setr

Introduction

Official Repo

Code Snippet

SETR (CVPR'2021)

@inproceedings{zheng2021rethinking,
    title={Rethinking semantic segmentation from a sequence-to-sequence perspective with transformers},
    author={Zheng, Sixiao and Lu, Jiachen and Zhao, Hengshuang and Zhu, Xiatian and Luo, Zekun and Wang, Yabiao and Fu, Yanwei and Feng, Jianfeng and Xiang, Tao and Torr, Philip HS and others},
    booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
    pages={6881--6890},
    year={2021}
}

Results

ADE20k

Segmentor	Pretrain	Backbone	Crop Size	Schedule	Train/Eval Set	mIoU	Download
Naive	ImageNet-22k-384x384	ViT-Large	512x512	LR/POLICY/BS/EPOCH: 0.01/poly/16/130	train/val	48.43%	cfg | model | log
PUP	ImageNet-22k-384x384	ViT-Large	512x512	LR/POLICY/BS/EPOCH: 0.01/poly/16/130	train/val	48.51%	cfg | model | log
MLA	ImageNet-22k-384x384	ViT-Large	512x512	LR/POLICY/BS/EPOCH: 0.01/poly/16/130	train/val	49.61%	cfg | model | log

More

You can also download the model weights from following sources:

• BaiduNetdisk: https://pan.baidu.com/s/1gD-NJJWOtaHCtB0qHE79rA with access code s757