Pith. sign in

REVIEW 4 cited by

PSAvatar: A Point-based Shape Model for Real-Time Head Avatar Animation with 3D Gaussian Splatting

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2401.12900 v5 pith:KKSFFZU5 submitted 2024-01-23 cs.GR cs.CV

classification cs.GRcs.CV
keywords headgaussianmodelshaperepresentationavataravatarscreation
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
abstract

Despite much progress, achieving real-time high-fidelity head avatar animation is still difficult and existing methods have to trade-off between speed and quality. 3DMM based methods often fail to model non-facial structures such as eyeglasses and hairstyles, while neural implicit models suffer from deformation inflexibility and rendering inefficiency. Although 3D Gaussian has been demonstrated to possess promising capability for geometry representation and radiance field reconstruction, applying 3D Gaussian in head avatar creation remains a major challenge since it is difficult for 3D Gaussian to model the head shape variations caused by changing poses and expressions. In this paper, we introduce PSAvatar, a novel framework for animatable head avatar creation that utilizes discrete geometric primitive to create a parametric morphable shape model and employs 3D Gaussian for fine detail representation and high fidelity rendering. The parametric morphable shape model is a Point-based Morphable Shape Model (PMSM) which uses points instead of meshes for 3D representation to achieve enhanced representation flexibility. The PMSM first converts the FLAME mesh to points by sampling on the surfaces as well as off the meshes to enable the reconstruction of not only surface-like structures but also complex geometries such as eyeglasses and hairstyles. By aligning these points with the head shape in an analysis-by-synthesis manner, the PMSM makes it possible to utilize 3D Gaussian for fine detail representation and appearance modeling, thus enabling the creation of high-fidelity avatars. We show that PSAvatar can reconstruct high-fidelity head avatars of a variety of subjects and the avatars can be animated in real-time ($\ge$ 25 fps at a resolution of 512 $\times$ 512 ).

Discussion (0). Sign in to comment.

Forward citations

Cited by 4 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. GeoAvatar: Adaptive Geometrical Gaussian Splatting for 3D Head Avatar

    cs.GR 2025-07 conditional novelty 7.0 of 10

    GeoAvatar improves 3D head avatar quality by adaptively regulating Gaussian offsets per facial region, adding a detailed mouth structure with part-wise deformation, and releasing a new expressive monocular dataset, Dy...

  2. S-Avatar: Diffusion-Guided Gaussian Head Avatars from a Single Image

    cs.CV 2026-07 conditional novelty 5.0 of 10

    A three-stage pipeline generates animatable 3D Gaussian head avatars from one image by diffusion-based splat synthesis, FLAME fitting, and inverse-distance binding with scale adaptation.

  3. AvatarBack: Back-Head Generation for Complete 3D Avatars from Front-View Images

    cs.CV 2025-08 conditional novelty 5.0 of 10

    AvatarBack adds a generative back-head prior and a learned spatial alignment to Gaussian-splatting head avatars, improving rear geometry and texture while keeping frontal quality.

  4. SyncTalk++: High-Fidelity and Efficient Synchronized Talking Heads Synthesis Using Gaussian Splatting

    cs.CV 2025-06 conditional novelty 5.0 of 10

    SyncTalk++ synthesizes speech-driven talking-head videos via 3D Gaussian Splatting and reports state-of-the-art synchronization and quality at up to 101 FPS.

Pith tools