提案されたPCLMP方法は、USVI-ReIDタスクにおいて、共通性と多様性の両方を学習することを可能にします。
The core message of this paper is to propose a novel unsupervised framework for visible-infrared person re-identification (VI-ReID) that addresses the challenges of noisy pseudo-labels and large modality gaps between visible and infrared images.