50 citations · 112 across the 27 of their papers we have counts for
27 papers
Concept Corrector: Erase concepts on the fly for text-to-image diffusion models
Zheling Meng, Bo Peng, Xiaochuan Jin +4
Text-to-image diffusion models have demonstrated the underlying risk of generating various unwanted content, such as sexual elements. To address this issue, the task of concept era…
S^3D-NeRF: Single-Shot Speech-Driven Neural Radiance Field for High Fidelity Talking Head Synthesis
Dongze Li, Kang Zhao, Wei Wang +4
Talking head synthesis is a practical technique with wide applications. Current Neural Radiance Field (NeRF) based approaches have shown their superiority on driving one-shot talki…
Probing Unlearned Diffusion Models: A Transferable Adversarial Attack Perspective
Xiaoxuan Han, Songlin Yang, Wei Wang +2
Advanced text-to-image diffusion models raise safety concerns regarding identity privacy violation, copyright infringement, and Not Safe For Work content generation. Towards this,…
Counterfactual Explanations for Face Forgery Detection via Adversarial Removal of Artifacts
Yang Li, Songlin Yang, Wei Wang +3
Highly realistic AI generated face forgeries known as deepfakes have raised serious social concerns. Although DNN-based face forgery detection models have achieved good performance…
Beyond Inserting: Learning Identity Embedding for Semantic-Fidelity Personalized Diffusion Generation
Yang Li, Songlin Yang, Wei Wang +1
Advanced diffusion-based Text-to-Image (T2I) models, such as the Stable Diffusion Model, have made significant progress in generating diverse and high-quality images using text pro…
Is It Possible to Backdoor Face Forgery Detection with Natural Triggers?
Xiaoxuan Han, Songlin Yang, Wei Wang +2
Deep neural networks have significantly improved the performance of face forgery detection models in discriminating Artificial Intelligent Generated Content (AIGC). However, their…