Accepted paper in Neurips2022:
Semi-Supervised Video Salient Object Detection Based on Uncertainty-Guided Pseudo Labels
Yongri Piao, Chenyang Lu, Miao Zhang, Huchuan Lu.
- Ubuntu 20.04
- CUDA 11.3
- PyTorch 1.7.0
- Python 3.6
pretrained models ,code：zve9
Modify the paths for the testing dataset and pre-trained model(10GT+50PL_best.pth).
- python test_fuse.py
1.Select a certain number of ground truth, and modify the training dataset and pre-trained model(pretrain_resnet50.pth) paths to train the pseudo-label generator.
- python train.py
You can also use our pretrained model (pseudo_label.pth) to generate pseudo-labels.
2.Select a certain number of pseudo-labels, and modify the training dataset and pre-trained model paths(pretrain_resnet50.pth for RGB stream & resnet50-19c8e357.pth for OPT stream) to collaboratively train NS-GAN with the ground truth.
- python ST-train.py
If you have any questions, please contact us (luchenyang0724@mail.dlut.edu.cn).