MOSE (Complex Video Object Segmentation)
Introduced by Ding et al. in MOSE: A New Dataset for Video Object Segmentation in Complex Scenes
CoMplex video Object SEgmentation (MOSE) is a dataset to study the tracking and segmenting objects in complex environments. MOSE contains 2,149 video clips and 5,200 objects from 36 categories, with 431,725 high-quality object segmentation masks. The most notable feature of MOSE dataset is complex scenes with crowded and occluded objects.
Source: MOSE: A New Dataset for Video Object Segmentation in Complex ScenesBenchmarks
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Papers
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