1k citations · 1.8k across the 53 of their papers we have counts for
13 papers · 1 filter
Polyblur: Removing mild blur by polynomial reblurring
Mauricio Delbracio, Ignacio Garcia-Dorado, Sungjoon Choi +2
We present a highly efficient blind restoration method to remove mild blur in natural images. Contrary to the mainstream, we focus on removing slight blur that is often present, da…
Projected Distribution Loss for Image Enhancement
Mauricio Delbracio, Hossein Talebi, Peyman Milanfar
Features obtained from object recognition CNNs have been widely used for measuring perceptual similarities between images. Such differentiable metrics can be used as perceptual lea…
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…
Rank-smoothed Pairwise Learning In Perceptual Quality Assessment
Hossein Talebi, Ehsan Amid, Peyman Milanfar +1
Conducting pairwise comparisons is a widely used approach in curating human perceptual preference data. Typically raters are instructed to make their choices according to a specifi…
Multi-path Neural Networks for On-device Multi-domain Visual Classification
Qifei Wang, Junjie Ke, Joshua Greaves +9
Learning multiple domains/tasks with a single model is important for improving data efficiency and lowering inference cost for numerous vision tasks, especially on resource-constra…
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…
Creating High Resolution Images with a Latent Adversarial Generator
David Berthelot, Peyman Milanfar, Ian Goodfellow
Generating realistic images is difficult, and many formulations for this task have been proposed recently. If we restrict the task to that of generating a particular class of image…
Super-Resolving Commercial Satellite Imagery Using Realistic Training Data
Xiang Zhu, Hossein Talebi, Xinwei Shi +2
In machine learning based single image super-resolution, the degradation model is embedded in training data generation. However, most existing satellite image super-resolution meth…
Image Stylization: From Predefined to Personalized
Ignacio Garcia-Dorado, Pascal Getreuer, Bartlomiej Wronski +1
We present a framework for interactive design of new image stylizations using a wide range of predefined filter blocks. Both novel and off-the-shelf image filtering and rendering t…
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…
Distortion Agnostic Deep Watermarking
Xiyang Luo, Ruohan Zhan, Huiwen Chang +2
Watermarking is the process of embedding information into an image that can survive under distortions, while requiring the encoded image to have little or no perceptual difference…