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
ANet_high99.57 799.67 599.28 8399.89 698.09 13499.14 4699.93 199.82 399.93 299.81 399.17 1299.94 2399.31 16100.00 199.82 9
LCM-MVSNet99.93 199.92 199.94 199.99 199.97 199.90 199.89 299.98 199.99 199.96 199.77 1100.00 199.81 1100.00 199.85 7
DROMVSNet99.09 3499.05 3799.20 9699.28 12998.93 7099.24 3499.84 399.08 6998.12 22598.37 24698.72 2699.90 4999.05 3199.77 9398.77 283
LCM-MVSNet-Re98.64 9398.48 9699.11 10998.85 22798.51 10298.49 10199.83 498.37 11199.69 1799.46 4698.21 5799.92 3594.13 28799.30 23898.91 264
CS-MVS-test98.41 12698.30 12598.73 17298.84 23098.39 10898.71 7999.79 597.98 14096.86 30297.38 31497.86 8199.83 14297.81 10399.46 21197.97 322
Vis-MVSNetpermissive99.34 2299.36 1699.27 8699.73 2598.26 11899.17 4399.78 699.11 5799.27 7699.48 4498.82 2199.95 1598.94 3699.93 2899.59 58
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
LTVRE_ROB98.40 199.67 399.71 299.56 2499.85 1399.11 5999.90 199.78 699.63 1499.78 1099.67 1699.48 699.81 16799.30 1799.97 1199.77 16
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
pmmvs699.67 399.70 399.60 1399.90 499.27 2199.53 799.76 899.64 1299.84 899.83 299.50 599.87 8799.36 1499.92 3799.64 41
Gipumacopyleft99.03 3799.16 3098.64 17699.94 298.51 10299.32 1799.75 999.58 2298.60 18699.62 2198.22 5599.51 31397.70 11299.73 11097.89 324
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
UA-Net99.47 1199.40 1499.70 299.49 8699.29 1899.80 399.72 1099.82 399.04 11699.81 398.05 6999.96 898.85 4299.99 599.86 6
Patchmatch-RL test97.26 22397.02 22497.99 24199.52 7495.53 25396.13 28999.71 1197.47 17999.27 7699.16 9084.30 33599.62 27797.89 9799.77 9398.81 275
mvs_tets99.63 599.67 599.49 4999.88 798.61 9299.34 1599.71 1199.27 4499.90 499.74 899.68 299.97 399.55 899.99 599.88 3
TDRefinement99.42 1699.38 1599.55 2699.76 2399.33 1699.68 599.71 1199.38 3499.53 3399.61 2398.64 2999.80 17698.24 7899.84 5999.52 98
CS-MVS98.16 15698.22 13597.97 24298.56 28097.01 21798.10 13799.70 1497.45 18697.29 28097.19 32097.72 9299.80 17698.37 7299.62 15897.11 349
anonymousdsp99.51 1099.47 1299.62 699.88 799.08 6399.34 1599.69 1598.93 8499.65 2299.72 1198.93 1999.95 1599.11 27100.00 199.82 9
Effi-MVS+98.02 16397.82 17398.62 18198.53 28597.19 20897.33 21899.68 1697.30 20196.68 30897.46 31098.56 3499.80 17696.63 18598.20 31598.86 269
PM-MVS98.82 6198.72 6099.12 10799.64 4898.54 10097.98 15699.68 1697.62 16599.34 6499.18 8497.54 10999.77 20897.79 10499.74 10799.04 240
PVSNet_Blended_VisFu98.17 15498.15 14698.22 22599.73 2595.15 26697.36 21699.68 1694.45 29698.99 12499.27 7196.87 15499.94 2397.13 14099.91 4399.57 69
jajsoiax99.58 699.61 799.48 5199.87 1098.61 9299.28 3099.66 1999.09 6799.89 699.68 1499.53 499.97 399.50 1099.99 599.87 4
PS-MVSNAJss99.46 1299.49 1099.35 7099.90 498.15 13099.20 3899.65 2099.48 2499.92 399.71 1298.07 6699.96 899.53 9100.00 199.93 1
pm-mvs199.44 1399.48 1199.33 7699.80 1798.63 8999.29 2699.63 2199.30 4299.65 2299.60 2599.16 1499.82 15399.07 2999.83 6599.56 74
CHOSEN 1792x268897.49 20597.14 22098.54 19799.68 4196.09 24196.50 27199.62 2291.58 33598.84 15598.97 13792.36 28099.88 7096.76 17399.95 1699.67 35
XXY-MVS99.14 3299.15 3299.10 11199.76 2397.74 17798.85 7199.62 2298.48 10899.37 5899.49 4298.75 2499.86 9498.20 8199.80 8099.71 26
v7n99.53 899.57 899.41 6199.88 798.54 10099.45 999.61 2499.66 1199.68 1999.66 1798.44 4099.95 1599.73 299.96 1499.75 22
EIA-MVS98.00 16597.74 17798.80 15898.72 24998.09 13498.05 14599.60 2597.39 19296.63 31095.55 35097.68 9499.80 17696.73 17799.27 24298.52 299
EG-PatchMatch MVS98.99 4099.01 3998.94 13999.50 7997.47 19098.04 14799.59 2698.15 13499.40 5399.36 6198.58 3399.76 21598.78 4699.68 13899.59 58
MIMVSNet199.38 2099.32 2199.55 2699.86 1199.19 3799.41 1299.59 2699.59 2099.71 1499.57 2897.12 14099.90 4999.21 2399.87 5599.54 86
UniMVSNet_ETH3D99.69 299.69 499.69 399.84 1499.34 1599.69 499.58 2899.90 299.86 799.78 599.58 399.95 1599.00 3499.95 1699.78 14
AllTest98.44 12398.20 13799.16 10299.50 7998.55 9798.25 12299.58 2896.80 23198.88 14999.06 10597.65 9799.57 29494.45 27499.61 16599.37 167
TestCases99.16 10299.50 7998.55 9799.58 2896.80 23198.88 14999.06 10597.65 9799.57 29494.45 27499.61 16599.37 167
diffmvs98.22 14898.24 13298.17 22899.00 19595.44 25796.38 27899.58 2897.79 15698.53 19998.50 23196.76 16499.74 22697.95 9699.64 15299.34 179
OurMVSNet-221017-099.37 2199.31 2299.53 3699.91 398.98 6599.63 699.58 2899.44 2999.78 1099.76 696.39 18299.92 3599.44 1399.92 3799.68 33
1112_ss97.29 22296.86 23498.58 18699.34 12396.32 23596.75 25999.58 2893.14 31796.89 30097.48 30892.11 28399.86 9496.91 15699.54 18999.57 69
ACMH+96.62 999.08 3599.00 4099.33 7699.71 3298.83 7598.60 8699.58 2899.11 5799.53 3399.18 8498.81 2299.67 25796.71 18099.77 9399.50 105
FC-MVSNet-test99.27 2599.25 2599.34 7399.77 2098.37 11199.30 2599.57 3599.61 1999.40 5399.50 3997.12 14099.85 10999.02 3399.94 2499.80 12
casdiffmvs98.95 4899.00 4098.81 15699.38 11297.33 19697.82 17199.57 3599.17 5499.35 6299.17 8898.35 4799.69 24598.46 6799.73 11099.41 148
TransMVSNet (Re)99.44 1399.47 1299.36 6599.80 1798.58 9599.27 3299.57 3599.39 3399.75 1299.62 2199.17 1299.83 14299.06 3099.62 15899.66 36
Baseline_NR-MVSNet98.98 4498.86 4799.36 6599.82 1698.55 9797.47 20999.57 3599.37 3599.21 8999.61 2396.76 16499.83 14298.06 8999.83 6599.71 26
door-mid99.57 35
RPSCF98.62 9798.36 11799.42 5899.65 4599.42 598.55 9299.57 3597.72 15998.90 14299.26 7396.12 19199.52 30995.72 24099.71 12299.32 187
CSCG98.68 8798.50 9199.20 9699.45 10098.63 8998.56 9199.57 3597.87 15098.85 15398.04 27497.66 9699.84 12796.72 17899.81 7299.13 229
GeoE99.05 3698.99 4299.25 9199.44 10298.35 11598.73 7699.56 4298.42 11098.91 14198.81 17998.94 1899.91 4598.35 7499.73 11099.49 109
MVSFormer98.26 14498.43 10697.77 25098.88 22293.89 30199.39 1399.56 4299.11 5798.16 22198.13 26493.81 25999.97 399.26 1899.57 18199.43 142
test_djsdf99.52 999.51 999.53 3699.86 1198.74 8199.39 1399.56 4299.11 5799.70 1599.73 1099.00 1599.97 399.26 1899.98 999.89 2
COLMAP_ROBcopyleft96.50 1098.99 4098.85 4899.41 6199.58 5399.10 6098.74 7499.56 4299.09 6799.33 6599.19 8298.40 4299.72 23895.98 22799.76 10399.42 145
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
v1098.97 4599.11 3398.55 19499.44 10296.21 23898.90 6699.55 4698.73 9399.48 4099.60 2596.63 17199.83 14299.70 399.99 599.61 51
WR-MVS_H99.33 2399.22 2799.65 599.71 3299.24 2499.32 1799.55 4699.46 2799.50 3999.34 6497.30 12999.93 2898.90 3899.93 2899.77 16
114514_t96.50 26695.77 27398.69 17399.48 9497.43 19397.84 16999.55 4681.42 36896.51 31698.58 22195.53 21599.67 25793.41 30899.58 17798.98 249
