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Numerical Analysis and Scientific Computing
Research Collection School Of Computing and Information Systems
Agent network; Breakings; Linear spaces; Linear time; Many to many; Novel domain; Object information; Query video; Single frames; Video objects segmentations
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Delving Deep Into Many-To-Many Attention For Few-Shot Video Object Segmentation, Haoxin Chen, Hanjie Wu, Nanxuan Zhao, Sucheng Ren, Shengfeng He
Delving Deep Into Many-To-Many Attention For Few-Shot Video Object Segmentation, Haoxin Chen, Hanjie Wu, Nanxuan Zhao, Sucheng Ren, Shengfeng He
Research Collection School Of Computing and Information Systems
This paper tackles the task of Few-Shot Video Object Segmentation (FSVOS), i.e., segmenting objects in the query videos with certain class specified in a few labeled support images. The key is to model the relationship between the query videos and the support images for propagating the object information. This is a many-to-many problem and often relies on full-rank attention, which is computationally intensive. In this paper, we propose a novel Domain Agent Network (DAN), breaking down the full-rank attention into two smaller ones. We consider one single frame of the query video as the domain agent, bridging between the support …