metadata

tags:
  - pytorch_model_hub_mixin
  - model_hub_mixin
datasets:
  - chuonghm/MaGGIe-HIM
metrics:
  - mse
  - sad
  - mad
  - conn
  - grad
  - dtssd
  - messddt
pipeline_tag: image-segmentation
license: cc-by-4.0

MaGGIe: Mask Guided Gradual Human Instance Matting

[Project Page] [Code]

Weights for Instance-awareness alpha human matting with binary mask guidance for images and video

Accepted at CVPR 2024

Chuong Huynh, Seoung Wug Oh, Abhinav Shrivastava, Joon-Young Lee

Work is a part of Summer Internship 2023 at Adobe Research

Please refer to our paper for details.

Citation

If you find MaGGIe useful in your research, please cite the following paper:

@inproceedings{huynh2024maggie,
  title={Maggie: Masked guided gradual human instance matting},
  author={Huynh, Chuong and Oh, Seoung Wug and Shrivastava, Abhinav and Lee, Joon-Young},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={3870--3879},
  year={2024}
}