Prof Jungong Han

Profile

Prof. Han holds a Chair and is the Director of Research in Computer Science at Aberystwyth University, UK. He is the Honorary Professor at the University of Warwick. He is the Fellow of the International Association of Pattern Recognition (IAPR). Previously, he was an Associate Professor of Data Science at the University of Warwick, a Senior Lecturer (Associate Professor) with the School of Computing and Communications at Lancaster University, UK. From 2004 to 2015, he spent eleven years in the Netherlands, doing research at the Technical University of Eindhoven (TU/e), the Centre for Mathematics and Computer Science (CWI) in Amsterdam, and at Civolution (Philips CI). Prior to arriving in Europe, he spent one year as a research assistant at Microsoft Research Asia, Beijing.

Prof. Han’s research interests include Computer Vision, Artificial Intelligence, and Machine Learning. He has written and co-authored over 200 papers, including 80+ IEEE/ACM Transactions (23 papers on IEEE Trans. Image Processing) and 50+ A* conference papers (21 papers on CVPR, ICCV, ECCV; 2 papers on NeurIPS; 1 paper on ICML). He is the Associate Editor-in-Chief of Elsevier Neurocomputing, the Associate Editor of Pattern Recognition,  Journal of Visual Communication and Image Representation, and IET Computer Vision.

Research

Selected Journal Papers:

  • Y. Liu, D. Zhang, Q. Zhang, J. Han: Part-object Relational Visual Saliency. IEEE Trans. Pattern Analysis and Machine Intelligence, in press, 2021
  • J. Zhao, J. Han, L. Shao, C. G. M. Snoek: Pixelated Semantic Colorization. Int. J. Comput. Vis. 128(4): 818-834 (2020)
  • G. Wu, J. Han, Y. Guo, L. Liu, G. Ding, Q. Ni, L. Shao: Unsupervised Deep Video Hashing via Balanced Code for Large-Scale Video Retrieval. IEEE Trans. Image Process. 28(4): 1993-2007 (2019)
  • S. Luan, C. Chen, B. Zhang, J. Han: Gabor Convolutional Networks. IEEE Trans. Image Process. 27(9): 4357-4366 (2018)
  • D. Zhang, J. Han, J. Han, L. Shao: Cosaliency Detection Based on Intrasaliency Prior Transfer and Deep Intersaliency Mining. IEEE Trans. Neural Networks Learn. Syst. 27(6): 1163-1176 (2016)
  • J. Han, L. Shao, D. Xu, J. Shotton: Enhanced Computer Vision With Microsoft Kinect Sensor: A Review. IEEE Trans. Cybern. 43(5): 1318-1334 (2013)
  • J. Han, D. Farin, P. H. N. de With: Broadcast Court-Net Sports Video Analysis Using Fast 3-D Camera Modeling. IEEE Trans. Circuits Syst. Video Techn. 18(11): 1628-1638 (2008)

Selected Conference Papers:

  • L. Xiang, G. Ding, J. Han: Learning from Multiple Experts: Self-paced Knowledge Distillation for Long-tailed Classification. European Conference on Computer Vision (ECCV2020) (Spotlight, top 5%)
  • Y. Pang, J. Nie, J. Xie, J. Han, X. Li: BidNet: Binocular Image Dehazing Without Explicit Disparity Estimation. CVPR 2020
  • Y. Liu, Q. Zhang, D. Zhang, J. Han: Employing Deep Part-Object Relationships for Salient Object Detection. ICCV 2019: 1232-1241
  • X. Ding, G. Ding, X. Zhou, Y. Guo, J. Han, J. Liu: Global Sparse Momentum SGD for Pruning Very Deep Neural Networks. NeurIPS 2019: 6379-6391
  • X. Ding, G. Ding, Y. Guo, J. Han, C. Yan: Approximated Oracle Filter Pruning for Destructive CNN Width Optimization. ICML 2019: 1607-1616
  • Y. Guo, X. Zhao, G. Ding, J. Han: On Trivial Solution and High Correlation Problems in Deep Supervised Hashing. AAAI 2018: 2240-2247