Kun-Yu Lin

I am now a post-doctoral research fellow at the University of Hong Kong, under the supervision of Prof. Kai Han. I obtained my PhD degree from Sun Yat-set University, under the supervision of Prof. Wei-Shi Zheng. Prior to this, I obtained my Bachelor's degree and Master degree from Sun Yat-Sen University. During my PhD, I was fortunate to have the opportunity to study as a visiting student at MMLab@NTU, under the supervision of Prof. Chen Change Loy and Prof. Henghui Ding. My research interests include computer vision and machine learning.

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Selected Works

Most of my research works are about human video understanding, transferable, generalizable and trustworthy deep learning, and robot learning. Some works are highlighted. # denotes equal contributions.

The first benchmark, named XOV-Action, for the cross-domain open-vocabulary action recognition task, and a simple yet effective method to address the scene bias for the task.

A new paradigm utilizing paired human-robot videos to adapt human-data pretrained models for robotic manipulation tasks.

A human-centric video network to address the context bias in domain adaptive action recognition.

A diversity-aware video network to address the bias to domain-specific information in video domain generalization.

A new event-guided paradigm to address the semantic gap between observed states and unobserved actions for procedure planning in instructional videos.

An asymmetric adaptation paradigm for few-shot domain adaptive object detection.

A new vision transformer architecture for efficient and effective visual understanding.

A theorectical method to balancing in-distribution generalization and out-of-distribution detection.

A theorectical method based on implicit generators to improve out-of-distribution detection.

A simple yet effective method based on cycle transformation to filter out outlier classes in partial domain adaptation.

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