Barret Zoph, Golnaz Ghiasi, Tsung-Yi Lin, Yin Cui, Hanxiao Liu, Ekin D. Cubuk, Quoc V. Le [arXiv]
We release the checkpoints of teacher model and student model in rethinking pre-training and self-training.
Object detection on COCO (results with SoftNMS):
model | #FLOPs | #Params | AP (val) | AP (test_dev) | download |
---|---|---|---|---|---|
SpineNet-143 | 524B | 67M | 50.9 | 51.0 | ckpt | config |
SpineNet-143 w/self-training | 524B | 67M | 52.6 | 52.8 | ckpt | config |
SpineNet-190 | 1885B | 164M | 52.6 | 52.8 | ckpt | config |
SpineNet-190 w/self-training | 1885B | 164M | 54.2 | 54.3 | ckpt | config |
Semantic segmentation on PASCAL VOC 2012:
model | #FLOPs | #Params | mIOU (val) | mIOU (test) | download |
---|---|---|---|---|---|
EfficientNet-B7-NASFPN | 60B | 71M | 85.2 | - | ckpt | config |
EfficientNet-B7-NASFPN w/ self-training | 60B | 71M | 86.7 | - | ckpt | config |
EfficientNet-L2-NASFPN | 229B | 485M | 88.7 | - | ckpt | config |
EfficientNet-L2-NASFPN w/ self-training | 229B | 485M | 90.0 | 90.5 | ckpt | config |
The training expects the data in TFExample format stored in TFRecord. Tools and scripts are provided to download and convert datasets.
Dataset | Tool |
---|---|
ImageNet | instructions |
COCO | instructions |
PASCAL | instructions |
@article{zoph20selftraining,
title={Rethinking pre-training and self-training},
author={Barret Zoph and Golnaz Ghiasi and Tsung-Yi Lin and Yin Cui and Hanxiao Liu and Ekin D. Cubuk and Quoc V. Le},
journal={CoRR},
volume={abs/2006.06882},
year={2020}
}