ACMH96.65 799.25 2799.24 2699.26 8999.72 3198.38 11099.07 5399.55 4698.30 11699.65 2299.45 5099.22 999.76 21598.44 6899.77 9399.64 41
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
FOURS199.73 2599.67 299.43 1099.54 5099.43 3099.26 80
KD-MVS_self_test99.25 2799.18 2899.44 5799.63 5099.06 6498.69 8099.54 5099.31 4099.62 2799.53 3697.36 12799.86 9499.24 2299.71 12299.39 157
xxxxxxxxxxxxxcwj98.44 12398.24 13299.06 12399.11 16997.97 15196.53 26899.54 5098.24 12298.83 15698.90 15297.80 8799.82 15395.68 24399.52 19699.38 164
PEN-MVS99.41 1799.34 1999.62 699.73 2599.14 5299.29 2699.54 5099.62 1799.56 2899.42 5298.16 6299.96 898.78 4699.93 2899.77 16
PS-CasMVS99.40 1899.33 2099.62 699.71 3299.10 6099.29 2699.53 5499.53 2399.46 4399.41 5598.23 5299.95 1598.89 4099.95 1699.81 11
Test_1112_low_res96.99 24796.55 25798.31 21899.35 12195.47 25695.84 30499.53 5491.51 33796.80 30698.48 23691.36 28799.83 14296.58 18799.53 19399.62 46
USDC97.41 21397.40 20197.44 27498.94 20693.67 30795.17 32499.53 5494.03 30698.97 12999.10 10295.29 22399.34 33595.84 23699.73 11099.30 194
FIs99.14 3299.09 3499.29 8199.70 3898.28 11799.13 4799.52 5799.48 2499.24 8599.41 5596.79 16199.82 15398.69 5599.88 5299.76 20
Anonymous2023121199.27 2599.27 2499.26 8999.29 12898.18 12799.49 899.51 5899.70 899.80 999.68 1496.84 15599.83 14299.21 2399.91 4399.77 16
DTE-MVSNet99.43 1599.35 1799.66 499.71 3299.30 1799.31 2199.51 5899.64 1299.56 2899.46 4698.23 5299.97 398.78 4699.93 2899.72 25
ETV-MVS98.03 16197.86 17198.56 19398.69 26098.07 14097.51 20599.50 6098.10 13597.50 26995.51 35198.41 4199.88 7096.27 21499.24 24797.71 337
Fast-Effi-MVS+-dtu98.27 14298.09 15198.81 15698.43 29398.11 13397.61 19399.50 6098.64 9597.39 27797.52 30598.12 6599.95 1596.90 16198.71 29998.38 307
abl_698.99 4098.78 5499.61 999.45 10099.46 498.60 8699.50 6098.59 10199.24 8599.04 11598.54 3599.89 5996.45 20299.62 15899.50 105
HPM-MVS_fast99.01 3898.82 5099.57 1899.71 3299.35 1299.00 5999.50 6097.33 19798.94 13898.86 16598.75 2499.82 15397.53 11899.71 12299.56 74
XVG-OURS98.53 11498.34 12099.11 10999.50 7998.82 7795.97 29399.50 6097.30 20199.05 11498.98 13599.35 799.32 33895.72 24099.68 13899.18 221
baseline98.96 4799.02 3898.76 16699.38 11297.26 20198.49 10199.50 6098.86 8799.19 9199.06 10598.23 5299.69 24598.71 5399.76 10399.33 185
FMVSNet596.01 27995.20 29498.41 20997.53 34096.10 23998.74 7499.50 6097.22 21598.03 23599.04 11569.80 37099.88 7097.27 12999.71 12299.25 205
HyFIR lowres test97.19 23096.60 25398.96 13699.62 5297.28 20095.17 32499.50 6094.21 30199.01 12098.32 25386.61 31499.99 297.10 14299.84 5999.60 52
testgi98.32 13698.39 11398.13 23099.57 5795.54 25297.78 17399.49 6897.37 19499.19 9197.65 29798.96 1799.49 31596.50 19998.99 28499.34 179
PGM-MVS98.66 9098.37 11699.55 2699.53 7299.18 3898.23 12399.49 6897.01 22498.69 17398.88 16198.00 7299.89 5995.87 23399.59 17199.58 64
new-patchmatchnet98.35 13498.74 5797.18 28399.24 13692.23 32896.42 27699.48 7098.30 11699.69 1799.53 3697.44 12299.82 15398.84 4399.77 9399.49 109
nrg03099.40 1899.35 1799.54 2999.58 5399.13 5598.98 6299.48 7099.68 999.46 4399.26 7398.62 3099.73 23099.17 2699.92 3799.76 20
APDe-MVS98.99 4098.79 5399.60 1399.21 14399.15 4898.87 6899.48 7097.57 17099.35 6299.24 7697.83 8399.89 5997.88 10099.70 12799.75 22
XVG-OURS-SEG-HR98.49 11898.28 12899.14 10599.49 8698.83 7596.54 26799.48 7097.32 19999.11 10098.61 21899.33 899.30 34196.23 21598.38 31099.28 199
LPG-MVS_test98.71 7898.46 10099.47 5499.57 5798.97 6698.23 12399.48 7096.60 23999.10 10399.06 10598.71 2799.83 14295.58 24999.78 8999.62 46
LGP-MVS_train99.47 5499.57 5798.97 6699.48 7096.60 23999.10 10399.06 10598.71 2799.83 14295.58 24999.78 8999.62 46
v899.01 3899.16 3098.57 18999.47 9696.31 23698.90 6699.47 7699.03 7399.52 3599.57 2896.93 15199.81 16799.60 499.98 999.60 52
LF4IMVS97.90 17197.69 18098.52 19899.17 15997.66 18197.19 23299.47 7696.31 25097.85 24398.20 26196.71 16899.52 30994.62 26899.72 11798.38 307
canonicalmvs98.34 13598.26 13098.58 18698.46 29097.82 16998.96 6399.46 7899.19 5397.46 27295.46 35398.59 3299.46 32298.08 8898.71 29998.46 301
XVG-ACMP-BASELINE98.56 10598.34 12099.22 9599.54 7098.59 9497.71 18299.46 7897.25 20698.98 12698.99 13197.54 10999.84 12795.88 23099.74 10799.23 209
DeepC-MVS97.60 498.97 4598.93 4399.10 11199.35 12197.98 15098.01 15399.46 7897.56 17299.54 3099.50 3998.97 1699.84 12798.06 8999.92 3799.49 109
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
Fast-Effi-MVS+97.67 19397.38 20398.57 18998.71 25297.43 19397.23 22599.45 8194.82 28896.13 32496.51 33398.52 3699.91 4596.19 21898.83 29298.37 309
v124098.55 10998.62 7598.32 21699.22 14195.58 25197.51 20599.45 8197.16 21799.45 4699.24 7696.12 19199.85 10999.60 499.88 5299.55 82
VPA-MVSNet99.30 2499.30 2399.28 8399.49 8698.36 11499.00 5999.45 8199.63 1499.52 3599.44 5198.25 5099.88 7099.09 2899.84 5999.62 46
Anonymous2024052198.69 8398.87 4598.16 22999.77 2095.11 26999.08 5099.44 8499.34 3899.33 6599.55 3294.10 25699.94 2399.25 2099.96 1499.42 145
tfpnnormal98.90 5498.90 4498.91 14399.67 4297.82 16999.00 5999.44 8499.45 2899.51 3899.24 7698.20 5899.86 9495.92 22999.69 13399.04 240
GBi-Net98.65 9198.47 9899.17 9998.90 21698.24 12099.20 3899.44 8498.59 10198.95 13299.55 3294.14 25299.86 9497.77 10699.69 13399.41 148
test198.65 9198.47 9899.17 9998.90 21698.24 12099.20 3899.44 8498.59 10198.95 13299.55 3294.14 25299.86 9497.77 10699.69 13399.41 148
FMVSNet199.17 3099.17 2999.17 9999.55 6798.24 12099.20 3899.44 8499.21 4699.43 4899.55 3297.82 8699.86 9498.42 7099.89 5199.41 148
TinyColmap97.89 17397.98 16197.60 26198.86 22594.35 28496.21 28699.44 8497.45 18699.06 10998.88 16197.99 7599.28 34494.38 28099.58 17799.18 221
HPM-MVScopyleft98.79 6598.53 8699.59 1799.65 4599.29 1899.16 4499.43 9096.74 23498.61 18498.38 24498.62 3099.87 8796.47 20099.67 14499.59 58
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
PVSNet_BlendedMVS97.55 20197.53 19297.60 26198.92 21293.77 30596.64 26499.43 9094.49 29297.62 25799.18 8496.82 15899.67 25794.73 26599.93 2899.36 173
PVSNet_Blended96.88 25096.68 24697.47 27298.92 21293.77 30594.71 33599.43 9090.98 34397.62 25797.36 31796.82 15899.67 25794.73 26599.56 18698.98 249
TranMVSNet+NR-MVSNet99.17 3099.07 3699.46 5699.37 11698.87 7298.39 11299.42 9399.42 3199.36 6099.06 10598.38 4399.95 1598.34 7599.90 4799.57 69
SF-MVS98.53 11498.27 12999.32 7899.31 12498.75 8098.19 12799.41 9496.77 23398.83 15698.90 15297.80 8799.82 15395.68 24399.52 19699.38 164
RRT_test8_iter0595.24 29695.13 29695.57 32597.32 34887.02 35997.99 15499.41 9498.06 13799.12 9899.05 11266.85 37599.85 10998.93 3799.47 21099.84 8
door99.41 94
PMMVS298.07 16098.08 15498.04 23899.41 10994.59 28194.59 34299.40 9797.50 17698.82 16098.83 17496.83 15799.84 12797.50 12099.81 7299.71 26
