An Improved Method for Personalizing Diffusion Models
<|reference_start|>An Improved Method for Personalizing Diffusion Models: Diffusion models have demonstrated impressive image generation capabilities. Personalized approaches, such as textual inversion and Dreambooth, enhance model individualization using specific images. These methods enable generating images of specific objects based on diverse textual contexts. Our proposed approach aims to retain the model's original knowledge during new information integration, resulting in superior outcomes while necessitating less training time compared to Dreambooth and textual inversion.<|reference_end|>
@article{zeng2024an,
    title={An Improved Method for Personalizing Diffusion Models},
    author={Yan Zeng and Masanori Suganuma and Takayuki Okatani},
    journal={arXiv preprint arXiv:2407.05312},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.05312},
    primaryClass={cs.CV}
}