GQA: A New Dataset for Real-World Visual Reasoning and Compositional Question Answering.

GQA is a new dataset for visual question answering featuring compositional questions over real-world images. The dataset consists of 22M questions about various day-to-day images, where each image is associated with a scene graph of the objects, attributes and relations. Each question is associated with a structured representation of its semantics, a functional program that specifies the reasoning steps. The dataset is designed to address shortcomings in existing VQA benchmarks by mitigating language priors and conditional biases, enabling fine-grained diagnosis for different question types.

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