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
DeepC-MVS_fast96.59 198.81 2298.54 2699.62 1599.90 4298.85 2999.24 21998.47 10398.14 499.08 7999.91 1393.09 116100.00 199.04 5499.99 20100.00 1
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
DeepPCF-MVS95.94 297.71 8598.98 1093.92 26799.63 8881.76 34299.96 2598.56 7799.47 199.19 7699.99 194.16 87100.00 199.92 999.93 63100.00 1
PLCcopyleft95.54 397.93 7297.89 6998.05 13699.82 6594.77 19099.92 6898.46 10593.93 12897.20 14099.27 12995.44 4499.97 5197.41 12599.51 10899.41 161
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
DeepC-MVS94.51 496.92 11196.40 11798.45 11699.16 11095.90 15499.66 15698.06 18696.37 4794.37 19099.49 11083.29 23499.90 7597.63 12199.61 10199.55 140
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
PCF-MVS94.20 595.18 15994.10 17498.43 11898.55 14295.99 15297.91 30797.31 25790.35 23589.48 24899.22 13585.19 22099.89 7990.40 24598.47 13399.41 161
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
IB-MVS92.85 694.99 16493.94 17898.16 12997.72 19295.69 16599.99 598.81 4894.28 11292.70 21196.90 23095.08 5099.17 15696.07 14773.88 33799.60 130
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
HY-MVS92.50 797.79 8197.17 9499.63 1298.98 11899.32 697.49 31299.52 1395.69 6698.32 11597.41 21393.32 10799.77 11598.08 10395.75 19099.81 98
TAPA-MVS92.12 894.42 18193.60 18596.90 17499.33 10691.78 25299.78 12698.00 18989.89 24394.52 18799.47 11191.97 14299.18 15569.90 34699.52 10699.73 109
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
ACMP92.05 992.74 21792.42 21493.73 27195.91 25588.72 30099.81 11797.53 23294.13 11587.00 29098.23 19574.07 30598.47 18696.22 14688.86 23493.99 283
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
ACMM91.95 1092.88 21492.52 21293.98 26695.75 26189.08 29899.77 12997.52 23493.00 15589.95 23497.99 20376.17 29198.46 18993.63 19988.87 23394.39 244
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
3Dnovator+91.53 1196.31 13595.24 15199.52 2696.88 23298.64 4999.72 14898.24 16495.27 7688.42 27298.98 15182.76 23699.94 6897.10 13399.83 8199.96 70
3Dnovator91.47 1296.28 13895.34 14999.08 7196.82 23597.47 9799.45 19298.81 4895.52 7089.39 24999.00 14881.97 24099.95 6097.27 12899.83 8199.84 95
PVSNet91.05 1397.13 10396.69 10898.45 11699.52 9695.81 15799.95 4399.65 1094.73 9099.04 8199.21 13684.48 22599.95 6094.92 16098.74 12899.58 137
COLMAP_ROBcopyleft90.47 1492.18 23091.49 23294.25 25499.00 11788.04 31198.42 28996.70 31282.30 32988.43 27099.01 14676.97 28199.85 9486.11 28996.50 17494.86 230
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
OpenMVScopyleft90.15 1594.77 16993.59 18698.33 12396.07 24997.48 9699.56 17498.57 7590.46 23286.51 29698.95 15778.57 27499.94 6893.86 18799.74 9097.57 219
ACMH+89.98 1690.35 26789.54 26492.78 29395.99 25286.12 31998.81 26497.18 26689.38 24683.14 31997.76 20768.42 32698.43 19289.11 25686.05 26093.78 299
ACMH89.72 1790.64 26089.63 26193.66 27795.64 26888.64 30398.55 27997.45 24089.03 25181.62 32697.61 20969.75 32098.41 19489.37 25387.62 25193.92 289
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
LTVRE_ROB88.28 1890.29 27089.05 27594.02 26295.08 27690.15 28497.19 31797.43 24384.91 31483.99 31597.06 22574.00 30698.28 21084.08 29987.71 24993.62 306
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
PVSNet_088.03 1991.80 23990.27 25196.38 19398.27 15690.46 27899.94 5899.61 1193.99 12486.26 30397.39 21571.13 31799.89 7998.77 7467.05 34998.79 200
OpenMVS_ROBcopyleft79.82 2083.77 31681.68 31990.03 31788.30 34882.82 33298.46 28495.22 34373.92 35176.00 34591.29 33955.00 35496.94 28068.40 34988.51 24290.34 344
CMPMVSbinary61.59 2184.75 31085.14 30483.57 33590.32 34062.54 35996.98 32297.59 22674.33 35069.95 35396.66 24064.17 34098.32 20687.88 27088.41 24389.84 348
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
MVEpermissive53.74 2251.54 33347.86 33762.60 34559.56 36750.93 36479.41 36077.69 36735.69 36436.27 36661.76 3655.79 37469.63 36337.97 36436.61 36067.24 358
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
PMVScopyleft49.05 2353.75 33151.34 33560.97 34640.80 37034.68 37074.82 36189.62 36337.55 36228.67 36872.12 3587.09 37281.63 36143.17 36368.21 34766.59 359
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
eth-test20.00 373
eth-test0.00 373
GeoE94.36 18593.48 19096.99 17197.29 21593.54 21299.96 2596.72 31188.35 26993.43 20098.94 15882.05 23998.05 22588.12 26896.48 17599.37 165
test_method80.79 32079.70 32384.08 33492.83 31567.06 35799.51 18295.42 33854.34 35781.07 33093.53 32444.48 36092.22 34978.90 32777.23 32792.94 320
Anonymous2024052185.15 30883.81 30989.16 32288.32 34782.69 33398.80 26595.74 33179.72 33681.53 32790.99 34065.38 33794.16 33872.69 34281.11 29790.63 343
hse-mvs394.92 16594.36 16896.59 18598.85 13291.29 26498.93 25198.94 3695.90 5698.77 9398.42 19290.89 16199.77 11597.80 11370.76 33998.72 202
hse-mvs294.38 18294.08 17595.31 21598.27 15690.02 28699.29 21598.56 7795.90 5698.77 9398.00 20190.89 16198.26 21497.80 11369.20 34597.64 217
CL-MVSNet_2432*160084.50 31283.15 31488.53 32786.00 35281.79 34198.82 26397.35 25285.12 31083.62 31890.91 34276.66 28591.40 35169.53 34760.36 35492.40 328
KD-MVS_2432*160088.00 29586.10 29993.70 27596.91 22894.04 20097.17 31897.12 27284.93 31281.96 32392.41 33492.48 13094.51 33679.23 32352.68 35792.56 324
DIV-MVS_2432*160083.59 31782.06 31788.20 32986.93 35080.70 34797.21 31696.38 32082.87 32582.49 32188.97 34567.63 32992.32 34873.75 34162.30 35391.58 336
AUN-MVS93.28 20592.60 20795.34 21398.29 15290.09 28599.31 21098.56 7791.80 20396.35 16398.00 20189.38 17898.28 21092.46 21269.22 34497.64 217
ZD-MVS99.92 3598.57 5198.52 9092.34 18699.31 6699.83 4995.06 5299.80 10699.70 3099.97 44
test117298.38 5398.25 4798.77 9099.88 4996.56 12999.80 12298.36 14494.68 9299.20 7399.80 5893.28 11099.78 11199.34 4299.92 6799.98 51
SR-MVS-dyc-post98.31 5698.17 5298.71 9399.79 7096.37 13699.76 13498.31 15394.43 10299.40 6199.75 7793.28 11099.78 11198.90 6499.92 6799.97 63
RE-MVS-def98.13 5599.79 7096.37 13699.76 13498.31 15394.43 10299.40 6199.75 7792.95 11998.90 6499.92 6799.97 63
SED-MVS99.28 599.11 699.77 699.93 2699.30 899.96 2598.43 11697.27 2099.80 1699.94 496.71 20100.00 1100.00 1100.00 1100.00 1
IU-MVS99.93 2699.31 798.41 13197.71 899.84 8100.00 1100.00 1100.00 1
OPU-MVS99.93 299.89 4599.80 299.96 2599.80 5897.44 11100.00 1100.00 199.98 33100.00 1
test_241102_TWO98.43 11697.27 2099.80 1699.94 497.18 17100.00 1100.00 1100.00 1100.00 1
test_241102_ONE99.93 2699.30 898.43 11697.26 2299.80 1699.88 2296.71 20100.00 1
xxxxxxxxxxxxxcwj98.98 1498.79 1599.54 2399.82 6598.79 3399.96 2597.52 23497.66 1099.81 1299.89 1994.70 6599.86 9099.84 1399.93 6399.96 70
SF-MVS98.67 3098.40 3599.50 2999.77 7398.67 4499.90 7698.21 16893.53 14299.81 1299.89 1994.70 6599.86 9099.84 1399.93 6399.96 70
ETH3D cwj APD-0.1698.40 5198.07 5999.40 4199.59 9098.41 6099.86 10198.24 16492.18 19099.73 2799.87 2693.47 10399.85 9499.74 2499.95 5199.93 81
cl-mvsnet293.77 19593.25 19995.33 21499.49 9994.43 19499.61 16798.09 18390.38 23389.16 25895.61 26890.56 16597.34 25291.93 21784.45 27294.21 259
