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 bysorted bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort by
HSP-MVS80.69 181.20 179.14 1086.21 2062.73 1286.09 985.03 1765.51 1583.81 190.51 1463.71 289.23 881.51 188.44 1385.45 92
ESAPD80.56 280.98 279.29 787.27 660.56 3985.71 1786.42 663.28 3783.27 491.83 364.96 190.47 176.41 1389.67 686.84 42
SMA-MVS80.28 380.39 479.95 286.60 1361.95 2286.33 585.75 1162.49 5282.20 692.28 156.53 1689.70 579.85 391.48 188.19 8
APDe-MVS80.16 480.59 378.86 2186.64 1260.02 4388.12 186.42 662.94 4382.40 592.12 259.64 789.76 478.70 688.32 1886.79 44
HPM-MVS++copyleft79.88 580.14 579.10 1388.17 164.80 186.59 483.70 4465.37 1678.78 1190.64 1058.63 1387.24 3479.00 590.37 385.26 104
CNVR-MVS79.84 679.97 679.45 587.90 262.17 2084.37 2485.03 1766.96 677.58 1490.06 2359.47 989.13 1078.67 789.73 487.03 38
SteuartSystems-ACMMP79.48 779.31 779.98 183.01 6062.18 1987.60 285.83 966.69 1178.03 1390.98 754.26 3690.06 278.42 889.02 987.69 19
Skip Steuart: Steuart Systems R&D Blog.
DeepPCF-MVS69.58 179.03 879.00 879.13 1184.92 4660.32 4183.03 4185.33 1362.86 4680.17 790.03 2461.76 388.95 1274.21 2288.67 1288.12 9
ACMMP_Plus78.77 978.78 978.74 2385.44 3461.04 3383.84 3285.16 1562.88 4578.10 1291.26 652.51 5488.39 1679.34 490.52 286.78 45
NCCC78.58 1078.31 1179.39 687.51 562.61 1685.20 2184.42 2566.73 1074.67 3389.38 3455.30 2789.18 974.19 2387.34 3086.38 51
DeepC-MVS69.38 278.56 1178.14 1479.83 383.60 5461.62 2684.17 2886.85 263.23 3873.84 4390.25 2157.68 1489.96 374.62 2189.03 887.89 11
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
TSAR-MVS + MP.78.44 1278.28 1278.90 1984.96 4261.41 2984.03 3083.82 4259.34 11979.37 989.76 3059.84 587.62 3176.69 1286.74 3887.68 20
MP-MVS-pluss78.35 1378.46 1078.03 3384.96 4259.52 4882.93 4385.39 1262.15 5776.41 1891.51 452.47 5686.78 4680.66 289.64 787.80 16
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
MP-MVScopyleft78.35 1378.26 1378.64 2486.54 1563.47 586.02 1183.55 4863.89 3173.60 4790.60 1154.85 3286.72 4777.20 1188.06 2385.74 77
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
GST-MVS78.14 1577.85 1678.99 1886.05 2661.82 2585.84 1285.21 1463.56 3574.29 3690.03 2452.56 5388.53 1574.79 2088.34 1586.63 47
APD-MVScopyleft78.02 1678.04 1577.98 3486.44 1760.81 3685.52 1984.36 2660.61 7879.05 1090.30 1955.54 2688.32 1973.48 3187.03 3384.83 116
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
HFP-MVS78.01 1777.65 1779.10 1386.71 962.81 1086.29 684.32 2762.82 4773.96 3890.50 1553.20 4988.35 1774.02 2487.05 3186.13 63
#test#77.83 1877.41 2079.10 1386.71 962.81 1085.69 1884.32 2761.61 6673.96 3890.50 1553.20 4988.35 1773.68 2787.05 3186.13 63
ACMMPR77.71 1977.23 2279.16 886.75 862.93 986.29 684.24 2962.82 4773.55 4890.56 1349.80 7888.24 2074.02 2487.03 3386.32 59
SD-MVS77.70 2077.62 1877.93 3584.47 4961.88 2484.55 2383.87 4060.37 8379.89 889.38 3454.97 2985.58 7576.12 1484.94 4886.33 57
region2R77.67 2177.18 2379.15 986.76 762.95 886.29 684.16 3162.81 4973.30 5190.58 1249.90 7688.21 2173.78 2687.03 3386.29 61
zzz-MVS77.61 2277.36 2178.35 2786.08 2463.57 283.37 3780.97 10565.13 1875.77 2190.88 848.63 10686.66 4877.23 988.17 2084.81 117
MCST-MVS77.48 2377.45 1977.54 3786.67 1158.36 6383.22 3986.93 156.91 15174.91 2988.19 4859.15 1187.68 3073.67 2887.45 2986.57 48
HPM-MVScopyleft77.28 2476.85 2578.54 2585.00 4160.81 3682.91 4485.08 1662.57 5073.09 5489.97 2750.90 7287.48 3275.30 1586.85 3687.33 33
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
DeepC-MVS_fast68.24 377.25 2576.63 2879.12 1286.15 2260.86 3584.71 2284.85 2161.98 6373.06 5588.88 4253.72 4389.06 1168.27 5388.04 2487.42 28
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
XVS77.17 2676.56 2979.00 1686.32 1862.62 1485.83 1383.92 3664.55 2272.17 6490.01 2647.95 11588.01 2571.55 3986.74 3886.37 54
CP-MVS77.12 2776.68 2778.43 2686.05 2663.18 787.55 383.45 5162.44 5472.68 5990.50 1548.18 11387.34 3373.59 2985.71 4584.76 121
CSCG76.92 2876.75 2677.41 3983.96 5359.60 4782.95 4286.50 560.78 7675.27 2484.83 10060.76 486.56 5467.86 5887.87 2886.06 66
MTAPA76.90 2976.42 3078.35 2786.08 2463.57 274.92 19480.97 10565.13 1875.77 2190.88 848.63 10686.66 4877.23 988.17 2084.81 117
test_prior376.89 3076.96 2476.69 4884.20 5157.27 7581.75 6584.88 1960.37 8375.01 2589.06 3756.22 2186.43 5872.19 3588.96 1086.38 51
PGM-MVS76.77 3176.06 3278.88 2086.14 2362.73 1282.55 5283.74 4361.71 6472.45 6390.34 1848.48 11088.13 2272.32 3486.85 3685.78 72
MVS_030476.73 3276.04 3378.78 2281.32 7758.89 5782.50 5484.07 3267.73 572.08 6687.28 5849.49 8089.57 673.52 3086.40 4287.87 13
mPP-MVS76.54 3375.93 3578.34 2986.47 1663.50 485.74 1682.28 7262.90 4471.77 6890.26 2046.61 13386.55 5571.71 3885.66 4684.97 113
CANet76.46 3475.93 3578.06 3281.29 7857.53 7282.35 5683.31 5767.78 370.09 8186.34 7654.92 3088.90 1372.68 3384.55 5087.76 18
CDPH-MVS76.31 3575.67 3878.22 3085.35 3759.14 5381.31 7584.02 3356.32 16674.05 3788.98 4053.34 4787.92 2769.23 5088.42 1487.59 22
train_agg76.27 3676.15 3176.64 5285.58 3261.59 2781.62 6981.26 9555.86 17374.93 2788.81 4353.70 4484.68 10375.24 1788.33 1683.65 161
agg_prior376.13 3775.89 3776.85 4685.76 2862.02 2181.65 6781.01 10355.51 18273.73 4488.60 4753.23 4884.90 9575.24 1788.33 1683.65 161
ACMMPcopyleft76.02 3875.33 4078.07 3185.20 3861.91 2385.49 2084.44 2463.04 4169.80 9489.74 3145.43 14487.16 3872.01 3782.87 6285.14 106
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
agg_prior175.94 3976.01 3475.72 6285.04 3959.96 4481.44 7381.04 10156.14 17174.68 3188.90 4153.91 4084.04 11575.01 1987.92 2783.16 172
PHI-MVS75.87 4075.36 3977.41 3980.62 9055.91 10084.28 2585.78 1056.08 17273.41 5086.58 7050.94 7188.54 1470.79 4389.71 587.79 17
3Dnovator+66.72 475.84 4174.57 4579.66 482.40 6459.92 4685.83 1386.32 866.92 967.80 13489.24 3642.03 17389.38 764.07 9386.50 4189.69 1
Regformer-275.63 4274.99 4177.54 3780.43 9258.32 6479.50 9982.92 6467.84 175.94 2080.75 19555.73 2486.80 4471.44 4180.38 8387.50 24
Regformer-175.47 4374.93 4377.09 4380.43 9257.70 7079.50 9982.13 7367.84 175.73 2380.75 19556.50 1786.07 6271.07 4280.38 8387.50 24
casdiffmvs175.24 4474.76 4476.69 4880.32 9455.61 10682.80 4583.60 4652.54 21676.15 1986.48 7259.44 1085.78 7269.78 4681.70 7288.69 2
APD-MVS_3200maxsize74.96 4574.39 4776.67 5182.20 6558.24 6583.67 3383.29 5858.41 13273.71 4590.14 2245.62 13985.99 6669.64 4882.85 6385.78 72
TSAR-MVS + GP.74.90 4674.15 4977.17 4282.00 6758.77 5981.80 6478.57 16358.58 12874.32 3584.51 10955.94 2387.22 3567.11 6484.48 5285.52 85
DELS-MVS74.76 4774.46 4675.65 6577.84 14952.25 14575.59 17884.17 3063.76 3273.15 5382.79 13459.58 886.80 4467.24 6386.04 4487.89 11
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
OPM-MVS74.73 4874.25 4876.19 5580.81 8659.01 5582.60 5183.64 4563.74 3372.52 6187.49 5347.18 12585.88 7069.47 4980.78 7583.66 160
canonicalmvs74.67 4974.98 4273.71 10278.94 11950.56 17280.23 8583.87 4060.30 8877.15 1586.56 7159.65 682.00 16966.01 7182.12 6688.58 5
