# SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/segformer-simple-and-efficient-design-for-semantic-segmentation-with/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Enze Xie,Wenhai Wang,Zhiding Yu,Anima Anandkumar,Jose M. Álvarez,Ping Luo |
| Citations | 848 |
| DOI | 10.48550/arxiv.2105.15203 |
| Fields | Computer Science |
| Open Access | true |
| OA Status | green |
| OA URL | https://arxiv.org/pdf/2105.15203 |
| OpenAlex ID | https://openalex.org/W3170544306 |
| Type | book-chapter |
| Year | 2021 |

## Paper authors

- [Anima Anandkumar](https://scholariq.org/researchers/anima-anandkumar/)

## Paper primary topic

- [Advanced Neural Network Applications](https://scholariq.org/topics/advanced-neural-network-applications/)

## Paper topics

- [Advanced Neural Network Applications](https://scholariq.org/topics/advanced-neural-network-applications/)
- [Advanced Image and Video Retrieval Techniques](https://scholariq.org/topics/advanced-image-and-video-retrieval-techniques/)
- [Video Surveillance and Tracking Methods](https://scholariq.org/topics/video-surveillance-and-tracking-methods/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.