Yoann Baveye
Impact in
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- Emotion and Mood Recognition
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- Video Analysis and Summarization
- Human Pose and Action Recognition
- Image and Video Quality Assessment
- Video Surveillance and Tracking Methods
Papers in
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- Image and Video Quality Assessment 3
- Video Analysis and Summarization 2
- Generative Adversarial Networks and Image Synthesis 2
- Data Visualization and Analytics 1
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- Emotion and Mood Recognition 3
- Co-authors
- Emmanuel Dellandréa (5 shared papers)Christel Chamaret (4 shared papers)Liming Chen (3 shared papers)Lukáš Krasula (2 shared papers)Mats Sjöberg (2 shared papers)Liming Chen (1 shared paper)Jing Li (1 shared paper)Patrick Le Callet (1 shared paper)
- Journals
- IEEE Transactions on Multimedia (2 papers)IEEE Transactions on Affective Computing (2 papers)Aaltodoc (Aalto University) (1 paper)HAL (Le Centre pour la Communication Scientifique Directe) (1 paper)
In The Last Decade
Yoann Baveye
7 papers receiving 286 citations
Peers
Comparison fields: 5 of 38
- Experimental and Cognitive Psychology 164
- Computer Vision and Pattern Recognition 170
- Signal Processing 79
- Cognitive Neuroscience 68
- Human-Computer Interaction 16
Countries citing papers authored by Yoann Baveye
This map shows the geographic impact of Yoann Baveye'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 Yoann Baveye with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yoann Baveye more than expected).
Fields of papers citing papers by Yoann Baveye
This network shows the impact of papers produced by Yoann Baveye. 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 Yoann Baveye. The network helps show where Yoann Baveye may publish in the future.
Co-authors
The 10 scholars most cited alongside Yoann Baveye, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 195 | |
| 2 | 2017 | 49 | |
| 3 | The MediaEval 2016 Emotional Impact of Movies Task | 2016 | 26 |
| 4 | 2019 | 18 | |
| 5 | 2019 | 9 | |
| 6 | 2019 | 3 | |
| 7 | Deep Learning vs. Kernel Methods: Performance for Emotion Prediction in Videos | 2015 | 1 |
About Yoann Baveye
Yoann Baveye is a scholar working on Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology, Social Psychology, Signal Processing and Literature and Literary Theory, having authored 7 papers that have together received 301 indexed citations. Recurring topics across this work include Image and Video Quality Assessment (3 papers), Emotion and Mood Recognition (3 papers), Emotions and Moral Behavior (2 papers), Video Analysis and Summarization (2 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Humor Studies and Applications (1 paper), Data Visualization and Analytics (1 paper) and Media Influence and Health (1 paper). The work is most often cited by research in Experimental and Cognitive Psychology (164 citations), Computer Vision and Pattern Recognition (170 citations), Signal Processing (79 citations), Cognitive Neuroscience (68 citations) and Human-Computer Interaction (16 citations). Yoann Baveye has collaborated with scholars based in France, Germany and Finland. Frequent co-authors include Emmanuel Dellandréa, Christel Chamaret, Liming Chen, Lukáš Krasula, Mats Sjöberg, Liming Chen, Jing Li, Patrick Le Callet, Zhi Li and Zhongzhe Xiao. Their work appears in journals such as IEEE Transactions on Multimedia, IEEE Transactions on Affective Computing, Aaltodoc (Aalto University) and HAL (Le Centre pour la Communication Scientifique Directe).
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.