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
indooroutdoorcourty.delive.electrofacadekickermeadowofficepipesplaygr.reliefrelief.terraceterrai.
sort bysort bysort bysort bysort bysort bysort bysort bysorted bysort bysort bysort bysort bysort bysort bysort bysort by
APDe-MVS88.00 290.50 285.08 290.95 591.58 492.03 175.53 891.15 180.10 992.27 388.34 680.80 288.00 1086.99 1491.09 495.16 2
DeepPCF-MVS79.04 185.30 1688.93 781.06 2688.77 2990.48 585.46 4073.08 2290.97 273.77 3184.81 1785.95 1477.43 1888.22 787.73 687.85 6694.34 4
ESAPD88.46 191.07 185.41 191.73 292.08 191.91 276.73 190.14 380.33 892.75 190.44 180.73 388.97 487.63 891.01 695.48 1
HSP-MVS87.45 390.22 384.22 790.00 1891.80 390.59 475.80 489.93 478.35 1592.54 289.18 380.89 187.99 1186.29 2589.70 3593.85 8
SD-MVS86.96 589.45 484.05 1090.13 1589.23 1789.77 1274.59 989.17 580.70 589.93 789.67 278.47 887.57 1586.79 1790.67 1293.76 11
TSAR-MVS + MP.86.88 689.23 584.14 889.78 2188.67 2690.59 473.46 2188.99 680.52 791.26 488.65 479.91 586.96 2586.22 2690.59 1393.83 9
HPM-MVS++87.09 488.92 884.95 392.61 187.91 3490.23 976.06 388.85 781.20 487.33 987.93 779.47 688.59 588.23 490.15 2893.60 15
MPTG85.71 1286.88 1884.34 590.54 1287.11 3889.77 1274.17 1388.54 883.08 278.60 2786.10 1378.11 1187.80 1387.46 1090.35 2492.56 21
ACMMP_Plus86.52 889.01 683.62 1290.28 1490.09 890.32 774.05 1588.32 979.74 1087.04 1185.59 1776.97 2489.35 188.44 390.35 2494.27 6
HFP-MVS86.15 1087.95 1384.06 990.80 689.20 1889.62 1474.26 1187.52 1080.63 686.82 1284.19 2378.22 1087.58 1487.19 1290.81 793.13 19
TSAR-MVS + ACMM85.10 1988.81 1080.77 2989.55 2388.53 2888.59 2272.55 2487.39 1171.90 3790.95 587.55 874.57 2987.08 2286.54 2187.47 7193.67 12
APD-MVScopyleft86.84 788.91 984.41 490.66 890.10 790.78 375.64 587.38 1278.72 1390.68 686.82 1080.15 487.13 2086.45 2390.51 1593.83 9
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
CNVR-MVS86.36 988.19 1284.23 691.33 489.84 990.34 675.56 687.36 1378.97 1281.19 2386.76 1178.74 789.30 288.58 190.45 2194.33 5
OMC-MVS80.26 3682.59 3677.54 4683.04 5685.54 4883.25 5165.05 6987.32 1472.42 3672.04 4478.97 4073.30 3783.86 4581.60 5588.15 5788.83 49
ACMMPR85.52 1387.53 1583.17 1790.13 1589.27 1589.30 1573.97 1686.89 1577.14 2086.09 1383.18 2677.74 1587.42 1687.20 1190.77 892.63 20
NCCC85.34 1586.59 2083.88 1191.48 388.88 2089.79 1175.54 786.67 1677.94 1876.55 3084.99 1978.07 1288.04 887.68 790.46 2093.31 16
CSCG85.28 1787.68 1482.49 2089.95 1991.99 288.82 1971.20 3186.41 1779.63 1179.26 2488.36 573.94 3486.64 2786.67 2091.40 294.41 3
DeepC-MVS78.47 284.81 2186.03 2483.37 1489.29 2690.38 688.61 2176.50 286.25 1877.22 1975.12 3480.28 3877.59 1788.39 688.17 591.02 593.66 13
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
CNLPA77.20 5477.54 5776.80 5082.63 5884.31 5779.77 6164.64 7185.17 1973.18 3356.37 10769.81 7074.53 3081.12 7278.69 9086.04 12787.29 59
CP-MVS84.74 2286.43 2282.77 1989.48 2488.13 3388.64 2073.93 1784.92 2076.77 2181.94 2183.50 2477.29 2186.92 2686.49 2290.49 1693.14 18
DeepC-MVS_fast78.24 384.27 2485.50 2682.85 1890.46 1389.24 1687.83 2774.24 1284.88 2176.23 2275.26 3381.05 3677.62 1688.02 987.62 990.69 1192.41 23
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
TAPA-MVS71.42 977.69 5380.05 4974.94 5780.68 6884.52 5681.36 5363.14 8184.77 2264.82 6468.72 5475.91 5071.86 4681.62 6179.55 8387.80 6785.24 76
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
TSAR-MVS + COLMAP78.34 5181.64 3874.48 6180.13 7285.01 5481.73 5265.93 6584.75 2361.68 7185.79 1466.27 8571.39 5182.91 5580.78 6286.01 12885.98 64
TSAR-MVS + GP.83.69 2586.58 2180.32 3085.14 4886.96 3984.91 4470.25 3584.71 2473.91 3085.16 1685.63 1677.92 1385.44 3585.71 3189.77 3292.45 22
SteuartSystems-ACMMP85.99 1188.31 1183.27 1690.73 789.84 990.27 874.31 1084.56 2575.88 2487.32 1085.04 1877.31 1989.01 388.46 291.14 393.96 7
Skip Steuart: Steuart Systems R&D Blog.
