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MaureenZOU 2023-10-04 16:59:23 -05:00
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<img src="https://user-images.githubusercontent.com/11957155/233526415-a0a44963-19a3-4e56-965a-afaa598e6127.gif" width="400" />
</p>
## :bookmark_tabs: Catelog
- [x] SEEM Demo
- [x] Inference and Installation Code
- [x] Evaluation Code
- [x] Training Code
:fire: **Related projects:**
* [FocalNet](https://github.com/microsoft/FocalNet) and [DaViT](https://github.com/dingmyu/davit) : We used FocalNet and DaViT as the vision backbones.
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* [X-GPT](https://github.com/microsoft/X-Decoder/tree/xgpt) : Conversational Visual Agent supported by X-Decoder.
* [LLaVA](https://github.com/haotian-liu/LLaVA) : Large Language and Vision Assistant.
## :bookmark_tabs: Catelog
- [x] SEEM Demo
- [x] Inference and Installation Code
- [x] Evaluation Code
- [x] Training Code
## :bulb: Highlights
Inspired by the appealing universal interface in LLMs, we are advocating a universal, interactive multi-modal interface for any type of segmentation with **ONE SINGLE MODEL**. We emphasize **4** important features of **SEEM** below.
1. **Versatility**: work with various types of prompts, for example, clicks, boxes, polygons, scribbles, texts, and referring image;