Learning Neural Duplex Radiance Fields for Real-Time View Synthesis

Understand

Neural radiance fields (NeRFs) enable novel view synthesis with unprecedented visual quality.

• However, to render photorealistic images, NeRFs require hundreds of deep multilayer perceptron (MLP) evaluations - for each pixel.
• This is prohibitively expensive and makes real-time rendering infeasible, even on powerful modern GPUs.
• In this paper, we propose a novel approach to distill and bake NeRFs into highly efficient mesh-based neural representations that are fully compatible with the massively parallel graphics rendering pipeline.