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PiClick: Picking the desired mask from multiple candidates in click-based interactive segmentation by Yan, Cilin; Wang, Haochen; Liu, Jie; Jiang, Xiaolong; Hu, Yao; Tang, Xu; Kang, Guoliang; Gavves, Efstratios is a scholarly article available to read on EtoBox.

What is PiClick: Picking the desired mask from multiple candidates in click-based interactive segmentation about?

Click-based interactive segmentation aims to generate target masks via human clicking, which facilitates efficient pixel-level annotation and image editing. In such a task, target ambiguity remains a problem hindering the accuracy and efficiency of segmentation. That is, in scenes with rich context, one click may correspond to multiple potential targets, while most previous interactive segmentors only generate a single mask and fail to deal with target ambiguity. In this paper, we propose a novel interactive segmentation network named PiClick, to yield all potentially reasonable masks and suggest the most plausible one for the user. Specifically, PiClick utilizes a Transformer-based architecture to generate all potential target masks by mutually interactive mask queries. Moreover, a Target Reasoning module(TRM) is designed in PiClick to automatically suggest the user-desired mask from all candidates, relieving target ambiguity and extra-human efforts. Extensive experiments on 9 interactive segmentation datasets demonstrate PiClick performs favorably against previous state-of-the-arts considering the segmentation results. Moreover, we show that PiClick effectively reduces human effo

Author

Yan, Cilin; Wang, Haochen; Liu, Jie; Jiang, Xiaolong; Hu, Yao; Tang, Xu; Kang, Guoliang; Gavves, Efstratios

Published

2023

Language

EN