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 bysort bysorted bysort bysort bysort bysort bysort bysort bysort bysort by
MVS_111021_HR98.72 2798.62 2299.01 7899.36 10197.18 10599.93 6199.90 196.81 3398.67 9199.77 6693.92 9199.89 7999.27 4399.94 5699.96 67
MVS_111021_LR98.42 4898.38 3898.53 10999.39 9995.79 15199.87 8799.86 296.70 3698.78 8699.79 6092.03 13499.90 7599.17 4499.86 7599.88 89
CHOSEN 1792x268896.81 11096.53 10897.64 14798.91 12393.07 21099.65 15399.80 395.64 6595.39 16998.86 16084.35 21599.90 7596.98 12899.16 11499.95 75
HyFIR lowres test96.66 12096.43 11197.36 15999.05 10993.91 19699.70 14499.80 390.54 22196.26 15598.08 19092.15 13298.23 20896.84 13395.46 18799.93 78
thres100view90096.74 11595.92 13099.18 5498.90 12498.77 3699.74 13499.71 592.59 16895.84 16198.86 16089.25 17099.50 14093.84 17994.57 19499.27 169
tfpn200view996.79 11195.99 12099.19 5398.94 11798.82 3199.78 12299.71 592.86 15096.02 15898.87 15889.33 16899.50 14093.84 17994.57 19499.27 169
thres600view796.69 11895.87 13399.14 6398.90 12498.78 3599.74 13499.71 592.59 16895.84 16198.86 16089.25 17099.50 14093.44 19294.50 19799.16 176
thres40096.78 11295.99 12099.16 5998.94 11798.82 3199.78 12299.71 592.86 15096.02 15898.87 15889.33 16899.50 14093.84 17994.57 19499.16 176
thres20096.96 10496.21 11599.22 5098.97 11598.84 3099.85 10199.71 593.17 14596.26 15598.88 15689.87 16399.51 13894.26 17394.91 19399.31 166
PVSNet91.05 1397.13 9996.69 10398.45 11499.52 9295.81 15099.95 4099.65 1094.73 8799.04 7599.21 13084.48 21399.95 6094.92 15298.74 12299.58 133
PVSNet_088.03 1991.80 22990.27 24096.38 18598.27 15090.46 26799.94 5599.61 1193.99 11786.26 29197.39 20571.13 30299.89 7998.77 6967.05 33698.79 194
MVS_030489.28 27788.31 27592.21 28797.05 21186.53 30497.76 29699.57 1285.58 29593.86 18992.71 31851.04 34196.30 29684.49 28792.72 21293.79 288
WTY-MVS98.10 6597.60 7499.60 1798.92 12199.28 1299.89 8199.52 1395.58 6798.24 11299.39 11693.33 10599.74 12097.98 10395.58 18699.78 100
HY-MVS92.50 797.79 7997.17 8999.63 1298.98 11499.32 697.49 29999.52 1395.69 6498.32 10797.41 20393.32 10699.77 11198.08 9795.75 18399.81 95
EPNet98.49 4398.40 3598.77 9099.62 8596.80 11899.90 7399.51 1597.60 1299.20 6899.36 11993.71 9899.91 7497.99 10198.71 12399.61 124
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
PGM-MVS98.34 5398.13 5398.99 7999.92 3597.00 11199.75 13199.50 1693.90 12399.37 5899.76 7093.24 110100.00 197.75 11299.96 4799.98 51
ACMMPcopyleft97.74 8197.44 7998.66 9599.92 3596.13 14199.18 21399.45 1794.84 8496.41 15399.71 8291.40 14199.99 3697.99 10198.03 14099.87 90
Qingshan Xu, Weihang Kong, Wenbing Tao, Marc Pollefeys: Multi-Scale Geometric Consistency Guided and Planar Prior Assisted Multi-View Stereo. IEEE Transactions on Pattern Analysis and Machine Intelligence
MG-MVS98.91 1798.65 2099.68 1199.94 1499.07 1899.64 15799.44 1897.33 1799.00 7999.72 8094.03 8999.98 4298.73 70100.00 1100.00 1
EPMVS96.53 12396.01 11998.09 13198.43 14296.12 14396.36 31299.43 1993.53 13597.64 12495.04 28494.41 6998.38 19791.13 21898.11 13599.75 103
CHOSEN 280x42099.01 1299.03 898.95 8399.38 10098.87 2798.46 27099.42 2097.03 2799.02 7699.09 13499.35 198.21 20999.73 2799.78 8499.77 101
D2MVS92.76 20792.59 20193.27 27295.13 26189.54 28199.69 14599.38 2192.26 17987.59 27094.61 29985.05 21097.79 22691.59 21388.01 23992.47 314
sss97.57 8597.03 9499.18 5498.37 14398.04 7199.73 13999.38 2193.46 13798.76 8799.06 13691.21 14399.89 7996.33 13697.01 16099.62 122
PAPM98.60 3398.42 3199.14 6396.05 23798.96 2099.90 7399.35 2396.68 3798.35 10699.66 9396.45 2598.51 18199.45 3699.89 7099.96 67
UGNet95.33 15394.57 16097.62 14998.55 13694.85 17798.67 26199.32 2495.75 6396.80 14296.27 24072.18 29699.96 5394.58 16699.05 11698.04 203
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
test_yl97.83 7597.37 8199.21 5199.18 10497.98 7499.64 15799.27 2591.43 20497.88 12098.99 14395.84 3599.84 10398.82 6495.32 19099.79 97
DCV-MVSNet97.83 7597.37 8199.21 5199.18 10497.98 7499.64 15799.27 2591.43 20497.88 12098.99 14395.84 3599.84 10398.82 6495.32 19099.79 97
VNet97.21 9896.57 10799.13 6898.97 11597.82 8099.03 23199.21 2794.31 10399.18 7198.88 15686.26 19999.89 7998.93 5894.32 19899.69 111
PVSNet_BlendedMVS96.05 13795.82 13496.72 17499.59 8696.99 11299.95 4099.10 2894.06 11498.27 10995.80 24989.00 17499.95 6099.12 4587.53 24593.24 305
PVSNet_Blended97.94 6997.64 7298.83 8899.59 8696.99 112100.00 199.10 2895.38 7098.27 10999.08 13589.00 17499.95 6099.12 4599.25 11299.57 134
UniMVSNet_NR-MVSNet92.95 20492.11 20895.49 20194.61 27195.28 16799.83 11199.08 3091.49 20089.21 24496.86 22387.14 19096.73 28093.20 19477.52 31494.46 227
CSCG97.10 10097.04 9397.27 16299.89 4491.92 23899.90 7399.07 3188.67 25295.26 17299.82 5293.17 11299.98 4298.15 9299.47 10599.90 86
PatchMatch-RL96.04 13895.40 14197.95 13599.59 8695.22 17199.52 17499.07 3193.96 11996.49 14998.35 18582.28 22699.82 10590.15 23899.22 11398.81 193
VPA-MVSNet92.70 20991.55 22096.16 18995.09 26296.20 13898.88 24499.00 3391.02 21491.82 20595.29 27876.05 27897.96 22095.62 14681.19 28794.30 242
CVMVSNet94.68 16894.94 15393.89 26096.80 22386.92 30399.06 22598.98 3494.45 9594.23 18499.02 13885.60 20395.31 31790.91 22595.39 18999.43 154
UniMVSNet (Re)93.07 20292.13 20795.88 19694.84 26696.24 13799.88 8498.98 3492.49 17589.25 24295.40 26887.09 19197.14 25593.13 19878.16 30994.26 245
tfpnnormal89.29 27687.61 28294.34 24394.35 27494.13 19298.95 23898.94 3683.94 30484.47 30195.51 26374.84 28597.39 23877.05 32180.41 29691.48 322
MVS96.60 12195.56 13999.72 996.85 22099.22 1598.31 27798.94 3691.57 19890.90 21399.61 9886.66 19599.96 5397.36 11899.88 7299.99 20
WR-MVS_H91.30 23590.35 23794.15 24794.17 27792.62 22499.17 21498.94 3688.87 24886.48 28794.46 30484.36 21496.61 28588.19 25578.51 30793.21 306
FIs94.10 18193.43 18396.11 19094.70 26996.82 11799.58 16498.93 3992.54 17289.34 24097.31 20687.62 18597.10 25994.22 17586.58 25094.40 234
EPNet_dtu95.71 14695.39 14296.66 17698.92 12193.41 20699.57 16698.90 4096.19 5197.52 12698.56 17792.65 12297.36 23977.89 31698.33 13099.20 174
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
FC-MVSNet-test93.81 18693.15 19295.80 19994.30 27596.20 13899.42 18798.89 4192.33 17889.03 24997.27 20887.39 18896.83 27693.20 19486.48 25194.36 236
baseline296.71 11796.49 10997.37 15895.63 25695.96 14799.74 13498.88 4292.94 14991.61 20698.97 14797.72 598.62 17694.83 15698.08 13997.53 211
API-MVS97.86 7297.66 7198.47 11299.52 9295.41 16399.47 18298.87 4391.68 19598.84 8399.85 3392.34 12899.99 3698.44 8399.96 47100.00 1
131496.84 10995.96 12799.48 3396.74 22798.52 5498.31 27798.86 4495.82 5689.91 22498.98 14587.49 18699.96 5397.80 10799.73 8799.96 67
MSLP-MVS++99.13 799.01 999.49 3199.94 1498.46 5899.98 898.86 4497.10 2599.80 1699.94 495.92 33100.00 199.51 33100.00 1100.00 1
