6 papers
AttriCtrl: Fine-Grained Control of Aesthetic Attribute Intensity in Diffusion Models
Die Chen, Zhongjie Duan, Zhiwen Li +4
Diffusion models have recently become the dominant paradigm for image generation, yet existing systems struggle to interpret and follow numeric instructions for adjusting semantic…
Comprehensive Evaluation and Analysis for NSFW Concept Erasure in Text-to-Image Diffusion Models
Die Chen, Zhiwen Li, Cen Chen +5
Text-to-image diffusion models have gained widespread application across various domains, demonstrating remarkable creative potential. However, the strong generalization capabiliti…
AutoLoRA: Automatic LoRA Retrieval and Fine-Grained Gated Fusion for Text-to-Image Generation
Zhiwen Li, Zhongjie Duan, Die Chen +4
Despite recent advances in photorealistic image generation through large-scale models like FLUX and Stable Diffusion v3, the practical deployment of these architectures remains con…
Responsible Diffusion Models via Constraining Text Embeddings within Safe Regions
Zhiwen Li, Die Chen, Mingyuan Fan +4
The remarkable ability of diffusion models to generate high-fidelity images has led to their widespread adoption. However, concerns have also arisen regarding their potential to pr…
Comprehensive Assessment and Analysis for NSFW Content Erasure in Text-to-Image Diffusion Models
Die Chen, Zhiwen Li, Cen Chen +2
Text-to-image (T2I) diffusion models have gained widespread application across various domains, demonstrating remarkable creative potential. However, the strong generalization capa…
Growth Inhibitors for Suppressing Inappropriate Image Concepts in Diffusion Models
Die Chen, Zhiwen Li, Mingyuan Fan +4
Despite their remarkable image generation capabilities, text-to-image diffusion models inadvertently learn inappropriate concepts from vast and unfiltered training data, which lead…