89 citations
- Centre National de la Recherche ScientifiqueFR24 papers
- École Normale Supérieure Paris-SaclayFR24 papers
- Université Paris-SaclayFR22 papers
- Université Paris-SudFR6 papers
- École Nationale Supérieure de Techniques AvancéesFR5 papers
- Office National d'Études et de Recherches AérospatialesFR5 papers
- École Nationale Supérieure de Techniques Avancées ParisFR4 papers
- École Normale Supérieure de RennesFR4 papers
- Istituto Nazionale di Ricerca MetrologicaIT4 papers
- Laboratoire des signaux et systèmesFR4 papers
- Laboratoire Traitement et Communication de l’InformationFR4 papers
- SupélecFR4 papers
13 papers · 1 filter
Anomaly-Aware YOLO: A Frugal yet Robust Approach to Infrared Small Target Detection
Alina Ciocarlan, Sylvie Le Hégarat-Mascle, Sidonie Lefebvre
Infrared Small Target Detection (IRSTD) is a challenging task in defense applications, where complex backgrounds and tiny target sizes often result in numerous false alarms using c…
ICPR 2024 Competition on Domain Adaptation and GEneralization for Character Classification (DAGECC)
Sofia Marino, Jennifer Vandoni, Emanuel Aldea +3
In this companion paper for the DAGECC (Domain Adaptation and GEneralization for Character Classification) competition organized within the frame of the ICPR 2024 conference, we pr…
Self-Supervised Learning for Real-World Object Detection: a Survey
Alina Ciocarlan, Sidonie Lefebvre, Sylvie Le Hégarat-Mascle +1
Self-Supervised Learning (SSL) has emerged as a promising approach in computer vision, enabling networks to learn meaningful representations from large unlabeled datasets. SSL meth…
Robust infrared small target detection using self-supervised and a contrario paradigms
Alina Ciocarlan, Sylvie Le Hégarat-Mascle, Sidonie Lefebvre +1
Detecting small targets in infrared images poses significant challenges in defense applications due to the presence of complex backgrounds and the small size of the targets. Tradit…
The Robust Semantic Segmentation UNCV2023 Challenge Results
Xuanlong Yu, Yi Zuo, Zitao Wang +34
This paper outlines the winning solutions employed in addressing the MUAD uncertainty quantification challenge held at ICCV 2023. The challenge was centered around semantic segment…
Discretization-Induced Dirichlet Posterior for Robust Uncertainty Quantification on Regression
Xuanlong Yu, Gianni Franchi, Jindong Gu +1
Uncertainty quantification is critical for deploying deep neural networks (DNNs) in real-world applications. An Auxiliary Uncertainty Estimator (AuxUE) is one of the most effective…