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Zhiding Yu 2023-06-13 15:01:29 -07:00
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Figure 1: Performance of SegFormer-B0 to SegFormer-B5.
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### [Project page](https://github.com/NVlabs/SegFormer) | [Paper](https://arxiv.org/abs/2105.15203) | [Demo (Youtube)](https://www.youtube.com/watch?v=J0MoRQzZe8U) | [Demo (Bilibili)](https://www.bilibili.com/video/BV1MV41147Ko/) | [Video](https://www.youtube.com/watch?v=nBjXyoltCHU)
### [Project page](https://github.com/NVlabs/SegFormer) | [Paper](https://arxiv.org/abs/2105.15203) | [Demo (Youtube)](https://www.youtube.com/watch?v=J0MoRQzZe8U) | [Demo (Bilibili)](https://www.bilibili.com/video/BV1MV41147Ko/) | [Intro Video](https://www.youtube.com/watch?v=nBjXyoltCHU)
SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers.<br>
[Enze Xie](https://xieenze.github.io/), [Wenhai Wang](https://whai362.github.io/), [Zhiding Yu](https://chrisding.github.io/), [Anima Anandkumar](http://tensorlab.cms.caltech.edu/users/anima/), [Jose M. Alvarez](https://rsu.data61.csiro.au/people/jalvarez/), and [Ping Luo](http://luoping.me/).<br>