7 citations · 7 across the 5 of their papers we have counts for
4 papers · 1 filter
Physically-admissible polarimetric data augmentation for road-scene analysis
Cyprien Ruffino, Rachel Blin, Samia Ainouz +4
Polarimetric imaging, along with deep learning, has shown improved performances on different tasks including scene analysis. However, its robustness may be questioned because of th…
Improving Unsupervised Domain Adaptive Re-Identification via Source-Guided Selection of Pseudo-Labeling Hyperparameters
Fabian Dubourvieux, Angélique Loesch, Romaric Audigier +2
Unsupervised Domain Adaptation (UDA) for re-identification (re-ID) is a challenging task: to avoid a costly annotation of additional data, it aims at transferring knowledge from a…
Unsupervised Domain Adaptation for Person Re-Identification through Source-Guided Pseudo-Labeling
Fabian Dubourvieux, Romaric Audigier, Angelique Loesch +2
Person Re-Identification (re-ID) aims at retrieving images of the same person taken by different cameras. A challenge for re-ID is the performance preservation when a model is used…
Road scenes analysis in adverse weather conditions by polarization-encoded images and adapted deep learning
Rachel Blin, Samia Ainouz, Stéphane Canu +1
Object detection in road scenes is necessary to develop both autonomous vehicles and driving assistance systems. Even if deep neural networks for recognition task have shown great…