VLM: Task-agnostic Video-Language Model Pre-training for Video Understanding

Hu Xu, Gargi Ghosh, Po-Yao Huang, Prahal Arora, Masoumeh Aminzadeh, Christoph Feichtenhofer, Florian Metze, Luke Zettlemoyer


Anthology ID:
2021.findings-acl.370
Volume:
Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
Month:
August
Year:
2021
Address:
Online
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
4227–4239
Language:
URL:
https://aclanthology.org/2021.findings-acl.370
DOI:
10.18653/v1/2021.findings-acl.370
Bibkey:
Cite (ACL):
Hu Xu, Gargi Ghosh, Po-Yao Huang, Prahal Arora, Masoumeh Aminzadeh, Christoph Feichtenhofer, Florian Metze, and Luke Zettlemoyer. 2021. VLM: Task-agnostic Video-Language Model Pre-training for Video Understanding. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pages 4227–4239, Online. Association for Computational Linguistics.
Cite (Informal):
VLM: Task-agnostic Video-Language Model Pre-training for Video Understanding (Xu et al., Findings 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.findings-acl.370.pdf
Video:
 https://aclanthology.org/2021.findings-acl.370.mp4
Code
 pytorch/fairseq
Data
COINCrossTaskHowTo100MMSR-VTTYouCook2