# 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)
