MAE (CVPR'2022)
@inproceedings{he2022masked,
title={Masked autoencoders are scalable vision learners},
author={He, Kaiming and Chen, Xinlei and Xie, Saining and Li, Yanghao and Doll{\'a}r, Piotr and Girshick, Ross},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
pages={16000--16009},
year={2022}
}
Segmentor | Pretrain | Backbone | Crop Size | Schedule | Train/Eval Set | mIoU | Download |
---|---|---|---|---|---|---|---|
UperNet | ImageNet-1k-224x224 | MAE-Vit-B | 512x512 | LR/POLICY/BS/EPOCH: 1e-4/poly/16/130 | train/val | 48.20% | 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