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eess.IV2022
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…
eess.IV2021★ 2 cited
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…
eess.IV2020
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…