Responsible Face Image Processing (ReFIP 2024) Call for Papers
First International Workshop on Responsible Face Image Processing (ReFIP 2024)
to be held as part of the 18th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2024)
Workshop: May 27 or May 31, 2024 (to be defined) - Istanbul, Turkey
https://responsiblefaceimageprocessing.github.io/fg2024/
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Important Dates
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Submission Deadline: March 14, 2024
Notification of Acceptance: April 10, 2024
Camera Ready Deadline: April 22, 2024
Workshop: May 27 or May 31, 2024 (to be defined) - Istanbul, Turkey
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Workshop Aims and Scope
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In the rapidly evolving landscape of facial biometric technology, the
interplay between bias, fairness, transparency, and privacy is
critical to building reliable artificial intelligence systems. Recent
studies have raised numerous questions about the risks of implementing
facial recognition technologies without comprehensive management of
these concerns, fostering an ethical discussion about their social
impact. Indeed, there is a growing demand for integrating facial image
processing systems into various aspects of daily life, reflecting the
potential for greater security and efficiency. On the other hand, this
demand is encountering significant resistance because of these ethical
concerns.
Biases in facial biometric systems can lead to discrimination, often
reinforcing pre-existing biases. On top of that, prioritizing fairness
in facial image processing research is becoming increasingly crucial
due to ethical and legislative reasons, with the aim of providing
equal performance and treatment for all users regardless of their
race, gender, age, or other protected attributes. Due to the black-box
nature of modern deep learning techniques, the transparency of such
systems is also becoming an increasingly discussed and relevant topic
as it relates to data management and how the decision-making
mechanisms behind biometric technologies can be explained and
understood. Transparency (and consequently explainability) of these
kinds of systems is mandatory to exercise effective supervision and
build trust in their use. Finally, privacy issues are among the most
pressing in facial image processing research because of the
sensitivity of the data collected. It is imperative to protect
individual biometric information from misuse and abuse.
This workshop aims to foster contributions on sophisticated strategies
for addressing critical challenges in responsible facial image
processing systems. In particular, it seeks to foster
interdisciplinary exchange among scholars, practitioners, and
decision-makers to tackle these challenges and propose innovative
solutions, encompassing more extensive ethical knowledge and the
development of effective and transparent biometric solutions. The main
goal is to explore approaches that enhance inclusiveness and equity in
facial image processing systems, involving advanced algorithmic
methods to minimize bias, improve privacy compliance, and enhance
decision-making transparency. Furthermore, the workshop seeks to
identify best practices for integrating these dimensions into the
resulting systems.
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Workshop Keywords
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Bias· Fairness· Privacy· Facial analysis
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Workshop Topics
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The workshop welcomes contributions on all topics related to fairness, accountability, transparency, ethics, and other aspects of facial image processing, focused (but not limited) on:
Fairness:
- Dataset collection and preparation for fair facial image processing
(e.g., designing methods for dealing with imbalances in data,
collecting datasets for the analysis of biased and unfair situations);
- Countermeasure design and development for fair facial image
processing (e.g., formalizing and operationalizing fairness concepts,
designing treatments that mitigate unfairness in
pre-/in-/post-processing);
- Evaluation protocols and metric formulation for fair facial image
processing (e.g., formulating fairness-aware protocols to evaluate
models, evaluating existing mitigation strategies in unexplored
domains);
- Applications of fair facial image processing (e.g., fairness methods
for access control, border control, healthcare, entertainment, and
e-learning systems)
Accountability:
- Methods for accountable facial image processing (e.g., requirements
to enable accountability, mechanisms for reporting or accounting,
interfaces empowering users to control their facial data);
- Processes for accountable facial image processing (e.g., feasibility
and effectiveness of independent audits, certification processes that
verify adherence to accountability standards);
- Studies to assess and increase accountability in facial image
processing (e.g., metrics and user studies of accountability
mechanisms, studies to assess the accountability of existing systems)
Transparency:
- Technical methods for explainable facial image processing (e.g.,
latent spaces explainability, neuro-symbolic reasoning, post-hoc
methods, self-explainable methods);
- Ethical considerations for explainable facial image processing
(e.g., philosophical consideration of synthetic explanations, expected
epistemic and moral goods, responsibility in policy guidelines);
- Psychological concepts for explainable facial image processing
(e.g., persuasiveness and robustness of explanations, psychometrics of
human explanations, cognitive approaches for explanations);
- Legal and administrative considerations for explainable facial image
processing (e.g., black-box model auditing, explainability in
regulatory compliance, human rights for explanations);
- Applications of explainable facial image processing (e.g.,
explainable methods for access / border control, healthcare,
entertainment, and e-learning systems)
Privacy:
- Technical methods for privacy-preserving facial image processing
(e.g., cryptographic techniques, federated learning, differential
privacy);
- Ethical considerations for privacy-preserving facial image
processing (e.g., ethical frameworks, societal impact assessment, data
sharing, anonymization, and privacy of synthetic data);
- Psychological concepts for privacy-preserving facial image
processing (e.g., user perceptions of privacy, trust in
privacy-preserving systems, cognitive approaches to privacy);
- Legal and administrative considerations for privacy-preserving
facial image processing (e.g., compliance with privacy regulations,
legal frameworks for privacy-preserving techniques, human rights in
privacy preservation);
- Applications of privacy-preserving facial image processing (e.g.,
privacy-preserving methods for access control, border control,
healthcare, entertainment, and e-learning systems)
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Submission Details
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All submissions must be written in English. Authors should consult FG
paper guidelines
(https://fg2024.ieee-biometrics.org/paper-submission/) for preparing
their papers and use their proceedings templates, either LaTeX or
Word. Papers should be submitted as PDF files to:
https://cmt3.research.microsoft.com/FGReFIP2024
We will consider two different submission types, i.e., Short and Long
Papers. Authors should carefully consider the category before
submitting a paper.
