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

DOI retrieved: December 16, 2024

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