219 citations · 227 across the 7 of their papers we have counts for
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cs.CV2024
E3: Ensemble of Expert Embedders for Adapting Synthetic Image Detectors to New Generators Using Limited Data
Aref Azizpour, Tai D. Nguyen, Manil Shrestha +3
As generative AI progresses rapidly, new synthetic image generators continue to emerge at a swift pace. Traditional detection methods face two main challenges in adapting to these…
cs.CV2023★ 1 cited
Semantic Adversarial Attacks via Diffusion Models
Chenan Wang, Jinhao Duan, Chaowei Xiao +3
Traditional adversarial attacks concentrate on manipulating clean examples in the pixel space by adding adversarial perturbations. By contrast, semantic adversarial attacks focus o…
cs.CV2023
DiffuGen: Adaptable Approach for Generating Labeled Image Datasets using Stable Diffusion Models
Michael Shenoda, Edward Kim
Generating high-quality labeled image datasets is crucial for training accurate and robust machine learning models in the field of computer vision. However, the process of manually…