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
DVP-MVS++90.23 191.01 187.89 2294.34 2771.25 5595.06 194.23 378.38 3192.78 495.74 682.45 397.49 389.42 496.68 294.95 8
SED-MVS90.08 290.85 287.77 2495.30 270.98 6193.57 794.06 1077.24 4893.10 195.72 882.99 197.44 589.07 996.63 494.88 12
DVP-MVScopyleft89.60 390.35 387.33 3895.27 571.25 5593.49 992.73 5977.33 4692.12 995.78 480.98 997.40 789.08 796.41 1293.33 76
Zhenlong Yuan, Jinguo Luo, Fei Shen, Zhaoxin Li, Cong Liu, Tianlu Mao, Zhaoqi Wang: DVP-MVS: Synergize Depth-Edge and Visibility Prior for Multi-View Stereo. AAAI2025
MSP-MVS89.51 489.91 588.30 994.28 3073.46 1692.90 1694.11 680.27 891.35 1494.16 3478.35 1396.77 2289.59 394.22 5694.67 22
Zhenlong Yuan, Cong Liu, Fei Shen, Zhaoxin Li, Jingguo luo, Tianlu Mao and Zhaoqi Wang: MSP-MVS: Multi-granularity Segmentation Prior Guided Multi-View Stereo. AAAI2025
DPE-MVScopyleft89.48 589.98 488.01 1494.80 1172.69 3091.59 4194.10 875.90 8392.29 795.66 1081.67 697.38 987.44 2096.34 1593.95 49
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
APDe-MVS89.15 689.63 687.73 2694.49 1871.69 5093.83 493.96 1375.70 8791.06 1696.03 176.84 1497.03 1589.09 695.65 2794.47 29
SMA-MVScopyleft89.08 789.23 788.61 594.25 3173.73 992.40 2393.63 2174.77 10392.29 795.97 274.28 2997.24 1188.58 1396.91 194.87 14
Yufeng Yin; Xiaoyan Liu; Zichao Zhang: SMA-MVS: Segmentation-Guided Multi-Scale Anchor Deformation Patch Multi-View Stereo. IEEE Transactions on Circuits and Systems for Video Technology
HPM-MVS++copyleft89.02 889.15 888.63 495.01 976.03 192.38 2692.85 5480.26 987.78 2794.27 3075.89 1996.81 2187.45 1996.44 993.05 86
CNVR-MVS88.93 989.13 988.33 794.77 1273.82 890.51 5993.00 4380.90 588.06 2594.06 3876.43 1696.84 1988.48 1495.99 1894.34 35
SteuartSystems-ACMMP88.72 1088.86 1088.32 892.14 6972.96 2493.73 593.67 2080.19 1088.10 2494.80 1573.76 3397.11 1387.51 1895.82 2194.90 11
Skip Steuart: Steuart Systems R&D Blog.
SF-MVS88.46 1188.74 1187.64 3392.78 6171.95 4892.40 2394.74 275.71 8589.16 1995.10 1375.65 2196.19 4187.07 2196.01 1794.79 19
DeepPCF-MVS80.84 188.10 1288.56 1286.73 4892.24 6869.03 9389.57 8393.39 3077.53 4389.79 1894.12 3578.98 1296.58 3385.66 2495.72 2494.58 25
SD-MVS88.06 1388.50 1386.71 4992.60 6672.71 2891.81 4093.19 3577.87 3490.32 1794.00 4074.83 2393.78 13487.63 1794.27 5593.65 63
Zhenlong Yuan, Jiakai Cao, Zhaoxin Li, Hao Jiang and Zhaoqi Wang: SD-MVS: Segmentation-driven Deformation Multi-View Stereo with Spherical Refinement and EM optimization. AAAI2024
NCCC88.06 1388.01 1788.24 1094.41 2273.62 1091.22 5092.83 5581.50 385.79 3793.47 4973.02 3997.00 1684.90 2994.94 3794.10 43
ACMMP_NAP88.05 1588.08 1687.94 1793.70 4173.05 2190.86 5493.59 2376.27 7788.14 2395.09 1471.06 5296.67 2787.67 1696.37 1494.09 44
TSAR-MVS + MP.88.02 1688.11 1587.72 2893.68 4372.13 4591.41 4592.35 7474.62 10788.90 2093.85 4475.75 2096.00 4787.80 1594.63 4595.04 6
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
ZNCC-MVS87.94 1787.85 1888.20 1194.39 2473.33 1893.03 1493.81 1776.81 6185.24 4294.32 2971.76 4696.93 1785.53 2695.79 2294.32 36
MP-MVScopyleft87.71 1887.64 2087.93 1994.36 2673.88 692.71 2292.65 6477.57 3983.84 6994.40 2872.24 4296.28 3885.65 2595.30 3393.62 66
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
MP-MVS-pluss87.67 1987.72 1987.54 3493.64 4472.04 4789.80 7793.50 2575.17 9686.34 3395.29 1270.86 5396.00 4788.78 1296.04 1694.58 25
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
HFP-MVS87.58 2087.47 2287.94 1794.58 1673.54 1493.04 1293.24 3376.78 6384.91 4794.44 2670.78 5496.61 3084.53 3694.89 3993.66 59
ACMMPR87.44 2187.23 2588.08 1394.64 1373.59 1193.04 1293.20 3476.78 6384.66 5494.52 1968.81 7596.65 2884.53 3694.90 3894.00 48
APD-MVScopyleft87.44 2187.52 2187.19 4094.24 3272.39 3891.86 3992.83 5573.01 14288.58 2194.52 1973.36 3496.49 3484.26 3995.01 3592.70 95
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
GST-MVS87.42 2387.26 2387.89 2294.12 3672.97 2392.39 2593.43 2876.89 5984.68 5193.99 4270.67 5696.82 2084.18 4395.01 3593.90 51
region2R87.42 2387.20 2688.09 1294.63 1473.55 1293.03 1493.12 3776.73 6684.45 5894.52 1969.09 7196.70 2584.37 3894.83 4294.03 47
MCST-MVS87.37 2587.25 2487.73 2694.53 1772.46 3789.82 7593.82 1673.07 14084.86 5092.89 6176.22 1796.33 3684.89 3195.13 3494.40 32
MTAPA87.23 2687.00 2787.90 2094.18 3574.25 586.58 17492.02 8579.45 1785.88 3594.80 1568.07 7796.21 4086.69 2395.34 3193.23 79
XVS87.18 2786.91 3188.00 1594.42 2073.33 1892.78 1892.99 4579.14 1983.67 7294.17 3367.45 8396.60 3183.06 5094.50 4894.07 45
HPM-MVScopyleft87.11 2886.98 2887.50 3693.88 3972.16 4492.19 3293.33 3176.07 8083.81 7093.95 4369.77 6596.01 4685.15 2794.66 4494.32 36
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
CP-MVS87.11 2886.92 3087.68 3294.20 3473.86 793.98 392.82 5876.62 6883.68 7194.46 2367.93 7895.95 5084.20 4294.39 5193.23 79
DeepC-MVS79.81 287.08 3086.88 3287.69 3191.16 8072.32 4290.31 6693.94 1477.12 5382.82 8394.23 3272.13 4497.09 1484.83 3295.37 3093.65 63
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
DeepC-MVS_fast79.65 386.91 3186.62 3487.76 2593.52 4672.37 4091.26 4693.04 3876.62 6884.22 6293.36 5171.44 5096.76 2380.82 7295.33 3294.16 41
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
SR-MVS86.73 3286.67 3386.91 4494.11 3772.11 4692.37 2792.56 6774.50 10886.84 3194.65 1867.31 8595.77 5284.80 3392.85 6592.84 93
CS-MVS86.69 3386.95 2985.90 6190.76 9067.57 12992.83 1793.30 3279.67 1584.57 5792.27 7371.47 4995.02 8484.24 4193.46 6195.13 5
PGM-MVS86.68 3486.27 3887.90 2094.22 3373.38 1790.22 6893.04 3875.53 8983.86 6894.42 2767.87 8096.64 2982.70 5994.57 4793.66 59
mPP-MVS86.67 3586.32 3787.72 2894.41 2273.55 1292.74 2092.22 8076.87 6082.81 8494.25 3166.44 9296.24 3982.88 5494.28 5493.38 73
CANet86.45 3686.10 4387.51 3590.09 10170.94 6589.70 8192.59 6681.78 281.32 9891.43 9370.34 5897.23 1284.26 3993.36 6294.37 33
train_agg86.43 3786.20 3987.13 4293.26 5072.96 2488.75 10691.89 9368.69 21885.00 4593.10 5474.43 2695.41 6584.97 2895.71 2593.02 88
PHI-MVS86.43 3786.17 4187.24 3990.88 8770.96 6392.27 3194.07 972.45 14585.22 4391.90 7969.47 6796.42 3583.28 4995.94 1994.35 34
CSCG86.41 3986.19 4087.07 4392.91 5872.48 3690.81 5593.56 2473.95 11983.16 7891.07 10375.94 1895.19 7379.94 8194.38 5293.55 69
CS-MVS-test86.29 4086.48 3585.71 6391.02 8367.21 13992.36 2893.78 1878.97 2683.51 7591.20 9870.65 5795.15 7581.96 6394.89 3994.77 20
DROMVSNet86.01 4186.38 3684.91 8289.31 12966.27 15392.32 2993.63 2179.37 1884.17 6491.88 8069.04 7495.43 6383.93 4493.77 5993.01 89
casdiffmvs_mvgpermissive85.99 4286.09 4485.70 6487.65 18967.22 13888.69 11093.04 3879.64 1685.33 4192.54 7073.30 3594.50 10583.49 4691.14 8795.37 1
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
APD-MVS_3200maxsize85.97 4385.88 4586.22 5592.69 6369.53 8691.93 3692.99 4573.54 13185.94 3494.51 2265.80 10295.61 5583.04 5292.51 6993.53 71
canonicalmvs85.91 4485.87 4686.04 5889.84 11169.44 9190.45 6493.00 4376.70 6788.01 2691.23 9673.28 3693.91 12981.50 6688.80 11194.77 20
ACMMPcopyleft85.89 4585.39 5087.38 3793.59 4572.63 3292.74 2093.18 3676.78 6380.73 10793.82 4564.33 11296.29 3782.67 6090.69 9193.23 79
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
SR-MVS-dyc-post85.77 4685.61 4886.23 5493.06 5570.63 7191.88 3792.27 7673.53 13285.69 3894.45 2465.00 11095.56 5682.75 5591.87 7792.50 103
CDPH-MVS85.76 4785.29 5487.17 4193.49 4771.08 5988.58 11392.42 7268.32 22484.61 5593.48 4772.32 4196.15 4379.00 8595.43 2994.28 38
TSAR-MVS + GP.85.71 4885.33 5186.84 4591.34 7872.50 3589.07 9587.28 22076.41 7085.80 3690.22 12174.15 3195.37 7081.82 6491.88 7692.65 99
dcpmvs_285.63 4986.15 4284.06 11391.71 7564.94 18486.47 17791.87 9573.63 12786.60 3293.02 5976.57 1591.87 21183.36 4792.15 7395.35 2
alignmvs85.48 5085.32 5285.96 6089.51 11869.47 8889.74 7992.47 6876.17 7887.73 2991.46 9270.32 5993.78 13481.51 6588.95 10894.63 24
3Dnovator+77.84 485.48 5084.47 6288.51 691.08 8173.49 1593.18 1193.78 1880.79 676.66 18193.37 5060.40 17496.75 2477.20 10493.73 6095.29 4
