Grunnleggende konsepter
This study proposes a new formulation of color guidance for diffusion models that can effectively control the global color aspect of generated images without hindering the quality of generation. The proposed fine color guidance is then applied in an image compression framework to improve fidelity and realism of compressed images at extremely low bitrates.
Sammendrag
The paper addresses the challenge of controlling the global color aspect of images generated with a diffusion model, without the need for training or fine-tuning. The authors rewrite the guidance equations to ensure that the outputs are closer to a known color map, without hindering the quality of the generation.
The key highlights and insights are:
The authors propose a new formulation of the guidance specific to color map control, called fine color guidance. This rewritten guidance equation, inspired by universal-guidance, shows that for color maps, contrary to the general case, the scaling of the guidance term should not decrease during diffusion.
The fine color guidance is applied in an image compression framework, where the image is encoded as a combination of semantic information (using CLIP) and a low-resolution color map. The authors show that their method effectively preserves the color information provided by the color map, improving fidelity and realism of compressed images at extremely low bitrates, compared to other classical or semantic-oriented approaches.
Experiments demonstrate that the proposed fine color guidance outperforms existing training-free methods for controlling color in both pixel-space and latent diffusion models. It can be advantageously used with the latest diffusion models to control the output.
The summary provides a comprehensive overview of the key contributions and findings of the paper, without the need to refer back to the original content.