Perceive, Attend, and Drive: Learning Spatial Attention for Safe Self-Driving
Uber ATG（优步先进技术集团）；University of Waterloo（滑铁卢大学）；University of Toronto（多伦多大学）
英文摘要：
In this paper, we propose an end-to-end self-driving network featuring a sparse attention module that learns to automatically attend to important regions of the input. The attention module specifically targets motion planning, whereas prior literature only applied attention in perception tasks. Learning an attention mask directly targeted for motion planning significantly improves the planner safety by performing more focused computation. Furthermore, visualizing the attention improves interpretability of end-to-end self-driving.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