MSLP-MVS++85.43 5285.76 4784.45 9691.93 7270.24 7490.71 5692.86 5377.46 4584.22 6292.81 6567.16 8792.94 17580.36 7794.35 5390.16 178
DELS-MVS85.41 5385.30 5385.77 6288.49 15867.93 12185.52 20693.44 2778.70 2783.63 7489.03 14974.57 2495.71 5480.26 7994.04 5793.66 59
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
HPM-MVS_fast85.35 5484.95 5886.57 5193.69 4270.58 7392.15 3491.62 10373.89 12282.67 8694.09 3662.60 13195.54 5880.93 7092.93 6493.57 68
MVS_111021_HR85.14 5584.75 5986.32 5391.65 7672.70 2985.98 18990.33 13876.11 7982.08 8991.61 8771.36 5194.17 11881.02 6992.58 6892.08 118
casdiffmvspermissive85.11 5685.14 5585.01 7687.20 20465.77 16687.75 14092.83 5577.84 3584.36 6192.38 7272.15 4393.93 12881.27 6890.48 9295.33 3
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
UA-Net85.08 5784.96 5785.45 6692.07 7068.07 11989.78 7890.86 12582.48 184.60 5693.20 5369.35 6895.22 7271.39 15990.88 9093.07 85
DPM-MVS84.93 5884.29 6386.84 4590.20 9973.04 2287.12 15693.04 3869.80 19182.85 8291.22 9773.06 3896.02 4576.72 11294.63 4591.46 135
baseline84.93 5884.98 5684.80 8687.30 20265.39 17587.30 15292.88 5277.62 3784.04 6792.26 7471.81 4593.96 12281.31 6790.30 9495.03 7
ETV-MVS84.90 6084.67 6085.59 6589.39 12368.66 10888.74 10892.64 6579.97 1384.10 6585.71 23969.32 6995.38 6780.82 7291.37 8492.72 94
EI-MVSNet-Vis-set84.19 6183.81 6485.31 6888.18 16867.85 12287.66 14289.73 15580.05 1282.95 7989.59 13370.74 5594.82 9380.66 7684.72 15993.28 78
nrg03083.88 6283.53 6584.96 7886.77 21269.28 9290.46 6392.67 6174.79 10282.95 7991.33 9572.70 4093.09 16980.79 7479.28 23092.50 103
EI-MVSNet-UG-set83.81 6383.38 6785.09 7487.87 17867.53 13087.44 14889.66 15679.74 1482.23 8889.41 14270.24 6094.74 9679.95 8083.92 16992.99 90
CPTT-MVS83.73 6483.33 6884.92 8193.28 4970.86 6792.09 3590.38 13468.75 21779.57 11892.83 6360.60 17093.04 17380.92 7191.56 8290.86 154
EPNet83.72 6582.92 7486.14 5784.22 24669.48 8791.05 5385.27 24681.30 476.83 17691.65 8466.09 9795.56 5676.00 11793.85 5893.38 73
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
patch_mono-283.65 6684.54 6180.99 20790.06 10665.83 16284.21 23488.74 19171.60 16085.01 4492.44 7174.51 2583.50 31282.15 6292.15 7393.64 65
HQP_MVS83.64 6783.14 6985.14 7290.08 10268.71 10491.25 4892.44 6979.12 2178.92 12791.00 10760.42 17295.38 6778.71 8986.32 14291.33 136
Effi-MVS+83.62 6883.08 7085.24 7088.38 16367.45 13188.89 10089.15 17275.50 9082.27 8788.28 17169.61 6694.45 10777.81 9887.84 12193.84 54
OPM-MVS83.50 6982.95 7385.14 7288.79 14870.95 6489.13 9491.52 10677.55 4280.96 10591.75 8260.71 16694.50 10579.67 8286.51 14089.97 194
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
Vis-MVSNetpermissive83.46 7082.80 7685.43 6790.25 9868.74 10290.30 6790.13 14476.33 7680.87 10692.89 6161.00 16394.20 11672.45 15390.97 8893.35 75
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
MG-MVS83.41 7183.45 6683.28 13992.74 6262.28 23488.17 12689.50 15975.22 9481.49 9792.74 6966.75 8895.11 7872.85 14791.58 8192.45 106
EPP-MVSNet83.40 7283.02 7284.57 9090.13 10064.47 19392.32 2990.73 12674.45 11179.35 12191.10 10169.05 7395.12 7672.78 14887.22 12994.13 42
3Dnovator76.31 583.38 7382.31 8286.59 5087.94 17772.94 2790.64 5792.14 8477.21 5075.47 20492.83 6358.56 18194.72 9773.24 14492.71 6792.13 117
EIA-MVS83.31 7482.80 7684.82 8489.59 11465.59 16888.21 12492.68 6074.66 10578.96 12586.42 22669.06 7295.26 7175.54 12390.09 9893.62 66
h-mvs3383.15 7582.19 8386.02 5990.56 9270.85 6888.15 12889.16 17176.02 8184.67 5291.39 9461.54 14995.50 5982.71 5775.48 27391.72 126
MVS_Test83.15 7583.06 7183.41 13686.86 20863.21 22086.11 18792.00 8774.31 11282.87 8189.44 14170.03 6193.21 15877.39 10388.50 11793.81 55
IS-MVSNet83.15 7582.81 7584.18 10689.94 10963.30 21891.59 4188.46 19779.04 2379.49 11992.16 7565.10 10794.28 11067.71 19491.86 7994.95 8
DP-MVS Recon83.11 7882.09 8586.15 5694.44 1970.92 6688.79 10492.20 8170.53 17979.17 12391.03 10664.12 11496.03 4468.39 19190.14 9791.50 132
PAPM_NR83.02 7982.41 7984.82 8492.47 6766.37 15187.93 13591.80 9873.82 12377.32 16590.66 11267.90 7994.90 8970.37 16889.48 10593.19 82
VDD-MVS83.01 8082.36 8184.96 7891.02 8366.40 15088.91 9988.11 20077.57 3984.39 6093.29 5252.19 23093.91 12977.05 10688.70 11394.57 27
MVSFormer82.85 8182.05 8685.24 7087.35 19770.21 7590.50 6090.38 13468.55 22081.32 9889.47 13661.68 14693.46 15178.98 8690.26 9592.05 119
OMC-MVS82.69 8281.97 8984.85 8388.75 15067.42 13287.98 13190.87 12474.92 9979.72 11691.65 8462.19 14193.96 12275.26 12586.42 14193.16 83
PVSNet_Blended_VisFu82.62 8381.83 9184.96 7890.80 8969.76 8488.74 10891.70 10269.39 19878.96 12588.46 16665.47 10494.87 9274.42 13088.57 11490.24 176
MVS_111021_LR82.61 8482.11 8484.11 10788.82 14571.58 5185.15 20986.16 23774.69 10480.47 10991.04 10462.29 13890.55 24380.33 7890.08 9990.20 177
HQP-MVS82.61 8482.02 8784.37 9889.33 12666.98 14289.17 8992.19 8276.41 7077.23 16890.23 12060.17 17595.11 7877.47 10185.99 14991.03 148
CLD-MVS82.31 8681.65 9284.29 10388.47 15967.73 12585.81 19792.35 7475.78 8478.33 14286.58 22164.01 11594.35 10876.05 11687.48 12690.79 155
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
VNet82.21 8782.41 7981.62 18790.82 8860.93 24884.47 22589.78 15276.36 7584.07 6691.88 8064.71 11190.26 24570.68 16588.89 10993.66 59
diffmvspermissive82.10 8881.88 9082.76 16983.00 27363.78 20683.68 24289.76 15372.94 14382.02 9089.85 12565.96 10190.79 23982.38 6187.30 12893.71 58
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
LPG-MVS_test82.08 8981.27 9584.50 9389.23 13368.76 10090.22 6891.94 9175.37 9276.64 18291.51 8954.29 21394.91 8678.44 9183.78 17089.83 199
FIs82.07 9082.42 7881.04 20688.80 14758.34 27288.26 12393.49 2676.93 5878.47 13991.04 10469.92 6392.34 19469.87 17584.97 15692.44 107
PS-MVSNAJss82.07 9081.31 9484.34 10186.51 21567.27 13689.27 8791.51 10771.75 15479.37 12090.22 12163.15 12594.27 11177.69 9982.36 19291.49 133
API-MVS81.99 9281.23 9684.26 10490.94 8570.18 8091.10 5189.32 16371.51 16278.66 13388.28 17165.26 10595.10 8164.74 22191.23 8687.51 257
UniMVSNet_NR-MVSNet81.88 9381.54 9382.92 15888.46 16063.46 21487.13 15592.37 7380.19 1078.38 14089.14 14571.66 4893.05 17170.05 17176.46 25892.25 112
MAR-MVS81.84 9480.70 10585.27 6991.32 7971.53 5289.82 7590.92 12169.77 19278.50 13786.21 23062.36 13794.52 10465.36 21592.05 7589.77 202
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
LFMVS81.82 9581.23 9683.57 13191.89 7363.43 21689.84 7481.85 29277.04 5683.21 7693.10 5452.26 22993.43 15371.98 15489.95 10193.85 52
hse-mvs281.72 9680.94 10284.07 11288.72 15167.68 12785.87 19387.26 22176.02 8184.67 5288.22 17461.54 14993.48 14982.71 5773.44 30091.06 146
GeoE81.71 9781.01 10183.80 12689.51 11864.45 19488.97 9788.73 19271.27 16578.63 13489.76 12766.32 9493.20 16169.89 17486.02 14893.74 57
xiu_mvs_v2_base81.69 9881.05 9983.60 12989.15 13668.03 12084.46 22790.02 14670.67 17681.30 10186.53 22463.17 12494.19 11775.60 12288.54 11588.57 239
PS-MVSNAJ81.69 9881.02 10083.70 12889.51 11868.21 11784.28 23390.09 14570.79 17381.26 10285.62 24363.15 12594.29 10975.62 12188.87 11088.59 238
mvsmamba81.69 9880.74 10484.56 9187.45 19666.72 14691.26 4685.89 24174.66 10578.23 14590.56 11454.33 21294.91 8680.73 7583.54 17792.04 121
PAPR81.66 10180.89 10383.99 12090.27 9764.00 20186.76 17091.77 10168.84 21677.13 17489.50 13467.63 8194.88 9167.55 19688.52 11693.09 84
UniMVSNet (Re)81.60 10281.11 9883.09 14988.38 16364.41 19587.60 14393.02 4278.42 3078.56 13688.16 17569.78 6493.26 15769.58 17876.49 25791.60 127
FC-MVSNet-test81.52 10382.02 8780.03 22688.42 16255.97 30987.95 13393.42 2977.10 5477.38 16390.98 10969.96 6291.79 21268.46 19084.50 16192.33 108
VDDNet81.52 10380.67 10684.05 11590.44 9564.13 20089.73 8085.91 24071.11 16883.18 7793.48 4750.54 25393.49 14873.40 14188.25 11994.54 28
ACMP74.13 681.51 10580.57 10784.36 9989.42 12168.69 10789.97 7291.50 11074.46 11075.04 22390.41 11753.82 21894.54 10277.56 10082.91 18489.86 198
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
jason81.39 10680.29 11484.70 8886.63 21469.90 8285.95 19086.77 22863.24 27581.07 10489.47 13661.08 16292.15 20078.33 9490.07 10092.05 119
jason: jason.
