setr

Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers

Introduction

Official Repo

Code Snippet

This head has two version head.

SETR (CVPR'2021)

@article{zheng2020rethinking,
  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},
  journal={arXiv preprint arXiv:2012.15840},
  year={2020}
}

Results and models

ADE20K

Method	Backbone	Crop Size	Batch Size	Lr schd	Mem (GB)	Inf time (fps)	mIoU	mIoU(ms+flip)	config	download
SETR-Naive	ViT-L	512x512	16	160000	18.40	4.72	48.28	49.56	config	model | log
SETR-PUP	ViT-L	512x512	16	160000	19.54	4.50	48.24	49.99	config	model | log
SETR-MLA	ViT-L	512x512	8	160000	10.96	-	47.34	49.05	config	model | log
SETR-MLA	ViT-L	512x512	16	160000	17.30	5.25	47.54	49.37	config	model | log