Decoupling What to Count and Where to See for Referring Expression Counting
NeutralArtificial Intelligence
A new paper on arXiv discusses Referring Expression Counting (REC), which aims to improve object counting by focusing on subclass-level details rather than just class-level features. This research is significant because it addresses a common oversight in the field: the reliance on class-representative locations for annotations, which can limit the effectiveness of models in recognizing distinguishing attributes. By refining how we count and categorize objects, this work could enhance various applications in computer vision and artificial intelligence.
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