Pedestrian Attribute Recognition and Attributed-based Person Retrieval Challenge Call for Papers

We cordially invite you to participate in our 
WACV'24 Pedestrian Attribute Recognition and Attributed-based Person Retrieval Challenge

Challenge description: The challenge will use an extension of the UPAR
Dataset, which consists of images of pedestrians annotated for 40
binary attributes. For deployment and long-term use of
machine-learning algorithms in a surveillance context, the algorithms
must be robust to domain gaps that occur when the environment
changes. This challenge aims to spotlight the problem of domain gaps
in a real-world surveillance context and highlight the challenges and
limitations of existing methods to provide a direction for future
research. It will be divided in two competition tracks:

    Track 1: Pedestrian Attribute Recognition: The task is to train an
    attribute classifier that accurately predicts persons’ semantic
    attributes, such as age or clothing information, under domain
    shifts.

    Track 2: Attribute-based Person Retrieval: Attribute-based person
    retrieval aims to find persons in a huge database of images called
    gallery that match a specific attribute description. The goal of
    this track is to develop an approach that takes binary attribute
    queries and gallery images as input and ranks the images according
    to their similarity to the query.


Challenge webpage:  https://chalearnlap.cvc.uab.cat/challenge/57/description/

Tentative Schedule:

    Start of the Challenge (development phase): Sep 13, 2023

    Start of test phase: Oct 16, 2023

    End of the Challenge: Oct 27, 2023

    Release of final results: Nov 3, 2023


Participants are invited to submit their contributions to the
associated 4rd Workshop on Real-World Surveillance: Applications and
Challenges (RWS @ WACV2024) (https://vap.aau.dk/rws-wacv2024/),
independently of their rank position.

ORGANIZATION

Sergio Escalera,Computer Vision Center (CVC) and University of
Barcelona, Spain

Mickael Cormier, Fraunhofer IOSB and Karlsruhe Institute of Technology
(KIT), Germany

Kamal Nasrollahi, Milestone Systems and Aalborg University, Denmark

Andreas Specker, Karlsruhe Institute of Technology (KIT), Germany and
Fraunhofer IOSB

Julio C. S. Jacques Junior, University of Barcelona and Computer
Vision Center (CVC), Spain

Jürgen Beyerer, Karlsruhe Institute of Technology (KIT), Germany
and Fraunhofer IOSB
Jürgen Metzler, Fraunhofer IOSB, Germany