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 bysort bysort bysort bysort bysort bysorted bysort bysort bysort bysort bysort bysort bysort bysort bysort by
CS-MVS97.74 8397.61 7798.15 13597.52 21196.69 128100.00 197.11 28294.93 8699.73 2999.41 12091.68 15098.25 22298.84 7199.24 12199.52 154
CS-MVS-test97.44 9197.41 8497.53 15797.46 21394.66 197100.00 197.04 29194.69 9899.72 3399.25 13591.22 15498.29 21498.33 9798.95 12799.64 126
DELS-MVS98.54 4098.22 4999.50 3299.15 11698.65 52100.00 198.58 7497.70 998.21 12599.24 13792.58 13199.94 7298.63 8799.94 6199.92 91
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
PVSNet_Blended97.94 7297.64 7598.83 9199.59 9596.99 119100.00 199.10 2995.38 7698.27 12199.08 14489.00 18999.95 6499.12 5199.25 12099.57 145
ET-MVSNet_ETH3D94.37 18793.28 20297.64 15498.30 15997.99 7899.99 597.61 23094.35 11471.57 35899.45 11796.23 3095.34 33396.91 14485.14 27599.59 138
alignmvs97.81 7997.33 8999.25 5298.77 14298.66 5099.99 598.44 11194.40 11398.41 11499.47 11493.65 10399.42 15598.57 8894.26 21399.67 120
lupinMVS97.85 7697.60 7898.62 10397.28 22497.70 8999.99 597.55 23695.50 7599.43 5999.67 9890.92 16398.71 18298.40 9399.62 10299.45 163
DROMVSNet97.38 9897.24 9197.80 14597.41 21495.64 17099.99 597.06 28794.59 10399.63 4099.32 12789.20 18798.14 22698.76 7899.23 12299.62 132
IB-MVS92.85 694.99 16893.94 18298.16 13297.72 20095.69 16999.99 598.81 4994.28 11992.70 21896.90 23695.08 5399.17 16296.07 15173.88 34599.60 137
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
EIA-MVS97.53 8997.46 8297.76 15098.04 17794.84 19199.98 1097.61 23094.41 11297.90 13299.59 10592.40 13698.87 17098.04 10899.13 12599.59 138
ETV-MVS97.92 7497.80 7298.25 13098.14 17396.48 13599.98 1097.63 22595.61 7199.29 7499.46 11692.55 13298.82 17299.02 6098.54 13599.46 161
CANet98.27 6097.82 7199.63 1599.72 8899.10 2199.98 1098.51 9897.00 2898.52 10999.71 8987.80 19899.95 6499.75 2699.38 11799.83 100
MSLP-MVS++99.13 899.01 1099.49 3499.94 1498.46 6399.98 1098.86 4697.10 2599.80 1699.94 495.92 36100.00 199.51 38100.00 1100.00 1
CNVR-MVS99.40 199.26 199.84 699.98 299.51 699.98 1098.69 5698.20 399.93 199.98 296.82 22100.00 199.75 26100.00 199.99 24
SteuartSystems-ACMMP99.02 1298.97 1299.18 5798.72 14397.71 8799.98 1098.44 11196.85 3099.80 1699.91 1597.57 699.85 9899.44 4299.99 2299.99 24
Skip Steuart: Steuart Systems R&D Blog.
PHI-MVS98.41 5098.21 5099.03 7899.86 5997.10 11699.98 1098.80 5190.78 23699.62 4399.78 6995.30 49100.00 199.80 2299.93 6799.99 24
CLD-MVS94.06 19393.90 18394.55 24796.02 25990.69 27999.98 1097.72 22096.62 4191.05 22998.85 17677.21 28398.47 19398.11 10489.51 23494.48 242
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
thisisatest051597.41 9697.02 10298.59 10797.71 20297.52 9699.97 1898.54 8891.83 20797.45 14199.04 14697.50 899.10 16494.75 17596.37 18499.16 189
Fast-Effi-MVS+95.02 16794.19 17597.52 15997.88 18494.55 19899.97 1897.08 28588.85 26694.47 19697.96 21084.59 22898.41 20089.84 25897.10 17099.59 138
MCST-MVS99.32 399.14 499.86 599.97 399.59 599.97 1898.64 6498.47 299.13 8299.92 1396.38 29100.00 199.74 28100.00 1100.00 1
TSAR-MVS + GP.98.60 3498.51 2998.86 9099.73 8696.63 13099.97 1897.92 20798.07 598.76 9999.55 10895.00 6099.94 7299.91 1597.68 15799.99 24
jason97.24 10296.86 10498.38 12695.73 27097.32 10899.97 1897.40 25795.34 7898.60 10899.54 11087.70 19998.56 18997.94 11499.47 11399.25 184
jason: jason.
NCCC99.37 299.25 299.71 1399.96 899.15 2099.97 1898.62 6898.02 699.90 299.95 397.33 16100.00 199.54 37100.00 1100.00 1
CP-MVS98.45 4798.32 4598.87 8999.96 896.62 13199.97 1898.39 14294.43 10998.90 9299.87 2894.30 84100.00 199.04 5899.99 2299.99 24
GeoE94.36 18993.48 19496.99 17797.29 22393.54 21999.96 2596.72 31988.35 27693.43 20798.94 16482.05 24398.05 23288.12 27596.48 18299.37 172
SED-MVS99.28 599.11 699.77 899.93 2799.30 1199.96 2598.43 11997.27 2099.80 1699.94 496.71 23100.00 1100.00 1100.00 1100.00 1
OPU-MVS99.93 299.89 5099.80 299.96 2599.80 6097.44 13100.00 1100.00 199.98 35100.00 1
xxxxxxxxxxxxxcwj98.98 1598.79 1699.54 2699.82 7098.79 3799.96 2597.52 24297.66 1099.81 1299.89 2194.70 6899.86 9499.84 1799.93 6799.96 74
save fliter99.82 7098.79 3799.96 2598.40 13997.66 10
test072699.93 2799.29 1499.96 2598.42 13197.28 1899.86 499.94 497.22 18
DPM-MVS98.83 2298.46 3199.97 199.33 11199.92 199.96 2598.44 11197.96 799.55 4899.94 497.18 20100.00 193.81 19899.94 6199.98 55
TEST999.92 3698.92 2799.96 2598.43 11993.90 13799.71 3599.86 3195.88 3799.85 98
train_agg98.88 2098.65 2199.59 2199.92 3698.92 2799.96 2598.43 11994.35 11499.71 3599.86 3195.94 3499.85 9899.69 3599.98 3599.99 24
test_899.92 3698.88 3099.96 2598.43 11994.35 11499.69 3799.85 3595.94 3499.85 98
agg_prior198.88 2098.66 2099.54 2699.93 2798.77 4099.96 2598.43 11994.63 10299.63 4099.85 3595.79 4099.85 9899.72 3299.99 2299.99 24
region2R98.54 4098.37 4199.05 7699.96 897.18 11299.96 2598.55 8494.87 9299.45 5799.85 3594.07 92100.00 198.67 82100.00 199.98 55
test-LLR96.47 13096.04 12597.78 14797.02 23295.44 17399.96 2598.21 17694.07 12695.55 18296.38 25393.90 9798.27 21990.42 25098.83 13099.64 126
TESTMET0.1,196.74 12196.26 12198.16 13297.36 21796.48 13599.96 2598.29 16591.93 20495.77 18098.07 20595.54 4398.29 21490.55 24798.89 12899.70 115
test-mter96.39 13495.93 13697.78 14797.02 23295.44 17399.96 2598.21 17691.81 20995.55 18296.38 25395.17 5098.27 21990.42 25098.83 13099.64 126
CPTT-MVS97.64 8797.32 9098.58 10899.97 395.77 16399.96 2598.35 15489.90 24998.36 11799.79 6491.18 15999.99 4098.37 9499.99 2299.99 24
cascas94.64 17893.61 18797.74 15297.82 19096.26 14499.96 2597.78 21985.76 30894.00 20297.54 21676.95 28699.21 15897.23 13395.43 20297.76 223
DeepPCF-MVS95.94 297.71 8598.98 1193.92 27399.63 9381.76 35099.96 2598.56 7899.47 199.19 8099.99 194.16 90100.00 199.92 1299.93 67100.00 1
DVP-MVS++99.26 699.09 899.77 899.91 4499.31 999.95 4398.43 11996.48 4299.80 1699.93 1197.44 13100.00 199.92 1299.98 35100.00 1
FOURS199.92 3697.66 9199.95 4398.36 15195.58 7299.52 53
DVP-MVScopyleft99.30 499.16 399.73 1199.93 2799.29 1499.95 4398.32 15997.28 1899.83 1099.91 1597.22 18100.00 199.99 5100.00 199.89 94
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
test_0728_SECOND99.82 799.94 1499.47 799.95 4398.43 119100.00 199.99 5100.00 1100.00 1
MSP-MVS99.09 999.12 598.98 8399.93 2797.24 10999.95 4398.42 13197.50 1499.52 5399.88 2497.43 1599.71 13399.50 3999.98 35100.00 1
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
mvs-test195.53 15795.97 13294.20 26197.77 19385.44 33299.95 4397.06 28794.92 8996.58 16198.72 17985.81 21698.98 16794.80 17298.11 14898.18 214
HFP-MVS98.56 3898.37 4199.14 6699.96 897.43 10499.95 4398.61 7094.77 9499.31 7099.85 3594.22 86100.00 198.70 8099.98 3599.98 55
#test#98.59 3698.41 3499.14 6699.96 897.43 10499.95 4398.61 7095.00 8499.31 7099.85 3594.22 86100.00 198.78 7699.98 3599.98 55
HPM-MVS++copyleft99.07 1098.88 1499.63 1599.90 4799.02 2399.95 4398.56 7897.56 1399.44 5899.85 3595.38 48100.00 199.31 4799.99 2299.87 97
test_prior398.99 1498.84 1599.43 3899.94 1498.49 6199.95 4398.65 6195.78 6399.73 2999.76 7596.00 3299.80 11099.78 24100.00 199.99 24
