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.
sorted bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort by
LTVRE_ROB99.19 199.88 499.87 499.88 1199.91 1599.90 499.96 199.92 699.90 799.97 699.87 3199.81 599.95 4599.54 2699.99 1299.80 24
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
3Dnovator99.15 299.43 6699.36 7599.65 10099.39 23799.42 14299.70 2299.56 17899.23 13299.35 20999.80 5499.17 5199.95 4598.21 16099.84 12399.59 128
3Dnovator+98.92 399.35 8999.24 10399.67 8899.35 24799.47 12499.62 4799.50 21399.44 10199.12 25399.78 6698.77 10499.94 5797.87 19199.72 19799.62 106
DeepC-MVS98.90 499.62 3499.61 3099.67 8899.72 10899.44 13599.24 12899.71 9399.27 12499.93 1499.90 2199.70 1199.93 7198.99 9999.99 1299.64 90
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
DeepC-MVS_fast98.47 599.23 11799.12 12299.56 14099.28 27399.22 19098.99 19699.40 24799.08 15499.58 14599.64 14198.90 8599.83 23697.44 22699.75 17599.63 95
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
DeepPCF-MVS98.42 699.18 14099.02 15599.67 8899.22 28299.75 5097.25 34399.47 22498.72 19999.66 11599.70 10799.29 3999.63 33698.07 17499.81 15099.62 106
ACMH98.42 699.59 3799.54 4499.72 7699.86 3099.62 9699.56 6499.79 5398.77 19499.80 6099.85 3799.64 1399.85 20898.70 12999.89 9299.70 49
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ACMH+98.40 899.50 5099.43 6299.71 8099.86 3099.76 4799.32 10099.77 6199.53 8499.77 7399.76 7699.26 4599.78 27397.77 19999.88 10099.60 119
HY-MVS98.23 998.21 26997.95 26998.99 25599.03 31398.24 26999.61 5398.72 31896.81 31698.73 29499.51 21394.06 29299.86 19096.91 25998.20 33898.86 307
OpenMVScopyleft98.12 1098.23 26797.89 27999.26 22499.19 28999.26 17799.65 4499.69 10391.33 35598.14 32899.77 7398.28 16799.96 3595.41 32299.55 24798.58 322
ACMM98.09 1199.46 6199.38 6999.72 7699.80 5699.69 7699.13 16599.65 12698.99 16399.64 12199.72 9399.39 2499.86 19098.23 15899.81 15099.60 119
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
COLMAP_ROBcopyleft98.06 1299.45 6399.37 7299.70 8499.83 3899.70 7299.38 8699.78 5899.53 8499.67 11199.78 6699.19 4999.86 19097.32 23299.87 10999.55 145
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
TAPA-MVS97.92 1398.03 27597.55 28999.46 16999.47 21499.44 13598.50 25899.62 13786.79 35899.07 26099.26 27698.26 16999.62 33797.28 23699.73 19199.31 236
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
ACMP97.51 1499.05 16798.84 19099.67 8899.78 7299.55 11698.88 20999.66 11597.11 30999.47 17999.60 17699.07 6599.89 14396.18 29799.85 11999.58 133
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
PVSNet97.47 1598.42 25198.44 22998.35 29999.46 21996.26 32696.70 35499.34 26397.68 28099.00 26499.13 29497.40 22999.72 29497.59 21899.68 20999.08 282
PLCcopyleft97.35 1698.36 25697.99 26599.48 16399.32 26399.24 18698.50 25899.51 20995.19 34098.58 30598.96 32496.95 25099.83 23695.63 31699.25 29599.37 222
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
OpenMVS_ROBcopyleft97.31 1797.36 29796.84 30898.89 27299.29 27099.45 13398.87 21299.48 22086.54 36099.44 18499.74 8397.34 23499.86 19091.61 34999.28 29197.37 354
PCF-MVS96.03 1896.73 31095.86 32199.33 20899.44 22499.16 19996.87 35299.44 23386.58 35998.95 26799.40 24194.38 29099.88 15787.93 35799.80 15598.95 299
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
PVSNet_095.53 1995.85 32895.31 33097.47 32498.78 33793.48 35095.72 35899.40 24796.18 32697.37 34797.73 35995.73 27799.58 34495.49 31981.40 36399.36 225
IB-MVS95.41 2095.30 33294.46 33597.84 31598.76 33995.33 33897.33 34096.07 35596.02 32795.37 36297.41 36376.17 37099.96 3597.54 22095.44 36198.22 339
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
PMVScopyleft92.94 2198.82 20598.81 19498.85 27399.84 3497.99 28599.20 13899.47 22499.71 4499.42 19099.82 4998.09 18399.47 35393.88 34499.85 11999.07 287
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
MVEpermissive92.54 2296.66 31296.11 31698.31 30399.68 13097.55 30197.94 31195.60 35899.37 11190.68 36598.70 34096.56 25698.61 36386.94 36299.55 24798.77 313
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
CMPMVSbinary77.52 2398.50 24298.19 25599.41 18998.33 35199.56 11399.01 18999.59 16295.44 33599.57 14899.80 5495.64 27899.46 35596.47 28599.92 7499.21 253
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
GeoE99.69 2199.66 2199.78 3799.76 8499.76 4799.60 5899.82 3799.46 9899.75 8099.56 19599.63 1499.95 4599.43 3799.88 10099.62 106
test_method91.72 33392.32 33689.91 34793.49 36770.18 36990.28 36199.56 17861.71 36495.39 36199.52 20993.90 29399.94 5798.76 12498.27 33799.62 106
Anonymous2024052199.44 6599.42 6499.49 15999.89 2198.96 22199.62 4799.76 6699.85 2099.82 5099.88 2896.39 26599.97 1799.59 2099.98 2199.55 145
hse-mvs398.61 22698.34 24099.44 17599.60 14898.67 24399.27 11899.44 23399.68 5299.32 21799.49 22192.50 309100.00 199.24 6696.51 35799.65 83
hse-mvs298.52 24098.30 24499.16 23899.29 27098.60 25098.77 23199.02 30699.68 5299.32 21799.04 30992.50 30999.85 20899.24 6697.87 34899.03 291
CL-MVSNet_2432*160098.71 21898.56 21999.15 24099.22 28298.66 24597.14 34699.51 20998.09 25799.54 16299.27 27396.87 25299.74 28998.43 14298.96 30999.03 291
KD-MVS_2432*160095.89 32595.41 32897.31 33094.96 36493.89 34697.09 34799.22 28997.23 30298.88 27699.04 30979.23 36699.54 34696.24 29596.81 35498.50 329
DIV-MVS_2432*160099.63 3199.59 3399.76 4699.84 3499.90 499.37 9099.79 5399.83 2699.88 3299.85 3798.42 15199.90 12999.60 1999.73 19199.49 181
AUN-MVS97.82 28097.38 29199.14 24199.27 27598.53 25298.72 23799.02 30698.10 25597.18 35299.03 31389.26 34199.85 20897.94 18497.91 34699.03 291
ZD-MVS99.43 22699.61 10299.43 23796.38 32299.11 25499.07 30497.86 20299.92 9094.04 34199.49 262
test117299.23 11799.05 14699.74 6299.52 18699.75 5099.20 13899.61 14498.97 16599.48 17799.58 18498.41 15299.91 10897.15 24999.55 24799.57 139
SR-MVS-dyc-post99.27 11099.11 12599.73 7099.54 17699.74 5699.26 12099.62 13799.16 14399.52 16999.64 14198.41 15299.91 10897.27 23799.61 23599.54 153
RE-MVS-def99.13 11899.54 17699.74 5699.26 12099.62 13799.16 14399.52 16999.64 14198.57 12897.27 23799.61 23599.54 153
SED-MVS99.40 7699.28 9599.77 4099.69 12199.82 2699.20 13899.54 18999.13 14999.82 5099.63 15198.91 8299.92 9097.85 19499.70 20399.58 133
IU-MVS99.69 12199.77 4199.22 28997.50 28999.69 10597.75 20199.70 20399.77 33
OPU-MVS99.29 21899.12 29999.44 13599.20 13899.40 24199.00 7198.84 36196.54 28099.60 23899.58 133
test_241102_TWO99.54 18999.13 14999.76 7599.63 15198.32 16599.92 9097.85 19499.69 20699.75 40
test_241102_ONE99.69 12199.82 2699.54 18999.12 15299.82 5099.49 22198.91 8299.52 350
xxxxxxxxxxxxxcwj99.11 15798.96 17299.54 14799.53 18199.25 18198.29 27499.76 6699.07 15699.42 19099.61 16998.86 8899.87 17096.45 28699.68 20999.49 181
SF-MVS99.10 16198.93 17599.62 12099.58 15499.51 11999.13 16599.65 12697.97 26499.42 19099.61 16998.86 8899.87 17096.45 28699.68 20999.49 181
