CHEN Chaofeng (ι™ˆθΆ…ι”‹)

Research Fellow @ S-Lab, NTU

Ph.D @ HKU; B.Eng. @ HUST
chaofenghust [at] gmail.com

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About Me

I am currently a postdoctoral research fellow at S-Lab in Nanyang Technological University, working with Prof. Weisi Lin. I received my Ph.D. degree from Dept. of Computer Science at the University of Hong Kong in January 2021. I did my Ph.D. research at Computer Vision Lab in HKU, advised by Dr. Kenneth K.Y. Wong. Prior to studying at HKU, I received my B.Eng. from Huazhong University of Science and Technology.

My interests are centered around Computer Vision and Deep Learning. Current research topics include:

News

  • ⭐ Use pip install pyiqa to try our PyTorch toolbox for Image Quality Assessment.
  • 2022-12: One paper about video prediction is accepted by AAAI 2023.
  • 2022-11: Our research team, NTU Visual Quality Assessment Group is created, which aims to build efficient and explainable Visual Quality Assessment approaches.
  • 2022-09: One paper is accepted by NeurIPS 2022.
  • 2022-07: Three papers have been accepted by ECCV2022.
  • 2022-06: Two papers, including QuanTexSR (renamed as FeMaSR) have been accepted by ACM MM2022.
  • 2022-06: One paper, FFRNet about masked face recognition has been accepted by ICIP2022.
  • 2022-03: We release our work about blind image resolution, QuanTexSR, together with the codes in Github.
  • 2022-02: We release a PyTorch toolbox for IQA as well as a comprehensive survey .
  • 2021-07: One paper about HDR video reconstruction is accepted by ICCV 2021.
  • 2021-03: Our paper PSFR-GAN about face SR has been accepted by CVPR2021.
  • 2020-11: Our paper SPARNet about face SR has been accepted by TIP2020.

Experience

Sep 2021 - Present Postdoctoral research fellow at S-Lab in NTU, working with Prof. Weisi Lin
Mar 2021 - Aug 2021 Research Assistant at GAP Lab CUHKSZ, worked with Dr. Xiaoguang Han
Nov 2019 - Mar 2021 Research Intern at Alibaba DAMO Academy, worked with Prof. Lei Zhang and Dr. Xiaoming Li
May 2019 - Oct 2019 Research Visitor at VLLab UC Merced, worked with Prof. Ming-Hsuan Yang
Jun 2018 - Mar 2019 Research Intern at Tencent AI Lab, worked with Prof. Zhifeng Li and Dr. Dihong Gong

Publications

Conference Proceedings

MIMO Is All You Need: A Strong Multi-In-Multi-Out Baseline for Video Prediction

Shuliang Ning*, Mengcheng Lan*, Yanran Li, Chaofeng Chen, Qian Chen, Xunlai Chen, Xiaoguang Han, Shuguang Cui

Association for the Advancement of Artificial Intelligence (AAAI), 2023

S3-NeRF: Neural Reflectance Field from Shading and Shadow under a Single Viewpoint

Wenqi Yang, Guanying Chen, Chaofeng Chen, Zhenfang Chen, Kwan-Yee K. Wong

Conference on Neural Information Processing Systems (NeurIPS), 2022

FAST-VQA: Efficient End-to-end Video Quality Assessment with Fragment Sampling

Haoning Wu, Chaofeng Chen, Jingwen Hou, Liang Liao, Annan Wang, Wenxiu Sun, Qiong Yan, Weisi Lin

European Conference on Computer Vision (ECCV), 2022

From Face to Natural Image: Learning Real Degradation for Blind Image Super-Resolution

Xiaoming Li, Chaofeng Chen, Xianhui Lin, Wangmeng Zuo, Lei Zhang

European Conference on Computer Vision (ECCV), 2022

PS-NeRF: Neural Inverse Rendering for Multi-view Photometric Stereo

Wenqi Yang, Guanying Chen, Chaofeng Chen, Zhenfang Chen, Kwan-Yee K. Wong

European Conference on Computer Vision (ECCV), 2022

Real-World Blind Super-Resolution via Feature Matching with Implicit High-Resolution Priors

Chaofeng Chen*, Xinyu Shi*, Yipeng Qin, Xiaoming Li, Tao Yang, Xiaoguang Han, Shihui Guo (* indicates equal contribution.)

ACM Multimedia, 2022 (Oral Presentation)

Exploring the Effectiveness of Video Perceptual Representation in Blind Video Quality Assessment

Liang Liao, Kangmin Xu, Haoning Wu, Chaofeng Chen, Wenxiu Sun, Qiong Yan, Weisi Lin

ACM Multimedia, 2022 (Oral Presentation)

A Unified Framework for Masked and Mask-Free Face Recognition via Feature Rectification

Shaozhe Hao, Chaofeng Chen, Zhenfang Chen, Kwan-Yee K. Wong

ICIP, 2022

HDR Video Reconstruction: A Coarse-to-fine Network and A Real-world Benchmark Dataset

Guanying Chen, Chaofeng Chen, Shi Guo, Zhetong Liang, K.-Y. K. Wong, Lei Zhang.

International Conference on Computer Vision (ICCV), 2021

Progressive Semantic-Aware Style Transformation for Blind Face Restoration

Chaofeng Chen, Xiaoming Li, Lingbo Yang, Xianhui Lin, Lei Zhang, K.-Y. K. Wong.

Computer Vision and Pattern Recognition (CVPR), 2021

Blind Face Restoration via Deep Multi-scale Component Dictionaries

Xiaoming Li, Chaofeng Chen, Shangchen Zhou, Xianhui Lin, Wangmeng Zuo, Lei Zhang

European Conference on Computer Vision (ECCV), 2020

Semi-Supervised Learning for Face Sketch Synthesis in the Wild

Chaofeng Chen, Wei Liu, Xiao Tan, K.-Y. K. Wong.

Asia Conference on Computer Vision (ACCV), 2018

SAFE: Scale Aware Feature Encoder for Scene Text Recognition

Wei Liu, Chaofeng Chen, K.-Y. K. Wong.

Asia Conference on Computer Vision (ACCV), 2018

Face Sketch Synthesis with Style Transfer using Pyramid Column Feature.

Chaofeng Chen*, Xiao Tan*, K.-Y. K. Wong. (* indicates equal contribution.)

IEEE Winter Conference on Applications of Computer Vision (WACV), 2018

Char-Net: A Character-Aware Neural Network for Distorted Scene Text Recognition

Wei Liu, Chaofeng Chen, K.-Y. K. Wong

AAAI Conference on Artificial Intelligence (AAAI), 2018 (Oral Presentation)

PDF PPT

STAR-Net: A SpaTial Attention Residue Network for Scene Text Recognition.

Wei Liu, Chaofeng Chen, K.-Y. K. Wong, Z. Su and J. Han

British Machine Vision Conference (BMVC), 2016

PDF

Academic Journals

Deep Face Video Inpainting via UV Mapping

Wenqi Yang, Zhenfang Chen, Chaofeng Chen, Guanying Chen, Kwan-Yee K. Wong

IEEE Transactions on Image Processing (TIP), 2023

Learning Spatial Attention for Face Super-Resolution

Chaofeng Chen, Dihong Gong, Hao Wang, Zhifeng Li, Kwan-Yee K. Wong

IEEE Transactions on Image Processing (TIP), 2020

PhD Dissertation

Face Sketch Synthesis and Face Super Resolution in the Wild with Deep Learning

Chaofeng Chen

Dept. of Computer Science, The University of Hong Kong, 2020

HKU Theses Online

Professional Activities

Awards

Teaching

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