57 8190.38 6359.38 16178.99 15257.91 15894.56 3391.23 16
v114473.29 12473.39 12073.01 13374.12 20548.11 20372.01 15981.08 10353.83 19881.77 8784.68 17258.07 18481.91 8868.10 8386.86 15988.99 45
TSAR-MVS + GP.73.08 12571.60 15877.54 7078.99 13470.73 5474.96 12869.38 23260.73 11774.39 18578.44 24857.72 19382.78 7560.16 14389.60 11679.11 211
v124073.06 12673.14 12672.84 13974.74 18547.27 22471.88 16581.11 9851.80 21682.28 8384.21 17856.22 20782.34 8268.82 7787.17 15688.91 48
IterMVS-LS73.01 12773.12 12872.66 14473.79 21149.90 18271.63 16978.44 15258.22 13480.51 10986.63 13658.15 18079.62 14662.51 13188.20 13488.48 60
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CANet73.00 12871.84 15176.48 7575.82 17161.28 11774.81 13180.37 11863.17 9662.43 28980.50 22361.10 14485.16 4264.00 12384.34 19783.01 140
v14419272.99 12973.06 13272.77 14074.58 19347.48 21671.90 16480.44 11751.57 21981.46 9684.11 18058.04 18582.12 8767.98 8987.47 14588.70 53
MVS_111021_HR72.98 13072.97 13572.99 13480.82 11165.47 8868.81 20872.77 20357.67 14275.76 16682.38 20371.01 6177.17 18461.38 13786.15 16576.32 235
v192192072.96 13172.98 13472.89 13874.67 18847.58 21571.92 16380.69 11051.70 21881.69 9183.89 18256.58 20582.25 8468.34 8187.36 14988.82 50
v1neww72.93 13273.07 13072.48 14873.41 21847.46 21872.17 15580.26 12055.63 16481.63 9385.07 16557.97 18781.28 10666.55 10684.98 19188.70 53
v7new72.93 13273.07 13072.48 14873.41 21847.46 21872.17 15580.26 12055.63 16481.63 9385.07 16557.97 18781.28 10666.55 10684.98 19188.70 53
v672.93 13273.08 12972.48 14873.42 21647.47 21772.17 15580.25 12255.63 16481.65 9285.04 16857.95 18981.28 10666.56 10585.01 19088.70 53
casdiffmvs172.89 13572.85 13673.04 13277.69 14953.36 16580.89 5280.76 10944.66 27972.86 20088.56 9966.45 9780.91 12461.58 13582.17 21884.84 98
CLD-MVS72.88 13672.36 14574.43 9877.03 15654.30 15868.77 21183.43 6152.12 21276.79 15474.44 28769.54 7083.91 5755.88 17693.25 5685.09 95
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
Regformer-372.86 13772.28 14774.62 9574.74 18560.18 12472.91 14571.76 21164.74 7678.42 13272.07 30767.00 9076.28 19567.97 9080.91 24487.39 69
EI-MVSNet-Vis-set72.78 13871.87 15075.54 8974.77 18459.02 13572.24 15371.56 21463.92 8578.59 12871.59 31466.22 10078.60 16067.58 9380.32 25289.00 44
PCF-MVS63.80 1372.70 13971.69 15475.72 8778.10 14160.01 12673.04 14481.50 8645.34 27379.66 11884.35 17765.15 10882.65 7748.70 22489.38 12084.50 111
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
EI-MVSNet-UG-set72.63 14071.68 15575.47 9074.67 18858.64 13972.02 15871.50 21563.53 9178.58 13071.39 31765.98 10178.53 16267.30 9980.18 25389.23 39
divwei89l23v2f11272.60 14172.73 13872.19 15573.10 22947.00 22871.48 17079.11 13755.01 17381.23 9984.95 16957.45 19680.89 12666.58 10385.67 17188.68 57
v172.60 14172.73 13872.19 15573.12 22847.01 22771.48 17079.10 13955.01 17381.24 9884.92 17157.46 19580.90 12566.59 10285.67 17188.68 57
v114172.59 14372.73 13872.19 15573.10 22947.00 22871.48 17079.11 13755.01 17381.23 9984.94 17057.45 19680.89 12666.58 10385.65 17488.68 57
Anonymous2024052972.56 14473.79 11268.86 19676.89 16045.21 24268.80 21077.25 17267.16 5076.89 15190.44 5665.95 10274.19 21650.75 20890.00 11187.18 73
FIs72.56 14473.80 11168.84 19778.74 13637.74 29171.02 18479.83 12956.12 15980.88 10789.45 7958.18 17878.28 17456.63 16693.36 5490.51 31
v2v48272.55 14672.58 14272.43 15172.92 24046.72 23271.41 17579.13 13655.27 16881.17 10185.25 16355.41 20981.13 11167.25 10085.46 17989.43 36
canonicalmvs72.29 14773.38 12169.04 18974.23 20047.37 22173.93 14283.18 6254.36 18976.61 15681.64 21472.03 5275.34 20357.12 16387.28 15384.40 113
casdiffmvs72.24 14871.83 15273.47 11975.01 17854.46 15779.73 6682.60 7245.66 26770.90 22887.73 11363.41 11882.32 8365.09 11776.36 28183.64 128
Effi-MVS+72.10 14972.28 14771.58 16074.21 20450.33 17874.72 13682.73 6962.62 10070.77 22976.83 25869.96 6880.97 11960.20 14278.43 27183.45 133
MVS_111021_LR72.10 14971.82 15372.95 13679.53 12173.90 3670.45 19066.64 24256.87 15376.81 15381.76 21268.78 7571.76 24561.81 13483.74 20573.18 255
testing_272.01 15172.36 14570.95 16570.79 25248.70 19172.81 14778.09 16048.79 24684.46 6689.15 8857.90 19178.55 16161.55 13687.74 14185.61 90
pmmvs671.82 15273.66 11566.31 22175.94 17042.01 25666.99 23272.53 20663.45 9376.43 16292.78 1072.95 4869.69 25851.41 20390.46 10287.22 71
PLCcopyleft62.01 1671.79 15370.28 17076.33 7980.31 11568.63 7178.18 8381.24 9654.57 18667.09 26680.63 22159.44 15981.74 9146.91 23984.17 19878.63 214
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
VDDNet71.60 15473.13 12767.02 21486.29 4541.11 26269.97 19466.50 24368.72 4474.74 17991.70 2559.90 15375.81 19848.58 22691.72 7184.15 118
3Dnovator65.95 1171.50 15571.22 16372.34 15373.16 22463.09 10778.37 7978.32 15357.67 14272.22 21384.61 17354.77 21078.47 16460.82 14181.07 24375.45 240