ETH3D cwj APD-0.1698.50 24298.16 25899.51 15399.04 31299.39 14998.47 26099.47 22496.70 31998.78 29099.33 26197.62 22399.86 19094.69 33499.38 27799.28 242
cl-mvsnet297.56 29197.28 29398.40 29798.37 35096.75 32097.24 34499.37 25797.31 29999.41 19899.22 28587.30 34499.37 35797.70 20699.62 22899.08 282
miper_ehance_all_eth98.59 23198.59 21298.59 29098.98 31697.07 31397.49 33499.52 20698.50 21999.52 16999.37 24796.41 26499.71 29897.86 19299.62 22899.00 297
miper_enhance_ethall98.03 27597.94 27398.32 30198.27 35296.43 32596.95 35099.41 24096.37 32399.43 18898.96 32494.74 28699.69 30697.71 20499.62 22898.83 310
ZNCC-MVS99.22 12699.04 15299.77 4099.76 8499.73 5999.28 11599.56 17898.19 25299.14 25099.29 26998.84 9199.92 9097.53 22299.80 15599.64 90
ETH3 D test640097.76 28397.19 29899.50 15699.38 24099.26 17798.34 26999.49 21892.99 35198.54 30899.20 28995.92 27699.82 24691.14 35299.66 22099.40 214
cl-mvsnet____98.54 23898.41 23298.92 26399.03 31397.80 29497.46 33599.59 16298.90 17799.60 14099.46 23293.85 29599.78 27397.97 18299.89 9299.17 262
cl-mvsnet198.54 23898.42 23198.92 26399.03 31397.80 29497.46 33599.59 16298.90 17799.60 14099.46 23293.87 29499.78 27397.97 18299.89 9299.18 260
eth_miper_zixun_eth98.68 22198.71 20198.60 28999.10 30596.84 31997.52 33399.54 18998.94 17099.58 14599.48 22496.25 26999.76 28398.01 17899.93 7099.21 253
9.1498.64 20799.45 22298.81 22399.60 15597.52 28899.28 22699.56 19598.53 13799.83 23695.36 32499.64 225
testtj98.56 23498.17 25799.72 7699.45 22299.60 10498.88 20999.50 21396.88 31299.18 24599.48 22497.08 24699.92 9093.69 34599.38 27799.63 95
uanet_test8.33 33811.11 3410.00 3500.00 3710.00 3720.00 3620.00 3720.00 3670.00 368100.00 10.00 3730.00 3680.00 3660.00 3660.00 364
ETH3D-3000-0.198.77 20998.50 22499.59 12799.47 21499.53 11898.77 23199.60 15597.33 29899.23 23399.50 21697.91 19799.83 23695.02 32999.67 21699.41 212
save fliter99.53 18199.25 18198.29 27499.38 25699.07 156
ET-MVSNet_ETH3D96.78 30896.07 31798.91 26599.26 27797.92 29197.70 32396.05 35697.96 26792.37 36498.43 35087.06 34699.90 12998.27 15597.56 35198.91 303
UniMVSNet_ETH3D99.85 799.83 799.90 499.89 2199.91 299.89 499.71 9399.93 499.95 1099.89 2599.71 999.96 3599.51 3099.97 3099.84 14
EIA-MVS99.12 15399.01 15899.45 17399.36 24599.62 9699.34 9599.79 5398.41 22798.84 28298.89 33198.75 10799.84 22598.15 16999.51 25898.89 304
miper_refine_blended95.89 32595.41 32897.31 33094.96 36493.89 34697.09 34799.22 28997.23 30298.88 27699.04 30979.23 36699.54 34696.24 29596.81 35498.50 329
miper_lstm_enhance98.65 22398.60 21098.82 28099.20 28797.33 30797.78 31999.66 11599.01 16299.59 14399.50 21694.62 28899.85 20898.12 17099.90 8499.26 243
ETV-MVS99.18 14099.18 10999.16 23899.34 25799.28 17399.12 16999.79 5399.48 8998.93 26998.55 34699.40 2399.93 7198.51 13999.52 25798.28 336
CS-MVS99.52 4999.54 4499.47 16599.51 19199.85 1299.62 4799.93 599.75 3899.34 21299.13 29499.39 2499.91 10899.43 3799.75 17598.66 316
D2MVS99.22 12699.19 10899.29 21899.69 12198.74 23998.81 22399.41 24098.55 21399.68 10799.69 11398.13 18199.87 17098.82 11899.98 2199.24 246
DVP-MVS99.32 10099.17 11099.77 4099.69 12199.80 3499.14 15999.31 27099.16 14399.62 13299.61 16998.35 16099.91 10897.88 18899.72 19799.61 115
Zhenlong Yuan, Jinguo Luo, Fei Shen, Zhaoxin Li, Cong Liu, Tianlu Mao, Zhaoqi Wang: DVP-MVS: Synergize Depth-Edge and Visibility Prior for Multi-View Stereo. AAAI2025
test_0728_THIRD99.18 13899.62 13299.61 16998.58 12799.91 10897.72 20399.80 15599.77 33
test_0728_SECOND99.83 2199.70 11899.79 3699.14 15999.61 14499.92 9097.88 18899.72 19799.77 33
test072699.69 12199.80 3499.24 12899.57 17399.16 14399.73 9399.65 13998.35 160
SR-MVS99.19 13699.00 16199.74 6299.51 19199.72 6399.18 14499.60 15598.85 18399.47 17999.58 18498.38 15799.92 9096.92 25899.54 25399.57 139
DPM-MVS98.28 26297.94 27399.32 21299.36 24599.11 20497.31 34198.78 31696.88 31298.84 28299.11 30197.77 20999.61 34194.03 34299.36 28299.23 249
GST-MVS99.16 14598.96 17299.75 5699.73 10499.73 5999.20 13899.55 18498.22 24999.32 21799.35 25798.65 12099.91 10896.86 26299.74 18499.62 106
test_yl98.25 26497.95 26999.13 24299.17 29298.47 25699.00 19198.67 32198.97 16599.22 23799.02 31491.31 31999.69 30697.26 23998.93 31099.24 246
thisisatest053097.45 29396.95 30498.94 25999.68 13097.73 29699.09 17694.19 36398.61 20899.56 15599.30 26684.30 35999.93 7198.27 15599.54 25399.16 264
Anonymous2024052999.42 6999.34 7799.65 10099.53 18199.60 10499.63 4699.39 25099.47 9499.76 7599.78 6698.13 18199.86 19098.70 12999.68 20999.49 181
Anonymous20240521198.75 21298.46 22699.63 11199.34 25799.66 8399.47 7497.65 34499.28 12399.56 15599.50 21693.15 30199.84 22598.62 13499.58 24199.40 214
DCV-MVSNet98.25 26497.95 26999.13 24299.17 29298.47 25699.00 19198.67 32198.97 16599.22 23799.02 31491.31 31999.69 30697.26 23998.93 31099.24 246
tttt051797.62 28897.20 29798.90 27199.76 8497.40 30599.48 7294.36 36199.06 16099.70 10299.49 22184.55 35899.94 5798.73 12799.65 22399.36 225
our_test_398.85 20299.09 13498.13 30899.66 13694.90 34297.72 32199.58 17199.07 15699.64 12199.62 16098.19 17799.93 7198.41 14399.95 4999.55 145
thisisatest051596.98 30496.42 31198.66 28899.42 23197.47 30297.27 34294.30 36297.24 30199.15 24898.86 33385.01 35699.87 17097.10 25199.39 27698.63 317
ppachtmachnet_test98.89 19799.12 12298.20 30699.66 13695.24 33997.63 32599.68 10699.08 15499.78 6899.62 16098.65 12099.88 15798.02 17599.96 4299.48 186
SMA-MVScopyleft99.19 13699.00 16199.73 7099.46 21999.73 5999.13 16599.52 20697.40 29499.57 14899.64 14198.93 7999.83 23697.61 21699.79 16099.63 95
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
GSMVS99.14 270
DPE-MVScopyleft99.14 14998.92 17999.82 2399.57 16499.77 4198.74 23499.60 15598.55 21399.76 7599.69 11398.23 17399.92 9096.39 28899.75 17599.76 37
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
test_part299.62 14599.67 8199.55 160
test_part198.63 22498.26 24799.75 5699.40 23599.49 12199.67 3599.68 10699.86 1699.88 3299.86 3686.73 35299.93 7199.34 5199.97 3099.81 23
thres100view90096.39 31696.03 31897.47 32499.63 14295.93 33199.18 14497.57 34598.75 19898.70 29797.31 36587.04 34799.67 32287.62 35898.51 33296.81 356
tfpnnormal99.43 6699.38 6999.60 12599.87 2899.75 5099.59 5999.78 5899.71 4499.90 2299.69 11398.85 9099.90 12997.25 24299.78 16699.15 266
tfpn200view996.30 31995.89 31997.53 32299.58 15496.11 32899.00 19197.54 34898.43 22498.52 30996.98 36786.85 34999.67 32287.62 35898.51 33296.81 356
cl_fuxian98.72 21798.71 20198.72 28599.12 29997.22 31097.68 32499.56 17898.90 17799.54 16299.48 22496.37 26699.73 29297.88 18899.88 10099.21 253
CHOSEN 280x42098.41 25298.41 23298.40 29799.34 25795.89 33396.94 35199.44 23398.80 19099.25 22999.52 20993.51 29999.98 798.94 11099.98 2199.32 234
CANet99.11 15799.05 14699.28 22098.83 32998.56 25198.71 23999.41 24099.25 12899.23 23399.22 28597.66 22099.94 5799.19 7499.97 3099.33 231
Fast-Effi-MVS+-dtu99.20 13399.12 12299.43 17999.25 27899.69 7699.05 18299.82 3799.50 8798.97 26599.05 30698.98 7399.98 798.20 16199.24 29798.62 318
