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Visual Question Answering as a Multi-Task Problem
Visual Question Answering(VQA) is a highly complex problem set, relying on many sub-problems to produce reasonable answers.
Eliminating Catastrophic Interference with Biased Competition
We create and exhibit a new toy dataset, based on the MNIST dataset, which we call MNIST-QA, for testing Visual Question Answering architectures in a low-dimensional environment while preserving the more difficult components of the Visual Question Answering task, and demonstrate the proposed network architecture on this new dataset, as well as on COCO-QA and DAQUAR-FULL.
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