Neural Radiance Field (NeRF) and its variants have exhibited great success on
representing 3D scenes and synthesizing photo-realistic novel views. However, they are …

Neural volumetric representations such as Neural Radiance Fields (NeRF) have emerged
as a compelling technique for learning to represent 3D scenes from images with the goal of …

Though neural radiance fields (" NeRF") have demonstrated impressive view synthesis
results on objects and small bounded regions of space, they struggle on" unbounded" …

Virtual Reality (VR) is becoming ubiquitous with the rise of consumer displays and
commercial VR platforms. Such displays require low latency and high quality rendering of …

Neural radiance fields (NeRFs) have shown impressive results for novel view synthesis.
However, they depend on the repetitive use of a single-input single-output multilayer …

Abstract Neural Radiance Fields (NeRF) has achieved unprecedented view synthesis
quality using coordinate-based neural scene representations. However, NeRF's view …

Neural Radiance Fields (NeRF) show impressive performance for the photo-realistic free-
view rendering of scenes. However, NeRFs require dense sampling of images in the given …

We introduce a method to render Neural Radiance Fields (NeRFs) in real time using
PlenOctrees, an octree-based 3D representation which supports view-dependent effects …

Abstract Neural Radiance Fields (NeRFs) are a very recent and very popular approach for
the problems of novel view synthesis and 3D reconstruction. A popular scene representation …

While Neural Radiance Fields (NeRFs) had achieved unprecedented novel view synthesis
results, they have been struggling in dealing with large-scale cluttered scenes with sparse …