7 citations · 9 across the 5 of their papers we have counts for
6 papers
InCaRPose: In-Cabin Relative Camera Pose Estimation Model and Dataset
Felix Stillger, Lukas Hahn, Frederik Hasecke +1
Camera extrinsic calibration is a fundamental task in computer vision. However, precise relative pose estimation in constrained, highly distorted environments, such as in-cabin aut…
Principal Component Clustering for Semantic Segmentation in Synthetic Data Generation
Felix Stillger, Frederik Hasecke, Tobias Meisen
This technical report outlines our method for generating a synthetic dataset for semantic segmentation using a latent diffusion model. Our approach eliminates the need for addition…
Fake it, Mix it, Segment it: Bridging the Domain Gap Between Lidar Sensors
Frederik Hasecke, Pascal Colling, Anton Kummert
Segmentation of lidar data is a task that provides rich, point-wise information about the environment of robots or autonomous vehicles. Currently best performing neural networks fo…
What Can be Seen is What You Get: Structure Aware Point Cloud Augmentation
Frederik Hasecke, Martin Alsfasser, Anton Kummert
To train a well performing neural network for semantic segmentation, it is crucial to have a large dataset with available ground truth for the network to generalize on unseen data.…
Fast Object Classification and Meaningful Data Representation of Segmented Lidar Instances
Lukas Hahn, Frederik Hasecke, Anton Kummert
Object detection algorithms for Lidar data have seen numerous publications in recent years, reporting good results on dataset benchmarks oriented towards automotive requirements. N…
FLIC: Fast Lidar Image Clustering
Frederik Hasecke, Lukas Hahn, Anton Kummert
Lidar sensors are widely used in various applications, ranging from scientific fields over industrial use to integration in consumer products. With an ever growing number of differ…