CSformer: Bridging Convolution and Transformer for Compressive Sensing-Reference-Cited by-同舟云学术

CSformer: Bridging Convolution and Transformer for Compressive Sensing

Published:2023 Issue: Volume:32 Page:2827-2842
ISSN:1057-7149
Container-title:IEEE Transactions on Image Processing
language:
Short-container-title:IEEE Trans. on Image Process.

Author:

Ye Dongjie¹^ORCID,Ni Zhangkai²^ORCID,Wang Hanli²^ORCID,Zhang Jian³^ORCID,Wang Shiqi¹^ORCID,Kwong Sam¹^ORCID

Affiliation:

1. Department of Computer Science, City University of Hong Kong, Hong Kong, China

2. Department of Computer Science and Technology, Key Laboratory of Embedded System and Service Computing (Ministry of Education), and Shanghai Institute of Intelligent Science and Technology, Tongji University, Shanghai, China

3. School of Electronic and Computer Engineering, Peking University Shenzhen Graduate School, Shenzhen, China

Funder

Hong Kong Innovation and Technology Commission [InnoHK Project Centre for Intelligent Multidimensional Data Analysis (CIMDA)]

Hong Kong GRF-RGC General Research Fund

Natural Science Foundation of China

Shanghai Pujiang Program

Fundamental Research Funds for the Central Universities

Key Project of Science and Technology Innovation 2030 supported by the Ministry of Science and Technology of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Graphics and Computer-Aided Design,Software

Link

http://xplorestaging.ieee.org/ielx7/83/9991910/10124835.pdf?arnumber=10124835

Reference72 articles.

1. ADMM-CSNet: A Deep Learning Approach for Image Compressive Sensing

2. Early convolutions help transformers see better;xiao;Proc Adv Neural Inf Process Syst,2021

3. ISTA-Net: Interpretable Optimization-Inspired Deep Network for Image Compressive Sensing

4. Feature Pyramid Networks for Object Detection

5. Optimization-Inspired Compact Deep Compressive Sensing

Cited by 22 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Scalable compressive sampling network with progressive hierarchical subspace learning;Pattern Recognition;2024-12

2. Dual-domain sampling and feature-domain optimization network for image compressive sensing;Engineering Applications of Artificial Intelligence;2024-11

3. LD-CSNet: A latent diffusion-based architecture for perceptual Compressed Sensing;Neural Networks;2024-11

4. Structured residual sparsity for video compressive sensing reconstruction;Signal Processing;2024-09

5. MTC-CSNet: Marrying Transformer and Convolution for Image Compressed Sensing;IEEE Transactions on Cybernetics;2024-09