PaddleSeg/configs/segformer

• SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers
• • Reference
  • Performance
  • • Cityscapes

SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers

Reference

Xie, Enze, Wenhai Wang, Zhiding Yu, Anima Anandkumar, Jose M. Alvarez, and Ping Luo. "SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers." arXiv preprint arXiv:2105.15203 (2021).

Performance

Cityscapes

Model	Backbone	Resolution	Training Iters	mIoU(slice)	mIoU (flip)	mIoU (ms+flip)	Links
SegFormer_B0	-	1024x1024	160000	76.73%	77.16%	-	model | log | vdl
SegFormer_B1	-	1024x1024	160000	78.35%	78.64%	-	model | log | vdl
SegFormer_B2	-	1024x1024	160000	81.60%	81.82%	-	model | log | vdl
SegFormer_B3	-	1024x1024	160000	82.47%	82.60%	-	model | log | vdl
SegFormer_B4	-	1024x1024	160000	82.38%	82.59%	-	model | log | vdl
SegFormer_B5	-	1024x1024	160000	82.58%	82.82%	-	model | log | vdl