Hierarchical Autoregressive Image Models with Auxiliary Decoders

Jeffrey De Fauw
Jeffrey De Fauw

arXiv: Computer Vision and Pattern Recognition, 2019.

Cited by: 12|Bibtex|Views65
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Other Links: dblp.uni-trier.de|academic.microsoft.com|arxiv.org

Abstract:

Autoregressive generative models of images tend to be biased towards capturing local structure, and as a result they often produce samples which are lacking in terms of large-scale coherence. To address this, we propose two methods to learn discrete representations of images which abstract away local detail. We show that autoregressive mo...More

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