lupinMVS81.39 10680.27 11584.76 8787.35 19770.21 7585.55 20286.41 23262.85 28281.32 9888.61 16161.68 14692.24 19878.41 9390.26 9591.83 123
test_yl81.17 10880.47 11083.24 14289.13 13763.62 20786.21 18489.95 14972.43 14881.78 9589.61 13157.50 19193.58 14270.75 16386.90 13392.52 101
DCV-MVSNet81.17 10880.47 11083.24 14289.13 13763.62 20786.21 18489.95 14972.43 14881.78 9589.61 13157.50 19193.58 14270.75 16386.90 13392.52 101
DU-MVS81.12 11080.52 10982.90 15987.80 18263.46 21487.02 15991.87 9579.01 2478.38 14089.07 14765.02 10893.05 17170.05 17176.46 25892.20 114
PVSNet_Blended80.98 11180.34 11282.90 15988.85 14265.40 17384.43 22992.00 8767.62 22878.11 14985.05 25766.02 9994.27 11171.52 15689.50 10489.01 222
FA-MVS(test-final)80.96 11279.91 11984.10 10888.30 16665.01 18284.55 22490.01 14773.25 13779.61 11787.57 18858.35 18394.72 9771.29 16086.25 14492.56 100
QAPM80.88 11379.50 12885.03 7588.01 17668.97 9691.59 4192.00 8766.63 24075.15 21992.16 7557.70 18895.45 6163.52 22588.76 11290.66 161
TranMVSNet+NR-MVSNet80.84 11480.31 11382.42 17487.85 17962.33 23287.74 14191.33 11280.55 777.99 15389.86 12465.23 10692.62 18167.05 20375.24 28292.30 110
UGNet80.83 11579.59 12684.54 9288.04 17468.09 11889.42 8488.16 19976.95 5776.22 19189.46 13849.30 26793.94 12568.48 18990.31 9391.60 127
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
Fast-Effi-MVS+80.81 11679.92 11883.47 13288.85 14264.51 19085.53 20489.39 16170.79 17378.49 13885.06 25667.54 8293.58 14267.03 20486.58 13892.32 109
XVG-OURS-SEG-HR80.81 11679.76 12283.96 12285.60 22568.78 9983.54 24890.50 13170.66 17776.71 18091.66 8360.69 16791.26 22676.94 10781.58 20091.83 123
xiu_mvs_v1_base_debu80.80 11879.72 12384.03 11787.35 19770.19 7785.56 19988.77 18769.06 21081.83 9188.16 17550.91 24792.85 17778.29 9587.56 12389.06 217
xiu_mvs_v1_base80.80 11879.72 12384.03 11787.35 19770.19 7785.56 19988.77 18769.06 21081.83 9188.16 17550.91 24792.85 17778.29 9587.56 12389.06 217
xiu_mvs_v1_base_debi80.80 11879.72 12384.03 11787.35 19770.19 7785.56 19988.77 18769.06 21081.83 9188.16 17550.91 24792.85 17778.29 9587.56 12389.06 217
ACMM73.20 880.78 12179.84 12183.58 13089.31 12968.37 11289.99 7191.60 10470.28 18377.25 16689.66 12953.37 22193.53 14774.24 13382.85 18588.85 230
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
114514_t80.68 12279.51 12784.20 10594.09 3867.27 13689.64 8291.11 11858.75 31774.08 23490.72 11158.10 18495.04 8369.70 17689.42 10690.30 174
iter_conf_final80.63 12379.35 13284.46 9589.36 12567.70 12689.85 7384.49 25673.19 13878.30 14388.94 15045.98 29194.56 10079.59 8384.48 16391.11 143
CANet_DTU80.61 12479.87 12082.83 16185.60 22563.17 22387.36 14988.65 19376.37 7475.88 19888.44 16753.51 22093.07 17073.30 14289.74 10392.25 112
VPA-MVSNet80.60 12580.55 10880.76 21288.07 17360.80 25186.86 16491.58 10575.67 8880.24 11189.45 14063.34 11990.25 24670.51 16779.22 23191.23 140
PVSNet_BlendedMVS80.60 12580.02 11682.36 17688.85 14265.40 17386.16 18692.00 8769.34 20078.11 14986.09 23466.02 9994.27 11171.52 15682.06 19487.39 259
AdaColmapbinary80.58 12779.42 12984.06 11393.09 5468.91 9789.36 8688.97 18169.27 20175.70 20189.69 12857.20 19595.77 5263.06 23088.41 11887.50 258
EI-MVSNet80.52 12879.98 11782.12 17784.28 24463.19 22286.41 17888.95 18274.18 11678.69 13187.54 19166.62 8992.43 18872.57 15180.57 21390.74 159
XVG-OURS80.41 12979.23 13683.97 12185.64 22469.02 9483.03 25890.39 13371.09 16977.63 15991.49 9154.62 21191.35 22475.71 11983.47 17891.54 129
PCF-MVS73.52 780.38 13078.84 14585.01 7687.71 18668.99 9583.65 24391.46 11163.00 27977.77 15790.28 11866.10 9695.09 8261.40 24788.22 12090.94 152
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
X-MVStestdata80.37 13177.83 16888.00 1594.42 2073.33 1892.78 1892.99 4579.14 1983.67 7212.47 37467.45 8396.60 3183.06 5094.50 4894.07 45
RRT_MVS80.35 13279.22 13783.74 12787.63 19065.46 17291.08 5288.92 18473.82 12376.44 18790.03 12349.05 27294.25 11576.84 10879.20 23291.51 130
test_djsdf80.30 13379.32 13383.27 14083.98 25165.37 17690.50 6090.38 13468.55 22076.19 19288.70 15756.44 19993.46 15178.98 8680.14 21990.97 151
v2v48280.23 13479.29 13483.05 15283.62 25664.14 19987.04 15889.97 14873.61 12878.18 14887.22 19961.10 16193.82 13276.11 11476.78 25591.18 141
NR-MVSNet80.23 13479.38 13082.78 16787.80 18263.34 21786.31 18191.09 11979.01 2472.17 25389.07 14767.20 8692.81 18066.08 21075.65 26992.20 114
Anonymous2024052980.19 13678.89 14484.10 10890.60 9164.75 18788.95 9890.90 12265.97 24880.59 10891.17 10049.97 25893.73 14069.16 18282.70 18993.81 55
IterMVS-LS80.06 13779.38 13082.11 17885.89 22063.20 22186.79 16789.34 16274.19 11575.45 20786.72 21166.62 8992.39 19072.58 15076.86 25290.75 158
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
Effi-MVS+-dtu80.03 13878.57 15084.42 9785.13 23468.74 10288.77 10588.10 20174.99 9874.97 22483.49 27957.27 19493.36 15473.53 13880.88 20791.18 141
v114480.03 13879.03 14183.01 15483.78 25464.51 19087.11 15790.57 13071.96 15378.08 15186.20 23161.41 15393.94 12574.93 12677.23 24690.60 164
iter_conf0580.00 14078.70 14683.91 12487.84 18065.83 16288.84 10384.92 25171.61 15978.70 13088.94 15043.88 30594.56 10079.28 8484.28 16691.33 136
v879.97 14179.02 14282.80 16484.09 24864.50 19287.96 13290.29 14174.13 11875.24 21786.81 20862.88 13093.89 13174.39 13175.40 27790.00 190
OpenMVScopyleft72.83 1079.77 14278.33 15784.09 11085.17 23069.91 8190.57 5890.97 12066.70 23672.17 25391.91 7854.70 20993.96 12261.81 24490.95 8988.41 242
v1079.74 14378.67 14782.97 15784.06 24964.95 18387.88 13890.62 12873.11 13975.11 22086.56 22261.46 15294.05 12173.68 13675.55 27189.90 196
ECVR-MVScopyleft79.61 14479.26 13580.67 21490.08 10254.69 32087.89 13777.44 32774.88 10080.27 11092.79 6648.96 27492.45 18768.55 18892.50 7094.86 15
BH-RMVSNet79.61 14478.44 15383.14 14789.38 12465.93 15984.95 21487.15 22373.56 13078.19 14789.79 12656.67 19893.36 15459.53 26186.74 13690.13 180
v119279.59 14678.43 15483.07 15183.55 25864.52 18986.93 16290.58 12970.83 17277.78 15685.90 23559.15 17893.94 12573.96 13577.19 24890.76 157
ab-mvs79.51 14778.97 14381.14 20388.46 16060.91 24983.84 24089.24 16870.36 18179.03 12488.87 15463.23 12390.21 24765.12 21782.57 19092.28 111
WR-MVS79.49 14879.22 13780.27 22288.79 14858.35 27185.06 21188.61 19578.56 2877.65 15888.34 16963.81 11890.66 24264.98 21977.22 24791.80 125
v14419279.47 14978.37 15582.78 16783.35 26163.96 20286.96 16090.36 13769.99 18777.50 16085.67 24160.66 16893.77 13674.27 13276.58 25690.62 162
BH-untuned79.47 14978.60 14982.05 17989.19 13565.91 16086.07 18888.52 19672.18 15075.42 20887.69 18561.15 16093.54 14660.38 25486.83 13586.70 278
test111179.43 15179.18 13980.15 22489.99 10753.31 33387.33 15177.05 33075.04 9780.23 11292.77 6848.97 27392.33 19568.87 18592.40 7294.81 18
mvs_anonymous79.42 15279.11 14080.34 22084.45 24357.97 27882.59 26087.62 21367.40 23176.17 19588.56 16468.47 7689.59 25570.65 16686.05 14793.47 72
thisisatest053079.40 15377.76 17384.31 10287.69 18865.10 18187.36 14984.26 26270.04 18677.42 16288.26 17349.94 25994.79 9570.20 16984.70 16093.03 87
