Related papers: Guided Interactive Video Object Segmentation Using Reliability-Based Attention Maps

Guided Interactive Video Object Segmentation Using Reliability-Based Attention Maps

URL: http://arxiv.org/abs/2104.10386v1
Date: Wed, 21 Apr 2021 07:08:57 GMT
Title: Guided Interactive Video Object Segmentation Using Reliability-Based Attention Maps
Authors: Yuk Heo, Yeong Jun Koh, Chang-Su Kim
Abstract summary: We propose a novel guided interactive segmentation (GIS) algorithm for video objects to improve the segmentation accuracy and reduce the interaction time. We develop the intersection-aware propagation module to propagate segmentation results to neighboring frames. Experimental results demonstrate that the proposed algorithm provides more accurate segmentation results at a faster speed than conventional algorithms.
Score: 55.94785248905853
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Abstract: We propose a novel guided interactive segmentation (GIS) algorithm for video objects to improve the segmentation accuracy and reduce the interaction time. First, we design the reliability-based attention module to analyze the reliability of multiple annotated frames. Second, we develop the intersection-aware propagation module to propagate segmentation results to neighboring frames. Third, we introduce the GIS mechanism for a user to select unsatisfactory frames quickly with less effort. Experimental results demonstrate that the proposed algorithm provides more accurate segmentation results at a faster speed than conventional algorithms. Codes are available at https://github.com/yuk6heo/GIS-RAmap.

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