This is the implementation of our IJCAI'21 paper (Learning from Complementary Labels via Partial-Output Regularization Consistency).
Requirements: Python 3.6, numpy 1.19, Pytorch 1.5, torchvision 0.6.
You need to:
- Download SVHN and CIFAR-10 datasets into './data/'.
- Run the following demos:
python main.py --dataset svhn --model lenet --data-dir ./data/svhn/
python main.py --dataset svhn --model preact --data-dir ./data/svhn/
python main.py --dataset cifar10 --model preact --data-dir ./data/cifar/
python main.py --dataset cifar10 --model widenet --data-dir ./data/cifar/
If you have any further questions, please feel free to send an e-mail to: wangdb@seu.edu.cn. Have fun!