Diffusion Self-Distillation for Zero-Shot Customized Image Generation
Shengqu Cai, Eric Ryan Chan, Yunzhi Zhang, Leonidas J. Guibas, Jiajun Wu, Gordon Wetzstein
2025年份
22顶会引用
摘要
Figure 1 . Given an input image, Diffusion Self-Distillation is a novel diffusion-based approach that generates diverse images that maintain the input's identity across various contexts. Unlike prior approaches that require fine-tuning or are limited to specific domains, Diffusion Self-Distillation offers instant customization without any additional inference-stage training, enabling precise control and editability in text-to-image diffusion models. This ability makes Diffusion Self-Distillation a valuable tool for general AI content creation.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper22
- Mixture of Contexts for Long Video GenerationShengqu Cai, Ceyuan Yang, Lvmin Zhang, Yuwei Guo 等ICLR 2026 · 被引用 92 次
- CreatiDesign: A Unified Multi-Conditional Diffusion Transformer for Creative Graphic DesignHui Zhang, Dexiang Hong, Maoke Yang, Yutao Cheng 等ICLR 2026 · 被引用 40 次
- OminiControl: Minimal and Universal Control for Diffusion TransformerZhenxiong Tan, Songhua Liu, Xingyi Yang, Qiaochu Xue 等ICCV 2025 · 被引用 34 次
- Mod-Adapter: Tuning-Free and Versatile Multi-concept Personalization via Modulation AdapterWeizhi Zhong, Huan Yang, Zheng Liu, Huiguo He 等ICLR 2026 · 被引用 17 次
- Learning an Image Editing Model without Image Editing PairsNupur Kumari, Sheng-Yu Wang, Nanxuan Zhao, Yotam Nitzan 等ICLR 2026 · 被引用 14 次
它引用的顶会 Paper29
- Learning Transferable Visual Models From Natural Language SupervisionAlec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh 等ICML 2021 · 被引用 47,906 次
- Chain-of-Thought Prompting Elicits Reasoning in Large Language ModelsJason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma 等NeurIPS 2022 · 被引用 22,562 次
- LoRA: Low-Rank Adaptation of Large Language ModelsEdward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu 等ICLR 2022 · 被引用 18,833 次
- High-Resolution Image Synthesis with Latent Diffusion ModelsRobin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser 等CVPR 2022 · 被引用 13,123 次
- Photorealistic Text-to-Image Diffusion Models with Deep Language UnderstandingChitwan Saharia, William Chan, Saurabh Saxena, Lala Li 等NeurIPS 2022 · 被引用 8,965 次
相关 Paper
- Not All Steps are Created Equal: Selective Diffusion Distillation for Image ManipulationLuozhou Wang, Shuai Yang, Shu Liu, Ying-Cong ChenICCV 2023 · 被引用 16 次
- On Distillation of Guided Diffusion ModelsChenlin Meng, Robin Rombach, Ruiqi Gao, Diederik P. Kingma 等CVPR 2023
- SINE: SINgle Image Editing with Text-to-Image Diffusion ModelsZhixing Zhang, Ligong Han, Arnab Ghosh, Dimitris N. Metaxas 等CVPR 2023
- Diffusion Model is Effectively Its Own TeacherXinyin Ma, Runpeng Yu, Songhua Liu, Gongfan Fang 等CVPR 2025
- DKDM: Data-Free Knowledge Distillation for Diffusion Models with Any ArchitectureQianlong Xiang, Miao Zhang, Yuzhang Shang, Jianlong Wu 等CVPR 2025
