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Found 6 papers, 1 papers with code
Regeneration Based Training-free Attribution of Fake Images Generated by Text-to-Image Generative Models
Comprehensive experiments reveal that (1) Our method can effectively attribute fake images to their source models, achieving comparable attribution performance with the state-of-the-art method; (2) Our method has high scalability ability, which is well adapted to real-world attribution scenarios.
Object-oriented backdoor attack against image captioning
After training with the poisoned data, the attacked model behaves normally on benign images, but for poisoned images, the model will generate some sentences irrelevant to the given image.
Towards Deep Network Steganography: From Networks to Networks
In this paper, we propose deep network steganography for the covert communication of DNN models.
Steganography of Steganographic Networks
We propose to disguise a steganographic network (termed as the secret DNN model) into a stego DNN model which performs an ordinary machine learning task (termed as the stego task).
Exploring Depth Information for Face Manipulation Detection
As one of the important face features, the face depth map, which has shown to be effective in other areas such as the face recognition or face detection, is unfortunately paid little attention to in literature for detecting the manipulated face images.
Joint Vehicular Localization and Reflective Mapping Based on Team Channel-SLAM
This approach exploits an initial (e. g. GPS-based) vehicle position information and allows subsequent tracking of vehicles by exploiting the shared nature of virtual transmitters associated to the reflecting surfaces.
