Abstract Neural Radiance Fields (NeRFs) have demonstrated amazing ability to synthesize
images of 3D scenes from novel views. However, they rely upon specialized volumetric …

Emerging neural radiance fields (NeRF) are a promising scene representation for computer
graphics, enabling high-quality 3D reconstruction and novel view synthesis from image …

Abstract Neural Radiance Fields (NeRF) have constituted a remarkable breakthrough in
image-based 3D reconstruction. However, their implicit volumetric representations differ …

We present Neural Feature Fusion Fields (N3F),\a method that improves dense 2D image
feature extractors when the latter are applied to the analysis of multiple images …

Abstract Neural Radiance Field (NeRF) has emerged as a compelling method to represent
3D objects and scenes for photo-realistic rendering. However, its implicit representation …

This paper presents one of the first learning-based NeRF 3D instance segmentation
pipelines, dubbed as Instance Neural Radiance Field, or Instance-NeRF. Taking a NeRF …

Neural Radiance Fields (NeRFs) have revolutionized novel view synthesis for captured
scenes, with recent methods allowing interactive free-viewpoint navigation and fast training …

3D Gaussian Splatting (3D-GS) has emerged as a significant advancement in the field of
Computer Graphics, offering explicit scene representation and novel view synthesis without …

Capturing and re-animating the 3D structure of articulated objects present significant
barriers. On one hand methods requiring extensively calibrated multi-view setups are …

Abstract The popularity of Neural Radiance Fields (NeRFs) for view synthesis has led to a
desire for NeRF editing tools. Here, we focus on inpainting regions in a view-consistent and …