更小、更轻、更通用视觉Transformer！苹果提出MobileViT模型！

喜欢ヅ旅行 2022-09-17 03:05 318阅读 0赞

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转载于：知乎Sophia  
https://zhuanlan.zhihu.com/p/420918360

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今天分享的文章是Apple公司提出的一种在移动端的轻量级通用视觉Transformer 框架MobileViT！这是基于CNN网络的轻量级ViT工作，性能优于主流网络！

![6fa0b0522177b3adfe2705dfa45e21a7.png][]

论文地址：arxiv.org/pdf/2110.02178

## 摘要： ##

![4796169f3dc43a89ab3d867994ac3b2d.png][]

## Visual transformers vs. MobileViT ##

![d713c1aab7c828a07bcb4b07b78d7605.png][] ![10ebcdc47b040cec72be6349ce15b6ab.png][]

## 性能对比 ##

![1cd78418ab2a459f4c7cec2c2f82399b.png][]

## 多尺度对比 ##

![1cce4132b0a63c34382b190dcac388a9.png][]

## ImageNet-1k的对比 ##

![e24f4b10208f5e02051ae413fadc0f7a.png][] ![a26be86643b6e41742358f6f642fc8ac.png][]

文章思路清晰，值得学习！

**往期论文推荐：**

[高效！Anchor DETR：旷视提出一种基于Transformer的目标检测神器！][Anchor DETR_Transformer]

[小目标神器！TPH-YOLOv5：将Transformer预测加载Yolov5！][TPH-YOLOv5_Transformer_Yolov5]

[全新思路！阿里达摩院将Transformer引入在线行为检测！ICCV2021][Transformer_ICCV2021]

[高效新思路！实例分割算法！腾讯、华科出品！入选ICCV 2021!][ICCV 2021]

[超强总结！456篇参考文献！《计算机视觉对抗攻击与防御》综述！][TPH-YOLOv5_Transformer_Yolov5]

[最新变体Transformer！∞-former！DeepMind 出品！][TPH-YOLOv5_Transformer_Yolov5]

[最新综述！深度神经网络视觉识别！329篇文献！西安交大、清华等出品][329]

[超强YOLOP！CVPR 2022领域主席团队开源！全景感知多任务SOTA！][TPH-YOLOv5_Transformer_Yolov5]

[Fastformer：史上最强最快Transformer！清华、MSRA出品！][Fastformer_Transformer_MSRA]

[脑洞大开！油画渲染的新算法 Paint Transformer！ICCV2021 Oral！][Paint Transformer_ICCV2021 Oral]

[首次！阿里达摩院将Pure Transformer 应用于目标重识别ReID！][Pure Transformer _ReID]

[ResNet超强变体CoTNet！一种新的Transformer计算机视觉模块！][ResNet_CoTNet_Transformer]

[新模型！Conformer！Transformer与CNN的超强融合！][Conformer_Transformer_CNN]

[ImageNet又被Long-Short Transformer 霸榜！][ImageNet_Long-Short Transformer]

[新想法！华科、清华、康奈尔联合提出“圆形卷积”！聚合方形和圆形优势][ImageNet_Long-Short Transformer]

[表现SOTA！DetCo算法：目标检测无监督对比学习][SOTA_DetCo]

[新模型SkipNet在ImageNet分类任务大放光彩！优化损失函数！][TPH-YOLOv5_Transformer_Yolov5]

[高效神器！小目标检测迎来曙光！SSPNet金字塔网络！川大出品][ImageNet_Long-Short Transformer]

[超强！MDETR：基于Transformer的端到端目标检测神器！开源！][TPH-YOLOv5_Transformer_Yolov5]

[优秀！一种巧妙组合算法YOLOX！旷视重磅开源！][YOLOX]

[新突破！Swin-UNet：基于纯 Transformer 结构的医学图像分割网络][Swin-UNet_ Transformer]

