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ACM SIGMM Interest List <[log in to unmask]>
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From:
"Julio Jacques Jr." <[log in to unmask]>
Date:
Thu, 23 Apr 2020 12:02:08 +0200
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Apologies if you receive multiple copies of this CFP
--------------------------

We cordially invite you to participate to our

*ECCV 2020 ChaLearn Looking at People Fair Face Recognition Workshop and
Challenge*

*Challenge* - http://chalearnlap.cvc.uab.es/challenge/38/description/
We present a new collected dataset with 13k images from 3k new subjects
along with a reannotated version of IJB-C (140k images from 3.5k subjects),
totalling 153k facial images from 6.1k unique identities. Both databases
have been accurately annotated for gender and skin colour (protected
attributes) as well as for age group, eyeglasses, head pose, image source
and face size. *The task:* Participants will be asked to develop their fair
face verification method aiming for a reduced bias in terms of gender and
skin color (protected attributes). The method developed by the participants
will need to output a list of confidence scores given test ID pairs to be
verified. Both the bias and accuracy of the method will be evaluated using
the provided face dataset. The final ranking of each model will depend both
on its bias and accuracy with the emphasis on bias.

- Start of the challenge (development phase): April 7th, 2020
- Start of test phase: June 22th, 2020
- End of the challenge: July 1st, 2020
- Fact sheets and code submission: July 4th, 2020
- Release of final results: July 12th, 2020

Winning teams will receive a travel grant from our sponsors to attend and
present their solutions at the ECCV workshop of the challenge.
Participants' methods are also welcome as a paper submission to the
workshop. Top ranked participants will be also invited to join a paper
preparation on the topic of the challenge to a relevant venue (i.e.
CVPR/TPAMI).

*Workshop* - http://chalearnlap.cvc.uab.es/workshop/37/description/
The workshop will focus on bias analysis and mitigation methodologies,
which will result in more fair face recognition and analysis systems. These
advances will have a direct impact within society's equality of
opportunity. In this proposal we plan to provide a comprehensive up to date
review on fair face recognition and analysis research. We find of crucial
interest to centralize ideas, discuss them and push the field to advance
towards more fair systems for the good of society. Complementary to that,
we will also contribute pushing research in the field by releasing a large
annotated dataset for fair face verification and running an associated
challenge. Paper submission is independent to challenge participation.

- Paper submission: July 7th, 2020
- Notification to authors: July 28th, 2020
- Camera-ready: September 4th, 2020

*ORGANIZATION & SPONSORS*
Sergio Escalera, Computer Vision Center (UAB) and University of Barcelona,
Spain
Rama Chellappa, University of Maryland, United States of America
Eduard Vazquez, Anyvision, Belfast, Northern Ireland
Neil Robertson, Queen’s University Belfast / Anyvision, Belfast, Northern
Ireland
Sankha Subhra Mukherjee, Anyvision, Belfast, Northern Ireland
Pau Buch-Cardona, Computer Vision Center (UAB) and University of Barcelona,
Spain
Tomas Sixta, Belfast, Northern Ireland
Julio C. S. Jacques Junior, Universitat Oberta de Catalunya (UOC) and
Computer Vision Center (CVC/UAB), Spain

*INVITED SPEAKERS*
Rama Chellappa, University of Maryland
Kate Saenko, Boston University
Matthew Turk, University of California
Walter J. Scheirer, University of Notre Dame
Alice O’Toole, University of Texas at Dallas
Dimitris Metaxas, Rutgers University
Olga Russakovsky, Princeton University
Judy Hoffman, Georgia Tech

*This event is sponsored by: *
ChaLearn - http://chalearnlap.cvc.uab.es/
Anyvision - https://www.anyvision.co/



-- 
Julio C. S. Jacques Junior
Postdoctoral researcher at Universitat Oberta de Catalunya (UOC), Spain
Research collaborator within HuPBA group at University of Barcelona (UB)
and
Computer Vision Center (CVC), Spain


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