OTB Results

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Benchmark Results

The trackers are ordered by the average overlap scores.

• AUC and Precision are the standard metrics.
• Deep Learning: deep learning features, deep learning method and RL.
• RealTime: Speeds from the original paper, not test on the same platform. (just focus magnitude)

Tracker	AUC-CVPR2013	Precision-CVPR2013	AUC-OTB100	Precision-OTB100	AUC-OTB50	Precision-OTB50	Deep Learning	RealTime
ECO	0.709	0.93	0.694	0.910	0.643	0.874	Y	N(6)
MDNet	0.708	0.948	0.678	0.909	0.645	0.890	Y	N(1)
SANet	0.686	0.95	0.692	0.928	-	-	Y	N(1)
BranchOut			0.678	0.917			Y	N(1)
TCNN	0.682	0.937	0.654	0.884	-	-	Y	N(1)
TSN			0.644	0.868	0.58	0.809	Y	N(1)
CRT	-	-	0.642	0.875	0.594	0.835	Y	N(1.3)
BACF	0.678		0.63				N	Y(35)
MCPF	0.677	0.916	0.628	0.873			Y	N(0.5)
CREST	0.673	0.908	0.623	0.837	-	-	Y	N(1)
C-COT	0.672	0.899	0.682	-	-	-	Y	N(0.3)
DNT	0.664	0.907	0.627	0.851	-	-	Y	N(5)
PTAV	0.663	0.894	0.635	0.849			Y	Y(25)
ADNet	0.659	0.903	0.646	0.88			Y	N(3)
DSiamM	0.656	0.891					Y	Y(25)
SINT+	0.655	0.882	-	-	-	-	Y	N(4)
DRT	0.655	0.892	-	-	-	-	Y	N(0.8)
RDT	0.654	-	0.603	-	-	-	Y	Y(43)
SRDCFdecon	0.653	0.87	0.627	0.825	0.56	0.764	N	N(1)
DeepLMCF	0.643	0.892					Y	N(8)
MUSTer	0.641	0.865	0.575	0.774	-	-	N	N(4)
DeepSRDCF	0.641	0.849	0.635	0.851	0.56	0.772	Y	N(<1)
EAST	0.638						Y	Y(23/159)
SINT	0.635	0.851	-	-	-	-	Y	N(4)
LCT	0.628	0.848	0.562	0.762	0.492	0.691	N	Y(27)
SRDCF	0.626	0.838	0.598	0.789	0.539	0.732	N	N(5)
LMCF	0.624	0.839	0.568				N	Y(85)
SCF	0.623	0.874	-	-	-	-	N	Y(35)
Staple_CA	0.621	0.833	0.598	0.81			N	Y(35)
RaF	0.615	0.919					Y	N(2)
SiamFC	0.612	0.815	-	-	-	-	Y	Y(58)
RFL			0.581				Y	Y(15)
CFNet_conv2	0.611	0.807	0.568	0.748	0.53	0.702	Y	Y(75)
SiamFC_{3s}	0.608	0.809	-	-	-	-	Y	Y(86)
ACFN	0.607	0.86	0.575	0.802			Y	Y(15)
CF2	0.605	0.891	0.562	0.837	0.513	0.803	Y	N(11)
HDT	0.603	0.889	0.654	0.848	0.515	0.804	Y	N(10)
Staple	0.6	0.793	0.578	0.784	-	-	N	Y(80)
CSR-DCF	0.599	0.8	0.598	0.733			N	Y(13)
FCNT	0.599	0.856	-	-	-	-	Y	N(1)
CNN-SVM	0.597	0.852	0.554	0.814	0.512	0.769	Y	N
SCT	0.595	0.845	-	-	-	-	Y	Y(40)
SO-DLT	0.595	0.81	-	-	-	-	Y	N
BIT	0.593	0.817	-	-	-	-	N	Y(45)
DLSSVM	0.589	0.829	0.541	0.767	-	-	Y	N(10)
SAMF	0.579	0.785	0.535	0.743	-	-	N	N(7)
RPT	0.577	0.805	-	-	-	-	N	N(4)
MEEM	0.566	0.83	0.53	0.781	0.473	0.712	N	N(10)
DSST	0.554	0.737	0.52	0.693	0.463	0.625	N	Y(24)
CNT	0.545	0.723	-	-	-	-	Y	N(1.5)
TGPR	0.529	0.766	0.458	0.643	-	-	N	N(1)
KCF	0.514	0.74	0.477	0.693	0.403	0.611	N	Y(172)
GOTURN	0.444	0.62	0.427	0.572	-	-	Y	Y(165)

