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Found 3 papers, 3 papers with code
Fast Diffusion EM: a diffusion model for blind inverse problems with application to deconvolution
Our method alternates between approximating the expected log-likelihood of the inverse problem using samples drawn from a diffusion model and a maximization step to estimate unknown model parameters.
Provably Convergent Plug & Play Linearized ADMM, applied to Deblurring Spatially Varying Kernels
Plug & Play methods combine proximal algorithms with denoiser priors to solve inverse problems.
Deep Model-Based Super-Resolution with Non-uniform Blur
Instead, in this paper, we address the more realistic and computationally challenging case of spatially-varying blur.
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