Vision Transformer
A Vision Transformer (ViT) is a neural network architecture that adapts the Transformer attention mechanism for computer vision tasks. By splitting images into grid patches and treating them like tokens in a sentence, ViT learns long-range visual relations.
Frequently Asked Questions
How does ViT compare to CNNs?▼
ViTs generally achieve higher accuracy on massive datasets because they do not have spatial translation limits (inductive bias) like CNNs, but require much more training data.
What is an image patch in ViT?▼
A small sub-grid of an image (e.g. 16x16 pixels) that is flattened into a vector and treated as a single token.
Quick Facts
- CategoryNeural Architectures
- Key ApplicationImage classification, medical anomaly detection, and video analysis
Coverage Trend12 Weeks
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