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Pedestrian-Attribute-Recognition-Paper-List [Survey-Paper]

The paper list of person attribute recognition Illustration of PAR

Illustration of PAR Performance comparison on the PETA and RAP dataset from 2014 to 2020. We can find that the baseline method CNN-SVM is outperformed by recent deep learning based PAR approaches significantly on both large scale benchmark datasets. Interestingly, we can also find that the accuracy of current deep learning based methods are comparable, and there are no significant improvement of current methods (in 2020) compared with deep PAR algorithms proposed in several years ago. So, what's next if the deep learning based PAR algorithms achieve its bottleneck?

Note：

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If you find more related papers about person attribute recognition, please email me: [email protected]

[arXiv paper] [High Resolution version] [Project-page]

Structure of Survey Papers of Survey Overview_Benchmark

If you find this survey useful for your research, please consider to cite this paper:

@article{wang2019parsurvey,
  title={Pedestrian attribute recognition: A survey},
  author={Wang, Xiao and Zheng, Shaofei and Yang, Rui and Luo, Bin and Tang, Jin},
  journal={arXiv preprint arXiv:1901.07474},
  year={2019}
}

Dataset:

  1. PETA Dataset: http://mmlab.ie.cuhk.edu.hk/projects/PETA.html
  2. RAP Dataset: http://rap.idealtest.org/
  3. PA-100K Dataset: https://drive.google.com/drive/folders/0B5_Ra3JsEOyOUlhKM0VPZ1ZWR2M
  4. WIDER Attribute Dataset: http://mmlab.ie.cuhk.edu.hk/projects/WIDERAttribute.html
  5. Database of Human Attributes (HAT): https://jurie.users.greyc.fr/datasets/hat.html
  6. Market-1501_Attribute: https://github.com/vana77/Market-1501_Attribute
  7. DukeMTMC-Attribute: https://github.com/vana77/DukeMTMC-attribute
  8. Clothing Attributes Dataset: https://purl.stanford.edu/tb980qz1002
  9. Parse27k Dataset: https://www.vision.rwth-aachen.de/page/parse27k
  10. RAP 2.0 Dataset: https://drive.google.com/file/d/1hoPIB5NJKf3YGMvLFZnIYG5JDcZTxHph/view
  11. CRP Dataset: http://www.vision.caltech.edu/~dhall/projects/CRP/
  12. APis dataset: http://www.cbsr.ia.ac.cn/english/APiS-1.0-Database.html. (Failed)
  13. Berkeley-Attributes of People dataset: https://www2.eecs.berkeley.edu/Research/Projects/CS/vision/shape/poselets/
  14. Deepfashion dataset: http://mmlab.ie.cuhk.edu.hk/projects/DeepFashion.html
  15. Video-Based PAR dataset: https://github.com/yuange250/MARS-Attribute

Related Survey Papers and Tutorial:

  1. Zheng, X., Guo, Y., Huang, H., Li, Y., & He, R. (2020). A Survey of Deep Facial Attribute Analysis. International Journal of Computer Vision, 1-33. Paper

  2. Human Parsing: Huang, Lili, Jiefeng Peng, Ruimao Zhang, Guanbin Li, and Liang Lin. "Learning deep representations for semantic image parsing: a comprehensive overview." Frontiers of Computer Science 12, no. 5 (2018): 840-857. Paper

  3. Awesome Imbalanced Learning [GitHub]

  4. Person Search Paper List [Github]

  5. Human Attribute Recognition: A Comprehensive Survey, Yaghoubi, E., Khezeli, F., Borza, D., Kumar, S. A., Neves, J., & Proença, H. (2020). [Paper]

Recommeded Code:

A solid and strong baseline of pedestrian attribute recognition: https://github.com/valencebond/Strong_Baseline_of_Pedestrian_Attribute_Recognition

A baseline model ( pytorch implementation ) for person attribute recognition task, training and testing on Market1501-attribute and DukeMTMC-reID-attribute dataset. https://github.com/hyk1996/Person-Attribute-Recognition-MarketDuke

DeepMAR from "Multi-attribute learning for pedestrian attribute recognition": https://github.com/kyu-sz/DeepMAR_deploy

Multi-attribute Learning for Pedestrian Attribute Recognition in Surveillance Scenarios, Dangwei Li and Xiaotang Chen and Kaiqi Huang, ACPR 2015: https://github.com/dangweili/pedestrian-attribute-recognition-pytorch

