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- Centre National de la Recherche ScientifiqueFR13 papers
- Institut national de recherche en sciences et technologies du numériqueFR10 papers
- Sorbonne UniversitéFR8 papers
- Laboratoire d'Informatique Gaspard-MongeFR7 papers
- Télécom ParisFR6 papers
- Centre de Robotique5 papers
- Institut de Recherche en Informatique et Systèmes AléatoiresFR5 papers
- Université Gustave EiffelFR5 papers
- Hôpital Saint-MichelFR4 papers
- Laboratoire d’Informatique et SystèmesFR4 papers
- Laboratoire Traitement et Communication de l’InformationFR4 papers
- Technicolor (France)FR4 papers
13 papers · 1 filter
Artificial Dummies for Urban Dataset Augmentation
Antonín Vobecký, David Hurych, Michal Uřičář +2
Existing datasets for training pedestrian detectors in images suffer from limited appearance and pose variation. The most challenging scenarios are rarely included because they are…
Driving Behavior Explanation with Multi-level Fusion
Hédi Ben-Younes, Éloi Zablocki, Patrick Pérez +1
In this era of active development of autonomous vehicles, it becomes crucial to provide driving systems with the capacity to explain their decisions. In this work, we focus on gene…
OBoW: Online Bag-of-Visual-Words Generation for Self-Supervised Learning
Spyros Gidaris, Andrei Bursuc, Gilles Puy +3
Learning image representations without human supervision is an important and active research field. Several recent approaches have successfully leveraged the idea of making such a…
Encoding the latent posterior of Bayesian Neural Networks for uncertainty quantification
Gianni Franchi, Andrei Bursuc, Emanuel Aldea +2
Bayesian neural networks (BNNs) have been long considered an ideal, yet unscalable solution for improving the robustness and the predictive uncertainty of deep neural networks. Whi…
Detecting 32 Pedestrian Attributes for Autonomous Vehicles
Taylor Mordan, Matthieu Cord, Patrick Pérez +1
Pedestrians are arguably one of the most safety-critical road users to consider for autonomous vehicles in urban areas. In this paper, we address the problem of jointly detecting p…
Semi-Supervised Semantic Segmentation in Earth Observation: The MiniFrance Suite, Dataset Analysis and Multi-task Network Study
Javiera Castillo-Navarro, Bertrand Le Saux, Alexandre Boulch +2
The development of semi-supervised learning techniques is essential to enhance the generalization capacities of machine learning algorithms. Indeed, raw image data are abundant whi…