全球最全计算机视觉资料（3：目标追踪）

目标检测和深度学习

Object Tracking

NIPS2013

• DLT: Naiyan Wang and Dit-Yan Yeung. "Learning A Deep Compact Image Representation for Visual Tracking." NIPS (2013).
  • paper [http://winsty.net/papers/dlt.pdf)]
  • project [http://winsty.net/dlt.html)]
  • code [http://winsty.net/dlt/DLTcode.zip)]

CVPR2014

• CN: Martin Danelljan, Fahad Shahbaz Khan, Michael Felsberg and Joost van de Weijer. "Adaptive Color Attributes for Real-Time Visual Tracking." CVPR (2014).
  • paper [http://www.cvl.isy.liu.se/research/objrec/visualtracking/colvistrack/CN_Tracking_CVPR14.pdf]
  • project [http://www.cvl.isy.liu.se/research/objrec/visualtracking/colvistrack/index.html]

ECCV2014

• MEEM: Jianming Zhang, Shugao Ma, and Stan Sclaroff. "MEEM: Robust Tracking via Multiple Experts using Entropy Minimization." ECCV (2014).
  • paper [http://cs-people.bu.edu/jmzhang/MEEM/MEEM-eccv-preprint.pdf]
  • project [http://cs-people.bu.edu/jmzhang/MEEM/MEEM.html]
• TGPR: Jin Gao, Haibin Ling, Weiming Hu, Junliang Xing. "Transfer Learning Based Visual Tracking with Gaussian Process Regression." ECCV (2014).
  • paper [http://www.dabi.temple.edu/~hbling/publication/tgpr-eccv14.pdf]
  • project [http://www.dabi.temple.edu/~hbling/code/TGPR.htm]
• STC: Kaihua Zhang, Lei Zhang, Ming-Hsuan Yang, David Zhang. "Fast Tracking via Spatio-Temporal Context Learning." ECCV (2014).
  • paper [http://arxiv.org/pdf/1311.1939v1.pdf]
  • project [http://www4.comp.polyu.edu.hk/~cslzhang/STC/STC.htm]
• SAMF: Yang Li, Jianke Zhu. "A Scale Adaptive Kernel Correlation Filter Tracker with Feature Integration." ECCV workshop (2014).
  • paper [http://link.springer.com/content/pdf/10.1007%2F978-3-319-16181-5_18.pdf]
  • github [https://github.com/ihpdep/samf]

BMVC2014

• DSST: Martin Danelljan, Gustav Häger, Fahad Shahbaz Khan and Michael Felsberg. "Accurate Scale Estimation for Robust Visual Tracking." BMVC (2014).
  • paper [http://www.cvl.isy.liu.se/research/objrec/visualtracking/scalvistrack/ScaleTracking_BMVC14.pdf]
  • PAMI [http://www.cvl.isy.liu.se/en/research/objrec/visualtracking/scalvistrack/DSST_TPAMI.pdf]
  • project [http://www.cvl.isy.liu.se/en/research/objrec/visualtracking/scalvistrack/index.html]
• SAMF: Yang Li, Jianke Zhu. "A Scale Adaptive Kernel Correlation Filter Tracker with Feature Integration." ECCV workshop (2014).
  • paper [https://github.com/ihpdep/ihpdep.github.io/raw/master/papers/eccvw14_samf.pdf]
  • github [https://github.com/ihpdep/samf]

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 [http://proceedings.mlr.press/v37/hong15.pdf]
  • project [http://cvlab.postech.ac.kr/research/CNN_SVM/]

