Image colorization, as an essential problem in computer vision (CV), has attracted an
increasing amount of researchers attention in recent years, especially deep learning-based …

Image colorization is a classic and important topic in computer graphics, where the aim is to
add color to a monochromatic input image to produce a colorful result. In this survey, we …

Colorization has attracted increasing interest in recent years. Classic reference-based
methods usually rely on external color images for plausible results. A large image database …

Interior color design is a creative process that endeavors to allocate colors to furniture and
other elements within an interior space. While much research focuses on generating realistic …

We propose the first unified framework UniColor to support colorization in multiple
modalities, including both unconditional and conditional ones, such as stroke, exemplar …

Recently, unsupervised exemplar-based image-to-image translation, conditioned on a given
exemplar without the paired data, has accomplished substantial advancements. In order to …

Despite recent advancements in deep learning-based automatic colorization, they are still
limited when it comes to few-shot learning. Existing models require a significant amount of …

Image colorization estimates RGB colors for grayscale images or video frames to improve
their aesthetic and perceptual quality. Over the last decade, deep learning techniques for …

Line art colorization is expensive and challenging to automate. A GAN approach is
proposed, called Tag2Pix, of line art colorization which takes as input a grayscale line art …

Colorization is multimodal by nature and challenges existing frameworks to achieve colorful
and structurally consistent results. Even the sophisticated autoregressive model struggles to …