Paint selection

137 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Getting to 99% Accuracy in Interactive Segmentation (2020, background): “The work of Liu et al. [4] (2009) is particularly interesting in that regard, as they acknowledge the progressive nature of image editing and pay particular attention to the artist workﬂow.”
ScribbleSup: Scribble-Supervised Convolutional Networks for Semantic Segmentation (2016, methodology): “Formulation in this form is widely used for interactive image segmentation [4, 26, 17, 11, 16, 19].”
Error-Tolerant Scribbles Based Interactive Image Segmentation (2014, methodology): “’s method [8] allows the user to override the erroneous scribbles by specifying new scribbles, which overlap partially with the inaccurate old scribbles.”
Geodesic star convexity for interactive image segmentation (2010, background): “Connectivity can also be imposed as a post-processing step as done in paint-select [13], but that is not principled and cannot be expressed as an energy function.”
Image smoothing via L0 gradient minimization (2011, methodology): “Graph-cut based methods [Rother et al. 2004; Li et al. 2004; Liu et al. 2009] and segmentation [Maji et al. 2011; Arbelaez et al. 2011] were employed.”
Learning an interactive segmentation system (2009, methodology): “Inspired by recent work [17], foreground regions are 4-connected to a user made brush stroke to avoid deserted foreground islands.”