1 code implementation • 26 Mar 2024 • Kerui Ren, Lihan Jiang, Tao Lu, Mulin Yu, Linning Xu, Zhangkai Ni, Bo Dai
The recent 3D Gaussian splatting (3D-GS) has shown remarkable rendering fidelity and efficiency compared to NeRF-based neural scene representations.
no code implementations • 25 Mar 2024 • Mulin Yu, Tao Lu, Linning Xu, Lihan Jiang, Yuanbo Xiangli, Bo Dai
We show on diverse scenes that our design unlocks the potential for more accurate and detailed surface reconstructions, and at the meantime benefits 3DGS rendering with structures that are more aligned with the underlying geometry.
1 code implementation • 30 Nov 2023 • Tao Lu, Mulin Yu, Linning Xu, Yuanbo Xiangli, LiMin Wang, Dahua Lin, Bo Dai
Neural rendering methods have significantly advanced photo-realistic 3D scene rendering in various academic and industrial applications.
no code implementations • 11 Jul 2023 • Johann Lussange, Mulin Yu, Yuliya Tarabalka, Florent Lafarge
We here propose a method for urban 3D reconstruction named KIBS(\textit{Keypoints Inference By Segmentation}), which comprises two novel features: i) a full deep learning approach for the 3D detection of the roof sections, and ii) only one single (non-orthogonal) satellite raster image as model input.
no code implementations • CVPR 2022 • Mulin Yu, Florent Lafarge
We present an algorithm for detecting planar primitives from unorganized 3D point clouds.