The 1st MeViS 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 referring video segmentation with motion expressions, i.e., segmenting objects in video content based on a sentence describing the motion of the objects. MeViS contains 2,006 video clips and 443k high-quality object segmentation masks, with 28,570 sentences indicating 8,171 objects in complex environments. The goal of MeViS dataset is to provide a platform that enables the development of effective language-guided video segmentation algorithms that leverage motion expressions as a primary cue for object segmentation in complex video scenes. 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 |
Shuting He Nanyang Technological University |
Xudong Jiang Nanyang Technological University |
Chen Change Loy Nanyang Technological University |
@inproceedings{MeViS,
title={{MeViS}: A Large-scale Benchmark for Video Segmentation with Motion Expressions},
author={Ding, Henghui and Liu, Chang and He, Shuting and Jiang, Xudong and Loy, Chen Change},
booktitle={ICCV},
year={2023}
}
MeViS is licensed under a CC BY-NC-SA 4.0 License. The data of MeViS is released for non-commercial research purpose only.
