NeuroPrompts: An Adaptive Framework to Optimize Prompts for Text-to-Image Generation (2024.eacl-demo)
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| Challenge: | Recent advances in text-to-image diffusion models have made it difficult to obtain high-quality images. |
| Approach: | They propose an adaptive framework that automatically enhances a user's prompt to improve the quality of generation models. |
| Outcome: | The proposed framework generates prompts similar to those produced by human prompt engineers and provides user control over stylistic features via constraint set specification. |
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Yilun Liu, Minggui He, Feiyu Yao, Yuhe Ji, Shimin Tao, Jingzhou Du, Justin Li, Jian Gao, Zhang Li, Hao Yang, Boxing Chen, Osamu Yoshie
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