Full Paper
Original, unpublished research papers submitted for double-blind peer review, following BMVC 2026 formatting guidelines, with possible supplementary material.
AI/CORE Unranked
RVSSE2026 2026
Workshop on Robust Vision in Synthetic Environments
The RVS-SE 2026 workshop, held in conjunction with BMVC 2026 in Lancaster, UK, focuses on the robustness, reliability, and trustworthiness of computer vision systems operating in environments increasingly dominated by synthetic media and generative AI. It brings together researchers to address challenges such as distribution shift, biometric security, foundation model training with synthetic data, and societal impacts of AI-generated content.
Paper fit
Contribution paths
A strong submission should clearly identify its contribution and evaluate it appropriately.
Research areas in scope
01
Topics of Interest
Robust vision under synthetic media: Distribution shift, failure modes, and robustness of vision systems in the presence of synthetic content.Biometrics and identity systems: Robust biometric recognition, presentation attacks, training, and identity consistency in generative settings.Foundation and multimodal models: Impact of synthetic data on large-scale training, pretraining/fine-tuning, and evaluation of foundation models.Synthetic data and learning systems: Synthetic data generation, dataset contamination, data curation, and learning under mixed real-synthetic distributions.Trustworthy and reliable vision systems: Calibration, uncertainty estimation, robustness evaluation, explainability, and failure analysis.Vision for security and digital identity: Applications in authentication, digital identity, surveillance, and content integrity.Deployment and real-world robustness: System-level robustness, operational challenges, and safety in real-world vision deployments.Broader impacts of synthetic media: AI safety, societal implications, and content authenticity in vision pipelines.
Policies worth checking twice
- Submissions must be original and unpublished.
- All submissions undergo a double-blind peer-review process.
- Papers must be anonymized and comply with BMVC reviewing policy.
- At least one author of each accepted paper must register for BMVC 2026 and present the work.
- Authors are encouraged to release code, models, and datasets to promote reproducibility.
- Submissions must follow BMVC 2026 page limits for workshop papers.
Official sources
Compiled from the official call for papers. The organizers’ pages remain authoritative.
Last verified September 9, 2026