UniMVSNet_NR-MVSNet98.86 5998.68 6899.40 6399.17 15998.74 8197.68 18599.40 9799.14 5599.06 10998.59 22096.71 16899.93 2898.57 6099.77 9399.53 94
DPE-MVScopyleft98.59 10398.26 13099.57 1899.27 13199.15 4897.01 24099.39 9997.67 16199.44 4798.99 13197.53 11199.89 5995.40 25399.68 13899.66 36
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
IterMVS-LS98.55 10998.70 6598.09 23199.48 9494.73 27597.22 22899.39 9998.97 7999.38 5699.31 6896.00 19699.93 2898.58 5899.97 1199.60 52
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
MP-MVS-pluss98.57 10498.23 13499.60 1399.69 4099.35 1297.16 23599.38 10194.87 28798.97 12998.99 13198.01 7199.88 7097.29 12899.70 12799.58 64
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
UniMVSNet (Re)98.87 5798.71 6299.35 7099.24 13698.73 8497.73 18199.38 10198.93 8499.12 9898.73 19096.77 16299.86 9498.63 5799.80 8099.46 129
PHI-MVS98.29 14197.95 16399.34 7398.44 29299.16 4398.12 13499.38 10196.01 26098.06 23198.43 23897.80 8799.67 25795.69 24299.58 17799.20 214
ACMP95.32 1598.41 12698.09 15199.36 6599.51 7698.79 7997.68 18599.38 10195.76 26898.81 16298.82 17798.36 4499.82 15394.75 26499.77 9399.48 119
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
ACMMPcopyleft98.75 7398.50 9199.52 4199.56 6499.16 4398.87 6899.37 10597.16 21798.82 16099.01 12897.71 9399.87 8796.29 21399.69 13399.54 86
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
OpenMVScopyleft96.65 797.09 23696.68 24698.32 21698.32 30197.16 21198.86 7099.37 10589.48 35196.29 32399.15 9496.56 17399.90 4992.90 31499.20 25297.89 324
MSDG97.71 19097.52 19398.28 22198.91 21596.82 22294.42 34599.37 10597.65 16398.37 21398.29 25597.40 12499.33 33794.09 28899.22 24998.68 295
ACMM96.08 1298.91 5298.73 5899.48 5199.55 6799.14 5298.07 14199.37 10597.62 16599.04 11698.96 14098.84 2099.79 19097.43 12299.65 15099.49 109
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
test_part197.91 17097.46 20099.27 8698.80 24098.18 12799.07 5399.36 10999.75 599.63 2599.49 4282.20 34899.89 5998.87 4199.95 1699.74 24
v14419298.54 11298.57 8398.45 20699.21 14395.98 24297.63 19099.36 10997.15 21999.32 7199.18 8495.84 20799.84 12799.50 1099.91 4399.54 86
v192192098.54 11298.60 8098.38 21299.20 14795.76 25097.56 19999.36 10997.23 21299.38 5699.17 8896.02 19499.84 12799.57 699.90 4799.54 86
v119298.60 10098.66 7198.41 20999.27 13195.88 24597.52 20399.36 10997.41 19099.33 6599.20 8196.37 18599.82 15399.57 699.92 3799.55 82
SD-MVS98.40 12998.68 6897.54 26898.96 20397.99 14697.88 16499.36 10998.20 12899.63 2599.04 11598.76 2395.33 37396.56 19299.74 10799.31 191
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
CP-MVS98.70 8198.42 10899.52 4199.36 11799.12 5798.72 7799.36 10997.54 17498.30 21498.40 24097.86 8199.89 5996.53 19799.72 11799.56 74
test072699.50 7999.21 2798.17 13199.35 11597.97 14299.26 8099.06 10597.61 103
MSP-MVS98.40 12998.00 16099.61 999.57 5799.25 2398.57 9099.35 11597.55 17399.31 7397.71 29394.61 24299.88 7096.14 22299.19 25699.70 31
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
VPNet98.87 5798.83 4999.01 13299.70 3897.62 18598.43 10999.35 11599.47 2699.28 7499.05 11296.72 16799.82 15398.09 8799.36 22799.59 58
UnsupCasMVSNet_eth97.89 17397.60 19098.75 16899.31 12497.17 21097.62 19199.35 11598.72 9498.76 16898.68 19992.57 27999.74 22697.76 11095.60 35999.34 179
DP-MVS Recon97.33 21896.92 23098.57 18999.09 17697.99 14696.79 25599.35 11593.18 31697.71 25198.07 27395.00 23099.31 33993.97 29099.13 26698.42 306
ITE_SJBPF98.87 14899.22 14198.48 10499.35 11597.50 17698.28 21698.60 21997.64 10099.35 33493.86 29699.27 24298.79 281
v114498.60 10098.66 7198.41 20999.36 11795.90 24497.58 19799.34 12197.51 17599.27 7699.15 9496.34 18799.80 17699.47 1299.93 2899.51 101
XVS98.72 7798.45 10299.53 3699.46 9799.21 2798.65 8199.34 12198.62 9997.54 26598.63 21397.50 11599.83 14296.79 16999.53 19399.56 74
X-MVStestdata94.32 30892.59 32699.53 3699.46 9799.21 2798.65 8199.34 12198.62 9997.54 26545.85 37297.50 11599.83 14296.79 16999.53 19399.56 74
CP-MVSNet99.21 2999.09 3499.56 2499.65 4598.96 6999.13 4799.34 12199.42 3199.33 6599.26 7397.01 14799.94 2398.74 5199.93 2899.79 13
test_040298.76 7198.71 6298.93 14099.56 6498.14 13298.45 10899.34 12199.28 4398.95 13298.91 14998.34 4899.79 19095.63 24699.91 4398.86 269
APD-MVS_3200maxsize98.84 6098.61 7899.53 3699.19 15099.27 2198.49 10199.33 12698.64 9599.03 11998.98 13597.89 7999.85 10996.54 19699.42 21899.46 129
DP-MVS98.93 5098.81 5299.28 8399.21 14398.45 10698.46 10699.33 12699.63 1499.48 4099.15 9497.23 13799.75 22297.17 13399.66 14999.63 45
DVP-MVS++98.90 5498.70 6599.51 4598.43 29399.15 4899.43 1099.32 12898.17 13199.26 8099.02 11998.18 5999.88 7097.07 14499.45 21499.49 109
9.1497.78 17499.07 18097.53 20299.32 12895.53 27398.54 19898.70 19697.58 10599.76 21594.32 28199.46 211
ETH3D-3000-0.198.03 16197.62 18899.29 8199.11 16998.80 7897.47 20999.32 12895.54 27198.43 20798.62 21596.61 17299.77 20893.95 29299.49 20799.30 194
test_0728_SECOND99.60 1399.50 7999.23 2598.02 15099.32 12899.88 7096.99 15099.63 15599.68 33
Anonymous2023120698.21 14998.21 13698.20 22699.51 7695.43 25898.13 13299.32 12896.16 25498.93 13998.82 17796.00 19699.83 14297.32 12799.73 11099.36 173
LS3D98.63 9598.38 11599.36 6597.25 35099.38 699.12 4999.32 12899.21 4698.44 20498.88 16197.31 12899.80 17696.58 18799.34 23198.92 261
test_one_060199.39 11199.20 3399.31 13498.49 10798.66 17799.02 11997.64 100
test117298.76 7198.49 9499.57 1899.18 15799.37 998.39 11299.31 13498.43 10998.90 14298.88 16197.49 11899.86 9496.43 20499.37 22699.48 119
SED-MVS98.91 5298.72 6099.49 4999.49 8699.17 3998.10 13799.31 13498.03 13899.66 2099.02 11998.36 4499.88 7096.91 15699.62 15899.41 148
test_241102_ONE99.49 8699.17 3999.31 13497.98 14099.66 2098.90 15298.36 4499.48 318
miper_lstm_enhance97.18 23197.16 21797.25 28298.16 31192.85 31795.15 32699.31 13497.25 20698.74 17198.78 18390.07 29399.78 20297.19 13299.80 8099.11 232
HFP-MVS98.71 7898.44 10499.51 4599.49 8699.16 4398.52 9599.31 13497.47 17998.58 19098.50 23197.97 7699.85 10996.57 18999.59 17199.53 94
region2R98.69 8398.40 11099.54 2999.53 7299.17 3998.52 9599.31 13497.46 18498.44 20498.51 22897.83 8399.88 7096.46 20199.58 17799.58 64
#test#98.50 11798.16 14499.51 4599.49 8699.16 4398.03 14899.31 13496.30 25198.58 19098.50 23197.97 7699.85 10995.68 24399.59 17199.53 94
ACMMPR98.70 8198.42 10899.54 2999.52 7499.14 5298.52 9599.31 13497.47 17998.56 19498.54 22497.75 9099.88 7096.57 18999.59 17199.58 64
SteuartSystems-ACMMP98.79 6598.54 8599.54 2999.73 2599.16 4398.23 12399.31 13497.92 14698.90 14298.90 15298.00 7299.88 7096.15 22199.72 11799.58 64
Skip Steuart: Steuart Systems R&D Blog.
