Gregory Slabaugh

Learning to Sample the Most Useful Training Patches from Images

Some image restoration tasks like demosaicing require difficult training...
11/24/2020 ∙ by Shuyang Sun, et al. ∙ 0 ∙ share

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Self-Adaptively Learning to Demoire from Focused and Defocused Image Pairs

Moire artifacts are common in digital photography, resulting from the in...
11/03/2020 ∙ by Lin Liu, et al. ∙ 2 ∙ share

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Diagnosing and Preventing Instabilities in Recurrent Video Processing

Recurrent models are becoming a popular choice for video enhancement tas...
10/10/2020 ∙ by Thomas Tanay, et al. ∙ 0 ∙ share

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Video Super-resolution with Temporal Group Attention

Video super-resolution, which aims at producing a high-resolution video ...
07/21/2020 ∙ by Takashi Isobe, et al. ∙ 0 ∙ share

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Wavelet-Based Dual-Branch Network for Image Demoireing

When smartphone cameras are used to take photos of digital screens, usua...
07/14/2020 ∙ by Lin Liu, et al. ∙ 6 ∙ share

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NTIRE 2020 Challenge on Real Image Denoising: Dataset, Methods and Results

This paper reviews the NTIRE 2020 challenge on real image denoising with...
05/08/2020 ∙ by Abdelrahman Abdelhamed, et al. ∙ 25 ∙ share

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NTIRE 2020 Challenge on Image Demoireing: Methods and Results

This paper reviews the Challenge on Image Demoireing that was part of th...
05/06/2020 ∙ by Shanxin Yuan, et al. ∙ 8 ∙ share

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Image Demoireing with Learnable Bandpass Filters

Image demoireing is a multi-faceted image restoration task involving bot...
04/01/2020 ∙ by Bolun Zheng, et al. ∙ 0 ∙ share

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DeepLPF: Deep Local Parametric Filters for Image Enhancement

Digital artists often improve the aesthetic quality of digital photograp...
03/31/2020 ∙ by Sean Moran, et al. ∙ 5 ∙ share

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Unsupervised Model Personalization while Preserving Privacy and Scalability: An Open Problem

This work investigates the task of unsupervised model personalization, a...
03/30/2020 ∙ by Matthias De Lange, et al. ∙ 0 ∙ share

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A Multi-Hypothesis Classification Approach to Color Constancy

Contemporary approaches frame the color constancy problem as learning ca...
02/28/2020 ∙ by Daniel Hernandez-Juarez, et al. ∙ 14 ∙ share

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A Multi-Hypothesis Approach to Color Constancy

Contemporary approaches frame the color constancy problem as learning ca...
02/28/2020 ∙ by Daniel Hernandez-Juarez, et al. ∙ 4 ∙ share

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Reconstructing the Noise Manifold for Image Denoising

Deep Convolutional Neural Networks (DCNNs) have been successfully used i...
02/11/2020 ∙ by Ioannis Marras, et al. ∙ 0 ∙ share

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DIFAR: Deep Image Formation and Retouching

We present a novel neural network architecture for the image signal proc...
11/29/2019 ∙ by Sean Moran, et al. ∙ 1 ∙ share

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Pixel Adaptive Filtering Units

State-of-the-art methods for computer vision rely heavily on the transla...
11/24/2019 ∙ by Filippos Kokkinos, et al. ∙ 27 ∙ share

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AIM 2019 Challenge on Image Demoireing: Methods and Results

This paper reviews the first-ever image demoireing challenge that was pa...
11/08/2019 ∙ by Shanxin Yuan, et al. ∙ 22 ∙ share

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AIM 2019 Challenge on Image Demoireing: Dataset and Study

This paper introduces a novel dataset, called LCDMoire, which was create...
11/06/2019 ∙ by Shanxin Yuan, et al. ∙ 12 ∙ share

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SteReFo: Efficient Image Refocusing with Stereo Vision

Whether to attract viewer attention to a particular object, give the imp...
09/29/2019 ∙ by Benjamin Busam, et al. ∙ 14 ∙ share

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Continual learning: A comparative study on how to defy forgetting in classification tasks

Artificial neural networks thrive in solving the classification problem ...
09/18/2019 ∙ by Matthias De Lange, et al. ∙ 0 ∙ share

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NODE: Extreme Low Light Raw Image Denoising using a Noise Decomposition Network

Denoising extreme low light images is a challenging task due to the high...
09/11/2019 ∙ by Hao Guan, et al. ∙ 3 ∙ share

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Meta-Learning for Few-shot Camera-Adaptive Color Constancy

Digital camera pipelines employ color constancy methods to estimate an u...
11/28/2018 ∙ by Steven McDonagh, et al. ∙ 0 ∙ share

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Generating Magnetic Resonance Spectroscopy Imaging Data of Brain Tumours from Linear, Non-Linear and Deep Learning Models

Magnetic Resonance Spectroscopy (MRS) provides valuable information to h...
08/23/2018 ∙ by Nathan J Olliverre, et al. ∙ 0 ∙ share

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Gregory Slabaugh

Featured Co-authors

Wei Liu

Qi Tian

Radu Timofte

Wangmeng Zuo

Jian Yang

Stefanos Zafeiriou

Bin Liu

Tinne Tuytelaars

Jie Wang

Yuan Xie

Guang Yang

Learning to Sample the Most Useful Training Patches from Images

Self-Adaptively Learning to Demoire from Focused and Defocused Image Pairs

Diagnosing and Preventing Instabilities in Recurrent Video Processing

Video Super-resolution with Temporal Group Attention

Wavelet-Based Dual-Branch Network for Image Demoireing

NTIRE 2020 Challenge on Real Image Denoising: Dataset, Methods and Results

NTIRE 2020 Challenge on Image Demoireing: Methods and Results

Image Demoireing with Learnable Bandpass Filters

DeepLPF: Deep Local Parametric Filters for Image Enhancement

Unsupervised Model Personalization while Preserving Privacy and Scalability: An Open Problem

A Multi-Hypothesis Classification Approach to Color Constancy

A Multi-Hypothesis Approach to Color Constancy

Reconstructing the Noise Manifold for Image Denoising

DIFAR: Deep Image Formation and Retouching

Pixel Adaptive Filtering Units

AIM 2019 Challenge on Image Demoireing: Methods and Results

AIM 2019 Challenge on Image Demoireing: Dataset and Study

SteReFo: Efficient Image Refocusing with Stereo Vision

Continual learning: A comparative study on how to defy forgetting in classification tasks

NODE: Extreme Low Light Raw Image Denoising using a Noise Decomposition Network

Meta-Learning for Few-shot Camera-Adaptive Color Constancy

Generating Magnetic Resonance Spectroscopy Imaging Data of Brain Tumours from Linear, Non-Linear and Deep Learning Models