This paper proposes a Bi-Directional Cascade Network for edge detection. By introducing a bi-directional cascade structure to enforce each layer to focus on a specific scale, BDCN trains each network layer with a layer-specific supervision. To enrich the multi-scale representations learned with a shallow network, we further introduce a Scale Enhancement Module (SEM). Here are the code for this paper.
- pytorch >= 0.2.0(Our code is based on the 0.2.0)
- numpy >= 1.11.0
- pillow >= 3.3.0
- Clone this repository to local
git clone https://github.com/pkuCactus/BDCN.git-
Download the imagenet pretrained vgg16 pytorch model [vgg16.pth](link: https://pan.baidu.com/s/10Tgjs7FiAYWjVyVgvEM0mA code: ab4g) or the caffemodel from the model zoo and then transfer to pytorch version. You also can download our pretrained model for only evaluation. The google drive link.
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Download the dataset to the local folder
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running the training code train.py or test code test.py
BDCN model for BSDS500 dataset and NYUDv2 datset of RGB and depth are availavble on Baidu Disk.
The link https://pan.baidu.com/s/18PcPQTASHKD1-fb1JTzIaQ
code: j3de