test_prior299.95 4395.78 6399.73 2999.76 7596.00 3299.78 24100.00 1
ACMMPR98.50 4398.32 4599.05 7699.96 897.18 11299.95 4398.60 7294.77 9499.31 7099.84 4893.73 101100.00 198.70 8099.98 3599.98 55
MP-MVScopyleft98.23 6497.97 6599.03 7899.94 1497.17 11599.95 4398.39 14294.70 9798.26 12399.81 5991.84 148100.00 198.85 7099.97 4899.93 85
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
mPP-MVS98.39 5398.20 5198.97 8499.97 396.92 12299.95 4398.38 14695.04 8398.61 10799.80 6093.39 107100.00 198.64 86100.00 199.98 55
PVSNet_BlendedMVS96.05 14395.82 14196.72 18699.59 9596.99 11999.95 4399.10 2994.06 12898.27 12195.80 26789.00 18999.95 6499.12 5187.53 25993.24 322
PAPR98.52 4298.16 5499.58 2399.97 398.77 4099.95 4398.43 11995.35 7798.03 12899.75 8094.03 9399.98 4698.11 10499.83 8599.99 24
PVSNet91.05 1397.13 10596.69 11098.45 12099.52 10195.81 16199.95 4399.65 1194.73 9699.04 8599.21 13984.48 22999.95 6494.92 16798.74 13299.58 144
ZNCC-MVS98.31 5798.03 6199.17 6099.88 5497.59 9299.94 6098.44 11194.31 11798.50 11199.82 5593.06 12099.99 4098.30 9899.99 2299.93 85
test_prior498.05 7599.94 60
XVS98.70 2998.55 2699.15 6499.94 1497.50 9999.94 6098.42 13196.22 5299.41 6199.78 6994.34 7999.96 5798.92 6499.95 5599.99 24
X-MVStestdata93.83 19592.06 22499.15 6499.94 1497.50 9999.94 6098.42 13196.22 5299.41 6141.37 37594.34 7999.96 5798.92 6499.95 5599.99 24
SD-MVS98.92 1798.70 1899.56 2499.70 9098.73 4599.94 6098.34 15696.38 4799.81 1299.76 7594.59 7099.98 4699.84 1799.96 5299.97 67
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
PVSNet_088.03 1991.80 24390.27 25596.38 19998.27 16490.46 28699.94 6099.61 1293.99 13186.26 31097.39 22171.13 32399.89 8398.77 7767.05 35798.79 207
ETH3 D test640098.81 2398.54 2799.59 2199.93 2798.93 2699.93 6698.46 10694.56 10499.84 899.92 1394.32 8399.86 9499.96 999.98 35100.00 1
GST-MVS98.27 6097.97 6599.17 6099.92 3697.57 9399.93 6698.39 14294.04 13098.80 9599.74 8492.98 121100.00 198.16 10199.76 9399.93 85
test0.0.03 193.86 19493.61 18794.64 24295.02 28692.18 25099.93 6698.58 7494.07 12687.96 28498.50 19193.90 9794.96 33881.33 32393.17 22396.78 229
MVS_111021_HR98.72 2898.62 2399.01 8199.36 11097.18 11299.93 6699.90 196.81 3498.67 10399.77 7193.92 9599.89 8399.27 4999.94 6199.96 74
thisisatest053097.10 10696.72 10998.22 13197.60 20596.70 12799.92 7098.54 8891.11 22897.07 14998.97 15697.47 1199.03 16593.73 20396.09 18798.92 199
PVSNet_Blended_VisFu97.27 10196.81 10698.66 10098.81 13996.67 12999.92 7098.64 6494.51 10696.38 16998.49 19289.05 18899.88 8997.10 13798.34 13999.43 166
DP-MVS Recon98.41 5098.02 6299.56 2499.97 398.70 4799.92 7098.44 11192.06 20298.40 11699.84 4895.68 41100.00 198.19 9999.71 9799.97 67
PLCcopyleft95.54 397.93 7397.89 7098.05 13999.82 7094.77 19599.92 7098.46 10693.93 13597.20 14599.27 13195.44 4799.97 5597.41 12999.51 11299.41 168
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
9.1498.38 3999.87 5799.91 7498.33 15793.22 15799.78 2499.89 2194.57 7199.85 9899.84 1799.97 48
APDe-MVS99.06 1198.91 1399.51 3199.94 1498.76 4499.91 7498.39 14297.20 2499.46 5699.85 3595.53 4599.79 11399.86 16100.00 199.99 24
MVSTER95.53 15795.22 15496.45 19498.56 14897.72 8699.91 7497.67 22392.38 19291.39 22597.14 22697.24 1797.30 26294.80 17287.85 25494.34 257
PMMVS96.76 11996.76 10896.76 18498.28 16292.10 25199.91 7497.98 20094.12 12399.53 5099.39 12386.93 20898.73 18096.95 14297.73 15599.45 163
SF-MVS98.67 3198.40 3699.50 3299.77 7898.67 4899.90 7898.21 17693.53 14999.81 1299.89 2194.70 6899.86 9499.84 1799.93 6799.96 74
testtj98.89 1998.69 1999.52 2999.94 1498.56 5799.90 7898.55 8495.14 8299.72 3399.84 4895.46 46100.00 199.65 3699.99 2299.99 24
ETH3D-3000-0.198.68 3098.42 3299.47 3799.83 6898.57 5599.90 7898.37 14993.81 14099.81 1299.90 1994.34 7999.86 9499.84 1799.98 3599.97 67
原ACMM299.90 78
HPM-MVScopyleft97.96 7197.72 7398.68 9899.84 6596.39 14099.90 7898.17 18292.61 18098.62 10699.57 10791.87 14799.67 14098.87 6999.99 2299.99 24
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
EPNet98.49 4498.40 3698.77 9399.62 9496.80 12699.90 7899.51 1697.60 1299.20 7799.36 12693.71 10299.91 7897.99 11198.71 13399.61 135
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CSCG97.10 10697.04 10097.27 17299.89 5091.92 25699.90 7899.07 3288.67 26995.26 18899.82 5593.17 11899.98 4698.15 10299.47 11399.90 93
PAPM98.60 3498.42 3299.14 6696.05 25898.96 2499.90 7899.35 2496.68 3898.35 11899.66 10096.45 2898.51 19299.45 4199.89 7899.96 74
RRT_test8_iter0594.58 18094.11 17795.98 20797.88 18496.11 15599.89 8697.45 24891.66 21388.28 28096.71 24496.53 2797.40 25594.73 17783.85 28894.45 248
114514_t97.41 9696.83 10599.14 6699.51 10397.83 8499.89 8698.27 16988.48 27399.06 8499.66 10090.30 17199.64 14396.32 14999.97 4899.96 74
WTY-MVS98.10 6897.60 7899.60 2098.92 13099.28 1699.89 8699.52 1495.58 7298.24 12499.39 12393.33 10999.74 12997.98 11395.58 20099.78 107
GA-MVS93.83 19592.84 20696.80 18295.73 27093.57 21799.88 8997.24 27092.57 18592.92 21496.66 24678.73 27797.67 24787.75 27894.06 21699.17 188
UniMVSNet (Re)93.07 21492.13 22195.88 20994.84 28796.24 14899.88 8998.98 3592.49 19089.25 26095.40 28687.09 20697.14 27293.13 21478.16 32694.26 261
HPM-MVS_fast97.80 8097.50 8198.68 9899.79 7596.42 13799.88 8998.16 18591.75 21198.94 9199.54 11091.82 14999.65 14297.62 12699.99 2299.99 24
DPE-MVScopyleft99.26 699.10 799.74 1099.89 5099.24 1899.87 9298.44 11197.48 1599.64 3999.94 496.68 2599.99 4099.99 5100.00 199.99 24
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
MTMP99.87 9296.49 326
Regformer-198.79 2598.60 2499.36 4899.85 6098.34 6699.87 9298.52 9196.05 5699.41 6199.79 6494.93 6399.76 12299.07 5399.90 7699.99 24
Regformer-298.78 2698.59 2599.36 4899.85 6098.32 6799.87 9298.52 9196.04 5799.41 6199.79 6494.92 6499.76 12299.05 5499.90 7699.98 55
CDPH-MVS98.65 3298.36 4399.49 3499.94 1498.73 4599.87 9298.33 15793.97 13299.76 2699.87 2894.99 6199.75 12598.55 89100.00 199.98 55
HQP-NCC95.78 26499.87 9296.82 3193.37 208
ACMP_Plane95.78 26499.87 9296.82 3193.37 208
APD-MVScopyleft98.62 3398.35 4499.41 4299.90 4798.51 6099.87 9298.36 15194.08 12599.74 2899.73 8694.08 9199.74 12999.42 4399.99 2299.99 24
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
MVS_111021_LR98.42 4998.38 3998.53 11599.39 10895.79 16299.87 9299.86 296.70 3798.78 9699.79 6492.03 14499.90 7999.17 5099.86 8399.88 96
HQP-MVS94.61 17994.50 17094.92 23395.78 26491.85 25799.87 9297.89 20996.82 3193.37 20898.65 18280.65 26198.39 20497.92 11589.60 22994.53 238
CNLPA97.76 8297.38 8598.92 8899.53 10096.84 12499.87 9298.14 18893.78 14296.55 16399.69 9492.28 13999.98 4697.13 13599.44 11599.93 85
ETH3D cwj APD-0.1698.40 5298.07 6099.40 4499.59 9598.41 6499.86 10398.24 17292.18 19799.73 2999.87 2893.47 10699.85 9899.74 2899.95 5599.93 85
SMA-MVScopyleft98.76 2798.48 3099.62 1899.87 5798.87 3199.86 10398.38 14693.19 15899.77 2599.94 495.54 43100.00 199.74 2899.99 22100.00 1
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
plane_prior91.74 26199.86 10396.76 3589.59 231
tttt051796.85 11496.49 11697.92 14397.48 21295.89 16099.85 10698.54 8890.72 23796.63 15998.93 16697.47 1199.02 16693.03 21695.76 19698.85 203
