Textbook Cover VQA is a Visual Question Answering (VQA) dataset developed for research on structured understanding of text-rich academic textbook covers. The dataset is designed to evaluate vision–language models (VLMs) on textual understanding, academic-domain recognition, spatial grounding, and visual content understanding. Textbook Cover VQA consists of 1,510 textbook-cover images covering 9 academic domains. Each textbook-cover image is associated with 8 predefined VQA questions, resulting in 12,080 question-answer annotations. The dataset captures four major types of information: - B. Vinay Kumar — L24AEC592 - A. Akash — Y23AEC404 - A. Pujitha — Y23AEC410 - B. Avinash — Y23AEC413…
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B.VINAY KUMAR
BVinay06
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Published tasks: Visual question answering.
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