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Benchmark Dataset and Evaluation Code for Video Semantic Salient Instance Segmentation

This project is based on DAVIS Challenge Evaluation Code.

Raw dataset is downloaded from DAVIS Challenge website. Our SESIV annotation and baseline results are downloaded from my website.

Citation

Please cite the following papers:

@inproceedings{ltnghia-wacv2019,
  author = {Trung-Nghia Le and Akihiro Sugimoto},
  title = {Semantic Instance Meets Salient Object: Study on Video Semantic Salient Instance Segmentation},
  booktitle = {IEEE Winter Conference on Applications of Computer Vision},
  year = {2019}
}

@article{Pont-Tuset_arXiv_2017,
  author = {Jordi Pont-Tuset and Federico Perazzi and Sergi Caelles and Pablo Arbel\'aez and Alexander Sorkine-Hornung and Luc {Van Gool}},
  title = {The 2017 DAVIS Challenge on Video Object Segmentation},
  journal = {arXiv: 1704.00675},
  year = {2017}
}

The code is used for academic purpose only.

Contact: Trung-Nghia Le.