Mairéad Grogan

4th January 2018

Position: Postdoctoral Research Fellow
Location: Stack B, Custom House Quay
Email: mgrogan@tcd.ie

Personal Webpage / Google Scholar / LinkedIn / Research Gate

Content

Biography
Research Topics
Publications


Biography

I am a Postdoctoral Research Fellow on the V-Sense research project, working with Professor Aljosa Smolic in Trinity College Dublin. I am also a member of the Graphics Vision and Visualization (GV2) group in the School of Computer Science and Statistics. I received my undergraduate degree in Pure Mathematics and Statistics from Maynooth University, and my masters degree in Interactive Entertainment Technology, from Trinity College Dublin. I also completed my PhD in Trinity College Dublin, in the areas of colour transfer and shape registration using functional data representations.


Research Topics

Mobile Video Color Transfer Project

Mobile Video Color Transfer Project

For the creation of online visual media, various multimedia software products can be used. Although these editing tasks were previously carried out by artists using software applications such as Adobe ...
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Augmenting Hand-Drawn Art with Global Illumination Effects through Surface Inflation

Augmenting Hand-Drawn Art with Global Illumination Effects through Surface Inflation

Abstract We present a method for augmenting hand-drawn characters and creatures with global illumination effects. Given a single view drawing only, we use a novel CNN to predict a high-quality ...
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Patch-Based Colour Transfer with Optimal Transport

Patch-Based Colour Transfer with Optimal Transport

This paper proposes a new colour transfer method with Optimal Transport to transfer the colour of a source image to match the colour of a target image of the same ...
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L2 based Colour Correction for Light Field Arrays

L2 based Colour Correction for Light Field Arrays

In recent years, there has been an increase in the popularity of Light Field (LF) imaging technology with the increase in availability of LF camera devices such as the Lytro, ...
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L2 Divergence for Robust Colour Transfer

L2 Divergence for Robust Colour Transfer

Optimal Transport is a very popular framework for performing colour transfer in images and videos. We have proposed an alternative framework where the cost function used for inferring a parametric ...
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User Interaction for Image Recolouring using L2

User Interaction for Image Recolouring using L2

Recently, an example based colour transfer approach proposed modelling the colour distributions of a palette and target image using Gaussian Mixture Models, and registers them by minimising the robust L2 ...
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Automatic Palette Extraction for Image Editing

Automatic Palette Extraction for Image Editing

Interactive palette based colour editing applications have grown in popularity in recent years, but while many methods propose fast palette extraction techniques, they typically rely on the user to define ...
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2D Shading for Cel Animation

2D Shading for Cel Animation

In this paper we present a semi-automatic method for creating shades and self-shadows in cel animation. Besides producing attractive images, shades and shadows provide important visual cues about depth, shapes, ...
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Deep Normal Estimation for Automatic Shading of Hand-Drawn Characters

Deep Normal Estimation for Automatic Shading of Hand-Drawn Characters

In this paper we present a new fully automatic pipeline for generating shading effects on hand-drawn characters. Our method takes as input a single digitized sketch of any resolution and ...
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DeepStereoBrush: Interactive Depth Map Creation

DeepStereoBrush: Interactive Depth Map Creation

In this paper, we introduce a novel interactive depth map creation approach for image sequences which uses depth scribbles as input at user-defined keyframes. These scribbled depth values are then ...
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AlphaGAN: Generative adversarial networks for natural image matting

AlphaGAN: Generative adversarial networks for natural image matting

Abstract We present the first generative adversarial network (GAN) for natural image matting. Our novel generator network is trained to predict visually appealing alphas with the addition of the adversarial ...
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Publications

2019

2018

2017

2016

2015