AdaColmapbinary97.23 9796.80 10098.51 11099.99 195.60 15999.09 21898.84 4693.32 14096.74 14399.72 8086.04 200100.00 198.01 9999.43 10899.94 77
IB-MVS92.85 694.99 16093.94 17198.16 12797.72 18595.69 15899.99 498.81 4794.28 10592.70 20196.90 22095.08 5099.17 15196.07 13973.88 32799.60 126
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
3Dnovator91.47 1296.28 13495.34 14499.08 7196.82 22297.47 9699.45 18598.81 4795.52 6889.39 23899.00 14281.97 22799.95 6097.27 12099.83 7799.84 92
PHI-MVS98.41 4998.21 4899.03 7599.86 5297.10 10999.98 898.80 4990.78 21999.62 3799.78 6495.30 46100.00 199.80 1899.93 6299.99 20
MAR-MVS97.43 8797.19 8798.15 13099.47 9694.79 18199.05 22998.76 5092.65 16498.66 9299.82 5288.52 18099.98 4298.12 9399.63 9399.67 114
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
DU-MVS92.46 21591.45 22395.49 20194.05 27895.28 16799.81 11498.74 5192.25 18089.21 24496.64 23181.66 23096.73 28093.20 19477.52 31494.46 227
无先验99.49 17998.71 5293.46 137100.00 194.36 16999.99 20
NR-MVSNet91.56 23490.22 24195.60 20094.05 27895.76 15398.25 28098.70 5391.16 21080.78 31396.64 23183.23 22396.57 28691.41 21477.73 31394.46 227
CNVR-MVS99.40 199.26 199.84 499.98 299.51 499.98 898.69 5498.20 399.93 199.98 296.82 19100.00 199.75 22100.00 199.99 20
WR-MVS92.31 21891.25 22595.48 20494.45 27295.29 16699.60 16298.68 5590.10 22888.07 26596.89 22180.68 24296.80 27893.14 19779.67 30294.36 236
ab-mvs94.69 16693.42 18498.51 11098.07 16096.26 13396.49 31198.68 5590.31 22694.54 17797.00 21876.30 27499.71 12495.98 14193.38 20899.56 135
QAPM95.40 15294.17 16699.10 6996.92 21697.71 8299.40 18898.68 5589.31 23788.94 25098.89 15482.48 22599.96 5393.12 19999.83 7799.62 122
Anonymous2024052992.10 22290.65 23296.47 17998.82 12790.61 26398.72 25698.67 5875.54 33193.90 18898.58 17566.23 31799.90 7594.70 16390.67 21498.90 189
test_prior398.99 1398.84 1499.43 3599.94 1498.49 5699.95 4098.65 5995.78 5899.73 2699.76 7096.00 2999.80 10699.78 20100.00 199.99 20
test_prior99.43 3599.94 1498.49 5698.65 5999.80 10699.99 20
TranMVSNet+NR-MVSNet91.68 23390.61 23394.87 21993.69 28593.98 19499.69 14598.65 5991.03 21388.44 25796.83 22780.05 25096.18 30090.26 23776.89 32194.45 232
旧先验199.76 7097.52 9098.64 6299.85 3395.63 3999.94 5699.99 20
MCST-MVS99.32 399.14 499.86 399.97 399.59 399.97 1698.64 6298.47 299.13 7299.92 1196.38 26100.00 199.74 24100.00 1100.00 1
PVSNet_Blended_VisFu97.27 9596.81 9998.66 9598.81 12896.67 12099.92 6598.64 6294.51 9496.38 15498.49 17989.05 17399.88 8597.10 12598.34 12999.43 154
新几何199.42 3899.75 7298.27 6498.63 6592.69 16199.55 4299.82 5294.40 70100.00 191.21 21699.94 5699.99 20
112198.03 6797.57 7699.40 4199.74 7398.21 6598.31 27798.62 6692.78 15699.53 4499.83 4995.08 50100.00 194.36 16999.92 6699.99 20
NCCC99.37 299.25 299.71 1099.96 899.15 1699.97 1698.62 6698.02 699.90 299.95 397.33 13100.00 199.54 32100.00 1100.00 1
HFP-MVS98.56 3798.37 4099.14 6399.96 897.43 9799.95 4098.61 6894.77 8599.31 6199.85 3394.22 82100.00 198.70 7199.98 3399.98 51
#test#98.59 3598.41 3399.14 6399.96 897.43 9799.95 4098.61 6895.00 7999.31 6199.85 3394.22 82100.00 198.78 6899.98 3399.98 51
ACMMPR98.50 4298.32 4499.05 7399.96 897.18 10599.95 4098.60 7094.77 8599.31 6199.84 4693.73 97100.00 198.70 7199.98 3399.98 51
VPNet91.81 22690.46 23495.85 19894.74 26895.54 16098.98 23498.59 7192.14 18290.77 21597.44 20268.73 30997.54 23494.89 15577.89 31194.46 227
test0.0.03 193.86 18393.61 17694.64 22795.02 26592.18 23299.93 6198.58 7294.07 11287.96 26698.50 17893.90 9394.96 32181.33 30593.17 20996.78 213
DELS-MVS98.54 3998.22 4799.50 2999.15 10798.65 48100.00 198.58 7297.70 998.21 11399.24 12892.58 12499.94 6898.63 7899.94 5699.92 84
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
CP-MVSNet91.23 23890.22 24194.26 24493.96 28092.39 22899.09 21898.57 7488.95 24686.42 28896.57 23379.19 25596.37 29290.29 23678.95 30494.02 268
OpenMVScopyleft90.15 1594.77 16493.59 17998.33 12196.07 23697.48 9599.56 16898.57 7490.46 22286.51 28598.95 15178.57 26099.94 6893.86 17899.74 8697.57 210
HPM-MVS++copyleft99.07 998.88 1399.63 1299.90 4199.02 1999.95 4098.56 7697.56 1399.44 5199.85 3395.38 45100.00 199.31 4199.99 2099.87 90
testdata98.42 11799.47 9695.33 16598.56 7693.78 12899.79 2199.85 3393.64 10099.94 6894.97 15199.94 56100.00 1
EPP-MVSNet96.69 11896.60 10596.96 16697.74 18193.05 21299.37 19598.56 7688.75 25095.83 16399.01 14096.01 2898.56 17896.92 13197.20 15699.25 171
DeepPCF-MVS95.94 297.71 8298.98 1093.92 25899.63 8481.76 32799.96 2398.56 7699.47 199.19 7099.99 194.16 86100.00 199.92 999.93 62100.00 1
testtj98.89 1898.69 1899.52 2699.94 1498.56 5299.90 7398.55 8095.14 7799.72 2999.84 4695.46 43100.00 199.65 3199.99 2099.99 20
region2R98.54 3998.37 4099.05 7399.96 897.18 10599.96 2398.55 8094.87 8399.45 5099.85 3394.07 88100.00 198.67 73100.00 199.98 51
test22299.55 9097.41 10099.34 19898.55 8091.86 19099.27 6599.83 4993.84 9599.95 5099.99 20
tpmvs94.28 18093.57 18096.40 18398.55 13691.50 25295.70 32298.55 8087.47 26792.15 20394.26 30691.42 14098.95 15788.15 25695.85 17998.76 195
thisisatest053097.10 10096.72 10298.22 12697.60 19096.70 11999.92 6598.54 8491.11 21197.07 13698.97 14797.47 999.03 15393.73 18796.09 17398.92 186
tttt051796.85 10896.49 10997.92 13797.48 19695.89 14999.85 10198.54 8490.72 22096.63 14598.93 15397.47 999.02 15493.03 20095.76 18298.85 190
thisisatest051597.41 9197.02 9598.59 10297.71 18797.52 9099.97 1698.54 8491.83 19197.45 12899.04 13797.50 899.10 15294.75 16096.37 17099.16 176
GG-mvs-BLEND98.54 10798.21 15398.01 7293.87 32798.52 8797.92 11897.92 19599.02 297.94 22398.17 9099.58 9999.67 114
Regformer-398.58 3698.41 3399.10 6999.84 5897.57 8799.66 15098.52 8795.79 5799.01 7799.77 6694.40 7099.75 11698.82 6499.83 7799.98 51
Regformer-498.56 3798.39 3799.08 7199.84 5897.52 9099.66 15098.52 8795.76 6099.01 7799.77 6694.33 7899.75 11698.80 6799.83 7799.98 51
Regformer-198.79 2498.60 2399.36 4599.85 5398.34 6199.87 8798.52 8796.05 5399.41 5499.79 6094.93 5999.76 11399.07 4799.90 6899.99 20
Regformer-298.78 2598.59 2499.36 4599.85 5398.32 6299.87 8798.52 8796.04 5499.41 5499.79 6094.92 6099.76 11399.05 4899.90 6899.98 51
PS-CasMVS90.63 25189.51 25593.99 25693.83 28291.70 24798.98 23498.52 8788.48 25686.15 29296.53 23575.46 28096.31 29588.83 24878.86 30693.95 276
CANet98.27 5797.82 6799.63 1299.72 7999.10 1799.98 898.51 9397.00 2898.52 9799.71 8287.80 18399.95 6099.75 2299.38 10999.83 93
gg-mvs-nofinetune93.51 19491.86 21598.47 11297.72 18597.96 7692.62 33198.51 9374.70 33397.33 13069.59 34398.91 397.79 22697.77 11099.56 10099.67 114
EI-MVSNet-Vis-set98.27 5798.11 5498.75 9199.83 6196.59 12499.40 18898.51 9395.29 7398.51 9899.76 7093.60 10199.71 12498.53 8199.52 10299.95 75
原ACMM198.96 8299.73 7796.99 11298.51 9394.06 11499.62 3799.85 3394.97 5899.96 5395.11 14999.95 5099.92 84