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 [http://openaccess.thecvf.com/content_cvpr_2015/papers/Hong_MUlti-Store_Tracker_MUSTer_2015_CVPR_paper.pdf]
  • project [https://sites.google.com/site/multistoretrackermuster/]
• LCT: Chao Ma, Xiaokang Yang, Chongyang Zhang, Ming-Hsuan Yang. "Long-term Correlation Tracking." CVPR (2015).
  • paper [http://openaccess.thecvf.com/content_cvpr_2015/papers/Ma_Long-Term_Correlation_Tracking_2015_CVPR_paper.pdf]
  • project [https://sites.google.com/site/chaoma99/cvpr15_tracking]
  • github [https://github.com/chaoma99/lct-tracker]
• DAT: Horst Possegger, Thomas Mauthner, and Horst Bischof. "In Defense of Color-based Model-free Tracking." CVPR (2015).
  • paper [https://lrs.icg.tugraz.at/pubs/possegger_cvpr15.pdf]
  • project [https://www.tugraz.at/institute/icg/research/team-bischof/lrs/downloads/dat]
  • code [https://lrs.icg.tugraz.at/downloads/dat-v1.0.zip]
• RPT: Yang Li, Jianke Zhu and Steven C.H. Hoi. "Reliable Patch Trackers: Robust Visual Tracking by Exploiting Reliable Patches." CVPR (2015).
  • paper [https://github.com/ihpdep/ihpdep.github.io/raw/master/papers/cvpr15_rpt.pdf]
  • github [https://github.com/ihpdep/rpt]

ICCV2015

• FCNT: Lijun Wang, Wanli Ouyang, Xiaogang Wang, and Huchuan Lu. "Visual Tracking with Fully Convolutional Networks." ICCV (2015).
  • paper [http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7410714]
  • project [http://scott89.github.io/FCNT/]
  • github [https://github.com/scott89/FCNT]
• SRDCF: Martin Danelljan, Gustav Häger, Fahad Khan, Michael Felsberg. "Learning Spatially Regularized Correlation Filters for Visual Tracking." ICCV (2015).
  • paper [https://www.cvl.isy.liu.se/research/objrec/visualtracking/regvistrack/SRDCF_ICCV15.pdf]
  • project [https://www.cvl.isy.liu.se/research/objrec/visualtracking/regvistrack/]
• CF2: Chao Ma, Jia-Bin Huang, Xiaokang Yang and Ming-Hsuan Yang. "Hierarchical Convolutional Features for Visual Tracking." ICCV (2015)
  • paper [http://faculty.ucmerced.edu/mhyang/papers/iccv15_tracking.pdf]
  • project [https://sites.google.com/site/jbhuang0604/publications/cf2]
  • github [https://github.com/jbhuang0604/CF2]
• Naiyan Wang, Jianping Shi, Dit-Yan Yeung and Jiaya Jia. "Understanding and Diagnosing Visual Tracking Systems." ICCV (2015).
  • paper [http://winsty.net/papers/diagnose.pdf]
  • project [http://winsty.net/tracker_diagnose.html]
  • code [http://winsty.net/diagnose/diagnose_code.zip]
• DeepSRDCF: Martin Danelljan, Gustav Häger, Fahad Khan, Michael Felsberg. "Convolutional Features for Correlation Filter Based Visual Tracking." ICCV workshop (2015).
  • paper [https://www.cvl.isy.liu.se/research/objrec/visualtracking/regvistrack/ConvDCF_ICCV15_VOTworkshop.pdf]
  • project [https://www.cvl.isy.liu.se/research/objrec/visualtracking/regvistrack/]
• 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 [http://www.cv-foundation.org//openaccess/content_iccv_2015_workshops/w14/papers/Zhang_Joint_Scale-Spatial_Correlation_ICCV_2015_paper.pdf]
  • poster [http://www.votchallenge.net/vot2015/download/poster_Mengdan_Zhang.pdf]

NIPS2016

• Learnet: Luca Bertinetto, João F. Henriques, Jack Valmadre, Philip H. S. Torr, Andrea Vedaldi. "Learning feed-forward one-shot learners." NIPS (2016).
  • paper [https://arxiv.org/pdf/1606.05233v1.pdf]

