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Instance-Guided Context Rendering for Cross-Domain Person Re-Identification

Yanbei Chen, Xiatian Zhu, Shaogang Gong
2019 2019 IEEE/CVF International Conference on Computer Vision (ICCV)  
To tackle this limitation, we propose a novel Instance-Guided Context Rendering scheme, which transfers the source person identities into diverse target domain contexts to enable supervised reid model  ...  Existing person re-identification (re-id) methods mostly assume the availability of large-scale identity labels for model learning in any target domain deployment.  ...  Conclusion We presented a novel Instance-Guided Context Rendering scheme for cross-domain re-id model learning.  ... 
doi:10.1109/iccv.2019.00032 dblp:conf/iccv/ChenZG19 fatcat:2ehie77suzbnjpa7hhgzwwwcce

Unsupervised Person Re-identification by Soft Multilabel Learning [article]

Hong-Xing Yu, Wei-Shi Zheng, Ancong Wu, Xiaowei Guo, Shaogang Gong, Jian-Huang Lai
2019 arXiv   pre-print
Although unsupervised person re-identification (RE-ID) has drawn increasing research attentions due to its potential to address the scalability problem of supervised RE-ID models, it is very challenging  ...  We propose the soft multilabel-guided hard negative mining to learn a discriminative embedding for the unlabeled target domain by exploring the similarity consistency of the visual features and the soft  ...  In the RE-ID context, most pairs are cross-view pairs which consist of two person images captured by different camera views.  ... 
arXiv:1903.06325v2 fatcat:46yateeco5egvhezshjiseh7yu

Unsupervised Person Re-Identification by Soft Multilabel Learning

Hong-Xing Yu, Wei-Shi Zheng, Ancong Wu, Xiaowei Guo, Shaogang Gong, Jian-Huang Lai
2019 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)  
Although unsupervised person re-identification (RE-ID) has drawn increasing research attentions due to its potential to address the scalability problem of supervised RE-ID models, it is very challenging  ...  The idea is to learn a soft multilabel (real-valued label likelihood vector) for each unlabeled person by comparing the unlabeled person with a set of known reference persons from an auxiliary domain.  ...  In the RE-ID context, most pairs are cross-view pairs which consist of two person images captured by different camera views.  ... 
doi:10.1109/cvpr.2019.00225 dblp:conf/cvpr/YuZWGGL19 fatcat:vihivkfjefh2xcfkaq7d4knf4a

Learning Shape Representations for Clothing Variations in Person Re-Identification [article]

Yu-Jhe Li, Zhengyi Luo, Xinshuo Weng, Kris M. Kitani
2020 arXiv   pre-print
Person re-identification (re-ID) aims to recognize instances of the same person contained in multiple images taken across different cameras.  ...  Due to the lack of large-scale re-ID datasets which contain clothing changes for the same person, we propose two synthetic datasets for evaluation.  ...  Abstract Person re-identification (re-ID) aims to recognize instances of the same person contained in multiple images taken across different cameras.  ... 
arXiv:2003.07340v1 fatcat:bvcsumynybdahnugv2lzr77ocu

Deep Learning for Person Re-identification: A Survey and Outlook [article]

Mang Ye, Jianbing Shen, Gaojie Lin, Tao Xiang, Ling Shao, Steven C. H. Hoi
2021 arXiv   pre-print
Person re-identification (Re-ID) aims at retrieving a person of interest across multiple non-overlapping cameras.  ...  Meanwhile, we introduce a new evaluation metric (mINP) for person Re-ID, indicating the cost for finding all the correct matches, which provides an additional criteria to evaluate the Re-ID system for  ...  [218] design an instance-guided context rendering scheme to transfer the person identities from source domain into diverse contexts in the target domain.  ... 
arXiv:2001.04193v2 fatcat:4d3thmsr3va2tnu72nawlu2wxy

Joint Disentangling and Adaptation for Cross-Domain Person Re-Identification [article]

Yang Zou, Xiaodong Yang, Zhiding Yu, B.V.K. Vijaya Kumar, Jan Kautz
2020 arXiv   pre-print
Although a significant progress has been witnessed in supervised person re-identification (re-id), it remains challenging to generalize re-id models to new domains due to the huge domain gaps.  ...  Our model involves a disentangling module that encodes cross-domain images into a shared appearance space and two separate structure spaces, and an adaptation module that performs adversarial alignment  ...  [4] present an instance-guided context rendering to enable supervised learning in target domain by transferring source person identities into target contexts.  ... 
arXiv:2007.10315v1 fatcat:b63qxatktrbcpnsklapuzmuoey

What do people think they're doing? Action identification and human behavior

Robin R. Vallacher, Daniel M. Wegner
1987 Psychological review  
that renders 1971).  ...  As Danto (1963) has ob-context alone is rarely an unambiguous guide to a person's preserved, without knowledge of circumstances or events outside potent level of identification.  ...  "Creating a piece of art," for instance, contions that seem diverse or even inconsistent when identified at veys more information about the person behind the action than lower levels (e.g., "giving constructive  ... 
doi:10.1037//0033-295x.94.1.3 fatcat:atyhj2ndkjbjliua22j5jhzg6a

