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-MVSNet99.43 199.49 199.24 199.95 198.13 199.37 199.57 199.82 199.86 199.85 199.52 199.73 197.58 199.94 199.85 1
LTVRE_ROB93.87 197.93 298.16 297.26 2698.81 2593.86 3299.07 298.98 597.01 1398.92 498.78 1495.22 3798.61 18096.85 299.77 1099.31 27
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
TDRefinement97.68 397.60 497.93 299.02 1295.95 598.61 398.81 897.41 1097.28 4998.46 2594.62 5898.84 13894.64 1799.53 3598.99 55
UA-Net97.35 497.24 1197.69 598.22 7093.87 3198.42 698.19 3696.95 1495.46 13199.23 493.45 7699.57 1395.34 1299.89 299.63 9
abl_697.31 597.12 1397.86 398.54 4395.32 796.61 2898.35 2095.81 3197.55 3797.44 6896.51 999.40 4594.06 3099.23 7998.85 78
UniMVSNet_ETH3D97.13 697.72 395.35 8999.51 287.38 13697.70 897.54 11198.16 298.94 299.33 297.84 499.08 10090.73 13099.73 1499.59 12
HPM-MVS_fast97.01 796.89 1597.39 2299.12 893.92 2997.16 1298.17 4193.11 7296.48 8097.36 7596.92 699.34 6494.31 2399.38 5598.92 69
SR-MVS-dyc-post96.84 896.60 2597.56 1098.07 7995.27 896.37 4198.12 4795.66 3397.00 5997.03 9694.85 5299.42 3193.49 4898.84 12798.00 154
mvs_tets96.83 996.71 1997.17 2798.83 2392.51 5096.58 3097.61 10687.57 20698.80 798.90 996.50 1099.59 1296.15 799.47 3999.40 21
v7n96.82 1097.31 1095.33 9198.54 4386.81 15096.83 2098.07 5796.59 2098.46 1798.43 2792.91 9599.52 1796.25 699.76 1199.65 8
APD-MVS_3200maxsize96.82 1096.65 2197.32 2597.95 9293.82 3496.31 4698.25 2895.51 3596.99 6197.05 9595.63 2199.39 5093.31 6498.88 12298.75 87
HPM-MVScopyleft96.81 1296.62 2397.36 2498.89 1993.53 3997.51 998.44 1392.35 8495.95 10896.41 13896.71 899.42 3193.99 3399.36 5699.13 40
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
pmmvs696.80 1397.36 995.15 10199.12 887.82 13196.68 2697.86 8496.10 2698.14 2499.28 397.94 398.21 21791.38 12199.69 1599.42 19
OurMVSNet-221017-096.80 1396.75 1896.96 3699.03 1191.85 5997.98 798.01 7094.15 5298.93 399.07 588.07 18699.57 1395.86 999.69 1599.46 18
test117296.79 1596.52 2797.60 998.03 8594.87 1096.07 5698.06 6095.76 3296.89 6496.85 10894.85 5299.42 3193.35 6398.81 13598.53 114
COLMAP_ROBcopyleft91.06 596.75 1696.62 2397.13 2898.38 5994.31 1796.79 2398.32 2196.69 1796.86 6697.56 6095.48 2598.77 15690.11 15299.44 4598.31 129
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
anonymousdsp96.74 1796.42 2997.68 798.00 8894.03 2696.97 1797.61 10687.68 20398.45 1898.77 1594.20 6799.50 1996.70 399.40 5399.53 14
DTE-MVSNet96.74 1797.43 594.67 11899.13 684.68 18796.51 3297.94 8298.14 398.67 1298.32 2995.04 4599.69 293.27 6799.82 899.62 10
SR-MVS96.70 1996.42 2997.54 1198.05 8194.69 1196.13 5398.07 5795.17 3796.82 6896.73 12095.09 4499.43 3092.99 7998.71 14498.50 116
PS-CasMVS96.69 2097.43 594.49 13199.13 684.09 19796.61 2897.97 7697.91 598.64 1398.13 3495.24 3699.65 393.39 6199.84 399.72 2
PEN-MVS96.69 2097.39 894.61 12099.16 484.50 18896.54 3198.05 6198.06 498.64 1398.25 3195.01 4899.65 392.95 8099.83 699.68 4
MTAPA96.65 2296.38 3397.47 1598.95 1694.05 2395.88 6497.62 10394.46 4596.29 9096.94 10193.56 7499.37 5894.29 2499.42 4798.99 55
test_djsdf96.62 2396.49 2897.01 3398.55 4191.77 6197.15 1397.37 12188.98 17498.26 2298.86 1093.35 8199.60 896.41 499.45 4399.66 6
ACMMPcopyleft96.61 2496.34 3497.43 1998.61 3493.88 3096.95 1898.18 3792.26 8796.33 8696.84 11195.10 4399.40 4593.47 5399.33 6099.02 52
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
Anonymous2023121196.60 2597.13 1295.00 10597.46 12486.35 16597.11 1698.24 3197.58 898.72 898.97 793.15 8799.15 8993.18 7099.74 1399.50 16
WR-MVS_H96.60 2597.05 1495.24 9799.02 1286.44 16196.78 2498.08 5497.42 998.48 1697.86 4991.76 12299.63 694.23 2699.84 399.66 6
jajsoiax96.59 2796.42 2997.12 2998.76 2892.49 5196.44 3897.42 11986.96 21598.71 1098.72 1795.36 3199.56 1695.92 899.45 4399.32 26
ACMH88.36 1296.59 2797.43 594.07 14498.56 3885.33 18196.33 4498.30 2494.66 4098.72 898.30 3097.51 598.00 23594.87 1499.59 2798.86 75
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
XVS96.49 2996.18 4297.44 1798.56 3893.99 2796.50 3397.95 7994.58 4194.38 17496.49 13294.56 5999.39 5093.57 4499.05 10398.93 65
ACMH+88.43 1196.48 3096.82 1695.47 8698.54 4389.06 10295.65 7298.61 1196.10 2698.16 2397.52 6396.90 798.62 17990.30 14399.60 2598.72 93
zzz-MVS96.47 3196.14 4597.47 1598.95 1694.05 2393.69 14397.62 10394.46 4596.29 9096.94 10193.56 7499.37 5894.29 2499.42 4798.99 55
APDe-MVS96.46 3296.64 2295.93 6397.68 10989.38 9996.90 1998.41 1792.52 7997.43 4497.92 4595.11 4299.50 1994.45 1999.30 6598.92 69
ACMMPR96.46 3296.14 4597.41 2198.60 3593.82 3496.30 4897.96 7792.35 8495.57 12696.61 12894.93 5199.41 3893.78 3899.15 9199.00 53
mPP-MVS96.46 3296.05 5197.69 598.62 3294.65 1396.45 3697.74 9792.59 7895.47 12996.68 12394.50 6199.42 3193.10 7499.26 7598.99 55
CP-MVS96.44 3596.08 4997.54 1198.29 6494.62 1496.80 2298.08 5492.67 7795.08 15196.39 14394.77 5499.42 3193.17 7199.44 4598.58 112
ZNCC-MVS96.42 3696.20 4197.07 3098.80 2792.79 4896.08 5598.16 4491.74 11195.34 13696.36 14695.68 1999.44 2694.41 2199.28 7398.97 61
region2R96.41 3796.09 4897.38 2398.62 3293.81 3696.32 4597.96 7792.26 8795.28 14096.57 13095.02 4799.41 3893.63 4299.11 9698.94 64
SteuartSystems-ACMMP96.40 3896.30 3696.71 4298.63 3191.96 5795.70 6998.01 7093.34 6996.64 7596.57 13094.99 4999.36 6093.48 5199.34 5898.82 80
Skip Steuart: Steuart Systems R&D Blog.
