• Computer Science
  • Published in ICCV 2019

Video Instance Segmentation

@article{Yang2019VideoIS,
  title={Video Instance Segmentation},
  author={Linjie Yang and Yuchen Fan and Ning Xu},
  journal={ArXiv},
  year={2019},
  volume={abs/1905.04804}
}
Highlight Information
In this paper we present a new computer vision task, named video instance segmentation. [...] Key Method To facilitate research on this new task, we propose a large-scale benchmark called YouTube-VIS, which consists of 2883 high-resolution YouTube videos, a 40-category label set and 131k high-quality instance masks. In addition, we propose a novel algorithm called MaskTrack R-CNN for this task.Expand Abstract
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Citations

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UnOVOST: Unsupervised Offline Video Object Segmentation and Tracking

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Spatio-temporal Attention Network for Video Instance Segmentation

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Classifying, Segmenting, and Tracking Object Instances in Video with Mask Propagation

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Temporal Feature Augmented Network for Video Instance Segmentation

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Instance-wise Depth and Motion Learning from Monocular Videos

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CITES METHODS & BACKGROUND

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