EI-MVSNet-UG-set98.14 6397.99 6098.60 10099.80 6796.27 13199.36 19798.50 9795.21 7698.30 10899.75 7593.29 10899.73 12398.37 8599.30 11199.81 95
LS3D95.84 14295.11 15198.02 13499.85 5395.10 17398.74 25498.50 9787.22 27293.66 19099.86 2987.45 18799.95 6090.94 22499.81 8399.02 184
PEN-MVS90.19 26389.06 26393.57 26793.06 29790.90 25899.06 22598.47 9988.11 26085.91 29496.30 23976.67 27095.94 31087.07 26876.91 32093.89 281
DeepC-MVS_fast96.59 198.81 2298.54 2699.62 1599.90 4198.85 2999.24 20998.47 9998.14 499.08 7399.91 1393.09 113100.00 199.04 5299.99 20100.00 1
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
ETH3 D test640098.81 2298.54 2699.59 1899.93 2698.93 2299.93 6198.46 10194.56 9299.84 899.92 1194.32 7999.86 9099.96 899.98 33100.00 1
PLCcopyleft95.54 397.93 7097.89 6698.05 13399.82 6394.77 18299.92 6598.46 10193.93 12197.20 13299.27 12395.44 4499.97 5197.41 11799.51 10499.41 156
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
UA-Net96.54 12295.96 12798.27 12498.23 15295.71 15698.00 29198.45 10393.72 13198.41 10299.27 12388.71 17899.66 13291.19 21797.69 14399.44 153
ZNCC-MVS98.31 5598.03 5799.17 5799.88 4897.59 8699.94 5598.44 10494.31 10398.50 9999.82 5293.06 11499.99 3698.30 8899.99 2099.93 78
DPM-MVS98.83 2198.46 3099.97 199.33 10299.92 199.96 2398.44 10497.96 799.55 4299.94 497.18 17100.00 193.81 18299.94 5699.98 51
DPE-MVS99.26 699.10 799.74 799.89 4499.24 1499.87 8798.44 10497.48 1599.64 3499.94 496.68 2299.99 3699.99 5100.00 199.99 20
alignmvs97.81 7797.33 8499.25 4998.77 13198.66 4699.99 498.44 10494.40 9998.41 10299.47 10893.65 9999.42 14698.57 7994.26 19999.67 114
test1198.44 104
SteuartSystems-ACMMP99.02 1198.97 1199.18 5498.72 13297.71 8299.98 898.44 10496.85 2999.80 1699.91 1397.57 699.85 9499.44 3799.99 2099.99 20
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MDTV_nov1_ep1395.69 13697.90 16894.15 19195.98 31898.44 10493.12 14697.98 11795.74 25195.10 4998.58 17790.02 23996.92 162
DP-MVS Recon98.41 4998.02 5899.56 2199.97 398.70 4399.92 6598.44 10492.06 18698.40 10499.84 4695.68 38100.00 198.19 8999.71 8999.97 62
SED-MVS99.28 599.11 699.77 699.93 2699.30 899.96 2398.43 11297.27 2099.80 1699.94 496.71 20100.00 1100.00 1100.00 1100.00 1
test_241102_TWO98.43 11297.27 2099.80 1699.94 497.18 17100.00 1100.00 1100.00 1100.00 1
test_241102_ONE99.93 2699.30 898.43 11297.26 2299.80 1699.88 2296.71 20100.00 1
test_0728_SECOND99.82 599.94 1499.47 599.95 4098.43 112100.00 199.99 5100.00 1100.00 1
TEST999.92 3598.92 2399.96 2398.43 11293.90 12399.71 3099.86 2995.88 3499.85 94
train_agg98.88 1998.65 2099.59 1899.92 3598.92 2399.96 2398.43 11294.35 10099.71 3099.86 2995.94 3199.85 9499.69 3099.98 3399.99 20
test_899.92 3598.88 2699.96 2398.43 11294.35 10099.69 3299.85 3395.94 3199.85 94
agg_prior198.88 1998.66 1999.54 2399.93 2698.77 3699.96 2398.43 11294.63 9199.63 3599.85 3395.79 3799.85 9499.72 2899.99 2099.99 20
agg_prior99.93 2698.77 3698.43 11299.63 3599.85 94
PAPM_NR98.12 6497.93 6598.70 9299.94 1496.13 14199.82 11298.43 11294.56 9297.52 12699.70 8494.40 7099.98 4297.00 12799.98 3399.99 20
PAPR98.52 4198.16 5199.58 2099.97 398.77 3699.95 4098.43 11295.35 7198.03 11699.75 7594.03 8999.98 4298.11 9499.83 7799.99 20
test072699.93 2699.29 1099.96 2398.42 12397.28 1899.86 499.94 497.22 15
DVP-MVS99.09 899.12 598.98 8099.93 2697.24 10299.95 4098.42 12397.50 1499.52 4799.88 2297.43 1299.71 12499.50 3499.98 33100.00 1
XVS98.70 2898.55 2599.15 6199.94 1497.50 9399.94 5598.42 12396.22 4999.41 5499.78 6494.34 7599.96 5398.92 5999.95 5099.99 20
X-MVStestdata93.83 18492.06 21099.15 6199.94 1497.50 9399.94 5598.42 12396.22 4999.41 5441.37 35194.34 7599.96 5398.92 5999.95 5099.99 20
IU-MVS99.93 2699.31 798.41 12797.71 899.84 8100.00 1100.00 1100.00 1
test_part10.00 3370.00 3570.00 34898.41 1270.00 3580.00 3540.00 3510.00 3510.00 350
save fliter99.82 6398.79 3399.96 2398.40 12997.66 10
test1299.43 3599.74 7398.56 5298.40 12999.65 3394.76 6299.75 11699.98 3399.99 20
PatchmatchNetpermissive95.94 14095.45 14097.39 15797.83 17494.41 18796.05 31798.40 12992.86 15097.09 13595.28 27994.21 8598.07 21589.26 24598.11 13599.70 109
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
GST-MVS98.27 5797.97 6199.17 5799.92 3597.57 8799.93 6198.39 13294.04 11698.80 8599.74 7792.98 115100.00 198.16 9199.76 8599.93 78
APDe-MVS99.06 1098.91 1299.51 2899.94 1498.76 4099.91 6998.39 13297.20 2499.46 4999.85 3395.53 4299.79 10899.86 12100.00 199.99 20
MP-MVScopyleft98.23 6197.97 6199.03 7599.94 1497.17 10899.95 4098.39 13294.70 8898.26 11199.81 5691.84 138100.00 198.85 6399.97 4499.93 78
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
CP-MVS98.45 4698.32 4498.87 8699.96 896.62 12299.97 1698.39 13294.43 9798.90 8299.87 2694.30 80100.00 199.04 5299.99 2099.99 20
SMA-MVS98.76 2698.48 2999.62 1599.87 5098.87 2799.86 9898.38 13693.19 14499.77 2399.94 495.54 40100.00 199.74 2499.99 20100.00 1
TSAR-MVS + MP.98.93 1598.77 1699.41 3999.74 7398.67 4499.77 12598.38 13696.73 3599.88 399.74 7794.89 6199.59 13599.80 1899.98 3399.97 62
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
mPP-MVS98.39 5298.20 4998.97 8199.97 396.92 11599.95 4098.38 13695.04 7898.61 9599.80 5793.39 103100.00 198.64 77100.00 199.98 51
ETH3D-3000-0.198.68 2998.42 3199.47 3499.83 6198.57 5199.90 7398.37 13993.81 12699.81 1299.90 1794.34 7599.86 9099.84 1399.98 3399.97 62
ACMMP_NAP98.49 4398.14 5299.54 2399.66 8398.62 5099.85 10198.37 13994.68 8999.53 4499.83 4992.87 116100.00 198.66 7699.84 7699.99 20
APD-MVScopyleft98.62 3298.35 4399.41 3999.90 4198.51 5599.87 8798.36 14194.08 11199.74 2599.73 7994.08 8799.74 12099.42 3899.99 2099.99 20
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
SR-MVS98.46 4598.30 4698.93 8499.88 4897.04 11099.84 10598.35 14294.92 8099.32 6099.80 5793.35 10499.78 11099.30 4299.95 5099.96 67
CPTT-MVS97.64 8497.32 8598.58 10399.97 395.77 15299.96 2398.35 14289.90 23298.36 10599.79 6091.18 14799.99 3698.37 8599.99 2099.99 20
SD-MVS98.92 1698.70 1799.56 2199.70 8198.73 4199.94 5598.34 14496.38 4499.81 1299.76 7094.59 6699.98 4299.84 1399.96 4799.97 62
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
9.1498.38 3899.87 5099.91 6998.33 14593.22 14399.78 2299.89 1994.57 6799.85 9499.84 1399.97 44
CDPH-MVS98.65 3198.36 4299.49 3199.94 1498.73 4199.87 8798.33 14593.97 11899.76 2499.87 2694.99 5799.75 11698.55 80100.00 199.98 51
MSP-MVS99.30 499.16 399.73 899.93 2699.29 1099.95 4098.32 14797.28 1899.83 1099.91 1397.22 15100.00 199.99 5100.00 199.89 87
SCA94.69 16693.81 17597.33 16197.10 20894.44 18598.86 24898.32 14793.30 14196.17 15795.59 25876.48 27297.95 22191.06 22097.43 14899.59 127
APD-MVS_3200maxsize98.25 6098.08 5598.78 8999.81 6696.60 12399.82 11298.30 14993.95 12099.37 5899.77 6692.84 11799.76 11398.95 5699.92 6699.97 62
TESTMET0.1,196.74 11596.26 11498.16 12797.36 19996.48 12599.96 2398.29 15091.93 18895.77 16498.07 19195.54 4098.29 20390.55 23098.89 11899.70 109
