Semantic Color

Semantic color research focuses on automatically assigning colors to images or 3D models based on their semantic content, aiming for realistic and perceptually pleasing results. Current efforts leverage diffusion models and other deep learning architectures, often incorporating multimodal information and sparse correspondences to improve color accuracy and reduce computational demands, particularly in applications like image colorization and compression. This field is significant for advancing image synthesis, 3D modeling, and image compression techniques, leading to more realistic and controllable visual outputs in various applications.