Currently, I am interested in machine learning, in particular meta-learning, self-supervised learning and multi-task learning with applications in vision and robotics. The following is my publications displayed in chronological order.
- Master Thesis: Universal Representations: Towards Multi-task Learning & Beyond.
*Awarded as distinguished thesis, Department of Computing at Imperial College.
- Shape Adaptor: A Learnable Resizing Module
European Conference on Computer Vision (ECCV), 2020
Shikun Liu, Zhe Lin, Yilin Wang, Jianming Zhang, Federico Perazzi, and Edward Johns
[paper] [arxiv] [code] [slide]
- Self-Supervised Generalisation with Meta Auxiliary Learning
Advances in Neural Information Processing Systems (NeurIPS), 2019
Shikun Liu, Andrew J. Davison and Edward Johns
[paper] [arxiv] [code] [poster] [slide]
- End-to-End Multi-task Learning with Attention
Computer Vision and Pattern Recognition (CVPR), 2019
Shikun Liu, Edward Johns, and Andrew J. Davison
[paper] [arxiv] [code]
- Learning a Hierarchical Latent-Variable Model of 3D Shapes
International Conference on 3D Vision (3DV), 2018 [ORAL]
Shikun Liu, C. Lee Giles, and Alexander G. Ororbia II.
[paper] [supplementary] [arxiv] [code] [project page]