A survey on weakly supervised 3D point cloud semantic segmentation

Article Properties
  • Language
    English
  • DOI (url)
    10.1049/cvi2.12250
  • Publication Date
    2023/11/02
  • Journal
    IET Computer Vision
  • Indian UGC (journal)
  • Refrences
    73
  • Jingyi Wang College of Systems Engineering National University of Defense Technology Changsha China ORCID (unauthenticated)
  • Yu Liu College of Systems Engineering National University of Defense Technology Changsha China
  • Hanlin Tan College of Systems Engineering National University of Defense Technology Changsha China
  • Maojun Zhang College of Systems Engineering National University of Defense Technology Changsha China
Abstract
Cite
Wang, Jingyi, et al. “A Survey on Weakly Supervised 3D Point Cloud Semantic Segmentation”. IET Computer Vision, vol. 18, no. 3, 2023, pp. 329-42, https://doi.org/10.1049/cvi2.12250.
Wang, J., Liu, Y., Tan, H., & Zhang, M. (2023). A survey on weakly supervised 3D point cloud semantic segmentation. IET Computer Vision, 18(3), 329-342. https://doi.org/10.1049/cvi2.12250
Wang, Jingyi, Yu Liu, Hanlin Tan, and Maojun Zhang. “A Survey on Weakly Supervised 3D Point Cloud Semantic Segmentation”. IET Computer Vision 18, no. 3 (2023): 329-42. https://doi.org/10.1049/cvi2.12250.
Wang J, Liu Y, Tan H, Zhang M. A survey on weakly supervised 3D point cloud semantic segmentation. IET Computer Vision. 2023;18(3):329-42.
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Refrences
Title Journal Journal Categories Citations Publication Date
Joint learning of 2d‐3d weakly supervised semantic segmentation 2022
Pointnet++: deep hierarchical feature learning on point sets in a metric space 2017
Attention is all you need 2017
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2022
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2022