tttt051779.40 15377.91 16583.90 12588.10 17163.84 20488.37 12084.05 26471.45 16376.78 17889.12 14649.93 26194.89 9070.18 17083.18 18292.96 91
V4279.38 15578.24 15982.83 16181.10 30665.50 17085.55 20289.82 15171.57 16178.21 14686.12 23360.66 16893.18 16475.64 12075.46 27589.81 201
jajsoiax79.29 15677.96 16383.27 14084.68 24066.57 14989.25 8890.16 14369.20 20575.46 20689.49 13545.75 29693.13 16776.84 10880.80 20990.11 182
v192192079.22 15778.03 16282.80 16483.30 26363.94 20386.80 16690.33 13869.91 18977.48 16185.53 24458.44 18293.75 13873.60 13776.85 25390.71 160
AUN-MVS79.21 15877.60 17884.05 11588.71 15267.61 12885.84 19587.26 22169.08 20977.23 16888.14 17953.20 22393.47 15075.50 12473.45 29991.06 146
TAPA-MVS73.13 979.15 15977.94 16482.79 16689.59 11462.99 22788.16 12791.51 10765.77 24977.14 17391.09 10260.91 16493.21 15850.26 32187.05 13192.17 116
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
mvs_tets79.13 16077.77 17283.22 14484.70 23966.37 15189.17 8990.19 14269.38 19975.40 20989.46 13844.17 30393.15 16576.78 11080.70 21190.14 179
UniMVSNet_ETH3D79.10 16178.24 15981.70 18686.85 20960.24 26087.28 15388.79 18674.25 11476.84 17590.53 11649.48 26491.56 21867.98 19282.15 19393.29 77
CDS-MVSNet79.07 16277.70 17583.17 14687.60 19168.23 11684.40 23186.20 23667.49 23076.36 18886.54 22361.54 14990.79 23961.86 24387.33 12790.49 168
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
MVSTER79.01 16377.88 16782.38 17583.07 27064.80 18684.08 23988.95 18269.01 21378.69 13187.17 20254.70 20992.43 18874.69 12780.57 21389.89 197
v124078.99 16477.78 17182.64 17083.21 26563.54 21186.62 17390.30 14069.74 19577.33 16485.68 24057.04 19693.76 13773.13 14576.92 25090.62 162
Anonymous2023121178.97 16577.69 17682.81 16390.54 9364.29 19790.11 7091.51 10765.01 25876.16 19688.13 18050.56 25293.03 17469.68 17777.56 24591.11 143
v7n78.97 16577.58 17983.14 14783.45 26065.51 16988.32 12191.21 11473.69 12672.41 25086.32 22957.93 18593.81 13369.18 18175.65 26990.11 182
TAMVS78.89 16777.51 18083.03 15387.80 18267.79 12484.72 21885.05 24967.63 22776.75 17987.70 18462.25 13990.82 23858.53 27387.13 13090.49 168
c3_l78.75 16877.91 16581.26 19882.89 27661.56 24384.09 23889.13 17469.97 18875.56 20284.29 26766.36 9392.09 20273.47 14075.48 27390.12 181
tt080578.73 16977.83 16881.43 19285.17 23060.30 25989.41 8590.90 12271.21 16677.17 17288.73 15646.38 28693.21 15872.57 15178.96 23390.79 155
v14878.72 17077.80 17081.47 19182.73 27961.96 23886.30 18288.08 20273.26 13676.18 19385.47 24662.46 13592.36 19271.92 15573.82 29690.09 184
VPNet78.69 17178.66 14878.76 24788.31 16555.72 31184.45 22886.63 23076.79 6278.26 14490.55 11559.30 17789.70 25466.63 20577.05 24990.88 153
ET-MVSNet_ETH3D78.63 17276.63 20084.64 8986.73 21369.47 8885.01 21284.61 25469.54 19666.51 31186.59 21950.16 25691.75 21376.26 11384.24 16792.69 97
anonymousdsp78.60 17377.15 18582.98 15680.51 31267.08 14087.24 15489.53 15865.66 25175.16 21887.19 20152.52 22492.25 19777.17 10579.34 22989.61 206
miper_ehance_all_eth78.59 17477.76 17381.08 20582.66 28161.56 24383.65 24389.15 17268.87 21575.55 20383.79 27566.49 9192.03 20373.25 14376.39 26089.64 205
WR-MVS_H78.51 17578.49 15178.56 25088.02 17556.38 30488.43 11592.67 6177.14 5273.89 23587.55 19066.25 9589.24 26158.92 26873.55 29890.06 188
GBi-Net78.40 17677.40 18181.40 19487.60 19163.01 22488.39 11789.28 16471.63 15675.34 21187.28 19554.80 20591.11 22962.72 23279.57 22490.09 184
test178.40 17677.40 18181.40 19487.60 19163.01 22488.39 11789.28 16471.63 15675.34 21187.28 19554.80 20591.11 22962.72 23279.57 22490.09 184
Vis-MVSNet (Re-imp)78.36 17878.45 15278.07 25888.64 15451.78 34086.70 17179.63 31474.14 11775.11 22090.83 11061.29 15789.75 25258.10 27791.60 8092.69 97
Anonymous20240521178.25 17977.01 18781.99 18191.03 8260.67 25384.77 21783.90 26670.65 17880.00 11491.20 9841.08 32291.43 22265.21 21685.26 15493.85 52
CP-MVSNet78.22 18078.34 15677.84 26087.83 18154.54 32287.94 13491.17 11677.65 3673.48 23888.49 16562.24 14088.43 27562.19 23874.07 29190.55 166
BH-w/o78.21 18177.33 18380.84 21088.81 14665.13 18084.87 21587.85 20969.75 19374.52 23084.74 26161.34 15593.11 16858.24 27685.84 15184.27 311
FMVSNet278.20 18277.21 18481.20 20187.60 19162.89 22887.47 14789.02 17771.63 15675.29 21687.28 19554.80 20591.10 23262.38 23679.38 22889.61 206
MVS78.19 18376.99 18981.78 18485.66 22366.99 14184.66 21990.47 13255.08 33572.02 25585.27 24963.83 11794.11 12066.10 20989.80 10284.24 312
Baseline_NR-MVSNet78.15 18478.33 15777.61 26585.79 22156.21 30786.78 16885.76 24273.60 12977.93 15487.57 18865.02 10888.99 26567.14 20275.33 27987.63 253
CNLPA78.08 18576.79 19481.97 18290.40 9671.07 6087.59 14484.55 25566.03 24772.38 25189.64 13057.56 19086.04 29459.61 26083.35 17988.79 233
cl2278.07 18677.01 18781.23 19982.37 28861.83 24083.55 24787.98 20468.96 21475.06 22283.87 27161.40 15491.88 21073.53 13876.39 26089.98 193
PLCcopyleft70.83 1178.05 18776.37 20583.08 15091.88 7467.80 12388.19 12589.46 16064.33 26669.87 27888.38 16853.66 21993.58 14258.86 26982.73 18787.86 249
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
Fast-Effi-MVS+-dtu78.02 18876.49 20182.62 17183.16 26966.96 14486.94 16187.45 21872.45 14571.49 26084.17 26854.79 20891.58 21767.61 19580.31 21689.30 213
PS-CasMVS78.01 18978.09 16177.77 26287.71 18654.39 32488.02 13091.22 11377.50 4473.26 24088.64 16060.73 16588.41 27661.88 24273.88 29590.53 167
HY-MVS69.67 1277.95 19077.15 18580.36 21987.57 19560.21 26183.37 25087.78 21166.11 24475.37 21087.06 20663.27 12190.48 24461.38 24882.43 19190.40 172
eth_miper_zixun_eth77.92 19176.69 19881.61 18983.00 27361.98 23783.15 25389.20 17069.52 19774.86 22684.35 26661.76 14592.56 18471.50 15872.89 30490.28 175
FMVSNet377.88 19276.85 19280.97 20886.84 21062.36 23186.52 17688.77 18771.13 16775.34 21186.66 21754.07 21691.10 23262.72 23279.57 22489.45 209
miper_enhance_ethall77.87 19376.86 19180.92 20981.65 29561.38 24582.68 25988.98 17965.52 25375.47 20482.30 29465.76 10392.00 20572.95 14676.39 26089.39 210
FE-MVS77.78 19475.68 21184.08 11188.09 17266.00 15783.13 25487.79 21068.42 22378.01 15285.23 25145.50 29895.12 7659.11 26585.83 15291.11 143
PEN-MVS77.73 19577.69 17677.84 26087.07 20753.91 32787.91 13691.18 11577.56 4173.14 24288.82 15561.23 15889.17 26259.95 25772.37 30690.43 170
cl____77.72 19676.76 19580.58 21582.49 28560.48 25683.09 25587.87 20769.22 20374.38 23285.22 25262.10 14291.53 21971.09 16175.41 27689.73 204
DIV-MVS_self_test77.72 19676.76 19580.58 21582.48 28660.48 25683.09 25587.86 20869.22 20374.38 23285.24 25062.10 14291.53 21971.09 16175.40 27789.74 203
PAPM77.68 19876.40 20481.51 19087.29 20361.85 23983.78 24189.59 15764.74 26071.23 26188.70 15762.59 13293.66 14152.66 30887.03 13289.01 222
CHOSEN 1792x268877.63 19975.69 21083.44 13389.98 10868.58 11078.70 30287.50 21656.38 33075.80 20086.84 20758.67 18091.40 22361.58 24685.75 15390.34 173
