Color vision deficiency (CVD), commonly known as color blindness, is identified among millions of the world-wide population and, to date, still poses barriers to communication, accessibility, and living. Although there is no therapeutic solution that can be used to bring typical vision, there has been considerable developments concerning technological solutions. These can broadly be classified as hardware based and software based with the former category comprising aid in the form of tinted glasses and filters, and the latter category being methods implemented on digital images in order to enhance perception. Initial studies presented heuristic algorithms and machine-learning frameworks, whereas more recent studies focus on customized and severity-sensitive algorithms, deep learning frameworks, and effective color-space frameworks that can be optimally adapted to real-time operations. There is also an increase in practical tools, with mobile apps providing instant recognition, gamified apps supporting the diagnosis of childhood, and virtual reality being experimented with the interactive evaluation and training. Besides this there are the studies on optical lenses, diagnosis, bi-medical directions like gene therapy that point to a diversity in the number of strategies being pursued. This set of developments is an indication of a movement to more dynamic, user-friendly, and machine-compatible solutions as opposed to inflexible and one-size-fits-all solutions. However, there are challenges that are still considered major such as delivering a consistent performance on platforms, large-scale validation, and addressing the diverse needs of users. The future is combining smart algorithms, cross-platform interconnection, immersive technology, and biomedical invention to develop a comprehensive and trusted service to people with CVD.