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The Uncanny Valley of Perfection

5 MIN READ

COMPUTER VISION

RESEARCH

State-of-the-art models like Flux and SDXL suffer from "aesthetic mode collapse," producing plastic, studio-like outputs. By fine-tuning on a curated Kled coreset of high-utility images, we successfully injected realistic optical factors—such as photon noise and lens aberrations—back into the generation process, consistently outperforming prompt engineering in texture fidelity.

3.1K

Coreset Images

3

Training Epochs

10

Metrics Evaluated

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