CGNet (TIP'2020)
@article{wu2020cgnet,
title={Cgnet: A light-weight context guided network for semantic segmentation},
author={Wu, Tianyi and Tang, Sheng and Zhang, Rui and Cao, Juan and Zhang, Yongdong},
journal={IEEE Transactions on Image Processing},
volume={30},
pages={1169--1179},
year={2020},
publisher={IEEE}
}
Segmentor | Pretrain | Backbone | Crop Size | Schedule | Train/Eval Set | mIoU | Download |
---|---|---|---|---|---|---|---|
FCN | - | M3N21 | 512x1024 | LR/POLICY/BS/EPOCH: 0.001/poly/16/340 | train/val | 68.53% | cfg | model | log |
You can also download the model weights from following sources:
- BaiduNetdisk: https://pan.baidu.com/s/1gD-NJJWOtaHCtB0qHE79rA with access code s757