WR-MVS71.20 15672.48 14367.36 21184.98 6135.70 30664.43 26368.66 23565.05 7381.49 9586.43 14357.57 19476.48 19350.36 21293.32 5589.90 33
V4271.06 15770.83 16671.72 15967.25 29147.14 22565.94 24680.35 11951.35 22183.40 7583.23 19359.25 16378.80 15665.91 11180.81 24889.23 39
FMVSNet171.06 15772.48 14366.81 21577.65 15140.68 26671.96 16073.03 19861.14 11279.45 12190.36 6560.44 14975.20 20550.20 21388.05 13684.54 107
API-MVS70.97 15971.51 16069.37 18275.20 17655.94 14780.99 5076.84 17362.48 10271.24 22377.51 25461.51 13780.96 12352.04 19885.76 17071.22 274
diffmvs170.85 16071.63 15668.50 20164.78 30946.14 23671.03 18377.76 16357.00 15272.44 20987.61 11461.32 13874.11 21769.58 7583.16 21185.26 92
VDD-MVS70.81 16171.44 16168.91 19479.07 13346.51 23367.82 22270.83 22661.23 11074.07 18988.69 9859.86 15475.62 20151.11 20590.28 10484.61 105
EG-PatchMatch MVS70.70 16270.88 16570.16 17582.64 9258.80 13671.48 17073.64 19654.98 17676.55 15781.77 21161.10 14478.94 15354.87 18480.84 24772.74 260
Baseline_NR-MVSNet70.62 16373.19 12562.92 24776.97 15734.44 31668.84 20670.88 22560.25 12179.50 12090.53 5361.82 13369.11 26054.67 18695.27 1585.22 93
alignmvs70.54 16471.00 16469.15 18873.50 21448.04 20669.85 19779.62 13053.94 19776.54 15882.00 20759.00 16674.68 21157.32 16187.21 15484.72 101
MG-MVS70.47 16571.34 16267.85 20679.26 12540.42 27174.67 13875.15 19058.41 13368.74 24988.14 11056.08 20883.69 6059.90 14681.71 23079.43 208
UGNet70.20 16669.05 17973.65 11276.24 16563.64 10275.87 11572.53 20661.48 10960.93 30086.14 15252.37 22077.12 18550.67 20985.21 18680.17 201
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
PVSNet_Blended_VisFu70.04 16768.88 18473.53 11782.71 9163.62 10374.81 13181.95 8148.53 24867.16 26579.18 24251.42 22778.38 17054.39 19079.72 26178.60 215
Fast-Effi-MVS+-dtu70.00 16868.74 18973.77 10973.47 21564.53 9671.36 17678.14 15955.81 16268.84 24874.71 28465.36 10775.75 19952.00 19979.00 26581.03 179
MVSFormer69.93 16969.03 18172.63 14674.93 17959.19 13183.98 3175.72 18252.27 21063.53 28576.74 25943.19 25980.56 13072.28 5278.67 26978.14 221
MVS_Test69.84 17070.71 16767.24 21267.49 29043.25 24969.87 19681.22 9752.69 20971.57 21986.68 13262.09 13174.51 21366.05 10978.74 26783.96 121
TransMVSNet (Re)69.62 17171.63 15663.57 24076.51 16235.93 30465.75 24971.29 21961.05 11375.02 17489.90 7565.88 10370.41 25649.79 21589.48 11884.38 114
EI-MVSNet69.61 17269.01 18271.41 16373.94 20749.90 18271.31 17871.32 21758.22 13475.40 17270.44 31858.16 17975.85 19662.51 13179.81 25888.48 60
diffmvs69.55 17370.18 17167.66 20963.63 31445.24 24171.26 18076.21 17755.79 16367.89 25286.41 14461.00 14673.76 22068.03 8581.40 23483.98 120
Gipumacopyleft69.55 17372.83 13759.70 27863.63 31453.97 16080.08 6275.93 18064.24 8373.49 19488.93 9657.89 19262.46 30259.75 14891.55 7762.67 330
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
tttt051769.46 17567.79 19874.46 9675.34 17452.72 16875.05 12663.27 25854.69 18378.87 12784.37 17626.63 34981.15 11063.95 12487.93 14089.51 35
BH-untuned69.39 17669.46 17469.18 18777.96 14456.88 14468.47 21777.53 16756.77 15577.79 14079.63 23460.30 15080.20 14046.04 24480.65 24970.47 280
v14869.38 17769.39 17569.36 18369.14 27044.56 24468.83 20772.70 20454.79 18078.59 12884.12 17954.69 21176.74 19259.40 15082.20 21786.79 75
112169.23 17868.26 19372.12 15888.36 3371.40 4668.59 21262.06 26443.80 28374.75 17886.18 14952.92 21776.85 18954.47 18783.27 20968.12 302
PAPR69.20 17968.66 19070.82 16675.15 17747.77 21075.31 12481.11 9849.62 24266.33 26879.27 23961.53 13682.96 7348.12 23081.50 23381.74 168
QAPM69.18 18069.26 17768.94 19171.61 25052.58 16980.37 5878.79 14549.63 24173.51 19385.14 16453.66 21579.12 15055.11 18275.54 28775.11 244
LCM-MVSNet-Re69.10 18171.57 15961.70 26070.37 26034.30 31761.45 29079.62 13056.81 15489.59 1088.16 10968.44 7972.94 22442.30 27187.33 15177.85 226
EPNet69.10 18167.32 20174.46 9668.33 28161.27 11877.56 8763.57 25660.95 11456.62 32182.75 19751.53 22681.24 10954.36 19190.20 10580.88 183
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
Test469.04 18368.95 18369.32 18669.52 26648.10 20470.69 18978.25 15745.90 26680.99 10382.24 20451.91 22178.11 17958.46 15482.58 21581.74 168
DI_MVS_plusplus_test69.01 18469.04 18068.93 19269.54 26546.74 23170.14 19275.49 18446.64 26278.30 13483.18 19658.80 16878.86 15457.14 16282.15 21981.18 175
test_normal68.88 18568.88 18468.88 19569.43 26847.03 22669.85 19774.83 19146.06 26578.30 13483.29 19158.76 17278.23 17557.51 15981.90 22481.36 173
DELS-MVS68.83 18668.31 19170.38 17070.55 25948.31 19863.78 26882.13 7654.00 19468.96 24575.17 27958.95 16780.06 14358.55 15382.74 21382.76 146
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
Fast-Effi-MVS+68.81 18768.30 19270.35 17174.66 19048.61 19566.06 24578.32 15350.62 23471.48 22275.54 27368.75 7679.59 14850.55 21178.73 26882.86 143
