37 citations · 38 across the 10 of their papers we have counts for
10 papers
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…
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…
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…
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…
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…
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…
A Unified Framework for Modality-Agnostic Deepfakes Detection
Cai Yu, Peng Chen, Jiahe Tian +7
As AI-generated content (AIGC) thrives, deepfakes have expanded from single-modality falsification to cross-modal fake content creation, where either audio or visual components can…
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…
OPT: One-shot Pose-Controllable Talking Head Generation
Jin Liu, Xi Wang, Xiaomeng Fu +4
One-shot talking head generation produces lip-sync talking heads based on arbitrary audio and one source face. To guarantee the naturalness and realness, recent methods propose to…
Rethinking Persistent Homology for Visual Recognition
Ekaterina Khramtsova, Guido Zuccon, Xi Wang +1
Persistent topological properties of an image serve as an additional descriptor providing an insight that might not be discovered by traditional neural networks. The existing resea…