PaddleClas/docs/zh_CN/models/CSWinTransformer.md

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# CSWinTransformer
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## 目录
* [1. 概述](#1)
* [2. 精度、FLOPs 和参数量](#2)
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## 1. 概述
CSWinTransformer 是一种新的视觉 Transformer 网络,可以用作计算机视觉领域的通用骨干网路。 CSWinTransformer 提出了通过十字形的窗口来做 self-attention它不仅计算效率非常高而且能够通过两层计算就获得全局的感受野。CSWinTransformer 还提出了新的编码方式LePE进一步提高了模型的准确率。[论文地址](https://arxiv.org/abs/2107.00652)。
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## 2. 精度、FLOPs 和参数量
| Models | Top1 | Top5 | Reference<br>top1 | Reference<br>top5 | FLOPs<br>(G) | Params<br>(M) |
|:--:|:--:|:--:|:--:|:--:|:--:|:--:|
| CSWinTransformer_tiny_224 | 0.8281 | 0.9628 | 0.828 | - | 4.1 | 22 |
| CSWinTransformer_small_224 | 0.8358 | 0.9658 | 0.836 | - | 6.4 | 35 |
| CSWinTransformer_base_224 | 0.8420 | 0.9692 | 0.842 | - | 14.3 | 77 |
| CSWinTransformer_large_224 | 0.8643 | 0.9799 | 0.865 | - | 32.2 | 173.3 |
| CSWinTransformer_base_384 | 0.8550 | 0.9749 | 0.855 | - | 42.2 | 77 |
| CSWinTransformer_large_384 | 0.8748 | 0.9833 | 0.875 | - | 94.7 | 173.3 |