OpenMVScopyleft62.51 1568.76 18868.75 18868.78 19870.56 25853.91 16178.29 8077.35 16948.85 24570.22 23783.52 18552.65 21976.93 18755.31 18181.99 22275.49 239
VPA-MVSNet68.71 18970.37 16963.72 23976.13 16738.06 28964.10 26571.48 21656.60 15874.10 18888.31 10564.78 11369.72 25747.69 23490.15 10783.37 136
BH-RMVSNet68.69 19068.20 19570.14 17676.40 16353.90 16264.62 26073.48 19758.01 13673.91 19181.78 21059.09 16578.22 17648.59 22577.96 27678.31 218
pm-mvs168.40 19169.85 17364.04 23673.10 22939.94 27364.61 26170.50 22755.52 16773.97 19089.33 8063.91 11768.38 27249.68 21788.02 13783.81 124
GBi-Net68.30 19268.79 18666.81 21573.14 22540.68 26671.96 16073.03 19854.81 17774.72 18090.36 6548.63 23775.20 20547.12 23685.37 18084.54 107
test168.30 19268.79 18666.81 21573.14 22540.68 26671.96 16073.03 19854.81 17774.72 18090.36 6548.63 23775.20 20547.12 23685.37 18084.54 107
TinyColmap67.98 19469.28 17664.08 23567.98 28546.82 23070.04 19375.26 18853.05 20577.36 14486.79 12559.39 16072.59 23545.64 24688.01 13872.83 258
xiu_mvs_v1_base_debu67.87 19567.07 20370.26 17279.13 13061.90 11367.34 22771.25 22047.98 25267.70 25474.19 29261.31 13972.62 23256.51 16778.26 27376.27 236
xiu_mvs_v1_base67.87 19567.07 20370.26 17279.13 13061.90 11367.34 22771.25 22047.98 25267.70 25474.19 29261.31 13972.62 23256.51 16778.26 27376.27 236
xiu_mvs_v1_base_debi67.87 19567.07 20370.26 17279.13 13061.90 11367.34 22771.25 22047.98 25267.70 25474.19 29261.31 13972.62 23256.51 16778.26 27376.27 236
MAR-MVS67.72 19866.16 20872.40 15274.45 19464.99 9474.87 12977.50 16848.67 24765.78 27368.58 33457.01 20377.79 18046.68 24281.92 22374.42 248
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
LF4IMVS67.50 19967.31 20268.08 20458.86 33961.93 11271.43 17475.90 18144.67 27872.42 21080.20 22557.16 19870.44 25458.99 15286.12 16671.88 268
FMVSNet267.48 20068.21 19465.29 22673.14 22538.94 28168.81 20871.21 22354.81 17776.73 15586.48 14248.63 23774.60 21247.98 23186.11 16782.35 155
MSDG67.47 20167.48 20067.46 21070.70 25554.69 15566.90 23478.17 15860.88 11570.41 23474.76 28161.22 14373.18 22247.38 23576.87 27974.49 247
ANet_high67.08 20269.94 17258.51 28557.55 34727.09 35058.43 30976.80 17463.56 8982.40 8291.93 2059.82 15564.98 29450.10 21488.86 12683.46 132
LFMVS67.06 20367.89 19764.56 23178.02 14238.25 28670.81 18859.60 27465.18 7171.06 22686.56 13943.85 25575.22 20446.35 24389.63 11580.21 196
thisisatest053067.05 20465.16 21072.73 14373.10 22950.55 17771.26 18063.91 25450.22 23774.46 18480.75 21926.81 34880.25 13759.43 14986.50 16387.37 70
MIMVSNet166.57 20569.23 17858.59 28481.26 10937.73 29264.06 26657.62 28257.02 15178.40 13390.75 4762.65 12258.10 31541.77 27789.58 11779.95 202
tfpnnormal66.48 20667.93 19662.16 25873.40 22036.65 29663.45 27064.99 25155.97 16072.82 20287.80 11257.06 20269.10 26148.31 22987.54 14380.72 188
Anonymous20240521166.02 20766.89 20663.43 24374.22 20138.14 28759.00 30566.13 24463.33 9569.76 24085.95 15851.88 22270.50 25344.23 25287.52 14481.64 170
VPNet65.58 20867.56 19959.65 27979.72 11830.17 34360.27 29962.14 26154.19 19171.24 22386.63 13658.80 16867.62 27844.17 25390.87 9781.18 175
PVSNet_BlendedMVS65.38 20964.30 21668.61 19969.81 26249.36 18665.60 25278.96 14145.50 27059.98 30578.61 24751.82 22378.20 17744.30 25084.11 19978.27 219
TAMVS65.31 21063.75 22069.97 18082.23 9759.76 12966.78 23563.37 25745.20 27469.79 23979.37 23847.42 24372.17 23734.48 31785.15 18877.99 225
0601test65.11 21165.09 21465.18 22770.59 25640.86 26463.22 27572.79 20157.91 13768.88 24679.07 24542.85 26274.89 20945.50 24784.97 19379.81 203
Anonymous2024052165.11 21165.09 21465.18 22770.59 25640.86 26463.22 27572.79 20157.91 13768.88 24679.07 24542.85 26274.89 20945.50 24784.97 19379.81 203
mvs_anonymous65.08 21365.49 20963.83 23863.79 31237.60 29366.52 23869.82 23143.44 28873.46 19586.08 15458.79 17171.75 24651.90 20075.63 28682.15 159
FMVSNet365.00 21465.16 21064.52 23269.47 26737.56 29466.63 23670.38 22851.55 22074.72 18083.27 19237.89 29074.44 21447.12 23685.37 18081.57 171
BH-w/o64.81 21564.29 21766.36 22076.08 16954.71 15465.61 25175.23 18950.10 23971.05 22771.86 31354.33 21379.02 15138.20 29776.14 28365.36 318
cascas64.59 21662.77 23470.05 17875.27 17550.02 18161.79 28771.61 21242.46 29263.68 28368.89 33149.33 23480.35 13447.82 23384.05 20079.78 205
TR-MVS64.59 21663.54 22367.73 20875.75 17350.83 17663.39 27170.29 22949.33 24371.55 22074.55 28550.94 22878.46 16540.43 28475.69 28573.89 251
PM-MVS64.49 21863.61 22267.14 21376.68 16175.15 2868.49 21642.85 34951.17 22577.85 13980.51 22245.76 24466.31 29052.83 19776.35 28259.96 338
jason64.47 21962.84 23369.34 18576.91 15959.20 13067.15 23165.67 24535.29 32665.16 27576.74 25944.67 25070.68 25054.74 18579.28 26478.14 221
jason: jason.
