Guided Interactive Video Object Segmentation Using Reliability-Based Attention Maps

CVPR 2021

Guided Interactive Video Object Segmentation Using Reliability-Based Attention Maps

Apr 21, 2021
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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. Authors: Yuk Heo, Yeong Jun Koh, Chang-Su Kim (Korea University, Chungnam National University)

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