ACMMP_NAP98.49 4498.14 5599.54 2699.66 9298.62 5499.85 10698.37 14994.68 9999.53 5099.83 5192.87 123100.00 198.66 8599.84 8499.99 24
thres20096.96 11096.21 12299.22 5398.97 12498.84 3499.85 10699.71 693.17 15996.26 17198.88 16989.87 17699.51 14794.26 18994.91 20799.31 179
F-COLMAP96.93 11296.95 10396.87 18199.71 8991.74 26199.85 10697.95 20393.11 16195.72 18199.16 14192.35 13799.94 7295.32 16099.35 11898.92 199
SR-MVS98.46 4698.30 4798.93 8799.88 5497.04 11799.84 11098.35 15494.92 8999.32 6999.80 6093.35 10899.78 11599.30 4899.95 5599.96 74
CANet_DTU96.76 11996.15 12398.60 10598.78 14197.53 9599.84 11097.63 22597.25 2399.20 7799.64 10281.36 25299.98 4692.77 21898.89 12898.28 213
casdiffmvs96.42 13395.97 13297.77 14997.30 22294.98 18799.84 11097.09 28493.75 14496.58 16199.26 13485.07 22598.78 17597.77 12297.04 17299.54 151
HQP_MVS94.49 18494.36 17294.87 23495.71 27391.74 26199.84 11097.87 21196.38 4793.01 21298.59 18680.47 26598.37 20997.79 12089.55 23294.52 240
plane_prior299.84 11096.38 47
BH-w/o95.71 15295.38 15096.68 18798.49 15492.28 24799.84 11097.50 24592.12 19992.06 22198.79 17784.69 22798.67 18595.29 16199.66 10099.09 195
UniMVSNet_NR-MVSNet92.95 21792.11 22295.49 21494.61 29295.28 17999.83 11699.08 3191.49 21789.21 26296.86 23987.14 20596.73 29793.20 21077.52 33194.46 243
APD-MVS_3200maxsize98.25 6398.08 5998.78 9299.81 7396.60 13299.82 11798.30 16493.95 13499.37 6799.77 7192.84 12499.76 12298.95 6199.92 7199.97 67
PAPM_NR98.12 6797.93 6998.70 9799.94 1496.13 15299.82 11798.43 11994.56 10497.52 13999.70 9194.40 7499.98 4697.00 13999.98 3599.99 24
nrg03093.51 20592.53 21596.45 19494.36 29497.20 11199.81 11997.16 27791.60 21489.86 24497.46 21786.37 21397.68 24695.88 15580.31 31494.46 243
RRT_MVS95.23 16294.77 16696.61 19098.28 16298.32 6799.81 11997.41 25592.59 18291.28 22797.76 21395.02 5797.23 26893.65 20587.14 26194.28 260
diffmvs97.00 10996.64 11198.09 13797.64 20396.17 15199.81 11997.19 27294.67 10198.95 9099.28 12886.43 21298.76 17898.37 9497.42 16399.33 177
DU-MVS92.46 22891.45 23795.49 21494.05 29995.28 17999.81 11998.74 5392.25 19689.21 26296.64 24881.66 24896.73 29793.20 21077.52 33194.46 243
ACMP92.05 992.74 22192.42 21893.73 27795.91 26388.72 30899.81 11997.53 24094.13 12287.00 29798.23 20174.07 31198.47 19396.22 15088.86 24193.99 290
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
test117298.38 5498.25 4898.77 9399.88 5496.56 13499.80 12498.36 15194.68 9999.20 7799.80 6093.28 11399.78 11599.34 4699.92 7199.98 55
Fast-Effi-MVS+-dtu93.72 20293.86 18593.29 28897.06 22986.16 32699.80 12496.83 31192.66 17792.58 21997.83 21281.39 25197.67 24789.75 25996.87 17696.05 236
zzz-MVS98.33 5698.00 6399.30 5099.85 6097.93 8299.80 12498.28 16695.76 6597.18 14699.88 2492.74 127100.00 198.67 8299.88 8099.99 24
BH-untuned95.18 16394.83 16496.22 20298.36 15891.22 27399.80 12497.32 26490.91 23291.08 22898.67 18183.51 23598.54 19194.23 19099.61 10598.92 199
tfpn200view996.79 11795.99 12799.19 5698.94 12698.82 3599.78 12899.71 692.86 16496.02 17498.87 17189.33 18299.50 14993.84 19594.57 20899.27 182
thres40096.78 11895.99 12799.16 6298.94 12698.82 3599.78 12899.71 692.86 16496.02 17498.87 17189.33 18299.50 14993.84 19594.57 20899.16 189
TAPA-MVS92.12 894.42 18593.60 18996.90 18099.33 11191.78 26099.78 12898.00 19789.89 25094.52 19499.47 11491.97 14599.18 16169.90 35399.52 11099.73 112
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
TSAR-MVS + MP.98.93 1698.77 1799.41 4299.74 8298.67 4899.77 13198.38 14696.73 3699.88 399.74 8494.89 6599.59 14499.80 2299.98 3599.97 67
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
OPM-MVS93.21 21092.80 20794.44 25493.12 31690.85 27899.77 13197.61 23096.19 5491.56 22498.65 18275.16 30598.47 19393.78 20189.39 23593.99 290
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
v2v48291.30 24990.07 26195.01 22993.13 31493.79 21299.77 13197.02 29288.05 27889.25 26095.37 29080.73 25997.15 27187.28 28480.04 31794.09 281
Baseline_NR-MVSNet90.33 27289.51 27092.81 29892.84 32289.95 29699.77 13193.94 36284.69 32389.04 26695.66 27381.66 24896.52 30590.99 23976.98 33791.97 340
ACMM91.95 1092.88 21892.52 21693.98 27295.75 26989.08 30699.77 13197.52 24293.00 16289.95 24197.99 20976.17 29598.46 19693.63 20688.87 24094.39 251
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
SR-MVS-dyc-post98.31 5798.17 5398.71 9699.79 7596.37 14199.76 13698.31 16194.43 10999.40 6599.75 8093.28 11399.78 11598.90 6799.92 7199.97 67
RE-MVS-def98.13 5699.79 7596.37 14199.76 13698.31 16194.43 10999.40 6599.75 8092.95 12298.90 6799.92 7199.97 67
BH-RMVSNet95.18 16394.31 17497.80 14598.17 17195.23 18299.76 13697.53 24092.52 18794.27 19999.25 13576.84 28798.80 17390.89 24399.54 10999.35 175
v14890.70 26289.63 26593.92 27392.97 32090.97 27599.75 13996.89 30787.51 28388.27 28195.01 30381.67 24797.04 28187.40 28277.17 33693.75 307
PGM-MVS98.34 5598.13 5698.99 8299.92 3697.00 11899.75 13999.50 1793.90 13799.37 6799.76 7593.24 116100.00 197.75 12499.96 5299.98 55
LPG-MVS_test92.96 21692.71 20993.71 27995.43 27988.67 30999.75 13997.62 22792.81 16790.05 23798.49 19275.24 30198.40 20295.84 15689.12 23694.07 282
thres100view90096.74 12195.92 13799.18 5798.90 13398.77 4099.74 14299.71 692.59 18295.84 17798.86 17389.25 18499.50 14993.84 19594.57 20899.27 182
MP-MVS-pluss98.07 6997.64 7599.38 4799.74 8298.41 6499.74 14298.18 18193.35 15396.45 16599.85 3592.64 13099.97 5598.91 6699.89 7899.77 108
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
pmmvs590.17 27889.09 27793.40 28692.10 33289.77 29999.74 14295.58 34485.88 30787.24 29695.74 26973.41 31496.48 30788.54 26883.56 28993.95 293
thres600view796.69 12495.87 14099.14 6698.90 13398.78 3999.74 14299.71 692.59 18295.84 17798.86 17389.25 18499.50 14993.44 20894.50 21199.16 189
baseline296.71 12396.49 11697.37 16795.63 27795.96 15899.74 14298.88 4492.94 16391.61 22398.97 15697.72 598.62 18794.83 17198.08 15297.53 227
miper_enhance_ethall94.36 18993.98 18195.49 21498.68 14595.24 18199.73 14797.29 26693.28 15689.86 24495.97 26594.37 7897.05 27992.20 22284.45 28094.19 267
testgi89.01 29388.04 29491.90 30893.49 30984.89 33599.73 14795.66 34293.89 13985.14 31798.17 20259.68 35594.66 34277.73 33888.88 23996.16 235
sss97.57 8897.03 10199.18 5798.37 15798.04 7699.73 14799.38 2293.46 15198.76 9999.06 14591.21 15599.89 8396.33 14897.01 17399.62 132
canonicalmvs97.09 10896.32 12099.39 4698.93 12898.95 2599.72 15097.35 26094.45 10797.88 13399.42 11886.71 20999.52 14698.48 9193.97 21799.72 114
3Dnovator+91.53 1196.31 13795.24 15399.52 2996.88 24098.64 5399.72 15098.24 17295.27 8088.42 27998.98 15482.76 24099.94 7297.10 13799.83 8599.96 74
HyFIR lowres test96.66 12696.43 11897.36 16999.05 11893.91 21199.70 15299.80 390.54 23896.26 17198.08 20492.15 14298.23 22396.84 14595.46 20199.93 85
D2MVS92.76 22092.59 21493.27 28995.13 28289.54 30299.69 15399.38 2292.26 19587.59 28894.61 31785.05 22697.79 24391.59 22988.01 25392.47 334
TranMVSNet+NR-MVSNet91.68 24790.61 24894.87 23493.69 30693.98 20999.69 15398.65 6191.03 23088.44 27596.83 24380.05 26896.18 31890.26 25476.89 33994.45 248
