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Neighbourhood Watch: Referring Expression Comprehension via Language-Guided Graph Attention Networks

CVPR 2019 · Graph learning › Knowledge and temporal graphs · approach: Graph-based dialog systems · 292 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
use language-guided graph attention over objects and their relationshipsLGRANs · RefCOCO testB, ground-truth regionsaccuracy: 82.39 -> 84.0Helped
use language-guided graph attention over objects and their relationshipsLGRANs · RefCOCO+ testA, ground-truth regionsaccuracy: 68.76 -> 67.6Hurt
use language-guided graph attention over objects and their relationshipsLGRANs · RefCOCO testB, automatically detected regionsaccuracy: 67.44 -> 66.4Hurt
add object-relationship edge representations to isolated node features (ablation)NodeRep · RefCOCOg valaccuracy: 67.1 -> 70.5Helped
add node attention to graph representations (ablation)GraphRep · RefCOCOg valaccuracy: 70.5 -> 72.4Helped
add edge attention to graph representations (ablation)GraphRep · RefCOCOg valaccuracy: 70.5 -> 73.9Helped
combine node attention and edge attention (ablation)LGRANs · RefCOCOg valaccuracy: 72.4 -> 75.4Helped
add object-relationship edge representations to isolated node features (ablation)NodeRep · RefCOCO valaccuracy: 77.6 -> 80.2Helped
add node attention to graph representations (ablation)GraphRep · RefCOCO valaccuracy: 80.2 -> 81.4Helped
add edge attention to graph representations (ablation)GraphRep · RefCOCO valaccuracy: 80.2 -> 81.9Helped
combine node attention and edge attention (ablation)LGRANs · RefCOCO valaccuracy: 81.9 -> 82.0Helped
add node attention to graph representations (ablation)GraphRep · RefCOCO+ testBaccuracy: 61.9 -> 64.2Helped

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