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README.md

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+<div align="center">
+<h1>SegGPT: Segmenting Everything In Context </h1>
+
+[Xinlong Wang](https://www.xloong.wang/)<sup>1*</sup>, &nbsp; [Xiaosong Zhang](https://scholar.google.com/citations?user=98exn6wAAAAJ&hl=en)<sup>1*</sup>, &nbsp; [Yue Cao](http://yue-cao.me/)<sup>1*</sup>, &nbsp; [Wen Wang](https://scholar.google.com/citations?user=1ks0R04AAAAJ&hl)<sup>2</sup>, &nbsp;  [Chunhua Shen](https://cshen.github.io/)<sup>2</sup>, &nbsp; [Tiejun Huang](https://scholar.google.com/citations?user=knvEK4AAAAAJ&hl=en)<sup>1,3</sup>
+
+<sup>1</sup>[BAAI](https://www.baai.ac.cn/english.html), &nbsp; <sup>2</sup>[ZJU](https://www.zju.edu.cn/english/), &nbsp; <sup>3</sup>[PKU](https://english.pku.edu.cn/)
+
+Enjoy the [Demo](https://huggingface.co/spaces/BAAI/SegGPT) and [Code](https://github.com/baaivision/Painter/edit/main/SegGPT)
+
+
+<br>
+  
+<image src="seggpt_teaser.png" width="720px" /> 
+<br>
+
+</div>
+
+<br>
+
+   We present SegGPT, a generalist model for segmenting everything in context. With only one single model, SegGPT can perform arbitrary segmentation tasks in images or videos via in-context inference, such as object instance, stuff, part, contour, and text. 
+   SegGPT is evaluated on a broad range of tasks, including few-shot semantic segmentation, video object segmentation, semantic segmentation, and panoptic segmentation. 
+   Our results show strong capabilities in segmenting in-domain and out-of-domain targets, either qualitatively or quantitatively. 
+
+[[Paper]](https://arxiv.org/abs/2304.03284)
+[[Code]](https://github.com/baaivision/Painter/edit/main/SegGPT)
+[[Demo]](https://huggingface.co/spaces/BAAI/SegGPT)
+
+## **Model**
+
+A pre-trained SegGPT model is available at [🤗 HF link](https://huggingface.co/BAAI/Painter/blob/main/painter_vit_large.pth).
+
+
+
+## Citation
+
+```
+@article{SegGPT,
+  title={SegGPT: Segmenting Everything In Context},
+  author={Wang, Xinlong and Zhang, Xiaosong and Cao, Yue and Wang, Wen and Shen, Chunhua and Huang, Tiejun},
+  journal={arXiv preprint arXiv:2304.03284},
+  year={2023}
+}
+```
+
+## Contact
+
+**We are hiring** at all levels at BAAI Vision Team, including full-time researchers, engineers and interns. 
+If you are interested in working with us on **foundation model, visual perception and multimodal learning**, please contact [Xinlong Wang](https://www.xloong.wang/) (`wangxinlong@baai.ac.cn`) and [Yue Cao](http://yue-cao.me/) (`caoyue@baai.ac.cn`).
+