• Optics and Precision Engineering
  • Vol. 31, Issue 5, 656 (2023)
Xianying LIU1, Qiuxia WU1,*, Wenxiong KANG2, and Yuqiong LI3
Author Affiliations
  • 1School of Software Engineering, South China University of Technology, Guangzhou50006, China
  • 2School of Automation Science and Engineering, South China University of Technology, Guangzhou510641, China
  • 3Institute of Mechanics, Chinese Academy of Sciences, Beijing100190, China
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    DOI: 10.37188/OPE.20233105.0656 Cite this Article
    Xianying LIU, Qiuxia WU, Wenxiong KANG, Yuqiong LI. Rotation-invariant 2D views-3D point clouds auto-encoder[J]. Optics and Precision Engineering, 2023, 31(5): 656 Copy Citation Text show less
    References

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    [6] 6杨军, 李博赞. 基于自注意力特征融合组卷积神经网络的三维点云语义分割[J]. 光学 精密工程, 2022, 30(7): 840-853. doi: 10.37188/OPE.20223007.0840YANGJ, LIB Z. Semantic segmentation of 3D point cloud based on self-attention feature fusion group convolutional neural network[J]. Opt. Precision Eng., 2022, 30(7): 840-853.(in Chinese). doi: 10.37188/OPE.20223007.0840

    [7] 7陈俊英, 白童垚, 赵亮. 互注意力融合图像和点云数据的3D目标检测[J]. 光学 精密工程, 2021, 29(9): 2247-2254. doi: 10.37188/OPE.20212909.2247CHENJ Y, BAIT Y, ZHAOL. 3D object detection based on fusion of point cloud and image by mutual attention[J]. Opt. Precision Eng., 2021, 29(9): 2247-2254.(in Chinese). doi: 10.37188/OPE.20212909.2247

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    Xianying LIU, Qiuxia WU, Wenxiong KANG, Yuqiong LI. Rotation-invariant 2D views-3D point clouds auto-encoder[J]. Optics and Precision Engineering, 2023, 31(5): 656
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