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-MVSNet95.70 196.40 193.61 398.67 185.39 3795.54 597.36 196.97 199.04 199.05 196.61 195.92 1685.07 6999.27 199.54 1
mamv495.37 294.51 297.96 196.31 1098.41 191.05 4797.23 295.32 299.01 297.26 980.16 14498.99 195.15 199.14 296.47 35
TDRefinement93.52 393.39 593.88 295.94 1590.26 495.70 496.46 390.58 992.86 5196.29 2288.16 3694.17 10286.07 5498.48 1897.22 18
LTVRE_ROB86.10 193.04 493.44 491.82 2293.73 6685.72 3496.79 195.51 1088.86 1695.63 1096.99 1384.81 7693.16 14591.10 297.53 7796.58 33
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
reproduce_model92.89 593.18 892.01 1394.20 5188.23 992.87 1394.32 2290.25 1195.65 995.74 3387.75 4295.72 3689.60 598.27 2892.08 226
reproduce-ours92.86 693.22 691.76 2394.39 4687.71 1192.40 2894.38 2089.82 1395.51 1295.49 4289.64 2295.82 2689.13 798.26 3091.76 237
our_new_method92.86 693.22 691.76 2394.39 4687.71 1192.40 2894.38 2089.82 1395.51 1295.49 4289.64 2295.82 2689.13 798.26 3091.76 237
HPM-MVS_fast92.50 892.54 1092.37 695.93 1685.81 3392.99 1294.23 2885.21 4492.51 5995.13 5290.65 1095.34 5588.06 1698.15 3995.95 46
lecture92.43 993.50 389.21 6694.43 4479.31 8492.69 1995.72 888.48 2294.43 2095.73 3491.34 494.68 7890.26 498.44 2093.63 141
SR-MVS-dyc-post92.41 1092.41 1192.39 594.13 5788.95 692.87 1394.16 3388.75 1893.79 3394.43 7688.83 2795.51 4787.16 3797.60 7192.73 183
SR-MVS92.23 1192.34 1291.91 1794.89 3887.85 1092.51 2593.87 5288.20 2493.24 4394.02 10090.15 1795.67 3886.82 4197.34 8192.19 221
HPM-MVScopyleft92.13 1292.20 1491.91 1795.58 2684.67 4693.51 894.85 1682.88 7091.77 7293.94 10890.55 1395.73 3588.50 1298.23 3395.33 61
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
APD-MVS_3200maxsize92.05 1392.24 1391.48 2593.02 8585.17 3992.47 2795.05 1587.65 2893.21 4494.39 8190.09 1895.08 6686.67 4397.60 7194.18 111
COLMAP_ROBcopyleft83.01 391.97 1491.95 1592.04 1193.68 6786.15 2493.37 1095.10 1490.28 1092.11 6495.03 5489.75 2194.93 7079.95 12898.27 2895.04 74
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
ACMMPcopyleft91.91 1591.87 2092.03 1295.53 2785.91 2893.35 1194.16 3382.52 7392.39 6294.14 9389.15 2695.62 3987.35 3298.24 3294.56 90
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
mPP-MVS91.69 1691.47 2792.37 696.04 1388.48 892.72 1892.60 10983.09 6791.54 7494.25 8787.67 4595.51 4787.21 3698.11 4093.12 166
CP-MVS91.67 1791.58 2491.96 1495.29 3187.62 1393.38 993.36 6983.16 6691.06 8494.00 10188.26 3395.71 3787.28 3598.39 2392.55 196
XVS91.54 1891.36 2992.08 995.64 2486.25 2292.64 2093.33 7185.07 4589.99 10694.03 9986.57 5695.80 2887.35 3297.62 6994.20 108
MTAPA91.52 1991.60 2391.29 3096.59 486.29 2192.02 3491.81 13684.07 5592.00 6794.40 8086.63 5595.28 5888.59 1198.31 2692.30 213
UA-Net91.49 2091.53 2591.39 2794.98 3582.95 5893.52 792.79 10188.22 2388.53 14297.64 683.45 9094.55 8686.02 5898.60 1396.67 30
ACMMPR91.49 2091.35 3191.92 1695.74 2085.88 3092.58 2393.25 7781.99 7691.40 7694.17 9287.51 4695.87 2087.74 2197.76 6093.99 118
LPG-MVS_test91.47 2291.68 2190.82 3794.75 4181.69 6390.00 6394.27 2582.35 7493.67 3894.82 6091.18 595.52 4585.36 6598.73 795.23 66
region2R91.44 2391.30 3591.87 1995.75 1985.90 2992.63 2293.30 7581.91 7890.88 9194.21 8887.75 4295.87 2087.60 2697.71 6393.83 127
HFP-MVS91.30 2491.39 2891.02 3395.43 2984.66 4792.58 2393.29 7681.99 7691.47 7593.96 10588.35 3295.56 4287.74 2197.74 6292.85 180
ZNCC-MVS91.26 2591.34 3291.01 3495.73 2183.05 5692.18 3294.22 3080.14 9991.29 8093.97 10287.93 4195.87 2088.65 1097.96 5194.12 115
APDe-MVScopyleft91.22 2691.92 1689.14 6892.97 8778.04 9692.84 1694.14 3783.33 6493.90 2995.73 3488.77 2896.41 387.60 2697.98 4892.98 176
Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition
PGM-MVS91.20 2790.95 4491.93 1595.67 2385.85 3190.00 6393.90 4980.32 9691.74 7394.41 7988.17 3595.98 1386.37 4797.99 4693.96 120
SteuartSystems-ACMMP91.16 2891.36 2990.55 4193.91 6280.97 7091.49 4193.48 6782.82 7192.60 5893.97 10288.19 3496.29 687.61 2598.20 3694.39 102
Skip Steuart: Steuart Systems R&D Blog.
MP-MVScopyleft91.14 2990.91 4591.83 2096.18 1186.88 1792.20 3193.03 9182.59 7288.52 14394.37 8286.74 5495.41 5386.32 4898.21 3493.19 162
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
GST-MVS90.96 3091.01 4190.82 3795.45 2882.73 5991.75 3993.74 5580.98 8991.38 7793.80 11287.20 5095.80 2887.10 3997.69 6593.93 121
MP-MVS-pluss90.81 3191.08 3889.99 5095.97 1479.88 7788.13 10594.51 1975.79 15592.94 4894.96 5588.36 3195.01 6890.70 398.40 2295.09 73
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
ACMH+77.89 1190.73 3291.50 2688.44 8193.00 8676.26 12289.65 7695.55 987.72 2793.89 3194.94 5691.62 393.44 13678.35 15098.76 495.61 55
ACMMP_NAP90.65 3391.07 4089.42 6295.93 1679.54 8289.95 6793.68 5977.65 13491.97 6894.89 5788.38 3095.45 5189.27 697.87 5693.27 157
ACMM79.39 990.65 3390.99 4289.63 5895.03 3483.53 5189.62 7793.35 7079.20 11293.83 3293.60 12290.81 892.96 15285.02 7298.45 1992.41 203
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
LS3D90.60 3590.34 5291.38 2889.03 19984.23 4993.58 694.68 1890.65 890.33 10093.95 10784.50 7895.37 5480.87 11895.50 15394.53 93
ACMP79.16 1090.54 3690.60 5090.35 4594.36 4880.98 6989.16 8794.05 4279.03 11592.87 5093.74 11790.60 1295.21 6182.87 9698.76 494.87 78
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
DPE-MVScopyleft90.53 3791.08 3888.88 7193.38 7678.65 9089.15 8894.05 4284.68 4993.90 2994.11 9588.13 3796.30 584.51 7997.81 5891.70 241
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
SED-MVS90.46 3891.64 2286.93 10594.18 5272.65 15290.47 5693.69 5783.77 5894.11 2794.27 8390.28 1595.84 2486.03 5597.92 5292.29 215
SMA-MVScopyleft90.31 3990.48 5189.83 5595.31 3079.52 8390.98 4893.24 7875.37 16492.84 5295.28 4885.58 6996.09 887.92 1897.76 6093.88 124
Yufeng Yin; Xiaoyan Liu; Zichao Zhang: SMA-MVS: Segmentation-Guided Multi-Scale Anchor Deformation Patch Multi-View Stereo. IEEE Transactions on Circuits and Systems for Video Technology
SF-MVS90.27 4090.80 4788.68 7892.86 9177.09 11191.19 4595.74 681.38 8492.28 6393.80 11286.89 5394.64 8185.52 6497.51 7894.30 107
v7n90.13 4190.96 4387.65 9691.95 11871.06 18489.99 6593.05 8886.53 3594.29 2396.27 2382.69 9794.08 10586.25 5197.63 6797.82 8
PMVScopyleft80.48 690.08 4290.66 4988.34 8496.71 392.97 290.31 6089.57 21188.51 2190.11 10295.12 5390.98 788.92 27277.55 16497.07 8883.13 398
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
DVP-MVS++90.07 4391.09 3787.00 10391.55 13572.64 15496.19 294.10 4085.33 4293.49 4094.64 6881.12 13295.88 1887.41 3095.94 13392.48 199
DVP-MVScopyleft90.06 4491.32 3386.29 11794.16 5572.56 15890.54 5391.01 16283.61 6193.75 3594.65 6589.76 1995.78 3286.42 4597.97 4990.55 278
Zhenlong Yuan, Jinguo Luo, Fei Shen, Zhaoxin Li, Cong Liu, Tianlu Mao, Zhaoqi Wang: DVP-MVS: Synergize Depth-Edge and Visibility Prior for Multi-View Stereo. AAAI2025
PS-CasMVS90.06 4491.92 1684.47 16796.56 658.83 35189.04 8992.74 10391.40 696.12 596.06 2987.23 4995.57 4179.42 13898.74 699.00 2
PEN-MVS90.03 4691.88 1984.48 16696.57 558.88 34888.95 9093.19 8091.62 596.01 796.16 2787.02 5195.60 4078.69 14698.72 998.97 3
OurMVSNet-221017-090.01 4789.74 5790.83 3693.16 8380.37 7491.91 3793.11 8481.10 8795.32 1497.24 1072.94 24594.85 7285.07 6997.78 5997.26 16
DTE-MVSNet89.98 4891.91 1884.21 17696.51 757.84 35988.93 9192.84 9991.92 496.16 496.23 2486.95 5295.99 1279.05 14298.57 1598.80 6
XVG-ACMP-BASELINE89.98 4889.84 5590.41 4394.91 3784.50 4889.49 8293.98 4479.68 10492.09 6593.89 11083.80 8593.10 14882.67 10098.04 4193.64 140
3Dnovator+83.92 289.97 5089.66 5890.92 3591.27 14481.66 6691.25 4394.13 3888.89 1588.83 13494.26 8677.55 17395.86 2384.88 7395.87 13995.24 65
WR-MVS_H89.91 5191.31 3485.71 13496.32 962.39 29489.54 8093.31 7490.21 1295.57 1195.66 3781.42 12995.90 1780.94 11798.80 398.84 5
OPM-MVS89.80 5289.97 5389.27 6494.76 4079.86 7886.76 13292.78 10278.78 11892.51 5993.64 12188.13 3793.84 11684.83 7597.55 7494.10 116
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
mvs_tets89.78 5389.27 6491.30 2993.51 7084.79 4489.89 6990.63 17270.00 24994.55 1996.67 1787.94 4093.59 12884.27 8195.97 12995.52 56
anonymousdsp89.73 5488.88 7492.27 889.82 18086.67 1890.51 5590.20 19369.87 25095.06 1596.14 2884.28 8193.07 14987.68 2396.34 11197.09 20
test_djsdf89.62 5589.01 6891.45 2692.36 10382.98 5791.98 3590.08 19671.54 22894.28 2596.54 1981.57 12794.27 9286.26 4996.49 10597.09 20
XVG-OURS-SEG-HR89.59 5689.37 6290.28 4694.47 4385.95 2786.84 12893.91 4880.07 10086.75 19193.26 12893.64 290.93 21184.60 7890.75 30693.97 119
APD-MVScopyleft89.54 5789.63 5989.26 6592.57 9681.34 6890.19 6293.08 8780.87 9191.13 8293.19 13086.22 6395.97 1482.23 10697.18 8690.45 280
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
jajsoiax89.41 5888.81 7791.19 3293.38 7684.72 4589.70 7290.29 19069.27 25794.39 2196.38 2186.02 6693.52 13283.96 8395.92 13595.34 60
