TY  - CONF
AU  - Mickael Cormier
AU  - Andreas Specker
AU  - Julio C. S. Jacques
AU  - Lucas Florin
AU  - Jurgen Metzler
AU  - Thomas B. Moeslund
AU  - Kamal Nasrollahi
AU  - Sergio Escalera
AU  - Jurgen Beyerer
A2  - WACVW
PY  - 2023//
TI  - UPAR Challenge: Pedestrian Attribute Recognition and Attribute-based Person Retrieval – Dataset, Design, and Results
BT  - 2023 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops
SP  - 166
EP  - 175
N2  - In civilian video security monitoring, retrieving and tracking a person of interest often rely on witness testimony and their appearance description. Deployed systems rely on a large amount of annotated training data and are expected to show consistent performance in diverse areas and gen-eralize well between diverse settings w.r.t. different view-points, illumination, resolution, occlusions, and poses for indoor and outdoor scenes. However, for such generalization, the system would require a large amount of various an-notated data for training and evaluation. The WACV 2023 Pedestrian Attribute Recognition and Attributed-based Per-son Retrieval Challenge (UPAR-Challenge) aimed to spot-light the problem of domain gaps in a real-world surveil-lance context and highlight the challenges and limitations of existing methods. The UPAR dataset, composed of 40 important binary attributes over 12 attribute categories across four datasets, was extended with data captured from a low-flying UAV from the P-DESTRE dataset. To this aim, 0.6M additional annotations were manually labeled and vali-dated. Each track evaluated the robustness of the competing methods to domain shifts by training on limited data from a specific domain and evaluating using data from unseen do-mains. The challenge attracted 41 registered participants, but only one team managed to outperform the baseline on one track, emphasizing the task's difficulty. This work de-scribes the challenge design, the adopted dataset, obtained results, as well as future directions on the topic.
UR  - https://ieeexplore.ieee.org/document/10031157
L1  - http://158.109.8.37/files/CSJ2023.pdf
UR  - http://dx.doi.org/10.1109/WACVW58289.2023.00022
N1  - HUPBA
ID  - Mickael Cormier2023
ER  -