Pedestrian Attribute

Pedestrian attribute recognition (PAR) focuses on automatically identifying various characteristics of pedestrians in images or videos, such as gender, clothing, and carrying objects. Current research emphasizes improving accuracy and robustness, particularly using transformer-based architectures and generative models to better capture attribute interdependencies and handle imbalanced datasets. This field is crucial for advancing applications like video surveillance, autonomous driving, and human-computer interaction by providing richer contextual information for improved object detection, tracking, and behavior prediction. Furthermore, extending PAR to open-vocabulary settings, where unseen attributes can be identified, is a growing area of interest.