This table lists the benchmark results for the high-res multi-view scenario. The following metrics are evaluated:

(*) For exact definitions, detailing how potentially incomplete ground truth is taken into account, see our paper.

The datasets are grouped into different categories, and result averages are computed for a category and method if results of the method are available for all datasets within the category. Note that the category "all" includes both the high-res multi-view and the low-res many-view scenarios.

Methods with suffix _ROB may participate in the Robust Vision Challenge.

Click a dataset result cell to show a visualization of the reconstruction. For training datasets, ground truth and accuracy / completeness visualizations are also available. The visualizations may not work with mobile browsers.




Method Infoallhigh-res
multi-view
indooroutdoorbotani.boulde.bridgedoorexhibi.lectur.living.loungeobserv.old co.statueterrac.
sort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysorted bysort bysort bysort bysort bysort by
APDe-MVS80.16 280.59 278.86 1886.64 960.02 3988.12 186.42 462.94 3982.40 292.12 159.64 689.76 378.70 588.32 1586.79 37
MP-MVS-pluss78.35 1178.46 878.03 2884.96 3759.52 4482.93 3985.39 862.15 5276.41 1491.51 252.47 4986.78 4280.66 289.64 587.80 11
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
ACMMP_Plus78.77 778.78 778.74 1985.44 2961.04 3183.84 2885.16 1062.88 4178.10 891.26 352.51 4788.39 1279.34 390.52 186.78 38
SteuartSystems-ACMMP79.48 579.31 579.98 183.01 5562.18 1987.60 285.83 666.69 1078.03 990.98 454.26 3190.06 178.42 789.02 787.69 13
Skip Steuart: Steuart Systems R&D Blog.
MPTG77.61 1977.36 1878.35 2386.08 2063.57 283.37 3380.97 9565.13 1775.77 1690.88 548.63 9986.66 4477.23 888.17 1784.81 102
MTAPA76.90 2676.42 2778.35 2386.08 2063.57 274.92 18480.97 9565.13 1775.77 1690.88 548.63 9986.66 4477.23 888.17 1784.81 102
HPM-MVS++79.88 380.14 379.10 1188.17 164.80 186.59 483.70 3765.37 1578.78 790.64 758.63 1187.24 3079.00 490.37 285.26 90
MP-MVScopyleft78.35 1178.26 1178.64 2086.54 1163.47 586.02 983.55 4063.89 3073.60 4190.60 854.85 2786.72 4377.20 1088.06 2085.74 65
region2R77.67 1877.18 2079.15 786.76 462.95 886.29 584.16 2562.81 4573.30 4490.58 949.90 6988.21 1773.78 2387.03 3086.29 49
ACMMPR77.71 1677.23 1979.16 686.75 562.93 986.29 584.24 2362.82 4373.55 4290.56 1049.80 7188.24 1674.02 2187.03 3086.32 47
HSP-MVS80.69 181.20 179.14 886.21 1662.73 1286.09 885.03 1265.51 1483.81 190.51 1163.71 189.23 581.51 188.44 1185.45 77
HFP-MVS78.01 1477.65 1479.10 1186.71 662.81 1086.29 584.32 2162.82 4373.96 3290.50 1253.20 4488.35 1374.02 2187.05 2886.13 51
#test#77.83 1577.41 1779.10 1186.71 662.81 1085.69 1484.32 2161.61 6173.96 3290.50 1253.20 4488.35 1373.68 2487.05 2886.13 51
CP-MVS77.12 2476.68 2478.43 2286.05 2263.18 787.55 383.45 4362.44 4972.68 5290.50 1248.18 10687.34 2973.59 2685.71 4184.76 106
PGM-MVS76.77 2876.06 2978.88 1786.14 1962.73 1282.55 4783.74 3661.71 5972.45 5690.34 1548.48 10388.13 1872.32 3086.85 3385.78 60
APD-MVScopyleft78.02 1378.04 1377.98 2986.44 1360.81 3485.52 1584.36 2060.61 7279.05 690.30 1655.54 2288.32 1573.48 2787.03 3084.83 101
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
mPP-MVS76.54 2975.93 3178.34 2586.47 1263.50 485.74 1382.28 6362.90 4071.77 6090.26 1746.61 12686.55 5071.71 3485.66 4284.97 98
DeepC-MVS69.38 278.56 978.14 1279.83 283.60 4961.62 2484.17 2486.85 263.23 3473.84 3790.25 1857.68 1289.96 274.62 1889.03 687.89 9
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
APD-MVS_3200maxsize74.96 4074.39 4276.67 4582.20 6058.24 6083.67 2983.29 4958.41 12373.71 3990.14 1945.62 13285.99 6169.64 4182.85 5985.78 60
CNVR-MVS79.84 479.97 479.45 487.90 262.17 2084.37 2085.03 1266.96 577.58 1090.06 2059.47 889.13 778.67 689.73 387.03 32
DeepPCF-MVS69.58 179.03 679.00 679.13 984.92 4160.32 3783.03 3785.33 962.86 4280.17 390.03 2161.76 288.95 974.21 1988.67 1088.12 7
XVS77.17 2376.56 2679.00 1486.32 1462.62 1485.83 1083.92 2964.55 2172.17 5790.01 2247.95 10888.01 2171.55 3586.74 3586.37 43
HPM-MVS77.28 2176.85 2278.54 2185.00 3660.81 3482.91 4085.08 1162.57 4673.09 4789.97 2350.90 6587.48 2875.30 1386.85 3387.33 27
abl_674.34 4573.50 4876.86 4082.43 5860.16 3883.48 3281.86 7058.81 11773.95 3489.86 2441.87 16786.62 4667.98 4981.23 6983.80 139
HPM-MVS_fast74.30 4773.46 5176.80 4284.45 4559.04 5083.65 3081.05 9160.15 8370.43 6789.84 2541.09 18185.59 6867.61 5382.90 5785.77 62
TSAR-MVS + MP.78.44 1078.28 1078.90 1684.96 3761.41 2784.03 2683.82 3559.34 11179.37 589.76 2659.84 487.62 2776.69 1186.74 3587.68 14
ACMMPcopyleft76.02 3375.33 3578.07 2785.20 3361.91 2285.49 1684.44 1863.04 3769.80 8189.74 2745.43 13787.16 3472.01 3382.87 5885.14 92
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
UA-Net73.13 5772.93 5573.76 9083.58 5051.66 14478.75 9577.66 16967.75 372.61 5389.42 2849.82 7083.29 12353.61 16083.14 5286.32 47
VDDNet71.81 7471.33 7173.26 11882.80 5747.60 21478.74 9675.27 19459.59 10472.94 4989.40 2941.51 17683.91 11158.75 13182.99 5588.26 5
SD-MVS77.70 1777.62 1577.93 3184.47 4461.88 2384.55 1983.87 3360.37 7779.89 489.38 3054.97 2585.58 6976.12 1284.94 4486.33 46
NCCC78.58 878.31 979.39 587.51 362.61 1685.20 1784.42 1966.73 974.67 2889.38 3055.30 2389.18 674.19 2087.34 2786.38 40
3Dnovator+66.72 475.84 3774.57 4079.66 382.40 5959.92 4285.83 1086.32 566.92 867.80 12189.24 3242.03 16489.38 464.07 8586.50 3889.69 1
test_prior376.89 2776.96 2176.69 4384.20 4657.27 7081.75 5884.88 1460.37 7775.01 2089.06 3356.22 1786.43 5372.19 3188.96 886.38 40
test_prior281.75 5860.37 7775.01 2089.06 3356.22 1772.19 3188.96 8
VDD-MVS72.50 6372.09 6173.75 9281.58 6649.69 19177.76 12377.63 17063.21 3573.21 4589.02 3542.14 16383.32 12261.72 11782.50 6088.25 6
CDPH-MVS76.31 3075.67 3378.22 2685.35 3259.14 4981.31 6884.02 2656.32 14774.05 3188.98 3653.34 4287.92 2369.23 4388.42 1287.59 16
agg_prior175.94 3576.01 3075.72 5685.04 3459.96 4081.44 6681.04 9256.14 15274.68 2688.90 3753.91 3584.04 10675.01 1787.92 2483.16 158
DeepC-MVS_fast68.24 377.25 2276.63 2579.12 1086.15 1860.86 3384.71 1884.85 1661.98 5873.06 4888.88 3853.72 3889.06 868.27 4688.04 2187.42 23
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
TEST985.58 2761.59 2581.62 6281.26 8655.65 16074.93 2288.81 3953.70 3984.68 94