MCST-MVS85.13 1886.62 1983.39 1390.55 1189.82 1189.29 1673.89 1884.38 2676.03 2379.01 2685.90 1578.47 887.81 1286.11 2892.11 193.29 17
train_agg84.86 2087.21 1782.11 2290.59 1085.47 4989.81 1073.55 2083.95 2773.30 3289.84 887.23 975.61 2786.47 2985.46 3389.78 3192.06 27
MP-MVScopyleft85.50 1487.40 1683.28 1590.65 989.51 1489.16 1874.11 1483.70 2878.06 1785.54 1584.89 2177.31 1987.40 1787.14 1390.41 2293.65 14
ACMMPcopyleft83.42 2685.27 2781.26 2588.47 3088.49 2988.31 2572.09 2683.42 2972.77 3582.65 1978.22 4275.18 2886.24 3285.76 3090.74 992.13 26
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
canonicalmvs79.16 4682.37 3775.41 5482.33 6186.38 4580.80 5663.18 8082.90 3067.34 5672.79 4276.07 4869.62 5883.46 5284.41 4089.20 4390.60 39
PGM-MVS84.42 2386.29 2382.23 2190.04 1788.82 2289.23 1771.74 2982.82 3174.61 2784.41 1882.09 2877.03 2387.13 2086.73 1990.73 1092.06 27
X-MVS83.23 2785.20 2880.92 2889.71 2288.68 2388.21 2673.60 1982.57 3271.81 4077.07 2881.92 3071.72 4986.98 2486.86 1590.47 1792.36 24
CPTT-MVS81.77 3283.10 3380.21 3185.93 4486.45 4487.72 2870.98 3282.54 3371.53 4374.23 3981.49 3376.31 2682.85 5681.87 5288.79 5192.26 25
PHI-MVS82.36 3085.89 2578.24 4386.40 4189.52 1385.52 3869.52 4282.38 3465.67 6081.35 2282.36 2773.07 3987.31 1986.76 1889.24 4291.56 30
abl_679.05 3787.27 3588.85 2183.62 4968.25 4881.68 3572.94 3473.79 4084.45 2272.55 4289.66 3790.64 38
HQP-MVS81.19 3583.27 3278.76 4087.40 3485.45 5086.95 2970.47 3481.31 3666.91 5879.24 2576.63 4671.67 5084.43 4283.78 4389.19 4492.05 29
3Dnovator+75.73 482.40 2982.76 3481.97 2388.02 3189.67 1286.60 3171.48 3081.28 3778.18 1664.78 6977.96 4477.13 2287.32 1886.83 1690.41 2291.48 31
MSLP-MVS++82.09 3182.66 3581.42 2487.03 3787.22 3785.82 3670.04 3680.30 3878.66 1468.67 5681.04 3777.81 1485.19 3884.88 3889.19 4491.31 32
CDPH-MVS82.64 2885.03 2979.86 3389.41 2588.31 3088.32 2471.84 2880.11 3967.47 5582.09 2081.44 3471.85 4785.89 3486.15 2790.24 2691.25 33
NP-MVS80.10 40
CLD-MVS79.35 4481.23 4077.16 4885.01 5186.92 4085.87 3560.89 12080.07 4175.35 2672.96 4173.21 5868.43 6585.41 3784.63 3987.41 7285.44 73
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
AdaColmapbinary79.74 4178.62 5281.05 2789.23 2786.06 4684.95 4371.96 2779.39 4275.51 2563.16 7368.84 7976.51 2583.55 4982.85 4888.13 5886.46 62
3Dnovator73.76 579.75 4080.52 4578.84 3984.94 5387.35 3584.43 4665.54 6678.29 4373.97 2963.00 7575.62 5174.07 3385.00 3985.34 3490.11 2989.04 47
LGP-MVS_train79.83 3881.22 4178.22 4486.28 4285.36 5286.76 3069.59 4077.34 4465.14 6275.68 3270.79 6571.37 5284.60 4084.01 4190.18 2790.74 37
ACMP73.23 779.79 3980.53 4478.94 3885.61 4685.68 4785.61 3769.59 4077.33 4571.00 4674.45 3769.16 7471.88 4583.15 5383.37 4689.92 3090.57 40
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
PLCcopyleft68.99 1175.68 5975.31 6976.12 5382.94 5781.26 7679.94 6066.10 6177.15 4666.86 5959.13 8868.53 8073.73 3580.38 8279.04 8787.13 8181.68 123
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
CANet81.62 3483.41 3179.53 3587.06 3688.59 2785.47 3967.96 5276.59 4774.05 2874.69 3581.98 2972.98 4086.14 3385.47 3289.68 3690.42 41
MVS_111021_LR78.13 5279.85 5076.13 5281.12 6581.50 7380.28 5865.25 6776.09 4871.32 4576.49 3172.87 5972.21 4382.79 5781.29 5786.59 11287.91 53
MVS_030481.73 3383.86 3079.26 3686.22 4389.18 1986.41 3267.15 5675.28 4970.75 4774.59 3683.49 2574.42 3187.05 2386.34 2490.58 1491.08 35
ACMM72.26 878.86 4978.13 5379.71 3486.89 3883.40 6386.02 3470.50 3375.28 4971.49 4463.01 7469.26 7373.57 3684.11 4483.98 4289.76 3387.84 54
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
PCF-MVS73.28 679.42 4380.41 4678.26 4284.88 5488.17 3186.08 3369.85 3775.23 5168.43 5068.03 5978.38 4171.76 4881.26 7080.65 7188.56 5491.18 34
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
EPNet79.08 4880.62 4377.28 4788.90 2883.17 6683.65 4872.41 2574.41 5267.15 5776.78 2974.37 5464.43 10083.70 4883.69 4487.15 7788.19 51
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
MAR-MVS79.21 4580.32 4777.92 4587.46 3388.15 3283.95 4767.48 5574.28 5368.25 5164.70 7077.04 4572.17 4485.42 3685.00 3788.22 5587.62 56
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
RPSCF67.64 13671.25 8463.43 16361.86 20570.73 18067.26 17350.86 19474.20 5458.91 8067.49 6169.33 7264.10 10171.41 17968.45 19577.61 18877.17 160
MVS_111021_HR80.13 3781.46 3978.58 4185.77 4585.17 5383.45 5069.28 4374.08 5570.31 4874.31 3875.26 5273.13 3886.46 3085.15 3689.53 3889.81 44
QAPM78.47 5080.22 4876.43 5185.03 5086.75 4280.62 5766.00 6373.77 5665.35 6165.54 6778.02 4372.69 4183.71 4783.36 4788.87 5090.41 42
LS3D74.08 6473.39 7474.88 5885.05 4982.62 6979.71 6268.66 4672.82 5758.80 8157.61 10061.31 9871.07 5480.32 8678.87 8986.00 13080.18 137
