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Towards Consistent and Explainable Motion Prediction using Heterogeneous Graph Attention
This paper introduces a new refinement module designed to project the predicted trajectories back onto the actual map, rectifying these discrepancies and leading towards more consistent predictions.
Self-Supervised Representation Learning from Temporal Ordering of Automated Driving Sequences
Self-supervised feature learning enables perception systems to benefit from the vast raw data recorded by vehicle fleets worldwide.
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