This video walks through the Keras Code Example implementation of Vision Transformers!! I see this as a huge opportunity for graduate students and researchers because this architecture has a serious room for improvement. I predict that Attention will outperform CNN models like ResNets, EfficientNets, etc. it will just take the discovery of complimentary priors, e.g. custom data augmentations or pre-training tasks. I hope you find this video useful, please check out the rest of the Keras Code Examples playlist!

Content Links:
Keras Code Exampes - Vision Transformers: [ Ссылка ]
Google AI Blog Visualization: [ Ссылка ]
Formal Paper describing this model: [ Ссылка ]
TensorFlow Addons: [ Ссылка ]
TensorFlow Addons -AdamW: [ Ссылка ]

Chapters
0:00 Welcome to the Keras Code Examples!
0:45 Vision Transformer Explained
2:47 TensorFlow Add-Ons
3:29 Hyperparameters
7:04 Data Augmentations
8:30 Patch Construction
11:52 Patch Embeddings
14:01 ViT Classifier
16:30 Compile and Run
19:02 Analysis of Final Performance

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