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CF-Caffe

Caffe designed for Deep Context Features

Basic Citation

If you use CF-Caffe, please cite:

@InProceedings{Hu_2018_CVPR,
     author = {Hu, Xiaowei and Zhu, Lei and Fu, Chi-Wing and Qin, Jing and Heng, Pheng-Ann},
     title = {Direction-Aware Spatial Context Features for Shadow Detection},
     booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
     pages={7454--7462},
     year = {2018}
}

@article{hu2019direction,
     author = {Hu, Xiaowei and Fu, Chi-Wing and Zhu, Lei and Qin, Jing and Heng, Pheng-Ann},
     title = {Direction-Aware Spatial Context Features for Shadow Detection and Removal},
     journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
     year = {2019},
     note={to appear}
}

@article{jia2014caffe,
     author = {Jia, Yangqing and Shelhamer, Evan and Donahue, Jeff and Karayev, Sergey and Long, Jonathan and Girshick, Ross and Guadarrama, Sergio and Darrell, Trevor},
     title = {Caffe: Convolutional Architecture for Fast Feature Embedding},
     journal = {arXiv preprint arXiv:1408.5093},
     year = {2014}
}

Installation

  1. Clone this repository.

    git clone https://github.com/xw-hu/CF-Caffe.git
  2. Build CF-Caffe

    *This model is tested on Ubuntu 16.04, CUDA 8.0.

    Follow the Caffe installation instructions here: https://caffe.berkeleyvision.org/installation.html

    make all -jXX
  3. If you want to use MATLAB or Python:

    make matcaffe
    make pycaffe

Models

If you use these models, please cite their papers accordingly.

  1. Segmentation models in examples/segmentation/:

    Deeplab v1, Deeplab v3, Deeplab v3 plus, PSPNet, PSANet, Non-local Network (FPN based).

  2. This version of Caffe is used in:

@InProceedings{Hu_2019_CVPR,
     author = {Hu, Xiaowei and Fu, Chi-Wing and Zhu, Lei and Heng, Pheng-Ann},
     title = {Depth-Attentional Features for Single-Image Rain Removal},
     booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
     pages={8022--8031},
     year = {2019}
}

@InProceedings{Hu_2018_CVPR,
     author = {Hu, Xiaowei and Zhu, Lei and Fu, Chi-Wing and Qin, Jing and Heng, Pheng-Ann},
     title = {Direction-Aware Spatial Context Features for Shadow Detection},
     booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
     pages={7454--7462},
     year = {2018}
}

@article{hu2019direction,
     author = {Hu, Xiaowei and Fu, Chi-Wing and Zhu, Lei and Qin, Jing and Heng, Pheng-Ann},
     title = {Direction-Aware Spatial Context Features for Shadow Detection and Removal},
     journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
     year = {2019},
     note={to appear}
}

@article{hu2020sac,
     author = {Hu, Xiaowei and Fu, Chi-Wing and Zhu, Lei and Wang, Tianyu and Heng, Pheng-Ann},
     title = {SAC-Net: Spatial Attenuation Context for Salient Object Detection},
     journal = {IEEE Transactions on Circuits and Systems for Video Technology},
     year = {2020},
     note = {to appear},
}

@article{zhu2020saliency,
     author = {Zhu, Lei and Hu, Xiaowei and Fu, Chi-Wing and Qin, Jing and Heng, Pheng-Ann},
     title = {Saliency-Aware Texture Smoothing},
     journal={IEEE Transactions on Visualization and Computer Graphics},
     volume={26},
     number={7},
     pages={2471-2484},
     year={2020} }

@inproceedings{hu18recurrently,
     author = {Hu, Xiaowei and Zhu, Lei and Qin, Jing and Fu, Chi-Wing and Heng, Pheng-Ann},
     title = {Recurrently Aggregating Deep Features for Salient Object Detection},
     booktitle = {AAAI},
     pages={6943--6950},
     year = {2018}
}

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Caffe designed for Deep Context Features

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