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Research map / Vision-language and multimodal / Human and embodied modeling

Scene Text Recognition from Two-Dimensional Perspective

AAAI 2019 · Vision-language and multimodal › Human and embodied modeling · approach: Language-grounded scene text and structure · 262 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Represent and classify characters in two-dimensional pixel space instead of compressing text features into a one-dimensional sequenceCA-FCN · CUTEaccuracy: 3.1 percents improvementHelped
Fine-tune with extra synthetic dataCA-FCN · SVT (50-word lexicon)accuracy: 98.5 -> 98.8Helped
Add character attention (ablation)CA-FCN baseline · IIITaccuracy: 90.5 -> 91.0Helped
Add character attention (ablation)CA-FCN baseline · IIIT-paccuracy: 87.0 -> 86.7Hurt
Add deformable convolution (ablation)CA-FCN baseline · IIIT-paccuracy: 87.0 -> 87.6Helped
Add character attention and deformable convolution (ablation)CA-FCN baseline · IIIT-paccuracy: 87.0 -> 89.3Helped
Add deformable convolution (ablation)CA-FCN baseline · IC13-exaccuracy: 83.2 -> 87.4Helped
Add character attention and deformable convolution (ablation)CA-FCN baseline · IC13-exaccuracy: 83.2 -> 87.2Helped
Add deformable convolution (ablation)CA-FCN baseline · IC13-r-exaccuracy: 82.3 -> 84.2Helped
Use a two-dimensional character prediction approach rather than sequence-based recognitionCA-FCN · IIIT-paccuracy gap ratio: 6.4% -> 2.6%Helped

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