Code release for "Say No to Freeloader: Protecting Intellectual Property of Your Deep Model" (PAMI 2024)
Say No to Freeloader: Protecting Intellectual Property of Your Deep Model (PAMI 2024)
We propose a Compact Un-transferable Pyramid Isolation Domain (CUPI-Domain) which serves as a barrier against illegal transfers from authorized to unauthorized domains, to protect the intellectual property (IP) of AI models.
The code is implemented with CUDA 11.4, Python 3.8.5 and Pytorch 1.8.0.
MNIST dataset can be found here.
USPS dataset can be found here.
SVHN dataset can be found here.
MNIST-M dataset can be found here.
CIFAR-10 dataset can be found here.
CIFAR-10 dataset can be found here.
VisDA 2017 dataset can be found here.
Office-Home dataset can be found here.
DomainNet dataset can be found here.
Target-Specified CUPI-Domain
python train_ts_dight.py
Ownership Verification by CUPI-Domain
python train_owner_dight.py
Target-free CUPI-Domain
python train_tf_dight.py
Applicability Authorization by CUPI-Domain
python train_author_dight.py
If you find this code useful for your research, please cite our paper:
@article{wang2024say,
title={Say No to Freeloader: Protecting Intellectual Property of Your Deep Model},
author={Wang, Lianyu and Wang, Meng and Fu, Huazhu and Zhang, Daoqaing},
journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
year={2024},
publisher={IEEE}
}
Some codes are adapted from NTL and SWIN-Transformer. We thank them for their excellent projects.
If you have any problem about our code, feel free to contact
or describe your problem in Issues.