# CF2 **Repository Path**: greitzmann/CF2 ## Basic Information - **Project Name**: CF2 - **Description**: Hierarchical Convolutional Features for Visual Tracking (ICCV 2015) - **Primary Language**: Unknown - **License**: MIT - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2019-11-14 - **Last Updated**: 2020-12-19 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # Hierarchical Convolutional Features for Visual Tracking (ICCV 2015) ### Introduction This is the research code for the paper: [Chao Ma](https://sites.google.com/site/chaoma99/), [Jia-Bin Huang](https://sites.google.com/site/jbhuang0604/), [Xiaokang Yang](http://english.seiee.sjtu.edu.cn/english/detail/842_802.htm) and [Ming-Hsuan Yang](http://faculty.ucmerced.edu/mhyang/), "Hierarchical Convolutional Features for Visual Tracking", ICCV 2015 - [PDF](https://uofi.box.com/shared/static/o8wkllte8sfyuvt8ei77o24we8l36qoj.pdf) - [Supplementary material](https://uofi.box.com/shared/static/6y3izswn40y6ckbwgm40ugledzp8fer9.pdf) - [Project page](https://sites.google.com/site/jbhuang0604/publications/cf2) - [Result visualization](https://sites.google.com/site/jbhuang0604/publications/cf2/visualization) Compared to the original implemetation, we have improved the code to achieve better results: 1. We added the scale estimation module 2. We adjust the layer weights according to [our extension work published on TPAMI](https://github.com/chaoma99/HCFTstar) To exactly reproduce the results reported in our ICCV 2015 paper, please check the early committed version [(4b895b5)](https://github.com/jbhuang0604/CF2/tree/4b895b516b2d73fc83174439729d2157902c9d63) ### Citation If you find the code and dataset useful in your research, please consider citing: @article{Ma-HCFTstar-2017, title={Robust Visual Tracking via Hierarchical Convolutional Features}, Author = {Ma, Chao and Huang, Jia-Bin and Yang, Xiaokang and Yang, Ming-Hsuan}, journal = {IEEE Transcations on Pattern Analysis and Machine Intelligence}, pages={}, Year = {2018} } @inproceedings{Ma-ICCV-2015, title={Hierarchical Convolutional Features for Visual Tracking}, Author = {Ma, Chao and Huang, Jia-Bin and Yang, Xiaokang and Yang, Ming-Hsuan}, booktitle = {Proceedings of the IEEE International Conference on Computer Vision}, pages={}, Year = {2015} } ### Contents | Folder | description | | ---|---| Feedbacks and comments are welcome! Feel free to contact us via [chaoma99@gmail.com](mailto:chaoma99@gmail.com) or [jbhuang1@illinois.edu](mailto:jbhuang1@illinois.edu). Enjoy! ### Results on visual tracking benchmark One-pass evaluation (OPE) on the 50 tracking sequences in [Wu et al. CVPR 2013](https://sites.google.com/site/trackerbenchmark/benchmarks/v10) Spatial robustness evaluation (SRE) on the 50 tracking sequences in [Wu et al. CVPR 2013](https://sites.google.com/site/trackerbenchmark/benchmarks/v10) Temporal robustness evaluation (TRE) on the 50 tracking sequences in [Wu et al. CVPR 2013](https://sites.google.com/site/trackerbenchmark/benchmarks/v10) One-pass evaluation (OPE) on the 100 tracking sequences in [Wu et al. PAMI 2015](https://sites.google.com/site/benchmarkpami) Spatial robustness evaluation (SRE) on the 100 tracking sequences in [Wu et al. PAMI 2015](https://sites.google.com/site/benchmarkpami) Temporal robustness evaluation (TRE) on the 100 tracking sequences in [Wu et al. PAMI 2015](https://sites.google.com/site/benchmarkpami)