HyFIR lowres test77.53 20075.40 21783.94 12389.59 11466.62 14780.36 28388.64 19456.29 33176.45 18485.17 25357.64 18993.28 15661.34 24983.10 18391.91 122
FMVSNet177.44 20176.12 20781.40 19486.81 21163.01 22488.39 11789.28 16470.49 18074.39 23187.28 19549.06 27191.11 22960.91 25178.52 23590.09 184
TR-MVS77.44 20176.18 20681.20 20188.24 16763.24 21984.61 22286.40 23367.55 22977.81 15586.48 22554.10 21593.15 16557.75 28082.72 18887.20 264
1112_ss77.40 20376.43 20380.32 22189.11 14160.41 25883.65 24387.72 21262.13 29173.05 24386.72 21162.58 13389.97 24962.11 24180.80 20990.59 165
thisisatest051577.33 20475.38 21883.18 14585.27 22963.80 20582.11 26483.27 27765.06 25675.91 19783.84 27349.54 26394.27 11167.24 20086.19 14591.48 134
test250677.30 20576.49 20179.74 23290.08 10252.02 33687.86 13963.10 36474.88 10080.16 11392.79 6638.29 33292.35 19368.74 18792.50 7094.86 15
bld_raw_dy_0_6477.29 20675.98 20881.22 20085.04 23665.47 17188.14 12977.56 32469.20 20573.77 23689.40 14442.24 31688.85 27176.78 11081.64 19989.33 212
pm-mvs177.25 20776.68 19978.93 24584.22 24658.62 27086.41 17888.36 19871.37 16473.31 23988.01 18161.22 15989.15 26364.24 22373.01 30389.03 221
LCM-MVSNet-Re77.05 20876.94 19077.36 26887.20 20451.60 34180.06 28680.46 30575.20 9567.69 29486.72 21162.48 13488.98 26663.44 22789.25 10791.51 130
DTE-MVSNet76.99 20976.80 19377.54 26786.24 21753.06 33587.52 14590.66 12777.08 5572.50 24888.67 15960.48 17189.52 25657.33 28470.74 31790.05 189
baseline176.98 21076.75 19777.66 26388.13 16955.66 31285.12 21081.89 29073.04 14176.79 17788.90 15262.43 13687.78 28363.30 22971.18 31589.55 208
LS3D76.95 21174.82 22483.37 13790.45 9467.36 13589.15 9386.94 22661.87 29369.52 28190.61 11351.71 24194.53 10346.38 34186.71 13788.21 244
GA-MVS76.87 21275.17 22281.97 18282.75 27862.58 22981.44 27386.35 23572.16 15274.74 22782.89 28646.20 29092.02 20468.85 18681.09 20591.30 139
DP-MVS76.78 21374.57 22683.42 13493.29 4869.46 9088.55 11483.70 26863.98 27270.20 26988.89 15354.01 21794.80 9446.66 33881.88 19786.01 290
cascas76.72 21474.64 22582.99 15585.78 22265.88 16182.33 26289.21 16960.85 29972.74 24581.02 30547.28 28193.75 13867.48 19785.02 15589.34 211
131476.53 21575.30 22180.21 22383.93 25262.32 23384.66 21988.81 18560.23 30370.16 27284.07 27055.30 20390.73 24167.37 19883.21 18187.59 256
thres100view90076.50 21675.55 21479.33 24089.52 11756.99 29385.83 19683.23 27873.94 12076.32 18987.12 20351.89 23891.95 20648.33 32983.75 17289.07 215
thres600view776.50 21675.44 21579.68 23489.40 12257.16 29085.53 20483.23 27873.79 12576.26 19087.09 20451.89 23891.89 20948.05 33483.72 17590.00 190
thres40076.50 21675.37 21979.86 22989.13 13757.65 28485.17 20783.60 26973.41 13476.45 18486.39 22752.12 23191.95 20648.33 32983.75 17290.00 190
tfpn200view976.42 21975.37 21979.55 23989.13 13757.65 28485.17 20783.60 26973.41 13476.45 18486.39 22752.12 23191.95 20648.33 32983.75 17289.07 215
Test_1112_low_res76.40 22075.44 21579.27 24189.28 13158.09 27481.69 26887.07 22459.53 31072.48 24986.67 21661.30 15689.33 25960.81 25380.15 21890.41 171
F-COLMAP76.38 22174.33 23182.50 17389.28 13166.95 14588.41 11689.03 17664.05 27066.83 30588.61 16146.78 28492.89 17657.48 28178.55 23487.67 252
LTVRE_ROB69.57 1376.25 22274.54 22881.41 19388.60 15564.38 19679.24 29589.12 17570.76 17569.79 28087.86 18249.09 27093.20 16156.21 29480.16 21786.65 279
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
MVP-Stereo76.12 22374.46 23081.13 20485.37 22869.79 8384.42 23087.95 20565.03 25767.46 29785.33 24853.28 22291.73 21558.01 27883.27 18081.85 333
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
XVG-ACMP-BASELINE76.11 22474.27 23281.62 18783.20 26664.67 18883.60 24689.75 15469.75 19371.85 25687.09 20432.78 34592.11 20169.99 17380.43 21588.09 245
ACMH+68.96 1476.01 22574.01 23382.03 18088.60 15565.31 17788.86 10187.55 21470.25 18467.75 29387.47 19341.27 32093.19 16358.37 27475.94 26687.60 254
ACMH67.68 1675.89 22673.93 23481.77 18588.71 15266.61 14888.62 11289.01 17869.81 19066.78 30686.70 21541.95 31991.51 22155.64 29578.14 24187.17 265
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
IB-MVS68.01 1575.85 22773.36 24083.31 13884.76 23866.03 15583.38 24985.06 24870.21 18569.40 28281.05 30445.76 29594.66 9965.10 21875.49 27289.25 214
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
baseline275.70 22873.83 23781.30 19783.26 26461.79 24182.57 26180.65 30166.81 23366.88 30383.42 28057.86 18792.19 19963.47 22679.57 22489.91 195
WTY-MVS75.65 22975.68 21175.57 28486.40 21656.82 29577.92 31082.40 28765.10 25576.18 19387.72 18363.13 12880.90 32460.31 25581.96 19589.00 224
thres20075.55 23074.47 22978.82 24687.78 18557.85 28183.07 25783.51 27272.44 14775.84 19984.42 26352.08 23391.75 21347.41 33683.64 17686.86 274
test_vis1_n_192075.52 23175.78 20974.75 29479.84 31957.44 28883.26 25185.52 24462.83 28379.34 12286.17 23245.10 30079.71 32878.75 8881.21 20487.10 271
EPNet_dtu75.46 23274.86 22377.23 27282.57 28354.60 32186.89 16383.09 28171.64 15566.25 31385.86 23755.99 20088.04 28054.92 29786.55 13989.05 220
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
IterMVS-SCA-FT75.43 23373.87 23680.11 22582.69 28064.85 18581.57 27083.47 27469.16 20770.49 26684.15 26951.95 23688.15 27869.23 18072.14 30987.34 261
XXY-MVS75.41 23475.56 21374.96 29083.59 25757.82 28280.59 28183.87 26766.54 24174.93 22588.31 17063.24 12280.09 32762.16 23976.85 25386.97 272
TransMVSNet (Re)75.39 23574.56 22777.86 25985.50 22757.10 29286.78 16886.09 23972.17 15171.53 25987.34 19463.01 12989.31 26056.84 28961.83 34287.17 265
CostFormer75.24 23673.90 23579.27 24182.65 28258.27 27380.80 27682.73 28561.57 29475.33 21483.13 28455.52 20191.07 23564.98 21978.34 24088.45 240
D2MVS74.82 23773.21 24179.64 23679.81 32062.56 23080.34 28487.35 21964.37 26568.86 28582.66 29046.37 28790.10 24867.91 19381.24 20386.25 283
pmmvs674.69 23873.39 23978.61 24981.38 30157.48 28786.64 17287.95 20564.99 25970.18 27086.61 21850.43 25489.52 25662.12 24070.18 31988.83 231
tfpnnormal74.39 23973.16 24278.08 25786.10 21958.05 27584.65 22187.53 21570.32 18271.22 26285.63 24254.97 20489.86 25043.03 35075.02 28486.32 282
IterMVS74.29 24072.94 24478.35 25481.53 29863.49 21381.58 26982.49 28668.06 22669.99 27583.69 27751.66 24285.54 29765.85 21271.64 31286.01 290
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
OurMVSNet-221017-074.26 24172.42 24879.80 23183.76 25559.59 26585.92 19286.64 22966.39 24266.96 30287.58 18739.46 32691.60 21665.76 21369.27 32288.22 243
SCA74.22 24272.33 24979.91 22884.05 25062.17 23579.96 28979.29 31666.30 24372.38 25180.13 31451.95 23688.60 27359.25 26377.67 24488.96 226
miper_lstm_enhance74.11 24373.11 24377.13 27380.11 31559.62 26472.23 33386.92 22766.76 23570.40 26782.92 28556.93 19782.92 31669.06 18372.63 30588.87 229
EG-PatchMatch MVS74.04 24471.82 25280.71 21384.92 23767.42 13285.86 19488.08 20266.04 24664.22 32583.85 27235.10 34192.56 18457.44 28280.83 20882.16 332
pmmvs474.03 24571.91 25180.39 21881.96 29268.32 11381.45 27282.14 28859.32 31169.87 27885.13 25452.40 22788.13 27960.21 25674.74 28784.73 307
