3 citations · 7 across the 18 of their papers we have counts for
6 papers · 1 filter
One VLM to Keep it Learning: Generation and Balancing for Data-free Continual Visual Question Answering
Deepayan Das, Davide Talon, Massimiliano Mancini +2
Vision-Language Models (VLMs) have shown significant promise in Visual Question Answering (VQA) tasks by leveraging web-scale multimodal datasets. However, these models often strug…
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…
Automatic benchmarking of large multimodal models via iterative experiment programming
Alessandro Conti, Enrico Fini, Paolo Rota +3
Assessing the capabilities of large multimodal models (LMMs) often requires the creation of ad-hoc evaluations. Currently, building new benchmarks requires tremendous amounts of ma…
Vocabulary-free Image Classification and Semantic Segmentation
Alessandro Conti, Enrico Fini, Massimiliano Mancini +3
Large vision-language models revolutionized image classification and semantic segmentation paradigms. However, they typically assume a pre-defined set of categories, or vocabulary,…
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…