casdiffmvs74.55 5073.78 5276.87 4479.00 11756.18 9382.36 5584.45 2353.88 20573.46 4985.76 8956.38 2086.59 5170.70 4478.04 12087.83 15
abl_674.34 5173.50 5476.86 4582.43 6360.16 4283.48 3681.86 7958.81 12573.95 4089.86 2841.87 17686.62 5067.98 5681.23 7483.80 154
HQP_MVS74.31 5273.73 5376.06 5681.41 7556.31 8884.22 2684.01 3464.52 2469.27 10686.10 8045.26 14887.21 3668.16 5480.58 7984.65 122
HPM-MVS_fast74.30 5373.46 5776.80 4784.45 5059.04 5483.65 3481.05 10060.15 9070.43 7689.84 2941.09 19185.59 7467.61 6182.90 6185.77 74
Regformer-474.25 5473.48 5576.57 5379.75 10556.54 8778.54 11081.49 8766.93 873.90 4180.30 20553.84 4285.98 6769.76 4776.84 13487.17 35
MVS_111021_HR74.02 5573.46 5775.69 6483.01 6060.63 3877.29 14778.40 17261.18 7170.58 7585.97 8354.18 3884.00 11967.52 6282.98 6082.45 184
MG-MVS73.96 5673.89 5174.16 8985.65 3049.69 20081.59 7181.29 9461.45 6771.05 7388.11 4951.77 6187.73 2961.05 12883.09 5785.05 110
Regformer-373.89 5773.28 5975.71 6379.75 10555.48 10978.54 11079.93 12866.58 1273.62 4680.30 20554.87 3184.54 10669.09 5176.84 13487.10 37
alignmvs73.86 5873.99 5073.45 11478.20 13850.50 17478.57 10882.43 7059.40 11776.57 1686.71 6456.42 1981.23 18265.84 7381.79 6888.62 3
MSLP-MVS++73.77 5973.47 5674.66 7983.02 5959.29 5282.30 6181.88 7859.34 11971.59 7086.83 6045.94 13783.65 12565.09 7885.22 4781.06 211
HQP-MVS73.45 6072.80 6275.40 6980.66 8754.94 11282.31 5883.90 3862.10 5867.85 12985.54 9345.46 14286.93 4267.04 6580.35 8584.32 129
CLD-MVS73.33 6172.68 6375.29 7278.82 12153.33 12978.23 11684.79 2261.30 7070.41 7781.04 18252.41 5787.12 3964.61 8382.49 6585.41 99
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
Effi-MVS+73.31 6272.54 6475.62 6677.87 14853.64 12379.62 9779.61 13361.63 6572.02 6782.61 13956.44 1885.97 6863.99 9679.07 10887.25 34
UA-Net73.13 6372.93 6173.76 9883.58 5551.66 15178.75 10377.66 18067.75 472.61 6089.42 3249.82 7783.29 13253.61 17283.14 5686.32 59
EPNet73.09 6472.16 6675.90 5875.95 19056.28 9083.05 4072.39 23466.53 1365.27 16687.00 5950.40 7485.47 8162.48 11086.32 4385.94 68
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
nrg03072.96 6573.01 6072.84 13575.41 19750.24 18180.02 8882.89 6758.36 13474.44 3486.73 6258.90 1280.83 18965.84 7374.46 14887.44 27
CPTT-MVS72.78 6672.08 6874.87 7684.88 4761.41 2984.15 2977.86 17655.27 18567.51 13988.08 5141.93 17581.85 17169.04 5280.01 8981.35 205
LPG-MVS_test72.74 6771.74 7075.76 6080.22 9757.51 7382.55 5283.40 5361.32 6866.67 14887.33 5639.15 20686.59 5167.70 5977.30 12983.19 169
PAPM_NR72.63 6871.80 6975.13 7381.72 7053.42 12879.91 9183.28 5959.14 12166.31 15485.90 8451.86 6086.06 6357.45 14380.62 7785.91 69
VDD-MVS72.50 6972.09 6773.75 10081.58 7149.69 20077.76 13377.63 18163.21 3973.21 5289.02 3942.14 17283.32 13161.72 12582.50 6488.25 7
3Dnovator64.47 572.49 7071.39 7675.79 5977.70 15158.99 5680.66 8283.15 6162.24 5665.46 16386.59 6942.38 17185.52 7759.59 13884.72 4982.85 178
MVS_Test72.45 7172.46 6572.42 15474.88 20248.50 21476.28 16583.14 6259.40 11772.46 6284.68 10255.66 2581.12 18365.98 7279.66 9687.63 21
EI-MVSNet-Vis-set72.42 7271.59 7174.91 7478.47 13154.02 11977.05 15179.33 15065.03 2071.68 6979.35 22952.75 5184.89 9666.46 6874.23 15185.83 71
ACMP63.53 672.30 7371.20 8175.59 6880.28 9557.54 7182.74 4882.84 6860.58 7965.24 16886.18 7839.25 20486.03 6566.95 6776.79 13683.22 167
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
PS-MVSNAJss72.24 7471.21 8075.31 7178.50 12955.93 9981.63 6882.12 7456.24 16970.02 8585.68 9047.05 12684.34 11065.27 7774.41 15085.67 79
Vis-MVSNetpermissive72.18 7571.37 7774.61 8281.29 7855.41 11080.90 7878.28 17460.73 7769.23 10988.09 5044.36 15782.65 15857.68 14281.75 7085.77 74
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
API-MVS72.17 7671.41 7474.45 8581.95 6857.22 7784.03 3080.38 12259.89 9868.40 11882.33 14649.64 7987.83 2851.87 18284.16 5478.30 244
EPP-MVSNet72.16 7771.31 7974.71 7778.68 12649.70 19882.10 6281.65 8360.40 8265.94 15785.84 8551.74 6286.37 6055.93 15079.55 9988.07 10
DP-MVS Recon72.15 7870.73 8676.40 5486.57 1457.99 6781.15 7782.96 6357.03 14866.78 14785.56 9144.50 15488.11 2351.77 18480.23 8883.10 173
EI-MVSNet-UG-set71.92 7971.06 8274.52 8477.98 14653.56 12576.62 15879.16 15264.40 2671.18 7178.95 23452.19 5984.66 10565.47 7673.57 16085.32 101
VDDNet71.81 8071.33 7873.26 12682.80 6247.60 22578.74 10475.27 20859.59 11272.94 5689.40 3341.51 18583.91 12058.75 13982.99 5988.26 6
LFMVS71.78 8171.59 7172.32 15783.40 5646.38 23479.75 9471.08 23964.18 2872.80 5888.64 4642.58 16883.72 12357.41 14484.49 5186.86 41
PAPR71.72 8270.82 8574.41 8681.20 8251.17 15579.55 9883.33 5655.81 17666.93 14684.61 10550.95 7086.06 6355.79 15379.20 10686.00 67
IS-MVSNet71.57 8371.00 8373.27 12578.86 12045.63 24080.22 8678.69 16164.14 2966.46 15087.36 5549.30 8485.60 7350.26 19383.71 5588.59 4
diffmvs171.56 8471.40 7572.04 15971.20 27948.71 21274.80 19777.10 19060.84 7371.10 7285.28 9752.65 5280.01 20270.26 4579.35 10387.40 29
MAR-MVS71.51 8570.15 9375.60 6781.84 6959.39 5081.38 7482.90 6654.90 19268.08 12678.70 23547.73 11785.51 7851.68 18684.17 5381.88 192
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
MVSFormer71.50 8670.38 9074.88 7578.76 12357.15 8282.79 4678.48 16751.26 23869.49 10183.22 13043.99 16083.24 13366.06 6979.37 10084.23 136
PVSNet_Blended_VisFu71.45 8770.39 8974.65 8082.01 6658.82 5879.93 9080.35 12455.09 18865.82 16182.16 15249.17 9882.64 15960.34 13278.62 11682.50 183
OMC-MVS71.40 8870.60 8773.78 9676.60 18153.15 13179.74 9579.78 12958.37 13368.75 11386.45 7445.43 14480.60 19462.58 10877.73 12287.58 23
UniMVSNet_NR-MVSNet71.11 8971.00 8371.44 17179.20 11244.13 25276.02 17482.60 6966.48 1468.20 12184.60 10656.82 1582.82 14954.62 16370.43 20687.36 32
PCF-MVS61.88 870.95 9069.49 10775.35 7077.63 15455.71 10276.04 17381.81 8150.30 24669.66 9585.40 9652.51 5484.89 9651.82 18380.24 8785.45 92
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
114514_t70.83 9169.56 10274.64 8186.21 2054.63 11682.34 5781.81 8148.22 26463.01 19285.83 8640.92 19487.10 4057.91 14179.79 9382.18 187
FIs70.82 9271.43 7368.98 21078.33 13538.14 29776.96 15383.59 4761.02 7267.33 14186.73 6255.07 2881.64 17454.61 16579.22 10587.14 36
ACMM61.98 770.80 9369.73 9774.02 9080.59 9158.59 6182.68 4982.02 7755.46 18367.18 14384.39 11138.51 21183.17 13560.65 12976.10 13980.30 224
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
v1neww70.66 9469.70 9873.53 10973.15 24150.22 18278.11 11980.68 11059.65 10669.83 9181.67 16449.29 8684.96 9164.55 8470.38 20985.42 95
v7new70.66 9469.70 9873.53 10973.15 24150.22 18278.11 11980.68 11059.65 10669.83 9181.67 16449.29 8684.96 9164.55 8470.38 20985.42 95
v670.66 9469.70 9873.53 10973.14 24450.21 18578.11 11980.67 11259.65 10669.82 9381.65 16649.29 8684.96 9164.55 8470.39 20885.42 95
UniMVSNet (Re)70.63 9770.20 9171.89 16178.55 12845.29 24275.94 17582.92 6463.68 3468.16 12383.59 12553.89 4183.49 12853.97 16871.12 19886.89 40
