May 21, 2024, 4:44 a.m. | Conghan Yue, Zhengwei Peng, Junlong Ma, Shiyan Du, Pengxu Wei, Dongyu Zhang

cs.LG updates on arXiv.org arxiv.org

arXiv:2312.10299v2 Announce Type: replace-cross
Abstract: Diffusion models exhibit powerful generative capabilities enabling noise mapping to data via reverse stochastic differential equations. However, in image restoration, the focus is on the mapping relationship from low-quality to high-quality images. Regarding this issue, we introduce the Generalized Ornstein-Uhlenbeck Bridge (GOUB) model. By leveraging the natural mean-reverting property of the generalized OU process and further eliminating the variance of its steady-state distribution through the Doob's h-transform, we achieve diffusion mappings from point to point …

arxiv bridge cs.ai cs.cv cs.lg generalized image image restoration replace restoration through type

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