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Semantic Equivalent Adversarial Data Augmentation for Visual Question Answering

Visual Question Answering (VQA) has achieved great success thanks to the fast development of deep neural networks (DNN). On the other hand, the data augmentation, as one of the major tricks for DNN, has been widely used in many computer vision tasks.

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Cite this as

Ruixue Tang, Chao Ma, Wei Emma Zhang, Qi Wu, Xiaokang Yang (2024). Dataset: Semantic Equivalent Adversarial Data Augmentation for Visual Question Answering. https://doi.org/10.57702/o5odpbmh

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Additional Info

Field	Value
Created	December 3, 2024
Last update	December 3, 2024
Defined In	https://doi.org/10.48550/arXiv.2007.09592
Author	Ruixue Tang
More Authors	Chao Ma Wei Emma Zhang Qi Wu Xiaokang Yang
Homepage	https://github.com/zaynmi/seada-vqa