Chen Feng

冯     晨

PhD Student
in Image and Video Processing
School of Computer Science
University of Bristol

1.23, 1 Cathedral Square
Bristol BS1 5DD, United Kingdom
chen.feng@bristol.ac.uk





About

I am currently a PhD student in Visual Information Laboratory within the School of Computer Science, University of Bristol under the supervision of Prof. David Bull and Dr Aaron Zhang, funded by the Amazon Research Awards 2023 . My main research interests include video processing and video quality assessment.

I obtained an MSc (Distinction) in image and video communication and signal processing from the University of Bristol, Where I researched on Video Compression with CNN-based Post Processing in Visual Information Laboratory under the supervision of Prof. David Bull. I completed BEng in Measuring and Control Technology at the School of Automation and Electrical Engineering at the University of Science and Technology Beijing under the supervision of Prof. Qing Li.

My current research is mainly focused on deep video quality assessment and deep video compression.

News & Activities

Research Areas and Projects

Publication


arXiv Papers
  1. BVI-Artefact: An Artefact Detection Benchmark Dataset for Streamed Videos. [paper][project]
    C. Feng, D. Danier, F. Zhang, and D. R. Bull, arXiv:2312.08859, 2023

  2. RankDVQA-mini: Knowledge Distillation-Driven Deep Video Quality Assessment. [paper][project]
    C. Feng, D. Danier, H. Wang, F. Zhang, and D. R. Bull, arXiv:2312.08864, 2023

  3. Full-reference Video Quality Assessment for User Generated Content Transcoding. [paper][project]
    Z. Qi, C. Feng, D. Danier, F. Zhang, X. Xu, S. Liu, and D. R. Bull, arXiv:2312.12317, 2023

  4. Enhancing HDR Video Compression through CNN-based Effective Bit Depth Adaptation. [paper][project]
    C. Feng, F. Zhang, and D. R. Bull, arXiv:2202.08595, 2022

  5. Enhancing VVC with Deep Learning based Multi-Frame Post-Processing. [paper][project]
    C. Feng, F. Zhang, and D. R. Bull, arXiv:2202.08595, 2022

Journal Papers
  1. Video Compression with CNN-based Post Processing. [paper][project]
    F. Zhang, D. Ma, C. Feng and D. R. Bull, IEEE MultiMedia Magazine, 2020.

Conference papers
  1. RankDVQA: Deep VQA based on Ranking-inspired Hybrid Training. [paper][project]
    C. Feng, D. Danier, F. Zhang, and D. R. Bull, accepted by IEEE/CVF WACV, 2024

  2. ViSTRA3: Video Coding with Deep Parameter Adaptation and Post Processing. [paper][project]
    C. Feng, D. Danier, C. Tan, F. Zhang, D. Bull, accepted by IEEE ISCAS, 2022

  3. Enhancing VVC through CNN-based Post-Processing. [paper][project]
    F. Zhang, C. Feng and D. Bull, ICME, 2020.

Professional Activities

  • Reviewer of IEEE Transactions on Image Processing (TIP)
  • Reviewer of IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT).
  • Reviewer of IEEE Signal Processing Letters
  • Reviewer of IEEE Transactions on Multimedia (T-MM)
  • Reviewer of IEEE International Conference on Multimedia and Expo (ICME)
  • Reviewer of Picture Coding Symposium (PCS)
  • Reviewer of IEEE International Conference on Image Processing (ICIP).

Awards and Honours

  • The FIRST Prize in IEEE/CVF WACV 2023 HDR VQM Grand Challenge hosted by Amazon Prime Video(award letter)
  • UKRI MyWorld Strength Research Students Awards Scheme Scholarship.
  • PhD is funded by the Amazon Research Awards 2023
  • Top Six in the Challenge on Learned Image Compression in IEEE/CVF CVPR 2022
  • Second Prize in the Grand Challenge on NN-based Video Coding in IEEE ISCAS 2022
  • University of Bristol - Bristol PLUS Award

Technical Skills

  • Programming: Python, Matlab, C++, C\#, Java, Assembly.
  • Machine Learning: PyTorch, Tensorflow, Generative Models, CNNs, Statistical Analysis.
  • Tools: Unity(VR\&AR Development), Git, Docker, IDEs, \textrm{\LaTeX}, Raspberry Pi, LabVIEW