OTB Results

https://github.com/foolwood/benchmark_results

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 All results in [Baidu Yun] 

Benchmark Results

The trackers are ordered by the average overlap scores.

• AUC and Precision are the standard metrics.

Tracker	AUC-CVPR2013	Precision-CVPR2013	AUC-OTB100	Precision-OTB100	AUC-OTB50	Precision-OTB50	Deep Learning
ECO	-	-	0.694	-	-	-	Y
SANet	-	-	0.692	0.928	-	-	Y
MDNet	0.708	0.948	0.678	0.909	0.645	0.890	Y
TCNN	0.682	0.937	0.654	0.884	-	-	Y
C-COT	0.673	0.899	0.671	0.898	0.614	0.843	N
CRT	-	-	0.644	0.875	0.594	0.835	N
DNT	0.664	0.907	0.627	0.851	-	-	Y
SINT+	0.655	0.882	-	-	-	-	Y
DRT	0.655	0.892	-	-	-	-	Y
RDT	0.654	-	0.603	-	-	-	Y
SRDCFdecon	0.653	0.870	0.627	0.825	0.560	0.764	N
DeepLMCF	0.643	0.892	-	-	-	-	Y
MUSTer	0.641	0.865	0.575	0.774	-	-	N
DeepSRDCF	0.641	0.849	0.635	0.851	0.560	0.772	Y
SINT	0.635	0.851	-	-	-	-	Y
LCT	0.628	0.848	0.562	0.762	0.492	0.691	N
SRDCF	0.626	0.838	0.598	0.789	0.539	0.732	N
LMCF	0.624	0.839	-	-	-	-	N
SCF	0.623	0.874	-	-	-	-	N
SiamFC	0.612	0.815	-	-	-	-	Y
SiamFC_{3s}	0.608	0.809	0.582	0.773	-	-	Y
CF2	0.605	0.891	0.562	0.837	0.513	0.803	Y
HDT	0.603	0.889	0.654	0.848	0.515	0.804	Y
Staple	0.600	0.793	0.578	0.784	-	-	N
FCNT	0.599	0.856	-	-	-	-	Y
CNN-SVM	0.597	0.852	0.554	0.814	0.512	0.769	Y
SCT	0.595	0.845	-	-	-	-	Y
SO-DLT	0.595	0.810	-	-	-	-	Y
BIT	0.593	0.817	-	-	-	-	N
DLSSVM	0.589	0.829	0.541	0.767	-	-	Y
SAMF	0.579	0.785	0.535	0.743	-	-	N
RPT	0.577	0.805	-	-	-	-	N
MEEM	0.566	0.830	0.530	0.781	0.473	0.712	N
DSST	0.554	0.737	0.520	0.693	0.463	0.625	N
CNT	0.545	0.723	-	-	-	-	Y
TGPR	0.529	0.766	0.458	0.643	-	-	N
KCF	0.514	0.740	0.477	0.693	0.403	0.611	N
GOTURN	0.444	0.620	0.427	0.572	-	-	Y

Visual Trackers

• 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]

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

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

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

• 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]

• 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]

• 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]

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

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

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

• 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]

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

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

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

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

• 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]

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

• 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]

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

Others

• 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]

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

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

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

• SANet: Heng Fan, Haibin Ling. "SANet: Structure-Aware Network for Visual Tracking." arXiv (2016). [paper]

• 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]

• CSR-DCF: Alan Lukežič, Tomáš Vojíř, Luka Čehovin, Jiří Matas, Matej Kristan. "Discriminative Correlation Filter with Channel and Spatial Reliability." arXiv (2016). [paper]

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

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

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

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

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

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

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

• 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]

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

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

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

• Dataset-MoBe2016: Luka Čehovin, Alan Lukežič, Aleš Leonardis, Matej Kristan. "Beyond standard benchmarks: Parameterizing performance evaluation in visual object tracking." arXiv (2016). [paper]

• 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

• 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-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

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, I will continue to supplement this part.)

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

Benchmark

• Wu, Yi, Jongwoo Lim, and Minghsuan Yang. "Online Object Tracking: A Benchmark." CVPR (2013). [paper]
• Wu, Yi, Jongwoo Lim, and Minghsuan Yang. "Object Tracking Benchmark." TPAMI (2015). [paper] [project]