gobunu/HAODiffPython
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We stably expand the latent channels of a pretrained diffusion restorer, enabling efficient one-step human restoration with higher fidelity and fewer artifacts.
We propose a physically grounded one-step diffusion method for face fill-light enhancement, trained on our 160K-pair dataset with 6D area-disk lighting control and physics-aware conditioning.