Liu Jun

Biography

Jun Liu received the PhD degree from Nanyang Technological University, the MSC degree from Fudan University, and the BEng degree from Central South University. His research interests include computer vision and artificial intelligence. His works have been published in premier computer vision journals and conferences, including TPAMI, CVPR, ICCV, and ECCV. He is listed in the top 2% scientists worldwide identified by Stanford University in 2021-2023. He is an Associate Editor of IEEE Transactions on Image Processing and IEEE Transactions on Biometrics, Behavior, and Identity Science, and a regular Area Chair of ICML, NeurIPS, ICLR, CVPR, and WACV, etc.

Open Positions

I am currently looking for motivated PhD students, Research Assistants, and Visiting Students with strong interests in computer vision and machine learning. If interested, kindly contact me via email.

We are hiring PhD Students, Postdoc Fellows and Research Assistants.

Selected Publications in 2023

For a full list of my publications, please see my Google Scholar Page.

1. Lanyun Zhu, Tianrun Chen, Jianxiong Yin, Simon See, Jun Liu, Continual Semantic Segmentation with Automatic Memory Sample Selection, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
2. Li Xu, Mark He Huang, Xindi Shang, Zehuan Yuan, Ying Sun, Jun Liu, Meta Compositional Referring Expression Segmentation, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
3. Tianjiao Li, Lin Geng Foo, Ping Hu, Xindi Shang, Hossein Rahmani, Zehuan Yuan, Jun Liu, Token Boosting for Robust Self-Supervised Visual Transformer Pre-training, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
4. Lin Geng Foo, Tianjiao Li, Hossein Rahmani, Qiuhong Ke, Jun Liu, Unified Pose Sequence Modeling, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
5. Jia Gong, Lin Geng Foo, Zhipeng Fan, Qiuhong Ke, Hossein Rahmani, Jun Liu, DiffPose: Toward More Reliable 3D Pose Estimation, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
6. Lin Geng Foo, Jia Gong, Zhipeng Fan, Jun Liu, System-status-aware Adaptive Network for Online Streaming Video Understanding, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
7. Haoxuan Qu, Yujun Cai, Lin Geng Foo, Ajay Kumar, Jun Liu, A Characteristic Function-based Method for Bottom-up Human Pose Estimation, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
8. Lanyun Zhu, Tianrun Chen, Jianxiong Yin, Simon See, Jun Liu, Learning Gabor Texture Features for Fine-Grained Recognition, International Conference on Computer Vision (ICCV), 2023.
9. Qihao Zhao, Chen Jiang, Wei Hu, Fan Zhang, Jun Liu, MDCS: More Diverse Experts with Consistency Self-distillation for Long-tailed Recognition, International Conference on Computer Vision (ICCV), 2023.
10. Lin Geng Foo, Jia Gong, Hossein Rahmani, Jun Liu, Distribution-Aligned Diffusion for Human Mesh Recovery, International Conference on Computer Vision (ICCV), 2023.
11. Kian Eng Ong, Xun Long Ng, Wenjie Ai, Yanchao Li, Kuangyi Zhao, Si Yong Yeo, Jun Liu, Chaotic World: A Large and Challenging Benchmark for Human Behavior Understanding in Chaotic Events, International Conference on Computer Vision (ICCV), 2023.
12. Duo Peng, Ping Hu, Qiuhong Ke, Jun Liu, Diffusion-based Image Translation with Label Guidance for Domain Adaptive Semantic Segmentation, International Conference on Computer Vision (ICCV), 2023.
13. Rui Li, Baopeng Zhang, Jun Liu, Wei Liu, Jian Zhao, Zhu Teng, Heterogeneous Diversity Driven Active Learning for Multi-object Tracking, International Conference on Computer Vision (ICCV), 2023.
14. Ming Li, Xiangyu Xu, Hehe Fan, Jun Liu et al., STPrivacy: Spatio-Temporal Privacy-Preserving Action Recognition, International Conference on Computer Vision (ICCV), 2023.
15. Haoxuan Qu, Xiaofei Hui, Yujun Cai, Jun Liu, LMC: Large Model Collaboration for Training-Free Open-Set Object Recognition, Annual Conference on Neural Information Processing Systems (NeurIPS), 2023.
16. Duo Peng, Li Xu, Qiuhong Ke, Ping Hu, Jun Liu, Joint Attribute and Model Generalization Learning for Privacy-Preserving Action Recognition, Annual Conference on Neural Information Processing Systems (NeurIPS), 2023.
17. Qihao Zhao, Yangyu Huang, Wei Hu, Fan Zhang, Jun Liu, MixPro: Data Augmentation with MaskMix and Progressive Attention Labeling for Vision Transformer, International Conference on Learning Representations (ICLR), 2023.
18. Jianhong Pan, Lin Geng Foo, Qichen Zheng, Zhipeng Fan, Hossein Rahmani, Qiuhong Ke, Jun Liu, GradMDM: Adversarial Attack on Dynamic Networks, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.
19. Zehua Sun, Qiuhong Ke, Hossein Rahmani, Mohammed Bennamoun, Gang Wang, Jun Liu, Human Action Recognition from Various Data Modalities: A Review, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.
20. Haoxuan Qu, Lin Geng Foo, Yanchao Li, Jun Liu, Towards More Reliable Confidence Estimation, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.
21. Siyuan Yang, Jun Liu, Shijian Lu, Er Meng Hwa, Yongjian Hu, Alex C. Kot, Self-Supervised 3D Action Representation Learning with Skeleton Cloud Colorization, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.

Datasets and Resources

• SUTD TrafficQA (traffic/video question answering/video reasoning)
• UAV-Human (drone/action recognition/pose estimation/human ReID)
• Animal Kingdom (animal action recognition/animal pose estimation/video grounding)
• Chaotic World (action recognition/scene graph generation/video grounding)