CVPR2016

• MDNet: Nam, Hyeonseob, and Bohyung Han. "Learning Multi-Domain Convolutional Neural Networks for Visual Tracking." CVPR (2016).
  • paper [http://arxiv.org/pdf/1510.07945v2.pdf]
  • VOT_presentation [http://votchallenge.net/vot2015/download/presentation_Hyeonseob.pdf]
  • project [http://cvlab.postech.ac.kr/research/mdnet/]
  • github [https://github.com/HyeonseobNam/MDNet]
• SINT: Ran Tao, Efstratios Gavves, Arnold W.M. Smeulders. "Siamese Instance Search for Tracking." CVPR (2016).
  • paper [https://staff.science.uva.nl/r.tao/pub/TaoCVPR2016.pdf]
  • project [https://staff.fnwi.uva.nl/r.tao/projects/SINT/SINT_proj.html]
• 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 [http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Choi_Visual_Tracking_Using_CVPR_2016_paper.pdf]
  • project [https://sites.google.com/site/jwchoivision/home/sct]
• STCT: Lijun Wang, Wanli Ouyang, Xiaogang Wang, and Huchuan Lu. "STCT: Sequentially Training Convolutional Networks for Visual Tracking." CVPR (2016).
  • paper [http://www.ee.cuhk.edu.hk/~wlouyang/Papers/WangLJ_CVPR16.pdf]
  • github [https://github.com/scott89/STCT]
• 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 [https://www.cvl.isy.liu.se/research/objrec/visualtracking/decontrack/AdaptiveDecon_CVPR16.pdf]
  • project [https://www.cvl.isy.liu.se/research/objrec/visualtracking/decontrack/index.html]
• HDT: Yuankai Qi, Shengping Zhang, Lei Qin, Hongxun Yao, Qingming Huang, Jongwoo Lim, Ming-Hsuan Yang. "Hedged Deep Tracking." CVPR (2016).
  • paper [http://faculty.ucmerced.edu/mhyang/papers/cvpr16_hedge_tracking.pdf]
  • project [https://sites.google.com/site/yuankiqi/hdt/]
• Staple: Luca Bertinetto, Jack Valmadre, Stuart Golodetz, Ondrej Miksik, Philip H.S. Torr. "Staple: Complementary Learners for Real-Time Tracking." CVPR (2016).
  • paper [https://arxiv.org/abs/1512.01355]
  • project [http://www.robots.ox.ac.uk/~luca/staple.html]
  • github [https://github.com/bertinetto/staple]
• EBT: Gao Zhu, Fatih Porikli, and Hongdong Li. "Beyond Local Search: Tracking Objects Everywhere with Instance-Specific Proposals." CVPR (2016).
  • paper [http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Zhu_Beyond_Local_Search_CVPR_2016_paper.pdf]
  • exe [http://www.votchallenge.net/vot2016/download/02_EBT.zip]
• 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 [http://www4.comp.polyu.edu.hk/~cslzhang/paper/cvpr16/DLSSVM.pdf]
  • code [http://www4.comp.polyu.edu.hk/~cslzhang/code/DLSSVM_CVPR.zip]
  • project [http://www4.comp.polyu.edu.hk/~cslzhang/DLSSVM/DLSSVM.htm]

