{"type":"ScholarlyArticle","title":"A Part Power Set Model for Scale-Free Person Retrieval","authors":[{"name":"Yunhang Shen","slug":"yunhang-shen","given":"Yunhang","family":"Shen","affiliation":"Fujian Key Laboratory of Sensing and Computing for Smart City , School of Information Science and Engineering , Xiamen University , 361005 , China"},{"name":"Rongrong Ji","slug":"rongrong-ji","given":"Rongrong","family":"Ji","affiliation":"Fujian Key Laboratory of Sensing and Computing for Smart City , School of Information Science and Engineering , Xiamen University , 361005 , China; Peng Cheng Laborotory , China"},{"name":"Xiaopeng Hong","slug":"xiaopeng-hong","given":"Xiaopeng","family":"Hong","affiliation":"Xi'an Jiaotong University , China; University of Oulu , Finland"},{"name":"Feng Zheng","slug":"feng-zheng","given":"Feng","family":"Zheng","affiliation":"Southern University of Science and Technology"},{"name":"Xiaowei Guo","slug":"xiaowei-guo","given":"Xiaowei","family":"Guo","affiliation":"Tencent Youtu Lab , Tencent Technology (Shanghai) Co. , Ltd."},{"name":"Yongjian Wu","slug":"yongjian-wu","given":"Yongjian","family":"Wu","affiliation":"Tencent Youtu Lab , Tencent Technology (Shanghai) Co. , Ltd."},{"name":"Feiyue Huang","slug":"feiyue-huang","given":"Feiyue","family":"Huang","affiliation":"Tencent Youtu Lab , Tencent Technology (Shanghai) Co. , Ltd."}],"abstract":"Recently, person re-identification (re-ID) has attracted increasing research attention, which has broad application prospects in video surveillance and beyond. To this end, most existing methods highly relied on well-aligned pedestrian images and hand-engineered part-based model on the coarsest feature map. In this paper, to lighten the restriction of such fixed and coarse input alignment, an end-to-end part power set model with multi-scale features is proposed, which captures the discriminative parts of pedestrians from global to local, and from coarse to fine, enabling part-based scale-free person re-ID. In particular, we first factorize the visual appearance by enumerating $k$-combinations for all $k$ of $n$ body parts to exploit rich global and partial information to learn discriminative feature maps. Then, a combination ranking module is introduced to guide the model training with all combinations of body parts, which alternates between ranking combinations and estimating an appearance model. To enable scale-free input, we further exploit the pyramid architecture of deep networks to construct multi-scale feature maps with a feasible amount of extra cost in term of memory and time. Extensive experiments on the mainstream evaluation datasets, including Market-1501, DukeMTMC-reID and CUHK03, validate that our method achieves the state-of-the-art performance.","doi":"10.24963/ijcai.2019/471","url":"https://ijcai.org/proceedings/2019/471","pdf":"https://ijcai.org/proceedings/2019/0471.pdf","markdown":"https://ijcai.org/proceedings/2019/471.md","bibtex":"https://ijcai.org/proceedings/2019/bibtex/471","volume":{"slug":"2019","title":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2019","url":"https://ijcai.org/proceedings/2019/","year":2019,"location":"Macao","dates":"10-16 August 2019","editors":"Sarit Kraus","isbn":"978-0-9992411-4-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2019"},"section":"Machine Learning M-Z","track":"Main track","number":471,"pages":{"first":3397,"last":3403},"keywords":["Computer Vision: Computer Vision","Computer Vision: Recognition: Detection, Categorization, Indexing, Matching, Retrieval, Semantic Interpretation","Machine Learning Applications: Applications of Supervised