Object-based reasoning in VQA

Mikyas T. Desta; Larry Chen; Tomasz Kornuta

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arXiv · 1801.09718

Object-based reasoning in VQA

Mikyas T. Desta·Larry Chen·Tomasz Kornuta

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Abstract

Visual Question Answering (VQA) is a novel problem domain where multi-modal inputs must be processed in order to solve the task given in the form of a natural language. As the solutions inherently require to combine visual and natural language processing with abstract reasoning, the problem is considered as AI-complete. Recent advances indicate that using high-level, abstract facts extracted from the inputs might facilitate reasoning. Following that direction we decided to develop a solution combining state-of-the-art object detection and reasoning modules. The results, achieved on the well-balanced CLEVR dataset, confirm the promises and show significant, few percent improvements of accuracy on the complex "counting" task.

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BibTeX RIS

Mikyas T. Desta, Larry Chen, Tomasz Kornuta. 2018-01-29. Object-based reasoning in VQA. https://arxiv.org/abs/1801.09718

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