Visual Trackers

NIPS2018

• DAT: Shi Pu, Yibing Song, Chao Ma, Honggang Zhang, Ming-Hsuan Yang.
  "Deep Attentive Tracking via Reciprocative Learning." NIPS (2018). [paper] [project] [code]

ECCV2018

• UPDT: Goutam Bhat, Joakim Johnander, Martin Danelljan, Fahad Shahbaz Khan, Michael Felsberg.
  "Unveiling the Power of Deep Tracking." ECCV (2018). [paper]

• DaSiamRPN: Zheng Zhu, Qiang Wang, Bo Li, Wu Wei, Junjie Yan, Weiming Hu.
  "Distractor-aware Siamese Networks for Visual Object Tracking." ECCV (2018). [paper] [github]

• SACF: Mengdan Zhang, Qiang Wang, Junliang Xing, Jin Gao, Peixi Peng, Weiming Hu, Steve Maybank.
  "Visual Tracking via Spatially Aligned Correlation Filters Network." ECCV (2018). [paper]

• RTINet: Yingjie Yao, Xiaohe Wu, Lei Zhang, Shiguang Shan, Wangmeng Zuo.
  "Joint Representation and Truncated Inference Learning for Correlation Filter based Tracking." ECCV (2018). [paper]

• Meta-Tracker: Eunbyung Park, Alexander C. Berg.
  "Meta-Tracker: Fast and Robust Online Adaptation for Visual Object Trackers." [paper] [github]

• DSLT: Xiankai Lu, Chao Ma*, Bingbing Ni, Xiaokang Yang, Ian Reid, Ming-Hsuan Yang.
  "Deep Regression Tracking with Shrinkage Loss." ECCV (2018). [paper] [github]

• DRL-IS: Liangliang Ren, Xin Yuan, Jiwen Lu, Ming Yang, Jie Zhou.
  "Deep Reinforcement Learning with Iterative Shift for Visual Tracking." ECCV (2018). [paper]

• RT-MDNet: Ilchae Jung, Jeany Son, Mooyeol Baek, Bohyung Han.
  "Real-Time MDNet." ECCV (2018). [paper]

• ACT: Boyu Chen, Dong Wang, Peixia Li, Huchuan Lu.
  "Real-time 'Actor-Critic' Tracking." ECCV (2018). [paper] [github]

• StructSiam: Yunhua Zhang, Lijun Wang, Dong Wang, Mengyang Feng, Huchuan Lu, Jinqing Qi.
  "Structured Siamese Network for Real-Time Visual Tracking." ECCV (2018). [paper]

• MemTrack: Tianyu Yang, Antoni B. Chan.
  "Learning Dynamic Memory Networks for Object Tracking." ECCV (2018). [paper]

• SiamFC-tri: Xingping Dong, Jianbing Shen.
  "Triplet Loss in Siamese Network for Object Tracking." ECCV (2018). [paper] [github]

• OxUvA long-term dataset+benchmark: Jack Valmadre, Luca Bertinetto, João F. Henriques, Ran Tao, Andrea Vedaldi, Arnold Smeulders, Philip Torr, Efstratios Gavves.
  "Long-term Tracking in the Wild: a Benchmark." ECCV (2018). [paper] [project]

• TrackingNet: Matthias Müller, Adel Bibi, Silvio Giancola, Salman Al-Subaihi, Bernard Ghanem.
  "TrackingNet: A Large-Scale Dataset and Benchmark for Object Tracking in the Wild." ECCV (2018). [paper] [project]

CVPR2018

• VITAL: Yibing Song, Chao Ma, Xiaohe Wu, Lijun Gong, Linchao Bao, Wangmeng Zuo, Chunhua Shen, Rynson Lau, and Ming-Hsuan Yang. "VITAL: VIsual Tracking via Adversarial Learning." CVPR (2018 Spotlight). [project] [paper] [github]

• LSART: Chong Sun, Dong Wang, Huchuan Lu, Ming-Hsuan Yang. "Learning Spatial-Aware Regressions for Visual Tracking." CVPR (2018 Spotlight). [paper]

• SiamRPN: Bo Li, Wei Wu, Zheng Zhu, Junjie Yan. "High Performance Visual Tracking with Siamese Region Proposal Network." CVPR (2018 Spotlight). [paper]