Multi-label Image Recognition by Recurrently Discovering Attentional Regions (Pytorch implementation): https://github.com/James-Yip/AttentionImageClass

A Richly Annotated Pedestrian Dataset for Person Retrieval in Real Surveillance Scenarios: Li, Dangwei and Zhang, Zhang and Chen, Xiaotang and Huang, Kaiqi, IEEE Transactions on Image Processing 2019: https://github.com/dangweili/RAP

PatchIt (BMVC-2016): https://github.com/psudowe/patchit

PANDA (CVOR-2014): https://github.com/facebookarchive/pose-aligned-deep-networks

HydraPlus-Net (ICCV-2017): https://github.com/xh-liu/HydraPlus-Net

WPAL-network (BMVC-2014) https://github.com/YangZhou1994/WPAL-network

Deep Imbalanced Attribute Classification using Visual Attention Aggregation (ECCV-2018): https://github.com/cvcode18/imbalanced_learning

Sarfraz, M. Saquib, et al. "Deep view-sensitive pedestrian attribute inference in an end-to-end model." arXiv preprint arXiv:1707.06089 (2017). https://github.com/asc-kit/vespa

The paper list of person attribute recognition:

Year-2020

Deep Template Matching for Pedestrian Attribute Recognition with the Auxiliary Supervision of Attribute-wise Keypoints, Jiajun Zhang, Pengyuan Ren, Jianmin Li, [arXiv]

Gu, Z., Zhang, J., Pan, Z., Zhao, H., & Zhang, L. (2019, July). Clothes keypoints localization and attribute recognition via prior knowledge. In 2019 IEEE International Conference on Multimedia and Expo (ICME) (pp. 550-555). IEEE.[Paper]

Ji, Z., Hu, Z., He, E., Han, J., & Pang, Y. (2020). Pedestrian Attribute Recognition Based on Multiple Time Steps Attention. Pattern Recognition Letters. [PRL]

Texture and Shape Biased Two-Stream Networks for Clothing Classification and Attribute Recognition, Yuwei Zhang, Peng Zhang, Chun Yuan, Zhi Wang [CVPR2020]

Hierarchical Feature Embedding for Attribute Recognition, Jie Yang, Jiarou Fan, Yiru Wang, Yige Wang, Weihao Gan, Lin Liu, Wei Wu [CVPR2020]

Rethinking of Pedestrian Attribute Recognition: Realistic Datasets and A Strong Baseline, Jian Jia, Houjing Huang, Wenjie Yang, Xiaotang Chen, and Kaiqi Huang [arXiv] [Code]

Multi-Task Learning via Co-Attentive Sharing for Pedestrian Attribute Recognition, Haitian Zeng, Haizhou Ai, Zijie Zhuang, Long Chen, [ICME 2020]

Distraction-Aware Feature Learning for Human Attribute Recognition via Coarse-to-Fine Attention Mechanism, Mingda Wu (Beihang University)*; Di Huang (Beihang University, China); Yuanfang Guo (Beihang University); Yunhong Wang (State Key Laboratory of Virtual Reality Technology and System, Beihang University, Beijing 100191, China), AAAI-2020 [Paper]

Relation-Aware Pedestrian Attribute Recognition with Graph Convolutional Networks, Zichang Tan (NLPR); Yang Yang (Institute of Automation, Chinese Academy of Sciences); Jun Wan (NLPR, CASIA)*; Guodong Guo (West Virginia University); Stan Li (National Lab. of Pattern Recognition, China), AAAI-2020, [Paper]

An Attention-Based Deep Learning Model for Multiple Pedestrian Attributes Recognition, Ehsan Yaghoubi, Diana Borza, Jo˜ao Neves, Aruna Kumar, Hugo Proen¸ca, [arXiv-Paper] [Code]

Year-2019

Zhang, S., Song, Z., Cao, X., Zhang, H., & Zhou, J. (2019). Task-aware attention model for clothing attribute prediction. IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT), 30(4), 1051-1064. [Paper]

GSR-MAR: Global Super-Resolution for Person Multi-Attribute Recognition. Siadari, Thomhert Suprapto, Mikyong Han, and Hyunjin Yoon. 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW). IEEE, 2019.[Paper]

Distraction-Aware Feature Learning for Human Attribute Recognition via Coarse-to-Fine Attention Mechanism, Mingda Wu, Di Huang, Yuanfang Guo Yunhong Wang [Paper] , AAAI-2020 oral presentation.

