15 citations · 16 across the 3 of their papers we have counts for
3 papers
Vid2Seq: Large-Scale Pretraining of a Visual Language Model for Dense Video Captioning
Antoine Yang, Arsha Nagrani, Paul Hongsuck Seo +5
In this work, we introduce Vid2Seq, a multi-modal single-stage dense event captioning model pretrained on narrated videos which are readily-available at scale. The Vid2Seq architec…
Connecting Vision and Language with Video Localized Narratives
Paul Voigtlaender, Soravit Changpinyo, Jordi Pont-Tuset +2
We propose Video Localized Narratives, a new form of multimodal video annotations connecting vision and language. In the original Localized Narratives, annotators speak and move th…
Video Swin Transformers for Egocentric Video Understanding @ Ego4D Challenges 2022
Maria Escobar, Laura Daza, Cristina González +2
We implemented Video Swin Transformer as a base architecture for the tasks of Point-of-No-Return temporal localization and Object State Change Classification. Our method achieved c…