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Towards Accurate Scene Text Recognition With Semantic Reasoning Networks

CVPR 2020 · Vision-language and multimodal › Human and embodied modeling · approach: Language-grounded scene text and structure · 382 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add transformer units to the backbone (ablation)SRN · IC13, IC15, IIIT5K, SVT, SVTP, CUTEaccuracy: 90.0 -> 93.0 (IC13); 80.5 -> 83.6 (CUTE)Helped
Add character reading order information to parallel visual attention (ablation)SRN · IC13, IC15, IIIT5K, SVT, SVTP, CUTEaccuracy: 93.0 -> 93.2 (IC13); 79.8 -> 79.4 (SVTP)Mixed
Add GSRM (ablation)SRN · IIIT5K and IC15accuracy: 92.3 -> 94.8 (IIIT5K); 77.5 -> 82.7 (IC15)Helped
Use 4 rather than 6 transformer units in GSRM (ablation)SRN · IC15accuracy: 82.7 -> 82.7No clear effect
Use global multi-way semantic reasoning instead of forward one-way reasoning (ablation)SRN · IC13accuracy: 94.7 -> 95.5Helped
Use global multi-way semantic reasoning instead of backward one-way reasoning (ablation)SRN · IC13accuracy: 94.5 -> 95.5Helped
Replace gated fusion with addition (ablation)SRN visual-semantic fusion decoder · IC13accuracy: 95.5 -> 95.2Hurt
Replace gated fusion with concatenation (ablation)SRN visual-semantic fusion decoder · IC13accuracy: 95.5 -> 95.0Hurt
Replace gated fusion with dot-product fusion (ablation)SRN visual-semantic fusion decoder · IC13accuracy: 95.5 -> 94.8Hurt
Add GSRM to SRN (ablation)SRN · TRW-T and TRW-Lcharacter-level accuracy: 80.6 -> 85.5 (TRW-T); 77.5 -> 84.3 (TRW-L)Helped
Use parallel semantic reasoning rather than serial attention decodingSRN · IC15 and TRW-Linference time: 191.6ms; 216.8msHelped

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