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 …
Part-based pseudo label refinement for unsupervised person re-identification
Unsupervised person re-identification (re-ID) aims at learning discriminative representations
for person retrieval from unlabeled data. Recent techniques accomplish this task by using …
for person retrieval from unlabeled data. Recent techniques accomplish this task by using …
Omni-scale feature learning for person re-identification
As an instance-level recognition problem, person re-identification (ReID) relies on
discriminative features, which not only capture different spatial scales but also encapsulate …
discriminative features, which not only capture different spatial scales but also encapsulate …
Joint discriminative and generative learning for person re-identification
Person re-identification (re-id) remains challenging due to significant intra-class variations
across different cameras. Recently, there has been a growing interest in using generative …
across different cameras. Recently, there has been a growing interest in using generative …
Pose-guided feature alignment for occluded person re-identification
Persons are often occluded by various obstacles in person retrieval scenarios. Previous
person re-identification (re-id) methods, either overlook this issue or resolve it based on an …
person re-identification (re-id) methods, either overlook this issue or resolve it based on an …
RGB-infrared cross-modality person re-identification via joint pixel and feature alignment
RGB-Infrared (IR) person re-identification is an important and challenging task due to large
cross-modality variations between RGB and IR images. Most conventional approaches aim …
cross-modality variations between RGB and IR images. Most conventional approaches aim …
Learning discriminative features with multiple granularities for person re-identification
G Wang, Y Yuan, X Chen, J Li, X Zhou - Proceedings of the 26th ACM …, 2018 - dl.acm.org
The combination of global and partial features has been an essential solution to improve
discriminative performances in person re-identification (Re-ID) tasks. Previous part-based …
discriminative performances in person re-identification (Re-ID) tasks. Previous part-based …
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 …
Beyond part models: Person retrieval with refined part pooling (and a strong convolutional baseline)
Employing part-level features offers fine-grained information for pedestrian image
description. A prerequisite of part discovery is that each part should be well located. Instead …
description. A prerequisite of part discovery is that each part should be well located. Instead …
Random erasing data augmentation
In this paper, we introduce Random Erasing, a new data augmentation method for training
the convolutional neural network (CNN). In training, Random Erasing randomly selects a …
the convolutional neural network (CNN). In training, Random Erasing randomly selects a …