diffmvs73.13 6875.65 6870.19 9474.07 14877.17 13178.24 9357.45 16672.44 5864.02 6769.05 5275.92 4964.86 9875.18 15875.27 16082.47 16984.53 86
OpenMVScopyleft70.44 1076.15 5876.82 6575.37 5585.01 5184.79 5578.99 7062.07 10771.27 5967.88 5357.91 9972.36 6070.15 5682.23 5981.41 5688.12 5987.78 55
DELS-MVS79.15 4781.07 4276.91 4983.54 5587.31 3684.45 4564.92 7069.98 6069.34 4971.62 4676.26 4769.84 5786.57 2885.90 2989.39 4089.88 43
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
PVSNet_BlendedMVS76.21 5677.52 5874.69 5979.46 7483.79 6077.50 9964.34 7469.88 6171.88 3868.54 5770.42 6767.05 6783.48 5079.63 7987.89 6486.87 60
PVSNet_Blended76.21 5677.52 5874.69 5979.46 7483.79 6077.50 9964.34 7469.88 6171.88 3868.54 5770.42 6767.05 6783.48 5079.63 7987.89 6486.87 60
MVS_Test75.37 6077.13 6373.31 6579.07 7781.32 7579.98 5960.12 13969.72 6364.11 6670.53 4873.22 5768.90 6180.14 9079.48 8587.67 6885.50 71
DI_MVS_plusplus_trai75.13 6276.12 6773.96 6378.18 8281.55 7280.97 5562.54 10168.59 6465.13 6361.43 7674.81 5369.32 6081.01 7479.59 8187.64 6985.89 65
CANet_DTU73.29 6776.96 6469.00 10677.04 10382.06 7179.49 6456.30 17367.85 6553.29 12071.12 4770.37 6961.81 11681.59 6280.96 6086.09 12284.73 85
USDC67.36 14167.90 13866.74 14171.72 16875.23 16171.58 15360.28 13267.45 6650.54 13760.93 7745.20 20562.08 11076.56 14874.50 16584.25 16075.38 174
Effi-MVS+75.28 6176.20 6674.20 6281.15 6483.24 6481.11 5463.13 8266.37 6760.27 7664.30 7168.88 7870.93 5581.56 6381.69 5488.61 5287.35 57
EPNet_dtu68.08 12571.00 8564.67 15379.64 7368.62 18875.05 11563.30 7966.36 6845.27 16667.40 6266.84 8443.64 19475.37 15674.98 16481.15 17477.44 158
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
MSDG71.52 7669.87 9673.44 6482.21 6279.35 10079.52 6364.59 7266.15 6961.87 7053.21 15556.09 13065.85 9678.94 10578.50 9186.60 11176.85 165
FC-MVSNet-train72.60 7275.07 7069.71 10181.10 6678.79 11073.74 13665.23 6866.10 7053.34 11970.36 4963.40 9356.92 14481.44 6480.96 6087.93 6284.46 87
tpmp4_e2368.32 12167.08 14869.76 10077.86 8675.22 16378.37 9056.17 17566.06 7164.27 6557.15 10454.89 13863.40 10470.97 18668.29 19678.46 18677.00 164
CostFormer68.92 11469.58 10268.15 11375.98 11576.17 15278.22 9451.86 18965.80 7261.56 7263.57 7262.83 9461.85 11470.40 19368.67 19179.42 18279.62 144
IS_MVSNet73.33 6677.34 6168.65 11081.29 6383.47 6274.45 11963.58 7865.75 7348.49 14567.11 6470.61 6654.63 16484.51 4183.58 4589.48 3986.34 63
Vis-MVSNet (Re-imp)67.83 13073.52 7361.19 17478.37 8176.72 14366.80 17762.96 8365.50 7434.17 20067.19 6369.68 7139.20 20379.39 10179.44 8685.68 14076.73 166
Fast-Effi-MVS+73.11 6973.66 7272.48 6777.72 9680.88 8278.55 8558.83 15865.19 7560.36 7559.98 8362.42 9671.22 5381.66 6080.61 7388.20 5684.88 84
EPP-MVSNet74.00 6577.41 6070.02 9780.53 7083.91 5974.99 11662.68 9765.06 7649.77 14268.68 5572.09 6163.06 10682.49 5880.73 6389.12 4688.91 48
UGNet72.78 7077.67 5667.07 13471.65 17083.24 6475.20 11063.62 7764.93 7756.72 10071.82 4573.30 5649.02 18081.02 7380.70 6986.22 11688.67 50
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
PVSNet_Blended_VisFu76.57 5577.90 5475.02 5680.56 6986.58 4379.24 6566.18 6064.81 7868.18 5265.61 6571.45 6267.05 6784.16 4381.80 5388.90 4890.92 36
pmmvs467.89 12867.39 14568.48 11171.60 17273.57 17274.45 11960.98 11964.65 7957.97 8854.95 12451.73 17761.88 11373.78 16575.11 16283.99 16377.91 155
MVSTER72.06 7374.24 7169.51 10270.39 17875.97 15376.91 10357.36 16864.64 8061.39 7368.86 5363.76 9163.46 10381.44 6479.70 7887.56 7085.31 75
OPM-MVS79.68 4279.28 5180.15 3287.99 3286.77 4188.52 2372.72 2364.55 8167.65 5467.87 6074.33 5574.31 3286.37 3185.25 3589.73 3489.81 44
GBi-Net70.78 7973.37 7567.76 11572.95 15878.00 11875.15 11162.72 9264.13 8251.44 12858.37 9369.02 7557.59 13681.33 6780.72 6486.70 10682.02 115
test170.78 7973.37 7567.76 11572.95 15878.00 11875.15 11162.72 9264.13 8251.44 12858.37 9369.02 7557.59 13681.33 6780.72 6486.70 10682.02 115
FMVSNet370.49 8372.90 7767.67 11972.88 16177.98 12174.96 11762.72 9264.13 8251.44 12858.37 9369.02 7557.43 13979.43 10079.57 8286.59 11281.81 122
COLMAP_ROBcopyleft62.73 1567.66 13466.76 15268.70 10980.49 7177.98 12175.29 10962.95 8463.62 8549.96 14047.32 19250.72 18358.57 13076.87 14375.50 15884.94 15275.33 175
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
EPMVS60.00 19361.97 19357.71 19168.46 18863.17 20864.54 18948.23 20663.30 8644.72 16960.19 8056.05 13150.85 17665.27 20762.02 21369.44 21563.81 208
FMVSNet270.39 8472.67 7967.72 11872.95 15878.00 11875.15 11162.69 9663.29 8751.25 13255.64 11168.49 8157.59 13680.91 7580.35 7586.70 10682.02 115
PatchmatchNetpermissive64.21 16764.65 17563.69 15971.29 17668.66 18769.63 15951.70 19163.04 8853.77 11759.83 8558.34 10760.23 12668.54 20066.06 20375.56 19768.08 201
