# Focus-Enhanced Scene Text Recognition with Deformable Convolutions

arXiv: https://arxiv.org/abs/1908.10998 · HTML: https://mlsanity.com/paper/1908.10998/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Aug 2019.

## Built on by (most cited first, 1 of 1)

- [Unified Chinese License Plate Detection and Recognition with High Efficiency](https://mlsanity.com/paper/2205.03582/) (2022)

## Abstract (arXiv)

Recently, scene text recognition methods based on deep learning have sprung up in computer vision area. The existing methods achieved great performances, but the recognition of irregular text is still challenging due to the various shapes and distorted patterns. Consider that at the time of reading words in the real world, normally we will not rectify it in our mind but adjust our focus and visual fields. Similarly, through utilizing deformable convolutional layers whose geometric structures are adjustable, we present an enhanced recognition network without the steps of rectification to deal with irregular text in this work. A number of experiments have been applied, where the results on public benchmarks demonstrate the effectiveness of our proposed components and shows that our method has reached satisfactory performances. The code will be publicly available at https://github.com/Alpaca07/dtr soon.