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@@ -11,7 +11,6 @@ metrics:
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  - conn
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  - grad
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  pipeline_tag: image-segmentation
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- arxiv: 2404.16035
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  license: cc-by-4.0
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  ---
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@@ -25,4 +24,15 @@ license: cc-by-4.0
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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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  - conn
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  pipeline_tag: image-segmentation
 
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  license: cc-by-4.0
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  ---
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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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+ @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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+
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+ ```