论文地址：An Image is Worth 16x16 Words:Transformers for Image Recognition at Scale
ViT，打破了NLP和CV的壁垒，同时在多模态领域也挖坑
- 将图片分割为16x16的各个patch，视作一个个的词，然后输入transformer结构中
- 在数据量足够大的情况下效果很好，能够学习到全局特征，并且暂时没有看到性能瓶颈
Comment: Fine-tuning code and pre-trained models are available at https://github.com/google-research/vision_transformer. ICLR camera-ready version with 2 small modifications: 1) Added a discussion of CLS vs GAP classifier in the appendix, 2) Fixed an error in exaFLOPs computation in Figure 5 and Table 6 (relative performance of models is basically not affected)
