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Name		Name	Last commit message	Last commit date
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ckpt		ckpt
models		models
IRNN_Backward_cuda.cu		IRNN_Backward_cuda.cu
IRNN_Forward_cuda.cu		IRNN_Forward_cuda.cu
KL_divergence.py		KL_divergence.py
README.md		README.md
config.py		config.py
dataset.py		dataset.py
dataset_category.py		dataset_category.py
infer.py		infer.py
irnn.py		irnn.py
joint_transforms.py		joint_transforms.py
misc.py		misc.py
modules.py		modules.py
nets.py		nets.py
train.py		train.py
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• README

FSDNet

Revisiting Shadow Detection: A New Benchmark Dataset for Complex World

by Xiaowei Hu, Tianyu Wang, Chi-Wing Fu, Yitong Jiang, Qiong Wang, and Pheng-Ann Heng.

Fast Shadow Detection Network

This implementation is written by Xiaowei Hu at the Chinese University of Hong Kong.

Citation

@article{hu2021revisiting, title={Revisiting Shadow Detection: A New Benchmark Dataset for Complex World}, author={Hu, Xiaowei and Wang, Tianyu and Fu, Chi-Wing and Jiang, Yitong and Wang, Qiong and Heng, Pheng-Ann}, journal={IEEE Transactions on Image Processing}, volume={30}, pages={1925--1934}, year={2021} }

Results

Please find the new results (without CRF for shadow detection) at https://github.com/xw-hu/Unveiling-Deep-Shadows.

Requirements

• PyTorch1.3.0
• Python3.6
• Cupy [Installation Guide]

Train and Test

1. Clone this repository:

   git clone https://github.com/xw-hu/FSDNet.git

2. Train:

   python3 train.py

3. Test:

   python3 infer.py

CUHK-Shadow Dataset

Please find the dataset at https://github.com/xw-hu/CUHK-Shadow#cuhk-shadow-dateset.

Evaluation Function

Please find the evaluation function at https://github.com/xw-hu/CUHK-Shadow#cuhk-shadow-evaluation.

About

Fast Shadow Detection Network

Topics

shadow-detection

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