Learning","Machine Learning: Deep Learning"],"videos":[],"references":[{"position":1,"raw":"[Chang et al., 2018] Xiaobin Chang, Timothy M. Hospedales, and Tao Xiang. Multi-Level Factorisation Net for Person Re- Identification. In CVPR, 2018.","title":"Multi-Level Factorisation Net for Person Re-Identification","authors":"Xiaobin Chang, Timothy M Hospedales, Tao Xiang","year":"2018","venue":"CVPR","doi":null,"url":null,"internal_url":null},{"position":2,"raw":"[Chen et al., 2017a] Weihua Chen, Xiaotang Chen, Jianguo Zhang, and Kaiqi Huang. Beyond triplet loss: a deep quadruplet network for person re-identification. In CVPR, 2017.","title":"Beyond triplet loss: a deep quadruplet network for person re-identification","authors":"Chen","year":"2017","venue":"CVPR","doi":null,"url":null,"internal_url":null},{"position":3,"raw":"[Chen et al., 2017b] Yanbei Chen, Xiatian Zhu, and Shaogang Gong. Person re-identification by deep learning multi-scale rep- resentations. In ICCV, 2017.","title":"Person re-identification by deep learning multi-scale representations","authors":"Chen","year":"2017","venue":"ICCV","doi":null,"url":null,"internal_url":null},{"position":4,"raw":"[Chen et al., 2018] Dapeng Chen, Dan Xu, Hongsheng Li, Nicu Sebe, and Xiaogang Wang. Group Consistent Similarity Learn- ing via Deep CRF for Person Re-Identification. In CVPR, 2018.","title":"Group Consistent Similarity Learning via Deep CRF for Person Re-Identification","authors":"Dapeng Chen, Dan Xu, Hongsheng Li, Nicu Sebe, Xiaogang Wang","year":"2018","venue":"CVPR","doi":null,"url":null,"internal_url":null},{"position":5,"raw":"[Fu et al., 2019] Yang Fu, Yunchao Wei, Yuqian Zhou, Honghui Shi, Gao Huang, Xinchao Wang, Zhiqiang Yao, and Thomas Huang. Horizontal Pyramid Matching for Person Re- identification. In AAAI, 2019.","title":"Horizontal Pyramid Matching for Person Reidentification","authors":"Yang Fu, Yunchao Wei, Yuqian Zhou, Honghui Shi, Gao Huang, Xinchao Wang, Zhiqiang Yao, Thomas Huang","year":"2019","venue":"AAAI","doi":null,"url":null,"internal_url":null},{"position":6,"raw":"[He et al., 2018] Lingxiao He, Jian Liang, Haiqing Li, and Zhenan Sun. Deep Spatial Feature Reconstruction for Partial Person Re- identification: Alignment-Free Approach. In CVPR, 2018.","title":"Deep Spatial Feature Reconstruction for Partial Person Reidentification: Alignment-Free Approach","authors":"He","year":"2018","venue":"CVPR","doi":null,"url":null,"internal_url":null},{"position":7,"raw":"[Hermans et al., 2017] Alexander Hermans, Lucas Beyer, and Bas- tian Leibe. In Defense of the Triplet Loss for Person Re- Identification. arXiv, 2017.","title":"Defense of the Triplet Loss for Person Re-Identification","authors":"Alexander Hermans, Lucas Beyer, Bastian Leibe","year":"2017","venue":null,"doi":null,"url":null,"internal_url":null},{"position":8,"raw":"[Honari et al., 2016] Sina Honari, Jason Yosinski, Pascal Vincent, and Christopher Pal. Recombinator networks: Learning coarse- to-fine feature aggregation. In CVPR, 2016.","title":"Recombinator networks: Learning coarseto-fine feature aggregation","authors":"Sina Honari, Jason Yosinski, Pascal Vincent, Christopher Pal","year":"2016","venue":"CVPR","doi":null,"url":null,"internal_url":null},{"position":9,"raw":"[Huang et al., 2018] Houjing Huang, Dangwei Li, Zhang Zhang, Xiaotang Chen, and Kaiqi Huang. Adversarially Occluded Sam- ples for Person Re-identification. In CVPR, 2018.","title":"Adversarially Occluded Samples for Person Re-identification","authors":"Huang","year":"2018","venue":"CVPR","doi":null,"url":null,"internal_url":null},{"position":10,"raw":"[Li et al., 2014] Wei Li, Rui