Zhaobin Chu

EditID: Training-Free Editable ID Customization for Text-to-Image Generation

We propose EditID, a training-free approach based on the DiT architecture, which achieves highly editable customized IDs for text to image generation. Existing text-to-image models for customized IDs typically focus more on ID consistency while neglecting editability. It is challenging to alter faci