This repo includes recent research works in multi-modality learning, especially with pre-training method.
HD-VILA-100M dataset: high-resolution and diversified video-langauge dataset
HD-VILA (CVPR 2022): high-resolution and diversified video-langauge pre-training model
Pixel-BERT: end-to-end image and language pre-training model
SOHO (CVPR 2021 oral): improved end-to-end image and language pre-training model with quantized visual tokens
VisualParsing(NeurIPS 2021): Transformer-based end-to-end image and language pre-training model
- March, 2022: HD-VILA-100M dataset was released publicly.
- March, 2022: HD-VILA was accepted by CVPR 2022.
This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.
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This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.
This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow Microsoft's Trademark & Brand Guidelines. Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party's policies.
For help or issues using the pre-trained models, please submit an issue.
For other communications, please contact Bei Liu (bei.liu@microsoft.com) and Jianlong Fu (jianf@microsoft.com).