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This repository is an effective implementation of a novel method for labelling each object candidates in videos by generating temporally consistent proposals in the form of object trajectories, which outperforms current state-of-the-art methods.

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Object Trajectory Proposal

@inproceedings{shang2017object,
  title={Object trajectory proposal},
  author={Shang, Xindi and Ren, Tongwei and Zhang, Hanwang and Wu, Gangshan and Chua, Tat-Seng},
  booktitle={Multimedia and Expo (ICME), 2017 IEEE International Conference on},
  pages={331--336},
  year={2017},
  organization={IEEE}
}

Acknowledgment

This research is supported by the National Research Foundation, Singapore under its International Research Centres in Singapore Funding Initiative, National Science Foundation of China (61321491, 61202320), and Collaborative Innovation Center of Novel Software Technology and Industrialization. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not reflect the views of National Research Foundation, Singapore.

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This repository is an effective implementation of a novel method for labelling each object candidates in videos by generating temporally consistent proposals in the form of object trajectories, which outperforms current state-of-the-art methods.

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