SR-MVS-dyc-post98.81 6398.55 8499.57 1899.20 14799.38 698.48 10499.30 14498.64 9598.95 13298.96 14097.49 11899.86 9496.56 19299.39 22299.45 133
RE-MVS-def98.58 8299.20 14799.38 698.48 10499.30 14498.64 9598.95 13298.96 14097.75 9096.56 19299.39 22299.45 133
test_241102_TWO99.30 14498.03 13899.26 8099.02 11997.51 11499.88 7096.91 15699.60 16799.66 36
RPMNet97.02 24396.93 22897.30 27997.71 33294.22 28598.11 13599.30 14499.37 3596.91 29699.34 6486.72 31399.87 8797.53 11897.36 33997.81 330
MVS_111021_LR98.30 13898.12 14998.83 15399.16 16198.03 14496.09 29099.30 14497.58 16998.10 22898.24 25798.25 5099.34 33596.69 18199.65 15099.12 230
F-COLMAP97.30 22096.68 24699.14 10599.19 15098.39 10897.27 22499.30 14492.93 31996.62 31198.00 27595.73 21099.68 25492.62 32398.46 30999.35 177
3Dnovator98.27 298.81 6398.73 5899.05 12598.76 24397.81 17199.25 3399.30 14498.57 10598.55 19699.33 6697.95 7899.90 4997.16 13499.67 14499.44 138
EGC-MVSNET85.24 33880.54 34199.34 7399.77 2099.20 3399.08 5099.29 15112.08 37420.84 37599.42 5297.55 10899.85 10997.08 14399.72 11798.96 254
ZNCC-MVS98.68 8798.40 11099.54 2999.57 5799.21 2798.46 10699.29 15197.28 20398.11 22798.39 24298.00 7299.87 8796.86 16699.64 15299.55 82
SR-MVS98.71 7898.43 10699.57 1899.18 15799.35 1298.36 11599.29 15198.29 11998.88 14998.85 16897.53 11199.87 8796.14 22299.31 23599.48 119
pmmvs-eth3d98.47 12098.34 12098.86 15099.30 12797.76 17497.16 23599.28 15495.54 27199.42 4999.19 8297.27 13299.63 27597.89 9799.97 1199.20 214
APD-MVScopyleft98.10 15797.67 18199.42 5899.11 16998.93 7097.76 17899.28 15494.97 28498.72 17298.77 18597.04 14399.85 10993.79 29899.54 18999.49 109
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
TAPA-MVS96.21 1196.63 26195.95 27198.65 17598.93 20898.09 13496.93 24699.28 15483.58 36698.13 22497.78 28996.13 19099.40 32893.52 30499.29 24098.45 303
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
HQP_MVS97.99 16897.67 18198.93 14099.19 15097.65 18297.77 17699.27 15798.20 12897.79 24797.98 27794.90 23199.70 24194.42 27699.51 19999.45 133
plane_prior599.27 15799.70 24194.42 27699.51 19999.45 133
CPTT-MVS97.84 18397.36 20599.27 8699.31 12498.46 10598.29 11899.27 15794.90 28697.83 24498.37 24694.90 23199.84 12793.85 29799.54 18999.51 101
UnsupCasMVSNet_bld97.30 22096.92 23098.45 20699.28 12996.78 22696.20 28799.27 15795.42 27698.28 21698.30 25493.16 26799.71 23994.99 25997.37 33798.87 268
MVS_111021_HR98.25 14698.08 15498.75 16899.09 17697.46 19195.97 29399.27 15797.60 16897.99 23698.25 25698.15 6499.38 33296.87 16499.57 18199.42 145
cascas94.79 30394.33 30996.15 31696.02 36992.36 32692.34 36499.26 16285.34 36495.08 34894.96 36092.96 27398.53 36594.41 27998.59 30697.56 342
GST-MVS98.61 9898.30 12599.52 4199.51 7699.20 3398.26 12199.25 16397.44 18898.67 17598.39 24297.68 9499.85 10996.00 22599.51 19999.52 98
IterMVS-SCA-FT97.85 18298.18 14096.87 29799.27 13191.16 34395.53 31499.25 16399.10 6499.41 5099.35 6293.10 26999.96 898.65 5699.94 2499.49 109
ACMMP_NAP98.75 7398.48 9699.57 1899.58 5399.29 1897.82 17199.25 16396.94 22698.78 16399.12 9898.02 7099.84 12797.13 14099.67 14499.59 58
DU-MVS98.82 6198.63 7499.39 6499.16 16198.74 8197.54 20199.25 16398.84 8999.06 10998.76 18796.76 16499.93 2898.57 6099.77 9399.50 105
OMC-MVS97.88 17597.49 19599.04 12798.89 22198.63 8996.94 24499.25 16395.02 28298.53 19998.51 22897.27 13299.47 32093.50 30699.51 19999.01 244
test20.0398.78 6898.77 5698.78 16399.46 9797.20 20797.78 17399.24 16899.04 7299.41 5098.90 15297.65 9799.76 21597.70 11299.79 8599.39 157
mPP-MVS98.64 9398.34 12099.54 2999.54 7099.17 3998.63 8399.24 16897.47 17998.09 22998.68 19997.62 10299.89 5996.22 21699.62 15899.57 69
MSLP-MVS++98.02 16398.14 14897.64 25998.58 27795.19 26597.48 20799.23 17097.47 17997.90 23998.62 21597.04 14398.81 36397.55 11599.41 21998.94 259
SMA-MVScopyleft98.40 12998.03 15899.51 4599.16 16199.21 2798.05 14599.22 17194.16 30398.98 12699.10 10297.52 11399.79 19096.45 20299.64 15299.53 94
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
IterMVS97.73 18998.11 15096.57 30499.24 13690.28 34495.52 31699.21 17298.86 8799.33 6599.33 6693.11 26899.94 2398.49 6599.94 2499.48 119
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CLD-MVS97.49 20597.16 21798.48 20399.07 18097.03 21594.71 33599.21 17294.46 29498.06 23197.16 32397.57 10699.48 31894.46 27399.78 8998.95 255
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
zzz-MVS98.79 6598.52 8799.61 999.67 4299.36 1097.33 21899.20 17498.83 9098.89 14598.90 15296.98 14999.92 3597.16 13499.70 12799.56 74
MTGPAbinary99.20 174
MTAPA98.88 5698.64 7399.61 999.67 4299.36 1098.43 10999.20 17498.83 9098.89 14598.90 15296.98 14999.92 3597.16 13499.70 12799.56 74
NR-MVSNet98.95 4898.82 5099.36 6599.16 16198.72 8699.22 3599.20 17499.10 6499.72 1398.76 18796.38 18499.86 9498.00 9499.82 6899.50 105
DELS-MVS98.27 14298.20 13798.48 20398.86 22596.70 22795.60 31299.20 17497.73 15898.45 20398.71 19397.50 11599.82 15398.21 8099.59 17198.93 260
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
V4298.78 6898.78 5498.76 16699.44 10297.04 21498.27 12099.19 17997.87 15099.25 8499.16 9096.84 15599.78 20299.21 2399.84 5999.46 129
MP-MVScopyleft98.46 12198.09 15199.54 2999.57 5799.22 2698.50 10099.19 17997.61 16797.58 26198.66 20497.40 12499.88 7094.72 26799.60 16799.54 86
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
QAPM97.31 21996.81 23998.82 15498.80 24097.49 18999.06 5599.19 17990.22 34797.69 25399.16 9096.91 15299.90 4990.89 34699.41 21999.07 234
3Dnovator+97.89 398.69 8398.51 8999.24 9398.81 23898.40 10799.02 5699.19 17998.99 7698.07 23099.28 6997.11 14299.84 12796.84 16799.32 23399.47 127
ETH3 D test640096.46 26995.59 28199.08 11598.88 22298.21 12696.53 26899.18 18388.87 35597.08 28797.79 28893.64 26499.77 20888.92 35399.40 22199.28 199
eth_miper_zixun_eth97.23 22797.25 21197.17 28498.00 32092.77 31994.71 33599.18 18397.27 20498.56 19498.74 18991.89 28599.69 24597.06 14699.81 7299.05 236
testtj97.79 18797.25 21199.42 5899.03 19098.85 7397.78 17399.18 18395.83 26698.12 22598.50 23195.50 21899.86 9492.23 32899.07 27299.54 86
OPM-MVS98.56 10598.32 12499.25 9199.41 10998.73 8497.13 23799.18 18397.10 22098.75 16998.92 14898.18 5999.65 27096.68 18299.56 18699.37 167
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
MVP-Stereo98.08 15997.92 16698.57 18998.96 20396.79 22397.90 16399.18 18396.41 24698.46 20298.95 14495.93 20399.60 28496.51 19898.98 28699.31 191
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
DeepPCF-MVS96.93 598.32 13698.01 15999.23 9498.39 29898.97 6695.03 32899.18 18396.88 22999.33 6598.78 18398.16 6299.28 34496.74 17599.62 15899.44 138
xiu_mvs_v1_base_debu97.86 17798.17 14196.92 29498.98 20093.91 29896.45 27399.17 18997.85 15298.41 20897.14 32598.47 3799.92 3598.02 9199.05 27396.92 350
xiu_mvs_v1_base97.86 17798.17 14196.92 29498.98 20093.91 29896.45 27399.17 18997.85 15298.41 20897.14 32598.47 3799.92 3598.02 9199.05 27396.92 350
