Not All Images are Worth 16x16 Words: Dynamic Transformers for Efficient Image Recognition

Yulin Wang, Rui Huang, Shiji Song, Zeyi Huang, Gao Huang. Not All Images are Worth 16x16 Words: Dynamic Transformers for Efficient Image Recognition. In Marc'Aurelio Ranzato, Alina Beygelzimer, Yann N. Dauphin, Percy Liang, Jennifer Wortman Vaughan, editors, Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual. pages 11960-11973, 2021. [doi]

@inproceedings{WangHSHH21,
  title = {Not All Images are Worth 16x16 Words: Dynamic Transformers for Efficient Image Recognition},
  author = {Yulin Wang and Rui Huang and Shiji Song and Zeyi Huang and Gao Huang},
  year = {2021},
  url = {https://proceedings.neurips.cc/paper/2021/hash/64517d8435994992e682b3e4aa0a0661-Abstract.html},
  researchr = {https://researchr.org/publication/WangHSHH21},
  cites = {0},
  citedby = {0},
  pages = {11960-11973},
  booktitle = {Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual},
  editor = {Marc'Aurelio Ranzato and Alina Beygelzimer and Yann N. Dauphin and Percy Liang and Jennifer Wortman Vaughan},
}