• TRACA: Jongwon Choi, Hyung Jin Chang, Tobias Fischer, Sangdoo Yun, Kyuewang Lee, Jiyeoup Jeong, Yiannis Demiris, Jin Young Choi. "Context-aware Deep Feature Compression for High-speed Visual Tracking." CVPR (2018). [project] [paper]

• RASNet: Qiang Wang, Zhu Teng, Junliang Xing, Jin Gao, Weiming Hu, Stephen Maybank. "Learning Attentions: Residual Attentional Siamese Network for High Performance Online Visual Tracking." CVPR 2018. [paper]

• SA-Siam: Anfeng He, Chong Luo, Xinmei Tian, Wenjun Zeng. "A Twofold Siamese Network for Real-Time Object Tracking." CVPR (2018). [paper]

• STRCF: Feng Li, Cheng Tian, Wangmeng Zuo, Lei Zhang, Ming-Hsuan Yang. "Learning Spatial-Temporal Regularized Correlation Filters for Visual Tracking." CVPR (2018). [paper] [github]

• FlowTrack: Zheng Zhu, Wei Wu, Wei Zou, Junjie Yan. "End-to-end Flow Correlation Tracking with Spatial-temporal Attention." CVPR (2018). [paper]

• DEDT: Kourosh Meshgi, Shigeyuki Oba, Shin Ishii. "Efficient Diverse Ensemble for Discriminative Co-Tracking." CVPR (2018). [paper]

• SINT++: Xiao Wang, Chenglong Li, Bin Luo, Jin Tang. "SINT++: Robust Visual Tracking via Adversarial Positive Instance Generation." CVPR (2018). [paper]

• DRT: Chong Sun, Dong Wang, Huchuan Lu, Ming-Hsuan Yang. "Correlation Tracking via Joint Discrimination and Reliability Learning." CVPR (2018). [paper]

• MCCT: Ning Wang, Wengang Zhou, Qi Tian, Richang Hong, Meng Wang, Houqiang Li. "Multi-Cue Correlation Filters for Robust Visual Tracking." CVPR (2018). [paper] [github]

• MKCF: Ming Tang, Bin Yu, Fan Zhang, Jinqiao Wang. "High-speed Tracking with Multi-kernel Correlation Filters." CVPR (2018). [paper]

• HP: Xingping Dong, Jianbing Shen, Wenguan Wang, Yu, Liu, Ling Shao, and Fatih Porikli. "Hyperparameter Optimization for Tracking with Continuous Deep Q-Learning." CVPR (2018). [paper]

NIPS2017

• HART: Adam R. Kosiorek, Alex Bewley, Ingmar Posner. "Hierarchical Attentive Recurrent Tracking." NIPS (2017). [paper] [github]

ICCV2017

• CREST: Yibing Song, Chao Ma, Lijun Gong, Jiawei Zhang, Rynson Lau, Ming-Hsuan Yang. "CREST: Convolutional Residual Learning for Visual Tracking." ICCV (2017 Spotlight). [paper] [project] [github]

• EAST: Chen Huang, Simon Lucey, Deva Ramanan. "Learning Policies for Adaptive Tracking with Deep Feature Cascades." ICCV (2017 Spotlight). [paper] [supp]

• PTAV: Heng Fan and Haibin Ling. "Parallel Tracking and Verifying: A Framework for Real-Time and High Accuracy Visual Tracking." ICCV (2017). [paper] [supp] [project] [code]

• BACF: Hamed Kiani Galoogahi, Ashton Fagg, Simon Lucey. "Learning Background-Aware Correlation Filters for Visual Tracking." ICCV (2017). [paper] [supp] [code] [project]

• TSN: Zhu Teng, Junliang Xing, Qiang Wang, Congyan Lang, Songhe Feng and Yi Jin. "Robust Object Tracking based on Temporal and Spatial Deep Networks." ICCV (2017). [paper]

• p-tracker: James Supančič, III; Deva Ramanan. "Tracking as Online Decision-Making: Learning a Policy From Streaming Videos With Reinforcement Learning." ICCV (2017). [paper] [supp]

• DSiam: Qing Guo; Wei Feng; Ce Zhou; Rui Huang; Liang Wan; Song Wang. "Learning Dynamic Siamese Network for Visual Object Tracking." ICCV (2017). [paper] [github]

