Enabling Region-Specific Control via Lassos in Point-Based Colorization
This addresses color intermingling issues for users of interactive image colorization tools, representing an incremental improvement.
The paper tackled the problem of color collapse in point-based interactive colorization by introducing a lasso tool to control color hint scope, resulting in a single lasso being as effective as 4.18 individual hints and reducing time by 30%.
Point-based interactive colorization techniques allow users to effortlessly colorize grayscale images using user-provided color hints. However, point-based methods often face challenges when different colors are given to semantically similar areas, leading to color intermingling and unsatisfactory results-an issue we refer to as color collapse. The fundamental cause of color collapse is the inadequacy of points for defining the boundaries for each color. To mitigate color collapse, we introduce a lasso tool that can control the scope of each color hint. Additionally, we design a framework that leverages the user-provided lassos to localize the attention masks. The experimental results show that using a single lasso is as effective as applying 4.18 individual color hints and can achieve the desired outcomes in 30% less time than using points alone.