CVPR 2019

Workshop on Autonomous Driving

June 18th & 22th | Long Beach, USA

Introduction

The CVPR 2019 Workshop on Autonomous Driving (WAD) is the combined venue for the 10th international workshop on computer vision in vehicle technology (CVVT) and perception challenges with newly collected and fine-annotated large scale datasets. It aims to get together researchers and engineers from academia and industries to discuss computer vision applications in autonomous driving. In this one and half day work, we will have regular paper presentations, invited speakers, panel discussions, and technical benchmark challenges to present the current state of the art, as well as the limitations and future directions for computer vision in autonomous driving, arguably the most promising application of computer vision and AI in general.

News and Updates

Participation

Paper Submission

We solicit paper submissions on novel methods and application scenarios of CV for Autonomous vehicles. We accept papers on a variety of topics, including autonomous navigation and exploration, ADAS, UAV, deep learning, calibration, SLAM, etc.. Papers will be peer reviewed under double-blind policy and the submission deadline is 20th March 2019. Accepted papers will be presented at the poster session, some as orals and one paper will be awarded as the best paper.

Challenge Track

We host a challenge to understand the current status of computer vision algorithms in solving the environmental perception problems for autonomous driving. We have prepared a number of large scale datasets with fine annotation, collected and annotated by Berkeley Deep Driving Consortium, nuTonomy and Didi. Based on the datasets, we have define a set of four realistic problems and encourage new algorithms and pipelines to be invented for autonomous driving. More specifically, they are nuScenes challenge (nuScenes 3D detection challenge), Berkeley Deep Drive challenge (Object tracking and instance segmentation challenges), and Didi (D-Net Detection Transfer Learning Challenge, D-Net Intelligent Annotation Teaser Challenge).

Invited Speakers

Trevor Darrell

UC Berkeley

Kurt Keutzer

UC Berkeley

Kilian Q. Weinberger

Cornell University

Raquel Urtasun

UofT & Uber

Edwin Olson

University of Michigan

Yan Liu

Didi Chuxing & USC

Bo Li

UIUC

Bastian Leibe

RWTH Aachen University

Manmohan Chandraker

UCSD & NEC Labs

Alex Kendall

Cambridge & Wayve

Sponsors

TBD