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Biometric Identification

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Self-Training With Progressive Representation Enhancement for Unsupervised Cross-Domain Person Re-Identification.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
In recent years, person re-identification (re-ID) has achieved relatively good performance, benefiting from the revival of deep neural networks. However, due to the existence of domain bias which refers to the different data distributions between two...

Passive imaging at 250 GHz for detection of face presentation attacks.

Optics express
Face presentation attacks are becoming more efficient since new 3D facial masks are used. Passive terahertz imaging offers specific physical properties that may improve presentation attack detection capabilities. The non-zero transmission capability ...

Batch Coherence-Driven Network for Part-Aware Person Re-Identification.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Existing part-aware person re-identification methods typically employ two separate steps: namely, body part detection and part-level feature extraction. However, part detection introduces an additional computational cost and is inherently challenging...

Unsupervised Cross Domain Person Re-Identification by Multi-Loss Optimization Learning.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Unsupervised cross domain (UCD) person re-identification (re-ID) aims to apply a model trained on a labeled source domain to an unlabeled target domain. It faces huge challenges as the identities have no overlap between these two domains. At present,...

HOReID: Deep High-Order Mapping Enhances Pose Alignment for Person Re-Identification.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Despite the remarkable progress in recent years, person Re-Identification (ReID) approaches frequently fail in cases where the semantic body parts are misaligned between the detected human boxes. To mitigate such cases, we propose a novel High-Order ...

Complementary Pseudo Labels for Unsupervised Domain Adaptation On Person Re-Identification.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
In recent years, supervised person re-identification (re-ID) models have received increasing studies. However, these models trained on the source domain always suffer dramatic performance drop when tested on an unseen domain. Existing methods are pri...

Multi-View Gait Image Generation for Cross-View Gait Recognition.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Gait recognition aims to recognize persons' identities by walking styles. Gait recognition has unique advantages due to its characteristics of non-contact and long-distance compared with face and fingerprint recognition. Cross-view gait recognition i...

Giant Panda Identification.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
The lack of automatic tools to identify giant panda makes it hard to keep track of and manage giant pandas in wildlife conservation missions. In this paper, we introduce a new Giant Panda Identification (GPID) task, which aims to identify each indivi...

Efficiently Updating ECG-Based Biometric Authentication Based on Incremental Learning.

Sensors (Basel, Switzerland)
Recently, the interest in biometric authentication based on electrocardiograms (ECGs) has increased. Nevertheless, the ECG signal of a person may vary according to factors such as the emotional or physical state, thus hindering authentication. We pro...

Deep Learning for Person Re-Identification: A Survey and Outlook.

IEEE transactions on pattern analysis and machine intelligence
Person re-identification (Re-ID) aims at retrieving a person of interest across multiple non-overlapping cameras. With the advancement of deep neural networks and increasing demand of intelligent video surveillance, it has gained significantly increa...