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.
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.
You can use the raw model for image matting. See the
model hub to look for other
fine-tuned versions that may interest you.
1@misc{yao2023vitmatte,
2 title={ViTMatte: Boosting Image Matting with Pretrained Plain Vision Transformers},
3 author={Jingfeng Yao and Xinggang Wang and Shusheng Yang and Baoyuan Wang},
4 year={2023},
5 eprint={2305.15272},
6 archivePrefix={arXiv},
7 primaryClass={cs.CV}
8}
