Vision Transformers (ViT)

Why It Was Important

Google researchers proved that dividing an image into 16x16 'patches' (treating them like a sequence of text words) and processing them with a standard Transformer actually outperformed sophisticated CNNs when trained on massive data. This proved the 'Transformer' is a universal, domain-agnostic reasoning architecture.

Who Invented It

Alexey Dosovitskiy et al. (Google Brain)

Computer vision experts scaling Transformers arbitrarily.

Applications

• State-of-the-Art Image Classification
• Autonomous Driving vision
• Multimodal foundations