LeVIT

2000년 도입 · 논문 2편에서 사용

LeVIT is a hybrid neural network for fast inference image classification. LeViT is a stack of transformer blocks, with pooling steps to reduce the resolution of the activation maps as in classical convolutional architectures. This replaces the uniform structure of a Transformer by a pyramid with pooling, similar to the LeNet architecture

출처: LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference

소개 논문: LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference