J
Jinqiao Wang
Researcher at Chinese Academy of Sciences
Publications - 270
Citations - 5680
Jinqiao Wang is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Feature extraction & Computer science. The author has an hindex of 31, co-authored 242 publications receiving 3910 citations. Previous affiliations of Jinqiao Wang include Communication University of China & Intel.
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Book ChapterDOI
The sixth visual object tracking VOT2018 challenge results
Matej Kristan,Ales Leonardis,Jiří Matas,Michael Felsberg,Roman Pflugfelder,Roman Pflugfelder,Luka Čehovin Zajc,Tomas Vojir,Goutam Bhat,Alan Lukežič,Abdelrahman Eldesokey,Gustavo Fernandez,Alvaro Garcia-Martin,Álvaro Iglesias-Arias,A. Aydin Alatan,Abel Gonzalez-Garcia,Alfredo Petrosino,Alireza Memarmoghadam,Andrea Vedaldi,Andrej Muhič,Anfeng He,Arnold W. M. Smeulders,Asanka G. Perera,Bo Li,Boyu Chen,Changick Kim,Changsheng Xu,Changzhen Xiong,Cheng Tian,Chong Luo,Chong Sun,Cong Hao,Daijin Kim,Deepak Mishra,Deming Chen,Dong Wang,Dongyoon Wee,Efstratios Gavves,Erhan Gundogdu,Erik Velasco-Salido,Fahad Shahbaz Khan,Fan Yang,Fei Zhao,Feng Li,Francesco Battistone,George De Ath,Gorthi R. K. Sai Subrahmanyam,Guilherme Sousa Bastos,Haibin Ling,Hamed Kiani Galoogahi,Hankyeol Lee,Haojie Li,Haojie Zhao,Heng Fan,Honggang Zhang,Horst Possegger,Houqiang Li,Huchuan Lu,Hui Zhi,Huiyun Li,Hyemin Lee,Hyung Jin Chang,Isabela Drummond,Jack Valmadre,Jaime Spencer Martin,Javaan Chahl,Jin-Young Choi,Jing Li,Jinqiao Wang,Jinqing Qi,Jinyoung Sung,Joakim Johnander,João F. Henriques,Jongwon Choi,Joost van de Weijer,Jorge Rodríguez Herranz,Jorge Rodríguez Herranz,José M. Martínez,Josef Kittler,Junfei Zhuang,Junyu Gao,Klemen Grm,Lichao Zhang,Lijun Wang,Lingxiao Yang,Litu Rout,Liu Si,Luca Bertinetto,Lutao Chu,Manqiang Che,Mario Edoardo Maresca,Martin Danelljan,Ming-Hsuan Yang,Mohamed H. Abdelpakey,Mohamed Shehata,Myunggu Kang,Namhoon Lee,Ning Wang,Ondrej Miksik,Payman Moallem,Pablo Vicente-Moñivar,Pedro Senna,Peixia Li,Philip H. S. Torr,Priya Mariam Raju,Qian Ruihe,Qiang Wang,Qin Zhou,Qing Guo,Rafael Martin-Nieto,Rama Krishna Sai Subrahmanyam Gorthi,Ran Tao,Richard Bowden,Richard M. Everson,Runling Wang,Sangdoo Yun,Seokeon Choi,Sergio Vivas,Shuai Bai,Shuangping Huang,Sihang Wu,Simon Hadfield,Siwen Wang,Stuart Golodetz,Tang Ming,Tianyang Xu,Tianzhu Zhang,Tobias Fischer,Vincenzo Santopietro,Vitomir Struc,Wang Wei,Wangmeng Zuo,Wei Feng,Wei Wu,Wei Zou,Weiming Hu,Wengang Zhou,Wenjun Zeng,Xiaofan Zhang,Xiaohe Wu,Xiaojun Wu,Xinmei Tian,Yan Li,Yan Lu,Yee Wei Law,Yi Wu,Yi Wu,Yiannis Demiris,Yicai Yang,Yifan Jiao,Yuhong Li,Yuhong Li,Yunhua Zhang,Yuxuan Sun,Zheng Zhang,Zheng Zhu,Zhen-Hua Feng,Zhihui Wang,Zhiqun He +158 more
TL;DR: The Visual Object Tracking challenge VOT2018 is the sixth annual tracker benchmarking activity organized by the VOT initiative; results of over eighty trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years.
