Generate And Adjust: A Novel Framework For Semi-Supervised Pedestrian Attribute Recognition

Conventional pedestrian attribute recognition methods typically rely on the assumption that enough well-labeled training samples are available. However, it is hard to be satisfied due to the unaffordable cost of human annotation, especially on big surveillance data. To address this problem, we propose a novel task-semi-supervised pedestrian attribute recognition (Semi-PAR), in which only a few lim...