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Person re-identification: A retrospective on domain specific open challenges and future trends
Abstract Person Re-Identification (Re-ID) is a critical aspect of visual surveillance systems,
which aims to automatically recognize and locate individuals across a multi-camera network …
which aims to automatically recognize and locate individuals across a multi-camera network …
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 …
Transformer for object re-identification: A survey
Abstract Object Re-identification (Re-ID) aims to identify specific objects across different
times and scenes, which is a widely researched task in computer vision. For a prolonged …
times and scenes, which is a widely researched task in computer vision. For a prolonged …
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 visible-infrared person re-identification via progressive graph matching and alternate learning
Unsupervised visible-infrared person re-identification is a challenging task due to the large
modality gap and the unavailability of cross-modality correspondences. Cross-modality …
modality gap and the unavailability of cross-modality correspondences. Cross-modality …
Cdul: Clip-driven unsupervised learning for multi-label image classification
This paper presents a CLIP-based unsupervised learning method for annotation-free multi-
label image classification, including three stages: initialization, training, and inference. At the …
label image classification, including three stages: initialization, training, and inference. At the …
Modality synergy complement learning with cascaded aggregation for visible-infrared person re-identification
Abstract Visible-Infrared Re-Identification (VI-ReID) is challenging in image retrievals. The
modality discrepancy will easily make huge intra-class variations. Most existing methods …
modality discrepancy will easily make huge intra-class variations. Most existing methods …
Adaptive memorization with group labels for unsupervised person re-identification
Re-identification (re-ID) aims to identify a person's images across different cameras.
However, the domain differences between different datasets make it a challenge for re-ID …
However, the domain differences between different datasets make it a challenge for re-ID …
Learning to purification for unsupervised person re-identification
Unsupervised person re-identification is a challenging and promising task in computer
vision. Nowadays unsupervised person re-identification methods have achieved great …
vision. Nowadays unsupervised person re-identification methods have achieved great …
A real-time memory updating strategy for unsupervised person re-identification
Recently, clustering-based methods have been the dominant solution for unsupervised
person re-identification (ReID). Memory-based contrastive learning is widely used for its …
person re-identification (ReID). Memory-based contrastive learning is widely used for its …