{"type":"ScholarlyArticle","title":"Variation Generalized Feature Learning via Intra-view Variation Adaptation","authors":[{"name":"Jiawei Li","slug":"jiawei-li","given":"Jiawei","family":"Li","affiliation":"Department of Computer Science , Hong Kong Baptist University , Hong Kong"},{"name":"Mang Ye","slug":"mang-ye","given":"Mang","family":"Ye","affiliation":"Department of Computer Science , Hong Kong Baptist University , Hong Kong"},{"name":"Andy Jinhua Ma","slug":"andy-jinhua-ma","given":"Andy Jinhua","family":"Ma","affiliation":"School of Data and Computer Science , Sun Yat-sen University , China"},{"name":"Pong C Yuen","slug":"pong-c-yuen","given":"Pong C.","family":"Yuen","affiliation":"Department of Computer Science , Hong Kong Baptist University , Hong Kong"}],"abstract":"This paper addresses the variation generalized feature learning problem in unsupervised video-based person re-identification (re-ID). With advanced tracking and detection algorithms, large-scale intra-view positive samples can be easily collected by assuming that the image frames within the tracking sequence belong to the same person. Existing methods either directly use the intra-view positives to model cross-view variations or simply minimize the intra-view variations to capture the invariant component with some discriminative information loss. In this paper, we propose a Variation Generalized Feature Learning (VGFL) method to learn adaptable feature representation with intra-view positives. The proposed method can learn a discriminative re-ID model without any manually annotated cross-view positive sample pairs. It could address the unseen testing variations with a novel variation generalized feature learning algorithm. In addition, an Adaptability-Discriminability (AD) fusion method is introduced to learn adaptable video-level features. Extensive experiments on different datasets demonstrate the effectiveness of the proposed method.","doi":"10.24963/ijcai.2019/116","url":"https://ijcai.org/proceedings/2019/116","pdf":"https://ijcai.org/proceedings/2019/0116.pdf","markdown":"https://ijcai.org/proceedings/2019/116.md","bibtex":"https://ijcai.org/proceedings/2019/bibtex/116","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":"Computer Vision","track":"Main track","number":116,"pages":{"first":826,"last":832},"keywords":["Computer Vision: Video: Events, Activities and Surveillance","Computer Vision: Computer Vision"],"videos":[],"references":[{"position":1,"raw":"[Aharon et al., 2006] Michal Aharon, Michael Elad, , and Alfred Bruckstein. k -svd: An algorithm for designing overcomplete dictionaries for sparse representation. IEEE Trans. Signal Processing, 54(11):4311-4322, 2006.","title":"k -svd: An algorithm for designing overcomplete dictionaries for sparse representation","authors":"Michal Aharon, Michael Elad, Alfred Bruckstein","year":"2006","venue":"IEEE Trans. Signal Processing","doi":null,"url":null,"internal_url":null},{"position":2,"raw":"[Basseville and Nikiforov, 1993] Michele Basseville and Ig- or V. Nikiforov. Detection of abrupt changes: theory and application, volume 104. 1993.","title":"Michele Basseville and Igor V. Nikiforov","authors":"Nikiforov Basseville","year":"1993","venue":"Detection of abrupt changes: theory and application","doi":null,"url":null,"internal_url":null},{"position":3,"raw":"[Chen et al., 2018] Dapeng Chen, Hongsheng Li, Tong X- iao, Shuai Yi, and Xiaogang Wang. Video person re- identification with competitive snippet-similarity aggrega- tion and co-attentive snippet embedding. In CVPR, pages 1169-1178, 2018.","title":"Video person reidentification with competitive snippet-similarity aggregation and co-attentive snippet embedding","authors":"Dapeng Chen, Hongsheng Li, Tong Xiao, Shuai Yi, Xiaogang Wang","year":"2018","venue":"CVPR","doi":null,"url":null,"internal_url":null},{"position":4,"raw":"[Deng et al., 2012] Weihong Deng, Jiani Hu, and Jun Guo. Extended src: Undersampled face recognition via intra- class variant dictionary. IEEE Trans. Pattern Anal. Ma- chine Intell., 34(9):1864-1870, 2012.","title":"Extended src: Undersampled face recognition via intraclass variant dictionary","authors":"Weihong Deng, Jiani Hu, Jun Guo","year":"2012","venue":"IEEE Trans. Pattern Anal. Machine Intell","doi":null,"url":null,"internal_url":null},{"position":5,"raw":"[Deng et al., 2018] Weijian Deng, Liang Zheng, Qixiang Ye, Guoliang Kang, Yi Yang, and Jianbin Jiao. Image- image domain adaptation with preserved self-similarity and domain-dissimilarity for person reidentification. In CVPR, pages 994-1003, 2018.","title":"Imageimage domain adaptation with preserved self-similarity and domain-dissimilarity for person