Improving Pedestrian Attribute Recognition With Weakly-Supervised Multi-Scale Attribute-Specific Localization Chufeng Tang, Lu Sheng, Zhaoxiang Zhang, Xiaolin Hu, ICCV-2019, [Paper] [Code]

Ji, Zhong, Erlu He, Haoran Wang, and Aiping Yang. "Image-attribute reciprocally guided attention network for pedestrian attribute recognition" Pattern Recognition Letters 120 (2019): 89-95.

Zichang Tan, Yang Yang, Jun Wan, Yingyi Chen, Guodong Guo, Stan Z. Li. Attention based Pedestrian Attribute Analysis. IEEE TIP, 2019.

Qiaozhe Li, Xin Zhao, Ran He, Kaiqi Huang, Pedestrian Attribute Recognition by Joint Visual-semantic Reasoning and Knowledge Distillation, IJCAI-2019.

Kai Han, Yunhe Wang, Han Shu, Chuanjian Liu, Chunjing Xu, Chang Xu, Attribute Aware Pooling for Pedestrian Attribute Recognition, IJCAI-2019

Liuyu Xiang, Xiaoming Jin, Guiguang Ding, Jungong Han, Leida Li Incremental Few-Shot Learning for Pedestrian Attribute Recognition, IJCAI-2019.

Esube Bekele and Wallace Lawson The Deeper, the Better: Analysis of Person Attributes Recognition, submitted to FG2019

Zhiyuan Chen, Annan Li, and Yunhong Wang, Video-Based Pedestrian Attribute Recognition, arXiv paper, 2019 [Paper]

Wang, Yiru, Weihao Gan, Wei Wu, and Junjie Yan. Dynamic Curriculum Learning for Imbalanced Data Classification, ICCV 2019.

Xin Zhao; Liufang Sang; guiguang ding; Jungong Han; Na Di; Chenggang Yan, Recurrent Attention Model for Pedestrian Attribute Recognition, AAAI-2019

Qiaozhe Li*; Xin Zhao; Ran He; KAIQI HUANG, Visual-semantic Graph Reasoning for Pedestrian Attribute Recognition, AAAI-2019

Li, Dangwei, Zhang Zhang, Xiaotang Chen, and Kaiqi Huang. "A richly annotated pedestrian dataset for person retrieval in real surveillance scenarios." IEEE transactions on image processing 28, no. 4 (2019): 1575-1590.

Year-2018

Wang, Wenguan, et al. "Attentive fashion grammar network for fashion landmark detection and clothing category classification." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2018. [Paper]

Li, Dangwei, Xiaotang Chen, Zhang Zhang, and Kaiqi Huang. "Pose Guided Deep Model for Pedestrian Attribute Recognition in Surveillance Scenarios." In 2018 IEEE International Conference on Multimedia and Expo (ICME), pp. 1-6. IEEE, 2018. Paper: http://dangweili.github.io/misc/pdfs/icme18.pdf

Chen, Tianshui, Zhouxia Wang, Guanbin Li, and Liang Lin. "Recurrent Attentional Reinforcement Learning for Multi-label Image Recognition." AAAI2018 Paper: http://www.linliang.net/wp-content/uploads/2018/01/AAAI2018_AttentionRL.pdf

Park, Seyoung, Bruce Xiaohan Nie, and Song-Chun Zhu. "Attribute and-or grammar for joint parsing of human pose, parts and attributes." IEEE transactions on pattern analysis and machine intelligence 40, no. 7 (2018): 1555-1569.

Zhao, Xin, Liufang Sang, Guiguang Ding, Yuchen Guo, and Xiaoming Jin. "Grouping Attribute Recognition for Pedestrian with Joint Recurrent Learning." In IJCAI, pp. 3177-3183. 2018. Paper：https://www.ijcai.org/proceedings/2018/0441.pdf Code:https://github.com/slf12/GRLModel

Sarafianos, Nikolaos, Theodoros Giannakopoulos, Christophoros Nikou, and Ioannis A. Kakadiaris. "Curriculum learning of visual attribute clusters for multi-task classification." Pattern Recognition 80 (2018): 94-108.

