Skip to content
Watch, Attend and Parse for Handwritten Mathematical Expression Recognition
Python Shell
Branch: master
Clone or download
Latest commit 92d416a Aug 27, 2018
Type Name Latest commit message Commit time
Failed to load latest commit information.
DenseNet 12G GPU description Apr 15, 2018
VGG init commit Mar 7, 2018
data CROHME 2016 image Aug 27, 2018
.gitignore Initial commit Feb 28, 2018 WAP clone 1 Feb 28, 2018


This repository contains the source code for WAP introduced in the following papers:

Here, VGG contains the code that employs VGG architecture as the watcher, DenseNet contains the code that employs DenseNet as the watcher.



If you find WAP useful in your research, please consider citing:

  title={Watch, attend and parse: An end-to-end neural network based approach to handwritten mathematical expression recognition},
  author={Zhang, Jianshu and Du, Jun and Zhang, Shiliang and Liu, Dan and Hu, Yulong and Hu, Jinshui and Wei, Si and Dai, Lirong},
  journal={Pattern Recognition},

  title={Multi-Scale Attention with Dense Encoder for Handwritten Mathematical Expression Recognition},
  author={Zhang, Jianshu and Du, Jun and Dai, Lirong},
  journal={arXiv preprint arXiv:1801.03530},


xysszjs at
West campus of University of Science and Technology of China
Any discussions, suggestions and questions are welcome!

You can’t perform that action at this time.