HFP-MVS96.39 3996.17 4497.04 3198.51 4793.37 4096.30 4897.98 7392.35 8495.63 12396.47 13395.37 2899.27 7793.78 3899.14 9298.48 118
LPG-MVS_test96.38 4096.23 3996.84 4098.36 6292.13 5495.33 8398.25 2891.78 10797.07 5497.22 8696.38 1399.28 7592.07 9999.59 2799.11 43
nrg03096.32 4196.55 2695.62 8097.83 9688.55 11595.77 6798.29 2792.68 7598.03 2697.91 4695.13 4098.95 12393.85 3699.49 3899.36 24
PGM-MVS96.32 4195.94 5597.43 1998.59 3793.84 3395.33 8398.30 2491.40 12095.76 11796.87 10795.26 3599.45 2592.77 8299.21 8299.00 53
ACMM88.83 996.30 4396.07 5096.97 3598.39 5892.95 4694.74 10698.03 6690.82 13397.15 5296.85 10896.25 1599.00 11593.10 7499.33 6098.95 63
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
GST-MVS96.24 4495.99 5497.00 3498.65 3092.71 4995.69 7198.01 7092.08 9295.74 11996.28 15195.22 3799.42 3193.17 7199.06 9898.88 74
ACMMP_NAP96.21 4596.12 4796.49 5098.90 1891.42 6494.57 11498.03 6690.42 14496.37 8397.35 7895.68 1999.25 7994.44 2099.34 5898.80 82
CP-MVSNet96.19 4696.80 1794.38 13798.99 1483.82 20096.31 4697.53 11397.60 798.34 1997.52 6391.98 11799.63 693.08 7699.81 999.70 3
MP-MVScopyleft96.14 4795.68 6797.51 1398.81 2594.06 2196.10 5497.78 9692.73 7493.48 20096.72 12194.23 6699.42 3191.99 10199.29 6899.05 50
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
LS3D96.11 4895.83 6296.95 3794.75 26294.20 1997.34 1197.98 7397.31 1195.32 13796.77 11393.08 9099.20 8591.79 10898.16 20497.44 206
MP-MVS-pluss96.08 4995.92 5796.57 4699.06 1091.21 6693.25 15398.32 2187.89 19796.86 6697.38 7195.55 2499.39 5095.47 1099.47 3999.11 43
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
TranMVSNet+NR-MVSNet96.07 5096.26 3895.50 8598.26 6787.69 13293.75 14197.86 8495.96 3097.48 4297.14 9095.33 3299.44 2690.79 12999.76 1199.38 22
PS-MVSNAJss96.01 5196.04 5295.89 6898.82 2488.51 11795.57 7697.88 8388.72 18098.81 698.86 1090.77 14799.60 895.43 1199.53 3599.57 13
SED-MVS96.00 5296.41 3294.76 11498.51 4786.97 14695.21 8798.10 5091.95 9497.63 3397.25 8396.48 1199.35 6193.29 6599.29 6897.95 162
DVP-MVS++95.93 5396.34 3494.70 11796.54 17186.66 15598.45 498.22 3393.26 7097.54 3897.36 7593.12 8899.38 5693.88 3498.68 14898.04 149
DPE-MVScopyleft95.89 5495.88 5895.92 6597.93 9389.83 8893.46 14998.30 2492.37 8297.75 3096.95 10095.14 3999.51 1891.74 11099.28 7398.41 124
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
#test#95.89 5495.51 7297.04 3198.51 4793.37 4095.14 9297.98 7389.34 16595.63 12396.47 13395.37 2899.27 7791.99 10199.14 9298.48 118
SF-MVS95.88 5695.88 5895.87 6998.12 7589.65 9195.58 7598.56 1291.84 10396.36 8496.68 12394.37 6499.32 7092.41 9399.05 10398.64 103
3Dnovator+92.74 295.86 5795.77 6596.13 5596.81 15790.79 7696.30 4897.82 9096.13 2594.74 16597.23 8591.33 13299.16 8893.25 6898.30 18898.46 120
DVP-MVScopyleft95.82 5896.18 4294.72 11698.51 4786.69 15395.20 8997.00 15391.85 10097.40 4797.35 7895.58 2299.34 6493.44 5799.31 6398.13 143
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
SMA-MVScopyleft95.77 5995.54 7196.47 5198.27 6691.19 6795.09 9397.79 9586.48 21997.42 4697.51 6594.47 6399.29 7393.55 4699.29 6898.93 65
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
test_040295.73 6096.22 4094.26 13998.19 7285.77 17693.24 15497.24 13896.88 1697.69 3197.77 5294.12 6899.13 9391.54 11899.29 6897.88 172
CS-MVS95.72 6195.58 7096.15 5396.86 15391.06 6996.74 2599.07 494.22 5092.42 23794.79 22693.58 7399.48 2493.45 5499.06 9897.91 168
ACMP88.15 1395.71 6295.43 7696.54 4798.17 7391.73 6294.24 12598.08 5489.46 16196.61 7796.47 13395.85 1799.12 9590.45 13599.56 3398.77 86
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
XVG-ACMP-BASELINE95.68 6395.34 7896.69 4398.40 5793.04 4394.54 11998.05 6190.45 14396.31 8896.76 11592.91 9598.72 16291.19 12299.42 4798.32 127
DP-MVS95.62 6495.84 6194.97 10697.16 13788.62 11294.54 11997.64 10296.94 1596.58 7897.32 8193.07 9198.72 16290.45 13598.84 12797.57 196
OPM-MVS95.61 6595.45 7496.08 5698.49 5591.00 7192.65 16997.33 13090.05 14996.77 7196.85 10895.04 4598.56 18892.77 8299.06 9898.70 96
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
RPSCF95.58 6694.89 9497.62 897.58 11696.30 495.97 6097.53 11392.42 8093.41 20197.78 5091.21 13897.77 25691.06 12397.06 25398.80 82
MIMVSNet195.52 6795.45 7495.72 7799.14 589.02 10396.23 5196.87 16693.73 6197.87 2798.49 2490.73 15199.05 10586.43 22799.60 2599.10 46
Anonymous2024052995.50 6895.83 6294.50 12997.33 13085.93 17395.19 9196.77 17496.64 1997.61 3698.05 3893.23 8498.79 14888.60 18899.04 10898.78 84
Vis-MVSNetpermissive95.50 6895.48 7395.56 8498.11 7689.40 9895.35 8198.22 3392.36 8394.11 17898.07 3792.02 11499.44 2693.38 6297.67 23697.85 176
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
DROMVSNet95.44 7095.62 6994.89 10896.93 14887.69 13296.48 3599.14 393.93 5792.77 22594.52 23493.95 7099.49 2293.62 4399.22 8197.51 201
pm-mvs195.43 7195.94 5593.93 15098.38 5985.08 18495.46 8097.12 14791.84 10397.28 4998.46 2595.30 3497.71 26190.17 15099.42 4798.99 55
DeepC-MVS91.39 495.43 7195.33 7995.71 7897.67 11090.17 8293.86 13998.02 6887.35 20896.22 9697.99 4294.48 6299.05 10592.73 8599.68 1897.93 164
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
XVG-OURS-SEG-HR95.38 7395.00 9196.51 4898.10 7794.07 2092.46 17798.13 4690.69 13693.75 19296.25 15498.03 297.02 29092.08 9895.55 28998.45 121
UniMVSNet_NR-MVSNet95.35 7495.21 8495.76 7597.69 10888.59 11392.26 19097.84 8894.91 3896.80 6995.78 17790.42 15699.41 3891.60 11599.58 3199.29 28
MSP-MVS95.34 7594.63 10897.48 1498.67 2994.05 2396.41 4098.18 3791.26 12395.12 14795.15 20586.60 21599.50 1993.43 5996.81 26398.89 72
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
FC-MVSNet-test95.32 7695.88 5893.62 16098.49 5581.77 22195.90 6398.32 2193.93 5797.53 4097.56 6088.48 17999.40 4592.91 8199.83 699.68 4
UniMVSNet (Re)95.32 7695.15 8695.80 7297.79 9988.91 10592.91 16198.07 5793.46 6796.31 8895.97 16690.14 16199.34 6492.11 9699.64 2399.16 37
Gipumacopyleft95.31 7895.80 6493.81 15797.99 9190.91 7396.42 3997.95 7996.69 1791.78 25598.85 1291.77 12195.49 32991.72 11199.08 9795.02 293
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
DU-MVS95.28 7995.12 8895.75 7697.75 10188.59 11392.58 17097.81 9193.99 5496.80 6995.90 16790.10 16599.41 3891.60 11599.58 3199.26 29
NR-MVSNet95.28 7995.28 8295.26 9697.75 10187.21 14095.08 9497.37 12193.92 5997.65 3295.90 16790.10 16599.33 6990.11 15299.66 2199.26 29
TransMVSNet (Re)95.27 8196.04 5292.97 18098.37 6181.92 22095.07 9596.76 17593.97 5697.77 2998.57 1995.72 1897.90 24188.89 18199.23 7999.08 47
SD-MVS95.19 8295.73 6693.55 16396.62 16588.88 10894.67 10898.05 6191.26 12397.25 5196.40 13995.42 2694.36 34692.72 8699.19 8597.40 210
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
CS-MVS-test95.15 8394.81 9696.19 5296.89 15091.14 6894.55 11798.85 694.31 4892.43 23691.91 30291.79 12099.49 2293.48 5199.06 9897.93 164
VPA-MVSNet95.14 8495.67 6893.58 16297.76 10083.15 20894.58 11397.58 10893.39 6897.05 5798.04 3993.25 8398.51 19389.75 16299.59 2799.08 47
xxxxxxxxxxxxxcwj95.03 8594.93 9295.33 9197.46 12488.05 12592.04 19898.42 1687.63 20496.36 8496.68 12394.37 6499.32 7092.41 9399.05 10398.64 103
HPM-MVS++copyleft95.02 8694.39 11596.91 3897.88 9493.58 3894.09 13196.99 15591.05 12892.40 23995.22 20491.03 14599.25 7992.11 9698.69 14797.90 170
APD-MVScopyleft95.00 8794.69 10395.93 6397.38 12790.88 7494.59 11197.81 9189.22 17095.46 13196.17 15993.42 7999.34 6489.30 16898.87 12597.56 198
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
PMVScopyleft87.21 1494.97 8895.33 7993.91 15298.97 1597.16 295.54 7795.85 21596.47 2193.40 20397.46 6795.31 3395.47 33086.18 23198.78 13989.11 357
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
TSAR-MVS + MP.94.96 8994.75 10095.57 8398.86 2188.69 10996.37 4196.81 17085.23 23994.75 16497.12 9191.85 11999.40 4593.45 5498.33 18398.62 107
