13 citations · 13 across the 11 of their papers we have counts for
11 papers
When 2D Cues Fail: Improving Image Manipulation Localization with Reliable 3D Geometry
Guofeng Yu, Zhiqing Guo, Dan Ma +1
Existing image manipulation localization (IML) methods rely heavily on 2D forensic cues, such as low-level artifacts, noise traces, and semantic inconsistencies in the manipulated…
The Courtroom Trial of Pixels: Robust Image Manipulation Localization via Adversarial Evidence and Reinforcement Learning Judgment
Songlin Li, Zhiqing Guo, Kebin Chen +6
Although some existing image manipulation localization (IML) methods incorporate authenticity-related supervision, this information is typically utilized merely as an auxiliary tra…
GIFGuard: Proactive Forensics against Deepfakes in Facial GIFs via Spatiotemporal Watermarking
Shupeng Che, Zhiqing Guo, Changtao Miao +2
The rapid evolution of deepfake technology poses an unprecedented threat to the authenticity of Graphics Interchange Format (GIF) imagery, which serves as a representative of short…
Whether, Which, and Whose: Solving the Triple Challenge of Deepfake Proactive Forensics in Multi-Face Scenarios
Lei Zhang, Zhiqing Guo, Dan Ma +2
Unlike single-face forgeries, deepfakes in complex multi-person interaction scenarios (such as group photos and multi-person meetings) more closely reflect real-world threats. Alth…
From Passive Perception to Active Memory: A Weakly Supervised Image Manipulation Localization Framework Driven by Coarse-Grained Annotations
Zhiqing Guo, Dongdong Xi, Songlin Li +1
Image manipulation localization (IML) faces a fundamental trade-off between minimizing annotation cost and achieving fine-grained localization accuracy. Existing fully-supervised I…
Forgery Guided Learning Strategy with Dual Perception Network for Deepfake Cross-domain Detection
Lixin Jia, Zhiqing Guo, Gaobo Yang +2
The emergence of deepfake technology has introduced a range of societal problems, garnering considerable attention. Current deepfake detection methods perform well on specific data…
Uncovering and Mitigating Destructive Multi-Embedding Attacks in Deepfake Proactive Forensics
Lixin Jia, Haiyang Sun, Zhiqing Guo +3
With the rapid evolution of deepfake technologies and the wide dissemination of digital media, personal privacy is facing increasingly serious security threats. Deepfake proactive…
Bridging Semantic Logic Gaps: A Cognition Inspired Multimodal Boundary Preserving Network for Image Manipulation Localization
Songlin Li, Zhiqing Guo, Yuanman Li +4
The existing image manipulation localization (IML) models mainly relies on visual cues, but ignores the semantic logical relationships between content features. In fact, the conten…
Beyond Fully Supervised Pixel Annotations: Scribble-Driven Weakly-Supervised Framework for Image Manipulation Localization
Songlin Li, Guofeng Yu, Zhiqing Guo +3
Deep learning-based image manipulation localization (IML) methods have achieved remarkable performance in recent years, but typically rely on large-scale pixel-level annotated data…
DiffMark: Diffusion-based Robust Watermark Against Deepfakes
Chen Sun, Haiyang Sun, Zhiqing Guo +5
Deepfakes pose significant security and privacy threats through malicious facial manipulations. While robust watermarking can aid in authenticity verification and source tracking,…
WaveGuard: Robust Deepfake Detection and Source Tracing via Dual-Tree Complex Wavelet and Graph Neural Networks
Ziyuan He, Zhiqing Guo, Liejun Wang +3
Deepfake technology poses increasing risks such as privacy invasion and identity theft. To address these threats, we propose WaveGuard, a proactive watermarking framework that enha…