[visionlist] [IEEE IJCB 2023]: Call for papers for special session on Synthetic data in Biometrics

Vitomir Struc vitomir.struc at fe.uni-lj.si
Thu Jun 8 03:00:52 -04 2023


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IEEE International Joint Conference on Biometrics  (IJCB 2023)
25-28 September 2023, Ljubljana, Slovenia

Special session on
Synthetic Data in Biometrics
https://lmi.fe.uni-lj.si/en/synthetic-data-in-biometrics/

Paper submission: 17 July 2023
Notifications: 14 August 2023
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*** CALL FOR PAPERS ***

In recent years, the field of biometrics has witnessed remarkable 
progress across different modalities, including facial images, 
fingerprints, iris scans, and behavioral biometrics. However, the 
development of accurate and robust biometric systems heavily relies on 
large-scale, diverse, and annotated datasets. Gathering such datasets, 
especially when dealing with sensitive personal information, can be 
challenging due to privacy concerns, legal constraints, and limited 
access to large-scale real-world data.

The IJCB 2023 special session on »Synthetic data in Biometrics« will 
explore the emerging field of synthetic data for biometrics and its 
potential to revolutionize the development, evaluation, and deployment 
of biometric systems. Synthetic data, generated through advanced machine 
learning models, offers a promising solution to address the limitations 
of real-world data collection. By synthesizing artificial biometric 
samples, researchers can create large-scale (annotated) datasets that 
exhibit diverse variations and can be used for training and testing of 
biometric models, all while respecting privacy constraints.

By bringing together researchers, practitioners, and industry experts, 
this special session will foster discussions on the potential of 
synthetic data for biometrics. The special session will solicit 
contributions exploring novel methodologies, applications, and 
challenges associated with synthetic data generation, evaluation, and 
utilization in biometric research. Topics of interest include, but are 
not limited to:

+ Novel generative models for biometric data synthesis
+ Label generation for synthetic data
+ Data factories for training biometric (detection, landmarking, 
recognition) models
+ Synthetic data for data augmentation
+ Data synthesis for bias mitigation and fairness
+ Quality assessment for synthetic data
+ Synthetic data for privacy protection
+ Novel applications of synthetic data
+ New synthetic datasets and performance benchmarks

*** Paper formatting and submission ***

Paper submitted to the special session should follow the formatting 
guidelines, instructions and templates provided for the main conference 
submissions, posted here: 
https://ijcb2023.ieee-biometrics.org/paper-submission/

In general, a paper can be up to 8 pages including figures and tables, 
plus an unlimited number of additional pages for references only. The 
reviewing process will be double blind.

All accepted papers will be included in the main part of the IEEE IJCB 
2023 proceedings and will be submitted for inclusion in IEEE Xplore.

Papers should be submitted to the Special session track of the IJCB 2023 
CMT instance. Select “Special Session: Synthetic data in Biometrics” as 
the primary subject area during the submission:

https://cmt3.research.microsoft.com/IJCB2023


*** Important Dates ***

Paper submission deadline: 17 July 2023
Notifications to authors: 14 August 2023


*** Organizers ***

Fadi Boutros, Fraunhofer IGD, Germany
Nasir Memon, NYU, USA
Vitomir Štruc, University of Ljubljana, Slovenia
Andreas Uhl, Salzburg University, Austria

-- 
Prof. Vitomir Struc, PhD
Laboratory for Machine Intelligence
Faculty of Electrical Engineering
University of Ljubljana, Slovenija
URL: https://lmi.fe.uni-lj.si/en/vitomir-struc/

VP Technical Activities, IEEE Biometrics Council
General Co-Chair: IEEE International Joint Conference on Biometrics (IJCB 2023), https://ijcb2023.ieee-biometrics.org
Program Co-Chair: IEEE International Conference on Automatic Face and Gesture Recognition (FG 2024), https://fg2024.ieee-biometrics.org/




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