reidentification","authors":"Weijian Deng, Liang Zheng, Qixiang Ye, Guoliang Kang, Yi Yang, Jianbin Jiao","year":"2018","venue":"CVPR","doi":null,"url":null,"internal_url":null},{"position":6,"raw":"[Ding et al., 2015] Changxing Ding, Xu Chang, and Dacheng Tao. Multi-task pose-invariant face recognition. IEEE Trans. Image Processing, 24(3):980-993, 2015.","title":"Multi-task pose-invariant face recognition","authors":"Changxing Ding, Xu Chang, Dacheng Tao","year":"2015","venue":"IEEE Trans. Image Processing","doi":null,"url":null,"internal_url":null},{"position":7,"raw":"[Farenzena et al., 2010] Michela Farenzena, Loris Bazzani, Alessandro Perina, Vittorio Murino, and Marco Cristani. Person re-identification by symmetry-driven accumulation of local features. In CVPR, pages 2360-2367, 2010.","title":"Person re-identification by symmetry-driven accumulation of local features","authors":"Michela Farenzena, Loris Bazzani, Alessandro Perina, Vittorio Murino, Marco Cristani","year":"2010","venue":"CVPR","doi":null,"url":null,"internal_url":null},{"position":8,"raw":"[Hirzer et al., 2011] Martin Hirzer, Csaba Beleznai, Peter M. Roth, and Horst Bischof. Person re-identification by de- scriptive and discriminative classification. In Image Anal- ysis, pages 91-102. 2011.","title":"Person re-identification by descriptive and discriminative classification","authors":"Martin Hirzer, Csaba Beleznai, Peter M Roth, Horst Bischof","year":"2011","venue":"Image Analysis","doi":null,"url":null,"internal_url":null},{"position":9,"raw":"[Khan and Bremond, 2016] Furqan M Khan and Francois Bremond. Unsupervised data association for metric learn- ing in the context of multi-shot person re-identification. In AVSS, pages 256-262, 2016.","title":"Unsupervised data association for metric learning in the context of multi-shot person re-identification","authors":"M Furqan, Francois Khan, Bremond","year":"2016","venue":"AVSS","doi":null,"url":null,"internal_url":null},{"position":10,"raw":"[Kodirov et al., 2016] Elyor Kodirov, Tao Xiang, Zhenyong Fu, and Shaogang Gong. Person re-identification by un- supervised l1 graph learning. In ECCV, pages 178-195, 2016.","title":"Person re-identification by unsupervised l1 graph learning","authors":"Kodirov","year":"2016","venue":"ECCV","doi":null,"url":null,"internal_url":null},{"position":11,"raw":"[Li et al., 2018] Minxian Li, Xiatian Zhu, and Shaogang Gong. Unsupervised person re-identification by deep learning tracklet association. In ECCV, pages 737-753, 2018.","title":"Unsupervised person re-identification by deep learning tracklet association","authors":"Li","year":"2018","venue":"ECCV","doi":null,"url":null,"internal_url":null},{"position":12,"raw":"[Liao et al., 2015] Shengcai Liao, Yang Hu, Xiangyu Zhu, and Stan Z. Li. Person re-identification by local maximal occurrence representation and metric learning. In CVPR, pages 2197-2206, 2015.","title":"Person re-identification by local maximal occurrence representation and metric learning","authors":"Shengcai Liao, Yang Hu, Xiangyu Zhu, Stan Z Li","year":"2015","venue":"CVPR","doi":null,"url":null,"internal_url":null},{"position":13,"raw":"[Liu et al., 2015] Kan Liu, Bingpeng Ma, Wei Zhang, and Rui Huang. A spatio-temporal appearance representa- tion for video-based pedestrian re-identification. In ICCV, pages 3810-3818, 2015.","title":"A spatio-temporal appearance representation for video-based pedestrian re-identification","authors":"Kan Liu, Bingpeng Ma, Wei Zhang, Rui Huang","year":"2015","venue":"ICCV","doi":null,"url":null,"internal_url":null},{"position":14,"raw":"[Liu et al., 2017] Zimo Liu, Dong Wang, and Huchuan Lu. Stepwise metric promotion for unsupervised video person re-identification. In ICCV, pages 2448-2457, 2017.","title":"Stepwise metric promotion for unsupervised video person re-identification","authors":"Zimo Liu, Dong Wang, Huchuan Lu","year":"2017","venue":"ICCV","doi":null,"url":null,"internal_url":null},{"position":15,"raw":"[Lv et al., 2018] Jianming Lv, Weihang Chen, Qing Li, and Can Yang. Unsupervised cross-dataset person re- identification by transfer learning of spatial-temporal pat- terns. In CVPR, pages 7948-7956, 2018.","title":"Unsupervised cross-dataset person reidentification by transfer learning of spatial-temporal patterns","authors":"Jianming Lv, Weihang Chen, Qing Li, Can Yang","year":"2018","venue":"CVPR","doi":null,"url":null,"internal_url":null},{"position":16,"raw":"[McLaughlin et al., 2016] Niall McLaughlin, Jesus Martinez del Rincon, and Paul Miller. Recurrent convolutional net- work for video-based person re-identification. In CVPR, pages 1325-1334, 2016.","title":"Recurrent convolutional network for video-based person