Publications (19)
STPLS3D: A Large-Scale Synthetic and Real Aerial Photogrammetry 3D Point Cloud Dataset
Meida Chen, Qingyong Hu, Zifan Yu +6
Although various 3D datasets with different functions and scales have been proposed recently, it remains challenging for individuals to complete the whole pipeline of large-scale d…
Descrip3D: Enhancing Large Language Model-based 3D Scene Understanding with Object-Level Text Descriptions
Jintang Xue, Ganning Zhao, Jie-En Yao +5
Understanding 3D scenes goes beyond simply recognizing objects; it requires reasoning about the spatial and semantic relationships between them. Current 3D scene-language models of…
Deformable Beta Splatting
Rong Liu, Dylan Sun, Meida Chen +2
3D Gaussian Splatting (3DGS) has advanced radiance field reconstruction by enabling real-time rendering. However, its reliance on Gaussian kernels for geometry and low-order Spheri…
Universal Beta Splatting
Rong Liu, Zhongpai Gao, Benjamin Planche +8
We introduce Universal Beta Splatting (UBS), a unified framework that generalizes 3D Gaussian Splatting to N-dimensional anisotropic Beta kernels for explicit radiance field render…
Fully Automated Photogrammetric Data Segmentation and Object Information Extraction Approach for Creating Simulation Terrain
Meida Chen, Andrew Feng, Kyle McCullough +4
Our previous works have demonstrated that visually realistic 3D meshes can be automatically reconstructed with low-cost, off-the-shelf unmanned aerial systems (UAS) equipped with c…
TransUPR: A Transformer-based Uncertain Point Refiner for LiDAR Point Cloud Semantic Segmentation
Zifan Yu, Meida Chen, Zhikang Zhang +4
Common image-based LiDAR point cloud semantic segmentation (LiDAR PCSS) approaches have bottlenecks resulting from the boundary-blurring problem of convolution neural networks (CNN…