CPTT-MVS89.39 5988.98 7090.63 4095.09 3386.95 1692.09 3392.30 11879.74 10387.50 17592.38 16281.42 12993.28 14183.07 9297.24 8491.67 242
ACMH76.49 1489.34 6091.14 3683.96 18392.50 9970.36 19389.55 7893.84 5381.89 7994.70 1795.44 4490.69 988.31 28883.33 8898.30 2793.20 161
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
testf189.30 6189.12 6589.84 5388.67 21085.64 3590.61 5193.17 8186.02 3893.12 4595.30 4684.94 7389.44 26474.12 21396.10 12494.45 96
APD_test289.30 6189.12 6589.84 5388.67 21085.64 3590.61 5193.17 8186.02 3893.12 4595.30 4684.94 7389.44 26474.12 21396.10 12494.45 96
CP-MVSNet89.27 6390.91 4584.37 16896.34 858.61 35488.66 9892.06 12590.78 795.67 895.17 5181.80 12495.54 4479.00 14398.69 1098.95 4
XVG-OURS89.18 6488.83 7690.23 4794.28 4986.11 2685.91 14793.60 6280.16 9889.13 13193.44 12483.82 8490.98 20883.86 8595.30 16193.60 144
DeepC-MVS82.31 489.15 6589.08 6789.37 6393.64 6879.07 8688.54 10194.20 3173.53 18989.71 11494.82 6085.09 7295.77 3484.17 8298.03 4393.26 159
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
UniMVSNet_ETH3D89.12 6690.72 4884.31 17497.00 264.33 26589.67 7588.38 23188.84 1794.29 2397.57 790.48 1491.26 19972.57 24397.65 6697.34 15
MSP-MVS89.08 6788.16 8491.83 2095.76 1886.14 2592.75 1793.90 4978.43 12389.16 12992.25 17172.03 25996.36 488.21 1390.93 29892.98 176
Zhenlong Yuan, Cong Liu, Fei Shen, Zhaoxin Li, Jingguo luo, Tianlu Mao and Zhaoqi Wang: MSP-MVS: Multi-granularity Segmentation Prior Guided Multi-View Stereo. AAAI2025
SD-MVS88.96 6889.88 5486.22 12191.63 12977.07 11289.82 7093.77 5478.90 11692.88 4992.29 16986.11 6490.22 23886.24 5297.24 8491.36 250
Zhenlong Yuan, Jiakai Cao, Zhaoxin Li, Hao Jiang and Zhaoqi Wang: SD-MVS: Segmentation-driven Deformation Multi-View Stereo with Spherical Refinement and EM optimization. AAAI2024
HPM-MVS++copyleft88.93 6988.45 8090.38 4494.92 3685.85 3189.70 7291.27 15478.20 12686.69 19592.28 17080.36 14295.06 6786.17 5396.49 10590.22 284
Elysia88.71 7088.89 7288.19 8791.26 14572.96 14888.10 10693.59 6384.31 5190.42 9694.10 9674.07 22394.82 7388.19 1495.92 13596.80 27
StellarMVS88.71 7088.89 7288.19 8791.26 14572.96 14888.10 10693.59 6384.31 5190.42 9694.10 9674.07 22394.82 7388.19 1495.92 13596.80 27
test_040288.65 7289.58 6185.88 13092.55 9772.22 16684.01 19389.44 21488.63 2094.38 2295.77 3286.38 6293.59 12879.84 12995.21 16291.82 235
DP-MVS88.60 7389.01 6887.36 9891.30 14277.50 10487.55 11492.97 9587.95 2689.62 11892.87 14684.56 7793.89 11377.65 16296.62 10090.70 270
APD_test188.40 7487.91 8689.88 5289.50 18686.65 2089.98 6691.91 13184.26 5390.87 9293.92 10982.18 11289.29 26873.75 22194.81 18193.70 135
Anonymous2023121188.40 7489.62 6084.73 15890.46 16565.27 25488.86 9293.02 9287.15 3093.05 4797.10 1182.28 11092.02 17876.70 17497.99 4696.88 26
PS-MVSNAJss88.31 7687.90 8789.56 6093.31 7877.96 9987.94 11091.97 12870.73 24094.19 2696.67 1776.94 18594.57 8483.07 9296.28 11396.15 38
OMC-MVS88.19 7787.52 9190.19 4891.94 12081.68 6587.49 11793.17 8176.02 14988.64 13991.22 20884.24 8293.37 13977.97 16097.03 8995.52 56
CS-MVS88.14 7887.67 9089.54 6189.56 18479.18 8590.47 5694.77 1779.37 11084.32 25989.33 27383.87 8394.53 8782.45 10294.89 17794.90 76
TSAR-MVS + MP.88.14 7887.82 8889.09 6995.72 2276.74 11592.49 2691.19 15767.85 28386.63 19694.84 5979.58 15095.96 1587.62 2494.50 19094.56 90
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
tt080588.09 8089.79 5682.98 21493.26 8063.94 26991.10 4689.64 20885.07 4590.91 8891.09 21389.16 2591.87 18382.03 10795.87 13993.13 164
EC-MVSNet88.01 8188.32 8387.09 10089.28 19172.03 16990.31 6096.31 480.88 9085.12 23589.67 26784.47 7995.46 5082.56 10196.26 11693.77 133
RPSCF88.00 8286.93 10591.22 3190.08 17389.30 589.68 7491.11 15879.26 11189.68 11594.81 6382.44 10187.74 29976.54 17988.74 34296.61 32
AllTest87.97 8387.40 9589.68 5691.59 13083.40 5289.50 8195.44 1179.47 10688.00 15893.03 13782.66 9891.47 19170.81 25696.14 12194.16 112
TranMVSNet+NR-MVSNet87.86 8488.76 7885.18 14694.02 6064.13 26684.38 18591.29 15184.88 4892.06 6693.84 11186.45 5993.73 11873.22 23498.66 1197.69 9
nrg03087.85 8588.49 7985.91 12890.07 17569.73 20187.86 11194.20 3174.04 18192.70 5794.66 6485.88 6791.50 19079.72 13197.32 8296.50 34
CNVR-MVS87.81 8687.68 8988.21 8692.87 8977.30 11085.25 16391.23 15577.31 13987.07 18591.47 19882.94 9594.71 7784.67 7796.27 11592.62 191
HQP_MVS87.75 8787.43 9488.70 7793.45 7276.42 11989.45 8393.61 6079.44 10886.55 19792.95 14374.84 21095.22 5980.78 12095.83 14194.46 94
sc_t187.70 8888.94 7183.99 18193.47 7167.15 23285.05 16888.21 23886.81 3291.87 7097.65 585.51 7187.91 29474.22 20897.63 6796.92 25
MM87.64 8987.15 9789.09 6989.51 18576.39 12188.68 9786.76 26984.54 5083.58 27893.78 11473.36 24096.48 287.98 1796.21 11794.41 101
MVSMamba_PlusPlus87.53 9088.86 7583.54 20092.03 11662.26 29891.49 4192.62 10788.07 2588.07 15596.17 2672.24 25495.79 3184.85 7494.16 20392.58 194
NCCC87.36 9186.87 10688.83 7292.32 10678.84 8986.58 13691.09 16078.77 11984.85 24690.89 22480.85 13595.29 5681.14 11595.32 15892.34 211
DeepPCF-MVS81.24 587.28 9286.21 11690.49 4291.48 13984.90 4283.41 21692.38 11470.25 24689.35 12690.68 23482.85 9694.57 8479.55 13595.95 13292.00 230
SixPastTwentyTwo87.20 9387.45 9386.45 11492.52 9869.19 21187.84 11288.05 23981.66 8194.64 1896.53 2065.94 29694.75 7683.02 9496.83 9495.41 58
fmvsm_s_conf0.5_n_987.04 9487.02 10287.08 10189.67 18275.87 12684.60 17889.74 20374.40 17889.92 11093.41 12580.45 14090.63 22686.66 4494.37 19694.73 87
SPE-MVS-test87.00 9586.43 11288.71 7689.46 18777.46 10589.42 8595.73 777.87 13281.64 31987.25 31882.43 10294.53 8777.65 16296.46 10794.14 114
UniMVSNet (Re)86.87 9686.98 10486.55 11293.11 8468.48 22183.80 20392.87 9780.37 9489.61 12091.81 18477.72 16994.18 10075.00 20198.53 1696.99 24
Vis-MVSNetpermissive86.86 9786.58 10987.72 9492.09 11377.43 10787.35 11892.09 12478.87 11784.27 26494.05 9878.35 16193.65 12180.54 12491.58 28592.08 226
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
UniMVSNet_NR-MVSNet86.84 9887.06 10086.17 12492.86 9167.02 23682.55 24391.56 14183.08 6890.92 8691.82 18378.25 16293.99 10774.16 21198.35 2497.49 13
DU-MVS86.80 9986.99 10386.21 12293.24 8167.02 23683.16 22692.21 11981.73 8090.92 8691.97 17677.20 17993.99 10774.16 21198.35 2497.61 10
casdiffmvs_mvgpermissive86.72 10087.51 9284.36 17087.09 25965.22 25584.16 18994.23 2877.89 13091.28 8193.66 12084.35 8092.71 15880.07 12594.87 18095.16 71
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
test_fmvsmconf0.01_n86.68 10186.52 11087.18 9985.94 29678.30 9286.93 12592.20 12065.94 30389.16 12993.16 13283.10 9389.89 25387.81 2094.43 19493.35 152
tt0320-xc86.67 10288.41 8181.44 25693.45 7260.44 32683.96 19588.50 22787.26 2990.90 9097.90 385.61 6886.40 32570.14 26898.01 4597.47 14
IS-MVSNet86.66 10386.82 10886.17 12492.05 11566.87 23991.21 4488.64 22486.30 3789.60 12192.59 15569.22 27794.91 7173.89 21897.89 5596.72 29
tt032086.63 10488.36 8281.41 25793.57 6960.73 32384.37 18688.61 22687.00 3190.75 9397.98 285.54 7086.45 32369.75 27397.70 6497.06 22
v1086.54 10587.10 9984.84 15288.16 22563.28 27686.64 13592.20 12075.42 16392.81 5494.50 7274.05 22694.06 10683.88 8496.28 11397.17 19
pmmvs686.52 10688.06 8581.90 24292.22 10962.28 29784.66 17789.15 21883.54 6389.85 11197.32 888.08 3986.80 31670.43 26597.30 8396.62 31
NormalMVS86.47 10785.32 13989.94 5194.43 4480.42 7288.63 9993.59 6374.56 17385.12 23590.34 24766.19 29394.20 9776.57 17798.44 2095.19 68
PHI-MVS86.38 10885.81 12688.08 8988.44 21977.34 10889.35 8693.05 8873.15 20284.76 24887.70 30778.87 15594.18 10080.67 12296.29 11292.73 183
CSCG86.26 10986.47 11185.60 13690.87 15774.26 13687.98 10991.85 13280.35 9589.54 12488.01 29479.09 15392.13 17475.51 19495.06 16990.41 281
DeepC-MVS_fast80.27 886.23 11085.65 13287.96 9291.30 14276.92 11387.19 12091.99 12770.56 24184.96 24190.69 23380.01 14695.14 6478.37 14995.78 14591.82 235
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
v886.22 11186.83 10784.36 17087.82 23362.35 29686.42 13991.33 15076.78 14392.73 5694.48 7473.41 23793.72 11983.10 9195.41 15497.01 23
Anonymous2024052986.20 11287.13 9883.42 20290.19 17064.55 26284.55 18090.71 16985.85 4089.94 10995.24 5082.13 11390.40 23369.19 28096.40 11095.31 62
fmvsm_s_conf0.5_n_386.19 11387.27 9682.95 21686.91 26770.38 19285.31 16292.61 10875.59 15988.32 15092.87 14682.22 11188.63 28088.80 992.82 24889.83 294
test_fmvsmconf0.1_n86.18 11485.88 12487.08 10185.26 31178.25 9385.82 15191.82 13465.33 31788.55 14192.35 16882.62 10089.80 25586.87 4094.32 19893.18 163
CDPH-MVS86.17 11585.54 13388.05 9192.25 10775.45 12983.85 20092.01 12665.91 30586.19 20891.75 18883.77 8694.98 6977.43 16796.71 9893.73 134
NR-MVSNet86.00 11686.22 11585.34 14393.24 8164.56 26182.21 25790.46 17880.99 8888.42 14691.97 17677.56 17293.85 11472.46 24498.65 1297.61 10
train_agg85.98 11785.28 14088.07 9092.34 10479.70 8083.94 19690.32 18565.79 30784.49 25390.97 21881.93 11993.63 12381.21 11496.54 10390.88 264
