18 citations · 32 across the 4 of their papers we have counts for
4 papers
MetaDIP: Accelerating Deep Image Prior with Meta Learning
Kevin Zhang, Mingyang Xie, Maharshi Gor +3
Deep image prior (DIP) is a recently proposed technique for solving imaging inverse problems by fitting the reconstructed images to the output of an untrained convolutional neural…
PROVES: Establishing Image Provenance using Semantic Signatures
Mingyang Xie, Manav Kulshrestha, Shaojie Wang +4
Modern AI tools, such as generative adversarial networks, have transformed our ability to create and modify visual data with photorealistic results. However, one of the deleterious…
CoIL: Coordinate-based Internal Learning for Imaging Inverse Problems
Yu Sun, Jiaming Liu, Mingyang Xie +2
We propose Coordinate-based Internal Learning (CoIL) as a new deep-learning (DL) methodology for the continuous representation of measurements. Unlike traditional DL methods that l…
Joint Reconstruction and Calibration using Regularization by Denoising
Mingyang Xie, Yu Sun, Jiaming Liu +2
Regularization by denoising (RED) is a broadly applicable framework for solving inverse problems by using priors specified as denoisers. While RED has been shown to provide state-o…