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Ablating Concepts in Text-to-Image Diffusion Models

Large-scale text-to-image diffusion models can gener-ate high-fidelity images with powerful compositional ability. However, these models are typically trained on an enormous amount of Internet data, often containing copyrighted material, licensed images, and personal photos.

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Cite this as

Nupur Kumari, Bingliang Zhang, Sheng-Yu Wang, Eli Shechtman, Richard Zhang, Jun-Yan Zhu (2024). Dataset: Ablating Concepts in Text-to-Image Diffusion Models. https://doi.org/10.57702/zh0aiuag

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Additional Info

Field	Value
Created	December 2, 2024
Last update	December 2, 2024
Defined In	https://doi.org/10.48550/arXiv.2310.16825
Citation	https://doi.org/10.48550/arXiv.2303.13516
Author	Nupur Kumari
More Authors	Bingliang Zhang Sheng-Yu Wang Eli Shechtman Richard Zhang Jun-Yan Zhu
Homepage	https://www.cs.cmu.edu/~concept-ablation/