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

A Theory of Stabilization by Skull Carving

SEED
Dec 3, 2024
A new approach to stabilizing facial motion for creating photo-real avatars that significantly enhances accuracy and robustness.

Gigi Lightning Talks

SEED
Sep 26, 2024
SEED brought together developers to show off their prowess using the Gigi rapid prototyping platform for real-time rendering.

SEED's Adventure in Gameplay Innovation

SEED
Sep 13, 2024
SEED is branching out into the world of game mechanics, storytelling magic, and interactive wonders.