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Progressive Contour Regression for Arbitrary-Shape Scene Text Detection

CVPR 2021 · Detection and segmentation › CNN features · approach: Arbitrary-shape scene text detection · 161 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add oriented text proposal generation before contour regression (ablation)PCR · CTW1500F-measure: 77.2 -> 79.8Helped
Add contour information aggregation (ablation)PCR with OTPG · CTW1500F-measure: 79.8 -> 82.4Helped
Add reliable contour localization (ablation)PCR with OTPG · CTW1500F-measure: 79.8 -> 80.5Helped
Add both contour information aggregation and reliable contour localization (ablation)PCR with OTPG · CTW1500F-measure: 79.8 -> 83.7Helped
Add one iterative contour localization module (ablation)PCR · CTW1500F-measure: 83.0 -> 83.7Helped
Increase iterative contour localization modules from 1 to 2 (ablation)PCR · CTW1500F-measure: 83.7 -> 84.0Helped
Increase iterative contour localization modules from 2 to 3 (ablation)PCR · CTW1500F-measure: 84.0 -> 83.8Hurt
Use 16 local sink nodes per CIA unit rather than 0 (ablation)PCR · CTW1500F-measure: 83.2 -> 84.0Helped
Vary local sink nodes per CIA unit from 16 to 32 (ablation)PCR · CTW1500F-measure: 84.0 -> 83.6Hurt
Replace CIA units with one circular convolution layer (ablation)PCR · CTW1500F-measure: 84.0 -> 82.6Hurt
Replace circular convolution layers with standard convolution layers (ablation)PCR · CTW1500F-measure: 84.0 -> 83.6Hurt
Use the proposed DLA-34 PCR configuration with external pretrainingPCR · CTW1500F-measure: 84.0 -> 84.7Helped

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