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Found 4 papers, 3 papers with code
Dataset and Benchmark for Urdu Natural Scenes Text Detection, Recognition and Visual Question Answering
The development of Urdu scene text detection, recognition, and Visual Question Answering (VQA) technologies is crucial for advancing accessibility, information retrieval, and linguistic diversity in digital content, facilitating better understanding and interaction with Urdu-language visual data.
The First Swahili Language Scene Text Detection and Recognition Dataset
We propose a comprehensive dataset of Swahili scene text images and evaluate the dataset on different scene text detection and recognition models.
Enhancing Scene Text Detectors with Realistic Text Image Synthesis Using Diffusion Models
We contend that one main limitation of existing generation methods is the insufficient integration of foreground text with the background.
Toward Understanding WordArt: Corner-Guided Transformer for Scene Text Recognition
Thirdly, we utilize Transformer to learn the global feature on image-level and model the global relationship of the corner points, with the assistance of a corner-query cross-attention mechanism.
