Existing neural radiance fields (NeRF)-based novel view synthesis methods for large-scale
outdoor scenes are mainly built on a single altitude. Moreover, they often require a priori …

Novel view synthesis (NVS) is a challenge in computer vision and graphics, focusing on
generating realistic images of a scene from unobserved camera poses, given a limited set of …

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 …

Given a set of images of a scene, the re-rendering of this scene from novel views and
lighting conditions is an important and challenging problem in Computer Vision and …

We present CDNeRF, a simple yet powerful learning framework that creates novel view
synthesis by reconstructing neural radiance fields from a single view RGB image. Novel …

The recently proposed neural radiance fields (NeRF) use a continuous function formulated
as a multi-layer perceptron (MLP) to model the appearance and geometry of a 3D scene …

We present a new neural representation, called Neural Ray (NeuRay), for the novel view
synthesis task. Recent works construct radiance fields from image features of input views to …

Novel view synthesis (NVS) is a challenging task requiring systems to generate
photorealistic images of scenes from new viewpoints, where both quality and speed are …

We represent the ResNeRF, a novel geometry-guided two-stage framework for indoor scene
novel view synthesis. Be aware of that a good geometry would greatly boost the …

Multi-task visual learning is a critical aspect of computer vision. Current research, however,
predominantly concentrates on the multi-task dense prediction setting, which overlooks the …