About

The 2nd Autonomous Vehicle Vision (AVVision) Workshop aims to bring together industry professionals and academics to brainstorm and exchange ideas on the advancement of computer vision techniques for autonomous driving. In this one-day workshop, we will have seven keynote talks and regular paper presentations (oral and poster) to discuss the state of the art as well as existing challenges in autonomous driving.

Speakers

Cordelia Schmid

INRIA

Raquel Urtasun

University of Toronto

Andreas Geiger

University of Tübingen

Fisher Yu

ETH Zürich

Laura Leal-Taixé

Technical University of Munich

Matthew Johnson-Roberson

University of Michigan

Carl Wellington

Aurora

Organizers

General Chairs

Rui Ranger Fan

UC San Diego

Nemanja Djuric

Aurora

Rowan McAllister

Toyota Research Institute

Ioannis Pitas

Aristotle University of Thessaloniki


Program Committee

David J. Kriegman UC San Diego Walterio Mayol-Cuevas Uni. of Bristol & Amazon Qijun Chen Tongji University Xinchen Yan Uber ATG Xiang Gao Idriverplus Ming Liu HKUST Xiao-Yang Liu Columbia University Junhao Xiao NUDT Kai Han Uni. of Bristol Hesham Eraqi American University in Cairo Wenshuo Wang McGill University

Dequan Wang UC Berkeley Sen Jia Uni. of Waterloo Yi Zhou HKUST Mohammud J. Bocus Uni. Of Bristol Lei Qiao SJTU Peng Yun HKUST Hengli Wang HKUST Sebastian Bujwid KTH Henggang Cui Motional Zhuwen Li Nuro Inc. Weikai Chen Tencent America

Carl Wellington Aurora Huaiyang Huang HKUST Peide Cai HKUST Anthony Tompkins Uni. of Sydney Bohuan Xue HKUST Yehya Abouelnaga TUM Slobodan Vucetic Temple University Zhaoen Su Aurora Fang-Chieh Chou Aurora Nick Rhinehard UC Berkeley Vladan Radosavljevic Spotify

Submission

Call for papers
With a number of breakthroughs in autonomous system technology over the past decade, the race to commercialize self-driving cars has become fiercer than ever. The integration of advanced sensing, computer vision, signal/image processing, and machine/deep learning into autonomous vehicles enables them to perceive the environment intelligently and navigate safely. Autonomous driving is required to ensure safe, reliable, and efficient automated mobility in complex uncontrolled real-world environments. Various applications range from automated transportation and farming to public safety and environment exploration. Visual perception is a critical component of autonomous driving. Enabling technologies include: a) affordable sensors that can acquire useful data under varying environmental conditions, b) reliable simultaneous localization and mapping, c) machine learning that can effectively handle varying real-world conditions and unforeseen events, as well as “machine-learning friendly” signal processing to enable more effective classification and decision making, d) hardware and software co-design for efficient real-time performance, e) resilient and robust platforms that can withstand adversarial attacks and failures, and f) end-to-end system integration of sensing, computer vision, signal/image processing and machine/deep learning. The 2nd AVVision workshop will cover all these topics. Research papers are solicited in, but not limited to, the following topics:

Important Dates
Submission Guidelines
Authors are encouraged to submit high-quality, original (i.e., not been previously published or accepted for publication in substantially similar form in any peer-reviewed venue including journal, conference or workshop) research. The paper template is identical to the ICCV 2021 main conference. Papers are limited to eight pages, including figures and tables, in the ICCV style. Additional pages containing only cited references are allowed. Please refer to the following files for detailed formatting instructions:

Papers that are not properly anonymized, or do not use the template, or have more than eight pages (excluding references) will be rejected without review. The submission site is now open.

Trulli

Contact

Phone: +1 (619) 630-8882

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