v770.57 9869.48 10873.85 9373.50 22950.92 15978.27 11481.43 8858.93 12269.61 9681.49 17247.56 12085.43 8363.94 9770.62 20285.21 105
xiu_mvs_v2_base70.52 9969.75 9672.84 13581.21 8155.63 10575.11 18978.92 15654.92 19169.96 8879.68 21847.00 13082.09 16861.60 12779.37 10080.81 219
PS-MVSNAJ70.51 10069.70 9872.93 13181.52 7255.79 10174.92 19479.00 15555.04 19069.88 8978.66 23647.05 12682.19 16561.61 12679.58 9780.83 218
v114170.50 10169.53 10373.41 11872.92 25150.00 19277.69 13480.60 11459.50 11469.60 9781.43 17349.24 9584.77 10064.48 8870.30 21585.46 91
divwei89l23v2f11270.50 10169.53 10373.41 11872.91 25250.00 19277.69 13480.59 11559.50 11469.60 9781.43 17349.26 9184.77 10064.48 8870.31 21485.47 89
v2v48270.50 10169.45 11073.66 10472.62 25850.03 19177.58 13880.51 11959.90 9669.52 10082.14 15347.53 12184.88 9865.07 7970.17 21886.09 65
v170.50 10169.53 10373.42 11772.91 25250.00 19277.69 13480.59 11559.50 11469.59 9981.42 17549.26 9184.77 10064.49 8770.30 21585.47 89
mvs-test170.44 10568.19 13077.18 4176.10 18763.22 680.59 8376.06 20159.83 10066.32 15379.87 21241.56 18285.53 7660.60 13072.77 17582.80 179
v114470.42 10669.31 11173.76 9873.22 23750.64 16777.83 13181.43 8858.58 12869.40 10481.16 17947.53 12185.29 8664.01 9570.64 20185.34 100
diffmvs70.36 10769.99 9571.46 17070.48 28548.19 21774.59 20376.30 19660.36 8767.75 13783.81 12251.22 6679.77 20367.92 5777.50 12586.42 50
TranMVSNet+NR-MVSNet70.36 10770.10 9471.17 18178.64 12742.97 26376.53 16081.16 9966.95 768.53 11785.42 9551.61 6383.07 13852.32 18069.70 23087.46 26
v870.33 10969.28 11273.49 11273.15 24150.22 18278.62 10780.78 10960.79 7566.45 15182.11 15449.35 8284.98 8963.58 10268.71 23885.28 102
Fast-Effi-MVS+70.28 11069.12 11573.73 10178.50 12951.50 15475.01 19179.46 14656.16 17068.59 11479.55 22553.97 3984.05 11453.34 17477.53 12485.65 81
X-MVStestdata70.21 11167.28 15179.00 1686.32 1862.62 1485.83 1383.92 3664.55 2272.17 646.49 36547.95 11588.01 2571.55 3986.74 3886.37 54
v1070.21 11169.02 11673.81 9573.51 22850.92 15978.74 10481.39 9060.05 9266.39 15281.83 16147.58 11985.41 8462.80 10768.86 23785.09 109
QAPM70.05 11368.81 11973.78 9676.54 18353.43 12783.23 3883.48 4952.89 21265.90 15886.29 7741.55 18486.49 5751.01 18878.40 11881.42 197
DU-MVS70.01 11469.53 10371.44 17178.05 14444.13 25275.01 19181.51 8664.37 2768.20 12184.52 10749.12 10182.82 14954.62 16370.43 20687.37 30
AdaColmapbinary69.99 11568.66 12273.97 9284.94 4457.83 6882.63 5078.71 16056.28 16864.34 18084.14 11341.57 18187.06 4146.45 21978.88 10977.02 261
v119269.97 11668.68 12173.85 9373.19 24050.94 15777.68 13781.36 9157.51 14268.95 11280.85 19145.28 14785.33 8562.97 10670.37 21185.27 103
Anonymous2024052969.91 11769.02 11672.56 14480.19 10047.65 22477.56 14080.99 10455.45 18469.88 8986.76 6139.24 20582.18 16654.04 16777.10 13187.85 14
FC-MVSNet-test69.80 11870.58 8867.46 22377.61 15934.73 32176.05 17283.19 6060.84 7365.88 15986.46 7354.52 3580.76 19352.52 17978.12 11986.91 39
v14419269.71 11968.51 12373.33 12273.10 24650.13 18977.54 14180.64 11356.65 15768.57 11680.55 19846.87 13184.96 9162.98 10569.66 23184.89 115
0601test69.69 12069.13 11371.36 17578.37 13345.74 23874.71 19980.20 12557.91 13770.01 8683.83 11942.44 16982.87 14554.97 15979.72 9485.48 87
Anonymous2024052169.69 12069.13 11371.36 17578.37 13345.74 23874.71 19980.20 12557.91 13770.01 8683.83 11942.44 16982.87 14554.97 15979.72 9485.48 87
VNet69.68 12270.19 9268.16 21879.73 10841.63 27370.53 25677.38 18660.37 8370.69 7486.63 6751.08 6877.09 24853.61 17281.69 7385.75 76
jason69.65 12368.39 12873.43 11678.27 13756.88 8477.12 14973.71 22746.53 27869.34 10583.22 13043.37 16479.18 21464.77 8079.20 10684.23 136
jason: jason.
Effi-MVS+-dtu69.64 12467.53 14275.95 5776.10 18762.29 1880.20 8776.06 20159.83 10065.26 16777.09 26441.56 18284.02 11860.60 13071.09 19981.53 195
lupinMVS69.57 12568.28 12973.44 11578.76 12357.15 8276.57 15973.29 22946.19 28169.49 10182.18 14943.99 16079.23 21264.66 8179.37 10083.93 146
NR-MVSNet69.54 12668.85 11871.59 16978.05 14443.81 25674.20 20680.86 10865.18 1762.76 19484.52 10752.35 5883.59 12650.96 18970.78 20087.37 30
MVS_111021_LR69.50 12768.78 12071.65 16778.38 13259.33 5174.82 19670.11 24558.08 13667.83 13384.68 10241.96 17476.34 25665.62 7577.54 12379.30 238
v192192069.47 12868.17 13173.36 12173.06 24750.10 19077.39 14380.56 11756.58 16368.59 11480.37 20144.72 15084.98 8962.47 11169.82 22685.00 111
test_djsdf69.45 12967.74 13674.58 8374.57 20954.92 11482.79 4678.48 16751.26 23865.41 16483.49 12838.37 21383.24 13366.06 6969.25 23485.56 83
DI_MVS_plusplus_test69.35 13068.03 13373.30 12471.11 28050.14 18875.49 18079.16 15254.57 19762.45 20480.76 19444.67 15284.20 11164.23 9179.81 9285.54 84
Anonymous2023121169.28 13168.47 12571.73 16580.28 9547.18 22979.98 8982.37 7154.61 19467.24 14284.01 11739.43 20282.41 16355.45 15772.83 17485.62 82
EI-MVSNet69.27 13268.44 12771.73 16574.47 21049.39 20575.20 18778.45 16959.60 10969.16 11076.51 27451.29 6482.50 16059.86 13771.45 19683.30 165
test_normal69.26 13367.90 13573.32 12370.84 28350.38 17775.30 18379.17 15154.23 20262.00 21280.61 19744.69 15183.89 12164.33 9079.95 9185.69 78
v124069.24 13467.91 13473.25 12773.02 24949.82 19577.21 14880.54 11856.43 16568.34 12080.51 19943.33 16584.99 8762.03 12169.77 22984.95 114
IterMVS-LS69.22 13568.48 12471.43 17374.44 21249.40 20476.23 16777.55 18259.60 10965.85 16081.59 17051.28 6581.58 17759.87 13669.90 22583.30 165
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
VPA-MVSNet69.02 13669.47 10967.69 22277.42 16241.00 27774.04 20779.68 13160.06 9169.26 10884.81 10151.06 6977.58 24254.44 16674.43 14984.48 127
v7n69.01 13767.36 14873.98 9172.51 26052.65 13778.54 11081.30 9360.26 8962.67 19681.62 16743.61 16284.49 10757.01 14568.70 23984.79 119
OpenMVScopyleft61.03 968.85 13867.56 14072.70 14074.26 21553.99 12081.21 7681.34 9252.70 21362.75 19585.55 9238.86 20984.14 11348.41 20983.01 5879.97 228
XVG-OURS-SEG-HR68.81 13967.47 14472.82 13774.40 21356.87 8570.59 25579.04 15454.77 19366.99 14586.01 8239.57 20178.21 23562.54 10973.33 16483.37 164
BH-RMVSNet68.81 13967.42 14572.97 13080.11 10252.53 14074.26 20576.29 19758.48 13168.38 11984.20 11242.59 16783.83 12246.53 21875.91 14082.56 180
UGNet68.81 13967.39 14673.06 12978.33 13554.47 11779.77 9375.40 20760.45 8163.22 18984.40 11032.71 28380.91 18851.71 18580.56 8183.81 151
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
XVG-OURS68.76 14267.37 14772.90 13274.32 21457.22 7770.09 26278.81 15855.24 18667.79 13585.81 8836.54 24078.28 23462.04 12075.74 14183.19 169
V4268.65 14367.35 14972.56 14468.93 30150.18 18672.90 22179.47 14556.92 15069.45 10380.26 20746.29 13582.99 13964.07 9367.82 25184.53 125
PVSNet_Blended68.59 14467.72 13771.19 18077.03 17450.57 17072.51 22981.52 8451.91 22264.22 18477.77 25049.13 9982.87 14555.82 15179.58 9780.14 227
