March 12, 2024, 4:48 a.m. | Chenhao Zhang, Yongyang Zhou, Lei Zhang

cs.CV updates on arXiv.org arxiv.org

arXiv:2403.06505v1 Announce Type: new
Abstract: The neural radiance field (NeRF) has emerged as a prominent methodology for synthesizing realistic images of novel views. While neural radiance representations based on voxels or mesh individually offer distinct advantages, excelling in either rendering quality or speed, each has limitations in the other aspect. In response, we propose a pioneering hybrid representation named Vosh, seamlessly combining both voxel and mesh components in hybrid rendering for view synthesis. Vosh is meticulously crafted by optimizing the …

abstract advantages arxiv cs.cv hybrid images limitations mesh methodology nerf neural radiance field novel quality real-time rendering representation speed synthesis type view voxel

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Data Science Analyst

@ Mayo Clinic | AZ, United States

Sr. Data Scientist (Network Engineering)

@ SpaceX | Redmond, WA