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:
Google AI Blog Visualization:
Formal Paper describing this model:
TensorFlow Addons:
TensorFlow Addons -AdamW:
Chapters
0:00 Welcome to the Keras Code
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4 years ago 00:21:54 11
Vision Transformer - Keras Code Examples!!
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Focal Transformer: Focal Self-attention for Local-Global Interactions in Vision Transformers
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[DeepReader] Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
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Vision Transformers (Ilya Kontaev, Xperience AI)
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Transformers: Prime “Tunnel Vision“
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When Vision Transformers Outperform ResNets without Pretraining | Paper Explained
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Will Transformers Replace CNNs in Computer Vision? + NVIDIA GTC Giveaway
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Vision Deep Learning
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Chrysler Eagle Vision - Barricade Transformers
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Productivity Future Vision
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VISION-S 02 | Concept Movie
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Boqing Gong -- When Vision Transformers Outperform ResNets Without Pretraining or Strong Data Aug...
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Swin Transformer paper animated and explained
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The Incredible Vision of Joshua Kimmich!
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Vision Transformers for Dense Prediction (ICCV 2021)