Customization Method

Customization methods for text-to-image diffusion models allow personalized image generation, but raise significant privacy concerns due to potential misuse for creating realistic fakes. Current research focuses on improving both the customization process itself, often employing techniques like LoRA for efficient adaptation, and developing robust anti-customization methods, including adversarial attacks targeting attention mechanisms and feature optimization within the diffusion process. These advancements are crucial for balancing the benefits of personalized image generation with the need to mitigate risks associated with deepfakes and unauthorized image manipulation.