7 citations · 12 across the 5 of their papers we have counts for
5 papers
Learning Nonlocal Sparse and Low-Rank Models for Image Compressive Sensing
Zhiyuan Zha, Bihan Wen, Xin Yuan +3
The compressive sensing (CS) scheme exploits much fewer measurements than suggested by the Nyquist-Shannon sampling theorem to accurately reconstruct images, which has attracted co…
R3L: Connecting Deep Reinforcement Learning to Recurrent Neural Networks for Image Denoising via Residual Recovery
Rongkai Zhang, Jiang Zhu, Zhiyuan Zha +2
State-of-the-art image denoisers exploit various types of deep neural networks via deterministic training. Alternatively, very recent works utilize deep reinforcement learning for…
The Power of Triply Complementary Priors for Image Compressive Sensing
Zhiyuan Zha, Xin Yuan, Joey Tianyi Zhou +3
Recent works that utilized deep models have achieved superior results in various image restoration applications. Such approach is typically supervised which requires a corpus of tr…
Image denoising using group sparsity residual and external nonlocal self-similarity prior
Zhiyuan Zha, Xinggan Zhang, Qiong Wang +2
Nonlocal image representation has been successfully used in many image-related inverse problems including denoising, deblurring and deblocking. However, a majority of reconstructio…
Image denoising via group sparsity residual constraint
Zhiyuan Zha, Xin Liu, Ziheng Zhou +7
Group sparsity has shown great potential in various low-level vision tasks (e.g, image denoising, deblurring and inpainting). In this paper, we propose a new prior model for image…