Y
Yang Li
Researcher at Zhejiang University
Publications - 30
Citations - 3806
Yang Li is an academic researcher from Zhejiang University. The author has contributed to research in topics: Video tracking & Deep learning. The author has an hindex of 12, co-authored 25 publications receiving 3164 citations. Previous affiliations of Yang Li include East China Normal University.
Papers
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Book ChapterDOI
A Scale Adaptive Kernel Correlation Filter Tracker with Feature Integration
Yang Li,Jianke Zhu +1 more
TL;DR: This paper presents a very appealing tracker based on the correlation filter framework and suggests an effective scale adaptive scheme to tackle the problem of the fixed template size in kernel correlation filter tracker.
Book ChapterDOI
The Visual Object Tracking VOT2016 Challenge Results
Matej Kristan,Ales Leonardis,Jiří Matas,Michael Felsberg,Roman Pflugfelder,Luka Cehovin,Tomas Vojir,Gustav Häger,Alan Lukežič,Gustavo Fernandez,Abhinav Gupta,Alfredo Petrosino,Alireza Memarmoghadam,Alvaro Garcia-Martin,Andres Solis Montero,Andrea Vedaldi,Andreas Robinson,Andy J. Ma,Anton Varfolomieiev,A. Aydin Alatan,Aykut Erdem,Bernard Ghanem,Bin Liu,Bohyung Han,Brais Martinez,Chang-Ming Chang,Changsheng Xu,Chong Sun,Daijin Kim,Dapeng Chen,Dawei Du,Deepak Mishra,Dit-Yan Yeung,Erhan Gundogdu,Erkut Erdem,Fahad Shahbaz Khan,Fatih Porikli,Fatih Porikli,Fei Zhao,Filiz Bunyak,Francesco Battistone,Gao Zhu,Giorgio Roffo,Gorthi R. K. Sai Subrahmanyam,Guilherme Sousa Bastos,Guna Seetharaman,Henry Medeiros,Hongdong Li,Honggang Qi,Horst Bischof,Horst Possegger,Huchuan Lu,Hyemin Lee,Hyeonseob Nam,Hyung Jin Chang,Isabela Drummond,Jack Valmadre,Jae-chan Jeong,Jaeil Cho,Jae-Yeong Lee,Jianke Zhu,Jiayi Feng,Jin Gao,Jin-Young Choi,Jingjing Xiao,Ji-Wan Kim,Jiyeoup Jeong,João F. Henriques,Jochen Lang,Jongwon Choi,José M. Martínez,Junliang Xing,Junyu Gao,Kannappan Palaniappan,Karel Lebeda,Ke Gao,Krystian Mikolajczyk,Lei Qin,Lijun Wang,Longyin Wen,Luca Bertinetto,Madan Kumar Rapuru,Mahdieh Poostchi,Mario Edoardo Maresca,Martin Danelljan,Matthias Mueller,Mengdan Zhang,Michael Arens,Michel Valstar,Ming Tang,Mooyeol Baek,Muhammad Haris Khan,Naiyan Wang,Nana Fan,Noor M. Al-Shakarji,Ondrej Miksik,Osman Akin,Payman Moallem,Pedro Senna,Philip H. S. Torr,Pong C. Yuen,Qingming Huang,Qingming Huang,Rafael Martin-Nieto,Rengarajan Pelapur,Richard Bowden,Robert Laganiere,Rustam Stolkin,Ryan Walsh,Sebastian B. Krah,Shengkun Li,Shengping Zhang,Shizeng Yao,Simon Hadfield,Simone Melzi,Siwei Lyu,Siyi Li,Stefan Becker,Stuart Golodetz,Sumithra Kakanuru,Sunglok Choi,Tao Hu,Thomas Mauthner,Tianzhu Zhang,Tony P. Pridmore,Vincenzo Santopietro,Weiming Hu,Wenbo Li,Wolfgang Hübner,Xiangyuan Lan,Xiaomeng Wang,Xin Li,Yang Li,Yiannis Demiris,Yifan Wang,Yuankai Qi,Zejian Yuan,Zexiong Cai,Zhan Xu,Zhenyu He,Zhizhen Chi +140 more
TL;DR: The Visual Object Tracking challenge VOT2016 goes beyond its predecessors by introducing a new semi-automatic ground truth bounding box annotation methodology and extending the evaluation system with the no-reset experiment.