What do people think they're doing? Action identification and human behavior

Robin R. Vallacher, Daniel M. Wegner
1987 Psychological review  
that renders 1971).  ...  As Danto (1963) has ob-context alone is rarely an unambiguous guide to a person's preserved, without knowledge of circumstances or events outside potent level of identification.  ...  "Creating a piece of art," for instance, contions that seem diverse or even inconsistent when identified at veys more information about the person behind the action than lower levels (e.g., "giving constructive  ... 
doi:10.1037/0033-295x.94.1.3 fatcat:d5lghp3rgbe3top3pcfeucgxu4

2021 Index IEEE Transactions on Image Processing Vol. 30

2021 IEEE Transactions on Image Processing  
The Author Index contains the primary entry for each item, listed under the first author's name.  ...  ., +, TIP 2021 7689-7701 Unsupervised Cross Domain Person Re-Identification by Multi-Loss Optimization Learning.  ...  Person Re-Identification.  ... 
doi:10.1109/tip.2022.3142569 fatcat:z26yhwuecbgrnb2czhwjlf73qu

Real-world Person Re-Identification via Degradation Invariance Learning [article]

Yukun Huang, Zheng-Jun Zha, Xueyang Fu, Richang Hong, Liang Li
2020 arXiv   pre-print
In this paper, to solve the above problem, we propose a degradation invariance learning framework for real-world person Re-ID.  ...  Person re-identification (Re-ID) in real-world scenarios usually suffers from various degradation factors, e.g., low-resolution, weak illumination, blurring and adverse weather.  ...  Introduction Person re-identification (Re-ID) is a pedestrian retrieval task for non-overlapping camera networks.  ... 
arXiv:2004.04933v1 fatcat:hrldgxr2hzarpl3g3ye3drbste

Joint Generative and Contrastive Learning for Unsupervised Person Re-identification [article]

Hao Chen, Yaohui Wang, Benoit Lagadec, Antitza Dantcheva, Francois Bremond
2021 arXiv   pre-print
Recent self-supervised contrastive learning provides an effective approach for unsupervised person re-identification (ReID) by learning invariance from different views (transformed versions) of an input  ...  In this context, we propose a mesh-based view generator. Specifically, mesh projections serve as references towards generating novel views of a person.  ...  Introduction A person re-identification (ReID) system is targeted at identifying subjects across different camera views.  ... 
arXiv:2012.09071v2 fatcat:nsjt6bdjqjcgzpvfgvkjh3b27u

Unsupervised Clustering Active Learning for Person Re-identification [article]

Wenjing Gao, Minxian Li
2021 arXiv   pre-print
Supervised person re-identification (re-id) approaches require a large amount of pairwise manual labeled data, which is not applicable in most real-world scenarios for re-id deployment.  ...  More importantly, because the representative centroid-pairs are selected for annotation, UCAL can work with very low-cost human effort.  ...  Instance-guided context rendering for cross-domain person re-identification. In Proc. IEEE Int. Conf. Comput. Vis., pages 232–242, 2019.  ... 
arXiv:2112.13308v1 fatcat:kk5d5ghlh5bvvblpsdcirmfow4

Joint Generative and Contrastive Learning for Unsupervised Person Re-identification

Hao Chen, Yaohui Wang, Benoit Lagadec, Antitza Dantcheva, Francois Bremond
2021 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)  
Recent self-supervised contrastive learning provides an effective approach for unsupervised person re-identification (ReID) by learning invariance from different views (transformed versions) of an input  ...  While the GAN provides online data augmentation for contrastive learning, the contrastive module learns view-invariant features for generation. In this context, we propose a meshbased view generator.  ...  The authors are grateful to the OPAL infrastructure from Université Côte d'Azur for providing resources and support.  ... 
doi:10.1109/cvpr46437.2021.00204 fatcat:4hjstodiyvadthbf5thqt2l7jq

Building Ontologies for Cross-domain Recommendation on Facial Skin Problem and Related Cosmetics

Hla Hla Moe, Win Thanda Aung
2014 International Journal of Information Technology and Computer Science  
For linking cross-domain recommendation, Ford-Fulkerson algorithm is used to build the bridge of the concepts between two domain ontologies (Problems domain as the source domain and Cosmetics domain as  ...  Cross-domain recommendation is an emerging research topic.  ...  They discussed four major types of mediation: cross-user, cross-item, cross-context, and cross representation.  ... 
doi:10.5815/ijitcs.2014.06.05 fatcat:aatqj2uxprgj7hkmn6h3cfpsuu

2020 Index IEEE Transactions on Image Processing Vol. 29

2020 IEEE Transactions on Image Processing  
Rong, X., +, TIP 2020 591-601 Unsupervised Person Re-identification via Cross-Camera Similarity Exploration.  ...  Tian, L., +, TIP 2020 8429-8442 Unsupervised Person Re-identification via Cross-Camera Similarity Exploration.  ... 
doi:10.1109/tip.2020.3046056 fatcat:24m6k2elprf2nfmucbjzhvzk3m
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