Real-World Surveillance: Applications and Challenges Workshop (RWS @ ECCV2022)

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 a 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: – July 1st, 2022
Submission for challenge participants: – July 5th, 2022
Decision notification: – July 27th, 2022
Camera ready: – August 1st, 2022


Submitted papers are handled via CMT at this link.
Paper template and guidelines for the workshop are similar to those of ECCV and they can be found here.

Accepted papers will be included in ECCV proceedings and will be published by Springer.

Best Paper Award will be sponsored by Milestone Systems A/S


The workshop includes a challenge on concept drift in object detection on the largest annotated public thermal database. More information can be found here.

Keynote Speakers

Kate Saenko,
Director of the Computer Vision
and Learning Group,
Boston University

Talk: Feature and Concept Drift in Computer Vision

Arun Ross,
CILLAG Endowed Chair Professor,
Computer Science & Engineering,
Michigan State University

Talk: Enhancing Face Privacy Using
Semi-Adversarial Neural Networks

Serena Yeung,
Stanford University,

Talk: Bias and Privacy Considerations for
Computer Vision in Healthcare Applications

Hua Zhang,
Chinese Academy of Science

Talk: Identity-Preserving Face Anonymization
via Adaptively Facial Attributes Obfuscation

Matthew Turk,
President of Toyota
Technological Institute at Chicago

Talk: Perspectives on Bias

Olga Russakovsky and Angelina Wang,
Princeton University

Talk: Fairness in Visual Recognition


Kamal Nasrollahi,
Aalborg University, Denmark
Milestones Systems, Denmark

Sergio Escalera Guerrero
Universitat de Barcelona, Spain
Computer Vision Center, Spain
Aalborg University, Denmark

Radu Ionescu
University of Bucharest, Romania

Fahad Shahbaz Khan
Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates
Linköping University,Sweden

Thomas Moeslund
Aalborg University, Denmark

Anthony Hoogs
Kitware, USA

Shmuel Peleg
Hebrew University, Israel

Mubarak Shah
University of Central Florida, USA