目录

Visual Trackers

一、按年份分类

二、按类别分类

三、目标跟踪参考资料汇总

四、数据集

五、评价标准


Visual Trackers

一、按年份分类

ICCV2021

  • Stark: Learning Spatio-Temporal Transformer for Visual Tracking. ICCV (2021). [paper][code]

  • ABA: Learning to Adversarially Blur Visual Object Tracking. ICCV (2021). [paper][code]

  • HiFT: Hierarchical Feature Transformer for Aerial Tracking. ICCV (2021). [paper][code]

  • SOTS: Learn to Match: Automatic Matching Network Design for Visual Tracking. ICCV (2021). [paper][code]

  • SAOT: Saliency-Associated Object Tracking. ICCV (2021). [paper][code]

持续更新。。。。

CVPR2021

  • STMTrack: Template-free Visual Tracking with Space-time Memory Networks. CVPR (2021). [paper][code]

  • SNL-RPN: Siamese Natural Language Tracker: Tracking by Natural Language Descriptions with Siamese Trackers. CVPR (2021). [paper]

  • Learning to Filter: Siamese Relation Network for Robust Tracking. CVPR (2021). [paper][code]

  • TransT: Transformer Tracking. CVPR (2021). [paper][code]

  • LightTrack: Finding Lightweight Neural Networks for Object Tracking via One-Shot Architecture Search. CVPR (2021). [paper][code]

  • Alpha-Refine: Boosting Tracking Performance by Precise Bounding Box Estimation. CVPR (2021). [paper][code]

  • SiamGAT: Graph Attention Tracking. CVPR (2021). [paper][code]

  • TrDiMP/TrSiam: Transformer Meets Tracker:Exploiting Temporal Context for Robust Visual Tracking. CVPR (2021). [paper][code]

  • CapsuleRRT: Relationships-aware Regression Tracking via Capsules. CVPR (2021). [paper]

  • PUL: Progressive Unsupervised Learning for Visual Object Tracking. CVPR (2021). [paper]

  • Towards More Flexible and Accurate Object Tracking with Natural Language:Algorithms and Benchmark. CVPR (2021). [paper]

  • Re-SiamNet: Rotation Equivariant Siamese Networks for Tracking. CVPR (2021). [paper][code]

CVPR2020

  • MAML: Guangting Wang, Chong Luo, Xiaoyan Sun, Zhiwei Xiong, Wenjun Zeng.
    "Tracking by Instance Detection: A Meta-Learning Approach." CVPR (2020 Oral). [paper]

  • LTMU: High-Performance Long-Term Tracking With Meta-Updater, CVPR (2020 Oral). [paper][code]

  • Siam R-CNN: Paul Voigtlaender, Jonathon Luiten, Philip H.S. Torr, Bastian Leibe.
    "Siam R-CNN: Visual Tracking by Re-Detection." CVPR (2020). [paper] [code]

  • D3S: Alan Lukežič, Jiří Matas, Matej Kristan.
    "D3S – A Discriminative Single Shot Segmentation Tracker." CVPR (2020). [paper] [code]

  • PrDiMP: Martin Danelljan, Luc Van Gool, Radu Timofte.
    "Probabilistic Regression for Visual Tracking." CVPR (2020). [paper] [code]

  • ROAM: Tianyu Yang, Pengfei Xu, Runbo Hu, Hua Chai, Antoni B. Chan.
    "ROAM: Recurrently Optimizing Tracking Model." CVPR (2020). [paper]

  • AutoTrack: Yiming Li, Changhong Fu, Fangqiang Ding, Ziyuan Huang, Geng Lu.
    "AutoTrack: Towards High-Performance Visual Tracking for UAV with Automatic Spatio-Temporal Regularization." CVPR (2020). [paper] [code]

  • SiamBAN: Zedu Chen, Bineng Zhong, Guorong Li, Shengping Zhang, Rongrong Ji.
    "Siamese Box Adaptive Network for Visual Tracking." CVPR (2020). [paper] [code]

  • SiamAttn: Yuechen Yu, Yilei Xiong, Weilin Huang, Matthew R. Scott.
    "Deformable Siamese Attention Networks for Visual Object Tracking." CVPR (2020). [paper]

  • CGACD: Fei Du, Peng Liu, Wei Zhao, Xianglong Tang.
    "Correlation-Guided Attention for Corner Detection Based Visual Tracking." CVPR (2020).

