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+# Instance Localization for Self-supervised Detection Pretraining
+
+![image](./docs/figures/teaser.png)
+[paper]
+
+## News
+- Full codebase and models are coming soon
+
+## Main Results
+
+Here we list the results on MSCOCO with the detector of R50-C4 and R50-FPN. Without any multi-crop/auto/random augmentation, our InsLoc outperforms many previous contrastive methods. In order to clearly clarify the improvements brought by InsLoc, the comparison to the corresponding baseline (i.e., MoCo-v2) is as follows:
+
+Mask R-CNN **R50-C4 1x**: 
+| Methods | Epoch | Box AP | Mask AP | Link | 
+| :---: | :------: | :--------: | :------: | :------: | 
+| MoCo-v2 | 200 | 38.9 | 34.1 | -    |
+| MoCo-v2 | 800 | 39.3 | 34.3 | -    |
+| InsLoc  | 200 | 39.5 | 34.5 | link |
+| InsLoc  | 400 | 39.8 | 34.7 | link |
+
+Mask R-CNN **R50-C4 2x**: 
+| Methods | Epoch | Box AP | Mask AP | Link | 
+| :---: | :------: | :--------: | :------: | :------: | 
+| MoCo-v2 | 200 | 40.7 | 35.6 | -    |
+| MoCo-v2 | 800 | 41.2 | 35.8 | -    |
+| InsLoc  | 200 | 41.4 | 35.9 | link |
+| InsLoc  | 400 | 41.8 | 36.3 | link |
+
+Mask R-CNN **R50-FPN 1x**: 
+| Methods | Epoch | Box AP | Mask AP | Link | 
+| :---: | :------: | :--------: | :------: | :------: | 
+| MoCo-v2 | 200 | 39.8 | 36.1 | -    |
+| MoCo-v2 | 800 | 40.4 | 36.4 | -    |
+| InsLoc  | 200 | 41.4 | 37.1 | link |
+| InsLoc  | 400 | 42.0 | 37.6 | link |
+
+Mask R-CNN **R50-FPN 2x**: 
+| Methods | Epoch | Box AP | Mask AP | Link | 
+| :---: | :------: | :--------: | :------: | :------: | 
+| MoCo-v2 | 200 | 41.7 | 37.6 | -    |
+| MoCo-v2 | 800 | 42.5 | 38.2 | -    |
+| InsLoc  | 200 | 43.2 | 38.7 | link |
+| InsLoc  | 400 | 43.3 | 38.8 | link |
+
+More results are available in our paper.
+
+
+## Bibtex
+```
+@inproceedings{yang2021insloc,
+  title={Instance Localization for Self-supervised Detection Pretraining},
+  author={Yang, Ceyuan and Wu, Zhirong and Zhou, Bolei and Lin, Stephen},
+  booktitle={arXiv preprint},
+  year={2021},
+}
+```