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Visual question answering is the task of answering questions about images. Weintroduce the VizWiz-VQA-Grounding dataset, the first dataset that visuallygrounds answers to visual questions asked by people with visual impairments. Weanalyze our dataset and compare it with five VQA-Grounding datasets todemonstrate what makes it similar and different. We then evaluate the SOTA VQAand VQA-Grounding models and demonstrate that current SOTA algorithms oftenfail to identify the correct visual evidence where the answer is located. Thesemodels regularly struggle when the visual evidence occupies a small fraction ofthe image, for images that are higher quality, as well as for visual questionsthat require skills in text recognition. The dataset, evaluation server, andleaderboard all can be found at the following link:https://vizwiz.org/tasks-and-datasets/answer-grounding-for-vqa/.

Grounding Answers for Visual Questions Asked by Visually Impaired People