# Word length-aware text spotting: Enhancing detection and recognition in dense text image

arXiv: https://arxiv.org/abs/2312.15690 · HTML: https://mlsanity.com/paper/2312.15690/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 33 of its 43 references that are in the map.
- First posted on arXiv 25 Dec 2023.

## Builds on (most cited first, 30 of 33)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Swin Transformer: Hierarchical Vision Transformer using Shifted Windows](https://mlsanity.com/paper/2103.14030/) (2021)
- [End-to-End Object Detection with Transformers](https://mlsanity.com/paper/2005.12872/) (2020)
- [V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation](https://mlsanity.com/paper/1606.04797/) (2016)
- [Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regression](https://mlsanity.com/paper/1902.09630/) (2019)
- [EfficientDet: Scalable and Efficient Object Detection](https://mlsanity.com/paper/1911.09070/) (2019)
- [An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition](https://mlsanity.com/paper/1507.05717/) (2015)
- [Sparse R-CNN: End-to-End Object Detection with Learnable Proposals](https://mlsanity.com/paper/2011.12450/) (2020)
- [Pix2seq: A Language Modeling Framework for Object Detection](https://mlsanity.com/paper/2109.10852/) (2021)
- [Character Region Awareness for Text Detection](https://mlsanity.com/paper/1904.01941/) (2019)
- [EAST: An Efficient and Accurate Scene Text Detector](https://mlsanity.com/paper/1704.03155/) (2017)
- [Mask TextSpotter: An End-to-End Trainable Neural Network for Spotting Text with Arbitrary Shapes](https://mlsanity.com/paper/1908.08207/) (2019)
- [ABCNet: Real-time Scene Text Spotting with Adaptive Bezier-Curve Network](https://mlsanity.com/paper/2002.10200/) (2020)
- [TextBoxes: A Fast Text Detector with a Single Deep Neural Network](https://mlsanity.com/paper/1611.06779/) (2016)
- [TextBoxes++: A Single-Shot Oriented Scene Text Detector](https://mlsanity.com/paper/1801.02765/) (2018)
- [Mask TextSpotter v3: Segmentation Proposal Network for Robust Scene Text Spotting](https://mlsanity.com/paper/2007.09482/) (2020)
- [FOTS: Fast Oriented Text Spotting with a Unified Network](https://mlsanity.com/paper/1801.01671/) (2018)
- [Detecting Text in Natural Image with Connectionist Text Proposal Network](https://mlsanity.com/paper/1609.03605/) (2016)
- [ABCNet v2: Adaptive Bezier-Curve Network for Real-time End-to-end Text Spotting](https://mlsanity.com/paper/2105.03620/) (2021)
- [Recursive Recurrent Nets with Attention Modeling for OCR in the Wild](https://mlsanity.com/paper/1603.03101/) (2016)
- [SwinTextSpotter: Scene Text Spotting via Better Synergy between Text Detection and Text Recognition](https://mlsanity.com/paper/2203.10209/) (2022)
- [Text Spotting Transformers](https://mlsanity.com/paper/2204.01918/) (2022)
- [PAN++: Towards Efficient and Accurate End-to-End Spotting of Arbitrarily-Shaped Text](https://mlsanity.com/paper/2105.00405/) (2021)
- [Towards End-to-end Text Spotting with Convolutional Recurrent Neural Networks](https://mlsanity.com/paper/1707.03985/) (2017)
- [Text Perceptron: Towards End-to-End Arbitrary-Shaped Text Spotting](https://mlsanity.com/paper/2002.06820/) (2020)
- [MANGO: A Mask Attention Guided One-Stage Scene Text Spotter](https://mlsanity.com/paper/2012.04350/) (2020)
- [PGNet: Real-time Arbitrarily-Shaped Text Spotting with Point Gathering Network](https://mlsanity.com/paper/2104.05458/) (2021)
- [Arbitrary Shape Scene Text Detection with Adaptive Text Region Representation](https://mlsanity.com/paper/1905.05980/) (2019)
- [SPTS: Single-Point Text Spotting](https://mlsanity.com/paper/2112.07917/) (2021)
- [Turning a CLIP Model into a Scene Text Detector](https://mlsanity.com/paper/2302.14338/) (2023)

## Abstract (arXiv)

Scene text spotting is essential in various computer vision applications, enabling extracting and interpreting textual information from images. However, existing methods often neglect the spatial semantics of word images, leading to suboptimal detection recall rates for long and short words within long-tailed word length distributions that exist prominently in dense scenes. In this paper, we present WordLenSpotter, a novel word length-aware spotter for scene text image detection and recognition, improving the spotting capabilities for long and short words, particularly in the tail data of dense text images. We first design an image encoder equipped with a dilated convolutional fusion module to integrate multiscale text image features effectively. Then, leveraging the Transformer framework, we synergistically optimize text detection and recognition accuracy after iteratively refining text region image features using the word length prior. Specially, we design a Spatial Length Predictor module (SLP) using character count prior tailored to different word lengths to constrain the regions of interest effectively. Furthermore, we introduce a specialized word Length-aware Segmentation (LenSeg) proposal head, enhancing the network's capacity to capture the distinctive features of long and short terms within categories characterized by long-tailed distributions. Comprehensive experiments on public datasets and our dense text spotting dataset DSTD1500 demonstrate the superiority of our proposed methods, particularly in dense text image detection and recognition tasks involving long-tailed word length distributions encompassing a range of long and short words.