xmed-lab / SC-Cor

ECCV 2022: Learning Shadow Correspondence for Video Shadow Detection

Learning Shadow Correspondence for Video Shadow Detection

Introduction

This is a PyTorch implementation of [Learning Shadow Correspondence for Video Shadow Detection][ECCV22].

Framework visualization

Preparation

Datasets ViSha dataset is available at ViSha Homepage

Run the code

Installation

  MedPy==0.4.0
  numpy==1.20.3
  Pillow==9.2.0
  pydensecrf==1.0rc2
  torch==1.9.0
  torchvision==0.10.0
  tqdm==4.61.2

or

 pip install -r requirements.txt

Train the model

 python train.py

You can also down the trained model from Google Driver and put them in ckpt/models.

Testing

python test.py

Citation If this code is useful for your research, please consider citing:

@inproceedings{ding2022learning,
  title={Learning Shadow Correspondence for Video Shadow Detection},
  author={Xinpeng Ding, Jingwen Yang, Xiaowei Hu and Xiaomeng Li},
  booktitle={Proceeding of the 17th European Conference on Computer Vision, ECCV},
  year={2022}
}