TransMatting
TransMatting (ECCV2022)
Install / Use
/learn @AceCHQ/TransMattingREADME
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 | Model | SAD | MSE | Grad | Conn | Results Download | | ---------- | ----- | --- | ---- | ----- | ----------- | | TransMattingV1 | 24.96 | 4.58 | 9.72 | 20.16 |GoogleDrive|
Transparent-460 Dataset
The Transparent-460 dataset is now open to the public. To support the community, we have simplified the access process for researchers. Please follow the guidelines below based on your intended use:
🎓 For Academic Research (Direct Download)
If you use this dataset for non-commercial research, you can download it directly. By downloading, you agree to the Terms & Conditions and MUST cite our paper in your work.
- Download Link: Transparent-460 (Google Drive)
- Requirement: Please include the Citation provided below in any publication or project using this data.
💼 For Commercial Use (Email Required)
If you intend to use this dataset for any commercial activity, you MUST contact the authors to discuss licensing and permission.
- Contact: Huanqia Cai (caihuanqia19@mails.ucas.ac.cn)
- Please use a valid corporate/institutional email and specify your intended use case.
Terms & Conditions
The Transparent-460 database is available for non-commercial research purposes only.
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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.
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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.
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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.
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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},
}
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