Image Representations and New Domains in Neural Image Captioning

Jack Hessel; Nicolas Savva; Michael J. Wilber

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arXiv · 1508.02091

Image Representations and New Domains in Neural Image Captioning

Jack Hessel·Nicolas Savva·Michael J. Wilber

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Abstract

We examine the possibility that recent promising results in automatic caption generation are due primarily to language models. By varying image representation quality produced by a convolutional neural network, we find that a state-of-the-art neural captioning algorithm is able to produce quality captions even when provided with surprisingly poor image representations. We replicate this result in a new, fine-grained, transfer learned captioning domain, consisting of 66K recipe image/title pairs. We also provide some experiments regarding the appropriateness of datasets for automatic captioning, and find that having multiple captions per image is beneficial, but not an absolute requirement.

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Jack Hessel, Nicolas Savva, Michael J. Wilber. 2015-08-09. Image Representations and New Domains in Neural Image Captioning. https://arxiv.org/abs/1508.02091

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