Dense Deep Unfolding Network with 3D-CNN Prior for Snapshot Compressive Imaging
This repository is the code for the following paper:
Zhuoyuan Wu, Jian Zhang, Chong Mou. Dense Deep Unfolding Network with 3D-CNN Prior for Snapshot Compressive Imaging. ICCV 2021. [PDF]
Introduction
Snapshot compressive imaging (SCI) aims to record three-dimensional signals via a two-dimensional camera. For the sake of building a fast and accurate SCI recovery algorithm, we incorporate the interpretability of model-based methods and the speed of learning-based ones and present a novel dense deep unfolding network (DUN) with 3D-CNN prior for SCI, where each phase is unrolled from an iteration of Half-Quadratic Splitting (HQS). To better exploit the spatial-temporal correlation among frames and address the problem of information loss between adjacent phases in existing DUNs, we propose to adopt the