Effi-MVS+-dtu99.07 16398.92 17999.52 15098.89 32399.78 3999.15 15799.66 11599.34 11498.92 27299.24 28397.69 21399.98 798.11 17199.28 29198.81 311
CANet_DTU98.91 19298.85 18899.09 24698.79 33598.13 27698.18 28199.31 27099.48 8998.86 28099.51 21396.56 25699.95 4599.05 9599.95 4999.19 258
MVS_030498.88 19898.71 20199.39 19498.85 32798.91 23099.45 7599.30 27398.56 21197.26 35099.68 12496.18 27199.96 3599.17 7999.94 6299.29 240
MP-MVS-pluss99.14 14998.92 17999.80 2999.83 3899.83 2298.61 24199.63 13496.84 31599.44 18499.58 18498.81 9299.91 10897.70 20699.82 14299.67 65
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
MSP-MVS99.04 17098.79 19799.81 2699.78 7299.73 5999.35 9499.57 17398.54 21699.54 16298.99 31696.81 25399.93 7196.97 25699.53 25599.77 33
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
sam_mvs190.81 32999.14 270
sam_mvs90.52 333
IterMVS-SCA-FT99.00 17999.16 11198.51 29299.75 9595.90 33298.07 29599.84 3099.84 2399.89 2699.73 8796.01 27499.99 599.33 54100.00 199.63 95
TSAR-MVS + MP.99.34 9499.24 10399.63 11199.82 4499.37 15599.26 12099.35 26198.77 19499.57 14899.70 10799.27 4499.88 15797.71 20499.75 17599.65 83
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
xiu_mvs_v1_base_debu99.23 11799.34 7798.91 26599.59 15198.23 27098.47 26099.66 11599.61 7299.68 10798.94 32699.39 2499.97 1799.18 7699.55 24798.51 326
OPM-MVS99.26 11299.13 11899.63 11199.70 11899.61 10298.58 24599.48 22098.50 21999.52 16999.63 15199.14 5599.76 28397.89 18799.77 17099.51 170
ACMMP_NAP99.28 10699.11 12599.79 3499.75 9599.81 2998.95 20499.53 19898.27 24799.53 16799.73 8798.75 10799.87 17097.70 20699.83 13399.68 58
ambc99.20 23499.35 24798.53 25299.17 14999.46 22899.67 11199.80 5498.46 14799.70 30097.92 18599.70 20399.38 219
zzz-MVS99.30 10399.14 11599.80 2999.81 5199.81 2998.73 23699.53 19899.27 12499.42 19099.63 15198.21 17499.95 4597.83 19799.79 16099.65 83
MTGPAbinary99.53 198
mvs-test198.83 20398.70 20499.22 23198.89 32399.65 8898.88 20999.66 11599.34 11498.29 31798.94 32697.69 21399.96 3598.11 17198.54 33198.04 346
Effi-MVS+99.06 16498.97 17099.34 20699.31 26498.98 21798.31 27399.91 998.81 18898.79 28898.94 32699.14 5599.84 22598.79 12098.74 32399.20 256
xiu_mvs_v2_base99.02 17399.11 12598.77 28299.37 24398.09 28198.13 28799.51 20999.47 9499.42 19098.54 34799.38 2999.97 1798.83 11699.33 28698.24 338
xiu_mvs_v1_base99.23 11799.34 7798.91 26599.59 15198.23 27098.47 26099.66 11599.61 7299.68 10798.94 32699.39 2499.97 1799.18 7699.55 24798.51 326
new-patchmatchnet99.35 8999.57 3998.71 28799.82 4496.62 32298.55 25199.75 7399.50 8799.88 3299.87 3199.31 3799.88 15799.43 37100.00 199.62 106
pmmvs699.86 699.86 699.83 2199.94 1099.90 499.83 699.91 999.85 2099.94 1199.95 1199.73 899.90 12999.65 1699.97 3099.69 52
pmmvs599.19 13699.11 12599.42 18199.76 8498.88 23298.55 25199.73 8198.82 18799.72 9599.62 16096.56 25699.82 24699.32 5699.95 4999.56 142
test_post199.14 15951.63 37289.54 34099.82 24696.86 262
test_post52.41 37190.25 33599.86 190
Fast-Effi-MVS+99.02 17398.87 18699.46 16999.38 24099.50 12099.04 18499.79 5397.17 30598.62 30198.74 33999.34 3599.95 4598.32 15199.41 27498.92 302
patchmatchnet-post99.62 16090.58 33199.94 57
Anonymous2023121199.62 3499.57 3999.76 4699.61 14699.60 10499.81 999.73 8199.82 2899.90 2299.90 2197.97 19499.86 19099.42 4399.96 4299.80 24
pmmvs-eth3d99.48 5499.47 5399.51 15399.77 8099.41 14698.81 22399.66 11599.42 10899.75 8099.66 13499.20 4899.76 28398.98 10199.99 1299.36 225
GG-mvs-BLEND97.36 32797.59 36096.87 31899.70 2288.49 36994.64 36397.26 36680.66 36399.12 35891.50 35096.50 35896.08 360
xiu_mvs_v1_base_debi99.23 11799.34 7798.91 26599.59 15198.23 27098.47 26099.66 11599.61 7299.68 10798.94 32699.39 2499.97 1799.18 7699.55 24798.51 326
Anonymous2023120699.35 8999.31 8399.47 16599.74 10199.06 21499.28 11599.74 7899.23 13299.72 9599.53 20797.63 22299.88 15799.11 9199.84 12399.48 186
MTAPA99.35 8999.20 10799.80 2999.81 5199.81 2999.33 9799.53 19899.27 12499.42 19099.63 15198.21 17499.95 4597.83 19799.79 16099.65 83
MTMP99.09 17698.59 325
gm-plane-assit97.59 36089.02 36893.47 34998.30 35299.84 22596.38 289
test9_res95.10 32799.44 26899.50 176
MVP-Stereo99.16 14599.08 13699.43 17999.48 20999.07 21299.08 17999.55 18498.63 20599.31 22199.68 12498.19 17799.78 27398.18 16599.58 24199.45 197
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
TEST999.35 24799.35 16298.11 29099.41 24094.83 34697.92 33598.99 31698.02 18999.85 208
train_agg98.35 25997.95 26999.57 13699.35 24799.35 16298.11 29099.41 24094.90 34297.92 33598.99 31698.02 18999.85 20895.38 32399.44 26899.50 176
gg-mvs-nofinetune95.87 32795.17 33197.97 31198.19 35496.95 31599.69 2889.23 36899.89 1196.24 35799.94 1281.19 36199.51 35193.99 34398.20 33897.44 352
SCA98.11 27198.36 23797.36 32799.20 28792.99 35298.17 28398.49 32998.24 24899.10 25699.57 19296.01 27499.94 5796.86 26299.62 22899.14 270
Patchmatch-test98.10 27297.98 26798.48 29499.27 27596.48 32399.40 8299.07 30298.81 18899.23 23399.57 19290.11 33699.87 17096.69 27299.64 22599.09 279
test_899.34 25799.31 16898.08 29499.40 24794.90 34297.87 33998.97 32298.02 18999.84 225
MS-PatchMatch99.00 17998.97 17099.09 24699.11 30498.19 27398.76 23399.33 26498.49 22199.44 18499.58 18498.21 17499.69 30698.20 16199.62 22899.39 217
Patchmatch-RL test98.60 22898.36 23799.33 20899.77 8099.07 21298.27 27699.87 1898.91 17699.74 8999.72 9390.57 33299.79 27098.55 13799.85 11999.11 274
cdsmvs_eth3d_5k24.88 33633.17 3380.00 3500.00 3710.00 3720.00 36299.62 1370.00 3670.00 36899.13 29499.82 40.00 3680.00 3660.00 3660.00 364
pcd_1.5k_mvsjas16.61 33722.14 3400.00 3500.00 3710.00 3720.00 3620.00 3720.00 3670.00 368100.00 199.28 410.00 3680.00 3660.00 3660.00 364
agg_prior198.33 26197.92 27599.57 13699.35 24799.36 15897.99 30499.39 25094.85 34597.76 34498.98 31998.03 18799.85 20895.49 31999.44 26899.51 170
agg_prior294.58 33599.46 26799.50 176
agg_prior99.35 24799.36 15899.39 25097.76 34499.85 208
tmp_tt95.75 32995.42 32796.76 33589.90 36894.42 34498.86 21397.87 34278.01 36199.30 22599.69 11397.70 21195.89 36499.29 6298.14 34299.95 1
canonicalmvs99.02 17399.00 16199.09 24699.10 30598.70 24199.61 5399.66 11599.63 6798.64 30097.65 36099.04 6999.54 34698.79 12098.92 31299.04 290
anonymousdsp99.80 1199.77 1299.90 499.96 499.88 799.73 1699.85 2499.70 4899.92 1899.93 1399.45 2299.97 1799.36 49100.00 199.85 13
alignmvs98.28 26297.96 26899.25 22799.12 29998.93 22799.03 18698.42 33199.64 6498.72 29597.85 35890.86 32899.62 33798.88 11499.13 30099.19 258
nrg03099.70 1999.66 2199.82 2399.76 8499.84 1899.61 5399.70 9799.93 499.78 6899.68 12499.10 5899.78 27399.45 3599.96 4299.83 18
v14419299.55 4499.54 4499.58 13199.78 7299.20 19699.11 17199.62 13799.18 13899.89 2699.72 9398.66 11899.87 17099.88 699.97 3099.66 75
FIs99.65 3099.58 3699.84 1999.84 3499.85 1299.66 3999.75 7399.86 1699.74 8999.79 6098.27 16899.85 20899.37 4899.93 7099.83 18