Zhao, Tong Xiao, and Xiaogang Wang. Deepreid: Deep filter pairing neural network for person re- identification. In CVPR, 2014.","title":"Deepreid: Deep filter pairing neural network for person reidentification","authors":"Wei Li, Rui Zhao, Tong Xiao, Xiaogang Wang","year":"2014","venue":"CVPR","doi":null,"url":null,"internal_url":null},{"position":11,"raw":"[Li et al., 2015] Xiang Li, Wei-shi Zheng, Xiaojuan Wang, Tao Xiang, and Shaogang Gong. Multi-scale Learning for Low- resolution Person Re-identification. In ICCV, 2015.","title":"Multi-scale Learning for Lowresolution Person Re-identification","authors":"Xiang Li, Wei-Shi Zheng, Xiaojuan Wang, Tao Xiang, Shaogang Gong","year":"2015","venue":"ICCV","doi":null,"url":null,"internal_url":null},{"position":12,"raw":"[Li et al., 2018] Wei Li, Xiatian Zhu, and Shaogang Gong. Harmo- nious Attention Network for Person Re-Identification. In CVPR, 2018.","title":"Harmonious Attention Network for Person Re-Identification","authors":"Wei Li, Xiatian Zhu, Shaogang Gong","year":"2018","venue":"CVPR","doi":null,"url":null,"internal_url":null},{"position":13,"raw":"[Liu et al., 2016] Jiawei Liu, Zheng-Jun Zha, QI Tian, Dong Liu, Ting Yao, Qiang Ling, and Tao Mei. Multi-Scale Triplet CNN for Person Re-Identification. In ACMMM, 2016.","title":"Multi-Scale Triplet CNN for Person Re-Identification","authors":"Jiawei Liu, Zheng-Jun Zha, Dong Qi Tian, Ting Liu, Qiang Yao, Tao Ling, Mei","year":"2016","venue":"ACMMM","doi":null,"url":null,"internal_url":null},{"position":14,"raw":"[Molchanov et al., 2017] Pavlo Molchanov, Stephen Tyree, Tero Karras, Timo Aila, and Jan Kautz. Pruning Convolutional Neural Networks for Resource Efficient Inference. In ICLR, 2017.","title":"Pruning Convolutional Neural Networks for Resource Efficient Inference","authors":"Pavlo Molchanov, Stephen Tyree, Tero Karras, Timo Aila, Jan Kautz","year":"2017","venue":"ICLR","doi":null,"url":null,"internal_url":null},{"position":15,"raw":"[Qian et al., 2017] Xuelin Qian, Yanwei Fu, Yu-Gang Jiang, Tao Xiang, and Xiangyang Xue. Multi-scale Deep Learning Archi- tectures for Person Re-identification. In ICCV, 2017.","title":"Multi-scale Deep Learning Architectures for Person Re-identification","authors":"Xuelin Qian, Yanwei Fu, Yu-Gang Jiang, Tao Xiang, Xiangyang Xue","year":"2017","venue":"ICCV","doi":null,"url":null,"internal_url":null},{"position":16,"raw":"[Qian et al., 2018] Xuelin Qian, Yanwei Fu, Tao Xiang, Wenxuan Wang, Jie Qiu, Yang Wu, Yu-Gang Jiang, and Xiangyang Xue. Pose-Normalized Image Generation for Person Re-identification. In ECCV, 2018.","title":"Pose-Normalized Image Generation for Person Re-identification","authors":"Xuelin Qian, Yanwei Fu, Tao Xiang, Wenxuan Wang, Jie Qiu, Yang Wu, Yu-Gang Jiang, Xiangyang Xue","year":"2018","venue":"ECCV","doi":null,"url":null,"internal_url":null},{"position":17,"raw":"[Radenović et al., 2016] Filip Radenović, Giorgos Tolias, and Ond\\vrej Chum. CNN image retrieval learns from BoW: Un- supervised fine-tuning with hard examples. In ECCV, 2016.","title":"CNN image retrieval learns from BoW: Unsupervised fine-tuning with hard examples","authors":"Filip Radenović, Giorgos Tolias, Ond\\vrej Chum","year":"2016","venue":"ECCV","doi":null,"url":null,"internal_url":null},{"position":18,"raw":"[Ristani et al., 2016] Ergys Ristani, Francesco Solera, Roger Zou, Rita Cucchiara, and Carlo Tomasi. Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking. In ECCV, 2016.","title":"Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking","authors":"Ristani","year":"2016","venue":"ECCV","doi":null,"url":null,"internal_url":null},{"position":19,"raw":"[Shen et al., 2018a] Yantao Shen, Hongsheng Li, Tong Xiao, Shuai Yi, Dapeng Chen, and Xiaogang Wang. Deep Group-shuffling Random Walk for Person Re-identification. In CVPR, 2018.","title":"Deep Group-shuffling Random Walk for Person Re-identification","authors":"Shen","year":"2018","venue":"CVPR","doi":null,"url":null,"internal_url":null},{"position":20,"raw":"[Shen et al., 2018b] Yantao Shen, Hongsheng Li, Shuai Yi, Dapeng Chen, and Xiaogang Wang. Person Re-identification with Deep Similarity-Guided Graph Neural Network. In ECCV, 2018.","title":"Person Re-identification with Deep Similarity-Guided Graph Neural Network","authors":"Shen","year":"2018","venue":"ECCV","doi":null,"url":null,"internal_url":null},{"position":21,"raw":"[Shen et al., 2018c] Yantao Shen, Tong Xiao, Hongsheng Li, Shuai Yi, and Xiaogang Wang. End-to-End Deep Kronecker-Product Matching for Person Re-identification. In CVPR, 2018.","title":"End-to-End Deep Kronecker-Product Matching for Person Re-identification","authors":"Shen","year":"2018","venue":"CVPR","doi":null,"url":null,"internal_url":null},{"position":22,"raw":"[Si et al., 2018] Jianlou Si, Honggang Zhang, Chun-Guang Li, Ja- son Kuen, Xiangfei Kong, Alex C. Kot, and Gang Wang. Dual Attention Matching Network for Context-Aware Feature Se- quence based Person Re-Identification. In CVPR, 2018.","title":"Dual Attention Matching Network for Context-Aware Feature Sequence based Person Re-Identification","authors":"Jianlou Si, Honggang Zhang, Chun-Guang Li, Jason Kuen, Xiangfei Kong, Alex C Kot, Gang Wang","year":"2018","venue":"CVPR","doi":null,"url":null,"internal_url":null},{"position":23,"raw":"[Song et al., 2018] Chunfeng Song, Yan Huang, Wanli Ouyang, and Liang Wang. Mask-guided Contrastive Attention Model for Person Re-Identification. In CVPR, 2018.","title":"Mask-guided Contrastive Attention Model for Person Re-Identification","authors":"Chunfeng Song, Yan Huang, Wanli Ouyang, Liang Wang","year":"2018","venue":"CVPR","doi":null,"url":null,"internal_url":null},{"position":24,"raw":"[Su et al., 2017] Chi Su, Jianing Li, Shiliang Zhang, Junliang Xing, Wen Gao, and Qi Tian. Pose-driven Deep Convolutional Model for Person Re-identification. In ICCV, 2017.","title":"Pose-driven Deep Convolutional Model for Person Re-identification","authors":"Su","year":"2017","venue":"ICCV","doi":null,"url":null,"internal_url":null},{"position":25,"raw":"[Suh et al., 2018] Yumin Suh, Jingdong Wang, Siyu Tang, Tao Mei, and Kyoung Mu Lee. Part-Aligned Bilinear Representations for Person Re-identification. In ECCV, 2018.","title":"Part-Aligned Bilinear Representations for Person Re-identification","authors":"Yumin Suh, Jingdong Wang, Siyu Tang, Tao Mei, Kyoung Mu, Lee","year":"2018","venue":"ECCV","doi":null,"url":null,"internal_url":null},{"position":26,"raw":"[Sun et al., 2018] Yifan Sun, Liang Zheng, Yi Yang, Qi Tian, and Shengjin Wang. Beyond Part Models: Person Retrieval with Re- fined Part Pooling (and a Strong Convolutional Baseline). In ECCV, 2018.","title":"Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)","authors":"Yifan Sun, Liang Zheng, Yi Yang, Qi Tian, Shengjin Wang","year":"2018","venue":"ECCV","doi":null,"url":null,"internal_url":null},{"position":27,"raw":"[Wang et al., 2018a] Guanshuo Wang, Yufeng Yuan, Xiong Chen, and Jiwei et al. Li. Learning Discriminative Features with Multi- ple Granularities for Person Re-Identification. In ACMMM, 2018.","title":"Learning Discriminative Features with Multiple Granularities for Person Re-Identification","authors":"Wang","year":"2018","venue":"ACMMM","doi":null,"url":null,"internal_url":null},{"position":28,"raw":"[Wang