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.

Data and Resources

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

DOI retrieved: December 3, 2024

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