Abstract
Neural Radiance Fields (NeRF) have emerged as a leading technology for 3D digitization, especially for their high accuracy and intricate detailing. Despite their advancements, early NeRF models struggle to handle reflections on specular surfaces effectively. To address this, alternative approaches such as Ref-NeRF and NRFF were proposed to improve fidelity in representing this physical phenomenon. This study compares these two models, providing an analysis of their effectiveness and limitations in dealing with complex specularities. We demonstrate that both methods struggle with inter-reflections and tend to model anisotropic specularities by altering the predicted surface normals.
This is an MLBriefs article, the source code has not been reviewed!
The original source codes are available here: Ref-NeRF
and NRFF (last checked 2025/02/06).
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- full text preprint manuscript: PDF (10.5MB)
- source code: ZIP