train_agg76.27 3176.15 2876.64 4685.58 2761.59 2581.62 6281.26 8655.86 15474.93 2288.81 3953.70 3984.68 9475.24 1588.33 1383.65 147
test_885.40 3060.96 3281.54 6581.18 8955.86 15474.81 2588.80 4153.70 3984.45 99
LFMVS71.78 7571.59 6572.32 14783.40 5146.38 22279.75 8671.08 22264.18 2772.80 5188.64 4242.58 16183.72 11457.41 13784.49 4686.86 35
agg_prior376.13 3275.89 3276.85 4185.76 2362.02 2181.65 6081.01 9455.51 16273.73 3888.60 4353.23 4384.90 8775.24 1588.33 1383.65 147
MCST-MVS77.48 2077.45 1677.54 3386.67 858.36 5883.22 3586.93 156.91 13774.91 2488.19 4459.15 987.68 2673.67 2587.45 2686.57 39
MG-MVS73.96 5073.89 4674.16 8185.65 2549.69 19181.59 6481.29 8561.45 6271.05 6488.11 4551.77 5487.73 2561.05 12083.09 5385.05 95
Vis-MVSNetpermissive72.18 6971.37 7074.61 7681.29 7255.41 10380.90 7178.28 16260.73 7169.23 9788.09 4644.36 15082.65 14857.68 13481.75 6685.77 62
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
CPTT-MVS72.78 6072.08 6274.87 7084.88 4261.41 2784.15 2577.86 16555.27 16467.51 12588.08 4741.93 16681.85 16069.04 4580.01 8481.35 185
旧先验183.04 5353.15 12467.52 24287.85 4844.08 15180.76 7178.03 221
OPM-MVS74.73 4374.25 4376.19 4980.81 8059.01 5182.60 4683.64 3863.74 3272.52 5487.49 4947.18 11885.88 6569.47 4280.78 7083.66 146
testdata64.66 23581.52 6752.93 12765.29 25446.09 24873.88 3687.46 5038.08 20666.26 26853.31 16378.48 10774.78 256
IS-MVSNet71.57 7771.00 7673.27 11778.86 10945.63 22580.22 7978.69 14964.14 2866.46 13587.36 5149.30 7685.60 6750.26 18083.71 5188.59 3
LPG-MVS_test72.74 6171.74 6475.76 5480.22 8957.51 6882.55 4783.40 4561.32 6366.67 13387.33 5239.15 19486.59 4767.70 5177.30 11883.19 155
LGP-MVS_train75.76 5480.22 8957.51 6883.40 4561.32 6366.67 13387.33 5239.15 19486.59 4767.70 5177.30 11883.19 155
EPNet73.09 5872.16 6075.90 5275.95 16656.28 8583.05 3672.39 21866.53 1265.27 15087.00 5450.40 6785.47 7362.48 10286.32 3985.94 56
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
MSLP-MVS++73.77 5373.47 5074.66 7383.02 5459.29 4882.30 5381.88 6959.34 11171.59 6286.83 5545.94 13083.65 11665.09 7085.22 4381.06 191
nrg03072.96 5973.01 5472.84 12775.41 17450.24 17280.02 8182.89 5958.36 12574.44 2986.73 5658.90 1080.83 17865.84 6574.46 13787.44 22
FIs70.82 8571.43 6768.98 19678.33 12238.14 27276.96 14383.59 3961.02 6767.33 12786.73 5655.07 2481.64 16354.61 15479.22 9787.14 30
alignmvs73.86 5273.99 4573.45 10678.20 12550.50 16578.57 9982.43 6259.40 10976.57 1286.71 5856.42 1681.23 17165.84 6581.79 6488.62 2
112168.53 13767.16 14372.63 13285.64 2661.14 2973.95 19566.46 24944.61 26170.28 7086.68 5941.42 17780.78 18053.62 15881.79 6475.97 238
新几何170.76 17485.66 2461.13 3066.43 25044.68 26070.29 6986.64 6041.29 17975.23 23549.72 18581.75 6675.93 241
VNet69.68 11170.19 8568.16 20479.73 9841.63 25670.53 23177.38 17560.37 7770.69 6586.63 6151.08 6177.09 22353.61 16081.69 6885.75 64
原ACMM174.69 7285.39 3159.40 4583.42 4451.47 20370.27 7186.61 6248.61 10186.51 5153.85 15787.96 2278.16 219
3Dnovator64.47 572.49 6471.39 6975.79 5377.70 13858.99 5280.66 7583.15 5362.24 5165.46 14786.59 6342.38 16285.52 7159.59 12984.72 4582.85 164
PHI-MVS75.87 3675.36 3477.41 3580.62 8455.91 9484.28 2185.78 756.08 15373.41 4386.58 6450.94 6488.54 1170.79 3989.71 487.79 12
canonicalmvs74.67 4474.98 3873.71 9478.94 10850.56 16380.23 7883.87 3360.30 8177.15 1186.56 6559.65 582.00 15866.01 6382.12 6288.58 4
FC-MVSNet-test69.80 10970.58 8167.46 20977.61 14634.73 29276.05 16283.19 5260.84 6865.88 14486.46 6654.52 3080.76 18252.52 16678.12 10986.91 33
OMC-MVS71.40 8170.60 8073.78 8876.60 15853.15 12479.74 8779.78 11758.37 12468.75 10186.45 6745.43 13780.60 18362.58 10077.73 11187.58 18
QAPM70.05 10568.81 10873.78 8876.54 16053.43 12083.23 3483.48 4152.89 18765.90 14386.29 6841.55 17586.49 5251.01 17578.40 10881.42 183
ACMP63.53 672.30 6771.20 7475.59 6280.28 8857.54 6782.74 4382.84 6060.58 7365.24 15286.18 6939.25 19386.03 6066.95 5976.79 12483.22 153
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
test22283.14 5258.68 5572.57 21363.45 26441.78 27967.56 12486.12 7037.13 21378.73 10474.98 252
HQP_MVS74.31 4673.73 4776.06 5081.41 7056.31 8384.22 2284.01 2764.52 2369.27 9486.10 7145.26 14187.21 3268.16 4780.58 7484.65 107
plane_prior486.10 71
XVG-OURS-SEG-HR68.81 12767.47 13172.82 12974.40 18756.87 8070.59 23079.04 14254.77 17166.99 13086.01 7339.57 19178.21 21162.54 10173.33 15383.37 150
MVS_111021_HR74.02 4973.46 5175.69 5883.01 5560.63 3677.29 13678.40 16061.18 6670.58 6685.97 7454.18 3384.00 11067.52 5482.98 5682.45 170
MVS_030575.96 3475.30 3677.97 3081.13 7757.59 6682.11 5483.22 5167.54 469.39 9285.95 7551.47 5788.72 1072.57 2984.29 4887.59 16
PAPM_NR72.63 6271.80 6375.13 6781.72 6553.42 12179.91 8383.28 5059.14 11366.31 13985.90 7651.86 5386.06 5857.45 13680.62 7285.91 57
EPP-MVSNet72.16 7171.31 7274.71 7178.68 11549.70 18982.10 5581.65 7460.40 7665.94 14285.84 7751.74 5586.37 5555.93 14379.55 9288.07 8
VPNet67.52 15868.11 12065.74 22879.18 10336.80 28072.17 21872.83 21662.04 5667.79 12285.83 7848.88 9876.60 22851.30 17472.97 15583.81 136
114514_t70.83 8469.56 9474.64 7586.21 1654.63 10982.34 4981.81 7248.22 22963.01 17485.83 7840.92 18487.10 3657.91 13379.79 8882.18 173
XVG-OURS68.76 13067.37 13472.90 12474.32 18857.22 7270.09 23778.81 14655.24 16567.79 12285.81 8036.54 21778.28 21062.04 11275.74 13083.19 155
PS-MVSNAJss72.24 6871.21 7375.31 6578.50 11855.93 9381.63 6182.12 6556.24 15070.02 7585.68 8147.05 11984.34 10165.27 6974.41 13985.67 67
DP-MVS Recon72.15 7270.73 7976.40 4886.57 1057.99 6281.15 7082.96 5557.03 13566.78 13285.56 8244.50 14788.11 1951.77 17180.23 8383.10 159
OpenMVScopyleft61.03 968.85 12667.56 12772.70 13174.26 18953.99 11381.21 6981.34 8352.70 18862.75 17785.55 8338.86 19784.14 10448.41 19583.01 5479.97 204
NP-MVS80.98 7956.05 9185.54 84
HQP-MVS73.45 5472.80 5675.40 6380.66 8154.94 10582.31 5083.90 3162.10 5367.85 11685.54 8445.46 13586.93 3867.04 5780.35 8084.32 115
TranMVSNet+NR-MVSNet70.36 10070.10 8771.17 16878.64 11642.97 24776.53 15081.16 9066.95 668.53 10585.42 8651.61 5683.07 12952.32 16769.70 20387.46 21
PCF-MVS61.88 870.95 8369.49 9975.35 6477.63 14155.71 9676.04 16381.81 7250.30 21269.66 8285.40 8752.51 4784.89 8851.82 17080.24 8285.45 77
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
Vis-MVSNet (Re-imp)63.69 20463.88 18863.14 24374.75 17931.04 30671.16 22563.64 26356.32 14759.80 21684.99 8844.51 14675.46 23439.12 25780.62 7282.92 161