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
tpm cat165.41 15163.81 18167.28 13075.61 11972.88 17375.32 10852.85 18362.97 8963.66 6853.24 15453.29 16061.83 11565.54 20564.14 20874.43 20274.60 177
PatchMatch-RL67.78 13166.65 15369.10 10573.01 15772.69 17468.49 16561.85 11062.93 9060.20 7756.83 10650.42 18469.52 5975.62 15574.46 16681.51 17273.62 185
PMMVS65.06 15769.17 11460.26 18055.25 22263.43 20566.71 17843.01 22062.41 9150.64 13569.44 5167.04 8363.29 10574.36 16273.54 16982.68 16873.99 182
MS-PatchMatch70.17 9170.49 8969.79 9980.98 6777.97 12377.51 9858.95 15062.33 9255.22 11053.14 15665.90 8662.03 11179.08 10477.11 12184.08 16177.91 155
tpmrst62.00 18262.35 19261.58 17271.62 17164.14 20169.07 16348.22 20762.21 9353.93 11558.26 9755.30 13455.81 15663.22 21062.62 21170.85 21270.70 195
UniMVSNet_NR-MVSNet70.59 8272.19 8068.72 10877.72 9680.72 8373.81 13469.65 3961.99 9443.23 17360.54 7957.50 10958.57 13079.56 9881.07 5989.34 4183.97 90
GG-mvs-BLEND46.86 21767.51 14222.75 2300.05 23776.21 15164.69 1880.04 23561.90 950.09 24055.57 11271.32 630.08 23570.54 18967.19 19971.58 21069.86 196
CHOSEN 1792x268869.20 11269.26 11269.13 10476.86 10478.93 10477.27 10160.12 13961.86 9654.42 11142.54 19961.61 9766.91 7378.55 10978.14 10279.23 18483.23 102
DWT-MVSNet_training67.24 14365.96 16068.74 10776.15 11174.36 17074.37 12356.66 17161.82 9760.51 7458.23 9849.76 18865.07 9770.04 19470.39 18179.70 18177.11 162
UniMVSNet (Re)69.53 10571.90 8166.76 14076.42 10680.93 7972.59 14668.03 5161.75 9841.68 18158.34 9657.23 11753.27 17179.53 9980.62 7288.57 5384.90 83
ACMH+66.54 1371.36 7770.09 9172.85 6682.59 5981.13 7778.56 8468.04 5061.55 9952.52 12651.50 17454.14 14368.56 6478.85 10679.50 8486.82 9883.94 92
IterMVS-LS71.69 7572.82 7870.37 9177.54 9876.34 14975.13 11460.46 12761.53 10057.57 8964.89 6867.33 8266.04 9277.09 14177.37 11785.48 14385.18 77
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
Baseline_NR-MVSNet67.53 13968.77 12266.09 14475.99 11374.75 16772.43 14768.41 4761.33 10138.33 18951.31 17554.13 14556.03 15379.22 10278.19 10085.37 14482.45 113
DU-MVS69.63 10070.91 8668.13 11475.99 11379.54 9773.81 13469.20 4461.20 10243.23 17358.52 9053.50 15058.57 13079.22 10280.45 7487.97 6183.97 90
NR-MVSNet68.79 11670.56 8866.71 14277.48 9979.54 9773.52 13969.20 4461.20 10239.76 18458.52 9050.11 18651.37 17580.26 8880.71 6888.97 4783.59 97
Effi-MVS+-dtu71.82 7471.86 8271.78 6878.77 7880.47 9178.55 8561.67 11360.68 10455.49 10758.48 9265.48 8768.85 6276.92 14275.55 15787.35 7385.46 72
UA-Net74.47 6377.80 5570.59 8285.33 4785.40 5173.54 13865.98 6460.65 10556.00 10672.11 4379.15 3954.63 16483.13 5482.25 5088.04 6081.92 121
Vis-MVSNetpermissive72.77 7177.20 6267.59 12174.19 14784.01 5876.61 10661.69 11260.62 10650.61 13670.25 5071.31 6455.57 15983.85 4682.28 4986.90 9188.08 52
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
TranMVSNet+NR-MVSNet69.25 11170.81 8767.43 12277.23 10279.46 9973.48 14069.66 3860.43 10739.56 18558.82 8953.48 15255.74 15779.59 9681.21 5888.89 4982.70 111
TDRefinement66.09 14965.03 17367.31 12869.73 18276.75 14275.33 10764.55 7360.28 10849.72 14345.63 19442.83 20860.46 12475.75 15275.95 15284.08 16178.04 154
MDTV_nov1_ep1364.37 16265.24 16863.37 16468.94 18770.81 17972.40 14850.29 19860.10 10953.91 11660.07 8259.15 10557.21 14069.43 19767.30 19877.47 18969.78 197
v1870.10 9269.52 10370.77 7574.66 14377.06 13478.84 7358.84 15760.01 11059.23 7855.06 11957.47 11066.34 8277.50 12976.75 13086.71 10582.77 109
v1670.07 9369.46 10570.79 7474.74 13877.08 13378.79 7858.86 15259.75 11159.15 7954.87 12657.33 11266.38 8077.61 12376.77 12586.81 10382.79 107
IB-MVS66.94 1271.21 7871.66 8370.68 7979.18 7682.83 6872.61 14561.77 11159.66 11263.44 6953.26 15359.65 10359.16 12976.78 14582.11 5187.90 6387.33 58
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
ADS-MVSNet55.94 20258.01 20253.54 20662.48 20258.48 21459.12 20646.20 21059.65 11342.88 17852.34 17153.31 15946.31 18962.00 21460.02 21864.23 22460.24 216
v1770.03 9569.43 11070.72 7874.75 13777.09 13278.78 8058.85 15459.53 11458.72 8254.87 12657.39 11166.38 8077.60 12476.75 13086.83 9782.80 105
FC-MVSNet-test56.90 20065.20 17047.21 21266.98 19063.20 20749.11 21958.60 16159.38 11511.50 23265.60 6656.68 12024.66 22371.17 18271.36 17972.38 20869.02 199
HyFIR lowres test69.47 10868.94 11670.09 9676.77 10582.93 6776.63 10560.17 13459.00 11654.03 11440.54 20565.23 8867.89 6676.54 14978.30 9885.03 14980.07 138
v670.35 8569.94 9370.83 7174.68 14080.62 8478.81 7560.16 13758.81 11758.17 8555.01 12057.31 11466.32 8577.53 12576.73 13686.82 9883.62 94
v870.23 8969.86 9870.67 8074.69 13979.82 9678.79 7859.18 14858.80 11858.20 8455.00 12157.33 11266.31 8677.51 12876.71 14086.82 9883.88 93
