* To appear in TNNLS 2021. Considering that a desirable VQA model
should correctly perceive the image context, understand the question, and
incorporate its learned knowledge, our proposed dataset aims to cutoff the
shortcut learning exploited by the current deep embedding models and push the
research boundary of the knowledge-based visual question reasoning Access Paper or Ask Questions
* Submitted to TPAMI 2020. We have achieved an end-to-end interpretable
structural reasoning for general images without the requirement of layout
annotations Access Paper or Ask Questions