2 citations · 3 across the 3 of their papers we have counts for
4 papers
FutureLift: Lifting Trajectory Proposals into Bidirectional Future Graphs for Motion Forecasting
Daniel Grimm, J. Marius Zöllner
Accurate motion prediction is critical for safe autonomous driving, yet even strong forecasters leave residual errors in their multimodal proposals. Existing refiners compress comp…
Goal-based Trajectory Prediction for improved Cross-Dataset Generalization
Daniel Grimm, Ahmed Abouelazm, J. Marius Zöllner
To achieve full autonomous driving, a good understanding of the surrounding environment is necessary. Especially predicting the future states of other traffic participants imposes…
One Stack to Rule them All: To Drive Automated Vehicles, and Reach for the 4th level
Sven Ochs, Jens Doll, Daniel Grimm +15
Most automated driving functions are designed for a specific task or vehicle. Most often, the underlying architecture is fixed to specific algorithms to increase performance. There…
Heterogeneous Graph-based Trajectory Prediction using Local Map Context and Social Interactions
Daniel Grimm, Maximilian Zipfl, Felix Hertlein +7
Precisely predicting the future trajectories of surrounding traffic participants is a crucial but challenging problem in autonomous driving, due to complex interactions between tra…