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Found 5 papers, 1 papers with code
Organic or Diffused: Can We Distinguish Human Art from AI-generated Images?
We curate real human art across 7 styles, generate matching images from 5 generative models, and apply 8 detectors (5 automated detectors and 3 different human groups including 180 crowdworkers, 4000+ professional artists, and 13 expert artists experienced at detecting AI).
Prompt-Specific Poisoning Attacks on Text-to-Image Generative Models
In this paper, we show that poisoning attacks can be successful on generative models.
Natural Backdoor Datasets
Research on physical backdoors is limited by access to large datasets containing real images of physical objects co-located with targets of classification.
Assessing Privacy Risks from Feature Vector Reconstruction Attacks
In deep neural networks for facial recognition, feature vectors are numerical representations that capture the unique features of a given face.
Backdoor Attacks Against Deep Learning Systems in the Physical World
A critical question remains unanswered: can backdoor attacks succeed using physical objects as triggers, thus making them a credible threat against deep learning systems in the real world?
