7 citations · 23 across the 19 of their papers we have counts for
6 papers · 1 filter
FLAIR: A Conditional Diffusion Framework with Applications to Face Video Restoration
Zihao Zou, Jiaming Liu, Shirin Shoushtari +3
Face video restoration (FVR) is a challenging but important problem where one seeks to recover a perceptually realistic face videos from a low-quality input. While diffusion probab…
Plug-and-Play Posterior Sampling under Mismatched Measurement and Prior Models
Marien Renaud, Jiaming Liu, Valentin de Bortoli +2
Posterior sampling has been shown to be a powerful Bayesian approach for solving imaging inverse problems. The recent plug-and-play unadjusted Langevin algorithm (PnP-ULA) has emer…
Prior Mismatch and Adaptation in PnP-ADMM with a Nonconvex Convergence Analysis
Shirin Shoushtari, Jiaming Liu, Edward P. Chandler +2
Plug-and-Play (PnP) priors is a widely-used family of methods for solving imaging inverse problems by integrating physical measurement models with image priors specified using imag…
DiffuseIR:Diffusion Models For Isotropic Reconstruction of 3D Microscopic Images
Mingjie Pan, Yulu Gan, Fangxu Zhou +4
Three-dimensional microscopy is often limited by anisotropic spatial resolution, resulting in lower axial resolution than lateral resolution. Current State-of-The-Art (SoTA) isotro…
Block Coordinate Plug-and-Play Methods for Blind Inverse Problems
Weijie Gan, Shirin Shoushtari, Yuyang Hu +3
Plug-and-play (PnP) prior is a well-known class of methods for solving imaging inverse problems by computing fixed-points of operators combining physical measurement models and lea…
Deep Equilibrium Learning of Explicit Regularizers for Imaging Inverse Problems
Zihao Zou, Jiaming Liu, Brendt Wohlberg +1
There has been significant recent interest in the use of deep learning for regularizing imaging inverse problems. Most work in the area has focused on regularization imposed implic…