zzz-MVS98.33 5498.00 5999.30 4799.85 5397.93 7799.80 11998.28 15195.76 6097.18 13399.88 2292.74 120100.00 198.67 7399.88 7299.99 20
MTGPAbinary98.28 151
MTAPA98.29 5697.96 6499.30 4799.85 5397.93 7799.39 19298.28 15195.76 6097.18 13399.88 2292.74 120100.00 198.67 7399.88 7299.99 20
114514_t97.41 9196.83 9899.14 6399.51 9497.83 7999.89 8198.27 15488.48 25699.06 7499.66 9390.30 15899.64 13496.32 13799.97 4499.96 67
Anonymous2023121189.86 26888.44 27394.13 24998.93 11990.68 26198.54 26798.26 15576.28 32786.73 28195.54 26070.60 30397.56 23390.82 22780.27 29994.15 258
ETH3D cwj APD-0.1698.40 5198.07 5699.40 4199.59 8698.41 5999.86 9898.24 15692.18 18199.73 2699.87 2693.47 10299.85 9499.74 2499.95 5099.93 78
Vis-MVSNetpermissive95.72 14495.15 15097.45 15397.62 18994.28 18999.28 20698.24 15694.27 10696.84 14098.94 15279.39 25398.76 16793.25 19398.49 12699.30 167
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
3Dnovator+91.53 1196.31 13195.24 14699.52 2696.88 21998.64 4999.72 14298.24 15695.27 7588.42 26198.98 14582.76 22499.94 6897.10 12599.83 7799.96 67
DTE-MVSNet89.40 27388.24 27792.88 28092.66 30489.95 27599.10 21798.22 15987.29 27085.12 29996.22 24176.27 27595.30 31883.56 29475.74 32493.41 299
SF-MVS98.67 3098.40 3599.50 2999.77 6998.67 4499.90 7398.21 16093.53 13599.81 1299.89 1994.70 6499.86 9099.84 1399.93 6299.96 67
VDDNet93.12 20091.91 21396.76 17296.67 23092.65 22398.69 25998.21 16082.81 31197.75 12399.28 12061.57 32999.48 14498.09 9694.09 20198.15 201
test-LLR96.47 12496.04 11897.78 14097.02 21395.44 16199.96 2398.21 16094.07 11295.55 16696.38 23693.90 9398.27 20690.42 23398.83 12099.64 120
test-mter96.39 12895.93 12997.78 14097.02 21395.44 16199.96 2398.21 16091.81 19395.55 16696.38 23695.17 4798.27 20690.42 23398.83 12099.64 120
DWT-MVSNet_test97.31 9397.19 8797.66 14698.24 15194.67 18398.86 24898.20 16493.60 13498.09 11498.89 15497.51 798.78 16494.04 17697.28 15399.55 136
MP-MVS-pluss98.07 6697.64 7299.38 4499.74 7398.41 5999.74 13498.18 16593.35 13996.45 15099.85 3392.64 12399.97 5198.91 6199.89 7099.77 101
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
PS-MVSNAJ98.44 4798.20 4999.16 5998.80 12998.92 2399.54 17298.17 16697.34 1699.85 699.85 3391.20 14499.89 7999.41 3999.67 9198.69 196
HPM-MVScopyleft97.96 6897.72 6998.68 9399.84 5896.39 13099.90 7398.17 16692.61 16698.62 9499.57 10191.87 13799.67 13198.87 6299.99 2099.99 20
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
tpmrst96.27 13595.98 12297.13 16397.96 16593.15 20996.34 31398.17 16692.07 18498.71 9095.12 28293.91 9298.73 16994.91 15496.62 16599.50 146
ADS-MVSNet94.79 16294.02 16997.11 16597.87 17193.79 19794.24 32398.16 16990.07 22996.43 15194.48 30290.29 15998.19 21087.44 26297.23 15499.36 160
HPM-MVS_fast97.80 7897.50 7798.68 9399.79 6896.42 12799.88 8498.16 16991.75 19498.94 8199.54 10491.82 13999.65 13397.62 11499.99 2099.99 20
Vis-MVSNet (Re-imp)96.32 13095.98 12297.35 16097.93 16794.82 17999.47 18298.15 17191.83 19195.09 17399.11 13391.37 14297.47 23693.47 19197.43 14899.74 104
abl_697.67 8397.34 8398.66 9599.68 8296.11 14499.68 14798.14 17293.80 12799.27 6599.70 8488.65 17999.98 4297.46 11699.72 8899.89 87
CNLPA97.76 8097.38 8098.92 8599.53 9196.84 11699.87 8798.14 17293.78 12896.55 14899.69 8792.28 12999.98 4297.13 12399.44 10799.93 78
JIA-IIPM91.76 23290.70 23194.94 21796.11 23587.51 30093.16 33098.13 17475.79 33097.58 12577.68 34092.84 11797.97 21888.47 25396.54 16699.33 164
cl-mvsnet293.77 18893.25 19195.33 20699.49 9594.43 18699.61 16198.09 17590.38 22389.16 24795.61 25690.56 15697.34 24191.93 20884.45 26694.21 250
cdsmvs_eth3d_5k23.43 32231.24 3240.00 3370.00 3560.00 3570.00 34898.09 1750.00 3520.00 35399.67 9183.37 2210.00 3540.00 3510.00 3510.00 350
xiu_mvs_v2_base98.23 6197.97 6199.02 7798.69 13398.66 4699.52 17498.08 17797.05 2699.86 499.86 2990.65 15499.71 12499.39 4098.63 12498.69 196
tpm cat193.51 19492.52 20396.47 17997.77 17891.47 25396.13 31598.06 17880.98 31892.91 19893.78 31089.66 16498.87 15987.03 27096.39 16999.09 182
DeepC-MVS94.51 496.92 10796.40 11298.45 11499.16 10695.90 14899.66 15098.06 17896.37 4794.37 18199.49 10783.29 22299.90 7597.63 11399.61 9799.55 136
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
EU-MVSNet90.14 26590.34 23889.54 30992.55 30581.06 33098.69 25998.04 18091.41 20686.59 28496.84 22680.83 24093.31 33486.20 27681.91 28294.26 245
TAPA-MVS92.12 894.42 17693.60 17896.90 16899.33 10291.78 24299.78 12298.00 18189.89 23394.52 17899.47 10891.97 13599.18 15069.90 33099.52 10299.73 105
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
baseline195.78 14394.86 15498.54 10798.47 14198.07 6999.06 22597.99 18292.68 16294.13 18598.62 17293.28 10998.69 17393.79 18485.76 25498.84 191
UnsupCasMVSNet_eth85.52 29283.99 29290.10 30589.36 33083.51 31896.65 30997.99 18289.14 23875.89 32893.83 30963.25 32693.92 32781.92 30367.90 33592.88 310
LFMVS94.75 16593.56 18198.30 12399.03 11095.70 15798.74 25497.98 18487.81 26598.47 10099.39 11667.43 31499.53 13698.01 9995.20 19299.67 114
dp95.05 15894.43 16296.91 16797.99 16492.73 21996.29 31497.98 18489.70 23595.93 16094.67 29793.83 9698.45 18686.91 27496.53 16799.54 140
PMMVS96.76 11396.76 10196.76 17298.28 14792.10 23399.91 6997.98 18494.12 10999.53 4499.39 11686.93 19398.73 16996.95 13097.73 14299.45 151
F-COLMAP96.93 10696.95 9696.87 16999.71 8091.74 24399.85 10197.95 18793.11 14795.72 16599.16 13292.35 12799.94 6895.32 14799.35 11098.92 186
OMC-MVS97.28 9497.23 8697.41 15599.76 7093.36 20899.65 15397.95 18796.03 5597.41 12999.70 8489.61 16599.51 13896.73 13498.25 13499.38 158
Anonymous20240521193.10 20191.99 21196.40 18399.10 10889.65 27998.88 24497.93 18983.71 30794.00 18698.75 16568.79 30799.88 8595.08 15091.71 21399.68 112
tpm295.47 15195.18 14996.35 18696.91 21791.70 24796.96 30797.93 18988.04 26298.44 10195.40 26893.32 10697.97 21894.00 17795.61 18599.38 158
TSAR-MVS + GP.98.60 3398.51 2898.86 8799.73 7796.63 12199.97 1697.92 19198.07 598.76 8799.55 10295.00 5699.94 6899.91 1197.68 14499.99 20
CDS-MVSNet96.34 12996.07 11797.13 16397.37 19894.96 17599.53 17397.91 19291.55 19995.37 17098.32 18695.05 5297.13 25693.80 18395.75 18399.30 167
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
HQP3-MVS97.89 19389.60 215
HQP-MVS94.61 17094.50 16194.92 21895.78 24391.85 23999.87 8797.89 19396.82 3093.37 19198.65 16980.65 24398.39 19397.92 10589.60 21594.53 222
HQP_MVS94.49 17594.36 16394.87 21995.71 25291.74 24399.84 10597.87 19596.38 4493.01 19598.59 17380.47 24798.37 19897.79 10889.55 21894.52 224
plane_prior597.87 19598.37 19897.79 10889.55 21894.52 224
xiu_mvs_v1_base_debu97.43 8797.06 9098.55 10497.74 18198.14 6699.31 20297.86 19796.43 4199.62 3799.69 8785.56 20499.68 12899.05 4898.31 13197.83 205
xiu_mvs_v1_base97.43 8797.06 9098.55 10497.74 18198.14 6699.31 20297.86 19796.43 4199.62 3799.69 8785.56 20499.68 12899.05 4898.31 13197.83 205
