Re-identification (re-ID) aims to identify a person's images across different cameras.
However, the domain differences between different datasets make it a challenge for re-ID …

Person re-identification (ReID) based on heterogeneous data aims to search for the same
pedestrian from different modalities. The existing unsupervised heterogeneous ReID …

Deep learning has achieved remarkable success in recent years; however, deep learning
methods face significant challenges on long-tailed datasets, which are prevalent in real …

无监督行人重识别因其在真实监控场景中具备良好的可扩展性而备受关注. 现有的无监督行人重
识别方法主要通过基础骨干网络获取粗略的全局特征来训练网络, 很少利用局部细化分支与全局 …

Deciding the signal length is an important challenge for one-class time-series classification
(OCTSC). This paper aims to develop an OCTSC algorithm that does not require model …

Unsupervised pedestrian re-identification (re-ID) is not merely a visual recognition task; it
represents a significant sub-field within the domain of pattern recognition. Despite the …

Recent studies have shown the effectiveness of generating pseudo-labels by measuring
feature similarity in unsupervised person re-identification (ReID). However, most of these …

Person re-identification (re-ID) aims at determining whether there is a specific person in
image sets or videos via computer vision technology. State-of-the-art unsupervised re-ID …

Clothing change person re-identification (CC-ReID) aims to match images of the same
person wearing different clothes across diverse scenes. Leveraging biological features or …

Recently, unsupervised person re-identification (Re-ID) has gained much attention due to its
important practical significance in real-world application scenarios without pairwise labeled …