v192192099.56 4199.57 3999.55 14399.75 9599.11 20499.05 18299.61 14499.15 14799.88 3299.71 10099.08 6399.87 17099.90 299.97 3099.66 75
UA-Net99.78 1399.76 1499.86 1699.72 10899.71 6599.91 399.95 499.96 299.71 10099.91 1999.15 5399.97 1799.50 32100.00 199.90 4
v119299.57 3899.57 3999.57 13699.77 8099.22 19099.04 18499.60 15599.18 13899.87 3899.72 9399.08 6399.85 20899.89 599.98 2199.66 75
FC-MVSNet-test99.70 1999.65 2399.86 1699.88 2499.86 1199.72 1999.78 5899.90 799.82 5099.83 4398.45 14899.87 17099.51 3099.97 3099.86 11
v114499.54 4699.53 4999.59 12799.79 6699.28 17399.10 17299.61 14499.20 13699.84 4399.73 8798.67 11699.84 22599.86 899.98 2199.64 90
sosnet-low-res8.33 33811.11 3410.00 3500.00 3710.00 3720.00 3620.00 3720.00 3670.00 368100.00 10.00 3730.00 3680.00 3660.00 3660.00 364
HFP-MVS99.25 11399.08 13699.76 4699.73 10499.70 7299.31 10499.59 16298.36 23399.36 20799.37 24798.80 9699.91 10897.43 22799.75 17599.68 58
v14899.40 7699.41 6599.39 19499.76 8498.94 22399.09 17699.59 16299.17 14199.81 5799.61 16998.41 15299.69 30699.32 5699.94 6299.53 158
sosnet8.33 33811.11 3410.00 3500.00 3710.00 3720.00 3620.00 3720.00 3670.00 368100.00 10.00 3730.00 3680.00 3660.00 3660.00 364
uncertanet8.33 33811.11 3410.00 3500.00 3710.00 3720.00 3620.00 3720.00 3670.00 368100.00 10.00 3730.00 3680.00 3660.00 3660.00 364
AllTest99.21 13199.07 14099.63 11199.78 7299.64 9099.12 16999.83 3298.63 20599.63 12599.72 9398.68 11399.75 28796.38 28999.83 13399.51 170
TestCases99.63 11199.78 7299.64 9099.83 3298.63 20599.63 12599.72 9398.68 11399.75 28796.38 28999.83 13399.51 170
v7n99.82 1099.80 1099.88 1199.96 499.84 1899.82 899.82 3799.84 2399.94 1199.91 1999.13 5799.96 3599.83 999.99 1299.83 18
region2R99.23 11799.05 14699.77 4099.76 8499.70 7299.31 10499.59 16298.41 22799.32 21799.36 25298.73 11099.93 7197.29 23499.74 18499.67 65
bset_n11_16_dypcd98.69 22098.45 22799.42 18199.69 12198.52 25496.06 35796.80 35299.71 4499.73 9399.54 20495.14 28299.96 3599.39 4599.95 4999.79 30
RRT_MVS98.75 21298.54 22099.41 18998.14 35898.61 24998.98 20099.66 11599.31 11999.84 4399.75 8091.98 31299.98 799.20 7299.95 4999.62 106
PS-MVSNAJss99.84 899.82 899.89 799.96 499.77 4199.68 3199.85 2499.95 399.98 399.92 1699.28 4199.98 799.75 13100.00 199.94 2
PS-MVSNAJ99.00 17999.08 13698.76 28399.37 24398.10 28098.00 30299.51 20999.47 9499.41 19898.50 34999.28 4199.97 1798.83 11699.34 28498.20 342
jajsoiax99.89 399.89 399.89 799.96 499.78 3999.70 2299.86 2099.89 1199.98 399.90 2199.94 199.98 799.75 13100.00 199.90 4
mvs_tets99.90 299.90 299.90 499.96 499.79 3699.72 1999.88 1699.92 699.98 399.93 1399.94 199.98 799.77 12100.00 199.92 3
#test#99.12 15398.90 18399.76 4699.73 10499.70 7299.10 17299.59 16297.60 28399.36 20799.37 24798.80 9699.91 10896.84 26599.75 17599.68 58
EI-MVSNet-UG-set99.48 5499.50 5199.42 18199.57 16498.65 24899.24 12899.46 22899.68 5299.80 6099.66 13498.99 7299.89 14399.19 7499.90 8499.72 43
EI-MVSNet-Vis-set99.47 6099.49 5299.42 18199.57 16498.66 24599.24 12899.46 22899.67 5699.79 6599.65 13998.97 7599.89 14399.15 8399.89 9299.71 46
Regformer-399.41 7399.41 6599.40 19199.52 18698.70 24199.17 14999.44 23399.62 6899.75 8099.60 17698.90 8599.85 20898.89 11399.84 12399.65 83
Regformer-499.45 6399.44 5999.50 15699.52 18698.94 22399.17 14999.53 19899.64 6499.76 7599.60 17698.96 7899.90 12998.91 11299.84 12399.67 65
Regformer-199.32 10099.27 9899.47 16599.41 23298.95 22298.99 19699.48 22099.48 8999.66 11599.52 20998.78 10199.87 17098.36 14699.74 18499.60 119
Regformer-299.34 9499.27 9899.53 14999.41 23299.10 20898.99 19699.53 19899.47 9499.66 11599.52 20998.80 9699.89 14398.31 15299.74 18499.60 119
HPM-MVS++copyleft98.96 18698.70 20499.74 6299.52 18699.71 6598.86 21399.19 29498.47 22398.59 30499.06 30598.08 18599.91 10896.94 25799.60 23899.60 119
test_prior499.19 19798.00 302
XVS99.27 11099.11 12599.75 5699.71 11199.71 6599.37 9099.61 14499.29 12098.76 29299.47 22998.47 14499.88 15797.62 21499.73 19199.67 65
v124099.56 4199.58 3699.51 15399.80 5699.00 21599.00 19199.65 12699.15 14799.90 2299.75 8099.09 6099.88 15799.90 299.96 4299.67 65
test_prior398.62 22598.34 24099.46 16999.35 24799.22 19097.95 30999.39 25097.87 27198.05 33099.05 30697.90 19899.69 30695.99 30499.49 26299.48 186
pm-mvs199.79 1299.79 1199.78 3799.91 1599.83 2299.76 1399.87 1899.73 4099.89 2699.87 3199.63 1499.87 17099.54 2699.92 7499.63 95
test_prior297.95 30997.87 27198.05 33099.05 30697.90 19895.99 30499.49 262
X-MVStestdata96.09 32294.87 33299.75 5699.71 11199.71 6599.37 9099.61 14499.29 12098.76 29261.30 37098.47 14499.88 15797.62 21499.73 19199.67 65
test_prior99.46 16999.35 24799.22 19099.39 25099.69 30699.48 186
旧先验297.94 31195.33 33798.94 26899.88 15796.75 269
新几何298.04 298
新几何199.52 15099.50 19899.22 19099.26 28195.66 33498.60 30399.28 27197.67 21699.89 14395.95 30899.32 28799.45 197
旧先验199.49 20399.29 17199.26 28199.39 24597.67 21699.36 28299.46 195
无先验98.01 30099.23 28895.83 33099.85 20895.79 31399.44 202
原ACMM297.92 313
原ACMM199.37 20199.47 21498.87 23499.27 27996.74 31898.26 31999.32 26297.93 19699.82 24695.96 30799.38 27799.43 208
test22299.51 19199.08 21197.83 31899.29 27595.21 33998.68 29899.31 26497.28 23699.38 27799.43 208
testdata299.89 14395.99 304
segment_acmp98.37 158
testdata99.42 18199.51 19198.93 22799.30 27396.20 32598.87 27999.40 24198.33 16499.89 14396.29 29299.28 29199.44 202
testdata197.72 32197.86 274
v899.68 2399.69 1899.65 10099.80 5699.40 14799.66 3999.76 6699.64 6499.93 1499.85 3798.66 11899.84 22599.88 699.99 1299.71 46
131498.00 27797.90 27898.27 30598.90 32097.45 30499.30 10799.06 30494.98 34197.21 35199.12 29998.43 14999.67 32295.58 31898.56 33097.71 350
112198.56 23498.24 24899.52 15099.49 20399.24 18699.30 10799.22 28995.77 33198.52 30999.29 26997.39 23199.85 20895.79 31399.34 28499.46 195
LFMVS98.46 24898.19 25599.26 22499.24 28098.52 25499.62 4796.94 35199.87 1499.31 22199.58 18491.04 32399.81 26298.68 13299.42 27399.45 197
VDD-MVS99.20 13399.11 12599.44 17599.43 22698.98 21799.50 6898.32 33599.80 3299.56 15599.69 11396.99 24999.85 20898.99 9999.73 19199.50 176
VDDNet98.97 18398.82 19399.42 18199.71 11198.81 23599.62 4798.68 31999.81 2999.38 20599.80 5494.25 29199.85 20898.79 12099.32 28799.59 128
v1099.69 2199.69 1899.66 9599.81 5199.39 14999.66 3999.75 7399.60 7899.92 1899.87 3198.75 10799.86 19099.90 299.99 1299.73 42
VPNet99.46 6199.37 7299.71 8099.82 4499.59 10799.48 7299.70 9799.81 2999.69 10599.58 18497.66 22099.86 19099.17 7999.44 26899.67 65
MVS95.72 33094.63 33498.99 25598.56 34597.98 29099.30 10798.86 31172.71 36397.30 34899.08 30398.34 16299.74 28989.21 35498.33 33599.26 243
v2v48299.50 5099.47 5399.58 13199.78 7299.25 18199.14 15999.58 17199.25 12899.81 5799.62 16098.24 17099.84 22599.83 999.97 3099.64 90
V4299.56 4199.54 4499.63 11199.79 6699.46 12899.39 8499.59 16299.24 13099.86 3999.70 10798.55 13199.82 24699.79 1199.95 4999.60 119
SD-MVS99.01 17799.30 8898.15 30799.50 19899.40 14798.94 20699.61 14499.22 13599.75 8099.82 4999.54 2195.51 36597.48 22499.87 10999.54 153
