Vision Models

In the field of image recognition, Convolutional Neural Networks (CNNs) have long been the dominant architecture. In recent years, Transformer models have achieved great success in Natural Language Processing (NLP), which has led researchers to consider applying the Transformer architecture to image processing tasks. Vision Transformer (ViT) is a model designed for image understanding based on the Transformer framework.

CLIP (Contrastive Language-Image Pre-training) is a model proposed by OpenAI in 2021. It achieves strong generalization capability by integrating visual and language representations, and it has extensive potential applications. This article will introduce both the theory and practical implementation of CLIP.

Convolutional neural networks (CNN) is a computer vision and image processing method based on neural networks. In this article, we will introduce the principles of various layers in CNN.