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

Joost van de Weijer

Fahad Shahbaz Khan

Jian Yang

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

9 / 9 papers shown

Title
Safer Prompts: Reducing IP Risk in Visual Generative AI Lena Reissinger Yuanyuan Li Anna-Carolina Haensch Neeraj Sarna 66 0 0 06 May 2025
TRCE: Towards Reliable Malicious Concept Erasure in Text-to-Image Diffusion Models Ruidong Chen Honglin Guo Lanjun Wang Chenyu Zhang Weizhi Nie An-an Liu DiffM 111 2 0 10 Mar 2025
A Comprehensive Survey on Concept Erasure in Text-to-Image Diffusion Models Changhoon Kim Yanjun Qi DiffM 127 4 0 17 Feb 2025
SAeUron: Interpretable Concept Unlearning in Diffusion Models with Sparse Autoencoders Bartosz Cywiński Kamil Deja DiffM 135 9 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 118 4 0 28 Jan 2025
Attentive Eraser: Unleashing Diffusion Model's Object Removal Potential via Self-Attention Redirection Guidance Wenhao Sun Benlei Cui Xue-Mei Dong Jingqun Tang DiffM 235 14 0 17 Dec 2024
Dynamic Negative Guidance of Diffusion Models Felix Koulischer Johannes Deleu G. Raya T. Demeester L. Ambrogioni DiffM 151 10 0 18 Oct 2024
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 118 12 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 136 12 0 25 Mar 2024