TAPA-MVS59.36 1066.60 17665.20 17870.81 17376.63 15748.75 20076.52 15180.04 11550.64 21065.24 15284.93 8939.15 19478.54 20736.77 26776.88 12185.14 92
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
CSCG76.92 2576.75 2377.41 3583.96 4859.60 4382.95 3886.50 360.78 7075.27 1984.83 9060.76 386.56 4967.86 5087.87 2586.06 54
VPA-MVSNet69.02 12469.47 10167.69 20877.42 14941.00 26074.04 19479.68 11960.06 8469.26 9684.81 9151.06 6277.58 21854.44 15574.43 13884.48 113
MVS_Test72.45 6572.46 5972.42 14474.88 17848.50 20376.28 15583.14 5459.40 10972.46 5584.68 9255.66 2181.12 17265.98 6479.66 8987.63 15
MVS_111021_LR69.50 11668.78 10971.65 15678.38 12159.33 4774.82 18670.11 22858.08 12767.83 12084.68 9241.96 16576.34 23165.62 6777.54 11279.30 212
LS3D64.71 19762.50 20471.34 16379.72 9955.71 9679.82 8474.72 20448.50 22656.62 24284.62 9433.59 23882.34 15329.65 29675.23 13375.97 238
PAPR71.72 7670.82 7874.41 8081.20 7551.17 14879.55 9083.33 4855.81 15766.93 13184.61 9550.95 6386.06 5855.79 14679.20 9886.00 55
UniMVSNet_NR-MVSNet71.11 8271.00 7671.44 15979.20 10244.13 23676.02 16482.60 6166.48 1368.20 10984.60 9656.82 1382.82 13854.62 15270.43 18187.36 26
DU-MVS70.01 10669.53 9571.44 15978.05 13144.13 23675.01 18181.51 7764.37 2668.20 10984.52 9749.12 9482.82 13854.62 15270.43 18187.37 24
NR-MVSNet69.54 11568.85 10771.59 15878.05 13143.81 24074.20 19380.86 9865.18 1662.76 17684.52 9752.35 5183.59 11750.96 17670.78 17687.37 24
TSAR-MVS + GP.74.90 4174.15 4477.17 3882.00 6258.77 5481.80 5778.57 15158.58 11974.32 3084.51 9955.94 1987.22 3167.11 5684.48 4785.52 72
UGNet68.81 12767.39 13373.06 12178.33 12254.47 11079.77 8575.40 19360.45 7563.22 17184.40 10032.71 24980.91 17751.71 17280.56 7683.81 136
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
ACMM61.98 770.80 8669.73 8974.02 8280.59 8558.59 5682.68 4482.02 6855.46 16367.18 12884.39 10138.51 19983.17 12660.65 12176.10 12880.30 200
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
BH-RMVSNet68.81 12767.42 13272.97 12280.11 9252.53 13374.26 19276.29 18358.48 12268.38 10784.20 10242.59 16083.83 11346.53 20475.91 12982.56 166
AdaColmapbinary69.99 10768.66 11173.97 8484.94 3957.83 6382.63 4578.71 14856.28 14964.34 16484.14 10341.57 17287.06 3746.45 20578.88 10177.02 231
jajsoiax68.25 14666.45 15973.66 9675.62 17055.49 10180.82 7278.51 15452.33 19264.33 16584.11 10428.28 27381.81 16263.48 9570.62 17883.67 145
mvs_tets68.18 15066.36 16373.63 9975.61 17155.35 10480.77 7378.56 15252.48 19164.27 16784.10 10527.45 27981.84 16163.45 9670.56 18083.69 142
PEN-MVS66.60 17666.45 15967.04 21377.11 15136.56 28277.03 14280.42 11162.95 3862.51 18284.03 10646.69 12579.07 20244.22 22463.08 25085.51 73
PAPM67.92 15366.69 15571.63 15778.09 12949.02 19877.09 14081.24 8851.04 20860.91 20483.98 10747.71 11184.99 7940.81 25079.32 9680.90 193
DTE-MVSNet65.58 18765.34 17566.31 21876.06 16534.79 29076.43 15279.38 13762.55 4761.66 19583.83 10845.60 13379.15 20041.64 24860.88 26585.00 96
PS-CasMVS66.42 18066.32 16566.70 21677.60 14736.30 28676.94 14479.61 12162.36 5062.43 18683.66 10945.69 13178.37 20845.35 22163.26 24885.42 80
WR-MVS68.47 13868.47 11468.44 20380.20 9139.84 26273.75 20076.07 18664.68 2068.11 11383.63 11050.39 6879.14 20149.78 18269.66 20486.34 45
UniMVSNet (Re)70.63 9070.20 8471.89 15178.55 11745.29 22675.94 16582.92 5663.68 3368.16 11183.59 11153.89 3683.49 11953.97 15671.12 17486.89 34
CNLPA65.43 18964.02 18669.68 18878.73 11458.07 6177.82 12270.71 22551.49 20261.57 19783.58 11238.23 20470.82 24943.90 22870.10 19580.16 202
ab-mvs66.65 17566.42 16167.37 21076.17 16241.73 25470.41 23476.14 18553.99 18065.98 14183.51 11349.48 7376.24 23248.60 19373.46 15184.14 129
test_djsdf69.45 11867.74 12474.58 7774.57 18354.92 10782.79 4178.48 15551.26 20665.41 14883.49 11438.37 20183.24 12466.06 6169.25 20785.56 70
CP-MVSNet66.49 17966.41 16266.72 21577.67 14036.33 28476.83 14679.52 13262.45 4862.54 18083.47 11546.32 12778.37 20845.47 21963.43 24785.45 77
MVSFormer71.50 7970.38 8374.88 6978.76 11257.15 7782.79 4178.48 15551.26 20669.49 8883.22 11643.99 15383.24 12466.06 6179.37 9384.23 122
jason69.65 11268.39 11673.43 10878.27 12456.88 7977.12 13973.71 21246.53 24369.34 9383.22 11643.37 15779.18 19964.77 7279.20 9884.23 122
jason: jason.
pm-mvs165.24 19264.97 18266.04 22372.38 22639.40 26572.62 21275.63 19055.53 16162.35 18783.18 11847.45 11676.47 22949.06 19066.54 22482.24 172
Baseline_NR-MVSNet67.05 16767.56 12765.50 23075.65 16937.70 27675.42 17174.65 20559.90 8968.14 11283.15 11949.12 9477.20 22152.23 16869.78 20081.60 180
DELS-MVS74.76 4274.46 4175.65 5977.84 13652.25 13875.59 16884.17 2463.76 3173.15 4682.79 12059.58 786.80 4067.24 5586.04 4087.89 9
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
GBi-Net67.21 16266.55 15669.19 19377.63 14143.33 24377.31 13377.83 16656.62 14165.04 15582.70 12141.85 16880.33 18647.18 19972.76 15783.92 132
test167.21 16266.55 15669.19 19377.63 14143.33 24377.31 13377.83 16656.62 14165.04 15582.70 12141.85 16880.33 18647.18 19972.76 15783.92 132
FMVSNet166.70 17465.87 16969.19 19377.49 14843.33 24377.31 13377.83 16656.45 14564.60 16282.70 12138.08 20680.33 18646.08 20972.31 16483.92 132
TransMVSNet (Re)64.72 19664.33 18465.87 22775.22 17538.56 26974.66 18875.08 20158.90 11661.79 19282.63 12451.18 6078.07 21343.63 23155.87 28480.99 192
Effi-MVS+73.31 5672.54 5875.62 6077.87 13553.64 11679.62 8979.61 12161.63 6072.02 5982.61 12556.44 1585.97 6363.99 8879.07 10087.25 28
mvs_anonymous68.03 15267.51 13069.59 19072.08 23144.57 23371.99 22075.23 19551.67 19767.06 12982.57 12654.68 2877.94 21456.56 14075.71 13186.26 50
ACMH+57.40 1166.12 18264.06 18572.30 14877.79 13752.83 12880.39 7778.03 16457.30 13257.47 23882.55 12727.68 27784.17 10345.54 21669.78 20079.90 205
WR-MVS_H67.02 16866.92 14767.33 21277.95 13437.75 27577.57 12982.11 6662.03 5762.65 17982.48 12850.57 6679.46 19442.91 23864.01 24284.79 104
LTVRE_ROB55.42 1663.15 20761.23 21268.92 19776.57 15947.80 21059.92 28176.39 18254.35 17758.67 22982.46 12929.44 26881.49 16742.12 24271.14 17377.46 224
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
DP-MVS65.68 18563.66 19271.75 15484.93 4056.87 8080.74 7473.16 21553.06 18559.09 22582.35 13036.79 21585.94 6432.82 28469.96 19772.45 273
API-MVS72.17 7071.41 6874.45 7981.95 6357.22 7284.03 2680.38 11259.89 9168.40 10682.33 13149.64 7287.83 2451.87 16984.16 5078.30 217
