[visionlist] [CFP][WACV 2025] 5th Workshop on Real-World Surveillance: Applications and Challenges (RWS)

[Specker, Andreas]

5th Workshop on Real-World Surveillance: Applications and Challenges (RWS)

in conjunction with the

IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 2025
(https://wacv2025.thecvf.com/)

 

WORKSHOP WEBSITE 

https://vap.aau.dk/rws-wacv2025/

 

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

• Multi-modal 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, AI Act, and US Executive Order on AI) or ethical
concerns (like detecting bias towards

gender, race, or other characteristics and mitigating strategies). The
workshop also hosts a competition on human

pose estimation and pose tracking.

 

IMPORTANT DATES

Paper submission:          November 20th, 2024 (11:59 PM, PT)

Paper submission for challenge participants: 

November 27th, 2024 (11:59 PM, PT)

Decision notification:     December 13th, 2024 (11:59 PM, PT)

Camera-ready:               January 7th, 2024 (11:59 PM, PT)

Workshop date:             February 28 or March 3 or 4, 2025

 

SUBMISSION

Submitted papers are handled via CMT.

Paper template and guidelines for the workshop are similar to those of WACV.

Accepted papers will be included in WACV Workshop proceedings and will be
published by the CVF / IEEE.

 

CHALLENGE: Human Pose Estimation on Thermal Imaging

 

Our workshop presents a new competition series on “Human Pose Estimation on
Thermal Imaging”. The competition will be hosted on the eval.ai platform.

Human Pose Estimation (HPE) using visual images has achieved significant
success. However, RGB-based models often struggle in poor weather and
low-light conditions. Thermal infrared images offer a solution, remaining
unaffected by such conditions and providing enhanced privacy.

To address the lack of large-scale thermal HPE datasets, we introduce the
Unified Pedestrian Pose Estimation in Thermal Imaging (UPPET) dataset. This
dataset combines LLVIP, CAMEL, and OpenThermalPose (OTP), providing
harmonized pose annotations across 19,333 images with 15 keypoints each and
is used for the challenge.

The competition aims to advance HPE in Thermal Imaging through three tracks:

 

1. Generalization of HPE in Thermal Imaging

2. HPE on Thermal Imaging

3. HPE on Thermal Imaging based on Synthetic Data

 

Participants will have a development phase to validate their results,
followed by a test phase with a limited number of leaderboard submissions. A
baseline model will be provided for reference.

Join us in advancing the field of Human Pose Estimation on Thermal Imaging!

Tentative challenge start date: November 4, 2024

 

ORGANIZERS

Andreas Specker

Fraunhofer Institute of Optronics, System Technologies and

Image Exploitation IOSB, Karlsruhe, Germany

Mail: andreas.specker at iosb.fraunhofer.de

 

Mickael Cormier

Karlsruhe Institute of Technology and Fraunhofer Institute for Optronics,
System Technologies and Image Exploitation IOSB, Karlsruhe, Germany

Mail: mickael.cormier at iosb.fraunhofer.de

 

Sergio Escalera Guerrero

Universitat de Barcelona, Spain

Computer Vision Center, Spain

Aalborg University, Denmark

Mail: sescalera at cvc.uab.cat

 

Radu Ionescu

University of Bucharest, Romania

Mail: raducu.ionescu at gmail.com

 

Fahad Shahbaz Khan

Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United
Arab Emirates

Linköping University,Sweden

Mail: fahad.khan at liu.se

 

Kamal Nasrollahi,

Aalborg University, Denmark

Milestones Systems, Denmark

Mail: kn at create.aau.dk

 

ADVISORY COMMITTEE

Thomas Moeslund

Aalborg University, Denmark

Mail: tbm at create.aau.dk

 

Anthony Hoogs

Kitware Inc, USA

Mail: anthony.hoogs at kitware.com

 

Shmuel Peleg

Hebrew University of Jerusalem, Israel

Mail: peleg at mail.huji.ac.il

 

Mubarak Shah

University of Central Florida, USA

Mail: shah at crcv.ucf.edu

 

 

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