Deep learning-based methods for person re-identification: A comprehensive review
D Wu, SJ Zheng, XP Zhang, CA Yuan, F Cheng… - Neurocomputing, 2019 - Elsevier
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 …
fundamental task in intelligent surveillance systems and has widespread application …
Uncertainty-aware joint salient object and camouflaged object detection
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 …
attention, while camouflaged object detection (COD) on the contrary intends to discover the …
Harmonious attention network for person re-identification
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 …
aligned person bounding box images as model input or rely on constrained attention …
Triplet loss in siamese network for object tracking
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 …
vision. For this challenge, more and more researchers pay attention to applying deep …
Unsupervised person re-identification by soft multilabel learning
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 …
attentions due to its potential to address the scalability problem of supervised RE-ID models …
In defense of the triplet loss for person re-identification
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 …
mainly by the advent of large datasets and the adoption of deep convolutional neural …
Pose-driven deep convolutional model for person re-identification
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 …
(ReID). The large pose deformations and the complex view variations exhibited by the …
Aanet: Attribute attention network for person re-identifications
Abstract This paper proposes Attribute Attention Network (AANet), a new architecture that
integrates person attributes and attribute attention maps into a classification framework to …
integrates person attributes and attribute attention maps into a classification framework to …
Transferable joint attribute-identity deep learning for unsupervised person re-identification
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 …
from a separate large set of pairwise labelled training data for every single camera pair. This …