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 [https://arxiv.org/abs/1606.09549]
  • project [http://www.robots.ox.ac.uk/~luca/siamese-fc.html]
  • github [https://github.com/bertinetto/siamese-fc]
• GOTURN: David Held, Sebastian Thrun, Silvio Savarese. "Learning to Track at 100 FPS with Deep Regression Networks." ECCV (2016).
  • paper [http://davheld.github.io/GOTURN/GOTURN.pdf]
  • project [http://davheld.github.io/GOTURN/GOTURN.html]
  • github [https://github.com/davheld/GOTURN]
• C-COT: Martin Danelljan, Andreas Robinson, Fahad Khan, Michael Felsberg. "Beyond Correlation Filters: Learning Continuous Convolution Operators for Visual Tracking." ECCV (2016).
  • paper [http://www.cvl.isy.liu.se/research/objrec/visualtracking/conttrack/C-COT_ECCV16.pdf]
  • project [http://www.cvl.isy.liu.se/research/objrec/visualtracking/conttrack/index.html]
  • github [https://github.com/martin-danelljan/Continuous-ConvOp]
• CF+AT: Adel Bibi, Matthias Mueller, and Bernard Ghanem. "Target Response Adaptation for Correlation Filter Tracking." ECCV (2016).
  • paper [http://www.adelbibi.com/papers/ECCV2016/Target_Adap.pdf]
• Yao Sui, Ziming Zhang, Guanghui Wang, Yafei Tang, Li Zhang. "Real-Time Visual Tracking: Promoting the Robustness of Correlation Filter Learning." ECCV (2016).
  • paper [https://arxiv.org/abs/1608.08173]
• Yao Sui, Guanghui Wang, Yafei Tang, Li Zhang. "Tracking Completion." ECCV (2016).
  • paper [https://arxiv.org/abs/1608.08171]

