Prof. Antoni B. Chan
Professor, Dept. of Computer Science
Associate Dean (Research & Postgraduate), College of Computing
Deputy Director, Multimedia Engineering Research Centre (MERC)
BSc MEng Cornell, PhD UC San Diego
SrMIEEE

Video, Image, and Sound Analysis Lab (VISAL)
Department of Computer Science
College of Computing
City University of Hong Kong

Office: Room AC1-G7311, Yeung Kin Man Academic Building (lift 7)
Phone: +852 3442 6509
Fax: +852 3442 0503
Email: abchan at cityu dot edu dot hk

News

  • Research Assistant and Technical Assistant positions are available for a project on using ChatGPT in teaching. Details here.

Bio

Dr. Antoni Chan is a Professor at the City University of Hong Kong in the Department of Computer Science.  Before joining CityU, he was a postdoctoral researcher in the Department of Electrical and Computer Engineering at the University of California, San Diego (UC San Diego).  He received the Ph.D. degree from UC San Diego in 2008 studying in the Statistical and Visual Computing Lab (SVCL). He received the B.Sc. and M.Eng. in Electrical Engineering from Cornell University in 2000 and 2001. From 2001 to 2003, he was a Visiting Scientist in the Computer Vision and Image Analysis lab at Cornell. In 2005, he was a summer intern at Google in New York City. In 2012, he was the recipient of an Early Career Award from the Research Grants Council of the Hong Kong SAR, China.

Research Interests [more]

Computer Vision, Surveillance, Machine Learning, Explainable AI (XAI), Pattern Recognition, Computer Audition, Music Information Retrieval, Eye Gaze Analysis

image captioning, object tracking, dynamic textures, motion segmentation, motion analysis, semantic image annotation, image retrieval, crowd counting, probabilistic graphical models, support vector machines, Bayesian regression, Gaussian processes, semantic music annotation and retrieval, music segmentation, feature extraction.

  • For more information about my current research projects, please visit my lab website.
  • Opportunities for graduate students and research assistants! If you are interested in joining the lab, please check this information. Outstanding non-HK students may also consider applying for the HK PhD fellowship.

Recent Publications [more]

  • Robust Zero-Shot Crowd Counting and Localization with Adaptive Resolution SAM.
    Jia Wan, Qiangqiang Wu, Wei Lin, and Antoni B. Chan,
    In: European Conference on Computer Vision (ECCV), Milano, Oct 2024.
  • A Secure Image Watermarking Framework with Statistical Guarantees via Adversarial Attacks on Secret Key Networks.
    Feiyu Chen, Wei Lin, Ziquan Liu, and Antoni B. Chan,
    In: European Conference on Computer Vision (ECCV), Milano, Oct 2024.
  • Boosting 3D Single Object Tracking with 2D Matching Distillation and 3D Pre-training.
    Qiangqiang Wu, Yan Xia, Jia Wan, and Antoni B. Chan,
    In: European Conference on Computer Vision (ECCV), Milano, Oct 2024.
  • Mahalanobis Distance-based Multi-view Optimal Transport for Multi-view Crowd Localization.
    Qi Zhang, Kaiyi Zhang, Antoni B. Chan, and Hui Huang,
    In: European Conference on Computer Vision (ECCV), Milano, Oct 2024. [Project&Code]
  • FreeDiff: Progressive Frequency Truncation for Image Editing with Diffusion Models.
    Wei Wu, Qingnan Fan, Shuai Qin, Hong Gu, Ruoyu Zhao, and Antoni B. Chan,
    In: European Conference on Computer Vision (ECCV), Milano, Oct 2024.
  • Human attention guided explainable artificial intelligence for computer vision models.
    Guoyang Liu, Jindi Zhang, Antoni B. Chan, and Janet H. Hsiao,
    Neural Networks, 177:106392, Sep 2024.
  • Edit Temporal-Consistent Videos with Image Diffusion Model.
    Yuanzhi Wang, Yong Li, Xiaoya Zhang, Xin Liu, Anbo Dai, Antoni B. Chan, and Zhen Cui,
    ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), to appear 2024.
  • Group-based Distinctive Image Captioning with Memory Difference Encoding and Attention.
    Jiuniu Wang, Wenjia Xu, Qingzhong Wang, and Antoni B. Chan,
    International Journal of Computer Vision (IJCV), to appear 2024.
  • Gradient-based Visual Explanation for Transformer-based CLIP.
    Chenyang Zhao, Kun Wang, Xingyu Zeng, Rui Zhao, and Antoni B. Chan,
    In: International Conference on Machine Learning (ICML), Vienna, Jul 2024.
  • The Pitfalls and Promise of Conformal Inference Under Adversarial Attacks.
    Ziquan Liu, Yufei Cui, Yan Yan, Yi Xu, Xiangyang Ji, Xue Liu, and Antoni B. Chan,
    In: International Conference on Machine Learning (ICML), Vienna, Jul 2024.
  • Is Holistic Processing Associated with Face Scanning Pattern and Performance in Face Recognition? Evidence from Deep Neural Network with Hidden Markov Modeling.
    Wei Xing, Yueyuan Zheng, Antoni B. Chan, and Janet H. Hsiao,
    In: Annual Conference of the Cognitive Science Society (CogSci), Rotterdam, Jul 2024.
  • Eye Movement Behavior during Mind Wandering across Different Tasks in Interactive Online Learning.
    Xiaoru Teng, Hui Lan, Gloria HY Wong, Antoni B. Chan, and Janet H. Hsiao,
    In: Annual Conference of the Cognitive Science Society (CogSci), Rotterdam, Jul 2024.
  • Do large language models resolve semantic ambiguities in the same way as humans? The case of word segmentation in Chinese sentence reading.
    Weiyan Liao, Zixuan Wang, Kathy Shum, Antoni B. Chan, and Janet H. Hsiao,
    In: Annual Conference of the Cognitive Science Society (CogSci), Rotterdam, Jul 2024.
  • Demystify Deep-learning AI for Object Detection using Human Attention Data.
    Jinhan Zhang, Guoyang Liu, Yunke Chen, Antoni B. Chan, and Janet H. Hsiao,
    In: Annual Conference of the Cognitive Science Society (CogSci), Rotterdam, Jul 2024.
  • Affecting Audience Valence and Arousal in 360 Immersive Environments: How Powerful Neural Style Transfer Is?
    Yanheng Li, Long Bai, Yaxuan Mao, Xuening Peng, Zehao Zhang, Jixing Li, Antoni B. Chan, Xin Tong, and RAY LC,
    In: HCI International 2024 Conference (HCII2024) - Virtual, Augmented, and Mixed Reality, Washington DC, Jun 2024.