V4291.28 25190.12 26094.74 23893.42 31193.46 22199.68 15597.02 29287.36 28689.85 24695.05 30181.31 25397.34 25987.34 28380.07 31693.40 317
testmvs40.60 34044.45 34329.05 35719.49 38114.11 38299.68 15518.47 38020.74 37364.59 36198.48 19510.95 37817.09 37756.66 36711.01 37355.94 370
abl_697.67 8697.34 8898.66 10099.68 9196.11 15599.68 15598.14 18893.80 14199.27 7599.70 9188.65 19499.98 4697.46 12899.72 9699.89 94
Regformer-398.58 3798.41 3499.10 7299.84 6597.57 9399.66 15898.52 9195.79 6299.01 8799.77 7194.40 7499.75 12598.82 7299.83 8599.98 55
Regformer-498.56 3898.39 3899.08 7499.84 6597.52 9699.66 15898.52 9195.76 6599.01 8799.77 7194.33 8299.75 12598.80 7599.83 8599.98 55
DeepC-MVS94.51 496.92 11396.40 11998.45 12099.16 11595.90 15999.66 15898.06 19496.37 5094.37 19799.49 11383.29 23899.90 7997.63 12599.61 10599.55 147
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
CHOSEN 1792x268896.81 11696.53 11597.64 15498.91 13293.07 22899.65 16199.80 395.64 7095.39 18598.86 17384.35 23199.90 7996.98 14099.16 12499.95 82
Test_1112_low_res95.72 15094.83 16498.42 12397.79 19296.41 13899.65 16196.65 32292.70 17492.86 21796.13 26292.15 14299.30 15691.88 22693.64 21999.55 147
1112_ss96.01 14595.20 15598.42 12397.80 19196.41 13899.65 16196.66 32192.71 17392.88 21699.40 12192.16 14199.30 15691.92 22593.66 21899.55 147
OMC-MVS97.28 10097.23 9297.41 16499.76 7993.36 22699.65 16197.95 20396.03 5897.41 14299.70 9189.61 17899.51 14796.73 14698.25 14499.38 170
test_yl97.83 7797.37 8699.21 5499.18 11397.98 7999.64 16599.27 2691.43 22197.88 13398.99 15295.84 3899.84 10798.82 7295.32 20499.79 104
DCV-MVSNet97.83 7797.37 8699.21 5499.18 11397.98 7999.64 16599.27 2691.43 22197.88 13398.99 15295.84 3899.84 10798.82 7295.32 20499.79 104
MG-MVS98.91 1898.65 2199.68 1499.94 1499.07 2299.64 16599.44 1997.33 1799.00 8999.72 8794.03 9399.98 4698.73 79100.00 1100.00 1
v114491.09 25489.83 26294.87 23493.25 31393.69 21699.62 16896.98 29786.83 29689.64 25294.99 30680.94 25697.05 27985.08 30281.16 30393.87 300
cl2293.77 19993.25 20395.33 22099.49 10494.43 20099.61 16998.09 19190.38 24089.16 26595.61 27490.56 16997.34 25991.93 22484.45 28094.21 266
WR-MVS92.31 23191.25 23995.48 21794.45 29395.29 17899.60 17098.68 5790.10 24588.07 28396.89 23780.68 26096.80 29593.14 21379.67 31894.36 253
Effi-MVS+-dtu94.53 18395.30 15292.22 30397.77 19382.54 34399.59 17197.06 28794.92 8995.29 18795.37 29085.81 21697.89 24194.80 17297.07 17196.23 234
DIV-MVS_self_test92.32 23091.60 23194.47 25297.31 22192.74 23599.58 17296.75 31786.99 29387.64 28795.54 27889.55 17996.50 30688.58 26782.44 29394.17 268
FIs94.10 19293.43 19596.11 20494.70 29096.82 12599.58 17298.93 4192.54 18689.34 25897.31 22287.62 20097.10 27694.22 19186.58 26494.40 250
cl____92.31 23191.58 23294.52 24897.33 22092.77 23399.57 17496.78 31686.97 29487.56 28995.51 28189.43 18096.62 30288.60 26682.44 29394.16 273
EPNet_dtu95.71 15295.39 14996.66 18898.92 13093.41 22399.57 17498.90 4296.19 5497.52 13998.56 19092.65 12997.36 25777.89 33798.33 14099.20 187
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
v14419290.79 26189.52 26994.59 24493.11 31792.77 23399.56 17696.99 29586.38 30089.82 24794.95 30880.50 26497.10 27683.98 30880.41 31293.90 297
OpenMVScopyleft90.15 1594.77 17393.59 19098.33 12796.07 25797.48 10199.56 17698.57 7690.46 23986.51 30398.95 16278.57 27899.94 7293.86 19499.74 9497.57 226
MVSFormer96.94 11196.60 11297.95 14197.28 22497.70 8999.55 17897.27 26891.17 22599.43 5999.54 11090.92 16396.89 28994.67 17999.62 10299.25 184
test_djsdf92.83 21992.29 22094.47 25291.90 33492.46 24499.55 17897.27 26891.17 22589.96 24096.07 26481.10 25496.89 28994.67 17988.91 23894.05 284
PS-MVSNAJ98.44 4898.20 5199.16 6298.80 14098.92 2799.54 18098.17 18297.34 1699.85 699.85 3591.20 15699.89 8399.41 4499.67 9998.69 210
CDS-MVSNet96.34 13596.07 12497.13 17497.37 21694.96 18899.53 18197.91 20891.55 21695.37 18698.32 20095.05 5697.13 27393.80 19995.75 19799.30 180
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
xiu_mvs_v2_base98.23 6497.97 6599.02 8098.69 14498.66 5099.52 18298.08 19397.05 2699.86 499.86 3190.65 16799.71 13399.39 4598.63 13498.69 210
PatchMatch-RL96.04 14495.40 14897.95 14199.59 9595.22 18399.52 18299.07 3293.96 13396.49 16498.35 19982.28 24299.82 10990.15 25599.22 12398.81 206
test_method80.79 32479.70 32784.08 34192.83 32367.06 36699.51 18495.42 34654.34 36481.07 33793.53 33044.48 36792.22 35778.90 33477.23 33592.94 327
baseline96.43 13295.98 12997.76 15097.34 21895.17 18499.51 18497.17 27593.92 13696.90 15299.28 12885.37 22298.64 18697.50 12796.86 17799.46 161
miper_ehance_all_eth93.16 21192.60 21194.82 23797.57 20693.56 21899.50 18697.07 28688.75 26788.85 26995.52 28090.97 16296.74 29690.77 24584.45 28094.17 268
v119290.62 26689.25 27494.72 24093.13 31493.07 22899.50 18697.02 29286.33 30189.56 25495.01 30379.22 27297.09 27882.34 31881.16 30394.01 287
v192192090.46 26889.12 27694.50 25092.96 32192.46 24499.49 18896.98 29786.10 30389.61 25395.30 29378.55 27997.03 28382.17 31980.89 31094.01 287
无先验99.49 18898.71 5493.46 151100.00 194.36 18599.99 24
pmmvs492.10 23691.07 24295.18 22592.82 32494.96 18899.48 19096.83 31187.45 28588.66 27396.56 25183.78 23496.83 29389.29 26184.77 27893.75 307
Vis-MVSNet (Re-imp)96.32 13695.98 12997.35 17097.93 18294.82 19299.47 19198.15 18791.83 20795.09 18999.11 14291.37 15397.47 25493.47 20797.43 16199.74 111
API-MVS97.86 7597.66 7498.47 11899.52 10195.41 17599.47 19198.87 4591.68 21298.84 9399.85 3592.34 13899.99 4098.44 9299.96 52100.00 1
旧先验299.46 19394.21 12199.85 699.95 6496.96 141
IterMVS-LS92.69 22392.11 22294.43 25696.80 24492.74 23599.45 19496.89 30788.98 26089.65 25195.38 28988.77 19196.34 31290.98 24082.04 29694.22 264
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
3Dnovator91.47 1296.28 14095.34 15199.08 7496.82 24397.47 10299.45 19498.81 4995.52 7489.39 25699.00 15181.97 24499.95 6497.27 13299.83 8599.84 99
bset_n11_16_dypcd93.05 21592.30 21995.31 22190.23 35095.05 18699.44 19697.28 26792.51 18890.65 23396.68 24585.30 22396.71 29994.49 18384.14 28394.16 273
FC-MVSNet-test93.81 19793.15 20495.80 21294.30 29696.20 14999.42 19798.89 4392.33 19489.03 26797.27 22487.39 20396.83 29393.20 21086.48 26594.36 253
c3_l92.53 22691.87 22894.52 24897.40 21592.99 23199.40 19896.93 30487.86 28088.69 27295.44 28489.95 17596.44 30890.45 24980.69 31194.14 278
EI-MVSNet-Vis-set98.27 6098.11 5898.75 9599.83 6896.59 13399.40 19898.51 9895.29 7998.51 11099.76 7593.60 10599.71 13398.53 9099.52 11099.95 82
新几何299.40 198
QAPM95.40 16094.17 17699.10 7296.92 23597.71 8799.40 19898.68 5789.31 25488.94 26898.89 16782.48 24199.96 5793.12 21599.83 8599.62 132
MTAPA98.29 5997.96 6899.30 5099.85 6097.93 8299.39 20298.28 16695.76 6597.18 14699.88 2492.74 127100.00 198.67 8299.88 8099.99 24
miper_lstm_enhance91.81 24091.39 23893.06 29597.34 21889.18 30599.38 20396.79 31586.70 29787.47 29195.22 29890.00 17495.86 32888.26 27181.37 30194.15 275
v124090.20 27688.79 28394.44 25493.05 31992.27 24899.38 20396.92 30585.89 30589.36 25794.87 31077.89 28297.03 28380.66 32681.08 30694.01 287