MS-PatchMatch73.83 24672.67 24577.30 27083.87 25366.02 15681.82 26584.66 25361.37 29768.61 28882.82 28847.29 28088.21 27759.27 26284.32 16577.68 347
sss73.60 24773.64 23873.51 30282.80 27755.01 31876.12 31781.69 29362.47 28874.68 22885.85 23857.32 19378.11 33560.86 25280.93 20687.39 259
RPMNet73.51 24870.49 26582.58 17281.32 30465.19 17875.92 31992.27 7657.60 32472.73 24676.45 33952.30 22895.43 6348.14 33377.71 24287.11 269
SixPastTwentyTwo73.37 24971.26 25979.70 23385.08 23557.89 28085.57 19883.56 27171.03 17065.66 31585.88 23642.10 31792.57 18359.11 26563.34 34088.65 237
CR-MVSNet73.37 24971.27 25879.67 23581.32 30465.19 17875.92 31980.30 30759.92 30672.73 24681.19 30252.50 22586.69 28959.84 25877.71 24287.11 269
MSDG73.36 25170.99 26080.49 21784.51 24265.80 16480.71 27986.13 23865.70 25065.46 31683.74 27644.60 30190.91 23751.13 31476.89 25184.74 306
tpm273.26 25271.46 25478.63 24883.34 26256.71 29880.65 28080.40 30656.63 32973.55 23782.02 29951.80 24091.24 22756.35 29378.42 23887.95 246
RPSCF73.23 25371.46 25478.54 25182.50 28459.85 26282.18 26382.84 28458.96 31471.15 26389.41 14245.48 29984.77 30458.82 27071.83 31191.02 150
PatchmatchNetpermissive73.12 25471.33 25778.49 25383.18 26760.85 25079.63 29178.57 31964.13 26771.73 25779.81 31951.20 24585.97 29557.40 28376.36 26388.66 236
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
COLMAP_ROBcopyleft66.92 1773.01 25570.41 26780.81 21187.13 20665.63 16788.30 12284.19 26362.96 28063.80 32987.69 18538.04 33392.56 18446.66 33874.91 28584.24 312
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
CVMVSNet72.99 25672.58 24674.25 29884.28 24450.85 34686.41 17883.45 27544.56 35273.23 24187.54 19149.38 26585.70 29665.90 21178.44 23786.19 285
test-LLR72.94 25772.43 24774.48 29581.35 30258.04 27678.38 30377.46 32566.66 23769.95 27679.00 32348.06 27779.24 32966.13 20784.83 15786.15 286
test_040272.79 25870.44 26679.84 23088.13 16965.99 15885.93 19184.29 26065.57 25267.40 29985.49 24546.92 28392.61 18235.88 35974.38 29080.94 338
MVS_030472.48 25970.89 26277.24 27182.20 28959.68 26384.11 23783.49 27367.10 23266.87 30480.59 31035.00 34287.40 28559.07 26779.58 22384.63 308
tpmrst72.39 26072.13 25073.18 30680.54 31149.91 35079.91 29079.08 31763.11 27771.69 25879.95 31655.32 20282.77 31765.66 21473.89 29486.87 273
PatchMatch-RL72.38 26170.90 26176.80 27688.60 15567.38 13479.53 29276.17 33562.75 28569.36 28382.00 30045.51 29784.89 30353.62 30380.58 21278.12 346
CL-MVSNet_self_test72.37 26271.46 25475.09 28979.49 32653.53 32980.76 27885.01 25069.12 20870.51 26582.05 29857.92 18684.13 30752.27 30966.00 33487.60 254
tpm72.37 26271.71 25374.35 29782.19 29052.00 33779.22 29677.29 32864.56 26272.95 24483.68 27851.35 24383.26 31558.33 27575.80 26787.81 250
PVSNet64.34 1872.08 26470.87 26375.69 28286.21 21856.44 30274.37 32980.73 30062.06 29270.17 27182.23 29642.86 31083.31 31454.77 29884.45 16487.32 262
pmmvs571.55 26570.20 27075.61 28377.83 33256.39 30381.74 26780.89 29757.76 32267.46 29784.49 26249.26 26885.32 30057.08 28675.29 28085.11 303
test-mter71.41 26670.39 26874.48 29581.35 30258.04 27678.38 30377.46 32560.32 30269.95 27679.00 32336.08 33979.24 32966.13 20784.83 15786.15 286
K. test v371.19 26768.51 27879.21 24383.04 27257.78 28384.35 23276.91 33172.90 14462.99 33282.86 28739.27 32791.09 23461.65 24552.66 35888.75 234
tpmvs71.09 26869.29 27376.49 27782.04 29156.04 30878.92 30081.37 29664.05 27067.18 30178.28 32949.74 26289.77 25149.67 32472.37 30683.67 319
AllTest70.96 26968.09 28479.58 23785.15 23263.62 20784.58 22379.83 31162.31 28960.32 33986.73 20932.02 34688.96 26850.28 31971.57 31386.15 286
test_fmvs170.93 27070.52 26472.16 31073.71 34855.05 31780.82 27578.77 31851.21 34678.58 13584.41 26431.20 34976.94 34175.88 11880.12 22084.47 310
test_fmvs1_n70.86 27170.24 26972.73 30772.51 35655.28 31581.27 27479.71 31351.49 34578.73 12984.87 25827.54 35377.02 34076.06 11579.97 22185.88 293
Patchmtry70.74 27269.16 27575.49 28680.72 30854.07 32674.94 32880.30 30758.34 31870.01 27381.19 30252.50 22586.54 29053.37 30571.09 31685.87 294
MIMVSNet70.69 27369.30 27274.88 29184.52 24156.35 30575.87 32179.42 31564.59 26167.76 29282.41 29241.10 32181.54 32146.64 34081.34 20186.75 277
tpm cat170.57 27468.31 28077.35 26982.41 28757.95 27978.08 30780.22 30952.04 34168.54 28977.66 33452.00 23587.84 28251.77 31072.07 31086.25 283
OpenMVS_ROBcopyleft64.09 1970.56 27568.19 28177.65 26480.26 31359.41 26785.01 21282.96 28358.76 31665.43 31782.33 29337.63 33591.23 22845.34 34676.03 26582.32 330
pmmvs-eth3d70.50 27667.83 28878.52 25277.37 33566.18 15481.82 26581.51 29458.90 31563.90 32880.42 31242.69 31186.28 29358.56 27265.30 33683.11 325
USDC70.33 27768.37 27976.21 27980.60 31056.23 30679.19 29786.49 23160.89 29861.29 33685.47 24631.78 34889.47 25853.37 30576.21 26482.94 329
Patchmatch-RL test70.24 27867.78 29077.61 26577.43 33459.57 26671.16 33670.33 34862.94 28168.65 28772.77 34850.62 25185.49 29869.58 17866.58 33187.77 251
CMPMVSbinary51.72 2170.19 27968.16 28276.28 27873.15 35357.55 28679.47 29383.92 26548.02 34956.48 35284.81 25943.13 30886.42 29262.67 23581.81 19884.89 304
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
ppachtmachnet_test70.04 28067.34 29578.14 25679.80 32161.13 24679.19 29780.59 30259.16 31365.27 31879.29 32046.75 28587.29 28649.33 32566.72 32986.00 292
gg-mvs-nofinetune69.95 28167.96 28575.94 28083.07 27054.51 32377.23 31470.29 34963.11 27770.32 26862.33 35743.62 30688.69 27253.88 30287.76 12284.62 309
TESTMET0.1,169.89 28269.00 27672.55 30879.27 32956.85 29478.38 30374.71 34157.64 32368.09 29177.19 33637.75 33476.70 34263.92 22484.09 16884.10 315
test_vis1_n69.85 28369.21 27471.77 31272.66 35555.27 31681.48 27176.21 33452.03 34275.30 21583.20 28328.97 35176.22 34674.60 12878.41 23983.81 318
FMVSNet569.50 28467.96 28574.15 29982.97 27555.35 31480.01 28882.12 28962.56 28763.02 33081.53 30136.92 33681.92 31948.42 32874.06 29285.17 302
PMMVS69.34 28568.67 27771.35 31775.67 34062.03 23675.17 32373.46 34450.00 34768.68 28679.05 32152.07 23478.13 33461.16 25082.77 18673.90 352
our_test_369.14 28667.00 29775.57 28479.80 32158.80 26877.96 30877.81 32259.55 30962.90 33378.25 33047.43 27983.97 30851.71 31167.58 32883.93 317
EPMVS69.02 28768.16 28271.59 31379.61 32449.80 35277.40 31266.93 35762.82 28470.01 27379.05 32145.79 29477.86 33756.58 29175.26 28187.13 268
KD-MVS_self_test68.81 28867.59 29372.46 30974.29 34645.45 35877.93 30987.00 22563.12 27663.99 32778.99 32542.32 31384.77 30456.55 29264.09 33987.16 267
Anonymous2024052168.80 28967.22 29673.55 30174.33 34554.11 32583.18 25285.61 24358.15 31961.68 33580.94 30730.71 35081.27 32357.00 28773.34 30285.28 299
Anonymous2023120668.60 29067.80 28971.02 31980.23 31450.75 34778.30 30680.47 30456.79 32866.11 31482.63 29146.35 28878.95 33143.62 34975.70 26883.36 322
MIMVSNet168.58 29166.78 29973.98 30080.07 31651.82 33980.77 27784.37 25764.40 26459.75 34282.16 29736.47 33783.63 31142.73 35170.33 31886.48 281