xiu_mvs_v2_base64.43 22063.96 21865.85 22577.72 14851.32 17463.63 26972.31 20945.06 27761.70 29069.66 32462.56 12373.93 21949.06 22173.91 29772.31 264
pmmvs-eth3d64.41 22163.27 22567.82 20775.81 17260.18 12469.49 20062.05 26538.81 30974.13 18782.23 20543.76 25668.65 27042.53 27080.63 25174.63 246
CDS-MVSNet64.33 22262.66 23569.35 18480.44 11458.28 14065.26 25665.66 24644.36 28067.30 26475.54 27343.27 25871.77 24437.68 30084.44 19678.01 224
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
PS-MVSNAJ64.27 22363.73 22165.90 22477.82 14651.42 17363.33 27272.33 20845.09 27661.60 29168.04 33562.39 12773.95 21849.07 22073.87 29872.34 263
ab-mvs64.11 22465.13 21361.05 26771.99 24838.03 29067.59 22368.79 23449.08 24465.32 27486.26 14758.02 18666.85 28539.33 28679.79 26078.27 219
CANet_DTU64.04 22563.83 21964.66 23068.39 27842.97 25173.45 14374.50 19352.05 21454.78 32975.44 27843.99 25470.42 25553.49 19678.41 27280.59 190
VNet64.01 22665.15 21260.57 27173.28 22335.61 30757.60 31267.08 24054.61 18566.76 26783.37 18856.28 20666.87 28342.19 27285.20 18779.23 210
lupinMVS63.36 22761.49 24368.97 19074.93 17959.19 13165.80 24864.52 25334.68 33163.53 28574.25 29043.19 25970.62 25153.88 19378.67 26977.10 231
MVSTER63.29 22861.60 24168.36 20259.77 33446.21 23560.62 29671.32 21741.83 29575.40 17279.12 24330.25 33075.85 19656.30 17279.81 25883.03 139
OpenMVS_ROBcopyleft54.93 1763.23 22963.28 22463.07 24669.81 26245.34 24068.52 21567.14 23943.74 28570.61 23379.22 24047.90 24172.66 23148.75 22373.84 29971.21 275
IterMVS63.12 23062.48 23665.02 22966.34 29952.86 16763.81 26762.25 26046.57 26371.51 22180.40 22444.60 25166.82 28651.38 20475.47 28875.38 242
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
HyFIR lowres test63.01 23160.47 24970.61 16783.04 8654.10 15959.93 30172.24 21033.67 33769.00 24475.63 27238.69 28376.93 18736.60 30775.45 28980.81 186
GA-MVS62.91 23261.66 23866.66 21967.09 29444.49 24561.18 29469.36 23351.33 22269.33 24274.47 28636.83 29174.94 20850.60 21074.72 29480.57 191
PVSNet_Blended62.90 23361.64 24066.69 21869.81 26249.36 18661.23 29378.96 14142.04 29459.98 30568.86 33251.82 22378.20 17744.30 25077.77 27872.52 261
view60062.88 23462.90 22962.82 24872.97 23633.66 32266.10 24155.01 29957.05 14772.66 20382.56 19931.60 31572.78 22642.64 26685.55 17582.02 160
view80062.88 23462.90 22962.82 24872.97 23633.66 32266.10 24155.01 29957.05 14772.66 20382.56 19931.60 31572.78 22642.64 26685.55 17582.02 160
conf0.05thres100062.88 23462.90 22962.82 24872.97 23633.66 32266.10 24155.01 29957.05 14772.66 20382.56 19931.60 31572.78 22642.64 26685.55 17582.02 160
tfpn62.88 23462.90 22962.82 24872.97 23633.66 32266.10 24155.01 29957.05 14772.66 20382.56 19931.60 31572.78 22642.64 26685.55 17582.02 160
USDC62.80 23863.10 22761.89 25965.19 30543.30 24867.42 22674.20 19435.80 32472.25 21284.48 17545.67 24571.95 24337.95 29984.97 19370.42 282
Vis-MVSNet (Re-imp)62.74 23963.21 22661.34 26572.19 24331.56 34167.31 23053.87 30653.60 20069.88 23883.37 18840.52 27670.98 24941.40 27886.78 16081.48 172
MDA-MVSNet-bldmvs62.34 24061.73 23764.16 23361.64 32349.90 18248.11 33657.24 28853.31 20480.95 10479.39 23749.00 23561.55 30645.92 24580.05 25581.03 179
wuyk23d61.97 24166.25 20749.12 31858.19 34560.77 12166.32 23952.97 31255.93 16190.62 786.91 12173.07 4535.98 35920.63 35891.63 7350.62 350
tfpn11161.91 24261.65 23962.68 25372.14 24435.01 31065.42 25356.99 28955.23 16970.71 23079.90 22832.07 31072.85 22538.80 29083.61 20680.18 197
thres600view761.82 24361.38 24463.12 24571.81 24934.93 31364.64 25956.99 28954.78 18170.33 23679.74 23332.07 31072.42 23638.61 29383.46 20782.02 160
PAPM61.79 24460.37 25066.05 22276.09 16841.87 25769.30 20276.79 17540.64 30353.80 33579.62 23544.38 25282.92 7429.64 33773.11 30173.36 254
MVP-Stereo61.56 24559.22 25668.58 20079.28 12460.44 12269.20 20471.57 21343.58 28756.42 32278.37 24939.57 28076.46 19434.86 31660.16 34368.86 300
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
CMPMVSbinary48.73 2061.54 24660.89 24763.52 24161.08 32651.55 17268.07 22068.00 23833.88 33365.87 27181.25 21637.91 28967.71 27649.32 21982.60 21471.31 273
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
conf200view1161.42 24761.09 24562.43 25672.14 24435.01 31065.42 25356.99 28955.23 16970.71 23079.90 22832.07 31072.09 23835.61 31281.73 22680.18 197
RPMNet61.25 24861.55 24260.36 27566.37 29748.24 20070.93 18654.45 30454.66 18461.35 29386.77 12833.29 30163.22 29955.93 17570.17 31569.62 293
thres100view90061.17 24961.09 24561.39 26472.14 24435.01 31065.42 25356.99 28955.23 16970.71 23079.90 22832.07 31072.09 23835.61 31281.73 22677.08 232
