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DeepSolo: Let Transformer Decoder With Explicit Points Solo for Text Spotting

CVPR 2023 · Detection and segmentation › CNN features · approach: Arbitrary-shape scene text detection · 128 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add TextOCR to pretraining data (ablation)DeepSolo (ResNet-50) · Total-Text testE2E None F1: 79.65 -> 82.54Helped
Add MLT17, IC13, and IC15 real training data (ablation)DeepSolo (ResNet-50) · Total-Text testE2E None F1: +0.82%Helped
Remove the text matching criterion (ablation)DeepSolo · Total-Text testE2E None F1: 78.83 -> 77.85Hurt
Share point embeddings across instances (ablation)DeepSolo · Total-Text testE2E None F1: 78.83 -> 77.58Hurt
Increase maximum recognition length from 25 to 50 (ablation)DeepSolo (ResNet-50, Synth150K) · CTW1500 testE2E None: 60.1 -> 63.2Helped
Replace ResNet-50 with ViTAEv2-S (ablation)DeepSolo · Total-Text testE2E None F1: 79.65 -> 81.79Helped
Set text loss weight to 0.25 instead of 0.5 (ablation)DeepSolo · Total-Text testE2E None F1: 78.83 -> 76.68Hurt
Set text loss weight to 0.75 instead of 0.5 (ablation)DeepSolo · Total-Text testE2E None F1: 78.83 -> 78.82No clear effect
Use line annotations instead of full polygon annotations (ablation)DeepSolo · Total-Text testE2E None: 81.6% vs. 82.5%No clear effect

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