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)

October 11-17, 2021 (TBC) - ONLINE EVENT

Workshop Aims and Scope

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, this workshop aims to generate a strong outcome and a wide community dialog.

Workshop Topics

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

Important Dates

  • Submissions: June 19, 2021
  • Notifications: July 22, 2021
  • Camera-Ready: August 7, 2021
  • Workshop: October 11-17, 2021 - ONLINE EVENT

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

Submission Details

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. Authors should consult the workshop paper guidelines 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.

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, same as ICCV 2021 main conference.

Keynote Speakers

Iyad Rahwan

Iyad Rahwan
Max Planck Institute for Human Development (Germany)

Arun Ross

Arun Ross
Michigan State University (US)

Attending

The registration to the workshop is managed by the ICCV 2021 Main Conference at http://iccv2021.thecvf.com/node/3.

Committees

Workshop Chairs

Program Committee

  • Andrea F. Abate, University of Salerno
  • Fernando Alonso-Fernandez, Halmstad University
  • Paola Barra, University of Salerno
  • Carmen Bisogni, University of Salerno
  • Modesto Castrillon Santana, Universidad de Las Palmas de Gran Canaria
  • Jacqueline Cavazos, University of California Irvine
  • Celia Cintas, IBM
  • Naser Damer, Fraunhofer Institute for Computer Graphics Research IGD
  • Maria De Marsico, Sapienza University of Rome
  • Julian Fierrez, Universidad Autonoma de Madrid
  • David Freire-Obregón, Universidad de Las Palmas de Gran Canaria
  • Chiara Galdi, EURECOM
  • Marta Gomez-Barrero, Hochschule Ansbach
  • Hatice Gunes, University of Cambridge
  • Jungseock Joo, University of California Los Angeles
  • Sinan Kalkan, Middle East Technical University
  • Pawel Korus, New York University
  • Emanuela Marasco, George Mason University
  • Shruti Nagpal, IIIT-Delhi
  • Michele Nappi, University of Salerno
  • Fabio Narducci, University of Salerno
  • Tempestt Neal, University of South Florida
  • Javier Ortega-Garcia, Universidad Autonoma de Madrid
  • Jonathon Phillips, National Institute of Standards and Technology
  • Alessandro Sebastian Podda, University of Cagliari
  • Florin Pop, University Politehnica of Bucharest
  • Hugo Proença, Univeristy of Beira Interior
  • Kiran Raja, Norwegian University of Science and Technology
  • Christian Rathgeb, Hochschule Darmstadt
  • Ajita Rattani, Wichita State University
  • Daniel Riccio, University of Naples Federico II
  • Thomas Swearingen, Michigan State University
  • Massimo Tistarelli, University of Sassari
  • Ruben Tolosana, Universidad Autonoma de Madrid
  • Ruben Vera-Rodriguez, Universidad Autonoma de Madrid

Contacts

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).