Patchmtry60.91 25063.01 22854.62 30366.10 30126.27 35467.47 22556.40 29454.05 19372.04 21486.66 13333.19 30260.17 30943.69 25487.45 14877.42 227
EU-MVSNet60.82 25160.80 24860.86 27068.37 27941.16 26172.27 15268.27 23726.96 35869.08 24375.71 27132.09 30967.44 27955.59 17978.90 26673.97 249
pmmvs460.78 25259.04 25866.00 22373.06 23357.67 14264.53 26260.22 27236.91 31965.96 27077.27 25539.66 27968.54 27138.87 28974.89 29371.80 269
thres40060.77 25359.97 25263.15 24470.78 25335.35 30863.27 27357.47 28353.00 20668.31 25077.09 25632.45 30772.09 23835.61 31281.73 22682.02 160
MVS60.62 25459.97 25262.58 25468.13 28347.28 22368.59 21273.96 19532.19 34259.94 30768.86 33250.48 22977.64 18241.85 27575.74 28462.83 328
thisisatest051560.48 25557.86 27368.34 20367.25 29146.42 23460.58 29762.14 26140.82 30063.58 28469.12 32726.28 35178.34 17248.83 22282.13 22080.26 195
tfpn200view960.35 25659.97 25261.51 26270.78 25335.35 30863.27 27357.47 28353.00 20668.31 25077.09 25632.45 30772.09 23835.61 31281.73 22677.08 232
ppachtmachnet_test60.26 25759.61 25562.20 25767.70 28844.33 24658.18 31060.96 27040.75 30165.80 27272.57 30241.23 27063.92 29746.87 24082.42 21678.33 217
Patchmatch-RL test59.95 25859.12 25762.44 25572.46 24254.61 15659.63 30247.51 33641.05 29974.58 18374.30 28931.06 32465.31 29151.61 20179.85 25767.39 306
131459.83 25958.86 26662.74 25265.71 30344.78 24368.59 21272.63 20533.54 34061.05 29767.29 33943.62 25771.26 24849.49 21867.84 32872.19 266
IB-MVS49.67 1859.69 26056.96 28067.90 20568.19 28250.30 17961.42 29165.18 25047.57 25855.83 32567.15 34023.77 35879.60 14743.56 25679.97 25673.79 252
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
1112_ss59.48 26158.99 25960.96 26977.84 14542.39 25561.42 29168.45 23637.96 31459.93 30867.46 33745.11 24865.07 29340.89 28171.81 30675.41 241
FPMVS59.43 26260.07 25157.51 29077.62 15271.52 4562.33 27850.92 32457.40 14569.40 24180.00 22739.14 28161.92 30537.47 30366.36 33139.09 360
conf0.0159.26 26358.88 26060.40 27368.66 27131.96 33562.04 28051.95 31650.99 22667.57 25775.91 26528.59 34069.07 26242.77 26081.40 23480.18 197
conf0.00259.26 26358.88 26060.40 27368.66 27131.96 33562.04 28051.95 31650.99 22667.57 25775.91 26528.59 34069.07 26242.77 26081.40 23480.18 197
CVMVSNet59.21 26558.44 27161.51 26273.94 20747.76 21171.31 17864.56 25226.91 35960.34 30270.44 31836.24 29367.65 27753.57 19568.66 32569.12 298
CR-MVSNet58.96 26658.49 27060.36 27566.37 29748.24 20070.93 18656.40 29432.87 34161.35 29386.66 13333.19 30263.22 29948.50 22770.17 31569.62 293
EPNet_dtu58.93 26758.52 26960.16 27767.91 28647.70 21269.97 19458.02 27949.73 24047.28 35073.02 30138.14 28662.34 30336.57 30885.99 16870.43 281
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
Test_1112_low_res58.78 26858.69 26859.04 28279.41 12238.13 28857.62 31166.98 24134.74 32959.62 30977.56 25342.92 26163.65 29838.66 29270.73 31275.35 243
PatchMatch-RL58.68 26957.72 27461.57 26176.21 16673.59 3961.83 28649.00 33147.30 26061.08 29568.97 32950.16 23159.01 31236.06 31168.84 32352.10 349
thresconf0.0258.38 27058.88 26056.91 29368.66 27131.96 33562.04 28051.95 31650.99 22667.57 25775.91 26528.59 34069.07 26242.77 26081.40 23469.70 288
tfpn_n40058.38 27058.88 26056.91 29368.66 27131.96 33562.04 28051.95 31650.99 22667.57 25775.91 26528.59 34069.07 26242.77 26081.40 23469.70 288
tfpnconf58.38 27058.88 26056.91 29368.66 27131.96 33562.04 28051.95 31650.99 22667.57 25775.91 26528.59 34069.07 26242.77 26081.40 23469.70 288
tfpnview1158.38 27058.88 26056.91 29368.66 27131.96 33562.04 28051.95 31650.99 22667.57 25775.91 26528.59 34069.07 26242.77 26081.40 23469.70 288
tfpn100058.28 27458.86 26656.53 29768.05 28432.26 33262.58 27751.67 32351.25 22467.38 26375.95 26427.24 34768.83 26843.51 25782.11 22168.49 301
CHOSEN 1792x268858.09 27556.30 28563.45 24279.95 11650.93 17554.07 32265.59 24728.56 35561.53 29274.33 28841.09 27266.52 28933.91 32167.69 32972.92 257
HY-MVS49.31 1957.96 27657.59 27559.10 28166.85 29536.17 30165.13 25865.39 24939.24 30754.69 33178.14 25044.28 25367.18 28233.75 32270.79 31173.95 250
Patchmatch-test157.81 27758.04 27257.13 29170.17 26141.07 26365.19 25753.38 31043.34 29161.00 29871.94 31145.20 24762.69 30141.81 27670.31 31467.63 305
tpmp4_e2357.57 27855.46 29263.93 23766.48 29641.56 26071.68 16860.65 27135.64 32555.35 32876.25 26229.53 33675.41 20234.40 31869.12 32274.83 245
thres20057.55 27957.02 27959.17 28067.89 28734.93 31358.91 30757.25 28750.24 23664.01 28071.46 31632.49 30671.39 24731.31 32879.57 26271.19 276
CostFormer57.35 28056.14 28660.97 26863.76 31338.43 28367.50 22460.22 27237.14 31859.12 31076.34 26132.78 30471.99 24239.12 28869.27 32172.47 262
tfpn_ndepth56.91 28157.30 27855.71 29967.22 29333.26 32761.72 28853.98 30548.49 24964.16 27971.94 31127.65 34668.71 26940.49 28380.08 25465.17 320
