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…
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…
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…
Advancements in Road Lane Mapping: Comparative Fine-Tuning Analysis of Deep Learning-based Semantic Segmentation Methods Using Aerial Imagery
Willow Liu, Shuxin Qiao, Kyle Gao +4
This research addresses the need for high-definition (HD) maps for autonomous vehicles (AVs), focusing on road lane information derived from aerial imagery. While Earth observation…
Enhanced 3D Urban Scene Reconstruction and Point Cloud Densification using Gaussian Splatting and Google Earth Imagery
Kyle Gao, Dening Lu, Hongjie He +2
3D urban scene reconstruction and modelling is a crucial research area in remote sensing with numerous applications in academia, commerce, industry, and administration. Recent adva…