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

Person searches aim to simultaneously locate and identify persons to be queried from
different scenes, which is crucial for disaster emergency management and public safety …

Person search aims to localize and identify specific pedestrians from numerous surveillance
scene images. In this work, we focus on the noise in person search. We categorize the noise …

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 …

Person search aims to localize the queried person from a gallery of uncropped, realistic
images. Unlike re-identification (Re-ID), person search deals with the entire scene image …

The key to efficient person search is jointly localizing pedestrians and learning
discriminative representation for person re-identification (re-ID). Some recently developed …

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

In urban surveillance systems, finding a specific vehicle in video frames efficiently and
accurately has always been an essential part of traffic supervision and criminal investigation …

Person search aims to jointly localize and identify a query person from natural, uncropped
images, which has been actively studied over the past few years. In this paper, we delve into …

With the rapid advancement of deep learning theory and hardware device computing
capacity, computer vision tasks, such as object detection and instance segmentation, have …