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Memory Efficient Diffusion Probabilistic Models via Patch-based Generation

Published in arXiv (Cornell University) • Apr 14, 2023
NobleIDNI1P61W79R22S28
Authors:
Shinei Arakawa
,
Hideki Tsunashima
,
Daichi Horita

Abstract

Diffusion probabilistic models have been successful in generating high-quality and diverse images. However, traditional models, whose input and output are high-resolution images, suffer from excessive memory requirements, making them less practical for edge devices. Previous approaches for generativ...

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