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

@article{Bertasius2020ClassifyingSA,
  title={Classifying, Segmenting, and Tracking Object Instances in Video with Mask Propagation},
  author={Gedas Bertasius and Lorenzo Torresani},
  journal={2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2020},
  pages={9736-9745}
}
  • Gedas Bertasius, L. Torresani
  • Published 10 December 2019
  • Computer Science
  • 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
We introduce a method for simultaneously classifying, segmenting and tracking object instances in a video sequence. Our method, named MaskProp, adapts the popular Mask R-CNN to video by adding a mask propagation branch that propagates frame-level object instance masks from each video frame to all the other frames in a video clip. This allows our system to predict clip-level instance tracks with respect to the object instances segmented in the middle frame of the clip. Clip-level instance tracks… 

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