10 citations · 13 across the 10 of their papers we have counts for
7 papers · 1 filter
Morphology-optimized Multi-Scale Fusion: Combining Local Artifacts and Mesoscopic Semantics for Deepfake Detection and Localization
Chao Shuai, Gaojian Wang, Kun Pan +7
While the pursuit of higher accuracy in deepfake detection remains a central goal, there is an increasing demand for precise localization of manipulated regions. Despite the remark…
Harnessing Frequency Spectrum Insights for Image Copyright Protection Against Diffusion Models
Zhenguang Liu, Chao Shuai, Shaojing Fan +4
Diffusion models have achieved remarkable success in novel view synthesis, but their reliance on large, diverse, and often untraceable Web datasets has raised pressing concerns abo…
FSFM: A Generalizable Face Security Foundation Model via Self-Supervised Facial Representation Learning
Gaojian Wang, Feng Lin, Tong Wu +3
This work asks: with abundant, unlabeled real faces, how to learn a robust and transferable facial representation that boosts various face security tasks with respect to generaliza…
Do As I Do: Pose Guided Human Motion Copy
Sifan Wu, Zhenguang Liu, Beibei Zhang +4
Human motion copy is an intriguing yet challenging task in artificial intelligence and computer vision, which strives to generate a fake video of a target person performing the mot…
Exposing the Deception: Uncovering More Forgery Clues for Deepfake Detection
Zhongjie Ba, Qingyu Liu, Zhenguang Liu +4
Deepfake technology has given rise to a spectrum of novel and compelling applications. Unfortunately, the widespread proliferation of high-fidelity fake videos has led to pervasive…
Locate and Verify: A Two-Stream Network for Improved Deepfake Detection
Chao Shuai, Jieming Zhong, Shuang Wu +6
Deepfake has taken the world by storm, triggering a trust crisis. Current deepfake detection methods are typically inadequate in generalizability, with a tendency to overfit to ima…
DFIL: Deepfake Incremental Learning by Exploiting Domain-invariant Forgery Clues
Kun Pan, Yin Yifang, Yao Wei +6
The malicious use and widespread dissemination of deepfake pose a significant crisis of trust. Current deepfake detection models can generally recognize forgery images by training…