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---
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}
}
```
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