arXiv Computer Vision
Sep 18

AGORA: Adversarial Generation Of Real-time Animatable 3D Gaussian Head Avatars

AGORA is a new framework that extends 3D Gaussian Splatting with a generative adversarial network to produce high‑fidelity, animatable 3D head avatars. It introduces a lightweight FLAME‑conditioned deformation branch that predicts per‑Gaussian residuals for identity‑preserving, fine‑grained expression control, and a dual‑discriminator training scheme that enforces expression fidelity. The system achieves real‑time inference at 250 FPS on a single GPU and, for the first time, CPU‑only animatable 3DGS avatar synthesis at ~9 FPS.

By Ramazan Fazylov, Sergey Zagoruyko, Aleksandr Parkin, Stamatis Lefkimmiatis, Ivan Laptev
arXiv Computer Vision
4d ago

GSHeadRelight: Fast Relightability for 3D Gaussian Head Synthesis

GSHeadRelight introduces a fast relighting method for 3D Gaussian head synthesis, addressing the need for photorealistic rendering, real‑time performance, and generalization to unseen subjects in portrait photography, VR, and AR. The approach uses a unified neural radiance transfer representation that linearly responds to incident light, relying only on in‑the‑wild images rather than expensive light stage data. It achieves state‑of‑the‑art relighting results while delivering a rendering speed 12× faster than prior 3D‑aware portrait relighting methods.

By Henglei Lv, Bailin Deng, Jianzhu Guo, Xiaoqiang Liu, Pengfei Wan, Di Zhang, Lin Gao
arXiv AI
Oct 2

One Basis to Animate Them All: Gaussian Blendshape Distillation for Real-Time Avatars

The paper introduces GALA, a distillation technique that replaces costly neural decoding in 3D Gaussian avatars with a shallow MLP predicting blendshape coefficients, enabling real‑time animation. By constructing a basis via block‑local PCA under a rendering‑aware metric, GALA achieves high fidelity while reducing memory usage. Experiments on three avatar models show up to three orders of magnitude lower CPU cost and frame rates up to 60fps on mobile devices.

By Ramazan Fazylov, Stamatis Lefkimmiatis, Ivan Laptev