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Context-Aware Graph Convolution Network for Target Re-identification
[article]
2021
arXiv
pre-print
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Most existing re-identification methods focus on learning robust and discriminative features with deep convolution networks. ...
In this paper, we present a novel Context-Aware Graph Convolution Network (CAGCN), where the probe-gallery relations are encoded into the graph nodes and the graph edge connections are well controlled ...
Overall, our contribution is threefold: • We propose a novel Context-Aware Graph Convolution Network (CAGCN) for target re-identification tasks. ...
arXiv:2012.04298v3
fatcat:2ylhyvu3qne6xgbbz7f2khd7u4
2020 Index IEEE Transactions on Image Processing Vol. 29
2020
IEEE Transactions on Image Processing
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Liu, D., +, TIP 2020 3695-3706
Context-Adaptive Neural Network-Based Prediction for Image Compres-
sion. Dumas, T., +, TIP 2020 679-693
Context-Interactive CNN for Person Re-Identification. ...
., +, TIP 2020
947-958
CDPM: Convolutional Deformable Part Models for Semantically Aligned
Person Re-Identification. ...
doi:10.1109/tip.2020.3046056
fatcat:24m6k2elprf2nfmucbjzhvzk3m
Table of contents
2021
IEEE transactions on circuits and systems for video technology (Print)
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Wang 3128 Attention-Aligned Network for Person Re-Identification ................................... S. Lian, W. Jiang, and H. ...
Xu 3105 Noise Augmented Double-Stream Graph Convolutional Networks for Image Captioning ................................. ............................................................................... ...
doi:10.1109/tcsvt.2021.3094682
fatcat:zmlbhxebxrbslbsi47cuwq7eqm
2020 Index IEEE Transactions on Circuits and Systems for Video Technology Vol. 30
2020
IEEE transactions on circuits and systems for video technology (Print)
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., +, TCSVT Jan. 2020 104-116 Complementation-Reinforced Attention Network for Person Re-Identification. ...
., +, TCSVT Dec. 2020 4453-4466
Convolution
Accelerator-Aware Pruning for Convolutional Neural Networks. ...
A Memory-Efficient Hardware Architecture for Connected Component Labeling in Embedded System. ...
doi:10.1109/tcsvt.2020.3043861
fatcat:s6z4wzp45vfflphgfcxh6x7npu
Graph Convolutional Tracking
2019
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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Specifically, the GCT jointly incorporates two types of Graph Convolutional Networks (GCNs) into a siamese framework for target appearance modeling. ...
To comprehensively leverage the spatial-temporal structure of historical target exemplars and get benefit from the context information, in this work, we present a novel Graph Convolutional Tracking (GCT ...
[56] utilize graph convolutional operator to learn probe-gallery relationships for person re-identification. ...
doi:10.1109/cvpr.2019.00478
dblp:conf/cvpr/GaoZX19
fatcat:gbvsjl2szjccnciwhajkynipwe
2021 Index IEEE Transactions on Image Processing Vol. 30
2021
IEEE Transactions on Image Processing
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The Author Index contains the primary entry for each item, listed under the first author's name. ...
., +, TIP 2021 8236-8250 An End-to-End Foreground-Aware Network for Person Re-Identification. ...
., +, TIP 2021 92-107 Robust and Efficient Graph Correspondence Transfer for Person Re-Identification. ...
doi:10.1109/tip.2022.3142569
fatcat:z26yhwuecbgrnb2czhwjlf73qu
Table of contents
2020
IEEE Transactions on Image Processing
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Qin 2845 Context-Interactive CNN for Person Re-Identification ....... W.Song, S. Li, T. Chang, A. Hao, Q. Zhao, and H. ...
Chul Ye 1856 Attention-Aware Multi-Task Convolutional Neural Networks ................................ K. Lyu, Y. Li, and Z. ...
doi:10.1109/tip.2019.2940372
fatcat:h23ul2rqazbstcho46uv3lunku
2021 Index IEEE Transactions on Multimedia Vol. 23
2021
IEEE transactions on multimedia
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The Author Index contains the primary entry for each item, listed under the first author's name. ...
., +, TMM 2021 3306-3317 Anisotropic Graph Convolutional Network for Semi-Supervised Learning. ...
