activity
20242026
collaborators

10 papers

cs.CV2026

Zero-Shot Temporal Action Localization Through Textual Guidance

Benedetta Liberatori, Alessandro Conti, Lorenzo Vaquero +3

Zero-shot temporal action localization (ZS-TAL) consists of classifying and localizing actions in untrimmed videos, where action classes are unseen at training time. Existing work…

cs.CV2026

Specificity-aware reinforcement learning for fine-grained open-world classification

Samuele Angheben, Davide Berasi, Alessandro Conti +2

Classifying fine-grained visual concepts under open-world settings, i.e., without a predefined label set, demands models to be both accurate and specific. Recent reasoning Large Mu…

cs.CV2025

Training-free Online Video Step Grounding

Luca Zanella, Massimiliano Mancini, Yiming Wang +2

Given a task and a set of steps composing it, Video Step Grounding (VSG) aims to detect which steps are performed in a video. Standard approaches for this task require a labeled tr…

cs.CV2025

Training-Free Personalization via Retrieval and Reasoning on Fingerprints

Deepayan Das, Davide Talon, Yiming Wang +2

Vision Language Models (VLMs) have lead to major improvements in multimodal reasoning, yet they still struggle to understand user-specific concepts. Existing personalization method…

cs.CV2025

ConViS-Bench: Estimating Video Similarity Through Semantic Concepts

Benedetta Liberatori, Alessandro Conti, Lorenzo Vaquero +3

What does it mean for two videos to be similar? Videos may appear similar when judged by the actions they depict, yet entirely different if evaluated based on the locations where t…

cs.CV2025

Can Text-to-Video Generation help Video-Language Alignment?

Luca Zanella, Massimiliano Mancini, Willi Menapace +3

Recent video-language alignment models are trained on sets of videos, each with an associated positive caption and a negative caption generated by large language models. A problem…