François Brémond

6.4k total citations
133 papers, 2.5k citations indexed

About

François Brémond is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Psychiatry and Mental health. According to data from OpenAlex, François Brémond has authored 133 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 99 papers in Computer Vision and Pattern Recognition, 35 papers in Artificial Intelligence and 21 papers in Psychiatry and Mental health. Recurrent topics in François Brémond's work include Video Surveillance and Tracking Methods (54 papers), Human Pose and Action Recognition (50 papers) and Anomaly Detection Techniques and Applications (32 papers). François Brémond is often cited by papers focused on Video Surveillance and Tracking Methods (54 papers), Human Pose and Action Recognition (50 papers) and Anomaly Detection Techniques and Applications (32 papers). François Brémond collaborates with scholars based in France, United States and Netherlands. François Brémond's co-authors include Monique Thonnat, Somboon Hongeng, Ram Nevatia, Etienne Corvée, Sławomir Bąk, Antitza Dantcheva, Gérard Medioni, I. Cohen, R. Nevatia and Piotr Biliński and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and Expert Systems with Applications.

In The Last Decade

François Brémond

123 papers receiving 2.4k citations

Peers

François Brémond
Hubert P. H. Shum United Kingdom
Ahmad Lotfi United Kingdom
Fani Deligianni United Kingdom
Oresti Baños Spain
Jesse S. Jin Australia
Guan Huang China
Marcos Faúndez-Zanuy Spain
Bogdan Ionescu Romania
Maheshkumar H. Kolekar India
Pritee Khanna India
Hubert P. H. Shum United Kingdom
François Brémond
Citations per year, relative to François Brémond François Brémond (= 1×) peers Hubert P. H. Shum

Countries citing papers authored by François Brémond

Since Specialization
Citations

This map shows the geographic impact of François Brémond'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 François Brémond with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites François Brémond more than expected).

Fields of papers citing papers by François Brémond

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by François Brémond. 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 François Brémond. The network helps show where François Brémond may publish in the future.

Co-authorship network of co-authors of François Brémond

This figure shows the co-authorship network connecting the top 25 collaborators of François Brémond. A scholar is included among the top collaborators of François Brémond 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 François Brémond. François Brémond 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.
Funk, M., Shogo Okada, François Brémond, et al.. (2025). MultiMediate '25: Cross-cultural Multi-domain Engagement Estimation. SPIRE - Sciences Po Institutional REpository. 14150–14155. 2 indexed citations
2.
Frey, Sébastien, Wen Bin Wei, Evren Ekmekçi, et al.. (2025). Optimizing intraoperative AI: evaluation of YOLOv8 for real-time recognition of robotic and laparoscopic instruments. Journal of Robotic Surgery. 19(1). 131–131. 1 indexed citations
3.
Brémond, François, et al.. (2024). UnWarpME: Unsupervised warping map estimation in real-world scenarios. Expert Systems with Applications. 257. 125042–125042. 1 indexed citations
4.
Yang, Di, et al.. (2024). LIA: Latent Image Animator. IEEE Transactions on Pattern Analysis and Machine Intelligence. 46(12). 10829–10844. 12 indexed citations
5.
Yang, Di, Yaohui Wang, Antitza Dantcheva, et al.. (2024). View-Invariant Skeleton Action Representation Learning via Motion Retargeting. International Journal of Computer Vision. 132(7). 2351–2366. 6 indexed citations
6.
Chen, Hao, François Brémond, Nicu Sebe, & Shiliang Zhang. (2024). Anti-Forgetting Adaptation for Unsupervised Person Re-Identification. IEEE Transactions on Pattern Analysis and Machine Intelligence. 47(2). 1056–1072.
7.
Yang, Di, Yaohui Wang, Quan Kong, et al.. (2023). Self-Supervised Video Representation Learning via Latent Time Navigation. Proceedings of the AAAI Conference on Artificial Intelligence. 37(3). 3118–3126. 2 indexed citations
8.
Calcagno, Vincent, et al.. (2023). TrichANet: An Attentive Network for Trichogramma Classification. 864–872. 1 indexed citations
9.
Brémond, François, et al.. (2022). Video-based Behavior Understanding of Children for Objective Diagnosis of Autism. HAL (Le Centre pour la Communication Scientifique Directe). 1 indexed citations
10.
Dai, Rui, et al.. (2022). MS-TCT: Multi-Scale Temporal ConvTransformer for Action Detection. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 20009–20019. 54 indexed citations
11.
Das, Abhijit, Xuesong Niu, Antitza Dantcheva, et al.. (2021). A Spatio-Temporal Approach for Apathy Classification. IEEE Transactions on Circuits and Systems for Video Technology. 32(5). 2561–2573. 6 indexed citations
12.
Caetano, Carlos, et al.. (2019). SkeleMotion: A New Representation of Skeleton Joint Sequences based on Motion Information for 3D Action Recognition. arXiv (Cornell University). 1–8. 10 indexed citations
13.
Das, Srijan, et al.. (2018). A Fusion of Appearance based CNNs and Temporal evolution of Skeleton with LSTM for Daily Living Action Recognition.. arXiv (Cornell University). 3 indexed citations
14.
Kenigsberg, Paul-Ariel, Jean‐Pierre Aquino, François Brémond, et al.. (2017). Assistive Technologies to Address Capabilities of People with Dementia: From Research to Practice. Dementia. 18(4). 1568–1595. 43 indexed citations
15.
Crispim-Junior, Carlos, Γεώργιος Μεδίτσκος, Alexia Briassouli, et al.. (2016). Semantic Event Fusion of Different Visual Modality Concepts for Activity Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence. 38(8). 1598–1611. 30 indexed citations
16.
Sacco, Guillaume, Grégory Ben-Sadoun, François Brémond, et al.. (2015). The Role of Information and Communication Technologies in Clinical Trials with Patients with Alzheimer’s Disease and Related Disorders. Frontiers in Aging Neuroscience. 7. 110–110. 10 indexed citations
17.
Robert, Philippe, Sandrine Andrieu, François Brémond, et al.. (2013). Recommendations for ICT use in Alzheimer's disease assessment: Monaco CTAD expert meeting. The journal of nutrition health & aging. 17(8). 653–660. 30 indexed citations
18.
Sacco, Guillaume, Nicole Darmon, Arnaud Dechamps, et al.. (2012). Detection of activities of daily living impairment in Alzheimer's disease and mild cognitive impairment using information and communication technology. SHILAP Revista de lepidopterología. 5 indexed citations
19.
Mulin, Emmanuel, Iracema Leroi, Renaud David, et al.. (2012). Automatic video monitoring system for assessment of Alzheimer's Disease symptoms. The journal of nutrition health & aging. 16(3). 213–218. 21 indexed citations
20.
Brémond, François, et al.. (2006). Video-understanding framework for automatic behavior recognition. Behavior Research Methods. 38(3). 416–426. 48 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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