A fully end-to-end instance segmentation method based on Transformers.
Backbone | Lr schd | Dataset | Test scale | mAP | AP50 | AP75 | APS | APM | APL | mAPbox | Config | Download |
---|---|---|---|---|---|---|---|---|---|---|---|---|
R-50 | 50e | COCO | (1333, 800) | 42.2 | 64.6 | 45.3 | 23.1 | 45.3 | 61.8 | 48.9 | config | Google Drive | BaiduYun |
R-101 | 50e | COCO | (1333, 800) | 42.9 | 65.7 | 46.0 | 23.1 | 46.4 | 63.3 | 49.5 | config | Google Drive | BaiduYun |
- AP without superscript denotes mask AP. mAPbox denotes bbox AP.
@inproceedings{yu2022soit,
title={SOIT: Segmenting Objects with Instance-Aware Transformers},
author={Yu, Xiaodong and Shi, Dahu and Wei, Xing and Ren, Ye and Ye, Tingqun and Tan, Wenming},
booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
year={2022}
}