Séverine Dubuisson

631 total citations
23 papers, 258 citations indexed

About

Séverine Dubuisson is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Experimental and Cognitive Psychology. According to data from OpenAlex, Séverine Dubuisson has authored 23 papers receiving a total of 258 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Computer Vision and Pattern Recognition, 8 papers in Artificial Intelligence and 4 papers in Experimental and Cognitive Psychology. Recurrent topics in Séverine Dubuisson's work include Video Surveillance and Tracking Methods (7 papers), Human Pose and Action Recognition (4 papers) and Emotion and Mood Recognition (4 papers). Séverine Dubuisson is often cited by papers focused on Video Surveillance and Tracking Methods (7 papers), Human Pose and Action Recognition (4 papers) and Emotion and Mood Recognition (4 papers). Séverine Dubuisson collaborates with scholars based in France, Réunion and Poland. Séverine Dubuisson's co-authors include Arnaud Dapogny, Kévin Bailly, Richard Kulpa, Catherine Achard, David Cohen, Michel Spodenkiewicz, Mohamed Chétouani, Jonathan Aigrain, Marcin Detyniecki and Christophe Gonzales and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Access and Journal of Investigative Dermatology.

In The Last Decade

Séverine Dubuisson

20 papers receiving 252 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Séverine Dubuisson France 8 112 82 58 44 30 23 258
Frerk Saxen Germany 11 185 1.7× 83 1.0× 43 0.7× 18 0.4× 49 1.6× 20 347
Panagiotis P. Filntisis Greece 11 168 1.5× 123 1.5× 73 1.3× 33 0.8× 26 0.9× 36 338
Suja Palaniswamy India 13 163 1.5× 157 1.9× 92 1.6× 39 0.9× 20 0.7× 63 432
Gibrán Fuentes-Pineda Mexico 9 54 0.5× 69 0.8× 103 1.8× 50 1.1× 12 0.4× 36 251
Guanming Lu China 11 205 1.8× 199 2.4× 100 1.7× 53 1.2× 18 0.6× 66 452
Esam Ghaleb Netherlands 10 168 1.5× 135 1.6× 87 1.5× 83 1.9× 34 1.1× 17 309
Zengwei Yao China 6 42 0.4× 153 1.9× 90 1.6× 115 2.6× 22 0.7× 12 262
Georges Matar Canada 6 46 0.4× 46 0.6× 35 0.6× 25 0.6× 105 3.5× 8 305
Yassine Ben Ayed Tunisia 10 56 0.5× 90 1.1× 142 2.4× 135 3.1× 20 0.7× 33 350
SeongKi Kim South Korea 9 68 0.6× 18 0.2× 61 1.1× 16 0.4× 35 1.2× 33 276

Countries citing papers authored by Séverine Dubuisson

Since Specialization
Citations

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

Fields of papers citing papers by Séverine Dubuisson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Séverine Dubuisson

This figure shows the co-authorship network connecting the top 25 collaborators of Séverine Dubuisson. A scholar is included among the top collaborators of Séverine Dubuisson 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 Séverine Dubuisson. Séverine Dubuisson 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.
Thümmler, Susanne, et al.. (2025). The Feasibility of RGB-D Gaze Intention Measurement in Children with Autism Using Azure Kinect. Bioengineering. 12(4). 370–370.
2.
Merad, Djamal, et al.. (2024). In-Depth Analysis of GAF-Net: Comparative Fusion Approaches in Video-Based Person Re-Identification. Algorithms. 17(8). 352–352. 1 indexed citations
3.
Dubuisson, Séverine, et al.. (2024). Enhancing Facial Expression Recognition through Light Field Cameras. Sensors. 24(17). 5724–5724. 1 indexed citations
4.
Monnier, Jilliana, M.‐A. Richard, Jean‐Jacques Grob, et al.. (2024). Fusion between an Algorithm Based on the Characterization of Melanocytic Lesions' Asymmetry with an Ensemble of Convolutional Neural Networks for Melanoma Detection. Journal of Investigative Dermatology. 144(7). 1600–1607.e2. 2 indexed citations
5.
Merad, Djamal, et al.. (2024). GAF-Net: Video-Based Person Re-Identification via Appearance and Gait Recognitions. SPIRE - Sciences Po Institutional REpository. 2 indexed citations
6.
Merad, Djamal, et al.. (2023). Facial Expression Recognition Using Light Field Cameras: A Comparative Study of Deep Learning Architectures. SPIRE - Sciences Po Institutional REpository. 4 indexed citations
7.
Franchi, Gianni, et al.. (2023). Encoding the Latent Posterior of Bayesian Neural Networks for Uncertainty Quantification. IEEE Transactions on Pattern Analysis and Machine Intelligence. 46(4). 2027–2040. 14 indexed citations
8.
Franchi, Gianni, et al.. (2022). Latent Discriminant deterministic Uncertainty. arXiv (Cornell University). 1 indexed citations
9.
Franchi, Gianni, et al.. (2021). One Versus All for Deep Neural Network for Uncertainty (OVNNI) Quantification. IEEE Access. 10. 7300–7312. 6 indexed citations
10.
Franchi, Gianni, et al.. (2020). Tracking Hundreds of People in Densely Crowded Scenes With Particle Filtering Supervising Deep Convolutional Neural Networks. HAL (Le Centre pour la Communication Scientifique Directe). 2071–2075. 1 indexed citations
11.
Dapogny, Arnaud, Charline Grossard, Stéphanie Hun, et al.. (2019). On Automatically Assessing Children's Facial Expressions Quality: A Study, Database, and Protocol. Frontiers in Computer Science. 1. 8 indexed citations
12.
Achard, Catherine, et al.. (2017). Automatic evaluation of sports motion: A generic computation of spatial and temporal errors. Image and Vision Computing. 64. 67–78. 9 indexed citations
13.
Spodenkiewicz, Michel, et al.. (2017). Distinguish self- and hetero-perceived stress through behavioral imaging and physiological features. Progress in Neuro-Psychopharmacology and Biological Psychiatry. 82. 107–114. 7 indexed citations
14.
Dapogny, Arnaud, Kévin Bailly, & Séverine Dubuisson. (2017). Multi-Output Random Forests for Facial Action Unit Detection. 45. 135–140. 3 indexed citations
15.
Dapogny, Arnaud, Kévin Bailly, & Séverine Dubuisson. (2016). Confidence-Weighted Local Expression Predictions for Occlusion Handling\n in Expression Recognition and Action Unit detection. arXiv (Cornell University). 53 indexed citations
16.
Aigrain, Jonathan, Michel Spodenkiewicz, Séverine Dubuisson, et al.. (2016). Multimodal Stress Detection from Multiple Assessments. IEEE Transactions on Affective Computing. 9(4). 491–506. 61 indexed citations
17.
Dubuisson, Séverine & Christophe Gonzales. (2015). A survey of datasets for visual tracking. Machine Vision and Applications. 27(1). 23–52. 15 indexed citations
18.
Dubuisson, Séverine, et al.. (2015). A Self-adaptive Likelihood Function for Tracking with Particle Filter. 446–453. 1 indexed citations
19.
Dubuisson, Séverine, et al.. (2012). Fuzzy spatial constraints and ranked partitioned sampling approach for multiple object tracking. Computer Vision and Image Understanding. 116(10). 1076–1094. 5 indexed citations
20.
Fabrizio, Jonathan, et al.. (2011). Motion compensation based on tangent distance prediction for video compression. Signal Processing Image Communication. 27(2). 153–171. 10 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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