Click to Correction: Interactive Bidirectional Dynamic Propagation Video Object Segmentation Network.

Shuting Yang, Xia Yuan, Sihan Luo
Author Information
  1. Shuting Yang: Institute of Agricultural Economy and Information Technology, Ningxia Academy of Agriculture and Forestry Sciences, Yinchuan 750002, China.
  2. Xia Yuan: School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China. ORCID
  3. Sihan Luo: School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China.

Abstract

High-quality video object segmentation is a challenging visual computing task. Interactive segmentation can improve segmentation results. This paper proposes a multi-round interactive dynamic propagation instance-level video object segmentation network based on click interaction. The network consists of two parts: a user interaction segmentation module and a bidirectional dynamic propagation module. A prior segmentation network was designed in the user interaction segmentation module to better segment objects of different scales that users click on. The dynamic propagation network achieves high-precision video object segmentation through the bidirectional propagation and fusion of segmentation masks obtained from multiple rounds of interaction. Experiments on interactive segmentation datasets and video object segmentation datasets show that our method achieves state-of-the-art segmentation results with fewer click interactions.

Keywords

References

  1. IEEE Trans Pattern Anal Mach Intell. 2019 Jun;41(6):1515-1530 [PMID: 29994298]
  2. IEEE Trans Neural Netw Learn Syst. 2024 Feb 05;PP: [PMID: 38315589]
  3. Entropy (Basel). 2024 Jul 10;26(7): [PMID: 39056952]

Grants

  1. NKYG-23-02/Ningxia Academy of Agriculture and Forestry Sciences

Word Cloud

Created with Highcharts 10.0.0segmentationvideoobjectpropagationinteractivenetworkinteractiondynamicclickmodulebidirectionalInteractiveresultsuserachievesdatasetsHigh-qualitychallengingvisualcomputingtaskcanimprovepaperproposesmulti-roundinstance-levelbasedconsiststwoparts:priordesignedbettersegmentobjectsdifferentscalesusershigh-precisionfusionmasksobtainedmultipleroundsExperimentsshowmethodstate-of-the-artfewerinteractionsClickCorrection:BidirectionalDynamicPropagationVideoObjectSegmentationNetworkclick-based

Similar Articles

Cited By