Due to the importance of practical applications, unsupervised domain adaptation (UDA)
person re-identification (re-ID) has attracted increasing attention. However, most of existing …

Occlusion perturbation presents a significant challenge in person re-identification (re-ID),
and existing methods that rely on external visual cues require additional computational …

Deep learning techniques have achieved impressive progress in the task of person re-
identification. However, how to generalize a learned model from the source domain to the …

Domain adaptation person re-identification (Re-ID) is a challenging task, which aims to
transfer the knowledge learned from the labeled source domain to the unlabeled target …

Large-scale synthetic traffic image datasets have been widely used to make compensate for
the insufficient data in real world. However, the mismatch in domain distribution between …

Anonymization methods have gained widespread use in safeguarding privacy. However,
conventional anonymization solutions inevitably lead to the loss of semantic information …

Infrared and visible image fusion is an important branch in the field of information fusion.
Fused images can provide more comprehensive and objective interpretations of complex …

Occluded person re-identification is one of the most challenging tasks in security
surveillance. Most existing methods focus on extracting human body features from occluded …

Learning descriptions of individual pedestrian is a common goal of both person re-
identification (P-ReID) and attribute recognition methods, which are typically differentiated …

Due to incomplete appearance features, the identity matching of occluded pedestrians
under multiple cross-camera views is a long-term challenge. Although existing re …