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
GA-MVS97.99 27897.68 28698.93 26299.52 18698.04 28497.19 34599.05 30598.32 24498.81 28598.97 32289.89 33999.41 35698.33 15099.05 30499.34 230
MSLP-MVS++99.05 16799.09 13498.91 26599.21 28498.36 26698.82 22299.47 22498.85 18398.90 27599.56 19598.78 10199.09 35998.57 13699.68 20999.26 243
APDe-MVS99.48 5499.36 7599.85 1899.55 17599.81 2999.50 6899.69 10398.99 16399.75 8099.71 10098.79 9999.93 7198.46 14199.85 11999.80 24
APD-MVS_3200maxsize99.31 10299.16 11199.74 6299.53 18199.75 5099.27 11899.61 14499.19 13799.57 14899.64 14198.76 10599.90 12997.29 23499.62 22899.56 142
ADS-MVSNet297.78 28297.66 28898.12 30999.14 29595.36 33799.22 13598.75 31796.97 31098.25 32099.64 14190.90 32699.94 5796.51 28299.56 24399.08 282
EI-MVSNet99.38 8299.44 5999.21 23299.58 15498.09 28199.26 12099.46 22899.62 6899.75 8099.67 13098.54 13399.85 20899.15 8399.92 7499.68 58
Regformer8.33 33811.11 3410.00 3500.00 3710.00 3720.00 3620.00 3720.00 3670.00 368100.00 10.00 3730.00 3680.00 3660.00 3660.00 364
CVMVSNet98.61 22698.88 18597.80 31699.58 15493.60 34999.26 12099.64 13299.66 6099.72 9599.67 13093.26 30099.93 7199.30 5999.81 15099.87 9
pmmvs499.13 15199.06 14299.36 20499.57 16499.10 20898.01 30099.25 28498.78 19399.58 14599.44 23698.24 17099.76 28398.74 12699.93 7099.22 251
EU-MVSNet99.39 8099.62 2698.72 28599.88 2496.44 32499.56 6499.85 2499.90 799.90 2299.85 3798.09 18399.83 23699.58 2399.95 4999.90 4
VNet99.18 14099.06 14299.56 14099.24 28099.36 15899.33 9799.31 27099.67 5699.47 17999.57 19296.48 25999.84 22599.15 8399.30 28999.47 191
test-LLR97.15 30096.95 30497.74 31998.18 35595.02 34097.38 33796.10 35398.00 26097.81 34198.58 34290.04 33799.91 10897.69 21298.78 31798.31 334
TESTMET0.1,196.24 32095.84 32297.41 32698.24 35393.84 34897.38 33795.84 35798.43 22497.81 34198.56 34579.77 36599.89 14397.77 19998.77 31998.52 325
test-mter96.23 32195.73 32497.74 31998.18 35595.02 34097.38 33796.10 35397.90 26997.81 34198.58 34279.12 36899.91 10897.69 21298.78 31798.31 334
VPA-MVSNet99.66 2599.62 2699.79 3499.68 13099.75 5099.62 4799.69 10399.85 2099.80 6099.81 5298.81 9299.91 10899.47 3499.88 10099.70 49
ACMMPR99.23 11799.06 14299.76 4699.74 10199.69 7699.31 10499.59 16298.36 23399.35 20999.38 24698.61 12499.93 7197.43 22799.75 17599.67 65
testgi99.29 10599.26 10099.37 20199.75 9598.81 23598.84 21699.89 1398.38 23199.75 8099.04 30999.36 3499.86 19099.08 9399.25 29599.45 197
test20.0399.55 4499.54 4499.58 13199.79 6699.37 15599.02 18799.89 1399.60 7899.82 5099.62 16098.81 9299.89 14399.43 3799.86 11699.47 191
thres600view796.60 31396.16 31597.93 31299.63 14296.09 33099.18 14497.57 34598.77 19498.72 29597.32 36487.04 34799.72 29488.57 35598.62 32897.98 347
ADS-MVSNet97.72 28697.67 28797.86 31499.14 29594.65 34399.22 13598.86 31196.97 31098.25 32099.64 14190.90 32699.84 22596.51 28299.56 24399.08 282
MP-MVScopyleft99.06 16498.83 19299.76 4699.76 8499.71 6599.32 10099.50 21398.35 23898.97 26599.48 22498.37 15899.92 9095.95 30899.75 17599.63 95
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs28.94 33533.33 33715.79 34926.03 3699.81 37196.77 35315.67 37011.55 36623.87 36750.74 37319.03 3728.53 36723.21 36533.07 36429.03 363
thres40096.40 31595.89 31997.92 31399.58 15496.11 32899.00 19197.54 34898.43 22498.52 30996.98 36786.85 34999.67 32287.62 35898.51 33297.98 347
test12329.31 33433.05 33918.08 34825.93 37012.24 37097.53 33110.93 37111.78 36524.21 36650.08 37421.04 3718.60 36623.51 36432.43 36533.39 362
thres20096.09 32295.68 32597.33 32999.48 20996.22 32798.53 25597.57 34598.06 25998.37 31696.73 36986.84 35199.61 34186.99 36198.57 32996.16 359
test0.0.03 197.37 29696.91 30798.74 28497.72 35997.57 30097.60 32797.36 35098.00 26099.21 23998.02 35690.04 33799.79 27098.37 14595.89 36098.86 307
pmmvs398.08 27397.80 28098.91 26599.41 23297.69 29897.87 31699.66 11595.87 32999.50 17599.51 21390.35 33499.97 1798.55 13799.47 26599.08 282
EMVS96.96 30597.28 29395.99 34598.76 33991.03 36395.26 36098.61 32399.34 11498.92 27298.88 33293.79 29699.66 32692.87 34699.05 30497.30 355
E-PMN97.14 30297.43 29096.27 34298.79 33591.62 36095.54 35999.01 30899.44 10198.88 27699.12 29992.78 30599.68 31794.30 33799.03 30697.50 351
PGM-MVS99.20 13399.01 15899.77 4099.75 9599.71 6599.16 15599.72 9097.99 26299.42 19099.60 17698.81 9299.93 7196.91 25999.74 18499.66 75
LCM-MVSNet-Re99.28 10699.15 11499.67 8899.33 26299.76 4799.34 9599.97 298.93 17399.91 2099.79 6098.68 11399.93 7196.80 26799.56 24399.30 237
LCM-MVSNet99.95 199.95 199.95 199.99 199.99 199.95 299.97 299.99 1100.00 199.98 899.78 6100.00 199.92 1100.00 199.87 9
MCST-MVS99.02 17398.81 19499.65 10099.58 15499.49 12198.58 24599.07 30298.40 22999.04 26299.25 27898.51 14299.80 26797.31 23399.51 25899.65 83
mvs_anonymous99.28 10699.39 6798.94 25999.19 28997.81 29399.02 18799.55 18499.78 3599.85 4099.80 5498.24 17099.86 19099.57 2499.50 26099.15 266
MVS_Test99.28 10699.31 8399.19 23599.35 24798.79 23799.36 9399.49 21899.17 14199.21 23999.67 13098.78 10199.66 32699.09 9299.66 22099.10 276
MDA-MVSNet-bldmvs99.06 16499.05 14699.07 25099.80 5697.83 29298.89 20899.72 9099.29 12099.63 12599.70 10796.47 26099.89 14398.17 16799.82 14299.50 176
CDPH-MVS98.56 23498.20 25299.61 12399.50 19899.46 12898.32 27299.41 24095.22 33899.21 23999.10 30298.34 16299.82 24695.09 32899.66 22099.56 142
test1299.54 14799.29 27099.33 16599.16 29798.43 31497.54 22499.82 24699.47 26599.48 186
casdiffmvs99.63 3199.61 3099.67 8899.79 6699.59 10799.13 16599.85 2499.79 3499.76 7599.72 9399.33 3699.82 24699.21 6999.94 6299.59 128
diffmvs99.34 9499.32 8299.39 19499.67 13598.77 23898.57 24999.81 4699.61 7299.48 17799.41 23998.47 14499.86 19098.97 10399.90 8499.53 158
baseline296.83 30796.28 31398.46 29599.09 30796.91 31798.83 21893.87 36497.23 30296.23 35898.36 35188.12 34399.90 12996.68 27398.14 34298.57 323
baseline197.73 28497.33 29298.96 25799.30 26897.73 29699.40 8298.42 33199.33 11799.46 18299.21 28791.18 32199.82 24698.35 14891.26 36299.32 234
YYNet198.95 18998.99 16698.84 27599.64 14097.14 31298.22 28099.32 26698.92 17599.59 14399.66 13497.40 22999.83 23698.27 15599.90 8499.55 145
PMMVS299.48 5499.45 5799.57 13699.76 8498.99 21698.09 29299.90 1298.95 16999.78 6899.58 18499.57 2099.93 7199.48 3399.95 4999.79 30
MDA-MVSNet_test_wron98.95 18998.99 16698.85 27399.64 14097.16 31198.23 27999.33 26498.93 17399.56 15599.66 13497.39 23199.83 23698.29 15399.88 10099.55 145
tpmvs97.39 29597.69 28596.52 34098.41 34891.76 35899.30 10798.94 31097.74 27797.85 34099.55 20292.40 31199.73 29296.25 29498.73 32598.06 345
PM-MVS99.36 8799.29 9399.58 13199.83 3899.66 8398.95 20499.86 2098.85 18399.81 5799.73 8798.40 15699.92 9098.36 14699.83 13399.17 262
HQP_MVS98.90 19498.68 20699.55 14399.58 15499.24 18698.80 22699.54 18998.94 17099.14 25099.25 27897.24 23799.82 24695.84 31199.78 16699.60 119
plane_prior799.58 15499.38 152
