Vosh: Voxel-Mesh Hybrid Representation for Real-Time View Synthesis
Chenhao Zhang Yongyang Zhou Lei Zhang
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 voxel grid
of NeRF, strategically with selected voxels replaced by mesh. Therefore, it
excels in fast rendering scenes with simple geometry and textures through its
mesh component, while simultaneously enabling high-quality rendering in
intricate regions by leveraging voxel component. The flexibility of Vosh is
showcased through the ability to adjust hybrid ratios, providing users the
ability to control the balance between rendering quality and speed based on
flexible usage. Experimental results demonstrates that our method achieves
commendable trade-off between rendering quality and speed, and notably has
real-time performance on mobile devices.