PointRend (CVPR'2020)
@inproceedings{kirillov2020pointrend,
title={Pointrend: Image segmentation as rendering},
author={Kirillov, Alexander and Wu, Yuxin and He, Kaiming and Girshick, Ross},
booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
pages={9799--9808},
year={2020}
}
Backbone | Pretrain | Crop Size | Schedule | Train/Eval Set | mIoU | Download |
---|---|---|---|---|---|---|
R-50-D32 | ImageNet-1k-224x224 | 512x512 | LR/POLICY/BS/EPOCH: 0.01/poly/16/60 | trainaug/val | 69.84% | cfg | model | log |
R-101-D32 | ImageNet-1k-224x224 | 512x512 | LR/POLICY/BS/EPOCH: 0.01/poly/16/60 | trainaug/val | 72.31% | cfg | model | log |
Backbone | Pretrain | Crop Size | Schedule | Train/Eval Set | mIoU | Download |
---|---|---|---|---|---|---|
R-50-D32 | ImageNet-1k-224x224 | 512x512 | LR/POLICY/BS/EPOCH: 0.01/poly/16/130 | train/val | 37.80% | cfg | model | log |
R-101-D32 | ImageNet-1k-224x224 | 512x512 | LR/POLICY/BS/EPOCH: 0.01/poly/16/130 | train/val | 40.26% | cfg | model | log |
Backbone | Pretrain | Crop Size | Schedule | Train/Eval Set | mIoU | Download |
---|---|---|---|---|---|---|
R-50-D32 | ImageNet-1k-224x224 | 512x1024 | LR/POLICY/BS/EPOCH: 0.01/poly/8/220 | train/val | 76.89% | cfg | model | log |
R-101-D32 | ImageNet-1k-224x224 | 512x1024 | LR/POLICY/BS/EPOCH: 0.01/poly/8/220 | train/val | 78.80% | 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