With a PG-CTC decoder, we gather high-level character classification vectors from two-dimensional space and decode them into text symbols without NMS and RoI operations involved, which guarantees high efficiency.
Ranked #1 on Scene Text Detection on ICDAR 2015 (Accuracy metric)
Moreover, we further investigate the recognition module of our method separately, which significantly outperforms state-of-the-art methods on both regular and irregular text datasets for scene text recognition.
Recently, models based on deep neural networks have dominated the fields of scene text detection and recognition.
Ranked #3 on Scene Text Detection on ICDAR 2013
SCENE text recognition has attracted great interest from the academia and the industry in recent years owing to its importance in a wide range of applications.
Ranked #8 on Scene Text Recognition on SVT
We propose to detect scene text by localizing corner points of text bounding boxes and segmenting text regions in relative positions.
Ranked #2 on Scene Text Detection on ICDAR 2017 MLT
In this paper, we investigate the Chinese calligraphy synthesis problem: synthesizing Chinese calligraphy images with specified style from standard font(eg.
Then, we combine the word embedding of the recognized words and the deep visual features into a single representation, which is optimized by a convolutional neural network for fine-grained image classification.