Editing Neural Radiance Fields

Abstract

Neural Radiance Fields (NeRFs) have emerged as a pivotal advancement in computer graphics and vision. They provide a framework for rendering highly detailed novel view images from sparse multi- view input data. NeRFs use a continuous function to represent scenes that can be estimated using neural networks. This approach enables the generation of photorealistic images for static scenes. Outside the domain of image synthesis, NeRFs have been widely adopted as a representation of several downstream including but not limited to scene understanding, augemented reality, scene nav- igation, segmentation, and 3D asset generation. In this thesis, we explore upon the segmentation and editing capabilities in radiance fields. We propose a fast style transfer method that leverages multi-view consistent generation of stylized priors to change the appearance vectors in a Tensorial Radiance Field. Our method promises a speed-up of several orders of magnitude in applying style transfer and adheres to the colorscheme from the style image better than previous works. Next, we tackle the task of segmentation in radiance fields. Our method uses a grid-based feature field which allows extremely fast feature querying and searching. Combined with our stroke-based seg- mentation, this allws the user to interactively segment objects in a captured radiance field. We improve the state-of-the-art in terms of segmentation quality by a huge margin and in terms of segmentation time by orders of magnitude. Our method enables basic editing capabilities like translation, appearance editing, removal, and composition for which we show preliminary results. We further explore the problem of composition of radiance fields. Composition of two radiance fields using ray marching requires twice the amount of memory and compute. We use distillation to fuse multiple radiance fields into one to circumvent this problem. Our distillation process is roughly thrice as fast as re-training and produces a unified representation for radiance fields.