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Retinex-inspired Unrolling with Cooperative Prior Architecture Search for Low-light Image Enhancement
Risheng Liu, Long Ma, Jiaao Zhang +2
Low-light image enhancement plays very important roles in low-level vision field. Recent works have built a large variety of deep learning models to address this task. However, the…
Optimization-Inspired Learning with Architecture Augmentations and Control Mechanisms for Low-Level Vision
Risheng Liu, Zhu Liu, Pan Mu +2
In recent years, there has been a growing interest in combining learnable modules with numerical optimization to solve low-level vision tasks. However, most existing approaches foc…
BOML: A Modularized Bilevel Optimization Library in Python for Meta Learning
Yaohua Liu, Risheng Liu
Meta-learning (a.k.a. learning to learn) has recently emerged as a promising paradigm for a variety of applications. There are now many meta-learning methods, each focusing on diff…
A Generic First-Order Algorithmic Framework for Bi-Level Programming Beyond Lower-Level Singleton
Risheng Liu, Pan Mu, Xiaoming Yuan +2
In recent years, a variety of gradient-based first-order methods have been developed to solve bi-level optimization problems for learning applications. However, theoretical guarant…
Learning Deformable Image Registration from Optimization: Perspective, Modules, Bilevel Training and Beyond
Risheng Liu, Zi Li, Xin Fan +3
Conventional deformable registration methods aim at solving an optimization model carefully designed on image pairs and their computational costs are exceptionally high. In contras…