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AI image generation experiment shows 512 resolution with upscaling can match 2048 output

By PulseAugur Editorial · [1 sources] ·

An experiment demonstrated that an image generated at 2048x2048 resolution, downscaled to 512, and then upscaled back to 2048x2048 using SeedVR2, resulted in an identical image to the original. This suggests that training models at lower resolutions like 512, combined with effective upscaling techniques, could be sufficient and more efficient in terms of speed and VRAM usage. The current challenge lies in VAEs distorting faces at these lower resolutions. AI

IMPACT Suggests potential for more efficient AI image model training by leveraging lower resolutions with advanced upscaling.

RANK_REASON User-conducted experiment demonstrating a technical finding about image generation resolution and upscaling. [lever_c_demoted from research: ic=1 ai=1.0]

Read on r/StableDiffusion →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI image generation experiment shows 512 resolution with upscaling can match 2048 output

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User-conducted experiment demonstrating a technical finding about image generation resolution and upscaling. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. r/StableDiffusion TIER_2 English(EN) · /u/More_Bid_2197 ·

    So, I conducted a very interesting experiment. I generated an image in Krea 2 at a resolution of 2048x2048. Then, I took that image and downscaled it to 512. Finally, I used seedvr2 to upscale it back to 2048x2048. The final result was IDENTICAL to the original image.

    <table> <tr><td> <a href="https://www.reddit.com/r/StableDiffusion/comments/1vcawfn/so_i_conducted_a_very_interesting_experiment_i/"> <img alt="So, I conducted a very interesting experiment. I generated an image in Krea 2 at a resolution of 2048x2048. Then, I took that image and …

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