pmmvs663.69 20462.82 20166.27 22070.63 24839.27 26673.13 20675.47 19252.69 18959.75 21782.30 13239.71 18977.03 22447.40 19864.35 24182.53 167
RPSCF55.80 25254.22 25660.53 25765.13 28842.91 24864.30 26457.62 28936.84 30258.05 23582.28 13328.01 27456.24 30637.14 26558.61 27982.44 171
cdsmvs_eth3d_5k17.50 30723.34 3040.00 3240.00 3370.00 3370.00 32978.63 1500.00 3330.00 33482.18 13449.25 850.00 3340.00 3330.00 3310.00 332
lupinMVS69.57 11468.28 11773.44 10778.76 11257.15 7776.57 14973.29 21446.19 24769.49 8882.18 13443.99 15379.23 19864.66 7379.37 9383.93 131
FMVSNet266.93 17066.31 16668.79 19977.63 14142.98 24676.11 15977.47 17256.62 14165.22 15482.17 13641.85 16880.18 18947.05 20272.72 16083.20 154
PVSNet_Blended_VisFu71.45 8070.39 8274.65 7482.01 6158.82 5379.93 8280.35 11455.09 16665.82 14682.16 13749.17 9182.64 14960.34 12478.62 10682.50 169
v2v48270.50 9469.45 10273.66 9672.62 22350.03 18277.58 12880.51 10959.90 8969.52 8782.14 13847.53 11484.88 9065.07 7170.17 19386.09 53
v870.33 10169.28 10473.49 10473.15 20650.22 17378.62 9880.78 9960.79 6966.45 13682.11 13949.35 7484.98 8163.58 9468.71 21185.28 88
PLCcopyleft56.13 1465.09 19463.21 19670.72 17681.04 7854.87 10878.57 9977.47 17248.51 22555.71 24781.89 14033.71 23679.71 19141.66 24670.37 18677.58 223
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
v1070.21 10369.02 10673.81 8773.51 19350.92 15178.74 9681.39 8160.05 8566.39 13781.83 14147.58 11285.41 7662.80 9968.86 21085.09 94
diffmvs67.72 15766.73 15370.70 17769.74 26047.69 21373.33 20474.74 20353.30 18464.51 16381.80 14249.25 8579.02 20359.15 13074.75 13585.39 85
TAMVS66.78 17365.27 17771.33 16479.16 10553.67 11573.84 19969.59 23452.32 19365.28 14981.72 14344.49 14877.40 22042.32 24178.66 10582.92 161
v1neww70.66 8769.70 9073.53 10173.15 20650.22 17378.11 11080.68 10059.65 9969.83 7881.67 14449.29 7884.96 8364.55 7670.38 18485.42 80
v7new70.66 8769.70 9073.53 10173.15 20650.22 17378.11 11080.68 10059.65 9969.83 7881.67 14449.29 7884.96 8364.55 7670.38 18485.42 80
v670.66 8769.70 9073.53 10173.14 20950.21 17678.11 11080.67 10259.65 9969.82 8081.65 14649.29 7884.96 8364.55 7670.39 18385.42 80
v7n69.01 12567.36 13573.98 8372.51 22552.65 13078.54 10181.30 8460.26 8262.67 17881.62 14743.61 15584.49 9857.01 13968.70 21284.79 104
BH-untuned68.27 14467.29 13771.21 16679.74 9753.22 12376.06 16177.46 17457.19 13366.10 14081.61 14845.37 13983.50 11845.42 22076.68 12676.91 234
F-COLMAP63.05 20860.87 21469.58 19176.99 15653.63 11778.12 10976.16 18447.97 23352.41 27381.61 14827.87 27578.11 21240.07 25366.66 22377.00 232
IterMVS-LS69.22 12368.48 11371.43 16174.44 18649.40 19476.23 15777.55 17159.60 10265.85 14581.59 15051.28 5981.58 16659.87 12769.90 19883.30 151
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
COLMAP_ROBcopyleft52.97 1761.27 22258.81 22368.64 20074.63 18152.51 13478.42 10473.30 21349.92 21650.96 27881.51 15123.06 29879.40 19531.63 28965.85 22774.01 263
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
v770.57 9169.48 10073.85 8573.50 19450.92 15178.27 10581.43 7958.93 11469.61 8381.49 15247.56 11385.43 7563.94 8970.62 17885.21 91
v114170.50 9469.53 9573.41 11072.92 21650.00 18377.69 12480.60 10459.50 10669.60 8481.43 15349.24 8884.77 9164.48 8070.30 19085.46 76
divwei89l23v2f11270.50 9469.53 9573.41 11072.91 21750.00 18377.69 12480.59 10559.50 10669.60 8481.43 15349.26 8384.77 9164.48 8070.31 18985.47 74
v170.50 9469.53 9573.42 10972.91 21750.00 18377.69 12480.59 10559.50 10669.59 8681.42 15549.26 8384.77 9164.49 7970.30 19085.47 74
xiu_mvs_v1_base_debu68.58 13367.28 13872.48 13878.19 12657.19 7475.28 17475.09 19851.61 19870.04 7281.41 15632.79 24579.02 20363.81 9077.31 11581.22 187
xiu_mvs_v1_base68.58 13367.28 13872.48 13878.19 12657.19 7475.28 17475.09 19851.61 19870.04 7281.41 15632.79 24579.02 20363.81 9077.31 11581.22 187
xiu_mvs_v1_base_debi68.58 13367.28 13872.48 13878.19 12657.19 7475.28 17475.09 19851.61 19870.04 7281.41 15632.79 24579.02 20363.81 9077.31 11581.22 187
MVS_dtu67.73 15566.31 16672.00 15077.04 15348.70 20176.70 14774.99 20257.07 13461.42 19881.29 15934.24 23082.66 14757.56 13576.47 12784.65 107
v114470.42 9969.31 10373.76 9073.22 20250.64 15877.83 12181.43 7958.58 11969.40 9181.16 16047.53 11485.29 7864.01 8770.64 17785.34 86
FMVSNet366.32 18165.61 17268.46 20276.48 16142.34 25074.98 18377.15 17855.83 15665.04 15581.16 16039.91 18680.14 19047.18 19972.76 15782.90 163
XVG-ACMP-BASELINE64.36 20162.23 20570.74 17572.35 22752.45 13670.80 22978.45 15753.84 18159.87 21481.10 16216.24 30879.32 19755.64 14871.76 16880.47 197
CLD-MVS73.33 5572.68 5775.29 6678.82 11053.33 12278.23 10784.79 1761.30 6570.41 6881.04 16352.41 5087.12 3564.61 7582.49 6185.41 84
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
ACMH55.70 1565.20 19363.57 19370.07 18478.07 13052.01 14379.48 9379.69 11855.75 15856.59 24380.98 16427.12 28180.94 17542.90 23971.58 17077.25 230
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
OurMVSNet-221017-061.37 22158.63 22669.61 18972.05 23248.06 20773.93 19872.51 21747.23 23954.74 25680.92 16521.49 30281.24 17048.57 19456.22 28379.53 209
HY-MVS56.14 1364.55 20063.89 18766.55 21774.73 18041.02 25869.96 23874.43 20649.29 21861.66 19580.92 16547.43 11776.68 22744.91 22371.69 16981.94 176
XXY-MVS60.68 22361.67 20857.70 26970.43 25038.45 27064.19 26566.47 24848.05 23263.22 17180.86 16749.28 8160.47 28645.25 22267.28 22274.19 261
v119269.97 10868.68 11073.85 8573.19 20550.94 14977.68 12781.36 8257.51 13168.95 10080.85 16845.28 14085.33 7762.97 9870.37 18685.27 89
anonymousdsp67.00 16964.82 18373.57 10070.09 25456.13 8876.35 15377.35 17648.43 22764.99 15880.84 16933.01 24280.34 18564.66 7367.64 22084.23 122
test_040263.25 20661.01 21369.96 18580.00 9354.37 11176.86 14572.02 22054.58 17358.71 22880.79 17035.00 22384.36 10026.41 30564.71 23671.15 285
DI_MVS_plusplus_test69.35 11968.03 12173.30 11671.11 24450.14 17975.49 17079.16 14054.57 17462.45 18480.76 17144.67 14584.20 10264.23 8379.81 8785.54 71
Regformer-175.47 3974.93 3977.09 3980.43 8657.70 6579.50 9182.13 6467.84 175.73 1880.75 17256.50 1486.07 5771.07 3880.38 7887.50 19
Regformer-275.63 3874.99 3777.54 3380.43 8658.32 5979.50 9182.92 5667.84 175.94 1580.75 17255.73 2086.80 4071.44 3780.38 7887.50 19
