VISUAL RECOGNITION OF FAMILIES IN THE WILD

Recognizing Families In the Wild

A 2020 IEEE FG Data Challenge Workshop

Joseph Robinson
Dec 2, 2019 · 5 min read

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Overview

We are happy to announce the 4th large-scale kinship recognition data competition, RFIW, in conjunction with 2020 AMFG. RFIW has x using the largest and most comprehensive database for visual kinship recognition, the Families in the Wild (FIW) dataset.

Submissions will be peer-reviewed, with accepted workshop papers part of the 2020 AMFG proceedings. The authors will present (oral or poster) at the workshop at the 2020 AMFG conference. The 2020 AMFG is on 18–22 May in Buenos Aire, Argentina.


What’s new for RFIW-2020?

The new components of RFIW2020 are listed as follows:

New challenges!

Along with the traditional verification task, RFIW2020 will support two new tracks, tri-subject verification, and large-scale search-and-retrieval.

Tri-subject verification (T-2) focuses on a slightly different view of kinship verification — the goal is to decide whether a child is related to a pair of parents. This paradigm follows a 2-to-1 verification protocol with all rules mimicking that of verification, with the difference being one item from each pair consisting of a man and woman, and the question then is “are these the parents.” Tri-subject is a natural extension of the verification task, as it is a more realistic assumption, as knowing one parent typically means information of the other is accessible.

Large-scale search-and-retrieval (T-3) will mimic that of template-based, open-sets protocols provided by benchmarks like IJB-B. A gallery of distractors and real relatives, with the task of ranking, faces are then sorted by the likelihood of being kin (i.e., blood relative). T-3 closely mimics the real-world application of missing children. For instance, a child is found online, exploited by the unknown, and it is unlikely not in any database; however, a family member likely is– identify a family member, determine the identity of the unknown. Additionally, reuniting families split from the modern-day refugee crisis. Provided technology to recognize family members via visual media, we could then match families together from different camps at the cost of a low-cost security video-feed.

Resources. Benchmarks, along with results of prior RFIW, will be provided; also, source code to reproduce and demonstrate each task end-to-end will be made available. Thus, enabling newcomers while challenging the experts. We will also call for general paper submissions of new work to expand the types of problems and the use-case of the FIW dataset.

Call for Papers!

In addition to the three organized task evaluations, we will also add this piece to RFIW2020 (i.e., papers that use FIW in novel ways). The main reason we added this is to challenge researchers to propose novel technology besides the task evaluations. We found the assessments to be great for structuring existing problems such that researchers and practitioners can make fair comparisons of algorithms. However, this limits the scope of the problems of automatic kinship recognition. From this, we expect the light to shed on one or more of the following ways:


Important Dates

1st CFP: 3 Nov 2019

Challenge begins: 8 Nov

Challenge ends: 13 Jan 2020

Papers due: 20 Jan

Author notifications (i.e., oral or poster): 5 Feb

Camera Ready due: 26 Feb

Paper presentations (general and top challenge submissions) & awards at FG Conference: May 18–22 (TBD)


Information for Authors

Submissions made via the workshop’s CMT website:
https://cmt3.research.microsoft.com/RFIW2020/Submission/Index

Guidelines of IEEE FG: https://fg2020.org/instructions-of-paper-submission-for-review/


People

Honorary Chairs

Rama Chellappa, University of Maryland

Matthew A. Turk, Toyota Technological Institute at Chicago (TTIC)

General Chair

Yun Fu, Northeastern University

Workshop Chairs

Joseph Robinson, Northeastern University

Ming Shao, University of Massachusetts (Dartmouth)

Siyu Xia, Southeast University (China), Nanjing

Mike Stopa, Konica Minolta

Samson Timoner, ISMConnect

Yu Yin, Northeastern University

Web and Publicity Co-Chairs

Zaid Khan, Northeastern University


That Publication

Want a vaguely-named publication for your fiction, non-fiction, essays, prose, and more? Looking for an editor to challenge you? Want a chance to say, “Oh, I was just published… Yeah, That Publication!” Welcome to THAT PUBLICATION, your home for every story.

Joseph Robinson

Written by

PhD student of Yun Fu and SMILE Lab Northeastern U. Focus: applied ML w emphasis on vision, big data, automatic face understanding. https://www.jrobsvision.com

That Publication

Want a vaguely-named publication for your fiction, non-fiction, essays, prose, and more? Looking for an editor to challenge you? Want a chance to say, “Oh, I was just published… Yeah, That Publication!” Welcome to THAT PUBLICATION, your home for every story.

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