CVMay 23, 2024

D-MiSo: Editing Dynamic 3D Scenes using Multi-Gaussians Soup

arXiv:2405.14276v319 citationsh-index: 16NIPS
Originality Incremental advance
AI Analysis

This work addresses a specific problem in 3D scene modeling for computer graphics and vision applications, representing an incremental improvement over existing methods.

The paper tackles the challenge of editing dynamic 3D scenes modeled with Gaussian Splatting, which is difficult due to issues like element selection and reproducibility, and proposes D-MiSo to enable editable scene dynamics over time.

Over the past years, we have observed an abundance of approaches for modeling dynamic 3D scenes using Gaussian Splatting (GS). Such solutions use GS to represent the scene's structure and the neural network to model dynamics. Such approaches allow fast rendering and extracting each element of such a dynamic scene. However, modifying such objects over time is challenging. SC-GS (Sparse Controlled Gaussian Splatting) enhanced with Deformed Control Points partially solves this issue. However, this approach necessitates selecting elements that need to be kept fixed, as well as centroids that should be adjusted throughout editing. Moreover, this task poses additional difficulties regarding the re-productivity of such editing. To address this, we propose Dynamic Multi-Gaussian Soup (D-MiSo), which allows us to model the mesh-inspired representation of dynamic GS. Additionally, we propose a strategy of linking parameterized Gaussian splats, forming a Triangle Soup with the estimated mesh. Consequently, we can separately construct new trajectories for the 3D objects composing the scene. Thus, we can make the scene's dynamic editable over time or while maintaining partial dynamics.

Code Implementations1 repo
Foundations

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