Video Polyp Segmentation: A Deep Learning Perspective

@article{Ji2022VideoPS,
  title={Video Polyp Segmentation: A Deep Learning Perspective},
  author={Ge-Peng Ji and Guobao Xiao and Yu-Cheng Chou and Deng-Ping Fan and Kai Zhao and Geng Chen and H. Fu and Luc Van Gool},
  journal={ArXiv},
  year={2022},
  volume={abs/2203.14291}
}
We present the first comprehensive video polyp segmentation (VPS) study in the deep learning era. Over the years, developments in VPS are not moving forward with ease due to the lack of large-scale fine-grained segmentation annotations. To address this issue, we first introduce a high-quality frame-by-frame annotated VPS dataset, named SUN-SEG, which contains 158,690 frames from the well-known SUN-database. We provide additional annotations with diverse types, i.e. , attribute , object mask… 

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