miper_ehance_all_eth93.16 20792.60 20794.82 23197.57 19893.56 21199.50 18497.07 28088.75 26088.85 26295.52 27490.97 15896.74 28990.77 23884.45 27294.17 261
miper_enhance_ethall94.36 18593.98 17795.49 20898.68 14095.24 17699.73 14597.29 25893.28 14989.86 23795.97 25994.37 7597.05 27292.20 21584.45 27294.19 260
ZNCC-MVS98.31 5698.03 6099.17 5799.88 4997.59 8799.94 5898.44 10894.31 11098.50 10799.82 5393.06 11799.99 3698.30 9499.99 2099.93 81
ETH3 D test640098.81 2298.54 2699.59 1899.93 2698.93 2299.93 6498.46 10594.56 9799.84 899.92 1194.32 8099.86 9099.96 899.98 33100.00 1
cl-mvsnet____92.31 22791.58 22894.52 24297.33 21292.77 22599.57 17296.78 30886.97 28787.56 28295.51 27589.43 17796.62 29588.60 25982.44 28594.16 266
cl-mvsnet192.32 22691.60 22794.47 24697.31 21392.74 22799.58 17096.75 30986.99 28687.64 28095.54 27289.55 17696.50 29988.58 26082.44 28594.17 261
eth_miper_zixun_eth92.41 22591.93 22293.84 27097.28 21690.68 27298.83 26296.97 29188.57 26589.19 25795.73 26589.24 18396.69 29389.97 25081.55 29194.15 268
9.1498.38 3899.87 5299.91 7298.33 14993.22 15099.78 2299.89 1994.57 6899.85 9499.84 1399.97 44
testtj98.89 1898.69 1899.52 2699.94 1498.56 5399.90 7698.55 8395.14 7899.72 3199.84 4695.46 43100.00 199.65 3299.99 2099.99 20
uanet_test0.00 3410.00 3440.00 3520.00 3730.00 3740.00 3640.00 3740.00 3690.00 3700.00 3700.00 3750.00 3700.00 3680.00 3680.00 366
ETH3D-3000-0.198.68 2998.42 3199.47 3499.83 6398.57 5199.90 7698.37 14293.81 13399.81 1299.90 1794.34 7699.86 9099.84 1399.98 3399.97 63
save fliter99.82 6598.79 3399.96 2598.40 13297.66 10
ET-MVSNet_ETH3D94.37 18393.28 19897.64 15198.30 15197.99 7499.99 597.61 22294.35 10771.57 35199.45 11496.23 2795.34 32696.91 14085.14 26899.59 131
UniMVSNet_ETH3D90.06 27688.58 28294.49 24594.67 28388.09 31097.81 30997.57 22783.91 32088.44 26897.41 21357.44 35297.62 24291.41 22388.59 24097.77 215
EIA-MVS97.53 8997.46 8297.76 14798.04 16994.84 18699.98 1097.61 22294.41 10597.90 12799.59 10292.40 13298.87 16398.04 10499.13 12299.59 131
miper_refine_blended88.00 29586.10 29993.70 27596.91 22894.04 20097.17 31897.12 27284.93 31281.96 32392.41 33492.48 13094.51 33679.23 32352.68 35792.56 324
miper_lstm_enhance91.81 23691.39 23493.06 28997.34 21089.18 29799.38 20196.79 30786.70 29087.47 28495.22 29290.00 17095.86 32188.26 26481.37 29394.15 268
ETV-MVS97.92 7397.80 7198.25 12798.14 16596.48 13099.98 1097.63 21795.61 6899.29 7099.46 11392.55 12998.82 16599.02 5698.54 13199.46 154
CS-MVS97.74 8397.61 7798.15 13297.52 20496.69 123100.00 197.11 27494.93 8299.73 2799.41 11891.68 14798.25 21598.84 6899.24 11999.52 147
D2MVS92.76 21692.59 21093.27 28395.13 27489.54 29499.69 15199.38 2192.26 18887.59 28194.61 31185.05 22297.79 23691.59 22288.01 24692.47 327
DVP-MVS99.30 499.16 399.73 899.93 2699.29 1099.95 4398.32 15197.28 1899.83 1099.91 1397.22 15100.00 199.99 5100.00 199.89 90
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_THIRD96.48 4099.83 1099.91 1397.87 4100.00 199.92 9100.00 1100.00 1
test_0728_SECOND99.82 599.94 1499.47 599.95 4398.43 116100.00 199.99 5100.00 1100.00 1
test072699.93 2699.29 1099.96 2598.42 12797.28 1899.86 499.94 497.22 15
SR-MVS98.46 4598.30 4698.93 8499.88 4997.04 11299.84 10898.35 14694.92 8399.32 6599.80 5893.35 10599.78 11199.30 4499.95 5199.96 70
DPM-MVS98.83 2198.46 3099.97 199.33 10699.92 199.96 2598.44 10897.96 799.55 4599.94 497.18 17100.00 193.81 19199.94 5799.98 51
GST-MVS98.27 5997.97 6499.17 5799.92 3597.57 8899.93 6498.39 13594.04 12398.80 9199.74 8192.98 118100.00 198.16 9799.76 8999.93 81
test_yl97.83 7797.37 8599.21 5199.18 10897.98 7599.64 16399.27 2591.43 21497.88 12898.99 14995.84 3599.84 10398.82 6995.32 19799.79 100
thisisatest053097.10 10496.72 10798.22 12897.60 19796.70 12299.92 6898.54 8791.11 22197.07 14498.97 15397.47 999.03 15893.73 19696.09 18098.92 192
Anonymous2024052992.10 23290.65 24396.47 18698.82 13390.61 27498.72 27098.67 5975.54 34793.90 19798.58 18266.23 33399.90 7594.70 17190.67 22198.90 195
Anonymous20240521193.10 20991.99 22196.40 19199.10 11289.65 29298.88 25697.93 19783.71 32194.00 19598.75 17268.79 32299.88 8595.08 15891.71 22099.68 115
DCV-MVSNet97.83 7797.37 8599.21 5199.18 10897.98 7599.64 16399.27 2591.43 21497.88 12898.99 14995.84 3599.84 10398.82 6995.32 19799.79 100
tttt051796.85 11296.49 11497.92 14097.48 20595.89 15699.85 10498.54 8790.72 23096.63 15398.93 16097.47 999.02 15993.03 20995.76 18998.85 196
our_test_390.39 26589.48 26893.12 28692.40 32089.57 29399.33 20796.35 32187.84 27485.30 30994.99 30084.14 22896.09 31580.38 32084.56 27193.71 305
thisisatest051597.41 9597.02 10098.59 10497.71 19497.52 9199.97 1898.54 8791.83 20097.45 13699.04 14397.50 899.10 15794.75 16896.37 17799.16 182
ppachtmachnet_test89.58 28388.35 28593.25 28492.40 32090.44 27999.33 20796.73 31085.49 30785.90 30795.77 26281.09 25196.00 31976.00 33882.49 28493.30 313
SMA-MVScopyleft98.76 2698.48 2999.62 1599.87 5298.87 2799.86 10198.38 13993.19 15199.77 2399.94 495.54 40100.00 199.74 2499.99 20100.00 1
Yufeng Yin; Xiaoyan Liu; Zichao Zhang: SMA-MVS: Segmentation-Guided Multi-Scale Anchor Deformation Patch Multi-View Stereo. IEEE Transactions on Circuits and Systems for Video Technology
GSMVS99.59 131
DPE-MVScopyleft99.26 699.10 799.74 799.89 4599.24 1499.87 9098.44 10897.48 1599.64 3699.94 496.68 2299.99 3699.99 5100.00 199.99 20
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
test_part299.89 4599.25 1399.49 51
test_part192.15 23190.72 24196.44 19098.87 13197.46 9898.99 24498.26 16285.89 29886.34 30196.34 25081.71 24297.48 24691.06 22978.99 31294.37 245
thres100view90096.74 11995.92 13599.18 5498.90 12898.77 3699.74 14099.71 592.59 17595.84 17098.86 16789.25 18199.50 14593.84 18894.57 20199.27 175
tfpnnormal89.29 28687.61 29394.34 25294.35 28794.13 19998.95 24998.94 3683.94 31884.47 31395.51 27574.84 30097.39 24977.05 33580.41 30491.48 337
tfpn200view996.79 11595.99 12599.19 5398.94 12198.82 3199.78 12699.71 592.86 15796.02 16798.87 16589.33 17999.50 14593.84 18894.57 20199.27 175
cl_fuxian92.53 22291.87 22494.52 24297.40 20792.99 22399.40 19696.93 29687.86 27388.69 26595.44 27889.95 17196.44 30190.45 24280.69 30394.14 271
CHOSEN 280x42099.01 1299.03 898.95 8399.38 10498.87 2798.46 28499.42 2097.03 2799.02 8299.09 14099.35 198.21 21799.73 2799.78 8899.77 104
CANet98.27 5997.82 7099.63 1299.72 8399.10 1799.98 1098.51 9797.00 2898.52 10599.71 8687.80 19499.95 6099.75 2299.38 11399.83 96
Fast-Effi-MVS+-dtu93.72 19893.86 18193.29 28297.06 22186.16 31899.80 12296.83 30392.66 17092.58 21297.83 20681.39 24797.67 24089.75 25296.87 16996.05 229
Effi-MVS+-dtu94.53 17995.30 15092.22 29797.77 18582.54 33599.59 16997.06 28194.92 8395.29 18095.37 28485.81 21297.89 23494.80 16597.07 16496.23 227
CANet_DTU96.76 11796.15 12198.60 10298.78 13697.53 9099.84 10897.63 21797.25 2399.20 7399.64 9981.36 24899.98 4292.77 21198.89 12498.28 206
MVS_030489.28 28788.31 28692.21 29897.05 22286.53 31797.76 31099.57 1285.58 30693.86 19892.71 33151.04 35896.30 30784.49 29892.72 21993.79 298
