Textual visual semantic dataset for text spotting
Document typeConference report
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Rights accessOpen Access
Text Spotting in the wild consists of detecting and recognizing text appearing in images (e.g. signboards, traffic signals or brands in clothing or objects). This is a challenging problem due to the complexity of the context where texts appear (uneven backgrounds, shading, occlusions, perspective distortions, etc.). Only a few approaches try to exploit the relation between text and its surrounding environment to better recognize text in the scene. In this paper, we propose a visual context dataset1 for Text Spotting in the wild, where the publicly available dataset COCO-text  has been extended with information about the scene (such as objects and places appearing in the image) to enable researchers to include semantic relations between texts and scene in their Text Spotting systems, and to offer a common framework for such approaches. For each text in an image, we extract three kinds of context information: objects in the scene, image location label and a textual image description (caption). We use state-of-the-art out-of-the-box available tools to extract this additional information. Since this information has textual form, it can be used to leverage text similarity or semantic relation methods into Text Spotting systems, either as a post-processing or in an end-to-end training strategy.
CitationSabir, A.; Moreno-Noguer, F.; Padró, L. Textual visual semantic dataset for text spotting. A: IEEE Conference on Computer Vision and Pattern Recognition. "2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops: Virtual, 14-19 June 2020: proceedings". Institute of Electrical and Electronics Engineers (IEEE), 2020, p. 2306-2315. ISBN 978-1-7281-9360-1. DOI 10.1109/CVPRW50498.2020.00279.
- GPLN - Grup de Processament del Llenguatge Natural - Ponències/Comunicacions de congressos 
- Departament de Ciències de la Computació - Ponències/Comunicacions de congressos [1.151]
- Doctorat en Intel·ligència Artificial - Ponències/Comunicacions de congressos 
- ROBiri - Grup de Robòtica de l'IRI - Ponències/Comunicacions de congressos 
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