StopNet: Scalable Trajectory and Occupancy Prediction for Urban Autonomous Driving
Jinkyu Kim,Reza Mahjourian,Scott Ettinger,Mayank Bansal,Brandyn White,Ben Sapp,Dragomir Anguelov,Jinkyu Kim,Reza Mahjourian,Scott Ettinger,Mayank Bansal,Brandyn White,Ben Sapp,Dragomir Anguelov
We introduce a motion forecasting (behavior prediction) method that meets the latency requirements for autonomous driving in dense urban environments without sacrificing accuracy. A whole-scene sparse input representation allows StopNet to scale to predicting trajectories for hundreds of road agents with reliable latency. In addition to predicting trajectories, our scene encoder lends itself to pr...
