1k citations · 1.8k across the 53 of their papers we have counts for
11 papers · 1 filter
Stochastic Deep Restoration Priors for Imaging Inverse Problems
Yuyang Hu, Albert Peng, Weijie Gan +3
Deep neural networks trained as image denoisers are widely used as priors for solving imaging inverse problems. While Gaussian denoising is thought sufficient for learning image pr…
A Restoration Network as an Implicit Prior
Yuyang Hu, Mauricio Delbracio, Peyman Milanfar +1
Image denoisers have been shown to be powerful priors for solving inverse problems in imaging. In this work, we introduce a generalization of these methods that allows any image re…
Inversion by Direct Iteration: An Alternative to Denoising Diffusion for Image Restoration
Mauricio Delbracio, Peyman Milanfar
Inversion by Direct Iteration (InDI) is a new formulation for supervised image restoration that avoids the so-called "regression to the mean" effect and produces more realistic and…
MAXIM: Multi-Axis MLP for Image Processing
Zhengzhong Tu, Hossein Talebi, Han Zhang +4
Recent progress on Transformers and multi-layer perceptron (MLP) models provide new network architectural designs for computer vision tasks. Although these models proved to be effe…
Interpretable Unsupervised Diversity Denoising and Artefact Removal
Mangal Prakash, Mauricio Delbracio, Peyman Milanfar +1
Image denoising and artefact removal are complex inverse problems admitting multiple valid solutions. Unsupervised diversity restoration, that is, obtaining a diverse set of possib…
Learning to Reduce Defocus Blur by Realistically Modeling Dual-Pixel Data
Abdullah Abuolaim, Mauricio Delbracio, Damien Kelly +2
Recent work has shown impressive results on data-driven defocus deblurring using the two-image views available on modern dual-pixel (DP) sensors. One significant challenge in this…
The Rate-Distortion-Accuracy Tradeoff: JPEG Case Study
Xiyang Luo, Hossein Talebi, Feng Yang +2
Handling digital images is almost always accompanied by a lossy compression in order to facilitate efficient transmission and storage. This introduces an unavoidable tension betwee…
Regularization by Denoising via Fixed-Point Projection (RED-PRO)
Regev Cohen, Michael Elad, Peyman Milanfar
Inverse problems in image processing are typically cast as optimization tasks, consisting of data-fidelity and stabilizing regularization terms. A recent regularization strategy of…
GIFnets: Differentiable GIF Encoding Framework
Innfarn Yoo, Xiyang Luo, Yilin Wang +2
Graphics Interchange Format (GIF) is a widely used image file format. Due to the limited number of palette colors, GIF encoding often introduces color banding artifacts. Traditiona…
Better Compression with Deep Pre-Editing
Hossein Talebi, Damien Kelly, Xiyang Luo +4
Could we compress images via standard codecs while avoiding visible artifacts? The answer is obvious -- this is doable as long as the bit budget is generous enough. What if the all…
LIDIA: Lightweight Learned Image Denoising with Instance Adaptation
Gregory Vaksman, Michael Elad, Peyman Milanfar
Image denoising is a well studied problem with an extensive activity that has spread over several decades. Despite the many available denoising algorithms, the quest for simple, po…