Sarafianos, Nikolaos, Xiang Xu, and Ioannis A. Kakadiaris. "Deep Imbalanced Attribute Classification using Visual Attention Aggregation." In Proceedings of the European Conference on Computer Vision (ECCV), pp. 680-697. 2018. Paper: http://openaccess.thecvf.com/content_ECCV_2018/papers/Nikolaos_Sarafianos_Deep_Imbalanced_Attribute_ECCV_2018_paper.pdf Code: https://github.com/cvcode18/imbalanced_learning

Liu, Hao, Jingjing Wu, Jianguo Jiang, Meibin Qi, and Ren Bo. "Sequence-based Person Attribute Recognition with Joint CTC-Attention Model." arXiv preprint arXiv:1811.08115 (2018).

Liu, P., Liu, X., Yan, J., & Shao, J. (2018). Localization guided learning for pedestrian attribute recognition. arXiv preprint arXiv:1808.09102. BMVC-paper

Year-2017

Fabbri, Matteo, Simone Calderara, and Rita Cucchiara. "Generative adversarial models for people attribute recognition in surveillance." In Advanced Video and Signal Based Surveillance (AVSS), 2017 14th IEEE International Conference on, pp. 1-6. IEEE, 2017.

Guo, Qi, Ce Zhu, Zhiqiang Xia, Zhengtao Wang, and Yipeng Liu. "Attribute-controlled face photo synthesis from simple line drawing." In Image Processing (ICIP), 2017 IEEE International Conference on, pp. 2946-2950. IEEE, 2017. Paper

Hand, Emily M., and Rama Chellappa. "Attributes for Improved Attributes: A Multi-Task Network Utilizing Implicit and Explicit Relationships for Facial Attribute Classification." In AAAI, pp. 4068-4074. 2017.

Wang, Jingya, Xiatian Zhu, Shaogang Gong, and Wei Li. "Attribute Recognition by Joint Recurrent Learning of Context and Correlation." In Computer Vision (ICCV), 2017 IEEE International Conference on, pp. 531-540. IEEE, 2017.

Wang, Z., Chen, T., Li, G., Xu, R., & Lin, L. (2017, October). Multi-label Image Recognition by Recurrently Discovering Attentional Regions. In Computer Vision (ICCV), 2017 IEEE International Conference on (pp. 464-472). IEEE. Paper: http://openaccess.thecvf.com/content_ICCV_2017/papers/Wang_Multi-Label_Image_Recognition_ICCV_2017_paper.pdf Code: https://github.com/James-Yip/AttentionImageClass

Trigeorgis, George, Konstantinos Bousmalis, Stefanos Zafeiriou, and Björn W. Schuller. "A deep matrix factorization method for learning attribute representations." IEEE transactions on pattern analysis and machine intelligence 39, no. 3 (2017): 417-429.

Lin, Yutian, Liang Zheng, Zhedong Zheng, Yu Wu, and Yi Yang. "Improving person re-identification by attribute and identity learning." arXiv preprint arXiv:1703.07220 (2017).

Liu, Xihui, Haiyu Zhao, Maoqing Tian, Lu Sheng, Jing Shao, Shuai Yi, Junjie Yan, and Xiaogang Wang. "Hydraplus-net: Attentive deep features for pedestrian analysis." arXiv preprint arXiv:1709.09930 (2017). Code: https://github.com/xh-liu/HydraPlus-Net

Fouhey, David F., Abhinav Gupta, and Andrew Zisserman. "Understanding higher-order shape via 3D shape attributes." IEEE TPAMI (2017).

Zhou, Yang, Kai Yu, Biao Leng, Zhang Zhang, Dangwei Li, Kaiqi Huang, Bailan Feng, and Chunfeng Yao. "Weakly-supervised learning of mid-level features for pedestrian attribute recognition and localization." In BMVC. 2017. Paper: Code: https://github.com/YangZhou1994/WPAL-network

Su, Jong-Chyi, Chenyun Wu, Huaizu Jiang, and Subhransu Maji. "Reasoning about fine-grained attribute phrases using reference games." arXiv preprint arXiv:1708.08874 (2017).

Dong, Qi, Shaogang Gong, and Xiatian Zhu. "Multi-task curriculum transfer deep learning of clothing attributes." In Applications of Computer Vision (WACV), 2017 IEEE Winter Conference on, pp. 520-529. IEEE, 2017.

