English

Per-Gaussian Embedding-Based Deformation for Deformable 3D Gaussian Splatting

Computer Vision and Pattern Recognition 2024-07-29 v5

Abstract

As 3D Gaussian Splatting (3DGS) provides fast and high-quality novel view synthesis, it is a natural extension to deform a canonical 3DGS to multiple frames for representing a dynamic scene. However, previous works fail to accurately reconstruct complex dynamic scenes. We attribute the failure to the design of the deformation field, which is built as a coordinate-based function. This approach is problematic because 3DGS is a mixture of multiple fields centered at the Gaussians, not just a single coordinate-based framework. To resolve this problem, we define the deformation as a function of per-Gaussian embeddings and temporal embeddings. Moreover, we decompose deformations as coarse and fine deformations to model slow and fast movements, respectively. Also, we introduce a local smoothness regularization for per-Gaussian embedding to improve the details in dynamic regions. Project page: https://jeongminb.github.io/e-d3dgs/

Keywords

Cite

@article{arxiv.2404.03613,
  title  = {Per-Gaussian Embedding-Based Deformation for Deformable 3D Gaussian Splatting},
  author = {Jeongmin Bae and Seoha Kim and Youngsik Yun and Hahyun Lee and Gun Bang and Youngjung Uh},
  journal= {arXiv preprint arXiv:2404.03613},
  year   = {2024}
}

Comments

ECCV 2024. Project page: https://jeongminb.github.io/e-d3dgs/

R2 v1 2026-06-28T15:44:22.116Z