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FEELVOS implementation in PyTorch; FEELVOS: Fast End-to-End Embedding Learning for Video Object Segmentation

Home Page: https://arxiv.org/abs/1902.09513

License: MIT License

Python 53.56% C++ 10.99% Cuda 35.45%

feelvos's Introduction

FEELVOS

FEELVOS implementation in PyTorch; FEELVOS: Fast End-to-End Embedding Learning for Video Object Segmentation

FEELVOS Architecture

LICENSE

Check LICENSE.

Installation

Please check Installation procedure in INSTALL.md.

Quick Start

Follow the instructions in QUICK_START.md.

Acknowledgments

@article{DBLP:journals/corr/abs-1902-09513,
  author    = {Paul Voigtlaender and
               Yuning Chai and
               Florian Schroff and
               Hartwig Adam and
               Bastian Leibe and
               Liang{-}Chieh Chen},
  title     = {{FEELVOS:} Fast End-to-End Embedding Learning for Video Object Segmentation},
  journal   = {CoRR},
  volume    = {abs/1902.09513},
  year      = {2019},
  url       = {http://arxiv.org/abs/1902.09513},
  archivePrefix = {arXiv},
  eprint    = {1902.09513},
  timestamp = {Tue, 21 May 2019 18:03:37 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1902-09513.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

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