Segment objects in videos using pyramid architecture and improved dataset with PAOT
Segment objects in videos using pyramid architecture and improved dataset with PAOT
Video Object Segmentation in Panoptic Wild Scenes
arXiv paper abstract https://arxiv.org/abs/2305.04470
arXiv PDF paper https://arxiv.org/pdf/2305.04470.pdf
... introduce semi-supervised video object segmentation (VOS) to panoptic wild scenes and ... large-scale benchmark as well as a baseline method ...
Previous benchmarks for VOS with sparse annotations are not sufficient ... to process all possible objects in real-world scenarios.
... new benchmark (VIPOSeg) contains exhaustive object annotations and covers various real-world object categories ... divided into subsets of thing/stuff and seen/unseen classes
... propose a strong baseline method named panoptic object association with transformers (PAOT), which uses panoptic identification to associate objects with a pyramid architecture on multiple scales.
.. show ... VIPOSeg can not only boost the performance of VOS models by panoptic training but also evaluate them comprehensively in panoptic scenes.
Previous methods for ... VOS ... need to improve in performance and efficiency ... with panoptic scenes, while ... PAOT achieves SOTA performance with good efficiency on VIPOSeg and previous VOS benchmarks ...
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