MOSE Dataset Examples
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The 1st MOSE challenge will be held in conjunction with CVPR 2024 PVUW Workshop in Seattle, USA. In this edition of the workshop and challenge, we focus on video object segmentation under complex environments. MOSE contains 2,149 video clips and 5,200 objects, with 431,725 high-quality object segmentation masks. The video resolution is 1920×1080 and the video lengths are 5 to 60 seconds in general. The most notable feature of MOSE is complex scenes, including the disappearance-reappearance of objects, inconspicuous small objects, heavy occlusions, crowded environments, etc. The goal of MOSE dataset is to provide a platform that promotes the development of more comprehensive and robust video object segmentation algorithms. The workshop will culminate in a round table discussion, in which speakers will debate the future of video object representations.
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| Henghui Ding Primary Organizer |
Chang Liu Primary Organizer |
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| Shuting He Nanyang Technological University |
Xudong Jiang Nanyang Technological University |
Philip H.S. Torr University of Oxford |
Song Bai ByteDance |
@inproceedings{MOSE,
title={{MOSE}: A New Dataset for Video Object Segmentation in Complex Scenes},
author={Ding, Henghui and Liu, Chang and He, Shuting and Jiang, Xudong and Torr, Philip HS and Bai, Song},
booktitle={ICCV},
year={2023}
}
MOSE is licensed under a CC BY-NC-SA 4.0 License. The data of MOSE is released for non-commercial research purpose only.
