HyperBones: Realtime Bone-driven Neural Garment Simulation with Hypernetwork Conditioning

TL;DR

HyperBones introduces a fast, neural-based garment simulation method that achieves realistic, physics-consistent dynamics at over 300 FPS, suitable for interactive applications.

Contribution

The paper presents a novel neural dynamics simulator with a coarse-fine architecture, decoupling identity-specific computation for real-time, plausible garment animation.

Findings

Runs at 300+ FPS on a commodity GPU

Produces physically plausible garment dynamics

Generalizes across diverse motions and body shapes

Abstract

Recent advances in garment simulation have brought high-quality results closer to real-time performance. Physics-based simulators can produce accurate motion, but remain too computationally expensive for interactive applications. In contrast, linear blend skinning is efficient, but cannot capture the complex dynamics of loose-fitting garments, often leading to unrealistic motion and visual artifacts. Neural methods offer a promising alternative, yet they still struggle to animate loose clothing plausibly under strict runtime constraints. We present a fast and physically plausible approach for dynamic garment simulation. Our method trains a reduced-space neural dynamics simulator composed of independent coarse- and fine-level components. At the coarse level, the garment is driven by a set of virtual bones integrated with a lightweight neural network. Fine-scale wrinkle details are then recovered using a trained convolutional neural map. By decoupling identity-specific computation from real-time neural integration, our architecture maintains high performance while supporting diverse body shapes and motions. We further introduce an effective physics-supervision scheme that enables accurate results without relying on an external simulator. Experiments show that our method produces physically plausible garment dynamics, generalizes across a range of motions and body shapes, and supports a fixed set of garments. Our simulator runs at 300+ FPS on a commodity GPU, making it suitable for real-time applications.