Reading Scene Text with Attention Convolutional Sequence Modeling

Understand

Reading text in the wild is a challenging task in the field of computer vision.

• Existing approaches mainly adopted Connectionist Temporal Classification (CTC) or Attention models based on Recurrent Neural Network (RNN), which is computationally expensive and hard to train.
• In this paper, we present an end-to-end Attention Convolutional Network for scene text recognition.
• Firstly, instead of RNN, we adopt the stacked convolutional layers to effectively capture the contextual dependencies of the input sequence, which is characterized by lower computational complexity and easier parallel computation.