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Scene Text Detection with Supervised Pyramid Context Network

AAAI 2019 · Detection and segmentation › CNN features · approach: Arbitrary-shape scene text detection · 242 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add the Text Context Module (ablation)Mask R-CNN · ICDAR2017 MLT validationPrecision: 76.2 -> 80.3Helped
Add the Text Context Module (ablation)Mask R-CNN · ICDAR2017 MLT validationRecall: 73.4 -> 73.4No clear effect
Add the Text Context Module (ablation)Mask R-CNN · ICDAR2017 MLT validationF-measure: 74.7 -> 76.8Helped
Add Re-Score to the Text Context Module (ablation)Mask R-CNN with Text Context Module · ICDAR2017 MLT validationPrecision: 80.3 -> 84.2Helped
Add Re-Score to the Text Context Module (ablation)Mask R-CNN with Text Context Module · ICDAR2017 MLT validationRecall: 73.4 -> 73.4No clear effect
Add Re-Score to the Text Context Module (ablation)Mask R-CNN with Text Context Module · ICDAR2017 MLT validationF-measure: 76.8 -> 78.5Helped
Use multi-scale testing instead of single-scale testingSPCNET · ICDAR2017 MLT testF-measure: 70.0 -> 74.1Helped
Add Text Context Module and Re-ScoreMask R-CNN · ICDAR2015F-measure: 85.5 -> 87.2Helped
Add Text Context Module and Re-ScoreMask R-CNN · ICDAR2013F-measure: 89.6 -> 92.1Helped
Add Text Context Module and Re-ScoreMask R-CNN · Total-TextF-measure: 81.0 -> 82.9Helped

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