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Shape Robust Text Detection With Progressive Scale Expansion Network

CVPR 2019 · Detection and segmentation › CNN features · approach: Arbitrary-shape scene text detection · 869 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use multiple kernel scales (n=6, m=0.5) instead of one full-scale segmentation mask (ablation)PSENet-1s · ICDAR 2015 testF-measure: 68.56 -> 87.08Helped
Increase the number of kernel scales from 2 toward 6 while keeping m=0.5 (ablation)PSENet-1s · ICDAR 2015 testF-measureHelped
Increase the number of kernel scales beyond 6 while keeping m=0.5 (ablation)PSENet-1s · ICDAR 2015 testF-measureNo clear effect
Choose a minimal scale m that is too large or too small (ablation)PSENet-1s with n=6 · ICDAR 2015 testF-measureHurt
Use 2s instead of 1s output-map scale (ablation)PSENet · ICDAR 2015 testF-measure: 87.08 -> 87.21Helped
Use 4s instead of 1s output-map scale (ablation)PSENet · ICDAR 2015 testF-measure: 87.08 -> 85.88Hurt
Use 2s instead of 1s output-map scale (ablation)PSENet · ICDAR 2017 MLT testF-measure: 72.45 -> 72.40No clear effect
Use 4s instead of 1s output-map scale (ablation)PSENet · ICDAR 2017 MLT testF-measure: 72.45 -> 71.52Hurt
Use 2s instead of 1s output-map scale (ablation)PSENet · SCUT-CTW1500 testF-measure: 81.17 -> 80.60Hurt
Use 4s instead of 1s output-map scale (ablation)PSENet · SCUT-CTW1500 testF-measure: 81.17 -> 79.29Hurt

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