KinetiMVS85.95 11886.10 11985.50 14087.56 24369.78 19983.70 20689.83 20280.42 9387.76 16993.24 12973.76 23191.54 18985.03 7193.62 22395.19 68
FC-MVSNet-test85.93 11987.05 10182.58 22792.25 10756.44 37085.75 15293.09 8677.33 13891.94 6994.65 6574.78 21293.41 13875.11 20098.58 1497.88 7
test_fmvsmconf_n85.88 12085.51 13486.99 10484.77 32078.21 9485.40 16191.39 14865.32 31887.72 17191.81 18482.33 10589.78 25686.68 4294.20 20192.99 174
Effi-MVS+-dtu85.82 12183.38 18793.14 487.13 25491.15 387.70 11388.42 23074.57 17283.56 27985.65 34278.49 16094.21 9672.04 24692.88 24494.05 117
TAPA-MVS77.73 1285.71 12284.83 14988.37 8388.78 20979.72 7987.15 12293.50 6669.17 25885.80 21889.56 26880.76 13692.13 17473.21 23995.51 15293.25 160
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
sasdasda85.50 12386.14 11783.58 19687.97 22767.13 23387.55 11494.32 2273.44 19288.47 14487.54 31086.45 5991.06 20675.76 19293.76 21492.54 197
canonicalmvs85.50 12386.14 11783.58 19687.97 22767.13 23387.55 11494.32 2273.44 19288.47 14487.54 31086.45 5991.06 20675.76 19293.76 21492.54 197
fmvsm_s_conf0.5_n_885.48 12585.75 12984.68 16187.10 25769.98 19784.28 18792.68 10474.77 16987.90 16292.36 16773.94 22790.41 23285.95 6092.74 25093.66 136
EPP-MVSNet85.47 12685.04 14486.77 10991.52 13869.37 20691.63 4087.98 24281.51 8387.05 18691.83 18266.18 29595.29 5670.75 25996.89 9195.64 53
GeoE85.45 12785.81 12684.37 16890.08 17367.07 23585.86 15091.39 14872.33 21987.59 17390.25 25284.85 7592.37 16878.00 15891.94 27593.66 136
MVS_030485.37 12884.58 15887.75 9385.28 31073.36 14186.54 13885.71 28677.56 13781.78 31792.47 16070.29 27196.02 1185.59 6395.96 13093.87 125
FIs85.35 12986.27 11482.60 22691.86 12257.31 36385.10 16793.05 8875.83 15491.02 8593.97 10273.57 23392.91 15673.97 21798.02 4497.58 12
test_fmvsmvis_n_192085.22 13085.36 13884.81 15485.80 29876.13 12585.15 16692.32 11761.40 35391.33 7890.85 22783.76 8786.16 33184.31 8093.28 23292.15 224
casdiffmvspermissive85.21 13185.85 12583.31 20586.17 28962.77 28383.03 22893.93 4774.69 17188.21 15292.68 15482.29 10991.89 18277.87 16193.75 21795.27 64
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
baseline85.20 13285.93 12283.02 21286.30 28462.37 29584.55 18093.96 4574.48 17587.12 18092.03 17582.30 10791.94 17978.39 14894.21 20094.74 86
SSM_040485.16 13385.09 14285.36 14290.14 17269.52 20486.17 14491.58 13974.41 17686.55 19791.49 19578.54 15693.97 10973.71 22293.21 23692.59 193
K. test v385.14 13484.73 15186.37 11591.13 15169.63 20385.45 15976.68 37184.06 5692.44 6196.99 1362.03 32394.65 8080.58 12393.24 23394.83 83
mmtdpeth85.13 13585.78 12883.17 21084.65 32274.71 13285.87 14990.35 18477.94 12983.82 27196.96 1577.75 16780.03 39078.44 14796.21 11794.79 85
EI-MVSNet-Vis-set85.12 13684.53 16186.88 10684.01 33572.76 15183.91 19985.18 29680.44 9288.75 13685.49 34680.08 14591.92 18082.02 10890.85 30395.97 44
fmvsm_l_conf0.5_n_385.11 13784.96 14685.56 13787.49 24675.69 12884.71 17590.61 17467.64 28784.88 24492.05 17482.30 10788.36 28683.84 8691.10 29192.62 191
MGCFI-Net85.04 13885.95 12182.31 23587.52 24463.59 27286.23 14393.96 4573.46 19088.07 15587.83 30586.46 5890.87 21676.17 18693.89 21192.47 201
EI-MVSNet-UG-set85.04 13884.44 16486.85 10783.87 33972.52 16083.82 20185.15 29780.27 9788.75 13685.45 34879.95 14791.90 18181.92 11190.80 30596.13 39
X-MVStestdata85.04 13882.70 20592.08 995.64 2486.25 2292.64 2093.33 7185.07 4589.99 10616.05 46786.57 5695.80 2887.35 3297.62 6994.20 108
MSLP-MVS++85.00 14186.03 12081.90 24291.84 12571.56 17986.75 13393.02 9275.95 15287.12 18089.39 27177.98 16489.40 26777.46 16594.78 18284.75 370
F-COLMAP84.97 14283.42 18689.63 5892.39 10283.40 5288.83 9391.92 13073.19 20180.18 34189.15 27777.04 18393.28 14165.82 31392.28 26492.21 220
SSM_040784.89 14384.85 14885.01 15089.13 19568.97 21485.60 15691.58 13974.41 17685.68 21991.49 19578.54 15693.69 12073.71 22293.47 22592.38 208
balanced_conf0384.80 14485.40 13683.00 21388.95 20261.44 30690.42 5992.37 11671.48 23088.72 13893.13 13370.16 27395.15 6379.26 14094.11 20492.41 203
3Dnovator80.37 784.80 14484.71 15485.06 14986.36 28274.71 13288.77 9590.00 19875.65 15784.96 24193.17 13174.06 22591.19 20178.28 15291.09 29289.29 304
SymmetryMVS84.79 14683.54 18188.55 7992.44 10180.42 7288.63 9982.37 33174.56 17385.12 23590.34 24766.19 29394.20 9776.57 17795.68 14991.03 258
IterMVS-LS84.73 14784.98 14583.96 18387.35 24863.66 27083.25 22189.88 20176.06 14789.62 11892.37 16573.40 23992.52 16378.16 15594.77 18495.69 51
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
MVS_111021_HR84.63 14884.34 16885.49 14190.18 17175.86 12779.23 30987.13 25973.35 19485.56 22689.34 27283.60 8990.50 22976.64 17694.05 20890.09 290
HQP-MVS84.61 14984.06 17386.27 11891.19 14770.66 18784.77 17092.68 10473.30 19780.55 33390.17 25772.10 25594.61 8277.30 16994.47 19293.56 148
v119284.57 15084.69 15684.21 17687.75 23562.88 28083.02 22991.43 14569.08 26089.98 10890.89 22472.70 24993.62 12682.41 10394.97 17496.13 39
fmvsm_s_conf0.5_n_584.56 15184.71 15484.11 17987.92 23072.09 16884.80 16988.64 22464.43 32788.77 13591.78 18678.07 16387.95 29385.85 6192.18 26892.30 213
FMVSNet184.55 15285.45 13581.85 24490.27 16961.05 31486.83 12988.27 23578.57 12289.66 11795.64 3875.43 20290.68 22369.09 28195.33 15793.82 128
v114484.54 15384.72 15384.00 18087.67 23962.55 28782.97 23190.93 16570.32 24589.80 11290.99 21773.50 23493.48 13481.69 11394.65 18895.97 44
Gipumacopyleft84.44 15486.33 11378.78 30184.20 33273.57 14089.55 7890.44 17984.24 5484.38 25694.89 5776.35 19880.40 38776.14 18796.80 9682.36 408
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
fmvsm_s_conf0.5_n_484.38 15584.27 16984.74 15787.25 25070.84 18683.55 21188.45 22968.64 26986.29 20791.31 20474.97 20888.42 28487.87 1990.07 32194.95 75
MCST-MVS84.36 15683.93 17785.63 13591.59 13071.58 17783.52 21292.13 12261.82 34683.96 26989.75 26579.93 14893.46 13578.33 15194.34 19791.87 234
VDDNet84.35 15785.39 13781.25 25995.13 3259.32 34085.42 16081.11 34286.41 3687.41 17696.21 2573.61 23290.61 22766.33 30696.85 9293.81 131
ETV-MVS84.31 15883.91 17885.52 13888.58 21570.40 19184.50 18493.37 6878.76 12084.07 26778.72 42180.39 14195.13 6573.82 22092.98 24291.04 257
v124084.30 15984.51 16283.65 19387.65 24061.26 31082.85 23591.54 14267.94 28090.68 9590.65 23871.71 26393.64 12282.84 9794.78 18296.07 41
MVS_111021_LR84.28 16083.76 17985.83 13289.23 19383.07 5580.99 27883.56 31972.71 21186.07 21189.07 27981.75 12686.19 33077.11 17193.36 22888.24 323
h-mvs3384.25 16182.76 20488.72 7591.82 12782.60 6084.00 19484.98 30371.27 23186.70 19390.55 24363.04 32093.92 11278.26 15394.20 20189.63 296
v14419284.24 16284.41 16583.71 19287.59 24261.57 30582.95 23291.03 16167.82 28489.80 11290.49 24473.28 24193.51 13381.88 11294.89 17796.04 43
dcpmvs_284.23 16385.14 14181.50 25488.61 21461.98 30282.90 23493.11 8468.66 26892.77 5592.39 16178.50 15987.63 30276.99 17392.30 26194.90 76
v192192084.23 16384.37 16783.79 18887.64 24161.71 30482.91 23391.20 15667.94 28090.06 10390.34 24772.04 25893.59 12882.32 10494.91 17596.07 41
VDD-MVS84.23 16384.58 15883.20 20891.17 15065.16 25783.25 22184.97 30479.79 10287.18 17994.27 8374.77 21390.89 21469.24 27796.54 10393.55 150
v2v48284.09 16684.24 17083.62 19487.13 25461.40 30782.71 23889.71 20672.19 22289.55 12291.41 19970.70 26993.20 14381.02 11693.76 21496.25 37
EG-PatchMatch MVS84.08 16784.11 17283.98 18292.22 10972.61 15782.20 25987.02 26572.63 21288.86 13291.02 21678.52 15891.11 20473.41 22991.09 29288.21 324
fmvsm_s_conf0.5_n_684.05 16884.14 17183.81 18687.75 23571.17 18283.42 21591.10 15967.90 28284.53 25190.70 23273.01 24488.73 27885.09 6893.72 21991.53 247
DP-MVS Recon84.05 16883.22 19086.52 11391.73 12875.27 13083.23 22392.40 11272.04 22482.04 30888.33 29077.91 16693.95 11166.17 30795.12 16790.34 283
viewmacassd2359aftdt84.04 17084.78 15081.81 24786.43 27660.32 32881.95 26192.82 10071.56 22786.06 21292.98 13981.79 12590.28 23476.18 18593.24 23394.82 84
TransMVSNet (Re)84.02 17185.74 13078.85 30091.00 15455.20 38282.29 25387.26 25479.65 10588.38 14895.52 4183.00 9486.88 31467.97 29596.60 10194.45 96
Baseline_NR-MVSNet84.00 17285.90 12378.29 31291.47 14053.44 39482.29 25387.00 26879.06 11489.55 12295.72 3677.20 17986.14 33272.30 24598.51 1795.28 63
fmvsm_l_conf0.5_n_983.98 17384.46 16382.53 23086.11 29270.65 18982.45 24889.17 21767.72 28686.74 19291.49 19579.20 15185.86 34184.71 7692.60 25491.07 256
TSAR-MVS + GP.83.95 17482.69 20687.72 9489.27 19281.45 6783.72 20581.58 34074.73 17085.66 22286.06 33772.56 25192.69 16075.44 19695.21 16289.01 317
LuminaMVS83.94 17583.51 18285.23 14489.78 18171.74 17284.76 17387.27 25372.60 21389.31 12790.60 24264.04 30990.95 20979.08 14194.11 20492.99 174
alignmvs83.94 17583.98 17583.80 18787.80 23467.88 22884.54 18291.42 14773.27 20088.41 14787.96 29572.33 25290.83 21776.02 18994.11 20492.69 187
Effi-MVS+83.90 17784.01 17483.57 19887.22 25265.61 25386.55 13792.40 11278.64 12181.34 32484.18 36783.65 8892.93 15474.22 20887.87 35692.17 223
