Linguistic Structure Guided Context Modeling for Referring Image Segmentation

Understand

Referring image segmentation aims to predict the foreground mask of the object referred by a natural language sentence.

• Multimodal context of the sentence is crucial to distinguish the referent from the background.
• Existing methods either insufficiently or redundantly model the multimodal context.
• To tackle this problem, we propose a "gather-propagate-distribute" scheme to model multimodal context by cross-modal interaction and implement this scheme as a novel Linguistic Structure guided Context Modeling (LSCM) module.