EPP-MVSNet96.69 12496.60 11296.96 17897.74 19693.05 23099.37 20598.56 7888.75 26795.83 17999.01 14996.01 3198.56 18996.92 14397.20 16999.25 184
MSDG94.37 18793.36 20097.40 16598.88 13593.95 21099.37 20597.38 25885.75 31090.80 23199.17 14084.11 23399.88 8986.35 29398.43 13898.36 212
EI-MVSNet-UG-set98.14 6697.99 6498.60 10599.80 7496.27 14399.36 20798.50 10295.21 8198.30 12099.75 8093.29 11299.73 13298.37 9499.30 11999.81 102
test22299.55 9997.41 10799.34 20898.55 8491.86 20699.27 7599.83 5193.84 9999.95 5599.99 24
our_test_390.39 26989.48 27293.12 29292.40 32889.57 30199.33 20996.35 32987.84 28185.30 31694.99 30684.14 23296.09 32280.38 32784.56 27993.71 312
ppachtmachnet_test89.58 28788.35 28993.25 29092.40 32890.44 28799.33 20996.73 31885.49 31485.90 31495.77 26881.09 25596.00 32676.00 34582.49 29293.30 320
mvs_anonymous95.65 15595.03 16097.53 15798.19 16995.74 16599.33 20997.49 24690.87 23390.47 23597.10 22888.23 19697.16 27095.92 15497.66 15899.68 118
AUN-MVS93.28 20992.60 21195.34 21998.29 16090.09 29399.31 21298.56 7891.80 21096.35 17098.00 20789.38 18198.28 21792.46 21969.22 35297.64 224
xiu_mvs_v1_base_debu97.43 9297.06 9798.55 11097.74 19698.14 7199.31 21297.86 21396.43 4499.62 4399.69 9485.56 21999.68 13799.05 5498.31 14197.83 219
xiu_mvs_v1_base97.43 9297.06 9798.55 11097.74 19698.14 7199.31 21297.86 21396.43 4499.62 4399.69 9485.56 21999.68 13799.05 5498.31 14197.83 219
xiu_mvs_v1_base_debi97.43 9297.06 9798.55 11097.74 19698.14 7199.31 21297.86 21396.43 4499.62 4399.69 9485.56 21999.68 13799.05 5498.31 14197.83 219
MVS_Test96.46 13195.74 14298.61 10498.18 17097.23 11099.31 21297.15 27891.07 22998.84 9397.05 23288.17 19798.97 16894.39 18497.50 16099.61 135
hse-mvs294.38 18694.08 17995.31 22198.27 16490.02 29499.29 21798.56 7895.90 5998.77 9798.00 20790.89 16598.26 22197.80 11769.20 35397.64 224
testdata199.28 21896.35 51
Vis-MVSNetpermissive95.72 15095.15 15797.45 16297.62 20494.28 20399.28 21898.24 17294.27 12096.84 15498.94 16479.39 27198.76 17893.25 20998.49 13699.30 180
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
FMVSNet392.69 22391.58 23295.99 20698.29 16097.42 10699.26 22097.62 22789.80 25189.68 24895.32 29281.62 25096.27 31587.01 28985.65 26994.29 259
DeepC-MVS_fast96.59 198.81 2398.54 2799.62 1899.90 4798.85 3399.24 22198.47 10498.14 499.08 8399.91 1593.09 119100.00 199.04 5899.99 22100.00 1
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
YYNet185.50 31083.33 31592.00 30690.89 34488.38 31699.22 22296.55 32479.60 34557.26 36592.72 33679.09 27593.78 35077.25 34077.37 33493.84 302
v890.54 26789.17 27594.66 24193.43 31093.40 22499.20 22396.94 30385.76 30887.56 28994.51 31881.96 24597.19 26984.94 30378.25 32593.38 319
MDA-MVSNet_test_wron85.51 30983.32 31692.10 30590.96 34388.58 31299.20 22396.52 32579.70 34457.12 36692.69 33879.11 27493.86 34977.10 34177.46 33393.86 301
ACMMPcopyleft97.74 8397.44 8398.66 10099.92 3696.13 15299.18 22599.45 1894.84 9396.41 16899.71 8991.40 15299.99 4097.99 11198.03 15399.87 97
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
WR-MVS_H91.30 24990.35 25294.15 26294.17 29892.62 24299.17 22698.94 3788.87 26586.48 30594.46 32284.36 23096.61 30388.19 27278.51 32493.21 323
TAMVS95.85 14795.58 14596.65 18997.07 22893.50 22099.17 22697.82 21791.39 22495.02 19098.01 20692.20 14097.30 26293.75 20295.83 19499.14 192
PS-MVSNAJss93.64 20493.31 20194.61 24392.11 33192.19 24999.12 22897.38 25892.51 18888.45 27496.99 23591.20 15697.29 26594.36 18587.71 25694.36 253
DTE-MVSNet89.40 28888.24 29292.88 29792.66 32689.95 29699.10 22998.22 17587.29 28785.12 31896.22 25976.27 29495.30 33583.56 31275.74 34293.41 316
CP-MVSNet91.23 25290.22 25694.26 25993.96 30192.39 24699.09 23098.57 7688.95 26386.42 30696.57 25079.19 27396.37 31090.29 25378.95 32194.02 285
AdaColmapbinary97.23 10396.80 10798.51 11699.99 195.60 17199.09 23098.84 4893.32 15496.74 15799.72 8786.04 215100.00 198.01 10999.43 11699.94 84
v1090.25 27588.82 28294.57 24693.53 30893.43 22299.08 23296.87 30985.00 31887.34 29594.51 31880.93 25797.02 28582.85 31579.23 31993.26 321
XVG-OURS-SEG-HR94.79 17194.70 16895.08 22798.05 17689.19 30399.08 23297.54 23893.66 14694.87 19199.58 10678.78 27699.79 11397.31 13193.40 22196.25 232
XVG-OURS94.82 17094.74 16795.06 22898.00 17889.19 30399.08 23297.55 23694.10 12494.71 19299.62 10380.51 26399.74 12996.04 15293.06 22596.25 232
IS-MVSNet96.29 13995.90 13897.45 16298.13 17494.80 19399.08 23297.61 23092.02 20395.54 18498.96 15890.64 16898.08 22993.73 20397.41 16499.47 160
v7n89.65 28688.29 29193.72 27892.22 33090.56 28499.07 23697.10 28385.42 31686.73 29994.72 31180.06 26797.13 27381.14 32478.12 32793.49 315
EI-MVSNet93.73 20193.40 19994.74 23896.80 24492.69 23899.06 23797.67 22388.96 26291.39 22599.02 14788.75 19297.30 26291.07 23587.85 25494.22 264
CVMVSNet94.68 17794.94 16293.89 27596.80 24486.92 32499.06 23798.98 3594.45 10794.23 20099.02 14785.60 21895.31 33490.91 24295.39 20399.43 166
baseline195.78 14994.86 16398.54 11398.47 15598.07 7499.06 23797.99 19892.68 17694.13 20198.62 18593.28 11398.69 18493.79 20085.76 26898.84 204
PEN-MVS90.19 27789.06 27893.57 28493.06 31890.90 27799.06 23798.47 10488.11 27785.91 31396.30 25776.67 28895.94 32787.07 28676.91 33893.89 298
Anonymous2023120686.32 30485.42 30689.02 32989.11 35580.53 35899.05 24195.28 34985.43 31582.82 32793.92 32674.40 30993.44 35366.99 35881.83 29893.08 325
MAR-MVS97.43 9297.19 9398.15 13599.47 10594.79 19499.05 24198.76 5292.65 17898.66 10499.82 5588.52 19599.98 4698.12 10399.63 10199.67 120
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
VNet97.21 10496.57 11499.13 7198.97 12497.82 8599.03 24399.21 2894.31 11799.18 8198.88 16986.26 21499.89 8398.93 6394.32 21299.69 117
LCM-MVSNet-Re92.31 23192.60 21191.43 31197.53 20779.27 36099.02 24491.83 36792.07 20080.31 33994.38 32383.50 23695.48 33097.22 13497.58 15999.54 151
jajsoiax91.92 23891.18 24094.15 26291.35 34090.95 27699.00 24597.42 25392.61 18087.38 29397.08 22972.46 31697.36 25794.53 18288.77 24294.13 279
test_part192.15 23590.72 24596.44 19698.87 13697.46 10398.99 24698.26 17085.89 30586.34 30896.34 25681.71 24697.48 25391.06 23678.99 32094.37 252
VPNet91.81 24090.46 24995.85 21194.74 28995.54 17298.98 24798.59 7392.14 19890.77 23297.44 21868.73 33097.54 25194.89 17077.89 32894.46 243
PS-CasMVS90.63 26589.51 27093.99 27193.83 30391.70 26598.98 24798.52 9188.48 27386.15 31196.53 25275.46 29996.31 31388.83 26578.86 32393.95 293
FMVSNet291.02 25589.56 26795.41 21897.53 20795.74 16598.98 24797.41 25587.05 29088.43 27795.00 30571.34 32096.24 31785.12 30185.21 27494.25 263
K. test v388.05 29887.24 30090.47 31991.82 33682.23 34698.96 25097.42 25389.05 25776.93 34995.60 27568.49 33195.42 33185.87 29881.01 30893.75 307
tfpnnormal89.29 29087.61 29794.34 25894.35 29594.13 20598.95 25198.94 3783.94 32584.47 32095.51 28174.84 30697.39 25677.05 34280.41 31291.48 344
AllTest92.48 22791.64 23095.00 23099.01 12088.43 31398.94 25296.82 31386.50 29888.71 27098.47 19674.73 30799.88 8985.39 29996.18 18596.71 230
h-mvs3394.92 16994.36 17296.59 19198.85 13791.29 27298.93 25398.94 3795.90 5998.77 9798.42 19890.89 16599.77 11997.80 11770.76 34798.72 209