v1neww70.34 8669.93 9470.82 7274.68 14080.61 8578.80 7660.17 13458.74 11958.10 8655.00 12157.28 11566.33 8377.53 12576.74 13286.82 9883.61 95
v7new70.34 8669.93 9470.82 7274.68 14080.61 8578.80 7660.17 13458.74 11958.10 8655.00 12157.28 11566.33 8377.53 12576.74 13286.82 9883.61 95
V4268.76 11769.63 10167.74 11764.93 19978.01 11778.30 9156.48 17258.65 12156.30 10454.26 13757.03 11864.85 9977.47 13077.01 12285.60 14184.96 82
tfpn_ndepth65.09 15667.12 14762.73 16575.75 11876.23 15068.00 16760.36 12858.16 12240.27 18354.89 12554.22 14246.80 18776.69 14775.66 15485.19 14673.98 183
Fast-Effi-MVS+-dtu68.34 12069.47 10467.01 13575.15 12177.97 12377.12 10255.40 17657.87 12346.68 15956.17 11060.39 9962.36 10976.32 15076.25 14685.35 14581.34 124
tpm62.41 17863.15 18361.55 17372.24 16463.79 20471.31 15446.12 21157.82 12455.33 10859.90 8454.74 13953.63 16867.24 20364.29 20670.65 21374.25 181
CR-MVSNet64.83 15865.54 16664.01 15870.64 17769.41 18365.97 18252.74 18457.81 12552.65 12354.27 13556.31 12360.92 12072.20 17573.09 17181.12 17575.69 171
RPMNet61.71 18862.88 18560.34 17969.51 18469.41 18363.48 19349.23 19957.81 12545.64 16550.51 17850.12 18553.13 17268.17 20268.49 19481.07 17675.62 173
dps64.00 16862.99 18465.18 14773.29 15572.07 17668.98 16453.07 18257.74 12758.41 8355.55 11347.74 19760.89 12269.53 19667.14 20076.44 19471.19 194
v1070.22 9069.76 10070.74 7674.79 13280.30 9479.22 6659.81 14257.71 12856.58 10354.22 14155.31 13366.95 7078.28 11277.47 11387.12 8485.07 79
v770.33 8869.87 9670.88 7074.79 13281.04 7879.22 6660.57 12457.70 12956.65 10254.23 13955.29 13566.95 7078.28 11277.47 11387.12 8485.05 80
v2v48270.05 9469.46 10570.74 7674.62 14480.32 9379.00 6960.62 12357.41 13056.89 9555.43 11455.14 13666.39 7977.25 13777.14 12086.90 9183.57 100
IterMVS66.36 14768.30 13364.10 15569.48 18574.61 16873.41 14150.79 19557.30 13148.28 14760.64 7859.92 10260.85 12374.14 16372.66 17381.80 17178.82 151
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
v1569.61 10168.88 11770.46 8674.81 13177.03 13778.75 8158.83 15857.06 13257.18 9154.55 13256.37 12166.13 9077.70 12076.76 12787.03 8882.69 112
thresconf0.0264.77 15965.90 16163.44 16276.37 10775.17 16669.51 16061.28 11456.98 13339.01 18756.24 10848.68 19249.78 17877.13 13975.61 15584.71 15671.53 192
v169.97 9669.45 10770.59 8274.78 13480.51 8878.84 7360.30 12956.98 13356.81 9754.69 12956.29 12565.91 9577.37 13276.71 14086.89 9383.59 97
divwei89l23v2f11269.97 9669.44 10870.58 8474.78 13480.50 8978.85 7160.30 12956.97 13556.75 9854.67 13156.27 12665.92 9477.37 13276.72 13786.88 9483.58 99
v114169.96 9869.44 10870.58 8474.78 13480.50 8978.85 7160.30 12956.95 13656.74 9954.68 13056.26 12765.93 9377.38 13176.72 13786.88 9483.57 100
V1469.59 10268.86 11870.45 8874.83 13077.04 13578.70 8258.83 15856.95 13657.08 9354.41 13356.34 12266.15 8777.77 11976.76 12787.08 8682.74 110
FMVSNet168.84 11570.47 9066.94 13671.35 17577.68 12674.71 11862.35 10656.93 13849.94 14150.01 18064.59 8957.07 14281.33 6780.72 6486.25 11582.00 118
V969.58 10368.83 11970.46 8674.85 12977.04 13578.65 8358.85 15456.83 13957.12 9254.26 13756.31 12366.14 8977.83 11876.76 12787.13 8182.79 107
v1269.54 10468.79 12170.41 8974.88 12677.03 13778.54 8858.85 15456.71 14056.87 9654.13 14256.23 12866.15 8777.89 11676.74 13287.17 7682.80 105
PatchT61.97 18364.04 17959.55 18560.49 20767.40 19156.54 20848.65 20356.69 14152.65 12351.10 17752.14 17360.92 12072.20 17573.09 17178.03 18775.69 171
tfpn11168.38 11969.23 11367.39 12477.83 8878.93 10474.28 12462.81 8556.64 14246.70 15556.24 10853.47 15356.59 14580.41 7778.43 9286.11 11980.53 132
conf0.0167.72 13267.99 13667.39 12477.82 9378.94 10274.28 12462.81 8556.64 14246.70 15553.33 15148.59 19356.59 14580.34 8478.43 9286.16 11879.67 143
conf0.00267.52 14067.64 14067.39 12477.80 9578.94 10274.28 12462.81 8556.64 14246.70 15553.65 14746.28 20156.59 14580.33 8578.37 9786.17 11779.23 147
conf200view1168.11 12368.72 12467.39 12477.83 8878.93 10474.28 12462.81 8556.64 14246.70 15552.65 16553.47 15356.59 14580.41 7778.43 9286.11 11980.53 132
thres100view90067.60 13868.02 13567.12 13377.83 8877.75 12573.90 13262.52 10256.64 14246.82 15352.65 16553.47 15355.92 15478.77 10777.62 11085.72 13979.23 147
tfpn200view968.11 12368.72 12467.40 12377.83 8878.93 10474.28 12462.81 8556.64 14246.82 15352.65 16553.47 15356.59 14580.41 7778.43 9286.11 11980.52 134
v1369.52 10668.76 12370.41 8974.88 12677.02 13978.52 8958.86 15256.61 14856.91 9454.00 14456.17 12966.11 9177.93 11576.74 13287.21 7582.83 104
tfpn100063.81 16966.31 15460.90 17675.76 11775.74 15465.14 18660.14 13856.47 14935.99 19755.11 11852.30 17043.42 19576.21 15175.34 15984.97 15173.01 187
MIMVSNet58.52 19761.34 19655.22 19960.76 20667.01 19366.81 17649.02 20156.43 15038.90 18840.59 20454.54 14140.57 20273.16 16871.65 17675.30 20066.00 204
