Overview
StyleNeRF is a neural radiance field (NeRF) based generative model designed for synthesizing high-resolution, photo-realistic images with multi-view consistency. It tackles challenges in generating detailed images without 3D-inconsistent artifacts. StyleNeRF integrates a style-based generator, similar to StyleGAN, with NeRF to improve rendering efficiency and 3D consistency. It uses volume rendering to produce a low-resolution feature map, then employs 2D upsampling to generate high-resolution images. Key innovations include a custom upsampler and regularization loss to mitigate inconsistencies introduced by 2D upsampling. This allows StyleNeRF to achieve interactive rendering rates while maintaining high-quality 3D consistency and enabling control over camera poses and style attributes. It supports tasks like zoom-in/out, style mixing, inversion, and semantic editing, trained on unstructured 2D images.