CVPR2017

• ECO: Martin Danelljan, Goutam Bhat, Fahad Shahbaz Khan, Michael Felsberg. "ECO: Efficient Convolution Operators for Tracking." CVPR (2017).
  • paper [http://openaccess.thecvf.com/content_cvpr_2017/papers/Danelljan_ECO_Efficient_Convolution_CVPR_2017_paper.pdf]
  • supp [http://openaccess.thecvf.com/content_cvpr_2017/supplemental/Danelljan_ECO_Efficient_Convolution_2017_CVPR_supplemental.pdf]
  • project [http://www.cvl.isy.liu.se/research/objrec/visualtracking/ecotrack/index.html]
  • github [https://github.com/martin-danelljan/ECO]
• 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 [http://openaccess.thecvf.com/content_cvpr_2017/papers/Valmadre_End-To-End_Representation_Learning_CVPR_2017_paper.pdf]
  • supp [http://openaccess.thecvf.com/content_cvpr_2017/supplemental/Valmadre_End-To-End_Representation_Learning_2017_CVPR_supplemental.pdf]
  • project [http://www.robots.ox.ac.uk/~luca/cfnet.html]
  • github [https://github.com/bertinetto/cfnet]
• CACF: Matthias Mueller, Neil Smith, Bernard Ghanem. "Context-Aware Correlation Filter Tracking." CVPR (2017 oral).
  • paper [http://openaccess.thecvf.com/content_cvpr_2017/papers/Mueller_Context-Aware_Correlation_Filter_CVPR_2017_paper.pdf]
  • supp [http://openaccess.thecvf.com/content_cvpr_2017/supplemental/Mueller_Context-Aware_Correlation_Filter_2017_CVPR_supplemental.zip]
  • project [https://ivul.kaust.edu.sa/Pages/pub-ca-cf-tracking.aspx]
  • code [https://github.com/thias15/Context-Aware-CF-Tracking]
• RaF: Le Zhang, Jagannadan Varadarajan, Ponnuthurai Nagaratnam Suganthan, Narendra Ahuja and Pierre Moulin "Robust Visual Tracking Using Oblique Random Forests." CVPR (2017).
  • paper [http://openaccess.thecvf.com/content_cvpr_2017/papers/Zhang_Robust_Visual_Tracking_CVPR_2017_paper.pdf]
  • supp [http://openaccess.thecvf.com/content_cvpr_2017/supplemental/Zhang_Robust_Visual_Tracking_2017_CVPR_supplemental.pdf]
  • project [https://sites.google.com/site/zhangleuestc/incremental-oblique-random-forest]
  • code [https://github.com/ZhangLeUestc/Incremental-Oblique-Random-Forest]
• MCPF: Tianzhu Zhang, Changsheng Xu, Ming-Hsuan Yang. "Multi-Task Correlation Particle Filter for Robust Object Tracking." CVPR (2017).
  • paper [http://openaccess.thecvf.com/content_cvpr_2017/papers/Zhang_Multi-Task_Correlation_Particle_CVPR_2017_paper.pdf]
  • project [http://nlpr-web.ia.ac.cn/mmc/homepage/tzzhang/mcpf.html]
  • code [http://nlpr-web.ia.ac.cn/mmc/homepage/tzzhang/mcpf.html]
• 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 [http://openaccess.thecvf.com/content_cvpr_2017/papers/Choi_Attentional_Correlation_Filter_CVPR_2017_paper.pdf]
  • supp [http://openaccess.thecvf.com/content_cvpr_2017/supplemental/Choi_Attentional_Correlation_Filter_2017_CVPR_supplemental.pdf]
  • project [https://sites.google.com/site/jwchoivision/home/acfn-1]
  • test code [https://drive.google.com/file/d/0B0ZkG8zaRQoLQUswbW9qSWFaU0U/view?usp=drive_web]
  • training code [https://drive.google.com/file/d/0B0ZkG8zaRQoLZVVranBnbHlydnM/view?usp=drive_web]
• LMCF: Mengmeng Wang, Yong Liu, Zeyi Huang. "Large Margin Object Tracking with Circulant Feature Maps." CVPR (2017).
  • paper [http://openaccess.thecvf.com/content_cvpr_2017/papers/Wang_Large_Margin_Object_CVPR_2017_paper.pdf]
  • zhihu [https://zhuanlan.zhihu.com/p/25761718]
• 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 [http://openaccess.thecvf.com/content_cvpr_2017/papers/Yun_Action-Decision_Networks_for_CVPR_2017_paper.pdf]
  • supp [http://openaccess.thecvf.com/content_cvpr_2017/supplemental/Yun_Action-Decision_Networks_for_2017_CVPR_supplemental.pdf]
  • project [https://sites.google.com/view/cvpr2017-adnet]
• CSR-DCF: Alan Lukežič, Tomáš Vojíř, Luka Čehovin, Jiří Matas, Matej Kristan. "Discriminative Correlation Filter with Channel and Spatial Reliability." CVPR (2017).
  • paper [http://openaccess.thecvf.com/content_cvpr_2017/papers/Lukezic_Discriminative_Correlation_Filter_CVPR_2017_paper.pdf]
  • supp [http://openaccess.thecvf.com/content_cvpr_2017/supplemental/Lukezic_Discriminative_Correlation_Filter_2017_CVPR_supplemental.pdf]
  • code [https://github.com/alanlukezic/csr-dcf]
• BranchOut: Bohyung Han, Jack Sim, Hartwig Adam. "BranchOut: Regularization for Online Ensemble Tracking with Convolutional Neural Networks." CVPR (2017).
  • paper [http://openaccess.thecvf.com/content_cvpr_2017/papers/Han_BranchOut_Regularization_for_CVPR_2017_paper.pdf]
• AMCT: Donghun Yeo, Jeany Son, Bohyung Han, Joonhee Han. "Superpixel-based Tracking-by-Segmentation using Markov Chains." CVPR (2017).
  • paper [http://openaccess.thecvf.com/content_cvpr_2017/papers/Yeo_Superpixel-Based_Tracking-By-Segmentation_Using_CVPR_2017_paper.pdf]
• SANet: Heng Fan, Haibin Ling. "SANet: Structure-Aware Network for Visual Tracking." CVPRW (2017).
  • paper [https://arxiv.org/pdf/1611.06878.pdf]
  • project [http://www.dabi.temple.edu/~hbling/code/SANet/SANet.html]
  • code [http://www.dabi.temple.edu/~hbling/code/SANet/sanet_code.zip]