test_normal69.26 12167.90 12373.32 11570.84 24750.38 16875.30 17379.17 13954.23 17862.00 18880.61 17444.69 14483.89 11264.33 8279.95 8685.69 66
v14419269.71 11068.51 11273.33 11473.10 21150.13 18077.54 13080.64 10356.65 14068.57 10480.55 17546.87 12484.96 8362.98 9769.66 20484.89 100
v124069.24 12267.91 12273.25 11973.02 21449.82 18677.21 13780.54 10856.43 14668.34 10880.51 17643.33 15884.99 7962.03 11369.77 20284.95 99
v74867.26 16165.67 17172.02 14969.90 25849.77 18876.24 15679.57 13058.58 11960.49 21080.38 17744.47 14982.17 15656.16 14265.26 23384.12 130
v192192069.47 11768.17 11973.36 11373.06 21250.10 18177.39 13280.56 10756.58 14468.59 10280.37 17844.72 14384.98 8162.47 10369.82 19985.00 96
MVSTER67.16 16465.58 17371.88 15270.37 25249.70 18970.25 23678.45 15751.52 20169.16 9880.37 17838.45 20082.50 15060.19 12571.46 17183.44 149
ITE_SJBPF62.09 25066.16 28244.55 23464.32 26047.36 23855.31 25280.34 18019.27 30462.68 28036.29 27462.39 25579.04 214
TR-MVS66.59 17865.07 18171.17 16879.18 10349.63 19373.48 20375.20 19652.95 18667.90 11580.33 18139.81 18883.68 11543.20 23573.56 15080.20 201
Regformer-373.89 5173.28 5375.71 5779.75 9555.48 10278.54 10179.93 11666.58 1173.62 4080.30 18254.87 2684.54 9769.09 4476.84 12287.10 31
Regformer-474.25 4873.48 4976.57 4779.75 9556.54 8278.54 10181.49 7866.93 773.90 3580.30 18253.84 3785.98 6269.76 4076.84 12287.17 29
V4268.65 13167.35 13672.56 13568.93 26350.18 17772.90 20979.47 13356.92 13669.45 9080.26 18446.29 12882.99 13064.07 8567.82 21784.53 111
CDS-MVSNet66.80 17265.37 17471.10 17078.98 10753.13 12673.27 20571.07 22352.15 19464.72 16080.23 18543.56 15677.10 22245.48 21878.88 10183.05 160
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
v14868.24 14867.19 14271.40 16270.43 25047.77 21275.76 16777.03 17958.91 11567.36 12680.10 18648.60 10281.89 15960.01 12666.52 22584.53 111
Test_1112_low_res62.32 21261.77 20764.00 23979.08 10639.53 26468.17 24570.17 22743.25 27259.03 22679.90 18744.08 15171.24 24843.79 23068.42 21381.25 186
mvs-test170.44 9868.19 11877.18 3776.10 16363.22 680.59 7676.06 18759.83 9366.32 13879.87 18841.56 17385.53 7060.60 12272.77 15682.80 165
AllTest57.08 24454.65 25164.39 23771.44 23949.03 19669.92 23967.30 24345.97 25047.16 28979.77 18917.47 30567.56 26133.65 28159.16 27776.57 235
TestCases64.39 23771.44 23949.03 19667.30 24345.97 25047.16 28979.77 18917.47 30567.56 26133.65 28159.16 27776.57 235
MVS_test032667.73 15566.55 15671.28 16575.71 16847.88 20977.14 13878.26 16356.89 13860.74 20779.74 19135.74 22182.26 15457.39 13877.35 11483.71 141
PVSNet_BlendedMVS68.56 13667.72 12571.07 17177.03 15450.57 16174.50 19081.52 7553.66 18264.22 16879.72 19249.13 9282.87 13655.82 14473.92 14479.77 207
xiu_mvs_v2_base70.52 9269.75 8872.84 12781.21 7455.63 9975.11 17978.92 14454.92 16969.96 7679.68 19347.00 12382.09 15761.60 11979.37 9380.81 195
Fast-Effi-MVS+70.28 10269.12 10573.73 9378.50 11851.50 14775.01 18179.46 13456.16 15168.59 10279.55 19453.97 3484.05 10553.34 16277.53 11385.65 69
LCM-MVSNet-Re61.88 21761.35 21063.46 24074.58 18231.48 30561.42 27558.14 28658.71 11853.02 27279.55 19443.07 15976.80 22545.69 21377.96 11082.11 175
EPNet_dtu61.90 21561.97 20661.68 25172.89 21939.78 26375.85 16665.62 25255.09 16654.56 25979.36 19637.59 20967.02 26439.80 25676.95 12078.25 218
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
EI-MVSNet-Vis-set72.42 6671.59 6574.91 6878.47 12054.02 11277.05 14179.33 13865.03 1971.68 6179.35 19752.75 4684.89 8866.46 6074.23 14085.83 59
SixPastTwentyTwo61.65 21958.80 22470.20 18375.80 16747.22 21775.59 16869.68 23254.61 17254.11 26479.26 19827.07 28282.96 13143.27 23349.79 30280.41 199
testgi51.90 26752.37 26450.51 29460.39 30723.55 32358.42 28558.15 28549.03 22151.83 27579.21 19922.39 29955.59 30829.24 29762.64 25272.40 277
WTY-MVS59.75 22860.39 21657.85 26772.32 22837.83 27461.05 27964.18 26145.95 25261.91 19079.11 20047.01 12260.88 28542.50 24069.49 20674.83 254
Test467.77 15465.97 16873.19 12068.64 26450.58 16074.80 18780.48 11054.13 17959.11 22479.07 20133.89 23583.12 12863.61 9379.98 8585.87 58
EI-MVSNet-UG-set71.92 7371.06 7574.52 7877.98 13353.56 11876.62 14879.16 14064.40 2571.18 6378.95 20252.19 5284.66 9665.47 6873.57 14985.32 87
MAR-MVS71.51 7870.15 8675.60 6181.84 6459.39 4681.38 6782.90 5854.90 17068.08 11478.70 20347.73 11085.51 7251.68 17384.17 4981.88 178
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
PS-MVSNAJ70.51 9369.70 9072.93 12381.52 6755.79 9574.92 18479.00 14355.04 16869.88 7778.66 20447.05 11982.19 15561.61 11879.58 9080.83 194
MVP-Stereo65.41 19063.80 18970.22 18177.62 14555.53 10076.30 15478.53 15350.59 21156.47 24478.65 20539.84 18782.68 14644.10 22772.12 16672.44 274
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
CHOSEN 1792x268865.08 19562.84 20071.82 15381.49 6956.26 8666.32 25274.20 20940.53 28963.16 17378.65 20541.30 17877.80 21645.80 21274.09 14181.40 184
V467.09 16565.16 17972.87 12566.76 27951.60 14573.69 20179.45 13557.88 12862.45 18478.58 20740.96 18283.34 12061.99 11464.71 23683.68 143
v5267.09 16565.16 17972.87 12566.77 27851.60 14573.69 20179.45 13557.88 12862.46 18378.57 20840.95 18383.34 12061.99 11464.70 23883.68 143
MVS67.37 15966.33 16470.51 17975.46 17350.94 14973.95 19581.85 7141.57 28362.54 18078.57 20847.98 10785.47 7352.97 16482.05 6375.14 248
BH-w/o66.85 17165.83 17069.90 18779.29 10052.46 13574.66 18876.65 18154.51 17564.85 15978.12 21045.59 13482.95 13243.26 23475.54 13274.27 260
TDRefinement53.44 26250.72 26861.60 25264.31 29246.96 21870.89 22865.27 25541.78 27944.61 29877.98 21111.52 31966.36 26728.57 30051.59 29671.49 282
HyFIR lowres test65.67 18663.01 19873.67 9579.97 9455.65 9869.07 24375.52 19142.68 27763.53 17077.95 21240.43 18581.64 16346.01 21071.91 16783.73 140
semantic-postprocess65.40 23171.99 23350.80 15569.63 23345.71 25460.61 20877.93 21336.56 21665.99 27055.67 14763.50 24679.42 210
pmmvs461.48 22059.39 22067.76 20771.57 23853.86 11471.42 22165.34 25344.20 26559.46 21877.92 21435.90 21874.71 23843.87 22964.87 23574.71 257
1112_ss64.00 20363.36 19565.93 22679.28 10142.58 24971.35 22272.36 21946.41 24560.55 20977.89 21546.27 12973.28 24146.18 20769.97 19681.92 177
ab-mvs-re6.49 3108.65 3110.00 3240.00 3370.00 3370.00 3290.00 3370.00 3330.00 33477.89 2150.00 3400.00 3340.00 3330.00 3310.00 332
CMPMVSbinary42.80 2157.81 24055.97 24463.32 24160.98 30447.38 21664.66 26369.50 23532.06 31046.83 29177.80 21729.50 26771.36 24748.68 19273.75 14571.21 284
