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20212026
most citedLearning to Discover Forgery Cues for Face Forgery Detection

37 citations · 39 across the 18 of their papers we have counts for

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6 papers · 1 filter

cs.CV2024

Multimodal Music Generation with Explicit Bridges and Retrieval Augmentation

Baisen Wang, Le Zhuo, Zhaokai Wang +7

Multimodal music generation aims to produce music from diverse input modalities, including text, videos, and images. Existing methods use a common embedding space for multimodal fu…

cs.CV2024

FreeEdit: Mask-free Reference-based Image Editing with Multi-modal Instruction

Runze He, Kai Ma, Linjiang Huang +6

Introducing user-specified visual concepts in image editing is highly practical as these concepts convey the user's intent more precisely than text-based descriptions. We propose F…

cs.CV2024★ 37 cited

Learning to Discover Forgery Cues for Face Forgery Detection

Jiahe Tian, Peng Chen, Cai Yu +4

Locating manipulation maps, i.e., pixel-level annotation of forgery cues, is crucial for providing interpretable detection results in face forgery detection. Related learning objec…

cs.CV2024

Unveiling Structural Memorization: Structural Membership Inference Attack for Text-to-Image Diffusion Models

Qiao Li, Xiaomeng Fu, Xi Wang +4

With the rapid advancements of large-scale text-to-image diffusion models, various practical applications have emerged, bringing significant convenience to society. However, model…

cs.CV2024

Explicit Correlation Learning for Generalizable Cross-Modal Deepfake Detection

Cai Yu, Shan Jia, Xiaomeng Fu +6

With the rising prevalence of deepfakes, there is a growing interest in developing generalizable detection methods for various types of deepfakes. While effective in their specific…

cs.CV2024

Model Will Tell: Training Membership Inference for Diffusion Models

Xiaomeng Fu, Xi Wang, Qiao Li +3

Diffusion models pose risks of privacy breaches and copyright disputes, primarily stemming from the potential utilization of unauthorized data during the training phase. The Traini…