Proceedings ArticleDOI
The Visual Object Tracking VOT2017 Challenge Results
Matej Kristan,Ales Leonardis,Jiri Matas,Michael Felsberg,Roman Pflugfelder,Luka Čehovin Zajc,Tomas Vojir,Gustav Häger,Alan Lukezic,Abdelrahman Eldesokey,Gustavo Fernandez,Alvaro Garcia-Martin,Andrej Muhič,Alfredo Petrosino,Alireza Memarmoghadam,Andrea Vedaldi,Antoine Manzanera,Antoine Tran,A. Aydin Alatan,Bogdan Mocanu,Boyu Chen,Chang Huang,Changsheng Xu,Chong Sun,Dalong Du,David Zhang,Dawei Du,Deepak Mishra,Erhan Gundogdu,Erhan Gundogdu,Erik Velasco-Salido,Fahad Shahbaz Khan,Francesco Battistone,Gorthi R. K. Sai Subrahmanyam,Goutam Bhat,Guan Huang,Guilherme Sousa Bastos,Guna Seetharaman,Hongliang Zhang,Houqiang Li,Huchuan Lu,Isabela Drummond,Jack Valmadre,Jae-chan Jeong,Jaeil Cho,Jae-Yeong Lee,Jana Noskova,Jianke Zhu,Jin Gao,Jingyu Liu,Ji-Wan Kim,João F. Henriques,José M. Martínez,Junfei Zhuang,Junliang Xing,Junyu Gao,Kai Chen,Kannappan Palaniappan,Karel Lebeda,Ke Gao,Kris M. Kitani,Lei Zhang,Lijun Wang,Lingxiao Yang,Longyin Wen,Luca Bertinetto,Mahdieh Poostchi,Martin Danelljan,Matthias Mueller,Mengdan Zhang,Ming-Hsuan Yang,Nianhao Xie,Ning Wang,Ondrej Miksik,Payman Moallem,Pallavi Venugopal M,Pedro Senna,Philip H. S. Torr,Qiang Wang,Qifeng Yu,Qingming Huang,Rafael Martin-Nieto,Richard Bowden,Risheng Liu,Ruxandra Tapu,Simon Hadfield,Siwei Lyu,Stuart Golodetz,Sunglok Choi,Tianzhu Zhang,Titus Zaharia,Vincenzo Santopietro,Wei Zou,Weiming Hu,Wenbing Tao,Wenbo Li,Wengang Zhou,Xianguo Yu,Xiao Bian,Yang Li,Yifan Xing,Yingruo Fan,Zheng Zhu,Zhipeng Zhang,Zhiqun He +104 more
TL;DR: The Visual Object Tracking challenge VOT2017 is the fifth annual tracker benchmarking activity organized by the VOT initiative; results of 51 trackers are presented; many are state-of-the-art published at major computer vision conferences or journals in recent years.
Book ChapterDOI
The Visual Object Tracking VOT2014 challenge results
Matej Kristan,Roman Pflugfelder,Ales Leonardis,Jiri Matas,Luka Cehovin,Georg Nebehay,Tomas Vojir,Gustavo Fernandez,Alan Lukezic,Aleksandar Dimitriev,Alfredo Petrosino,Amir Saffari,Bo Li,Bohyung Han,Cherkeng Heng,Christophe Garcia,Dominik Pangersic,Gustav Häger,Fahad Shahbaz Khan,Franci Oven,Horst Possegger,Horst Bischof,Hyeonseob Nam,Jianke Zhu,Jijia Li,Jin-Young Choi,Jin-Woo Choi,João F. Henriques,Joost van de Weijer,Jorge Batista,Karel Lebeda,Kristoffer Öfjäll,Kwang Moo Yi,Lei Qin,Longyin Wen,Mario Edoardo Maresca,Martin Danelljan,Michael Felsberg,Ming-Ming Cheng,Philip H. S. Torr,Qingming Huang,Richard Bowden,Sam Hare,Samantha Yueying Lim,Seunghoon Hong,Shengcai Liao,Simon Hadfield,Stan Z. Li,Stefan Duffner,Stuart Golodetz,Thomas Mauthner,Vibhav Vineet,Weiyao Lin,Yang Li,Yuankai Qi,Zhen Lei,Zhiheng Niu +56 more
TL;DR: The evaluation protocol of the VOT2013 challenge and the results of a comparison of 27 trackers on the benchmark dataset are presented, offering a more systematic comparison of the trackers.
Proceedings ArticleDOI
Reliable Patch Trackers: Robust visual tracking by exploiting reliable patches
TL;DR: A tracking reliability metric is presented to measure how reliably a patch can be tracked, where a probability model is proposed to estimate the distribution of reliable patches under a sequential Monte Carlo framework.