xiu_mvs_v1_base_debu68.58 14567.28 15172.48 14878.19 13957.19 7975.28 18475.09 21251.61 23070.04 8281.41 17632.79 27979.02 22263.81 9877.31 12681.22 207
xiu_mvs_v1_base68.58 14567.28 15172.48 14878.19 13957.19 7975.28 18475.09 21251.61 23070.04 8281.41 17632.79 27979.02 22263.81 9877.31 12681.22 207
xiu_mvs_v1_base_debi68.58 14567.28 15172.48 14878.19 13957.19 7975.28 18475.09 21251.61 23070.04 8281.41 17632.79 27979.02 22263.81 9877.31 12681.22 207
PVSNet_BlendedMVS68.56 14867.72 13771.07 18477.03 17450.57 17074.50 20481.52 8453.66 20864.22 18479.72 21749.13 9982.87 14555.82 15173.92 15579.77 233
112168.53 14967.16 15672.63 14185.64 3161.14 3173.95 20866.46 27644.61 29570.28 7986.68 6541.42 18680.78 19153.62 17081.79 6875.97 269
WR-MVS68.47 15068.47 12568.44 21780.20 9939.84 28073.75 21376.07 20064.68 2168.11 12583.63 12450.39 7579.14 22049.78 19569.66 23186.34 56
v1668.38 15167.01 15772.47 15273.22 23750.29 17978.10 12279.59 13859.71 10461.72 21877.60 25649.28 8982.89 14362.36 11361.54 29384.23 136
v1768.37 15267.00 15872.48 14873.22 23750.31 17878.10 12279.58 14059.71 10461.67 21977.60 25649.31 8382.89 14362.37 11261.48 29684.23 136
v1868.33 15366.96 15972.42 15473.13 24550.16 18777.97 12779.57 14259.57 11361.80 21677.50 26149.30 8482.90 14262.31 11461.50 29484.20 142
v1368.29 15466.84 16172.63 14173.50 22950.83 16278.25 11579.58 14060.05 9260.76 23477.68 25349.11 10482.77 15162.17 11760.45 30784.30 131
v1268.28 15566.83 16372.60 14373.43 23150.74 16578.18 11779.59 13860.01 9460.89 23377.66 25449.12 10182.77 15162.18 11560.46 30684.29 132
V968.27 15666.84 16172.56 14473.39 23450.63 16878.10 12279.60 13559.94 9561.05 23177.62 25549.18 9782.77 15162.17 11760.48 30584.27 133
BH-untuned68.27 15667.29 15071.21 17979.74 10753.22 13076.06 17177.46 18557.19 14466.10 15581.61 16845.37 14683.50 12745.42 23476.68 13876.91 265
jajsoiax68.25 15866.45 17073.66 10475.62 19355.49 10880.82 7978.51 16652.33 21864.33 18184.11 11428.28 30981.81 17363.48 10370.62 20283.67 159
V1468.25 15866.82 16472.52 14773.33 23550.53 17378.02 12579.60 13559.83 10061.16 22977.57 25849.19 9682.77 15162.18 11560.50 30484.26 134
v14868.24 16067.19 15571.40 17470.43 28747.77 22375.76 17777.03 19158.91 12367.36 14080.10 20948.60 10981.89 17060.01 13466.52 25984.53 125
v1568.22 16166.81 16572.47 15273.25 23650.40 17677.92 12979.60 13559.77 10361.28 22777.52 26049.25 9382.77 15162.16 11960.51 30384.24 135
CANet_DTU68.18 16267.71 13969.59 20274.83 20346.24 23578.66 10676.85 19359.60 10963.45 18882.09 15535.25 25177.41 24459.88 13578.76 11385.14 106
mvs_tets68.18 16266.36 17473.63 10775.61 19455.35 11180.77 8078.56 16452.48 21764.27 18384.10 11527.45 31581.84 17263.45 10470.56 20583.69 156
v1168.15 16466.73 16672.42 15473.43 23150.28 18077.94 12879.65 13259.88 9961.11 23077.55 25948.25 11282.75 15661.88 12460.85 30084.23 136
mvs_anonymous68.03 16567.51 14369.59 20272.08 26644.57 24971.99 24075.23 20951.67 22967.06 14482.57 14054.68 3377.94 23856.56 14675.71 14286.26 62
thisisatest053067.92 16665.78 18274.33 8776.29 18551.03 15676.89 15574.25 22153.67 20765.59 16281.76 16235.15 25285.50 7955.94 14972.47 18086.47 49
PAPM67.92 16666.69 16771.63 16878.09 14249.02 20877.09 15081.24 9751.04 24160.91 23283.98 11847.71 11884.99 8740.81 26479.32 10480.90 217
tttt051767.83 16865.66 18474.33 8776.69 17950.82 16377.86 13073.99 22454.54 19864.64 17882.53 14235.06 25385.50 7955.71 15469.91 22486.67 46
Test467.77 16965.97 17973.19 12868.64 30250.58 16974.80 19780.48 12054.13 20359.11 25279.07 23333.89 26883.12 13763.61 10179.98 9085.87 70
VPNet67.52 17068.11 13265.74 24979.18 11336.80 30972.17 23472.83 23262.04 6167.79 13585.83 8648.88 10576.60 25351.30 18772.97 17383.81 151
Fast-Effi-MVS+-dtu67.37 17165.33 18973.48 11372.94 25057.78 6977.47 14276.88 19257.60 14161.97 21376.85 26839.31 20380.49 19554.72 16270.28 21782.17 188
MVS67.37 17166.33 17570.51 19175.46 19650.94 15773.95 20881.85 8041.57 31962.54 20078.57 24047.98 11485.47 8152.97 17782.05 6775.14 278
v74867.26 17365.67 18372.02 16069.90 29549.77 19776.24 16679.57 14258.58 12860.49 23780.38 20044.47 15682.17 16756.16 14865.26 26784.12 145
GBi-Net67.21 17466.55 16869.19 20777.63 15443.33 25977.31 14477.83 17756.62 16065.04 17182.70 13541.85 17780.33 19747.18 21372.76 17683.92 147
test167.21 17466.55 16869.19 20777.63 15443.33 25977.31 14477.83 17756.62 16065.04 17182.70 13541.85 17780.33 19747.18 21372.76 17683.92 147
MVSTER67.16 17665.58 18671.88 16270.37 28949.70 19870.25 26178.45 16951.52 23369.16 11080.37 20138.45 21282.50 16060.19 13371.46 19583.44 163
v5267.09 17765.16 19272.87 13366.77 31551.60 15273.69 21479.45 14757.88 13962.46 20378.57 24040.95 19383.34 12961.99 12264.70 27283.68 157
V467.09 17765.16 19272.87 13366.76 31651.60 15273.69 21479.45 14757.88 13962.45 20478.58 23940.96 19283.34 12961.99 12264.71 27083.68 157
Baseline_NR-MVSNet67.05 17967.56 14065.50 25575.65 19237.70 30175.42 18174.65 21759.90 9668.14 12483.15 13349.12 10177.20 24652.23 18169.78 22781.60 194
WR-MVS_H67.02 18066.92 16067.33 22677.95 14737.75 30077.57 13982.11 7562.03 6262.65 19782.48 14350.57 7379.46 20842.91 25264.01 27684.79 119
anonymousdsp67.00 18164.82 19673.57 10870.09 29156.13 9476.35 16377.35 18748.43 26264.99 17480.84 19233.01 27680.34 19664.66 8167.64 25484.23 136
FMVSNet266.93 18266.31 17768.79 21377.63 15442.98 26276.11 16977.47 18356.62 16065.22 17082.17 15141.85 17780.18 20047.05 21672.72 17983.20 168
BH-w/o66.85 18365.83 18169.90 19979.29 11052.46 14274.66 20176.65 19454.51 19964.85 17578.12 24245.59 14182.95 14143.26 24875.54 14374.27 291
Anonymous20240521166.84 18465.99 17869.40 20680.19 10042.21 26771.11 25071.31 23858.80 12667.90 12786.39 7529.83 30179.65 20549.60 20178.78 11286.33 57
CDS-MVSNet66.80 18565.37 18771.10 18378.98 11853.13 13373.27 21771.07 24052.15 22064.72 17680.23 20843.56 16377.10 24745.48 23278.88 10983.05 174
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
TAMVS66.78 18665.27 19071.33 17879.16 11553.67 12273.84 21269.59 25052.32 21965.28 16581.72 16344.49 15577.40 24542.32 25578.66 11582.92 175
FMVSNet166.70 18765.87 18069.19 20777.49 16143.33 25977.31 14477.83 17756.45 16464.60 17982.70 13538.08 21880.33 19746.08 22372.31 18883.92 147
ab-mvs66.65 18866.42 17267.37 22476.17 18641.73 27170.41 25976.14 19953.99 20465.98 15683.51 12749.48 8176.24 25748.60 20773.46 16284.14 143
PEN-MVS66.60 18966.45 17067.04 22777.11 17236.56 31177.03 15280.42 12162.95 4262.51 20284.03 11646.69 13279.07 22144.22 23863.08 28485.51 86
TAPA-MVS59.36 1066.60 18965.20 19170.81 18676.63 18048.75 21176.52 16180.04 12750.64 24465.24 16884.93 9939.15 20678.54 22736.77 28276.88 13385.14 106
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
TR-MVS66.59 19165.07 19471.17 18179.18 11349.63 20273.48 21675.20 21052.95 21167.90 12780.33 20439.81 19883.68 12443.20 24973.56 16180.20 225
CP-MVSNet66.49 19266.41 17366.72 22977.67 15336.33 31376.83 15779.52 14462.45 5362.54 20083.47 12946.32 13478.37 23245.47 23363.43 28185.45 92
