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Found 5 papers, 2 papers with code
End-to-End Video Text Spotting with Transformer
Recent video text spotting methods usually require the three-staged pipeline, i. e., detecting text in individual images, recognizing localized text, tracking text streams with post-processing to generate final results.
A Bilingual, OpenWorld Video Text Dataset and End-to-end Video Text Spotter with Transformer
Most existing video text spotting benchmarks focus on evaluating a single language and scenario with limited data.
Towards Spatio-Temporal Video Scene Text Detection via Temporal Clustering
With only bounding-box annotations in the spatial domain, existing video scene text detection (VSTD) benchmarks lack temporal relation of text instances among video frames, which hinders the development of video text-related applications.
Explore Faster Localization Learning For Scene Text Detection
Generally pre-training and long-time training computation are necessary for obtaining a good-performance text detector based on deep networks.
Uni-Removal: A Semi-Supervised Framework for Simultaneously Addressing Multiple Degradations in Real-World Images
In this paper, we introduce Uni-Removal, a twostage semi-supervised framework for addressing the removal of multiple degradations in real-world images using a unified model and parameters.
