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 …
Diverse part discovery: Occluded person re-identification with part-aware transformer
Occluded person re-identification (Re-ID) is a challenging task as persons are frequently
occluded by various obstacles or other persons, especially in the crowd scenario. To …
occluded by various obstacles or other persons, especially in the crowd scenario. To …
Dynamic dual-attentive aggregation learning for visible-infrared person re-identification
Visible-infrared person re-identification (VI-ReID) is a challenging cross-modality pedestrian
retrieval problem. Due to the large intra-class variations and cross-modality discrepancy with …
retrieval problem. Due to the large intra-class variations and cross-modality discrepancy with …
Beyond appearance: a semantic controllable self-supervised learning framework for human-centric visual tasks
Human-centric visual tasks have attracted increasing research attention due to their
widespread applications. In this paper, we aim to learn a general human representation from …
widespread applications. In this paper, we aim to learn a general human representation from …
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 …
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 …
KD-PAR: A knowledge distillation-based pedestrian attribute recognition model with multi-label mixed feature learning network
In this paper, a novel knowledge distillation (KD)-based pedestrian attribute recognition
(PAR) model is developed, where a multi-label mixed feature learning network (MMFL-Net) …
(PAR) model is developed, where a multi-label mixed feature learning network (MMFL-Net) …
Attention, please! A survey of neural attention models in deep learning
A de Santana Correia, EL Colombini - Artificial Intelligence Review, 2022 - Springer
In humans, Attention is a core property of all perceptual and cognitive operations. Given our
limited ability to process competing sources, attention mechanisms select, modulate, and …
limited ability to process competing sources, attention mechanisms select, modulate, and …
Mixed high-order attention network for person re-identification
Attention has become more attractive in person re-identification (ReID) as it is capable of
biasing the allocation of available resources towards the most informative parts of an input …
biasing the allocation of available resources towards the most informative parts of an input …
Partmix: Regularization strategy to learn part discovery for visible-infrared person re-identification
Modern data augmentation using a mixture-based technique can regularize the models from
overfitting to the training data in various computer vision applications, but a proper data …
overfitting to the training data in various computer vision applications, but a proper data …