9 papers
Tracking Intermittent Particles with Self-Learned Visual Features
Raphael Reme, Victor Piriou, Alison Hanson +5
In time-lapse fluorescence imaging, single-particle-tracking is a powerful tool to monitor the dynamics of objects of interest, and extract information about biological processes.…
FlowID : Enhancing Forensic Identification with Latent Flow-Matching Models
Jules Ripoll, David Bertoin, Alasdair Newson +2
Every day, many people die under violent circumstances, whether from crimes, war, migration, or climate disasters. Medico-legal and law enforcement institutions document many portr…
Diff-CA: Separating Common and Salient Factors with Diffusion Models
Michaël Soumm, Alexandre Fournier Montgieux, Yunlong He +2
Contrastive Analysis aims to separate factors that are common between two data distributions from those that are salient to only one of them. Existing contrastive methods are based…
When Prompts Override Vision: Prompt-Induced Hallucinations in LVLMs
Pegah Khayatan, Jayneel Parekh, Arnaud Dapogny +3
Despite impressive progress in capabilities of large vision-language models (LVLMs), these systems remain vulnerable to hallucinations, i.e., outputs that are not grounded in the v…
Stochastic Orthogonal Regularization for deep projective priors
Ali Joundi, Yann Traonmilin, Alasdair Newson
Many crucial tasks of image processing and computer vision are formulated as inverse problems. Thus, it is of great importance to design fast and robust algorithms to solve these p…
Learning to Steer: Input-dependent Steering for Multimodal LLMs
Jayneel Parekh, Pegah Khayatan, Mustafa Shukor +3
Steering has emerged as a practical approach to enable post-hoc guidance of LLMs towards enforcing a specific behavior. However, it remains largely underexplored for multimodal LLM…