Creation of Virtual Worlds for Machine Learning
Unreal Engine is a powerful 3D rendering tool widely used in game development. In recent years, it has become increasingly popular in science and industry. This course teaches you how to use Unreal Engine to generate synthetic data for machine learning projects.
Praktische info:
Inschrijven?
- Voorwaarden: Basic familiarity with 3D/graphics concepts, machine learning. Basic Python or scripting experience is useful but not essential. Previous knowlegde of Unreal Engine is essential.
- Prijs: Free
A personal institutional email address (university/research institution, government agency, organisation, or company) is required to register for JSC training courses. If you don't have an institutional email address, please get in touch with the contact person for this course.
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Leertraject
You will learn to create 3D assets using AI tools (ComfyUI), build large virtual worlds automatically using Unreal's Procedural Content Generation (PCG) framework, export video footage from these worlds via Network Device Interface (NDI), and prepare the data for training video generation models. By the end of the course, you will have built a complete working pipeline and understand how to use it for machine learning workflows.
What you will learn:
- Generate 3D assets using AI (ComfyUI) and import them into Unreal Engine
- Build scalable virtual worlds with Unreal's PCG framework
- Export camera footage and metadata from virtual scenes using NDI (network video over IP)
- Getting to know city sample and how NDI outputs data streams for training data
- Organise and prepare synthetic datasets for machine learning
- Understand training pipelines for video generation models
Gerelateerde opleidingen
Artificial Intelligence in Business and Industry
Postgraduate - Kortrijk - KU Leuven, PUC - KU Leuven Continue, VAIA