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 [http://openaccess.thecvf.com/content_ICCV_2017/papers/Song_CREST_Convolutional_Residual_ICCV_2017_paper.pdf]
  • project [http://www.cs.cityu.edu.hk/~yibisong/iccv17/index.html]
  • github [https://github.com/ybsong00/CREST-Release]
• EAST: Chen Huang, Simon Lucey, Deva Ramanan. "Learning Policies for Adaptive Tracking with Deep Feature Cascades." ICCV (2017 Spotlight).
  • paper [http://openaccess.thecvf.com/content_ICCV_2017/papers/Huang_Learning_Policies_for_ICCV_2017_paper.pdf]
  • supp [http://openaccess.thecvf.com/content_ICCV_2017/supplemental/Huang_Learning_Policies_for_ICCV_2017_supplemental.zip]
• PTAV: Heng Fan and Haibin Ling. "Parallel Tracking and Verifying: A Framework for Real-Time and High Accuracy Visual Tracking." ICCV (2017).
  • paper [http://openaccess.thecvf.com/content_ICCV_2017/papers/Fan_Parallel_Tracking_and_ICCV_2017_paper.pdf]
  • supp [http://openaccess.thecvf.com/content_ICCV_2017/supplemental/Fan_Parallel_Tracking_and_ICCV_2017_supplemental.pdf]
  • project [http://www.dabi.temple.edu/~hbling/code/PTAV/ptav.htm]
  • code [http://www.dabi.temple.edu/~hbling/code/PTAV/serial_ptav_v1.zip]
• BACF: Hamed Kiani Galoogahi, Ashton Fagg, Simon Lucey. "Learning Background-Aware Correlation Filters for Visual Tracking." ICCV (2017).
  • paper [http://openaccess.thecvf.com/content_ICCV_2017/papers/Galoogahi_Learning_Background-Aware_Correlation_ICCV_2017_paper.pdf]
  • supp [http://openaccess.thecvf.com/content_ICCV_2017/supplemental/Galoogahi_Learning_Background-Aware_Correlation_ICCV_2017_supplemental.pdf]
• 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 [http://openaccess.thecvf.com/content_ICCV_2017/papers/Teng_Robust_Object_Tracking_ICCV_2017_paper.pdf]
• p-tracker: James Supančič, III; Deva Ramanan. "Tracking as Online Decision-Making: Learning a Policy From Streaming Videos With Reinforcement Learning." ICCV (2017).
  • paper [http://openaccess.thecvf.com/content_ICCV_2017/papers/Supancic_Tracking_as_Online_ICCV_2017_paper.pdf]
  • supp [http://openaccess.thecvf.com/content_ICCV_2017/supplemental/Supancic_Tracking_as_Online_ICCV_2017_supplemental.pdf]
• DSiam: Qing Guo; Wei Feng; Ce Zhou; Rui Huang; Liang Wan; Song Wang. "Learning Dynamic Siamese Network for Visual Object Tracking." ICCV (2017).
  • paper [http://openaccess.thecvf.com/content_ICCV_2017/papers/Guo_Learning_Dynamic_Siamese_ICCV_2017_paper.pdf]
• 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 [http://openaccess.thecvf.com/content_ICCV_2017/papers/Sun_Non-Rigid_Object_Tracking_ICCV_2017_paper.pdf]
• 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 [http://openaccess.thecvf.com/content_ICCV_2017_workshops/papers/w28/Zhu_UCT_Learning_Unified_ICCV_2017_paper.pdf]
• Tobias Bottger, Patrick Follmann. "The Benefits of Evaluating Tracker Performance Using Pixel-Wise Segmentations." ICCV workshop (2017).
  • paper [http://openaccess.thecvf.com/content_ICCV_2017_workshops/papers/w28/Bottger_The_Benefits_of_ICCV_2017_paper.pdf]
• CFWCR: Zhiqun He, Yingruo Fan, Junfei Zhuang, Yuan Dong, HongLiang Bai. "Correlation Filters With Weighted Convolution Responses." ICCV workshop (2017).
  • paper [http://openaccess.thecvf.com/content_ICCV_2017_workshops/papers/w28/He_Correlation_Filters_With_ICCV_2017_paper.pdf]
• 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 [http://openaccess.thecvf.com/content_ICCV_2017_workshops/papers/w28/Li_Integrating_Boundary_and_ICCV_2017_paper.pdf]
• RFL: Tianyu Yang, Antoni B. Chan. "Recurrent Filter Learning for Visual Tracking." ICCV workshop (2017).
  • paper [http://openaccess.thecvf.com/content_ICCV_2017_workshops/papers/w28/Yang_Recurrent_Filter_Learning_ICCV_2017_paper.pdf]

