COLLIDER: A Robust Training Framework for Backdoor Data

Hadi M. Dolatabadi, Sarah M. Erfani, Christopher Leckie. COLLIDER: A Robust Training Framework for Backdoor Data. In Lei Wang 0001, Juergen Gall, Tat-Jun Chin, Imari Sato, Rama Chellappa, editors, Computer Vision - ACCV 2022 - 16th Asian Conference on Computer Vision, Macao, China, December 4-8, 2022, Proceedings, Part VI. Volume 13846 of Lecture Notes in Computer Science, pages 681-698, Springer, 2022. [doi]

@inproceedings{DolatabadiEL22-0,
  title = {COLLIDER: A Robust Training Framework for Backdoor Data},
  author = {Hadi M. Dolatabadi and Sarah M. Erfani and Christopher Leckie},
  year = {2022},
  doi = {10.1007/978-3-031-26351-4_41},
  url = {https://doi.org/10.1007/978-3-031-26351-4_41},
  researchr = {https://researchr.org/publication/DolatabadiEL22-0},
  cites = {0},
  citedby = {0},
  pages = {681-698},
  booktitle = {Computer Vision - ACCV 2022 - 16th Asian Conference on Computer Vision, Macao, China, December 4-8, 2022, Proceedings, Part VI},
  editor = {Lei Wang 0001 and Juergen Gall and Tat-Jun Chin and Imari Sato and Rama Chellappa},
  volume = {13846},
  series = {Lecture Notes in Computer Science},
  publisher = {Springer},
  isbn = {978-3-031-26351-4},
}