Text-Image Person Re-identification (TIReID) aims to retrieve the image corresponding to
the given text query from a pool of candidate images. Existing methods employ prior …

Text-based person retrieval is a challenging task that aims to search pedestrian images with
the same identity according to language descriptions. Current methods usually …

Incomplete multi-view clustering aims to exploit the information of multiple incomplete views
to partition data into their clusters. Existing methods only utilize the pair-wise sample …

Unsupervised hashing methods have attracted widespread attention with the explosive
growth of large-scale data, which can greatly reduce storage and computation by learning …

Incomplete multi-view clustering primarily focuses on dividing unlabeled data into
corresponding categories with missing instances, and has received intensive attention due …

Occluded person re-identification (re-ID) presents a challenging task due to occlusion
perturbations. Although great efforts have been made to prevent the model from being …

Multi-view clustering is a long-standing important task, however, it remains challenging to
exploit valuable information from the complex multi-view data located in diverse high …

Text-based person search (TBPS) is a challenging task that aims to search pedestrian
images with the same identity from an image gallery given a query text. In recent years …

Due to the scarcity of manually annotated data required for fine-grained video
understanding, few-shot fine-grained (FS-FG) action recognition has gained significant …

Advanced deep convolutional neural networks (CNNs) have shown great success in video-
based person re-identification (Re-ID). However, they usually focus on the most obvious …