About Me

I received the PhD degree from National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences (CASIA) in 2009 under the supervision of Prof. Tieniu Tan. From 2009 to 2010, I was a research fellow working with Prof. Dacheng Tao at the School of Computer Science and Engineering, Nanyang Technological University (NTU). In September 2010, I joined the NLPR, Institute of Automation, Chinese Academy of Sciences(CASIA). In 2019, I worked as a visiting researcher under the direction of Prof. Song-Chun Zhu at University of California, Los Angeles (UCLA). Now, I am an Associate Professor at the Center for Research on Intelligent Perception and Computing (CRIPAC) and NLPR, CASIA.

Research Interests

My research field is computer vision and pattern recognition. The main research interests include human action and activity recognition, human attribute recognition, person re-identification, and large-scale person retrieval. Nowdays, the problem of alignment between machine learning and human values has been very essential for a safe, trusty and evolutionary human-machine collaboration system. Here is a Chinese translation on The Alignment Problem by BRIAN CHRISTIAN which is a comprehensive and insightful review on the AI history from the perspective of human-AI alignment. And our group also launch a new key R&D programme on human machine collaboration with the background of autonomous driving. Any discussions are welcome!

Selected Publications (My Page on Google Scholar)

Journal Papers

  1. D. Li, Z. Zhang, C. Shan, L. Wang, “Incremental Pedestrian Attribute Recognition via Dual Uncertainty-Aware Pseudo-Labeling,” IEEE Transactions on Information Forensics and Security (TIFS), 2023.
  2. W. Chen, Z. Zhang, W. Wang, L. Wang, Z. Wang, and T. Tan, “Few-Shot Learning with Unsupervised Part Discovery and Part-Aligned Similarity,” Pattern Recognition (PR), Volume 133, 2023.
  3. Y. Song, Z. Zhang, C. Shan, L. Wang, “Constructing Stronger and Faster Baselines for Skeleton-based Action Recognition,” IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), VOL. 45, NO. 2, 2023. [paper] [code]
  4. Y-F. Zhang, Z. Zhang, D. Li, Z. Jia, L. Wang and T. Tan, “Learning Domain Invariant Representations for Generalizable Person Re-Identifification,” IEEE Transactions on Image Processing (TIP), vol. 23, pp.509 - 523, 2022
  5. Z. Jia, Z. Zhang, L. Wang, C. Shan and T. Tan, “Deep Unbiased Embedding Transfer for Zero-shot Learning,” IEEE Transactions on Image Processing (TIP), 2019. [paper]
  6. D. Li, Z. Zhang, K. Yu, K. Huang and T. Tan, “ISEE: An Intelligent Scene Exploration and Evaluation Platform for Large-Scale Visual Surveillance,” IEEE Transactions on Parallel and Distributed Systems (TPDS), 2019. [paper]
  7. Y. Li, Z. Zhang, L. Wang, and T. Tan, “MAPNet: Multi-modal Attentive Pooling Network for RGB-D Indoor Scene Classification,” Pattern Recognition (PR), 2019. [paper]
  8. D. Li, Z. Zhang, X. Chen, and K. Huang, “A Richly Annotated Pedestrian Dataset for Person Retrieval in Real Surveillance Scenarios,” IEEE Trans. on Image Processing (IEEE TIP), Vol. 28, Issue: 4, pp. 1575 – 1590, 2019. [paper][website of dataset]
  9. Z. Zhang and D. Tao, “Slow Feature Analysis for Human Action Recognition,” IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), vol.34, no. 3, pp. 436-450, 2012. [paper]
  10. Z. Zhang, T. Tan and K. Huang, “An Extended Grammar System for Learning and Recognizing Complex Visual Events,” IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), vol. 33, no. 2, pp. 240-255, 2011. [paper]

Conference Papers

  1. Y-F. Zhang, X. Wang, K. Jin, K. Yuan, Z. Zhang, L. Wang, R. Jin, and T. Tan, “AdaNPC: Exploring Non-Parametric Classifier for Test-Time Adaptation,” International Conference on Machine Learning (ICML), 2023.
  2. W. Chen, C. Si, Z. Zhang, L. Wang, Z. Wang and T. Tan, “Semantic Prompt for Few-Shot Learning,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
  3. Y-F. Zhang, X. Wang, J. Liang, Z. Zhang, L. Wang, R. Jin and T. Tan, “Free Lunch for Domain Adversarial Training: Environment Label Smoothing,” International Conference on Learning Representation (ICLR), 2023
  4. W. Chen, Z. Zhang, W. Wang, L. Wang, Z. Wang, and T. Tan, “Cross-Domain Cross-Set Few-Shot Learning via Learning Compact and Aligned Representations,” European Conference on Computer Vision (ECCV), 2022
  5. Y. Song, Z. Zhang, C. Shan, and L. Wang, “Stronger, Faster and More Explainable: A Graph Convolutional Baseline for Skeleton-based Action Recognition,” ACM Conference on Multimedia (MM), 2020.
  6. W. Yang, H. Huang, Z. Zhang, X. Chen, and K. Huang, “Towards Rich Feature Discovery with Class Activation Maps Augmentation for Person Re-Identification,” IEEE Conference on Computre Vision and Pattern Recognition (CVPR), 2019. [paper]
  7. H. Huang, D. Li, Z. Zhang, X. Chen, and K. Huang, “Adversarially Occluded Samples For Person Re-identification,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
  8. D. Li, X. Chen, Z. Zhang, and K. Huang, “Learning Deep Context-aware Features over Body and Latent Parts for Person Re-identification,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
  9. Z. Zhang, K. Huang, T. Tan, P. Yang and J. Li, “ReD-SFA: Relation Discovery Based Slow Feature Analysis for Trajectory Clustering,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 752-760, 2016. [paper]
  10. Z. Zhang, K. Huang, T. Tan and L. Wang, “Trajectory Series Analysis based Event Rule Induction for Visual Surveillance,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2007.

Other Hobbies

A slow runnner (Compeleted the Beijing Marathan in 2014 and 2015)

A drum player (Exercising at Simon Drum Community since 2016)

My page on NetEase Cloud Music


Thanks Ankit Sultana for Page design!