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.
Yuk Heo, Yeong Jun Koh, and Chang-Su Kim,
"Guided Interactive Video Object Segmentation Using Reliability-Based Attention Maps," accepted to Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
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