67 citations · 142 across the 35 of their papers we have counts for
22 papers · 1 filter
Venus-DefakerOne2: A Vision-Forensics Foundation Model with Broader Coverage
Chenfan Qu, Yachao Liang, Mingqi Fang +28
Real-world forgery is inherently heterogeneous: it manifests not only as digital manipulation but also as physical spoofing, and is carried not only by images but also by videos. D…
Grounding and Explaining Visual Evidence for AI-Generated Image Detection in Human-Centric Scenes
Kun Guo, Yuzhou Yang, Haoyue Wang +3
Rapid advances in image generation models call for interpretable AI-generated image detection methods that not only determine authenticity but also provide supporting visual eviden…
SimuFreeMark: A Noise-Simulation-Free Robust Watermarking Against Image Editing
Yichao Tang, Mingyang Li, Di Miao +3
The advancement of artificial intelligence generated content (AIGC) has created a pressing need for robust image watermarking that can withstand both conventional signal processing…
MoFRR: Mixture of Diffusion Models for Face Retouching Restoration
Jiaxin Liu, Qichao Ying, Zhenxing Qian +4
The widespread use of face retouching on social media platforms raises concerns about the authenticity of face images. While existing methods focus on detecting face retouching, ho…
Adversarial Shallow Watermarking
Guobiao Li, Lei Tan, Yuliang Xue +4
Recent advances in digital watermarking make use of deep neural networks for message embedding and extraction. They typically follow the ``encoder-noise layer-decoder''-based archi…
Exploring Depth Information for Detecting Manipulated Face Videos
Haoyue Wang, Sheng Li, Ji He +3
Face manipulation detection has been receiving a lot of attention for the reliability and security of the face images/videos. Recent studies focus on using auxiliary information or…
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…
Object-oriented backdoor attack against image captioning
Meiling Li, Nan Zhong, Xinpeng Zhang +2
Backdoor attack against image classification task has been widely studied and proven to be successful, while there exist little research on the backdoor attack against vision-langu…
PROMPT-IML: Image Manipulation Localization with Pre-trained Foundation Models Through Prompt Tuning
Xuntao Liu, Yuzhou Yang, Qichao Ying +3
Deceptive images can be shared in seconds with social networking services, posing substantial risks. Tampering traces, such as boundary artifacts and high-frequency information, ha…
From Covert Hiding to Visual Editing: Robust Generative Video Steganography
Xueying Mao, Xiaoxiao Hu, Wanli Peng +5
Traditional video steganography methods are based on modifying the covert space for embedding, whereas we propose an innovative approach that embeds secret message within semantic…
Steal My Artworks for Fine-tuning? A Watermarking Framework for Detecting Art Theft Mimicry in Text-to-Image Models
Ge Luo, Junqiang Huang, Manman Zhang +3
The advancement in text-to-image models has led to astonishing artistic performances. However, several studios and websites illegally fine-tune these models using artists' artworks…
PatchCraft: Exploring Texture Patch for Efficient AI-generated Image Detection
Nan Zhong, Yiran Xu, Sheng Li +2
Recent generative models show impressive performance in generating photographic images. Humans can hardly distinguish such incredibly realistic-looking AI-generated images from rea…
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…
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…
Generative Steganographic Flow
Ping Wei, Ge Luo, Qi Song +3
Generative steganography (GS) is a new data hiding manner, featuring direct generation of stego media from secret data. Existing GS methods are generally criticized for their poor…
Exploring Depth Information for Face Manipulation Detection
Haoyue Wang, Meiling Li, Sheng Li +2
Face manipulation detection has been receiving a lot of attention for the reliability and security of the face images. Recent studies focus on using auxiliary information or prior…
Generative Steganography Network
Ping Wei, Sheng Li, Xinpeng Zhang +3
Steganography usually modifies cover media to embed secret data. A new steganographic approach called generative steganography (GS) has emerged recently, in which stego images (ima…
Image Generation Network for Covert Transmission in Online Social Network
Zhengxin You, Qichao Ying, Sheng Li +2
Online social networks have stimulated communications over the Internet more than ever, making it possible for secret message transmission over such noisy channels. In this paper,…
Multimodal Fake News Detection via CLIP-Guided Learning
Yangming Zhou, Qichao Ying, Zhenxing Qian +2
Multimodal fake news detection has attracted many research interests in social forensics. Many existing approaches introduce tailored attention mechanisms to guide the fusion of un…
Invertible Image Dataset Protection
Kejiang Chen, Xianhan Zeng, Qichao Ying +3
Deep learning has achieved enormous success in various industrial applications. Companies do not want their valuable data to be stolen by malicious employees to train pirated model…
On Generating Identifiable Virtual Faces
Zhuowen Yuan, Zhengxin You, Sheng Li +3
Face anonymization with generative models have become increasingly prevalent since they sanitize private information by generating virtual face images, ensuring both privacy and im…
RWN: Robust Watermarking Network for Image Cropping Localization
Qichao Ying, Xiaoxiao Hu, Xiangyu Zhang +2
Image cropping can be maliciously used to manipulate the layout of an image and alter the underlying meaning. Previous image crop detection schemes only predicts whether an image h…