mlsanityData to 7 Oct 2026

A3S: Adversarial learning of semantic representations for Scene-Text Spotting

arXiv 2302.10641 ↗First posted 21 Feb 2023cs.CVcited by 6

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Abstract (arXiv)

Scene-text spotting is a task that predicts a text area on natural scene images and recognizes its text characters simultaneously. It has attracted much attention in recent years due to its wide applications. Existing research has mainly focused on improving text region detection, not text recognition. Thus, while detection accuracy is improved, the end-to-end accuracy is insufficient. Texts in natural scene images tend to not be a random string of characters but a meaningful string of characters, a word. Therefore, we propose adversarial learning of semantic representations for scene text spotting (A3S) to improve end-to-end accuracy, including text recognition. A3S simultaneously predicts semantic features in the detected text area instead of only performing text recognition based on existing visual features. Experimental results on publicly available datasets show that the proposed method achieves better accuracy than other methods.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 18 of its 26 references that are in the map. First posted on arXiv 21 Feb 2023.

Builds on

18 of 26 references.

References · 18

  1. 2017Attention Is All You Needcited by 59,932
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  3. 2022Generative Adversarial Networkscited by 5,603
  4. 2016Feature Pyramid Networks for Object Detectioncited by 5,021
  5. 2015An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognitioncited by 519
  6. 2017EAST: An Efficient and Accurate Scene Text Detectorcited by 248
  7. 2019ICDAR2019 Robust Reading Challenge on Multi-lingual Scene Text Detection and Recognition -- RRC-MLT-2019cited by 138
  8. 2016TextBoxes: A Fast Text Detector with a Single Deep Neural Networkcited by 119
  9. 2020Mask TextSpotter v3: Segmentation Proposal Network for Robust Scene Text Spottingcited by 114
  10. 2018FOTS: Fast Oriented Text Spotting with a Unified Networkcited by 109
  11. 2021ABCNet v2: Adaptive Bezier-Curve Network for Real-time End-to-end Text Spottingcited by 84
  12. 2022SwinTextSpotter: Scene Text Spotting via Better Synergy between Text Detection and Text Recognitioncited by 70
6 more
  1. 2022Text Spotting Transformerscited by 70
  2. 2017Towards End-to-end Text Spotting with Convolutional Recurrent Neural Networkscited by 56
  3. 2020MANGO: A Mask Attention Guided One-Stage Scene Text Spottercited by 51
  4. 2021PGNet: Real-time Arbitrarily-Shaped Text Spotting with Point Gathering Networkcited by 49
  5. 2022GLASS: Global to Local Attention for Scene-Text Spottingcited by 34
  6. 2021Decoupling Visual-Semantic Feature Learning for Robust Scene Text Recognitioncited by 2

Built on by

Cited by year

Citing papers per year: 2023: 3; 2024: 3.

6 papers.

  1. 2023DTrOCR: Decoder-only Transformer for Optical Character Recognitioncited by 40
  2. 2024LayoutLLM: Large Language Model Instruction Tuning for Visually Rich Document Understandingcited by 24
  3. 2023DiffusionSTR: Diffusion Model for Scene Text Recognitioncited by 7
  4. 2023RL-LOGO: Deep Reinforcement Learning Localization for Logo Recognitioncited by 4
  5. 2024JSTR: Judgment Improves Scene Text Recognitioncited by 1
  6. 2024JaPOC: Japanese Post-OCR Correction Benchmark using Voucherscited by 1