Bangti Jin, Professor, Department of Mathematics, The Chinese University of Hong Kong

Wei Gong, Associate Professor

Deep image prior for inverse problems: acceleration and probabilistic treatment

10:00-11:00 November 15(Tuesday), Tencent Meeting ID: 427-400-798

Since its first proposal in 2018, deep image prior has emerged as a very powerful unsupervised deep learning technique for solving inverse problems. The approach has demonstrated very encouraging empirical success in image denoising, deblurring, super-resolution etc. However, there are also several known drawbacks of the approach, notably high computational expense. In this talk, we describe some of our efforts: we propose to accelerate the training process by pretraining on synthetic dataset and further we propose a novel probabilistic treatment of deep image prior to facilitate uncertainty quantification.