8 papers
SemCityLoc: Aerial 6DoF Localization Using Semantic 3D City Models
Jingfeng Mao, Xuyang Chen, Qilin Zhang +6
Aerial 6DoF localization typically relies on precise GNSS signals or radiometrically rich 3D reconstructions, limiting scalability and on-board deployment. We propose SemCityLoc, a…
GS4City: Hierarchical Semantic Gaussian Splatting via City-Model Priors
Qilin Zhang, Jinyu Zhu, Olaf Wysocki +2
Recent semantic 3D Gaussian Splatting (3DGS) methods primarily rely on 2D foundation models, often yielding ambiguous boundaries and limited support for structured urban semantics.…
VLM-Loc: Localization in Point Cloud Maps via Vision-Language Models
Shuhao Kang, Youqi Liao, Peijie Wang +5
Text-to-point-cloud (T2P) localization aims to infer precise spatial positions within 3D point cloud maps from natural language descriptions, reflecting how humans perceive and com…
TrueCity: Real and Simulated Urban Data for Cross-Domain 3D Scene Understanding
Duc Nguyen, Yan-Ling Lai, Qilin Zhang +4
3D semantic scene understanding remains a long-standing challenge in the 3D computer vision community. One of the key issues pertains to limited real-world annotated data to facili…
GS4Buildings: Prior-Guided Gaussian Splatting for 3D Building Reconstruction
Qilin Zhang, Olaf Wysocki, Boris Jutzi
Recent advances in Gaussian Splatting (GS) have demonstrated its effectiveness in photo-realistic rendering and 3D reconstruction. Among these, 2D Gaussian Splatting (2DGS) is part…
To Glue or Not to Glue? Classical vs Learned Image Matching for Mobile Mapping Cameras to Textured Semantic 3D Building Models
Simone Gaisbauer, Prabin Gyawali, Qilin Zhang +2
Feature matching is a necessary step for many computer vision and photogrammetry applications such as image registration, structure-from-motion, and visual localization. Classical…