166 citations · 545 across the 25 of their papers we have counts for
25 papers
Perceptually Regularized Diffusion Model for Image Super-Resolution
Chuxiangbo Wang, Pavithra Venkatachalapathy, Ying Liang +4
Image super-resolution, which aims to reconstruct high-resolution images from their low-resolution observations, is fundamental to medical imaging, remote sensing, surveillance, mi…
Minimizing Quotient Regularization Model
Chao Wang, Jean-Francois Aujol, Guy Gilboa +1
Quotient regularization models (QRMs) are a class of powerful regularization techniques that have gained considerable attention in recent years, due to their ability to handle comp…
Non-convex approaches for low-rank tensor completion under tubal sampling
Zheng Tan, Longxiu Huang, HanQin Cai +1
Tensor completion is an important problem in modern data analysis. In this work, we investigate a specific sampling strategy, referred to as tubal sampling. We propose two novel no…
Accelerated Sparse Recovery via Gradient Descent with Nonlinear Conjugate Gradient Momentum
Mengqi Hu, Yifei Lou, Bao Wang +3
This paper applies an idea of adaptive momentum for the nonlinear conjugate gradient to accelerate optimization problems in sparse recovery. Specifically, we consider two types of…
A Lifted Framework for Sparse Recovery
Yaghoub Rahimi, Sung Ha Kang, Yifei Lou
Motivated by re-weighted approaches for sparse recovery, we propose a lifted (LL1) regularization which is a generalized form of several popular regularizations i…
An Efficient Smoothing and Thresholding Image Segmentation Framework with Weighted Anisotropic-Isotropic Total Variation
Kevin Bui, Yifei Lou, Fredrick Park +1
In this paper, we design an efficient, multi-stage image segmentation framework that incorporates a weighted difference of anisotropic and isotropic total variation (AITV). The seg…