Transformers in Vision

This lecture covers the concept of Transformers in computer vision, focusing on the 'Attention Is All You Need' architecture. It explains the Transformer Encoder and Decoder, multi-head self-attention, positional encoding, and the use of transformers for visual intelligence tasks. The lecture also discusses the application of transformers in vision tasks, such as image recognition and dense prediction. Various transformer types, including Vision Transformers (ViT), Dense Prediction Transformers (DPT), and BERT Pre-Training of Image Transformers (BEIT), are explored. Additionally, it delves into the concepts of masked autoencoders, parallel decoding, and the role of transformers in high-resolution image synthesis.