xiu_mvs_v1_base_debi97.86 17798.17 14196.92 29498.98 20093.91 29896.45 27399.17 18997.85 15298.41 20897.14 32598.47 3799.92 3598.02 9199.05 27396.92 350
cl____97.02 24396.83 23797.58 26397.82 32894.04 29194.66 33899.16 19297.04 22298.63 18098.71 19388.68 30599.69 24597.00 14899.81 7299.00 247
DIV-MVS_self_test97.02 24396.84 23697.58 26397.82 32894.03 29294.66 33899.16 19297.04 22298.63 18098.71 19388.69 30399.69 24597.00 14899.81 7299.01 244
c3_l97.36 21597.37 20497.31 27898.09 31593.25 31095.01 32999.16 19297.05 22198.77 16698.72 19292.88 27499.64 27296.93 15599.76 10399.05 236
Effi-MVS+-dtu98.26 14497.90 16899.35 7098.02 31899.49 398.02 15099.16 19298.29 11997.64 25697.99 27696.44 18099.95 1596.66 18398.93 28998.60 296
mvs-test197.83 18597.48 19898.89 14698.02 31899.20 3397.20 22999.16 19298.29 11996.46 32097.17 32296.44 18099.92 3596.66 18397.90 32897.54 343
v2v48298.56 10598.62 7598.37 21399.42 10795.81 24897.58 19799.16 19297.90 14899.28 7499.01 12895.98 20099.79 19099.33 1599.90 4799.51 101
MDA-MVSNet-bldmvs97.94 16997.91 16798.06 23699.44 10294.96 27196.63 26599.15 19898.35 11298.83 15699.11 10094.31 24999.85 10996.60 18698.72 29799.37 167
ETH3D cwj APD-0.1697.55 20197.00 22599.19 9898.51 28698.64 8896.85 25299.13 19994.19 30297.65 25598.40 24095.78 20899.81 16793.37 30999.16 25999.12 230
FMVSNet298.49 11898.40 11098.75 16898.90 21697.14 21398.61 8599.13 19998.59 10199.19 9199.28 6994.14 25299.82 15397.97 9599.80 8099.29 198
DSMNet-mixed97.42 21297.60 19096.87 29799.15 16591.46 33498.54 9399.12 20192.87 32197.58 26199.63 2096.21 18999.90 4995.74 23999.54 18999.27 201
CMPMVSbinary75.91 2396.29 27395.44 28698.84 15296.25 36698.69 8797.02 23999.12 20188.90 35497.83 24498.86 16589.51 29798.90 36191.92 32999.51 19998.92 261
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
PCF-MVS92.86 1894.36 30793.00 32498.42 20898.70 25697.56 18693.16 36099.11 20379.59 36997.55 26497.43 31192.19 28199.73 23079.85 37099.45 21497.97 322
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
cdsmvs_eth3d_5k24.66 34132.88 3440.00 3590.00 3820.00 3830.00 37099.10 2040.00 3770.00 37897.58 30199.21 100.00 3780.00 3760.00 3760.00 374
miper_ehance_all_eth97.06 23997.03 22397.16 28697.83 32793.06 31294.66 33899.09 20595.99 26198.69 17398.45 23792.73 27799.61 28396.79 16999.03 27798.82 272
Regformer-298.60 10098.46 10099.02 13198.85 22797.71 17996.91 24999.09 20598.98 7899.01 12098.64 20997.37 12699.84 12797.75 11199.57 18199.52 98
DeepC-MVS_fast96.85 698.30 13898.15 14698.75 16898.61 27297.23 20297.76 17899.09 20597.31 20098.75 16998.66 20497.56 10799.64 27296.10 22499.55 18899.39 157
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
ZD-MVS99.01 19498.84 7499.07 20894.10 30498.05 23398.12 26796.36 18699.86 9492.70 32299.19 256
v14898.45 12298.60 8098.00 24099.44 10294.98 27097.44 21299.06 20998.30 11699.32 7198.97 13796.65 17099.62 27798.37 7299.85 5799.39 157
Regformer-498.73 7698.68 6898.89 14699.02 19297.22 20497.17 23399.06 20999.21 4699.17 9698.85 16897.45 12199.86 9498.48 6699.70 12799.60 52
PatchMatch-RL97.24 22696.78 24098.61 18399.03 19097.83 16696.36 27999.06 20993.49 31497.36 27997.78 28995.75 20999.49 31593.44 30798.77 29498.52 299
PLCcopyleft94.65 1696.51 26495.73 27598.85 15198.75 24597.91 15996.42 27699.06 20990.94 34495.59 33497.38 31494.41 24699.59 28890.93 34498.04 32699.05 236
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
ppachtmachnet_test97.50 20397.74 17796.78 30298.70 25691.23 34294.55 34399.05 21396.36 24799.21 8998.79 18296.39 18299.78 20296.74 17599.82 6899.34 179
CANet97.87 17697.76 17598.19 22797.75 33095.51 25496.76 25899.05 21397.74 15796.93 29398.21 26095.59 21499.89 5997.86 10299.93 2899.19 219
pmmvs597.64 19597.49 19598.08 23499.14 16695.12 26896.70 26299.05 21393.77 30998.62 18298.83 17493.23 26599.75 22298.33 7799.76 10399.36 173
HQP3-MVS99.04 21699.26 245
HQP-MVS97.00 24696.49 25998.55 19498.67 26596.79 22396.29 28299.04 21696.05 25795.55 33896.84 32893.84 25799.54 30392.82 31799.26 24599.32 187
TEST998.71 25298.08 13895.96 29599.03 21891.40 33895.85 33197.53 30396.52 17599.76 215
train_agg97.10 23596.45 26099.07 11898.71 25298.08 13895.96 29599.03 21891.64 33395.85 33197.53 30396.47 17899.76 21593.67 30099.16 25999.36 173
test_prior397.48 20797.00 22598.95 13798.69 26097.95 15695.74 30799.03 21896.48 24396.11 32597.63 29995.92 20499.59 28894.16 28299.20 25299.30 194
test_prior98.95 13798.69 26097.95 15699.03 21899.59 28899.30 194
save fliter99.11 16997.97 15196.53 26899.02 22298.24 122
test_898.67 26598.01 14595.91 30099.02 22291.64 33395.79 33397.50 30696.47 17899.76 215
MVS_Test98.18 15298.36 11797.67 25598.48 28894.73 27598.18 12899.02 22297.69 16098.04 23499.11 10097.22 13899.56 29798.57 6098.90 29098.71 289
agg_prior197.06 23996.40 26199.03 12898.68 26397.99 14695.76 30599.01 22591.73 33295.59 33497.50 30696.49 17799.77 20893.71 29999.14 26399.34 179
agg_prior98.68 26397.99 14699.01 22595.59 33499.77 208
CDPH-MVS97.26 22396.66 24999.07 11899.00 19598.15 13096.03 29199.01 22591.21 34197.79 24797.85 28696.89 15399.69 24592.75 32099.38 22599.39 157
ambc98.24 22498.82 23695.97 24398.62 8499.00 22899.27 7699.21 7996.99 14899.50 31496.55 19599.50 20699.26 204
Anonymous2024052998.93 5098.87 4599.12 10799.19 15098.22 12599.01 5798.99 22999.25 4599.54 3099.37 5897.04 14399.80 17697.89 9799.52 19699.35 177
Regformer-198.55 10998.44 10498.87 14898.85 22797.29 19896.91 24998.99 22998.97 7998.99 12498.64 20997.26 13599.81 16797.79 10499.57 18199.51 101
our_test_397.39 21497.73 17996.34 30898.70 25689.78 34694.61 34198.97 23196.50 24299.04 11698.85 16895.98 20099.84 12797.26 13099.67 14499.41 148
TSAR-MVS + MP.98.63 9598.49 9499.06 12399.64 4897.90 16098.51 9998.94 23296.96 22599.24 8598.89 16097.83 8399.81 16796.88 16399.49 20799.48 119
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
WR-MVS98.40 12998.19 13999.03 12899.00 19597.65 18296.85 25298.94 23298.57 10598.89 14598.50 23195.60 21399.85 10997.54 11799.85 5799.59 58
CNVR-MVS98.17 15497.87 17099.07 11898.67 26598.24 12097.01 24098.93 23497.25 20697.62 25798.34 25097.27 13299.57 29496.42 20599.33 23299.39 157
CNLPA97.17 23296.71 24498.55 19498.56 28098.05 14396.33 28098.93 23496.91 22897.06 28997.39 31394.38 24899.45 32491.66 33299.18 25898.14 315
AdaColmapbinary97.14 23496.71 24498.46 20598.34 30097.80 17296.95 24398.93 23495.58 27096.92 29497.66 29695.87 20699.53 30590.97 34399.14 26398.04 318
CR-MVSNet96.28 27495.95 27197.28 28097.71 33294.22 28598.11 13598.92 23792.31 32796.91 29699.37 5885.44 32699.81 16797.39 12497.36 33997.81 330
Patchmtry97.35 21696.97 22798.50 20297.31 34996.47 23198.18 12898.92 23798.95 8398.78 16399.37 5885.44 32699.85 10995.96 22899.83 6599.17 225
FMVSNet397.50 20397.24 21398.29 22098.08 31695.83 24797.86 16798.91 23997.89 14998.95 13298.95 14487.06 31199.81 16797.77 10699.69 13399.23 209