v1169.37 10968.65 12770.20 9374.87 12876.97 14078.29 9258.55 16256.38 15156.04 10554.02 14354.98 13766.47 7878.30 11176.91 12386.97 8983.02 103
thres20067.98 12668.55 12967.30 12977.89 8578.86 10874.18 13162.75 9056.35 15246.48 16052.98 15953.54 14956.46 15080.41 7777.97 10386.05 12579.78 142
thres40067.95 12768.62 12867.17 13177.90 8378.59 11374.27 12962.72 9256.34 15345.77 16453.00 15853.35 15856.46 15080.21 8978.43 9285.91 13480.43 135
ACMH65.37 1470.71 8170.00 9271.54 6982.51 6082.47 7077.78 9668.13 4956.19 15446.06 16254.30 13451.20 18068.68 6380.66 7680.72 6486.07 12384.45 88
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
thres600view767.68 13368.43 13066.80 13877.90 8378.86 10873.84 13362.75 9056.07 15544.70 17052.85 16252.81 16355.58 15880.41 7777.77 10686.05 12580.28 136
view60067.63 13768.36 13166.77 13977.84 8778.66 11173.74 13662.62 9956.04 15644.98 16752.86 16152.83 16255.48 16180.36 8377.75 10785.95 13380.02 139
v114469.93 9969.36 11170.61 8174.89 12580.93 7979.11 6860.64 12255.97 15755.31 10953.85 14654.14 14366.54 7778.10 11477.44 11587.14 8085.09 78
view80067.35 14268.22 13466.35 14377.83 8878.62 11272.97 14462.58 10055.71 15844.13 17152.69 16452.24 17254.58 16680.27 8778.19 10086.01 12879.79 141
v14867.85 12967.53 14168.23 11273.25 15677.57 12974.26 13057.36 16855.70 15957.45 9053.53 14855.42 13261.96 11275.23 15773.92 16785.08 14881.32 125
tfpnview1164.33 16366.17 15762.18 16776.25 10875.23 16167.45 17061.16 11555.50 16036.38 19455.35 11551.89 17446.96 18377.28 13676.10 15184.86 15471.85 191
TinyColmap62.84 17361.03 19764.96 15169.61 18371.69 17768.48 16659.76 14355.41 16147.69 15147.33 19134.20 21862.76 10874.52 16072.59 17481.44 17371.47 193
tfpn66.58 14667.18 14665.88 14577.82 9378.45 11572.07 14962.52 10255.35 16243.21 17552.54 16946.12 20253.68 16780.02 9178.23 9985.99 13179.55 145
CHOSEN 280x42058.70 19661.88 19454.98 20055.45 22150.55 22564.92 18740.36 22255.21 16338.13 19048.31 18463.76 9163.03 10773.73 16668.58 19368.00 21873.04 186
FMVSNet557.24 19860.02 20053.99 20356.45 21762.74 20965.27 18547.03 20855.14 16439.55 18640.88 20253.42 15741.83 19672.35 17171.10 18073.79 20464.50 207
GA-MVS68.14 12269.17 11466.93 13773.77 15378.50 11474.45 11958.28 16355.11 16548.44 14660.08 8153.99 14661.50 11778.43 11077.57 11185.13 14780.54 131
v119269.50 10768.83 11970.29 9274.49 14580.92 8178.55 8560.54 12555.04 16654.21 11252.79 16352.33 16866.92 7277.88 11777.35 11887.04 8785.51 70
PM-MVS60.48 19160.94 19859.94 18158.85 21266.83 19464.27 19151.39 19255.03 16748.03 14850.00 18240.79 21258.26 13369.20 19867.13 20178.84 18577.60 157
v14419269.34 11068.68 12670.12 9574.06 14980.54 8778.08 9560.54 12554.99 16854.13 11352.92 16052.80 16466.73 7577.13 13976.72 13787.15 7785.63 66
v192192069.03 11368.32 13269.86 9874.03 15080.37 9277.55 9760.25 13354.62 16953.59 11852.36 17051.50 17966.75 7477.17 13876.69 14286.96 9085.56 67
test-LLR64.42 16164.36 17764.49 15475.02 12363.93 20266.61 17961.96 10854.41 17047.77 14957.46 10160.25 10055.20 16270.80 18769.33 18680.40 17874.38 179
TESTMET0.1,161.10 18964.36 17757.29 19257.53 21563.93 20266.61 17936.22 22654.41 17047.77 14957.46 10160.25 10055.20 16270.80 18769.33 18680.40 17874.38 179
test-mter60.84 19064.62 17656.42 19555.99 22064.18 20065.39 18434.23 22854.39 17246.21 16157.40 10359.49 10455.86 15571.02 18569.65 18480.87 17776.20 167
pmmvs-eth3d63.52 17062.44 19164.77 15266.82 19370.12 18269.41 16259.48 14554.34 17352.71 12246.24 19344.35 20756.93 14372.37 17073.77 16883.30 16575.91 168
WR-MVS63.03 17167.40 14457.92 19075.14 12277.60 12860.56 20166.10 6154.11 17423.88 21253.94 14553.58 14834.50 20873.93 16477.71 10887.35 7380.94 127
tfpn_n40064.23 16566.05 15862.12 16976.20 10975.24 15967.43 17161.15 11654.04 17536.38 19455.35 11551.89 17446.94 18477.31 13476.15 14984.59 15772.36 188
tfpnconf64.23 16566.05 15862.12 16976.20 10975.24 15967.43 17161.15 11654.04 17536.38 19455.35 11551.89 17446.94 18477.31 13476.15 14984.59 15772.36 188
CDS-MVSNet67.65 13569.83 9965.09 14875.39 12076.55 14474.42 12263.75 7653.55 17749.37 14459.41 8662.45 9544.44 19279.71 9479.82 7783.17 16777.36 159
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
v124068.64 11867.89 13969.51 10273.89 15280.26 9576.73 10459.97 14153.43 17853.08 12151.82 17350.84 18266.62 7676.79 14476.77 12586.78 10485.34 74
test0.0.03 158.80 19561.58 19555.56 19875.02 12368.45 18959.58 20561.96 10852.74 17929.57 20449.75 18354.56 14031.46 21171.19 18169.77 18375.75 19564.57 206
CP-MVSNet62.68 17465.49 16759.40 18671.84 16675.34 15762.87 19667.04 5752.64 18027.19 20953.38 15048.15 19541.40 19971.26 18075.68 15386.07 12382.00 118
PEN-MVS62.96 17265.77 16459.70 18373.98 15175.45 15663.39 19467.61 5452.49 18125.49 21153.39 14949.12 19140.85 20171.94 17777.26 11986.86 9680.72 129
