Antoni B. Chan

12.2k total citations · 2 hit papers
163 papers, 6.8k citations indexed

About

Antoni B. Chan is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Cognitive Neuroscience. According to data from OpenAlex, Antoni B. Chan has authored 163 papers receiving a total of 6.8k indexed citations (citations by other indexed papers that have themselves been cited), including 129 papers in Computer Vision and Pattern Recognition, 54 papers in Artificial Intelligence and 27 papers in Cognitive Neuroscience. Recurrent topics in Antoni B. Chan's work include Video Surveillance and Tracking Methods (53 papers), Human Pose and Action Recognition (34 papers) and Anomaly Detection Techniques and Applications (30 papers). Antoni B. Chan is often cited by papers focused on Video Surveillance and Tracking Methods (53 papers), Human Pose and Action Recognition (34 papers) and Anomaly Detection Techniques and Applications (30 papers). Antoni B. Chan collaborates with scholars based in Hong Kong, United States and China. Antoni B. Chan's co-authors include Nuno Vasconcelos, Jerome Liang, Jia Wan, Janet H. Hsiao, Pedro J. Moreno, Gustavo Carneiro, Zheng Ma, Gert Lanckriet, Qi Zhang and Qingzhong Wang and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Scientific Reports and IEEE Transactions on Image Processing.

In The Last Decade

Antoni B. Chan

159 papers receiving 6.5k citations

Hit Papers

Privacy preserving crowd monitoring: Counting people with... 2007 2026 2013 2019 2008 2007 250 500 750

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Antoni B. Chan Hong Kong 43 5.2k 2.7k 548 525 493 163 6.8k
Clinton Fookes Australia 41 3.1k 0.6× 1.5k 0.6× 261 0.5× 656 1.2× 1.0k 2.1× 318 5.6k
Kaiqi Huang China 38 5.9k 1.1× 1.5k 0.6× 517 0.9× 228 0.4× 248 0.5× 198 6.7k
Rita Cucchiara Italy 42 7.9k 1.5× 2.2k 0.8× 774 1.4× 177 0.3× 579 1.2× 387 10.1k
Rainer Stiefelhagen Germany 46 6.3k 1.2× 2.0k 0.8× 321 0.6× 618 1.2× 750 1.5× 309 8.9k
Zhaoxiang Zhang China 39 5.1k 1.0× 1.9k 0.7× 165 0.3× 291 0.6× 310 0.6× 230 6.5k
Xiaopeng Hong China 35 3.3k 0.6× 1.7k 0.6× 190 0.3× 223 0.4× 494 1.0× 146 4.8k
James Hays United States 37 8.1k 1.6× 2.2k 0.8× 159 0.3× 446 0.8× 308 0.6× 80 10.0k
Shaogang Gong United Kingdom 68 15.1k 2.9× 5.1k 1.9× 523 1.0× 260 0.5× 1.1k 2.1× 287 17.2k
Baocai Yin China 39 4.1k 0.8× 1.4k 0.5× 164 0.3× 462 0.9× 666 1.4× 446 7.8k
Kris Kitani United States 43 4.0k 0.8× 1.2k 0.4× 314 0.6× 1.2k 2.3× 230 0.5× 175 6.3k

Countries citing papers authored by Antoni B. Chan

Since Specialization
Citations

This map shows the geographic impact of Antoni B. Chan's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Antoni B. Chan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Antoni B. Chan more than expected).

Fields of papers citing papers by Antoni B. Chan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Antoni B. Chan. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Antoni B. Chan. The network helps show where Antoni B. Chan may publish in the future.

