SVD-Guided Diffusion for Training-Free Low-Light Image Enhancement

This work proposes a novel and training-free method that integrates the Singular Value Decomposition (SVD) with a pretrained diffusion model and defines a semantic-aware scaling scheme based on a vision-language model that efficiently improves the performance of low-light image enhancement compared to other training-free methods.