anonymousdsp91.79 24590.92 24394.41 25790.76 34592.93 23298.93 25397.17 27589.08 25687.46 29295.30 29378.43 28196.92 28892.38 22088.73 24393.39 318
DP-MVS94.54 18193.42 19697.91 14499.46 10794.04 20698.93 25397.48 24781.15 33990.04 23999.55 10887.02 20799.95 6488.97 26498.11 14899.73 112
IterMVS-SCA-FT90.85 26090.16 25992.93 29696.72 24989.96 29598.89 25696.99 29588.95 26386.63 30195.67 27276.48 29195.00 33787.04 28784.04 28793.84 302
IterMVS90.91 25790.17 25893.12 29296.78 24790.42 28898.89 25697.05 29089.03 25886.49 30495.42 28576.59 29095.02 33687.22 28584.09 28493.93 295
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
Anonymous20240521193.10 21391.99 22596.40 19799.10 11789.65 30098.88 25897.93 20583.71 32894.00 20298.75 17868.79 32899.88 8995.08 16391.71 22799.68 118
VPA-MVSNet92.70 22291.55 23496.16 20395.09 28396.20 14998.88 25899.00 3491.02 23191.82 22295.29 29676.05 29797.96 23795.62 15881.19 30294.30 258
test20.0384.72 31583.99 30986.91 33788.19 35880.62 35798.88 25895.94 33688.36 27578.87 34394.62 31668.75 32989.11 36466.52 35975.82 34191.00 346
XXY-MVS91.82 23990.46 24995.88 20993.91 30295.40 17698.87 26197.69 22288.63 27187.87 28597.08 22974.38 31097.89 24191.66 22884.07 28594.35 256
test111195.57 15694.98 16197.37 16798.56 14893.37 22598.86 26298.45 10894.95 8596.63 15998.95 16275.21 30499.11 16395.02 16498.14 14799.64 126
SCA94.69 17593.81 18697.33 17197.10 22794.44 19998.86 26298.32 15993.30 15596.17 17395.59 27676.48 29197.95 23891.06 23697.43 16199.59 138
DWT-MVSNet_test97.31 9997.19 9397.66 15398.24 16694.67 19698.86 26298.20 18093.60 14898.09 12698.89 16797.51 798.78 17594.04 19297.28 16699.55 147
ECVR-MVScopyleft95.66 15495.05 15997.51 16098.66 14693.71 21598.85 26598.45 10894.93 8696.86 15398.96 15875.22 30399.20 15995.34 15998.15 14599.64 126
eth_miper_zixun_eth92.41 22991.93 22693.84 27697.28 22490.68 28098.83 26696.97 29988.57 27289.19 26495.73 27189.24 18696.69 30089.97 25781.55 29994.15 275
CL-MVSNet_self_test84.50 31683.15 31888.53 33386.00 36181.79 34998.82 26797.35 26085.12 31783.62 32590.91 34976.66 28991.40 35969.53 35460.36 36292.40 335
test250697.53 8997.19 9398.58 10898.66 14696.90 12398.81 26899.77 594.93 8697.95 13098.96 15892.51 13399.20 15994.93 16698.15 14599.64 126
ACMH+89.98 1690.35 27189.54 26892.78 29995.99 26086.12 32798.81 26897.18 27489.38 25383.14 32697.76 21368.42 33298.43 19889.11 26386.05 26793.78 306
Anonymous2024052185.15 31283.81 31389.16 32888.32 35682.69 34198.80 27095.74 33979.72 34381.53 33490.99 34765.38 34394.16 34572.69 34981.11 30590.63 350
N_pmnet80.06 32780.78 32577.89 34591.94 33345.28 37698.80 27056.82 37978.10 34880.08 34193.33 33177.03 28495.76 32968.14 35782.81 29192.64 330
VDD-MVS93.77 19992.94 20596.27 20198.55 15090.22 29098.77 27297.79 21890.85 23496.82 15599.42 11861.18 35499.77 11998.95 6194.13 21498.82 205
LFMVS94.75 17493.56 19298.30 12899.03 11995.70 16898.74 27397.98 20087.81 28298.47 11299.39 12367.43 33699.53 14598.01 10995.20 20699.67 120
LS3D95.84 14895.11 15898.02 14099.85 6095.10 18598.74 27398.50 10287.22 28993.66 20699.86 3187.45 20299.95 6490.94 24199.81 9199.02 197
Anonymous2024052992.10 23690.65 24796.47 19298.82 13890.61 28298.72 27598.67 6075.54 35493.90 20498.58 18866.23 33999.90 7994.70 17890.67 22898.90 202
TR-MVS94.54 18193.56 19297.49 16197.96 18094.34 20298.71 27697.51 24490.30 24494.51 19598.69 18075.56 29898.77 17792.82 21795.99 18999.35 175
USDC90.00 28188.96 28093.10 29494.81 28888.16 31798.71 27695.54 34593.66 14683.75 32497.20 22565.58 34198.31 21383.96 30987.49 26092.85 329
VDDNet93.12 21291.91 22796.76 18496.67 25192.65 24198.69 27898.21 17682.81 33397.75 13699.28 12861.57 35299.48 15398.09 10694.09 21598.15 215
EU-MVSNet90.14 27990.34 25389.54 32692.55 32781.06 35498.69 27898.04 19691.41 22386.59 30296.84 24280.83 25893.31 35486.20 29481.91 29794.26 261
mvs_tets91.81 24091.08 24194.00 27091.63 33890.58 28398.67 28097.43 25192.43 19187.37 29497.05 23271.76 31897.32 26194.75 17588.68 24494.11 280
MDA-MVSNet-bldmvs84.09 31881.52 32491.81 30991.32 34188.00 32098.67 28095.92 33780.22 34255.60 36793.32 33268.29 33393.60 35273.76 34776.61 34093.82 304
UGNet95.33 16194.57 16997.62 15698.55 15094.85 19098.67 28099.32 2595.75 6896.80 15696.27 25872.18 31799.96 5794.58 18199.05 12698.04 217
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
pm-mvs189.36 28987.81 29694.01 26993.40 31291.93 25598.62 28396.48 32786.25 30283.86 32396.14 26173.68 31397.04 28186.16 29575.73 34393.04 326
test_040285.58 30783.94 31190.50 31893.81 30485.04 33498.55 28495.20 35276.01 35179.72 34295.13 29964.15 34796.26 31666.04 36186.88 26390.21 353
ACMH89.72 1790.64 26489.63 26593.66 28395.64 27688.64 31198.55 28497.45 24889.03 25881.62 33397.61 21569.75 32698.41 20089.37 26087.62 25893.92 296
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
Anonymous2023121189.86 28288.44 28894.13 26498.93 12890.68 28098.54 28698.26 17076.28 35086.73 29995.54 27870.60 32497.56 25090.82 24480.27 31594.15 275
TransMVSNet (Re)87.25 30285.28 30793.16 29193.56 30791.03 27498.54 28694.05 36183.69 32981.09 33696.16 26075.32 30096.40 30976.69 34368.41 35492.06 338
XVG-ACMP-BASELINE91.22 25390.75 24492.63 30093.73 30585.61 32998.52 28897.44 25092.77 17189.90 24396.85 24066.64 33898.39 20492.29 22188.61 24593.89 298
CHOSEN 280x42099.01 1399.03 998.95 8699.38 10998.87 3198.46 28999.42 2197.03 2799.02 8699.09 14399.35 198.21 22499.73 3199.78 9299.77 108
OpenMVS_ROBcopyleft79.82 2083.77 32081.68 32390.03 32388.30 35782.82 34098.46 28995.22 35173.92 35876.00 35291.29 34655.00 36096.94 28768.40 35688.51 24990.34 351
GBi-Net90.88 25889.82 26394.08 26597.53 20791.97 25298.43 29196.95 30087.05 29089.68 24894.72 31171.34 32096.11 31987.01 28985.65 26994.17 268
test190.88 25889.82 26394.08 26597.53 20791.97 25298.43 29196.95 30087.05 29089.68 24894.72 31171.34 32096.11 31987.01 28985.65 26994.17 268
FMVSNet188.50 29586.64 30194.08 26595.62 27891.97 25298.43 29196.95 30083.00 33186.08 31294.72 31159.09 35696.11 31981.82 32284.07 28594.17 268
COLMAP_ROBcopyleft90.47 1492.18 23491.49 23694.25 26099.00 12288.04 31998.42 29496.70 32082.30 33688.43 27799.01 14976.97 28599.85 9886.11 29696.50 18194.86 237
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
test12337.68 34139.14 34433.31 35619.94 38024.83 38198.36 2959.75 38115.53 37451.31 36987.14 35619.62 37617.74 37647.10 3693.47 37557.36 369
131496.84 11595.96 13499.48 3696.74 24898.52 5998.31 29698.86 4695.82 6189.91 24298.98 15487.49 20199.96 5797.80 11799.73 9599.96 74
112198.03 7097.57 8099.40 4499.74 8298.21 7098.31 29698.62 6892.78 17099.53 5099.83 5195.08 53100.00 194.36 18599.92 7199.99 24
MVS96.60 12795.56 14699.72 1296.85 24199.22 1998.31 29698.94 3791.57 21590.90 23099.61 10486.66 21099.96 5797.36 13099.88 8099.99 24
NR-MVSNet91.56 24890.22 25695.60 21394.05 29995.76 16498.25 29998.70 5591.16 22780.78 33896.64 24883.23 23996.57 30491.41 23077.73 33094.46 243
MS-PatchMatch90.65 26390.30 25491.71 31094.22 29785.50 33198.24 30097.70 22188.67 26986.42 30696.37 25567.82 33498.03 23383.62 31199.62 10291.60 342
