
Bridging Text Spotting introduces a novel approach that resolves the error accumulation and suboptimal performance issues in two-step text spotting methods while retaining modularity.


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bridging-the-gap-between-two-step-and-end-to-end-text-spotting-a-novel-modular-approach


Bridging the Gap Between Two-Step and End-to-End Text Spotting: A Novel Modular Approach


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TextFormer, a novel query-based end-to-end text spotter, utilizes a multi-task model design and mixed supervision training to achieve state-of-the-art performance on scene text detection and recognition tasks.


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A Query-based End-to-End Text Spotter with Mixed Supervision for Improved Scene Text Detection and Recognition



An ensemble learning framework that combines multiple state-of-the-art scene text detection and recognition models significantly improves the performance of Vietnamese scene text spotting in complex urban settings.


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Ensemble Learning Boosts Vietnamese Scene Text Spotting in Challenging Urban Environments
