Historical context & research account
GLIDE compares CLIP guidance with classifier-free guidance and demonstrates photorealistic text-to-image generation and inpainting. It is a precursor to DALL·E 2 and later diffusion-based products. The combination of generation and editing is especially relevant to the development of interfaces for modifying existing visual material.
Dates & version record
Date displayed for this node：2021-12 · Date recorded in the research master：2021-12
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Original sources & further reading
These links lead to the cited paper, article, institution or conference page. External texts retain their source languages.
GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models
https://arxiv.org/abs/2112.10741
Current cited URL
Provenance, translation & verification
Archive node #079 · Historical node
Research masters & supplement references · 3
AI Art Genealogy Research Master · p. 24 · 079
Date as recorded: 2021-12
GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models ↗
GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models
GenAI Visual Release Chronology Research Master · p. 3 · R009
Date as recorded: 2021-12
GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models ↗
GLIDE
GenAI Visual Release Chronology Research Master · p. 3 · R011
Date as recorded: 2021-12
GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models ↗
OpenAI GLIDE
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Cite this node
ANTI-AI ARCHIVE. GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models. Art-history node #079. https://salondesrefuses.cn/en/art-history/079
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