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Found 4 papers, 2 papers with code
BiFF: Bi-level Future Fusion with Polyline-based Coordinate for Interactive Trajectory Prediction
Predicting future trajectories of surrounding agents is essential for safety-critical autonomous driving.
The Devil is in the Wrongly-classified Samples: Towards Unified Open-set Recognition
Recently, Unified Open-set Recognition (UOSR) has been proposed to reject not only unknown samples but also known but wrongly classified samples, which tends to be more practical in real-world applications.
Open-world Semantic Segmentation for LIDAR Point Clouds
Current methods for LIDAR semantic segmentation are not robust enough for real-world applications, e. g., autonomous driving, since it is closed-set and static.
Learning to Predict Vehicle Trajectories with Model-based Planning
Predicting the future trajectories of on-road vehicles is critical for autonomous driving.
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