plane_prior699.47 21499.26 17797.24 237
plane_prior599.54 18999.82 24695.84 31199.78 16699.60 119
plane_prior499.25 278
plane_prior399.31 16898.36 23399.14 250
plane_prior298.80 22698.94 170
plane_prior199.51 191
plane_prior99.24 18698.42 26697.87 27199.71 201
PS-CasMVS99.66 2599.58 3699.89 799.80 5699.85 1299.66 3999.73 8199.62 6899.84 4399.71 10098.62 12299.96 3599.30 5999.96 4299.86 11
UniMVSNet_NR-MVSNet99.37 8499.25 10299.72 7699.47 21499.56 11398.97 20299.61 14499.43 10699.67 11199.28 27197.85 20499.95 4599.17 7999.81 15099.65 83
PEN-MVS99.66 2599.59 3399.89 799.83 3899.87 899.66 3999.73 8199.70 4899.84 4399.73 8798.56 13099.96 3599.29 6299.94 6299.83 18
TransMVSNet (Re)99.78 1399.77 1299.81 2699.91 1599.85 1299.75 1499.86 2099.70 4899.91 2099.89 2599.60 1999.87 17099.59 2099.74 18499.71 46
DTE-MVSNet99.68 2399.61 3099.88 1199.80 5699.87 899.67 3599.71 9399.72 4399.84 4399.78 6698.67 11699.97 1799.30 5999.95 4999.80 24
DU-MVS99.33 9899.21 10699.71 8099.43 22699.56 11398.83 21899.53 19899.38 11099.67 11199.36 25297.67 21699.95 4599.17 7999.81 15099.63 95
UniMVSNet (Re)99.37 8499.26 10099.68 8699.51 19199.58 11098.98 20099.60 15599.43 10699.70 10299.36 25297.70 21199.88 15799.20 7299.87 10999.59 128
CP-MVSNet99.54 4699.43 6299.87 1499.76 8499.82 2699.57 6299.61 14499.54 8299.80 6099.64 14197.79 20899.95 4599.21 6999.94 6299.84 14
WR-MVS_H99.61 3699.53 4999.87 1499.80 5699.83 2299.67 3599.75 7399.58 8199.85 4099.69 11398.18 17999.94 5799.28 6499.95 4999.83 18
WR-MVS99.11 15798.93 17599.66 9599.30 26899.42 14298.42 26699.37 25799.04 16199.57 14899.20 28996.89 25199.86 19098.66 13399.87 10999.70 49
NR-MVSNet99.40 7699.31 8399.68 8699.43 22699.55 11699.73 1699.50 21399.46 9899.88 3299.36 25297.54 22499.87 17098.97 10399.87 10999.63 95
Baseline_NR-MVSNet99.49 5299.37 7299.82 2399.91 1599.84 1898.83 21899.86 2099.68 5299.65 11999.88 2897.67 21699.87 17099.03 9699.86 11699.76 37
TranMVSNet+NR-MVSNet99.54 4699.47 5399.76 4699.58 15499.64 9099.30 10799.63 13499.61 7299.71 10099.56 19598.76 10599.96 3599.14 8999.92 7499.68 58
TSAR-MVS + GP.99.12 15399.04 15299.38 19899.34 25799.16 19998.15 28499.29 27598.18 25399.63 12599.62 16099.18 5099.68 31798.20 16199.74 18499.30 237
abl_699.36 8799.23 10599.75 5699.71 11199.74 5699.33 9799.76 6699.07 15699.65 11999.63 15199.09 6099.92 9097.13 25099.76 17299.58 133
n20.00 372
nn0.00 372
mPP-MVS99.19 13699.00 16199.76 4699.76 8499.68 7999.38 8699.54 18998.34 24299.01 26399.50 21698.53 13799.93 7197.18 24799.78 16699.66 75
door-mid99.83 32
XVG-OURS-SEG-HR99.16 14598.99 16699.66 9599.84 3499.64 9098.25 27899.73 8198.39 23099.63 12599.43 23799.70 1199.90 12997.34 23198.64 32799.44 202
DWT-MVSNet_test96.03 32495.80 32396.71 33998.50 34791.93 35799.25 12797.87 34295.99 32896.81 35497.61 36181.02 36299.66 32697.20 24697.98 34598.54 324
MVSFormer99.41 7399.44 5999.31 21599.57 16498.40 26299.77 1199.80 4799.73 4099.63 12599.30 26698.02 18999.98 799.43 3799.69 20699.55 145
jason99.16 14599.11 12599.32 21299.75 9598.44 25998.26 27799.39 25098.70 20099.74 8999.30 26698.54 13399.97 1798.48 14099.82 14299.55 145
jason: jason.
lupinMVS98.96 18698.87 18699.24 22999.57 16498.40 26298.12 28899.18 29598.28 24699.63 12599.13 29498.02 18999.97 1798.22 15999.69 20699.35 228
test_djsdf99.84 899.81 999.91 299.94 1099.84 1899.77 1199.80 4799.73 4099.97 699.92 1699.77 799.98 799.43 37100.00 199.90 4
HPM-MVS_fast99.43 6699.30 8899.80 2999.83 3899.81 2999.52 6699.70 9798.35 23899.51 17499.50 21699.31 3799.88 15798.18 16599.84 12399.69 52
RRT_test8_iter0597.35 29897.25 29597.63 32198.81 33393.13 35199.26 12099.89 1399.51 8699.83 4899.68 12479.03 36999.88 15799.53 2899.72 19799.89 8
K. test v398.87 20098.60 21099.69 8599.93 1399.46 12899.74 1594.97 35999.78 3599.88 3299.88 2893.66 29899.97 1799.61 1899.95 4999.64 90
lessismore_v099.64 10799.86 3099.38 15290.66 36699.89 2699.83 4394.56 28999.97 1799.56 2599.92 7499.57 139
SixPastTwentyTwo99.42 6999.30 8899.76 4699.92 1499.67 8199.70 2299.14 29999.65 6299.89 2699.90 2196.20 27099.94 5799.42 4399.92 7499.67 65
OurMVSNet-221017-099.75 1599.71 1699.84 1999.96 499.83 2299.83 699.85 2499.80 3299.93 1499.93 1398.54 13399.93 7199.59 2099.98 2199.76 37
HPM-MVScopyleft99.25 11399.07 14099.78 3799.81 5199.75 5099.61 5399.67 11197.72 27899.35 20999.25 27899.23 4699.92 9097.21 24599.82 14299.67 65
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
XVG-OURS99.21 13199.06 14299.65 10099.82 4499.62 9697.87 31699.74 7898.36 23399.66 11599.68 12499.71 999.90 12996.84 26599.88 10099.43 208
XVG-ACMP-BASELINE99.23 11799.10 13399.63 11199.82 4499.58 11098.83 21899.72 9098.36 23399.60 14099.71 10098.92 8099.91 10897.08 25299.84 12399.40 214
LPG-MVS_test99.22 12699.05 14699.74 6299.82 4499.63 9499.16 15599.73 8197.56 28499.64 12199.69 11399.37 3199.89 14396.66 27599.87 10999.69 52
LGP-MVS_train99.74 6299.82 4499.63 9499.73 8197.56 28499.64 12199.69 11399.37 3199.89 14396.66 27599.87 10999.69 52
baseline99.63 3199.62 2699.66 9599.80 5699.62 9699.44 7899.80 4799.71 4499.72 9599.69 11399.15 5399.83 23699.32 5699.94 6299.53 158
test1199.29 275
door99.77 61
EPNet_dtu97.62 28897.79 28297.11 33496.67 36392.31 35598.51 25798.04 33799.24 13095.77 35999.47 22993.78 29799.66 32698.98 10199.62 22899.37 222
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CHOSEN 1792x268899.39 8099.30 8899.65 10099.88 2499.25 18198.78 23099.88 1698.66 20299.96 899.79 6097.45 22799.93 7199.34 5199.99 1299.78 32
EPNet98.13 27097.77 28399.18 23794.57 36697.99 28599.24 12897.96 33999.74 3997.29 34999.62 16093.13 30299.97 1798.59 13599.83 13399.58 133
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
HQP5-MVS98.94 223
HQP-NCC99.31 26497.98 30597.45 29198.15 324
ACMP_Plane99.31 26497.98 30597.45 29198.15 324
APD-MVScopyleft98.87 20098.59 21299.71 8099.50 19899.62 9699.01 18999.57 17396.80 31799.54 16299.63 15198.29 16699.91 10895.24 32599.71 20199.61 115
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
BP-MVS94.73 331
HQP4-MVS98.15 32499.70 30099.53 158
HQP3-MVS99.37 25799.67 216
HQP2-MVS96.67 254
CNVR-MVS98.99 18298.80 19699.56 14099.25 27899.43 13998.54 25499.27 27998.58 21098.80 28799.43 23798.53 13799.70 30097.22 24499.59 24099.54 153
NCCC98.82 20598.57 21699.58 13199.21 28499.31 16898.61 24199.25 28498.65 20398.43 31499.26 27697.86 20299.81 26296.55 27999.27 29499.61 115
114514_t98.49 24598.11 26099.64 10799.73 10499.58 11099.24 12899.76 6689.94 35799.42 19099.56 19597.76 21099.86 19097.74 20299.82 14299.47 191
CP-MVS99.23 11799.05 14699.75 5699.66 13699.66 8399.38 8699.62 13798.38 23199.06 26199.27 27398.79 9999.94 5797.51 22399.82 14299.66 75
DSMNet-mixed99.48 5499.65 2398.95 25899.71 11197.27 30899.50 6899.82 3799.59 8099.41 19899.85 3799.62 16100.00 199.53 2899.89 9299.59 128
tpm296.35 31796.22 31496.73 33798.88 32691.75 35999.21 13798.51 32793.27 35097.89 33799.21 28784.83 35799.70 30096.04 30198.18 34198.75 314
NP-MVS99.40 23599.13 20298.83 334