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
SixPastTwentyTwo94.91 9095.21 8493.98 14698.52 4683.19 20795.93 6194.84 24594.86 3998.49 1598.74 1681.45 25799.60 894.69 1699.39 5499.15 38
FIs94.90 9195.35 7793.55 16398.28 6581.76 22295.33 8398.14 4593.05 7397.07 5497.18 8887.65 19399.29 7391.72 11199.69 1599.61 11
Regformer-494.90 9194.67 10695.59 8192.78 30789.02 10392.39 18295.91 21294.50 4396.41 8195.56 18992.10 11399.01 11394.23 2698.14 20698.74 90
AllTest94.88 9394.51 11396.00 5898.02 8692.17 5295.26 8698.43 1490.48 14195.04 15396.74 11892.54 10597.86 24785.11 24298.98 11197.98 158
ETH3D-3000-0.194.86 9494.55 11095.81 7097.61 11389.72 8994.05 13298.37 1888.09 19395.06 15295.85 16992.58 10399.10 9990.33 14298.99 11098.62 107
Regformer-294.86 9494.55 11095.77 7492.83 30589.98 8491.87 21096.40 19394.38 4796.19 10095.04 21292.47 10899.04 10893.49 4898.31 18698.28 131
FMVSNet194.84 9695.13 8793.97 14797.60 11484.29 19095.99 5796.56 18592.38 8197.03 5898.53 2190.12 16298.98 11688.78 18399.16 9098.65 99
ANet_high94.83 9796.28 3790.47 26396.65 16173.16 33194.33 12398.74 1096.39 2398.09 2598.93 893.37 8098.70 16890.38 13899.68 1899.53 14
testtj94.81 9894.42 11496.01 5797.23 13290.51 8094.77 10597.85 8791.29 12294.92 15895.66 18291.71 12399.40 4588.07 19898.25 19498.11 145
3Dnovator92.54 394.80 9994.90 9394.47 13295.47 24287.06 14396.63 2797.28 13691.82 10694.34 17697.41 6990.60 15498.65 17792.47 9198.11 21097.70 188
CPTT-MVS94.74 10094.12 12596.60 4598.15 7493.01 4495.84 6597.66 10189.21 17193.28 20795.46 19488.89 17698.98 11689.80 15998.82 13397.80 181
XVG-OURS94.72 10194.12 12596.50 4998.00 8894.23 1891.48 22398.17 4190.72 13595.30 13896.47 13387.94 19096.98 29191.41 12097.61 23998.30 130
CSCG94.69 10294.75 10094.52 12897.55 11887.87 12995.01 9897.57 10992.68 7596.20 9893.44 26891.92 11898.78 15289.11 17699.24 7896.92 228
v1094.68 10395.27 8392.90 18596.57 16880.15 24094.65 11097.57 10990.68 13797.43 4498.00 4188.18 18399.15 8994.84 1599.55 3499.41 20
v894.65 10495.29 8192.74 19096.65 16179.77 25494.59 11197.17 14291.86 9997.47 4397.93 4488.16 18499.08 10094.32 2299.47 3999.38 22
canonicalmvs94.59 10594.69 10394.30 13895.60 23987.03 14595.59 7398.24 3191.56 11795.21 14692.04 30194.95 5098.66 17591.45 11997.57 24097.20 220
CNVR-MVS94.58 10694.29 11995.46 8796.94 14689.35 10091.81 21696.80 17189.66 15793.90 18995.44 19692.80 9998.72 16292.74 8498.52 16398.32 127
GeoE94.55 10794.68 10594.15 14197.23 13285.11 18394.14 12997.34 12988.71 18195.26 14195.50 19294.65 5799.12 9590.94 12798.40 17198.23 134
Regformer-194.55 10794.33 11895.19 9992.83 30588.54 11691.87 21095.84 21693.99 5495.95 10895.04 21292.00 11598.79 14893.14 7398.31 18698.23 134
EG-PatchMatch MVS94.54 10994.67 10694.14 14297.87 9586.50 15792.00 20196.74 17688.16 19296.93 6397.61 5893.04 9297.90 24191.60 11598.12 20998.03 152
IS-MVSNet94.49 11094.35 11794.92 10798.25 6986.46 16097.13 1594.31 25996.24 2496.28 9396.36 14682.88 24199.35 6188.19 19399.52 3798.96 62
Baseline_NR-MVSNet94.47 11195.09 8992.60 19798.50 5480.82 23692.08 19696.68 17893.82 6096.29 9098.56 2090.10 16597.75 25990.10 15499.66 2199.24 31
test_part194.39 11294.55 11093.92 15196.14 20382.86 21295.54 7798.09 5395.36 3698.27 2098.36 2875.91 29899.44 2693.41 6099.84 399.47 17
VDD-MVS94.37 11394.37 11694.40 13697.49 12186.07 17193.97 13693.28 27694.49 4496.24 9497.78 5087.99 18998.79 14888.92 17999.14 9298.34 126
EI-MVSNet-Vis-set94.36 11494.28 12094.61 12092.55 30985.98 17292.44 17894.69 25293.70 6296.12 10395.81 17391.24 13698.86 13593.76 4198.22 19998.98 60
EI-MVSNet-UG-set94.35 11594.27 12294.59 12592.46 31085.87 17492.42 18094.69 25293.67 6696.13 10295.84 17291.20 13998.86 13593.78 3898.23 19799.03 51
PHI-MVS94.34 11693.80 13095.95 6095.65 23591.67 6394.82 10397.86 8487.86 19893.04 21894.16 24691.58 12698.78 15290.27 14598.96 11797.41 207
casdiffmvs94.32 11794.80 9892.85 18796.05 21081.44 22792.35 18598.05 6191.53 11895.75 11896.80 11293.35 8198.49 19491.01 12698.32 18598.64 103
Regformer-394.28 11894.23 12494.46 13392.78 30786.28 16792.39 18294.70 25193.69 6595.97 10695.56 18991.34 13198.48 19893.45 5498.14 20698.62 107
tfpnnormal94.27 11994.87 9592.48 20297.71 10580.88 23594.55 11795.41 23293.70 6296.67 7497.72 5391.40 13098.18 22187.45 20899.18 8798.36 125
HQP_MVS94.26 12093.93 12795.23 9897.71 10588.12 12394.56 11597.81 9191.74 11193.31 20495.59 18486.93 20798.95 12389.26 17298.51 16598.60 110
baseline94.26 12094.80 9892.64 19396.08 20880.99 23393.69 14398.04 6590.80 13494.89 15996.32 14893.19 8598.48 19891.68 11398.51 16598.43 122
OMC-MVS94.22 12293.69 13595.81 7097.25 13191.27 6592.27 18997.40 12087.10 21494.56 16995.42 19793.74 7198.11 22686.62 22298.85 12698.06 146
LCM-MVSNet-Re94.20 12394.58 10993.04 17795.91 22183.13 20993.79 14099.19 292.00 9398.84 598.04 3993.64 7299.02 11181.28 27998.54 16196.96 227
DeepPCF-MVS90.46 694.20 12393.56 14196.14 5495.96 21792.96 4589.48 27797.46 11785.14 24296.23 9595.42 19793.19 8598.08 22790.37 13998.76 14197.38 213
KD-MVS_self_test94.10 12594.73 10292.19 20897.66 11179.49 25994.86 10297.12 14789.59 16096.87 6597.65 5690.40 15998.34 20789.08 17799.35 5798.75 87
NCCC94.08 12693.54 14295.70 7996.49 17689.90 8792.39 18296.91 16290.64 13892.33 24594.60 23190.58 15598.96 12190.21 14997.70 23498.23 134
VDDNet94.03 12794.27 12293.31 17298.87 2082.36 21695.51 7991.78 30697.19 1296.32 8798.60 1884.24 23298.75 15787.09 21598.83 13298.81 81
ETH3D cwj APD-0.1693.99 12893.38 14695.80 7296.82 15589.92 8592.72 16598.02 6884.73 25293.65 19695.54 19191.68 12499.22 8288.78 18398.49 16898.26 133
dcpmvs_293.96 12995.01 9090.82 25597.60 11474.04 32693.68 14598.85 689.80 15597.82 2897.01 9991.14 14399.21 8390.56 13398.59 15599.19 35
EPP-MVSNet93.91 13093.68 13694.59 12598.08 7885.55 17997.44 1094.03 26494.22 5094.94 15696.19 15682.07 25299.57 1387.28 21298.89 12098.65 99
Effi-MVS+-dtu93.90 13192.60 16697.77 494.74 26496.67 394.00 13495.41 23289.94 15091.93 25392.13 29990.12 16298.97 12087.68 20597.48 24297.67 191
IterMVS-LS93.78 13294.28 12092.27 20596.27 19279.21 26691.87 21096.78 17291.77 10996.57 7997.07 9387.15 20298.74 16091.99 10199.03 10998.86 75
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
DeepC-MVS_fast89.96 793.73 13393.44 14494.60 12496.14 20387.90 12893.36 15297.14 14485.53 23693.90 18995.45 19591.30 13498.59 18489.51 16598.62 15297.31 216
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
MVS_111021_LR93.66 13493.28 14994.80 11296.25 19590.95 7290.21 25595.43 23187.91 19593.74 19494.40 23792.88 9796.38 31190.39 13798.28 18997.07 221
MVS_111021_HR93.63 13593.42 14594.26 13996.65 16186.96 14889.30 28396.23 20188.36 18993.57 19894.60 23193.45 7697.77 25690.23 14898.38 17698.03 152
v114493.50 13693.81 12992.57 19896.28 19179.61 25791.86 21496.96 15686.95 21695.91 11296.32 14887.65 19398.96 12193.51 4798.88 12299.13 40
v119293.49 13793.78 13192.62 19696.16 20179.62 25691.83 21597.22 14086.07 22796.10 10496.38 14487.22 20099.02 11194.14 2998.88 12299.22 32
WR-MVS93.49 13793.72 13392.80 18997.57 11780.03 24690.14 25995.68 21993.70 6296.62 7695.39 20087.21 20199.04 10887.50 20799.64 2399.33 25
V4293.43 13993.58 13992.97 18095.34 24881.22 23092.67 16896.49 19087.25 21096.20 9896.37 14587.32 19998.85 13792.39 9598.21 20098.85 78
K. test v393.37 14093.27 15093.66 15998.05 8182.62 21494.35 12286.62 33796.05 2897.51 4198.85 1276.59 29699.65 393.21 6998.20 20298.73 92
PM-MVS93.33 14192.67 16495.33 9196.58 16794.06 2192.26 19092.18 29785.92 23096.22 9696.61 12885.64 22695.99 32290.35 14098.23 19795.93 266
v124093.29 14293.71 13492.06 21596.01 21577.89 28491.81 21697.37 12185.12 24496.69 7396.40 13986.67 21399.07 10494.51 1898.76 14199.22 32
test_prior393.29 14292.85 15694.61 12095.95 21887.23 13890.21 25597.36 12689.33 16690.77 26894.81 22290.41 15798.68 17288.21 19198.55 15897.93 164
