English(EN) FlexReader: Towards Adaptive Decoding Paths for Efficient Arbitrary-Length Scene Text Recognition

FlexReader 模型为高效场景文本识别提供自适应解码

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-02 05:00

研究人员推出 FlexReader，这是一种新颖的场景文本识别 (STR) 模型，旨在提高效率和灵活性。FlexReader 包含一个子字符串感知模块来识别目标子字符串，并利用多个并行解码块进行逐字符解码。一项关键创新是自适应前缀解码，它根据字符置信度动态选择解码步长，从而优化每个输入的解码路径。这种方法使单个模型能够在包括长文本、弯曲文本或被遮挡文本在内的各种基准测试中实现卓越的准确性-效率权衡，与传统的自回归方法相比，速度提高了六倍。 AI

影响该模型可以提高自动驾驶和文档分析等现实世界应用中文本识别系统的效率和准确性。

排序理由这是一篇详细介绍场景文本识别新模型和方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.CV TIER_1 English(EN) · Zhibin Ma, Pengwen Dai, Zhigang Yao, Xugong Qin, Wenqi Ren, Xiaochun Cao · 2026-11-02 05:00

FlexReader: Towards Adaptive Decoding Paths for Efficient Arbitrary-Length Scene Text Recognition

arXiv:2610.41426v1 Announce Type: new Abstract: Existing Scene Text Recognition (STR) models are inherently coupled with a specific decoding strategy by their training paradigms, limiting their flexibility in deployment across diverse recognition scenarios. In this paper, we prop…

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FlexReader: Towards Adaptive Decoding Paths for Efficient Arbitrary-Length Scene Text Recognition

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