re-identification","authors":"Niall Mclaughlin, Jesus Martinez Del Rincon, Paul Miller","year":"2016","venue":"CVPR","doi":null,"url":null,"internal_url":null},{"position":17,"raw":"[Wang et al., 2014] Taiqing Wang, Shaogang Gong, Xiatian Zhu, and Shengjin Wang. Person re-identification by video ranking. In ECCV, pages 688-703, 2014.","title":"Person re-identification by video ranking","authors":"Wang","year":"2014","venue":"ECCV","doi":null,"url":null,"internal_url":null},{"position":18,"raw":"[Wang et al., 2018a] Guanshuo Wang, Yufeng Yuan, Xiong Chen, Jiwei Li, and Xi Zhou. Learning discrimina- tive features with multiple granularities for person re- identification. In ACM MM, pages 274-282, 2018.","title":"Learning discriminative features with multiple granularities for person reidentification","authors":"Wang","year":"2018","venue":"ACM MM","doi":null,"url":null,"internal_url":null},{"position":19,"raw":"[Wang et al., 2018b] Jingya Wang, Xiatian Zhu, Shaogang Gong, and Wei Li. Transferable joint attribute-identity deep learning for unsupervised person re-identification. In CVPR, pages 2275-2284, 2018.","title":"Transferable joint attribute-identity deep learning for unsupervised person re-identification","authors":"Wang","year":"2018","venue":"CVPR","doi":null,"url":null,"internal_url":null},{"position":20,"raw":"[Wei et al., 2018] Longhui Wei, Shiliang Zhang, Wen Gao, and Qi Tian. Person transfer gan to bridge domain gap for person re-identification. In CVPR, pages 79-88, 2018.","title":"Person transfer gan to bridge domain gap for person re-identification","authors":"Wei","year":"2018","venue":"CVPR","doi":null,"url":null,"internal_url":null},{"position":21,"raw":"[Wu et al., 2018] Yu Wu, Yutian Lin, Xuanyi Dong, Yan Yan, Wanli Ouyang, and Yi Yang. Exploit the unknown gradually: One-shot video-based person re-identification by stepwise learning. In CVPR, 2018.","title":"Exploit the unknown gradually: One-shot video-based person re-identification by stepwise learning","authors":"Yu Wu, Yutian Lin, Xuanyi Dong, Yan Yan, Wanli Ouyang, Yi Yang","year":"2018","venue":"CVPR","doi":null,"url":null,"internal_url":null},{"position":22,"raw":"[Yang et al., 2013] Meng Yang, Luc Van, and Lei Zhang. Sparse variation dictionary learning for face recognition with a single training sample per person. In ICCV, pages 689-696, 2013.","title":"Sparse variation dictionary learning for face recognition with a single training sample per person","authors":"Meng Yang, Luc Van, Lei Zhang","year":"2013","venue":"ICCV","doi":null,"url":null,"internal_url":null},{"position":23,"raw":"[Ye et al., 2017] Mang Ye, Andy J Ma, Liang Zheng, Jiawei Li, and Pong C. Yuen. Dynamic label graph matching for unsupervised video re-identification. In ICCV, pages 5142-5150, 2017.","title":"Dynamic label graph matching for unsupervised video re-identification","authors":"Mang Ye, Andy J Ma, Liang Zheng, Jiawei Li, Pong C Yuen","year":"2017","venue":"ICCV","doi":null,"url":null,"internal_url":null},{"position":24,"raw":"[Ye et al., 2019a] Mang Ye, Xiangyuan Lan, Zheng Wang, and Pong C Yuen. Bi-directional center-constrained top- ranking for visible thermal person re-identification. IEEE Trans. Inf. Forensics Secur, 2019.","title":"Bi-directional center-constrained topranking for visible thermal person re-identification","authors":"Ye","year":"2019","venue":"IEEE Trans. Inf. Forensics Secur","doi":null,"url":null,"internal_url":null},{"position":25,"raw":"[Ye et al., 2019b] Mang Ye, Jiawei Li, Andy J Ma, Liang Zheng, and Pong C. Yuen. Dynamic graph co-matching for unsupervised video-based person re-identification. In IEEE Trans. Image Processing, 2019.","title":"Dynamic graph co-matching for unsupervised video-based person re-identification","authors":"Ye","year":"2019","venue":"IEEE Trans. Image Processing","doi":null,"url":null,"internal_url":null},{"position":26,"raw":"[Zhang et al., 2016] Li Zhang, Tao Xiang, and Shaogang Gong. Learning a discriminative null space for person re- identification. In CVPR, pages 1239-1248, 2016.","title":"Learning a discriminative null space for person reidentification","authors":"Li Zhang, Tao Xiang, Shaogang Gong","year":"2016","venue":"CVPR","doi":null,"url":null,"internal_url":null},{"position":27,"raw":"[Zheng et al., 2016] Liang Zheng, Zhi Bie, Yifan Sun, Jing- dong Wang, Chi Su, Shengjin Wang, and Qi Tian. Mars: A video benchmark for large-scale person re-identification. In ECCV, 2016.","title":"Mars: A video benchmark for large-scale person re-identification","authors":"Liang Zheng, Zhi Bie, Yifan Sun, Jingdong Wang, Chi Su, Shengjin Wang, Qi Tian","year":"2016","venue":"ECCV","doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}