AAAI 2020

  • SiamFC++: Yinda Xu, Zeyu Wang, Zuoxin Li, Ye Yuan, Gang Yu.
    "SiamFC++: Towards Robust and Accurate Visual Tracking with Target Estimation Guidelines." AAAI (2020). [paper] [code]

ICCV2019

  • DiMP: Goutam Bhat, Martin Danelljan, Luc Van Gool, Radu Timofte.
    "Learning Discriminative Model Prediction for Tracking." ICCV (2019 oral). [paper] [code]

  • GradNet: Peixia Li, Boyu Chen, Wanli Ouyang, Dong Wang, Xiaoyun Yang, Huchuan Lu.
    "GradNet: Gradient-Guided Network for Visual Object Tracking." ICCV (2019 oral). [paper] [code]

  • MLT: Janghoon Choi, Junseok Kwon, Kyoung Mu Lee.
    "Deep Meta Learning for Real-Time Target-Aware Visual Tracking." ICCV (2019). [paper]

  • SPLT: Bin Yan, Haojie Zhao, Dong Wang, Huchuan Lu, Xiaoyun Yang
    "'Skimming-Perusal' Tracking: A Framework for Real-Time and Robust Long-Term Tracking." ICCV (2019). [paper] [code]

  • ARCF: Ziyuan Huang, Changhong Fu, Yiming Li, Fuling Lin, Peng Lu.
    "Learning Aberrance Repressed Correlation Filters for Real-Time UAV Tracking." ICCV (2019). [paper] [code]

  • Lianghua Huang, Xin Zhao, Kaiqi Huang.
    "Bridging the Gap Between Detection and Tracking: A Unified Approach." ICCV (2019). [paper]

  • UpdateNet: Lichao Zhang, Abel Gonzalez-Garcia, Joost van de Weijer, Martin Danelljan, Fahad Shahbaz Khan.
    "Learning the Model Update for Siamese Trackers." ICCV (2019). [paper] [code]

  • PAT: Rey Reza Wiyatno, Anqi Xu.
    "Physical Adversarial Textures That Fool Visual Object Tracking." ICCV (2019). [paper]

  • GFS-DCF: Tianyang Xu, Zhen-Hua Feng, Xiao-Jun Wu, Josef Kittler.
    "Joint Group Feature Selection and Discriminative Filter Learning for Robust Visual Object Tracking." ICCV (2019). [paper] [code]

  • CDTB: Alan Lukežič, Ugur Kart, Jani Käpylä, Ahmed Durmush, Joni-Kristian Kämäräinen, Jiří Matas, Matej Kristan.

    "CDTB: A Color and Depth Visual Object Tracking Dataset and Benchmark." ICCV (2019). [paper]

  • VOT2019: Kristan, Matej, et al.
    "The Seventh Visual Object Tracking VOT2019 Challenge Results." ICCV workshops (2019). [paper]

CVPR2019

  • SiamMask: Qiang Wang, Li Zhang, Luca Bertinetto, Weiming Hu, Philip H.S. Torr.
    "Fast Online Object Tracking and Segmentation: A Unifying Approach." CVPR (2019). [paper] [project] [code]

  • SiamRPN++: Bo Li, Wei Wu, Qiang Wang, Fangyi Zhang, Junliang Xing, Junjie Yan.
    "SiamRPN++: Evolution of Siamese Visual Tracking with Very Deep Networks." CVPR (2019 oral). [paper] [project]

  • ATOM: Martin Danelljan, Goutam Bhat, Fahad Shahbaz Khan, Michael Felsberg. 
    "ATOM: Accurate Tracking by Overlap Maximization." CVPR (2019 oral). [paper] [code]