xiu_mvs_v1_base_debi97.43 8797.06 9098.55 10497.74 18198.14 6699.31 20297.86 19796.43 4199.62 3799.69 8785.56 20499.68 12899.05 4898.31 13197.83 205
CostFormer96.10 13695.88 13296.78 17197.03 21292.55 22597.08 30497.83 20090.04 23198.72 8994.89 29195.01 5598.29 20396.54 13595.77 18199.50 146
TAMVS95.85 14195.58 13896.65 17797.07 20993.50 20399.17 21497.82 20191.39 20795.02 17498.01 19292.20 13097.30 24493.75 18695.83 18099.14 179
VDD-MVS93.77 18892.94 19396.27 18798.55 13690.22 27198.77 25397.79 20290.85 21796.82 14199.42 11261.18 33199.77 11198.95 5694.13 20098.82 192
cascas94.64 16993.61 17697.74 14597.82 17596.26 13399.96 2397.78 20385.76 29094.00 18697.54 20076.95 26899.21 14997.23 12195.43 18897.76 209
CLD-MVS94.06 18293.90 17294.55 23296.02 23890.69 26099.98 897.72 20496.62 3991.05 21298.85 16377.21 26598.47 18298.11 9489.51 22094.48 226
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
MS-PatchMatch90.65 24990.30 23991.71 29394.22 27685.50 31098.24 28197.70 20588.67 25286.42 28896.37 23867.82 31398.03 21683.62 29399.62 9491.60 321
XXY-MVS91.82 22590.46 23495.88 19693.91 28195.40 16498.87 24797.69 20688.63 25487.87 26797.08 21374.38 28997.89 22491.66 21284.07 27094.35 239
EI-MVSNet93.73 19093.40 18794.74 22396.80 22392.69 22099.06 22597.67 20788.96 24591.39 20899.02 13888.75 17797.30 24491.07 21987.85 24094.22 248
MVSTER95.53 14995.22 14796.45 18198.56 13597.72 8199.91 6997.67 20792.38 17791.39 20897.14 21097.24 1497.30 24494.80 15787.85 24094.34 240
ETV-MVS97.92 7197.80 6898.25 12598.14 15896.48 12599.98 897.63 20995.61 6699.29 6499.46 11092.55 12598.82 16199.02 5498.54 12599.46 149
CANet_DTU96.76 11396.15 11698.60 10098.78 13097.53 8999.84 10597.63 20997.25 2399.20 6899.64 9681.36 23499.98 4292.77 20298.89 11898.28 199
RPMNet89.39 27487.20 28595.94 19496.29 23292.66 22192.01 33497.63 20970.19 33896.94 13785.87 33687.25 18996.03 30662.69 33995.96 17699.13 180
LPG-MVS_test92.96 20392.71 19793.71 26495.43 25888.67 28899.75 13197.62 21292.81 15390.05 21998.49 17975.24 28298.40 19195.84 14489.12 22294.07 265
LGP-MVS_train93.71 26495.43 25888.67 28897.62 21292.81 15390.05 21998.49 17975.24 28298.40 19195.84 14489.12 22294.07 265
FMVSNet392.69 21091.58 21895.99 19298.29 14697.42 9999.26 20897.62 21289.80 23489.68 23095.32 27481.62 23296.27 29787.01 27185.65 25594.29 243
ET-MVSNet_ETH3D94.37 17793.28 19097.64 14798.30 14597.99 7399.99 497.61 21594.35 10071.57 33399.45 11196.23 2795.34 31696.91 13285.14 26299.59 127
EIA-MVS97.53 8697.46 7897.76 14398.04 16294.84 17899.98 897.61 21594.41 9897.90 11999.59 9992.40 12698.87 15998.04 9899.13 11599.59 127
OPM-MVS93.21 19892.80 19594.44 23993.12 29590.85 25999.77 12597.61 21596.19 5191.56 20798.65 16975.16 28498.47 18293.78 18589.39 22193.99 273
IS-MVSNet96.29 13395.90 13197.45 15398.13 15994.80 18099.08 22097.61 21592.02 18795.54 16898.96 14990.64 15598.08 21393.73 18797.41 15199.47 148
CMPMVSbinary61.59 2184.75 29885.14 29183.57 32090.32 32662.54 34296.98 30697.59 21974.33 33469.95 33596.66 22964.17 32398.32 20187.88 25988.41 23689.84 332
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
UniMVSNet_ETH3D90.06 26688.58 27194.49 23694.67 27088.09 29797.81 29597.57 22083.91 30688.44 25797.41 20357.44 33597.62 23291.41 21488.59 23397.77 208
lupinMVS97.85 7397.60 7498.62 9897.28 20597.70 8499.99 497.55 22195.50 6999.43 5299.67 9190.92 15298.71 17198.40 8499.62 9499.45 151
XVG-OURS94.82 16194.74 15895.06 21398.00 16389.19 28299.08 22097.55 22194.10 11094.71 17699.62 9780.51 24599.74 12096.04 14093.06 21196.25 216
XVG-OURS-SEG-HR94.79 16294.70 15995.08 21298.05 16189.19 28299.08 22097.54 22393.66 13294.87 17599.58 10078.78 25899.79 10897.31 11993.40 20796.25 216
PatchT90.38 25688.75 26995.25 20895.99 23990.16 27291.22 33897.54 22376.80 32697.26 13186.01 33591.88 13696.07 30566.16 33695.91 17899.51 144
BH-RMVSNet95.18 15594.31 16497.80 13998.17 15695.23 17099.76 13097.53 22592.52 17394.27 18399.25 12776.84 26998.80 16290.89 22699.54 10199.35 162
ACMP92.05 992.74 20892.42 20593.73 26295.91 24288.72 28799.81 11497.53 22594.13 10887.00 27998.23 18774.07 29098.47 18296.22 13888.86 22793.99 273
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
xxxxxxxxxxxxxcwj98.98 1498.79 1599.54 2399.82 6398.79 3399.96 2397.52 22797.66 1099.81 1299.89 1994.70 6499.86 9099.84 1399.93 6299.96 67
CS-MVS97.84 7497.69 7098.31 12298.28 14796.27 131100.00 197.52 22795.29 7399.25 6799.65 9591.18 14798.94 15898.96 5599.04 11799.73 105
ACMM91.95 1092.88 20592.52 20393.98 25795.75 24889.08 28599.77 12597.52 22793.00 14889.95 22397.99 19376.17 27698.46 18593.63 19088.87 22694.39 235
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
TR-MVS94.54 17293.56 18197.49 15297.96 16594.34 18898.71 25797.51 23090.30 22794.51 17998.69 16775.56 27998.77 16692.82 20195.99 17599.35 162
BH-w/o95.71 14695.38 14396.68 17598.49 14092.28 22999.84 10597.50 23192.12 18392.06 20498.79 16484.69 21198.67 17495.29 14899.66 9299.09 182
mvs_anonymous95.65 14895.03 15297.53 15098.19 15495.74 15499.33 19997.49 23290.87 21690.47 21797.10 21288.23 18197.16 25395.92 14297.66 14599.68 112
DP-MVS94.54 17293.42 18497.91 13899.46 9894.04 19398.93 24097.48 23381.15 31790.04 22199.55 10287.02 19299.95 6088.97 24798.11 13599.73 105
RRT_test8_iter0594.58 17194.11 16795.98 19397.88 16996.11 14499.89 8197.45 23491.66 19688.28 26296.71 22896.53 2497.40 23794.73 16283.85 27394.45 232
ACMH89.72 1790.64 25089.63 25093.66 26695.64 25588.64 29098.55 26597.45 23489.03 24181.62 31097.61 19969.75 30598.41 18989.37 24387.62 24493.92 279
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
XVG-ACMP-BASELINE91.22 23990.75 23092.63 28393.73 28485.61 30898.52 26997.44 23692.77 15789.90 22596.85 22466.64 31698.39 19392.29 20488.61 23193.89 281
mvs_tets91.81 22691.08 22794.00 25591.63 31690.58 26498.67 26197.43 23792.43 17687.37 27697.05 21671.76 29797.32 24394.75 16088.68 23094.11 263
LTVRE_ROB88.28 1890.29 26089.05 26494.02 25395.08 26390.15 27397.19 30397.43 23784.91 30083.99 30397.06 21574.00 29198.28 20584.08 28887.71 24293.62 296
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
jajsoiax91.92 22491.18 22694.15 24791.35 31890.95 25799.00 23397.42 23992.61 16687.38 27597.08 21372.46 29597.36 23994.53 16788.77 22894.13 262
K. test v388.05 28487.24 28490.47 30291.82 31482.23 32498.96 23797.42 23989.05 24076.93 32495.60 25768.49 31095.42 31485.87 28081.01 29293.75 290
RRT_MVS95.23 15494.77 15796.61 17898.28 14798.32 6299.81 11497.41 24192.59 16891.28 21097.76 19795.02 5397.23 25093.65 18987.14 24794.28 244
FMVSNet291.02 24189.56 25295.41 20597.53 19295.74 15498.98 23497.41 24187.05 27388.43 25995.00 28771.34 29996.24 29985.12 28385.21 26094.25 247
jason97.24 9696.86 9798.38 12095.73 24997.32 10199.97 1697.40 24395.34 7298.60 9699.54 10487.70 18498.56 17897.94 10499.47 10599.25 171
jason: jason.
