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- license: apache-2.0
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+ ---
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+ license: cc-by-nc-2.0
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+ ---
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+ # MaTe3D Pretrained Models
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+ > **[ArXiv] MaTe3D: Mask-guided Text-based 3D-aware Portrait Editing**
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+ >
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+ > [Kangneng Zhou](https://montaellis.github.io/), [Daiheng Gao](https://tomguluson92.github.io/), [Xuan Wang](https://xuanwangvc.github.io/), [Jie Zhang](https://scholar.google.com/citations?user=gBkYZeMAAAAJ), [Peng Zhang](https://scholar.google.com/citations?user=QTgxKmkAAAAJ&hl=zh-CN), [Xusen Sun](https://dblp.org/pid/308/0824.html), [Longhao Zhang](https://scholar.google.com/citations?user=qkJD6c0AAAAJ), [Shiqi Yang](https://www.shiqiyang.xyz/), [Bang Zhang](https://dblp.org/pid/11/4046.html), [Liefeng Bo](https://scholar.google.com/citations?user=FJwtMf0AAAAJ&hl=zh-CN), [Yaxing Wang](https://scholar.google.es/citations?user=6CsB8k0AAAAJ), [Yaxing Wang](https://scholar.google.es/citations?user=6CsB8k0AAAAJ), [Ming-Ming Cheng](https://mmcheng.net/cmm)
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+ To expand the scope beyond human face and explore the model generalization and expansion, we design the CatMask-HQ dataset with the following representative features:
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+ **Specialization**: CatMask-HQ is specifically designed for cat faces, including precise annotations for six facial parts (background, skin, ears, eyes, nose, and mouth) relevant to feline features.
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+ **High-Quality Annotations**: The dataset benefits from manual annotations by 50 annotators and undergoes 3 accuracy checks, ensuring high-quality labels and reducing individual differences.
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+ **Substantial Dataset Scale**: With approximately 5,060 high-quality real cat face images and corresponding annotations, CatMask-HQ provides ample training database for deep learning models.
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+ <a href='https://montaellis.github.io/mate-3d/'><img src='https://img.shields.io/badge/Project-Page-Green'></a>
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+ <a href='https://arxiv.org/abs/2312.06947'><img src='https://img.shields.io/badge/Paper-Arxiv-red'></a>
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+ <a href='https://youtu.be/zMNYan1mIds'><img src='https://badges.aleen42.com/src/youtube.svg'></a>
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+ <a href='https://huggingface.co/datasets/Ellis/CatMaskHQ'><img src='https://img.shields.io/static/v1?label=Dataset&message=HuggingFace&color=yellow'></a>
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+ <a href='https://huggingface.co/Ellis/MaTe3D'><img src='https://img.shields.io/static/v1?label=Models&message=HuggingFace&color=yellow'></a>
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+ ### Available sources
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+ * FFHQ-Mask:
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+ * CatMask-HQ:
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+ ### Contact
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+ [elliszkn@163.com](mailto:elliszkn@163.com)
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+ ### Citation
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+ If you find this project helpful to your research, please consider citing:
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+ ```
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+ @article{zhou2023mate3d,
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+ title = {MaTe3D: Mask-guided Text-based 3D-aware Portrait Editing},
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+ author = {Kangneng Zhou, Daiheng Gao, Xuan Wang, Jie Zhang, Peng Zhang, Xusen Sun, Longhao Zhang, Shiqi Yang, Bang Zhang, Liefeng Bo, Yaxing Wang, Ming-Ming Cheng},
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+ journal = {arXiv preprint arXiv:2312.06947},
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+ website = {https://montaellis.github.io/mate-3d/},
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+ year = {2023}}
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+ ```
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