Biography

Ying-Cong Chen is an Assistant Professor at AI Thrust, Information Hub of Hong Kong University of Science and Technology (Guangzhou). He is also an Affiliated Assistant Professor of the department of Computer Science & Engineering (Clear Water Bay Campus). He is a faculty member of the Deep Vision Lab. He was a Postdoctoral Associate at Computer Science & Artificial Intelligence Lab of Massachusetts Institute of Technology, working with Prof. Dina Katabi. He obtained his Ph.D. degree from the Chinese University of Hong Kong, working with Prof. Jiaya Jia.

His research lies in the broad area of computer vision and machine learning, aiming for empowering machine with the capacity to perceive and understand the world, so as to develop and reshape our society. His works contribute to a wide range of applications, including semantic face editing, image synthesis, intelligent video surveillance, etc.

Interests
  • Computer Vision
  • Machine Learning
  • Artificial Intelligence

Recent Publications

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Yuzhe Yang, Yuan Yuan, Guo Zhang, Hao Wang, Ying-Cong Chen, Yingcheng Liu, Christopher Tarolli, Daniel Crepeau, Jan Bukartyk, Mithri Junna, Aleksandar Videnovic, Terry Ellis, Melissa Lipford, Ray Dorsey, Dina Katabi. Artificial intelligence-enabled detection and assessment of Parkinson’s disease using nocturnal breathing signals. Nature Medicine, 2022.
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Xin Lai, Zhuotao Tian, Xiaogang Xu, Ying-Cong Chen, Shu Liu, Hengshuang Zhao, Liwei Wang, Jiaya Jia. DecoupleNet: Decoupled Network for Domain Adaptive Semantic Segmentation. Proceedings of the European conference on computer vision (ECCV), 2022.
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Di Chang, Aljaz Bozic, Tong Zhang, Qingsong Yan, Ying-Cong Chen, Sabine Susstrunk, Matthias Niebner. RC-MVSNet: Unsupervised Multi-View Stereo with Neural Rendering. Proceedings of the European conference on computer vision (ECCV), 2022.
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Qing Lian, Yanbo Xu, Weilong Yao, Ying-Cong Chen, Tong Zhang. Semi-supervised Monocular 3D Object Detection by Multi-view Consistency. Proceedings of the European conference on computer vision (ECCV), 2022.
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Chang-Bin Zhang, Jia-Wen Xiao, Xialei Liu, Ying-Cong Chen, Ming-Ming Cheng. Representation Compensation Networks for Continual Semantic Segmentation. In Computer Vision and Pattern Recognition (CVPR), 2022.
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Research Topics

3D Vision AI for Healthcare Domain Adaptation Face Manipulation Generative Adversarial Networks Graph Convolutional Network Image Generation Image Inpainting Image Processing Image-to-image Translation Instance Segmentation Latent Space Interpolation Machine Learning Metric Learning Multimodal NeRF Novel View Synthesis Person Re-identification Regression Semantic Segmentation

Academic Services

Reviewer/(Senior) Program Committee Member of:

  • International Joint Conference on Artificial Intelligence (IJCAI) (Senior PC)
  • AAAI Conference on Artificial Intelligence (AAAI) (Senior PC)
  • International Conference on Computer Vision and Pattern Recognition (CVPR)
  • International Conference on Computer Vision (ICCV)
  • European Conference on Computer Vision (ECCV)
  • International Conference on Learning Representations (ICLR)
  • International Conference on Machine Learning (ICML)
  • Neural Information Processing Systems (NeurIPS)
  • Winter Conference on Applications of Computer Vision (WACV)
  • British Machine Vision Conference (BMVC)
  • European Conference on AI (ECAI)
  • IEEE Transaction on Pattern Analysis and Machine Intelligence (TPAMI)
  • International Journal of Computer Vision (IJCV)
  • IEEE Transaction on Image Processing (TIP)
  • Neurocomputing

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