STN-OCR: A single Neural Network for Text Detection and Text Recognition

This Page grants access to our purpose build SVHN datasets and trained models, that we created for our experiments described in (the code is available here).

SVHN Experiments

In the attachment you can find two datasets we used for our training on SVHN data. We created these datasets using the original SVHN dataset images and our scripts that can be found here. You can also find prepared evaluation data in the evaluation folder.

Besides these datasets you can also find several models

  1. a model trained on original SVHN data
  2. a model trained on SVHN data evenly distributed on a grid
  3. a model trained on SVHN house number crops randomly placed in an image

Text Recognition

We can, unfortunately, not provide the dataset we used for these experiments, as it is too large and we have not been able to find a suitable place to host it. If you know a good place, please let us know, by opening an issue in our Github repository.

But the file contains a model trained for performing text recognition on already cropped scene text images. This model can be used with script from our repository on Github.


For our training we used the standard FSNS dataset. Please this file, for downloading and preparing the FSNS dataset for usage with our system.

The file contains our best performing model trained on the FSNS dataset. This model can be used with the script from our repository.

Supplementary Material

In the paper we mentioned some videos that show how the model learns to find the regions of text and the pretraining steps that we performed. You can find the videos in