pmmvs380.27 32677.77 33087.76 33680.32 36782.43 34498.23 30191.97 36672.74 35978.75 34487.97 35457.30 35990.99 36170.31 35262.37 36089.87 354
SixPastTwentyTwo88.73 29488.01 29590.88 31491.85 33582.24 34598.22 30295.18 35388.97 26182.26 32996.89 23771.75 31996.67 30184.00 30782.98 29093.72 311
EG-PatchMatch MVS85.35 31183.81 31389.99 32490.39 34781.89 34898.21 30396.09 33481.78 33874.73 35593.72 32951.56 36497.12 27579.16 33388.61 24590.96 347
OurMVSNet-221017-089.81 28389.48 27290.83 31691.64 33781.21 35298.17 30495.38 34891.48 21885.65 31597.31 22272.66 31597.29 26588.15 27384.83 27793.97 292
LF4IMVS89.25 29288.85 28190.45 32092.81 32581.19 35398.12 30594.79 35591.44 22086.29 30997.11 22765.30 34498.11 22888.53 26985.25 27392.07 337
RPSCF91.80 24392.79 20888.83 33098.15 17269.87 36498.11 30696.60 32383.93 32694.33 19899.27 13179.60 27099.46 15491.99 22393.16 22497.18 228
pmmvs-eth3d84.03 31981.97 32290.20 32184.15 36487.09 32398.10 30794.73 35783.05 33074.10 35687.77 35565.56 34294.01 34681.08 32569.24 35189.49 357
DSMNet-mixed88.28 29788.24 29288.42 33489.64 35375.38 36298.06 30889.86 37085.59 31288.20 28292.14 34476.15 29691.95 35878.46 33596.05 18897.92 218
MVP-Stereo90.93 25690.45 25192.37 30291.25 34288.76 30798.05 30996.17 33287.27 28884.04 32195.30 29378.46 28097.27 26783.78 31099.70 9891.09 345
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
UA-Net96.54 12895.96 13498.27 12998.23 16795.71 16798.00 31098.45 10893.72 14598.41 11499.27 13188.71 19399.66 14191.19 23397.69 15699.44 165
new-patchmatchnet81.19 32379.34 32886.76 33882.86 36680.36 35997.92 31195.27 35082.09 33772.02 35786.87 35762.81 35090.74 36271.10 35163.08 35989.19 359
PCF-MVS94.20 595.18 16394.10 17898.43 12298.55 15095.99 15797.91 31297.31 26590.35 24289.48 25599.22 13885.19 22499.89 8390.40 25298.47 13799.41 168
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
pmmvs685.69 30683.84 31291.26 31390.00 35284.41 33797.82 31396.15 33375.86 35281.29 33595.39 28861.21 35396.87 29183.52 31373.29 34692.50 333
UniMVSNet_ETH3D90.06 28088.58 28694.49 25194.67 29188.09 31897.81 31497.57 23583.91 32788.44 27597.41 21957.44 35897.62 24991.41 23088.59 24797.77 222
MVS_030489.28 29188.31 29092.21 30497.05 23086.53 32597.76 31599.57 1385.58 31393.86 20592.71 33751.04 36596.30 31484.49 30592.72 22693.79 305
TinyColmap87.87 30186.51 30291.94 30795.05 28585.57 33097.65 31694.08 36084.40 32481.82 33296.85 24062.14 35198.33 21180.25 32886.37 26691.91 341
HY-MVS92.50 797.79 8197.17 9699.63 1598.98 12399.32 897.49 31799.52 1495.69 6998.32 11997.41 21993.32 11099.77 11998.08 10795.75 19799.81 102
Effi-MVS+96.30 13895.69 14398.16 13297.85 18896.26 14497.41 31897.21 27190.37 24198.65 10598.58 18886.61 21198.70 18397.11 13697.37 16599.52 154
TDRefinement84.76 31382.56 32091.38 31274.58 36984.80 33697.36 31994.56 35884.73 32280.21 34096.12 26363.56 34898.39 20487.92 27663.97 35890.95 348
FMVSNet588.32 29687.47 29890.88 31496.90 23988.39 31597.28 32095.68 34182.60 33584.67 31992.40 34279.83 26991.16 36076.39 34481.51 30093.09 324
KD-MVS_self_test83.59 32182.06 32188.20 33586.93 35980.70 35697.21 32196.38 32882.87 33282.49 32888.97 35267.63 33592.32 35673.75 34862.30 36191.58 343
LTVRE_ROB88.28 1890.29 27489.05 27994.02 26895.08 28490.15 29297.19 32297.43 25184.91 32183.99 32297.06 23174.00 31298.28 21784.08 30687.71 25693.62 313
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
KD-MVS_2432*160088.00 29986.10 30393.70 28196.91 23694.04 20697.17 32397.12 28084.93 31981.96 33092.41 34092.48 13494.51 34379.23 33052.68 36592.56 331
miper_refine_blended88.00 29986.10 30393.70 28196.91 23694.04 20697.17 32397.12 28084.93 31981.96 33092.41 34092.48 13494.51 34379.23 33052.68 36592.56 331
CostFormer96.10 14295.88 13996.78 18397.03 23192.55 24397.08 32597.83 21690.04 24898.72 10194.89 30995.01 5998.29 21496.54 14795.77 19599.50 158
tpm93.70 20393.41 19894.58 24595.36 28187.41 32297.01 32696.90 30690.85 23496.72 15894.14 32590.40 17096.84 29290.75 24688.54 24899.51 156
CMPMVSbinary61.59 2184.75 31485.14 30883.57 34290.32 34862.54 36896.98 32797.59 23474.33 35769.95 36096.66 24664.17 34698.32 21287.88 27788.41 25089.84 355
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
tpm295.47 15995.18 15696.35 20096.91 23691.70 26596.96 32897.93 20588.04 27998.44 11395.40 28693.32 11097.97 23594.00 19395.61 19999.38 170
new_pmnet84.49 31782.92 31989.21 32790.03 35182.60 34296.89 32995.62 34380.59 34175.77 35489.17 35165.04 34594.79 34172.12 35081.02 30790.23 352
UnsupCasMVSNet_eth85.52 30883.99 30990.10 32289.36 35483.51 33996.65 33097.99 19889.14 25575.89 35393.83 32763.25 34993.92 34781.92 32167.90 35692.88 328
MIMVSNet182.58 32280.51 32688.78 33186.68 36084.20 33896.65 33095.41 34778.75 34678.59 34592.44 33951.88 36389.76 36365.26 36278.95 32192.38 336
ab-mvs94.69 17593.42 19698.51 11698.07 17596.26 14496.49 33298.68 5790.31 24394.54 19397.00 23476.30 29399.71 13395.98 15393.38 22299.56 146
EPMVS96.53 12996.01 12698.09 13798.43 15696.12 15496.36 33399.43 2093.53 14997.64 13795.04 30294.41 7398.38 20891.13 23498.11 14899.75 110
tpmrst96.27 14195.98 12997.13 17497.96 18093.15 22796.34 33498.17 18292.07 20098.71 10295.12 30093.91 9698.73 18094.91 16996.62 17899.50 158
dp95.05 16694.43 17196.91 17997.99 17992.73 23796.29 33597.98 20089.70 25295.93 17694.67 31593.83 10098.45 19786.91 29296.53 18099.54 151
EGC-MVSNET69.38 32963.76 33686.26 33990.32 34881.66 35196.24 33693.85 3630.99 3763.22 37792.33 34352.44 36292.92 35559.53 36684.90 27684.21 362
tpm cat193.51 20592.52 21696.47 19297.77 19391.47 27196.13 33798.06 19480.98 34092.91 21593.78 32889.66 17798.87 17087.03 28896.39 18399.09 195
MDTV_nov1_ep13_2view96.26 14496.11 33891.89 20598.06 12794.40 7494.30 18899.67 120
PatchmatchNetpermissive95.94 14695.45 14797.39 16697.83 18994.41 20196.05 33998.40 13992.86 16497.09 14895.28 29794.21 8998.07 23189.26 26298.11 14899.70 115
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
MDTV_nov1_ep1395.69 14397.90 18394.15 20495.98 34098.44 11193.12 16097.98 12995.74 26995.10 5298.58 18890.02 25696.92 175
FPMVS68.72 33068.72 33268.71 35065.95 37344.27 37895.97 34194.74 35651.13 36553.26 36890.50 35025.11 37383.00 36860.80 36480.97 30978.87 364
PM-MVS80.47 32578.88 32985.26 34083.79 36572.22 36395.89 34291.08 36885.71 31176.56 35188.30 35336.64 36893.90 34882.39 31769.57 35089.66 356
test_post195.78 34359.23 37493.20 11797.74 24591.06 236
tpmvs94.28 19193.57 19196.40 19798.55 15091.50 27095.70 34498.55 8487.47 28492.15 22094.26 32491.42 15198.95 16988.15 27395.85 19398.76 208
ADS-MVSNet293.80 19893.88 18493.55 28597.87 18685.94 32894.24 34596.84 31090.07 24696.43 16694.48 32090.29 17295.37 33287.44 28097.23 16799.36 173
ADS-MVSNet94.79 17194.02 18097.11 17697.87 18693.79 21294.24 34598.16 18590.07 24696.43 16694.48 32090.29 17298.19 22587.44 28097.23 16799.36 173
EMVS51.44 33951.22 34152.11 35570.71 37144.97 37794.04 34775.66 37835.34 37242.40 37261.56 37328.93 37165.87 37427.64 37424.73 37045.49 371
PMMVS267.15 33264.15 33576.14 34770.56 37262.07 36993.89 34887.52 37458.09 36360.02 36378.32 36322.38 37484.54 36759.56 36547.03 36781.80 363
