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MSVD

Text-Video Retrieval (TVR) aims to align relevant video content with natural language queries. To date, most state-of-the-art TVR methods learn image-to-video transfer learning based on large-scale pre-trained vision-language models (e.g., CLIP). However, fully fine-tuning these pre-trained models for TVR incurs prohibitively expensive computation costs.

Data and Resources

Cite this as

Meng Cao, Long Chen, Mike Zheng Shou, Can Zhang, Yuexian Zou (2024). Dataset: MSVD. https://doi.org/10.57702/x9xwguf4

DOI retrieved: December 2, 2024

Additional Info

Field Value
Created December 2, 2024
Last update December 2, 2024
Defined In https://doi.org/10.1109/TMM.2018.2832602
Citation
  • https://doi.org/10.48550/arXiv.2307.09972
  • https://doi.org/10.48550/arXiv.2111.12476
  • https://doi.org/10.48550/arXiv.2209.13853
  • https://doi.org/10.48550/arXiv.2306.11341
  • https://doi.org/10.48550/arXiv.1501.02530
  • https://doi.org/10.1609/aaai.v37i3.25483
  • https://doi.org/10.48550/arXiv.2105.08276
Author Meng Cao
More Authors
Long Chen
Mike Zheng Shou
Can Zhang
Yuexian Zou
Homepage https://www.msvd.org/