fmvsm_s_conf0.1_n_283.82 17883.49 18384.84 15285.99 29570.19 19580.93 27987.58 24967.26 29387.94 16192.37 16571.40 26588.01 29086.03 5591.87 27696.31 36
mvs5depth83.82 17884.54 16081.68 25082.23 36468.65 21986.89 12689.90 20080.02 10187.74 17097.86 464.19 30882.02 37576.37 18195.63 15194.35 103
CANet83.79 18082.85 20386.63 11086.17 28972.21 16783.76 20491.43 14577.24 14074.39 39687.45 31475.36 20395.42 5277.03 17292.83 24792.25 219
pm-mvs183.69 18184.95 14779.91 28690.04 17759.66 33782.43 24987.44 25075.52 16187.85 16595.26 4981.25 13185.65 34568.74 28796.04 12694.42 100
AdaColmapbinary83.66 18283.69 18083.57 19890.05 17672.26 16586.29 14190.00 19878.19 12781.65 31887.16 32083.40 9194.24 9561.69 34994.76 18584.21 380
MIMVSNet183.63 18384.59 15780.74 27094.06 5962.77 28382.72 23784.53 31177.57 13690.34 9995.92 3176.88 19185.83 34261.88 34797.42 7993.62 142
fmvsm_s_conf0.5_n_283.62 18483.29 18984.62 16285.43 30870.18 19680.61 28587.24 25567.14 29487.79 16791.87 17871.79 26287.98 29286.00 5991.77 27995.71 50
test_fmvsm_n_192083.60 18582.89 20085.74 13385.22 31277.74 10284.12 19190.48 17659.87 37386.45 20691.12 21275.65 20085.89 33982.28 10590.87 30193.58 146
WR-MVS83.56 18684.40 16681.06 26493.43 7554.88 38378.67 31885.02 30181.24 8590.74 9491.56 19372.85 24691.08 20568.00 29498.04 4197.23 17
CNLPA83.55 18783.10 19584.90 15189.34 19083.87 5084.54 18288.77 22179.09 11383.54 28088.66 28774.87 20981.73 37766.84 30192.29 26389.11 310
viewcassd2359sk1183.53 18883.96 17682.25 23686.97 26661.13 31280.80 28393.22 7970.97 23785.36 23091.08 21481.84 12391.29 19874.79 20390.58 31794.33 105
LCM-MVSNet-Re83.48 18985.06 14378.75 30285.94 29655.75 37680.05 29194.27 2576.47 14496.09 694.54 7183.31 9289.75 25959.95 36094.89 17790.75 267
hse-mvs283.47 19081.81 22188.47 8091.03 15382.27 6182.61 23983.69 31771.27 23186.70 19386.05 33863.04 32092.41 16678.26 15393.62 22390.71 269
V4283.47 19083.37 18883.75 19083.16 35863.33 27581.31 27290.23 19269.51 25490.91 8890.81 22974.16 22292.29 17280.06 12690.22 31995.62 54
VPA-MVSNet83.47 19084.73 15179.69 29190.29 16857.52 36281.30 27488.69 22376.29 14587.58 17494.44 7580.60 13987.20 30866.60 30496.82 9594.34 104
mamba_040883.44 19382.88 20185.11 14789.13 19568.97 21472.73 39391.28 15272.90 20585.68 21990.61 24076.78 19293.97 10973.37 23193.47 22592.38 208
PAPM_NR83.23 19483.19 19283.33 20490.90 15665.98 24988.19 10490.78 16878.13 12880.87 32987.92 29973.49 23692.42 16570.07 26988.40 34591.60 244
CLD-MVS83.18 19582.64 20784.79 15589.05 19867.82 22977.93 32892.52 11068.33 27285.07 23881.54 39682.06 11692.96 15269.35 27697.91 5493.57 147
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
ANet_high83.17 19685.68 13175.65 35081.24 37645.26 43879.94 29392.91 9683.83 5791.33 7896.88 1680.25 14385.92 33568.89 28495.89 13895.76 48
FA-MVS(test-final)83.13 19783.02 19683.43 20186.16 29166.08 24888.00 10888.36 23275.55 16085.02 23992.75 15265.12 30292.50 16474.94 20291.30 28991.72 239
114514_t83.10 19882.54 21084.77 15692.90 8869.10 21386.65 13490.62 17354.66 40581.46 32190.81 22976.98 18494.38 9072.62 24296.18 11990.82 266
RRT-MVS82.97 19983.44 18481.57 25285.06 31558.04 35787.20 11990.37 18277.88 13188.59 14093.70 11963.17 31793.05 15076.49 18088.47 34493.62 142
viewmanbaseed2359cas82.95 20083.43 18581.52 25385.18 31360.03 33381.36 27192.38 11469.55 25384.84 24791.38 20079.85 14990.09 24774.22 20892.09 27094.43 99
BP-MVS182.81 20181.67 22386.23 11987.88 23268.53 22086.06 14684.36 31275.65 15785.14 23490.19 25445.84 40994.42 8985.18 6794.72 18695.75 49
UGNet82.78 20281.64 22486.21 12286.20 28876.24 12386.86 12785.68 28777.07 14173.76 40092.82 14869.64 27491.82 18569.04 28393.69 22090.56 277
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
LF4IMVS82.75 20381.93 21985.19 14582.08 36580.15 7685.53 15788.76 22268.01 27785.58 22587.75 30671.80 26186.85 31574.02 21693.87 21288.58 320
EI-MVSNet82.61 20482.42 21283.20 20883.25 35563.66 27083.50 21385.07 29876.06 14786.55 19785.10 35473.41 23790.25 23578.15 15790.67 31295.68 52
QAPM82.59 20582.59 20982.58 22786.44 27566.69 24089.94 6890.36 18367.97 27984.94 24392.58 15772.71 24892.18 17370.63 26287.73 35988.85 318
fmvsm_s_conf0.1_n_a82.58 20681.93 21984.50 16587.68 23873.35 14286.14 14577.70 36061.64 35185.02 23991.62 19077.75 16786.24 32782.79 9887.07 36793.91 123
Fast-Effi-MVS+-dtu82.54 20781.41 23385.90 12985.60 30376.53 11883.07 22789.62 21073.02 20479.11 35183.51 37280.74 13790.24 23768.76 28689.29 33290.94 261
MVS_Test82.47 20883.22 19080.22 28282.62 36357.75 36182.54 24491.96 12971.16 23582.89 29192.52 15977.41 17490.50 22980.04 12787.84 35892.40 205
viewdifsd2359ckpt1182.46 20982.98 19880.88 26783.53 34261.00 31779.46 30285.97 28269.48 25587.89 16391.31 20482.10 11488.61 28174.28 20692.86 24593.02 170
viewmsd2359difaftdt82.46 20982.99 19780.88 26783.52 34361.00 31779.46 30285.97 28269.48 25587.89 16391.31 20482.10 11488.61 28174.28 20692.86 24593.02 170
v14882.31 21182.48 21181.81 24785.59 30459.66 33781.47 26986.02 28072.85 20788.05 15790.65 23870.73 26890.91 21375.15 19991.79 27794.87 78
API-MVS82.28 21282.61 20881.30 25886.29 28569.79 19888.71 9687.67 24878.42 12482.15 30484.15 36877.98 16491.59 18865.39 31692.75 24982.51 407
MVSFormer82.23 21381.57 22984.19 17885.54 30569.26 20891.98 3590.08 19671.54 22876.23 37685.07 35758.69 34594.27 9286.26 4988.77 34089.03 315
viewdifsd2359ckpt1382.22 21481.98 21882.95 21685.48 30764.44 26383.17 22592.11 12365.97 30283.72 27489.73 26677.60 17190.80 21970.61 26389.42 33093.59 145
fmvsm_s_conf0.5_n_a82.21 21581.51 23284.32 17386.56 27273.35 14285.46 15877.30 36461.81 34784.51 25290.88 22677.36 17586.21 32982.72 9986.97 37293.38 151
EIA-MVS82.19 21681.23 24085.10 14887.95 22969.17 21283.22 22493.33 7170.42 24278.58 35679.77 41277.29 17694.20 9771.51 25288.96 33891.93 233
GDP-MVS82.17 21780.85 24886.15 12688.65 21268.95 21785.65 15593.02 9268.42 27083.73 27389.54 26945.07 42094.31 9179.66 13393.87 21295.19 68
fmvsm_s_conf0.1_n82.17 21781.59 22783.94 18586.87 27071.57 17885.19 16577.42 36362.27 34584.47 25591.33 20276.43 19585.91 33783.14 8987.14 36594.33 105
PCF-MVS74.62 1582.15 21980.92 24685.84 13189.43 18872.30 16480.53 28691.82 13457.36 38987.81 16689.92 26277.67 17093.63 12358.69 36595.08 16891.58 245
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
PLCcopyleft73.85 1682.09 22080.31 25587.45 9790.86 15880.29 7585.88 14890.65 17168.17 27576.32 37586.33 33273.12 24392.61 16261.40 35290.02 32389.44 299
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
fmvsm_l_conf0.5_n82.06 22181.54 23183.60 19583.94 33673.90 13883.35 21886.10 27658.97 37583.80 27290.36 24674.23 22086.94 31382.90 9590.22 31989.94 292
fmvsm_s_conf0.5_n_782.04 22282.05 21682.01 24086.98 26571.07 18378.70 31689.45 21368.07 27678.14 35891.61 19174.19 22185.92 33579.61 13491.73 28089.05 314
GBi-Net82.02 22382.07 21481.85 24486.38 27961.05 31486.83 12988.27 23572.43 21486.00 21395.64 3863.78 31390.68 22365.95 30993.34 22993.82 128
test182.02 22382.07 21481.85 24486.38 27961.05 31486.83 12988.27 23572.43 21486.00 21395.64 3863.78 31390.68 22365.95 30993.34 22993.82 128
OpenMVScopyleft76.72 1381.98 22582.00 21781.93 24184.42 32768.22 22388.50 10289.48 21266.92 29781.80 31591.86 17972.59 25090.16 24171.19 25591.25 29087.40 340
KD-MVS_self_test81.93 22683.14 19478.30 31184.75 32152.75 39880.37 28889.42 21570.24 24790.26 10193.39 12674.55 21986.77 31768.61 28996.64 9995.38 59
fmvsm_s_conf0.5_n81.91 22781.30 23783.75 19086.02 29471.56 17984.73 17477.11 36762.44 34284.00 26890.68 23476.42 19685.89 33983.14 8987.11 36693.81 131
SDMVSNet81.90 22883.17 19378.10 31588.81 20762.45 29376.08 36286.05 27973.67 18683.41 28193.04 13582.35 10480.65 38470.06 27095.03 17091.21 252
tfpnnormal81.79 22982.95 19978.31 31088.93 20355.40 37880.83 28282.85 32676.81 14285.90 21794.14 9374.58 21786.51 32166.82 30295.68 14993.01 173
AstraMVS81.67 23081.40 23482.48 23287.06 26266.47 24381.41 27081.68 33768.78 26588.00 15890.95 22265.70 29887.86 29876.66 17592.38 25893.12 166
c3_l81.64 23181.59 22781.79 24980.86 38259.15 34578.61 31990.18 19468.36 27187.20 17887.11 32269.39 27591.62 18778.16 15594.43 19494.60 89
guyue81.57 23281.37 23682.15 23786.39 27766.13 24781.54 26883.21 32169.79 25187.77 16889.95 26065.36 30187.64 30175.88 19092.49 25692.67 188
PVSNet_Blended_VisFu81.55 23380.49 25384.70 16091.58 13373.24 14684.21 18891.67 13862.86 33680.94 32787.16 32067.27 28792.87 15769.82 27288.94 33987.99 330
fmvsm_l_conf0.5_n_a81.46 23480.87 24783.25 20683.73 34173.21 14783.00 23085.59 28958.22 38182.96 29090.09 25972.30 25386.65 31981.97 11089.95 32489.88 293
SSM_0407281.44 23582.88 20177.10 33089.13 19568.97 21472.73 39391.28 15272.90 20585.68 21990.61 24076.78 19269.94 42773.37 23193.47 22592.38 208
DELS-MVS81.44 23581.25 23882.03 23984.27 33162.87 28176.47 35692.49 11170.97 23781.64 31983.83 36975.03 20692.70 15974.29 20592.22 26790.51 279
