activity
20222024
most citedGenerative Steganography Network

67 citations · 91 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CR2024

Revocable Backdoor for Deep Model Trading

Yiran Xu, Nan Zhong, Zhenxing Qian +1

Deep models are being applied in numerous fields and have become a new important digital product. Meanwhile, previous studies have shown that deep models are vulnerable to backdoor…

cs.CV2024

Are handcrafted filters helpful for attributing AI-generated images?

Jialiang Li, Haoyue Wang, Sheng Li +3

Recently, a vast number of image generation models have been proposed, which raises concerns regarding the misuse of these artificial intelligence (AI) techniques for generating fa…

cs.CR2024

Purified and Unified Steganographic Network

Guobiao Li, Sheng Li, Zicong Luo +2

Steganography is the art of hiding secret data into the cover media for covert communication. In recent years, more and more deep neural network (DNN)-based steganographic schemes…

cs.CR202318 cited

Securing Fixed Neural Network Steganography

Zicong Luo, Sheng Li, Guobiao Li +2

Image steganography is the art of concealing secret information in images in a way that is imperceptible to unauthorized parties. Recent advances show that is possible to use a fix…

cs.CV2023

DRAW: Defending Camera-shooted RAW against Image Manipulation

Xiaoxiao Hu, Qichao Ying, Zhenxing Qian +2

RAW files are the initial measurement of scene radiance widely used in most cameras, and the ubiquitously-used RGB images are converted from RAW data through Image Signal Processin…

cs.CV2023

RetouchingFFHQ: A Large-scale Dataset for Fine-grained Face Retouching Detection

Qichao Ying, Jiaxin Liu, Sheng Li +3

The widespread use of face retouching filters on short-video platforms has raised concerns about the authenticity of digital appearances and the impact of deceptive advertising. To…