VEDAL: Variational Error-Driven Asynchronous Learning for 3D Gaussian Splatting Pruning 事件

VEDAL: Variational Error-Driven Asynchronous Learning for 3D Gaussian Splatting Pruning arXiv:2606.02346v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) achieves remarkable novel view synthesis quality with real-time rendering, yet suffers from excessive memory consumption due to millions of Gaussian primitives. Existing pruning methods rely on heuristic importance scores or synchronous batch updates, leading to suboptimal compression and training instability. We propose VEDAL, a pr