AniGS: Bridging Rendering and Diffusion Prior for 3D Scene Animation

2026-07-20

AI Summary

This work addresses the lack of natural dynamics in static, large-scale 3D Gaussian splatting scenes by proposing a time-conditioned deformation field method that integrates a pretrained video diffusion model. Through an iterative data–model update and render–optimization pipeline, the approach injects environmental dynamics—such as swaying vegetation—while preserving rigid structures. It represents the first effort to incorporate diffusion priors into scene-level 3D animation generation, overcoming the limitations of existing methods that are confined to small regions or object-centric settings. The framework enables modeling of distributed, subtle motions across complex outdoor environments. Experiments on five real-world, large-scale outdoor scenes demonstrate that the method produces high-quality novel-view animations, significantly enhancing visual realism and viewer immersion.

Abstract

Novel view rendering of large and complex reconstructed scenes is becoming increasingly photorealistic. However, most reconstructions remain static and lack the ambient motion that makes environments immersive. We present AniGS, a method for scene-level animation of 3D Gaussian Splatting (3DGS) reconstructions that adds subtle, distributed dynamics, e.g., vegetation motion, while preserving rigid structures. Unlike existing 3D animation techniques which are limited to object-centric subjects or small regions, AniGS is designed for large, cluttered, navigable scenes. AniGS represents the scene with a canonical 3DGS and models motion using a time-conditioned deformation field. To animate the entire scene, we leverage a pretrained video diffusion model and introduce an iterative dataset--model update strategy that progressively expands viewpoint coverage and repeatedly updates camera-fixed training videos using a render-and-refine scheme. To prevent artifacts from unintended motion in static areas, we further introduce a composed video-to-video refinement scheme that restricts motion to desired regions. Experiments on five real-world, large-scale outdoor scenes demonstrate that AniGS produces natural ambient dynamics and high-quality novel view videos, enabling more immersive viewing experiences of reconstructed environments.

Problem

• 3D scene animation
• ambient motion
• novel view synthesis
• 3D Gaussian Splatting
• large-scale scenes

Innovation

• 3D Gaussian Splatting
• video diffusion model
• scene-level animation
• deformation field
• render-and-refine