PS-MVSNAJss93.64 19393.31 18994.61 22892.11 30992.19 23199.12 21697.38 24492.51 17488.45 25696.99 21991.20 14497.29 24794.36 16987.71 24294.36 236
MSDG94.37 17793.36 18897.40 15698.88 12693.95 19599.37 19597.38 24485.75 29290.80 21499.17 13184.11 21799.88 8586.35 27598.43 12898.36 198
canonicalmvs97.09 10296.32 11399.39 4398.93 11998.95 2199.72 14297.35 24694.45 9597.88 12099.42 11286.71 19499.52 13798.48 8293.97 20399.72 108
UnsupCasMVSNet_bld79.97 30977.03 31188.78 31385.62 33581.98 32593.66 32897.35 24675.51 33270.79 33483.05 33748.70 34294.91 32278.31 31560.29 34089.46 335
MVS-HIRNet86.22 28983.19 29995.31 20796.71 22990.29 27092.12 33397.33 24862.85 33986.82 28070.37 34269.37 30697.49 23575.12 32597.99 14198.15 201
BH-untuned95.18 15594.83 15596.22 18898.36 14491.22 25499.80 11997.32 24990.91 21591.08 21198.67 16883.51 21998.54 18094.23 17499.61 9798.92 186
PCF-MVS94.20 595.18 15594.10 16898.43 11698.55 13695.99 14697.91 29397.31 25090.35 22589.48 23799.22 12985.19 20899.89 7990.40 23598.47 12799.41 156
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
miper_enhance_ethall94.36 17993.98 17095.49 20198.68 13495.24 16999.73 13997.29 25193.28 14289.86 22695.97 24794.37 7497.05 26292.20 20684.45 26694.19 251
MVSFormer96.94 10596.60 10597.95 13597.28 20597.70 8499.55 17097.27 25291.17 20899.43 5299.54 10490.92 15296.89 27294.67 16499.62 9499.25 171
test_djsdf92.83 20692.29 20694.47 23791.90 31292.46 22699.55 17097.27 25291.17 20889.96 22296.07 24681.10 23696.89 27294.67 16488.91 22494.05 267
GA-MVS93.83 18492.84 19496.80 17095.73 24993.57 20199.88 8497.24 25492.57 17192.92 19796.66 22978.73 25997.67 23087.75 26094.06 20299.17 175
Effi-MVS+96.30 13295.69 13698.16 12797.85 17396.26 13397.41 30097.21 25590.37 22498.65 9398.58 17586.61 19698.70 17297.11 12497.37 15299.52 143
Patchmatch-test92.65 21291.50 22196.10 19196.85 22090.49 26691.50 33697.19 25682.76 31290.23 21895.59 25895.02 5398.00 21777.41 31896.98 16199.82 94
diffmvs97.00 10396.64 10498.09 13197.64 18896.17 14099.81 11497.19 25694.67 9098.95 8099.28 12086.43 19798.76 16798.37 8597.42 15099.33 164
ACMH+89.98 1690.35 25789.54 25392.78 28295.99 23986.12 30698.81 25197.18 25889.38 23683.14 30697.76 19768.42 31198.43 18789.11 24686.05 25393.78 289
anonymousdsp91.79 23190.92 22994.41 24290.76 32392.93 21498.93 24097.17 25989.08 23987.46 27495.30 27578.43 26396.92 27192.38 20388.73 22993.39 301
baseline96.43 12695.98 12297.76 14397.34 20095.17 17299.51 17697.17 25993.92 12296.90 13999.28 12085.37 20798.64 17597.50 11596.86 16499.46 149
nrg03093.51 19492.53 20296.45 18194.36 27397.20 10499.81 11497.16 26191.60 19789.86 22697.46 20186.37 19897.68 22995.88 14380.31 29894.46 227
MVS_Test96.46 12595.74 13598.61 9998.18 15597.23 10399.31 20297.15 26291.07 21298.84 8397.05 21688.17 18298.97 15694.39 16897.50 14799.61 124
MIMVSNet90.30 25988.67 27095.17 21196.45 23191.64 24992.39 33297.15 26285.99 28790.50 21693.19 31666.95 31594.86 32382.01 30293.43 20699.01 185
v7n89.65 27188.29 27693.72 26392.22 30890.56 26599.07 22497.10 26485.42 29886.73 28194.72 29380.06 24997.13 25681.14 30678.12 31093.49 298
casdiffmvs96.42 12795.97 12597.77 14297.30 20494.98 17499.84 10597.09 26593.75 13096.58 14699.26 12685.07 20998.78 16497.77 11097.04 15999.54 140
Fast-Effi-MVS+95.02 15994.19 16597.52 15197.88 16994.55 18499.97 1697.08 26688.85 24994.47 18097.96 19484.59 21298.41 18989.84 24197.10 15799.59 127
miper_ehance_all_eth93.16 19992.60 19994.82 22297.57 19193.56 20299.50 17797.07 26788.75 25088.85 25195.52 26290.97 15196.74 27990.77 22884.45 26694.17 252
Effi-MVS+-dtu94.53 17495.30 14592.22 28697.77 17882.54 32199.59 16397.06 26894.92 8095.29 17195.37 27285.81 20197.89 22494.80 15797.07 15896.23 218
mvs-test195.53 14995.97 12594.20 24697.77 17885.44 31199.95 4097.06 26894.92 8096.58 14698.72 16685.81 20198.98 15594.80 15798.11 13598.18 200
IterMVS90.91 24390.17 24393.12 27596.78 22690.42 26998.89 24297.05 27089.03 24186.49 28695.42 26776.59 27195.02 31987.22 26784.09 26993.93 278
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
v119290.62 25289.25 25994.72 22593.13 29393.07 21099.50 17797.02 27186.33 28489.56 23695.01 28579.22 25497.09 26182.34 30081.16 28894.01 270
v2v48291.30 23590.07 24695.01 21493.13 29393.79 19799.77 12597.02 27188.05 26189.25 24295.37 27280.73 24197.15 25487.28 26680.04 30194.09 264
V4291.28 23790.12 24594.74 22393.42 29093.46 20499.68 14797.02 27187.36 26989.85 22895.05 28381.31 23597.34 24187.34 26580.07 30093.40 300
testing_285.10 29681.72 30395.22 20982.25 34094.16 19097.54 29897.01 27488.15 25962.23 33786.43 33444.43 34397.18 25292.28 20585.20 26194.31 241
IterMVS-SCA-FT90.85 24690.16 24492.93 27996.72 22889.96 27498.89 24296.99 27588.95 24686.63 28395.67 25476.48 27295.00 32087.04 26984.04 27293.84 285
v14419290.79 24789.52 25494.59 22993.11 29692.77 21599.56 16896.99 27586.38 28389.82 22994.95 29080.50 24697.10 25983.98 29080.41 29693.90 280
v192192090.46 25489.12 26194.50 23592.96 30092.46 22699.49 17996.98 27786.10 28689.61 23595.30 27578.55 26197.03 26682.17 30180.89 29494.01 270
v114491.09 24089.83 24794.87 21993.25 29293.69 20099.62 16096.98 27786.83 27989.64 23494.99 28880.94 23897.05 26285.08 28481.16 28893.87 283
eth_miper_zixun_eth92.41 21691.93 21293.84 26197.28 20590.68 26198.83 25096.97 27988.57 25589.19 24695.73 25389.24 17296.69 28289.97 24081.55 28494.15 258
GBi-Net90.88 24489.82 24894.08 25097.53 19291.97 23498.43 27296.95 28087.05 27389.68 23094.72 29371.34 29996.11 30187.01 27185.65 25594.17 252
test190.88 24489.82 24894.08 25097.53 19291.97 23498.43 27296.95 28087.05 27389.68 23094.72 29371.34 29996.11 30187.01 27185.65 25594.17 252
FMVSNet188.50 28186.64 28694.08 25095.62 25791.97 23498.43 27296.95 28083.00 31086.08 29394.72 29359.09 33396.11 30181.82 30484.07 27094.17 252
v890.54 25389.17 26094.66 22693.43 28993.40 20799.20 21196.94 28385.76 29087.56 27194.51 30081.96 22897.19 25184.94 28578.25 30893.38 302
cl_fuxian92.53 21391.87 21494.52 23397.40 19792.99 21399.40 18896.93 28487.86 26388.69 25495.44 26689.95 16296.44 29090.45 23280.69 29594.14 261
v124090.20 26288.79 26894.44 23993.05 29892.27 23099.38 19396.92 28585.89 28889.36 23994.87 29277.89 26497.03 26680.66 30881.08 29094.01 270
tpm93.70 19293.41 18694.58 23095.36 26087.41 30197.01 30596.90 28690.85 21796.72 14494.14 30790.40 15796.84 27590.75 22988.54 23499.51 144
