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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
[ECCV 2024] OMG: Occlusion-friendly Personalized Multi-concept Generation In Diffusion Models
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| 2026-07-31 | 701 |
| 2026-08-04 | 701 |
| 2026-08-06 | 701 |
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<div align="center"> <h1>OMG: Occlusion-friendly Personalized Multi-concept Generation In Diffusion Models (ECCV 2024)</h1> [Zhe Kong](https://scholar.google.com/citations?user=4X3yLwsAAAAJ&hl=zh-CN) · [Yong Zhang*](https://yzhang2016.github.io/) · [Tianyu Yang](https://tianyu-yang.com/) · [Tao Wang](https://taowangzj.github.io/)· [Kaihao Zhang](https://zhangkaihao.github.io/) [Bizhu Wu](https://scholar.google.com/citations?user=u7nZ3bgAAAAJ&hl=zh-CN) · [Guanying Chen](https://guanyingc.github.io/) · [Wei Liu](https://scholar.google.com/citations?user=AjxoEpIAAAAJ&hl=en) · [Wenhan Luo*](https://whluo.github.io/) <sup>*</sup>Corresponding Authors **OMG + LORA** : <a href='https://huggingface.co/spaces/Fucius/OMG'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue'></a> **OMG + InstantID**: <a href='https://huggingface.co/spaces/Fucius/OMG-InstantID'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue'></a> <a href='https://kongzhecn.github.io/omg-project/'><img src='https://img.shields.io/badge/Project-Page-green'></a> <a href='https://arxiv.org/abs/2403.10983'><img src='https://img.shields.io/badge/Technique-Report-red'></a> [](https://github.com/kongzhecn/OMG) </div> > **TL; DR:** OMG is a framework for multi-concept image generation, supporting character and style LoRAs on [Civitai.com](https://civitai.com/). It also can be combined with [InstantID](https://github.com/InstantID/InstantID) for multiple IDs with using a single image for each ID. <p align="center"> <img src="assets/teaser.png"> </p> > **Introduction of OMG:** A tool for high-quality multi-character image generation. [](https://youtu.be/5BI_a7nTb8Q) > **Trailor Demo:** A short trailor "Home Defense" created by using OMG + SVD. [](https://www.youtube.com/embed/c-dYmPo7rVM) ## :label: Change Log - [2023/3/22] 🔥 We release the Hugging space for [OMG + InstantID](https://huggingface.co/spaces/Fucius/OMG-InstantID). Support ID personalization with a single image. - [2023/3/19] 🔥 We release the [technical report](https://arxiv.org/abs/2403.10983) and Hugging space for [OMG-LoRAs](https://huggingface.co/spaces/Fucius/OMG) - [2023/3/18] 🔥 We release the source code and gradio demo of OMG. ## 🔆 Introduction ### 1. OMG + LoRA (ID with multiple images) <p align="center"> <img src="assets/lora.png" height=390> </p> ### 2. OMG + InstantID (ID with single image) <p align="center"> <img src="assets/instantid.png" height=390> </p> ### 3. OMG + ControlNet (Layout Control ) <p align="center"> <img src="assets/controlnet.png" height=1024> </p> ### 4. OMG + style LoRAs (Style Control) <p align="center"> <img src="assets/style.png" height=390> </p> ## :wrench: Dependencies and Installation 1. The code requires `python==3.10.6`, as well as `pytorch==2.0.1` and `torchvision==0.15.2`. Please follow the instructions [here](https://pytorch.org/get-started/locally/) to install both PyTorch and TorchVision dependencies. Installing both PyTorch and TorchVision with CUDA support is strongly recommended. ```bash conda create -n OMG python=3.10.6 conda activate OMG pip install torch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2 pip install -r requirements.txt pip install git+https://github.com/facebookresearch/segment-anything.git ``` 2. For Visual comprehension, you can choose `YoloWorld + EfficientViT SAM` or `GroundingDINO + SAM` - 1) (Recommend) YoloWorld + EfficientViT SAM: ```bash pip install inference[yolo-world]==0.9.13 pip install onnxsim==0.4.35 ``` - 2) (Optional) If you can not install `inference[yolo-world]`. You can install `GroundingDINO` for visual comprehension. `GroundingDINO` requires manual installation. Run this so the environment variable will be set under c
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