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cs.LG2024★ 5 cited
CASPFormer: Trajectory Prediction from BEV Images with Deformable Attention
Harsh Yadav, Maximilian Schaefer, Kun Zhao +1
Motion prediction is an important aspect for Autonomous Driving (AD) and Advance Driver Assistance Systems (ADAS). Current state-of-the-art motion prediction methods rely on High D…
cs.LG2024★ 4 cited
Task Weighting through Gradient Projection for Multitask Learning
Christian Bohn, Ido Freeman, Hasan Tercan +1
In multitask learning, conflicts between task gradients are a frequent issue degrading a model's training performance. This is commonly addressed by using the Gradient Projection a…
cs.LG2023★ 4 cited
Quantification of Uncertainties in Deep Learning-based Environment Perception
Marco Braun, Moritz Luszek, Jan Siegemund +2
In this work, we introduce a novel Deep Learning-based method to perceive the environment of a vehicle based on radar scans while accounting for uncertainties in its predictions. T…