v2v48293.29 14293.63 13792.29 20496.35 18578.82 27291.77 21896.28 19788.45 18695.70 12296.26 15386.02 22198.90 12793.02 7798.81 13599.14 39
alignmvs93.26 14592.85 15694.50 12995.70 23187.45 13493.45 15095.76 21791.58 11695.25 14392.42 29581.96 25498.72 16291.61 11497.87 22697.33 215
v192192093.26 14593.61 13892.19 20896.04 21478.31 27891.88 20997.24 13885.17 24196.19 10096.19 15686.76 21299.05 10594.18 2898.84 12799.22 32
MSLP-MVS++93.25 14793.88 12891.37 23396.34 18682.81 21393.11 15597.74 9789.37 16494.08 18095.29 20390.40 15996.35 31390.35 14098.25 19494.96 294
GBi-Net93.21 14892.96 15393.97 14795.40 24484.29 19095.99 5796.56 18588.63 18295.10 14898.53 2181.31 25998.98 11686.74 21898.38 17698.65 99
test193.21 14892.96 15393.97 14795.40 24484.29 19095.99 5796.56 18588.63 18295.10 14898.53 2181.31 25998.98 11686.74 21898.38 17698.65 99
v14419293.20 15093.54 14292.16 21296.05 21078.26 27991.95 20297.14 14484.98 24895.96 10796.11 16087.08 20499.04 10893.79 3798.84 12799.17 36
VPNet93.08 15193.76 13291.03 24598.60 3575.83 31291.51 22295.62 22091.84 10395.74 11997.10 9289.31 17398.32 20885.07 24499.06 9898.93 65
UGNet93.08 15192.50 16894.79 11393.87 28887.99 12795.07 9594.26 26190.64 13887.33 32597.67 5586.89 21098.49 19488.10 19698.71 14497.91 168
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
mvs-test193.07 15391.80 18396.89 3994.74 26495.83 692.17 19395.41 23289.94 15089.85 28790.59 32590.12 16298.88 13087.68 20595.66 28795.97 264
TSAR-MVS + GP.93.07 15392.41 17095.06 10495.82 22490.87 7590.97 23492.61 29188.04 19494.61 16893.79 26088.08 18597.81 25189.41 16798.39 17496.50 244
ETV-MVS92.99 15592.74 16093.72 15895.86 22386.30 16692.33 18697.84 8891.70 11492.81 22386.17 35892.22 11099.19 8688.03 19997.73 23095.66 279
EI-MVSNet92.99 15593.26 15192.19 20892.12 31779.21 26692.32 18794.67 25491.77 10995.24 14495.85 16987.14 20398.49 19491.99 10198.26 19198.86 75
MCST-MVS92.91 15792.51 16794.10 14397.52 11985.72 17791.36 22797.13 14680.33 28692.91 22294.24 24291.23 13798.72 16289.99 15697.93 22397.86 174
h-mvs3392.89 15891.99 17795.58 8296.97 14490.55 7893.94 13794.01 26789.23 16893.95 18696.19 15676.88 29399.14 9191.02 12495.71 28697.04 224
QAPM92.88 15992.77 15893.22 17595.82 22483.31 20496.45 3697.35 12883.91 25793.75 19296.77 11389.25 17498.88 13084.56 25097.02 25597.49 202
v14892.87 16093.29 14791.62 22796.25 19577.72 28791.28 22895.05 23889.69 15695.93 11196.04 16287.34 19898.38 20390.05 15597.99 22098.78 84
Anonymous2024052192.86 16193.57 14090.74 25796.57 16875.50 31494.15 12895.60 22189.38 16395.90 11397.90 4880.39 26697.96 23992.60 8999.68 1898.75 87
Effi-MVS+92.79 16292.74 16092.94 18395.10 25283.30 20594.00 13497.53 11391.36 12189.35 29690.65 32494.01 6998.66 17587.40 21095.30 29796.88 231
FMVSNet292.78 16392.73 16292.95 18295.40 24481.98 21994.18 12795.53 22988.63 18296.05 10597.37 7281.31 25998.81 14587.38 21198.67 15098.06 146
Fast-Effi-MVS+-dtu92.77 16492.16 17294.58 12794.66 27088.25 12092.05 19796.65 18089.62 15890.08 28191.23 31292.56 10498.60 18286.30 22996.27 27596.90 229
LF4IMVS92.72 16592.02 17694.84 11195.65 23591.99 5692.92 16096.60 18285.08 24692.44 23593.62 26386.80 21196.35 31386.81 21798.25 19496.18 257
train_agg92.71 16691.83 18195.35 8996.45 17889.46 9490.60 24396.92 16079.37 29590.49 27394.39 23891.20 13998.88 13088.66 18798.43 17097.72 187
VNet92.67 16792.96 15391.79 22096.27 19280.15 24091.95 20294.98 24092.19 9094.52 17196.07 16187.43 19797.39 27884.83 24698.38 17697.83 177
CDPH-MVS92.67 16791.83 18195.18 10096.94 14688.46 11890.70 24197.07 15077.38 31192.34 24495.08 21092.67 10298.88 13085.74 23398.57 15798.20 138
agg_prior192.60 16991.76 18495.10 10396.20 19788.89 10690.37 25096.88 16479.67 29290.21 27894.41 23691.30 13498.78 15288.46 19098.37 18197.64 193
Anonymous20240521192.58 17092.50 16892.83 18896.55 17083.22 20692.43 17991.64 30794.10 5395.59 12596.64 12681.88 25697.50 26985.12 24198.52 16397.77 183
XXY-MVS92.58 17093.16 15290.84 25497.75 10179.84 25091.87 21096.22 20385.94 22995.53 12897.68 5492.69 10194.48 34283.21 26097.51 24198.21 137
MVS_Test92.57 17293.29 14790.40 26693.53 29275.85 31092.52 17296.96 15688.73 17992.35 24296.70 12290.77 14798.37 20692.53 9095.49 29196.99 226
TAPA-MVS88.58 1092.49 17391.75 18594.73 11596.50 17589.69 9092.91 16197.68 10078.02 30992.79 22494.10 24790.85 14697.96 23984.76 24898.16 20496.54 239
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
patch_mono-292.46 17492.72 16391.71 22496.65 16178.91 27088.85 29297.17 14283.89 25892.45 23496.76 11589.86 16997.09 28790.24 14798.59 15599.12 42
ab-mvs92.40 17592.62 16591.74 22297.02 14281.65 22395.84 6595.50 23086.95 21692.95 22197.56 6090.70 15297.50 26979.63 29797.43 24496.06 261
CANet92.38 17691.99 17793.52 16793.82 29083.46 20391.14 23097.00 15389.81 15486.47 32994.04 24987.90 19199.21 8389.50 16698.27 19097.90 170
EIA-MVS92.35 17792.03 17593.30 17395.81 22683.97 19892.80 16498.17 4187.71 20189.79 29087.56 34891.17 14299.18 8787.97 20097.27 24896.77 235
DP-MVS Recon92.31 17891.88 18093.60 16197.18 13686.87 14991.10 23297.37 12184.92 24992.08 25094.08 24888.59 17898.20 21883.50 25798.14 20695.73 275
F-COLMAP92.28 17991.06 20295.95 6097.52 11991.90 5893.53 14797.18 14183.98 25688.70 30894.04 24988.41 18198.55 19080.17 29095.99 28097.39 211
OpenMVScopyleft89.45 892.27 18092.13 17492.68 19294.53 27384.10 19695.70 6997.03 15182.44 27491.14 26596.42 13788.47 18098.38 20385.95 23297.47 24395.55 283
hse-mvs292.24 18191.20 19895.38 8896.16 20190.65 7792.52 17292.01 30489.23 16893.95 18692.99 27876.88 29398.69 17091.02 12496.03 27896.81 233
MVSFormer92.18 18292.23 17192.04 21694.74 26480.06 24497.15 1397.37 12188.98 17488.83 30092.79 28377.02 29099.60 896.41 496.75 26696.46 246
HQP-MVS92.09 18391.49 19193.88 15496.36 18284.89 18591.37 22497.31 13187.16 21188.81 30293.40 26984.76 22998.60 18286.55 22497.73 23098.14 141
DELS-MVS92.05 18492.16 17291.72 22394.44 27480.13 24287.62 30597.25 13787.34 20992.22 24793.18 27589.54 17298.73 16189.67 16398.20 20296.30 252
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
TinyColmap92.00 18592.76 15989.71 28295.62 23877.02 29590.72 24096.17 20687.70 20295.26 14196.29 15092.54 10596.45 30881.77 27498.77 14095.66 279
ETH3 D test640091.91 18691.25 19793.89 15396.59 16684.41 18992.10 19597.72 9978.52 30591.82 25493.78 26188.70 17799.13 9383.61 25698.39 17498.14 141
CLD-MVS91.82 18791.41 19393.04 17796.37 18083.65 20286.82 32497.29 13484.65 25392.27 24689.67 33492.20 11197.85 24983.95 25499.47 3997.62 194
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
diffmvs91.74 18891.93 17991.15 24393.06 30078.17 28088.77 29597.51 11686.28 22392.42 23793.96 25488.04 18797.46 27290.69 13296.67 26897.82 179
CNLPA91.72 18991.20 19893.26 17496.17 20091.02 7091.14 23095.55 22890.16 14890.87 26793.56 26686.31 21794.40 34579.92 29697.12 25294.37 307
IterMVS-SCA-FT91.65 19091.55 18791.94 21793.89 28779.22 26587.56 30893.51 27391.53 11895.37 13496.62 12778.65 27598.90 12791.89 10694.95 30397.70 188
PVSNet_Blended_VisFu91.63 19191.20 19892.94 18397.73 10483.95 19992.14 19497.46 11778.85 30492.35 24294.98 21584.16 23399.08 10086.36 22896.77 26595.79 273
AdaColmapbinary91.63 19191.36 19492.47 20395.56 24086.36 16492.24 19296.27 19888.88 17889.90 28692.69 28691.65 12598.32 20877.38 31697.64 23792.72 340
pmmvs-eth3d91.54 19390.73 21093.99 14595.76 22987.86 13090.83 23793.98 26878.23 30894.02 18596.22 15582.62 24796.83 29786.57 22398.33 18397.29 217
API-MVS91.52 19491.61 18691.26 23794.16 27986.26 16894.66 10994.82 24691.17 12692.13 24991.08 31590.03 16897.06 28979.09 30497.35 24790.45 355
xiu_mvs_v1_base_debu91.47 19591.52 18891.33 23495.69 23281.56 22489.92 26696.05 20983.22 26291.26 26190.74 31991.55 12798.82 14089.29 16995.91 28193.62 326
xiu_mvs_v1_base91.47 19591.52 18891.33 23495.69 23281.56 22489.92 26696.05 20983.22 26291.26 26190.74 31991.55 12798.82 14089.29 16995.91 28193.62 326