Kalayeh, Mahdi M., Boqing Gong, and Mubarak Shah. "Improving facial attribute prediction using semantic segmentation." In Computer Vision and Pattern Recognition (CVPR), 2017 IEEE Conference on, pp. 4227-4235. IEEE, 2017.

Lu, Yongxi, Abhishek Kumar, Shuangfei Zhai, Yu Cheng, Tara Javidi, and Rogério Schmidt Feris. "Fully-adaptive Feature Sharing in Multi-Task Networks with Applications in Person Attribute Classification." In CVPR, vol. 1, no. 2, p. 6. 2017.

Guo, Hao, Xiaochuan Fan, and Song Wang. "Human attribute recognition by refining attention heat map." Pattern Recognition Letters 94 (2017): 38-45.

Zhu, Jianqing, et al. "Multi-label convolutional neural network based pedestrian attribute classification." Image and Vision Computing 58 (2017): 224-229.

Sarafianos, Nikolaos, Theodore Giannakopoulos, Christophoros Nikou, and Ioannis A. Kakadiaris. "Curriculum Learning for Multi-Task Classification of Visual Attributes." In Proceedings of the IEEE International Conference on Computer Vision, pp. 2608-2615. 2017.

He, Keke, Zhanxiong Wang, Yanwei Fu, Rui Feng, Yu-Gang Jiang, and Xiangyang Xue. "Adaptively Weighted Multi-task Deep Network for Person Attribute Classification." In Proceedings of the 2017 ACM on Multimedia Conference, pp. 1636-1644. ACM, 2017. https://dl.acm.org/citation.cfm?id=3123424

Sarfraz, M. Saquib, Arne Schumann, Yan Wang, and Rainer Stiefelhagen. "Deep View-Sensitive Pedestrian Attribute Inference in an end-to-end Model." arXiv preprint arXiv:1707.06089 (2017). [Paper], [Code]

Liu, Xihui, Haiyu Zhao, Maoqing Tian, Lu Sheng, Jing Shao, Shuai Yi, Junjie Yan, and Xiaogang Wang. "HydraPlus-Net: Attentive Deep Features for Pedestrian Analysis." In Proceedings of the IEEE International Conference on Computer Vision, pp. 350-359. 2017. Paper: http://openaccess.thecvf.com/content_ICCV_2017/papers/Liu_HydraPlus-Net_Attentive_Deep_ICCV_2017_paper.pdf Code: https://github.com/xh-liu/HydraPlus-Net

Year-2016

Li, Dangwei, Zhang Zhang, Xiaotang Chen, Haibin Ling, and Kaiqi Huang. "A richly annotated dataset for pedestrian attribute recognition." arXiv preprint arXiv:1603.07054 (2016).

Yan, Xinchen, Jimei Yang, Kihyuk Sohn, and Honglak Lee. "Attribute2image: Conditional image generation from visual attributes." In European Conference on Computer Vision, pp. 776-791. Springer, Cham, 2016.

Li, Yining, Chen Huang, Chen Change Loy, and Xiaoou Tang. "Human attribute recognition by deep hierarchical contexts." In European Conference on Computer Vision, pp. 684-700. Springer, Cham, 2016.

Yang, L. , Zhu, L. , Wei, Y. , Liang, S. , & Tan, P. . (2016). Attribute recognition from adaptive parts.

Wang, Jiang, Yi Yang, Junhua Mao, Zhiheng Huang, Chang Huang, and Wei Xu. "Cnn-rnn: A unified framework for multi-label image classification." In Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 2285-2294. 2016.

Fouhey, David F., Abhinav Gupta, and Andrew Zisserman. "3D shape attributes." In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1516-1524. 2016.

Wang, Jing, Yu Cheng, and Rogerio Schmidt Feris. "Walk and learn: Facial attribute representation learning from egocentric video and contextual data." In Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 2295-2304. 2016.

Pedestrian Attribute Detection using CNN, Standford University, CS231n, 2016, Agrim Gupta and Jayanth Ramesh, Paper: http://cs231n.stanford.edu/reports/2016/pdfs/255_Report.pdf

Sudowe, Patrick, and Bastian Leibe. "PatchIt: Self-Supervised Network Weight Initialization for Fine-grained Recognition" In BMVC. 2016.

