Superpoint Gaussian Splatting for Real-Time High-Fidelity Dynamic Scene Reconstruction

Understand

Rendering novel view images in dynamic scenes is a crucial yet challenging task.

• Current methods mainly utilize NeRF-based methods to represent the static scene and an additional time-variant MLP to model scene deformations, resulting in relatively low rendering quality as well as slow inference speed.
• To tackle these challenges, we propose a novel framework named Superpoint Gaussian Splatting (SP-GS).
• Specifically, our framework first employs explicit 3D Gaussians to reconstruct the scene and then clusters Gaussians with similar properties (e.g., rotation, translation, and location) into superpoints.