xiu_mvs_v1_base_debi91.47 19591.52 18891.33 23495.69 23281.56 22489.92 26696.05 20983.22 26291.26 26190.74 31991.55 12798.82 14089.29 16995.91 28193.62 326
RRT_MVS91.36 19890.05 22595.29 9589.21 35488.15 12292.51 17694.89 24386.73 21895.54 12795.68 18161.82 35399.30 7294.91 1399.13 9598.43 122
LFMVS91.33 19991.16 20191.82 21996.27 19279.36 26195.01 9885.61 34896.04 2994.82 16197.06 9472.03 31298.46 20084.96 24598.70 14697.65 192
c3_l91.32 20091.42 19291.00 24892.29 31276.79 30187.52 31196.42 19285.76 23394.72 16793.89 25782.73 24498.16 22390.93 12898.55 15898.04 149
Fast-Effi-MVS+91.28 20190.86 20592.53 20095.45 24382.53 21589.25 28696.52 18985.00 24789.91 28588.55 34492.94 9398.84 13884.72 24995.44 29396.22 255
MDA-MVSNet-bldmvs91.04 20290.88 20491.55 22994.68 26980.16 23985.49 33692.14 30090.41 14594.93 15795.79 17485.10 22796.93 29485.15 23994.19 32097.57 196
PAPM_NR91.03 20390.81 20791.68 22696.73 15981.10 23293.72 14296.35 19688.19 19188.77 30692.12 30085.09 22897.25 28282.40 26993.90 32196.68 238
MVS_030490.96 20490.15 22393.37 16993.17 29787.06 14393.62 14692.43 29589.60 15982.25 35495.50 19282.56 24897.83 25084.41 25297.83 22895.22 287
MSDG90.82 20590.67 21191.26 23794.16 27983.08 21086.63 32996.19 20490.60 14091.94 25291.89 30389.16 17595.75 32480.96 28594.51 31394.95 295
test20.0390.80 20690.85 20690.63 26095.63 23779.24 26489.81 27192.87 28289.90 15294.39 17396.40 13985.77 22295.27 33773.86 33599.05 10397.39 211
FMVSNet390.78 20790.32 21992.16 21293.03 30279.92 24992.54 17194.95 24186.17 22695.10 14896.01 16469.97 31898.75 15786.74 21898.38 17697.82 179
eth_miper_zixun_eth90.72 20890.61 21291.05 24492.04 31976.84 30086.91 32096.67 17985.21 24094.41 17293.92 25579.53 27098.26 21489.76 16197.02 25598.06 146
X-MVStestdata90.70 20988.45 25197.44 1798.56 3893.99 2796.50 3397.95 7994.58 4194.38 17426.89 37494.56 5999.39 5093.57 4499.05 10398.93 65
BH-untuned90.68 21090.90 20390.05 27795.98 21679.57 25890.04 26294.94 24287.91 19594.07 18193.00 27787.76 19297.78 25579.19 30395.17 30092.80 338
cl____90.65 21190.56 21490.91 25291.85 32176.98 29886.75 32595.36 23585.53 23694.06 18294.89 21977.36 28897.98 23890.27 14598.98 11197.76 184
DIV-MVS_self_test90.65 21190.56 21490.91 25291.85 32176.99 29786.75 32595.36 23585.52 23894.06 18294.89 21977.37 28797.99 23790.28 14498.97 11597.76 184
114514_t90.51 21389.80 22992.63 19598.00 8882.24 21793.40 15197.29 13465.84 36189.40 29594.80 22586.99 20598.75 15783.88 25598.61 15396.89 230
miper_ehance_all_eth90.48 21490.42 21790.69 25891.62 32676.57 30386.83 32396.18 20583.38 26094.06 18292.66 28882.20 25098.04 22989.79 16097.02 25597.45 204
BH-RMVSNet90.47 21590.44 21690.56 26295.21 25178.65 27689.15 28793.94 26988.21 19092.74 22694.22 24386.38 21697.88 24378.67 30695.39 29595.14 290
Vis-MVSNet (Re-imp)90.42 21690.16 22091.20 24197.66 11177.32 29294.33 12387.66 33091.20 12592.99 21995.13 20775.40 30098.28 21077.86 30999.19 8597.99 157
PLCcopyleft85.34 1590.40 21788.92 24394.85 11096.53 17490.02 8391.58 22196.48 19180.16 28786.14 33192.18 29785.73 22398.25 21576.87 31994.61 31296.30 252
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
test111190.39 21890.61 21289.74 28198.04 8471.50 34295.59 7379.72 37189.41 16295.94 11098.14 3370.79 31598.81 14588.52 18999.32 6298.90 71
testgi90.38 21991.34 19587.50 31697.49 12171.54 34189.43 27895.16 23788.38 18894.54 17094.68 23092.88 9793.09 35671.60 34897.85 22797.88 172
mvs_anonymous90.37 22091.30 19687.58 31592.17 31668.00 35589.84 27094.73 25083.82 25993.22 21297.40 7087.54 19597.40 27787.94 20195.05 30297.34 214
PVSNet_BlendedMVS90.35 22189.96 22691.54 23094.81 25978.80 27490.14 25996.93 15879.43 29488.68 30995.06 21186.27 21898.15 22480.27 28798.04 21697.68 190
UnsupCasMVSNet_eth90.33 22290.34 21890.28 26894.64 27180.24 23889.69 27395.88 21385.77 23293.94 18895.69 18081.99 25392.98 35784.21 25391.30 34897.62 194
MAR-MVS90.32 22388.87 24694.66 11994.82 25891.85 5994.22 12694.75 24980.91 28187.52 32388.07 34786.63 21497.87 24676.67 32096.21 27694.25 310
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
RPMNet90.31 22490.14 22490.81 25691.01 33378.93 26892.52 17298.12 4791.91 9789.10 29796.89 10668.84 31999.41 3890.17 15092.70 33794.08 311
112190.26 22589.23 23593.34 17097.15 13987.40 13591.94 20494.39 25767.88 35691.02 26694.91 21886.91 20998.59 18481.17 28297.71 23394.02 316
IterMVS90.18 22690.16 22090.21 27293.15 29875.98 30987.56 30892.97 28186.43 22194.09 17996.40 13978.32 27997.43 27487.87 20294.69 31097.23 218
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
TAMVS90.16 22789.05 24093.49 16896.49 17686.37 16390.34 25292.55 29280.84 28492.99 21994.57 23381.94 25598.20 21873.51 33698.21 20095.90 269
ECVR-MVScopyleft90.12 22890.16 22090.00 27897.81 9772.68 33695.76 6878.54 37289.04 17295.36 13598.10 3570.51 31698.64 17887.10 21499.18 8798.67 97
test_yl90.11 22989.73 23291.26 23794.09 28279.82 25190.44 24792.65 28890.90 12993.19 21393.30 27173.90 30398.03 23082.23 27096.87 26195.93 266
DCV-MVSNet90.11 22989.73 23291.26 23794.09 28279.82 25190.44 24792.65 28890.90 12993.19 21393.30 27173.90 30398.03 23082.23 27096.87 26195.93 266
Patchmtry90.11 22989.92 22790.66 25990.35 34277.00 29692.96 15992.81 28390.25 14794.74 16596.93 10367.11 32497.52 26885.17 23798.98 11197.46 203
MVP-Stereo90.07 23288.92 24393.54 16596.31 18986.49 15890.93 23595.59 22579.80 28891.48 25795.59 18480.79 26397.39 27878.57 30791.19 34996.76 236
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
AUN-MVS90.05 23388.30 25495.32 9496.09 20790.52 7992.42 18092.05 30382.08 27788.45 31192.86 28065.76 33498.69 17088.91 18096.07 27796.75 237
CL-MVSNet_self_test90.04 23489.90 22890.47 26395.24 25077.81 28586.60 33192.62 29085.64 23593.25 21193.92 25583.84 23496.06 32079.93 29498.03 21797.53 200
bset_n11_16_dypcd89.99 23589.15 23892.53 20094.75 26281.34 22884.19 34887.56 33185.13 24393.77 19192.46 29072.82 30799.01 11392.46 9299.21 8297.23 218
D2MVS89.93 23689.60 23490.92 25094.03 28478.40 27788.69 29794.85 24478.96 30293.08 21595.09 20974.57 30196.94 29288.19 19398.96 11797.41 207
miper_lstm_enhance89.90 23789.80 22990.19 27491.37 33077.50 28983.82 35295.00 23984.84 25093.05 21794.96 21676.53 29795.20 33889.96 15798.67 15097.86 174
CANet_DTU89.85 23889.17 23791.87 21892.20 31580.02 24790.79 23895.87 21486.02 22882.53 35391.77 30580.01 26798.57 18785.66 23497.70 23497.01 225
tttt051789.81 23988.90 24592.55 19997.00 14379.73 25595.03 9783.65 36089.88 15395.30 13894.79 22653.64 36899.39 5091.99 10198.79 13898.54 113
EPNet89.80 24088.25 25694.45 13483.91 37586.18 16993.87 13887.07 33591.16 12780.64 36394.72 22878.83 27398.89 12985.17 23798.89 12098.28 131
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CDS-MVSNet89.55 24188.22 25993.53 16695.37 24786.49 15889.26 28493.59 27179.76 29091.15 26492.31 29677.12 28998.38 20377.51 31497.92 22495.71 276
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
MG-MVS89.54 24289.80 22988.76 29794.88 25572.47 33889.60 27492.44 29485.82 23189.48 29495.98 16582.85 24297.74 26081.87 27395.27 29896.08 260
OpenMVS_ROBcopyleft85.12 1689.52 24389.05 24090.92 25094.58 27281.21 23191.10 23293.41 27577.03 31593.41 20193.99 25383.23 23897.80 25279.93 29494.80 30793.74 323
DPM-MVS89.35 24488.40 25292.18 21196.13 20684.20 19486.96 31996.15 20775.40 32287.36 32491.55 31083.30 23798.01 23482.17 27296.62 26994.32 309
MVSTER89.32 24588.75 24791.03 24590.10 34476.62 30290.85 23694.67 25482.27 27595.24 14495.79 17461.09 35698.49 19490.49 13498.26 19197.97 161
PatchMatch-RL89.18 24688.02 26492.64 19395.90 22292.87 4788.67 29991.06 31080.34 28590.03 28391.67 30783.34 23694.42 34476.35 32394.84 30690.64 354
jason89.17 24788.32 25391.70 22595.73 23080.07 24388.10 30293.22 27771.98 33990.09 28092.79 28378.53 27898.56 18887.43 20997.06 25396.46 246
jason: jason.
