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  - guidance matting
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  - human matting
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  pretty_name: MaGGIe - Human Instance Image and Video Matting
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- arxiv: arxiv.org/abs/2404.16035
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  ---
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  <img src="maggie.png" alt="maggie" width="128"/>
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  **[Chuong Huynh](https://hmchuong.github.io/), [Seoung Wug Oh](https://sites.google.com/view/seoungwugoh/), [Abhinav Shrivastava](https://www.cs.umd.edu/~abhinav/), [Joon-Young Lee](https://joonyoung-cv.github.io/)**
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- Work is a part of Summer Internship 2023 at [Adobe Research](https://research.adobe.com/)
 
 
 
 
 
 
 
 
 
 
 
 
 
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  - guidance matting
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  - human matting
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  pretty_name: MaGGIe - Human Instance Image and Video Matting
 
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  ---
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  <img src="maggie.png" alt="maggie" width="128"/>
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  **[Chuong Huynh](https://hmchuong.github.io/), [Seoung Wug Oh](https://sites.google.com/view/seoungwugoh/), [Abhinav Shrivastava](https://www.cs.umd.edu/~abhinav/), [Joon-Young Lee](https://joonyoung-cv.github.io/)**
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+ Work is a part of Summer Internship 2023 at [Adobe Research](https://research.adobe.com/)
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+
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+ ## Citation
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+
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+ If you find MaGGIe useful in your research, please cite the following paper:
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+ ```latex
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+ @article{chuonghm_maggie,
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+ author = {Chuong Huynh and Seoung Wug Oh and and Abhinav Shrivastava and Joon-Young Lee},
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+ title = {MaGGIe: Masked Guided Gradual Human Instance Matting},
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+ journal = {arXiv:2404.16035},
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+ year = {2024}
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+ }
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+ ```