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 …

Part feature learning is critical for fine-grained semantic understanding in vehicle re-
identification. However, existing approaches directly model part features and global …

Existing object re-identification methods usually utilize backbone networks developed based
on classification tasks to obtain the final object features. However, these backbone networks …

Vehicle re-identification's methods usually exploit the spatial uniform partition strategy via
dividing deep feature maps into several parts. Then each of them is further independently …

Synthetic aperture radar (SAR) ships have rich multi-frequency information, however,
existing SAR ship detection methods mostly only consider high-frequency information …

Object re-identification method is made up of backbone network, feature aggregation, and
loss function. However, most backbone networks lack a special mechanism to handle rich …

As a significant part of Intelligent Transportation System (ITS), vehicle Re-Identification (Re-
ID) aims to retrieve all target vehicle images captured from non-overlapping cameras …

Aerial oriented object detection is a vital task in computer vision, receiving significant
attention for its role in remote image understanding. However, most Convolutional Neural …

Aerial object detection is a crucial task in computer vision because it plays a pivotal role in
understanding remote images. However, most Convolutional Neural Network (CNN) …

Small object detection presents a significant challenge in computer vision and object
detection. The performance of small object detectors is often compromised by a lack of …