2 citations · 3 across the 15 of their papers we have counts for
16 papers
Spot-the-shift: Evaluating Grounded Image Difference Captioning of Long-term Changes
Benedetta Liberatori, Nermin Samet, Paolo Rota +4
Long-term change understanding from images of the same place revisited over time is a challenging task with applications in map maintenance and urban infrastructure monitoring. Pri…
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…
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…
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…
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…
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…
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…
Retrieval-enriched zero-shot image classification in low-resource domains
Nicola Dall'Asen, Yiming Wang, Enrico Fini +1
Low-resource domains, characterized by scarce data and annotations, present significant challenges for language and visual understanding tasks, with the latter much under-explored…
Text-Enhanced Zero-Shot Action Recognition: A training-free approach
Massimo Bosetti, Shibingfeng Zhang, Benedetta Liberatori +3
Vision-language models (VLMs) have demonstrated remarkable performance across various visual tasks, leveraging joint learning of visual and textual representations. While these mod…
Test-Time Zero-Shot Temporal Action Localization
Benedetta Liberatori, Alessandro Conti, Paolo Rota +2
Zero-Shot Temporal Action Localization (ZS-TAL) seeks to identify and locate actions in untrimmed videos unseen during training. Existing ZS-TAL methods involve fine-tuning a model…
Harnessing Large Language Models for Training-free Video Anomaly Detection
Luca Zanella, Willi Menapace, Massimiliano Mancini +2
Video anomaly detection (VAD) aims to temporally locate abnormal events in a video. Existing works mostly rely on training deep models to learn the distribution of normality with e…
Snap Video: Scaled Spatiotemporal Transformers for Text-to-Video Synthesis
Willi Menapace, Aliaksandr Siarohin, Ivan Skorokhodov +8
Contemporary models for generating images show remarkable quality and versatility. Swayed by these advantages, the research community repurposes them to generate videos. Since vide…
Diversified in-domain synthesis with efficient fine-tuning for few-shot classification
Victor G. Turrisi da Costa, Nicola Dall'Asen, Yiming Wang +2
Few-shot image classification aims to learn an image classifier using only a small set of labeled examples per class. A recent research direction for improving few-shot classifiers…
Collaborative Neural Painting
Nicola Dall'Asen, Willi Menapace, Elia Peruzzo +3
The process of painting fosters creativity and rational planning. However, existing generative AI mostly focuses on producing visually pleasant artworks, without emphasizing the pa…
Novel class discovery meets foundation models for 3D semantic segmentation
Luigi Riz, Cristiano Saltori, Yiming Wang +2
The task of Novel Class Discovery (NCD) in semantic segmentation entails training a model able to accurately segment unlabelled (novel) classes, relying on the available supervisio…
Delving into CLIP latent space for Video Anomaly Recognition
Luca Zanella, Benedetta Liberatori, Willi Menapace +3
We tackle the complex problem of detecting and recognising anomalies in surveillance videos at the frame level, utilising only video-level supervision. We introduce the novel metho…