Mathematical Cookbook for Snapshot Compressive Imaging
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Abstract (arXiv)
The author intends to provide you with a beautiful, elegant, user-friendly cookbook for mathematics in Snapshot Compressive Imaging (SCI). Currently, the cookbook is composed of introduction, conventional optimization, and deep equilibrium models. The latest releases are strongly recommended! For any other questions, suggestions, or comments, feel free to email the author.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 10 of its 22 references that are in the map. First posted on arXiv 9 Feb 2022.
Builds on
10 of 22 references.
References · 10
- 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
- 2021Deep Equilibrium Architectures for Inverse Problems in Imagingcited by 126
- 2018Rank Minimization for Snapshot Compressive Imagingcited by 99
- 2020Plug-and-Play Algorithms for Large-scale Snapshot Compressive Imagingcited by 78
- 2013Coded aperture compressive temporal imagingcited by 57
- 2020GAP-net for Snapshot Compressive Imagingcited by 54
- 2021Plug-and-Play Algorithms for Video Snapshot Compressive Imagingcited by 42
- 2021Dense Deep Unfolding Network with 3D-CNN Prior for Snapshot Compressive Imagingcited by 31
- 2022Deep Equilibrium Models for Video Snapshot Compressive Imagingcited by 5
- 2021Revisit Dictionary Learning for Video Compressive Sensing under the Plug-and-Play Frameworkcited by 2
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