• SP-KCF: Xin Sun; Ngai-Man Cheung; Hongxun Yao; Yiluan Guo. "Non-Rigid Object Tracking via Deformable Patches Using Shape-Preserved KCF and Level Sets." ICCV (2017). [paper]

• UCT: Zheng Zhu, Guan Huang, Wei Zou, Dalong Du, Chang Huang. "UCT: Learning Unified Convolutional Networks for Real-Time Visual Tracking." ICCV workshop (2017). [paper]

• Tobias Bottger, Patrick Follmann. "The Benefits of Evaluating Tracker Performance Using Pixel-Wise Segmentations." ICCV workshop (2017). [paper]

• CFWCR: Zhiqun He, Yingruo Fan, Junfei Zhuang, Yuan Dong, HongLiang Bai. "Correlation Filters With Weighted Convolution Responses." ICCV workshop (2017). [paper] [github]

• IBCCF: Feng Li, Yingjie Yao, Peihua Li, David Zhang, Wangmeng Zuo, Ming-Hsuan Yang. "Integrating Boundary and Center Correlation Filters for Visual Tracking With Aspect Ratio Variation." ICCV workshop (2017). [paper] [github]

• RFL: Tianyu Yang, Antoni B. Chan. "Recurrent Filter Learning for Visual Tracking." ICCV workshop (2017). [paper]

CVPR2017

• ECO: Martin Danelljan, Goutam Bhat, Fahad Shahbaz Khan, Michael Felsberg. "ECO: Efficient Convolution Operators for Tracking." CVPR (2017). [paper] [supp] [project] [github]

• CFNet: Jack Valmadre, Luca Bertinetto, João F. Henriques, Andrea Vedaldi, Philip H. S. Torr. "End-to-end representation learning for Correlation Filter based tracking." CVPR (2017). [paper] [supp] [project] [github]

• CACF: Matthias Mueller, Neil Smith, Bernard Ghanem. "Context-Aware Correlation Filter Tracking." CVPR (2017 oral). [paper] [supp] [project] [code]

• RaF: Le Zhang, Jagannadan Varadarajan, Ponnuthurai Nagaratnam Suganthan, Narendra Ahuja and Pierre Moulin "Robust Visual Tracking Using Oblique Random Forests." CVPR (2017). [paper] [supp] [project] [code]

• MCPF: Tianzhu Zhang, Changsheng Xu, Ming-Hsuan Yang. "Multi-Task Correlation Particle Filter for Robust Object Tracking." CVPR (2017). [paper] [project] [code]

• ACFN: Jongwon Choi, Hyung Jin Chang, Sangdoo Yun, Tobias Fischer, Yiannis Demiris, and Jin Young Choi. "Attentional Correlation Filter Network for Adaptive Visual Tracking." CVPR (2017). [paper] [supp] [project] [test code] [training code]

• LMCF: Mengmeng Wang, Yong Liu, Zeyi Huang. "Large Margin Object Tracking with Circulant Feature Maps." CVPR (2017). [paper] [zhihu]

• ADNet: Sangdoo Yun, Jongwon Choi, Youngjoon Yoo, Kimin Yun, Jin Young Choi. "Action-Decision Networks for Visual Tracking with Deep Reinforcement Learning." CVPR (2017 Spotlight). [paper] [supp] [project]

• CSR-DCF: Alan Lukežič, Tomáš Vojíř, Luka Čehovin, Jiří Matas, Matej Kristan. "Discriminative Correlation Filter with Channel and Spatial Reliability." CVPR (2017). [paper] [supp] [code]

• BranchOut: Bohyung Han, Jack Sim, Hartwig Adam. "BranchOut: Regularization for Online Ensemble Tracking with Convolutional Neural Networks." CVPR (2017). [paper]

• AMCT: Donghun Yeo, Jeany Son, Bohyung Han, Joonhee Han. "Superpixel-based Tracking-by-Segmentation using Markov Chains." CVPR (2017). [paper]

• SANet: Heng Fan, Haibin Ling. "SANet: Structure-Aware Network for Visual Tracking." CVPRW (2017). [paper] [project] [code]

ECCV2016

• SiameseFC: Luca Bertinetto, Jack Valmadre, João F. Henriques, Andrea Vedaldi, Philip H.S. Torr. "Fully-Convolutional Siamese Networks for Object Tracking." ECCV workshop (2016). [paper] [project] [github]

