Subject-Driven and Personalized Image Generation
Adapting a pretrained text-to-image generator to reproduce a specific subject or object supplied as reference images, preserving its identity (appearance, distinctive details) while placing it in new contexts, poses, and styles. Covers the identity-preservation challenge and approaches such as fine-tuning on a few reference images (DreamBooth), learned text embeddings (Textual Inversion), and image-prompt adapters.
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Adapting a pretrained text-to-image generator to reproduce a specific subject or object supplied as reference images, preserving its identity (appearance, distinctive details) while placing it in new contexts, poses, and styles. Covers the identity-preservation challenge and approaches such as fine-tuning on a few reference images (DreamBooth), learned text embeddings (Textual Inversion), and image-prompt adapters.
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