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DeepPFCN: Deep Parallel Feature Consensus Network For Person Re-Identification [article]

Shubham Kumar Singh, Krishna P Miyapuram, Shanmuganathan Raman
2019 arXiv   pre-print
The feature representations learned by DeepPFCN are more robust for the person re-identification task, as we learn discriminative scale-specific features and maximize multi-scale feature fusion selections  ...  We propose Deep Parallel Feature Consensus Network (DeepPFCN), a novel network architecture that learns multi-scale person appearance features using convolutional neural networks.  ...  The number of training iterations is 80 epochs for all the person re-identification datasets. Cross-Entropy loss is used during training.  ... 
arXiv:1911.07776v1 fatcat:ua3mnshdbzhcrilicqpncdxuh4

Multi-Level Joint Feature Learning for Person Re-Identification

Shaojun Wu, Ling Gao
2020 Algorithms  
The experiments have proved that our deep learning model based on multi-level feature fusion works well in person re-identification.  ...  In person re-identification, extracting image features is an important step when retrieving pedestrian images.  ...  Therefore, in this paper, the local features and global features are jointly learned for person re-identification.  ... 
doi:10.3390/a13050111 fatcat:wmnp4askbngmlc6zzqacwc4hpi

Pose Guided Gated Fusion for Person Re-identification

Amran Bhuiyan, Yang Liu, Parthipan Siva, Mehrsan Javan, Ismail Ben Ayed, Eric Granger
2020 2020 IEEE Winter Conference on Applications of Computer Vision (WACV)  
Person re-identification is an important yet challenging problem in visual recognition.  ...  Despite the recent advances with deep learning (DL) models for spatio-temporal and multi-modal fusion, re-identification approaches often fail to leverage the contextual information (e.g., pose and illumination  ...  State-of-the art approaches for person re-identification typically learning global appearance features in an end-toend fashion through various metric learning losses [10, 33, 56] .  ... 
doi:10.1109/wacv45572.2020.9093370 dblp:conf/wacv/BhuiyanLSJAG20 fatcat:2pxr7d6bybfv5pm33rlwpv2tye

Video-based Person Re-identification Based on Distributed Cloud Computing

Chengyan Zhong, Xiaoyu Jiang, Guanqiu Qi
2021 Journal of Artificial Intelligence and Technology  
Person re-identification(Re-ID) has been a hot research issues in the field of computer vision.  ...  re-identification task.  ...  The network level of Re-ID is Transmit it to the next node 6: end for 7: end for Video-based Person Re-identification deep.  ... 
doi:10.37965/jait.2020.0058 fatcat:wnml4yhs35bfjntjnktgzkmcoy

Multi-scale 3D Convolution Network for Video Based Person Re-Identification [article]

Jianing Li, Shiliang Zhang, Tiejun Huang
2018 arXiv   pre-print
The other stream in our network is implemented with a 2D CNN for spatial feature extraction. The spatial and temporal features from two streams are finally fused for the video based person ReID.  ...  This paper proposes a two-stream convolution network to extract spatial and temporal cues for video based person Re-Identification (ReID).  ...  Introduction Current researches on person Re-Identification (ReID) mainly focus on two lines of tasks depending on still images and video sequences, respectively.  ... 
arXiv:1811.07468v1 fatcat:chly76zuurcrtnajqzh5dtvvvm

A Color/Illuminance Aware Data Augmentation and Style Adaptation Approach to Person Re-identification

Zhouchi Lin, Chenyang Liu, Wenbo Qi, S. C. Chan
2021 IEEE Access  
This calls for a new approach to fuse the augmented data and hence the associated features for metric learning.  ...  CONCLUSION An effective CIADA and local metric learning approach to person re-identification problem has been presented.  ... 
doi:10.1109/access.2021.3100571 fatcat:vetccagaunhlflc6nmakob4y3a

Multi-Scale 3D Convolution Network for Video Based Person Re-Identification

Jianing Li, Shiliang Zhang, Tiejun Huang
2019 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
The other stream in our network is implemented with a 2D CNN for spatial feature extraction. The spatial and temporal features from two streams are finally fused for the video based person ReID.  ...  This paper proposes a two-stream convolution network to extract spatial and temporal cues for video based person ReIdentification (ReID).  ...  Introduction Current researches on person Re-Identification (ReID) mainly focus on two lines of tasks depending on still images and video sequences, respectively.  ... 
doi:10.1609/aaai.v33i01.33018618 fatcat:3rise2zyi5dadpkmicfdwzngrq

A Dual-Path Model With Adaptive Attention For Vehicle Re-Identification [article]

Pirazh Khorramshahi, Amit Kumar, Neehar Peri, Sai Saketh Rambhatla, Jun-Cheng Chen, Rama Chellappa
2019 arXiv   pre-print
In recent years, attention models have been extensively used for person and vehicle re-identification. Most re-identification methods are designed to focus attention on key-point locations.  ...  In this paper, we present a novel dual-path adaptive attention model for vehicle re-identification (AAVER).  ...  This research is supported in part by the Northrop Grumman Mission Systems Research in Applications for Learning Machines (REALM) initiative, It is also supported in part by the Office of the Director  ... 
arXiv:1905.03397v3 fatcat:xv6bqswmojd3jmavsmeccua3h4