MP-MVS-pluss98.07 6897.64 7599.38 4499.74 7798.41 6099.74 14098.18 17393.35 14696.45 15899.85 3392.64 12799.97 5198.91 6399.89 7499.77 104
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
MSP-MVS99.09 899.12 598.98 8099.93 2697.24 10499.95 4398.42 12797.50 1499.52 5099.88 2297.43 1299.71 12999.50 3599.98 33100.00 1
Zhenlong Yuan, Cong Liu, Fei Shen, Zhaoxin Li, Jingguo luo, Tianlu Mao and Zhaoqi Wang: MSP-MVS: Multi-granularity Segmentation Prior Guided Multi-View Stereo. AAAI2025
sam_mvs194.72 6499.59 131
sam_mvs94.25 82
IterMVS-SCA-FT90.85 25690.16 25592.93 29096.72 24189.96 28798.89 25496.99 28788.95 25686.63 29495.67 26676.48 28795.00 33087.04 28084.04 27993.84 295
TSAR-MVS + MP.98.93 1598.77 1699.41 3999.74 7798.67 4499.77 12998.38 13996.73 3599.88 399.74 8194.89 6299.59 14099.80 1899.98 3399.97 63
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_debu97.43 9197.06 9598.55 10697.74 18898.14 6799.31 21097.86 20596.43 4199.62 4099.69 9185.56 21599.68 13399.05 5098.31 13797.83 212
OPM-MVS93.21 20692.80 20394.44 24893.12 30890.85 27099.77 12997.61 22296.19 5191.56 21798.65 17675.16 29998.47 18693.78 19489.39 22893.99 283
ACMMP_NAP98.49 4398.14 5499.54 2399.66 8798.62 5099.85 10498.37 14294.68 9299.53 4799.83 4992.87 120100.00 198.66 8299.84 8099.99 20
ambc83.23 33677.17 35962.61 35887.38 35794.55 35176.72 34386.65 35130.16 36296.36 30484.85 29769.86 34090.73 342
zzz-MVS98.33 5598.00 6299.30 4799.85 5597.93 7899.80 12298.28 15895.76 6297.18 14199.88 2292.74 124100.00 198.67 7999.88 7699.99 20
MTGPAbinary98.28 158
mvs-test195.53 15395.97 13094.20 25597.77 18585.44 32499.95 4397.06 28194.92 8396.58 15498.72 17385.81 21298.98 16094.80 16598.11 14198.18 207
CS-MVS-test97.85 7597.70 7398.30 12497.57 19896.72 121100.00 197.11 27495.06 7999.76 2499.45 11492.12 14098.44 19198.97 5799.28 11699.75 106
Effi-MVS+96.30 13695.69 14198.16 12997.85 18096.26 13997.41 31397.21 26390.37 23498.65 10198.58 18286.61 20798.70 17697.11 13297.37 15899.52 147
xiu_mvs_v2_base98.23 6397.97 6499.02 7798.69 13998.66 4699.52 18098.08 18597.05 2699.86 499.86 2990.65 16399.71 12999.39 4198.63 13098.69 203
xiu_mvs_v1_base97.43 9197.06 9598.55 10697.74 18898.14 6799.31 21097.86 20596.43 4199.62 4099.69 9185.56 21599.68 13399.05 5098.31 13797.83 212
new-patchmatchnet81.19 31979.34 32486.76 33282.86 35780.36 35097.92 30695.27 34282.09 33072.02 35086.87 35062.81 34490.74 35471.10 34463.08 35189.19 352
pmmvs685.69 30283.84 30891.26 30790.00 34384.41 32997.82 30896.15 32575.86 34581.29 32895.39 28261.21 34796.87 28483.52 30673.29 33892.50 326
pmmvs590.17 27489.09 27393.40 28092.10 32489.77 29199.74 14095.58 33685.88 30087.24 28995.74 26373.41 30896.48 30088.54 26183.56 28193.95 286
test_post195.78 33759.23 36793.20 11497.74 23891.06 229
test_post63.35 36494.43 6998.13 220
Fast-Effi-MVS+95.02 16394.19 17197.52 15597.88 17694.55 19299.97 1897.08 27888.85 25994.47 18997.96 20484.59 22498.41 19489.84 25197.10 16399.59 131
patchmatchnet-post91.70 33895.12 4897.95 231
Anonymous2023121189.86 27888.44 28494.13 25898.93 12390.68 27298.54 28198.26 16276.28 34386.73 29295.54 27270.60 31897.56 24390.82 23780.27 30794.15 268
pmmvs-eth3d84.03 31581.97 31890.20 31584.15 35587.09 31598.10 30294.73 34983.05 32374.10 34987.77 34865.56 33694.01 33981.08 31869.24 34389.49 350
GG-mvs-BLEND98.54 10998.21 16098.01 7393.87 34398.52 9097.92 12697.92 20599.02 297.94 23398.17 9699.58 10399.67 117
xiu_mvs_v1_base_debi97.43 9197.06 9598.55 10697.74 18898.14 6799.31 21097.86 20596.43 4199.62 4099.69 9185.56 21599.68 13399.05 5098.31 13797.83 212
Anonymous2023120686.32 30085.42 30289.02 32389.11 34680.53 34999.05 23995.28 34185.43 30882.82 32093.92 32074.40 30393.44 34666.99 35181.83 29093.08 318
MTAPA98.29 5897.96 6799.30 4799.85 5597.93 7899.39 20098.28 15895.76 6297.18 14199.88 2292.74 124100.00 198.67 7999.88 7699.99 20
MTMP99.87 9096.49 318
gm-plane-assit96.97 22693.76 20891.47 21298.96 15598.79 16794.92 160
test9_res99.71 2999.99 20100.00 1
MVP-Stereo90.93 25290.45 24792.37 29691.25 33488.76 29998.05 30496.17 32487.27 28184.04 31495.30 28778.46 27697.27 26083.78 30399.70 9491.09 338
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
TEST999.92 3598.92 2399.96 2598.43 11693.90 13099.71 3299.86 2995.88 3499.85 94
train_agg98.88 1998.65 2099.59 1899.92 3598.92 2399.96 2598.43 11694.35 10799.71 3299.86 2995.94 3199.85 9499.69 3199.98 3399.99 20
gg-mvs-nofinetune93.51 20191.86 22598.47 11497.72 19297.96 7792.62 34798.51 9774.70 34997.33 13869.59 36098.91 397.79 23697.77 11899.56 10499.67 117
SCA94.69 17193.81 18297.33 16597.10 21994.44 19398.86 26098.32 15193.30 14896.17 16695.59 27076.48 28797.95 23191.06 22997.43 15499.59 131
Patchmatch-test92.65 22191.50 23196.10 19996.85 23390.49 27791.50 35297.19 26482.76 32790.23 22995.59 27095.02 5498.00 22777.41 33296.98 16799.82 97
test_899.92 3598.88 2699.96 2598.43 11694.35 10799.69 3499.85 3395.94 3199.85 94
MS-PatchMatch90.65 25990.30 25091.71 30494.22 28985.50 32398.24 29597.70 21388.67 26286.42 29996.37 24967.82 32898.03 22683.62 30499.62 9891.60 335
Patchmatch-RL test86.90 29985.98 30189.67 31984.45 35475.59 35289.71 35592.43 35686.89 28877.83 34090.94 34194.22 8393.63 34487.75 27169.61 34199.79 100
cdsmvs_eth3d_5k23.43 33731.24 3400.00 3520.00 3730.00 3740.00 36498.09 1830.00 3690.00 37099.67 9583.37 2330.00 3700.00 3680.00 3680.00 366
pcd_1.5k_mvsjas7.60 34010.13 3430.00 3520.00 3730.00 3740.00 3640.00 3740.00 3690.00 3700.00 37091.20 1520.00 3700.00 3680.00 3680.00 366
agg_prior198.88 1998.66 1999.54 2399.93 2698.77 3699.96 2598.43 11694.63 9699.63 3899.85 3395.79 3799.85 9499.72 2899.99 2099.99 20
agg_prior299.48 36100.00 1100.00 1
agg_prior99.93 2698.77 3698.43 11699.63 3899.85 94
tmp_tt65.23 32962.94 33272.13 34244.90 36950.03 36581.05 35989.42 36438.45 36148.51 36399.90 1754.09 35578.70 36291.84 22018.26 36487.64 354
canonicalmvs97.09 10696.32 11899.39 4398.93 12398.95 2199.72 14897.35 25294.45 10097.88 12899.42 11686.71 20599.52 14298.48 8893.97 21099.72 111
anonymousdsp91.79 24190.92 23994.41 25190.76 33792.93 22498.93 25197.17 26789.08 24987.46 28595.30 28778.43 27796.92 28192.38 21388.73 23693.39 311
alignmvs97.81 7997.33 8899.25 4998.77 13798.66 4699.99 598.44 10894.40 10698.41 11099.47 11193.65 10099.42 15198.57 8594.26 20699.67 117
nrg03093.51 20192.53 21196.45 18894.36 28697.20 10699.81 11797.16 26991.60 20789.86 23797.46 21186.37 20997.68 23995.88 15180.31 30694.46 236
v14419290.79 25789.52 26594.59 23893.11 30992.77 22599.56 17496.99 28786.38 29389.82 24094.95 30280.50 26097.10 26983.98 30180.41 30493.90 290
FIs94.10 18893.43 19196.11 19894.70 28296.82 11999.58 17098.93 4092.54 17989.34 25197.31 21687.62 19697.10 26994.22 18486.58 25794.40 243
v192192090.46 26489.12 27294.50 24492.96 31392.46 23699.49 18696.98 28986.10 29689.61 24695.30 28778.55 27597.03 27682.17 31280.89 30294.01 280
UA-Net96.54 12695.96 13298.27 12698.23 15995.71 16398.00 30598.45 10793.72 13898.41 11099.27 12988.71 18999.66 13791.19 22697.69 14999.44 158
