Titlebook: Document Analysis and Recognition - ICDAR 2024; 18th International C Elisa H. Barney Smith,Marcus Liwicki,Liangrui Peng Conference proceedi

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Adaptive Scaling and?Refined Pyramid Feature Fusion Network for?Scene Text Segmentationn pixel-level foreground text masks from scene images. In this paper, we adaptively resize the input images to their optimal scales and propose the Refined Pyramid Feature Fusion Network (RPFF-Net) for robust scene text segmentation. To address the issue of inconsistent text scaling, we propose an a

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Knowledge Mining of?Scene Text for?Referring Expression Comprehensionural language expression. Existing methods predominantly focus on the literal interpretation of scene text. Such methods often fall short when the scene text has a tenuous connection to the objects in the referring expressions. To address this limitation, we introduce a novel approach that leverages

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Indic Scene Text on?the?Roadsidecenario differs for Indian languages, where the complexities in syntax and semantics have posed?many challenges, resulting in limited datasets and comparatively?less research in this domain. Overcoming these challenges is crucial?for advancing scene text recognition in Indian languages. Although a?f

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Analytische Berechnung der Spannungens the development and assessment of methods that can handle diverse text layouts, intricate shapes, and non-standard orientations commonly encountered in real-world scenarios. Besides, the?VQA annotations make it the first benchmark for the Urdu Text?VQA method, which can prompt the development of Urdu scene?text understanding.

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