5 citations · 11 across the 8 of their papers we have counts for
8 papers · 1 filter
XD-MAP: Cross-Modal Domain Adaptation via Semantic Parametric Maps for Scalable Training Data Generation
Frank Bieder, Hendrik Königshof, Haohao Hu +4
Until open-world foundation models match the performance of specialized approaches, deep learning systems remain dependent on task- and sensor-specific data availability. To bridge…
Improving Lidar-Based Semantic Segmentation of Top-View Grid Maps by Learning Features in Complementary Representations
Frank Bieder, Maximilian Link, Simon Romanski +2
In this paper we introduce a novel way to predict semantic information from sparse, single-shot LiDAR measurements in the context of autonomous driving. In particular, we fuse lear…
Large-Scale 3D Semantic Reconstruction for Automated Driving Vehicles with Adaptive Truncated Signed Distance Function
Haohao Hu, Hexing Yang, Jian Wu +4
The Large-scale 3D reconstruction, texturing and semantic mapping are nowadays widely used for automated driving vehicles, virtual reality and automatic data generation. However, m…
TEScalib: Targetless Extrinsic Self-Calibration of LiDAR and Stereo Camera for Automated Driving Vehicles with Uncertainty Analysis
Haohao Hu, Fengze Han, Frank Bieder +2
In this paper, we present TEScalib, a novel extrinsic self-calibration approach of LiDAR and stereo camera using the geometric and photometric information of surrounding environmen…
Learned Enrichment of Top-View Grid Maps Improves Object Detection
Sascha Wirges, Ye Yang, Sven Richter +2
We propose an object detector for top-view grid maps which is additionally trained to generate an enriched version of its input. Our goal in the joint model is to improve generaliz…
Localization in Aerial Imagery with Grid Maps using LocGAN
Haohao Hu, Junyi Zhu, Sascha Wirges +1
In this work, we present LocGAN, our localization approach based on a geo-referenced aerial imagery and LiDAR grid maps. Currently, most self-localization approaches relate the cur…
Accurate Global Trajectory Alignment using Poles and Road Markings
Haohao Hu, Marc Sons, Christoph Stiller
Currently, digital maps are indispensable for automated driving. However, due to the low precision and reliability of GNSS particularly in urban areas, fusing trajectories of indep…
An Approach to Vehicle Trajectory Prediction Using Automatically Generated Traffic Maps
Jannik Quehl, Haohao Hu, Sascha Wirges +1
Trajectory and intention prediction of traffic participants is an important task in automated driving and crucial for safe interaction with the environment. In this paper, we prese…