3 papers
cs.CV2024
UnO: Unsupervised Occupancy Fields for Perception and Forecasting
Ben Agro, Quinlan Sykora, Sergio Casas +2
Perceiving the world and forecasting its future state is a critical task for self-driving. Supervised approaches leverage annotated object labels to learn a model of the world -- t…
cs.RO2024
QuAD: Query-based Interpretable Neural Motion Planning for Autonomous Driving
Sourav Biswas, Sergio Casas, Quinlan Sykora +3
A self-driving vehicle must understand its environment to determine the appropriate action. Traditional autonomy systems rely on object detection to find the agents in the scene. H…
cs.CV2023
Implicit Occupancy Flow Fields for Perception and Prediction in Self-Driving
Ben Agro, Quinlan Sykora, Sergio Casas +1
A self-driving vehicle (SDV) must be able to perceive its surroundings and predict the future behavior of other traffic participants. Existing works either perform object detection…