v119290.62 26289.25 27094.72 23493.13 30693.07 22099.50 18497.02 28486.33 29489.56 24795.01 29779.22 26897.09 27182.34 31181.16 29594.01 280
FC-MVSNet-test93.81 19393.15 20095.80 20694.30 28896.20 14499.42 19598.89 4292.33 18789.03 26097.27 21887.39 19996.83 28693.20 20386.48 25894.36 246
v114491.09 25089.83 25894.87 22893.25 30593.69 20999.62 16696.98 28986.83 28989.64 24594.99 30080.94 25297.05 27285.08 29581.16 29593.87 293
sosnet-low-res0.00 3410.00 3440.00 3520.00 3730.00 3740.00 3640.00 3740.00 3690.00 3700.00 3700.00 3750.00 3700.00 3680.00 3680.00 366
HFP-MVS98.56 3798.37 4099.14 6399.96 897.43 9999.95 4398.61 6994.77 8899.31 6699.85 3394.22 83100.00 198.70 7799.98 3399.98 51
v14890.70 25889.63 26193.92 26792.97 31290.97 26799.75 13796.89 29987.51 27688.27 27495.01 29781.67 24397.04 27487.40 27577.17 32893.75 300
sosnet0.00 3410.00 3440.00 3520.00 3730.00 3740.00 3640.00 3740.00 3690.00 3700.00 3700.00 3750.00 3700.00 3680.00 3680.00 366
uncertanet0.00 3410.00 3440.00 3520.00 3730.00 3740.00 3640.00 3740.00 3690.00 3700.00 3700.00 3750.00 3700.00 3680.00 3680.00 366
AllTest92.48 22391.64 22695.00 22499.01 11588.43 30598.94 25096.82 30586.50 29188.71 26398.47 19074.73 30199.88 8585.39 29296.18 17896.71 223
TestCases95.00 22499.01 11588.43 30596.82 30586.50 29188.71 26398.47 19074.73 30199.88 8585.39 29296.18 17896.71 223
v7n89.65 28288.29 28793.72 27292.22 32290.56 27699.07 23497.10 27685.42 30986.73 29294.72 30580.06 26397.13 26681.14 31778.12 31993.49 308
region2R98.54 3998.37 4099.05 7399.96 897.18 10799.96 2598.55 8394.87 8699.45 5399.85 3394.07 89100.00 198.67 79100.00 199.98 51
bset_n11_16_dypcd93.05 21192.30 21595.31 21590.23 34195.05 18199.44 19497.28 25992.51 18190.65 22696.68 23985.30 21996.71 29294.49 17684.14 27594.16 266
RRT_MVS95.23 15894.77 16296.61 18498.28 15498.32 6399.81 11797.41 24792.59 17591.28 22097.76 20795.02 5497.23 26193.65 19887.14 25494.28 253
PS-MVSNAJss93.64 20093.31 19794.61 23792.11 32392.19 24199.12 22697.38 25092.51 18188.45 26796.99 22991.20 15297.29 25894.36 17887.71 24994.36 246
PS-MVSNAJ98.44 4798.20 5099.16 5998.80 13598.92 2399.54 17898.17 17497.34 1699.85 699.85 3391.20 15299.89 7999.41 4099.67 9598.69 203
jajsoiax91.92 23491.18 23694.15 25691.35 33290.95 26899.00 24397.42 24592.61 17387.38 28697.08 22372.46 31097.36 25094.53 17588.77 23594.13 272
mvs_tets91.81 23691.08 23794.00 26491.63 33090.58 27598.67 27597.43 24392.43 18487.37 28797.05 22671.76 31297.32 25494.75 16888.68 23794.11 273
#test#98.59 3598.41 3399.14 6399.96 897.43 9999.95 4398.61 6995.00 8199.31 6699.85 3394.22 83100.00 198.78 7399.98 3399.98 51
EI-MVSNet-UG-set98.14 6597.99 6398.60 10299.80 6996.27 13899.36 20598.50 10195.21 7798.30 11699.75 7793.29 10999.73 12898.37 9199.30 11599.81 98
EI-MVSNet-Vis-set98.27 5998.11 5798.75 9299.83 6396.59 12899.40 19698.51 9795.29 7598.51 10699.76 7293.60 10299.71 12998.53 8799.52 10699.95 78
Regformer-398.58 3698.41 3399.10 6999.84 6097.57 8899.66 15698.52 9095.79 5999.01 8399.77 6894.40 7199.75 12198.82 6999.83 8199.98 51
Regformer-498.56 3798.39 3799.08 7199.84 6097.52 9199.66 15698.52 9095.76 6299.01 8399.77 6894.33 7999.75 12198.80 7299.83 8199.98 51
Regformer-198.79 2498.60 2399.36 4599.85 5598.34 6299.87 9098.52 9096.05 5399.41 5799.79 6294.93 6099.76 11899.07 4999.90 7299.99 20
Regformer-298.78 2598.59 2499.36 4599.85 5598.32 6399.87 9098.52 9096.04 5499.41 5799.79 6294.92 6199.76 11899.05 5099.90 7299.98 51
HPM-MVS++copyleft99.07 998.88 1399.63 1299.90 4299.02 1999.95 4398.56 7797.56 1399.44 5499.85 3395.38 45100.00 199.31 4399.99 2099.87 93
test_prior498.05 7199.94 58
XVS98.70 2898.55 2599.15 6199.94 1497.50 9499.94 5898.42 12796.22 4999.41 5799.78 6694.34 7699.96 5398.92 6199.95 5199.99 20
v124090.20 27288.79 27994.44 24893.05 31192.27 24099.38 20196.92 29785.89 29889.36 25094.87 30477.89 27897.03 27680.66 31981.08 29894.01 280
test_prior398.99 1398.84 1499.43 3599.94 1498.49 5799.95 4398.65 6095.78 6099.73 2799.76 7296.00 2999.80 10699.78 20100.00 199.99 20
pm-mvs189.36 28587.81 29294.01 26393.40 30491.93 24798.62 27896.48 31986.25 29583.86 31696.14 25573.68 30797.04 27486.16 28875.73 33593.04 319
test_prior299.95 4395.78 6099.73 2799.76 7296.00 2999.78 20100.00 1
X-MVStestdata93.83 19192.06 22099.15 6199.94 1497.50 9499.94 5898.42 12796.22 4999.41 5741.37 36894.34 7699.96 5398.92 6199.95 5199.99 20
test_prior99.43 3599.94 1498.49 5798.65 6099.80 10699.99 20
旧先验299.46 19194.21 11499.85 699.95 6096.96 137
新几何299.40 196
新几何199.42 3899.75 7698.27 6598.63 6692.69 16899.55 4599.82 5394.40 71100.00 191.21 22599.94 5799.99 20
旧先验199.76 7497.52 9198.64 6399.85 3395.63 3999.94 5799.99 20
无先验99.49 18698.71 5393.46 144100.00 194.36 17899.99 20
原ACMM299.90 76
原ACMM198.96 8299.73 8196.99 11498.51 9794.06 12199.62 4099.85 3394.97 5999.96 5395.11 15799.95 5199.92 87
test22299.55 9497.41 10299.34 20698.55 8391.86 19999.27 7199.83 4993.84 9699.95 5199.99 20
testdata299.99 3690.54 241
segment_acmp96.68 22
testdata98.42 11999.47 10095.33 17298.56 7793.78 13599.79 2199.85 3393.64 10199.94 6894.97 15999.94 57100.00 1
testdata199.28 21696.35 48
v890.54 26389.17 27194.66 23593.43 30293.40 21799.20 22196.94 29585.76 30187.56 28294.51 31281.96 24197.19 26284.94 29678.25 31793.38 312
131496.84 11395.96 13299.48 3396.74 24098.52 5598.31 29198.86 4595.82 5889.91 23598.98 15187.49 19799.96 5397.80 11399.73 9199.96 70
112198.03 6997.57 8099.40 4199.74 7798.21 6698.31 29198.62 6792.78 16399.53 4799.83 4995.08 50100.00 194.36 17899.92 6799.99 20
LFMVS94.75 17093.56 18898.30 12499.03 11495.70 16498.74 26897.98 19287.81 27598.47 10899.39 12167.43 33099.53 14198.01 10595.20 19999.67 117
VDD-MVS93.77 19592.94 20196.27 19598.55 14290.22 28298.77 26797.79 21090.85 22796.82 14999.42 11661.18 34899.77 11598.95 5894.13 20798.82 198
VDDNet93.12 20891.91 22396.76 17896.67 24392.65 23398.69 27398.21 16882.81 32697.75 13199.28 12661.57 34699.48 14998.09 10294.09 20898.15 208
v1090.25 27188.82 27894.57 24093.53 30093.43 21599.08 23096.87 30185.00 31187.34 28894.51 31280.93 25397.02 27882.85 30879.23 31193.26 314
VPNet91.81 23690.46 24595.85 20594.74 28195.54 16798.98 24598.59 7292.14 19190.77 22597.44 21268.73 32497.54 24494.89 16377.89 32094.46 236
MVS96.60 12595.56 14499.72 996.85 23399.22 1598.31 29198.94 3691.57 20890.90 22399.61 10186.66 20699.96 5397.36 12699.88 7699.99 20
v2v48291.30 24590.07 25795.01 22393.13 30693.79 20699.77 12997.02 28488.05 27189.25 25395.37 28480.73 25597.15 26487.28 27780.04 30994.09 274
V4291.28 24790.12 25694.74 23293.42 30393.46 21499.68 15397.02 28487.36 27989.85 23995.05 29581.31 24997.34 25287.34 27680.07 30893.40 310
SD-MVS98.92 1698.70 1799.56 2199.70 8598.73 4199.94 5898.34 14896.38 4499.81 1299.76 7294.59 6799.98 4299.84 1399.96 4899.97 63
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-MVS93.83 19192.84 20296.80 17695.73 26293.57 21099.88 8797.24 26292.57 17892.92 20796.66 24078.73 27397.67 24087.75 27194.06 20999.17 181
MSLP-MVS++99.13 799.01 999.49 3199.94 1498.46 5999.98 1098.86 4597.10 2599.80 1699.94 495.92 33100.00 199.51 34100.00 1100.00 1
