Autonomous Driving: Perception, Prediction and Planning

CVPR 2021 Workshop

Autonomous driving research can improve society by reducing road accidents, giving independence to those unable to drive, and inspiring younger generations towards computer vision with tangible examples of the technology clearly visible on local streets in many cities around the world. The goal of this workshop is to draw attention to the problems connecting the whole perception, prediction and planning stack. To that end, we will host a planning competition powered by a real-world self-driving dataset, which, to the best of our knowledge, has never been done in autonomous driving before. We hope that the competition will encourage mutually informed progress on all three components, including the fundamental challenges of autonomous driving such as few shot generalization, domain adaptation, self-supervised or semi-supervised learning, and planning friendly perception models. Furthermore, the workshop intends to foster interdisciplinary communication of researchers working on autonomous driving from both academia and industry.

We will be accepting paper contributions to the workshop, details coming soon.