Sergio Casas
Sergio is a Masters' student at the University of Toronto with a variety of research interests including Deep Learning for Computer Vision, Reinforcement Learning and Imitation Learning. His supervisor is Prof. Raquel Urtasun. At the same time, he is working full-time at Uber ATG Toronto to apply his research to the development of Self-Driving Cars technology, focusing on Perception and Prediction problems. Before coming to UofT, he completed two Bachelor degrees at Universitat Politecnica de Catalunya (UPC), in Computer Science and Industrial Engineering. He is originally from Barcelona, Spain.
Research Papers
IntentNet: Learning to Predict Intention from Raw Sensor Data
S. Casas, W. Luo, R. Urtasun
In order to plan a safe maneuver, self-driving vehicles need to understand the intent of other traffic participants. We define intent as a combination of discrete high level behaviors as well as continuous trajectories describing future motion. In this paper we develop a one-stage detector and forecaster that exploits both 3D point clouds produced by a LiDAR sensor as well as dynamic maps of the environment. [...] [PDF]
Conference on Robot Learning (CORL), 2018
In order to plan a safe maneuver, self-driving vehicles need to understand the intent of other traffic participants. We define intent as a combination of discrete high level behaviors as well as continuous trajectories describing future motion. In this paper we develop a one-stage detector and forecaster that exploits both 3D point clouds produced by a LiDAR sensor as well as dynamic maps of the environment. [...] [PDF]
Conference on Robot Learning (CORL), 2018
