Update README.md

README.md

@@ -1,3 +1,45 @@
 ---
+language: 
+  - en
+tags:
+- background-removal
 license: apache-2.0
+library: pytorch
+model-index:
+- name: IS-Net_DIS
+  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.
+
+![](https://raw.githubusercontent.com/xuebinqin/DIS/main/figures/is-net.png)
+
+# 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}
+}
+```