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Rethinking the Distribution Gap of Person Re-identification with Camera-based Batch Normalization [article]

Zijie Zhuang, Longhui Wei, Lingxi Xie, Tianyu Zhang, Hengheng Zhang, Haozhe Wu, Haizhou Ai, Qi Tian
2020 arXiv   pre-print
With an effective operator named Camera-based Batch Normalization (CBN), we force the image data of all cameras to fall onto the same subspace, so that the distribution gap between any camera pair is largely  ...  The fundamental difficulty in person re-identification (ReID) lies in learning the correspondence among individual cameras.  ...  Introduction Person re-identification (ReID) aims at matching identities across disjoint cameras.  ... 
arXiv:2001.08680v3 fatcat:cfa3mwbtkbeafamyk52sr3pzm4

Bridging the Distribution Gap of Visible-Infrared Person Re-identification with Modality Batch Normalization [article]

Wenkang Li, Qi Ke, Wenbin Chen, Yicong Zhou
2021 arXiv   pre-print
Visible-infrared cross-modality person re-identification (VI-ReID), whose aim is to match person images between visible and infrared modality, is a challenging cross-modality image retrieval task.  ...  Most existing works integrate batch normalization layers into their neural network, but we found out that batch normalization layers would lead to two types of distribution gap: 1) inter-mini-batch distribution  ...  INTRODUCTION Person re-identification is an image retrieval task, which matches person images across multiple disjoint cameras.  ... 
arXiv:2103.04778v1 fatcat:lyk6opsbrbaatkprr3zsdjchom

Adaptive Domain-Specific Normalization for Generalizable Person Re-Identification [article]

Jiawei Liu, Zhipeng Huang, Kecheng Zheng, Dong Liu, Xiaoyan Sun, Zheng-Jun Zha
2021 arXiv   pre-print
Although existing person re-identification (Re-ID) methods have shown impressive accuracy, most of them usually suffer from poor generalization on unseen target domain.  ...  In this work, we propose a novel adaptive domain-specific normalization approach (AdsNorm) for generalizable person Re-ID.  ...  INTRODUCTION Person re-identification (Re-ID) aims to identify a person-of-interest across non-overlapping camera networks.  ... 
arXiv:2105.03042v2 fatcat:e4ukjdtdnrh7faizuljzjx3fri

Debiased Batch Normalization via Gaussian Process for Generalizable Person Re-Identification [article]

Jiawei Liu, Zhipeng Huang, Liang Li, Kecheng Zheng, Zheng-Jun Zha
2022 arXiv   pre-print
In this paper, we propose a novel Debiased Batch Normalization via Gaussian Process approach (GDNorm) for generalizable person re-identification, which models the feature statistic estimation from BN layers  ...  Generalizable person re-identification aims to learn a model with only several labeled source domains that can perform well on unseen domains.  ...  Natural Science Foundation of China (NSFC) under Grant U19B2038 and 62106245, the University Synergy Innovation Program of Anhui Province under Grants GXXT-2019-025, and the Fundamental Research Funds for  ... 
arXiv:2203.01723v2 fatcat:hotc5igxmnee7k5thy4rzcbcjm

HAVANA: Hierarchical and Variation-Normalized Autoencoder for Person Re-identification [article]

Jiawei Ren, Xiao Ma, Chen Xu, Haiyu Zhao, Shuai Yi
2021 arXiv   pre-print
Person Re-Identification (Re-ID) is of great importance to the many video surveillance systems.  ...  To the best of our knowledge, HAVANA is the first VAE-based framework for person ReID.  ...  Effectiveness of Capturing Variations in Feature Space Random Erasing (RE) [52] is an augmentation method commonly seen in Person Re-ID works.  ... 
arXiv:2101.02568v2 fatcat:ku3nlq3gozgc3izoea6rb2efxa

Learning Multi-scale Features and Batch-normalized Global Features for Person Re-identification

Zongjing Cao, Hyo Jong Lee
2020 IEEE Access  
His more recent research focuses on image retrieval and person reidentification.  ...  The goals of feature-based methods are to find an effective descriptor for pedestrian representations, while the metricbased methods focus on learning an effective feature metric to reduce the distance  ...  PERSON RE-ID BASED ON DEEP LEARNING METHODS After the success of AlexNet [14] in ILSVRC 2012, more and more methods based on deep learning have been proposed for person re-ID.  ... 
doi:10.1109/access.2020.3029594 fatcat:6opjvzmy6bgujewgituqkgv7tm

A Strong Baseline and Batch Normalization Neck for Deep Person Re-identification [article]

Hao Luo, Wei Jiang, Youzhi Gu, Fuxu Liu, Xingyu Liao, Shenqi Lai, Jianyang Gu
2019 arXiv   pre-print
This study explores a simple but strong baseline for person re-identification (ReID). Person ReID with deep neural networks has progressed and achieved high performance in recent years.  ...  The performance surpasses all existing global- and part-based baselines in person ReID. We propose a novel neck structure named as batch normalization neck (BNNeck).  ...  INTRODUCTION Person re-identification (ReID) is widely applied in video surveillance and criminal investigation applications [2] .  ... 
arXiv:1906.08332v1 fatcat:a7k6jhw5qfbgnk5twtgux65bly