EG-PatchMatch MVS99.57 3899.56 4399.62 12099.77 8099.33 16599.26 12099.76 6699.32 11899.80 6099.78 6699.29 3999.87 17099.15 8399.91 8399.66 75
tpm cat196.78 30896.98 30396.16 34498.85 32790.59 36699.08 17999.32 26692.37 35297.73 34699.46 23291.15 32299.69 30696.07 30098.80 31698.21 340
SteuartSystems-ACMMP99.30 10399.14 11599.76 4699.87 2899.66 8399.18 14499.60 15598.55 21399.57 14899.67 13099.03 7099.94 5797.01 25499.80 15599.69 52
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CostFormer96.71 31196.79 31096.46 34198.90 32090.71 36599.41 8198.68 31994.69 34798.14 32899.34 26086.32 35599.80 26797.60 21798.07 34498.88 305
CR-MVSNet98.35 25998.20 25298.83 27799.05 31098.12 27799.30 10799.67 11197.39 29599.16 24699.79 6091.87 31599.91 10898.78 12398.77 31998.44 331
JIA-IIPM98.06 27497.92 27598.50 29398.59 34497.02 31498.80 22698.51 32799.88 1397.89 33799.87 3191.89 31499.90 12998.16 16897.68 35098.59 320
Patchmtry98.78 20898.54 22099.49 15998.89 32399.19 19799.32 10099.67 11199.65 6299.72 9599.79 6091.87 31599.95 4598.00 17999.97 3099.33 231
PatchT98.45 24998.32 24398.83 27798.94 31898.29 26899.24 12898.82 31499.84 2399.08 25799.76 7691.37 31899.94 5798.82 11899.00 30898.26 337
tpmrst97.73 28498.07 26296.73 33798.71 34192.00 35699.10 17298.86 31198.52 21798.92 27299.54 20491.90 31399.82 24698.02 17599.03 30698.37 333
BH-w/o97.20 29997.01 30297.76 31799.08 30895.69 33498.03 29998.52 32695.76 33297.96 33498.02 35695.62 27999.47 35392.82 34797.25 35398.12 344
tpm97.15 30096.95 30497.75 31898.91 31994.24 34599.32 10097.96 33997.71 27998.29 31799.32 26286.72 35399.92 9098.10 17396.24 35999.09 279
DELS-MVS99.34 9499.30 8899.48 16399.51 19199.36 15898.12 28899.53 19899.36 11399.41 19899.61 16999.22 4799.87 17099.21 6999.68 20999.20 256
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
BH-untuned98.22 26898.09 26198.58 29199.38 24097.24 30998.55 25198.98 30997.81 27699.20 24498.76 33897.01 24899.65 33394.83 33098.33 33598.86 307
RPMNet98.60 22898.53 22298.83 27799.05 31098.12 27799.30 10799.62 13799.86 1699.16 24699.74 8392.53 30899.92 9098.75 12598.77 31998.44 331
MVSTER98.47 24798.22 25099.24 22999.06 30998.35 26799.08 17999.46 22899.27 12499.75 8099.66 13488.61 34299.85 20899.14 8999.92 7499.52 168
CPTT-MVS98.74 21498.44 22999.64 10799.61 14699.38 15299.18 14499.55 18496.49 32099.27 22799.37 24797.11 24599.92 9095.74 31599.67 21699.62 106
GBi-Net99.42 6999.31 8399.73 7099.49 20399.77 4199.68 3199.70 9799.44 10199.62 13299.83 4397.21 23999.90 12998.96 10599.90 8499.53 158
PVSNet_Blended_VisFu99.40 7699.38 6999.44 17599.90 1998.66 24598.94 20699.91 997.97 26499.79 6599.73 8799.05 6899.97 1799.15 8399.99 1299.68 58
PVSNet_BlendedMVS99.03 17199.01 15899.09 24699.54 17697.99 28598.58 24599.82 3797.62 28299.34 21299.71 10098.52 14099.77 28197.98 18099.97 3099.52 168
UnsupCasMVSNet_eth98.83 20398.57 21699.59 12799.68 13099.45 13398.99 19699.67 11199.48 8999.55 16099.36 25294.92 28399.86 19098.95 10996.57 35699.45 197
UnsupCasMVSNet_bld98.55 23798.27 24699.40 19199.56 17499.37 15597.97 30899.68 10697.49 29099.08 25799.35 25795.41 28199.82 24697.70 20698.19 34099.01 296
PVSNet_Blended98.70 21998.59 21299.02 25499.54 17697.99 28597.58 32899.82 3795.70 33399.34 21298.98 31998.52 14099.77 28197.98 18099.83 13399.30 237
FMVSNet597.80 28197.25 29599.42 18198.83 32998.97 21999.38 8699.80 4798.87 18199.25 22999.69 11380.60 36499.91 10898.96 10599.90 8499.38 219
test199.42 6999.31 8399.73 7099.49 20399.77 4199.68 3199.70 9799.44 10199.62 13299.83 4397.21 23999.90 12998.96 10599.90 8499.53 158
new_pmnet98.88 19898.89 18498.84 27599.70 11897.62 29998.15 28499.50 21397.98 26399.62 13299.54 20498.15 18099.94 5797.55 21999.84 12398.95 299
FMVSNet398.80 20798.63 20999.32 21299.13 29798.72 24099.10 17299.48 22099.23 13299.62 13299.64 14192.57 30699.86 19098.96 10599.90 8499.39 217
dp96.86 30697.07 30096.24 34398.68 34390.30 36799.19 14398.38 33497.35 29798.23 32299.59 18287.23 34599.82 24696.27 29398.73 32598.59 320
FMVSNet299.35 8999.28 9599.55 14399.49 20399.35 16299.45 7599.57 17399.44 10199.70 10299.74 8397.21 23999.87 17099.03 9699.94 6299.44 202
FMVSNet199.66 2599.63 2599.73 7099.78 7299.77 4199.68 3199.70 9799.67 5699.82 5099.83 4398.98 7399.90 12999.24 6699.97 3099.53 158
N_pmnet98.73 21698.53 22299.35 20599.72 10898.67 24398.34 26994.65 36098.35 23899.79 6599.68 12498.03 18799.93 7198.28 15499.92 7499.44 202
cascas96.99 30396.82 30997.48 32397.57 36295.64 33596.43 35699.56 17891.75 35397.13 35397.61 36195.58 28098.63 36296.68 27399.11 30198.18 343
BH-RMVSNet98.41 25298.14 25999.21 23299.21 28498.47 25698.60 24398.26 33698.35 23898.93 26999.31 26497.20 24299.66 32694.32 33699.10 30299.51 170
UGNet99.38 8299.34 7799.49 15998.90 32098.90 23199.70 2299.35 26199.86 1698.57 30699.81 5298.50 14399.93 7199.38 4699.98 2199.66 75
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
WTY-MVS98.59 23198.37 23699.26 22499.43 22698.40 26298.74 23499.13 30198.10 25599.21 23999.24 28394.82 28599.90 12997.86 19298.77 31999.49 181
XXY-MVS99.71 1899.67 2099.81 2699.89 2199.72 6399.59 5999.82 3799.39 10999.82 5099.84 4299.38 2999.91 10899.38 4699.93 7099.80 24
sss98.90 19498.77 19899.27 22299.48 20998.44 25998.72 23799.32 26697.94 26899.37 20699.35 25796.31 26799.91 10898.85 11599.63 22799.47 191
Test_1112_low_res98.95 18998.73 19999.63 11199.68 13099.15 20198.09 29299.80 4797.14 30799.46 18299.40 24196.11 27299.89 14399.01 9899.84 12399.84 14
1112_ss99.05 16798.84 19099.67 8899.66 13699.29 17198.52 25699.82 3797.65 28199.43 18899.16 29296.42 26299.91 10899.07 9499.84 12399.80 24
ab-mvs-re8.26 34411.02 3470.00 3500.00 3710.00 3720.00 3620.00 3720.00 3670.00 36899.16 2920.00 3730.00 3680.00 3660.00 3660.00 364
ab-mvs99.33 9899.28 9599.47 16599.57 16499.39 14999.78 1099.43 23798.87 18199.57 14899.82 4998.06 18699.87 17098.69 13199.73 19199.15 266
TR-MVS97.44 29497.15 29998.32 30198.53 34697.46 30398.47 26097.91 34196.85 31498.21 32398.51 34896.42 26299.51 35192.16 34897.29 35297.98 347
MDTV_nov1_ep13_2view91.44 36299.14 15997.37 29699.21 23991.78 31796.75 26999.03 291
MDTV_nov1_ep1397.73 28498.70 34290.83 36499.15 15798.02 33898.51 21898.82 28499.61 16990.98 32499.66 32696.89 26198.92 312
MIMVSNet199.66 2599.62 2699.80 2999.94 1099.87 899.69 2899.77 6199.78 3599.93 1499.89 2597.94 19599.92 9099.65 1699.98 2199.62 106
MIMVSNet98.43 25098.20 25299.11 24499.53 18198.38 26599.58 6198.61 32398.96 16899.33 21599.76 7690.92 32599.81 26297.38 23099.76 17299.15 266
IterMVS-LS99.41 7399.47 5399.25 22799.81 5198.09 28198.85 21599.76 6699.62 6899.83 4899.64 14198.54 13399.97 1799.15 8399.99 1299.68 58
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CDS-MVSNet99.22 12699.13 11899.50 15699.35 24799.11 20498.96 20399.54 18999.46 9899.61 13899.70 10796.31 26799.83 23699.34 5199.88 10099.55 145
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
ACMMP++_ref99.94 62
IterMVS98.97 18399.16 11198.42 29699.74 10195.64 33598.06 29799.83 3299.83 2699.85 4099.74 8396.10 27399.99 599.27 65100.00 199.63 95