PS-CasMVS66.42 19366.32 17666.70 23177.60 16036.30 31576.94 15479.61 13362.36 5562.43 20983.66 12345.69 13878.37 23245.35 23563.26 28285.42 95
FMVSNet366.32 19465.61 18568.46 21676.48 18442.34 26674.98 19377.15 18955.83 17565.04 17181.16 17939.91 19680.14 20147.18 21372.76 17682.90 177
ACMH+57.40 1166.12 19564.06 19872.30 15877.79 15052.83 13580.39 8478.03 17557.30 14357.47 27382.55 14127.68 31384.17 11245.54 23069.78 22779.90 229
testing_266.02 19663.77 20372.76 13966.03 32150.48 17572.93 22080.36 12354.41 20054.25 29976.76 27030.89 29383.16 13664.19 9274.08 15384.65 122
cascas65.98 19763.42 20873.64 10677.26 17052.58 13972.26 23377.21 18848.56 25961.21 22874.60 29132.57 28785.82 7150.38 19276.75 13782.52 182
thisisatest051565.83 19863.50 20772.82 13773.75 22549.50 20371.32 24573.12 23149.39 25263.82 18676.50 27634.95 25584.84 9953.20 17675.49 14484.13 144
DP-MVS65.68 19963.66 20571.75 16484.93 4556.87 8580.74 8173.16 23053.06 21059.09 25382.35 14536.79 23885.94 6932.82 30069.96 22372.45 309
HyFIR lowres test65.67 20063.01 21273.67 10379.97 10455.65 10469.07 27075.52 20542.68 31363.53 18777.95 24440.43 19581.64 17446.01 22471.91 19183.73 155
DTE-MVSNet65.58 20165.34 18866.31 23476.06 18934.79 31976.43 16279.38 14962.55 5161.66 22083.83 11945.60 14079.15 21941.64 26260.88 29985.00 111
GA-MVS65.53 20263.70 20471.02 18570.87 28248.10 21870.48 25774.40 21956.69 15664.70 17776.77 26933.66 27081.10 18455.42 15870.32 21383.87 150
CNLPA65.43 20364.02 19969.68 20078.73 12558.07 6677.82 13270.71 24251.49 23461.57 22283.58 12638.23 21670.82 28343.90 24270.10 22080.16 226
MVP-Stereo65.41 20463.80 20270.22 19377.62 15855.53 10776.30 16478.53 16550.59 24556.47 28078.65 23739.84 19782.68 15744.10 24172.12 19072.44 310
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
IB-MVS56.42 1265.40 20562.73 21673.40 12074.89 20152.78 13673.09 21975.13 21155.69 17858.48 26173.73 29632.86 27886.32 6150.63 19070.11 21981.10 210
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-mvs165.24 20664.97 19566.04 24372.38 26139.40 28572.62 22775.63 20455.53 18162.35 21183.18 13247.45 12376.47 25449.06 20466.54 25882.24 186
ACMH55.70 1565.20 20763.57 20670.07 19678.07 14352.01 15079.48 10179.69 13055.75 17756.59 27980.98 18627.12 31780.94 18642.90 25371.58 19477.25 259
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
PLCcopyleft56.13 1465.09 20863.21 21070.72 18981.04 8454.87 11578.57 10877.47 18348.51 26055.71 28381.89 16033.71 26979.71 20441.66 26070.37 21177.58 252
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
CHOSEN 1792x268865.08 20962.84 21471.82 16381.49 7456.26 9166.32 28774.20 22240.53 32563.16 19178.65 23741.30 18777.80 24045.80 22674.09 15281.40 198
TransMVSNet (Re)64.72 21064.33 19765.87 24875.22 19938.56 29474.66 20175.08 21558.90 12461.79 21782.63 13851.18 6778.07 23743.63 24555.87 32080.99 216
EG-PatchMatch MVS64.71 21162.87 21370.22 19377.68 15253.48 12677.99 12678.82 15753.37 20956.03 28277.41 26324.75 33184.04 11546.37 22073.42 16373.14 302
LS3D64.71 21162.50 21871.34 17779.72 10955.71 10279.82 9274.72 21648.50 26156.62 27884.62 10433.59 27182.34 16429.65 32575.23 14575.97 269
131464.61 21363.21 21068.80 21271.87 27147.46 22673.95 20878.39 17342.88 31259.97 24076.60 27338.11 21779.39 21054.84 16172.32 18779.55 234
HY-MVS56.14 1364.55 21463.89 20066.55 23274.73 20641.02 27569.96 26374.43 21849.29 25361.66 22080.92 18847.43 12476.68 25244.91 23771.69 19381.94 190
XVG-ACMP-BASELINE64.36 21562.23 22370.74 18872.35 26252.45 14370.80 25478.45 16953.84 20659.87 24281.10 18116.24 34379.32 21155.64 15671.76 19280.47 221
CostFormer64.04 21662.51 21768.61 21571.88 27045.77 23771.30 24670.60 24347.55 27164.31 18276.61 27241.63 18079.62 20749.74 19769.00 23580.42 222
1112_ss64.00 21763.36 20965.93 24679.28 11142.58 26571.35 24472.36 23546.41 27960.55 23677.89 24746.27 13673.28 27446.18 22169.97 22281.92 191
pmmvs663.69 21862.82 21566.27 23870.63 28439.27 28673.13 21875.47 20652.69 21459.75 24582.30 14739.71 19977.03 24947.40 21264.35 27582.53 181
Vis-MVSNet (Re-imp)63.69 21863.88 20163.14 27274.75 20531.04 34271.16 24963.64 29956.32 16659.80 24484.99 9844.51 15375.46 26039.12 27180.62 7782.92 175
conf200view1163.38 22062.41 21966.29 23777.31 16338.66 29172.65 22369.11 25757.07 14562.45 20481.03 18337.01 22979.17 21531.84 30473.25 16681.03 212
tfpn11163.33 22162.34 22166.30 23577.31 16338.66 29172.65 22369.11 25757.07 14562.45 20481.03 18337.01 22979.23 21231.38 31373.09 17181.03 212
thres40063.31 22262.18 22466.72 22976.85 17739.62 28271.96 24169.44 25356.63 15862.61 19879.83 21337.18 22479.17 21531.84 30473.25 16681.36 199
thres600view763.30 22362.27 22266.41 23377.18 17138.87 28872.35 23169.11 25756.98 14962.37 21080.96 18737.01 22979.00 22531.43 31273.05 17281.36 199
thres100view90063.28 22462.41 21965.89 24777.31 16338.66 29172.65 22369.11 25757.07 14562.45 20481.03 18337.01 22979.17 21531.84 30473.25 16679.83 230
test_040263.25 22561.01 23969.96 19780.00 10354.37 11876.86 15672.02 23654.58 19658.71 25680.79 19335.00 25484.36 10926.41 34064.71 27071.15 322
tfpn200view963.18 22662.18 22466.21 23976.85 17739.62 28271.96 24169.44 25356.63 15862.61 19879.83 21337.18 22479.17 21531.84 30473.25 16679.83 230
LTVRE_ROB55.42 1663.15 22761.23 23768.92 21176.57 18247.80 22159.92 31776.39 19554.35 20158.67 25782.46 14429.44 30481.49 17842.12 25671.14 19777.46 253
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
F-COLMAP63.05 22860.87 24069.58 20476.99 17653.63 12478.12 11876.16 19847.97 26852.41 31081.61 16827.87 31178.11 23640.07 26766.66 25777.00 262
IterMVS62.79 22961.27 23667.35 22569.37 29952.04 14971.17 24868.24 26452.63 21559.82 24376.91 26737.32 22372.36 27752.80 17863.19 28377.66 251
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
view60062.77 23061.84 22765.55 25177.28 16636.87 30572.15 23567.78 26556.79 15261.46 22381.92 15636.88 23378.42 22829.86 32072.46 18181.36 199
view80062.77 23061.84 22765.55 25177.28 16636.87 30572.15 23567.78 26556.79 15261.46 22381.92 15636.88 23378.42 22829.86 32072.46 18181.36 199
conf0.05thres100062.77 23061.84 22765.55 25177.28 16636.87 30572.15 23567.78 26556.79 15261.46 22381.92 15636.88 23378.42 22829.86 32072.46 18181.36 199
tfpn62.77 23061.84 22765.55 25177.28 16636.87 30572.15 23567.78 26556.79 15261.46 22381.92 15636.88 23378.42 22829.86 32072.46 18181.36 199
tpmp4_e2362.71 23460.13 24370.45 19273.40 23348.39 21572.82 22269.49 25244.88 29159.91 24174.99 28737.79 22081.47 17940.22 26667.71 25381.48 196
tfpnnormal62.47 23561.63 23364.99 26074.81 20439.01 28771.22 24773.72 22655.22 18760.21 23880.09 21041.26 19076.98 25030.02 31968.09 24878.97 242
MS-PatchMatch62.42 23661.46 23465.31 25875.21 20052.10 14672.05 23974.05 22346.41 27957.42 27474.36 29234.35 26377.57 24345.62 22973.67 15766.26 333
Test_1112_low_res62.32 23761.77 23164.00 26679.08 11639.53 28468.17 27970.17 24443.25 30859.03 25479.90 21144.08 15871.24 28243.79 24468.42 24081.25 206
