6 papers · 1 filter
Gaussian Building Mesh (GBM): Extract a Building's 3D Mesh with Google Earth and Gaussian Splatting
Kyle Gao, Liangzhi Li, Hongjie He +3
Recently released open-source pre-trained foundational image segmentation and object detection models (SAM2+GroundingDINO) allow for geometrically consistent segmentation of object…
UDHF2-Net: Uncertainty-diffusion-model-based High-Frequency TransFormer Network for Remotely Sensed Imagery Interpretation
Pengfei Zhang, Chang Li, Yongjun Zhang +3
Remotely sensed imagery interpretation (RSII) faces the three major problems: (1) objective representation of spatial distribution patterns; (2) edge uncertainty problem caused by…
Digital Twin Buildings: 3D Modeling, GIS Integration, and Visual Descriptions Using Gaussian Splatting, ChatGPT/Deepseek, and Google Maps Platform
Kyle Gao, Dening Lu, Liangzhi Li +4
Urban digital twins are virtual replicas of cities that use multi-source data and data analytics to optimize urban planning, infrastructure management, and decision-making. Towards…
L4DR: LiDAR-4DRadar Fusion for Weather-Robust 3D Object Detection
Xun Huang, Ziyu Xu, Hai Wu +7
LiDAR-based vision systems are integral for 3D object detection, which is crucial for autonomous navigation. However, they suffer from performance degradation in adverse weather co…
3D Learnable Supertoken Transformer for LiDAR Point Cloud Scene Segmentation
Dening Lu, Jun Zhou, Kyle Gao +2
3D Transformers have achieved great success in point cloud understanding and representation. However, there is still considerable scope for further development in effective and eff…
Efficient Point Transformer with Dynamic Token Aggregating for LiDAR Point Cloud Processing
Dening Lu, Jun Zhou, Kyle +3
Recently, LiDAR point cloud processing and analysis have made great progress due to the development of 3D Transformers. However, existing 3D Transformer methods usually are computa…