论文标题
伪基：单击模仿的交互式图像分割
PseudoClick: Interactive Image Segmentation with Click Imitation
论文作者
论文摘要
基于点击的交互式图像分割的目的是获得用户交互有限的精确对象分割掩码，即通过最少的用户点击数量。现有方法要求用户提供所有点击：首先检查分割面膜，然后在迭代区域上提供标记区域错误的点。我们提出一个问题：我们的模型可以直接预测在哪里单击，以进一步降低用户互动成本？为此，我们提出{\ pseudoclick}，这是一个通用框架，使现有的分割网络下次单击。这些自动生成的点击，称为伪单击，这是模仿人类点击的模仿，以完善分割掩码。
The goal of click-based interactive image segmentation is to obtain precise object segmentation masks with limited user interaction, i.e., by a minimal number of user clicks. Existing methods require users to provide all the clicks: by first inspecting the segmentation mask and then providing points on mislabeled regions, iteratively. We ask the question: can our model directly predict where to click, so as to further reduce the user interaction cost? To this end, we propose {\PseudoClick}, a generic framework that enables existing segmentation networks to propose candidate next clicks. These automatically generated clicks, termed pseudo clicks in this work, serve as an imitation of human clicks to refine the segmentation mask.
