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The access to masks for objects in images is of great importance to many computer vision tasks. Manually annotating such object masks (for example with polygon drawings), however, takes an extensive amount of time. In addition to this, the annotation of finely jagged edges and delicate structures poses a considerable problem. Interactive segmentation systems try to drastically ease this task by using forms of user guidance that can be annotated cheaply in order to predict an object mask. Usually this guidance takes the form of right/left mouse clicks to annotate single background/foreground pixels.

Semantic segmentation constitutes the task of classfiying every single pixel into one of several predefined classes. In consequence interactive segmentation systems constitute a combination of the two tasks: The segmentation happens on the basis of user guidance while the goal is to circumvent a costly annotation process. Instead of annotating single objects, the goal is to divide the entire input image into several class surfaces.

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Literature:

[1] : https://ceur-ws.org/Vol-2766/paper1.pdf

[2] : https://arxiv.org/abs/2003.14200

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If case of interest, contact Robin Sch?n (robin.schoen@uni-a.de)