mvs_anonymous97.83 18598.16 14496.87 29798.18 31091.89 33097.31 22098.90 24097.37 19498.83 15699.46 4696.28 18899.79 19098.90 3898.16 31898.95 255
NCCC97.86 17797.47 19999.05 12598.61 27298.07 14096.98 24298.90 24097.63 16497.04 29097.93 28295.99 19999.66 26595.31 25498.82 29399.43 142
miper_enhance_ethall96.01 27995.74 27496.81 30196.41 36492.27 32793.69 35798.89 24291.14 34298.30 21497.35 31890.58 29099.58 29396.31 21199.03 27798.60 296
D2MVS97.84 18397.84 17297.83 24799.14 16694.74 27496.94 24498.88 24395.84 26598.89 14598.96 14094.40 24799.69 24597.55 11599.95 1699.05 236
CHOSEN 280x42095.51 29295.47 28395.65 32498.25 30588.27 35293.25 35998.88 24393.53 31294.65 35097.15 32486.17 31899.93 2897.41 12399.93 2898.73 288
IU-MVS99.49 8699.15 4898.87 24592.97 31899.41 5096.76 17399.62 15899.66 36
EI-MVSNet-UG-set98.69 8398.71 6298.62 18199.10 17396.37 23397.23 22598.87 24599.20 4999.19 9198.99 13197.30 12999.85 10998.77 4999.79 8599.65 40
EI-MVSNet98.40 12998.51 8998.04 23899.10 17394.73 27597.20 22998.87 24598.97 7999.06 10999.02 11996.00 19699.80 17698.58 5899.82 6899.60 52
test1198.87 245
MVSTER96.86 25196.55 25797.79 24997.91 32494.21 28797.56 19998.87 24597.49 17899.06 10999.05 11280.72 35099.80 17698.44 6899.82 6899.37 167
MSC_two_6792asdad99.32 7898.43 29398.37 11198.86 25099.89 5997.14 13899.60 16799.71 26
No_MVS99.32 7898.43 29398.37 11198.86 25099.89 5997.14 13899.60 16799.71 26
EI-MVSNet-Vis-set98.68 8798.70 6598.63 17999.09 17696.40 23297.23 22598.86 25099.20 4999.18 9598.97 13797.29 13199.85 10998.72 5299.78 8999.64 41
PS-MVSNAJ97.08 23797.39 20296.16 31598.56 28092.46 32395.24 32398.85 25397.25 20697.49 27095.99 34398.07 6699.90 4996.37 20798.67 30296.12 362
DVP-MVScopyleft98.77 7098.52 8799.52 4199.50 7999.21 2798.02 15098.84 25497.97 14299.08 10699.02 11997.61 10399.88 7096.99 15099.63 15599.48 119
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
xiu_mvs_v2_base97.16 23397.49 19596.17 31398.54 28392.46 32395.45 31898.84 25497.25 20697.48 27196.49 33498.31 4999.90 4996.34 21098.68 30196.15 361
MS-PatchMatch97.68 19297.75 17697.45 27398.23 30893.78 30497.29 22198.84 25496.10 25698.64 17998.65 20696.04 19399.36 33396.84 16799.14 26399.20 214
Regformer-398.61 9898.61 7898.63 17999.02 19296.53 23097.17 23398.84 25499.13 5699.10 10398.85 16897.24 13699.79 19098.41 7199.70 12799.57 69
PMMVS96.51 26495.98 27098.09 23197.53 34095.84 24694.92 33198.84 25491.58 33596.05 32995.58 34995.68 21199.66 26595.59 24898.09 32298.76 285
原ACMM198.35 21498.90 21696.25 23798.83 25992.48 32596.07 32898.10 26995.39 22299.71 23992.61 32498.99 28499.08 233
ab-mvs98.41 12698.36 11798.59 18599.19 15097.23 20299.32 1798.81 26097.66 16298.62 18299.40 5796.82 15899.80 17695.88 23099.51 19998.75 286
TAMVS98.24 14798.05 15698.80 15899.07 18097.18 20997.88 16498.81 26096.66 23899.17 9699.21 7994.81 23799.77 20896.96 15499.88 5299.44 138
testdata98.09 23198.93 20895.40 25998.80 26290.08 34997.45 27398.37 24695.26 22499.70 24193.58 30398.95 28899.17 225
CL-MVSNet_self_test97.44 21197.22 21498.08 23498.57 27995.78 24994.30 34898.79 26396.58 24198.60 18698.19 26294.74 24199.64 27296.41 20698.84 29198.82 272
CANet_DTU97.26 22397.06 22297.84 24697.57 33794.65 27996.19 28898.79 26397.23 21295.14 34798.24 25793.22 26699.84 12797.34 12699.84 5999.04 240
test22298.92 21296.93 22095.54 31398.78 26585.72 36396.86 30298.11 26894.43 24599.10 27199.23 209
RRT_MVS97.07 23896.57 25598.58 18695.89 37096.33 23497.36 21698.77 26697.85 15299.08 10699.12 9882.30 34599.96 898.82 4499.90 4799.45 133
新几何198.91 14398.94 20697.76 17498.76 26787.58 36096.75 30798.10 26994.80 23899.78 20292.73 32199.00 28399.20 214
旧先验198.82 23697.45 19298.76 26798.34 25095.50 21899.01 28299.23 209
PAPM_NR96.82 25496.32 26498.30 21999.07 18096.69 22897.48 20798.76 26795.81 26796.61 31296.47 33694.12 25599.17 35190.82 34797.78 32999.06 235
HPM-MVS++copyleft98.10 15797.64 18699.48 5199.09 17699.13 5597.52 20398.75 27097.46 18496.90 29997.83 28796.01 19599.84 12795.82 23799.35 22999.46 129
CDS-MVSNet97.69 19197.35 20698.69 17398.73 24797.02 21696.92 24898.75 27095.89 26498.59 18898.67 20192.08 28499.74 22696.72 17899.81 7299.32 187
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
无先验95.74 30798.74 27289.38 35299.73 23092.38 32699.22 213
112196.73 25696.00 26998.91 14398.95 20597.76 17498.07 14198.73 27387.65 35996.54 31398.13 26494.52 24499.73 23092.38 32699.02 28099.24 208
MCST-MVS98.00 16597.63 18799.10 11199.24 13698.17 12996.89 25198.73 27395.66 26997.92 23797.70 29597.17 13999.66 26596.18 22099.23 24899.47 127
PAPR95.29 29494.47 30497.75 25297.50 34495.14 26794.89 33298.71 27591.39 33995.35 34595.48 35294.57 24399.14 35484.95 36197.37 33798.97 253
PMVScopyleft91.26 2097.86 17797.94 16597.65 25799.71 3297.94 15898.52 9598.68 27698.99 7697.52 26799.35 6297.41 12398.18 36791.59 33599.67 14496.82 353
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
VNet98.42 12598.30 12598.79 16098.79 24297.29 19898.23 12398.66 27799.31 4098.85 15398.80 18094.80 23899.78 20298.13 8399.13 26699.31 191
test1298.93 14098.58 27797.83 16698.66 27796.53 31495.51 21799.69 24599.13 26699.27 201
TSAR-MVS + GP.98.18 15297.98 16198.77 16598.71 25297.88 16196.32 28198.66 27796.33 24899.23 8898.51 22897.48 12099.40 32897.16 13499.46 21199.02 243
OpenMVS_ROBcopyleft95.38 1495.84 28495.18 29597.81 24898.41 29797.15 21297.37 21598.62 28083.86 36598.65 17898.37 24694.29 25099.68 25488.41 35498.62 30596.60 356
MAR-MVS96.47 26895.70 27698.79 16097.92 32399.12 5798.28 11998.60 28192.16 33095.54 34196.17 34194.77 24099.52 30989.62 35198.23 31397.72 336
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
h-mvs3397.77 18897.33 20999.10 11199.21 14397.84 16598.35 11698.57 28299.11 5798.58 19099.02 11988.65 30699.96 898.11 8496.34 35299.49 109
UGNet98.53 11498.45 10298.79 16097.94 32296.96 21899.08 5098.54 28399.10 6496.82 30599.47 4596.55 17499.84 12798.56 6399.94 2499.55 82
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
cl2295.79 28595.39 28996.98 29196.77 35892.79 31894.40 34698.53 28494.59 29197.89 24098.17 26382.82 34499.24 34696.37 20799.03 27798.92 261
pmmvs497.58 20097.28 21098.51 20098.84 23096.93 22095.40 32098.52 28593.60 31198.61 18498.65 20695.10 22899.60 28496.97 15399.79 8598.99 248
API-MVS97.04 24296.91 23297.42 27597.88 32598.23 12498.18 12898.50 28697.57 17097.39 27796.75 33096.77 16299.15 35390.16 34999.02 28094.88 367
sss97.21 22896.93 22898.06 23698.83 23395.22 26496.75 25998.48 28794.49 29297.27 28197.90 28392.77 27699.80 17696.57 18999.32 23399.16 228
Vis-MVSNet (Re-imp)97.46 20897.16 21798.34 21599.55 6796.10 23998.94 6498.44 28898.32 11598.16 22198.62 21588.76 30299.73 23093.88 29599.79 8599.18 221
MDA-MVSNet_test_wron97.60 19897.66 18497.41 27699.04 18793.09 31195.27 32198.42 28997.26 20598.88 14998.95 14495.43 22199.73 23097.02 14798.72 29799.41 148
jason97.45 21097.35 20697.76 25199.24 13693.93 29795.86 30198.42 28994.24 30098.50 20198.13 26494.82 23599.91 4597.22 13199.73 11099.43 142
jason: jason.
