A Survey on Deep Learning Technique for Video Segmentation

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Overview

A Survey on Deep Learning Technique for Video Segmentation

A Survey on Deep Learning Technique for Video Segmentation
Wenguan Wang, Tianfei Zhou, Fatih Porikli, David Crandall, and Luc Van Gool.
paper

Contributing

Please feel free to create issues or pull requests to add papers.

Welcome any discussions on video segmentation at Gitter

1. Introduction

Video segmentation, i.e., partitioning video frames into multiple segments or objects, plays a critical role in a broad range of practical applications, from enhancing visual effects in movie, to understanding scenes in autonomous driving, to virtual background creation in video conferencing. In this survey, we comprehensively review two basic lines of research — video object segmentation and video semantic segmentation — by introducing their respective task settings, background concepts, perceived need, development history, and main challenges. In particular, we review eight sub-fields as given in the following figure:

2. Deep Learning-based Video Object Segmentation

3. Deep Learning-based Video Semantic Segmentation

4. Datasets

Citation

If you find our survey and repository useful for your research, please consider citing our paper:

@article{wang2021survey,
  title={A survey on deep learning technique for video segmentation},
  author={Wang, Wenguan and Zhou, Tianfei and Porikli, Fatih and Crandall, David and Van Gool, Luc},
  journal={arXiv preprint arXiv:2107.01153},
  year={2021}
}
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Comments
  • Great work! Could you please add papers from our group.

    Great work! Could you please add papers from our group.

    Hi! Dr.Tianfei. @tfzhou .

    Could you consider adding three works from our groups on video detection/segmentation. Thanks!!

    Video Object Detection by extending DETR. TransVOD: End-to-end Video Object Detection with Spatial-Temporal Transformers PAMI-2022, paper: https://arxiv.org/abs/2201.05047 code: https://github.com/SJTU-LuHe/TransVOD

    Video Panopitc Segmentation using Query based approaches-CVPR-2022, paper: https://arxiv.org/abs/2204.04656 code: https://github.com/lxtGH/Video-K-Net

    Video Instance Segmentation using Dynamic Network, PAMI-2022, paper: https://arxiv.org/abs/2107.13155 code: https://github.com/lxtGH/TemporalPyramidRouting

    Thanks!!!

    opened by lxtGH 1
  • Please consider adding RPCM (AAAI 2022) for semi-supervised video object segmentation, thanks!

    Please consider adding RPCM (AAAI 2022) for semi-supervised video object segmentation, thanks!

    Hi, thanks for the awesome survey & repo!

    We believe a related semi-supervised video object segmentation work RPCM (AAAI2022, paper: https://arxiv.org/abs/2112.02853, code: https://github.com/JerryX1110/RPCMVOS) is missing, please consider add it, thanks!

    opened by JerryX1110 1
  • Please consider add CrossVIS (ICCV 2021) for video instance segmentation

    Please consider add CrossVIS (ICCV 2021) for video instance segmentation

    Hello, thanks for the awesome survey & repo!

    We believe a related video instance segmentation work CrossVIS (ICCV 2021, paper: https://arxiv.org/abs/2104.05970, code: https://github.com/hustvl/CrossVIS) is missing, please consider add it, thanks!

    opened by Yuxin-CV 1
Owner
Tianfei Zhou
Tianfei Zhou
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