TY  - CONF
AU  - Sergi Garcia Bordils
AU  - Dimosthenis Karatzas
AU  - Marçal Rusiñol
A2  - WACV
PY  - 2024//
TI  - STEP – Towards Structured Scene-Text Spotting
BT  - Winter Conference on Applications of Computer Vision
SP  - 883
EP  - 892
N2  - We introduce the structured scene-text spotting task, which requires a scene-text OCR system to spot text in the wild according to a query regular expression. Contrary to generic scene text OCR, structured scene-text spotting seeks to dynamically condition both scene text detection and recognition on user-provided regular expressions. To tackle this task, we propose the Structured TExt sPotter (STEP), a model that exploits the provided text structure to guide the OCR process. STEP is able to deal with regular expressions that contain spaces and it is not bound to detection at the word-level granularity. Our approach enables accurate zero-shot structured text spotting in a wide variety of real-world reading scenarios and is solely trained on publicly available data. To demonstrate the effectiveness of our approach, we introduce a new challenging test dataset that contains several types of out-of-vocabulary structured text, reflecting important reading applications of fields such as prices, dates, serial numbers, license plates etc. We demonstrate that STEP can provide specialised OCR performance on demand in all tested scenarios.
UR  - https://openaccess.thecvf.com/content/WACV2024/html/Garcia-Bordils_STEP_-_Towards_Structured_Scene-Text_Spotting_WACV_2024_paper.html
L1  - http://refbase.cvc.uab.es/files/GKR2023b.pdf
N1  - DAG
ID  - Sergi Garcia Bordils2024
ER  -