v14890.70 24889.63 25093.92 25892.97 29990.97 25699.75 13196.89 28787.51 26688.27 26395.01 28581.67 22997.04 26487.40 26477.17 31893.75 290
IterMVS-LS92.69 21092.11 20894.43 24196.80 22392.74 21799.45 18596.89 28788.98 24389.65 23395.38 27188.77 17696.34 29490.98 22382.04 28194.22 248
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
v1090.25 26188.82 26794.57 23193.53 28793.43 20599.08 22096.87 28985.00 29987.34 27794.51 30080.93 23997.02 26882.85 29779.23 30393.26 304
ADS-MVSNet293.80 18793.88 17393.55 26897.87 17185.94 30794.24 32396.84 29090.07 22996.43 15194.48 30290.29 15995.37 31587.44 26297.23 15499.36 160
Fast-Effi-MVS+-dtu93.72 19193.86 17493.29 27197.06 21086.16 30599.80 11996.83 29192.66 16392.58 20297.83 19681.39 23397.67 23089.75 24296.87 16396.05 220
pmmvs492.10 22291.07 22895.18 21092.82 30294.96 17599.48 18196.83 29187.45 26888.66 25596.56 23483.78 21896.83 27689.29 24484.77 26493.75 290
AllTest92.48 21491.64 21695.00 21599.01 11188.43 29298.94 23996.82 29386.50 28188.71 25298.47 18374.73 28699.88 8585.39 28196.18 17196.71 214
TestCases95.00 21599.01 11188.43 29296.82 29386.50 28188.71 25298.47 18374.73 28699.88 8585.39 28196.18 17196.71 214
miper_lstm_enhance91.81 22691.39 22493.06 27897.34 20089.18 28499.38 19396.79 29586.70 28087.47 27395.22 28090.00 16195.86 31188.26 25481.37 28694.15 258
cl-mvsnet_92.31 21891.58 21894.52 23397.33 20292.77 21599.57 16696.78 29686.97 27787.56 27195.51 26389.43 16796.62 28488.60 24982.44 27894.16 257
cl-mvsnet192.32 21791.60 21794.47 23797.31 20392.74 21799.58 16496.75 29786.99 27687.64 26995.54 26089.55 16696.50 28888.58 25082.44 27894.17 252
ppachtmachnet_test89.58 27288.35 27493.25 27392.40 30690.44 26899.33 19996.73 29885.49 29685.90 29595.77 25081.09 23796.00 30976.00 32482.49 27793.30 303
COLMAP_ROBcopyleft90.47 1492.18 22191.49 22294.25 24599.00 11388.04 29898.42 27596.70 29982.30 31488.43 25999.01 14076.97 26799.85 9486.11 27896.50 16894.86 221
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
1112_ss96.01 13995.20 14898.42 11797.80 17696.41 12899.65 15396.66 30092.71 15992.88 19999.40 11492.16 13199.30 14791.92 20993.66 20499.55 136
Test_1112_low_res95.72 14494.83 15598.42 11797.79 17796.41 12899.65 15396.65 30192.70 16092.86 20096.13 24492.15 13299.30 14791.88 21093.64 20599.55 136
RPSCF91.80 22992.79 19688.83 31298.15 15769.87 33998.11 28796.60 30283.93 30594.33 18299.27 12379.60 25299.46 14591.99 20793.16 21097.18 212
YYNet185.50 29483.33 29792.00 28990.89 32288.38 29599.22 21096.55 30379.60 32257.26 34192.72 31779.09 25793.78 33077.25 31977.37 31793.84 285
MDA-MVSNet_test_wron85.51 29383.32 29892.10 28890.96 32188.58 29199.20 21196.52 30479.70 32157.12 34292.69 31979.11 25693.86 32977.10 32077.46 31693.86 284
MTMP99.87 8796.49 305
pm-mvs189.36 27587.81 28194.01 25493.40 29191.93 23798.62 26496.48 30686.25 28583.86 30496.14 24373.68 29297.04 26486.16 27775.73 32593.04 309
our_test_390.39 25589.48 25793.12 27592.40 30689.57 28099.33 19996.35 30787.84 26485.30 29794.99 28884.14 21696.09 30480.38 30984.56 26593.71 295
CR-MVSNet93.45 19792.62 19895.94 19496.29 23292.66 22192.01 33496.23 30892.62 16596.94 13793.31 31491.04 14996.03 30679.23 31295.96 17699.13 180
Patchmtry89.70 27088.49 27293.33 27096.24 23489.94 27791.37 33796.23 30878.22 32487.69 26893.31 31491.04 14996.03 30680.18 31182.10 28094.02 268
MVP-Stereo90.93 24290.45 23692.37 28591.25 32088.76 28698.05 29096.17 31087.27 27184.04 30295.30 27578.46 26297.27 24983.78 29299.70 9091.09 323
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
pmmvs685.69 29083.84 29591.26 29690.00 32884.41 31697.82 29496.15 31175.86 32981.29 31195.39 27061.21 33096.87 27483.52 29573.29 32892.50 313
EG-PatchMatch MVS85.35 29583.81 29689.99 30790.39 32581.89 32698.21 28496.09 31281.78 31674.73 33093.72 31151.56 34097.12 25879.16 31388.61 23190.96 325
DeepMVS_CXcopyleft82.92 32295.98 24158.66 34496.01 31392.72 15878.34 32195.51 26358.29 33498.08 21382.57 29885.29 25892.03 318
test20.0384.72 29983.99 29286.91 31788.19 33380.62 33298.88 24495.94 31488.36 25878.87 31894.62 29868.75 30889.11 34066.52 33575.82 32391.00 324
MDA-MVSNet-bldmvs84.09 30181.52 30591.81 29291.32 31988.00 29998.67 26195.92 31580.22 32055.60 34393.32 31368.29 31293.60 33273.76 32676.61 32293.82 287
lessismore_v090.53 30090.58 32480.90 33195.80 31677.01 32395.84 24866.15 31896.95 26983.03 29675.05 32693.74 293
ITE_SJBPF92.38 28495.69 25485.14 31295.71 31792.81 15389.33 24198.11 18970.23 30498.42 18885.91 27988.16 23893.59 297
FMVSNet588.32 28287.47 28390.88 29796.90 21888.39 29497.28 30295.68 31882.60 31384.67 30092.40 32179.83 25191.16 33676.39 32381.51 28593.09 307
testgi89.01 27988.04 27991.90 29193.49 28884.89 31499.73 13995.66 31993.89 12585.14 29898.17 18859.68 33294.66 32577.73 31788.88 22596.16 219
new_pmnet84.49 30082.92 30089.21 31090.03 32782.60 32096.89 30895.62 32080.59 31975.77 32989.17 32765.04 32294.79 32472.12 32781.02 29190.23 329
pmmvs590.17 26489.09 26293.40 26992.10 31089.77 27899.74 13495.58 32185.88 28987.24 27895.74 25173.41 29396.48 28988.54 25183.56 27493.95 276
USDC90.00 26788.96 26593.10 27794.81 26788.16 29698.71 25795.54 32293.66 13283.75 30597.20 20965.58 31998.31 20283.96 29187.49 24692.85 311
MIMVSNet182.58 30480.51 30788.78 31386.68 33484.20 31796.65 30995.41 32378.75 32378.59 32092.44 32051.88 33989.76 33965.26 33878.95 30492.38 315
OurMVSNet-221017-089.81 26989.48 25790.83 29991.64 31581.21 32898.17 28595.38 32491.48 20185.65 29697.31 20672.66 29497.29 24788.15 25684.83 26393.97 275
Anonymous2023120686.32 28885.42 28989.02 31189.11 33180.53 33399.05 22995.28 32585.43 29782.82 30793.92 30874.40 28893.44 33366.99 33481.83 28393.08 308
new-patchmatchnet81.19 30579.34 30886.76 31882.86 33980.36 33497.92 29295.27 32682.09 31572.02 33286.87 33262.81 32790.74 33871.10 32863.08 33889.19 336
OpenMVS_ROBcopyleft79.82 2083.77 30381.68 30490.03 30688.30 33282.82 31998.46 27095.22 32773.92 33576.00 32791.29 32455.00 33796.94 27068.40 33288.51 23590.34 328
test_040285.58 29183.94 29490.50 30193.81 28385.04 31398.55 26595.20 32876.01 32879.72 31795.13 28164.15 32496.26 29866.04 33786.88 24990.21 330
SixPastTwentyTwo88.73 28088.01 28090.88 29791.85 31382.24 32398.22 28395.18 32988.97 24482.26 30896.89 22171.75 29896.67 28384.00 28982.98 27593.72 294