Selected Publications [more]

Google Scholar Google Scholar
Microsoft Academic Microsoft Academic
ORCID orcid.org/0000-0002-2886-2513
Scopus ID: 14015159100

Recent Project Pages [more]

Adversarial-Noise Watermark Framework

We propose a novel watermarking framework that leverages adversarial attacks to embed watermarks into images via two secret keys (network and signature) and deploys hypothesis tests to detect these watermarks with statistical guarantees.

  • Feiyu Chen, Wei Lin, Ziquan Liu, and Antoni B. Chan, "A Secure Image Watermarking Framework with Statistical Guarantees via Adversarial Attacks on Secret Key Networks." In: European Conference on Computer Vision (ECCV), Milano, Oct 2024.
Scalable Video Object Segmentation with Simplified Framework

We propose a Simplified VOS framework (SimVOS), which removes the hand-crafted feature extraction and matching modules in previous approaches, to perform joint feature extraction and interaction via a single scalable transformer backbone. We also demonstrate that large-scale self-supervised pre-trained models can provide significant benefits to the VOS task. In addition, a new token refinement module is proposed to achieve a better speed-accuracy trade-off for scalable video object segmentation.

DropMAE: Masked Autoencoders with Spatial-Attention Dropout for Tracking Tasks

We study masked autoencoder (MAE) pre-training on videos for matching-based downstream tasks, including visual object tracking (VOT) and video object segmentation (VOS).

Grad-ECLIP: Gradient-based Visual Explanation for CLIP

We propose a Gradient-based visual Explanation method for CLIP (Grad-ECLIP), which interprets the matching result of CLIP for specific input image-text pair

  • Chenyang Zhao, Kun Wang, Xingyu Zeng, Rui Zhao, and Antoni B. Chan, "Gradient-based Visual Explanation for Transformer-based CLIP." In: International Conference on Machine Learning (ICML), Vienna, Jul 2024.
Pareto Optimization for Active Learning under Out-of-Distribution Data Scenarios

We propose a batch-mode Pareto Optimization Active Learning (POAL) framework for Active Learning under Out-of-Distribution data scenarios.

Recent Datasets and Code [more]

Modeling Eye Movements with Deep Neural Networks and Hidden Markov Models (DNN+HMM)

This is the toolbox for modeling eye movements and feature learning with deep neural networks and hidden Markov models (DNN+HMM).

Dolphin-14k: Chinese White Dolphin detection dataset

A dataset consisting of  Chinese White Dolphin (CWD) and distractors for detection tasks.

