Problem
Research questions and friction points this paper is trying to address.
Answerability
Visual Question Answering
regression task
Vision And Text Transformer For Predicting Answerability On Visual Question Answering
🤖 AI Summary
论文针对视觉问答的可回答性预测问题，提出了一种基于Transformer架构的方法VT-Transformer来处理图像和文本特征，实验表明其有效性。
📝 Abstract
Answerability on Visual Question Answering is a novel and attractive task to predict answerable scores between images and questions in multi-modal data. Existing works often utilize a binary mapping from visual question answering systems into Answerability. It does not reflect the essence of this problem. Together with our consideration of Answerability in a regression task, we propose VT-Transformer, which exploits visual and textual features through Transformer architecture. Experimental results on VizWiz 2020 dataset show the effectiveness and robustness of VT-Transformer for Answerability on Visual Question Answering when comparing with competitive baselines.
Innovation
Methods, ideas, or system contributions that make the work stand out.
VT-Transformer
Visual and Textual Features
Regression Task
Answerability
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