Person re-identification (Re-ID) technology plays an increasingly crucial role in intelligent
surveillance systems. Widespread occlusion significantly impacts the performance of person …

This paper contributes a new high quality dataset for person re-identification, named" Market-
1501". Generally, current datasets: 1) are limited in scale; 2) consist of hand-drawn bboxes …

To help accelerate progress in multi-target, multi-camera tracking systems, we present (i) a
new pair of precision-recall measures of performance that treats errors of all types uniformly …

Existing person re-identification (re-id) methods either assume the availability of well-
aligned person bounding box images as model input or rely on constrained attention …

When considering person re-identification (re-ID) as a retrieval process, re-ranking is a
critical step to improve its accuracy. Yet in the re-ID community, limited effort has been …

Most salient object detection approaches use U-Net or feature pyramid networks (FPN) as
their basic structures. These methods ignore two key problems when the encoder …

Person re-identification is to match pedestrian images from disjoint camera views detected
by pedestrian detectors. Challenges are presented in the form of complex variations of …

Person re-identification (ReID) is an important task in wide area video surveillance which
focuses on identifying people across different cameras. Recently, deep learning networks …

Person re-identification (re-ID) models trained on one domain often fail to generalize well to
another. In our attempt, we present a``learning via translation''framework. In the baseline, we …