Neural Radiance Fields (NeRF) have significantly impacted the novel view synthesis task.
While it can render realistic images from unseen viewpoints, the boundaries of the object or …

Abstract Neural Radiance Fields (NeRF) can achieve state-of-the-art new view results when
given a sufficient number of training views. However, NeRF's rendering is based on …

Neural radiance fields (NeRFs) have been proposed as methods of novel view synthesis
and have been used to address various problems because of its versatility. NeRF can …

Recent research explosion on Neural Radiance Field (NeRF) shows the encouraging
potential to represent complex scenes with neural networks. One major drawback of NeRF is …

Traditional neural radiance fields for rendering novel views require intensive input images
and pre-scene optimization, which limits their practical applications. We propose a …

Neural radiance fields (NeRF) have brought tremendous progress to novel view synthesis.
Though NeRF enables the rendering of subtle details in a scene by learning from a dense …

In this paper, we introduce a novel approach to improve the performance of Neural
Radiance Fields (NeRF) from limited input views. NeRF has exhibited impressive …

Novel view synthesis is a classical research problem in computer vision and has been well
studied in various ways. While recently proposed NeRF model achieves photo-realistic …

By modelling complex scenes via a continuous volumetric scene function, neural radiance
fields (NeRF) achieves state-of-the-art results in novel view synthesis. However, since NeRF …

Novel view synthesis using implicit neural functions such as Neural Radiance Field (NeRF)
has achieved significant progress recently. However, it is very computationally expensive to …