Auke discusses the innovative approach of treating images as collections of patches, akin to how language transformers process text. He highlights the advantages of swin transformers, which utilize local self-attention to enhance memory efficiency, making them ideal for large image and video encoding. By integrating these transformers into existing compression architectures, researchers aim to demonstrate their superiority over traditional convolutional methods.
