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Deep learning-based methods for person re-identification: A comprehensive review
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 …
Cluster contrast for unsupervised person re-identification
Thanks to the recent research development in contrastive learning, the gap of visual
representation learning between supervised and unsupervised approaches has been …
representation learning between supervised and unsupervised approaches has been …
Unsupervised person re-identification via multi-label classification
The challenge of unsupervised person re-identification (ReID) lies in learning discriminative
features without true labels. This paper formulates unsupervised person ReID as a multi …
features without true labels. This paper formulates unsupervised person ReID as a multi …
Style normalization and restitution for generalizable person re-identification
Existing fully-supervised person re-identification (ReID) methods usually suffer from poor
generalization capability caused by domain gaps. The key to solving this problem lies in …
generalization capability caused by domain gaps. The key to solving this problem lies in …
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 …
Intra-inter camera similarity for unsupervised person re-identification
Most of unsupervised person Re-Identification (Re-ID) works produce pseudo-labels by
measuring the feature similarity without considering the distribution discrepancy among …
measuring the feature similarity without considering the distribution discrepancy among …
Invariance matters: Exemplar memory for domain adaptive person re-identification
This paper considers the domain adaptive person re-identification (re-ID) problem: learning
a re-ID model from a labeled source domain and an unlabeled target domain. Conventional …
a re-ID model from a labeled source domain and an unlabeled target domain. Conventional …
Group-aware label transfer for domain adaptive person re-identification
Abstract Unsupervised Domain Adaptive (UDA) person re-identification (ReID) aims at
adapting the model trained on a labeled source-domain dataset to a target-domain dataset …
adapting the model trained on a labeled source-domain dataset to a target-domain dataset …
Ad-cluster: Augmented discriminative clustering for domain adaptive person re-identification
Abstract Domain adaptive person re-identification (re-ID) is a challenging task, especially
when person identities in target domains are unknown. Existing methods attempt to address …
when person identities in target domains are unknown. Existing methods attempt to address …