François Brémond

1.5k total citations
33 papers, 856 citations indexed

About

François Brémond is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Biomedical Engineering. According to data from OpenAlex, François Brémond has authored 33 papers receiving a total of 856 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Computer Vision and Pattern Recognition, 7 papers in Artificial Intelligence and 6 papers in Biomedical Engineering. Recurrent topics in François Brémond's work include Human Pose and Action Recognition (18 papers), Video Surveillance and Tracking Methods (14 papers) and Context-Aware Activity Recognition Systems (9 papers). François Brémond is often cited by papers focused on Human Pose and Action Recognition (18 papers), Video Surveillance and Tracking Methods (14 papers) and Context-Aware Activity Recognition Systems (9 papers). François Brémond collaborates with scholars based in France, United Kingdom and United States. François Brémond's co-authors include Monique Thonnat, Benoit Lagadec, Hao Chen, Serhan Coşar, Luís Otávio Álvares, Vânia Bogorny, Etienne Corvée, Mohamed Kaâniche, Bernard Boulay and James Ferryman and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Sensors and Pattern Recognition.

In The Last Decade

François Brémond

32 papers receiving 824 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
François Brémond France 14 676 278 206 107 58 33 856
Bogdan Kwolek Poland 13 844 1.2× 272 1.0× 530 2.6× 62 0.6× 29 0.5× 60 1.0k
Barnan Das United States 10 419 0.6× 210 0.8× 97 0.5× 142 1.3× 39 0.7× 15 663
Juan Manuel Gálvez Spain 8 362 0.5× 139 0.5× 198 1.0× 90 0.8× 51 0.9× 10 667
Alexandros André Chaaraoui Spain 11 659 1.0× 250 0.9× 225 1.1× 39 0.4× 43 0.7× 14 769
Alain St-Arnaud Canada 9 835 1.2× 236 0.8× 504 2.4× 81 0.8× 12 0.2× 14 936
Pau Climent-Pérez Spain 10 465 0.7× 191 0.7× 161 0.8× 46 0.4× 18 0.3× 23 570
Bessam Abdulrazak Canada 12 248 0.4× 77 0.3× 154 0.7× 182 1.7× 22 0.4× 79 614
Mohamed E. Hussein Egypt 15 772 1.1× 316 1.1× 346 1.7× 22 0.2× 55 0.9× 39 1.0k
M. Harville United States 17 883 1.3× 117 0.4× 70 0.3× 32 0.3× 35 0.6× 35 1.1k
Gerald Pirkl Germany 13 696 1.0× 247 0.9× 215 1.0× 258 2.4× 122 2.1× 26 984

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.
Dai, Rui, et al.. (2024). Human-Scene Network: A novel baseline with self-rectifying loss for weakly supervised video anomaly detection. Computer Vision and Image Understanding. 241. 103955–103955. 10 indexed citations
2.
Mohammadzade, Hoda, et al.. (2024). EEG classification with limited data: A deep clustering approach. Pattern Recognition. 157. 110934–110934. 3 indexed citations
3.
Ferrari, Laura M., et al.. (2024). Video Representation Learning for Conversational Facial Expression Recognition Guided by Multiple View Reconstruction. SPIRE - Sciences Po Institutional REpository. 4693–4702.
4.
Thümmler, Susanne, et al.. (2022). Video-based Behavior Understanding of Children for Objective Diagnosis of Autism. 475–484. 24 indexed citations
5.
Fraïssé, R., et al.. (2022). Transforming Temporal Embeddings to Keypoint Heatmaps for Detection of Tiny Vehicles in Wide Area Motion Imagery (WAMI) Sequences. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). 35. 1431–1440. 3 indexed citations
6.
Dai, Rui, et al.. (2022). THORN: Temporal Human-Object Relation Network for Action Recognition. 2022 26th International Conference on Pattern Recognition (ICPR). 3303–3309. 1 indexed citations
7.
Chen, Hao, Benoit Lagadec, & François Brémond. (2021). ICE: Inter-instance Contrastive Encoding for Unsupervised Person Re-identification. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 14940–14949. 189 indexed citations
8.
Das, Srijan, et al.. (2021). Weakly-supervised Joint Anomaly Detection and Classification. arXiv (Cornell University). 1–7. 17 indexed citations
9.
Coşar, Serhan, et al.. (2016). Toward Abnormal Trajectory and Event Detection in Video Surveillance. IEEE Transactions on Circuits and Systems for Video Technology. 27(3). 683–695. 134 indexed citations
10.
Bąk, Sławomir, et al.. (2015). Person re-identification by pose priors. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9399. 93990H–93990H. 10 indexed citations
11.
Kaâniche, Mohamed & François Brémond. (2012). Recognizing Gestures by Learning Local Motion Signatures of HOG Descriptors. IEEE Transactions on Pattern Analysis and Machine Intelligence. 34(11). 2247–2258. 29 indexed citations
12.
Sacco, Guillaume, et al.. (2012). Detection of activities of daily living impairment in Alzheimer's disease and mild cognitive impairment using information and communication technology. Clinical Interventions in Aging. 7. 539–539. 60 indexed citations
13.
Corvée, Etienne, et al.. (2011). Boosted human re-identification using Riemannian manifolds. Image and Vision Computing. 30(6-7). 443–452. 60 indexed citations
14.
Brémond, François, et al.. (2011). Video Activity Recognition Framework for assessing motor behavioural disorders in Alzheimer Disease Patients. HAL (Le Centre pour la Communication Scientifique Directe). 9. 1 indexed citations
15.
Le, Thi‐Lan, Alain Boucher, Monique Thonnat, & François Brémond. (2010). Surveillance video retrieval: what we have already done?. HAL (Le Centre pour la Communication Scientifique Directe). 5 indexed citations
16.
Brémond, François, et al.. (2010). An Activity Monitoring System for Real Elderly at Home: Validation Study. 278–285. 34 indexed citations
17.
Brémond, François, et al.. (2009). A computer system to monitor older adults at home: Preliminary results. Gerontechnology. 8(3). 23 indexed citations
18.
Brémond, François, et al.. (2009). Multisensor Fusion for Monitoring Elderly Activities at Home. HAL (Le Centre pour la Communication Scientifique Directe). 32. 98–103. 29 indexed citations
19.
Brémond, François, et al.. (2007). Multi-sensors Analysis for Everyday Activity Monitoring. 7 indexed citations
20.
Brémond, François, et al.. (2002). Human Behaviour Visualisation and Simulation for Automatic Video Understanding.. SPIRE - Sciences Po Institutional REpository. 485–492. 8 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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