mlsanityData to 14 Oct 2026

AI-Driven Innovations in Volumetric Video Streaming: A Review

arXiv 2412.12208 ↗First posted 15 Dec 2024cs.CVcited by 2

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Abstract (arXiv)

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.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 71 of its 118 references that are in the map. First posted on arXiv 15 Dec 2024.

Builds on

71 of 118 references.

References · 71

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38 more
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50 most cited of 71 All 71 (JSON)

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 1.

2 papers.

  1. 2025Dynamic Scene Reconstruction: Recent Advance in Real-time Rendering and Streamingcited by 9
  2. 2026GenStream: Semantic Streaming Framework for Generative Reconstruction of Human-centric Mediacited by 0