APDe-MVS99.06 1098.91 1299.51 2899.94 1498.76 4099.91 7298.39 13597.20 2499.46 5299.85 3395.53 4299.79 10999.86 12100.00 199.99 20
APD-MVS_3200maxsize98.25 6298.08 5898.78 8999.81 6896.60 12799.82 11598.30 15693.95 12799.37 6399.77 6892.84 12199.76 11898.95 5899.92 6799.97 63
ADS-MVSNet293.80 19493.88 18093.55 27997.87 17885.94 32094.24 33996.84 30290.07 23996.43 15994.48 31490.29 16895.37 32587.44 27397.23 16099.36 166
EI-MVSNet93.73 19793.40 19594.74 23296.80 23692.69 23099.06 23597.67 21588.96 25591.39 21899.02 14488.75 18897.30 25591.07 22887.85 24794.22 257
Regformer0.00 3410.00 3440.00 3520.00 3730.00 3740.00 3640.00 3740.00 3690.00 3700.00 3700.00 3750.00 3700.00 3680.00 3680.00 366
CVMVSNet94.68 17394.94 15893.89 26996.80 23686.92 31699.06 23598.98 3494.45 10094.23 19399.02 14485.60 21495.31 32790.91 23595.39 19699.43 159
pmmvs492.10 23291.07 23895.18 21992.82 31694.96 18399.48 18896.83 30387.45 27888.66 26696.56 24583.78 23096.83 28689.29 25484.77 27093.75 300
EU-MVSNet90.14 27590.34 24989.54 32092.55 31981.06 34598.69 27398.04 18891.41 21686.59 29596.84 23680.83 25493.31 34786.20 28781.91 28994.26 254
VNet97.21 10296.57 11299.13 6898.97 11997.82 8199.03 24199.21 2794.31 11099.18 7798.88 16386.26 21099.89 7998.93 6094.32 20599.69 114
test-LLR96.47 12896.04 12397.78 14497.02 22495.44 16899.96 2598.21 16894.07 11995.55 17596.38 24793.90 9498.27 21290.42 24398.83 12699.64 124
TESTMET0.1,196.74 11996.26 11998.16 12997.36 20996.48 13099.96 2598.29 15791.93 19795.77 17398.07 19995.54 4098.29 20890.55 24098.89 12499.70 112
test-mter96.39 13295.93 13497.78 14497.02 22495.44 16899.96 2598.21 16891.81 20295.55 17596.38 24795.17 4798.27 21290.42 24398.83 12699.64 124
VPA-MVSNet92.70 21891.55 23096.16 19795.09 27596.20 14498.88 25699.00 3391.02 22491.82 21595.29 29076.05 29397.96 23095.62 15481.19 29494.30 251
ACMMPR98.50 4298.32 4499.05 7399.96 897.18 10799.95 4398.60 7194.77 8899.31 6699.84 4693.73 98100.00 198.70 7799.98 3399.98 51
testgi89.01 28988.04 29091.90 30293.49 30184.89 32799.73 14595.66 33493.89 13285.14 31098.17 19659.68 34994.66 33577.73 33188.88 23296.16 228
test20.0384.72 31183.99 30586.91 33188.19 34980.62 34898.88 25695.94 32888.36 26878.87 33694.62 31068.75 32389.11 35666.52 35275.82 33391.00 339
thres600view796.69 12295.87 13899.14 6398.90 12898.78 3599.74 14099.71 592.59 17595.84 17098.86 16789.25 18199.50 14593.44 20194.50 20499.16 182
ADS-MVSNet94.79 16794.02 17697.11 17097.87 17893.79 20694.24 33998.16 17790.07 23996.43 15994.48 31490.29 16898.19 21887.44 27397.23 16099.36 166
MP-MVScopyleft98.23 6397.97 6499.03 7599.94 1497.17 11099.95 4398.39 13594.70 9198.26 11999.81 5791.84 145100.00 198.85 6799.97 4499.93 81
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs40.60 33544.45 33829.05 35019.49 37214.11 37399.68 15318.47 37120.74 36664.59 35498.48 18910.95 37117.09 36956.66 35911.01 36555.94 362
thres40096.78 11695.99 12599.16 5998.94 12198.82 3199.78 12699.71 592.86 15796.02 16798.87 16589.33 17999.50 14593.84 18894.57 20199.16 182
test12337.68 33639.14 33933.31 34919.94 37124.83 37298.36 2909.75 37215.53 36751.31 36287.14 34919.62 36917.74 36847.10 3613.47 36757.36 361
thres20096.96 10896.21 12099.22 5098.97 11998.84 3099.85 10499.71 593.17 15296.26 16498.88 16389.87 17299.51 14394.26 18294.91 20099.31 172
test0.0.03 193.86 19093.61 18394.64 23695.02 27892.18 24299.93 6498.58 7394.07 11987.96 27798.50 18593.90 9494.96 33181.33 31693.17 21696.78 222
pmmvs380.27 32277.77 32687.76 33080.32 35882.43 33698.23 29691.97 35772.74 35278.75 33787.97 34757.30 35390.99 35370.31 34562.37 35289.87 347
EMVS51.44 33451.22 33652.11 34870.71 36244.97 36894.04 34175.66 36935.34 36542.40 36561.56 36628.93 36465.87 36627.64 36624.73 36245.49 363
E-PMN52.30 33252.18 33452.67 34771.51 36145.40 36693.62 34576.60 36836.01 36343.50 36464.13 36327.11 36567.31 36531.06 36526.06 36145.30 364
PGM-MVS98.34 5498.13 5598.99 7999.92 3597.00 11399.75 13799.50 1693.90 13099.37 6399.76 7293.24 113100.00 197.75 12099.96 4899.98 51
LCM-MVSNet-Re92.31 22792.60 20791.43 30597.53 20079.27 35199.02 24291.83 35892.07 19380.31 33294.38 31783.50 23295.48 32397.22 13097.58 15299.54 144
LCM-MVSNet67.77 32664.73 33076.87 33962.95 36656.25 36389.37 35693.74 35544.53 36061.99 35580.74 35520.42 36886.53 35869.37 34859.50 35687.84 353
MCST-MVS99.32 399.14 499.86 399.97 399.59 399.97 1898.64 6398.47 299.13 7899.92 1196.38 26100.00 199.74 24100.00 1100.00 1
mvs_anonymous95.65 15295.03 15797.53 15498.19 16195.74 16199.33 20797.49 23890.87 22690.47 22897.10 22288.23 19297.16 26395.92 15097.66 15199.68 115
MVS_Test96.46 12995.74 14098.61 10198.18 16297.23 10599.31 21097.15 27091.07 22298.84 8997.05 22688.17 19398.97 16194.39 17797.50 15399.61 128
MDA-MVSNet-bldmvs84.09 31481.52 32091.81 30391.32 33388.00 31298.67 27595.92 32980.22 33555.60 36093.32 32668.29 32793.60 34573.76 34076.61 33293.82 297
CDPH-MVS98.65 3198.36 4299.49 3199.94 1498.73 4199.87 9098.33 14993.97 12599.76 2499.87 2694.99 5899.75 12198.55 86100.00 199.98 51
test1299.43 3599.74 7798.56 5398.40 13299.65 3594.76 6399.75 12199.98 3399.99 20
casdiffmvs96.42 13195.97 13097.77 14697.30 21494.98 18299.84 10897.09 27793.75 13796.58 15499.26 13285.07 22198.78 16897.77 11897.04 16599.54 144
diffmvs97.00 10796.64 10998.09 13497.64 19596.17 14699.81 11797.19 26494.67 9498.95 8699.28 12686.43 20898.76 17198.37 9197.42 15699.33 170
baseline296.71 12196.49 11497.37 16295.63 26995.96 15399.74 14098.88 4392.94 15691.61 21698.97 15397.72 598.62 18094.83 16498.08 14597.53 220
baseline195.78 14794.86 15998.54 10998.47 14798.07 7099.06 23597.99 19092.68 16994.13 19498.62 17993.28 11098.69 17793.79 19385.76 26198.84 197
YYNet185.50 30683.33 31192.00 30090.89 33688.38 30899.22 22096.55 31679.60 33857.26 35892.72 33079.09 27193.78 34377.25 33377.37 32693.84 295
PMMVS267.15 32764.15 33176.14 34070.56 36362.07 36093.89 34287.52 36558.09 35660.02 35678.32 35622.38 36784.54 35959.56 35847.03 35981.80 355
MDA-MVSNet_test_wron85.51 30583.32 31292.10 29990.96 33588.58 30499.20 22196.52 31779.70 33757.12 35992.69 33279.11 27093.86 34277.10 33477.46 32593.86 294
tpmvs94.28 18793.57 18796.40 19198.55 14291.50 26295.70 33898.55 8387.47 27792.15 21394.26 31891.42 14898.95 16288.15 26695.85 18698.76 201
PM-MVS80.47 32178.88 32585.26 33383.79 35672.22 35495.89 33691.08 35985.71 30476.56 34488.30 34636.64 36193.90 34182.39 31069.57 34289.66 349
HQP_MVS94.49 18094.36 16894.87 22895.71 26591.74 25399.84 10897.87 20396.38 4493.01 20598.59 18080.47 26198.37 20397.79 11689.55 22594.52 233
plane_prior795.71 26591.59 261
plane_prior695.76 26091.72 25680.47 261
plane_prior597.87 20398.37 20397.79 11689.55 22594.52 233
plane_prior498.59 180
plane_prior391.64 25996.63 3893.01 205
plane_prior299.84 10896.38 44
plane_prior195.73 262
plane_prior91.74 25399.86 10196.76 3489.59 224
PS-CasMVS90.63 26189.51 26693.99 26593.83 29591.70 25798.98 24598.52 9088.48 26686.15 30496.53 24675.46 29596.31 30688.83 25878.86 31593.95 286
UniMVSNet_NR-MVSNet92.95 21392.11 21895.49 20894.61 28495.28 17499.83 11499.08 3091.49 21089.21 25596.86 23387.14 20196.73 29093.20 20377.52 32394.46 236
