A user has developed a small, 0.48M parameter residual network designed to remove specific artifacts generated by GPT Image 2. These artifacts, including over-sharpening, bright specks, and scale-like patterns, are unique to the model and can be addressed by adding a scaled residual prediction in the latent space before decoding. The solution operates efficiently, taking about 0.7 seconds per image on a recent GPU with minimal VRAM usage, and is available via a web demo and code repository. AI
IMPACT Provides a method to improve the visual quality of images generated by GPT Image 2, addressing common user complaints.
RANK_REASON User-developed tool to mitigate issues with a specific AI model's output.
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