Work

Calibrated Degradation-Aware Augmentation for Robust Complex Street-View Text Detection

Year: 2026

Type: conference-paper

Abstract: Street-view text detection is sensitive to small text and capture degradation. This paper studies a compact detection-only pipeline combining high-resolution one-stage detectors with Calibrated Degradation-Aware Augmentation (CDAA). On ICDAR2015 validation, YOLOv8s improves from 0.7415 mAP50 at 640 to 0.8097 at 1152. Medium CDAA provides the clearest degraded-set robustness for YOLOv8s, while YOLO11s with curriculum CDAA is selected as the balanced final model. Supplementary MSRA-TD500 evidence is mixed because oriented text is simplified into horizontal boxes.

Source: International Symposium on Semiconductor and Electronic Technology (ISSET)

DOI: 10.1109/isset70600.2026.11682160

Authors: Jinghui Ma, A.Dzh.Kartanova

Institution: Kyrgyz State Technical University

Language: English

Topic: Handwritten Text Recognition Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W7212273892

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Cites: 12

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Related to: 10