PAMI & IJCV & TIP

• KCF: João F. Henriques, Rui Caseiro, Pedro Martins, Jorge Batista. "High-Speed Tracking with Kernelized Correlation Filters." TPAMI (2015).
  • paper [http://www.robots.ox.ac.uk/~joao/publications/henriques_tpami2015.pdf]
  • project [http://www.robots.ox.ac.uk/~joao/circulant/]
• CLRST: Tianzhu Zhang, Si Liu, Narendra Ahuja, Ming-Hsuan Yang, Bernard Ghanem. "Robust Visual Tracking Via Consistent Low-Rank Sparse Learning." IJCV (2015).
  • paper [http://nlpr-web.ia.ac.cn/mmc/homepage/tzzhang/tianzhu%20zhang_files/Journal%20Articles/IJCV15_zhang_Low-Rank%20Sparse%20Learning.pdf]
  • project [http://nlpr-web.ia.ac.cn/mmc/homepage/tzzhang/Project_Tianzhu/zhang_IJCV14/Robust%20Visual%20Tracking%20Via%20Consistent%20Low-Rank%20Sparse.html]
  • code [http://nlpr-web.ia.ac.cn/mmc/homepage/tzzhang/Project_Tianzhu/zhang_IJCV14/material/LRT_Code.zip]
• DNT: Zhizhen Chi, Hongyang Li, Huchuan Lu, Ming-Hsuan Yang. "Dual Deep Network for Visual Tracking." TIP (2017).
  • paper [https://arxiv.org/pdf/1612.06053v1.pdf]
• DRT: Junyu Gao, Tianzhu Zhang, Xiaoshan Yang, Changsheng Xu. "Deep Relative Tracking." TIP (2017).
  • paper [http://ieeexplore.ieee.org/abstract/document/7828108/]
• BIT: Bolun Cai, Xiangmin Xu, Xiaofen Xing, Kui Jia, Jie Miao, Dacheng Tao. "BIT: Biologically Inspired Tracker." TIP (2016).
  • paper [http://caibolun.github.io/papers/BIT_TIP.pdf]
  • project [http://caibolun.github.io/BIT/index.html]
  • github [https://github.com/caibolun/BIT]
• CNT: Kaihua Zhang, Qingshan Liu, Yi Wu, Minghsuan Yang. "Robust Visual Tracking via Convolutional Networks Without Training." TIP (2016).
  • paper [http://kaihuazhang.net/CNT.pdf]
  • code [http://kaihuazhang.net/CNT_matlab.rar]

