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Tell-and-Answer: Towards Explainable Visual Question Answering using Attributes and Captions
Most existing approaches adopt the pipeline of representing an image via pre-trained CNNs, and then using the uninterpretable CNN features in conjunction with the question to predict the answer.
Multi-Level Attention Networks for Visual Question Answering
To solve the challenges, we propose a multi-level attention network for visual question answering that can simultaneously reduce the semantic gap by semantic attention and benefit fine-grained spatial inference by visual attention.
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