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Found 5 papers, 2 papers with code
Plug-and-Play image restoration with Stochastic deNOising REgularization
Even if they produce impressive image restoration results, these algorithms rely on a non-standard use of a denoiser on images that are less and less noisy along the iterations, which contrasts with recent algorithms based on Diffusion Models (DM), where the denoiser is applied only on re-noised images.
Inverse problem regularization with hierarchical variational autoencoders
Our experiments show that the proposed PnP-HVAE method is competitive with both SOTA denoiser-based PnP approaches, and other SOTA restoration methods based on generative models.
SCOTCH and SODA: A Transformer Video Shadow Detection Framework
In this work, we argue that accounting for shadow deformation is essential when designing a video shadow detection method.
Diverse super-resolution with pretrained deep hiererarchical VAEs
We investigate the problem of producing diverse solutions to an image super-resolution problem.
Learning local regularization for variational image restoration
In this work, we propose a framework to learn a local regularization model for solving general image restoration problems.
