Biometrics 2026
 


In conjunction with CVPR 2026,


Call for Papers

Biometric technologies are no longer confined to laboratories and they are reshaping global identity ecosystems on an unprecedented scale and with profound societal implications. From national digital ID infrastructures that secure billions of citizens to seamless authentication powering next-generation e-commerce, biometrics now underpin critical trust frameworks across governments, industries, and everyday consumer experiences. The mainstream adoption of facial and fingerprint recognition in mobile ecosystems has ignited a paradigm shift, demanding rigorous innovation to address escalating challenges in accuracy, inclusivity, and ethical deployment. Yet, as applications proliferate, from social welfare distribution to border security and personalized healthcare, current methodologies struggle to cope with the complexities of real-world environments, multimodal integration, and evolving adversarial threats.

This premier CVPR workshop confronts these frontiers head-on. We seek impactful research findings that can redefine the boundaries of biometrics, emphasizing responsible innovation and real-world impact. Building on 19 years of CVPR-affiliated workshops (since 2006), we curate a forum where academia, industry R&D, and policy leaders converge to advance the field beyond incremental progress. Submissions should propose novel solutions in:



Why submit? This workshop is renowned for its selective rigor (recent acceptance rates: <29%) and high-impact discourse. Accepted papers will engage a global audience of 150+ practitioners, with opportunities for special journal issues and industry collaboration. We prioritize work that bridges theoretical excellence with tangible societal benefit, including contributions from underrepresented voices and early-career researchers.

- Next-Gen Sensing and Modalities: Novel sensing paradigms (depth, thermal, time-series, behavioral); emerging biometrics (vein, gait, body, knuckle, physiological signals)
- Robust Fusion Architectures: Score/feature-level fusion, cross-spectral matching, and multimodal learning under uncertainty
- Trustworthy Systems: Bias mitigation, privacy-preserving templates, adversarial robustness, and explainable AI for biometrics
- Real-World Deployment: Mobile/edge optimization, large-scale performance modeling, and standards evolution
- Societal Integration: Ethical frameworks for public-sector use, accessibility for diverse populations, and social impact assessment

Overall Meeting Sponsors

Computer Vision Foundation IEEE Computer Society