7 citations · 7 across the 5 of their papers we have counts for
5 papers · 1 filter
Leveraging Auxiliary Information in Text-to-Video Retrieval: A Review
Adriano Fragomeni, Dima Damen, Michael Wray
Text-to-Video (T2V) retrieval aims to identify the most relevant item from a gallery of videos based on a user's text query. Traditional methods rely solely on aligning video and t…
Leveraging Modality Tags for Enhanced Cross-Modal Video Retrieval
Adriano Fragomeni, Dima Damen, Michael Wray
Video retrieval requires aligning visual content with corresponding natural language descriptions. In this paper, we introduce Modality Auxiliary Concepts for Video Retrieval (MAC-…
Video Editing for Video Retrieval
Bin Zhu, Kevin Flanagan, Adriano Fragomeni +2
Though pre-training vision-language models have demonstrated significant benefits in boosting video-text retrieval performance from large-scale web videos, fine-tuning still plays…
ConTra: (Con)text (Tra)nsformer for Cross-Modal Video Retrieval
Adriano Fragomeni, Michael Wray, Dima Damen
In this paper, we re-examine the task of cross-modal clip-sentence retrieval, where the clip is part of a longer untrimmed video. When the clip is short or visually ambiguous, know…
Ego4D: Around the World in 3,000 Hours of Egocentric Video
Kristen Grauman, Andrew Westbury, Eugene Byrne +82
We introduce Ego4D, a massive-scale egocentric video dataset and benchmark suite. It offers 3,670 hours of daily-life activity video spanning hundreds of scenarios (household, outd…