Gipumacopyleft66.95 31365.00 31372.79 32691.52 31767.96 34066.16 34695.15 33047.89 34258.54 34067.99 34429.74 34687.54 34150.20 34377.83 31262.87 344
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
LF4IMVS89.25 27888.85 26690.45 30392.81 30381.19 32998.12 28694.79 33191.44 20386.29 29097.11 21165.30 32198.11 21288.53 25285.25 25992.07 316
FPMVS68.72 31068.72 31268.71 32865.95 34744.27 35295.97 31994.74 33251.13 34153.26 34490.50 32625.11 34983.00 34460.80 34080.97 29378.87 340
pmmvs-eth3d84.03 30281.97 30290.20 30484.15 33787.09 30298.10 28894.73 33383.05 30974.10 33187.77 33065.56 32094.01 32681.08 30769.24 33289.49 334
TDRefinement84.76 29782.56 30191.38 29574.58 34384.80 31597.36 30194.56 33484.73 30180.21 31596.12 24563.56 32598.39 19387.92 25863.97 33790.95 326
ambc83.23 32177.17 34262.61 34187.38 34194.55 33576.72 32586.65 33330.16 34596.36 29384.85 28669.86 32990.73 327
TinyColmap87.87 28586.51 28791.94 29095.05 26485.57 30997.65 29794.08 33684.40 30381.82 30996.85 22462.14 32898.33 20080.25 31086.37 25291.91 320
TransMVSNet (Re)87.25 28685.28 29093.16 27493.56 28691.03 25598.54 26794.05 33783.69 30881.09 31296.16 24275.32 28196.40 29176.69 32268.41 33392.06 317
Baseline_NR-MVSNet90.33 25889.51 25592.81 28192.84 30189.95 27599.77 12593.94 33884.69 30289.04 24895.66 25581.66 23096.52 28790.99 22276.98 31991.97 319
LCM-MVSNet67.77 31164.73 31476.87 32462.95 34956.25 34689.37 34093.74 33944.53 34361.99 33880.74 33820.42 35186.53 34269.37 33159.50 34187.84 337
Patchmatch-RL test86.90 28785.98 28889.67 30884.45 33675.59 33689.71 33992.43 34086.89 27877.83 32290.94 32594.22 8293.63 33187.75 26069.61 33099.79 97
pmmvs380.27 30777.77 31087.76 31680.32 34182.43 32298.23 28291.97 34172.74 33678.75 31987.97 32957.30 33690.99 33770.31 32962.37 33989.87 331
LCM-MVSNet-Re92.31 21892.60 19991.43 29497.53 19279.27 33599.02 23291.83 34292.07 18480.31 31494.38 30583.50 22095.48 31397.22 12297.58 14699.54 140
PM-MVS80.47 30678.88 30985.26 31983.79 33872.22 33895.89 32091.08 34385.71 29376.56 32688.30 32836.64 34493.90 32882.39 29969.57 33189.66 333
door90.31 344
DSMNet-mixed88.28 28388.24 27788.42 31589.64 32975.38 33798.06 28989.86 34585.59 29488.20 26492.14 32276.15 27791.95 33578.46 31496.05 17497.92 204
door-mid89.69 346
PMVScopyleft49.05 2353.75 31651.34 31960.97 33140.80 35334.68 35374.82 34589.62 34737.55 34528.67 35172.12 3417.09 35581.63 34543.17 34668.21 33466.59 343
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
tmp_tt65.23 31462.94 31672.13 32744.90 35250.03 34881.05 34389.42 34838.45 34448.51 34699.90 1754.09 33878.70 34691.84 21118.26 34787.64 338
PMMVS267.15 31264.15 31576.14 32570.56 34662.07 34393.89 32687.52 34958.09 34060.02 33978.32 33922.38 35084.54 34359.56 34147.03 34281.80 339
ANet_high56.10 31552.24 31767.66 32949.27 35156.82 34583.94 34282.02 35070.47 33733.28 35064.54 34517.23 35369.16 34845.59 34523.85 34677.02 341
MVEpermissive53.74 2251.54 31847.86 32162.60 33059.56 35050.93 34779.41 34477.69 35135.69 34736.27 34961.76 3485.79 35769.63 34737.97 34736.61 34367.24 342
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
E-PMN52.30 31752.18 31852.67 33271.51 34445.40 34993.62 32976.60 35236.01 34643.50 34764.13 34627.11 34867.31 34931.06 34826.06 34445.30 348
EMVS51.44 31951.22 32052.11 33370.71 34544.97 35194.04 32575.66 35335.34 34842.40 34861.56 34928.93 34765.87 35027.64 34924.73 34545.49 347
N_pmnet80.06 30880.78 30677.89 32391.94 31145.28 35098.80 25256.82 35478.10 32580.08 31693.33 31277.03 26695.76 31268.14 33382.81 27692.64 312
testmvs40.60 32044.45 32229.05 33519.49 35514.11 35699.68 14718.47 35520.74 34964.59 33698.48 18210.95 35417.09 35356.66 34211.01 34855.94 346
test12337.68 32139.14 32333.31 33419.94 35424.83 35598.36 2769.75 35615.53 35051.31 34587.14 33119.62 35217.74 35247.10 3443.47 35057.36 345
wuyk23d20.37 32320.84 32518.99 33665.34 34827.73 35450.43 3477.67 3579.50 3518.01 3526.34 3526.13 35626.24 35123.40 35010.69 3492.99 349
uanet_test0.00 3260.00 3280.00 3370.00 3560.00 3570.00 3480.00 3580.00 3520.00 3530.00 3530.00 3580.00 3540.00 3510.00 3510.00 350
pcd_1.5k_mvsjas7.60 32510.13 3270.00 3370.00 3560.00 3570.00 3480.00 3580.00 3520.00 3530.00 35391.20 1440.00 3540.00 3510.00 3510.00 350
sosnet-low-res0.00 3260.00 3280.00 3370.00 3560.00 3570.00 3480.00 3580.00 3520.00 3530.00 3530.00 3580.00 3540.00 3510.00 3510.00 350
sosnet0.00 3260.00 3280.00 3370.00 3560.00 3570.00 3480.00 3580.00 3520.00 3530.00 3530.00 3580.00 3540.00 3510.00 3510.00 350
uncertanet0.00 3260.00 3280.00 3370.00 3560.00 3570.00 3480.00 3580.00 3520.00 3530.00 3530.00 3580.00 3540.00 3510.00 3510.00 350
Regformer0.00 3260.00 3280.00 3370.00 3560.00 3570.00 3480.00 3580.00 3520.00 3530.00 3530.00 3580.00 3540.00 3510.00 3510.00 350
n20.00 358
nn0.00 358
ab-mvs-re8.28 32411.04 3260.00 3370.00 3560.00 3570.00 3480.00 3580.00 3520.00 35399.40 1140.00 3580.00 3540.00 3510.00 3510.00 350
uanet0.00 3260.00 3280.00 3370.00 3560.00 3570.00 3480.00 3580.00 3520.00 3530.00 3530.00 3580.00 3540.00 3510.00 3510.00 350
OPU-MVS99.93 299.89 4499.80 299.96 2399.80 5797.44 11100.00 1100.00 199.98 33100.00 1
test_0728_THIRD96.48 4099.83 1099.91 1397.87 4100.00 199.92 9100.00 1100.00 1
GSMVS99.59 127
test_part299.89 4499.25 1399.49 48
sam_mvs194.72 6399.59 127
sam_mvs94.25 81
test_post195.78 32159.23 35093.20 11197.74 22891.06 220
test_post63.35 34794.43 6898.13 211
patchmatchnet-post91.70 32395.12 4897.95 221
gm-plane-assit96.97 21593.76 19991.47 20298.96 14998.79 16394.92 152
test9_res99.71 2999.99 20100.00 1
agg_prior299.48 35100.00 1100.00 1
test_prior498.05 7099.94 55
test_prior299.95 4095.78 5899.73 2699.76 7096.00 2999.78 20100.00 1
旧先验299.46 18494.21 10799.85 699.95 6096.96 129
新几何299.40 188
原ACMM299.90 73
testdata299.99 3690.54 231
segment_acmp96.68 22
testdata199.28 20696.35 48
plane_prior795.71 25291.59 251
plane_prior695.76 24791.72 24680.47 247
plane_prior498.59 173
plane_prior391.64 24996.63 3893.01 195
plane_prior299.84 10596.38 44
plane_prior195.73 249
plane_prior91.74 24399.86 9896.76 3489.59 217
HQP5-MVS91.85 239
HQP-NCC95.78 24399.87 8796.82 3093.37 191
ACMP_Plane95.78 24399.87 8796.82 3093.37 191
BP-MVS97.92 105
HQP4-MVS93.37 19198.39 19394.53 222
HQP2-MVS80.65 243
NP-MVS95.77 24691.79 24198.65 169
MDTV_nov1_ep13_2view96.26 13396.11 31691.89 18998.06 11594.40 7094.30 17299.67 114
ACMMP++_ref87.04 248
ACMMP++88.23 237
Test By Simon92.82 119