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An important goal of computer vision is to build systems that learn visual representations over time that can be applied to many tasks.
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A focused dynamic attention model for visual question answering
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Revisiting visual question answering baselines
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Visual genome: Connecting language and vision using crowdsourced dense image annotations
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Hierarchical question-image co-attention for visual question answering
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A. Mallya · 2016
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Generation and comprehension of unambiguous object descriptions
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Solving visual madlibs with multiple cues
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Learning deep structure-preserving image-text embeddings
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Google’s neural machine translation system: Bridging the gap between human and machine translation
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Ask, attend and answer: Exploring question-guided spatial attention for visual question answering
H. Xu and K. Saenko · 2016
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