7 citations · 9 across the 9 of their papers we have counts for
9 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…
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…
Rethinking Gradient Operator for Exposing AI-enabled Face Forgeries
Zhiqing Guo, Gaobo Yang, Dengyong Zhang +1
For image forensics, convolutional neural networks (CNNs) tend to learn content features rather than subtle manipulation traces, which limits forensic performance. Existing methods…
Exposing Deepfake Face Forgeries with Guided Residuals
Zhiqing Guo, Gaobo Yang, Jiyou Chen +1
Residual-domain feature is very useful for Deepfake detection because it suppresses irrelevant content features and preserves key manipulation traces. However, inappropriate residu…
Fake face detection via adaptive manipulation traces extraction network
Zhiqing Guo, Gaobo Yang, Jiyou Chen +1
With the proliferation of face image manipulation (FIM) techniques such as Face2Face and Deepfake, more fake face images are spreading over the internet, which brings serious chall…