ArXiv TLDR

Alexander Kolesnikov

2 papers · Latest:

Computer Vision

Scaling Vision Transformers

This paper studies how Vision Transformers scale with model size and data, improving their architecture and training to achieve state-of-the-art ImageNet accuracy with a 2-billion parameter model.

2106.04560
Computer Vision

An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

This paper demonstrates that a pure Transformer model applied directly to image patches can achieve state-of-the-art image classification performance without relying on convolutional networks.

2010.11929

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