37 citations · 43 across the 12 of their papers we have counts for
13 papers
Adversarial Attacks Against MLLMs via Progressive Resolution Processing and Adaptive Feature Alignment
Haobo Wang, Xiaorong Ma, Weiqi Luo +2
Adversarial perturbations can mislead Multimodal Large Language Models (MLLMs) recognize a benign image as a specific target object, posing serious risks in safety-critical scenari…
AttDiff-GAN: A Hybrid Diffusion-GAN Framework for Facial Attribute Editing
Wenmin Huang, Weiqi Luo, Xiaochun Cao +1
Facial attribute editing aims to modify target attributes while preserving attribute-irrelevant content and overall image fidelity. Existing GAN-based methods provide favorable con…
LatRef-Diff: Latent and Reference-Guided Diffusion for Facial Attribute Editing and Style Manipulation
Wenmin Huang, Weiqi Luo, Xiaochun Cao +1
Facial attribute editing and style manipulation are crucial for applications like virtual avatars and photo editing. However, achieving precise control over facial attributes witho…
A Novel Residual-guided Learning Method for Image Steganography
Miaoxin Ye, Dongxia Huang, Kangkang Wei +1
Traditional steganographic techniques have often relied on manually crafted attributes related to image residuals. These methods demand a significant level of expertise and face ch…
AI-Generated Image Detection using a Cross-Attention Enhanced Dual-Stream Network
Ziyi Xi, Wenmin Huang, Kangkang Wei +2
With the rapid evolution of AI Generated Content (AIGC), forged images produced through this technology are inherently more deceptive and require less human intervention compared t…
Dual Stream Computer-Generated Image Detection Network Based On Channel Joint And Softpool
Ziyi Xi, Hao Lin, Weiqi Luo
With the development of computer graphics technology, the images synthesized by computer software become more and more closer to the photographs. While computer graphics technology…
Universal Deep Network for Steganalysis of Color Image based on Channel Representation
Kangkang Wei, Weiqi Luo, Shunquan Tan +1
Up to now, most existing steganalytic methods are designed for grayscale images, and they are not suitable for color images that are widely used in current social networks. In this…
Improved Xception with Dual Attention Mechanism and Feature Fusion for Face Forgery Detection
Hao Lin, Weiqi Luo, Kangkang Wei +1
With the rapid development of deep learning technology, more and more face forgeries by deepfake are widely spread on social media, causing serious social concern. Face forgery det…
Universal Stego Post-processing for Enhancing Image Steganography
Bolin Chen, Weiqi Luo, Peijia Zheng +1
It is well known that the designing or improving embedding cost becomes a key issue for current steganographic methods. Unlike existing works, we propose a novel framework to enhan…
Enhancing JPEG Steganography using Iterative Adversarial Examples
Huaxiao Mo, Tingting Song, Bolin Chen +2
Convolutional Neural Networks (CNN) based methods have significantly improved the performance of image steganalysis compared with conventional ones based on hand-crafted features.…
Image Processing Operations Identification via Convolutional Neural Network
Bolin Chen, Haodong Li, Weiqi Luo
In recent years, image forensics has attracted more and more attention, and many forensic methods have been proposed for identifying image processing operations. Up to now, most ex…
Anti-Forensics of Camera Identification and the Triangle Test by Improved Fingerprint-Copy Attack
Haodong Li, Weiqi Luo, Quanquan Rao +1
The fingerprint-copy attack aims to confuse camera identification based on sensor pattern noise. However, the triangle test shows that the forged images undergone fingerprint-copy…
Identification of Image Operations Based on Steganalytic Features
Haodong Li, Weiqi Luo, Xiaoqing Qiu +1
Image forensics have attracted wide attention during the past decade. Though many forensic methods have been proposed to identify image forgeries, most of them are targeted ones, s…