Feb. 5, 2024, 3:47 p.m. | Zhiyu Zhang Guo Lu Huanxiong Liang Anni Tang Qiang Hu Li Song

cs.CV updates on arXiv.org arxiv.org

Volumetric videos, benefiting from immersive 3D realism and interactivity, hold vast potential for various applications, while the tremendous data volume poses significant challenges for compression. Recently, NeRF has demonstrated remarkable potential in volumetric video compression thanks to its simple representation and powerful 3D modeling capabilities, where a notable work is ReRF. However, ReRF separates the modeling from compression process, resulting in suboptimal compression efficiency. In contrast, in this paper, we propose a volumetric video compression method based on dynamic NeRF …

3d modeling applications capabilities challenges coding compression cs.cv data dynamic eess.iv immersive modeling nerf optimization rate representation simple vast video video compression videos work

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