Awesome
Joint Salient Object Detection and Camouflaged Object Detection via Uncertainty-aware Learning
This code is the journal extension version of: Uncertainty-aware Joint Salient Object and Camouflaged Object Detection (CVPR2021)
Train the model
Set up
pip install -r requirements.txt
Train Model
- Prepare data for training (We provided the related data in:[Google_Drive]. Please download it and put it in the './train_data/' folder)
- 'duts+wmae' means the augmented SOD training set
- 'COD_train' means the COD training dataset
- 'JPEGImages_select' means the selected PASCAL VOC dataset
python train.py
Test and Evaluate Model
- Prepare data for testing (We provided the related SOD and COD test image and ground-truth in:[Google_Drive]. Please download it and put it in the './test_data/' folder)
python test.py
Pretrained model and Prediction Maps
Trained model:
Please download the trained model and put it in "./models/": [Google_Drive];
Prediction Maps:
Results of our model on four benchmark datasets (CAMO, CHAMELEON, COD10K, NC4K) for COD:[Google_Drive]; and six benchmark datasets (DUTS, ECSSD, DUT, HKU-IS, PASCAL, SOD ) for SOD: [Google_Drive]