<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-07-08T08:44:08Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/20478066-CF81-4C4C-8295-FA2E140799D6" ns1:id="20478066-CF81-4C4C-8295-FA2E140799D6"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/5F589EB5-05F1-41B9-80AD-35BED764D0A5" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/79D5C497-16E1-4061-BDF8-B09BA4FE392B" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/79D5C497-16E1-4061-BDF8-B09BA4FE392B" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/6C41905E-3842-4AD4-9F8B-5F205870CD13" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2024-02-29T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/217926A7-A3EA-4603-9F81-B636B9827E9F" ns1:rel="FUND" ns1:start="2023-08-31T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10081575</ns2:identifier></ns2:identifiers><ns2:title>Feasibility of using Artist-AI co-creativity workflows for remastering classic video games</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>In the video games industry, there is currently the opportunity to remaster classic game titles from previous generations of gaming. This trend has gained momentum in recent years, with many game studios and publishers remastering their classic games for modern platforms. Remastering older titles can be an excellent way for game studios to generate substantial additional revenue by appealing to both older fans and new audiences who may not have played the original and to preserve classic titles and keep them relevant for a new generation of gamers. Remastering typically involves enhancing the graphics and sound of the original game and improving the user experience to make it more appealing and accessible to modern audiences. There is however still a large time commitment and the upfront cost of remastering classic game titles that can be prohibitively expensive.

This project will investigate the feasibility of implementing Artificial Intelligence (AI), to integrate into existing workflows, in order to reduce the overall work hours, and therefore upfront cost, required for the development of remastered versions of classic games. Specifically, we will investigate how AI can be developed, trained and utilised to upscale very low-resolution images, in order to remaster classic game titles. Traditionally, image upscaling involved simple methods such as interpolation, which would create new pixels by estimating the values between the existing pixels. However, these methods often resulted in blurry or pixelated images. In recent years, there has been a significant advancement in image upscaling technology using AI. AI can learn to identify patterns in low-resolution images and generate high-resolution versions of the same image with significantly improved quality.

Whilst there are a number of companies and research institutions investigating upscaling technology, there is currently no investigation, product or research into how to upscale very-low-resolution hand-drawn art assets for game asset remastering. This project will investigate the feasibility of integrating current upscaling technologies within this space into existing game studio workflows and develop a generalised, commercialisable tool, as a demonstrator.</ns2:abstractText></ns2:project>