• GOTURN: David Held, Sebastian Thrun, Silvio Savarese. "Learning to Track at 100 FPS with Deep Regression Networks." ECCV (2016). [paper] [project] [github]

• C-COT: Martin Danelljan, Andreas Robinson, Fahad Khan, Michael Felsberg. "Beyond Correlation Filters: Learning Continuous Convolution Operators for Visual Tracking." ECCV (2016). [paper] [project] [github]

• CF+AT: Adel Bibi, Matthias Mueller, and Bernard Ghanem. "Target Response Adaptation for Correlation Filter Tracking." ECCV (2016). [paper] [project] [github]

• Yao Sui, Ziming Zhang, Guanghui Wang, Yafei Tang, Li Zhang. "Real-Time Visual Tracking: Promoting the Robustness of Correlation Filter Learning." ECCV (2016). [paper]

• Yao Sui, Guanghui Wang, Yafei Tang, Li Zhang. "Tracking Completion." ECCV (2016). [paper]

CVPR2016

• MDNet: Nam, Hyeonseob, and Bohyung Han. "Learning Multi-Domain Convolutional Neural Networks for Visual Tracking." CVPR (2016). [paper] [VOT_presentation] [project] [github]

• SINT: Ran Tao, Efstratios Gavves, Arnold W.M. Smeulders. "Siamese Instance Search for Tracking." CVPR (2016). [paper] [project]

• SCT: Jongwon Choi, Hyung Jin Chang, Jiyeoup Jeong, Yiannis Demiris, and Jin Young Choi. "Visual Tracking Using Attention-Modulated Disintegration and Integration." CVPR (2016). [paper] [project]

• STCT: Lijun Wang, Wanli Ouyang, Xiaogang Wang, and Huchuan Lu. "STCT: Sequentially Training Convolutional Networks for Visual Tracking." CVPR (2016). [paper] [github]

• SRDCFdecon: Martin Danelljan, Gustav Häger, Fahad Khan, Michael Felsberg. "Adaptive Decontamination of the Training Set: A Unified Formulation for Discriminative Visual Tracking." CVPR (2016). [paper] [project]

• HDT: Yuankai Qi, Shengping Zhang, Lei Qin, Hongxun Yao, Qingming Huang, Jongwoo Lim, Ming-Hsuan Yang. "Hedged Deep Tracking." CVPR (2016). [paper] [project]

• Staple: Luca Bertinetto, Jack Valmadre, Stuart Golodetz, Ondrej Miksik, Philip H.S. Torr. "Staple: Complementary Learners for Real-Time Tracking." CVPR (2016). [paper] [project] [github]

• EBT: Gao Zhu, Fatih Porikli, and Hongdong Li. "Beyond Local Search: Tracking Objects Everywhere with Instance-Specific Proposals." CVPR (2016). [paper] [exe]

• DLSSVM: Jifeng Ning, Jimei Yang, Shaojie Jiang, Lei Zhang and Ming-Hsuan Yang. "Object Tracking via Dual Linear Structured SVM and Explicit Feature Map." CVPR (2016). [paper] [code] [project]

NIPS2016

• Learnet: Luca Bertinetto, João F. Henriques, Jack Valmadre, Philip H. S. Torr, Andrea Vedaldi. "Learning feed-forward one-shot learners." NIPS (2016). [paper]

ICCV2015

• FCNT: Lijun Wang, Wanli Ouyang, Xiaogang Wang, and Huchuan Lu. "Visual Tracking with Fully Convolutional Networks." ICCV (2015). [paper] [project] [github]

• SRDCF: Martin Danelljan, Gustav Häger, Fahad Khan, Michael Felsberg. "Learning Spatially Regularized Correlation Filters for Visual Tracking." ICCV (2015). [paper] [project]

• CF2: Chao Ma, Jia-Bin Huang, Xiaokang Yang and Ming-Hsuan Yang. "Hierarchical Convolutional Features for Visual Tracking." ICCV (2015) [paper] [project] [github]

• Naiyan Wang, Jianping Shi, Dit-Yan Yeung and Jiaya Jia. "Understanding and Diagnosing Visual Tracking Systems." ICCV (2015). [paper] [project] [code]\

• DeepSRDCF: Martin Danelljan, Gustav Häger, Fahad Khan, Michael Felsberg. "Convolutional Features for Correlation Filter Based Visual Tracking." ICCV workshop (2015). [paper] [project]