PEN-MVS90.19 27389.06 27493.57 27893.06 31090.90 26999.06 23598.47 10388.11 27085.91 30696.30 25176.67 28495.94 32087.07 27976.91 33093.89 291
TransMVSNet (Re)87.25 29885.28 30393.16 28593.56 29991.03 26698.54 28194.05 35383.69 32281.09 32996.16 25475.32 29696.40 30276.69 33668.41 34692.06 331
DTE-MVSNet89.40 28488.24 28892.88 29192.66 31889.95 28899.10 22798.22 16787.29 28085.12 31196.22 25376.27 29095.30 32883.56 30575.74 33493.41 309
DU-MVS92.46 22491.45 23395.49 20894.05 29195.28 17499.81 11798.74 5292.25 18989.21 25596.64 24281.66 24496.73 29093.20 20377.52 32394.46 236
UniMVSNet (Re)93.07 21092.13 21795.88 20394.84 27996.24 14399.88 8798.98 3492.49 18389.25 25395.40 28087.09 20297.14 26593.13 20778.16 31894.26 254
CP-MVSNet91.23 24890.22 25294.26 25393.96 29392.39 23899.09 22898.57 7588.95 25686.42 29996.57 24479.19 26996.37 30390.29 24678.95 31394.02 278
WR-MVS_H91.30 24590.35 24894.15 25694.17 29092.62 23499.17 22498.94 3688.87 25886.48 29894.46 31684.36 22696.61 29688.19 26578.51 31693.21 316
WR-MVS92.31 22791.25 23595.48 21194.45 28595.29 17399.60 16898.68 5690.10 23888.07 27696.89 23180.68 25696.80 28893.14 20679.67 31094.36 246
NR-MVSNet91.56 24490.22 25295.60 20794.05 29195.76 16098.25 29498.70 5491.16 22080.78 33196.64 24283.23 23596.57 29791.41 22377.73 32294.46 236
Baseline_NR-MVSNet90.33 26889.51 26692.81 29292.84 31489.95 28899.77 12993.94 35484.69 31689.04 25995.66 26781.66 24496.52 29890.99 23276.98 32991.97 333
TranMVSNet+NR-MVSNet91.68 24390.61 24494.87 22893.69 29893.98 20399.69 15198.65 6091.03 22388.44 26896.83 23780.05 26496.18 31190.26 24776.89 33194.45 241
TSAR-MVS + GP.98.60 3398.51 2898.86 8799.73 8196.63 12599.97 1897.92 19998.07 598.76 9599.55 10595.00 5799.94 6899.91 1197.68 15099.99 20
abl_697.67 8697.34 8798.66 9799.68 8696.11 15099.68 15398.14 18093.80 13499.27 7199.70 8888.65 19099.98 4297.46 12499.72 9299.89 90
n20.00 374
nn0.00 374
mPP-MVS98.39 5298.20 5098.97 8199.97 396.92 11799.95 4398.38 13995.04 8098.61 10399.80 5893.39 104100.00 198.64 83100.00 199.98 51
door-mid89.69 362
XVG-OURS-SEG-HR94.79 16794.70 16495.08 22198.05 16889.19 29599.08 23097.54 23093.66 13994.87 18499.58 10378.78 27299.79 10997.31 12793.40 21496.25 225
DWT-MVSNet_test97.31 9797.19 9297.66 15098.24 15894.67 19198.86 26098.20 17293.60 14198.09 12298.89 16197.51 798.78 16894.04 18597.28 15999.55 140
MVSFormer96.94 10996.60 11097.95 13897.28 21697.70 8599.55 17697.27 26091.17 21899.43 5599.54 10790.92 15996.89 28294.67 17299.62 9899.25 177
jason97.24 10096.86 10298.38 12295.73 26297.32 10399.97 1897.40 24995.34 7498.60 10499.54 10787.70 19598.56 18297.94 11099.47 10999.25 177
jason: jason.
lupinMVS97.85 7597.60 7898.62 10097.28 21697.70 8599.99 597.55 22895.50 7199.43 5599.67 9590.92 15998.71 17598.40 9099.62 9899.45 156
test_djsdf92.83 21592.29 21694.47 24691.90 32692.46 23699.55 17697.27 26091.17 21889.96 23396.07 25881.10 25096.89 28294.67 17288.91 23194.05 277
HPM-MVS_fast97.80 8097.50 8198.68 9599.79 7096.42 13299.88 8798.16 17791.75 20498.94 8799.54 10791.82 14699.65 13897.62 12299.99 2099.99 20
RRT_test8_iter0594.58 17694.11 17395.98 20197.88 17696.11 15099.89 8497.45 24091.66 20688.28 27396.71 23896.53 2497.40 24894.73 17083.85 28094.45 241
K. test v388.05 29487.24 29690.47 31391.82 32882.23 33898.96 24897.42 24589.05 25076.93 34295.60 26968.49 32595.42 32485.87 29181.01 30093.75 300
lessismore_v090.53 31190.58 33880.90 34695.80 33077.01 34195.84 26066.15 33496.95 27983.03 30775.05 33693.74 303
SixPastTwentyTwo88.73 29088.01 29190.88 30891.85 32782.24 33798.22 29795.18 34588.97 25482.26 32296.89 23171.75 31396.67 29484.00 30082.98 28293.72 304
OurMVSNet-221017-089.81 27989.48 26890.83 31091.64 32981.21 34398.17 29995.38 34091.48 21185.65 30897.31 21672.66 30997.29 25888.15 26684.83 26993.97 285
HPM-MVScopyleft97.96 7097.72 7298.68 9599.84 6096.39 13599.90 7698.17 17492.61 17398.62 10299.57 10491.87 14499.67 13698.87 6699.99 2099.99 20
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
XVG-OURS94.82 16694.74 16395.06 22298.00 17089.19 29599.08 23097.55 22894.10 11794.71 18599.62 10080.51 25999.74 12596.04 14893.06 21896.25 225
XVG-ACMP-BASELINE91.22 24990.75 24092.63 29493.73 29785.61 32198.52 28397.44 24292.77 16489.90 23696.85 23466.64 33298.39 19892.29 21488.61 23893.89 291
LPG-MVS_test92.96 21292.71 20593.71 27395.43 27188.67 30199.75 13797.62 21992.81 16090.05 23098.49 18675.24 29798.40 19695.84 15289.12 22994.07 275
LGP-MVS_train93.71 27395.43 27188.67 30197.62 21992.81 16090.05 23098.49 18675.24 29798.40 19695.84 15289.12 22994.07 275
baseline96.43 13095.98 12797.76 14797.34 21095.17 17999.51 18297.17 26793.92 12996.90 14799.28 12685.37 21898.64 17997.50 12396.86 17099.46 154
test1198.44 108
door90.31 360
EPNet_dtu95.71 15095.39 14796.66 18298.92 12593.41 21699.57 17298.90 4196.19 5197.52 13498.56 18492.65 12697.36 25077.89 33098.33 13699.20 180
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CHOSEN 1792x268896.81 11496.53 11397.64 15198.91 12793.07 22099.65 15999.80 395.64 6795.39 17898.86 16784.35 22799.90 7596.98 13699.16 12199.95 78
EPNet98.49 4398.40 3598.77 9099.62 8996.80 12099.90 7699.51 1597.60 1299.20 7399.36 12493.71 9999.91 7497.99 10798.71 12999.61 128
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
HQP5-MVS91.85 249
HQP-NCC95.78 25699.87 9096.82 3093.37 201
ACMP_Plane95.78 25699.87 9096.82 3093.37 201
APD-MVScopyleft98.62 3298.35 4399.41 3999.90 4298.51 5699.87 9098.36 14494.08 11899.74 2699.73 8394.08 8899.74 12599.42 3999.99 2099.99 20
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
BP-MVS97.92 111
HQP4-MVS93.37 20198.39 19894.53 231
HQP3-MVS97.89 20189.60 222
HQP2-MVS80.65 257
CNVR-MVS99.40 199.26 199.84 499.98 299.51 499.98 1098.69 5598.20 399.93 199.98 296.82 19100.00 199.75 22100.00 199.99 20
NCCC99.37 299.25 299.71 1099.96 899.15 1699.97 1898.62 6798.02 699.90 299.95 397.33 13100.00 199.54 33100.00 1100.00 1
114514_t97.41 9596.83 10399.14 6399.51 9897.83 8099.89 8498.27 16188.48 26699.06 8099.66 9790.30 16799.64 13996.32 14599.97 4499.96 70
CP-MVS98.45 4698.32 4498.87 8699.96 896.62 12699.97 1898.39 13594.43 10298.90 8899.87 2694.30 81100.00 199.04 5499.99 2099.99 20
DSMNet-mixed88.28 29388.24 28888.42 32889.64 34475.38 35398.06 30389.86 36185.59 30588.20 27592.14 33776.15 29291.95 35078.46 32896.05 18197.92 211
tpm295.47 15595.18 15496.35 19496.91 22891.70 25796.96 32397.93 19788.04 27298.44 10995.40 28093.32 10797.97 22894.00 18695.61 19299.38 163
NP-MVS95.77 25991.79 25198.65 176
EG-PatchMatch MVS85.35 30783.81 30989.99 31890.39 33981.89 34098.21 29896.09 32681.78 33174.73 34893.72 32351.56 35797.12 26879.16 32688.61 23890.96 340
tpm cat193.51 20192.52 21296.47 18697.77 18591.47 26396.13 33198.06 18680.98 33392.91 20893.78 32289.66 17398.87 16387.03 28196.39 17699.09 188
SteuartSystems-ACMMP99.02 1198.97 1199.18 5498.72 13897.71 8399.98 1098.44 10896.85 2999.80 1699.91 1397.57 699.85 9499.44 3899.99 2099.99 20
Skip Steuart: Steuart Systems R&D Blog.
