Person search detects and retrieves simultaneously a query person across uncropped
scene images captured by multiple non-overlapping cameras. In light of the deep learning …

Object detection (OD) is a crucial computer vision task that has seen the development of
many algorithms and models over the years. While the performance of current OD models …

Composed image retrieval (CIR) is a new and flexible image retrieval paradigm, which can
retrieve the target image for a multimodal query, including a reference image and its …

Existing mainstream multiobject tracking (MOT) methods can be categorized into two
frameworks, including two-and one-stage ones. Two-stage ones divide MOT task into object …

In this work, we construct a large-scale dataset for Ground-to-Aerial Person Search, named
G2APS, which contains 31,770 images of 260,559 annotated bounding boxes for 2,644 …

Deep learning techniques have been demonstrated to surpass preceding cutting-edge
machine learning techniques in recent years, with computer vision being one of the most …

Recently, one-stage trackers that use a joint model to predict both detections and
appearance embeddings in one forward pass received much attention and achieved state-of …

Recent multiobject tracking (MOT) methods usually use very deep neural networks to
achieve competitive accuracy, which inevitably results in degraded inference speed. To …

Person search is an integrated task of multiple sub-tasks such as foreground/background
classification, bounding box regression and person re-identification. Therefore, person …

Weakly supervised person search targets to detect and identify a person with only bounding
box annotations. Recent approaches have focused on learning person relations in a single …