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Found 13 papers, 2 papers with code
Hierarchical Invariance for Robust and Interpretable Vision Tasks at Larger Scales
Developing robust and interpretable vision systems is a crucial step towards trustworthy artificial intelligence.
Robust Retraining-free GAN Fingerprinting via Personalized Normalization
In recent years, there has been significant growth in the commercial applications of generative models, licensed and distributed by model developers to users, who in turn use them to offer services.
Wide Flat Minimum Watermarking for Robust Ownership Verification of GANs
We present the results of extensive experiments showing that the presence of the watermark has a negligible impact on the quality of the generated images, and proving the superior robustness of the watermark against model modification and surrogate model attacks.
Reversible Quantization Index Modulation for Static Deep Neural Network Watermarking
In this paper, we propose a novel RDH-based static DNN watermarking scheme using quantization index modulation (QIM).
CHEAT: A Large-scale Dataset for Detecting ChatGPT-writtEn AbsTracts
The powerful ability of ChatGPT has caused widespread concern in the academic community.
Learning to mask: Towards generalized face forgery detection
Our goal is to reduce the features that are easy to learn in the training phase, so as to reduce the risk of overfitting on specific forgery types.
General GAN-generated image detection by data augmentation in fingerprint domain
To our knowledge, we are the first to conduct data augmentation in the fingerprint domain.
Watermarking in Secure Federated Learning: A Verification Framework Based on Client-Side Backdooring
In this paper, we propose a novel client-side FL watermarking scheme to tackle the copyright protection issue in secure FL with HE.
Learning Second Order Local Anomaly for General Face Forgery Detection
We also propose a Local Enhancement Module (LEM) to improve the discrimination between local features of real and forged regions, so as to ensure accuracy in calculating anomalies.
Supervised GAN Watermarking for Intellectual Property Protection
The aim is to watermark the GAN model so that any image generated by the GAN contains an invisible watermark (signature), whose presence inside the image can be checked at a later stage for ownership verification.
Deniable Steganography
With a stego media discovered, the adversary could find out the sender or receiver and coerce them to disclose the secret message, which we name as coercive attack in this paper.
A Screen-Shooting Resilient Document Image Watermarking Scheme using Deep Neural Network
By applying this scheme, when the watermarked image is displayed on the screen and captured by a camera, the watermark can be still extracted from the captured photographs.
A Robust Document Image Watermarking Scheme using Deep Neural Network
Then the identity can be extracted to prove the copyright from the watermarked carrier even after suffering various attacks.
