REFIT: A Unified Watermark Removal Framework For Deep Learning Systems With Limited Data

Author:

Chen Xinyun1,Wang Wenxiao2,Bender Chris1,Ding Yiming1,Jia Ruoxi3,Li Bo4,Song Dawn1

Affiliation:

1. University of California, Berkeley, Berkeley, CA, USA

2. Tsinghua University, Beijing, China

3. Virginia Tech, Blacksburg, VA, USA

4. University of Illinois at Urbana-Champaign, Champaign, IL, USA

Funder

DARPA D3M

National Science Foundation

Publisher

ACM

Cited by 37 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. An Explainable Intellectual Property Protection Method for Deep Neural Networks Based on Intrinsic Features;IEEE Transactions on Artificial Intelligence;2024-09

2. A Self-Supervised CNN for Image Watermark Removal;IEEE Transactions on Circuits and Systems for Video Technology;2024-08

3. Perceptive Self-Supervised Learning Network for Noisy Image Watermark Removal;IEEE Transactions on Circuits and Systems for Video Technology;2024-08

4. Data-Free Watermark for Deep Neural Networks by Truncated Adversarial Distillation;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

5. When deep learning meets watermarking: A survey of application, attacks and defenses;Computer Standards & Interfaces;2024-04

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