  • SiamDW: Zhipeng Zhang, Houwen Peng.
    "Deeper and Wider Siamese Networks for Real-Time Visual Tracking." CVPR (2019 oral). [paper] [code]

  • GCT: Junyu Gao, Tianzhu Zhang, Changsheng Xu.
    "Graph Convolutional Tracking." CVPR (2019 oral). [paper] [code]

  • ASRCF: Kenan Dai, Dong Wang, Huchuan Lu, Chong Sun, Jianhua Li. 
    "Visual Tracking via Adaptive Spatially-Regularized Correlation Filters." CVPR (2019 oral). [paper] [code]

  • UDT: Ning Wang, Yibing Song, Chao Ma, Wengang Zhou, Wei Liu, Houqiang Li.
    "Unsupervised Deep Tracking." CVPR (2019). [paper] [code]

  • TADT: Xin Li, Chao Ma, Baoyuan Wu, Zhenyu He, Ming-Hsuan Yang.
    "Target-Aware Deep Tracking." CVPR (2019). [paper] [project] [code]

  • C-RPN: Heng Fan, Haibin Ling.
    "Siamese Cascaded Region Proposal Networks for Real-Time Visual Tracking." CVPR (2019). [paper]

  • SPM: Guangting Wang, Chong Luo, Zhiwei Xiong, Wenjun Zeng.
    "SPM-Tracker: Series-Parallel Matching for Real-Time Visual Object Tracking." CVPR (2019). [paper]

  • OTR: Ugur Kart, Alan Lukezic, Matej Kristan, Joni-Kristian Kamarainen, Jiri Matas. 
    "Object Tracking by Reconstruction with View-Specific Discriminative Correlation Filters." CVPR (2019). [paper] [code]

  • RPCF: Yuxuan Sun, Chong Sun, Dong Wang, Huchuan Lu, You He. 
    "ROI Pooled Correlation Filters for Visual Tracking." CVPR (2019). [paper]

  • LaSOT: Heng Fan, Liting Lin, Fan Yang, Peng Chu, Ge Deng, Sijia Yu, Hexin Bai, Yong Xu, Chunyuan Liao, Haibin Ling.
    "LaSOT: A High-quality Benchmark for Large-scale Single Object Tracking." CVPR (2019). [paper] [project]

AAAI2019

  • LDES: Yang Li, Jianke Zhu, Steven C.H. Hoi, Wenjie Song, Zhefeng Wang, Hantang Liu.
    "Robust Estimation of Similarity Transformation for Visual Object Tracking." AAAI (2019). [paper] [code]

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).

  • 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).

  • 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, Alex 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). [github]

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

  • : Ilchae Jung, Jeany Son, Mooyeol Baek, Bohyung Han.
    "Real-Time Tracking with Discriminative Multi-Domain Convolutional Neural Networks." ECCV (2018).

  • : Boyu Chen, Dong Wang, Peixia Li, Huchuan Lu.
    "Real-time Actor-Critic Tracking." ECCV (2018).

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

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

  • : Xingping Dong, Jianbing Shen.
    "Triplet Loss with Theoretical Analysis in Siamese Network for Real-Time Object Tracking." ECCV (2018).

  • 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]

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]

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]

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

  • 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

  • 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

二、按类别分类

Baseline

  • MOSSE: David S. Bolme, J. Ross Beveridge, Bruce A. Draper, Yui Man Lui. "Visual Object Tracking using Adaptive Correlation Filters." ICCV (2010). [paper] [project]

  • CSK: João F. Henriques, Rui Caseiro, Pedro Martins, Jorge Batista. "Exploiting the Circulant Structure of Tracking-by-detection with Kernels." ECCV (2012). [paper] [project]

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

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

Color

  • CN: Martin Danelljan, Fahad Shahbaz Khan, Michael Felsberg and Joost van de Weijer. "Adaptive Color Attributes for Real-Time Visual Tracking." CVPR (2014). [paper] [project]

  • MOCA: Guibo Zhu, Jinqiao Wang, Yi Wu, Xiaoyu Zhang, Hanqing Lu. "MC-HOG Correlation Tracking with Saliency Proposal." AAAI (2016). [paper]

