Video Colorization

Video colorization aims to automatically add realistic and temporally consistent color to grayscale video footage. Current research heavily utilizes deep learning, particularly diffusion models and recurrent neural networks, often incorporating techniques like attention mechanisms and memory modules to improve color accuracy and temporal coherence. These advancements are improving the quality of colorized videos, enabling applications in film restoration, artistic expression, and potentially aiding in the analysis of historical or scientific monochrome footage. Furthermore, incorporating user control and semantic information is a growing focus, allowing for more creative and nuanced colorization results.