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Person Re-ID Model Training Method Based on Heterogeneous Dual Network and Feature Consistency

A pedestrian re-identification and model training technology, applied in biometric recognition, character and pattern recognition, instruments, etc., can solve problems such as pseudo-label noise interference, improve robustness, overcome triple loss, and enhance heterogeneity The effect of sex and complementarity

Active Publication Date: 2022-07-15
JIANGNAN UNIV
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] For this reason, the technical problem to be solved by the present invention is to overcome the problem that the training process in the prior art is seriously disturbed by pseudo-label noise

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  • Person Re-ID Model Training Method Based on Heterogeneous Dual Network and Feature Consistency
  • Person Re-ID Model Training Method Based on Heterogeneous Dual Network and Feature Consistency
  • Person Re-ID Model Training Method Based on Heterogeneous Dual Network and Feature Consistency

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Embodiment Construction

[0063] The core of the present invention is to provide a domain adaptive pedestrian re-identification model training method, equipment, device and computer storage medium and pedestrian re-identification method based on heterogeneous dual networks and feature consistency, so as to solve the serious problems in the training methods in the prior art. suffers from the problem of pseudo-label noise.

[0064] In order to make those skilled in the art better understand the solution of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. Obviously, the described embodiments are only some, but not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0065] Please refer to Figure 1 an...

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Abstract

The invention discloses a domain adaptive pedestrian re-identification model training method, equipment, device, computer storage medium and pedestrian re-identification method based on heterogeneous dual networks and feature consistency. The invention designs a heterogeneous dual network framework, It contains two asymmetric branches, one of which uses convolution with limited receptive field to obtain local information, the other uses Transformer module to capture long-range dependencies, and uses the mutual learning of heterogeneous dual networks to improve the heterogeneity and complementarity between networks In order to reduce the interference of noise pseudo-labels in the network optimization process, a feature consistency loss is proposed, which does not need to rely on any label information, and pays more attention to the consistency of samples in the feature space In order to enhance the semantic information of the network, the present invention designs an adaptive channel mutual perception module to perform feature extraction on the salient area of ​​pedestrians, thereby improving the accuracy and efficiency of pedestrian re-identification.

Description

technical field [0001] The invention relates to the technical field of machine vision, in particular to a domain adaptive pedestrian re-identification model training method, equipment, device, computer storage medium and pedestrian re-identification method based on heterogeneous dual networks and feature consistency. Background technique [0002] Person re-identification is a very important research topic in the field of machine vision. Traditional person re-identification mainly uses a large amount of labeled image data for training in specific scenes. Although supervised learning methods have achieved good results, obtaining labeled data requires a lot of manpower and material resources. In addition, in practical applications, pedestrians have different appearances, backgrounds, and lighting conditions in different scenes, so that a model trained on one dataset cannot be directly applied to another dataset. The generalization of person re-id models to other domains is a r...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06V40/20G06V40/10G06K9/62G06V10/762G06V10/764G06V10/774
Inventor 孔军周花蒋敏
Owner JIANGNAN UNIV
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