SqueezeMe: Mobile-Ready Distillation of Gaussian Full-Body Avatars

present SqueezeMe, a simple and highly effective framework to convert highfidelity 3D Gaussian full-body avatars into a lightweight representation that supports both animation and rendering with mobile-grade compute.Our key observation is that the decoding of pose-dependent Gaussian attributes from a neural network creates non-negligible memory and computational overhead.Inspired by blendshapes and linear pose correctives widely used in Computer Graphics, we address this by distilling the pose correctives learned with neural networks into linear layers.Moreover, we further reduce the parameters by sharing the correctives among nearby Gaussians.Combining them with a custom splatting pipeline based on Vulkan, we achieve, for the first time, simultaneous animation and rendering of 3 Gaussian avatars in real-time (72 FPS) on a Meta Quest 3 VR headset.