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TransMatting: Enhancing Transparent Objects Matting with Transformers

Official project page of TransMatting (ECCV2022)

Updates

<h3><strong><i>🚀 News</i></strong></h3>

The extended paper TransMatting: Tri-token Equipped Transformer Model for Image Matting is published on arXiv. We further propose TransMattingV2, which extends tri-token to both convolutional networks and Transformer. Various experiments demonstrate that it could boost both Transformer and convolutional networks, indicating that the proposed tri-token has the potential to be a new paradigm for image matting.

Results

Quantitative Results on Composition-1k

Transparent-460

Our dataset Transparent-460 is now open to the public. If you want to use it for research rather than commercial activity, you can directly download it using the following link: Transparent-460

Please note that you are still required to send an email to Huanqia Cai (caihuanqia19@mails.ucas.ac.cn) to inform us of your usage. Your email MUST be sent from a valid university or research institute account and MUST include the following text:

Subject: Application to download the Transparent-460 Database          
Name: <Your first and last name>
Affiliation: <University or institute where you work>
Department: <Your department>
Position: <Your job title>
Email: <Must be the email at the above mentioned institution>

I have read and agree to the terms and conditions specified in the Transparent-460 database webpage. 
This database will only be used for research purposes. 
I will not make any part of this database available to a third party. 
I'll not sell any part of this database or make any profit from its use.

Terms & Conditions

The Transparent-460 database is available for non-commercial research purposes only.

1. All images of the Transparent-460 database are obtained from the Internet and are not the authors' property. The authors are not responsible for these images' content or meaning.

2. You agree not to reproduce, duplicate, copy, sell, trade, resell or exploit any portion of the images and any portion of derived data for any commercial purposes.

3. You agree not to further copy, publish or distribute any portion of the Transparent-460 database. Except for internal use at a single site within the same organization, it is allowed to make copies of the dataset.

4. The authors reserve the right to terminate your access to the Transparent-460 database at any time.

Citation

@inproceedings{cai2022TransMatting,
  title={TransMatting: Enhancing Transparent Objects Matting with Transformers},
  author={Cai, Huanqia and Xue, Fanglei, and Xu, Lele and Guo, Lili},
  booktitle={European Conference on Computer Vision (ECCV)},
  year={2022},
}