Cross-Modal Distillation for RGB-Depth Person Re-Identification [article]

Frank Hafner, Amran Bhuiyan, Julian F. P. Kooij, Eric Granger
2022 arXiv   pre-print
Our main contribution is a novel method for cross-modal distillation for robust person re-identification, which learns a shared feature representation space of person's appearance in both RGB and depth  ...  Person re-identification is a key challenge for surveillance across multiple sensors.  ...  Conventional approaches for person re-identification from a single modality can be catego-rized into two main groups -direct methods with hand-crafted descriptors or learned features and metric learning  ... 
arXiv:1810.11641v3 fatcat:lwrhwae66vgsbnj3rvtlcdl63a

RGB-Depth Cross-Modal Person Re-identification

Frank M. Hafner, Amran Bhuiyan, Julian F. P. Kooij, Eric Granger
2019 2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)  
Our main contribution is a novel cross-modal distillation network for robust person re-identification, which learns a shared feature representation space of person's appearance in both RGB and depth images  ...  Person re-identification is a key challenge for surveillance across multiple sensors.  ...  Conventional approaches for person re-identification from a single modality can be categorized into two main groups -direct methods with hand-crafted descriptors or learned features and metric learning  ... 
doi:10.1109/avss.2019.8909838 dblp:conf/avss/HafnerBKG19 fatcat:levi4qaznjgfvlxgqaf2tkpskq

Clothing Change Aware Person Identification

Jia Xue, Zibo Meng, Karthik Katipally, Haibo Wang, Kees van Zon
2018 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)  
We develop a person identification approach -Clothing Change Aware Network (CCAN) for the task of clothing assisted person identification.  ...  With a pair of two person images as input, CCAN simultaneously performs a verification task to detect change in clothing and an identification task to predict person identity.  ...  Concluding Remarks This paper presents CCAN, a deep learning approach for person identification in the wild.  ... 
doi:10.1109/cvprw.2018.00285 dblp:conf/cvpr/XueMKWZ18 fatcat:l7zuy3s6yfhtdml7jcq4e4bg3q

Improving Slice-Based Model for Person Re-ID with Multi-Level Representation and Triplet-Center Loss

Yusheng ZHANG, Zhiheng ZHOU, Bo LI, Yu HUANG, Junchu HUANG, Zengqun CHEN
2019 IEICE transactions on information and systems  
Person Re-Identification has received extensive study in the past few years and achieves impressive progress.  ...  Also, our proposed method creatively introduces a triplet-center loss to elaborate combined loss function, which helps train the joint-learning network.  ...  DukeMTMC-reID It is a subset of the DukeMTMC which is designed for person re-identification.  ... 
doi:10.1587/transinf.2019edp7067 fatcat:nwedriuksbhb7lwbv3fufmcs4q

HAT: Hierarchical Aggregation Transformers for Person Re-identification [article]

Guowen Zhang and Pingping Zhang and Jinqing Qi and Huchuan Lu
2021 arXiv   pre-print
Recently, with the advance of deep Convolutional Neural Networks (CNNs), person Re-Identification (Re-ID) has witnessed great success in various applications.  ...  In this work, we take advantages of both CNNs and Transformers, and propose a novel learning framework named Hierarchical Aggregation Transformer (HAT) for image-based person Re-ID with high performance  ...  INTRODUCTION Person Re-identification (Re-ID) aims to retrieve the same person under different cameras, places and times.  ... 
arXiv:2107.05946v2 fatcat:i6qdb4nibnh5rl2ldmaz42usoq

Multi-Level Fusion Model for Person Re-Identification by Attribute Awareness

Shengyu Pei, Xiaoping Fan
2022 Algorithms  
In this study, we propose a person re-recognition network with part-based attribute-enhanced features.  ...  The multi-task module, local module, and global module are used in parallel for feature extraction.  ...  For the two sets D and E, we use a bidirectional parallel approach to solve the person re-identification problem [26, 27] . Therefore, we can define the following three functions.  ... 
doi:10.3390/a15040120 fatcat:b6cakzqi6fasth77suk4pvn634

Fused Deep Neural Network based Transfer Learning in Occluded Face Classification and Person re-Identification [article]

Mohamed Mohana, Prasanalakshmi B, Salem Alelyani, Mohammed Saleh Alsaqer
2022 arXiv   pre-print
Recent period of pandemic has brought person identification even with occluded face image a great importance with increased number of mask usage.  ...  Various transfer learning methods were tested, and the results show that MobileNet V2 with Gated Recurrent Unit(GRU) performs better than any other Transfer Learning methods, with a perfect accuracy of  ...  Figure 6 Facial Landmark detection The detected face is selected for preliminary identification which seeks for a matching score in the re-identification process, the final step of the prototype.  ... 
arXiv:2205.07203v1 fatcat:tknsvlh7ofcsdizcgedutwiqaa
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