Training Image Estimators without Image Ground-Truth

13 Jun 2019Zhihao XiaAyan Chakrabarti

Deep neural networks have been very successful in image estimation applications such as compressive-sensing and image restoration, as a means to estimate images from partial, blurry, or otherwise degraded measurements. These networks are trained on a large number of corresponding pairs of measurements and ground-truth images, and thus implicitly learn to exploit domain-specific image statistics... (read more)

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