PCF-MVS84.52 1789.12 24887.71 26793.34 17096.06 20985.84 17586.58 33297.31 13168.46 35493.61 19793.89 25787.51 19698.52 19267.85 35998.11 21095.66 279
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
cl2289.02 24988.50 25090.59 26189.76 34676.45 30486.62 33094.03 26482.98 26892.65 22892.49 28972.05 31197.53 26788.93 17897.02 25597.78 182
USDC89.02 24989.08 23988.84 29695.07 25374.50 32188.97 28996.39 19473.21 33393.27 20896.28 15182.16 25196.39 31077.55 31398.80 13795.62 282
xiu_mvs_v2_base89.00 25189.19 23688.46 30494.86 25774.63 31886.97 31895.60 22180.88 28287.83 31988.62 34391.04 14498.81 14582.51 26894.38 31491.93 346
new-patchmatchnet88.97 25290.79 20883.50 34394.28 27855.83 37785.34 33793.56 27286.18 22595.47 12995.73 17983.10 23996.51 30685.40 23698.06 21498.16 139
pmmvs488.95 25387.70 26892.70 19194.30 27785.60 17887.22 31492.16 29974.62 32589.75 29294.19 24477.97 28296.41 30982.71 26496.36 27496.09 259
N_pmnet88.90 25487.25 27493.83 15694.40 27693.81 3684.73 34187.09 33479.36 29793.26 20992.43 29479.29 27191.68 36177.50 31597.22 25096.00 263
PS-MVSNAJ88.86 25588.99 24288.48 30394.88 25574.71 31686.69 32795.60 22180.88 28287.83 31987.37 35190.77 14798.82 14082.52 26794.37 31591.93 346
Patchmatch-RL test88.81 25688.52 24989.69 28395.33 24979.94 24886.22 33392.71 28778.46 30695.80 11694.18 24566.25 33295.33 33589.22 17498.53 16293.78 321
Anonymous2023120688.77 25788.29 25590.20 27396.31 18978.81 27389.56 27693.49 27474.26 32792.38 24095.58 18782.21 24995.43 33272.07 34498.75 14396.34 250
PVSNet_Blended88.74 25888.16 26290.46 26594.81 25978.80 27486.64 32896.93 15874.67 32488.68 30989.18 34086.27 21898.15 22480.27 28796.00 27994.44 306
thisisatest053088.69 25987.52 27092.20 20796.33 18779.36 26192.81 16384.01 35986.44 22093.67 19592.68 28753.62 36999.25 7989.65 16498.45 16998.00 154
ppachtmachnet_test88.61 26088.64 24888.50 30291.76 32370.99 34584.59 34492.98 28079.30 29992.38 24093.53 26779.57 26997.45 27386.50 22697.17 25197.07 221
UnsupCasMVSNet_bld88.50 26188.03 26389.90 27995.52 24178.88 27187.39 31294.02 26679.32 29893.06 21694.02 25180.72 26494.27 34775.16 32993.08 33396.54 239
miper_enhance_ethall88.42 26287.87 26590.07 27588.67 35975.52 31385.10 33895.59 22575.68 31892.49 23289.45 33778.96 27297.88 24387.86 20397.02 25596.81 233
1112_ss88.42 26287.41 27191.45 23196.69 16080.99 23389.72 27296.72 17773.37 33287.00 32790.69 32277.38 28698.20 21881.38 27893.72 32495.15 289
lupinMVS88.34 26487.31 27291.45 23194.74 26480.06 24487.23 31392.27 29671.10 34388.83 30091.15 31377.02 29098.53 19186.67 22196.75 26695.76 274
RRT_test8_iter0588.21 26588.17 26088.33 30691.62 32666.82 36191.73 21996.60 18286.34 22294.14 17795.38 20247.72 37499.11 9791.78 10998.26 19199.06 49
YYNet188.17 26688.24 25787.93 31192.21 31473.62 32880.75 36088.77 32082.51 27394.99 15595.11 20882.70 24593.70 35183.33 25893.83 32296.48 245
MDA-MVSNet_test_wron88.16 26788.23 25887.93 31192.22 31373.71 32780.71 36188.84 31982.52 27294.88 16095.14 20682.70 24593.61 35283.28 25993.80 32396.46 246
MS-PatchMatch88.05 26887.75 26688.95 29393.28 29477.93 28287.88 30492.49 29375.42 32192.57 23193.59 26580.44 26594.24 34981.28 27992.75 33694.69 302
CR-MVSNet87.89 26987.12 27890.22 27191.01 33378.93 26892.52 17292.81 28373.08 33489.10 29796.93 10367.11 32497.64 26488.80 18292.70 33794.08 311
pmmvs587.87 27087.14 27790.07 27593.26 29676.97 29988.89 29192.18 29773.71 33188.36 31293.89 25776.86 29596.73 30080.32 28696.81 26396.51 241
wuyk23d87.83 27190.79 20878.96 35290.46 34188.63 11192.72 16590.67 31491.65 11598.68 1197.64 5796.06 1677.53 37359.84 36899.41 5270.73 371
FMVSNet587.82 27286.56 28791.62 22792.31 31179.81 25393.49 14894.81 24883.26 26191.36 25996.93 10352.77 37097.49 27176.07 32498.03 21797.55 199
GA-MVS87.70 27386.82 28290.31 26793.27 29577.22 29484.72 34392.79 28585.11 24589.82 28890.07 32666.80 32797.76 25884.56 25094.27 31895.96 265
TR-MVS87.70 27387.17 27689.27 29094.11 28179.26 26388.69 29791.86 30581.94 27890.69 27189.79 33182.82 24397.42 27572.65 34291.98 34591.14 351
thres600view787.66 27587.10 27989.36 28896.05 21073.17 33092.72 16585.31 35191.89 9893.29 20690.97 31663.42 34698.39 20173.23 33896.99 26096.51 241
PAPR87.65 27686.77 28490.27 26992.85 30477.38 29188.56 30096.23 20176.82 31784.98 33789.75 33386.08 22097.16 28572.33 34393.35 32796.26 254
baseline187.62 27787.31 27288.54 30194.71 26874.27 32493.10 15688.20 32686.20 22492.18 24893.04 27673.21 30695.52 32779.32 30185.82 36195.83 271
our_test_387.55 27887.59 26987.44 31791.76 32370.48 34683.83 35190.55 31579.79 28992.06 25192.17 29878.63 27795.63 32584.77 24794.73 30896.22 255
PatchT87.51 27988.17 26085.55 32990.64 33666.91 35792.02 20086.09 34192.20 8989.05 29997.16 8964.15 34296.37 31289.21 17592.98 33593.37 330
Test_1112_low_res87.50 28086.58 28690.25 27096.80 15877.75 28687.53 31096.25 19969.73 35086.47 32993.61 26475.67 29997.88 24379.95 29293.20 32995.11 291
SCA87.43 28187.21 27588.10 30992.01 32071.98 34089.43 27888.11 32882.26 27688.71 30792.83 28178.65 27597.59 26579.61 29893.30 32894.75 299
EU-MVSNet87.39 28286.71 28589.44 28593.40 29376.11 30794.93 10190.00 31757.17 37095.71 12197.37 7264.77 34097.68 26392.67 8794.37 31594.52 304
thres100view90087.35 28386.89 28188.72 29896.14 20373.09 33293.00 15885.31 35192.13 9193.26 20990.96 31763.42 34698.28 21071.27 35096.54 27094.79 297
CMPMVSbinary68.83 2287.28 28485.67 29792.09 21488.77 35885.42 18090.31 25394.38 25870.02 34988.00 31793.30 27173.78 30594.03 35075.96 32696.54 27096.83 232
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
sss87.23 28586.82 28288.46 30493.96 28577.94 28186.84 32292.78 28677.59 31087.61 32291.83 30478.75 27491.92 36077.84 31094.20 31995.52 284
BH-w/o87.21 28687.02 28087.79 31494.77 26177.27 29387.90 30393.21 27981.74 27989.99 28488.39 34683.47 23596.93 29471.29 34992.43 34189.15 356
thres40087.20 28786.52 28989.24 29295.77 22772.94 33391.89 20786.00 34390.84 13192.61 22989.80 32963.93 34398.28 21071.27 35096.54 27096.51 241
CHOSEN 1792x268887.19 28885.92 29691.00 24897.13 14079.41 26084.51 34595.60 22164.14 36490.07 28294.81 22278.26 28097.14 28673.34 33795.38 29696.46 246
HyFIR lowres test87.19 28885.51 29892.24 20697.12 14180.51 23785.03 33996.06 20866.11 36091.66 25692.98 27970.12 31799.14 9175.29 32895.23 29997.07 221
MIMVSNet87.13 29086.54 28888.89 29596.05 21076.11 30794.39 12188.51 32281.37 28088.27 31496.75 11772.38 30995.52 32765.71 36495.47 29295.03 292
tfpn200view987.05 29186.52 28988.67 29995.77 22772.94 33391.89 20786.00 34390.84 13192.61 22989.80 32963.93 34398.28 21071.27 35096.54 27094.79 297
cascas87.02 29286.28 29389.25 29191.56 32876.45 30484.33 34796.78 17271.01 34486.89 32885.91 35981.35 25896.94 29283.09 26195.60 28894.35 308