CVMVSNet62.55 17565.89 16258.64 18866.95 19169.15 18566.49 18156.29 17452.46 18232.70 20159.27 8758.21 10850.09 17771.77 17871.39 17879.31 18378.99 150
MDTV_nov1_ep13_2view60.16 19260.51 19959.75 18265.39 19669.05 18668.00 16748.29 20551.99 18345.95 16348.01 18649.64 18953.39 17068.83 19966.52 20277.47 18969.55 198
CMPMVSbinary47.78 1762.49 17762.52 18962.46 16670.01 18070.66 18162.97 19551.84 19051.98 18456.71 10142.87 19753.62 14757.80 13572.23 17370.37 18275.45 19975.91 168
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
WR-MVS_H61.83 18665.87 16357.12 19371.72 16876.87 14161.45 19966.19 5951.97 18522.92 21953.13 15752.30 17033.80 20971.03 18475.00 16386.65 11080.78 128
PS-CasMVS62.38 18065.06 17159.25 18771.73 16775.21 16462.77 19766.99 5851.94 18626.96 21052.00 17247.52 19841.06 20071.16 18375.60 15685.97 13281.97 120
DTE-MVSNet61.85 18464.96 17458.22 18974.32 14674.39 16961.01 20067.85 5351.76 18721.91 22253.28 15248.17 19437.74 20472.22 17476.44 14386.52 11478.49 152
conf0.05thres100066.26 14866.77 15165.66 14677.45 10078.10 11671.85 15262.44 10551.47 18843.00 17647.92 18751.66 17853.40 16979.71 9477.97 10385.82 13580.56 130
v7n67.05 14566.94 14967.17 13172.35 16378.97 10173.26 14358.88 15151.16 18950.90 13348.21 18550.11 18660.96 11977.70 12077.38 11686.68 10985.05 80
pmmvs562.37 18164.04 17960.42 17865.03 19771.67 17867.17 17452.70 18650.30 19044.80 16854.23 13951.19 18149.37 17972.88 16973.48 17083.45 16474.55 178
FPMVS51.87 20950.00 21454.07 20266.83 19257.25 21560.25 20350.91 19350.25 19134.36 19936.04 21232.02 22041.49 19858.98 22256.07 22270.56 21459.36 217
TAMVS59.58 19462.81 18755.81 19766.03 19565.64 19963.86 19248.74 20249.95 19237.07 19354.77 12858.54 10644.44 19272.29 17271.79 17574.70 20166.66 203
v5265.23 15366.24 15564.06 15661.94 20376.42 14672.06 15054.30 17849.94 19350.04 13947.41 19052.42 16660.23 12675.71 15376.22 14785.78 13685.56 67
v74865.12 15565.24 16864.98 15069.77 18176.45 14569.47 16157.06 17049.93 19450.70 13447.87 18849.50 19057.14 14173.64 16775.18 16185.75 13884.14 89
V465.23 15366.23 15664.06 15661.94 20376.42 14672.05 15154.31 17749.91 19550.06 13847.42 18952.40 16760.24 12575.71 15376.22 14785.78 13685.56 67
pm-mvs165.62 15067.42 14363.53 16173.66 15476.39 14869.66 15860.87 12149.73 19643.97 17251.24 17657.00 11948.16 18179.89 9277.84 10584.85 15579.82 140
N_pmnet47.35 21450.13 21344.11 21759.98 20851.64 22351.86 21444.80 21649.58 19720.76 22340.65 20340.05 21429.64 21359.84 22055.15 22357.63 22654.00 224
Anonymous2023120656.36 20157.80 20454.67 20170.08 17966.39 19660.46 20257.54 16549.50 19829.30 20533.86 21546.64 19935.18 20770.44 19168.88 19075.47 19868.88 200
anonymousdsp65.28 15267.98 13762.13 16858.73 21373.98 17167.10 17550.69 19648.41 19947.66 15254.27 13552.75 16561.45 11876.71 14680.20 7687.13 8189.53 46
LP53.62 20753.43 20753.83 20458.51 21462.59 21157.31 20746.04 21247.86 20042.69 17936.08 21136.86 21646.53 18864.38 20864.25 20771.92 20962.00 213
tfpnnormal64.27 16463.64 18265.02 14975.84 11675.61 15571.24 15562.52 10247.79 20142.97 17742.65 19844.49 20652.66 17378.77 10776.86 12484.88 15379.29 146
TransMVSNet (Re)64.74 16065.66 16563.66 16077.40 10175.33 15869.86 15762.67 9847.63 20241.21 18250.01 18052.33 16845.31 19179.57 9777.69 10985.49 14277.07 163
ambc53.42 20864.99 19863.36 20649.96 21747.07 20337.12 19228.97 21916.36 23441.82 19775.10 15967.34 19771.55 21175.72 170
EG-PatchMatch MVS67.24 14366.94 14967.60 12078.73 7981.35 7473.28 14259.49 14446.89 20451.42 13143.65 19653.49 15155.50 16081.38 6680.66 7087.15 7781.17 126
SixPastTwentyTwo61.84 18562.45 19061.12 17569.20 18672.20 17562.03 19857.40 16746.54 20538.03 19157.14 10541.72 21058.12 13469.67 19571.58 17781.94 17078.30 153
MVS-HIRNet54.41 20452.10 21157.11 19458.99 21156.10 21749.68 21849.10 20046.18 20652.15 12733.18 21646.11 20356.10 15263.19 21159.70 21976.64 19360.25 215
EU-MVSNet54.63 20358.69 20149.90 21056.99 21662.70 21056.41 20950.64 19745.95 20723.14 21650.42 17946.51 20036.63 20565.51 20664.85 20575.57 19674.91 176
MDA-MVSNet-bldmvs53.37 20853.01 21053.79 20543.67 23067.95 19059.69 20457.92 16443.69 20832.41 20241.47 20027.89 22852.38 17456.97 22465.99 20476.68 19267.13 202
testgi54.39 20557.86 20350.35 20971.59 17367.24 19254.95 21153.25 18143.36 20923.78 21344.64 19547.87 19624.96 22070.45 19068.66 19273.60 20562.78 211
test20.0353.93 20656.28 20651.19 20872.19 16565.83 19753.20 21361.08 11842.74 21022.08 22037.07 20845.76 20424.29 22470.44 19169.04 18874.31 20363.05 210
new-patchmatchnet46.97 21649.47 21544.05 21862.82 20156.55 21645.35 22252.01 18842.47 21117.04 22835.73 21335.21 21721.84 22961.27 21554.83 22465.26 22360.26 214
