1 citations · 1 across the 2 of their papers we have counts for
Showing cs.CVShow all
3 papers · 1 filter
cs.CV2023★ 3 cited
Supervised Masked Knowledge Distillation for Few-Shot Transformers
Han Lin, Guangxing Han, Jiawei Ma +3
Vision Transformers (ViTs) emerge to achieve impressive performance on many data-abundant computer vision tasks by capturing long-range dependencies among local features. However,…
cs.CV2022★ 1 cited
Knowledge Prompting for Few-shot Action Recognition
Yuheng Shi, Xinxiao Wu, Hanxi Lin
Few-shot action recognition in videos is challenging for its lack of supervision and difficulty in generalizing to unseen actions. To address this task, we propose a simple yet eff…
cs.CV2021
Adaptive Recursive Circle Framework for Fine-grained Action Recognition
Hanxi Lin, Xinxiao Wu, Jiebo Luo
How to model fine-grained spatial-temporal dynamics in videos has been a challenging problem for action recognition. It requires learning deep and rich features with superior disti…