Proceedings ArticleDOI
The Seventh Visual Object Tracking VOT2019 Challenge Results
Matej Kristan,Amanda Berg,Linyu Zheng,Litu Rout,Luc Van Gool,Luca Bertinetto,Martin Danelljan,Matteo Dunnhofer,Meng Ni,Min Young Kim,Ming Tang,Ming-Hsuan Yang,Abdelrahman Eldesokey,Naveen Paluru,Niki Martinel,Pengfei Xu,Pengfei Zhang,Pengkun Zheng,Pengyu Zhang,Philip H. S. Torr,Qi Zhang Qiang Wang,Qing Guo,Radu Timofte,Jani Käpylä,Rama Krishna Sai Subrahmanyam Gorthi,Richard M. Everson,Ruize Han,Ruohan Zhang,Shan You,Shaochuan Zhao,Shengwei Zhao,Shihu Li,Shikun Li,Shiming Ge,Gustavo Fernandez,Shuai Bai,Shuosen Guan,Tengfei Xing,Tianyang Xu,Tianyu Yang,Ting Zhang,Tomas Vojir,Wei Feng,Weiming Hu,Weizhao Wang,Abel Gonzalez-Garcia,Wenjie Tang,Wenjun Zeng,Wenyu Liu,Xi Chen,Xi Qiu,Xiang Bai,Xiaojun Wu,Xiaoyun Yang,Xier Chen,Xin Li,Alireza Memarmoghadam,Xing Sun,Xingyu Chen,Xinmei Tian,Xu Tang,Xue-Feng Zhu,Yan Huang,Yanan Chen,Yanchao Lian,Yang Gu,Yang Liu,Andong Lu,Chen Yanjie,Yi Zhang,Yinda Xu,Yingming Wang,Yingping Li,Yu Zhou,Yuan Dong,Yufei Xu,Yunhua Zhang,Yunkun Li,Anfeng He,Zeyu Wang Zhao Luo,Zhaoliang Zhang,Zhen-Hua Feng,Zhenyu He,Zhichao Song,Zhihao Chen,Zhipeng Zhang,Zhirong Wu,Zhiwei Xiong,Zhongjian Huang,Anton Varfolomieiev,Zhu Teng,Zihan Ni,Antoni Chan,Jiri Matas,Ardhendu Shekhar Tripathi,Arnold W. M. Smeulders,Bala Suraj Pedasingu,Bao Xin Chen,Baopeng Zhang,Baoyuan Wu,Bi Li,Bin He,Bin Yan,Bing Bai,Ales Leonardis,Bing Li,Bo Li,Byeong Hak Kim,Chao Ma,Chen Fang,Chen Qian,Cheng Chen,Chenglong Li,Chengquan Zhang,Chi-Yi Tsai,Michael Felsberg,Chong Luo,Christian Micheloni,Chunhui Zhang,Dacheng Tao,Deepak K. Gupta,Dejia Song,Dong Wang,Efstratios Gavves,Eunu Yi,Fahad Shahbaz Khan,Roman Pflugfelder,Fangyi Zhang,Fei Wang,Fei Zhao,George De Ath,Goutam Bhat,Guangqi Chen,Guangting Wang,Guoxuan Li,Hakan Cevikalp,Hao Du,Joni-Kristian Kamarainen,Haojie Zhao,Hasan Saribas,Ho Min Jung,Hongliang Bai,Hongyuan Yu,Houwen Peng,Huchuan Lu,Hui Li,Jiakun Li,Luka Čehovin Zajc,Jianhua Li,Jianlong Fu,Jie Chen,Jie Gao,Jie Zhao,Jin Tang,Jing Li,Jingjing Wu,Jingtuo Liu,Jinqiao Wang,Ondrej Drbohlav,Jinqing Qi,Jinyue Zhang,John K. Tsotsos,Jong Hyuk Lee,Joost van de Weijer,Josef Kittler,Jun Ha Lee,Junfei Zhuang,Kangkai Zhang,Kangkang Wang,Alan Lukezic,Kenan Dai,Lei Chen,Lei Liu,Leida Guo,Li Zhang,Liang Wang,Liangliang Wang,Lichao Zhang,Lijun Wang,Lijun Zhou +179 more
TL;DR: The Visual Object Tracking challenge VOT2019 is the seventh annual tracker benchmarking activity organized by the VOT initiative; results of 81 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years.
Proceedings ArticleDOI
CoupleNet: Coupling Global Structure with Local Parts for Object Detection
TL;DR: CoupleNet as discussed by the authors proposes a fully convolutional network, named CoupleNet, to couple the global structure with local parts for object detection, where the object proposals obtained by the RPN are fed into the coupling module which consists of two branches.
Journal ArticleDOI
Attention CoupleNet: Fully Convolutional Attention Coupling Network for Object Detection
TL;DR: This paper proposes a novel fully convolutional network, named as Attention CoupleNet, to incorporate the attention-related information and global and local information of objects to improve the detection performance.
Proceedings Article
Learning Coarse-to-Fine Structured Feature Embedding for Vehicle Re-Identification.
TL;DR: This paper learns a structured feature embedding for vehicle re-ID with a novel coarse-to-fine ranking loss to pull images of the same vehicle as close as possible and achieve discrimination between images from different vehicles as well as vehicles from different vehicle models.