Neural Reflectance Fields for Appearance Acquisition
2020
Abstract
AI
AI
Neural Reflectance Fields, a novel deep scene representation, are introduced for modeling complex scene geometry and reflectance through a fully-connected neural network that encodes volume density, normals, and reflectance properties at any 3D point in a scene. By integrating this representation with a differentiable ray marching framework, the method facilitates high-quality view synthesis and relighting from images captured with a simple camera-light setup. The proposed approach demonstrates capabilities in rendering photo-realistic images under novel viewpoints and non-collocated lighting, effectively reproducing challenging visual effects such as specularities and shadows, while also enabling compatibility with traditional graphical rendering engines.
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