thres20062.20 23861.16 23865.34 25775.38 19839.99 27969.60 26569.29 25555.64 18061.87 21576.99 26537.07 22878.96 22631.28 31473.28 16577.06 260
PatchFormer-LS_test62.20 23860.59 24167.04 22772.18 26546.82 23270.36 26068.62 26251.92 22159.19 25170.23 31436.86 23775.07 26950.23 19465.68 26479.23 239
tpm262.07 24060.10 24467.99 21972.79 25543.86 25571.05 25166.85 27443.14 31062.77 19375.39 28538.32 21480.80 19041.69 25968.88 23679.32 237
DWT-MVSNet_test61.90 24159.93 24567.83 22071.98 26946.09 23671.03 25269.71 24650.09 24758.51 26070.62 31130.21 29877.63 24149.28 20267.91 24979.78 232
EPNet_dtu61.90 24161.97 22661.68 28072.89 25439.78 28175.85 17665.62 28055.09 18854.56 29579.36 22837.59 22167.02 29939.80 27076.95 13278.25 245
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
LCM-MVSNet-Re61.88 24361.35 23563.46 26774.58 20831.48 34161.42 31158.14 32358.71 12753.02 30979.55 22543.07 16676.80 25145.69 22777.96 12182.11 189
MSDG61.81 24459.23 24769.55 20572.64 25752.63 13870.45 25875.81 20351.38 23653.70 30376.11 27829.52 30281.08 18537.70 27765.79 26374.93 283
SixPastTwentyTwo61.65 24558.80 25770.20 19575.80 19147.22 22875.59 17869.68 24854.61 19454.11 30079.26 23027.07 31882.96 14043.27 24749.79 33780.41 223
pmmvs461.48 24659.39 24667.76 22171.57 27353.86 12171.42 24365.34 28244.20 30059.46 24677.92 24635.90 24174.71 27143.87 24364.87 26974.71 287
OurMVSNet-221017-061.37 24758.63 26069.61 20172.05 26748.06 21973.93 21172.51 23347.23 27454.74 29280.92 18821.49 33881.24 18148.57 20856.22 31979.53 235
COLMAP_ROBcopyleft52.97 1761.27 24858.81 25068.64 21474.63 20752.51 14178.42 11373.30 22849.92 25050.96 31581.51 17123.06 33479.40 20931.63 30965.85 26174.01 298
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
XXY-MVS60.68 24961.67 23257.70 30470.43 28738.45 29564.19 30166.47 27548.05 26763.22 18980.86 19049.28 8960.47 32145.25 23667.28 25674.19 296
K. test v360.47 25057.11 26870.56 19073.74 22748.22 21675.10 19062.55 30758.27 13553.62 30576.31 27727.81 31281.59 17647.42 21139.18 34981.88 192
OpenMVS_ROBcopyleft52.78 1860.03 25158.14 26365.69 25070.47 28644.82 24475.33 18270.86 24145.04 29056.06 28176.00 27926.89 32079.65 20535.36 29267.29 25572.60 306
conf0.0159.97 25258.81 25063.42 26874.15 21733.83 32768.32 27364.22 29051.79 22358.04 26479.57 21935.41 24475.41 26129.57 32668.26 24181.03 212
conf0.00259.97 25258.81 25063.42 26874.15 21733.83 32768.32 27364.22 29051.79 22358.04 26479.57 21935.41 24475.41 26129.57 32668.26 24181.03 212
CR-MVSNet59.91 25457.90 26665.96 24469.96 29352.07 14765.31 29563.15 30342.48 31459.36 24774.84 28835.83 24270.75 28445.50 23164.65 27375.06 279
PatchmatchNetpermissive59.84 25558.24 26164.65 26373.05 24846.70 23369.42 26762.18 30947.55 27158.88 25571.96 30334.49 26169.16 29042.99 25163.60 27978.07 247
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
Patchmatch-test159.75 25658.00 26564.98 26174.14 22348.06 21963.35 30363.23 30249.13 25559.33 25071.46 30537.45 22269.59 28841.39 26362.57 28777.30 255
WTY-MVS59.75 25660.39 24257.85 30272.32 26337.83 29961.05 31564.18 29645.95 28661.91 21479.11 23247.01 12960.88 32042.50 25469.49 23374.83 284
CVMVSNet59.63 25859.14 24861.08 29074.47 21038.84 28975.20 18768.74 26131.15 34758.24 26276.51 27432.39 28868.58 29349.77 19665.84 26275.81 272
tfpn_ndepth59.57 25959.02 24961.23 28573.81 22435.60 31769.40 26865.59 28150.96 24257.96 27077.72 25134.81 25675.91 25930.36 31770.57 20472.18 315
thresconf0.0259.40 26058.81 25061.17 28674.15 21733.83 32768.32 27364.22 29051.79 22358.04 26479.57 21935.41 24475.41 26129.57 32668.26 24174.25 292
tfpn_n40059.40 26058.81 25061.17 28674.15 21733.83 32768.32 27364.22 29051.79 22358.04 26479.57 21935.41 24475.41 26129.57 32668.26 24174.25 292
tfpnconf59.40 26058.81 25061.17 28674.15 21733.83 32768.32 27364.22 29051.79 22358.04 26479.57 21935.41 24475.41 26129.57 32668.26 24174.25 292
tfpnview1159.40 26058.81 25061.17 28674.15 21733.83 32768.32 27364.22 29051.79 22358.04 26479.57 21935.41 24475.41 26129.57 32668.26 24174.25 292
tpm cat159.25 26456.95 27166.15 24072.19 26446.96 23068.09 28065.76 27940.03 32857.81 27170.56 31238.32 21474.51 27238.26 27561.50 29477.00 262
tfpn100059.24 26558.70 25860.86 29173.75 22533.99 32568.86 27163.98 29751.25 24057.29 27579.51 22734.58 25875.26 26729.08 33369.99 22173.32 301
pmmvs-eth3d58.81 26656.31 27666.30 23567.61 30952.42 14472.30 23264.76 28643.55 30654.94 29174.19 29428.95 30672.60 27643.31 24657.21 31573.88 299
RPMNet58.70 26756.29 27765.96 24469.96 29352.07 14765.31 29562.15 31043.20 30959.36 24770.15 31635.37 25070.75 28436.42 28964.65 27375.06 279
tpmvs58.47 26856.95 27163.03 27470.20 29041.21 27467.90 28267.23 27249.62 25154.73 29370.84 30934.14 26476.24 25736.64 28661.29 29771.64 318
PVSNet50.76 1958.40 26957.39 26761.42 28275.53 19544.04 25461.43 31063.45 30047.04 27656.91 27673.61 29727.00 31964.76 30839.12 27172.40 18575.47 276
tpmrst58.24 27058.70 25856.84 30666.97 31234.32 32369.57 26661.14 31447.17 27558.58 25971.60 30441.28 18960.41 32249.20 20362.84 28575.78 273
Patchmatch-RL test58.16 27155.49 28166.15 24067.92 30848.89 21060.66 31651.07 34847.86 26959.36 24762.71 34034.02 26672.27 27956.41 14759.40 31077.30 255
test-LLR58.15 27258.13 26458.22 29968.57 30344.80 24565.46 29257.92 32450.08 24855.44 28669.82 31732.62 28457.44 33149.66 19973.62 15872.41 311
ppachtmachnet_test58.06 27355.38 28266.10 24269.51 29748.99 20968.01 28166.13 27844.50 29754.05 30170.74 31032.09 29072.34 27836.68 28556.71 31876.99 264
gg-mvs-nofinetune57.86 27456.43 27562.18 27872.62 25835.35 31866.57 28456.33 33250.65 24357.64 27257.10 34730.65 29476.36 25537.38 27978.88 10974.82 285
CMPMVSbinary42.80 2157.81 27555.97 27863.32 27060.98 34147.38 22764.66 29969.50 25132.06 34646.83 32877.80 24929.50 30371.36 28148.68 20673.75 15671.21 321
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
MIMVSNet57.35 27657.07 26958.22 29974.21 21637.18 30262.46 30660.88 31548.88 25755.29 28975.99 28131.68 29162.04 31731.87 30372.35 18675.43 277
tpm57.34 27758.16 26254.86 31471.80 27234.77 32067.47 28356.04 33548.20 26560.10 23976.92 26637.17 22653.41 34840.76 26565.01 26876.40 268
Patchmtry57.16 27856.47 27459.23 29369.17 30034.58 32262.98 30463.15 30344.53 29656.83 27774.84 28835.83 24268.71 29240.03 26860.91 29874.39 290
AllTest57.08 27954.65 28664.39 26471.44 27449.03 20669.92 26467.30 27045.97 28447.16 32679.77 21517.47 34067.56 29633.65 29759.16 31176.57 266
our_test_356.49 28054.42 28862.68 27669.51 29745.48 24166.08 28861.49 31344.11 30350.73 31869.60 31933.05 27568.15 29438.38 27456.86 31674.40 289
pmmvs556.47 28155.68 28058.86 29661.41 33836.71 31066.37 28662.75 30640.38 32653.70 30376.62 27134.56 25967.05 29840.02 26965.27 26672.83 304
test-mter56.42 28255.82 27958.22 29968.57 30344.80 24565.46 29257.92 32439.94 32955.44 28669.82 31721.92 33757.44 33149.66 19973.62 15872.41 311