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
FMVSNet281.31 23781.61 22680.41 27886.38 27958.75 35283.93 19886.58 27172.43 21487.65 17292.98 13963.78 31390.22 23866.86 29993.92 21092.27 217
TinyColmap81.25 23882.34 21377.99 31885.33 30960.68 32482.32 25288.33 23371.26 23386.97 18792.22 17377.10 18286.98 31262.37 34195.17 16486.31 353
diffmvs_AUTHOR81.24 23981.55 23080.30 28080.61 38760.22 32977.98 32790.48 17667.77 28583.34 28389.50 27074.69 21587.42 30478.78 14590.81 30493.27 157
AUN-MVS81.18 24078.78 27888.39 8290.93 15582.14 6282.51 24583.67 31864.69 32680.29 33785.91 34151.07 38492.38 16776.29 18493.63 22290.65 274
IMVS_040781.08 24181.23 24080.62 27585.76 29962.46 28982.46 24687.91 24365.23 31982.12 30587.92 29977.27 17790.18 24071.67 24890.74 30789.20 305
tttt051781.07 24279.58 26885.52 13888.99 20166.45 24487.03 12475.51 37973.76 18588.32 15090.20 25337.96 44194.16 10479.36 13995.13 16595.93 47
Fast-Effi-MVS+81.04 24380.57 25082.46 23387.50 24563.22 27778.37 32289.63 20968.01 27781.87 31182.08 39082.31 10692.65 16167.10 29888.30 35191.51 248
BH-untuned80.96 24480.99 24480.84 26988.55 21668.23 22280.33 28988.46 22872.79 21086.55 19786.76 32674.72 21491.77 18661.79 34888.99 33782.52 406
IMVS_040380.93 24581.00 24380.72 27285.76 29962.46 28981.82 26287.91 24365.23 31982.07 30787.92 29975.91 19990.50 22971.67 24890.74 30789.20 305
eth_miper_zixun_eth80.84 24680.22 25982.71 22481.41 37460.98 31977.81 33090.14 19567.31 29286.95 18887.24 31964.26 30692.31 17075.23 19891.61 28394.85 82
xiu_mvs_v1_base_debu80.84 24680.14 26182.93 21988.31 22071.73 17379.53 29887.17 25665.43 31379.59 34382.73 38476.94 18590.14 24473.22 23488.33 34786.90 347
xiu_mvs_v1_base80.84 24680.14 26182.93 21988.31 22071.73 17379.53 29887.17 25665.43 31379.59 34382.73 38476.94 18590.14 24473.22 23488.33 34786.90 347
xiu_mvs_v1_base_debi80.84 24680.14 26182.93 21988.31 22071.73 17379.53 29887.17 25665.43 31379.59 34382.73 38476.94 18590.14 24473.22 23488.33 34786.90 347
IterMVS-SCA-FT80.64 25079.41 26984.34 17283.93 33769.66 20276.28 35881.09 34372.43 21486.47 20490.19 25460.46 33093.15 14677.45 16686.39 37890.22 284
BH-RMVSNet80.53 25180.22 25981.49 25587.19 25366.21 24677.79 33186.23 27474.21 18083.69 27588.50 28873.25 24290.75 22063.18 33787.90 35587.52 338
VortexMVS80.51 25280.63 24980.15 28483.36 35161.82 30380.63 28488.00 24167.11 29587.23 17789.10 27863.98 31088.00 29173.63 22692.63 25390.64 275
Anonymous20240521180.51 25281.19 24278.49 30788.48 21757.26 36476.63 35182.49 32981.21 8684.30 26292.24 17267.99 28386.24 32762.22 34295.13 16591.98 232
DIV-MVS_self_test80.43 25480.23 25781.02 26579.99 39259.25 34277.07 34487.02 26567.38 28986.19 20889.22 27463.09 31890.16 24176.32 18295.80 14393.66 136
cl____80.42 25580.23 25781.02 26579.99 39259.25 34277.07 34487.02 26567.37 29086.18 21089.21 27563.08 31990.16 24176.31 18395.80 14393.65 139
diffmvspermissive80.40 25680.48 25480.17 28379.02 40560.04 33177.54 33590.28 19166.65 30082.40 29887.33 31773.50 23487.35 30677.98 15989.62 32893.13 164
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
EPNet80.37 25778.41 28686.23 11976.75 41973.28 14487.18 12177.45 36276.24 14668.14 43088.93 28165.41 30093.85 11469.47 27596.12 12391.55 246
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
miper_ehance_all_eth80.34 25880.04 26481.24 26179.82 39558.95 34777.66 33289.66 20765.75 31085.99 21685.11 35368.29 28291.42 19576.03 18892.03 27193.33 153
MG-MVS80.32 25980.94 24578.47 30888.18 22352.62 40182.29 25385.01 30272.01 22579.24 35092.54 15869.36 27693.36 14070.65 26189.19 33589.45 298
mvsmamba80.30 26078.87 27584.58 16488.12 22667.55 23092.35 3084.88 30563.15 33485.33 23190.91 22350.71 38695.20 6266.36 30587.98 35490.99 259
VPNet80.25 26181.68 22275.94 34692.46 10047.98 42576.70 34981.67 33873.45 19184.87 24592.82 14874.66 21686.51 32161.66 35096.85 9293.33 153
MAR-MVS80.24 26278.74 28084.73 15886.87 27078.18 9585.75 15287.81 24765.67 31277.84 36278.50 42273.79 23090.53 22861.59 35190.87 30185.49 363
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
PM-MVS80.20 26379.00 27483.78 18988.17 22486.66 1981.31 27266.81 43569.64 25288.33 14990.19 25464.58 30383.63 36671.99 24790.03 32281.06 426
Anonymous2024052180.18 26481.25 23876.95 33283.15 35960.84 32182.46 24685.99 28168.76 26686.78 18993.73 11859.13 34277.44 40173.71 22297.55 7492.56 195
LFMVS80.15 26580.56 25178.89 29989.19 19455.93 37285.22 16473.78 39182.96 6984.28 26392.72 15357.38 35490.07 24963.80 33195.75 14690.68 271
DPM-MVS80.10 26679.18 27382.88 22290.71 16169.74 20078.87 31490.84 16660.29 36975.64 38585.92 34067.28 28693.11 14771.24 25491.79 27785.77 359
MSDG80.06 26779.99 26680.25 28183.91 33868.04 22777.51 33689.19 21677.65 13481.94 30983.45 37476.37 19786.31 32663.31 33686.59 37586.41 351
FE-MVS79.98 26878.86 27683.36 20386.47 27466.45 24489.73 7184.74 30972.80 20984.22 26691.38 20044.95 42193.60 12763.93 32991.50 28690.04 291
sd_testset79.95 26981.39 23575.64 35188.81 20758.07 35676.16 36182.81 32773.67 18683.41 28193.04 13580.96 13477.65 40058.62 36695.03 17091.21 252
ab-mvs79.67 27080.56 25176.99 33188.48 21756.93 36684.70 17686.06 27868.95 26380.78 33093.08 13475.30 20484.62 35356.78 37590.90 29989.43 300
VNet79.31 27180.27 25676.44 34087.92 23053.95 39075.58 36884.35 31374.39 17982.23 30290.72 23172.84 24784.39 35860.38 35893.98 20990.97 260
thisisatest053079.07 27277.33 29684.26 17587.13 25464.58 26083.66 20875.95 37468.86 26485.22 23387.36 31638.10 43893.57 13175.47 19594.28 19994.62 88
cl2278.97 27378.21 28881.24 26177.74 40959.01 34677.46 33987.13 25965.79 30784.32 25985.10 35458.96 34490.88 21575.36 19792.03 27193.84 126
patch_mono-278.89 27479.39 27077.41 32784.78 31968.11 22575.60 36683.11 32360.96 36179.36 34789.89 26375.18 20572.97 41673.32 23392.30 26191.15 254
RPMNet78.88 27578.28 28780.68 27479.58 39662.64 28582.58 24194.16 3374.80 16875.72 38392.59 15548.69 39395.56 4273.48 22882.91 41483.85 385
PAPR78.84 27678.10 28981.07 26385.17 31460.22 32982.21 25790.57 17562.51 33875.32 38984.61 36274.99 20792.30 17159.48 36388.04 35390.68 271
viewmambaseed2359dif78.80 27778.47 28579.78 28780.26 39159.28 34177.31 34187.13 25960.42 36782.37 29988.67 28674.58 21787.87 29767.78 29787.73 35992.19 221
PVSNet_BlendedMVS78.80 27777.84 29081.65 25184.43 32563.41 27379.49 30190.44 17961.70 35075.43 38687.07 32369.11 27891.44 19360.68 35692.24 26590.11 289
FMVSNet378.80 27778.55 28279.57 29382.89 36256.89 36881.76 26385.77 28569.04 26186.00 21390.44 24551.75 38290.09 24765.95 30993.34 22991.72 239
test_yl78.71 28078.51 28379.32 29684.32 32958.84 34978.38 32085.33 29375.99 15082.49 29686.57 32858.01 34890.02 25162.74 33892.73 25189.10 311
DCV-MVSNet78.71 28078.51 28379.32 29684.32 32958.84 34978.38 32085.33 29375.99 15082.49 29686.57 32858.01 34890.02 25162.74 33892.73 25189.10 311
test111178.53 28278.85 27777.56 32492.22 10947.49 42782.61 23969.24 42372.43 21485.28 23294.20 8951.91 38090.07 24965.36 31796.45 10895.11 72
FE-MVSNET78.46 28379.36 27175.75 34886.53 27354.53 38578.03 32485.35 29269.01 26285.41 22990.68 23464.27 30585.73 34362.59 34092.35 26087.00 346
icg_test_0407_278.46 28379.68 26774.78 35885.76 29962.46 28968.51 42287.91 24365.23 31982.12 30587.92 29977.27 17772.67 41771.67 24890.74 30789.20 305
ECVR-MVScopyleft78.44 28578.63 28177.88 32091.85 12348.95 42183.68 20769.91 41972.30 22084.26 26594.20 8951.89 38189.82 25463.58 33296.02 12794.87 78
pmmvs-eth3d78.42 28677.04 29982.57 22987.44 24774.41 13580.86 28179.67 35155.68 39884.69 24990.31 25160.91 32885.42 34662.20 34391.59 28487.88 334
mvs_anonymous78.13 28778.76 27976.23 34579.24 40250.31 41778.69 31784.82 30761.60 35283.09 28992.82 14873.89 22987.01 30968.33 29386.41 37791.37 249
TAMVS78.08 28876.36 30683.23 20790.62 16272.87 15079.08 31080.01 35061.72 34981.35 32386.92 32563.96 31288.78 27650.61 41493.01 24188.04 329
miper_enhance_ethall77.83 28976.93 30080.51 27676.15 42658.01 35875.47 37088.82 22058.05 38383.59 27780.69 40064.41 30491.20 20073.16 24092.03 27192.33 212
Vis-MVSNet (Re-imp)77.82 29077.79 29177.92 31988.82 20651.29 41183.28 21971.97 40774.04 18182.23 30289.78 26457.38 35489.41 26657.22 37495.41 15493.05 169
CANet_DTU77.81 29177.05 29880.09 28581.37 37559.90 33583.26 22088.29 23469.16 25967.83 43383.72 37060.93 32789.47 26169.22 27989.70 32790.88 264
OpenMVS_ROBcopyleft70.19 1777.77 29277.46 29378.71 30384.39 32861.15 31181.18 27682.52 32862.45 34183.34 28387.37 31566.20 29288.66 27964.69 32485.02 39486.32 352
SSC-MVS77.55 29381.64 22465.29 42490.46 16520.33 47173.56 38668.28 42585.44 4188.18 15494.64 6870.93 26781.33 37971.25 25392.03 27194.20 108
MDA-MVSNet-bldmvs77.47 29476.90 30179.16 29879.03 40464.59 25966.58 43475.67 37773.15 20288.86 13288.99 28066.94 28881.23 38064.71 32388.22 35291.64 243
jason77.42 29575.75 31282.43 23487.10 25769.27 20777.99 32681.94 33551.47 42577.84 36285.07 35760.32 33289.00 27070.74 26089.27 33489.03 315
jason: jason.
