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Angelique Loesch
Angelique Loesch
Research Engineer, CEA LIST
Verified email at cea.fr
Title
Cited by
Cited by
Year
Padim: a patch distribution modeling framework for anomaly detection and localization
T Defard, A Setkov, A Loesch, R Audigier
International Conference on Pattern Recognition, 475-489, 2021
6882021
Unsupervised domain adaptation for person re-identification through source-guided pseudo-labeling
F Dubourvieux, R Audigier, A Loesch, S Ainouz, S Canu
2020 25th International Conference on Pattern Recognition (ICPR), 4957-4964, 2021
232021
Vulnerability of person re-identification models to metric adversarial attacks
Q Bouniot, R Audigier, A Loesch
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
232020
Generic edgelet-based tracking of 3D objects in real-time
A Loesch, S Bourgeois, V Gay-Bellile, M Dhome
2015 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2015
162015
Improving unsupervised domain adaptive re-identification via source-guided selection of pseudo-labeling hyperparameters
F Dubourvieux, A Loesch, R Audigier, S Ainouz, S Canu
IEEE Access 9, 149780-149795, 2021
102021
End-to-end person search sequentially trained on aggregated dataset
A Loesch, J Rabarisoa, R Audigier
2019 IEEE International Conference on Image Processing (ICIP), 4574-4578, 2019
102019
A formal approach to good practices in pseudo-labeling for unsupervised domain adaptive re-identification
F Dubourvieux, R Audigier, A Loesch, S Ainouz, S Canu
Computer Vision and Image Understanding 223, 103527, 2022
92022
Brightflow: Brightness-change-aware unsupervised learning of optical flow
R Marsal, F Chabot, A Loesch, H Sahbi
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023
82023
Optimal transport as a defense against adversarial attacks
Q Bouniot, R Audigier, A Loesch
2020 25th International Conference on Pattern Recognition (ICPR), 5044-5051, 2021
82021
PaDiM: A Patch Distribution Modeling Framework for Anomaly Detection and Localization. arXiv 2020
T Defard, A Setkov, A Loesch, R Audigier
arXiv preprint arXiv:2011.08785, 0
8
Improving few-shot learning through multi-task representation learning theory
Q Bouniot, I Redko, R Audigier, A Loesch, A Habrard
European Conference on Computer Vision, 435-452, 2022
72022
Localization of 3D objects using model-constrained SLAM
A Loesch, S Bourgeois, V Gay-Bellile, O Gomez, M Dhome
Machine Vision and Applications 29 (7), 1041-1068, 2018
72018
Describe me if you can! Characterized instance-level human parsing
A Loesch, R Audigier
2021 IEEE International Conference on Image Processing (ICIP), 2528-2532, 2021
62021
Towards few-annotation learning for object detection: are transformer-based models more efficient?
Q Bouniot, A Loesch, R Audigier, A Habrard
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023
52023
Towards better understanding meta-learning methods through multi-task representation learning theory
Q Bouniot, I Redko, R Audigier, A Loesch, Y Zotkin, A Habrard
arXiv preprint arXiv:2010.01992, 2020
52020
Object-centric and memory-guided normality reconstruction for video anomaly detection
K Bergaoui, Y Naji, A Setkov, A Loesch, M Gouiffès, R Audigier
2022 IEEE International Conference on Image Processing (ICIP), 2691-2695, 2022
42022
Cumulative unsupervised multi-domain adaptation for Holstein cattle re-identification
F Dubourvieux, G Lapouge, A Loesch, B Luvison, R Audigier
Artificial Intelligence in Agriculture 10, 46-60, 2023
12023
Proposal-contrastive pretraining for object detection from fewer data
Q Bouniot, R Audigier, A Loesch, A Habrard
arXiv preprint arXiv:2310.16835, 2023
12023
Spatio-temporal predictive tasks for abnormal event detection in videos
Y Naji, A Setkov, A Loesch, M Gouiffès, R Audigier
2022 18th IEEE International Conference on Advanced Video and Signal Based …, 2022
12022
Towards the engineering of trustworthy AI applications for critical systems-The Confiance. ai program
M Adedjouma, JL Adam, P Aknin, C Alix, X Baril, G Bernard, Y Bonhomme, ...
12022
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