test_method79.78 33979.50 34280.62 35580.21 37845.76 38070.82 36998.41 29131.08 37380.89 37497.71 29384.85 32897.37 36991.51 33780.03 37298.75 286
YYNet197.60 19897.67 18197.39 27799.04 18793.04 31595.27 32198.38 29297.25 20698.92 14098.95 14495.48 22099.73 23096.99 15098.74 29599.41 148
IS-MVSNet98.19 15197.90 16899.08 11599.57 5797.97 15199.31 2198.32 29399.01 7598.98 12699.03 11891.59 28699.79 19095.49 25199.80 8099.48 119
131495.74 28695.60 28096.17 31397.53 34092.75 32098.07 14198.31 29491.22 34094.25 35396.68 33195.53 21599.03 35591.64 33497.18 34296.74 354
DPM-MVS96.32 27295.59 28198.51 20098.76 24397.21 20694.54 34498.26 29591.94 33196.37 32197.25 31993.06 27199.43 32691.42 33898.74 29598.89 265
BH-untuned96.83 25296.75 24297.08 28798.74 24693.33 30996.71 26198.26 29596.72 23598.44 20497.37 31695.20 22599.47 32091.89 33097.43 33598.44 304
EU-MVSNet97.66 19498.50 9195.13 33399.63 5085.84 36298.35 11698.21 29798.23 12499.54 3099.46 4695.02 22999.68 25498.24 7899.87 5599.87 4
SixPastTwentyTwo98.75 7398.62 7599.16 10299.83 1597.96 15599.28 3098.20 29899.37 3599.70 1599.65 1992.65 27899.93 2899.04 3299.84 5999.60 52
new_pmnet96.99 24796.76 24197.67 25598.72 24994.89 27295.95 29798.20 29892.62 32498.55 19698.54 22494.88 23499.52 30993.96 29199.44 21798.59 298
CVMVSNet96.25 27597.21 21593.38 35099.10 17380.56 37697.20 22998.19 30096.94 22699.00 12399.02 11989.50 29899.80 17696.36 20999.59 17199.78 14
KD-MVS_2432*160092.87 32791.99 33195.51 32891.37 37589.27 34794.07 35098.14 30195.42 27697.25 28296.44 33767.86 37299.24 34691.28 33996.08 35698.02 319
miper_refine_blended92.87 32791.99 33195.51 32891.37 37589.27 34794.07 35098.14 30195.42 27697.25 28296.44 33767.86 37299.24 34691.28 33996.08 35698.02 319
MG-MVS96.77 25596.61 25197.26 28198.31 30293.06 31295.93 29898.12 30396.45 24597.92 23798.73 19093.77 26199.39 33091.19 34299.04 27699.33 185
EPP-MVSNet98.30 13898.04 15799.07 11899.56 6497.83 16699.29 2698.07 30499.03 7398.59 18899.13 9792.16 28299.90 4996.87 16499.68 13899.49 109
MVS93.19 32592.09 32996.50 30696.91 35494.03 29298.07 14198.06 30568.01 37094.56 35296.48 33595.96 20299.30 34183.84 36396.89 34796.17 359
MVS_030497.64 19597.35 20698.52 19897.87 32696.69 22898.59 8898.05 30697.44 18893.74 36198.85 16893.69 26399.88 7098.11 8499.81 7298.98 249
lupinMVS97.06 23996.86 23497.65 25798.88 22293.89 30195.48 31797.97 30793.53 31298.16 22197.58 30193.81 25999.91 4596.77 17299.57 18199.17 225
GA-MVS95.86 28395.32 29197.49 27198.60 27494.15 28993.83 35597.93 30895.49 27496.68 30897.42 31283.21 34099.30 34196.22 21698.55 30899.01 244
WTY-MVS96.67 25996.27 26797.87 24598.81 23894.61 28096.77 25797.92 30994.94 28597.12 28497.74 29291.11 28899.82 15393.89 29498.15 31999.18 221
Patchmatch-test96.55 26396.34 26397.17 28498.35 29993.06 31298.40 11197.79 31097.33 19798.41 20898.67 20183.68 33999.69 24595.16 25699.31 23598.77 283
ADS-MVSNet295.43 29394.98 29996.76 30398.14 31291.74 33197.92 16097.76 31190.23 34596.51 31698.91 14985.61 32399.85 10992.88 31596.90 34598.69 292
PVSNet93.40 1795.67 28795.70 27695.57 32598.83 23388.57 34992.50 36297.72 31292.69 32396.49 31996.44 33793.72 26299.43 32693.61 30199.28 24198.71 289
pmmvs395.03 30094.40 30696.93 29397.70 33492.53 32295.08 32797.71 31388.57 35697.71 25198.08 27279.39 35799.82 15396.19 21899.11 27098.43 305
alignmvs97.35 21696.88 23398.78 16398.54 28398.09 13497.71 18297.69 31499.20 4997.59 26095.90 34588.12 31099.55 30098.18 8298.96 28798.70 291
AUN-MVS96.24 27695.45 28598.60 18498.70 25697.22 20497.38 21497.65 31595.95 26295.53 34297.96 28182.11 34999.79 19096.31 21197.44 33498.80 280
tpm cat193.29 32493.13 32393.75 34597.39 34684.74 36697.39 21397.65 31583.39 36794.16 35498.41 23982.86 34399.39 33091.56 33695.35 36197.14 348
hse-mvs297.46 20897.07 22198.64 17698.73 24797.33 19697.45 21197.64 31799.11 5798.58 19097.98 27788.65 30699.79 19098.11 8497.39 33698.81 275
PVSNet_089.98 2191.15 33790.30 34093.70 34697.72 33184.34 37090.24 36697.42 31890.20 34893.79 35993.09 36990.90 28998.89 36286.57 35972.76 37397.87 326
BH-w/o95.13 29894.89 30295.86 31798.20 30991.31 33895.65 31097.37 31993.64 31096.52 31595.70 34893.04 27299.02 35688.10 35595.82 35897.24 347
test_yl96.69 25796.29 26597.90 24398.28 30395.24 26297.29 22197.36 32098.21 12598.17 21997.86 28486.27 31699.55 30094.87 26298.32 31198.89 265
DCV-MVSNet96.69 25796.29 26597.90 24398.28 30395.24 26297.29 22197.36 32098.21 12598.17 21997.86 28486.27 31699.55 30094.87 26298.32 31198.89 265
BH-RMVSNet96.83 25296.58 25497.58 26398.47 28994.05 29096.67 26397.36 32096.70 23797.87 24197.98 27795.14 22799.44 32590.47 34898.58 30799.25 205
ADS-MVSNet95.24 29694.93 30196.18 31298.14 31290.10 34597.92 16097.32 32390.23 34596.51 31698.91 14985.61 32399.74 22692.88 31596.90 34598.69 292
VDDNet98.21 14997.95 16399.01 13299.58 5397.74 17799.01 5797.29 32499.67 1098.97 12999.50 3990.45 29199.80 17697.88 10099.20 25299.48 119
PAPM91.88 33690.34 33996.51 30598.06 31792.56 32192.44 36397.17 32586.35 36190.38 36896.01 34286.61 31499.21 34970.65 37395.43 36097.75 334
FPMVS93.44 32392.23 32897.08 28799.25 13597.86 16395.61 31197.16 32692.90 32093.76 36098.65 20675.94 36595.66 37179.30 37197.49 33297.73 335
E-PMN94.17 31294.37 30793.58 34796.86 35585.71 36490.11 36797.07 32798.17 13197.82 24697.19 32084.62 33198.94 35989.77 35097.68 33196.09 363
VDD-MVS98.56 10598.39 11399.07 11899.13 16898.07 14098.59 8897.01 32899.59 2099.11 10099.27 7194.82 23599.79 19098.34 7599.63 15599.34 179
tpmrst95.07 29995.46 28493.91 34397.11 35284.36 36997.62 19196.96 32994.98 28396.35 32298.80 18085.46 32599.59 28895.60 24796.23 35497.79 333
wuyk23d96.06 27897.62 18891.38 35398.65 27198.57 9698.85 7196.95 33096.86 23099.90 499.16 9099.18 1198.40 36689.23 35299.77 9377.18 371
HY-MVS95.94 1395.90 28295.35 29097.55 26797.95 32194.79 27398.81 7396.94 33192.28 32895.17 34698.57 22289.90 29599.75 22291.20 34197.33 34198.10 316
MIMVSNet96.62 26296.25 26897.71 25499.04 18794.66 27899.16 4496.92 33297.23 21297.87 24199.10 10286.11 32099.65 27091.65 33399.21 25198.82 272
SCA96.41 27196.66 24995.67 32298.24 30688.35 35195.85 30396.88 33396.11 25597.67 25498.67 20193.10 26999.85 10994.16 28299.22 24998.81 275
tpmvs95.02 30195.25 29294.33 33996.39 36585.87 36198.08 14096.83 33495.46 27595.51 34398.69 19785.91 32199.53 30594.16 28296.23 35497.58 341
PatchmatchNetpermissive95.58 28995.67 27895.30 33297.34 34787.32 35697.65 18996.65 33595.30 27997.07 28898.69 19784.77 32999.75 22294.97 26098.64 30398.83 271
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PatchT96.65 26096.35 26297.54 26897.40 34595.32 26097.98 15696.64 33699.33 3996.89 30099.42 5284.32 33499.81 16797.69 11497.49 33297.48 344
TR-MVS95.55 29095.12 29796.86 30097.54 33993.94 29696.49 27296.53 33794.36 29997.03 29196.61 33294.26 25199.16 35286.91 35896.31 35397.47 345
dp93.47 32293.59 31693.13 35296.64 35981.62 37597.66 18796.42 33892.80 32296.11 32598.64 20978.55 36299.59 28893.31 31092.18 37098.16 314
EMVS93.83 31894.02 31093.23 35196.83 35784.96 36589.77 36896.32 33997.92 14697.43 27596.36 34086.17 31898.93 36087.68 35697.73 33095.81 364
Anonymous20240521197.90 17197.50 19499.08 11598.90 21698.25 11998.53 9496.16 34098.87 8699.11 10098.86 16590.40 29299.78 20297.36 12599.31 23599.19 219
MDTV_nov1_ep1395.22 29397.06 35383.20 37197.74 18096.16 34094.37 29896.99 29298.83 17483.95 33799.53 30593.90 29397.95 327
baseline195.96 28195.44 28697.52 27098.51 28693.99 29598.39 11296.09 34298.21 12598.40 21297.76 29186.88 31299.63 27595.42 25289.27 37198.95 255
CostFormer93.97 31693.78 31394.51 33897.53 34085.83 36397.98 15695.96 34389.29 35394.99 34998.63 21378.63 36099.62 27794.54 27096.50 35098.09 317
JIA-IIPM95.52 29195.03 29897.00 28996.85 35694.03 29296.93 24695.82 34499.20 4994.63 35199.71 1283.09 34199.60 28494.42 27694.64 36397.36 346
