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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…

cs.CV2023

OSM-Net: One-to-Many One-shot Talking Head Generation with Spontaneous Head Motions

Jin Liu, Xi Wang, Xiaomeng Fu +4

One-shot talking head generation has no explicit head movement reference, thus it is difficult to generate talking heads with head motions. Some existing works only edit the mouth…

cs.CV2023

MFR-Net: Multi-faceted Responsive Listening Head Generation via Denoising Diffusion Model

Jin Liu, Xi Wang, Xiaomeng Fu +4

Face-to-face communication is a common scenario including roles of speakers and listeners. Most existing research methods focus on producing speaker videos, while the generation of…

cs.CV2023

FONT: Flow-guided One-shot Talking Head Generation with Natural Head Motions

Jin Liu, Xi Wang, Xiaomeng Fu +4

One-shot talking head generation has received growing attention in recent years, with various creative and practical applications. An ideal natural and vivid generated talking head…