Pedestrian Image

Pedestrian image analysis focuses on extracting meaningful information from images containing pedestrians, aiming for accurate identification, attribute recognition, and privacy preservation. Current research emphasizes developing robust models, often employing transformer architectures and incorporating large language models, to address challenges like cross-domain variations, text-image matching, and viewpoint changes. This field is crucial for advancing applications in surveillance, security, and human-centered computing, while simultaneously tackling critical privacy concerns through innovative anonymization techniques. The development of large-scale, diverse datasets is also a key focus to improve model generalizability and benchmark performance.