"Vid2Seq: Large-Scale Pretraining of a Visual Language Model for Dense ..."

Antoine Yang et al. (2023)

> Home

Details and statistics

DOI: 10.1109/CVPR52729.2023.01032

access: closed

type: Conference or Workshop Paper

metadata version: 2023-08-29

- view
  - electronic edition via DOI
  - unpaywalled version
  authority control:
- export record
  dblp key:
  - conf/cvpr/YangNSMPLSS23
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/conf/cvpr/YangNSMPLSS23
Antoine Yang, Arsha Nagrani, Paul Hongsuck Seo, Antoine Miech, Jordi Pont-Tuset, Ivan Laptev, Josef Sivic, Cordelia Schmid:
Vid2Seq: Large-Scale Pretraining of a Visual Language Model for Dense Video Captioning. CVPR 2023: 10714-10726

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.