OUYANG Wanli

*SHB = Ho Sin Hang Engineering Building, The Chinese University of Hong Kong

Research Interest
  • AI for Science
  • Computer Vision
  • Pattern recognition
  • Machine learning
Courses Taught

OUYANG Wanli 歐陽萬里教授

Professor
Global STEM Scholar
PhD (CUHK)
(852) 3943-8378
Room 706, SHB*
wlouyang [at] ie.cuhk.edu.hk
Website

Wanli Ouyang received the PhD degree in the Department of Electronic Engineering, The Chinese University of Hong Kong. He has won a number of competitions and awards such as the first in 2016 ImageNet ILSVRC Challenge and the first in 2018 COCO object detection Challenge. He was awarded Future Fellowship by The Australian Research Council and Vice-Chancellor’s Award for Outstanding Research by The University of Sydney. He served as the associate editor of TPAMI, IJCV and PR, the Senior Area Chair of CVPR.

Recent / Selected Publications
  • Chen, T. Han, J. Gong, L. Bai, … & W. Ouyang, “Fengwu: Pushing the skillful global medium-range weather forecast beyond 10 days lead”, arXiv preprint arXiv:2304.02948, 2023. (Operationally deployed in China Meteorological Administration, Shanghai Meteorological Bureau, and Hong Kong Observatory)
  • Li, X. Yuan, C. Lin, M. Guo, W. Wu, J. Yan, W. Ouyang. “AM-LFS: AutoML for Loss Function Search”, Proc. ICCV, 2019. (The first automated deep learning method for automatically learning loss functions from data)
  • Zeng (equal contribution), W. Ouyang (equal contribution), et. al, “Crafting GBD-Net for Object Detection,” IEEE Trans. Pattern Anal. Mach. Intell. (PAMI),40(9): 2109-2123, 2018. (Winning the ImageNet Challenge 2016)
  • Wang, W. Ouyang, X. Wang, H. Lu, “Visual Tracking with Fully Convolutional Networks”, In Proc. ICCV, 2015. (The first fully convolutional network for visual tracking)
  • Zhao, W. Ouyang, H. Li, and X. Wang, “Saliency Detection by Multi-context Deep Learning”, In Proc. CVPR, 2015. (The first deep model for saliency detection).
  • Ouyang, and X. Wang, “Joint Deep Learning for Pedestrian Detection,” In Proc. ICCV, 2013. (The most influential paper by Paperdigest.org)
  • Rui Zhao, Ouyang, and X. Wang, “Unsupervised Salience Learning for Person Re-identification,” In Proc. CVPR, 2013. (The most influential paper by Paperdigest.org)
  • K. Kang, H. Li, J. Yan, X. Zeng, B. Yang, T. Xiao, C. Zhang, Z. Wang, R. Wang,X. Wang, W. Ouyang, “T-CNN: Tubelets with Convolutional Neural Networks for Object Detection from Videos”, IEEE Trans. Circuits Syst. Video Technol. (CSVT),28(10): 2896-2907, 2017. (Outstanding Young Author Award)
Research Interest

  • AI for Science
  • Computer Vision
  • Pattern recognition
  • Machine learning
Courses Taught