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Home›Tech News›Ask HN: Why are AI generated images so shiny/glossy?

Ask HN: Why are AI generated images so shiny/glossy?

By Matthew Lynch
August 17, 2024
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I’ve been experimenting with various AI image generation tools lately, and I’ve noticed a recurring pattern: many of the images produced have an unusually shiny or glossy appearance. This effect seems particularly pronounced in renders of objects, surfaces, and even skin textures.

Has anyone else observed this phenomenon? I’m curious about the technical reasons behind this effect. Could it be related to:

1.Training data bias towards high-quality, well-lit product photos?

2.The way AI models interpret and reproduce lighting and reflections?

3.Some quirk in the image synthesis process that amplifies specular highlights?

I’ve tried adjusting prompts to request more matte or natural finishes, but the glossiness often persists to some degree. It’s as if the AI has a default “beauty mode” that it’s reluctant to fully disable.

For those with deeper knowledge of the underlying tech:

1.Is this a known issue in the field?

2.Are there specific architectural choices in popular models that might contribute to this effect?

3.How might this be addressed in future iterations of AI image generation systems?

I’d love to hear insights from anyone involved in developing or researching these technologies. Has your team encountered similar challenges? What approaches are being explored to create more naturalistic textures and lighting?

This glossy tendency seems like an interesting quirk that could reveal something about how these AI systems “understand” and reconstruct visual information. What are your thoughts?

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Since technology is not going anywhere and does more good than harm, adapting is the best course of action. That is where The Tech Edvocate comes in. We plan to cover the PreK-12 and Higher Education EdTech sectors and provide our readers with the latest news and opinion on the subject. From time to time, I will invite other voices to weigh in on important issues in EdTech. We hope to provide a well-rounded, multi-faceted look at the past, present, the future of EdTech in the US and internationally.

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