Liu, Ziwei, Ping Luo, Shi Qiu, Xiaogang Wang, and Xiaoou Tang. "Deepfashion: Powering robust clothes recognition and retrieval with rich annotations." In Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 1096-1104. 2016.

Li, Mu, Wangmeng Zuo, and David Zhang. "Deep identity-aware transfer of facial attributes." arXiv preprint arXiv:1610.05586 (2016).

Diba, Ali, Ali Mohammad Pazandeh, Hamed Pirsiavash, and Luc Van Gool. "Deepcamp: Deep convolutional action & attribute mid-level patterns." In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3557-3565. 2016.

Year-2015

Sudowe, Patrick, Hannah Spitzer, and Bastian Leibe. "Person attribute recognition with a jointly-trained holistic cnn model." In Proceedings of the IEEE International Conference on Computer Vision Workshops, pp. 87-95. 2015.

Park, Seyoung, and Song-Chun Zhu. "Attributed grammars for joint estimation of human attributes, part and pose." In Proceedings of the IEEE International Conference on Computer Vision, pp. 2372-2380. 2015.

Gkioxari, Georgia, Ross Girshick, and Jitendra Malik. "Actions and attributes from wholes and parts." In Proceedings of the IEEE International Conference on Computer Vision, pp. 2470-2478. 2015.

Deng, Y., Luo, P., Loy, C. C., & Tang, X. (2015). Learning to recognize pedestrian attribute. arXiv preprint arXiv:1501.00901.Paper

Zhu, Jianqing, Shengcai Liao, Dong Yi, Zhen Lei, and Stan Z. Li. "Multi-label cnn based pedestrian attribute learning for soft biometrics." In Biometrics (ICB), 2015 International Conference on, pp. 535-540. IEEE, 2015.

Yamaguchi, Kota, Takayuki Okatani, Kyoko Sudo, Kazuhiko Murasaki, and Yukinobu Taniguchi. "Mix and Match: Joint Model for Clothing and Attribute Recognition." In BMVC, vol. 1, no. 2, p. 4. 2015.

Li, Dangwei, Xiaotang Chen, and Kaiqi Huang. "Multi-attribute learning for pedestrian attribute recognition in surveillance scenarios." In Pattern Recognition (ACPR), 2015 3rd IAPR Asian Conference on, pp. 111-115. IEEE, 2015.

Hall, David, and Pietro Perona. "Fine-grained classification of pedestrians in video: Benchmark and state of the art." In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5482-5491. 2015.

Abdulnabi, Abrar H., Gang Wang, Jiwen Lu, and Kui Jia. "Multi-task CNN model for attribute prediction." IEEE Transactions on Multimedia 17, no. 11 (2015): 1949-1959.

Before Year-2015

Deng, Yubin, Ping Luo, Chen Change Loy, and Xiaoou Tang. "Pedestrian attribute recognition at far distance." In Proceedings of the 22nd ACM international conference on Multimedia, pp. 789-792. ACM, 2014.

Zhang, Ning, Manohar Paluri, Marc'Aurelio Ranzato, Trevor Darrell, and Lubomir Bourdev. "Panda: Pose aligned networks for deep attribute modeling." In Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 1637-1644. 2014.

Lampert, Christoph H., Hannes Nickisch, and Stefan Harmeling. "Attribute-based classification for zero-shot visual object categorization." IEEE Transactions on Pattern Analysis and Machine Intelligence 36, no. 3 (2014): 453-465.

Zhu, Jianqing, Shengcai Liao, Zhen Lei, Dong Yi, and Stan Li. "Pedestrian attribute classification in surveillance: Database and evaluation." In Proceedings of the IEEE International Conference on Computer Vision Workshops, pp. 331-338. 2013.

Joo, Jungseock, Shuo Wang, and Song-Chun Zhu. "Human attribute recognition by rich appearance dictionary." In Proceedings of the IEEE International Conference on Computer Vision, pp. 721-728. 2013. Paper

Chen, Huizhong, Andrew Gallagher, and Bernd Girod. "Describing clothing by semantic attributes." European conference on computer vision. Springer, Berlin, Heidelberg, 2012.

Sharma, G. and Jurie, F., 2011, August. Learning discriminative spatial representation for image classification. In BMVC 2011-British Machine Vision Conference (pp. 1-11). BMVA Press.

