6 papers
SeqLoc: Beyond the Single Frame for Cross-View Geo-Localization in Feature-Sparse Scenes
Junwei Zheng, Yun Huang, Ruize Dai +8
Cross-View Geo-Localization (CVGL) with OpenStreetMap (OSM) performs well in structure-rich urban environments but collapses in feature-sparse scenes such as rural roads. To study…
OrthoTrack: Continuous 6-DoF UAV Trajectory Estimation Anchored in Public Orthophotos
Oussema Dhaouadi, Zuria Bauer, Johannes Michael Meier +3
Continuous 6-DoF pose estimation is essential for autonomous UAV operations. Yet, existing visual odometry and SLAM methods accumulate drift and yield only relative, up-to-scale tr…
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…
EnerGS: Energy-Based Gaussian Splatting with Partial Geometric Priors
Rui Song, Tianhui Cai, Markus Gross +5
3D Gaussian Splatting (3DGS) has been widely adopted for scene reconstruction, where training inherently constitutes a highly coupled and non-convex optimization problem. Recent wo…
From Propagation to Prediction: Point-level Uncertainty Evaluation of MLS Point Clouds under Limited Ground Truth
Ziyang Xu, Olaf Wysocki, Christoph Holst
Evaluating uncertainty is critical for reliable use of Mobile Laser Scanning (MLS) point clouds in many high-precision applications such as Scan-to-BIM, deformation analysis, and 3…
Point-level Uncertainty Evaluation of Mobile Laser Scanning Point Clouds
Ziyang Xu, Olaf Wysocki, Christoph Holst
Reliable quantification of uncertainty in Mobile Laser Scanning (MLS) point clouds is essential for ensuring the accuracy and credibility of downstream applications such as 3D mapp…