GG-mvs-BLEND98.54 11398.21 16898.01 7793.87 34998.52 9197.92 13197.92 21199.02 297.94 24098.17 10099.58 10799.67 120
UnsupCasMVSNet_bld79.97 32877.03 33188.78 33185.62 36281.98 34793.66 35097.35 26075.51 35570.79 35983.05 36148.70 36694.91 33978.31 33660.29 36389.46 358
E-PMN52.30 33752.18 33952.67 35471.51 37045.40 37593.62 35176.60 37736.01 37043.50 37164.13 37027.11 37267.31 37331.06 37326.06 36945.30 372
JIA-IIPM91.76 24690.70 24694.94 23296.11 25687.51 32193.16 35298.13 19075.79 35397.58 13877.68 36492.84 12497.97 23588.47 27096.54 17999.33 177
gg-mvs-nofinetune93.51 20591.86 22998.47 11897.72 20097.96 8192.62 35398.51 9874.70 35697.33 14369.59 36798.91 397.79 24397.77 12299.56 10899.67 120
MIMVSNet90.30 27388.67 28595.17 22696.45 25291.64 26792.39 35497.15 27885.99 30490.50 23493.19 33566.95 33794.86 34082.01 32093.43 22099.01 198
MVS-HIRNet86.22 30583.19 31795.31 22196.71 25090.29 28992.12 35597.33 26362.85 36286.82 29870.37 36669.37 32797.49 25275.12 34697.99 15498.15 215
CR-MVSNet93.45 20892.62 21095.94 20896.29 25392.66 23992.01 35696.23 33092.62 17996.94 15093.31 33391.04 16096.03 32479.23 33095.96 19099.13 193
RPMNet89.76 28487.28 29997.19 17396.29 25392.66 23992.01 35698.31 16170.19 36196.94 15085.87 36087.25 20499.78 11562.69 36395.96 19099.13 193
Patchmatch-test92.65 22591.50 23596.10 20596.85 24190.49 28591.50 35897.19 27282.76 33490.23 23695.59 27695.02 5798.00 23477.41 33996.98 17499.82 101
Patchmtry89.70 28588.49 28793.33 28796.24 25589.94 29891.37 35996.23 33078.22 34787.69 28693.31 33391.04 16096.03 32480.18 32982.10 29594.02 285
PatchT90.38 27088.75 28495.25 22495.99 26090.16 29191.22 36097.54 23876.80 34997.26 14486.01 35991.88 14696.07 32366.16 36095.91 19299.51 156
Patchmatch-RL test86.90 30385.98 30589.67 32584.45 36375.59 36189.71 36192.43 36586.89 29577.83 34790.94 34894.22 8693.63 35187.75 27869.61 34999.79 104
LCM-MVSNet67.77 33164.73 33476.87 34662.95 37556.25 37289.37 36293.74 36444.53 36761.99 36280.74 36220.42 37586.53 36669.37 35559.50 36487.84 360
ambc83.23 34377.17 36862.61 36787.38 36394.55 35976.72 35086.65 35830.16 36996.36 31184.85 30469.86 34890.73 349
ANet_high56.10 33552.24 33867.66 35149.27 37756.82 37183.94 36482.02 37570.47 36033.28 37464.54 36917.23 37769.16 37245.59 37023.85 37177.02 365
tmp_tt65.23 33462.94 33772.13 34944.90 37850.03 37481.05 36589.42 37338.45 36848.51 37099.90 1954.09 36178.70 37091.84 22718.26 37287.64 361
MVEpermissive53.74 2251.54 33847.86 34262.60 35259.56 37650.93 37379.41 36677.69 37635.69 37136.27 37361.76 3725.79 38169.63 37137.97 37236.61 36867.24 366
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
PMVScopyleft49.05 2353.75 33651.34 34060.97 35340.80 37934.68 37974.82 36789.62 37237.55 36928.67 37572.12 3657.09 37981.63 36943.17 37168.21 35566.59 367
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
Gipumacopyleft66.95 33365.00 33372.79 34891.52 33967.96 36566.16 36895.15 35447.89 36658.54 36467.99 36829.74 37087.54 36550.20 36877.83 32962.87 368
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
wuyk23d20.37 34320.84 34618.99 35865.34 37427.73 38050.43 3697.67 3829.50 3758.01 3766.34 3766.13 38026.24 37523.40 37510.69 3742.99 373
test_blank0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.02 3770.00 3820.00 3780.00 3760.00 3760.00 374
uanet_test0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3780.00 3820.00 3780.00 3760.00 3760.00 374
cdsmvs_eth3d_5k23.43 34231.24 3450.00 3590.00 3820.00 3830.00 37098.09 1910.00 3770.00 37899.67 9883.37 2370.00 3780.00 3760.00 3760.00 374
pcd_1.5k_mvsjas7.60 34510.13 3480.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 37891.20 1560.00 3780.00 3760.00 3760.00 374
sosnet-low-res0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3780.00 3820.00 3780.00 3760.00 3760.00 374
sosnet0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3780.00 3820.00 3780.00 3760.00 3760.00 374
uncertanet0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3780.00 3820.00 3780.00 3760.00 3760.00 374
Regformer0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3780.00 3820.00 3780.00 3760.00 3760.00 374
ab-mvs-re8.28 34411.04 3470.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 37899.40 1210.00 3820.00 3780.00 3760.00 3760.00 374
uanet0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3780.00 3820.00 3780.00 3760.00 3760.00 374
MSC_two_6792asdad99.93 299.91 4499.80 298.41 135100.00 199.96 9100.00 1100.00 1
PC_three_145296.96 2999.80 1699.79 6497.49 9100.00 199.99 599.98 35100.00 1
No_MVS99.93 299.91 4499.80 298.41 135100.00 199.96 9100.00 1100.00 1
test_one_060199.94 1499.30 1198.41 13596.63 3999.75 2799.93 1197.49 9
eth-test20.00 382
eth-test0.00 382
ZD-MVS99.92 3698.57 5598.52 9192.34 19399.31 7099.83 5195.06 5599.80 11099.70 3499.97 48
IU-MVS99.93 2799.31 998.41 13597.71 899.84 8100.00 1100.00 1100.00 1
test_241102_TWO98.43 11997.27 2099.80 1699.94 497.18 20100.00 1100.00 1100.00 1100.00 1
test_241102_ONE99.93 2799.30 1198.43 11997.26 2299.80 1699.88 2496.71 23100.00 1
test_0728_THIRD96.48 4299.83 1099.91 1597.87 4100.00 199.92 12100.00 1100.00 1
GSMVS99.59 138
test_part299.89 5099.25 1799.49 55
sam_mvs194.72 6799.59 138
sam_mvs94.25 85
MTGPAbinary98.28 166
test_post63.35 37194.43 7298.13 227
patchmatchnet-post91.70 34595.12 5197.95 238
gm-plane-assit96.97 23493.76 21491.47 21998.96 15898.79 17494.92 167
test9_res99.71 3399.99 22100.00 1
agg_prior299.48 40100.00 1100.00 1
agg_prior99.93 2798.77 4098.43 11999.63 4099.85 98
TestCases95.00 23099.01 12088.43 31396.82 31386.50 29888.71 27098.47 19674.73 30799.88 8985.39 29996.18 18596.71 230
test_prior99.43 3899.94 1498.49 6198.65 6199.80 11099.99 24
新几何199.42 4199.75 8198.27 6998.63 6792.69 17599.55 4899.82 5594.40 74100.00 191.21 23299.94 6199.99 24
旧先验199.76 7997.52 9698.64 6499.85 3595.63 4299.94 6199.99 24
原ACMM198.96 8599.73 8696.99 11998.51 9894.06 12899.62 4399.85 3594.97 6299.96 5795.11 16299.95 5599.92 91
testdata299.99 4090.54 248
segment_acmp96.68 25
testdata98.42 12399.47 10595.33 17798.56 7893.78 14299.79 2399.85 3593.64 10499.94 7294.97 16599.94 61100.00 1
test1299.43 3899.74 8298.56 5798.40 13999.65 3894.76 6699.75 12599.98 3599.99 24
plane_prior795.71 27391.59 269
plane_prior695.76 26891.72 26480.47 265
plane_prior597.87 21198.37 20997.79 12089.55 23294.52 240
plane_prior498.59 186
plane_prior391.64 26796.63 3993.01 212
plane_prior195.73 270
n20.00 383
nn0.00 383
door-mid89.69 371
lessismore_v090.53 31790.58 34680.90 35595.80 33877.01 34895.84 26666.15 34096.95 28683.03 31475.05 34493.74 310
LGP-MVS_train93.71 27995.43 27988.67 30997.62 22792.81 16790.05 23798.49 19275.24 30198.40 20295.84 15689.12 23694.07 282
test1198.44 111
door90.31 369
HQP5-MVS91.85 257
BP-MVS97.92 115
HQP4-MVS93.37 20898.39 20494.53 238
HQP3-MVS97.89 20989.60 229
HQP2-MVS80.65 261
NP-MVS95.77 26791.79 25998.65 182
ACMMP++_ref87.04 262
ACMMP++88.23 251
Test By Simon92.82 126
ITE_SJBPF92.38 30195.69 27585.14 33395.71 34092.81 16789.33 25998.11 20370.23 32598.42 19985.91 29788.16 25293.59 314
DeepMVS_CXcopyleft82.92 34495.98 26258.66 37096.01 33592.72 17278.34 34695.51 28158.29 35798.08 22982.57 31685.29 27292.03 339