Hierarchical Autoregressive Image Models with Auxiliary Decoders
arXiv: Computer Vision and Pattern Recognition, 2019.
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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