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Responsible PR&MI 2021 : First International Workshop on Responsible Pattern Recognition and Machine Intelligence

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Link: https://rprmiworkshop.github.io/iccv2021/
 
When Oct 17, 2021 - Oct 17, 2021
Where ONLINE EVENT
Submission Deadline Jul 7, 2021
Notification Due Jul 22, 2021
Final Version Due Aug 7, 2021
Categories    computer vision   fairness   responsible ai   pattern recognition
 

Call For Papers

Call for Papers
First International Workshop on Responsible Pattern Recognition and Machine Intelligence (Responsible PR&MI 2021)
to be held as part of the 18th International Conference on Computer Vision (ICCV 2021)
Workshop: October 17 2021 - ONLINE EVENT

https://rprmiworkshop.github.io/iccv2021

Keynote Speakers
- Iyad Rahwan, Max Planck Institute for Human Development (Germany)
- Arun Ross, Michigan State University (US)

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Important Dates
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Submissions: July 7, 2021
Notifications: July 22, 2021
Camera-Ready: August 7, 2021
Workshop: October 17, 2021

All deadlines are 11:59pm, AoE time (Anywhere on Earth).

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Workshop Aims and Scope
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The consideration of ethical and beyond-accuracy aspects is of increasing importance in industrial and academic spheres, as systems empowered with AI are influencing all facets of our daily life. It is now commonplace to see evidence on the harmful impacts of current AI systems deployed in various real world, high-stakes environments. Indeed, pattern recognition and machine intelligence that leverage computer vision are among the domains exposed to ethical risks, and recent work emphasizes that the methodologies and countermeasures for facing challenges related to these issues are highly domain-specific. Despite the recent attention, important aspects like fairness, accountability, transparency, and ethics are still under-explored in the computer vision domain. To extend domain-generic studies conducted in literature and enhance our understanding of these aspects specifically, exploring what fairness, accountability, transparency, ethics, and other beyond-accuracy aspects deeply mean in computer vision applications becomes hence essential. Responsible PR&MI 2021 will be the ICCV's workshop aimed at collecting high-quality, high-impact, original research in this emerging field and providing a common ground for all interested researchers and practitioners. Given the growing interest of the community in these topics, we expect that this workshop will generate a strong outcome and a wide community dialog.

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Workshop Keywords
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Pattern Recognition · Computer Vision · Bias · Fairness · Transparency · Accountability

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Workshop Topics
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The workshop welcomes contributions in all topics related to fairness, accountability, transparency, ethics, and other beyond-accuracy aspects in pattern recognition and machine intelligence applications, with special attention to computer vision, focused (but not limited) to:

- Data Collection and Problem Modelling:
-- Modelling fairness and/or other ethical aspects of pattern recognition and machine intelligence models (e.g., auditing, fairness concepts, definition of fairness, representative data collection)
-- Modelling accountability of pattern recognition and machine intelligence models (e.g., accountability for different user's groups, accountability-aware model design)
-- Modelling transparency of pattern recognition and machine intelligence models (e.g., participatory studies to identify explanatory needs, explainable prediction schemas)
-- Modelling privacy and security in pattern recognition and machine intelligence models (e.g., privacy-preserving models, attacks threats modelling, requirements on protection of user's representation)

- Design and Development:
-- Methodologies to improve fairness and/or other ethical aspects in pattern recognition and machine intelligence (e.g., multi-task learning and trade-offs, unfairness mitigation and countermeasures)
-- Methodologies to improve accountability of pattern recognition and machine intelligence (e.g., methods for describing the system, data usage and integrity)
-- Methodologies to improve transparency of pattern recognition and machine intelligence (e.g., explainable user's interfaces, taxonomies for explanations)
-- Methodologies to improve privacy and security of pattern recognition and machine intelligence (e.g., methods that enable user control of shared sensitive attributes, multi-task learning for trade-offs between privacy and accuracy)

- Evaluation:
-- Methods to assess fairness and/or other ethical aspects in pattern recognition and machine intelligence (e.g., metrics for fairness assessment, evaluation protocols, assessing stakeholder unfairness at group or individual level)
-- Methods to assess accountability in pattern recognition and machine intelligence (e.g., metrics, protocols, and field studies to validate accountability strategies, studies to assess accountability of existing systems)
-- Methods to assess transparency in pattern recognition and machine intelligence (e.g., metrics, protocols, and evaluation frameworks for assessing the impact of explainable strategies and interfaces)
-- Methods to assess privacy and security in pattern recognition and machine intelligence (e.g., metrics, protocols, and evaluation frameworks for assessing privacy and robustness)

- Applications:
-- Action and behavior recognition
-- Biometric recognition
-- Computational photography
-- Image and video retrieval
-- Medical, biological, and cell microscopy
-- Scene analysis and understanding
-- Vision for robotics and autonomous vehicles
-- ... and more related

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Submission Details
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We invite authors to submit 8-page unpublished original papers, with additional pages containing only cited references allowed. Submitted papers should not have been previously published or accepted for publication in substantially similar form in any peer-reviewed venue, such as journals, conferences, or workshops.

All submissions will go through a double-blind review process and be reviewed by at least three reviewers on the basis of relevance for the workshop, novelty/originality, significance, technical quality and correctness, quality and clarity of presentation, quality of references and reproducibility. Submitted papers must be formatted according to the Latex template of the workshop (http://iccv2021.thecvf.com/sites/default/files/2020-09/iccv2021AuthorKit.zip). Authors should consult the workshop paper guidelines (http://iccv2021.thecvf.com/sites/default/files/2020-09/egpaper_for_review.pdf) for the preparation of their papers. Both the template and the guidelines are identical to the ICCV 2021 main conference ones. All contributions must be submitted as PDF files to https://easychair.org/my/conference?conf=rprmi2021.

Accepted papers will be published in the ICCV 2021 proceedings.

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 ICCV 2021 workshop proceedings.

We expect authors, PC, and the organizing committee to adhere to these policies (http://iccv2021.thecvf.com/node/4#policies), same as the ICCV 2021 the main conference.

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Attending
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TBD

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Workshop Chairs
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Silvio Barra
https://www.silviobarra.com
University of Naples, Federico II, Naples, Italy
Email: silvio.barra@unina.it

Mirko Marras
http://www.mirkomarras.com/
École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
Email: mirko.marras@epfl.ch

Aythami Morales
https://aythami.me/
Universidad Autónoma de Madrid, Madrid, Spain
Email: aythami.morales@uam.es

Vishal Patel
https://engineering.jhu.edu/vpatel36/sciencex_teams/vishalpatel/
Johns Hopkins University, Baltimore, Maryland, US
Email: vpatel36@jhu.edu

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Contacts
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For general enquiries on the workshop, please send an email to silvio.barra@unina.it, mirko.marras@epfl.ch, aythami.morales@uam.es, and vpatel36@jhu.edu (all in copy).

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