CDS-MVSNet77.32 29675.40 31683.06 21189.00 20072.48 16177.90 32982.17 33360.81 36278.94 35383.49 37359.30 34088.76 27754.64 39492.37 25987.93 333
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
IMVS_040477.24 29777.75 29275.73 34985.76 29962.46 28970.84 40887.91 24365.23 31972.21 40887.92 29967.48 28575.53 40971.67 24890.74 30789.20 305
xiu_mvs_v2_base77.19 29876.75 30378.52 30687.01 26361.30 30975.55 36987.12 26361.24 35874.45 39578.79 42077.20 17990.93 21164.62 32684.80 40183.32 394
MVSTER77.09 29975.70 31381.25 25975.27 43461.08 31377.49 33885.07 29860.78 36386.55 19788.68 28443.14 43090.25 23573.69 22590.67 31292.42 202
PS-MVSNAJ77.04 30076.53 30578.56 30587.09 25961.40 30775.26 37187.13 25961.25 35774.38 39777.22 43476.94 18590.94 21064.63 32584.83 40083.35 393
IterMVS76.91 30176.34 30778.64 30480.91 38064.03 26776.30 35779.03 35464.88 32583.11 28789.16 27659.90 33684.46 35668.61 28985.15 39287.42 339
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
D2MVS76.84 30275.67 31480.34 27980.48 38962.16 30173.50 38784.80 30857.61 38782.24 30187.54 31051.31 38387.65 30070.40 26693.19 23791.23 251
CL-MVSNet_self_test76.81 30377.38 29575.12 35486.90 26851.34 40973.20 39080.63 34768.30 27381.80 31588.40 28966.92 28980.90 38155.35 38894.90 17693.12 166
TR-MVS76.77 30475.79 31179.72 29086.10 29365.79 25177.14 34283.02 32465.20 32381.40 32282.10 38866.30 29190.73 22255.57 38585.27 38882.65 401
MonoMVSNet76.66 30577.26 29774.86 35679.86 39454.34 38786.26 14286.08 27771.08 23685.59 22488.68 28453.95 37285.93 33463.86 33080.02 43084.32 376
USDC76.63 30676.73 30476.34 34283.46 34657.20 36580.02 29288.04 24052.14 42183.65 27691.25 20763.24 31686.65 31954.66 39394.11 20485.17 365
BH-w/o76.57 30776.07 31078.10 31586.88 26965.92 25077.63 33386.33 27265.69 31180.89 32879.95 40968.97 28090.74 22153.01 40485.25 38977.62 437
Patchmtry76.56 30877.46 29373.83 36479.37 40146.60 43182.41 25076.90 36873.81 18485.56 22692.38 16248.07 39683.98 36363.36 33595.31 16090.92 262
PVSNet_Blended76.49 30975.40 31679.76 28984.43 32563.41 27375.14 37290.44 17957.36 38975.43 38678.30 42369.11 27891.44 19360.68 35687.70 36184.42 375
miper_lstm_enhance76.45 31076.10 30977.51 32576.72 42060.97 32064.69 43885.04 30063.98 33083.20 28688.22 29156.67 35878.79 39773.22 23493.12 23892.78 182
lupinMVS76.37 31174.46 32582.09 23885.54 30569.26 20876.79 34780.77 34650.68 43276.23 37682.82 38258.69 34588.94 27169.85 27188.77 34088.07 326
cascas76.29 31274.81 32180.72 27284.47 32462.94 27973.89 38487.34 25155.94 39675.16 39176.53 43963.97 31191.16 20265.00 32090.97 29788.06 328
SD_040376.08 31376.77 30273.98 36287.08 26149.45 42083.62 20984.68 31063.31 33175.13 39287.47 31371.85 26084.56 35449.97 41687.86 35787.94 332
WB-MVS76.06 31480.01 26564.19 42789.96 17920.58 47072.18 39768.19 42683.21 6586.46 20593.49 12370.19 27278.97 39565.96 30890.46 31893.02 170
thres600view775.97 31575.35 31877.85 32287.01 26351.84 40780.45 28773.26 39675.20 16583.10 28886.31 33445.54 41189.05 26955.03 39192.24 26592.66 189
GA-MVS75.83 31674.61 32279.48 29581.87 36759.25 34273.42 38882.88 32568.68 26779.75 34281.80 39350.62 38789.46 26266.85 30085.64 38589.72 295
MVP-Stereo75.81 31773.51 33482.71 22489.35 18973.62 13980.06 29085.20 29560.30 36873.96 39887.94 29657.89 35289.45 26352.02 40874.87 44885.06 367
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
test_fmvs375.72 31875.20 31977.27 32875.01 43769.47 20578.93 31184.88 30546.67 43987.08 18487.84 30450.44 38971.62 42277.42 16888.53 34390.72 268
thres100view90075.45 31975.05 32076.66 33887.27 24951.88 40681.07 27773.26 39675.68 15683.25 28586.37 33145.54 41188.80 27351.98 40990.99 29489.31 302
ET-MVSNet_ETH3D75.28 32072.77 34382.81 22383.03 36168.11 22577.09 34376.51 37260.67 36577.60 36780.52 40438.04 43991.15 20370.78 25890.68 31189.17 309
thres40075.14 32174.23 32777.86 32186.24 28652.12 40379.24 30773.87 38973.34 19581.82 31384.60 36346.02 40488.80 27351.98 40990.99 29492.66 189
wuyk23d75.13 32279.30 27262.63 43075.56 43075.18 13180.89 28073.10 39875.06 16794.76 1695.32 4587.73 4452.85 46234.16 46097.11 8759.85 458
EU-MVSNet75.12 32374.43 32677.18 32983.11 36059.48 33985.71 15482.43 33039.76 45985.64 22388.76 28244.71 42387.88 29673.86 21985.88 38484.16 381
HyFIR lowres test75.12 32372.66 34582.50 23191.44 14165.19 25672.47 39587.31 25246.79 43880.29 33784.30 36552.70 37792.10 17751.88 41386.73 37390.22 284
CMPMVSbinary59.41 2075.12 32373.57 33279.77 28875.84 42967.22 23181.21 27582.18 33250.78 43076.50 37287.66 30855.20 36882.99 36962.17 34590.64 31689.09 313
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
pmmvs474.92 32672.98 34180.73 27184.95 31671.71 17676.23 35977.59 36152.83 41577.73 36686.38 33056.35 36184.97 35057.72 37387.05 36885.51 362
tfpn200view974.86 32774.23 32776.74 33786.24 28652.12 40379.24 30773.87 38973.34 19581.82 31384.60 36346.02 40488.80 27351.98 40990.99 29489.31 302
1112_ss74.82 32873.74 33078.04 31789.57 18360.04 33176.49 35587.09 26454.31 40673.66 40179.80 41060.25 33386.76 31858.37 36784.15 40587.32 341
EGC-MVSNET74.79 32969.99 37389.19 6794.89 3887.00 1591.89 3886.28 2731.09 4682.23 47095.98 3081.87 12289.48 26079.76 13095.96 13091.10 255
ppachtmachnet_test74.73 33074.00 32976.90 33480.71 38556.89 36871.53 40378.42 35658.24 38079.32 34982.92 38157.91 35184.26 36065.60 31591.36 28889.56 297
Patchmatch-RL test74.48 33173.68 33176.89 33584.83 31866.54 24172.29 39669.16 42457.70 38586.76 19086.33 33245.79 41082.59 37069.63 27490.65 31581.54 417
PatchMatch-RL74.48 33173.22 33878.27 31387.70 23785.26 3875.92 36470.09 41764.34 32876.09 37981.25 39865.87 29778.07 39953.86 39683.82 40771.48 446
XXY-MVS74.44 33376.19 30869.21 39984.61 32352.43 40271.70 40077.18 36660.73 36480.60 33190.96 22075.44 20169.35 43056.13 38088.33 34785.86 358
test250674.12 33473.39 33576.28 34391.85 12344.20 44184.06 19248.20 46672.30 22081.90 31094.20 8927.22 46689.77 25764.81 32296.02 12794.87 78
reproduce_monomvs74.09 33573.23 33776.65 33976.52 42154.54 38477.50 33781.40 34165.85 30682.86 29386.67 32727.38 46484.53 35570.24 26790.66 31490.89 263
CR-MVSNet74.00 33673.04 34076.85 33679.58 39662.64 28582.58 24176.90 36850.50 43375.72 38392.38 16248.07 39684.07 36268.72 28882.91 41483.85 385
SSC-MVS3.273.90 33775.67 31468.61 40784.11 33441.28 44964.17 44072.83 39972.09 22379.08 35287.94 29670.31 27073.89 41555.99 38194.49 19190.67 273
Test_1112_low_res73.90 33773.08 33976.35 34190.35 16755.95 37173.40 38986.17 27550.70 43173.14 40285.94 33958.31 34785.90 33856.51 37783.22 41187.20 343
test20.0373.75 33974.59 32471.22 38581.11 37851.12 41370.15 41472.10 40670.42 24280.28 33991.50 19464.21 30774.72 41346.96 43494.58 18987.82 336
test_fmvs273.57 34072.80 34275.90 34772.74 45168.84 21877.07 34484.32 31445.14 44582.89 29184.22 36648.37 39470.36 42673.40 23087.03 36988.52 321
SCA73.32 34172.57 34775.58 35281.62 37155.86 37478.89 31371.37 41261.73 34874.93 39383.42 37560.46 33087.01 30958.11 37182.63 41983.88 382
baseline173.26 34273.54 33372.43 37884.92 31747.79 42679.89 29474.00 38765.93 30478.81 35486.28 33556.36 36081.63 37856.63 37679.04 43787.87 335
131473.22 34372.56 34875.20 35380.41 39057.84 35981.64 26685.36 29151.68 42473.10 40376.65 43861.45 32585.19 34863.54 33379.21 43582.59 402
MVS73.21 34472.59 34675.06 35580.97 37960.81 32281.64 26685.92 28446.03 44371.68 41177.54 42968.47 28189.77 25755.70 38485.39 38674.60 443
HY-MVS64.64 1873.03 34572.47 34974.71 35983.36 35154.19 38882.14 26081.96 33456.76 39569.57 42586.21 33660.03 33484.83 35249.58 42182.65 41785.11 366
thisisatest051573.00 34670.52 36580.46 27781.45 37359.90 33573.16 39174.31 38657.86 38476.08 38077.78 42637.60 44292.12 17665.00 32091.45 28789.35 301
EPNet_dtu72.87 34771.33 35977.49 32677.72 41060.55 32582.35 25175.79 37566.49 30158.39 46181.06 39953.68 37385.98 33353.55 39992.97 24385.95 356
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CVMVSNet72.62 34871.41 35876.28 34383.25 35560.34 32783.50 21379.02 35537.77 46376.33 37485.10 35449.60 39287.41 30570.54 26477.54 44381.08 424
CHOSEN 1792x268872.45 34970.56 36478.13 31490.02 17863.08 27868.72 42183.16 32242.99 45375.92 38185.46 34757.22 35685.18 34949.87 41981.67 42186.14 354
testgi72.36 35074.61 32265.59 42180.56 38842.82 44668.29 42373.35 39566.87 29881.84 31289.93 26172.08 25766.92 44446.05 43892.54 25587.01 345
thres20072.34 35171.55 35774.70 36083.48 34551.60 40875.02 37373.71 39270.14 24878.56 35780.57 40346.20 40288.20 28946.99 43389.29 33284.32 376
FPMVS72.29 35272.00 35173.14 36988.63 21385.00 4074.65 37767.39 42971.94 22677.80 36487.66 30850.48 38875.83 40749.95 41779.51 43158.58 460
FMVSNet572.10 35371.69 35373.32 36781.57 37253.02 39776.77 34878.37 35763.31 33176.37 37391.85 18036.68 44378.98 39447.87 43092.45 25787.95 331
our_test_371.85 35471.59 35472.62 37580.71 38553.78 39169.72 41771.71 41158.80 37778.03 35980.51 40556.61 35978.84 39662.20 34386.04 38385.23 364
PAPM71.77 35570.06 37176.92 33386.39 27753.97 38976.62 35286.62 27053.44 41063.97 45084.73 36157.79 35392.34 16939.65 45081.33 42584.45 374
ttmdpeth71.72 35670.67 36274.86 35673.08 44855.88 37377.41 34069.27 42255.86 39778.66 35593.77 11638.01 44075.39 41060.12 35989.87 32593.31 155