USDC56.35 28354.24 29162.69 27564.74 32640.31 27865.05 29773.83 22543.93 30447.58 32477.71 25215.36 34575.05 27038.19 27661.81 29172.70 305
PatchMatch-RL56.25 28454.55 28761.32 28477.06 17356.07 9665.57 29154.10 34444.13 30253.49 30871.27 30825.20 32866.78 30036.52 28863.66 27861.12 342
sss56.17 28556.57 27354.96 31366.93 31336.32 31457.94 32361.69 31241.67 31758.64 25875.32 28638.72 21056.25 34042.04 25766.19 26072.31 314
FMVSNet555.86 28654.93 28458.66 29871.05 28136.35 31264.18 30262.48 30846.76 27750.66 31974.73 29025.80 32564.04 31033.11 29965.57 26575.59 275
RPSCF55.80 28754.22 29260.53 29265.13 32542.91 26464.30 30057.62 32636.84 33858.05 26382.28 14828.01 31056.24 34137.14 28058.61 31382.44 185
EU-MVSNet55.61 28854.41 28959.19 29465.41 32433.42 33472.44 23071.91 23728.81 34951.27 31373.87 29524.76 33069.08 29143.04 25058.20 31475.06 279
TESTMET0.1,155.28 28954.90 28556.42 30766.56 31743.67 25765.46 29256.27 33339.18 33153.83 30267.44 32524.21 33255.46 34548.04 21073.11 17070.13 325
MIMVSNet155.17 29054.31 29057.77 30370.03 29232.01 33965.68 29064.81 28549.19 25446.75 32976.00 27925.53 32764.04 31028.65 33462.13 29077.26 258
Anonymous2023120655.10 29155.30 28354.48 31669.81 29633.94 32662.91 30562.13 31141.08 32055.18 29075.65 28332.75 28256.59 33730.32 31867.86 25072.91 303
TinyColmap54.14 29251.72 30061.40 28366.84 31441.97 26866.52 28568.51 26344.81 29242.69 34375.77 28211.66 35372.94 27531.96 30256.77 31769.27 329
EPMVS53.96 29353.69 29454.79 31566.12 32031.96 34062.34 30849.05 35144.42 29955.54 28471.33 30730.22 29756.70 33541.65 26162.54 28875.71 274
PMMVS53.96 29353.26 29756.04 30862.60 33450.92 15961.17 31456.09 33432.81 34453.51 30766.84 32734.04 26559.93 32444.14 24068.18 24757.27 348
test20.0353.87 29554.02 29353.41 32061.47 33728.11 34861.30 31259.21 31951.34 23752.09 31177.43 26233.29 27458.55 32829.76 32460.27 30873.58 300
MDA-MVSNet-bldmvs53.87 29550.81 30263.05 27366.25 31848.58 21356.93 32663.82 29848.09 26641.22 34470.48 31330.34 29668.00 29534.24 29545.92 34472.57 307
TDRefinement53.44 29750.72 30361.60 28164.31 32946.96 23070.89 25365.27 28441.78 31544.61 33577.98 24311.52 35466.36 30228.57 33551.59 33271.49 319
test0.0.03 153.32 29853.59 29552.50 32462.81 33329.45 34559.51 31854.11 34350.08 24854.40 29774.31 29332.62 28455.92 34230.50 31663.95 27772.15 317
PatchT53.17 29953.44 29652.33 32568.29 30725.34 35658.21 32254.41 34144.46 29854.56 29569.05 32033.32 27360.94 31936.93 28161.76 29270.73 324
UnsupCasMVSNet_eth53.16 30052.47 29855.23 31159.45 34833.39 33559.43 31969.13 25645.98 28350.35 32172.32 30129.30 30558.26 32942.02 25844.30 34674.05 297
PM-MVS52.33 30150.19 30458.75 29762.10 33545.14 24365.75 28940.38 36143.60 30553.52 30672.65 2999.16 35965.87 30650.41 19154.18 32665.24 335
testgi51.90 30252.37 29950.51 32960.39 34423.55 35958.42 32158.15 32249.03 25651.83 31279.21 23122.39 33555.59 34329.24 33262.64 28672.40 313
dp51.89 30351.60 30152.77 32368.44 30632.45 33762.36 30754.57 34044.16 30149.31 32267.91 32228.87 30856.61 33633.89 29654.89 32369.24 330
JIA-IIPM51.56 30447.68 31263.21 27164.61 32750.73 16647.71 34658.77 32142.90 31148.46 32351.72 35124.97 32970.24 28736.06 29153.89 32768.64 331
ADS-MVSNet251.33 30548.76 30859.07 29566.02 32244.60 24850.90 34159.76 31836.90 33650.74 31666.18 33126.38 32163.11 31227.17 33654.76 32469.50 327
YYNet150.73 30648.96 30556.03 30961.10 34041.78 27051.94 33956.44 33140.94 32244.84 33367.80 32430.08 29955.08 34636.77 28250.71 33471.22 320
MDA-MVSNet_test_wron50.71 30748.95 30656.00 31061.17 33941.84 26951.90 34056.45 33040.96 32144.79 33467.84 32330.04 30055.07 34736.71 28450.69 33571.11 323
UnsupCasMVSNet_bld50.07 30848.87 30753.66 31860.97 34233.67 33357.62 32464.56 28839.47 33047.38 32564.02 33627.47 31459.32 32534.69 29443.68 34767.98 332
Patchmatch-test49.08 30948.28 30951.50 32764.40 32830.85 34345.68 34948.46 35435.60 34046.10 33272.10 30234.47 26246.37 35427.08 33860.65 30277.27 257
LP48.51 31045.51 31657.52 30562.86 33244.53 25152.38 33859.84 31738.11 33342.81 34261.02 34123.23 33363.02 31324.10 34345.24 34565.02 336
ADS-MVSNet48.48 31147.77 31050.63 32866.02 32229.92 34450.90 34150.87 35036.90 33650.74 31666.18 33126.38 32152.47 35027.17 33654.76 32469.50 327
CHOSEN 280x42047.83 31246.36 31352.24 32667.37 31149.78 19638.91 35743.11 36035.00 34143.27 34163.30 33928.95 30649.19 35336.53 28760.80 30157.76 347
new-patchmatchnet47.56 31347.73 31147.06 33458.81 3499.37 36748.78 34559.21 31943.28 30744.22 33668.66 32125.67 32657.20 33431.57 31149.35 34074.62 288
PVSNet_043.31 2047.46 31445.64 31552.92 32267.60 31044.65 24754.06 33254.64 33941.59 31846.15 33058.75 34630.99 29258.66 32732.18 30124.81 35555.46 349
test123567845.66 31544.46 32149.26 33059.88 34628.68 34756.36 32855.54 33839.12 33240.89 34663.40 33814.41 34757.32 33321.05 34949.47 33961.78 340
test235645.61 31644.66 31948.47 33360.15 34528.08 34952.44 33752.83 34738.01 33446.13 33160.98 34215.08 34655.54 34420.43 35255.85 32161.78 340
MVS-HIRNet45.52 31744.48 32048.65 33268.49 30534.05 32459.41 32044.50 35927.03 35137.96 35050.47 35426.16 32464.10 30926.74 33959.52 30947.82 352
pmmvs344.92 31841.95 32453.86 31752.58 35543.55 25862.11 30946.90 35826.05 35340.63 34760.19 34411.08 35657.91 33031.83 30846.15 34360.11 344
testus44.59 31943.87 32246.76 33559.85 34724.65 35753.86 33355.82 33636.26 33943.97 33963.42 3378.39 36053.14 34920.70 35152.52 33062.51 338
111144.40 32045.00 31842.61 34157.55 35117.33 36453.82 33557.05 32840.78 32344.11 33766.57 32813.37 34845.77 35522.15 34549.58 33864.73 337
testpf44.11 32145.40 31740.26 34360.52 34327.34 35033.26 35954.33 34245.87 28741.08 34560.26 34316.46 34259.14 32646.09 22250.68 33634.31 358
LF4IMVS42.95 32242.26 32345.04 33748.30 35932.50 33654.80 33048.49 35328.03 35040.51 34870.16 3159.24 35843.89 35831.63 30949.18 34158.72 345
testmv42.25 32340.11 32748.66 33153.23 35327.02 35156.62 32755.74 33737.25 33533.10 35259.52 3457.78 36156.58 33819.61 35338.13 35162.40 339
FPMVS42.18 32441.11 32545.39 33658.03 35041.01 27649.50 34353.81 34530.07 34833.71 35164.03 33411.69 35252.08 35114.01 35855.11 32243.09 355
ANet_high41.38 32537.47 33053.11 32139.73 36524.45 35856.94 32569.69 24747.65 27026.04 35652.32 35012.44 35062.38 31621.80 34810.61 36372.49 308
no-one40.85 32636.09 33155.14 31248.55 35838.72 29042.15 35562.92 30534.60 34323.55 35749.74 35512.21 35166.16 30426.27 34124.84 35460.54 343
LCM-MVSNet40.30 32735.88 33353.57 31942.24 36229.15 34645.21 35160.53 31622.23 35728.02 35550.98 3533.72 36761.78 31831.22 31538.76 35069.78 326
N_pmnet39.35 32840.28 32636.54 34563.76 3301.62 37149.37 3440.76 37334.62 34243.61 34066.38 33026.25 32342.57 36026.02 34251.77 33165.44 334
DSMNet-mixed39.30 32938.72 32941.03 34251.22 35619.66 36145.53 35031.35 36615.83 36139.80 34967.42 32622.19 33645.13 35722.43 34452.69 32958.31 346
PMVScopyleft28.69 2236.22 33033.29 33545.02 33836.82 36735.98 31654.68 33148.74 35226.31 35221.02 35851.61 3522.88 36960.10 3239.99 36247.58 34238.99 357
