The 1st International Workshop on Human-Autonomous Vehicle Interaction at WACV 2025 will provide a platform for researchers focused on the human aspect of autonomous vehicles. We aim to encourage discussions on innovative solutions and cross-disciplinary research. Specifically, the workshop topics will include (but are not limited to):
- Human perception (face, hand, gaze and etc.) for autonomous vehicles.
- Human-centric autonomous driving.
- In-vehicle human interaction.
- Driver assistance and monitoring systems.
- Pedestrian detection, re-identification, and trajectory prediction.
- Simulation and generation for autonomous vehicles.
- Large Language Models (LLMs) for autonomous vehicles.
- New datasets, benchmarks, and evaluation metrics for autonomous vehicles.
- Analysis of drivers, passengers, pedestrians, and all individuals related to autonomous vehicles.
Call for Contributions
Full Workshop Papers
We invite authors to submit unpublished papers to our workshop, to be presented at a poster session upon acceptance. All submissions will go through a double-blind review process. Accepted papers will be published in the official WACV Workshops proceedings and the Computer Vision Foundation (CVF) Open Access archive.
Submission CMT*: All contributions must be submitted (along with supplementary materials, if any) at this CMT link.
Author guidelines: 8-page, following WACV main conference WACV format
Templates: Overleaf template; .zip template.
Important Dates
Paper Submission Deadline | 22 November, 2024 (23:59 Pacific time). Submission Now! | |
Papers Reviews Deadline | 20 December, 2024 | |
Notification to Authors | 27 December, 2024 | |
Camera-Ready Deadline | 10 January, 2025 | |
Workshop Day | 28 February or 4 March, 2025 |
Invited Keynote Speakers
Surrey University, U.K.
TBC
Abstract
TBC
Dr. Xiatian Zhu is a Senior Lecturer at the Surrey Institute of People-Centred AI and the Centre for Vision, Speech, and Signal Processing (CVSSP) at the University of Surrey in Guildford, UK. He leads the Universal Perception (UP) lab, which focuses on advancing multimodal generative AI for real-world applications and business. Dr. Zhu earned his PhD from Queen Mary University of London and received the 2016 Sullivan Doctoral Thesis Prize from the British Machine Vision Association, an honour recognizing excellence in AI technologies within computer vision. His contributions include the development and commercialization of multi-camera object association systems for industry. During his time as a research scientist at the Samsung AI Centre in Cambridge, Dr. Zhu pioneered sustainable AI algorithms for understanding visual content in images and videos. His work has garnered several best paper awards, and he has been recognized as one of the UK's and the world's best rising stars in science. Dr. Zhu's extensive research output includes over 120 articles in top-tier conferences and journals, with more than 17,000 citations and an H-index of 54. He actively contributes to the academic community through workshop organization, serving as a senior program committee member and area chair, and participating in panel debates on emerging trends in AI. Additionally, Dr. Zhu holds five US patents in the fields of AI and computer vision.
University of Birmingham
University of Birmingham
University of Birmingham
Durham University
Imperial College London
University of Birmingham
Boeun Kim (b.e.kim@bham.ac.uk); Zhongqun Zhang (zxz064@student.bham.ac.uk)