et al., 2018b] Yan Wang, Lequn Wang, Yurong You, Xu Zou, Vincent Chen, Serena Li, Gao Huang, Bharath Hari- haran, and Kilian Q. Weinberger. Resource Aware Person Re- identification across Multiple Resolutions. In CVPR, 2018.","title":"Resource Aware Person Reidentification across Multiple Resolutions","authors":"Wang","year":"2018","venue":"CVPR","doi":null,"url":null,"internal_url":null},{"position":29,"raw":"[Wang et al., 2018c] Yicheng Wang, Zhenzhong Chen, Feng Wu, and Gang Wang. Person Re-identification with Cascaded Pair- wise Convolutions. In CVPR, 2018.","title":"Person Re-identification with Cascaded Pairwise Convolutions","authors":"Wang","year":"2018","venue":"CVPR","doi":null,"url":null,"internal_url":null},{"position":30,"raw":"[Xu et al., 2018] Jing Xu, Rui Zhao, Feng Zhu, Huaming Wang, and Wanli Ouyang. Attention-Aware Compositional Network for Person Re-identification. In CVPR, 2018.","title":"Attention-Aware Compositional Network for Person Re-identification","authors":"Jing Xu, Rui Zhao, Feng Zhu, Huaming Wang, Wanli Ouyang","year":"2018","venue":"CVPR","doi":null,"url":null,"internal_url":null},{"position":31,"raw":"[Yang et al., 2018] Jiwei Yang, Xu Shen, Xinmei Tian, Houqiang Li, and Jianqiang et al. Huang. Local Convolutional Neural Net- works for Person Re-Identification. In ACMMM, 2018.","title":"Local Convolutional Neural Networks for Person Re-Identification","authors":"Jiwei Yang, Xu Shen, Xinmei Tian, Houqiang Li, Jianqiang","year":"2018","venue":"ACMMM","doi":null,"url":null,"internal_url":null},{"position":32,"raw":"[Yu et al., 2018] Rui Yu, Zhiyong Dou, Song Bai, Zhaoxiang Zhang, Yongchao Xu, and Xiang Bai. Hard-Aware Point-to-Set Deep Metric for Person Re-identification. In ECCV, 2018.","title":"Hard-Aware Point-to-Set Deep Metric for Person Re-identification","authors":"Rui Yu, Zhiyong Dou, Song Bai, Zhaoxiang Zhang, Yongchao Xu, Xiang Bai","year":"2018","venue":"ECCV","doi":null,"url":null,"internal_url":null},{"position":33,"raw":"[Zheng et al., 2015] Liang Zheng, Liyue Shen, Lu Tian, Shengjin Wang, Jingdong Wang, and Qi Tian. Scalable person re- identification: A benchmark. In ICCV, 2015.","title":"Scalable person reidentification: A benchmark","authors":"Liang Zheng, Liyue Shen, Lu Tian, Shengjin Wang, Jingdong Wang, Qi Tian","year":"2015","venue":"ICCV","doi":null,"url":null,"internal_url":null},{"position":34,"raw":"[Zheng et al., 2017] Zhedong Zheng, Liang Zheng, and Yi Yang. Unlabeled samples generated by gan improve the person re- identification baseline in vitro. In ICCV, 2017.","title":"Unlabeled samples generated by gan improve the person reidentification baseline in vitro","authors":"Zheng","year":"2017","venue":"ICCV","doi":null,"url":null,"internal_url":null},{"position":35,"raw":"[Zheng et al., 2019] Feng Zheng, Cheng Deng, Xing Sun, Xinyang Jiang, Xiaowei Guo, Zongqiao Yu, Feiyue Huang, and Rongrong Ji. Pyramidal Person Re-IDentification via Multi-Loss Dynamic Training. In CVPR, 2019.","title":"Pyramidal Person Re-IDentification via Multi-Loss Dynamic Training","authors":"Feng Zheng, Cheng Deng, Xing Sun, Xinyang Jiang, Xiaowei Guo, Zongqiao Yu, Feiyue Huang, Rongrong Ji","year":"2019","venue":"CVPR","doi":null,"url":null,"internal_url":null},{"position":36,"raw":"[Zhong et al., 2018] Zhun Zhong, Liang Zheng, Zhedong Zheng, Shaozi Li, and Yi Yang. Camera Style Adaptation for Person Re-identification. In CVPR, 2018.","title":"Camera Style Adaptation for Person Re-identification","authors":"Zhun Zhong, Liang Zheng, Zhedong Zheng, Shaozi Li, Yi Yang","year":"2018","venue":"CVPR","doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}