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
DP-MVS Recon98.50 24298.23 24999.31 21599.49 20399.46 12898.56 25099.63 13494.86 34498.85 28199.37 24797.81 20699.59 34396.08 29999.44 26898.88 305
MVS_111021_LR99.13 15199.03 15499.42 18199.58 15499.32 16797.91 31599.73 8198.68 20199.31 22199.48 22499.09 6099.66 32697.70 20699.77 17099.29 240
DP-MVS99.48 5499.39 6799.74 6299.57 16499.62 9699.29 11499.61 14499.87 1499.74 8999.76 7698.69 11299.87 17098.20 16199.80 15599.75 40
ACMMP++99.79 160
HQP-MVS98.36 25698.02 26499.39 19499.31 26498.94 22397.98 30599.37 25797.45 29198.15 32498.83 33496.67 25499.70 30094.73 33199.67 21699.53 158
QAPM98.40 25497.99 26599.65 10099.39 23799.47 12499.67 3599.52 20691.70 35498.78 29099.80 5498.55 13199.95 4594.71 33399.75 17599.53 158
Vis-MVSNetpermissive99.75 1599.74 1599.79 3499.88 2499.66 8399.69 2899.92 699.67 5699.77 7399.75 8099.61 1799.98 799.35 5099.98 2199.72 43
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
MVS-HIRNet97.86 27998.22 25096.76 33599.28 27391.53 36198.38 26892.60 36599.13 14999.31 22199.96 1097.18 24399.68 31798.34 14999.83 13399.07 287
IS-MVSNet99.03 17198.85 18899.55 14399.80 5699.25 18199.73 1699.15 29899.37 11199.61 13899.71 10094.73 28799.81 26297.70 20699.88 10099.58 133
HyFIR lowres test98.91 19298.64 20799.73 7099.85 3399.47 12498.07 29599.83 3298.64 20499.89 2699.60 17692.57 306100.00 199.33 5499.97 3099.72 43
EPMVS96.53 31496.32 31297.17 33398.18 35592.97 35399.39 8489.95 36798.21 25098.61 30299.59 18286.69 35499.72 29496.99 25599.23 29998.81 311
PAPM_NR98.36 25698.04 26399.33 20899.48 20998.93 22798.79 22999.28 27897.54 28698.56 30798.57 34497.12 24499.69 30694.09 34098.90 31499.38 219
TAMVS99.49 5299.45 5799.63 11199.48 20999.42 14299.45 7599.57 17399.66 6099.78 6899.83 4397.85 20499.86 19099.44 3699.96 4299.61 115
PAPR97.56 29197.07 30099.04 25398.80 33498.11 27997.63 32599.25 28494.56 34898.02 33398.25 35497.43 22899.68 31790.90 35398.74 32399.33 231
RPSCF99.18 14099.02 15599.64 10799.83 3899.85 1299.44 7899.82 3798.33 24399.50 17599.78 6697.90 19899.65 33396.78 26899.83 13399.44 202
Vis-MVSNet (Re-imp)98.77 20998.58 21599.34 20699.78 7298.88 23299.61 5399.56 17899.11 15399.24 23299.56 19593.00 30499.78 27397.43 22799.89 9299.35 228
test_040299.22 12699.14 11599.45 17399.79 6699.43 13999.28 11599.68 10699.54 8299.40 20399.56 19599.07 6599.82 24696.01 30299.96 4299.11 274
MVS_111021_HR99.12 15399.02 15599.40 19199.50 19899.11 20497.92 31399.71 9398.76 19799.08 25799.47 22999.17 5199.54 34697.85 19499.76 17299.54 153
CSCG99.37 8499.29 9399.60 12599.71 11199.46 12899.43 8099.85 2498.79 19199.41 19899.60 17698.92 8099.92 9098.02 17599.92 7499.43 208
PatchMatch-RL98.68 22198.47 22599.30 21799.44 22499.28 17398.14 28699.54 18997.12 30899.11 25499.25 27897.80 20799.70 30096.51 28299.30 28998.93 301
API-MVS98.38 25598.39 23498.35 29998.83 32999.26 17799.14 15999.18 29598.59 20998.66 29998.78 33798.61 12499.57 34594.14 33999.56 24396.21 358
Test By Simon98.41 152
TDRefinement99.72 1799.70 1799.77 4099.90 1999.85 1299.86 599.92 699.69 5199.78 6899.92 1699.37 3199.88 15798.93 11199.95 4999.60 119
USDC98.96 18698.93 17599.05 25299.54 17697.99 28597.07 34999.80 4798.21 25099.75 8099.77 7398.43 14999.64 33597.90 18699.88 10099.51 170
EPP-MVSNet99.17 14499.00 16199.66 9599.80 5699.43 13999.70 2299.24 28799.48 8999.56 15599.77 7394.89 28499.93 7198.72 12899.89 9299.63 95
PMMVS98.49 24598.29 24599.11 24498.96 31798.42 26197.54 32999.32 26697.53 28798.47 31398.15 35597.88 20199.82 24697.46 22599.24 29799.09 279
PAPM95.61 33194.71 33398.31 30399.12 29996.63 32196.66 35598.46 33090.77 35696.25 35698.68 34193.01 30399.69 30681.60 36397.86 34998.62 318
ACMMPcopyleft99.25 11399.08 13699.74 6299.79 6699.68 7999.50 6899.65 12698.07 25899.52 16999.69 11398.57 12899.92 9097.18 24799.79 16099.63 95
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
CNLPA98.57 23398.34 24099.28 22099.18 29199.10 20898.34 26999.41 24098.48 22298.52 30998.98 31997.05 24799.78 27395.59 31799.50 26098.96 298
PatchmatchNetpermissive97.65 28797.80 28097.18 33298.82 33292.49 35499.17 14998.39 33398.12 25498.79 28899.58 18490.71 33099.89 14397.23 24399.41 27499.16 264
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PHI-MVS99.11 15798.95 17499.59 12799.13 29799.59 10799.17 14999.65 12697.88 27099.25 22999.46 23298.97 7599.80 26797.26 23999.82 14299.37 222
F-COLMAP98.74 21498.45 22799.62 12099.57 16499.47 12498.84 21699.65 12696.31 32498.93 26999.19 29197.68 21599.87 17096.52 28199.37 28199.53 158
ANet_high99.88 499.87 499.91 299.99 199.91 299.65 44100.00 199.90 7100.00 199.97 999.61 1799.97 1799.75 13100.00 199.84 14
wuyk23d97.58 29099.13 11892.93 34699.69 12199.49 12199.52 6699.77 6197.97 26499.96 899.79 6099.84 399.94 5795.85 31099.82 14279.36 361
OMC-MVS98.90 19498.72 20099.44 17599.39 23799.42 14298.58 24599.64 13297.31 29999.44 18499.62 16098.59 12699.69 30696.17 29899.79 16099.22 251
MG-MVS98.52 24098.39 23498.94 25999.15 29497.39 30698.18 28199.21 29398.89 18099.23 23399.63 15197.37 23399.74 28994.22 33899.61 23599.69 52
AdaColmapbinary98.60 22898.35 23999.38 19899.12 29999.22 19098.67 24099.42 23997.84 27598.81 28599.27 27397.32 23599.81 26295.14 32699.53 25599.10 276
uanet8.33 33811.11 3410.00 3500.00 3710.00 3720.00 3620.00 3720.00 3670.00 368100.00 10.00 3730.00 3680.00 3660.00 3660.00 364
ITE_SJBPF99.38 19899.63 14299.44 13599.73 8198.56 21199.33 21599.53 20798.88 8799.68 31796.01 30299.65 22399.02 295
DeepMVS_CXcopyleft97.98 31099.69 12196.95 31599.26 28175.51 36295.74 36098.28 35396.47 26099.62 33791.23 35197.89 34797.38 353
TinyColmap98.97 18398.93 17599.07 25099.46 21998.19 27397.75 32099.75 7398.79 19199.54 16299.70 10798.97 7599.62 33796.63 27799.83 13399.41 212
MAR-MVS98.24 26697.92 27599.19 23598.78 33799.65 8899.17 14999.14 29995.36 33698.04 33298.81 33697.47 22699.72 29495.47 32199.06 30398.21 340
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
LF4IMVS99.01 17798.92 17999.27 22299.71 11199.28 17398.59 24499.77 6198.32 24499.39 20499.41 23998.62 12299.84 22596.62 27899.84 12398.69 315
MSDG99.08 16298.98 16999.37 20199.60 14899.13 20297.54 32999.74 7898.84 18699.53 16799.55 20299.10 5899.79 27097.07 25399.86 11699.18 260
LS3D99.24 11699.11 12599.61 12398.38 34999.79 3699.57 6299.68 10699.61 7299.15 24899.71 10098.70 11199.91 10897.54 22099.68 20999.13 273
CLD-MVS98.76 21198.57 21699.33 20899.57 16498.97 21997.53 33199.55 18496.41 32199.27 22799.13 29499.07 6599.78 27396.73 27199.89 9299.23 249
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
FPMVS96.32 31895.50 32698.79 28199.60 14898.17 27598.46 26598.80 31597.16 30696.28 35599.63 15182.19 36099.09 35988.45 35698.89 31599.10 276
Gipumacopyleft99.57 3899.59 3399.49 15999.98 399.71 6599.72 1999.84 3099.81 2999.94 1199.78 6698.91 8299.71 29898.41 14399.95 4999.05 289
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015