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Fast Dynamic Radiance Fields with Time-Aware Neural Voxels
A fast neural rendering framework for dynamic scenes, representing scenes with time-aware neural voxels to accelerate the training speed and maintain high rendering quality. -
Unsupervised Learning of Style-Aware Facial Animation from Real Acting Perfor...
A new approach for creating an animatable and photo-realistic 3D head model from multi-view video footage of a real actor, together with a neural animation model based on... -
Neural Reflectance Fields for Appearance Acquisition
A dataset of images captured with a cellphone camera and its built-in flash, used to train a neural reflectance field representation that models scene geometry and reflectance. -
MomentsNeRF: Leveraging Orthogonal Moments for Few-Shot Neural Rendering
A novel framework for one- and few-shot neural rendering that predicts a neural representation of a 3D scene using Orthogonal Moments. -
NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis
NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis -
Mip-NeRF360
The Mip-NeRF360 dataset contains scenes taken from a 360 degree view, with emphasis on minimizing photometric variations.
