Call for Papers

Computer vision models trained on public datasets often exhibit performance drift when deployed in real-world surveillance, diverging from their reported test-set results. This workshop invites papers presenting experimental results from any real-world surveillance or asset-protection application (e.g.,guarding buildings and critical infrastructure), the challenges encountered, and strategies for mitigation on topics including, but not limited to:

• Object detection
• Tracking
• Action recognition
• 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). We particularly encourage submissions addressing safety, reliability, and regulatory compliance for critical infrastructure protection, as well as privacy-preserving approaches in high-security environments.

Important Dates

• Paper submission deadline: December 7th, 2025 (11:59 PM, AoE)
• Paper submission deadline for challenge participants: December 14th, 2025 (11:59 PM, AoE)
• Decision notification: December 23rd, 2025
• Camera-ready: January 9th, 2026 (11:59 PM, PT)
• Workshop: March 6th or 7th, 2026

Publication

Submitted papers are handled via OpenReview accessible here

Paper template and guidelines for the workshop are similar to those of WACV and can be found here

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

Robust Thermal-Image Object Detection Challenge

Ready to stress-test your detector in the wild? The 6th RWS workshop introduce a new challenge on Robust Thermal-Image Object Detection to advance multi-object detection performance under long-term thermal drift.

Real-world thermal imaging is messy: sensors re-calibrate, ambient temperatures swing, and weather keeps changing, slowly eroding detector performance. The RWS Robust Thermal-Image Object Detection Challenge puts this problem front using the LTDv2, a large-scale dataset purpose-built for bechmarking long-term robustness wtih 1 million frames from video over 8 months, 6.8+ million annotated boxes, and rich weather metadata.Your mission: build object detectors that don’t just perform well on a sunny day, but stay consistent across seasons, weather patterns, and day–night cycles. We’ll score submissions on overall mAP and temporal consistency to reward models that are both accurate and stable over time. The challenge features a development phase for method iteration and a final test phase for the leaderboard. A starter kit with dataloaders and YOLOv8 baselines are available to get you up and running quickly. Now it’s your turn to beat them.

The CodaBench Robust Thermal Image Object Detection Challenge Platform can be found here: https://www.codabench.org/competitions/10954/

Challenge Schedule:

• October 17^th AoE:  Start of competition and Development Phase
• December 1^st AoE: Start of Testing Phase and end of Development Phase
• December 7^th AoE: End of competition
• December 14^th AoE: Paper submission deadline (Challenge Participants only)
• December 23^rd AoE: Decision notification and announcement of challenge winner
• January 9^th 11:59 PM, PT: Camera-ready deadline

Venue

RWS 2026 will be held in conjunction with WACV 2026 at the JW Marriott Starpass in Tucson, Arizona