IB-MVS62.13 1971.64 35768.97 38379.66 29280.80 38462.26 29873.94 38376.90 36863.27 33368.63 42976.79 43633.83 44791.84 18459.28 36487.26 36384.88 368
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
UnsupCasMVSNet_eth71.63 35872.30 35069.62 39676.47 42352.70 40070.03 41580.97 34459.18 37479.36 34788.21 29260.50 32969.12 43158.33 36977.62 44287.04 344
testing371.53 35970.79 36173.77 36588.89 20541.86 44876.60 35459.12 45572.83 20880.97 32582.08 39019.80 47287.33 30765.12 31991.68 28292.13 225
test_vis3_rt71.42 36070.67 36273.64 36669.66 45870.46 19066.97 43389.73 20442.68 45588.20 15383.04 37743.77 42560.07 45665.35 31886.66 37490.39 282
Anonymous2023120671.38 36171.88 35269.88 39386.31 28354.37 38670.39 41274.62 38252.57 41776.73 37188.76 28259.94 33572.06 41944.35 44293.23 23583.23 396
test_vis1_n_192071.30 36271.58 35670.47 38877.58 41259.99 33474.25 37884.22 31551.06 42774.85 39479.10 41655.10 36968.83 43368.86 28579.20 43682.58 403
MIMVSNet71.09 36371.59 35469.57 39787.23 25150.07 41878.91 31271.83 40860.20 37171.26 41291.76 18755.08 37076.09 40541.06 44787.02 37082.54 405
test_fmvs1_n70.94 36470.41 36872.53 37773.92 43966.93 23875.99 36384.21 31643.31 45279.40 34679.39 41443.47 42668.55 43569.05 28284.91 39782.10 411
MS-PatchMatch70.93 36570.22 36973.06 37081.85 36862.50 28873.82 38577.90 35852.44 41875.92 38181.27 39755.67 36581.75 37655.37 38777.70 44174.94 442
pmmvs570.73 36670.07 37072.72 37377.03 41752.73 39974.14 37975.65 37850.36 43472.17 40985.37 35155.42 36780.67 38352.86 40587.59 36284.77 369
testing3-270.72 36770.97 36069.95 39288.93 20334.80 46269.85 41666.59 43678.42 12477.58 36885.55 34331.83 45382.08 37446.28 43593.73 21892.98 176
PatchT70.52 36872.76 34463.79 42979.38 40033.53 46377.63 33365.37 44073.61 18871.77 41092.79 15144.38 42475.65 40864.53 32785.37 38782.18 410
test_vis1_n70.29 36969.99 37371.20 38675.97 42866.50 24276.69 35080.81 34544.22 44875.43 38677.23 43350.00 39068.59 43466.71 30382.85 41678.52 436
N_pmnet70.20 37068.80 38574.38 36180.91 38084.81 4359.12 45176.45 37355.06 40175.31 39082.36 38755.74 36454.82 46147.02 43287.24 36483.52 389
tpmvs70.16 37169.56 37671.96 38174.71 43848.13 42379.63 29675.45 38065.02 32470.26 42081.88 39245.34 41685.68 34458.34 36875.39 44782.08 412
new-patchmatchnet70.10 37273.37 33660.29 43881.23 37716.95 47359.54 44974.62 38262.93 33580.97 32587.93 29862.83 32271.90 42055.24 38995.01 17392.00 230
YYNet170.06 37370.44 36668.90 40173.76 44153.42 39558.99 45267.20 43158.42 37987.10 18285.39 35059.82 33767.32 44159.79 36183.50 41085.96 355
MVStest170.05 37469.26 37772.41 37958.62 47055.59 37776.61 35365.58 43853.44 41089.28 12893.32 12722.91 47071.44 42474.08 21589.52 32990.21 288
MDA-MVSNet_test_wron70.05 37470.44 36668.88 40273.84 44053.47 39358.93 45367.28 43058.43 37887.09 18385.40 34959.80 33867.25 44259.66 36283.54 40985.92 357
CostFormer69.98 37668.68 38673.87 36377.14 41550.72 41579.26 30674.51 38451.94 42370.97 41584.75 36045.16 41987.49 30355.16 39079.23 43483.40 392
testing9169.94 37768.99 38272.80 37283.81 34045.89 43471.57 40273.64 39468.24 27470.77 41877.82 42534.37 44684.44 35753.64 39887.00 37188.07 326
baseline269.77 37866.89 39578.41 30979.51 39858.09 35576.23 35969.57 42057.50 38864.82 44877.45 43146.02 40488.44 28353.08 40177.83 43988.70 319
PatchmatchNetpermissive69.71 37968.83 38472.33 38077.66 41153.60 39279.29 30569.99 41857.66 38672.53 40682.93 38046.45 40180.08 38960.91 35572.09 45183.31 395
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
test_fmvs169.57 38069.05 38071.14 38769.15 45965.77 25273.98 38283.32 32042.83 45477.77 36578.27 42443.39 42968.50 43668.39 29284.38 40479.15 434
JIA-IIPM69.41 38166.64 39977.70 32373.19 44571.24 18175.67 36565.56 43970.42 24265.18 44492.97 14233.64 44983.06 36753.52 40069.61 45778.79 435
Syy-MVS69.40 38270.03 37267.49 41281.72 36938.94 45471.00 40561.99 44661.38 35470.81 41672.36 45061.37 32679.30 39264.50 32885.18 39084.22 378
testing9969.27 38368.15 39072.63 37483.29 35345.45 43671.15 40471.08 41367.34 29170.43 41977.77 42732.24 45284.35 35953.72 39786.33 37988.10 325
UnsupCasMVSNet_bld69.21 38469.68 37567.82 41079.42 39951.15 41267.82 42775.79 37554.15 40777.47 36985.36 35259.26 34170.64 42548.46 42779.35 43381.66 415
test_cas_vis1_n_192069.20 38569.12 37869.43 39873.68 44262.82 28270.38 41377.21 36546.18 44280.46 33678.95 41852.03 37965.53 44965.77 31477.45 44479.95 432
gg-mvs-nofinetune68.96 38669.11 37968.52 40876.12 42745.32 43783.59 21055.88 46086.68 3364.62 44997.01 1230.36 45783.97 36444.78 44182.94 41376.26 439
WBMVS68.76 38768.43 38769.75 39583.29 35340.30 45267.36 42972.21 40557.09 39277.05 37085.53 34533.68 44880.51 38548.79 42590.90 29988.45 322
WB-MVSnew68.72 38869.01 38167.85 40983.22 35743.98 44274.93 37465.98 43755.09 40073.83 39979.11 41565.63 29971.89 42138.21 45585.04 39387.69 337
tpm268.45 38966.83 39673.30 36878.93 40648.50 42279.76 29571.76 40947.50 43769.92 42283.60 37142.07 43288.40 28548.44 42879.51 43183.01 399
tpm67.95 39068.08 39167.55 41178.74 40743.53 44475.60 36667.10 43454.92 40272.23 40788.10 29342.87 43175.97 40652.21 40780.95 42983.15 397
WTY-MVS67.91 39168.35 38866.58 41780.82 38348.12 42465.96 43572.60 40053.67 40971.20 41381.68 39558.97 34369.06 43248.57 42681.67 42182.55 404
testing1167.38 39265.93 40071.73 38383.37 35046.60 43170.95 40769.40 42162.47 34066.14 43776.66 43731.22 45484.10 36149.10 42384.10 40684.49 372
test-LLR67.21 39366.74 39768.63 40576.45 42455.21 38067.89 42467.14 43262.43 34365.08 44572.39 44843.41 42769.37 42861.00 35384.89 39881.31 419
testing22266.93 39465.30 40771.81 38283.38 34945.83 43572.06 39867.50 42864.12 32969.68 42476.37 44027.34 46583.00 36838.88 45188.38 34686.62 350
sss66.92 39567.26 39365.90 41977.23 41451.10 41464.79 43771.72 41052.12 42270.13 42180.18 40757.96 35065.36 45050.21 41581.01 42781.25 421
KD-MVS_2432*160066.87 39665.81 40370.04 39067.50 46047.49 42762.56 44379.16 35261.21 35977.98 36080.61 40125.29 46882.48 37153.02 40284.92 39580.16 430
miper_refine_blended66.87 39665.81 40370.04 39067.50 46047.49 42762.56 44379.16 35261.21 35977.98 36080.61 40125.29 46882.48 37153.02 40284.92 39580.16 430
dmvs_re66.81 39866.98 39466.28 41876.87 41858.68 35371.66 40172.24 40360.29 36969.52 42673.53 44752.38 37864.40 45244.90 44081.44 42475.76 440
tpm cat166.76 39965.21 40871.42 38477.09 41650.62 41678.01 32573.68 39344.89 44668.64 42879.00 41745.51 41382.42 37349.91 41870.15 45481.23 423
UWE-MVS66.43 40065.56 40669.05 40084.15 33340.98 45073.06 39264.71 44254.84 40376.18 37879.62 41329.21 45980.50 38638.54 45489.75 32685.66 360
PVSNet58.17 2166.41 40165.63 40568.75 40381.96 36649.88 41962.19 44572.51 40251.03 42868.04 43175.34 44450.84 38574.77 41145.82 43982.96 41281.60 416
tpmrst66.28 40266.69 39865.05 42572.82 45039.33 45378.20 32370.69 41653.16 41367.88 43280.36 40648.18 39574.75 41258.13 37070.79 45381.08 424
Patchmatch-test65.91 40367.38 39261.48 43575.51 43143.21 44568.84 42063.79 44462.48 33972.80 40583.42 37544.89 42259.52 45848.27 42986.45 37681.70 414
ADS-MVSNet265.87 40463.64 41372.55 37673.16 44656.92 36767.10 43174.81 38149.74 43566.04 43982.97 37846.71 39977.26 40242.29 44469.96 45583.46 390
myMVS_eth3d2865.83 40565.85 40165.78 42083.42 34835.71 46067.29 43068.01 42767.58 28869.80 42377.72 42832.29 45174.30 41437.49 45689.06 33687.32 341
test_vis1_rt65.64 40664.09 41070.31 38966.09 46470.20 19461.16 44681.60 33938.65 46072.87 40469.66 45352.84 37560.04 45756.16 37977.77 44080.68 428
mvsany_test365.48 40762.97 41673.03 37169.99 45776.17 12464.83 43643.71 46843.68 45080.25 34087.05 32452.83 37663.09 45551.92 41272.44 45079.84 433
test-mter65.00 40863.79 41268.63 40576.45 42455.21 38067.89 42467.14 43250.98 42965.08 44572.39 44828.27 46269.37 42861.00 35384.89 39881.31 419
ETVMVS64.67 40963.34 41568.64 40483.44 34741.89 44769.56 41961.70 45161.33 35668.74 42775.76 44228.76 46079.35 39134.65 45986.16 38284.67 371
myMVS_eth3d64.66 41063.89 41166.97 41581.72 36937.39 45771.00 40561.99 44661.38 35470.81 41672.36 45020.96 47179.30 39249.59 42085.18 39084.22 378
test0.0.03 164.66 41064.36 40965.57 42275.03 43646.89 43064.69 43861.58 45262.43 34371.18 41477.54 42943.41 42768.47 43740.75 44982.65 41781.35 418
UBG64.34 41263.35 41467.30 41383.50 34440.53 45167.46 42865.02 44154.77 40467.54 43574.47 44632.99 45078.50 39840.82 44883.58 40882.88 400
test_f64.31 41365.85 40159.67 43966.54 46362.24 30057.76 45570.96 41440.13 45784.36 25782.09 38946.93 39851.67 46361.99 34681.89 42065.12 454
pmmvs362.47 41460.02 42769.80 39471.58 45464.00 26870.52 41158.44 45839.77 45866.05 43875.84 44127.10 46772.28 41846.15 43784.77 40273.11 444
EPMVS62.47 41462.63 41862.01 43170.63 45638.74 45574.76 37552.86 46253.91 40867.71 43480.01 40839.40 43666.60 44555.54 38668.81 45980.68 428
ADS-MVSNet61.90 41662.19 42061.03 43673.16 44636.42 45967.10 43161.75 44949.74 43566.04 43982.97 37846.71 39963.21 45342.29 44469.96 45583.46 390
PMMVS61.65 41760.38 42465.47 42365.40 46769.26 20863.97 44161.73 45036.80 46460.11 45668.43 45559.42 33966.35 44648.97 42478.57 43860.81 457
E-PMN61.59 41861.62 42161.49 43466.81 46255.40 37853.77 45860.34 45466.80 29958.90 45965.50 45840.48 43566.12 44755.72 38386.25 38062.95 456
