Hybrid contrastive learning for unsupervised person re-identification
Unsupervised person re-identification (Re-ID) aims to learn discriminative features without
human-annotated labels. Recently, contrastive learning has provided a new prospect for …
human-annotated labels. Recently, contrastive learning has provided a new prospect for …
Cluster-guided asymmetric contrastive learning for unsupervised person re-identification
Unsupervised person re-identification (Re-ID) aims to match pedestrian images from
different camera views in an unsupervised setting. Existing methods for unsupervised …
different camera views in an unsupervised setting. Existing methods for unsupervised …
Meta pairwise relationship distillation for unsupervised person re-identification
Unsupervised person re-identification (Re-ID) remains challenging due to the lack of ground-
truth labels. Existing methods often rely on estimated pseudo labels via iterative clustering …
truth labels. Existing methods often rely on estimated pseudo labels via iterative clustering …
Global relation-aware contrast learning for unsupervised person re-identification
H Zhang, G Zhang, Y Chen… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The goal of unsupervised person re-identification (Re-ID) is to use unlabeled person images
to learn discriminative features. In recent years, many approaches have adopted clustered …
to learn discriminative features. In recent years, many approaches have adopted clustered …
Structured domain adaptation with online relation regularization for unsupervised person re-id
Unsupervised domain adaptation (UDA) aims at adapting the model trained on a labeled
source-domain dataset to an unlabeled target-domain dataset. The task of UDA on open-set …
source-domain dataset to an unlabeled target-domain dataset. The task of UDA on open-set …
Sharc: Shape and appearance recognition for person identification in-the-wild
Identifying individuals in unconstrained video settings is a valuable yet challenging task in
biometric analysis due to variations in appearances, environments, degradations, and …
biometric analysis due to variations in appearances, environments, degradations, and …
CA-Jaccard: Camera-aware Jaccard Distance for Person Re-identification
Y Chen, Z Fan, Z Chen, Y Zhu - Proceedings of the IEEE …, 2024 - openaccess.thecvf.com
Person re-identification (re-ID) is a challenging task that aims to learn discriminative features
for person retrieval. In person re-ID Jaccard distance is a widely used distance metric …
for person retrieval. In person re-ID Jaccard distance is a widely used distance metric …
Unsupervised person re-identification with multi-label learning guided self-paced clustering
Although unsupervised person re-identification (Re-ID) has drawn increasing research
attention recently, it remains challenging to learn discriminative features without annotations …
attention recently, it remains challenging to learn discriminative features without annotations …
Unsupervised Person Re-Identification: A Review of Recent Works
ABSTRACT Re-identification (Re-ID) is a process that seeks to identify concern individuals
from successive non-overlapping photographs. The area of computer vision has recently …
from successive non-overlapping photographs. The area of computer vision has recently …
The devil in the tail: Cluster consolidation plus cluster adaptive balancing loss for unsupervised person re-identification
Unsupervised person re-identification (Re-ID) is to retrieve pedestrians from different
camera views without supervision information. State-of-the-art methods are usually built …
camera views without supervision information. State-of-the-art methods are usually built …