Christopher A. Metzler | DeepAI

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∙ 03/30/2023

TiDy-PSFs: Computational Imaging with Time-Averaged Dynamic Point-Spread-Functions

Point-spread-function (PSF) engineering is a powerful computational imag...

0 Sachin Shah, et al. ∙

∙ 03/16/2023

SUD^2: Supervision by Denoising Diffusion Models for Image Reconstruction

Many imaging inverse problemsx2014such as image-dependent in-painting an...

0 Matthew A. Chan, et al. ∙

∙ 12/26/2022

Weakly-Supervised Semantic Segmentation of Ships Using Thermal Imagery

The United States coastline spans 95,471 miles; a distance that cannot b...

0 Rushil Joshi, et al. ∙

∙ 09/18/2022

MetaDIP: Accelerating Deep Image Prior with Meta Learning

Deep image prior (DIP) is a recently proposed technique for solving imag...

18 Kevin Zhang, et al. ∙

∙ 06/09/2022

Denoising Generalized Expectation-Consistent Approximation for MRI Image Recovery

To solve inverse problems, plug-and-play (PnP) methods have been develop...

6 Saurav K. Shastri, et al. ∙

∙ 03/13/2022

TurbuGAN: An Adversarial Learning Approach to Spatially-Varying Multiframe Blind Deconvolution with Applications to Imaging Through Turbulence

We present a self-supervised and self-calibrating multi-shot approach to...

0 Brandon Y. Feng, et al. ∙

∙ 02/11/2022

Expectation Consistent Plug-and-Play for MRI

For image recovery problems, plug-and-play (PnP) methods have been devel...

0 Saurav K. Shastri, et al. ∙

∙ 10/25/2020

SUREMap: Predicting Uncertainty in CNN-based Image Reconstruction Using Stein's Unbiased Risk Estimate

Convolutional neural networks (CNN) have emerged as a powerful tool for ...

0 Ruangrawee Kitichotkul, et al. ∙

∙ 05/12/2020

Deep Learning Techniques for Inverse Problems in Imaging

Recent work in machine learning shows that deep neural networks can be u...

11 Gregory Ongie, et al. ∙

∙ 02/14/2020

Deep S^3PR: Simultaneous Source Separation and Phase Retrieval Using Deep Generative Models

This paper introduces and solves the simultaneous source separation and ...

0 Christopher A. Metzler, et al. ∙

∙ 12/13/2019

Keyhole Imaging: Non-Line-of-Sight Imaging and Tracking of Moving Objects Along a Single Optical Path at Long Standoff Distances

Non-line-of-sight (NLOS) imaging and tracking is an emerging paradigm th...

26 Christopher A. Metzler, et al. ∙

∙ 08/01/2019

Deep Optics for Single-shot High-dynamic-range Imaging

High-dynamic-range (HDR) imaging is crucial for many computer graphics a...

1 Christopher A. Metzler, et al. ∙

∙ 06/26/2018

An Expectation-Maximization Approach to Tuning Generalized Vector Approximate Message Passing

Generalized Vector Approximate Message Passing (GVAMP) is an efficient i...

0 Christopher A. Metzler, et al. ∙

∙ 05/26/2018

Unsupervised Learning with Stein's Unbiased Risk Estimator

Learning from unlabeled and noisy data is one of the grand challenges of...

0 Christopher A. Metzler, et al. ∙

∙ 03/01/2018

prDeep: Robust Phase Retrieval with Flexible Deep Neural Networks

Phase retrieval (PR) algorithms have become an important component in ma...

0 Christopher A. Metzler, et al. ∙

∙ 04/21/2017

Learned D-AMP: Principled Neural Network based Compressive Image Recovery

Compressive image recovery is a challenging problem that requires fast a...

0 Christopher A. Metzler, et al. ∙