1 citations · 1 across the 3 of their papers we have counts for
5 papers
Protecting Sensitive Data in Image Synthesis via PAC-Private Adaptation for Diffusion Models
Boming Miao, Tao Zhang, Netanel Raviv +3
Synthetic data are increasingly used as an alternative to sharing sensitive records. However, synthetic data generation does not guarantee privacy, as diffusion models trained or a…
Bridging the Gap Between Ideal and Real-world Evaluation: Benchmarking AI-Generated Image Detection in Challenging Scenarios
Chunxiao Li, Xiaoxiao Wang, Meiling Li +5
With the rapid advancement of generative models, highly realistic image synthesis has posed new challenges to digital security and media credibility. Although AI-generated image de…
An Efficient Framework for Enhancing Discriminative Models via Diffusion Techniques
Chunxiao Li, Xiaoxiao Wang, Boming Miao +3
Image classification serves as the cornerstone of computer vision, traditionally achieved through discriminative models based on deep neural networks. Recent advancements have intr…
Noise Diffusion for Enhancing Semantic Faithfulness in Text-to-Image Synthesis
Boming Miao, Chunxiao Li, Xiaoxiao Wang +4
Diffusion models have achieved impressive success in generating photorealistic images, but challenges remain in ensuring precise semantic alignment with input prompts. Optimizing t…
AdvLogo: Adversarial Patch Attack against Object Detectors based on Diffusion Models
Boming Miao, Chunxiao Li, Yao Zhu +4
With the rapid development of deep learning, object detectors have demonstrated impressive performance; however, vulnerabilities still exist in certain scenarios. Current research…