EU-MVSNet68.53 29267.61 29271.31 31878.51 33147.01 35684.47 22584.27 26142.27 35566.44 31284.79 26040.44 32483.76 30958.76 27168.54 32783.17 323
PatchT68.46 29367.85 28770.29 32280.70 30943.93 36572.47 33274.88 33860.15 30470.55 26476.57 33849.94 25981.59 32050.58 31574.83 28685.34 298
test_fmvs268.35 29467.48 29470.98 32069.50 35951.95 33880.05 28776.38 33349.33 34874.65 22984.38 26523.30 35975.40 35174.51 12975.17 28385.60 295
test0.0.03 168.00 29567.69 29168.90 32777.55 33347.43 35475.70 32272.95 34666.66 23766.56 30782.29 29548.06 27775.87 34844.97 34774.51 28983.41 321
TDRefinement67.49 29664.34 30576.92 27473.47 35161.07 24784.86 21682.98 28259.77 30758.30 34685.13 25426.06 35487.89 28147.92 33560.59 34781.81 334
test20.0367.45 29766.95 29868.94 32675.48 34244.84 36377.50 31177.67 32366.66 23763.01 33183.80 27447.02 28278.40 33342.53 35268.86 32683.58 320
UnsupCasMVSNet_eth67.33 29865.99 30171.37 31573.48 35051.47 34375.16 32485.19 24765.20 25460.78 33880.93 30942.35 31277.20 33957.12 28553.69 35785.44 297
TinyColmap67.30 29964.81 30374.76 29381.92 29356.68 29980.29 28581.49 29560.33 30156.27 35383.22 28124.77 35687.66 28445.52 34469.47 32179.95 342
dp66.80 30065.43 30270.90 32179.74 32348.82 35375.12 32674.77 33959.61 30864.08 32677.23 33542.89 30980.72 32548.86 32766.58 33183.16 324
MDA-MVSNet-bldmvs66.68 30163.66 30975.75 28179.28 32860.56 25573.92 33078.35 32064.43 26350.13 35979.87 31844.02 30483.67 31046.10 34256.86 35083.03 327
testgi66.67 30266.53 30067.08 33475.62 34141.69 36975.93 31876.50 33266.11 24465.20 32186.59 21935.72 34074.71 35343.71 34873.38 30184.84 305
CHOSEN 280x42066.51 30364.71 30471.90 31181.45 29963.52 21257.98 36468.95 35553.57 33762.59 33476.70 33746.22 28975.29 35255.25 29679.68 22276.88 349
PM-MVS66.41 30464.14 30673.20 30573.92 34756.45 30178.97 29964.96 36263.88 27464.72 32280.24 31319.84 36283.44 31366.24 20664.52 33879.71 343
JIA-IIPM66.32 30562.82 31576.82 27577.09 33661.72 24265.34 35775.38 33658.04 32164.51 32362.32 35842.05 31886.51 29151.45 31369.22 32382.21 331
KD-MVS_2432*160066.22 30663.89 30773.21 30375.47 34353.42 33170.76 33984.35 25864.10 26866.52 30978.52 32734.55 34384.98 30150.40 31750.33 36181.23 336
miper_refine_blended66.22 30663.89 30773.21 30375.47 34353.42 33170.76 33984.35 25864.10 26866.52 30978.52 32734.55 34384.98 30150.40 31750.33 36181.23 336
ADS-MVSNet266.20 30863.33 31074.82 29279.92 31758.75 26967.55 35075.19 33753.37 33865.25 31975.86 34142.32 31380.53 32641.57 35368.91 32485.18 300
YYNet165.03 30962.91 31371.38 31475.85 33956.60 30069.12 34774.66 34257.28 32654.12 35577.87 33245.85 29374.48 35449.95 32261.52 34483.05 326
MDA-MVSNet_test_wron65.03 30962.92 31271.37 31575.93 33856.73 29669.09 34874.73 34057.28 32654.03 35677.89 33145.88 29274.39 35549.89 32361.55 34382.99 328
Patchmatch-test64.82 31163.24 31169.57 32479.42 32749.82 35163.49 36169.05 35451.98 34359.95 34180.13 31450.91 24770.98 35940.66 35573.57 29787.90 248
ADS-MVSNet64.36 31262.88 31468.78 32979.92 31747.17 35567.55 35071.18 34753.37 33865.25 31975.86 34142.32 31373.99 35641.57 35368.91 32485.18 300
LF4IMVS64.02 31362.19 31669.50 32570.90 35753.29 33476.13 31677.18 32952.65 34058.59 34480.98 30623.55 35876.52 34353.06 30766.66 33078.68 345
UnsupCasMVSNet_bld63.70 31461.53 31970.21 32373.69 34951.39 34472.82 33181.89 29055.63 33357.81 34871.80 35038.67 32978.61 33249.26 32652.21 35980.63 339
test_fmvs363.36 31561.82 31767.98 33162.51 36646.96 35777.37 31374.03 34345.24 35167.50 29678.79 32612.16 37072.98 35872.77 14966.02 33383.99 316
mvsany_test162.30 31661.26 32065.41 33669.52 35854.86 31966.86 35249.78 37346.65 35068.50 29083.21 28249.15 26966.28 36556.93 28860.77 34575.11 351
new-patchmatchnet61.73 31761.73 31861.70 34072.74 35424.50 37969.16 34678.03 32161.40 29556.72 35175.53 34438.42 33076.48 34445.95 34357.67 34984.13 314
PVSNet_057.27 2061.67 31859.27 32168.85 32879.61 32457.44 28868.01 34973.44 34555.93 33258.54 34570.41 35344.58 30277.55 33847.01 33735.91 36771.55 355
test_vis1_rt60.28 31958.42 32265.84 33567.25 36255.60 31370.44 34160.94 36644.33 35359.00 34366.64 35524.91 35568.67 36362.80 23169.48 32073.25 353
MVS-HIRNet59.14 32057.67 32363.57 33881.65 29543.50 36671.73 33465.06 36139.59 35951.43 35857.73 36338.34 33182.58 31839.53 35673.95 29364.62 359
pmmvs357.79 32154.26 32568.37 33064.02 36556.72 29775.12 32665.17 36040.20 35752.93 35769.86 35420.36 36175.48 35045.45 34555.25 35672.90 354
DSMNet-mixed57.77 32256.90 32460.38 34267.70 36135.61 37269.18 34553.97 37132.30 36757.49 34979.88 31740.39 32568.57 36438.78 35772.37 30676.97 348
LCM-MVSNet54.25 32349.68 33267.97 33253.73 37445.28 36166.85 35380.78 29935.96 36339.45 36462.23 3598.70 37478.06 33648.24 33251.20 36080.57 340
mvsany_test353.99 32451.45 32861.61 34155.51 37044.74 36463.52 36045.41 37743.69 35458.11 34776.45 33917.99 36363.76 36854.77 29847.59 36376.34 350
FPMVS53.68 32551.64 32759.81 34365.08 36451.03 34569.48 34469.58 35241.46 35640.67 36272.32 34916.46 36670.00 36224.24 36965.42 33558.40 364
APD_test153.31 32649.93 33163.42 33965.68 36350.13 34971.59 33566.90 35834.43 36440.58 36371.56 3518.65 37576.27 34534.64 36155.36 35563.86 360
N_pmnet52.79 32753.26 32651.40 35178.99 3307.68 38269.52 3433.89 38251.63 34457.01 35074.98 34540.83 32365.96 36637.78 35864.67 33780.56 341
test_f52.09 32850.82 32955.90 34753.82 37342.31 36859.42 36358.31 36936.45 36256.12 35470.96 35212.18 36957.79 37053.51 30456.57 35267.60 356
EGC-MVSNET52.07 32947.05 33367.14 33383.51 25960.71 25280.50 28267.75 3560.07 3770.43 37875.85 34324.26 35781.54 32128.82 36362.25 34159.16 362
new_pmnet50.91 33050.29 33052.78 35068.58 36034.94 37463.71 35956.63 37039.73 35844.95 36065.47 35621.93 36058.48 36934.98 36056.62 35164.92 358
ANet_high50.57 33146.10 33563.99 33748.67 37739.13 37070.99 33880.85 29861.39 29631.18 36657.70 36417.02 36573.65 35731.22 36215.89 37479.18 344
test_vis3_rt49.26 33247.02 33456.00 34654.30 37145.27 36266.76 35448.08 37436.83 36144.38 36153.20 3667.17 37764.07 36756.77 29055.66 35358.65 363
testf145.72 33341.96 33657.00 34456.90 36845.32 35966.14 35559.26 36726.19 36830.89 36760.96 3614.14 37870.64 36026.39 36746.73 36555.04 365
APD_test245.72 33341.96 33657.00 34456.90 36845.32 35966.14 35559.26 36726.19 36830.89 36760.96 3614.14 37870.64 36026.39 36746.73 36555.04 365
Gipumacopyleft45.18 33541.86 33855.16 34977.03 33751.52 34232.50 37080.52 30332.46 36627.12 36935.02 3709.52 37375.50 34922.31 37060.21 34838.45 369
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
PMVScopyleft37.38 2244.16 33640.28 33955.82 34840.82 37942.54 36765.12 35863.99 36334.43 36424.48 37057.12 3653.92 38076.17 34717.10 37255.52 35448.75 367
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
PMMVS240.82 33738.86 34046.69 35253.84 37216.45 38048.61 36749.92 37237.49 36031.67 36560.97 3608.14 37656.42 37128.42 36430.72 36967.19 357
E-PMN31.77 33830.64 34135.15 35552.87 37527.67 37657.09 36547.86 37524.64 37016.40 37533.05 37111.23 37154.90 37214.46 37418.15 37222.87 371
