AI助力体积视频流传输，突破3D内容传输与渲染瓶颈
AI-Driven Innovations in Volumetric Video Streaming: A Review
- 用AI优化点云、网格等3D表示的压缩与传输
- 提升6自由度沉浸式视频的实时渲染效率
- 适合虚拟现实、元宇宙等场景开发者参考
为提升沉浸式与交互式用户体验，体积视频作为支持6自由度（6 DoF）的3D内容形式受到关注。与传统2D内容不同，体积视频可通过点云、网格或神经表示等多种方式呈现，但其复杂结构和海量数据导致传输与渲染面临重大挑战，限制了其在日常应用中的普及。近年来，研究人员提出多种基于人工智能的技术以应对这些挑战，显著提升了体积内容流媒体的效率与质量。本文系统综述了近期在AI驱动体积视频流传输方面的进展，旨在梳理当前最先进技术，并为真实世界中体积视频流部署提供未来研究方向。
原文摘要 · Abstract (English)
Recent efforts to enhance immersive and interactive user experiences have driven the development of volumetric video, a form of 3D content that enables 6 DoF. Unlike traditional 2D content, volumetric content can be represented in various ways, such as point clouds, meshes, or neural representations. However, due to its complex structure and large amounts of data size, deploying this new form of 3D data presents significant challenges in transmission and rendering. These challenges have hindered the widespread adoption of volumetric video in daily applications. In recent years, researchers have proposed various AI-driven techniques to address these challenges and improve the efficiency and quality of volumetric content streaming. This paper provides a comprehensive overview of recent advances in AI-driven approaches to facilitate volumetric content streaming. Through this review, we aim to offer insights into the current state-of-the-art and suggest potential future directions for advancing the deployment of volumetric video streaming in real-world applications.
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