This is the code for the paper "Video Salient Object Detection via Adaptive Local-Global Refinement". Paper link: https://arxiv.org/abs/2104.14360
ubuntu 18.04
PyTorch 1.8.0
cuda 10.2
- config.py. It is for dataset path. You can configure your image path in this file.
- infer.py. It is for testing. After configuring the image path, you can use it to generate saliency maps.
- pretrained. The pretrained model can save here. And, the saliency results also can save here. The pretrained model link is https://drive.google.com/file/d/1TqhwJ-D0i6WrQQDlAI7Di0H90GDYJBvA/view?usp=sharing
- We also provide the generated saliency maps. The download link is https://drive.google.com/file/d/1MHdC4g3MDZQ5XWmhBiEOIGoH_RRVdKFR/view?usp=sharing
- You can put your images in data folder. Inside, there is a example. A txt file is used to list the images and ViSal is a short testing dataset.