The main difference between the two is in the size of the
contributions, not in their importance or technical quality. In other
words, a long paper is expected to have a greater contribution than a
short paper. More specifically:
Long papers (8 pages excluding references) should present original
reports of substantive new research techniques, findings, and
applications. They should place the work within the field and
clearly indicate innovative aspects. Research procedures and
technical methods should be presented in sufficient detail to
ensure scrutiny and reproducibility. Results should be clearly
communicated, and the implications of the contributions/findings
for FG and beyond should be explicitly discussed.
Short papers (4 pages + 1 page for references) should present
original and highly promising research or applications. Merit will
be assessed in terms of originality, importance, and technical
quality, more so than the scope and maturity of the work.
Please note that both long and short papers will undergo the same
review process. Rejected long papers will NOT be considered for
acceptance as short papers, except in rare cases when reviewers
unanimously make this recommendation. Both long and short papers can
be accepted for oral or poster presentations.
All submissions will undergo a double-blind review process. Therefore,
the submitted paper must be appropriately anonymized. Authors should
remove author and institutional identities from the title and header
areas of the paper. There should also be no acknowledgments. Authors
can leave citations to their previous work unanonymized so that
reviewers can ensure that all previous research has been taken into
account. However, they should cite their own work in the third person
(e.g., "[22] found that...").
Authors will have the opportunity to address issues raised by the
reviewers during a rebuttal period before the final decision is
made. All contributions will be reviewed by at least three members of
the Program Committee. We strongly encourage making code and data
available anonymously (e.g., in an anonymous GitHub repository via
Anonymous GitHub).
Submissions have to be in pdf format and are limited to a 10MB file
size for both categories. Supplementary material (images, video, etc.)
may optionally be submitted with papers, but be sure to maintain
anonymity, including the file properties or other hidden text. The
entire submission (paper + supplemental material) has a file size
limit of 100MB. The supplemental materials will not be part of the
conference proceedings, so they are only there to aid the reviewing
process. Reviewers are not required to view the supplemental material
(though most reviewers are likely to do so), so any information
critical to understanding the work should be in the main paper. All
supplementary material must be self-contained and zipped into a single
file. Note that reviewers will be encouraged to look at it, but are
not obligated to do so.
Submitted papers will be rejected without review in case they are not
properly anonymized, do not comply with the template, or do not follow
the above guidelines.
Accepted papers will be published in the FG 2024 main conference proceedings.
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Attending
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The registration will be managed by the FG 2024 main conference organization at
https://fg2024.ieee-biometrics.org/.
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Workshop Chairs
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Andrea Atzori
University of Cagliari, Cagliari, Italy
Email: andrea.atzori@unica.it
Fadi Boutros
Fraunhofer Institute for Computer Graphics Research IGD, Darmstadt, Germany
Email: fadi.boutros@igd.fraunhofer.de
Lucia Cascone
University of Salerno, Fisciano, Italy
Email: lcascone@unisa.it
Naser Damer
Fraunhofer Institute for Computer Graphics Research IGD, Darmstadt, Germany
Email: naser.damer@igd.fraunhofer.de
Mirko Marras
http://www.mirkomarras.com/
University of Cagliari, Cagliari, Italy
Email: mirko.marras@acm.org
Ruben Tolosana
Universidad Autónoma de Madrid, Madrid, Spain
Email: ruben.tolosana@uam.es
Ruben Vera-Rodriguez
Universidad Autónoma de Madrid, Madrid, Spain
Email: ruben.vera@uam.es
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Contacts
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For general inquiries on the workshop, please send an email to
andrea.atzori@unica.it, fadi.boutros@igd.fraunhofer.de,
lcascone@unisa.it, naser.damer@igd.fraunhofer.de,
mirko.marras@acm.org, ruben.tolosana@uam.es , and ruben.vera@uam.es.