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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
10 papers · 1 filter
GEPS: Boosting Generalization in Parametric PDE Neural Solvers through Adaptive Conditioning
Armand Kassaï Koupaï, Jorge Mifsut Benet, Yuan Yin +2
Solving parametric partial differential equations (PDEs) presents significant challenges for data-driven methods due to the sensitivity of spatio-temporal dynamics to variations in…
Expected Improvement applied to an industrialcontext -- Prediction of new geometries increasing theefficiency of fans
Agnès Lagnoux, T. M. Ngoc Nguyen, Bruno Demory +1
In automotive industry, client needs evolve quickly in a competitiveness context, particularly, regarding the fan involved in the engine cooling module. This study has been done in…
CLIP's Visual Embedding Projector is a Few-shot Cornucopia
Mohammad Fahes, Tuan-Hung Vu, Andrei Bursuc +2
We introduce ProLIP, a simple and architecture-agnostic method for adapting contrastively pretrained vision-language models, such as CLIP, to few-shot classification. ProLIP fine-t…
Annealed Winner-Takes-All for Motion Forecasting
Yihong Xu, Victor Letzelter, Mickaël Chen +2
In autonomous driving, motion prediction aims at forecasting the future trajectories of nearby agents, helping the ego vehicle to anticipate behaviors and drive safely. A key chall…
Lost and Found: Overcoming Detector Failures in Online Multi-Object Tracking
Lorenzo Vaquero, Yihong Xu, Xavier Alameda-Pineda +2
Multi-object tracking (MOT) endeavors to precisely estimate the positions and identities of multiple objects over time. The prevailing approach, tracking-by-detection (TbD), first…
GalLoP: Learning Global and Local Prompts for Vision-Language Models
Marc Lafon, Elias Ramzi, Clément Rambour +2
Prompt learning has been widely adopted to efficiently adapt vision-language models (VLMs), e.g. CLIP, for few-shot image classification. Despite their success, most prompt learnin…