test_method31.52 33929.28 34338.23 35427.03 3816.50 38320.94 37262.21 3654.05 37522.35 37352.50 36713.33 36747.58 37427.04 36634.04 36860.62 361
EMVS30.81 34029.65 34234.27 35650.96 37625.95 37856.58 36646.80 37624.01 37115.53 37630.68 37212.47 36854.43 37312.81 37517.05 37322.43 372
MVEpermissive26.22 2330.37 34125.89 34543.81 35344.55 37835.46 37328.87 37139.07 37818.20 37218.58 37440.18 3692.68 38147.37 37517.07 37323.78 37148.60 368
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
cdsmvs_eth3d_5k19.96 34226.61 3440.00 3620.00 3850.00 3860.00 37389.26 1670.00 3800.00 38188.61 16161.62 1480.00 3810.00 3790.00 3790.00 377
tmp_tt18.61 34321.40 34610.23 3594.82 38210.11 38134.70 36930.74 3801.48 37623.91 37226.07 37328.42 35213.41 37827.12 36515.35 3757.17 373
wuyk23d16.82 34415.94 34719.46 35858.74 36731.45 37539.22 3683.74 3836.84 3746.04 3772.70 3771.27 38224.29 37710.54 37614.40 3762.63 374
ab-mvs-re7.23 3459.64 3480.00 3620.00 3850.00 3860.00 3730.00 3860.00 3800.00 38186.72 2110.00 3850.00 3810.00 3790.00 3790.00 377
test1236.12 3468.11 3490.14 3600.06 3840.09 38471.05 3370.03 3850.04 3790.25 3801.30 3790.05 3830.03 3800.21 3780.01 3780.29 375
testmvs6.04 3478.02 3500.10 3610.08 3830.03 38569.74 3420.04 3840.05 3780.31 3791.68 3780.02 3840.04 3790.24 3770.02 3770.25 376
pcd_1.5k_mvsjas5.26 3487.02 3510.00 3620.00 3850.00 3860.00 3730.00 3860.00 3800.00 3810.00 38063.15 1250.00 3810.00 3790.00 3790.00 377
test_blank0.00 3490.00 3520.00 3620.00 3850.00 3860.00 3730.00 3860.00 3800.00 3810.00 3800.00 3850.00 3810.00 3790.00 3790.00 377
uanet_test0.00 3490.00 3520.00 3620.00 3850.00 3860.00 3730.00 3860.00 3800.00 3810.00 3800.00 3850.00 3810.00 3790.00 3790.00 377
DCPMVS0.00 3490.00 3520.00 3620.00 3850.00 3860.00 3730.00 3860.00 3800.00 3810.00 3800.00 3850.00 3810.00 3790.00 3790.00 377
sosnet-low-res0.00 3490.00 3520.00 3620.00 3850.00 3860.00 3730.00 3860.00 3800.00 3810.00 3800.00 3850.00 3810.00 3790.00 3790.00 377
sosnet0.00 3490.00 3520.00 3620.00 3850.00 3860.00 3730.00 3860.00 3800.00 3810.00 3800.00 3850.00 3810.00 3790.00 3790.00 377
uncertanet0.00 3490.00 3520.00 3620.00 3850.00 3860.00 3730.00 3860.00 3800.00 3810.00 3800.00 3850.00 3810.00 3790.00 3790.00 377
Regformer0.00 3490.00 3520.00 3620.00 3850.00 3860.00 3730.00 3860.00 3800.00 3810.00 3800.00 3850.00 3810.00 3790.00 3790.00 377
uanet0.00 3490.00 3520.00 3620.00 3850.00 3860.00 3730.00 3860.00 3800.00 3810.00 3800.00 3850.00 3810.00 3790.00 3790.00 377
FOURS195.00 1072.39 3895.06 193.84 1574.49 10991.30 15
MSC_two_6792asdad89.16 194.34 2775.53 292.99 4597.53 189.67 196.44 994.41 30
PC_three_145268.21 22592.02 1294.00 4082.09 595.98 4984.58 3596.68 294.95 8
No_MVS89.16 194.34 2775.53 292.99 4597.53 189.67 196.44 994.41 30
test_one_060195.07 771.46 5394.14 578.27 3392.05 1195.74 680.83 11
eth-test20.00 385
eth-test0.00 385
ZD-MVS94.38 2572.22 4392.67 6170.98 17187.75 2894.07 3774.01 3296.70 2584.66 3494.84 41
RE-MVS-def85.48 4993.06 5570.63 7191.88 3792.27 7673.53 13285.69 3894.45 2463.87 11682.75 5591.87 7792.50 103
IU-MVS95.30 271.25 5592.95 5166.81 23392.39 688.94 1196.63 494.85 17
OPU-MVS89.06 394.62 1575.42 493.57 794.02 3982.45 396.87 1883.77 4596.48 894.88 12
test_241102_TWO94.06 1077.24 4892.78 495.72 881.26 897.44 589.07 996.58 694.26 39
test_241102_ONE95.30 270.98 6194.06 1077.17 5193.10 195.39 1182.99 197.27 10
9.1488.26 1492.84 6091.52 4494.75 173.93 12188.57 2294.67 1775.57 2295.79 5186.77 2295.76 23
save fliter93.80 4072.35 4190.47 6291.17 11674.31 112
test_0728_THIRD78.38 3192.12 995.78 481.46 797.40 789.42 496.57 794.67 22
test_0728_SECOND87.71 3095.34 171.43 5493.49 994.23 397.49 389.08 796.41 1294.21 40
test072695.27 571.25 5593.60 694.11 677.33 4692.81 395.79 380.98 9
GSMVS88.96 226
test_part295.06 872.65 3191.80 13
sam_mvs151.32 24488.96 226
sam_mvs50.01 257
ambc75.24 28873.16 35250.51 34863.05 36287.47 21764.28 32477.81 33317.80 36489.73 25357.88 27960.64 34685.49 296
MTGPAbinary92.02 85
test_post178.90 3015.43 37648.81 27685.44 29959.25 263
test_post5.46 37550.36 25584.24 306
patchmatchnet-post74.00 34651.12 24688.60 273
GG-mvs-BLEND75.38 28781.59 29755.80 31079.32 29469.63 35167.19 30073.67 34743.24 30788.90 27050.41 31684.50 16181.45 335
MTMP92.18 3332.83 379
gm-plane-assit81.40 30053.83 32862.72 28680.94 30792.39 19063.40 228
test9_res84.90 2995.70 2692.87 92
TEST993.26 5072.96 2488.75 10691.89 9368.44 22285.00 4593.10 5474.36 2895.41 65
test_893.13 5272.57 3488.68 11191.84 9768.69 21884.87 4993.10 5474.43 2695.16 74
agg_prior282.91 5395.45 2892.70 95
agg_prior92.85 5971.94 4991.78 10084.41 5994.93 85
TestCases79.58 23785.15 23263.62 20779.83 31162.31 28960.32 33986.73 20932.02 34688.96 26850.28 31971.57 31386.15 286
test_prior472.60 3389.01 96
test_prior288.85 10275.41 9184.91 4793.54 4674.28 2983.31 4895.86 20
test_prior86.33 5292.61 6569.59 8592.97 5095.48 6093.91 50
旧先验286.56 17558.10 32087.04 3088.98 26674.07 134
新几何286.29 183
新几何183.42 13493.13 5270.71 6985.48 24557.43 32581.80 9491.98 7763.28 12092.27 19664.60 22292.99 6387.27 263
旧先验191.96 7165.79 16586.37 23493.08 5869.31 7092.74 6688.74 235
无先验87.48 14688.98 17960.00 30594.12 11967.28 19988.97 225
原ACMM286.86 164
原ACMM184.35 10093.01 5768.79 9892.44 6963.96 27381.09 10391.57 8866.06 9895.45 6167.19 20194.82 4388.81 232
test22291.50 7768.26 11584.16 23583.20 28054.63 33679.74 11591.63 8658.97 17991.42 8386.77 276
testdata291.01 23662.37 237
segment_acmp73.08 37
testdata79.97 22790.90 8664.21 19884.71 25259.27 31285.40 4092.91 6062.02 14489.08 26468.95 18491.37 8486.63 280
testdata184.14 23675.71 85
test1286.80 4792.63 6470.70 7091.79 9982.71 8571.67 4796.16 4294.50 4893.54 70
plane_prior790.08 10268.51 111
plane_prior689.84 11168.70 10660.42 172
plane_prior592.44 6995.38 6778.71 8986.32 14291.33 136
plane_prior491.00 107
plane_prior368.60 10978.44 2978.92 127
plane_prior291.25 4879.12 21
plane_prior189.90 110
plane_prior68.71 10490.38 6577.62 3786.16 146
n20.00 386
nn0.00 386
door-mid69.98 350
lessismore_v078.97 24481.01 30757.15 29165.99 35961.16 33782.82 28839.12 32891.34 22559.67 25946.92 36488.43 241
LGP-MVS_train84.50 9389.23 13368.76 10091.94 9175.37 9276.64 18291.51 8954.29 21394.91 8678.44 9183.78 17089.83 199
test1192.23 79
door69.44 353
HQP5-MVS66.98 142
HQP-NCC89.33 12689.17 8976.41 7077.23 168
ACMP_Plane89.33 12689.17 8976.41 7077.23 168
BP-MVS77.47 101
HQP4-MVS77.24 16795.11 7891.03 148
HQP3-MVS92.19 8285.99 149
HQP2-MVS60.17 175
NP-MVS89.62 11368.32 11390.24 119
MDTV_nov1_ep13_2view37.79 37175.16 32455.10 33466.53 30849.34 26653.98 30187.94 247
MDTV_nov1_ep1369.97 27183.18 26753.48 33077.10 31580.18 31060.45 30069.33 28480.44 31148.89 27586.90 28851.60 31278.51 236
ACMMP++_ref81.95 196
ACMMP++81.25 202
Test By Simon64.33 112
ITE_SJBPF78.22 25581.77 29460.57 25483.30 27669.25 20267.54 29587.20 20036.33 33887.28 28754.34 30074.62 28886.80 275
DeepMVS_CXcopyleft27.40 35740.17 38026.90 37724.59 38117.44 37323.95 37148.61 3689.77 37226.48 37618.06 37124.47 37028.83 370