SEED Research & Announcements Blogs Publications Careers Contact Us Research & Announcements Blogs Publications Careers Contact Us

SIGGRAPH 21: Swish – Neural Network Cloth Simulation in Madden NFL 21

This project paper was presented at ACM SIGGRAPH 2021. https://s2021.siggraph.org/

Swish is a real-time machine-learning-based cloth simulation technique for games.

Swish was used to generate realistic cloth deformation and wrinkles for NFL player jerseys in Madden NFL 21. To our knowledge, this is the first neural cloth simulation featured in a shipped game. This technique allows accurate high-resolution simulation for tight clothing, which is a case where traditional real-time cloth simulations often achieve poor results. We represent cloth detail using both mesh deformations and a database of normal maps and train a simple neural network to predict cloth shape from the pose of a character’s skeleton.

This presentation shares implementation and performance details that will be useful to other practitioners seeking to introduce machine learning into their real-time character pipelines.

Author: Chris Lewin

Download the presentation slides (PDF 48 MB)

Download the project paper (PDF 2.2 MB)

Watch the full presentation below.

test

Related News

From Photo to Expression: Generating Photorealistic Facial Rigs

SEED
Apr 25, 2024
This presentation from GDC 2024 discusses how machine learning can improve facial animation.

EA presents on graphics, gameplay, and generative tech at GDC 2024

Electronic Arts Inc.
Mar 12, 2024
Don’t miss these GDC 2024 talks from Electronic Arts engineers, scientists, and technical artists.

Machine Learning for Game Devs: Part 3

SEED
Jan 16, 2024
An introduction to machine learning for game developers using C++. Part 3: Training a neural network.