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Omni-Attribute Open-vocabulary Attribute Encoder for Visual Concept Personalization

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AK

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14,029 görüntüleme • 7 ay önce •via X (Twitter)

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Designing an Encoder for Fast Personalization of Text-to-Image Models TL;DR: use an encoder to personalize a text-to-image model to new concepts with a single image and 5-15 tuning steps abs: project page:

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Personalized 3D Generative Avatars from a Single Portrait Contributions: 1. Generate a personalized 3D avatar from a reference portrait image with controllable facial attributes. 2. Create high-quality synthetic 2D video datasets with diverse attribute editing from a reference portrait image. 3. Use latent space regularization with face morphing supervision for a continuous and smooth latent space, enhancing the generative ability for unseen or interpolated attribute appearances. 4. Employ an efficient fine-tuning technique via Low-Rank Adaptation (LoRA) [26] to integrate any new facial attribute into the avatar model.

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