vitmatte-small-composition-1k EU AI Act Compliance Profile

ViTMatte model

ViTMatte model trained on Composition-1k. It was introduced in the paper ViTMatte: Boosting Image Matting with Pretrained Plain Vision Transformers by Yao et al. and first released in this repository.

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 to look for other fine-tuned versions that may interest you.

How to use

We refer to the docs.

BibTeX entry and citation info

@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}
}

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