Style Normalization and Restitution for Domain Generalization and Adaptation [article]

Xin Jin, Cuiling Lan, Wenjun Zeng, Zhibo Chen
2022 arXiv   pre-print
An effective domain generalizable model is expected to be able to learn feature representations that are both generalizable and discriminative.  ...  For many practical computer vision applications, the learned models usually have high performance on the datasets used for training but suffer from significant performance degradation when deployed in  ...  This work is an extension of our conference paper [37] which is specifically designed for person re-identification.  ... 
arXiv:2101.00588v3 fatcat:q63qby7hijd67jznllgxsz7pwy

Intra-Inter Camera Similarity for Unsupervised Person Re-Identification [article]

Shiyu Xuan, Shiliang Zhang
2021 arXiv   pre-print
Most of unsupervised person Re-Identification (Re-ID) works produce pseudo-labels by measuring the feature similarity without considering the distribution discrepancy among cameras, leading to degraded  ...  This new feature effectively alleviates the distribution discrepancy among cameras and generates more reliable pseudo-labels.  ...  Introduction Person Re-Identification (ReID) aims to match a given query person in an image gallery collected from nonoverlapping camera networks [41, 23] .  ... 
arXiv:2103.11658v1 fatcat:fwiguuaw4bf6zk4p7epnxicqqq

Vehicle Re-Identification in Aerial Imagery Based on Normalized Virtual Softmax Loss

Wenzuo Qiao, Wenjuan Ren, Liangjin Zhao
2022 Applied Sciences  
With the development and popularization of unmanned aerial vehicles (UAVs) and surveillance cameras, vehicle re-identification (ReID) task plays an important role in the field of urban safety.  ...  The experimental results show that comparing with the other softmax-based losses, our method achieves better performance and gets 76.70% and 98.95% in Rank-1 on VRAI and VRAI_AIR dataset, respectively.  ...  Thus, the vehicle re-identification (ReID) technology that distinguishes vehicles by visual features has been developed and plays an important role in urban governance [1] , anti-terrorist attacks [2  ... 
doi:10.3390/app12094731 fatcat:4lrlzzq4avbnvcumebcwmkui5a

Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-identification [article]

Zhun Zhong, Liang Zheng, Zhiming Luo, Shaozi Li, Yi Yang
2019 arXiv   pre-print
This paper considers the domain adaptive person re-identification (re-ID) problem: learning a re-ID model from a labeled source domain and an unlabeled target domain.  ...  Conventional methods are mainly to reduce feature distribution gap between the source and target domains.  ...  An effective approach for addressing UDA is by aligning the feature distributions between the two domains.  ... 
arXiv:1904.01990v1 fatcat:n2ap6rt5pzgupjylzlohixt7gi

Deep Camera-Aware Metric Learning for Person Reidentification

Wei Liu, Ping Liang, Lei Liu, Zhiqiang Hao, Xin Xu, Zhili Zhou
2021 Wireless Communications and Mobile Computing  
Extensive experiments on the three public datasets demonstrated that our method performs competitive results compared to the state-of-the-art person re-id methods.  ...  Person reidentification (re-id) suffers from a challenging issue due to the significant inconsistency of the camera network, including position, view, and brands.  ...  Recently, with the use of deep learning in person re-id, the performance of person re-id methods has improved to an unprecedented level.  ... 
doi:10.1155/2021/8859088 fatcat:t27cv37qtbbrbdagqsh6olhxzu

Cluster-level Feature Alignment for Person Re-identification [article]

Qiuyu Chen, Wei Zhang, Jianping Fan
2020 arXiv   pre-print
Instance-level alignment is widely exploited for person re-identification, e.g. spatial alignment, latent semantic alignment and triplet alignment.  ...  In both theoretical and experimental aspects, our proposed methods can result in more stable and guided optimization towards better representation and generalization for well-aligned embedding.  ...  Related Work Person Re-Identification A large group of person re-identification network focuses on feature alignment.  ... 
arXiv:2008.06810v1 fatcat:6oeqgytzfvffnfkcic3fcwvpf4

Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-Identification

Zhun Zhong, Liang Zheng, Zhiming Luo, Shaozi Li, Yi Yang
2019 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)  
This paper considers the domain adaptive person reidentification (re-ID) problem: learning a re-ID model from a labeled source domain and an unlabeled target domain.  ...  Conventional methods are mainly to reduce feature distribution gap between the source and target domains.  ...  An effective approach for addressing UDA is by aligning the feature distributions between the two domains.  ... 
doi:10.1109/cvpr.2019.00069 dblp:conf/cvpr/Zhong0LL019 fatcat:dxvrbvnmjnfx7gkstjke5rpm34

Parts Semantic Segmentation Aware Representation Learning for Person Re-Identification

Hua Gao, Shengyong Chen, Zhaosheng Zhang
2019 Applied Sciences  
Since three body parts are well aligned, the approach significantly improves person re-identification.  ...  Person re-identification is a typical computer vision problem which aims at matching pedestrians across disjoint camera views.  ...  Many scholars focus on person re-identification based on part alignment [7, 10, 17, 22, 23] .  ... 
doi:10.3390/app9061239 fatcat:vvcpps6m4rfnpgvgqwc34tma24
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