文章总览 - 12
Towards Universal Fake Image Detectors That Generalize Across Generative Models
Towards Universal Fake Image Detectors That Generalize Across Generative Models

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Forgery-aware Adaptive Transformer for Generalizable Synthetic Image Detection
Forgery-aware Adaptive Transformer for Generalizable Synthetic Image Detection

发表于CVPR2024,。

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MarkDown(四)
MarkDown(四)

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Incomplete Multi-View Multi-Label Learning via Label-Guided Masked View- and Category-Aware Transformers
Incomplete Multi-View Multi-Label Learning via Label-Guided Masked View- and Category-Aware Transformers

4
Pixel-Level Anomaly Detection via Uncertainty-aware Prototypical Transformer
Pixel-Level Anomaly Detection via Uncertainty-aware Prototypical Transformer

发表于ACM MM 2022,基于不确定性感知原型transformer,该模型同时考虑异常区域的多样性和不确定性,从而实现精准的像素级视觉异常检测。

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ALDEN:Dual-Level Disentanglement with Meta-learning for Generalizable Audio Deepfake Detection
ALDEN:Dual-Level Disentanglement with Meta-learning for Generalizable Audio Deepfake Detection

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Unsupervised_Domain_Adaptation_for_Face_Anti-Spoofing
Unsupervised_Domain_Adaptation_for_Face_Anti-Spoofing

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Standing on the Shoulders of Giants:Reprogramming Visual-Language Model for General Deepfake Detection
Standing on the Shoulders of Giants:Reprogramming Visual-Language Model for General Deepfake Detection

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Guard Me If You Know Me:Protecting Specific Face-Identity from Deepfakes
Guard Me If You Know Me:Protecting Specific Face-Identity from Deepfakes

aixiv文章,基于大语言模型完成人脸篡改的检测任务,其核心的创新点是利用已知面部特征实现个性化、精准且可解释的检测框架VIPGuard。评价:其提出来一种新的MLLM的训练模式,第一阶段让MLLM正确描述人脸,第二阶段让MLLM正确区分人脸,第三阶段让MLLM正确认识给定的身份信息。 - 人脸篡改检测 - MLLM

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Generalizable Synthetic Image Detection via Language-guided Contrastive Learning
Generalizable Synthetic Image Detection via Language-guided Contrastive Learning

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