… for scene text recognition that … attention mechanism, to the unified text recognition framework
to deal with the task of STR. We propose a five-stage model for scene text recognition, and …

… Supervised Network with Attention Mechanism (DSAN), a novel end-to-end trainable
framework for scene text recognition. It incorporates one text attention module during feature …

… character sequences. Our CAN is different from these methods; our CAN is completely built
on CNN and includes an attention mechanism… (ii) the attention mechanism is applied in every …

… The self-attention mechanism, which plays a key role in the Transformer to model long-…
text recognition. Firstly, instead of using self-attention, we use a CNN to encode input scene text …

… The attention mechanism has been extensively applied in recent years for neural machine
translation [31], [32], [33] and image caption [34], and its principle of selecting specific parts for …

… with attention mechanism produces final character sequences. Ghosh et al. [13] show
visual attention can effectively boost the performance in a LSTM-based text recognition model. …

… For multi-step attention mechanism, the attention of the first layer determines a useful … layer
that takes this information into account when computing attention. This makes it easier for the …

… -attention based scene text recognizer that (1) not only encodes the input-output attention
but also learns self-attention … [8] uses a 2D-attention mechanism to guide the encoder-decoder …

… In this work, we focus on scene text recognition, in which the texts have a wide range of …
Since a text is an important element in a scene image, solving the text recognition problem has …

… introduced the attention mechanism into the deep neural network. The attention mechanism
is … enhance the feature value extracted by CNN and increase the accuracy of recognition. …