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 bysort bysort bysort bysorted bysort bysort by
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
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
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
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
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
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
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
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
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
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
test9_res75.28 1488.31 1683.81 136
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
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
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-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
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
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
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
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
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
#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
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
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
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
agg_prior273.09 2887.93 2384.33 114
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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_prior584.01 2787.21 3268.16 4780.58 7484.65 107
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
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
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
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
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
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
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
BP-MVS67.04 57
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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.
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
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
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
旧先验276.08 16045.32 25576.55 1365.56 27258.75 131
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
无先验79.66 8874.30 20848.40 22880.78 18053.62 15879.03 215
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
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
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
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
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
gm-plane-assit71.40 24241.72 25548.85 22373.31 26482.48 15248.90 191
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
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
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
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
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
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
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
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
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
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
testdata272.18 24646.95 203
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
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
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
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
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
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
lessismore_v069.91 18671.42 24147.80 21050.90 31250.39 28275.56 24927.43 28081.33 16945.91 21134.10 31780.59 196
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
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
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
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
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
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
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
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
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
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
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
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
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
test_post168.67 2443.64 33032.39 25469.49 25544.17 225
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
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.
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
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
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
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
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
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
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
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
MDTV_nov1_ep13_2view25.89 31761.22 27740.10 29151.10 27732.97 24338.49 25978.61 216
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
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
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
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
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
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
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
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
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
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
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
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-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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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)
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
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)
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
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
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
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
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
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
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
test_post3.55 33133.90 23466.52 266
patchmatchnet-post64.03 29834.50 22674.27 240
MTMP17.08 332
TEST985.58 2761.59 2581.62 6281.26 8655.65 16074.93 2288.81 3953.70 3984.68 94
test_885.40 3060.96 3281.54 6581.18 8955.86 15474.81 2588.80 4153.70 3984.45 99
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
新几何276.12 158
旧先验183.04 5353.15 12467.52 24287.85 4844.08 15180.76 7178.03 221
原ACMM279.02 94
test22283.14 5258.68 5572.57 21363.45 26441.78 27967.56 12486.12 7037.13 21378.73 10474.98 252
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_prior486.10 71
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
HQP4-MVS67.85 11686.93 3884.32 115
HQP3-MVS83.90 3180.35 80
HQP2-MVS45.46 135
NP-MVS80.98 7956.05 9185.54 84
ACMMP++_ref74.07 143
ACMMP++72.16 165
Test By Simon48.33 104