• RAJSSC: Mengdan Zhang, Junliang Xing, Jin Gao, Xinchu Shi, Qiang Wang, Weiming Hu. "Joint Scale-Spatial Correlation Tracking with Adaptive Rotation Estimation." ICCV workshop (2015). [paper] [poster]

CVPR2015

• MUSTer: Zhibin Hong, Zhe Chen, Chaohui Wang, Xue Mei, Danil Prokhorov, Dacheng Tao. "MUlti-Store Tracker (MUSTer): A Cognitive Psychology Inspired Approach to Object Tracking." CVPR (2015). [paper] [project]

• LCT: Chao Ma, Xiaokang Yang, Chongyang Zhang, Ming-Hsuan Yang. "Long-term Correlation Tracking." CVPR (2015). [paper] [project] [github]

• DAT: Horst Possegger, Thomas Mauthner, and Horst Bischof. "In Defense of Color-based Model-free Tracking." CVPR (2015). [paper] [project] [code]

• RPT: Yang Li, Jianke Zhu and Steven C.H. Hoi. "Reliable Patch Trackers: Robust Visual Tracking by Exploiting Reliable Patches." CVPR (2015). [paper] [github]

ICML2015

• CNN-SVM: Seunghoon Hong, Tackgeun You, Suha Kwak and Bohyung Han. "Online Tracking by Learning Discriminative Saliency Map with Convolutional Neural Network ." ICML (2015) [paper] [project]

BMVC2014

• DSST: Martin Danelljan, Gustav Häger, Fahad Shahbaz Khan and Michael Felsberg. "Accurate Scale Estimation for Robust Visual Tracking." BMVC (2014). [paper] [PAMI] [project]

ECCV2014

• MEEM: Jianming Zhang, Shugao Ma, and Stan Sclaroff. "MEEM: Robust Tracking via Multiple Experts using Entropy Minimization." ECCV (2014). [paper] [project]

• TGPR: Jin Gao, Haibin Ling, Weiming Hu, Junliang Xing. "Transfer Learning Based Visual Tracking with Gaussian Process Regression." ECCV (2014). [paper] [project]

• STC: Kaihua Zhang, Lei Zhang, Ming-Hsuan Yang, David Zhang. "Fast Tracking via Spatio-Temporal Context Learning." ECCV (2014). [paper] [project]

• SAMF: Yang Li, Jianke Zhu. "A Scale Adaptive Kernel Correlation Filter Tracker with Feature Integration." ECCV workshop (2014). [paper] [github]

NIPS2013

• DLT: Naiyan Wang and Dit-Yan Yeung. "Learning A Deep Compact Image Representation for Visual Tracking." NIPS (2013). [paper] [project] [code]

PAMI & IJCV & TIP

• AOGTracker: Tianfu Wu , Yang Lu and Song-Chun Zhu. "Online Object Tracking, Learning and Parsing with And-Or Graphs." TPAMI (2017). [paper] [project] [github]

• MCPF: Tianzhu Zhang, Changsheng Xu, Ming-Hsuan Yang. " Learning Multi-task Correlation Particle Filters for Visual Tracking." TPAMI (2017). [[paper]] [project] [code]

• RSST: Tianzhu Zhang, Changsheng Xu, Ming-Hsuan Yang. " Robust Structural Sparse Tracking." TPAMI (2017). [[paper]] [project] [code]

• fDSST: Martin Danelljan, Gustav Häger, Fahad Khan, Michael Felsberg. "Discriminative Scale Space Tracking." TPAMI (2017). [paper] [project] [code]

• KCF: João F. Henriques, Rui Caseiro, Pedro Martins, Jorge Batista. "High-Speed Tracking with Kernelized Correlation Filters." TPAMI (2015). [paper] [project]

• CLRST: Tianzhu Zhang, Si Liu, Narendra Ahuja, Ming-Hsuan Yang, Bernard Ghanem.
  "Robust Visual Tracking Via Consistent Low-Rank Sparse Learning." IJCV (2015). [paper] [project] [code]

• DNT: Zhizhen Chi, Hongyang Li, Huchuan Lu, Ming-Hsuan Yang. "Dual Deep Network for Visual Tracking." TIP (2017). [paper]

• DRT: Junyu Gao, Tianzhu Zhang, Xiaoshan Yang, Changsheng Xu. "Deep Relative Tracking." TIP (2017). [paper]

• BIT: Bolun Cai, Xiangmin Xu, Xiaofen Xing, Kui Jia, Jie Miao, Dacheng Tao. "BIT: Biologically Inspired Tracker." TIP (2016). [paper] [project] [github]

