Charlie Hewitt

Fake It Till You Make It

Fake It Till You Make It

Project Page

We demonstrate that it is possible to perform face-related computer vision in the wild using synthetic data alone.

The community has long enjoyed the benefits of synthesizing training data with graphics, but the domain gap between real and synthetic data has remained a problem, especially for human faces. Researchers have tried to bridge this gap with data mixing, domain adaptation, and domain-adversarial training, but we show that it is possible to synthesize data with minimal domain gap, so that models trained on synthetic data generalize to real in-the-wild datasets.

OpticSim.jl

OpticSim.jl

GitHub

OpticSim.jl is a Julia package for simulation and optimization of complex optical systems developed by the Microsoft Research Interactive Media Group and the Microsoft HART group.

I spent most of 2020 working with Brian Guenter on the package and it has now been open sourced on GitHub.

Microsoft

Microsoft

Website

I'm joining Microsoft's Mixed Reality & AI Labs in Cambridge as a research scientist.

I interned with the group over the summer of 2019 and will be returning permanently to work at the intersection of computer graphics, computer vision and machine learning.

Face Synthetics

Face Synthetics

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Technical report describing the synthetic faces system which I worked on while with Microsoft over the summer of 2019.

Microsoft Research

Microsoft Research

Website

I'm rejoining Microsoft's research lab in Cambridge at the start of 2020 as a research consultant for six eighteen months. I'll be working with the Interactive Media Group on future display technologies.

OLM

OLM

Website

I'm heading to Tokyo for a three month internship with the R&D department at OLM Digital, starting in September 2019. I'll be building in-house tooling for their 3D animation and visual effects pipelines, primarily developing custom modelling tools for Autodesk Maya.

Mocrosoft HoloLens

Mocrosoft HoloLens

Website

I'm joining the Cognition research and development team based at Microsoft's lab in Cambridge as a research consultant over the summer of 2019, working on application of machine learning to problems in computer graphics and vision.

The AVAM

The AVAM

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Paper introducing the Autonomous Vehicle Acceptance Model (AVAM), a model of user acceptance for autonomous vehicles, adapted from existing models of user acceptance for generic technologies.

Presented at Intelligent User Interfaces 2019.

The complete data and analysis code can be downloaded here

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CMIC

CMIC

Website

I'm taking up a research assistant position at the Computational Media Innovation Centre (CMIC) at the Victoria University of Wellington in New Zealand for three months starting in January 2019.

I'll be working with researchers and industry partners to help develop innovative augmented, virtual and mixed reality technologies.

Microsoft Research

Microsoft Research

Website

I'm joining Microsoft Research in Cambridge for a three six month research internship starting in summer 2018

I'll be helping to develop the next generation of head mounted displays using digital holography.

Some more details about the project are available here.

Animal Face Alignment

Animal Face Alignment

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For my fourth year (masters) project I looked at head pose estimation and facial landmark detection for animals, specifically sheep. This included the adaption of deep learning models for sheep head pose estimation and combination with classical techniques to enable accurate facial alignment. This culminated in the implementation of a near real-time pipeline for farm survellience videos, the end-goal being automated livestock health monitoring.

A condensed version of the dissertation was presented at ACII 2019.

Leaf Identification

Leaf Identification

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Paper presenting a novel feature set for shape-only leaf identification from images. Over 90% accuracy is achieved on all but one public dataset, with top-four accuracy for these datasets over 98%.

Source code available on GitHub.

Emosic

Emosic

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Paper focussing on the design, deployment and evaluation of Convolutional Neural Network (CNN) architectures for facial affect analysis on mobile devices. The proposed architectures equal the dataset baseline while minimising storage requirements. A user study demonstrates the feasibility of deploying the models for real-world applications.

Source code is available on GitHub.

GP Confidences for CNNs

GP Confidences for CNNs

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Paper presenting a hybrid classification technique using Gaussian processes fitted on features extracted by a convolutional neural network to enable estimation of prediction confidence. The classifier is evaluated on the MNIST dataset and shown to have somewhat meaningful implications for confidence estimation.

THJE Website

THJE Website

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Website design and other graphics for the 2018 Trinity Hall June Event, in addition to managing the ticketing service provided through Qpay.

Cydar

Cydar

Website

I'll be joining the team at Cydar in Cambridge for a two month internship over the summer of 2017.

I will help to develop technologies for medical imaging to be used by surgeons during operations.

Tree Generation

Tree Generation

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For my third year project I explored the procedural modelling of trees for use in computer graphics.

I implemented two systems which generate tree models of many types within the Blender modelling application, one of which now forms the basis of a fully featured plugin.

Source code available on GitHub.

Jagex

Jagex

Website

I'm joining the team at Jagex Games Studio for three months in the summer of 2016 as an intern.

I'll be working on a project as part of a small team aimed at exploring new areas which Jagex may be interested in expanding into in the future.

THBC Site Redesign

THBC Site Redesign

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Trinity Hall Boat Club's original website was designed in the 90s and was starting to show its age. I carried out a complete visual redesign and tidied up many aspects of the website code.

I also wrote a new voting system to be used for captaincy elections, as well as updating the content of many of the site's pages and adding some new ones.

Fingal

Fingal

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Animated icon theming platform (similar to Winterboard) for iOS 8 and 9.

Available for free from the ModMyi Cydia repo. Source code available on GitHub.

seng

seng

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Seng is a sleek and highly customisable replacement for your iOS 8 & 9 app switcher and control center, providing 2 core features; Multi Centre and Hot Corners.

Available to purchase from the Cydia Store.

CustomCover

CustomCover

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Customise the iOS LockScreen Now Playing view and Music app. Packed full of features and compatible with all devices running iOS 7 through 9.

Available to purchase from the Cydia Store.

Developer Info

Messages Customiser

Messages Customiser

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The most fully featured tweak available for modifying the iOS Messages app. Messages Customiser is the one stop solution for tweaking your texting experience on all devices running iOS 7 - 9

Free and Premium version available from the Cydia Store.

Subtle7

Subtle7

Simple winterboard theme with subtle changes from the default iOS 7 look. Inspired by the work of Louie Mantia

Includes all stock icons, and a few extra. Compatible with all devices on iOS 7.

Available from my personal repo.

Tinct & Chroma

Tinct & Chroma

Chroma, and the more fully featured Tinct, are a duo of UI tweaks for iOS 7 and 8. Both allow for extensive customisation of the colours of various elements of the iOS interface, while remaining lightweight and simple to use.

Chroma is available for free from Cydia (source on GitHub), and Tinct is available to purchase from the Cydia Store.

Linen Growl Style

Linen Growl Style

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Custom style for the popular Growl notification management app.

Inspired by the iOS 5 and OSX Mountain Lion interface styling and with custom slide in animation.

Flippers Ain't Wings

Flippers Ain't Wings

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Block jumping, arcade style game for all iOS devices.

Follow the story of Percy the Penguin in his adventure to discover the source of mysterious ice blocks falling from the sky.

Copyright © 2021 Charlie Hewitt