metadata

language:
  - en
tags:
  - background-removal
license: apache-2.0
library: pytorch
model-index:
  - name: IS-Net_DIS-general-use
    results:
      - task:
          name: Image Segmentation
          type: image-segmentation
        metrics:
          - name: Human Correction Efforts
            type: human_correction_efforts
            value: 1016

IS-Net_DIS-general-use

Model Authors: Xuebin Qin, Hang Dai, Xiaobin Hu, Deng-Ping Fan*, Ling Shao, Luc Van Gool
Paper: Highly Accurate Dichotomous Image Segmentation (ECCV 2022 - https://arxiv.org/pdf/2203.03041.pdf
Code Repo: https://github.com/xuebinqin/DIS
Project Homepage: https://xuebinqin.github.io/dis/index.html

Note that this is an optimized version of the IS-NET model.

From the paper abstract:

[...] we introduce a simple intermediate supervision baseline (IS- Net) using both feature-level and mask-level guidance for DIS model training. Without tricks, IS-Net outperforms var- ious cutting-edge baselines on the proposed DIS5K, mak- ing it a general self-learned supervision network that can help facilitate future research in DIS.

Citation

@InProceedings{qin2022,
      author={Xuebin Qin and Hang Dai and Xiaobin Hu and Deng-Ping Fan and Ling Shao and Luc Van Gool},
      title={Highly Accurate Dichotomous Image Segmentation},
      booktitle={ECCV},
      year={2022}
}