Journal of Infrared and Millimeter Waves, Volume. 42, Issue 6, 906(2023)

Depth estimation of thermal infrared images based on self-supervised learning

Meng DING1、*, Song GUAN2, Shuai LI1, Kuai-Kuai YU2, and Yi-Ming XU1
Author Affiliations
  • 1College of Civil Aviation,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China
  • 2Science and Technology on Electro-Optical Information Security Control Laboratory,Tianjin 300308,China
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    References(30)

    [1] Huang J, Wang C, Liu Y et al. The progress of monocular depth estimation technology[J]. Journal of Image and Graphics, 24, 2081-2097(2019).

    [2] Jia D, Zhu N D, Yang N H et al. Image matching methods[J]. Journal of Image and Graphics, 24, 677-699(2019).

    [3] Dong X, Garratt A M A, Anavatti G S et al. Towards Real-Time Monocular Depth Estimation for Robotics: A Survey[J]. IEEE Transactions on Intelligent Transportation Systems, 23, 16940-16961(2022).

    [4] Liu Y, Jiang J, Sun J et al. A survey of depth estimation based on computer vision[C], 135-141.

    [5] Ming Y, Meng X, Fan C et al. Deep learning for monocular depth estimation: A review[J]. Neurocomputing, 438, 14-33(2021).

    [6] Masoumian A, Rashwan H A, Cristiano J et al. Monocular Depth Estimation Using Deep Learning: A Review[J]. Sensors, 22, 5353(2022).

    [7] Qi X, Liao R, Liu Z et al. Geonet: Geometric neural network for joint depth and surface normal estimation[C], 283-291.

    [8] Ummenhofer B, Zhou H, Uhrig J et al. Demon: Depth and motion network for learning monocular stereo[C], 5038-5047.

    [9] Luo Y, Ren J, Lin M et al. Single view stereo matching[C], 155-163.

    [10] Xie J, Girshick R, Farhadi A. Deep3d: Fully automatic 2d-to-3d video conversion with deep convolutional neural networks[C], 842-857.

    [11] Zhan H, Garg R, Weerasekera C S et al. Unsupervised learning of monocular depth estimation and visual odometry with deep feature reconstruction[C], 340-349.

    [12] Ding M, Jiang X Y. Scene Depth Estimation Based on Monocular Vision in Advanced Driving Assistance System[J]. Acta Optica Sinica, 40, 1715001-9(2020).

    [13] Garg R, Bg V K, Carneiro G et al. Unsupervised cnn for single view depth estimation: Geometry to the rescue[C], 740-756.

    [14] Godard C, Mac Aodha O, Brostow G J. Unsupervised monocular depth estimation with left-right consistency[C], 270-279.

    [15] Tosi F, Aleotti F, Poggi M et al. Learning monocular depth estimation infusing traditional stereo knowledge[C], 9799-9809.

    [16] Zhou T, Brown M, Snavely N et al. Unsupervised learning of depth and ego-motion from video[C], 1851-1858.

    [17] Lai H Y, Tsai Y H, Chiu W C. Bridging stereo matching and optical flow via spatiotemporal correspondence[C], 1890-1899.

    [18] Zou Y, Luo Z, Huang J B. Df-net: Unsupervised joint learning of depth and flow using cross-task consistency[C], 36-53.

    [19] Godard C, Mac Aodha O, Firman M et al. Digging into self-supervised monocular depth estimation[C], 3828-3838.

    [20] Li X G, Cao M T, Li B et al. GPNet: Lightweight infrared image target detection algorithm[J]. Journal of Infrared and Millimeter Waves, 41, 1092-1101(2022).

    [22] He Y, Deng B, Wang H et al. Infrared machine vision and infrared thermography with deep learning: A review[J]. Infrared physics & technology, 116, 2021.

    [23] Li X, Ding M, Wei D H et al. Depth estimation method based on monocular infrared image in VDAS[J]. Systems Engineering and Electronics, 43, 1210-1217(2021).

    [24] Wang Z, Bovik A C, Sheikh H R et al. Image Quality Assessment: From Error Visibility to Structural Similarity[J]. IEEE Transactions on Image Processing, 13, 600-612(2004).

    [25] Long J, Shelhamer E, Darrell T. Fully convolutional networks for semantic segmentation[C], 3431-3440(2015).

    [26] Zhou Z, Rahman Siddiquee M M, Tajbakhsh N et al. Unet++: A nested u-net architecture for medical image segmentation[C], 3-11(2018).

    [27] Wang J, Sun K, Cheng T et al. Deep high-resolution representation learning for visual recognition[J]. IEEE transactions on pattern analysis and machine intelligence, 43, 3349-3364(2020).

    [28] Hu J, Shen L, Sun G. Squeeze-and-excitation networks[C], 7132-7141.

    [29] Wang Q, Wu B, Zhu P et al. ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks[C], 11534-11542.

    [30] Lyu X, Liu L, Wang M et al. HR-depth: High resolution self-supervised monocular depth estimation[C], 35, 2294-2301.

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    Meng DING, Song GUAN, Shuai LI, Kuai-Kuai YU, Yi-Ming XU. Depth estimation of thermal infrared images based on self-supervised learning[J]. Journal of Infrared and Millimeter Waves, 2023, 42(6): 906

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    Paper Information

    Category: Research Articles

    Received: Dec. 13, 2022

    Accepted: --

    Published Online: Dec. 26, 2023

    The Author Email: Meng DING (nuaa_dm@nuaa.edu.cn)

    DOI:10.11972/j.issn.1001-9014.2023.06.024

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