Image Editing of Light and Color from a Single Image: A Baseline Framework
Yixiong Yang, Hassan Ahmed Sial, Ramon Baldrich, María Vanrell · Color and Imaging Conference · 2022
Smart image editing is drawing attention and a wide range of edit operations have been investigated. We address the problem of creating new image versions where light conditions and object colors can be altered while maintaining physical coherence across the scene. We propose a baseline framework comprised of a surreal dataset with a large Ground-Truth on light effects and a set of basic deep architectures relying on intrinsic decomposition. Our proposal is evaluated for image relighting and outperforms the state-of-the-art on the previous VIDIT dataset. The codes and datasets are available: https://github.com/ liulisixin/ImageEditingSI