MixGen: A New Multi-Modal Data Augmentation

@article{Hao2022MixGenAN,
  title={MixGen: A New Multi-Modal Data Augmentation},
  author={Xiaoshuai Hao and Yi Zhu and Srikar Appalaraju and Aston Zhang and Wanqian Zhang and Boyang Li and Mu Li},
  journal={ArXiv},
  year={2022},
  volume={abs/2206.08358}
}
Data augmentation is a necessity to enhance data efficiency in deep learning. For vision-language pre-training, data is only augmented either for images or for text in previous works. In this paper, we present MixGen: a joint data augmentation for vision-language representation learning to further improve data efficiency. It generates new image-text pairs with semantic relationships preserved by interpolating images and concatenating text. It’s simple, and can be plug-and-played into existing… 

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