Bourdev, Lubomir, Subhransu Maji, and Jitendra Malik. "Describing people: A poselet-based approach to attribute classification." In Computer Vision (ICCV), 2011 IEEE International Conference on, pp. 1543-1550. IEEE, 2011.

Applications (Person Attribute based Tasks)

Person Re-ID based on Attributes

Han, Kai, Jianyuan Guo, Chao Zhang, and Mingjian Zhu. "Attribute-aware attention model for fine-grained representation learning" In 2018 ACM Multimedia Conference on Multimedia Conference, pp. 2040-2048. ACM, 2018.

Su, Chi, Shiliang Zhang, Junliang Xing, Wen Gao, and Qi Tian. "Deep attributes driven multi-camera person re-identification." In European conference on computer vision, pp. 475-491. Springer, Cham, 2016.

Layne, Ryan, Timothy M. Hospedales, and Shaogang Gong. "Towards person identification and re-identification with attributes." In European Conference on Computer Vision, pp. 402-412. Springer, Berlin, Heidelberg, 2012.

Layne, Ryan, Timothy M. Hospedales, Shaogang Gong, and Q. Mary. "Person re-identification by attributes." In Bmvc, vol. 2, no. 3, p. 8. 2012.

Lin, Yutian, Liang Zheng, Zhedong Zheng, Yu Wu, Zhilan Hu, Chenggang Yan, and Yi Yang. "Improving person re-identification by attribute and identity learning." Pattern Recognition (2019).

Khamis, Sameh, Cheng-Hao Kuo, Vivek K. Singh, Vinay D. Shet, and Larry S. Davis. "Joint learning for attribute-consistent person re-identification." In European Conference on Computer Vision, pp. 134-146. Springer, Cham, 2014.

Layne, Ryan, Timothy M. Hospedales, and Shaogang Gong. "Attributes-based re-identification." In Person Re-Identification, pp. 93-117. Springer, London, 2014.

Li, Annan, Luoqi Liu, Kang Wang, Si Liu, and Shuicheng Yan. "Clothing attributes assisted person reidentification." IEEE Transactions on Circuits and Systems for Video Technology 25, no. 5 (2015): 869-878.

Schumann, Arne, and Rainer Stiefelhagen. "Person re-identification by deep learning attribute-complementary information." In Computer Vision and Pattern Recognition Workshops (CVPRW), 2017 IEEE Conference on, pp. 1435-1443. IEEE, 2017.

Shuzhao Li, Huimin Yu, Wei Huang, Jing Zhang, Attributes-aided Part Detection and Refinement for Person Re-identification, Zhejiang University, arXiv paper-2019

Ling, Hefei, Ziyang Wang, Ping Li, Yuxuan Shi, Jiazhong Chen, and Fuhao Zou. "Improving person re-identification by multi-task learning." Neurocomputing 347 (2019): 109-118.

Su, Chi, Shiliang Zhang, Fan Yang, Guangxiao Zhang, Qi Tian, Wen Gao, and Larry S. Davis. "Attributes driven tracklet-to-tracklet person re-identification using latent prototypes space mapping." Pattern Recognition 66 (2017): 4-15.

Pedestrian Detection based on Attributes

Tian, Yonglong, Ping Luo, Xiaogang Wang, and Xiaoou Tang. "Pedestrian detection aided by deep learning semantic tasks." In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5079-5087. 2015.

Person Retrieval based on Attributes

Wang, Xianwang, Tong Zhang, Daniel R. Tretter, and Qian Lin. "Personal clothing retrieval on photo collections by color and attributes." IEEE Transactions on Multimedia 15, no. 8 (2013): 2035-2045.

Feris, Rogerio, Russel Bobbitt, Lisa Brown, and Sharath Pankanti. "Attribute-based people search: Lessons learnt from a practical surveillance system." In Proceedings of International Conference on Multimedia Retrieval, p. 153. ACM, 2014.

Action Recognition and Scene Understanding

Liu, Jingen, Benjamin Kuipers, and Silvio Savarese. "Recognizing human actions by attributes." In Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on, pp. 3337-3344. IEEE, 2011.

Shao, Jing, Kai Kang, Chen Change Loy, and Xiaogang Wang. "Deeply learned attributes for crowded scene understanding." In Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 4657-4666. 2015.