CV4DT Research Group
CV4DT Research Group
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Olaf Wysocki
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OPAL: Visibility-aware Lidar-to-OpenStreetMap Place Recognition via Adaptive Radial Fusion
Texture2LoD3: Enabling LoD3 Building Reconstruction With Panoramic Images
RADLER: Radar Object Detection Leveraging Semantic 3D City Models and Self-Supervised Radar-Image Learning
Zaha: Introducing the level of facade generalization and the large-scale point cloud facade semantic segmentation benchmark dataset
FacaDiffy: Inpainting Unseen Facade Parts Using Diffusion Models
CDGS: Confidence-Aware Depth Regularization for 3D Gaussian Splatting
Mind the domain gap: Measuring the domain gap between real-world and synthetic point clouds for automated driving development
To Glue or Not to Glue? Classical vs Learned Image Matching for Mobile Mapping Cameras to Textured Semantic 3D Building Models
TUM2TWIN: Introducing the Large-Scale Multimodal Urban Digital Twin Benchmark Dataset
Analyzing the impact of semantic LoD3 building models on image-based vehicle localization
Enriching Thermal Point Clouds of Buildings using Semantic 3D building Models
Reviewing Open Data Semantic 3D City Models to Develop Novel 3D Reconstruction Methods
Classifying point clouds at the facade-level using geometric features and deep learning networks
MLS2LoD3: Refining low LoDs building models with MLS point clouds to reconstruct semantic LoD3 building models
Reconstructing facade details using MLS point clouds and Bag-of-Words approach
Scan2LoD3: Reconstructing semantic 3D building models at LoD3 using ray casting and Bayesian networks
Transferring facade labels between point clouds with semantic octrees while considering change detection
Combining visibility analysis and deep learning for refinement of semantic 3D building models by conflict classification
Refinement of semantic 3D building models by reconstructing underpasses from MLS point clouds
TUM-FAÇADE: Reviewing and enriching point cloud benchmarks for façade segmentation
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