., +, TMM 2021 624-635 C-GCN: Correlation Based Graph Convolutional Network for Audio-Video Emotion Recognition. ...
doi:10.1109/tmm.2022.3141947
fatcat:lil2nf3vd5ehbfgtslulu7y3lq
Double Graph Based Reasoning for Document-level Relation Extraction
[article]
2020
arXiv
pre-print
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In this paper, we propose Graph Aggregation-and-Inference Network (GAIN) featuring double graphs. ...
GAIN first constructs a heterogeneous mention-level graph (hMG) to model complex interaction among different mentions across the document. ...
Acknowledgments The authors would like to thank the anonymous reviewers for their thoughtful and constructive comments and ByteDance AI Lab for providing the computational resources for this work. ...
arXiv:2009.13752v1
fatcat:pum6oqpmlnalbgwxjy6v7nnaqq
Relation-Aware Global Attention for Person Re-identification
[article]
2020
arXiv
pre-print
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For person re-identification (re-id), attention mechanisms have become attractive as they aim at strengthening discriminative features and suppressing irrelevant ones, which matches well the key of re-id ...
The source code is available at https://github.com/microsoft/Relation-Aware-Global-Attention-Networks. ...
Introduction Person re-identification (re-id) aims to match a specific person across different times, places, or cameras, which has drawn a surge of interests from both industry and academia. ...
arXiv:1904.02998v2
fatcat:l2mncsfiqfcehk6up4opg4asna
Person Re-identification: A Retrospective on Domain Specific Open Challenges and Future Trends
[article]
2022
arXiv
pre-print
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In this context, a comprehensive review of current re-ID approaches in solving theses challenges is needed to analyze and focus on particular aspects for further advancements. ...
Person re-identification (Re-ID) is one of the primary components of an automated visual surveillance system. ...
graph convolution network. ...
arXiv:2202.13121v1
fatcat:luwwbcwspndqpauj4dosmmojee
Pose-Guided Multi-Scale Structural Relationship Learning for Video-Based Pedestrian Re-Identification
2021
IEEE Access
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INDEX TERMS Pedestrian re-identification, relationship model, graph convolutional network, multi-scale structure relationship. ...
How to extract discriminative features from redundant video information is a key issue for video pedestrian re-identification. ...
This paper considers the use of graph convolutional network (GCN) for pedestrian feature extraction. ...
doi:10.1109/access.2021.3062967
fatcat:rec42qjynbg7dhpbfvvwy7t3ja
IEEE Access Special Section Editorial: Advanced Data Mining Methods for Social Computing
2020
IEEE Access
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The article by Li et al., ''MV-GCN: Multi-view graph convolutional networks for link prediction,'' proposes a novel multiview graph convolutional neural network (MV-GCN) model based on the Matrix Completion ...
gating mechanism to learn mutual relation between the target and corresponding review context. ...
doi:10.1109/access.2020.3043060
fatcat:qbqk5f4ojvadlazhk2mc343sra
Table of Contents
2021
2021 IEEE International Conference on Image Processing (ICIP)
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LEARNING FOR IMAGE AND VIDEO ANALYSIS, SYNTHESIS, AND RETRIEVAL 3 MLR-APPL-IVASR-3.1: LIGHTWEIGHT MULTI-BRANCH NETWORK FOR PERSON ............................................1129 RE-IDENTIFICATION Fabian ...
A*STAR, Singapore MLR-APPL-IVASR-1.8: HIGH-ORDER JOINT INFORMATION INPUT FOR GRAPH ............................................... 1064 CONVOLUTIONAL NETWORK BASED ACTION RECOGNITION Wen-Nung Lie, Yong-Jhu ...
doi:10.1109/icip42928.2021.9506758
fatcat:5g2bwdt2efafjd2mubhxyv4m4y
Document-level Relation Extraction as Semantic Segmentation
[article]
2021
arXiv
pre-print
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2021 pre-print arXiv:2106.03618v1 fatcat:ykctievxybdjnai6eumdzqctqa
Herein, we propose a Document U-shaped Network for document-level relation extraction. ...
Previously proposed graph-based or transformer-based models utilize the entities independently, regardless of global information among relational triples. ...
Acknowledgments We want to express gratitude to the anonymous reviewers for their hard work and kind comments. We thank Ning Ding for helpful discussions and feedback on this paper. ...
arXiv:2106.03618v2
fatcat:gdusrbswoffkxes4scsfc223ai
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