OmniAvatar: Geometry-Guided Controllable 3D Head Synthesis

TL;DR

OmniAvatar is a geometry-guided 3D head synthesis model that enables highly controllable, detailed, and realistic head generation from in-the-wild images, with explicit control over pose, expression, and shape.

Contribution

It introduces a novel semantic signed distance function for explicit control and a differentiable volumetric correspondence map, enabling high-quality, controllable 3D head synthesis from unstructured images.

Findings

Outperforms state-of-the-art methods in quality and control accuracy.

Generates dynamic, identity-preserved 3D heads with detailed expressions.

Demonstrates effective disentangled control over multiple head attributes.

Abstract

We present OmniAvatar, a novel geometry-guided 3D head synthesis model trained from in-the-wild unstructured images that is capable of synthesizing diverse identity-preserved 3D heads with compelling dynamic details under full disentangled control over camera poses, facial expressions, head shapes, articulated neck and jaw poses. To achieve such high level of disentangled control, we first explicitly define a novel semantic signed distance function (SDF) around a head geometry (FLAME) conditioned on the control parameters. This semantic SDF allows us to build a differentiable volumetric correspondence map from the observation space to a disentangled canonical space from all the control parameters. We then leverage the 3D-aware GAN framework (EG3D) to synthesize detailed shape and appearance of 3D full heads in the canonical space, followed by a volume rendering step guided by the volumetric correspondence map to output into the observation space. To ensure the control accuracy on the synthesized head shapes and expressions, we introduce a geometry prior loss to conform to head SDF and a control loss to conform to the expression code. Further, we enhance the temporal realism with dynamic details conditioned upon varying expressions and joint poses. Our model can synthesize more preferable identity-preserved 3D heads with compelling dynamic details compared to the state-of-the-art methods both qualitatively and quantitatively. We also provide an ablation study to justify many of our system design choices.