LogInThe release introduces a new performance-improving Bone Mask feature and adds the Houdini scene the team used for training.
In case you missed the news, Epic Games has just rolled out Unreal Engine 5.3, the latest version of their flagship real-time 3D creation tool and game engine, expanding and enhancing the engine's capabilities and functionality by introducing an array of exciting experimental features for rendering, animation, and simulation.
In addition to unveiling brand-new features for users to explore, this update also brings significant improvements to Unreal Engine 5's existing arsenal, upgrading its Lumen, Nanite, Path Tracing, and other tools. Among these enhancements is the remarkable ML Deformer Sample, which was initially launched by Epic Games earlier this year and has now received further improvements in version 5.3.
For those unaware, the Machine Learning Deformer Sample was designed to demonstrate how Unreal Engine's ML technology can be used to create a high-fidelity next-generation character with deformations driven by full muscle, flesh, and cloth simulation. The sample includes an anatomically correct digi-double derived from 3D, 4D, and MRI data, using the latest ML techniques to drive surface deformations in Unreal Engine.
The release introduces two new features for ML Deformer Sample, with the first one being the performance-enhancing Bone Mask feature, which can give GPU and memory improvements of around 40% when using the Neural Morph Model.
Moreover, the 5.3 version of the sample now includes Houdini assets that were used by the team to generate muscle and flesh simulation data for training. As noted by Matt Stoneham, a Principal Technical Animator at Epic Games, the Houdini scene is "included in the sample download, inside of ArtSource.zip".
If you would like to learn more about Unreal Engine's ML technology, we also recommend checking out Epic's State of Unreal keynote session shared during GDC 2023, which provides an in-depth look at Unreal Engine 5.2's updated ML Deformer, a machine learning-powered feature that can approximate any complex deformation model to create accurate non-linear deformer systems.
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