详细信息
- 来源站点
- ArXiv CS.CV
- 作者
- Han Jiao, Jiakai Sun, Lei Zhao, Wei Xing, Huaizhong Lin, Zhanjie Zhang, Ao Ma
- 文章类型
- PAPER
- 语言
- en
- 发布日期
- 2026-08-04
摘要
arXiv:2608.01053v1 Announce Type: new Abstract: Constructing photorealistic Free-Viewpoint Videos (FVVs) of dynamic scenes from a set of posed 2D images has been an intriguing yet challenging task in computer vision. Methods based on neural rendering achieve high-fidelity image quality in FVV construction. However, most of these methods are unable to achieve real-time rendering and often require complete video sequences to train. Despite the existence of some online training methods capable of rendering FVVs in real time, they struggle to meet the requirements for storage and training time for downstream applications. To overcome this problem, we propose Struct-GStream, which can achieve efficient FVV streaming using structured 3D Gaussians (3DGs). Specifically, we introduce dynamic anchor points to generate structured 3DGs to construct basic scenes and model approximate scene movements based on the assumption of local rigidity in object motion.