EntitySeg is an open source toolbox which towards precise and open-world image segmentation on top of detectron2. All works related to image segmentation from our group are open-sourced here.
To date, EntitySeg implements the following algorthms:
- Open-World Entity Segmentation
- High Quality Segmentation for Ultra High-resolution Images ---code to be released
- CaSP: Class-agnostic Semi-Supervised Pretraining for Detection and Segmentation ---code to be released
- Scale-aware Automatic Augmentation for Object Detection ---code to be merged
Please refer to the README.md of each project. All projects shared the similar detectron2 base code and could support each other.
@article{qi2021open,
title={Open-World Entity Segmentation},
author={Qi, Lu and Kuen, Jason and Wang, Yi and Gu, Jiuxiang and Zhao, Hengshuang and Lin, Zhe and Torr, Philip and Jia, Jiaya},
journal={arXiv preprint arXiv:2107.14228},
year={2021}
}
@inproceedings{chen2021scale,
title={Scale-aware Automatic Augmentation for Object Detection},
author={Chen, Yukang and Li, Yanwei and Kong, Tao and Qi, Lu and Chu, Ruihang and Li, Lei and Jia, Jiaya},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
pages={9563--9572},
year={2021}
}