Imagen is a new AI system developed by the Google AI team that generates photorealistic images from text input.
In the real world, data is typically presented in a variety of formats. Images, for example, are frequently paired with tags and text explanations; the text may use images to better explain the main topic of the article. Different statistical characteristics distinguish different modalities. Texts are typically represented as discrete word count vectors, whereas images are typically represented as pixel intensities or feature extractor outputs. Because different information resources have different statistical features, determining the link between different modalities is critical. Multimodal learning has emerged as a promising method for representing the combination of representations from various modalities. Text-to-image synthesis and image-text contrastive learning are two recent examples of multimodal learning. Imagen, a text-to-image diffusion model that combines, is introduced in a new Google Brain Research. Diffusion models with high fidelity In text-to-image synthesis, th...
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