Neural Proximal Gradient Descent for Compressive Imaging

1 code implementation • NeurIPS 2018 • Morteza Mardani, Qingyun Sun, Shreyas Vasawanala, Vardan Papyan, Hatef Monajemi, John Pauly, David Donoho

Recovering high-resolution images from limited sensory data typically leads to a serious ill-posed inverse problem, demanding inversion algorithms that effectively capture the prior information.

Recurrent Generative Adversarial Networks for Proximal Learning and Automated Compressive Image Recovery

no code implementations • 27 Nov 2017 • Morteza Mardani, Hatef Monajemi, Vardan Papyan, Shreyas Vasanawala, David Donoho, John Pauly

Building effective priors is however challenged by the low train and test overhead dictated by real-time tasks; and the need for retrieving visually "plausible" and physically "feasible" images with minimal hallucination.

Denoising Hallucination +1