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Clicking Matters:Towards Interactive Human Parsing by Gao, Yutong; Liang, Liqian; Lang, Congyan; Feng, Songhe; Li, Yidong; Wei, Yunchao is a scholarly article available to read on EtoBox.

What is Clicking Matters:Towards Interactive Human Parsing about?

In this work, we focus on Interactive Human Parsing (IHP), which aims to segment a human image into multiple human body parts with guidance from users' interactions. This new task inherits the class-aware property of human parsing, which cannot be well solved by traditional interactive image segmentation approaches that are generally class-agnostic. To tackle this new task, we first exploit user clicks to identify different human parts in the given image. These clicks are subsequently transformed into semantic-aware localization maps, which are concatenated with the RGB image to form the input of the segmentation network and generate the initial parsing result. To enable the network to better perceive user's purpose during the correction process, we investigate several principal ways for the refinement, and reveal that random-sampling-based click augmentation is the best way for promoting the correction effectiveness. Furthermore, we also propose a semantic-perceiving loss (SP-loss) to augment the training, which can effectively exploit the semantic relationships of clicks for better optimization. To the best knowledge, this work is the first attempt to tackle the human parsing tas

Author

Gao, Yutong; Liang, Liqian; Lang, Congyan; Feng, Songhe; Li, Yidong; Wei, Yunchao

Published

2021

Language

EN