SP$^3$: Spherical Priors for Plug-and-Play Restoration
In this paper, we introduce SP$^3$, a novel Plug-and-Play algorithm that accelerates maximum a posteriori image restoration by replacing denoisers with Spherical Encoders (SE) as generative priors. SP$^3$ approximates the intractable proximal prior step by utilizing the SE tightly structured latent space as a robust projection onto the natural image manifold. Alternating this projection with a closed-form data-consistency step, via Half-Quadratic Splitting, achieves stable convergence without requiring gradient computation during inference. This unique formulation unlocks "anytime" restoration capabilities, producing sharp, plausible images from the first iteration. Evaluations across a v...
| Authors | Sean Man, Ron Raphaeli, Matan Kleiner et al. |
|---|---|
| Primary category | cs.CV |
| Published | 15 June 2026 |
| Last updated at source | 15 June 2026 |
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