See the program
Call for Papers
Computer vision methods trained on public databases demonstrate performance drift when deployed for real-world surveillance, compared to their initial results on the test set of those employed databases. In this workshop, we are interested in papers reporting their experimental results on any application of computer vision in real-world surveillance, challenges they have faced, and their mitigation strategy on topics like, but not limited to:
• Object detection
• Tracking
• Anomaly detection
• Scene understanding
• Super-resolution
• Multimodal surveillance
Furthermore, the workshop has special attention to legal and ethical issues of computer vision applications in real-world scenarios. We therefore also welcome papers describing their methodology and experimental results on legal matters (like GDPR) or ethical concerns (like detecting bias towards gender, race, or other characteristics and mitigating strategies).
Important Dates
Paper submission: October 20 October 27, 2022 (11:59 PM, PT)
Submission for challenge participants: November 8, 2022 (11:59 PM, PT)
Decision notification: November 15, 2022 (11:59 PM, PT)
Camera ready: November 17, 2022 (11:59 PM, PT)
Submission
Submitted papers are handled via CMT via this link.
Paper template and guidelines for the workshop are similar to those of WACV and they can be found here.
Accepted papers will be included in WACV proceedings and will be published by the CVF / IEEE.
Best Paper Award will be sponsored by Milestone Systems A/S
Challenge
The workshop includes a challenge on Pedestrian Attribute Recognition and Attribute-based Person Retrieval. This challenge aims to spotlight the problem of domain gap in a real-world surveillance context and highlight the challenges and limitations of existing methods to provide a direction of research for the future. It will be based on a subset of the UPAR Dataset composed of annotations for 40 binary attributes [1].
More information can be found here.
[1] Specker, Andreas; Cormier, Mickael; Beyerer, Jürgen (2022): UPAR: Unified Pedestrian Attribute Recognition and Person Retrieval https://arxiv.org/abs/2209.02522
Keynote Speakers
Mats Thulin,
Director Computer Vision and Core Technologies, AXIS Communications AB, Sweden
Talk: Analytics performance in challenging video surveillance scenes
Chen Chen,
Assistant Professor, UCF, USA
Talk: Privacy-preserving video analysis
Jack Cooper,
Program Manager, Intelligence Advanced Research Projects Activity (IARPA)
Talk: Deep Intermodal Video Analytics
Bart Russell,
Program Manager at Defense Advanced Research Projects Agency (DARPA)
Talk: Legal and Ethical Considerations in Urban Reconnaissance through Supervised Autonomy (URSA)
Cees G.M. Snoek,
Professor in Computer Science, University of Amsterdam, Netherlands
Talk: Video surveillance with trustworthiness built-in
Organizers
Kamal Nasrollahi,
Aalborg University, Denmark
Milestones Systems, Denmark
Mail: kn@create.aau.dk
Sergio Escalera Guerrero
Universitat de Barcelona, Spain
Computer Vision Center, Spain
Aalborg University, Denmark
Mail: sescalera@cvc.uab.cat
Radu Ionescu
University of Bucharest, Romania
Mail: raducu.ionescu@gmail.com
Fahad Shahbaz Khan
Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates
Linköping University,Sweden
Mail: fahad.khan@liu.se
Thomas Moeslund
Aalborg University, Denmark
Mail: tbm@create.aau.dk
Anthony Hoogs
Kitware, USA
Mail: anthony.hoogs@kitware.com
Mubarak Shah
University of Central Florida, USA
Mail: shah@crcv.ucf.edu
