Free Information Center
Neural radiance field (NeRF) is a deep learning technique for synthesizing novel views of complex 3D scenes by representing the scene as a continuous volumetric function. It uses neural networks to model light emission and density, enabling photo-realistic rendering from sparse input images.
Voxel-based neural rendering is a computer graphics technique that combines volumetric voxel representations with neural networks to generate realistic images. It enhances rendering by leveraging 3D voxel grids and deep learning to synthesize novel views or scenes with improved detail and efficiency.
Instant neural graphics primitive (Instant NGP) is a machine learning framework designed for efficient and rapid neural representation of 3D scenes. It utilizes a multi-resolution hash encoding to accelerate training and rendering of neural graphics primitives, enabling real-time applications in graphics and vision.
MixNeRF is a computational approach that integrates neural radiance fields with mixed reality applications to enable realistic rendering and interaction of 3D scenes. It leverages neural networks to model complex light transport and scene geometry, facilitating immersive augmented and virtual reality experiences.