Providing fully immersive volumetric videos on mobile devices requires photo-realistic, full-scene rendering with smooth playback experiences. Since traditional 3D representations such as point clouds struggle with visual quality, 3D Gaussian Splatting (3DGS) 4 has emerged as an effective way to represent high-quality 3D scenes. However, existing approaches for 3DGS-based video streaming incur significant rendering overhead, making realtime playback challenging. This article presents Vega 5, a 3DGS-based system that enables fully immersive volumetric video streaming on smartphones. Vega bridges the gap between highquality 3DGS rendering and the constraints of mobile devices—specifically, limited network bandwidth and compute power. The core idea is object-level selective computation, which optimizes both data size and rendering overhead by prioritizing visually significant objects. To realize this idea, Vega introduces a mobile-friendly encoding scheme on the server, in which key frames store full scene data while residual frames encode only dynamic object information to reduce redundancy. On the client side, Vega employs a view-adaptive rendering pipeline that selectively renders visually important objects to meet strict real-time deadlines while effectively utilizing the smartphone's CPU, GPU, and NPU.
Kim et al. (Thu,) studied this question.