February 12th, 2025 
Daniela Lopez de Luise The Fourth Workshop on Federated Learning for Computer Vision (FedVision)
in Conjunction with CVPR 2025
Call for paper
Main research topics of relevance to this workshop include, but are not limited to:
- Novel FL models for computer vision tasks, e.g., scene understanding, face recognition, object detection, person re-identification, image segmentation, human action recognition, medical image processing, etc.
- Privacy-preserving machine learning for computer vision tasks
- Personalized FL models for computer vision applications
- Novel computer vision applications of FL and privacy-preserving machine learning
- FL frameworks and tools designed for computer vision applications and benchmarking
- Novel vision datasets for FL
- Optimization algorithms for FL, particularly algorithms tolerant of data heterogeneity and resource heterogeneity
- Approaches that scale FL to larger models, including model pruning and gradient compression techniques
- Label efficient learning in FL, e.g., self-supervised learning, semi-supervised learning, active learning, etc.
- Neural architecture search (NAS) for FL
- Life-long learning in FL
- Attacks on FL including model poisoning, data poisoning, and corresponding defenses
- Fairness in FL
- Federated domain adaptation
- Privacy leakage and defense in the FL environments
- Privacy-preserving Generative models for CV
- FL based CV pipeline for scene understanding and visual analytics
Keynote speakers
- Dr. Shandong Wu, Associate Professor, Department of Radiology, University of Pittsburgh
- Dr. Shiqiang Wang, Staff Research Scientist, IBM T. J. Watson Research Center, NY, USA
- Dr. Xi Peng, Assistant Professor, Department of Computer & Information Sciences at the University of Delaware
- Dr. Gauri Joshi, Associate Professor, Department of Electrical and Computer Engineering, Carnegie Mellon University
- Salman Avestimehr, Professor, University of Southern California, Inaugural Director of the USC-Amazon Center for Secure and Trusted Machine Learning
- Dr. Yinzhi Cao, Associate Professor, Department of Computer Science, Johns Hopkins University
- Dr. Xiaoxiao Li, Assistant Professor, Electrical and Computer Engineering Department, the University of British Columbia
Organizers
- Chen Chen, Associate Professor, Center for Research in Computer Vision, University of Central Florida
- Guangyu Sun, Ph.D. Candidate, Center for Research in Computer Vision, University of Central Florida
- Mahdi Morafah, Ph.D. Candidate, Department of Electrical and Computer Engineering, UCSD
- Nathalie Baracaldo, Research Staff Member at IBM’s Almaden Research Center in San Jose, CA
- Peter Richtaìrik, Computer Science at the King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
- Mi Zhang, Associate Professor, Ohio State University
- Ang Li, Assistant Professor, Department of Electrical and Computer Engineering, University of Maryland (UMD) College Park
- Nicholas Lane, University of Cambridge and Flower Labs
- Bo Li, Associate Professor, Department of Computer Science, University of Chicago
- Shiqiang Wang, Staff Research Scientist, IBM T. J. Watson Research Center
- Yang Liu, Associate Professor, Institute for AI Industry Research (AIR), Tsinghua University
- Lingjuan Lyu, Senior research scientist and team leader in Sony AI
Paper (& supplementary material) Submission Deadline: March 15, 2025 (11:59 PM, PST)
Notification: April 1, 2025 (11:59 PM, PST)
Camera-Ready: April 6, 2025 (11:59 PM, PST)
Accepted papers will be published in conjunction with CVPR 2025 proceedings. Paper submissions will adhere to the CVPR 2025 paper submission style, format, and length restrictions.
The CVPR 2025 author kit is available: https://github.com/cvpr-org/author-kit/releases
Paper submission website: https://cmt3.research.microsoft.com/FedVision2025
For any questions, please contact Dr. Chen Chen (chen.chen@crcv.ucf.edu)
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Dr. Chen Chen, Associate Professor
CRCV | Center for Research in Computer Vision
HEC 221 | University of Central Florida
4328 Scorpius St., Orlando, FL 32816-2365
E-mail: chen.chen@crcv.ucf.edu | URL: https://www.crcv.ucf.edu/chenchen/
E-mail: chen.chen@crcv.ucf.edu | URL: https://www.crcv.ucf.edu/chenchen/
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