The evolution of volumetric video: A survey of smart transcoding and compression approaches
Preetish Kakkar, Hariharan Ragothaman

TL;DR
This survey reviews the evolution of volumetric video technology, emphasizing AI-driven transcoding and compression methods to improve efficient delivery of high-bandwidth 3D media content.
Contribution
It provides a comprehensive overview of current approaches in volumetric video compression and highlights the potential of AI techniques to enhance delivery efficiency.
Findings
AI-driven compression techniques show promise in reducing data size.
Smart transcoding approaches improve streaming efficiency.
Volumetric video technology is rapidly evolving with new methods.
Abstract
Volumetric video, the capture and display of three-dimensional (3D) imagery, has emerged as a revolutionary technology poised to transform the media landscape, enabling immersive experiences that transcend the limitations of traditional 2D video. One of the key challenges in this domain is the efficient delivery of these high-bandwidth, data-intensive volumetric video streams, which requires innovative transcoding and compression techniques. This research paper explores the state-of-the-art in volumetric video compression and delivery, with a focus on the potential of AI-driven solutions to address the unique challenges posed by this emerging medium.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
MethodsFocus