tpm293.09 32692.58 32794.62 33797.56 33886.53 36097.66 18795.79 34586.15 36294.07 35798.23 25975.95 36499.53 30590.91 34596.86 34897.81 330
EPNet_dtu94.93 30294.78 30395.38 33193.58 37487.68 35596.78 25695.69 34697.35 19689.14 37098.09 27188.15 30999.49 31594.95 26199.30 23898.98 249
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
DWT-MVSNet_test92.75 32992.05 33094.85 33596.48 36287.21 35797.83 17094.99 34792.22 32992.72 36394.11 36770.75 36999.46 32295.01 25894.33 36697.87 326
tpm94.67 30494.34 30895.66 32397.68 33688.42 35097.88 16494.90 34894.46 29496.03 33098.56 22378.66 35999.79 19095.88 23095.01 36298.78 282
EPNet96.14 27795.44 28698.25 22390.76 37795.50 25597.92 16094.65 34998.97 7992.98 36298.85 16889.12 30099.87 8795.99 22699.68 13899.39 157
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
thres20093.72 32093.14 32295.46 33098.66 27091.29 33996.61 26694.63 35097.39 19296.83 30493.71 36879.88 35299.56 29782.40 36798.13 32095.54 366
DeepMVS_CXcopyleft93.44 34998.24 30694.21 28794.34 35164.28 37191.34 36794.87 36389.45 29992.77 37477.54 37293.14 36893.35 369
tfpn200view994.03 31593.44 31795.78 32098.93 20891.44 33597.60 19494.29 35297.94 14497.10 28594.31 36579.67 35599.62 27783.05 36498.08 32396.29 357
thres40094.14 31393.44 31796.24 31198.93 20891.44 33597.60 19494.29 35297.94 14497.10 28594.31 36579.67 35599.62 27783.05 36498.08 32397.66 338
thres100view90094.19 31193.67 31595.75 32199.06 18491.35 33798.03 14894.24 35498.33 11497.40 27694.98 35979.84 35399.62 27783.05 36498.08 32396.29 357
thres600view794.45 30693.83 31296.29 30999.06 18491.53 33397.99 15494.24 35498.34 11397.44 27495.01 35779.84 35399.67 25784.33 36298.23 31397.66 338
LFMVS97.20 22996.72 24398.64 17698.72 24996.95 21998.93 6594.14 35699.74 798.78 16399.01 12884.45 33299.73 23097.44 12199.27 24299.25 205
bset_n11_16_dypcd96.99 24796.56 25698.27 22299.00 19595.25 26192.18 36594.05 35798.75 9299.01 12098.38 24488.98 30199.93 2898.77 4999.92 3799.64 41
test0.0.03 194.51 30593.69 31496.99 29096.05 36793.61 30894.97 33093.49 35896.17 25297.57 26394.88 36182.30 34599.01 35893.60 30294.17 36798.37 309
N_pmnet97.63 19797.17 21698.99 13499.27 13197.86 16395.98 29293.41 35995.25 28099.47 4298.90 15295.63 21299.85 10996.91 15699.73 11099.27 201
IB-MVS91.63 1992.24 33490.90 33896.27 31097.22 35191.24 34194.36 34793.33 36092.37 32692.24 36594.58 36466.20 37899.89 5993.16 31294.63 36497.66 338
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
ET-MVSNet_ETH3D94.30 31093.21 32097.58 26398.14 31294.47 28294.78 33493.24 36194.72 28989.56 36995.87 34678.57 36199.81 16796.91 15697.11 34498.46 301
K. test v398.00 16597.66 18499.03 12899.79 1997.56 18699.19 4292.47 36299.62 1799.52 3599.66 1789.61 29699.96 899.25 2099.81 7299.56 74
test-LLR93.90 31793.85 31194.04 34196.53 36084.62 36794.05 35292.39 36396.17 25294.12 35595.07 35582.30 34599.67 25795.87 23398.18 31697.82 328
test-mter92.33 33391.76 33694.04 34196.53 36084.62 36794.05 35292.39 36394.00 30794.12 35595.07 35565.63 37999.67 25795.87 23398.18 31697.82 328
MTMP97.93 15991.91 365
TESTMET0.1,192.19 33591.77 33593.46 34896.48 36282.80 37294.05 35291.52 36694.45 29694.00 35894.88 36166.65 37699.56 29795.78 23898.11 32198.02 319
thisisatest051594.12 31493.16 32196.97 29298.60 27492.90 31693.77 35690.61 36794.10 30496.91 29695.87 34674.99 36699.80 17694.52 27199.12 26998.20 312
tttt051795.64 28894.98 29997.64 25999.36 11793.81 30398.72 7790.47 36898.08 13698.67 17598.34 25073.88 36799.92 3597.77 10699.51 19999.20 214
thisisatest053095.27 29594.45 30597.74 25399.19 15094.37 28397.86 16790.20 36997.17 21698.22 21897.65 29773.53 36899.90 4996.90 16199.35 22998.95 255
baseline293.73 31992.83 32596.42 30797.70 33491.28 34096.84 25489.77 37093.96 30892.44 36495.93 34479.14 35899.77 20892.94 31396.76 34998.21 311
MVS-HIRNet94.32 30895.62 27990.42 35498.46 29075.36 37796.29 28289.13 37195.25 28095.38 34499.75 792.88 27499.19 35094.07 28999.39 22296.72 355
test111196.49 26796.82 23895.52 32799.42 10787.08 35899.22 3587.14 37299.11 5799.46 4399.58 2788.69 30399.86 9498.80 4599.95 1699.62 46
lessismore_v098.97 13599.73 2597.53 18886.71 37399.37 5899.52 3889.93 29499.92 3598.99 3599.72 11799.44 138
ECVR-MVScopyleft96.42 27096.61 25195.85 31899.38 11288.18 35399.22 3586.00 37499.08 6999.36 6099.57 2888.47 30899.82 15398.52 6499.95 1699.54 86
EPMVS93.72 32093.27 31995.09 33496.04 36887.76 35498.13 13285.01 37594.69 29096.92 29498.64 20978.47 36399.31 33995.04 25796.46 35198.20 312
MVEpermissive83.40 2292.50 33091.92 33394.25 34098.83 23391.64 33292.71 36183.52 37695.92 26386.46 37395.46 35395.20 22595.40 37280.51 36998.64 30395.73 365
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
gg-mvs-nofinetune92.37 33291.20 33795.85 31895.80 37192.38 32599.31 2181.84 37799.75 591.83 36699.74 868.29 37199.02 35687.15 35797.12 34396.16 360
GG-mvs-BLEND94.76 33694.54 37392.13 32999.31 2180.47 37888.73 37191.01 37167.59 37498.16 36882.30 36894.53 36593.98 368
tmp_tt78.77 34078.73 34378.90 35658.45 37974.76 37994.20 34978.26 37939.16 37286.71 37292.82 37080.50 35175.19 37586.16 36092.29 36986.74 370
test250692.39 33191.89 33493.89 34499.38 11282.28 37399.32 1766.03 38099.08 6998.77 16699.57 2866.26 37799.84 12798.71 5399.95 1699.54 86
testmvs17.12 34220.53 3456.87 35812.05 3804.20 38293.62 3586.73 3814.62 37610.41 37624.33 3738.28 3813.56 3779.69 37515.07 37412.86 373
test12317.04 34320.11 3467.82 35710.25 3814.91 38194.80 3334.47 3824.93 37510.00 37724.28 3749.69 3803.64 37610.14 37412.43 37514.92 372
test_blank0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 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 3770.00 3820.00 3780.00 3760.00 3760.00 374
pcd_1.5k_mvsjas8.17 34410.90 3470.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 37798.07 660.00 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 3770.00 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 3770.00 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 3770.00 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 3770.00 3820.00 3780.00 3760.00 3760.00 374
n20.00 383
nn0.00 383
ab-mvs-re8.12 34510.83 3480.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 37897.48 3080.00 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 3770.00 3820.00 3780.00 3760.00 3760.00 374
PC_three_145293.27 31599.40 5398.54 22498.22 5597.00 37095.17 25599.45 21499.49 109
eth-test20.00 382
eth-test0.00 382
OPU-MVS98.82 15498.59 27698.30 11698.10 13798.52 22798.18 5998.75 36494.62 26899.48 20999.41 148
test_0728_THIRD98.17 13199.08 10699.02 11997.89 7999.88 7097.07 14499.71 12299.70 31
GSMVS98.81 275
test_part299.36 11799.10 6099.05 114
sam_mvs184.74 33098.81 275
sam_mvs84.29 336
test_post197.59 19620.48 37683.07 34299.66 26594.16 282
test_post21.25 37583.86 33899.70 241
patchmatchnet-post98.77 18584.37 33399.85 109
gm-plane-assit94.83 37281.97 37488.07 35894.99 35899.60 28491.76 331
test9_res93.28 31199.15 26299.38 164
agg_prior292.50 32599.16 25999.37 167
test_prior497.97 15195.86 301
test_prior295.74 30796.48 24396.11 32597.63 29995.92 20494.16 28299.20 252
旧先验295.76 30588.56 35797.52 26799.66 26594.48 272
新几何295.93 298
原ACMM295.53 314
testdata299.79 19092.80 319
segment_acmp97.02 146
testdata195.44 31996.32 249
plane_prior799.19 15097.87 162
plane_prior698.99 19997.70 18094.90 231
plane_prior497.98 277
plane_prior397.78 17397.41 19097.79 247
plane_prior297.77 17698.20 128
plane_prior199.05 186
plane_prior97.65 18297.07 23896.72 23599.36 227
HQP5-MVS96.79 223
HQP-NCC98.67 26596.29 28296.05 25795.55 338
ACMP_Plane98.67 26596.29 28296.05 25795.55 338
BP-MVS92.82 317
HQP4-MVS95.56 33799.54 30399.32 187
HQP2-MVS93.84 257
NP-MVS98.84 23097.39 19596.84 328
MDTV_nov1_ep13_2view74.92 37897.69 18490.06 35097.75 25085.78 32293.52 30498.69 292
ACMMP++_ref99.77 93
ACMMP++99.68 138
Test By Simon96.52 175