our_test_356.46 28256.51 28356.30 29867.70 28839.66 27555.36 31952.34 31540.57 30463.85 28169.91 32340.04 27858.22 31443.49 25875.29 29271.03 279
tpm256.12 28354.64 29560.55 27266.24 30036.01 30268.14 21956.77 29333.60 33958.25 31475.52 27530.25 33074.33 21533.27 32369.76 32071.32 272
no-one56.11 28455.62 29057.60 28962.68 31749.23 18839.12 35558.99 27733.72 33560.98 29980.90 21836.07 29460.36 30830.68 33097.40 163.22 327
tpmvs55.84 28555.45 29357.01 29260.33 33033.20 32865.89 24759.29 27647.52 25956.04 32373.60 29531.05 32568.06 27440.64 28264.64 33469.77 287
gg-mvs-nofinetune55.75 28656.75 28252.72 30762.87 31628.04 34968.92 20541.36 35771.09 3050.80 34192.63 1220.74 36166.86 28429.97 33572.41 30363.25 326
test20.0355.74 28757.51 27650.42 31159.89 33332.09 33350.63 32949.01 33050.11 23865.07 27683.23 19345.61 24648.11 33030.22 33383.82 20471.07 278
MS-PatchMatch55.59 28854.89 29457.68 28869.18 26949.05 18961.00 29562.93 25935.98 32258.36 31368.93 33036.71 29266.59 28837.62 30263.30 33757.39 342
XXY-MVS55.19 28957.40 27748.56 32164.45 31034.84 31551.54 32853.59 30838.99 30863.79 28279.43 23656.59 20445.57 33536.92 30671.29 30865.25 319
FMVSNet555.08 29055.54 29153.71 30465.80 30233.50 32656.22 31452.50 31443.72 28661.06 29683.38 18725.46 35554.87 31830.11 33481.64 23272.75 259
PatchmatchNetpermissive54.60 29154.27 29755.59 30065.17 30739.08 27866.92 23351.80 32239.89 30558.39 31273.12 30031.69 31458.33 31343.01 25958.38 35269.38 296
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
MIMVSNet54.39 29256.12 28749.20 31672.57 24130.91 34259.98 30048.43 33341.66 29655.94 32483.86 18341.19 27150.42 32426.05 34475.38 29066.27 314
Anonymous2023120654.13 29355.82 28849.04 31970.89 25135.96 30351.73 32750.87 32534.86 32762.49 28879.22 24042.52 26544.29 34427.95 34281.88 22566.88 310
JIA-IIPM54.03 29451.62 30761.25 26659.14 33855.21 15059.10 30447.72 33550.85 23350.31 34585.81 15920.10 36363.97 29636.16 31055.41 35764.55 324
tpm cat154.02 29552.63 30358.19 28664.85 30839.86 27466.26 24057.28 28632.16 34356.90 31970.39 32032.75 30565.30 29234.29 31958.79 34869.41 295
testgi54.00 29656.86 28145.45 32958.20 34425.81 35549.05 33249.50 32945.43 27267.84 25381.17 21751.81 22543.20 34829.30 33879.41 26367.34 308
PatchFormer-LS_test53.94 29752.64 30257.85 28761.87 32139.59 27661.60 28957.63 28140.65 30254.52 33258.64 35429.07 33964.18 29546.78 24162.98 33969.78 286
PatchT53.35 29856.47 28443.99 33664.19 31117.46 36359.15 30343.10 34752.11 21354.74 33086.95 12029.97 33349.98 32743.62 25574.40 29564.53 325
DWT-MVSNet_test53.04 29951.12 31058.77 28361.23 32438.67 28262.16 27957.74 28038.24 31151.76 33959.07 35321.36 36067.40 28044.80 24963.76 33670.25 283
LP53.02 30052.27 30655.27 30155.76 35640.55 26955.64 31755.07 29742.46 29256.95 31873.21 29933.67 30054.18 32238.41 29559.29 34771.08 277
testmv52.91 30154.31 29648.71 32072.13 24736.18 30050.26 33047.78 33444.15 28164.61 27779.78 23238.18 28550.20 32621.96 35569.93 31759.75 339
new-patchmatchnet52.89 30255.76 28944.26 33559.94 3326.31 36937.36 35950.76 32641.10 29764.28 27879.82 23144.77 24948.43 32936.24 30987.61 14278.03 223
YYNet152.58 30353.50 29949.85 31254.15 36236.45 29940.53 35046.55 33938.09 31375.52 17073.31 29841.08 27343.88 34541.10 27971.14 31069.21 297
MDA-MVSNet_test_wron52.57 30453.49 30049.81 31354.24 36136.47 29840.48 35146.58 33838.13 31275.47 17173.32 29741.05 27443.85 34640.98 28071.20 30969.10 299
pmmvs552.49 30552.58 30452.21 30954.99 35932.38 33155.45 31853.84 30732.15 34455.49 32774.81 28038.08 28757.37 31634.02 32074.40 29566.88 310
UnsupCasMVSNet_eth52.26 30653.29 30149.16 31755.08 35833.67 32150.03 33158.79 27837.67 31563.43 28774.75 28241.82 26845.83 33438.59 29459.42 34667.98 304
N_pmnet52.06 30751.11 31154.92 30259.64 33571.03 5037.42 35861.62 26833.68 33657.12 31672.10 30337.94 28831.03 36329.13 34171.35 30762.70 329
PVSNet43.83 2151.56 30851.17 30952.73 30668.34 28038.27 28548.22 33553.56 30936.41 32054.29 33364.94 34334.60 29754.20 32130.34 33269.87 31865.71 317
tpm50.60 30952.42 30545.14 33165.18 30626.29 35360.30 29843.50 34637.41 31657.01 31779.09 24430.20 33242.32 35032.77 32566.36 33166.81 312
test-LLR50.43 31050.69 31349.64 31460.76 32741.87 25753.18 32445.48 34443.41 28949.41 34660.47 35129.22 33744.73 34142.09 27372.14 30462.33 332
tpmrst50.15 31151.38 30846.45 32656.05 35224.77 35764.40 26449.98 32736.14 32153.32 33669.59 32535.16 29648.69 32839.24 28758.51 35165.89 315
UnsupCasMVSNet_bld50.01 31251.03 31246.95 32258.61 34132.64 33048.31 33453.27 31134.27 33260.47 30171.53 31541.40 26947.07 33230.68 33060.78 34261.13 334
