Self Supervised Person Re Identification

Currently, self-supervised representation learning is primarily applied to image classification tasks, but its effectiveness needs to be further validated through visual matching tasks, and person re-identification (ReID) is a suitable test scenario. Self-supervised person ReID aims to extract robust pedestrian feature representations without the need for labeled data, thereby achieving pedestrian matching across different camera views. This task not only enhances the model's generalization capability but also has broad application prospects, such as intelligent surveillance, crowd management, and security protection.