Get What You Want, Not What You Don't: Image Content Suppression for
Text-to-Image Diffusion Models

Get What You Want, Not What You Don't: Image Content Suppression for Text-to-Image Diffusion Models

8 February 2024

Fahad Shahbaz Khan

Jian Yang

Papers citing "Get What You Want, Not What You Don't: Image Content Suppression for Text-to-Image Diffusion Models"

6 / 6 papers shown

Title
A Comprehensive Survey on Concept Erasure in Text-to-Image Diffusion Models Changhoon Kim Yanjun Qi DiffM 33 1 0 17 Feb 2025
SAeUron: Interpretable Concept Unlearning in Diffusion Models with Sparse Autoencoders Bartosz Cywiñski Kamil Deja DiffM 52 6 0 29 Jan 2025
CE-SDWV: Effective and Efficient Concept Erasure for Text-to-Image Diffusion Models via a Semantic-Driven Word Vocabulary Jiahang Tu Qian Feng Chufan Chen Jiahua Dong Hanbin Zhao Chao Zhang Hui Qian 54 2 0 28 Jan 2025
Dynamic Negative Guidance of Diffusion Models Felix Koulischer Johannes Deleu G. Raya T. Demeester L. Ambrogioni DiffM 39 2 0 03 Jan 2025
Fantastic Copyrighted Beasts and How (Not) to Generate Them Luxi He Yangsibo Huang Weijia Shi Tinghao Xie Haotian Liu Yue Wang Luke Zettlemoyer Chiyuan Zhang Danqi Chen Peter Henderson 37 9 0 20 Jun 2024
Continuous, Subject-Specific Attribute Control in T2I Models by Identifying Semantic Directions S. A. Baumann Felix Krause Michael Neumayr Nick Stracke Vincent Tao Hu Bjorn Ommer Björn Ommer DiffM LM&Ro 44 11 0 25 Mar 2024