Generative Radiance Field

Generative Radiance Fields (GRFs) are a class of 3D-aware generative models that synthesize photorealistic images and 3D scenes from 2D image collections, often without requiring precise camera pose information. Current research focuses on improving GRF capabilities through novel architectures like tri-plane networks and vertex-based representations, addressing challenges such as handling low-quality input, achieving disentanglement of shape and appearance, and enabling fine-grained control over generated content. This field is significant for its potential to revolutionize 3D data creation, enabling efficient data augmentation for computer vision tasks, high-fidelity 3D modeling from limited data, and the creation of realistic virtual environments.