47 citations · 47 across the 5 of their papers we have counts for
5 papers
VR-NeRF: High-Fidelity Virtualized Walkable Spaces
Linning Xu, Vasu Agrawal, William Laney +10
We present an end-to-end system for the high-fidelity capture, model reconstruction, and real-time rendering of walkable spaces in virtual reality using neural radiance fields. To…
MatrixCity: A Large-scale City Dataset for City-scale Neural Rendering and Beyond
Yixuan Li, Lihan Jiang, Linning Xu +4
Neural radiance fields (NeRF) and its subsequent variants have led to remarkable progress in neural rendering. While most of recent neural rendering works focus on objects and smal…
Grid-guided Neural Radiance Fields for Large Urban Scenes
Linning Xu, Yuanbo Xiangli, Sida Peng +5
Purely MLP-based neural radiance fields (NeRF-based methods) often suffer from underfitting with blurred renderings on large-scale scenes due to limited model capacity. Recent appr…
AssetField: Assets Mining and Reconfiguration in Ground Feature Plane Representation
Yuanbo Xiangli, Linning Xu, Xingang Pan +3
Both indoor and outdoor environments are inherently structured and repetitive. Traditional modeling pipelines keep an asset library storing unique object templates, which is both v…
OmniCity: Omnipotent City Understanding with Multi-level and Multi-view Images
Weijia Li, Yawen Lai, Linning Xu +5
This paper presents OmniCity, a new dataset for omnipotent city understanding from multi-level and multi-view images. More precisely, the OmniCity contains multi-view satellite ima…