• CNT: Kaihua Zhang, Qingshan Liu, Yi Wu, Minghsuan Yang. "Robust Visual Tracking via Convolutional Networks Without Training." TIP (2016). [paper] [code]

ArXiv

• MLT: Janghoon Choi, Junseok Kwon, Kyoung Mu Lee. "Deep Meta Learning for Real-Time Visual Tracking based on Target-Specific Feature Space." arXiv (2017). [paper]

• STECF: Yang Li, Jianke Zhu, Wenjie Song, Zhefeng Wang, Hantang Liu, Steven C. H. Hoi. "Robust Estimation of Similarity Transformation for Visual Object Tracking with Correlation Filters." arXiv (2017). [paper]

• PAWSS: Xiaofei Du, Alessio Dore, Danail Stoyanov. "Patch-based adaptive weighting with segmentation and scale (PAWSS) for visual tracking." arXiv (2017). [paper]

• SFT: Zhen Cui, You yi Cai, Wen ming Zheng, Jian Yang. "Spectral Filter Tracking." arXiv (2017). [paper]

• Re3: Daniel Gordon, Ali Farhadi, Dieter Fox. "Re3 : Real-Time Recurrent Regression Networks for Object Tracking." arXiv (2017). [paper]

• DCFNet: Qiang Wang, Jin Gao, Junliang Xing, Mengdan Zhang, Weiming Hu. "DCFNet: Discriminant Correlation Filters Network for Visual Tracking." arXiv (2017). [paper] [code]

• TCNN: Hyeonseob Nam, Mooyeol Baek, Bohyung Han. "Modeling and Propagating CNNs in a Tree Structure for Visual Tracking." arXiv (2016). [paper] [code]

• RDT: Janghoon Choi, Junseok Kwon, Kyoung Mu Lee. "Visual Tracking by Reinforced Decision Making." arXiv (2017). [paper]

• MSDAT: Xinyu Wang, Hanxi Li, Yi Li, Fumin Shen, Fatih Porikli . "Robust and Real-time Deep Tracking Via Multi-Scale Domain Adaptation." arXiv (2017). [paper]

• RLT: Da Zhang, Hamid Maei, Xin Wang, Yuan-Fang Wang. "Deep Reinforcement Learning for Visual Object Tracking in Videos." arXiv (2017). [paper]

• SCF: Wangmeng Zuo, Xiaohe Wu, Liang Lin, Lei Zhang, Ming-Hsuan Yang. "Learning Support Correlation Filters for Visual Tracking." arXiv (2016). [paper] [project]

• CRT: Kai Chen, Wenbing Tao. "Convolutional Regression for Visual Tracking." arXiv (2016). [paper]

• BMR: Kaihua Zhang, Qingshan Liu, and Ming-Hsuan Yang. "Visual Tracking via Boolean Map Representations." arXiv (2016). [paper]

• YCNN: Kai Chen, Wenbing Tao. "Once for All: a Two-flow Convolutional Neural Network for Visual Tracking." arXiv (2016). [paper]

• ROLO: Guanghan Ning, Zhi Zhang, Chen Huang, Zhihai He, Xiaobo Ren, Haohong Wang. "Spatially Supervised Recurrent Convolutional Neural Networks for Visual Object Tracking." arXiv (2016). [paper] [project] [github]

• RATM: Samira Ebrahimi Kahou, Vincent Michalski, Roland Memisevic. "RATM: Recurrent Attentive Tracking Model." arXiv (2015). [paper] [github]

• SO-DLT: Naiyan Wang, Siyi Li, Abhinav Gupta, Dit-Yan Yeung. "Transferring Rich Feature Hierarchies for Robust Visual Tracking." arXiv (2015). [paper] [code]

• DMSRDCF: Susanna Gladh, Martin Danelljan, Fahad Shahbaz Khan, Michael Felsberg. "Deep Motion Features for Visual Tracking." ICPR Best Paper (2016). [paper]

Benchmark

• LaSOT: Heng Fan, Liting Lin, Fan Yang, Peng Chu, Ge Deng, Sijia Yu, Hexin Bai, Yong Xu, Chunyuan Liao, Haibin Ling. "Deep Meta Learning for Real-Time Visual Tracking based on Target-Specific Feature Space." arXiv (2018). [paper] [project]

