"Segmenter: Transformer for Semantic Segmentation" reproduced via mmsegmentation

Last update: Feb 24, 2022

Overview

Segmenter-based-on-OpenMMLab

"Segmenter: Transformer for Semantic Segmentation, arxiv 2105.05633." reproduced via mmsegmentation.

We reproduce Segmenter via mmsegmentation based on official open-sourced code.

Environment

python=3.7
pytorch=1.7.1
torchvision=0.8.2
cudatoolkit=10.1
mmcv-full=1.3.10
mmsegmentation=0.16.0

Note: You should install pytorch with a version higher than 1.7, because the pretrained model of DeiT is saved via 1.7+ pytorch. Otherwise you may encounter some errors while loading the state_dict.

Results on ADE20K

The passwds of download links are all 'nopw'.

Exp	Name	backbone	Our mIoU-SS	mIoU in paper	Resolution	BS	Download
4th line in Table3	Seg-B†-Linear/16	DeiT-B	46.83	47.10	512x512	8	model	config	log
4th line in Table6	Seg-B†-Mask/16	DeiT-B	48.41	47.67	512x512	8	model	config	log
6th line in Table3	Seg-B -Linear/16	ViT-B	45.70	45.69	512x512	8	model	config	log

Owner

EricKani

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