AI RESEARCH
FlowADMM: Plug-and-play ADMM with Flow-based Renoise-Denoise Priors
arXiv CS.CV
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ArXi:2605.08640v1 Announce Type: new Plug-and-play (PnP) methods for solving inverse problems have recently achieved strong performance by leveraging denoising priors based on powerful generative diffusion and flow models. However, existing diffusion- and flow-based PnP methods typically rely on stochastic renoise-denoise operations, which complicate the analysis of their convergence behavior. In this work, we identify and formalize the deterministic renoise-denoise operator underlying flow-based plug-and-play methods.