Person re-identification (Re-ID) aims at retrieving a person of interest across multiple non-
overlapping cameras. With the advancement of deep neural networks and increasing …

In recent years, person re-identification (ReID) has received much attention since it is a
fundamental task in intelligent surveillance systems and has widespread application …

Visual salient object detection (SOD) aims at finding the salient object (s) that attract human
attention, while camouflaged object detection (COD) on the contrary intends to discover the …

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 …

Object tracking is still a critical and challenging problem with many applications in computer
vision. For this challenge, more and more researchers pay attention to applying deep …

Although unsupervised person re-identification (RE-ID) has drawn increasing research
attentions due to its potential to address the scalability problem of supervised RE-ID models …

In the past few years, the field of computer vision has gone through a revolution fueled
mainly by the advent of large datasets and the adoption of deep convolutional neural …

Abstract This paper proposes Attribute Attention Network (AANet), a new architecture that
integrates person attributes and attribute attention maps into a classification framework to …

Feature extraction and matching are two crucial components in person Re-Identification
(ReID). The large pose deformations and the complex view variations exhibited by the …

Most existing person re-identification (re-id) methods require supervised model learning
from a separate large set of pairwise labelled training data for every single camera pair. This …