About Me

I am currently a postdoc fellow, supervised by Prof. Kin-Man Lam, in the department of Electrical and Electronic Engineering, the Hong Kong Polytechnic University.

My research interests include image/video processing, restoration and enhancement (e.g., image/video super-resolution, image/video denoising, high dynamic range imaging, etc.), machine learning (e.g., bayesian machine learning, domain adaptation and generalization, robustness, etc.), deep generative models (e.g., diffusion models and flow matching), and AIGC-related topics.

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Interests
  • Image/Video Processing, Restoration, and Enhancement
  • SDE-based Generative Models (e.g., diffusion models, flow models, etc.)
  • Domain Adaptation and Robustness
  • Signal Processing Methods in Finance.
Education

  • Ph.D., Department of Electronic and Information Engineering, 2018.09-2022.10

    The Hong Kong Polytechnic University (PolyU)

  • M.S.c in Electronic and Information Engineering (with distinction), 2016.09-2018.03

    The Hong Kong Polytechnic University (PolyU)

  • BSc in Telecommunication Engineering, 2012.09-2016.06

    Guangdong University of Technology

News

  1. Jun Xiao, Zihang Lyu, Cong Zhang, Yakun Ju, Changjian Shui, and Kin-Man Lam. ``Towards Progressive Multi-Frequency Representation for Image Warping “, in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024.

  2. Jun Xiao, Qian Ye, Tianshan Liu, Cong Zhang, and Kin-Man Lam, ``Deep Progressive Feature Aggregation Network for Multi-frame High Dynamic Range Imaging”, Neurocomputing, 2024.

  3. Jun Xiao, Qian Ye, Rui Zhao, Kin-Man Lam, and Kao Wan, ``Deep Multi-scale Feature Mixture Model for Image Super-resolution with Multiple-Focal-length Degradation", Signal Processing: Image Communication, 2024.

  4. I co-organize the workshop “Photography Measurement and Imaging in the Deep Learning Era” in the 20th IEEE International Conference on Ubiquitous Intelligence and Computing (UIC 2023)

Publications

Cuixin Yang, Jun Xiao, Cong Zhang, Kin-Man Lam (2023). Improving Robustness of Single Image Super-Resolution Models with Monte Carlo Method. In ICIP.

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Cong Zhang, Tianshan Liu, Jun Xiao, Kin-Man Lam, Qi Wang (2023). Boosting Object Detectors via Strong-Classification Weak-Localization Pretraining in Remote Sensing Imagery. In IEEE Transactions on Instrumentation and Measurement (TIM).

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Jun Xiao, Xinyang Jiang, Ningxin Zheng, Huan Yang, Yifan Yang, Yuqing Yang, Dongsheng Li, Kin-Man Lam (2023). Online Video Super-Resolution with Convolutional Kernel Bypass Grafts. In IEEE Transaction on Multimedia (TMM).

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Yakun Ju, Kin-Man Lam, Jun Xiao, Cong Zhang, Cuixin Yang, Junyu Dong (2023). Efficient Feature Fusion for Learning-based Photometric Stereo. In ICASSP.

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Jun Xiao, Qian Ye, Rui Zhao, Kin-Man Lam, Kao Wan (2021). Self-feature Learning: An Efficient Deep Lightweight Network for Image Super-resolution. In ACM-MM.

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Qian Ye, Jun Xiao, Kin-Man Lam, Takayuki Okatani (2021). Progressive and Selective Fusion Network for High Dynamic Range Imaging. In ACM-MM.

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Jun Xiao, Tianshan Liu, Rui Zhao, Kin-Man Lam (2021). Balanced distortion and perception in single-image super-resolution based on optimal transport in wavelet domain. In Neurocomputing.

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Rui Zhao, Tianshan Liu, Jun Xiao, Kin-Man Lam (2021). Invertible image decolorization. In IEEE Transactions on Image Processing (TIP).

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Jun Xiao, Wenqi Jia, Kin-Man Lam (2021). Feature redundancy mining: Deep light-weight image super-resolution model. In ICASSP.

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Jun Xiao, Rui Zhao, Kin-Man Lam (2021). Bayesian sparse hierarchical model for image denoising. In Signal Processing:Image Communication.

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Rui Zhao, Tianshan Liu, Jun Xiao, Kin-Man Lam (2020). Deep multi-task learning for facial expression recognition and synthesis based on selective feature sharing. In ICPR.

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Tianshan Liu, Rui Zhao, Jun Xiao, Kin-Man Lam (2020). Progressive Motion Representation Distillation With Two-Branch Networks for Egocentric Activity Recognition. In Signal Processing Letter.

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Jun Xiao, Rui Zhao, Shun-Cheung Lai, Wenqi Jia, Kin-Man Lam (2019). Deep Progressive Convolutional Neural Network for Blind Super-Resolution With Multiple Degradations. In ICIP.

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Experience

 
 
 
 
 
The Hong Kong Polytechnic University
Postdoc Fellow (the research talent hub scheme)
The Hong Kong Polytechnic University
Oct 2022 – Present Hong Kong
focus on research in image/video processing, high-dimensional signal processing, and diffusion models.
 
 
 
 
 
Microsoft Research Aisa
Computer Vision Researcher in MSRA
Microsoft Research Aisa
Sep 2021 – Jan 2022 Shanghai

Responsibilities include:

  • The core member in the project ``online video restoration and enhancement system" is responsible for investigating deep spatial-temporal models (i.e., RNN, LSTM, Transformer, etc.) for real-time video processing.
  • Proposed a novel knowledge transfer method based on the optimal transport theory. The performance of the lightweight models can be improved by 0.15 dB without increasing model complexity. The proposed method can significantly accelerate the running speed by 400%.

Services

Journal Reviwer

  • IEEE Transactions on Circuits and Systems for Video Technology.
  • Knowledge-based Systems
  • Information Fusion
  • Pattern Recognition

Conference Reviwer

  • ECCV: 2024
  • ACM-MM: 2022, 2023, 2024
  • WACV: 2023
  • ACCV 2022
  • VCIP 2020, 2022