目标跟踪算法2017

时间：2022-01-03 12:51:43

强力推荐@Qiang Wang维护的资源benchmark_results：大量*方法在OTB库上的性能对比，各种论文代码应有尽有，大神自己C++实现并开源的CSK, KCF和DAT.

foolwood/benchmark_results（https://github.com/foolwood/benchmark_results），还有他自己最新论文DCFNet论文加源码。

隆重推荐@H Hakase维护的相关滤波类资源 HakaseH/CF_benchmark_results（https://github.com/HakaseH/CF_benchmark_results），详细分类和论文代码资源，最详尽的相关滤波资源！



HakaseH/CF_benchmark_results

Benchmark Results of Correlation Filters

Collect and share results for correlation filter trackers.

Results on OTB

目标跟踪算法2017

目标跟踪算法2017

  • All results run on a 3.5GHz Intel Core i7 CPU with 32 GB memory.
  • We use the first frame's ground truth instead of the second frame's in the code of HDT. So there may be a gap between the result above and the paper.
  • You can find more plots in the OTB code folder of the repository.

Papers & Codes

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]

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]

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." arXiv (2017). [paper]

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]


foolwood/benchmark_results



OTB Results

Share results for more recent trackers.

标签：

相关文章