Text-To-Image Generation in Any Style
StyleDrop is a text-to-image generation method that can produce images in any style specified by a single reference image. It uses a vision transformer model called Muse to learn the style from natural language descriptions and fine-tune a small number of parameters. StyleDrop can capture the nuances and details of the desired style, such as color schemes, shading, design patterns, and local and global effects. StyleDrop can also collaborate with another method called Dreambooth to generate images of new objects in custom styles.
✅ Enables the generation of images that faithfully follow a specific style, powered by Muse, a text-to-image generative vision transformer
✅ Captures nuances and details of a user-provided style, such as color schemes, shading, design patterns, and local and global effects
✅ Learns a new style by fine-tuning very few trainable parameters (less than 1% of total model parameters), and improves the quality via iterative training with either human or automated feedback
✅ Delivers impressive results even when the user supplies only a single image specifying the desired style
✅ Outperforms other methods for style-tuning text-to-image models, such as DreamBooth, LoRA, Textual Inversion on Imagen, or Stable Diffusion
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