Innovative reasoning time handling mechanism
SynthLight employs a diffusion sampling procedure based on no classifier guidance in the inference stage, a technological breakthrough that effectively preserves key detailed features of the input portrait. While traditional diffusion models tend to lose the subtle facial features and textures of the original image during image conversion, SynthLight's sampling algorithm strikes a perfect balance between preserving the details of the original image and realizing the light conversion by dynamically adjusting the guidance scale during the denoising process.
- Adoption of progressive feature retention strategies
- Dynamic tuning of CFG (Classifier-Free Guidance) parameters
- Introduction of attention mechanisms to protect critical facial areas
- Multi-stage detail repair algorithm
This technology ensures that character identity features and facial details are perfectly preserved even when extensive adjustments are made to lighting conditions. User tests have shown that SynthLight has a 23% improvement in detail retention compared to similar tools such as IC-Light.
This answer comes from the articleSynthLight: natural light rendering of portrait images (unreleased)The
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