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
- 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)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/2021.findings-acl.370.pdf
- Code
- pytorch/fairseq
- Data
- COIN, CrossTask, HowTo100M, MSR-VTT, YouCook2