A sparse control model for image and video editing

It is common that users draw strokes, as control samples, to modify color, structure, or tone of a picture. We discover inherent limitation of existing methods for their implicit requirement on where and how the strokes are drawn, and present a new system that is principled on minimizing the amount of work put in user interaction. Our method automatically determines the influence of edit samples across the whole image jointly considering spatial distance, sample location, and appearance. It greatly reduces the number of samples that are needed, while allowing for a decent level of global and local manipulation of resulting effects and reducing propagation ambiguity. Our method is broadly beneficial to applications adjusting visual content.