IconQA

Current visual question answering (VQA) tasks mainly consider answering human-annotated questions for natural images in the daily-life context. In this work, we propose a new challenging benchmark, icon question answering (IconQA), which aims to highlight the importance of abstract diagram understanding and comprehensive cognitive reasoning in real-world diagram word problems. For this benchmark, we build up a large-scale IconQA dataset that consists of three sub-tasks: multi-image-choice, multi-text-choice, and filling-in-the-blank. Compared to existing VQA benchmarks, IconQA requires not only perception skills like object recognition and text understanding, but also diverse cognitive reasoning skills, such as geometric reasoning, commonsense reasoning, and arithmetic reasoning.