Video segmentation with less carrying over of errors by using a cyclic workflow
Video segmentation with less carrying over of errors by using a cyclic workflow
Exploring the Semi-supervised Video Object Segmentation Problem from a Cyclic Perspective
arXiv paper abstract https://arxiv.org/abs/2111.01323v1
arXiv PDF paper https://arxiv.org/pdf/2111.01323v1.pdf
Modern video object segmentation (VOS) algorithms have achieved remarkably high performance in a sequential processing order, while most of currently prevailing pipelines still show some obvious inadequacy like accumulative error ...
... place ... segmentation problem into a cyclic workflow and find the defects above can be collectively addressed via the inherent cyclic property of semi-supervised VOS systems.
... Relying on the accurate reference mask in the starting frame, we show that the error propagation problem can be mitigated.
Next, ... highlight the high-frequent and detailed part of results to further improve the segmentation quality while keeping feasible computation cost.
... develop cycle effective receptive field (cycle-ERF) ... to provide a new perspective into analyzing object-specific regions of interests.
... demonstrating that the cyclic mechanism is helpful to enhance segmentation quality, improve the robustness of VOS systems, and further provide qualitative comparison and interpretation on how different VOS algorithms work. ...
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