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20222026
most citedLearning Second Order Local Anomaly for General Face Forgery Detection

2 citations · 2 across the 7 of their papers we have counts for

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9 papers · 1 filter

cs.CV2026

PGC: Peak-Guided Calibration for Generalizable AI-Generated Image Detection

Xiaoyu Zhou, Jianwei Fei, Peipeng Yu +3

The rapid evolution of generative AI, from GANs to modern diffusion models, has resulted in increasingly subtle discriminative clues. These fine-grained signals are often overshado…

cs.CV2026

ID-Eraser: Proactive Defense Against Face Swapping via Identity Perturbation

Junyan Luo, Peipeng Yu, Jianwei Fei +4

Deepfake technologies have rapidly advanced with modern generative AI, and face swapping in particular poses serious threats to privacy and digital security. Existing proactive def…

cs.CV2026

LBFTI: Layer-Based Facial Template Inversion for Identity-Preserving Fine-Grained Face Reconstruction

Zixuan Shen, Zhihua Xia, Kaikai Gan +1

In face recognition systems, facial templates are widely adopted for identity authentication due to their compliance with the data minimization principle. However, facial template…

cs.CV2026

High-Fidelity Face Content Recovery via Tamper-Resilient Versatile Watermarking

Peipeng Yu, Jinfeng Xie, Chengfu Ou +5

The proliferation of AIGC-driven face manipulation and deepfakes poses severe threats to media provenance, integrity, and copyright protection. Existing versatile watermarking syst…

cs.CV2025

CLIP-FTI: Fine-Grained Face Template Inversion via CLIP-Driven Attribute Conditioning

Longchen Dai, Zixuan Shen, Zhiheng Zhou +2

Face recognition systems store face templates for efficient matching. Once leaked, these templates pose a threat: inverting them can yield photorealistic surrogates that compromise…

cs.CV2025

Fine-Grained DINO Tuning with Dual Supervision for Face Forgery Detection

Tianxiang Zhang, Peipeng Yu, Zhihua Xia +3

The proliferation of sophisticated deepfakes poses significant threats to information integrity. While DINOv2 shows promise for detection, existing fine-tuning approaches treat it…