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Found 3 papers, 1 papers with code
Harnessing the Power of Multi-Lingual Datasets for Pre-training: Towards Enhancing Text Spotting Performance
The adaptation capability to a wide range of domains is crucial for scene text spotting models when deployed to real-world conditions.
Diving into the Depths of Spotting Text in Multi-Domain Noisy Scenes
When used in a real-world noisy environment, the capacity to generalize to multiple domains is essential for any autonomous scene text spotting system.
FAST: Font-Agnostic Scene Text Editing
However, most of the existing STE methods show inferior editing performance because of (1) complex image backgrounds, (2) various font styles, and (3) varying word lengths within the text.
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