[HTML][HTML] Deep metric learning: A survey
M Kaya, HŞ Bilge - Symmetry, 2019 - mdpi.com
Metric learning aims to measure the similarity among samples while using an optimal
distance metric for learning tasks. Metric learning methods, which generally use a linear …
distance metric for learning tasks. Metric learning methods, which generally use a linear …
Attention-aware compositional network for person re-identification
Person re-identification (ReID) is to identify pedestrians observed from different camera
views based on visual appearance. It is a challenging task due to large pose variations …
views based on visual appearance. It is a challenging task due to large pose variations …
Deep transfer learning for person re-identification
Person re-identification (Re-ID) poses a unique challenge to deep learning: how to learn a
deep model with millions of parameters on a small training set of few or no labels. In this …
deep model with millions of parameters on a small training set of few or no labels. In this …
Leader-based multi-scale attention deep architecture for person re-identification
Person re-identification (re-id) aims to match people across non-overlapping camera views
in a public space. This is a challenging problem because the people captured in …
in a public space. This is a challenging problem because the people captured in …
Survey on reliable deep learning-based person re-identification models: Are we there yet?
Intelligent video-surveillance (IVS) is currently an active research field in computer vision
and machine learning and provides useful tools for surveillance operators and forensic …
and machine learning and provides useful tools for surveillance operators and forensic …
Human-in-the-loop person re-identification
Current person re-identification (re-id) methods assume that (1) pre-labelled training data
are available for every camera pair,(2) the gallery size for re-identification is moderate. Both …
are available for every camera pair,(2) the gallery size for re-identification is moderate. Both …
Parameter-free spatial attention network for person re-identification
Global average pooling (GAP) allows to localize discriminative information for recognition
[40]. While GAP helps the convolution neural network to attend to the most discriminative …
[40]. While GAP helps the convolution neural network to attend to the most discriminative …
Deep multi-view feature learning for person re-identification
Person re-identification aims to identify the same pedestrians across different camera views
at different locations. This important yet difficult intelligent video analysis problem remains a …
at different locations. This important yet difficult intelligent video analysis problem remains a …
A novel deep model with multi-loss and efficient training for person re-identification
D Wu, SJ Zheng, WZ Bao, XP Zhang, CA Yuan… - Neurocomputing, 2019 - Elsevier
The purpose of Person re-identification (PReID) is to identify the same individual from the
non-overlapping cameras, the task has been greatly promoted by the deep learning system …
non-overlapping cameras, the task has been greatly promoted by the deep learning system …
Survey on deep learning techniques for person re-identification task
Intelligent video-surveillance is currently an active research field in computer vision and
machine learning techniques. It provides useful tools for surveillance operators and forensic …
machine learning techniques. It provides useful tools for surveillance operators and forensic …