A Bayesian Perspective on the Deep Image Prior

Understand

The deep image prior was recently introduced as a prior for natural images.

• It represents images as the output of a convolutional network with random inputs.
• For "inference", gradient descent is performed to adjust network parameters to make the output match observations.
• This approach yields good performance on a range of image reconstruction tasks.