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  • Data-efficient learning of geometric structures from single-view images

    Lin, Y., 2022, 123 p.

    Research output: ThesisDissertation (TU Delft)

    Open Access
    File
    16 Downloads (Pure)
  • Investigating transformers in the decomposition of polygonal shapes as point collections

    Alfieri, A., Lin, Y. & van Gemert, J. C., 2021, Proceedings - 2021 IEEE/CVF International Conference on Computer Vision Workshops, ICCVW 2021: Proceedings. O'Conner, L. (ed.). Piscataway: IEEE , p. 2076-2085 10 p. 9607442. (Proceedings of the IEEE International Conference on Computer Vision; vol. 2021-October).

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

  • Semi-Supervised Lane Detection With Deep Hough Transform

    Lin, Y., Pintea, S-L. & van Gemert, J., 2021, 2021 IEEE International Conference on Image Processing (ICIP): Proceedings. Piscataway: IEEE , p. 1514-1518 5 p. 9506299

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

    Open Access
    File
    10 Downloads (Pure)
  • Deep Hough-Transform Line Priors

    Lin, Y., Pintea, S. & van Gemert, J. C., 2020, Computer Vision – ECCV 2020 - 16th European Conference, 2020, Proceedings. Vedaldi, A., Bischof, H., Brox, T. & Frahm, J-M. (eds.). European Conference on Computer Vision ECCV 2020: Computer Vision – ECCV 2020: Springer, Vol. 12367. p. 323-340 18 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12367 LNCS).

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

    Open Access
    8 Citations (Scopus)