Laser & Optoelectronics Progress, Volume. 59, Issue 18, 1810007(2022)

Real-Time Indoor Scene Layout Estimation Based on Improved Lightweight Network

Youjun Yue1, Jie Zhang1、*, Hui Zhao1,2, and Hongjun Wang1
Author Affiliations
  • 1Tianjin Key Laboratory of Control Theory & Applications in Complicated Systems, School of Electrical and Electronic Engineering, Tianjin University of Technology, Tianjin 300384, China
  • 2College of Engineering and Technology, Tianjin Agricultural University, Tianjin 300392, China
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    References(25)

    [2] Ji Z, Kong Q K, Wang J. Object detection algorithm guided by dual attention models[J]. Laser & Optoelectronics Progress, 57, 061008(2020).

    [4] Li X T, Dang J W, Wang Y P et al. Augmented reality recognition registration method based on text features[J]. Laser & Optoelectronics Progress, 57, 021502(2020).

    [6] Coughlan J M, Yuille A L. The manhattan world assumption: regularities in scene statistics which enable Bayesian inference[C], 845-851(2000).

    [21] Huang R Z, Meng Q H, Liu Y B. Real-time indoor layout estimation method based on multi-task supervised learning[J]. Laser & Optoelectronics Progress, 58, 1410023(2021).

    [23] Wang X C, Liu H H, Niu Y M. Indoor RGB-D image semantic segmentation based on dual-stream weighted Gabor convolutional network fusion[J]. Acta Optica Sinica, 40, 1910001(2020).

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    Youjun Yue, Jie Zhang, Hui Zhao, Hongjun Wang. Real-Time Indoor Scene Layout Estimation Based on Improved Lightweight Network[J]. Laser & Optoelectronics Progress, 2022, 59(18): 1810007

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    Paper Information

    Category: Image Processing

    Received: Jul. 8, 2021

    Accepted: Jul. 28, 2021

    Published Online: Aug. 31, 2022

    The Author Email: Zhang Jie (2580690058@qq.com)

    DOI:10.3788/LOP202259.1810007

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