conference paper

Intriguing Properties of Diffusion Models: An Empirical Study of the Natural Attack Capability in Text-to-Image Generative Models

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

Publication Date

January 1, 2024

Author(s)

Takami Sato, Justin Yue, Nanze Chen, Ningfei Wang, Qi Alfred Chen
Suggested Citation
Takami Sato, Justin Yue, Nanze Chen, Ningfei Wang and Qi Alfred Chen (2024) “Intriguing Properties of Diffusion Models: An Empirical Study of the Natural Attack Capability in Text-to-Image Generative Models”. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 24635–24644. Available at: https://openaccess.thecvf.com/content/CVPR2024/html/Sato_Intriguing_Properties_of_Diffusion_Models_An_Empirical_Study_of_the_CVPR_2024_paper.html (Accessed: October 23, 2024).