Co-authorship network of co-authors of Antoni B. Chan

This figure shows the co-authorship network connecting the top 25 collaborators of Antoni B. Chan. A scholar is included among the top collaborators of Antoni B. Chan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Antoni B. Chan. Antoni B. Chan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Cui, Zhen, et al.. (2024). Collaborative contrastive learning for cross-domain gaze estimation. Pattern Recognition. 161. 111244–111244. 2 indexed citations
2.
Hsiao, Janet H., et al.. (2024). Gradient-Based Instance-Specific Visual Explanations for Object Specification and Object Discrimination. IEEE Transactions on Pattern Analysis and Machine Intelligence. 46(9). 5967–5985. 6 indexed citations
3.
Wu, Qiangqiang, et al.. (2023). A Lightweight and Detector-Free 3D Single Object Tracker on Point Clouds. IEEE Transactions on Intelligent Transportation Systems. 24(5). 5543–5554. 27 indexed citations
4.
Li, Qiao, et al.. (2022). Bits-Ensemble: Toward Light-Weight Robust Deep Ensemble by Bits-Sharing. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 41(11). 4397–4408. 2 indexed citations
5.
Chan, Antoni B., et al.. (2021). Hierarchical Learning of Hidden Markov Models with Clustering Regularization. Uncertainty in Artificial Intelligence. 1 indexed citations
6.
Hsiao, Janet H., et al.. (2020). The role of eye movement consistency in learning to recognise faces: Computational and experimental examinations.. Cognitive Science. 4 indexed citations
7.
Wan, Jia & Antoni B. Chan. (2020). Modeling Noisy Annotations for Crowd Counting.. Neural Information Processing Systems. 33. 3386–3396. 36 indexed citations
8.
Hsiao, Janet H., et al.. (2019). Understanding Individual Differences in Eye Movement Pattern During Scene Perception through Co-Clustering of Hidden Markov Models. Cognitive Science. 3283. 2 indexed citations
9.
Kang, Di & Antoni B. Chan. (2018). Crowd Counting by Adaptively Fusing Predictions from an Image Pyramid. British Machine Vision Conference. 89. 19 indexed citations
10.
Hayward, William G., et al.. (2018). Optimal face recognition performance involves a balance between global and local information processing: Evidence from cultural difference.. Cognitive Science. 2 indexed citations
11.
Yang, Tianyu, et al.. (2018). Density-Preserving Hierarchical EM Algorithm: Simplifying Gaussian Mixture Models for Approximate Inference. IEEE Transactions on Pattern Analysis and Machine Intelligence. 41(6). 1323–1337. 23 indexed citations
12.
Zhang, Jinxiao, Antoni B. Chan, Esther Yuet Ying Lau, & Janet H. Hsiao. (2017). Insomniacs misidentify angry faces as fearful faces because of missing the eyes: An eye-tracking study. Cognitive Science. 1430–1435. 2 indexed citations
13.
Chan, Antoni B., et al.. (2016). Hidden Markov modeling of eye movements with image information leads to better discovery of regions of interest. Cognitive Science. 3 indexed citations
14.
Chan, Antoni B., et al.. (2016). Mind reading: Discovering individual preferences from eye movements using switching hidden Markov models.. Cognitive Science. 8 indexed citations
15.
Chan, Antoni B., et al.. (2015). Eye movement pattern in face recognition is associated with cognitive decline in the elderly. Cognitive Science. 2 indexed citations
16.
Crookes, Kate, et al.. (2014). Caucasian and Asian eye movement patterns in face recognition: A computational exploration using hidden Markov models. Journal of Vision. 14(10). 1212–1212. 3 indexed citations
17.
Coviello, Emanuele, et al.. (2013). That was fast! Speeding up NN search of high dimensional distributions.. International Conference on Machine Learning. 468–476. 2 indexed citations
18.
Coviello, Emanuele, et al.. (2013). Understanding eye movements in face recognition with hidden Markov model. Cognitive Science. 35(35). 2 indexed citations
19.
Chan, Antoni B., et al.. (2010). Automatic Musical Pattern Feature Extraction Using Convolutional Neural Network. International MultiConference of Engineers and Computer Scientists. 546–550. 71 indexed citations
20.
Chan, Antoni B. & Nuno Vasconcelos. (2005). Layered Dynamic Textures. Neural Information Processing Systems. 18. 203–210. 15 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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