2 citations · 3 across the 8 of their papers we have counts for
8 papers · 1 filter
A Lightweight and Effective Image Tampering Localization Network with Vision Mamba
Kun Guo, Gang Cao, Zijie Lou +2
Current image tampering localization methods primarily rely on Convolutional Neural Networks (CNNs) and Transformers. While CNNs suffer from limited local receptive fields, Transfo…
Image Forgery Localization with State Space Models
Zijie Lou, Gang Cao, Kun Guo +2
Pixel dependency modeling from tampered images is pivotal for image forgery localization. Current approaches predominantly rely on Convolutional Neural Networks (CNNs) or Transform…
Video Inpainting Localization with Contrastive Learning
Zijie Lou, Gang Cao, Man Lin
Deep video inpainting is typically used as malicious manipulation to remove important objects for creating fake videos. It is significant to identify the inpainted regions blindly.…
Trusted Video Inpainting Localization via Deep Attentive Noise Learning
Zijie Lou, Gang Cao, Man Lin
Digital video inpainting techniques have been substantially improved with deep learning in recent years. Although inpainting is originally designed to repair damaged areas, it can…
Exploring Multi-view Pixel Contrast for General and Robust Image Forgery Localization
Zijie Lou, Gang Cao, Kun Guo +2
Image forgery localization, which aims to segment tampered regions in an image, is a fundamental yet challenging digital forensic task. While some deep learning-based forensic meth…
Transferable Adversarial Attack on Image Tampering Localization
Yuqi Wang, Gang Cao, Zijie Lou +1
It is significant to evaluate the security of existing digital image tampering localization algorithms in real-world applications. In this paper, we propose an adversarial attack s…
Spatio-temporal Co-attention Fusion Network for Video Splicing Localization
Man Lin, Gang Cao, Zijie Lou
Digital video splicing has become easy and ubiquitous. Malicious users copy some regions of a video and paste them to another video for creating realistic forgeries. It is signific…
Black-Box Attack against GAN-Generated Image Detector with Contrastive Perturbation
Zijie Lou, Gang Cao, Man Lin
Visually realistic GAN-generated facial images raise obvious concerns on potential misuse. Many effective forensic algorithms have been developed to detect such synthetic images in…