211 citations · 386 across the 5 of their papers we have counts for
8 papers
TNT: Target-driveN Trajectory Prediction
Hang Zhao, Jiyang Gao, Tian Lan +9
Predicting the future behavior of moving agents is essential for real world applications. It is challenging as the intent of the agent and the corresponding behavior is unknown and…
SoDA: Multi-Object Tracking with Soft Data Association
Wei-Chih Hung, Henrik Kretzschmar, Tsung-Yi Lin +4
Robust multi-object tracking (MOT) is a prerequisite fora safe deployment of self-driving cars. Tracking objects, however, remains a highly challenging problem, especially in clutt…
SurfelGAN: Synthesizing Realistic Sensor Data for Autonomous Driving
Zhenpei Yang, Yuning Chai, Dragomir Anguelov +5
Autonomous driving system development is critically dependent on the ability to replay complex and diverse traffic scenarios in simulation. In such scenarios, the ability to accura…
Scalability in Perception for Autonomous Driving: Waymo Open Dataset
Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla +22
The research community has increasing interest in autonomous driving research, despite the resource intensity of obtaining representative real world data. Existing self-driving dat…
MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction
Yuning Chai, Benjamin Sapp, Mayank Bansal +1
Predicting human behavior is a difficult and crucial task required for motion planning. It is challenging in large part due to the highly uncertain and multi-modal set of possible…
StarNet: Targeted Computation for Object Detection in Point Clouds
Jiquan Ngiam, Benjamin Caine, Wei Han +10
Detecting objects from LiDAR point clouds is an important component of self-driving car technology as LiDAR provides high resolution spatial information. Previous work on point-clo…