  • 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]

Scale

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

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

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

  • SKCF: Solis Montero, Andres, Jochen Lang, Robert Laganiere. "Scalable Kernel Correlation Filter with Sparse Feature Integration." ICCV workshop (2015). [paper] [project] [github]

  • KCFDP/KCFDPT: Dafei Huang, Lei Luo, Mei Wen, Zhaoyun Chen and Chunyuan Zhang. "Enable Scale and Aspect Ratio Adaptability in Visual Tracking with Detection Proposals." BMVC (2015). [paper] [github1] [github2]

  • 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]

Multi kernel & feature & template & task

  • MKCF: Ming Tang, Jiayi Feng. "Multi-kernel Correlation Filter for Visual Tracking." ICCV (2015). [paper] [exe]

  • CF+MT: Adel Bibi, Bernard Ghanem. "Multi-Template Scale Adaptive Kernelized Correlation Filters." ICCV workshop (2015). [paper] [github]

  • 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]

  • MvCFT: Xin Li, Qiao Liu, Zhenyu He, Hongpeng Wang, Chunkai Zhang, Wen-Sheng Chen. "A Multi-view Model for Visual Tracking via Correlation Filters." KNOSYS (2016). [paper] [exe]

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

Part-based

  • RPAC: Liu Ting, Gang Wang, Qingxiong Yang. "Real-time part-based visual tracking via adaptive correlation filters." CVPR (2015). [paper]

  • RPAC+: Liu Ting, Gang Wang, Qingxiong Yang, Li Wang. "Part-based Tracking via Discriminative Correlation Filters." TCSVT (2016). [paper]

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

  • DPCF: Osman Akina, Erkut Erdema, Aykut Erdema, Krystian Mikolajczykb. "Deformable Part-based Tracking by Coupled Global and Local Correlation Filters." JVCIR (2016). [paper] [code]

  • DPT: Alan Lukežič, Luka Čehovin, Matej Kristan. "Deformable Parts Correlation Filters for Robust Visual Tracking." CVPR (2016). [paper]

  • StructCF: Si Liu, Tianzhu Zhang, Changsheng Xu, Xiaochun Cao. "Structural Correlation Filter for Robust Visual Tracking." CVPR (2016). [paper]

  • Rui Yao, Shixiong Xia, Zhen Zhang, Yanning Zhang. "Real-time Correlation Filter Tracking by Efficient Dense Belief Propagation with Structure Preserving." TMM (2016). [paper]

  • LGCF: Heng Fan, Jinhai Xiang. "Robust Visual Tracking via Local-Global Correlation Filter." AAAI (2017). [paper]

  • DCCO: Joakim Johnander, Martin Danelljan, Fahad Shahbaz Khan, Michael Felsberg. "DCCO: Towards Deformable Continuous Convolution Operators." arXiv (2017). [paper]

  • 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]

Long-term

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

  • LCT+: Chao Ma, Jia-Bin Huang, Xiaokang Yang, Ming-Hsuan Yang. "Adaptive Correlation Filters with Long-Term and Short-Term Memory for Object Tracking." IJCV (under review) [project]

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

  • CCT: Guibo Zhu, Jinqiao Wang, Yi Wu, Hanqing Lu. "Collobarative Correlation Tracking." BMVC (2015). [paper] [code]

Response adaptation

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

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

  • OCT-KCF: Baochang Zhang, Zhigang Li, Xianbin Cao, Qixiang Ye, Chen Chen, Linlin Shen, Alessandro Perina, Rongrong Ji. "Output Constraint Transfer for Kernelized Correlation Filter in Tracking." TSMC (2016). [paper] [github]

  • Yao Sui, Guanghui Wang, Li Zhang. "Correlation Filter Learning Toward Peak Strength for Visual Tracking." TCYB (2017). [paper]

Training set adaptation

  • 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]

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

Bound effect

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

  • CFLB Hamed Kiani Galoogahi, Terence Sim, Simon Lucey. "Correlation Filters with Limited Boundaries." CVPR (2015). [paper] [project] [code]