CostFormer96.10 14095.88 13796.78 17797.03 22392.55 23597.08 32097.83 20890.04 24198.72 9794.89 30395.01 5698.29 20896.54 14395.77 18899.50 151
CR-MVSNet93.45 20492.62 20695.94 20296.29 24592.66 23192.01 35096.23 32292.62 17296.94 14593.31 32791.04 15696.03 31779.23 32395.96 18399.13 186
JIA-IIPM91.76 24290.70 24294.94 22696.11 24887.51 31393.16 34698.13 18275.79 34697.58 13377.68 35792.84 12197.97 22888.47 26396.54 17299.33 170
Patchmtry89.70 28188.49 28393.33 28196.24 24789.94 29091.37 35396.23 32278.22 34087.69 27993.31 32791.04 15696.03 31780.18 32282.10 28794.02 278
PatchT90.38 26688.75 28095.25 21895.99 25290.16 28391.22 35497.54 23076.80 34297.26 13986.01 35291.88 14396.07 31666.16 35395.91 18599.51 149
tpmrst96.27 13995.98 12797.13 16897.96 17293.15 21996.34 32998.17 17492.07 19398.71 9895.12 29493.91 9398.73 17394.91 16296.62 17199.50 151
BH-w/o95.71 15095.38 14896.68 18198.49 14692.28 23999.84 10897.50 23792.12 19292.06 21498.79 17184.69 22398.67 17895.29 15699.66 9699.09 188
tpm93.70 19993.41 19494.58 23995.36 27387.41 31497.01 32196.90 29890.85 22796.72 15294.14 31990.40 16696.84 28590.75 23988.54 24199.51 149
DELS-MVS98.54 3998.22 4899.50 2999.15 11198.65 48100.00 198.58 7397.70 998.21 12199.24 13492.58 12899.94 6898.63 8499.94 5799.92 87
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-untuned95.18 15994.83 16096.22 19698.36 15091.22 26599.80 12297.32 25690.91 22591.08 22198.67 17583.51 23198.54 18494.23 18399.61 10198.92 192
RPMNet89.76 28087.28 29597.19 16796.29 24592.66 23192.01 35098.31 15370.19 35496.94 14585.87 35387.25 20099.78 11162.69 35695.96 18399.13 186
MVSTER95.53 15395.22 15296.45 18898.56 14197.72 8299.91 7297.67 21592.38 18591.39 21897.14 22097.24 1497.30 25594.80 16587.85 24794.34 250
CPTT-MVS97.64 8797.32 8998.58 10599.97 395.77 15999.96 2598.35 14689.90 24298.36 11399.79 6291.18 15599.99 3698.37 9199.99 2099.99 20
GBi-Net90.88 25489.82 25994.08 25997.53 20091.97 24498.43 28696.95 29287.05 28389.68 24194.72 30571.34 31496.11 31287.01 28285.65 26294.17 261
PVSNet_Blended_VisFu97.27 9996.81 10498.66 9798.81 13496.67 12499.92 6898.64 6394.51 9996.38 16298.49 18689.05 18499.88 8597.10 13398.34 13599.43 159
PVSNet_BlendedMVS96.05 14195.82 13996.72 18099.59 9096.99 11499.95 4399.10 2894.06 12198.27 11795.80 26189.00 18599.95 6099.12 4787.53 25293.24 315
UnsupCasMVSNet_eth85.52 30483.99 30590.10 31689.36 34583.51 33196.65 32597.99 19089.14 24875.89 34693.83 32163.25 34393.92 34081.92 31467.90 34892.88 321
UnsupCasMVSNet_bld79.97 32477.03 32788.78 32585.62 35381.98 33993.66 34497.35 25275.51 34870.79 35283.05 35448.70 35994.91 33278.31 32960.29 35589.46 351
PVSNet_Blended97.94 7197.64 7598.83 8899.59 9096.99 114100.00 199.10 2895.38 7298.27 11799.08 14189.00 18599.95 6099.12 4799.25 11799.57 138
FMVSNet588.32 29287.47 29490.88 30896.90 23188.39 30797.28 31595.68 33382.60 32884.67 31292.40 33679.83 26591.16 35276.39 33781.51 29293.09 317
test190.88 25489.82 25994.08 25997.53 20091.97 24498.43 28696.95 29287.05 28389.68 24194.72 30571.34 31496.11 31287.01 28285.65 26294.17 261
new_pmnet84.49 31382.92 31589.21 32190.03 34282.60 33496.89 32495.62 33580.59 33475.77 34789.17 34465.04 33994.79 33472.12 34381.02 29990.23 345
FMVSNet392.69 21991.58 22895.99 20098.29 15297.42 10199.26 21897.62 21989.80 24489.68 24195.32 28681.62 24696.27 30887.01 28285.65 26294.29 252
dp95.05 16294.43 16796.91 17397.99 17192.73 22996.29 33097.98 19289.70 24595.93 16994.67 30993.83 9798.45 19086.91 28596.53 17399.54 144
FMVSNet291.02 25189.56 26395.41 21297.53 20095.74 16198.98 24597.41 24787.05 28388.43 27095.00 29971.34 31496.24 31085.12 29485.21 26794.25 256
FMVSNet188.50 29186.64 29794.08 25995.62 27091.97 24498.43 28696.95 29283.00 32486.08 30594.72 30559.09 35096.11 31281.82 31584.07 27794.17 261
N_pmnet80.06 32380.78 32177.89 33891.94 32545.28 36798.80 26556.82 37078.10 34180.08 33493.33 32577.03 28095.76 32268.14 35082.81 28392.64 323
cascas94.64 17493.61 18397.74 14997.82 18296.26 13999.96 2597.78 21185.76 30194.00 19597.54 21076.95 28299.21 15497.23 12995.43 19597.76 216
BH-RMVSNet95.18 15994.31 17097.80 14398.17 16395.23 17799.76 13497.53 23292.52 18094.27 19299.25 13376.84 28398.80 16690.89 23699.54 10599.35 168
UGNet95.33 15794.57 16597.62 15398.55 14294.85 18598.67 27599.32 2495.75 6596.80 15096.27 25272.18 31199.96 5394.58 17499.05 12398.04 210
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-MVS98.10 6797.60 7899.60 1798.92 12599.28 1299.89 8499.52 1395.58 6998.24 12099.39 12193.33 10699.74 12597.98 10995.58 19399.78 103
XXY-MVS91.82 23590.46 24595.88 20393.91 29495.40 17198.87 25997.69 21488.63 26487.87 27897.08 22374.38 30497.89 23491.66 22184.07 27794.35 249
DROMVSNet97.45 9097.30 9097.90 14297.43 20695.90 15499.99 597.08 27894.64 9599.64 3699.33 12589.56 17598.15 21998.76 7599.25 11799.65 123
sss97.57 8897.03 9999.18 5498.37 14998.04 7299.73 14599.38 2193.46 14498.76 9599.06 14291.21 15199.89 7996.33 14497.01 16699.62 126
Test_1112_low_res95.72 14894.83 16098.42 11997.79 18496.41 13399.65 15996.65 31492.70 16792.86 21096.13 25692.15 13899.30 15291.88 21993.64 21299.55 140
1112_ss96.01 14395.20 15398.42 11997.80 18396.41 13399.65 15996.66 31392.71 16692.88 20999.40 11992.16 13799.30 15291.92 21893.66 21199.55 140
ab-mvs-re8.28 33911.04 3420.00 3520.00 3730.00 3740.00 3640.00 3740.00 3690.00 37099.40 1190.00 3750.00 3700.00 3680.00 3680.00 366
ab-mvs94.69 17193.42 19298.51 11298.07 16796.26 13996.49 32798.68 5690.31 23694.54 18697.00 22876.30 28999.71 12995.98 14993.38 21599.56 139
TR-MVS94.54 17793.56 18897.49 15697.96 17294.34 19698.71 27197.51 23690.30 23794.51 18898.69 17475.56 29498.77 17092.82 21095.99 18299.35 168
MDTV_nov1_ep13_2view96.26 13996.11 33291.89 19898.06 12394.40 7194.30 18199.67 117
MDTV_nov1_ep1395.69 14197.90 17594.15 19895.98 33498.44 10893.12 15397.98 12595.74 26395.10 4998.58 18190.02 24996.92 168
MIMVSNet182.58 31880.51 32288.78 32586.68 35184.20 33096.65 32595.41 33978.75 33978.59 33892.44 33351.88 35689.76 35565.26 35578.95 31392.38 329
MIMVSNet90.30 26988.67 28195.17 22096.45 24491.64 25992.39 34897.15 27085.99 29790.50 22793.19 32966.95 33194.86 33382.01 31393.43 21399.01 191
IterMVS-LS92.69 21992.11 21894.43 25096.80 23692.74 22799.45 19296.89 29988.98 25389.65 24495.38 28388.77 18796.34 30590.98 23382.04 28894.22 257
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CDS-MVSNet96.34 13396.07 12297.13 16897.37 20894.96 18399.53 17997.91 20091.55 20995.37 17998.32 19495.05 5397.13 26693.80 19295.75 19099.30 173
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
ACMMP++_ref87.04 255
IterMVS90.91 25390.17 25493.12 28696.78 23990.42 28098.89 25497.05 28389.03 25186.49 29795.42 27976.59 28695.02 32987.22 27884.09 27693.93 288
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