**-------------------**

***END***

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我是[王博Kings][Kings]，985AI博士，华为云专家、CSDN博客专家（人工智能领域优质作者）。单个AI开源项目现在已经获得了2100+标星。现在在做AI相关内容，欢迎一起交流学习、生活各方面的问题，一起加油进步！

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[Anchor DETR_Transformer]: https://blog.csdn.net/Sophia_11/article/details/120465460
[TPH-YOLOv5_Transformer_Yolov5]: https://blog.csdn.net/Sophia_11/article/details/120446147
[Transformer_ICCV2021]: http://mp.weixin.qq.com/s?__biz=MzU2NTc5MjIwOA==&mid=2247520701&idx=2&sn=ce909619d50417c6353b740550126ec3&chksm=fcb48d02cbc30414f71967d9d83496db71344e0a393b80806186d732092a0c3ebfaa3d207b40&scene=21#wechat_redirect
[ICCV 2021]: http://mp.weixin.qq.com/s?__biz=MzU2NTc5MjIwOA==&mid=2247520601&idx=2&sn=f06f7deb121d774b8683ab5043bbdd53&chksm=fcb48de6cbc304f0c5a699798315ccf14ff3898308df8bb637852c8c7ab2461fb86cd27314ce&scene=21#wechat_redirect
[329]: https://blog.csdn.net/Sophia_11/article/details/120212914
[Fastformer_Transformer_MSRA]: https://blog.csdn.net/Sophia_11/article/details/120072544
[Paint Transformer_ICCV2021 Oral]: https://blog.csdn.net/Sophia_11/article/details/120386973
[Pure Transformer _ReID]: https://blog.csdn.net/gzq0723/article/details/119813919
[ResNet_CoTNet_Transformer]: https://blog.csdn.net/amusi1994/article/details/119363684
[Conformer_Transformer_CNN]: https://blog.csdn.net/Sophia_11/article/details/119860627
[ImageNet_Long-Short Transformer]: https://blog.csdn.net/Sophia_11/article/details/120375839
[SOTA_DetCo]: https://blog.csdn.net/qq_29462849/article/details/119123163
[YOLOX]: https://blog.csdn.net/Sophia_11/article/details/119012008
[Swin-UNet_ Transformer]: https://blog.csdn.net/amusi1994/article/details/116957208
[Kings]: https://blog.csdn.net/Sophia_11/article/details/114274846
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[Transformer _]: http://mp.weixin.qq.com/s?__biz=MzU2NTc5MjIwOA==&mid=2247502134&idx=1&sn=ed4a262db0be219feb017c08f2185779&chksm=fcb4d589cbc35c9f0156ac454dccb82a501f4b8129adbbcf94a3ca83d3af129f4ebadf173e75&scene=21#wechat_redirect
[Scaled-YOLOv4_ _]: http://mp.weixin.qq.com/s?__biz=MzU2NTc5MjIwOA==&mid=2247500056&idx=2&sn=95a04371dc0b49e8c862b03a88edbb8c&chksm=fcb4dda7cbc354b14c4cd4f63eadf02680112ee21015fe372cf3055f9b577b7dd989843eda1f&scene=21#wechat_redirect
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[PyTorch_ _ 1]: http://mp.weixin.qq.com/s?__biz=MzU2NTc5MjIwOA==&mid=2247497036&idx=2&sn=552069978cf317b9581b4c9a62a003e2&chksm=fcb4e9f3cbc360e51de7a7ceb3a6adde123e488d98a3baf4204270311ef609fa5510682ff29b&scene=21#wechat_redirect
[Numpy]: https://blog.csdn.net/dafeidouzi/article/details/100520906
[10]: https://blog.csdn.net/lvsehaiyang1993/article/details/80342473
[CVPR 2020]: https://blog.csdn.net/u013685264/article/details/104984809
[Link 27]: https://blog.csdn.net/fengdu78/article/details/107308594
[YOLOv4]: https://blog.csdn.net/fengdu78/article/details/106450074
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