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cs.CV2026

HAC: Parameter-Efficient Hyperbolic Adaptation of CLIP for Zero-Shot VQA

Francesco Dibitonto, Cigdem Beyan, Vittorio Murino

Recent advances in representation learning have shown that hyperbolic geometry can offer a more expressive alternative to the Euclidean embeddings used in CLIP models, capturing hi…

cs.CV2026

Geometry-Conditioned Diffusion for Occlusion-Robust In-Bed Pose Estimation

Navid Aslankhani Khameneh, Marco Carletti, Cigdem Beyan

Robust in-bed human pose estimation under blanket occlusion remains challenging due to the scarcity of reliable labeled training data for heavily covered poses. Existing approaches…

cs.CV2026

Discriminator-Guided Adaptive Diffusion for Source-Free Test-Time Adaptation under Image Corruptions

Francesco Olivato, Cigdem Beyan, Vittorio Murino

In this work, we study Source-Free Unsupervised Domain Adaptation under corruption-induced domain shifts, where performance degradation is caused by natural image corruptions that…

cs.CV2026

Lifelong Imitation Learning with Multimodal Latent Replay and Incremental Adjustment

Fanqi Yu, Matteo Tiezzi, Tommaso Apicella +2

We introduce a lifelong imitation learning framework that enables continual policy refinement across sequential tasks under realistic memory and data constraints. Our approach depa…

cs.CV2025

Dynamic Scoring with Enhanced Semantics for Training-Free Human-Object Interaction Detection

Francesco Tonini, Lorenzo Vaquero, Alessandro Conti +2

Human-Object Interaction (HOI) detection aims to identify humans and objects within images and interpret their interactions. Existing HOI methods rely heavily on large datasets wit…

cs.CV2025

MADPOT: Medical Anomaly Detection with CLIP Adaptation and Partial Optimal Transport

Mahshid Shiri, Cigdem Beyan, Vittorio Murino

Medical anomaly detection (AD) is challenging due to diverse imaging modalities, anatomical variations, and limited labeled data. We propose a novel approach combining visual adapt…