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Creating Beyond the Frame: A Practical Guide to Image Outpainting with Stable Diffusion
Computer Vision   Latest   Machine Learning

Creating Beyond the Frame: A Practical Guide to Image Outpainting with Stable Diffusion

Author(s): Vincent Liu

Originally published on Towards AI.

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Figure 1. Example of image outpainting. Source: Photo by Jon Tyson on Unsplash, modified by author.

In a world where artificial intelligence can generate everything from poems to entire works of art, it’s no surprise that AI is now helping us reimagine existing images as well. In computer vision, there’s a related field focused on seamlessly filling in or extending specific areas within or beyond an image. These techniques, known as β€˜image inpainting’ and β€˜outpainting,’ have made significant advancements over time.

Figure 2. Example of image inpainting. Source: image inpainting

The journey starts with image inpainting. Specific areas in an image are restored based on the neighboring information. In Figure 2, the inpainting is applied based on the targets specified in a binary mask to remove the strokes.

Image outpainting, on the other hand, is the process of extending an image beyond its original borders, generating new content that blends seamlessly with the existing scene. An example of image outpainting is given in Figure 1. The source image contains clipped text and a limited background, which are fully recovered and further extended in the outpainting result.

Figure 3. Example of image outpainting based on… Read the full blog for free on Medium.

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