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