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
PVSNet_Blended68.59 13267.72 12571.19 16777.03 15450.57 16172.51 21481.52 7551.91 19664.22 16877.77 21849.13 9282.87 13655.82 14479.58 9080.14 203
USDC56.35 24754.24 25562.69 24764.74 28940.31 26165.05 26173.83 21143.93 26847.58 28777.71 21915.36 31075.05 23738.19 26161.81 25772.70 269
v1368.29 14266.84 14872.63 13273.50 19450.83 15478.25 10679.58 12860.05 8560.76 20677.68 22049.11 9782.77 14062.17 10960.45 27384.30 117
v1268.28 14366.83 15072.60 13473.43 19650.74 15678.18 10879.59 12660.01 8760.89 20577.66 22149.12 9482.77 14062.18 10760.46 27284.29 118
V968.27 14466.84 14872.56 13573.39 19950.63 15978.10 11379.60 12359.94 8861.05 20377.62 22249.18 9082.77 14062.17 10960.48 27184.27 119
v1768.37 14067.00 14572.48 13873.22 20250.31 16978.10 11379.58 12859.71 9761.67 19477.60 22349.31 7582.89 13462.37 10461.48 26284.23 122
v1668.38 13967.01 14472.47 14273.22 20250.29 17078.10 11379.59 12659.71 9761.72 19377.60 22349.28 8182.89 13462.36 10561.54 25984.23 122
V1468.25 14666.82 15172.52 13773.33 20050.53 16478.02 11679.60 12359.83 9361.16 20177.57 22549.19 8982.77 14062.18 10760.50 27084.26 120
v1168.15 15166.73 15372.42 14473.43 19650.28 17177.94 11979.65 12059.88 9261.11 20277.55 22648.25 10582.75 14561.88 11660.85 26684.23 122
v1568.22 14966.81 15272.47 14273.25 20150.40 16777.92 12079.60 12359.77 9661.28 19977.52 22749.25 8582.77 14062.16 11160.51 26984.24 121
v1868.33 14166.96 14672.42 14473.13 21050.16 17877.97 11879.57 13059.57 10561.80 19177.50 22849.30 7682.90 13362.31 10661.50 26084.20 128
test20.0353.87 26054.02 25753.41 28561.47 30028.11 31261.30 27659.21 28251.34 20552.09 27477.43 22933.29 24158.55 29329.76 29560.27 27473.58 265
EG-PatchMatch MVS64.71 19762.87 19970.22 18177.68 13953.48 11977.99 11778.82 14553.37 18356.03 24677.41 23024.75 29584.04 10646.37 20673.42 15273.14 266
Effi-MVS+-dtu69.64 11367.53 12975.95 5176.10 16362.29 1880.20 8076.06 18759.83 9365.26 15177.09 23141.56 17384.02 10960.60 12271.09 17581.53 181
tpm57.34 24258.16 22854.86 27971.80 23734.77 29167.47 24856.04 29848.20 23060.10 21176.92 23237.17 21253.41 31340.76 25165.01 23476.40 237
IterMVS62.79 20961.27 21167.35 21169.37 26152.04 14271.17 22468.24 24152.63 19059.82 21576.91 23337.32 21172.36 24452.80 16563.19 24977.66 222
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
Fast-Effi-MVS+-dtu67.37 15965.33 17673.48 10572.94 21557.78 6477.47 13176.88 18057.60 13061.97 18976.85 23439.31 19280.49 18454.72 15170.28 19282.17 174
GA-MVS65.53 18863.70 19171.02 17270.87 24648.10 20670.48 23274.40 20756.69 13964.70 16176.77 23533.66 23781.10 17355.42 14970.32 18883.87 135
testing_266.02 18363.77 19072.76 13066.03 28450.48 16672.93 20880.36 11354.41 17654.25 26376.76 23630.89 25883.16 12764.19 8474.08 14284.65 107
pmmvs556.47 24555.68 24658.86 26161.41 30136.71 28166.37 25162.75 27040.38 29053.70 26676.62 23734.56 22567.05 26340.02 25565.27 23272.83 268
CostFormer64.04 20262.51 20368.61 20171.88 23545.77 22471.30 22370.60 22647.55 23664.31 16676.61 23841.63 17179.62 19349.74 18469.00 20880.42 198
131464.61 19963.21 19668.80 19871.87 23647.46 21573.95 19578.39 16142.88 27659.97 21276.60 23938.11 20579.39 19654.84 15072.32 16379.55 208
EI-MVSNet69.27 12068.44 11571.73 15574.47 18449.39 19575.20 17778.45 15759.60 10269.16 9876.51 24051.29 5882.50 15059.86 12871.45 17283.30 151
CVMVSNet59.63 23059.14 22261.08 25674.47 18438.84 26775.20 17768.74 23831.15 31158.24 23476.51 24032.39 25468.58 25949.77 18365.84 22875.81 242
K. test v360.47 22457.11 23470.56 17873.74 19248.22 20575.10 18062.55 27158.27 12653.62 26876.31 24227.81 27681.59 16547.42 19739.18 31481.88 178
MSDG61.81 21859.23 22169.55 19272.64 22252.63 13170.45 23375.81 18951.38 20453.70 26676.11 24329.52 26681.08 17437.70 26265.79 22974.93 253
MIMVSNet155.17 25554.31 25457.77 26870.03 25532.01 30365.68 25464.81 25649.19 21946.75 29276.00 24425.53 29164.04 27528.65 29962.13 25677.26 229
OpenMVS_ROBcopyleft52.78 1860.03 22558.14 22965.69 22970.47 24944.82 22875.33 17270.86 22445.04 25656.06 24576.00 24426.89 28479.65 19235.36 27667.29 22172.60 270
MIMVSNet57.35 24157.07 23558.22 26474.21 19037.18 27762.46 27060.88 27848.88 22255.29 25375.99 24631.68 25662.04 28231.87 28772.35 16275.43 247
TinyColmap54.14 25751.72 26561.40 25466.84 27741.97 25166.52 25068.51 24044.81 25842.69 30675.77 24711.66 31872.94 24231.96 28656.77 28269.27 292
Anonymous2023120655.10 25655.30 24854.48 28169.81 25933.94 29662.91 26962.13 27541.08 28455.18 25475.65 24832.75 24856.59 30230.32 29467.86 21672.91 267
lessismore_v069.91 18671.42 24147.80 21050.90 31250.39 28275.56 24927.43 28081.33 16945.91 21134.10 31780.59 196
tpm262.07 21460.10 21867.99 20572.79 22043.86 23971.05 22666.85 24743.14 27462.77 17575.39 25038.32 20280.80 17941.69 24568.88 20979.32 211
sss56.17 24956.57 23954.96 27866.93 27636.32 28557.94 28761.69 27641.67 28158.64 23075.32 25138.72 19856.25 30542.04 24366.19 22672.31 278
tpmp4_e2362.71 21060.13 21770.45 18073.40 19848.39 20472.82 21069.49 23644.88 25759.91 21374.99 25237.79 20881.47 16840.22 25267.71 21981.48 182
CR-MVSNet59.91 22657.90 23265.96 22469.96 25652.07 14065.31 25963.15 26742.48 27859.36 21974.84 25335.83 21970.75 25045.50 21764.65 23975.06 249
Patchmtry57.16 24356.47 24059.23 25869.17 26234.58 29362.98 26863.15 26744.53 26256.83 24174.84 25335.83 21968.71 25840.03 25460.91 26474.39 259
FMVSNet555.86 25154.93 24958.66 26371.05 24536.35 28364.18 26662.48 27246.76 24250.66 28174.73 25525.80 28964.04 27533.11 28365.57 23175.59 245
cascas65.98 18463.42 19473.64 9877.26 15052.58 13272.26 21777.21 17748.56 22461.21 20074.60 25632.57 25385.82 6650.38 17976.75 12582.52 168
MS-PatchMatch62.42 21161.46 20965.31 23275.21 17652.10 13972.05 21974.05 21046.41 24557.42 23974.36 25734.35 22977.57 21945.62 21573.67 14666.26 296
test0.0.03 153.32 26353.59 26052.50 28962.81 29629.45 30959.51 28254.11 30650.08 21454.40 26174.31 25832.62 25055.92 30730.50 29363.95 24372.15 280
pmmvs-eth3d58.81 23256.31 24266.30 21967.61 27252.42 13772.30 21664.76 25743.55 27054.94 25574.19 25928.95 27072.60 24343.31 23257.21 28173.88 264
EU-MVSNet55.61 25354.41 25359.19 25965.41 28733.42 29872.44 21571.91 22128.81 31351.27 27673.87 26024.76 29469.08 25743.04 23658.20 28075.06 249
