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Found 4 papers, 3 papers with code
Diverse and Admissible Trajectory Prediction through Multimodal Context Understanding
Multi-agent trajectory forecasting in autonomous driving requires an agent to accurately anticipate the behaviors of the surrounding vehicles and pedestrians, for safe and reliable decision-making.
Trajformer: Trajectory Prediction with Local Self-Attentive Contexts for Autonomous Driving
Effective feature-extraction is critical to models' contextual understanding, particularly for applications to robotics and autonomous driving, such as multimodal trajectory prediction.
CurbScan: Curb Detection and Tracking Using Multi-Sensor Fusion
In this paper, we propose an approach to detect and track curbs by fusing together data from multiple sensors: sparse LiDAR data, a mono camera and low-cost ultrasonic sensors.
Diverse and Admissible Trajectory Forecasting through Multimodal Context Understanding
Multi-agent trajectory forecasting in autonomous driving requires an agent to accurately anticipate the behaviors of the surrounding vehicles and pedestrians, for safe and reliable decision-making.