WTY-MVS49.39 31350.31 31446.62 32561.22 32532.00 33446.61 34049.77 32833.87 33454.12 33469.55 32641.96 26745.40 33731.28 32964.42 33562.47 331
ADS-MVSNet248.76 31447.25 32353.29 30555.90 35440.54 27047.34 33854.99 30331.41 35050.48 34272.06 30931.23 32154.26 32025.93 34555.93 35465.07 321
test-mter48.56 31548.20 32049.64 31460.76 32741.87 25753.18 32445.48 34431.91 34849.41 34660.47 35118.34 36444.73 34142.09 27372.14 30462.33 332
test123567848.41 31649.60 31644.83 33368.52 27733.81 32046.33 34245.89 34138.72 31058.46 31172.08 30429.85 33547.82 33119.67 35966.91 33052.88 347
Patchmatch-test47.93 31749.96 31541.84 34057.42 34824.26 35848.75 33341.49 35639.30 30656.79 32073.48 29630.48 32933.87 36229.29 33972.61 30267.39 306
test0.0.03 147.72 31848.31 31945.93 32755.53 35729.39 34446.40 34141.21 35843.41 28955.81 32667.65 33629.22 33743.77 34725.73 34769.87 31864.62 323
sss47.59 31948.32 31845.40 33056.73 35133.96 31845.17 34448.51 33232.11 34652.37 33865.79 34140.39 27741.91 35331.85 32661.97 34060.35 335
pmmvs346.71 32045.09 32951.55 31056.76 35048.25 19955.78 31639.53 36224.13 36250.35 34463.40 34515.90 36851.08 32329.29 33970.69 31355.33 345
EPMVS45.74 32146.53 32443.39 33754.14 36322.33 36055.02 32035.00 36534.69 33051.09 34070.20 32225.92 35342.04 35237.19 30455.50 35665.78 316
MVS-HIRNet45.53 32247.29 32240.24 34462.29 32026.82 35256.02 31537.41 36329.74 35443.69 36181.27 21533.96 29955.48 31724.46 35056.79 35338.43 361
testpf45.32 32348.47 31735.88 34953.56 36426.84 35158.86 30842.95 34847.78 25646.18 35263.70 34413.73 36950.29 32550.81 20758.61 35030.51 363
TESTMET0.1,145.17 32444.93 33045.89 32856.02 35338.31 28453.18 32441.94 35527.85 35644.86 35656.47 35617.93 36541.50 35538.08 29868.06 32657.85 341
E-PMN45.17 32445.36 32844.60 33450.07 36542.75 25238.66 35642.29 35346.39 26439.55 36351.15 36126.00 35245.37 33837.68 30076.41 28045.69 356
111145.08 32647.96 32136.43 34859.56 33614.82 36543.56 34545.65 34245.60 26860.04 30375.47 2769.31 37134.46 36023.66 35168.76 32460.02 337
testus45.03 32746.49 32540.65 34362.53 31825.24 35642.54 34746.23 34031.16 35257.69 31562.90 34634.60 29742.33 34917.72 36163.01 33854.37 346
PMMVS44.69 32843.95 33446.92 32350.05 36653.47 16448.08 33742.40 35122.36 36344.01 36053.05 35842.60 26445.49 33631.69 32761.36 34141.79 358
ADS-MVSNet44.62 32945.58 32741.73 34155.90 35420.83 36147.34 33839.94 36131.41 35050.48 34272.06 30931.23 32139.31 35625.93 34555.93 35465.07 321
EMVS44.61 33044.45 33345.10 33248.91 36743.00 25037.92 35741.10 35946.75 26138.00 36548.43 36326.42 35046.27 33337.11 30575.38 29046.03 355
dp44.09 33144.88 33141.72 34258.53 34223.18 35954.70 32142.38 35234.80 32844.25 35965.61 34224.48 35744.80 34029.77 33649.42 36057.18 343
DSMNet-mixed43.18 33244.66 33238.75 34654.75 36028.88 34757.06 31327.42 36913.47 36447.27 35177.67 25238.83 28239.29 35725.32 34960.12 34448.08 352
CHOSEN 280x42041.62 33339.89 34046.80 32461.81 32251.59 17133.56 36135.74 36427.48 35737.64 36653.53 35723.24 35942.09 35127.39 34358.64 34946.72 354
PVSNet_036.71 2241.12 33440.78 33742.14 33859.97 33140.13 27240.97 34942.24 35430.81 35344.86 35649.41 36240.70 27545.12 33923.15 35334.96 36241.16 359
test235640.85 33540.47 33841.98 33958.78 34028.65 34839.45 35340.98 36031.95 34748.47 34856.63 35512.54 37044.41 34315.84 36359.58 34552.88 347
test1235638.35 33640.80 33631.01 35058.31 3439.09 36836.67 36046.65 33733.65 33844.39 35860.94 35017.56 36639.23 35816.01 36253.03 35844.72 357
PMMVS237.74 33740.87 33528.36 35342.41 3695.35 37024.61 36227.75 36832.15 34447.85 34970.27 32135.85 29529.51 36419.08 36067.85 32750.22 351
new_pmnet37.55 33839.80 34130.79 35156.83 34916.46 36439.35 35430.65 36725.59 36045.26 35461.60 34924.54 35628.02 36521.60 35652.80 35947.90 353
PNet_i23d36.76 33936.63 34337.12 34758.19 34533.00 32939.86 35232.55 36648.44 25039.64 36251.31 3606.89 37341.83 35422.29 35430.55 36336.54 362
MVEpermissive27.91 2336.69 34035.64 34439.84 34543.37 36835.85 30519.49 36324.61 37024.68 36139.05 36462.63 34838.67 28427.10 36621.04 35747.25 36156.56 344
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
pcd1.5k->3k35.00 34136.93 34229.21 35284.62 680.00 3740.00 36578.90 1430.00 3690.00 3710.00 37178.26 140.00 3710.00 36890.55 10187.62 66
v1.034.83 34246.44 3260.00 35985.90 470.00 3740.00 36584.94 3173.27 2084.61 6189.25 840.00 3760.00 3710.00 3680.00 3690.00 369
.test124534.47 34340.38 33916.73 35459.56 33614.82 36543.56 34545.65 34245.60 26860.04 30375.47 2769.31 37134.46 36023.66 3510.55 3670.90 366
cdsmvs_eth3d_5k17.71 34423.62 3450.00 3590.00 3740.00 3740.00 36570.17 2300.00 3690.00 37174.25 29068.16 820.00 3710.00 3680.00 3690.00 369
tmp_tt11.98 34514.73 3463.72 3562.28 3714.62 37119.44 36414.50 3720.47 36621.55 3679.58 36625.78 3544.57 36811.61 36427.37 3641.96 365