IB-MVS56.42 1265.40 19162.73 20273.40 11274.89 17752.78 12973.09 20775.13 19755.69 15958.48 23373.73 26132.86 24486.32 5650.63 17770.11 19481.10 190
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
PVSNet50.76 1958.40 23557.39 23361.42 25375.53 17244.04 23861.43 27463.45 26447.04 24156.91 24073.61 26227.00 28364.76 27339.12 25772.40 16175.47 246
Anonymous2023121155.92 25053.63 25962.77 24668.22 27035.56 28874.48 19169.89 22946.42 24449.07 28573.45 26321.13 30376.77 22628.74 29851.30 29875.97 238
gm-plane-assit71.40 24241.72 25548.85 22373.31 26482.48 15248.90 191
PM-MVS52.33 26650.19 26958.75 26262.10 29845.14 22765.75 25340.38 32443.60 26953.52 26972.65 2659.16 32465.87 27150.41 17854.18 29065.24 298
MDTV_nov1_ep1357.00 23672.73 22138.26 27165.02 26264.73 25844.74 25955.46 24972.48 26632.61 25270.47 25237.47 26367.75 218
UnsupCasMVSNet_eth53.16 26552.47 26355.23 27659.45 31133.39 29959.43 28369.13 23745.98 24950.35 28372.32 26729.30 26958.26 29442.02 24444.30 31174.05 262
Patchmatch-test49.08 27448.28 27451.50 29264.40 29130.85 30745.68 31348.46 31735.60 30446.10 29572.10 26834.47 22846.37 31927.08 30360.65 26877.27 228
PatchmatchNetpermissive59.84 22758.24 22764.65 23673.05 21346.70 22169.42 24162.18 27347.55 23658.88 22771.96 26934.49 22769.16 25642.99 23763.60 24578.07 220
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
tpmrst58.24 23658.70 22556.84 27166.97 27534.32 29469.57 24061.14 27747.17 24058.58 23171.60 27041.28 18060.41 28749.20 18962.84 25175.78 243
Patchmatch-test159.75 22858.00 23164.98 23474.14 19148.06 20763.35 26763.23 26649.13 22059.33 22271.46 27137.45 21069.59 25441.39 24962.57 25377.30 226
ambc65.13 23363.72 29437.07 27847.66 31178.78 14754.37 26271.42 27211.24 32080.94 17545.64 21453.85 29277.38 225
EPMVS53.96 25853.69 25854.79 28066.12 28331.96 30462.34 27249.05 31444.42 26455.54 24871.33 27330.22 26256.70 30041.65 24762.54 25475.71 244
PatchMatch-RL56.25 24854.55 25261.32 25577.06 15256.07 9065.57 25554.10 30744.13 26753.49 27171.27 27425.20 29266.78 26536.52 27263.66 24461.12 305
tpmvs58.47 23456.95 23763.03 24570.20 25341.21 25767.90 24767.23 24549.62 21754.73 25770.84 27534.14 23176.24 23236.64 27061.29 26371.64 281
DWT-MVSNet_test61.90 21559.93 21967.83 20671.98 23446.09 22371.03 22769.71 23050.09 21358.51 23270.62 27630.21 26377.63 21749.28 18867.91 21579.78 206
tpm cat159.25 23156.95 23766.15 22172.19 22946.96 21868.09 24665.76 25140.03 29257.81 23670.56 27738.32 20274.51 23938.26 26061.50 26077.00 232
MDA-MVSNet-bldmvs53.87 26050.81 26763.05 24466.25 28148.58 20256.93 29063.82 26248.09 23141.22 30770.48 27830.34 26168.00 26034.24 27945.92 30972.57 271
PatchFormer-LS_test62.20 21360.59 21567.04 21372.18 23046.82 22070.36 23568.62 23951.92 19559.19 22370.23 27936.86 21475.07 23650.23 18165.68 23079.23 213
LF4IMVS42.95 28742.26 28745.04 30248.30 32232.50 30054.80 29448.49 31628.03 31440.51 31170.16 2809.24 32343.89 32331.63 28949.18 30658.72 308
RPMNet58.70 23356.29 24365.96 22469.96 25652.07 14065.31 25962.15 27443.20 27359.36 21970.15 28135.37 22270.75 25036.42 27364.65 23975.06 249
test-LLR58.15 23858.13 23058.22 26468.57 26544.80 22965.46 25657.92 28750.08 21455.44 25069.82 28232.62 25057.44 29649.66 18673.62 14772.41 275
test-mter56.42 24655.82 24558.22 26468.57 26544.80 22965.46 25657.92 28739.94 29355.44 25069.82 28221.92 30157.44 29649.66 18673.62 14772.41 275
PatchT53.17 26453.44 26152.33 29068.29 26925.34 32058.21 28654.41 30444.46 26354.56 25969.05 28433.32 24060.94 28436.93 26661.76 25870.73 287
new-patchmatchnet47.56 27847.73 27647.06 29958.81 3129.37 33148.78 30959.21 28243.28 27144.22 29968.66 28525.67 29057.20 29931.57 29149.35 30574.62 258
dp51.89 26851.60 26652.77 28868.44 26832.45 30162.36 27154.57 30344.16 26649.31 28467.91 28628.87 27256.61 30133.89 28054.89 28769.24 293
MDA-MVSNet_test_wron50.71 27248.95 27156.00 27561.17 30241.84 25251.90 30456.45 29340.96 28544.79 29767.84 28730.04 26555.07 31236.71 26950.69 30071.11 286
YYNet150.73 27148.96 27056.03 27461.10 30341.78 25351.94 30356.44 29440.94 28644.84 29667.80 28830.08 26455.08 31136.77 26750.71 29971.22 283
TESTMET0.1,155.28 25454.90 25056.42 27266.56 28043.67 24165.46 25656.27 29639.18 29553.83 26567.44 28924.21 29655.46 31048.04 19673.11 15470.13 288
DSMNet-mixed39.30 29438.72 29341.03 30751.22 31919.66 32545.53 31431.35 32915.83 32539.80 31267.42 29022.19 30045.13 32222.43 30952.69 29358.31 309
PMMVS53.96 25853.26 26256.04 27362.60 29750.92 15161.17 27856.09 29732.81 30853.51 27066.84 29134.04 23259.93 28944.14 22668.18 21457.27 311
111144.40 28545.00 28242.61 30657.55 31417.33 32853.82 29957.05 29140.78 28744.11 30066.57 29213.37 31345.77 32022.15 31049.58 30364.73 300
.test124534.88 29739.49 29221.04 31857.55 31417.33 32853.82 29957.05 29140.78 28744.11 30066.57 29213.37 31345.77 32022.15 3100.00 3310.03 330
N_pmnet39.35 29340.28 29036.54 31063.76 2931.62 33549.37 3080.76 33634.62 30643.61 30366.38 29426.25 28742.57 32526.02 30751.77 29565.44 297
ADS-MVSNet251.33 27048.76 27359.07 26066.02 28544.60 23250.90 30559.76 28136.90 30050.74 27966.18 29526.38 28563.11 27727.17 30154.76 28869.50 290
ADS-MVSNet48.48 27647.77 27550.63 29366.02 28529.92 30850.90 30550.87 31336.90 30050.74 27966.18 29526.38 28552.47 31527.17 30154.76 28869.50 290
GG-mvs-BLEND62.34 24871.36 24337.04 27969.20 24257.33 29054.73 25765.48 29730.37 26077.82 21534.82 27774.93 13472.17 279
patchmatchnet-post64.03 29834.50 22674.27 240
FPMVS42.18 28941.11 28945.39 30158.03 31341.01 25949.50 30753.81 30830.07 31233.71 31464.03 29811.69 31752.08 31614.01 32355.11 28643.09 318
UnsupCasMVSNet_bld50.07 27348.87 27253.66 28360.97 30533.67 29757.62 28864.56 25939.47 29447.38 28864.02 30027.47 27859.32 29034.69 27843.68 31267.98 295
testus44.59 28443.87 28646.76 30059.85 31024.65 32153.86 29755.82 29936.26 30343.97 30263.42 3018.39 32553.14 31420.70 31652.52 29462.51 301
test123567845.66 28044.46 28549.26 29559.88 30928.68 31156.36 29255.54 30139.12 29640.89 30963.40 30214.41 31257.32 29821.05 31449.47 30461.78 303
CHOSEN 280x42047.83 27746.36 27852.24 29167.37 27449.78 18738.91 32143.11 32335.00 30543.27 30463.30 30328.95 27049.19 31836.53 27160.80 26757.76 310
Patchmatch-RL test58.16 23755.49 24766.15 22167.92 27148.89 19960.66 28051.07 31147.86 23459.36 21962.71 30434.02 23372.27 24556.41 14159.40 27677.30 226