pmmvs662.41 17862.88 18561.87 17171.38 17475.18 16567.76 16959.45 14641.64 21242.52 18037.33 20752.91 16146.87 18677.67 12276.26 14583.23 16679.18 149
MIMVSNet149.27 21153.25 20944.62 21644.61 22761.52 21353.61 21252.18 18741.62 21318.68 22428.14 22341.58 21125.50 21868.46 20169.04 18873.15 20662.37 212
new_pmnet38.40 22342.64 22433.44 22537.54 23345.00 22936.60 22932.72 23040.27 21412.72 23129.89 21828.90 22624.78 22153.17 22652.90 22756.31 22748.34 225
Gipumacopyleft36.38 22435.80 22737.07 22345.76 22633.90 23229.81 23148.47 20439.91 21518.02 2268.00 2358.14 23725.14 21959.29 22161.02 21655.19 23040.31 228
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
gg-mvs-nofinetune62.55 17565.05 17259.62 18478.72 8077.61 12770.83 15653.63 17939.71 21622.04 22136.36 20964.32 9047.53 18281.16 7179.03 8885.00 15077.17 160
test235647.20 21548.62 21845.54 21556.38 21854.89 21950.62 21545.08 21538.65 21723.40 21436.23 21031.10 22229.31 21462.76 21262.49 21268.48 21754.23 223
testus45.61 21949.06 21741.59 22056.13 21955.28 21843.51 22339.64 22437.74 21818.23 22535.52 21431.28 22124.69 22262.46 21362.90 21067.33 21958.26 219
tmp_tt14.50 23314.68 2357.17 23810.46 2382.21 23437.73 21928.71 20725.26 22616.98 2324.37 23431.49 23029.77 23026.56 234
testpf47.41 21348.47 21946.18 21366.30 19450.67 22448.15 22042.60 22137.10 22028.75 20640.97 20139.01 21530.82 21252.95 22753.74 22660.46 22564.87 205
111143.08 22044.02 22241.98 21959.22 20949.27 22741.48 22545.63 21335.01 22123.06 21728.60 22130.15 22427.22 21560.42 21857.97 22055.27 22946.74 226
.test124530.81 22729.14 22932.77 22659.22 20949.27 22741.48 22545.63 21335.01 22123.06 21728.60 22130.15 22427.22 21560.42 2180.10 2330.01 2370.43 235
pmmvs347.65 21249.08 21645.99 21444.61 22754.79 22050.04 21631.95 23133.91 22329.90 20330.37 21733.53 21946.31 18963.50 20963.67 20973.14 20763.77 209
gm-plane-assit57.00 19957.62 20556.28 19676.10 11262.43 21247.62 22146.57 20933.84 22423.24 21537.52 20640.19 21359.61 12879.81 9377.55 11284.55 15972.03 190
LTVRE_ROB59.44 1661.82 18762.64 18860.87 17772.83 16277.19 13064.37 19058.97 14933.56 22528.00 20852.59 16842.21 20963.93 10274.52 16076.28 14477.15 19182.13 114
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
PMVScopyleft39.38 1846.06 21843.30 22349.28 21162.93 20038.75 23141.88 22453.50 18033.33 22635.46 19828.90 22031.01 22333.04 21058.61 22354.63 22568.86 21657.88 220
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
Anonymous2023121151.46 21050.59 21252.46 20767.30 18966.70 19555.00 21059.22 14729.96 22717.62 22719.11 22928.74 22735.72 20666.42 20469.52 18579.92 18073.71 184
testmv42.58 22144.36 22040.49 22154.63 22352.76 22141.21 22744.37 21728.83 22812.87 22927.16 22425.03 22923.01 22560.83 21661.13 21466.88 22054.81 221
test123567842.57 22244.36 22040.49 22154.63 22352.75 22241.21 22744.37 21728.82 22912.87 22927.15 22525.01 23023.01 22560.83 21661.13 21466.88 22054.81 221
DeepMVS_CXcopyleft18.74 23718.55 2348.02 23326.96 2307.33 23423.81 22813.05 23625.99 21725.17 23222.45 23636.25 231
test1235635.10 22638.50 22531.13 22744.14 22943.70 23032.27 23034.42 22726.51 2319.47 23325.22 22720.34 23110.86 23253.47 22556.15 22155.59 22844.11 227
PMMVS225.60 22829.75 22820.76 23128.00 23430.93 23323.10 23329.18 23223.14 2321.46 23918.23 23016.54 2335.08 23340.22 22941.40 22937.76 23137.79 230
no-one36.35 22537.59 22634.91 22446.13 22549.89 22627.99 23243.56 21920.91 2337.03 23514.64 23115.50 23518.92 23042.95 22860.20 21765.84 22259.03 218
EMVS20.98 23017.15 23225.44 22939.51 23219.37 23612.66 23539.59 22519.10 2346.62 2379.27 2334.40 23922.43 22717.99 23424.40 23231.81 23325.53 233
E-PMN21.77 22918.24 23125.89 22840.22 23119.58 23512.46 23639.87 22318.68 2356.71 2369.57 2324.31 24022.36 22819.89 23327.28 23133.73 23228.34 232
MVEpermissive19.12 1920.47 23123.27 23017.20 23212.66 23625.41 23410.52 23734.14 22914.79 2366.53 2388.79 2344.68 23816.64 23129.49 23141.63 22822.73 23538.11 229
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
testmvs0.09 2320.15 2330.02 2340.01 2380.02 2390.05 2400.01 2360.11 2370.01 2410.26 2370.01 2410.06 2370.10 2350.10 2330.01 2370.43 235
test1230.09 2320.14 2340.02 2340.00 2390.02 2390.02 2410.01 2360.09 2380.00 2420.30 2360.00 2420.08 2350.03 2360.09 2350.01 2370.45 234
sosnet-low-res0.00 2340.00 2350.00 2360.00 2390.00 2410.00 2420.00 2380.00 2390.00 2420.00 2380.00 2420.00 2380.00 2370.00 2360.00 2400.00 237
sosnet0.00 2340.00 2350.00 2360.00 2390.00 2410.00 2420.00 2380.00 2390.00 2420.00 2380.00 2420.00 2380.00 2370.00 2360.00 2400.00 237
MTAPA83.48 186.45 12
MTMP82.66 384.91 20
Patchmatch-RL test2.85 239
XVS86.63 3988.68 2385.00 4171.81 4081.92 3090.47 17
X-MVStestdata86.63 3988.68 2385.00 4171.81 4081.92 3090.47 17
mPP-MVS89.90 2081.29 35
Patchmtry65.80 19865.97 18252.74 18452.65 123