skip to main content
10.1145/3447450.3447468acmotherconferencesArticle/Chapter ViewAbstractPublication PagesicvipConference Proceedingsconference-collections
research-article

SPF-Net: Semantic Parsed Feature for Pedestrian Attribute Recognition

Published: 09 April 2021 Publication History
First page of PDF

References

[1]
Jianqing Zhu, Shengcai Liao, Zhen Lei, Stan Z. Li,2017,Multi-label convolutional neural network based pedestrian attribute classification, Image and Vision Computing, Volume 58, Pages 224-229, ISSN 0262-8856, https://doi.org/10.1016/j.imavis.2016.07.004.
[2]
Chunfeng Yao, Bailan Feng, Defeng Li and Jian Li, 2017. Hierarchical pedestrian attribute recognition based on adaptive region localization," 2017 IEEE International Conference on Multimedia & Expo Workshops (ICMEW), Hong Kong, pp. 471-476.
[3]
Pengze Liu, Xihui Liu, Junjie Yan, and Jing Shao. 2018. Localization guided learning for pedestrian attribute recognition. In British Machine Vision Conference 2018, BMVC 2018, Northumbria University, Newcastle, UK, September 3-6, 2018, page 142. BMVA Press,2018 2
[4]
L. Bourdev and J. Malik, 2009, Poselets: Body part detectors trained using 3D human pose annotations, 2009 IEEE 12th International Conference on Computer Vision, Kyoto, pp. 1365-1372.
[5]
Lubomir D. Bourdev, Subhransu Maji, Jitendra Malik, 2011, Describing people: A poselet-based approach to attribute classification, 2011 International Conference on Computer Vision, Barcelona, pp. 1543-1550.
[6]
Joo, Jungseock, Shuo Wang, and Song-Chun Zhu. 2013. Human attribute recognition by rich appearance dictionary. In Proceedings of the IEEE International Conference on Computer Vision, pp. 721-728.
[7]
Zhang, Ning, Manohar Paluri, Marc'Aurelio Ranzato, Trevor Darrell, and Lubomir Bourdev. 2014. Panda: Pose aligned networks for deep attribute modeling. In Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 1637-1644.
[8]
G. Gkioxari, R. Girshick and J. Malik, 2015. Actions and Attributes from Wholes and Parts, 2015 IEEE International Conference on Computer Vision (ICCV), Santiago, pp. 2470-2478.
[9]
Yang, Luwei, Ligen Zhu, Yichen Wei, Shuang Liang, and Ping Tan. 2016. Attribute recognition from adaptive parts. arXiv preprint arXiv:1607.01437.
[10]
Li Y., Huang C., Loy C.C., Tang X. 2016 Human Attribute Recognition by Deep Hierarchical Contexts. In: Leibe B., Matas J., Sebe N., Welling M. (eds) Computer Vision – ECCV 2016. ECCV 2016. Lecture Notes in Computer Science, vol 9910. Springer, Cham. https://doi.org/10.1007/978-3-319-46466-4_41
[11]
D. Li, X. Chen, Z. Zhang and K. Huang, 2018. Pose Guided Deep Model for Pedestrian Attribute Recognition in Surveillance Scenarios, 2018 IEEE International Conference on Multimedia and Expo (ICME), San Diego, CA, pp. 1-6.
[12]
P. Sudowe, H. Spitzer and B. Leibe, 2015, Person Attribute Recognition with a Jointly-Trained Holistic CNN Model, 2015 IEEE International Conference on Computer Vision Workshop (ICCVW), Santiago, pp. 329-337.
[13]
Dangwei. Li, Xiaotang. Chen and Kaiqi. Huang, "Multi-attribute learning for pedestrian attribute recognition in surveillance scenarios," 2015 3rd IAPR Asian Conference on Pattern Recognition (ACPR), Kuala Lumpur, 2015, pp. 111-115.
[14]
Deng, Yubin & Luo, Ping & Loy, Chen Change & Tang, Xiaoou. 2014. Pedestrian Attribute Recognition At Far Distance. 789-792. 10.1145/2647868.2654966.
[15]
Krizhevsky, Alex & Sutskever, Ilya & Hinton, Geoffrey. 2012. ImageNet Classification with Deep Convolutional Neural Networks. Neural Information Processing Systems. 25. 10.1145/3065386.
[16]
Joo, Jungseock & Wang, Shuo & Zhu, Song. 2013. Human Attribute Recognition by Rich Appearance Dictionary. 721-728. 10.1109/ICCV.2013.95.
[17]
K. He, X. Zhang, S. Ren and J. Sun, "Deep Residual Learning for Image Recognition," 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, 2016, pp. 770-778.
[18]
Gong, Ke, Xiaodan Liang, Dongyu Zhang, Xiaohui Shen, and Liang Lin. 2017.Look into person: Self-supervised structure-sensitive learning and a new benchmark for human parsing. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 932-940. 2017.
[19]
Chen, Liang-Chieh, Yukun Zhu, George Papandreou, Florian Schroff, and Hartwig Adam. 2018. Encoder-decoder with atrous separable convolution for semantic image segmentation.In Proceedings of the European conference on computer vision (ECCV), pp. 801-818. 2018.
[20]
Li, Dangwei, Zhang Zhang, Xiaotang Chen, Haibin Ling, and Kaiqi Huang. 2016. A richly annotated dataset for pedestrian attribute recognition. arXiv preprint arXiv:1603.07054.

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences
ICVIP '20: Proceedings of the 2020 4th International Conference on Video and Image Processing
December 2020
255 pages
ISBN:9781450389075
DOI:10.1145/3447450
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 09 April 2021

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. attribute correlation
  2. human parsing
  3. pedestrian attribute recognition
  4. region localization

Qualifiers

  • Research-article
  • Research
  • Refereed limited

Conference

ICVIP 2020

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 32
    Total Downloads
  • Downloads (Last 12 months)2
  • Downloads (Last 6 weeks)1
Reflects downloads up to 20 Jan 2025

Other Metrics

Citations

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

HTML Format

View this article in HTML Format.

HTML Format

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media