LP48.51 27545.51 28057.52 27062.86 29544.53 23552.38 30259.84 28038.11 29742.81 30561.02 30523.23 29763.02 27824.10 30845.24 31065.02 299
test235645.61 28144.66 28348.47 29860.15 30828.08 31352.44 30152.83 31038.01 29846.13 29460.98 30615.08 31155.54 30920.43 31755.85 28561.78 303
testpf44.11 28645.40 28140.26 30860.52 30627.34 31433.26 32354.33 30545.87 25341.08 30860.26 30716.46 30759.14 29146.09 20850.68 30134.31 321
pmmvs344.92 28341.95 28853.86 28252.58 31843.55 24262.11 27346.90 32126.05 31740.63 31060.19 30811.08 32157.91 29531.83 28846.15 30860.11 307
testmv42.25 28840.11 29148.66 29653.23 31627.02 31556.62 29155.74 30037.25 29933.10 31559.52 3097.78 32656.58 30319.61 31838.13 31662.40 302
PVSNet_043.31 2047.46 27945.64 27952.92 28767.60 27344.65 23154.06 29654.64 30241.59 28246.15 29358.75 31030.99 25758.66 29232.18 28524.81 32055.46 312
gg-mvs-nofinetune57.86 23956.43 24162.18 24972.62 22335.35 28966.57 24956.33 29550.65 20957.64 23757.10 31130.65 25976.36 23037.38 26478.88 10174.82 255
test1235636.16 29635.94 29636.83 30950.82 3208.52 33244.84 31653.49 30932.72 30930.11 31755.08 3127.11 32849.47 31716.60 32032.68 31852.50 313
new_pmnet34.13 29934.29 29833.64 31152.63 31718.23 32744.43 31733.90 32722.81 32030.89 31653.18 31310.48 32235.72 32920.77 31539.51 31346.98 316
ANet_high41.38 29037.47 29453.11 28639.73 32824.45 32256.94 28969.69 23147.65 23526.04 31952.32 31412.44 31562.38 28121.80 31310.61 32872.49 272
JIA-IIPM51.56 26947.68 27763.21 24264.61 29050.73 15747.71 31058.77 28442.90 27548.46 28651.72 31524.97 29370.24 25336.06 27553.89 29168.64 294
PMVScopyleft28.69 2236.22 29533.29 29945.02 30336.82 33035.98 28754.68 29548.74 31526.31 31621.02 32151.61 3162.88 33460.10 2889.99 32747.58 30738.99 320
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
LCM-MVSNet40.30 29235.88 29753.57 28442.24 32529.15 31045.21 31560.53 27922.23 32128.02 31850.98 3173.72 33261.78 28331.22 29238.76 31569.78 289
MVS-HIRNet45.52 28244.48 28448.65 29768.49 26734.05 29559.41 28444.50 32227.03 31537.96 31350.47 31826.16 28864.10 27426.74 30459.52 27547.82 315
no-one40.85 29136.09 29555.14 27748.55 32138.72 26842.15 31962.92 26934.60 30723.55 32049.74 31912.21 31666.16 26926.27 30624.84 31960.54 306
PMMVS227.40 30325.91 30331.87 31439.46 3296.57 33331.17 32428.52 33023.96 31820.45 32248.94 3204.20 33137.94 32816.51 32119.97 32151.09 314
PNet_i23d27.88 30225.99 30233.55 31247.54 32325.89 31747.24 31232.91 32821.44 32215.90 32438.09 3210.85 33642.76 32416.90 31913.03 32632.00 322
MVEpermissive17.77 2321.41 30617.77 30832.34 31334.34 33225.44 31916.11 32724.11 33111.19 32713.22 32631.92 3221.58 33530.95 33010.47 32517.03 32240.62 319
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
DeepMVS_CXcopyleft12.03 32017.97 33310.91 33010.60 3347.46 32811.07 32728.36 3233.28 33311.29 3328.01 3299.74 33013.89 326
Gipumacopyleft34.77 29831.91 30043.33 30562.05 29937.87 27320.39 32667.03 24623.23 31918.41 32325.84 3244.24 33062.73 27914.71 32251.32 29729.38 323
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
E-PMN23.77 30422.73 30526.90 31642.02 32620.67 32442.66 31835.70 32517.43 32310.28 32825.05 3256.42 32942.39 32610.28 32614.71 32317.63 324
wuykxyi23d28.12 30122.54 30644.87 30434.97 33132.11 30237.96 32247.31 31913.32 3269.29 33023.72 3260.45 33756.58 30321.85 31213.98 32445.93 317
EMVS22.97 30521.84 30726.36 31740.20 32719.53 32641.95 32034.64 32617.09 3249.73 32922.83 3277.29 32742.22 3279.18 32813.66 32517.32 325
tmp_tt9.43 30911.14 3104.30 3212.38 3344.40 33413.62 32816.08 3330.39 33015.89 32513.06 32815.80 3095.54 33312.63 32410.46 3292.95 327
X-MVStestdata70.21 10367.28 13879.00 1486.32 1462.62 1485.83 1083.92 2964.55 2172.17 576.49 32947.95 10888.01 2171.55 3586.74 3586.37 43
test_post168.67 2443.64 33032.39 25469.49 25544.17 225
test_post3.55 33133.90 23466.52 266
wuyk23d13.32 30812.52 30915.71 31947.54 32326.27 31631.06 3251.98 3354.93 3295.18 3311.94 3320.45 33718.54 3316.81 33012.83 3272.33 328
testmvs4.52 3126.03 3130.01 3230.01 3350.00 33753.86 2970.00 3370.01 3310.04 3320.27 3330.00 3400.00 3340.04 3310.00 3310.03 330
test1234.73 3116.30 3120.02 3220.01 3350.01 33656.36 2920.00 3370.01 3310.04 3320.21 3340.01 3390.00 3340.03 3320.00 3310.04 329
pcd_1.5k_mvsjas3.92 3135.23 3140.00 3240.00 3370.00 3370.00 3290.00 3370.00 3330.00 3340.00 33547.05 1190.00 3340.00 3330.00 3310.00 332
pcd1.5k->3k30.06 30030.56 30128.55 31578.81 1110.00 3370.00 32982.07 670.00 3330.00 3340.00 33539.61 1900.00 3340.00 33374.56 13685.66 68
sosnet-low-res0.00 3140.00 3150.00 3240.00 3370.00 3370.00 3290.00 3370.00 3330.00 3340.00 3350.00 3400.00 3340.00 3330.00 3310.00 332
sosnet0.00 3140.00 3150.00 3240.00 3370.00 3370.00 3290.00 3370.00 3330.00 3340.00 3350.00 3400.00 3340.00 3330.00 3310.00 332
uncertanet0.00 3140.00 3150.00 3240.00 3370.00 3370.00 3290.00 3370.00 3330.00 3340.00 3350.00 3400.00 3340.00 3330.00 3310.00 332
Regformer0.00 3140.00 3150.00 3240.00 3370.00 3370.00 3290.00 3370.00 3330.00 3340.00 3350.00 3400.00 3340.00 3330.00 3310.00 332
uanet0.00 3140.00 3150.00 3240.00 3370.00 3370.00 3290.00 3370.00 3330.00 3340.00 3350.00 3400.00 3340.00 3330.00 3310.00 332
sam_mvs134.74 224
sam_mvs33.43 239
MTGPAbinary80.97 95
MTMP17.08 332
test9_res75.28 1488.31 1683.81 136
agg_prior273.09 2887.93 2384.33 114
agg_prior85.04 3459.96 4081.04 9274.68 2684.04 106
test_prior462.51 1782.08 56
test_prior76.69 4384.20 4657.27 7084.88 1486.43 5386.38 40
旧先验276.08 16045.32 25576.55 1365.56 27258.75 131
新几何276.12 158
无先验79.66 8874.30 20848.40 22880.78 18053.62 15879.03 215
原ACMM279.02 94
testdata272.18 24646.95 203
segment_acmp54.23 32
testdata172.65 21160.50 74
test1277.76 3284.52 4358.41 5783.36 4772.93 5054.61 2988.05 2088.12 1986.81 36
plane_prior781.41 7055.96 92
plane_prior681.20 7556.24 8745.26 141
plane_prior584.01 2787.21 3268.16 4780.58 7484.65 107
plane_prior356.09 8963.92 2969.27 94
plane_prior284.22 2264.52 23
plane_prior181.27 73
plane_prior56.31 8383.58 3163.19 3680.48 77
n20.00 337
nn0.00 337
door-mid47.19 320
test1183.47 42
door47.60 318
HQP5-MVS54.94 105
HQP-NCC80.66 8182.31 5062.10 5367.85 116
ACMP_Plane80.66 8182.31 5062.10 5367.85 116
BP-MVS67.04 57
HQP4-MVS67.85 11686.93 3884.32 115
HQP3-MVS83.90 3180.35 80
HQP2-MVS45.46 135
MDTV_nov1_ep13_2view25.89 31761.22 27740.10 29151.10 27732.97 24338.49 25978.61 216
ACMMP++_ref74.07 143
ACMMP++72.16 165
Test By Simon48.33 104