WTY-MVS86.93 29386.50 29188.24 30794.96 25474.64 31787.19 31592.07 30278.29 30788.32 31391.59 30978.06 28194.27 34774.88 33093.15 33195.80 272
HY-MVS82.50 1886.81 29485.93 29589.47 28493.63 29177.93 28294.02 13391.58 30875.68 31883.64 34693.64 26277.40 28597.42 27571.70 34792.07 34493.05 335
131486.46 29586.33 29286.87 32191.65 32574.54 31991.94 20494.10 26374.28 32684.78 33987.33 35283.03 24095.00 33978.72 30591.16 35091.06 352
ET-MVSNet_ETH3D86.15 29684.27 30591.79 22093.04 30181.28 22987.17 31686.14 34079.57 29383.65 34588.66 34257.10 36198.18 22187.74 20495.40 29495.90 269
Patchmatch-test86.10 29786.01 29486.38 32690.63 33774.22 32589.57 27586.69 33685.73 23489.81 28992.83 28165.24 33891.04 36377.82 31295.78 28593.88 320
thres20085.85 29885.18 29987.88 31394.44 27472.52 33789.08 28886.21 33988.57 18591.44 25888.40 34564.22 34198.00 23568.35 35895.88 28493.12 332
EPNet_dtu85.63 29984.37 30389.40 28786.30 36974.33 32391.64 22088.26 32484.84 25072.96 37289.85 32771.27 31497.69 26276.60 32197.62 23896.18 257
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
test250685.42 30084.57 30287.96 31097.81 9766.53 36296.14 5256.35 37989.04 17293.55 19998.10 3542.88 38198.68 17288.09 19799.18 8798.67 97
PatchmatchNetpermissive85.22 30184.64 30186.98 32089.51 35169.83 35290.52 24587.34 33378.87 30387.22 32692.74 28566.91 32696.53 30481.77 27486.88 36094.58 303
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
CVMVSNet85.16 30284.72 30086.48 32292.12 31770.19 34792.32 18788.17 32756.15 37190.64 27295.85 16967.97 32296.69 30188.78 18390.52 35292.56 341
JIA-IIPM85.08 30383.04 31291.19 24287.56 36186.14 17089.40 28084.44 35888.98 17482.20 35597.95 4356.82 36396.15 31676.55 32283.45 36591.30 350
MVS84.98 30484.30 30487.01 31991.03 33277.69 28891.94 20494.16 26259.36 36984.23 34387.50 35085.66 22496.80 29871.79 34593.05 33486.54 362
thisisatest051584.72 30582.99 31389.90 27992.96 30375.33 31584.36 34683.42 36177.37 31288.27 31486.65 35353.94 36798.72 16282.56 26697.40 24595.67 278
FPMVS84.50 30683.28 31088.16 30896.32 18894.49 1685.76 33485.47 34983.09 26585.20 33594.26 24163.79 34586.58 37063.72 36691.88 34783.40 365
tpm84.38 30784.08 30685.30 33390.47 34063.43 37289.34 28185.63 34777.24 31487.62 32195.03 21461.00 35797.30 28179.26 30291.09 35195.16 288
tpmvs84.22 30883.97 30784.94 33487.09 36665.18 36591.21 22988.35 32382.87 26985.21 33490.96 31765.24 33896.75 29979.60 30085.25 36292.90 337
ADS-MVSNet284.01 30982.20 31789.41 28689.04 35576.37 30687.57 30690.98 31172.71 33784.46 34092.45 29168.08 32096.48 30770.58 35483.97 36395.38 285
test-LLR83.58 31083.17 31184.79 33689.68 34866.86 35983.08 35384.52 35683.07 26682.85 35184.78 36262.86 34993.49 35382.85 26294.86 30494.03 314
baseline283.38 31181.54 32088.90 29491.38 32972.84 33588.78 29481.22 36678.97 30179.82 36587.56 34861.73 35497.80 25274.30 33390.05 35496.05 262
IB-MVS77.21 1983.11 31281.05 32389.29 28991.15 33175.85 31085.66 33586.00 34379.70 29182.02 35886.61 35448.26 37398.39 20177.84 31092.22 34293.63 325
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
CostFormer83.09 31382.21 31685.73 32889.27 35367.01 35690.35 25186.47 33870.42 34783.52 34893.23 27461.18 35596.85 29677.21 31788.26 35893.34 331
PMMVS83.00 31481.11 32288.66 30083.81 37686.44 16182.24 35785.65 34661.75 36882.07 35685.64 36079.75 26891.59 36275.99 32593.09 33287.94 361
PVSNet76.22 2082.89 31582.37 31584.48 33893.96 28564.38 37078.60 36388.61 32171.50 34184.43 34286.36 35774.27 30294.60 34169.87 35693.69 32594.46 305
tpmrst82.85 31682.93 31482.64 34587.65 36058.99 37590.14 25987.90 32975.54 32083.93 34491.63 30866.79 32995.36 33381.21 28181.54 36993.57 329
test0.0.03 182.48 31781.47 32185.48 33089.70 34773.57 32984.73 34181.64 36583.07 26688.13 31686.61 35462.86 34989.10 36966.24 36390.29 35393.77 322
ADS-MVSNet82.25 31881.55 31984.34 33989.04 35565.30 36487.57 30685.13 35572.71 33784.46 34092.45 29168.08 32092.33 35970.58 35483.97 36395.38 285
DSMNet-mixed82.21 31981.56 31884.16 34089.57 35070.00 35190.65 24277.66 37454.99 37283.30 34997.57 5977.89 28390.50 36566.86 36295.54 29091.97 345
KD-MVS_2432*160082.17 32080.75 32786.42 32482.04 37770.09 34981.75 35890.80 31282.56 27090.37 27689.30 33842.90 37996.11 31874.47 33192.55 33993.06 333
miper_refine_blended82.17 32080.75 32786.42 32482.04 37770.09 34981.75 35890.80 31282.56 27090.37 27689.30 33842.90 37996.11 31874.47 33192.55 33993.06 333
gg-mvs-nofinetune82.10 32281.02 32485.34 33287.46 36471.04 34394.74 10667.56 37696.44 2279.43 36698.99 645.24 37596.15 31667.18 36192.17 34388.85 358
PAPM81.91 32380.11 33387.31 31893.87 28872.32 33984.02 35093.22 27769.47 35176.13 37089.84 32872.15 31097.23 28353.27 37289.02 35592.37 343
tpm281.46 32480.35 33184.80 33589.90 34565.14 36690.44 24785.36 35065.82 36282.05 35792.44 29357.94 36096.69 30170.71 35388.49 35792.56 341
PMMVS281.31 32583.44 30974.92 35490.52 33946.49 37969.19 36885.23 35484.30 25587.95 31894.71 22976.95 29284.36 37264.07 36598.09 21293.89 319
new_pmnet81.22 32681.01 32581.86 34790.92 33570.15 34884.03 34980.25 37070.83 34585.97 33289.78 33267.93 32384.65 37167.44 36091.90 34690.78 353
test-mter81.21 32780.01 33484.79 33689.68 34866.86 35983.08 35384.52 35673.85 33082.85 35184.78 36243.66 37893.49 35382.85 26294.86 30494.03 314
EPMVS81.17 32880.37 33083.58 34285.58 37165.08 36790.31 25371.34 37577.31 31385.80 33391.30 31159.38 35892.70 35879.99 29182.34 36892.96 336
EGC-MVSNET80.97 32975.73 34196.67 4498.85 2294.55 1596.83 2096.60 1822.44 3765.32 37798.25 3192.24 10998.02 23391.85 10799.21 8297.45 204
pmmvs380.83 33078.96 33786.45 32387.23 36577.48 29084.87 34082.31 36363.83 36585.03 33689.50 33649.66 37193.10 35573.12 34095.10 30188.78 360
DWT-MVSNet_test80.74 33179.18 33685.43 33187.51 36366.87 35889.87 26986.01 34274.20 32880.86 36280.62 36848.84 37296.68 30381.54 27683.14 36792.75 339
E-PMN80.72 33280.86 32680.29 35085.11 37268.77 35472.96 36581.97 36487.76 20083.25 35083.01 36662.22 35289.17 36877.15 31894.31 31782.93 366
tpm cat180.61 33379.46 33584.07 34188.78 35765.06 36889.26 28488.23 32562.27 36781.90 35989.66 33562.70 35195.29 33671.72 34680.60 37091.86 348
EMVS80.35 33480.28 33280.54 34984.73 37469.07 35372.54 36780.73 36787.80 19981.66 36081.73 36762.89 34889.84 36675.79 32794.65 31182.71 367
CHOSEN 280x42080.04 33577.97 34086.23 32790.13 34374.53 32072.87 36689.59 31866.38 35976.29 36985.32 36156.96 36295.36 33369.49 35794.72 30988.79 359
dp79.28 33678.62 33881.24 34885.97 37056.45 37686.91 32085.26 35372.97 33581.45 36189.17 34156.01 36595.45 33173.19 33976.68 37191.82 349
TESTMET0.1,179.09 33778.04 33982.25 34687.52 36264.03 37183.08 35380.62 36870.28 34880.16 36483.22 36544.13 37790.56 36479.95 29293.36 32692.15 344
