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🪄🖼 Edge#241: Emerging Capabilities of Text-to-Image Synthesis Models

🪄🖼 Edge#241: Emerging Capabilities of Text-to-Image Synthesis Models

+NVIDIA's textual inversion approach; +Outpainting interfaces

Nov 08, 2022
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TheSequence
🪄🖼 Edge#241: Emerging Capabilities of Text-to-Image Synthesis Models
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In this issue:

  • we conclude our text-to-image series discussing the emerging capabilities of text-to-image synthesis models; 

  • we explain NVIDIA’s textual inversion approach to improving text-to-image synthesis;  

  • we explore DALL-E and Stable Diffusion Outpainting Interfaces. 

Enjoy the learning!  


💡 ML Concept of the Day: Emerging Capabilities of Text-to-Image Synthesis Models 

To conclude our series about text-to-image synthesis models, today I would like to discuss some of the new areas of research that are powering new capabilities in this type of model. The first efforts in large-scale text-to-image generation have been focused on the creation of high-fidelity outputs. As that problem looks more and more solved, complementary capabilities are commanding a lot of research in the text-to-image space. Specifically, we think the following capabilities are going to become prominent components of the next generation of text-to-image generation models: 

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