ab-mvs-re5.62 3467.50 3470.00 3590.00 3740.00 3740.00 3650.00 3760.00 3690.00 37167.46 3370.00 3760.00 3710.00 3680.00 3690.00 369
pcd_1.5k_mvsjas5.20 3476.93 3480.00 3590.00 3740.00 3740.00 3650.00 3760.00 3690.00 3710.00 37162.39 1270.00 3710.00 3680.00 3690.00 369
test1234.43 3485.78 3490.39 3580.97 3720.28 37246.33 3420.45 3740.31 3670.62 3691.50 3690.61 3750.11 3700.56 3660.63 3660.77 368
testmvs4.06 3495.28 3500.41 3570.64 3730.16 37342.54 3470.31 3750.26 3680.50 3701.40 3700.77 3740.17 3690.56 3660.55 3670.90 366
sosnet-low-res0.00 3500.00 3510.00 3590.00 3740.00 3740.00 3650.00 3760.00 3690.00 3710.00 3710.00 3760.00 3710.00 3680.00 3690.00 369
sosnet0.00 3500.00 3510.00 3590.00 3740.00 3740.00 3650.00 3760.00 3690.00 3710.00 3710.00 3760.00 3710.00 3680.00 3690.00 369
uncertanet0.00 3500.00 3510.00 3590.00 3740.00 3740.00 3650.00 3760.00 3690.00 3710.00 3710.00 3760.00 3710.00 3680.00 3690.00 369
Regformer0.00 3500.00 3510.00 3590.00 3740.00 3740.00 3650.00 3760.00 3690.00 3710.00 3710.00 3760.00 3710.00 3680.00 3690.00 369
uanet0.00 3500.00 3510.00 3590.00 3740.00 3740.00 3650.00 3760.00 3690.00 3710.00 3710.00 3760.00 3710.00 3680.00 3690.00 369
GSMVS70.05 284
test_part285.90 4766.44 8284.61 61
test_part10.00 3590.00 3740.00 36584.94 310.00 3760.00 3710.00 3680.00 3690.00 369
sam_mvs131.41 31970.05 284
sam_mvs31.21 323
semantic-postprocess72.49 14773.34 22158.20 14165.55 24848.10 25176.91 15082.64 19842.25 26678.84 15561.20 13977.89 27780.44 193
ambc70.10 17777.74 14750.21 18074.28 14077.93 16279.26 12388.29 10654.11 21479.77 14564.43 12191.10 8780.30 194
MTGPAbinary80.63 111
test_post166.63 2362.08 36730.66 32859.33 31140.34 285
test_post1.99 36830.91 32654.76 319
patchmatchnet-post68.99 32831.32 32069.38 259
GG-mvs-BLEND52.24 30860.64 32929.21 34669.73 19942.41 35045.47 35352.33 35920.43 36268.16 27325.52 34865.42 33359.36 340
MTMP84.83 2619.26 371
gm-plane-assit62.51 31933.91 31937.25 31762.71 34772.74 23038.70 291
test9_res72.12 5491.37 8077.40 228
TEST985.47 5469.32 6676.42 10278.69 14653.73 19976.97 14686.74 12966.84 9281.10 114
test_885.09 6067.89 7576.26 10778.66 14854.00 19476.89 15186.72 13166.60 9480.89 126
agg_prior270.70 6290.93 9278.55 216
agg_prior84.44 7366.02 8578.62 14976.95 14880.34 135
TestCases78.35 6179.19 12870.81 5288.64 265.37 6780.09 11588.17 10770.33 6478.43 16755.60 17790.90 9485.81 86
test_prior470.14 5977.57 86
test_prior275.57 11858.92 13176.53 15986.78 12667.83 8669.81 7092.76 61
test_prior75.27 9282.15 9859.85 12784.33 4183.39 6782.58 150
旧先验271.17 18245.11 27578.54 13161.28 30759.19 151
新几何271.33 177
新几何169.99 17988.37 3271.34 4862.08 26343.85 28274.99 17586.11 15352.85 21870.57 25250.99 20683.23 21068.05 303
旧先验184.55 7060.36 12363.69 25587.05 11954.65 21283.34 20869.66 292
无先验74.82 13070.94 22447.75 25776.85 18954.47 18772.09 267
原ACMM274.78 134
原ACMM173.90 10585.90 4765.15 9381.67 8450.97 23274.25 18686.16 15161.60 13583.54 6356.75 16591.08 8873.00 256
test22287.30 3669.15 6967.85 22159.59 27541.06 29873.05 19985.72 16048.03 24080.65 24966.92 309
testdata267.30 28148.34 228
segment_acmp68.30 81
testdata64.13 23485.87 5063.34 10561.80 26747.83 25576.42 16386.60 13848.83 23662.31 30454.46 18981.26 24166.74 313
testdata168.34 21857.24 146
test1276.51 7482.28 9660.94 12081.64 8573.60 19264.88 11085.19 4190.42 10383.38 134
plane_prior785.18 5766.21 84
plane_prior684.18 7765.31 9060.83 147
plane_prior585.49 2186.15 2271.09 5690.94 9084.82 99
plane_prior489.11 89
plane_prior365.67 8763.82 8778.23 136
plane_prior282.74 3965.45 64
plane_prior184.46 72
plane_prior65.18 9180.06 6361.88 10689.91 114
n20.00 376
nn0.00 376
door-mid55.02 298
lessismore_v072.75 14179.60 12056.83 14557.37 28583.80 7189.01 9247.45 24278.74 15864.39 12286.49 16482.69 148
LGP-MVS_train80.90 3387.00 3870.41 5786.35 1269.77 3987.75 1891.13 3681.83 386.20 1977.13 2895.96 786.08 80
test1182.71 70
door52.91 313
HQP5-MVS58.80 136
HQP-NCC82.37 9377.32 9059.08 12771.58 216
ACMP_Plane82.37 9377.32 9059.08 12771.58 216
BP-MVS67.38 97
HQP4-MVS71.59 21585.31 3583.74 125
HQP3-MVS84.12 4889.16 121
HQP2-MVS58.09 181
NP-MVS83.34 8463.07 10885.97 156
MDTV_nov1_ep13_2view18.41 36253.74 32331.57 34944.89 35529.90 33432.93 32471.48 271
MDTV_nov1_ep1354.05 29865.54 30429.30 34559.00 30555.22 29635.96 32352.44 33775.98 26330.77 32759.62 31038.21 29673.33 300
ACMMP++_ref89.47 119
ACMMP++91.96 70
Test By Simon62.56 123
ITE_SJBPF80.35 3976.94 15873.60 3880.48 11566.87 5283.64 7386.18 14970.25 6679.90 14461.12 14088.95 12587.56 68
DeepMVS_CXcopyleft11.83 35515.51 37013.86 36711.25 3735.76 36520.85 36826.46 36417.06 3679.22 3679.69 36513.82 36512.42 364