SOURCE-LINKED INTELLIGENCE
InterHier: Learning Interconnected Hierarchical Semantics for Open-Vocabulary Object Detection
In this paper, we investigate the limitations of fixed, hand-crafted connectors in hierarchical semantic representations for open-vocabulary object detection. Existing methods establish semantic relationships between base categories and unseen novel categories by placing a fixed connector between adjacent super-/sub-categories. However, such fixed connectors may not optimally capture the relationships within a semantic hierarchy. To address this limitation, we propose interconnected hierarchical semantic representations (InterHier), which utilize a prepended learnable context to globally guide
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-21T02:48:16.000Z
First collected: 2026-09-23T09:51:33.063Z. This is not the publication date.