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
test1235636.16 33135.94 33236.83 34450.82 3578.52 36844.84 35253.49 34632.72 34530.11 35455.08 3487.11 36349.47 35216.60 35532.68 35352.50 350
.test124534.88 33239.49 32821.04 35357.55 35117.33 36453.82 33557.05 32840.78 32344.11 33766.57 32813.37 34845.77 35522.15 3450.00 3660.03 367
Gipumacopyleft34.77 33331.91 33643.33 34062.05 33637.87 29820.39 36267.03 27323.23 35518.41 36025.84 3604.24 36562.73 31414.71 35751.32 33329.38 360
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
v1.034.38 33445.84 3140.00 35987.58 30.00 3730.00 36586.64 363.49 3683.42 291.40 50.00 3750.00 3690.00 3680.00 3660.00 369
new_pmnet34.13 33534.29 33433.64 34652.63 35418.23 36344.43 35333.90 36422.81 35630.89 35353.18 34910.48 35735.72 36420.77 35039.51 34846.98 353
pcd1.5k->3k30.06 33630.56 33728.55 35078.81 1220.00 3730.00 36582.07 760.00 3690.00 3710.00 37139.61 2000.00 3690.00 36874.56 14785.66 80
wuykxyi23d28.12 33722.54 34244.87 33934.97 36832.11 33837.96 35847.31 35613.32 3629.29 36723.72 3620.45 37256.58 33821.85 34713.98 35945.93 354
PNet_i23d27.88 33825.99 33833.55 34747.54 36025.89 35347.24 34832.91 36521.44 35815.90 36138.09 3570.85 37142.76 35916.90 35413.03 36132.00 359
PMMVS227.40 33925.91 33931.87 34939.46 3666.57 36931.17 36028.52 36723.96 35420.45 35948.94 3564.20 36637.94 36316.51 35619.97 35651.09 351
E-PMN23.77 34022.73 34126.90 35142.02 36320.67 36042.66 35435.70 36217.43 35910.28 36525.05 3616.42 36442.39 36110.28 36114.71 35817.63 361
EMVS22.97 34121.84 34326.36 35240.20 36419.53 36241.95 35634.64 36317.09 3609.73 36622.83 3637.29 36242.22 3629.18 36313.66 36017.32 362
MVEpermissive17.77 2321.41 34217.77 34432.34 34834.34 36925.44 35516.11 36324.11 36811.19 36313.22 36331.92 3581.58 37030.95 36510.47 36017.03 35740.62 356
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
cdsmvs_eth3d_5k17.50 34323.34 3400.00 3590.00 3740.00 3730.00 36578.63 1620.00 3690.00 37182.18 14949.25 930.00 3690.00 3680.00 3660.00 369
wuyk23d13.32 34412.52 34515.71 35447.54 36026.27 35231.06 3611.98 3724.93 3655.18 3681.94 3680.45 37218.54 3666.81 36512.83 3622.33 365
tmp_tt9.43 34511.14 3464.30 3562.38 3714.40 37013.62 36416.08 3700.39 36615.89 36213.06 36415.80 3445.54 36812.63 35910.46 3642.95 364
ab-mvs-re6.49 3468.65 3470.00 3590.00 3740.00 3730.00 3650.00 3740.00 3690.00 37177.89 2470.00 3750.00 3690.00 3680.00 3660.00 369
test1234.73 3476.30 3480.02 3570.01 3720.01 37256.36 3280.00 3740.01 3670.04 3690.21 3700.01 3740.00 3690.03 3670.00 3660.04 366
testmvs4.52 3486.03 3490.01 3580.01 3720.00 37353.86 3330.00 3740.01 3670.04 3690.27 3690.00 3750.00 3690.04 3660.00 3660.03 367
pcd_1.5k_mvsjas3.92 3495.23 3500.00 3590.00 3740.00 3730.00 3650.00 3740.00 3690.00 3710.00 37147.05 1260.00 3690.00 3680.00 3660.00 369
sosnet-low-res0.00 3500.00 3510.00 3590.00 3740.00 3730.00 3650.00 3740.00 3690.00 3710.00 3710.00 3750.00 3690.00 3680.00 3660.00 369
sosnet0.00 3500.00 3510.00 3590.00 3740.00 3730.00 3650.00 3740.00 3690.00 3710.00 3710.00 3750.00 3690.00 3680.00 3660.00 369
uncertanet0.00 3500.00 3510.00 3590.00 3740.00 3730.00 3650.00 3740.00 3690.00 3710.00 3710.00 3750.00 3690.00 3680.00 3660.00 369
Regformer0.00 3500.00 3510.00 3590.00 3740.00 3730.00 3650.00 3740.00 3690.00 3710.00 3710.00 3750.00 3690.00 3680.00 3660.00 369
uanet0.00 3500.00 3510.00 3590.00 3740.00 3730.00 3650.00 3740.00 3690.00 3710.00 3710.00 3750.00 3690.00 3680.00 3660.00 369
GSMVS78.05 248
test_part287.58 360.47 4083.42 2
test_part10.00 3590.00 3730.00 36586.64 30.00 3750.00 3690.00 3680.00 3660.00 369
sam_mvs134.74 25778.05 248
sam_mvs33.43 272
semantic-postprocess65.40 25671.99 26850.80 16469.63 24945.71 28860.61 23577.93 24536.56 23965.99 30555.67 15563.50 28079.42 236
ambc65.13 25963.72 33137.07 30347.66 34778.78 15954.37 29871.42 30611.24 35580.94 18645.64 22853.85 32877.38 254
MTGPAbinary80.97 105
test_post168.67 2723.64 36632.39 28869.49 28944.17 239
test_post3.55 36733.90 26766.52 301
patchmatchnet-post64.03 33434.50 26074.27 273
GG-mvs-BLEND62.34 27771.36 27837.04 30469.20 26957.33 32754.73 29365.48 33330.37 29577.82 23934.82 29374.93 14672.17 316
MTMP86.03 1017.08 369
gm-plane-assit71.40 27741.72 27248.85 25873.31 29882.48 16248.90 205
test9_res75.28 1688.31 1983.81 151
TEST985.58 3261.59 2781.62 6981.26 9555.65 17974.93 2788.81 4353.70 4484.68 103
test_885.40 3560.96 3481.54 7281.18 9855.86 17374.81 3088.80 4553.70 4484.45 108
agg_prior273.09 3287.93 2684.33 128
agg_prior85.04 3959.96 4481.04 10174.68 3184.04 115
TestCases64.39 26471.44 27449.03 20667.30 27045.97 28447.16 32679.77 21517.47 34067.56 29633.65 29759.16 31176.57 266
test_prior462.51 1782.08 63
test_prior281.75 6560.37 8375.01 2589.06 3756.22 2172.19 3588.96 10
test_prior76.69 4884.20 5157.27 7584.88 1986.43 5886.38 51
旧先验276.08 17045.32 28976.55 1765.56 30758.75 139
新几何276.12 168
新几何170.76 18785.66 2961.13 3266.43 27744.68 29470.29 7886.64 6641.29 18875.23 26849.72 19881.75 7075.93 271
旧先验183.04 5853.15 13167.52 26987.85 5244.08 15880.76 7678.03 250
无先验79.66 9674.30 22048.40 26380.78 19153.62 17079.03 241
原ACMM279.02 102
原ACMM174.69 7885.39 3659.40 4983.42 5251.47 23570.27 8086.61 6848.61 10886.51 5653.85 16987.96 2578.16 246
test22283.14 5758.68 6072.57 22863.45 30041.78 31567.56 13886.12 7937.13 22778.73 11474.98 282
testdata272.18 28046.95 217
segment_acmp54.23 37
testdata64.66 26281.52 7252.93 13465.29 28346.09 28273.88 4287.46 5438.08 21866.26 30353.31 17578.48 11774.78 286
testdata172.65 22360.50 80
test1277.76 3684.52 4858.41 6283.36 5572.93 5754.61 3488.05 2488.12 2286.81 43
plane_prior781.41 7555.96 98
plane_prior681.20 8256.24 9245.26 148
plane_prior584.01 3487.21 3668.16 5480.58 7984.65 122
plane_prior486.10 80
plane_prior356.09 9563.92 3069.27 106
plane_prior284.22 2664.52 24
plane_prior181.27 80
plane_prior56.31 8883.58 3563.19 4080.48 82
n20.00 374
nn0.00 374
door-mid47.19 357
lessismore_v069.91 19871.42 27647.80 22150.90 34950.39 32075.56 28427.43 31681.33 18045.91 22534.10 35280.59 220
LGP-MVS_train75.76 6080.22 9757.51 7383.40 5361.32 6866.67 14887.33 5639.15 20686.59 5167.70 5977.30 12983.19 169
test1183.47 50
door47.60 355
HQP5-MVS54.94 112
HQP-NCC80.66 8782.31 5862.10 5867.85 129
ACMP_Plane80.66 8782.31 5862.10 5867.85 129
BP-MVS67.04 65
HQP4-MVS67.85 12986.93 4284.32 129
HQP3-MVS83.90 3880.35 85
HQP2-MVS45.46 142
NP-MVS80.98 8556.05 9785.54 93
MDTV_nov1_ep13_2view25.89 35361.22 31340.10 32751.10 31432.97 27738.49 27378.61 243
MDTV_nov1_ep1357.00 27072.73 25638.26 29665.02 29864.73 28744.74 29355.46 28572.48 30032.61 28670.47 28637.47 27867.75 252
ACMMP++_ref74.07 154
ACMMP++72.16 189
Test By Simon48.33 111
ITE_SJBPF62.09 27966.16 31944.55 25064.32 28947.36 27355.31 28880.34 20319.27 33962.68 31536.29 29062.39 28979.04 240
DeepMVS_CXcopyleft12.03 35517.97 37010.91 36610.60 3717.46 36411.07 36428.36 3593.28 36811.29 3678.01 3649.74 36513.89 363