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 ## BLIP-Diffusion: Pre-trained Subject Representation for Controllable Text-to-Image Generation and Editing
-[Paper](https://arxiv.org/abs/2305.14720), [Demo Site](https://dxli94.github.io/BLIP-Diffusion-website/)
+[Paper](https://arxiv.org/abs/2305.14720), [Demo Site](https://dxli94.github.io/BLIP-Diffusion-website/), [Video](https://youtu.be/Wf09s4JnDb0)
 
 This repo will host the official implementation of BLIP-Diffusion, a text-to-image diffusion model with built-in support for multimodal subject-and-text condition. BLIP-Diffusion enables zero-shot subject-driven generation, and efficient fine-tuning for customized subjects with up to 20x speedup. In addition, BLIP-Diffusion can be flexibly combiend with ControlNet and prompt-to-prompt to enable novel subject-driven generation and editing applications.