|Academic Profile |
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Assoc Prof Chen Change Loy
Nanyang Associate Professor, School of Computer Science and Engineering
NTU Co-Associate Lab Director, SenseTime-NTU Joint Research Centre
|Chen Change Loy is a Nanyang Associate Professor with the School of Computer Science and Engineering, Nanyang Technological University, Singapore. He is also an Adjunct Associate Professor at the Chinese University of Hong Kong, and a visiting scholar of Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, China. He received his PhD (2010) in Computer Science from the Queen Mary University of London. Prior to joining NTU, he served as a Research Assistant Professor at the MMLab of the Chinese University of Hong Kong, from 2013 to 2018. He was a postdoctoral researcher at Queen Mary University of London and Vision Semantics Limited, from 2010 to 2013.|
His research interests include computer vision and deep learning. He has published more than 120 papers in top journals and conferences of computer vision and machine learning. He and his research group pioneer the research in face detection, face alignment, and image super-resolution by deep learning. His journal paper on image super-resolution was selected as the `Most Popular Article' by IEEE Transactions on Pattern Analysis and Machine Intelligence in 2016. It remains as one of the top 10 articles to date. His current h-index is 58. He was selected as the outstanding reviewer of ACCV 2014, BMVC 2017, and CVPR 2017.
He serves as an Associate Editor of the International Journal of Computer Vision (IJCV) and IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). He also serves/served as the Area Chair of CVPR 2021, CVPR 2019, BMVC 2019, ECCV 2018, and BMVC 2018. He is a senior member of IEEE.
== Recent Honours and Award ==
Champion, COCO 2019 Object Detection Challenge (Without External Data), 2019
Champions of all four tracks, Facebook AI Self-Supervision Challenge, 2019
Champion, Open Images Challenge (Object Detection), 2019
Champions of all four tracks, NTIRE 2019 Challenge on Video Restoration and Enhancement, 2019
Nanyang Associate Professorship (Career Award), 2019
Champion, COCO Object Detection Challenge, 2018
Champion, PIRM Challenge on Perceptual Super-Resolution (Third Region), 2018
First Runner-up, DAVIS Challenge on Video Object Segmentation, 2018
First Runner-up, NTIRE 2018 Challenge on Single Image Super-Resolution, 2018
|Dr Loy's research interests include computer vision and deep learning. |
Google Scholar Profile: https://scholar.google.co.uk/citations?user=559LF80AAAAJ&hl=
- Deep Surround Visual Reasoning for Autonomous Driving
- Effective and Efficient Image Super-Resolution by Convolutional Neural Network on Mobile Devices
- Learning Dynamic-Routing Deep Convolutional Networks for Image Restoration by Reinforcement Learning
- X. Wang, K. Yu, C. Dong, X. Tang, C. C. Loy. (2019). Deep Network Interpolation for Continuous Imagery Effect Transition. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
- R. Xu, X. Li, B. Zhou, C. C. Loy. (2019). Deep Flow-Guided Video Inpainting. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
- D. Liu, B. Wen, Y. Fan, C. C. Loy, T. S. Huang. (2018). Non-Local Recurrent Network for Image Restoration. Neural Information Processing Systems (NeurIPS).
- X. Wang, K. Yu, S. Wu, J. Gu, Y. Liu, C. Dong, Y. Qiao, C. C. Loy. (2018). ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks. Workshop Proceedings of European Conference on Computer Vision, 2018 (Champion, Region 3 in the PIRM2018-SR Challenge, ECCV).
- C. Dong, C. C. Loy, K. He, X. Tang. (2015). Image Super-Resolution Using Deep Convolutional Networks. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), .