MVS-HIRNet78.83 33880.60 32973.51 35593.07 29947.37 37887.10 31778.00 37368.94 35277.53 36897.26 8271.45 31394.62 34063.28 36788.74 35678.55 370
PVSNet_070.34 2174.58 33972.96 34279.47 35190.63 33766.24 36373.26 36483.40 36263.67 36678.02 36778.35 37072.53 30889.59 36756.68 37060.05 37482.57 368
MVEpermissive59.87 2373.86 34072.65 34377.47 35387.00 36874.35 32261.37 37060.93 37867.27 35769.69 37386.49 35681.24 26272.33 37456.45 37183.45 36585.74 363
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
test_method50.44 34148.94 34454.93 35639.68 38012.38 38228.59 37190.09 3166.82 37441.10 37678.41 36954.41 36670.69 37550.12 37351.26 37581.72 369
tmp_tt37.97 34244.33 34518.88 35811.80 38121.54 38163.51 36945.66 3824.23 37551.34 37550.48 37359.08 35922.11 37744.50 37468.35 37313.00 373
cdsmvs_eth3d_5k23.35 34331.13 3460.00 3610.00 3840.00 3850.00 37295.58 2270.00 3790.00 38091.15 31393.43 780.00 3800.00 3780.00 3780.00 376
test1239.49 34412.01 3471.91 3592.87 3821.30 38382.38 3561.34 3841.36 3772.84 3786.56 3762.45 3820.97 3782.73 3765.56 3763.47 374
testmvs9.02 34511.42 3481.81 3602.77 3831.13 38479.44 3621.90 3831.18 3782.65 3796.80 3751.95 3830.87 3792.62 3773.45 3773.44 375
pcd_1.5k_mvsjas7.56 34610.09 3490.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 37990.77 1470.00 3800.00 3780.00 3780.00 376
ab-mvs-re7.56 34610.08 3500.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 38090.69 3220.00 3840.00 3800.00 3780.00 3780.00 376
test_blank0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
uanet_test0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
DCPMVS0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
sosnet-low-res0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
sosnet0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
uncertanet0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
Regformer0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
uanet0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
FOURS199.21 394.68 1298.45 498.81 897.73 698.27 20
MSC_two_6792asdad95.90 6696.54 17189.57 9296.87 16699.41 3894.06 3099.30 6598.72 93
PC_three_145275.31 32395.87 11495.75 17892.93 9496.34 31587.18 21398.68 14898.04 149
No_MVS95.90 6696.54 17189.57 9296.87 16699.41 3894.06 3099.30 6598.72 93
test_one_060198.26 6787.14 14198.18 3794.25 4996.99 6197.36 7595.13 40
eth-test20.00 384
eth-test0.00 384
ZD-MVS97.23 13290.32 8197.54 11184.40 25494.78 16395.79 17492.76 10099.39 5088.72 18698.40 171
RE-MVS-def96.66 2098.07 7995.27 896.37 4198.12 4795.66 3397.00 5997.03 9695.40 2793.49 4898.84 12798.00 154
IU-MVS98.51 4786.66 15596.83 16972.74 33695.83 11593.00 7899.29 6898.64 103
OPU-MVS95.15 10196.84 15489.43 9695.21 8795.66 18293.12 8898.06 22886.28 23098.61 15397.95 162
test_241102_TWO98.10 5091.95 9497.54 3897.25 8395.37 2899.35 6193.29 6599.25 7698.49 117
test_241102_ONE98.51 4786.97 14698.10 5091.85 10097.63 3397.03 9696.48 1198.95 123
9.1494.81 9697.49 12194.11 13098.37 1887.56 20795.38 13396.03 16394.66 5699.08 10090.70 13198.97 115
save fliter97.46 12488.05 12592.04 19897.08 14987.63 204
test_0728_THIRD93.26 7097.40 4797.35 7894.69 5599.34 6493.88 3499.42 4798.89 72
test_0728_SECOND94.88 10998.55 4186.72 15295.20 8998.22 3399.38 5693.44 5799.31 6398.53 114
test072698.51 4786.69 15395.34 8298.18 3791.85 10097.63 3397.37 7295.58 22
GSMVS94.75 299
test_part298.21 7189.41 9796.72 72
sam_mvs166.64 33094.75 299
sam_mvs66.41 331
ambc92.98 17996.88 15183.01 21195.92 6296.38 19596.41 8197.48 6688.26 18297.80 25289.96 15798.93 11998.12 144
MTGPAbinary97.62 103
test_post190.21 2555.85 37865.36 33696.00 32179.61 298
test_post6.07 37765.74 33595.84 323
patchmatchnet-post91.71 30666.22 33397.59 265
GG-mvs-BLEND83.24 34485.06 37371.03 34494.99 10065.55 37774.09 37175.51 37144.57 37694.46 34359.57 36987.54 35984.24 364
MTMP94.82 10354.62 380
gm-plane-assit87.08 36759.33 37471.22 34283.58 36497.20 28473.95 334
test9_res88.16 19598.40 17197.83 177
TEST996.45 17889.46 9490.60 24396.92 16079.09 30090.49 27394.39 23891.31 13398.88 130
test_896.37 18089.14 10190.51 24696.89 16379.37 29590.42 27594.36 24091.20 13998.82 140
agg_prior287.06 21698.36 18297.98 158
agg_prior96.20 19788.89 10696.88 16490.21 27898.78 152
TestCases96.00 5898.02 8692.17 5298.43 1490.48 14195.04 15396.74 11892.54 10597.86 24785.11 24298.98 11197.98 158
test_prior489.91 8690.74 239
test_prior290.21 25589.33 16690.77 26894.81 22290.41 15788.21 19198.55 158
test_prior94.61 12095.95 21887.23 13897.36 12698.68 17297.93 164
旧先验290.00 26468.65 35392.71 22796.52 30585.15 239
新几何290.02 263
新几何193.17 17697.16 13787.29 13794.43 25667.95 35591.29 26094.94 21786.97 20698.23 21681.06 28497.75 22993.98 317
旧先验196.20 19784.17 19594.82 24695.57 18889.57 17197.89 22596.32 251
无先验89.94 26595.75 21870.81 34698.59 18481.17 28294.81 296
原ACMM289.34 281
原ACMM192.87 18696.91 14984.22 19397.01 15276.84 31689.64 29394.46 23588.00 18898.70 16881.53 27798.01 21995.70 277
test22296.95 14585.27 18288.83 29393.61 27065.09 36390.74 27094.85 22184.62 23197.36 24693.91 318
testdata298.03 23080.24 289
segment_acmp92.14 112
testdata91.03 24596.87 15282.01 21894.28 26071.55 34092.46 23395.42 19785.65 22597.38 28082.64 26597.27 24893.70 324
testdata188.96 29088.44 187
test1294.43 13595.95 21886.75 15196.24 20089.76 29189.79 17098.79 14897.95 22297.75 186
plane_prior797.71 10588.68 110
plane_prior697.21 13588.23 12186.93 207
plane_prior597.81 9198.95 12389.26 17298.51 16598.60 110
plane_prior495.59 184
plane_prior388.43 11990.35 14693.31 204
plane_prior294.56 11591.74 111
plane_prior197.38 127
plane_prior88.12 12393.01 15788.98 17498.06 214
n20.00 385
nn0.00 385
door-mid92.13 301
lessismore_v093.87 15598.05 8183.77 20180.32 36997.13 5397.91 4677.49 28499.11 9792.62 8898.08 21398.74 90
LGP-MVS_train96.84 4098.36 6292.13 5498.25 2891.78 10797.07 5497.22 8696.38 1399.28 7592.07 9999.59 2799.11 43
test1196.65 180
door91.26 309
HQP5-MVS84.89 185
HQP-NCC96.36 18291.37 22487.16 21188.81 302
ACMP_Plane96.36 18291.37 22487.16 21188.81 302
BP-MVS86.55 224
HQP4-MVS88.81 30298.61 18098.15 140
HQP3-MVS97.31 13197.73 230
HQP2-MVS84.76 229
NP-MVS96.82 15587.10 14293.40 269
MDTV_nov1_ep13_2view42.48 38088.45 30167.22 35883.56 34766.80 32772.86 34194.06 313
MDTV_nov1_ep1383.88 30889.42 35261.52 37388.74 29687.41 33273.99 32984.96 33894.01 25265.25 33795.53 32678.02 30893.16 330
ACMMP++_ref98.82 133
ACMMP++99.25 76
Test By Simon90.61 153
ITE_SJBPF95.95 6097.34 12993.36 4296.55 18891.93 9694.82 16195.39 20091.99 11697.08 28885.53 23597.96 22197.41 207
DeepMVS_CXcopyleft53.83 35770.38 37964.56 36948.52 38133.01 37365.50 37474.21 37256.19 36446.64 37638.45 37570.07 37250.30 372