  • SWCF: Erhan Gundogdu, A. Aydın Alatan. "Spatial Windowing for Correlation Filter based Visual Tracking." ICIP (2016). [paper] [code]

  • CF+CA: Matthias Mueller, Neil Smith, Bernard Ghanem. "Context-Aware Correlation Filter Tracking." CVPR (2017). [paper] [project] [github]

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

  • MRCT: Hongwei Hu, Bo Ma, Jianbing Shen, Ling Shao. "Manifold Regularized Correlation Object Tracking." TNNLS (2017). [paper] [github]

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

Continuous

  • 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]

SVM

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

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

Deep

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

  • HCFT+: Chao Ma, Yi Xu, Bingbing Ni, Xiaokang Yang. "When Correlation Filters Meet Convolutional Neural Networks for Visual Tracking." SPL (2016). [paper]

  • HCFTstar: Chao Ma, Jia-Bin Huang, Xiaokang Yang, Ming-Hsuan Yang. "Robust Visual Tracking via Hierarchical Convolutional Features." arXiv (2017). [paper] [project] [github]

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

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

  • CFNet: Jack Valmadre, Luca Bertinetto, João Henriques, Andrea Vedaldi, Philip Torr. "End-to-end Representation Learning for Correlation Filter based Tracking." CVPR (2017). [paper] [project] [github]

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

  • CFCF Erhan Gundogdu, A. Aydin Alatan. "Good Features to Correlate for Visual Tracking." arXiv (2017). [paper]

  • 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]

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

三、目标跟踪参考资料汇总

1、知乎目标跟踪之NIUBILITY的相关滤波专栏; 
2、知乎目标跟踪算法专栏; 
3、GitHub,foolwood代码汇总; 
4、Github,HakaseH代码汇总;

四、数据集

  1. 首先,用的最广泛的是OTB-50和OTB-100,网址 Object Tracking Benchmark,里面涉及到灰度图像和彩色图像,均可以免费下载,涉及到目标跟踪的11个属性,包括光照变化、尺度变化、遮挡、形变、运动模糊、快速运动、平面内旋转、平面外旋转、出视野、背景干扰、低像素。每个图像序列都对应着两个或多个属性,每个序列都对应着一个txt文件,记录着人工标注的目标中心位置和目标的大小。更多的详细信息请参阅博客在线目标跟踪:一种评估基准 A Benchmark 翻译。
  2. VOT数据集是基于每年一次的VOT比赛的,每年都会有新的数据集产生,当然其中一部分图像序列是和OTB重合的,但是总的来说VOT数据集略难于OTB数据集,一般用VOT16,一般在这两个数据集上跑的效果都好,才算真的好,如果只在一个数据集上效果好,那只能说明这个算法的泛化能力还不够。VOT的网址Visual Object Tracking。
  3. Temple Color 128数据集里面包含的全是彩色序列,部分序列也是和OTB重合的,如果算法只适用于彩色序列的话可以在此数据集上跑一下,此数据集也是免费下载,网址Temple Color 128 - Color Tracking Benchmark。
  4. VIVID Tracking数据集里面包含9个序列,均是从高空拍摄的车辆视频图像,包括灰度图像和彩色图像,相对时间都比较长,目标也比较小,遮挡情况比较多,网址VIVID Tracking Evaluation Web Site 。
  5. UAV123 Dataset数据集是均是通过无人机拍摄的彩色图像,但是需要翻墙下载,如果是做无人机目标跟踪方面的同学,此数据集一定必不可少,网址A Benchmark and Simulator for UAV Tracking。 
    除此之外还有许多目标跟踪的数据集,在此就不一一列举。

五、评价标准

目前用的最多的是OTB的评价标准,它可以给出各个算法的精确度图和成功率图,和各个属性的精确度图和成功率图,并对各个算法进行排序。除了有一次评估OPE外,还有时间鲁棒性评估(TRE),空间鲁棒性评估 (SRE),但是一般论文里都只用OPE,至于怎么用这个评估标准,可参考在线目标跟踪:一种评估基准 A Benchmark 翻译和目标跟踪 benchmark用法 添加、测试自己的代码。

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