5 papers
FLaRA: Predicting Future Latent Representations for Accident Anticipation
Lorenzo Caselli, Tomaso Trinci, Tommaso Bianconcini +4
Anticipating traffic accidents from dashcam videos is a critical challenge in intelligent transportation systems. Existing methods typically map visual context directly to a collis…
Preventing Latent Rehearsal Decay in Online Continual SSL with SOLAR
Giacomo Cignoni, Simone Magistri, Andrew D. Bagdanov +1
This paper explores Online Continual Self-Supervised Learning (OCSSL), a scenario in which models learn from continuous streams of unlabeled, non-stationary data, where methods typ…
Project and Mix: Task-Semantic Prototypes for Few-Shot Image Classification
Dipam Goswami, Simone Magistri, Gido M. van de Ven +4
Vision-language models like CLIP are trained with the objective of aligning text and image pairs. Beyond text prompts alone, recent works show that exploiting few-shot image embedd…
IsoCLIP: Decomposing CLIP Projectors for Efficient Intra-modal Alignment
Simone Magistri, Dipam Goswami, Marco Mistretta +3
Vision-Language Models like CLIP are extensively used for inter-modal tasks which involve both visual and text modalities. However, when the individual modality encoders are applie…
SpectralGCD: Spectral Concept Selection and Cross-modal Representation Learning for Generalized Category Discovery
Lorenzo Caselli, Marco Mistretta, Simone Magistri +1
Generalized Category Discovery (GCD) aims to identify novel categories in unlabeled data while leveraging a small labeled subset of known classes. Training a parametric classifier…