# HierCode: A Lightweight Hierarchical Codebook for Zero-shot Chinese Text Recognition

arXiv: https://arxiv.org/abs/2403.13761 · HTML: https://mlsanity.com/paper/2403.13761/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 30 references that are in the map.
- First posted on arXiv 20 Mar 2024.

## Builds on (most cited first, 11 of 11)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [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)
- [MaskOCR: Text Recognition with Masked Encoder-Decoder Pretraining](https://mlsanity.com/paper/2206.00311/) (2022)
- [Accurate, Data-Efficient, Unconstrained Text Recognition with Convolutional Neural Networks](https://mlsanity.com/paper/1812.11894/) (2018)
- [A Multi-Object Rectified Attention Network for Scene Text Recognition](https://mlsanity.com/paper/1901.03003/) (2019)
- [Zero-Shot Chinese Character Recognition with Stroke-Level Decomposition](https://mlsanity.com/paper/2106.11613/) (2021)
- [DenseRAN for Offline Handwritten Chinese Character Recognition](https://mlsanity.com/paper/1808.04134/) (2018)
- [Recognition of Handwritten Chinese Text by Segmentation: A Segment-annotation-free Approach](https://mlsanity.com/paper/2207.14801/) (2022)
- [Building Fast and Compact Convolutional Neural Networks for Offline Handwritten Chinese Character Recognition](https://mlsanity.com/paper/1702.07975/) (2017)
- [Towards Open-Set Text Recognition via Label-to-Prototype Learning](https://mlsanity.com/paper/2203.05179/) (2022)
- [Writer-Aware CNN for Parsimonious HMM-Based Offline Handwritten Chinese Text Recognition](https://mlsanity.com/paper/1812.09809/) (2018)

## Built on by (most cited first, 6 of 6)

- [Reviving Cultural Heritage: A Novel Approach for Comprehensive Historical Document Restoration](https://mlsanity.com/paper/2507.05108/) (2025)
- [MegaHan97K: A Large-Scale Dataset for Mega-Category Chinese Character Recognition with over 97K Categories](https://mlsanity.com/paper/2506.04807/) (2025)
- [MCCD: A Multi-Attribute Chinese Calligraphy Character Dataset Annotated with Script Styles, Dynasties, and Calligraphers](https://mlsanity.com/paper/2507.06948/) (2025)
- [CoLa: Chinese Character Decomposition with Compositional Latent Components](https://mlsanity.com/paper/2506.03798/) (2025)
- [Entropy-Aware Structural Alignment for Zero-Shot Handwritten Chinese Character Recognition](https://mlsanity.com/paper/2602.03913/) (2026)
- [Zero-Shot Chinese Character Recognition via Global-Local Dual-Branch Alignment and Hierarchical Inference](https://mlsanity.com/paper/2605.08814/) (2026)

## Abstract (arXiv)

Text recognition, especially for complex scripts like Chinese, faces unique challenges due to its intricate character structures and vast vocabulary. Traditional one-hot encoding methods struggle with the representation of hierarchical radicals, recognition of Out-Of-Vocabulary (OOV) characters, and on-device deployment due to their computational intensity. To address these challenges, we propose HierCode, a novel and lightweight codebook that exploits the innate hierarchical nature of Chinese characters. HierCode employs a multi-hot encoding strategy, leveraging hierarchical binary tree encoding and prototype learning to create distinctive, informative representations for each character. This approach not only facilitates zero-shot recognition of OOV characters by utilizing shared radicals and structures but also excels in line-level recognition tasks by computing similarity with visual features, a notable advantage over existing methods. Extensive experiments across diverse benchmarks, including handwritten, scene, document, web, and ancient text, have showcased HierCode's superiority for both conventional and zero-shot Chinese character or text recognition, exhibiting state-of-the-art performance with significantly fewer parameters and fast inference speed.