DP-MVS Recon98.41 4998.02 6199.56 2199.97 398.70 4399.92 6898.44 10892.06 19598.40 11299.84 4695.68 38100.00 198.19 9599.71 9399.97 63
MVS_111021_LR98.42 4898.38 3898.53 11199.39 10395.79 15899.87 9099.86 296.70 3698.78 9299.79 6292.03 14199.90 7599.17 4699.86 7999.88 92
DP-MVS94.54 17793.42 19297.91 14199.46 10294.04 20098.93 25197.48 23981.15 33290.04 23299.55 10587.02 20399.95 6088.97 25798.11 14199.73 109
ACMMP++88.23 244
HQP-MVS94.61 17594.50 16694.92 22795.78 25691.85 24999.87 9097.89 20196.82 3093.37 20198.65 17680.65 25798.39 19897.92 11189.60 22294.53 231
QAPM95.40 15694.17 17299.10 6996.92 22797.71 8399.40 19698.68 5689.31 24788.94 26198.89 16182.48 23799.96 5393.12 20899.83 8199.62 126
Vis-MVSNetpermissive95.72 14895.15 15597.45 15797.62 19694.28 19799.28 21698.24 16494.27 11396.84 14898.94 15879.39 26798.76 17193.25 20298.49 13299.30 173
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
MVS-HIRNet86.22 30183.19 31395.31 21596.71 24290.29 28192.12 34997.33 25562.85 35586.82 29170.37 35969.37 32197.49 24575.12 33997.99 14798.15 208
IS-MVSNet96.29 13795.90 13697.45 15798.13 16694.80 18899.08 23097.61 22292.02 19695.54 17798.96 15590.64 16498.08 22293.73 19697.41 15799.47 153
HyFIR lowres test96.66 12496.43 11697.36 16399.05 11393.91 20599.70 15099.80 390.54 23196.26 16498.08 19892.15 13898.23 21696.84 14195.46 19499.93 81
EPMVS96.53 12796.01 12498.09 13498.43 14896.12 14996.36 32899.43 1993.53 14297.64 13295.04 29694.41 7098.38 20291.13 22798.11 14199.75 106
PAPM_NR98.12 6697.93 6898.70 9499.94 1496.13 14799.82 11598.43 11694.56 9797.52 13499.70 8894.40 7199.98 4297.00 13599.98 3399.99 20
TAMVS95.85 14595.58 14396.65 18397.07 22093.50 21399.17 22497.82 20991.39 21795.02 18398.01 20092.20 13697.30 25593.75 19595.83 18799.14 185
PAPR98.52 4198.16 5399.58 2099.97 398.77 3699.95 4398.43 11695.35 7398.03 12499.75 7794.03 9099.98 4298.11 10099.83 8199.99 20
RPSCF91.80 23992.79 20488.83 32498.15 16469.87 35598.11 30196.60 31583.93 31994.33 19199.27 12979.60 26699.46 15091.99 21693.16 21797.18 221
Vis-MVSNet (Re-imp)96.32 13495.98 12797.35 16497.93 17494.82 18799.47 18998.15 17991.83 20095.09 18299.11 13991.37 15097.47 24793.47 20097.43 15499.74 108
test_040285.58 30383.94 30790.50 31293.81 29685.04 32698.55 27995.20 34476.01 34479.72 33595.13 29364.15 34196.26 30966.04 35486.88 25690.21 346
MVS_111021_HR98.72 2798.62 2299.01 7899.36 10597.18 10799.93 6499.90 196.81 3398.67 9999.77 6893.92 9299.89 7999.27 4599.94 5799.96 70
CSCG97.10 10497.04 9897.27 16699.89 4591.92 24899.90 7699.07 3188.67 26295.26 18199.82 5393.17 11599.98 4298.15 9899.47 10999.90 89
PatchMatch-RL96.04 14295.40 14697.95 13899.59 9095.22 17899.52 18099.07 3193.96 12696.49 15798.35 19382.28 23899.82 10590.15 24899.22 12098.81 199
API-MVS97.86 7497.66 7498.47 11499.52 9695.41 17099.47 18998.87 4491.68 20598.84 8999.85 3392.34 13499.99 3698.44 8999.96 48100.00 1
Test By Simon92.82 123
TDRefinement84.76 30982.56 31691.38 30674.58 36084.80 32897.36 31494.56 35084.73 31580.21 33396.12 25763.56 34298.39 19887.92 26963.97 35090.95 341
USDC90.00 27788.96 27693.10 28894.81 28088.16 30998.71 27195.54 33793.66 13983.75 31797.20 21965.58 33598.31 20783.96 30287.49 25392.85 322
EPP-MVSNet96.69 12296.60 11096.96 17297.74 18893.05 22299.37 20398.56 7788.75 26095.83 17299.01 14696.01 2898.56 18296.92 13997.20 16299.25 177
PMMVS96.76 11796.76 10696.76 17898.28 15492.10 24399.91 7297.98 19294.12 11699.53 4799.39 12186.93 20498.73 17396.95 13897.73 14899.45 156
PAPM98.60 3398.42 3199.14 6396.05 25098.96 2099.90 7699.35 2396.68 3798.35 11499.66 9796.45 2598.51 18599.45 3799.89 7499.96 70
ACMMPcopyleft97.74 8397.44 8398.66 9799.92 3596.13 14799.18 22399.45 1794.84 8796.41 16199.71 8691.40 14999.99 3697.99 10798.03 14699.87 93
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
CNLPA97.76 8297.38 8498.92 8599.53 9596.84 11899.87 9098.14 18093.78 13596.55 15699.69 9192.28 13599.98 4297.13 13199.44 11199.93 81
PatchmatchNetpermissive95.94 14495.45 14597.39 16197.83 18194.41 19596.05 33398.40 13292.86 15797.09 14395.28 29194.21 8698.07 22489.26 25598.11 14199.70 112
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PHI-MVS98.41 4998.21 4999.03 7599.86 5497.10 11199.98 1098.80 5090.78 22999.62 4099.78 6695.30 46100.00 199.80 1899.93 6399.99 20
F-COLMAP96.93 11096.95 10196.87 17599.71 8491.74 25399.85 10497.95 19593.11 15495.72 17499.16 13892.35 13399.94 6895.32 15599.35 11498.92 192
ANet_high56.10 33052.24 33367.66 34449.27 36856.82 36283.94 35882.02 36670.47 35333.28 36764.54 36217.23 37069.16 36445.59 36223.85 36377.02 357
wuyk23d20.37 33820.84 34118.99 35165.34 36527.73 37150.43 3637.67 3739.50 3688.01 3696.34 3696.13 37326.24 36723.40 36710.69 3662.99 365
OMC-MVS97.28 9897.23 9197.41 15999.76 7493.36 21899.65 15997.95 19596.03 5597.41 13799.70 8889.61 17499.51 14396.73 14298.25 14099.38 163
MG-MVS98.91 1798.65 2099.68 1199.94 1499.07 1899.64 16399.44 1897.33 1799.00 8599.72 8494.03 9099.98 4298.73 76100.00 1100.00 1
AdaColmapbinary97.23 10196.80 10598.51 11299.99 195.60 16699.09 22898.84 4793.32 14796.74 15199.72 8486.04 211100.00 198.01 10599.43 11299.94 80
uanet0.00 3410.00 3440.00 3520.00 3730.00 3740.00 3640.00 3740.00 3690.00 3700.00 3700.00 3750.00 3700.00 3680.00 3680.00 366
ITE_SJBPF92.38 29595.69 26785.14 32595.71 33292.81 16089.33 25298.11 19770.23 31998.42 19385.91 29088.16 24593.59 307
DeepMVS_CXcopyleft82.92 33795.98 25458.66 36196.01 32792.72 16578.34 33995.51 27558.29 35198.08 22282.57 30985.29 26592.03 332
TinyColmap87.87 29786.51 29891.94 30195.05 27785.57 32297.65 31194.08 35284.40 31781.82 32596.85 23462.14 34598.33 20580.25 32186.37 25991.91 334
MAR-MVS97.43 9197.19 9298.15 13299.47 10094.79 18999.05 23998.76 5192.65 17198.66 10099.82 5388.52 19199.98 4298.12 9999.63 9799.67 117
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
LF4IMVS89.25 28888.85 27790.45 31492.81 31781.19 34498.12 30094.79 34791.44 21386.29 30297.11 22165.30 33898.11 22188.53 26285.25 26692.07 330
MSDG94.37 18393.36 19697.40 16098.88 13093.95 20499.37 20397.38 25085.75 30390.80 22499.17 13784.11 22999.88 8586.35 28698.43 13498.36 205
LS3D95.84 14695.11 15698.02 13799.85 5595.10 18098.74 26898.50 10187.22 28293.66 19999.86 2987.45 19899.95 6090.94 23499.81 8799.02 190
CLD-MVS94.06 18993.90 17994.55 24196.02 25190.69 27199.98 1097.72 21296.62 3991.05 22298.85 17077.21 27998.47 18698.11 10089.51 22794.48 235
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
FPMVS68.72 32568.72 32868.71 34365.95 36444.27 36995.97 33594.74 34851.13 35853.26 36190.50 34325.11 36683.00 36060.80 35780.97 30178.87 356
Gipumacopyleft66.95 32865.00 32972.79 34191.52 33167.96 35666.16 36295.15 34647.89 35958.54 35767.99 36129.74 36387.54 35750.20 36077.83 32162.87 360
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015