With the rise and development of deep learning, computer vision has been tremendously
transformed and reshaped. As an important research area in computer vision, scene text …

This paper analyzes, compares, and contrasts technical challenges, methods, and the
performance of text detection and recognition research in color imagery. It summarizes the …

Scene text detection has witnessed rapid development in recent years. However, there still
exists two main challenges: 1) many methods suffer from false positives in their text …

Driven by deep neural networks and large scale datasets, scene text detection methods
have progressed substantially over the past years, continuously refreshing the performance …

Arbitrary shape text detection is a challenging task due to the high variety and complexity of
scenes texts. In this paper, we propose a novel unified relational reasoning graph network …

Previous approaches for scene text detection have already achieved promising
performances across various benchmarks. However, they usually fall short when dealing …

This paper introduces a novel rotation-based framework for arbitrary-oriented text detection
in natural scene images. We present the Rotation Region Proposal Networks, which are …

Incidental scene text spotting is considered one of the most difficult and valuable challenges
in the document analysis community. Most existing methods treat text detection and …

Most state-of-the-art text detection methods are specific to horizontal Latin text and are not
fast enough for real-time applications. We introduce Segment Linking (SegLink), an oriented …

In this paper, we propose a novel method called Rotational Region CNN (R2CNN) for
detecting arbitrary-oriented texts in natural scene images. The framework is based on Faster …