ArXiv

• PAWSS: Xiaofei Du, Alessio Dore, Danail Stoyanov. "Patch-based adaptive weighting with segmentation and scale (PAWSS) for visual tracking." arXiv (2017).
  • paper [https://arxiv.org/pdf/1708.01179v1.pdf]
• SFT: Zhen Cui, You yi Cai, Wen ming Zheng, Jian Yang. "Spectral Filter Tracking." arXiv (2017).
  • paper [https://arxiv.org/pdf/1707.05553v1.pdf]
• HART: Adam R. Kosiorek, Alex Bewley, Ingmar Posner. "Hierarchical Attentive Recurrent Tracking." arXiv (2017).
  • paper [https://arxiv.org/pdf/1706.09262.pdf]
  • github [https://github.com/akosiorek/hart]
• Re3: Daniel Gordon, Ali Farhadi, Dieter Fox. "Re3 : Real-Time Recurrent Regression Networks for Object Tracking." arXiv (2017).
  • paper [https://arxiv.org/pdf/1705.06368.pdf]
• DCFNet: Qiang Wang, Jin Gao, Junliang Xing, Mengdan Zhang, Weiming Hu. "DCFNet: Discriminant Correlation Filters Network for Visual Tracking." arXiv (2017).
  • paper [https://arxiv.org/pdf/1704.04057.pdf]
  • code [https://github.com/foolwood/DCFNet#dcfnet-discriminant-correlation-filters-network-for-visual-tracking]
• TCNN: Hyeonseob Nam, Mooyeol Baek, Bohyung Han. "Modeling and Propagating CNNs in a Tree Structure for Visual Tracking." arXiv (2016).
  • paper [http://arxiv.org/pdf/1608.07242v1.pdf]
  • code [http://www.votchallenge.net/vot2016/download/44_TCNN.zip]
• RDT: Janghoon Choi, Junseok Kwon, Kyoung Mu Lee. "Visual Tracking by Reinforced Decision Making." arXiv (2017).
  • paper [https://arxiv.org/pdf/1702.06291.pdf]
• 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 [https://arxiv.org/pdf/1701.00561.pdf]
• RLT: Da Zhang, Hamid Maei, Xin Wang, Yuan-Fang Wang. "Deep Reinforcement Learning for Visual Object Tracking in Videos." arXiv (2017).
  • paper](https://arxiv.org/pdf/1701.08936v1.pdf]
• SCF: Wangmeng Zuo, Xiaohe Wu, Liang Lin, Lei Zhang, Ming-Hsuan Yang. "Learning Support Correlation Filters for Visual Tracking." arXiv (2016).
  • paper [https://arxiv.org/pdf/1601.06032.pdf]
  • project [http://faculty.ucmerced.edu/mhyang/project/scf/]
• CRT: Kai Chen, Wenbing Tao. "Convolutional Regression for Visual Tracking." arXiv (2016).
  • paper](https://arxiv.org/pdf/1611.04215.pdf]
• BMR: Kaihua Zhang, Qingshan Liu, and Ming-Hsuan Yang. "Visual Tracking via Boolean Map Representations." arXiv (2016).
  • paper](https://arxiv.org/pdf/1610.09652v1.pdf]
• YCNN: Kai Chen, Wenbing Tao. "Once for All: a Two-flow Convolutional Neural Network for Visual Tracking." arXiv (2016).
  • paper](https://arxiv.org/pdf/1604.07507v1.pdf]
• 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 [http://arxiv.org/pdf/1607.05781v1.pdf]
  • project [http://guanghan.info/projects/ROLO/]
  • github [https://github.com/Guanghan/ROLO/]
• RATM: Samira Ebrahimi Kahou, Vincent Michalski, Roland Memisevic. "RATM: Recurrent Attentive Tracking Model." arXiv (2015).
  • paper [https://arxiv.org/pdf/1510.08660v4.pdf]
  • github [https://github.com/saebrahimi/RATM]
• SO-DLT: Naiyan Wang, Siyi Li, Abhinav Gupta, Dit-Yan Yeung. "Transferring Rich Feature Hierarchies for Robust Visual Tracking." arXiv (2015).
  • paper [https://arxiv.org/pdf/1501.04587v2.pdf]
  • code [http://www.votchallenge.net/vot2016/download/08_SO-DLT.zip]
• DMSRDCF: Susanna Gladh, Martin Danelljan, Fahad Shahbaz Khan, Michael Felsberg. "Deep Motion Features for Visual Tracking." ICPR Best Paper(2016).
  • paper](https://arxiv.org/pdf/1612.06615v1.pdf]

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