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DSC-PyTorch

This is a PyTorch implementation of "Direction-Aware Spatial Context Features for Shadow Detection, CVPR'18" and "Direction-Aware Spatial Context Features for Shadow Detection and Removal, T-PAMI'19" based on Xiaowei's DSC (Caffe) written by Tianyu Wang.

The Spacial IRNN is implemented by using CUDA 11.x. The backbone is ResNeXt101 pre-trained on ImageNet and the implementation of loss is from Quanlong Zheng.

Results

We use two GTX 1080Ti to train the DSC on SBU dataset.

SBU

Methods	BER	Accuracy
DSC (Caffe)	5.59	0.97
DSC (Our)	5.19	0.95

Pre-trained model is available. You can download from OneDrive and put it into SBU_model folder.

You can download the ResNeXt101 model from Google Drive and put it in main folder.

Requirements

PyTorch == 1.8.1 (training and testing)
Cupy (Installation Guide)
TensorBoardX
Python
progressbar2
scikit-image
pydensecrf

Train/Test

Clone this repository

git clone https://github.com/stevewongv/DSC-PyTorch.git

Train

python3 main.py -a train    # For Shadow Detection
python3 main_sr.py -a train # For Shadow Removal

Test

python3 main.py -a test    # For Shadow Detection
python3 main_sr.py -a test # For Shadow Removal

Citations

@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{hu2020direction,
     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},
     pages={2795--2808},
     year = {2020}
}

Modified DSC module is used in SPANet:

@InProceedings{Wang_2019_CVPR,
  author = {Wang, Tianyu and Yang, Xin and Xu, Ke and Chen, Shaozhe and Zhang, Qiang and Lau, Rynson W.H.},
  title = {Spatial Attentive Single-Image Deraining with a High Quality Real Rain Dataset},
  booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  month = {June},
  year = {2019}
}