Jie Yang 杨杰

PhD Student

Computer and Information Engineering
The Chinese University of Hong Kong, Shenzhen

Email: jieyang5@link.cuhk.edu.cn

Biography

I am a PhD student since 2021.9, at The Chinese University of Hong Kong, Shenzhen, co-supervised by Prof. Ruimao Zhang and Prof. Zhen Li.

My long-term research goal is to develop intelligent machines that can actively perceive, analyze, and interpret human states, behaviors, and underlying motivations in dynamic scenes.

News

[2024.02.27] One paper is accepted to CVPR2024.
[2023.10.13] We present UniPose to detect any keypoints of any objects.
[2023.07.14] One paper is accepted to ICCV2023.
[2023.03.02] Two papers are accepted to MIDL2023 and one is rated as an oral presentation.
[2023.02.28] One paper is accepted to CVPR2023.
[2023.01.21] One paper is accepted to ICLR2023.
[2022.09.17] One paper is accepted to NeurIPS2022.

Selected Publications [Google Scholar]

UniPose: Detecting Any Keypoints
Jie Yang, Ailing Zeng, Ruimao Zhang, Lei Zhang.
arXiv:2310.08530, Technical Report, 2023.

Open-World Human-Object Interaction Detection via Multi-modal Prompts
Jie Yang, Bingliang Li, Ailing Zeng, Lei Zhang, Ruimao Zhang.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024.

Neural Interactive Keypoint Detection
Jie Yang, Ailing Zeng, Feng Li, Shilong Liu, Ruimao Zhang, Lei Zhang.
IEEE International Conference on Computer Vision (ICCV), 2023.

Semantic Human Parsing via Scalable Semantic Transfer over Multiple Label Domains
Jie Yang, Chaoqun Wang, Zhen Li, Junle Wang, Ruimao Zhang.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.

Explicit Box Detection Unifies End-to-End Multi-Person Pose Estimation
Jie Yang, Ailing Zeng, Shilong Liu, Feng Li, Ruimao Zhang, Lei Zhang.
International Conference on Learning Representations (ICLR), 2023.

Toward Unpaired Multi-modal Medical Image Segmentation via Learning Structured Semantic Consistency
Jie Yang, Ye Zhu, Chaoqun Wang, Zhen Li, Ruimao Zhang.
International Conference on Medical Imaging with Deep Learning (MIDL), 2023.

Honors & Awards

The First Prize Scholarship, 2018，2019，2020.
National Scholarship, 2018