TESTMET0.1,161.29 41960.32 42564.19 42772.06 45251.30 41067.89 42462.09 44545.27 44460.65 45569.01 45427.93 46364.74 45156.31 37881.65 42376.53 438
MVS-HIRNet61.16 42062.92 41755.87 44279.09 40335.34 46171.83 39957.98 45946.56 44059.05 45891.14 21149.95 39176.43 40438.74 45271.92 45255.84 461
EMVS61.10 42160.81 42361.99 43265.96 46555.86 37453.10 45958.97 45767.06 29656.89 46363.33 45940.98 43367.03 44354.79 39286.18 38163.08 455
DSMNet-mixed60.98 42261.61 42259.09 44172.88 44945.05 43974.70 37646.61 46726.20 46565.34 44390.32 25055.46 36663.12 45441.72 44681.30 42669.09 450
dp60.70 42360.29 42661.92 43372.04 45338.67 45670.83 40964.08 44351.28 42660.75 45477.28 43236.59 44471.58 42347.41 43162.34 46175.52 441
dmvs_testset60.59 42462.54 41954.72 44477.26 41327.74 46774.05 38161.00 45360.48 36665.62 44267.03 45755.93 36368.23 43932.07 46369.46 45868.17 451
CHOSEN 280x42059.08 42556.52 43166.76 41676.51 42264.39 26449.62 46059.00 45643.86 44955.66 46468.41 45635.55 44568.21 44043.25 44376.78 44667.69 452
mvsany_test158.48 42656.47 43264.50 42665.90 46668.21 22456.95 45642.11 46938.30 46165.69 44177.19 43556.96 35759.35 45946.16 43658.96 46265.93 453
UWE-MVS-2858.44 42757.71 42960.65 43773.58 44331.23 46469.68 41848.80 46553.12 41461.79 45278.83 41930.98 45568.40 43821.58 46680.99 42882.33 409
PVSNet_051.08 2256.10 42854.97 43359.48 44075.12 43553.28 39655.16 45761.89 44844.30 44759.16 45762.48 46054.22 37165.91 44835.40 45847.01 46359.25 459
new_pmnet55.69 42957.66 43049.76 44575.47 43230.59 46559.56 44851.45 46343.62 45162.49 45175.48 44340.96 43449.15 46537.39 45772.52 44969.55 449
PMMVS255.64 43059.27 42844.74 44664.30 46812.32 47440.60 46149.79 46453.19 41265.06 44784.81 35953.60 37449.76 46432.68 46289.41 33172.15 445
MVEpermissive40.22 2351.82 43150.47 43455.87 44262.66 46951.91 40531.61 46339.28 47040.65 45650.76 46574.98 44556.24 36244.67 46633.94 46164.11 46071.04 448
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
dongtai41.90 43242.65 43539.67 44770.86 45521.11 46961.01 44721.42 47457.36 38957.97 46250.06 46316.40 47358.73 46021.03 46727.69 46739.17 463
kuosan30.83 43332.17 43626.83 44953.36 47119.02 47257.90 45420.44 47538.29 46238.01 46637.82 46515.18 47433.45 4687.74 46920.76 46828.03 464
test_method30.46 43429.60 43733.06 44817.99 4733.84 47613.62 46473.92 3882.79 46718.29 46953.41 46228.53 46143.25 46722.56 46435.27 46552.11 462
cdsmvs_eth3d_5k20.81 43527.75 4380.00 4540.00 4770.00 4790.00 46585.44 2900.00 4720.00 47382.82 38281.46 1280.00 4730.00 4720.00 4710.00 469
tmp_tt20.25 43624.50 4397.49 4514.47 4748.70 47534.17 46225.16 4721.00 46932.43 46818.49 46639.37 4379.21 47021.64 46543.75 4644.57 466
ab-mvs-re6.65 4378.87 4400.00 4540.00 4770.00 4790.00 4650.00 4780.00 4720.00 47379.80 4100.00 4770.00 4730.00 4720.00 4710.00 469
pcd_1.5k_mvsjas6.41 4388.55 4410.00 4540.00 4770.00 4790.00 4650.00 4780.00 4720.00 4730.00 47276.94 1850.00 4730.00 4720.00 4710.00 469
test1236.27 4398.08 4420.84 4521.11 4760.57 47762.90 4420.82 4760.54 4701.07 4722.75 4711.26 4750.30 4711.04 4701.26 4701.66 467
testmvs5.91 4407.65 4430.72 4531.20 4750.37 47859.14 4500.67 4770.49 4711.11 4712.76 4700.94 4760.24 4721.02 4711.47 4691.55 468
mmdepth0.00 4410.00 4440.00 4540.00 4770.00 4790.00 4650.00 4780.00 4720.00 4730.00 4720.00 4770.00 4730.00 4720.00 4710.00 469
monomultidepth0.00 4410.00 4440.00 4540.00 4770.00 4790.00 4650.00 4780.00 4720.00 4730.00 4720.00 4770.00 4730.00 4720.00 4710.00 469
test_blank0.00 4410.00 4440.00 4540.00 4770.00 4790.00 4650.00 4780.00 4720.00 4730.00 4720.00 4770.00 4730.00 4720.00 4710.00 469
uanet_test0.00 4410.00 4440.00 4540.00 4770.00 4790.00 4650.00 4780.00 4720.00 4730.00 4720.00 4770.00 4730.00 4720.00 4710.00 469
DCPMVS0.00 4410.00 4440.00 4540.00 4770.00 4790.00 4650.00 4780.00 4720.00 4730.00 4720.00 4770.00 4730.00 4720.00 4710.00 469
sosnet-low-res0.00 4410.00 4440.00 4540.00 4770.00 4790.00 4650.00 4780.00 4720.00 4730.00 4720.00 4770.00 4730.00 4720.00 4710.00 469
sosnet0.00 4410.00 4440.00 4540.00 4770.00 4790.00 4650.00 4780.00 4720.00 4730.00 4720.00 4770.00 4730.00 4720.00 4710.00 469
uncertanet0.00 4410.00 4440.00 4540.00 4770.00 4790.00 4650.00 4780.00 4720.00 4730.00 4720.00 4770.00 4730.00 4720.00 4710.00 469
Regformer0.00 4410.00 4440.00 4540.00 4770.00 4790.00 4650.00 4780.00 4720.00 4730.00 4720.00 4770.00 4730.00 4720.00 4710.00 469
uanet0.00 4410.00 4440.00 4540.00 4770.00 4790.00 4650.00 4780.00 4720.00 4730.00 4720.00 4770.00 4730.00 4720.00 4710.00 469
WAC-MVS37.39 45752.61 406
FOURS196.08 1287.41 1496.19 295.83 592.95 396.57 3
MSC_two_6792asdad88.81 7391.55 13577.99 9791.01 16296.05 987.45 2898.17 3792.40 205
PC_three_145258.96 37690.06 10391.33 20280.66 13893.03 15175.78 19195.94 13392.48 199
No_MVS88.81 7391.55 13577.99 9791.01 16296.05 987.45 2898.17 3792.40 205
test_one_060193.85 6473.27 14594.11 3986.57 3493.47 4294.64 6888.42 29
eth-test20.00 477
eth-test0.00 477
ZD-MVS92.22 10980.48 7191.85 13271.22 23490.38 9892.98 13986.06 6596.11 781.99 10996.75 97
RE-MVS-def92.61 994.13 5788.95 692.87 1394.16 3388.75 1893.79 3394.43 7690.64 1187.16 3797.60 7192.73 183
IU-MVS94.18 5272.64 15490.82 16756.98 39389.67 11685.78 6297.92 5293.28 156
OPU-MVS88.27 8591.89 12177.83 10090.47 5691.22 20881.12 13294.68 7874.48 20495.35 15692.29 215
test_241102_TWO93.71 5683.77 5893.49 4094.27 8389.27 2495.84 2486.03 5597.82 5792.04 228
test_241102_ONE94.18 5272.65 15293.69 5783.62 6094.11 2793.78 11490.28 1595.50 49
9.1489.29 6391.84 12588.80 9495.32 1375.14 16691.07 8392.89 14587.27 4893.78 11783.69 8797.55 74
save fliter93.75 6577.44 10686.31 14089.72 20570.80 239
test_0728_THIRD85.33 4293.75 3594.65 6587.44 4795.78 3287.41 3098.21 3492.98 176
test_0728_SECOND86.79 10894.25 5072.45 16290.54 5394.10 4095.88 1886.42 4597.97 4992.02 229
test072694.16 5572.56 15890.63 5093.90 4983.61 6193.75 3594.49 7389.76 19
GSMVS83.88 382
test_part293.86 6377.77 10192.84 52
sam_mvs146.11 40383.88 382
sam_mvs45.92 408
ambc82.98 21490.55 16464.86 25888.20 10389.15 21889.40 12593.96 10571.67 26491.38 19778.83 14496.55 10292.71 186
MTGPAbinary91.81 136
test_post178.85 3153.13 46845.19 41880.13 38858.11 371
test_post3.10 46945.43 41477.22 403
patchmatchnet-post81.71 39445.93 40787.01 309
GG-mvs-BLEND67.16 41473.36 44446.54 43384.15 19055.04 46158.64 46061.95 46129.93 45883.87 36538.71 45376.92 44571.07 447
MTMP90.66 4933.14 471
gm-plane-assit75.42 43344.97 44052.17 41972.36 45087.90 29554.10 395
test9_res80.83 11996.45 10890.57 276
TEST992.34 10479.70 8083.94 19690.32 18565.41 31684.49 25390.97 21882.03 11793.63 123
test_892.09 11378.87 8883.82 20190.31 18765.79 30784.36 25790.96 22081.93 11993.44 136
agg_prior279.68 13296.16 12090.22 284
agg_prior91.58 13377.69 10390.30 18884.32 25993.18 144
TestCases89.68 5691.59 13083.40 5295.44 1179.47 10688.00 15893.03 13782.66 9891.47 19170.81 25696.14 12194.16 112
test_prior478.97 8784.59 179
test_prior283.37 21775.43 16284.58 25091.57 19281.92 12179.54 13696.97 90
test_prior86.32 11690.59 16371.99 17092.85 9894.17 10292.80 181
旧先验281.73 26456.88 39486.54 20384.90 35172.81 241
新几何281.72 265
新几何182.95 21693.96 6178.56 9180.24 34855.45 39983.93 27091.08 21471.19 26688.33 28765.84 31293.07 23981.95 413
旧先验191.97 11771.77 17181.78 33691.84 18173.92 22893.65 22183.61 388
无先验82.81 23685.62 28858.09 38291.41 19667.95 29684.48 373
原ACMM282.26 256
原ACMM184.60 16392.81 9474.01 13791.50 14362.59 33782.73 29590.67 23776.53 19494.25 9469.24 27795.69 14885.55 361
test22293.31 7876.54 11679.38 30477.79 35952.59 41682.36 30090.84 22866.83 29091.69 28181.25 421
testdata286.43 32463.52 334
segment_acmp81.94 118
testdata79.54 29492.87 8972.34 16380.14 34959.91 37285.47 22891.75 18867.96 28485.24 34768.57 29192.18 26881.06 426
testdata179.62 29773.95 183
test1286.57 11190.74 15972.63 15690.69 17082.76 29479.20 15194.80 7595.32 15892.27 217
plane_prior793.45 7277.31 109
plane_prior692.61 9576.54 11674.84 210
plane_prior593.61 6095.22 5980.78 12095.83 14194.46 94
plane_prior492.95 143
plane_prior376.85 11477.79 13386.55 197
plane_prior289.45 8379.44 108
plane_prior192.83 93
plane_prior76.42 11987.15 12275.94 15395.03 170
n20.00 478
nn0.00 478
door-mid74.45 385
lessismore_v085.95 12791.10 15270.99 18570.91 41591.79 7194.42 7861.76 32492.93 15479.52 13793.03 24093.93 121
LGP-MVS_train90.82 3794.75 4181.69 6394.27 2582.35 7493.67 3894.82 6091.18 595.52 4585.36 6598.73 795.23 66
test1191.46 144
door72.57 401
HQP5-MVS70.66 187
HQP-NCC91.19 14784.77 17073.30 19780.55 333
ACMP_Plane91.19 14784.77 17073.30 19780.55 333
BP-MVS77.30 169
HQP4-MVS80.56 33294.61 8293.56 148
HQP3-MVS92.68 10494.47 192
HQP2-MVS72.10 255
NP-MVS91.95 11874.55 13490.17 257
MDTV_nov1_ep13_2view27.60 46870.76 41046.47 44161.27 45345.20 41749.18 42283.75 387
MDTV_nov1_ep1368.29 38978.03 40843.87 44374.12 38072.22 40452.17 41967.02 43685.54 34445.36 41580.85 38255.73 38284.42 403
ACMMP++_ref95.74 147
ACMMP++97.35 80
Test By Simon79.09 153
ITE_SJBPF90.11 4990.72 16084.97 4190.30 18881.56 8290.02 10591.20 21082.40 10390.81 21873.58 22794.66 18794.56 90
DeepMVS_CXcopyleft24.13 45032.95 47229.49 46621.63 47312.07 46637.95 46745.07 46430.84 45619.21 46917.94 46833.06 46623.69 465