BlenderNeRF is designed for the creation of synthetic NeRF datasets within Blender, providing users with the capability to obtain renders and camera parameters effortlessly.
One-Click Operation: Enables the generation of synthetic NeRF datasets, producing both renders and camera parameters seamlessly.
Neural Radiance Fields Integration: Represents 3D scenes as view-dependent volumetric objects using 2D images and their corresponding camera information, reconstructing the 3D scene from training images through a neural network.
Efficient Rendering Process: Addresses the challenges of traditional rendering by leveraging NeRFs, which provide a more streamlined approach to extracting camera information.
Diverse Data Creation Methods: Incorporates three methods for creating NeRF training and testing data: Subset of Frames, Train and Test Cameras, and Camera on Sphere.