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DPText-DETR: Towards Better Scene Text Detection with Dynamic Points in Transformer

AAAI 2023 · Detection and segmentation › CNN features · approach: Arbitrary-shape scene text detection · 118 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Replace box-based positional queries with explicit sampled points and update points across decoder layers (ablation)DPText-DETR · Total-TextF-measure: 83.90 -> 85.15Helped
Add positional label form (ablation)DPText-DETR · Rot.Total-TextF-measure: 71.37 -> 74.11Helped
Add positional label form (ablation)DPText-DETR · Inverse-TextF-measure: 78.71 -> 81.20Helped
Add positional label form (ablation)DPText-DETR · Total-TextF-measure: 84.71 -> 84.77Helped
Add EPQM to positional-label model (ablation)DPText-DETR · Total-TextF-measure: 84.77 -> 85.80Helped
Add EPQM to positional-label model (ablation)DPText-DETR · Rot.Total-TextF-measure: 74.11 -> 73.82Hurt
Add EPQM to positional-label model (ablation)DPText-DETR · Inverse-TextF-measure: 81.20 -> 80.86Hurt
Add EFSA (ablation)DPText-DETR · Total-TextF-measure: 85.28 -> 86.17Helped
Add EFSA (ablation)DPText-DETR · Total-Text with 25% training dataF-measure: 58.54 -> 70.49Helped
Add EFSA (ablation)DPText-DETR · Inverse-Text with 25% training dataF-measure: 52.32 -> 60.15Helped
Use rotation augmentation (ablation)DPText-DETR · Rot.Total-TextF-measure: 70.02 -> 83.99Helped
Use EFSA with circular convolution for Bezier control points (ablation)Bezier variant detector · Total-TextF-measure: 85.80 -> 85.21Hurt

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