Crowd counting: Zero-shot cross-domain counting

Generalized loss function for crowd counting.

CVCS: Cross-View Cross-Scene Multi-View Crowd Counting Dataset

Synthetic dataset for cross-view cross-scene multi-view counting. The dataset contains 31 scenes, each with about ~100 camera views. For each scene, we capture 100 multi-view images of crowds.

Crowd counting: Generalized loss function

Generalized loss function for crowd counting.

Teaching

  • CS 4487 – Machine Learning (undergraduate) — 2015A-2018A.
  • CS 5487 – Machine Learning: Principles & Practice (postgraduate) — 2012A-2024A.
  • CS 5489 – Machine Learning: Algorithms & Applications (postgraduate) — 2020B-2025B
  • CS 6487 – Topics in Machine Learning (postgraduate) — 2019B.
  • GE 2326 – Probability in Action: From the Unfinished Game to the Modern World — 2015B-2017B.
  • GE 1319 – Interdisciplinary Research for Smart Professionals — 2013B-2017B.
  • CS 5301 – Computer Programming — 2012A-2014A.
  • CS 2363 – Computer Programming — 2009A-2011A.
  • CS 3306 (B) – Contemporary Programming Methods in Java — 2010B.
  • CS 4380 (B) – Web 2.0 Technologies — 2011B, 2012B.
  • Multimedia Subject Group leader
  • Research Mentoring Scheme Coordinator
  • Final Year Project Coordinator (2016-2022)
  • MSCS Project and Guided Study Coordinator (2016-2022)
  • BScCM Deputy Programme Leader (2020-2022)

Service

  • Associate Editor, IEEE Transactions on Pattern Analysis and Machine Intelligence (2023-now)
  • Action Editor, Transactions on Machine Learning Research (2022-now)
  • Guest Editor, Special Issue on “Applications of artificial intelligence, computer vision, physics and econometrics modelling methods in pedestrian traffic modelling and crowd safety”, Transportation Research Part C: Emerging Technologies (2022-23)
  • Senior Area Editor, IEEE Signal Processing Letters (2016-2020)
  • Associate Editor, IEEE Signal Processing Letters (2014-2016)
  • Conference Area Chair
    • CVPR – 2020, 2023
    • ICCV – 2015, 2017, 2019, 2021
    • ECCV – 2022, 2024
    • NeurIPS – 2020, 2021, 2022, 2023, 2024
    • ICML – 2021, 2022, 2023, 2024
    • ICLR – 2021, 2023, 2024, 2025
    • ICPR – 2020
    • Pacific Graphics – 2018
  • Conference Senior PC
    • AAAI – 2021, 2022
    • IJCAI – 2019-20
  • Conference Program Committees
    • CVPR – 2012-2019, 2021, 2022, 2024
    • ICCV – 2011, 2013, 2023
    • ECCV – 2012, 2014, 2016, 2018
    • ACCV – 2011, 2014, 2016
    • ICML – 2012, 2013, 2014, 2015, 2018, 2019, 2020
    • NIPS – 2015, 2017, 2018, 2019
    • ICLR – 2022
    • Siggraph (tertiary)- 2018
  • Journal Reviewing
    • IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI)
    • IEEE Trans. on Image Processing (TIP)
    • Intl. Journal Computer Vision (IJCV)
    • IEEE Trans. on Circuits and Systems for Video Technology (TCSVT)
    • IEEE Trans. on Neural Networks (TNN)
    • IEEE Trans. on Multimedia
    • IEEE Trans. Intelligent Transportation Systems
  • Organized Events
    • CogSci 2022 Hong Kong Meetup & Symposium: Computational Approaches to Psychological Research, Aug 2022.

Awards and Honors

  • Top 2% Most Highly Cited Researchers (Ioannidis et al. 2019. Plos Biology)
  • The President’s Award, City University of Hong Kong, 2016.
  • Early Career Award, Research Grants Council of Hong Kong, 2012.
  • NSF IGERT Fellowship: Vision and Learning in Humans and Machines, UCSD, 2006-07.
  • Outstanding Teaching Assistant Award, ECE Department, UCSD, 2005-06.
  • Office of the President Award, UCSD, 2003.
  • Henry G. White Scholorship, Cornell University, 2001.
  • Knauss M. Engineering Scholorship, Cornell University, 2001.
  • GTE Fellowship, Cornell University, 2001.
Mailing Address:

Prof. Antoni Chan,
Department of Computer Science,
City University of Hong Kong,
Tat Chee Avenue,
Kowloon Tong, Hong Kong.

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