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SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers

Semantic segmentation is a fundamental task in computer vision and enables many downstream applications. It is related to image classification since it produces per-pixel category prediction instead of image-level prediction.

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Cite this as

Enze Xie, Wenhai Wang, Zhiding Yu, Anima Anandkumar, Jose M. Alvarez, Ping Luo (2024). Dataset: SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers. https://doi.org/10.57702/kry2unhm

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Additional Info

Field	Value
Created	December 16, 2024
Last update	December 16, 2024
Author	Enze Xie
More Authors	Wenhai Wang Zhiding Yu Anima Anandkumar Jose M. Alvarez Ping Luo
Homepage	https://github.com/NVlabs/SegFormer