• OxUvA long-term dataset+benchmark: Jack Valmadre, Luca Bertinetto, João F. Henriques, Ran Tao, Andrea Vedaldi, Arnold Smeulders, Philip Torr, Efstratios Gavves.
  "Long-term Tracking in the Wild: a Benchmark." ECCV (2018). [paper] [project]

• TrackingNet: Matthias Müller, Adel Bibi, Silvio Giancola, Salman Al-Subaihi, Bernard Ghanem.
  "TrackingNet: A Large-Scale Dataset and Benchmark for Object Tracking in the Wild." ECCV (2018). [project] [paper]

• UAVDT: Dawei Du, Yuankai Qi, Hongyang Yu, Yifang Yang, Kaiwen Duan, GuoRong Li, Weigang Zhang, Weihai; Qingming Huang, Qi Tian.
  "The Unmanned Aerial Vehicle Benchmark: Object Detection and Tracking." ECCV (2018). [paper]

• Dataset-AMP: Luka Čehovin Zajc; Alan Lukežič; Aleš Leonardis; Matej Kristan. "Beyond Standard Benchmarks: Parameterizing Performance Evaluation in Visual Object Tracking." ICCV (2017). [paper]

• Dataset-Nfs: Hamed Kiani Galoogahi, Ashton Fagg, Chen Huang, Deva Ramanan and Simon Lucey. "Need for Speed: A Benchmark for Higher Frame Rate Object Tracking." ICCV (2017) [paper] [supp] [project]

• Dataset-DTB70: Siyi Li, Dit-Yan Yeung. "Visual Object Tracking for Unmanned Aerial Vehicles: A Benchmark and New Motion Models." AAAI (2017) [paper] [project] [dataset]

• Dataset-UAV123: Matthias Mueller, Neil Smith and Bernard Ghanem. "A Benchmark and Simulator for UAV Tracking." ECCV (2016) [paper] [project] [dataset]

• Dataset-TColor-128: Pengpeng Liang, Erik Blasch, Haibin Ling. "Encoding color information for visual tracking: Algorithms and benchmark." TIP (2015) [paper] [project] [dataset]

• Dataset-NUS-PRO: Annan Li, Min Lin, Yi Wu, Ming-Hsuan Yang, and Shuicheng Yan. "NUS-PRO: A New Visual Tracking Challenge." PAMI (2015) [paper] [project] [Data_360(code:bf28)] [Data_baidu]] [View_360(code:515a)] [View_baidu]]

• Dataset-PTB: Shuran Song and Jianxiong Xiao. "Tracking Revisited using RGBD Camera: Unified Benchmark and Baselines." ICCV (2013) [paper] [project] [5 validation] [95 evaluation]

• Dataset-ALOV300+: Arnold W. M. Smeulders, Dung M. Chu, Rita Cucchiara, Simone Calderara, Afshin Dehghan, Mubarak Shah. "Visual Tracking: An Experimental Survey." PAMI (2014) [paper] [project] Mirror Link:ALOV300++ Dataset Mirror Link:ALOV300++ Groundtruth

• OTB2013: Wu, Yi, Jongwoo Lim, and Minghsuan Yang. "Online Object Tracking: A Benchmark." CVPR (2013). [paper]

• OTB2015: Wu, Yi, Jongwoo Lim, and Minghsuan Yang. "Object Tracking Benchmark." TPAMI (2015). [paper] [project]

• Dataset-VOT: [project]

[VOT13_paper_ICCV]The Visual Object Tracking VOT2013 challenge results

[VOT14_paper_ECCV]The Visual Object Tracking VOT2014 challenge results

[VOT15_paper_ICCV]The Visual Object Tracking VOT2015 challenge results

[VOT16_paper_ECCV]The Visual Object Tracking VOT2016 challenge results

[VOT17_paper_ICCV]The Visual Object Tracking VOT2017 challenge results

Distinguished Researchers & Teams

Distinguished visual tracking researchers who have published +3 papers which have a major impact on the field of visual tracking and are still active in the field of visual tracking.(Names listed in no particular order.)

• Ming-Hsuan Yang
• Haibin Ling
• Huchuan Lu
• Hongdong Li
• Lei Zhang
• Matej Kristan
• João F. Henriques
• Martin Danelljan
• Kaihua Zhang
• Hamed Kiani
• Luca Bertinetto
• Tianzhu Zhang
• Chao Ma
• Yibing Song
• Torr Vision Group
• Computer Vision Laboratory, POSTECH