Papers by Zhaobin Chu
EditID: Training-Free Editable ID Customization for Text-to-Image Generation (2025.findings-emnlp)
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| Challenge: | Existing text-to-image models for customized IDs focus on ID consistency while neglecting editability. |
| Approach: | They propose a training-free approach to editable customized IDs based on the DiT architecture . EditID deconstructs existing text-to-image models into image generation branch and character feature branch . |
| Outcome: | The proposed solution achieves high-quality images with editable IDs while maintaining ID consistency. |