DONeRF: Towards Real-Time Rendering of Neural Radiance Fields using Depth Oracle Networks
(Graz Uni, FRL)

❗️ Another attempt to speedup NeRF: 15 FPS at 800x800.

The number of samples required for each view ray can be significantly reduced when local samples are placed around surfaces in the scene. Authors propose a depth oracle network, which predicts ray sample locations for each view ray with a single network evaluation. They show that using a classification network around logarithmically discretized and spherically warped depth values is essential to encode surface locations rather than directly estimating depth.

DONeRF is a combination of these techniques: A dual network design with a depth oracle network as a first step and a locally sampled shading network for ray accumulation.

➕ 48x speedup compared to NeRF, while equal or better quality compared to NeRF. Obviously it is not that fast as NeF or FastNeRF, but the approach is different.

📝 Paper
🌐 Proj page