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  [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
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  [![Github](https://img.shields.io/badge/GitHub-AIDC--AI/UNIC-Adapter-blue?style=flat&logo=github)](https://github.com/AIDC-AI/UNIC-Adapter)
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- UNIC-Adapter is a unified image-instruction adapter that integrates multimodal instructions for controllable image generation. This repository contains the official implementation for the CVPR 2025 paper "UNIC-Adapter: Unified Image-instruction Adapter with Multi-modal Transformer for Image Generation".
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- In this repository, we release a model based on SD3 Medium, which supports the tasks described in our paper. In addition, we also provide two further models: one built on SD3.5 Medium, which is capable of traditional computer vision perception tasks, and another on FLUX.1-dev, which supports both instruction-based image editing and traditional computer vision perception tasks.
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  ## Generated samples
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  <img src='./examples/example_2.png' width='100%'/>
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- *(Left: condition image, Center: SD 3.5 medium with UNIC-Adapter, Right: FLUX.1-dev with UNIC-Adapter)*
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  <img src='./examples/example_3.png' width='75%'/>
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  [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
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  [![Github](https://img.shields.io/badge/GitHub-AIDC--AI/UNIC-Adapter-blue?style=flat&logo=github)](https://github.com/AIDC-AI/UNIC-Adapter)
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+ UNIC-Adapter is a unified image-instruction adapter that integrates multimodal instructions for controllable image generation. This model card hosts the official models for the CVPR 2025 paper "UNIC-Adapter: Unified Image-instruction Adapter with Multi-modal Transformer for Image Generation".
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+ On this model card, we release a model based on SD3 Medium, which supports the tasks described in our paper. In addition, we also provide two additional models: one built on SD3.5 Medium, which is capable of traditional computer vision perception tasks, and another on FLUX.1-dev, which supports both instruction-based image editing and traditional computer vision perception tasks.
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  ## Generated samples
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  <img src='./examples/example_2.png' width='100%'/>
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+ *(Left: condition image, Center: SD 3.5 Medium with UNIC-Adapter, Right: FLUX.1-dev with UNIC-Adapter)*
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  <img src='./examples/example_3.png' width='75%'/>
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