This paper aims to re-assess scene text recognition (STR) from a data-oriented perspective.
We begin by revisiting the six commonly used benchmarks in STR and observe a trend of …

The diversity in length constitutes a significant characteristic of text. Due to the long-tail
distribution of text lengths, most existing methods for scene text recognition (STR) only work …

Reading text in real-world scenarios often requires understanding the context surrounding it,
especially when dealing with poor-quality text. However, current scene text recognizers are …

This work draws attention to the large fraction of near-duplicates in the training and test sets
of datasets widely adopted in License Plate Recognition (LPR) research. These duplicates …

Abstract Open-Set Text Recognition (OSTR) is an emerging task that models the constantly
evolving char-set in open-world character recognition applications. Compared to …

开放环境下的模式识别与文字识别应用中, 新数据, 新模式和新类别不断涌现,
要求算法具备应对新类别模式的能力. 针对这一问题, 研究者们开始聚焦开放集文字识别(open …

Online product reviews are valuable resources to collect customer preferences for product
improvement. To retrieve consumer preferences, it is important to automatically extract …

We introduce the structured scene-text spotting task, which requires a scene-text OCR
system to spot text in the wild according to a query regular expression. Contrary to generic …

The adaptation capability to a wide range of domains is crucial for scene text spotting
models when deployed to real-world conditions. However, existing state-of-the-art …

Abstract License Plate Recognition (LPR) plays a critical role in various applications, such
as toll collection, parking management, and traffic law enforcement. Although LPR has …