DCF-VQA: Counterfactual structure based on multi-feature enhancement - Yang, Guan; Ji, Cheng; Liu, Xiaoming; Zhang, Ziming; Wang, Chen (Zielona Góra: Uniwersytet Zielonogórski)
Visual question answering (VQA) is a pivotal topic at the intersection of computer vision and natural language processing. This paper addresses the challenges of linguistic bias and bias fusion within invalid regions encountered in existing VQA models due to insufficient representation of multi-modal features. To overcome those issues, we propose a multi-feature enhancement scheme. This scheme involves the fusion of one or more features with the original ones, incorporating discrete cosine transform (DCT) features into the counterfactual reasoning framework.
Keywords: visual question answering; multi-feature enhancement; counterfactual; discrete cosine transform