Text-to-image Diffusion Models in Generative AI: A Survey
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2023
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| _version_ | 1866915008948994048 |
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| author | Zhang, Chenshuang Zhang, Chaoning Zhang, Mengchun Kweon, In So Kim, Junmo |
| author_facet | Zhang, Chenshuang Zhang, Chaoning Zhang, Mengchun Kweon, In So Kim, Junmo |
| contents | This survey reviews the progress of diffusion models in generating images from text, ~\textit{i.e.} text-to-image diffusion models. As a self-contained work, this survey starts with a brief introduction of how diffusion models work for image synthesis, followed by the background for text-conditioned image synthesis. Based on that, we present an organized review of pioneering methods and their improvements on text-to-image generation. We further summarize applications beyond image generation, such as text-guided generation for various modalities like videos, and text-guided image editing. Beyond the progress made so far, we discuss existing challenges and promising future directions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2303_07909 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Text-to-image Diffusion Models in Generative AI: A Survey Zhang, Chenshuang Zhang, Chaoning Zhang, Mengchun Kweon, In So Kim, Junmo Computer Vision and Pattern Recognition Artificial Intelligence Machine Learning This survey reviews the progress of diffusion models in generating images from text, ~\textit{i.e.} text-to-image diffusion models. As a self-contained work, this survey starts with a brief introduction of how diffusion models work for image synthesis, followed by the background for text-conditioned image synthesis. Based on that, we present an organized review of pioneering methods and their improvements on text-to-image generation. We further summarize applications beyond image generation, such as text-guided generation for various modalities like videos, and text-guided image editing. Beyond the progress made so far, we discuss existing challenges and promising future directions. |
| title | Text-to-image Diffusion Models in Generative AI: A Survey |
| topic | Computer Vision and Pattern Recognition Artificial Intelligence Machine Learning |
| url | https://arxiv.org/abs/2303.07909 |