| license: apache-2.0 | |
| tags: | |
| - vision | |
| # ViTMatte model | |
| ViTMatte model trained on Composition-1k. It was introduced in the paper [ViTMatte: Boosting Image Matting with Pretrained Plain Vision Transformers](https://arxiv.org/abs/2305.15272) by Yao et al. and first released in [this repository](https://github.com/hustvl/ViTMatte). | |
| Disclaimer: The team releasing ViTMatte did not write a model card for this model so this model card has been written by the Hugging Face team. | |
| ## Model description | |
| ViTMatte is a simple approach to image matting, the task of accurately estimating the foreground object in an image. The model consists of a Vision Transformer (ViT) with a lightweight head on top. | |
| <img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/model_doc/vitmatte_architecture.png" | |
| alt="drawing" width="600"/> | |
| <small> ViTMatte high-level overview. Taken from the <a href="https://arxiv.org/abs/2305.15272">original paper.</a> </small> | |
| ## Intended uses & limitations | |
| You can use the raw model for image matting. See the [model hub](https://huggingface.co/models?search=vitmatte) to look for other | |
| fine-tuned versions that may interest you. | |
| ### How to use | |
| We refer to the [docs](https://huggingface.co/docs/transformers/main/en/model_doc/vitmatte#transformers.VitMatteForImageMatting.forward.example). | |
| ### BibTeX entry and citation info | |
| ```bibtex | |
| @misc{yao2023vitmatte, | |
| title={ViTMatte: Boosting Image Matting with Pretrained Plain Vision Transformers}, | |
| author={Jingfeng Yao and Xinggang Wang and Shusheng Yang and Baoyuan Wang}, | |
| year={2023}, | |
| eprint={2305.15272}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cs.CV} | |
| } | |
| ``` |