Minghui Liao

6.5k total citations · 4 hit papers
20 papers, 2.3k citations indexed

About

Minghui Liao is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Artificial Intelligence. According to data from OpenAlex, Minghui Liao has authored 20 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Computer Vision and Pattern Recognition, 10 papers in Media Technology and 4 papers in Artificial Intelligence. Recurrent topics in Minghui Liao's work include Handwritten Text Recognition Techniques (16 papers), Vehicle License Plate Recognition (9 papers) and Advanced Image and Video Retrieval Techniques (7 papers). Minghui Liao is often cited by papers focused on Handwritten Text Recognition Techniques (16 papers), Vehicle License Plate Recognition (9 papers) and Advanced Image and Video Retrieval Techniques (7 papers). Minghui Liao collaborates with scholars based in China, India and United Kingdom. Minghui Liao's co-authors include Xiang Bai, Baoguang Shi, Cong Yao, Zhaoyi Wan, Wenyu Liu, Xinggang Wang, Kai Chen, Pengyuan Lyu, Minghang He and Mingkun Yang and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and Pattern Recognition.

In The Last Decade

Minghui Liao

19 papers receiving 2.2k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

TextBoxes++: A Single-Shot Oriented Scene Text Detector

2018 559 citations Minghui Liao, Baoguang Shi et al. IEEE Transactions on Image Processing profile →
TextBoxes: A Fast Text Detector with a Single Deep Neural Network

2017 539 citations Minghui Liao, Baoguang Shi et al. Proceedings of the AAAI Conference on Artificial Intelligence profile →
Real-Time Scene Text Detection with Differentiable Binarization

2020 414 citations Minghui Liao, Zhaoyi Wan et al. Proceedings of the AAAI Conference on Artificial Intelligence profile →
Real-Time Scene Text Detection With Differentiable Binarization and Adaptive Scale Fusion

2022 181 citations Minghui Liao, Zhaoyi Wan et al. IEEE Transactions on Pattern Analysis and Machine Intelligence profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Minghui Liao China	11	2.2k	1.1k	390	70	70	20	2.3k
Junyu Han China	20	1.6k 0.7×	494 0.4×	421 1.1×	42 0.6×	41 0.6×	33	1.8k
Lukáš Neumann Czechia	12	2.1k 1.0×	1.0k 0.9×	346 0.9×	62 0.9×	16 0.2×	16	2.2k
Ehsanollah Kabir Iran	19	810 0.4×	286 0.3×	280 0.7×	54 0.8×	107 1.5×	89	1.1k
Mingkun Yang China	11	1.1k 0.5×	350 0.3×	220 0.6×	27 0.4×	20 0.3×	25	1.2k
Carlos Hernández Mexico	14	936 0.4×	132 0.1×	155 0.4×	27 0.4×	23 0.3×	35	1.2k
Mohand Saïd Allili Canada	16	482 0.2×	188 0.2×	177 0.5×	45 0.6×	180 2.6×	54	756
Ni Zhang China	13	495 0.2×	100 0.1×	171 0.4×	97 1.4×	36 0.5×	55	986
Sam S. Tsai United States	23	2.0k 0.9×	269 0.2×	173 0.4×	59 0.8×	17 0.2×	57	2.2k
Dar-Shyang Lee United States	11	856 0.4×	114 0.1×	222 0.6×	33 0.5×	20 0.3×	22	1.0k

Countries citing papers authored by Minghui Liao

Since Specialization

Citations

This map shows the geographic impact of Minghui Liao's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Minghui Liao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Minghui Liao more than expected).

Fields of papers citing papers by Minghui Liao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Minghui Liao. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Minghui Liao. The network helps show where Minghui Liao may publish in the future.

Co-authorship network of co-authors of Minghui Liao

This figure shows the co-authorship network connecting the top 25 collaborators of Minghui Liao. A scholar is included among the top collaborators of Minghui Liao based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Minghui Liao. Minghui Liao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Liao, Minghui, Guojia Wan, Wenbin Hu, & Boxue Du. (2025). Building connectome analysis tools with representation learning on neuronal skeleton and circuit topology. Neural Networks. 190. 107603–107603.

Yang, Mingkun, et al.. (2024). Sequential visual and semantic consistency for semi-supervised text recognition. Pattern Recognition Letters. 178. 174–180. 2 indexed citations

Liao, Minghui, Guojia Wan, & Bo Du. (2024). Joint Learning Neuronal Skeleton and Brain Circuit Topology with Permutation Invariant Encoders for Neuron Classification. Proceedings of the AAAI Conference on Artificial Intelligence. 38(1). 197–205. 2 indexed citations

Zhang, Ziyin, Ning Lü, Minghui Liao, et al.. (2024). Self-Distillation Regularized Connectionist Temporal Classification Loss for Text Recognition: A Simple Yet Effective Approach. Proceedings of the AAAI Conference on Artificial Intelligence. 38(7). 7441–7449. 5 indexed citations

Yang, Mingkun, et al.. (2023). Class-Aware Mask-guided feature refinement for scene text recognition. Pattern Recognition. 149. 110244–110244. 10 indexed citations

Liao, Minghui, et al.. (2022). Real-Time Scene Text Detection With Differentiable Binarization and Adaptive Scale Fusion. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(1). 919–931. 181 indexed citations breakdown →

Yang, Mingkun, Minghui Liao, Jing Wang, et al.. (2022). Reading and Writing: Discriminative and Generative Modeling for Self-Supervised Text Recognition. Proceedings of the 30th ACM International Conference on Multimedia. 4214–4223. 33 indexed citations

Liang, Dingkang, et al.. (2022). Comprehensive benchmark datasets for Amharic scene text detection and recognition. Science China Information Sciences. 65(6). 1 indexed citations

He, Minghang, Minghui Liao, Zhibo Yang, et al.. (2021). MOST: A Multi-Oriented Scene Text Detector with Localization Refinement. 8809–8818. 64 indexed citations

10.

Wang, Zhen, et al.. (2020). Scanning Imaging Restoration of Moving or Dynamically Deforming Objects. IEEE Transactions on Image Processing. 29. 7290–7305. 5 indexed citations

11.

Liao, Minghui, et al.. (2020). SynthText3D: synthesizing scene text images from 3D virtual worlds. Science China Information Sciences. 63(2). 24 indexed citations

12.

Liao, Minghui, Zhaoyi Wan, Cong Yao, Kai Chen, & Xiang Bai. (2020). Real-Time Scene Text Detection with Differentiable Binarization. Proceedings of the AAAI Conference on Artificial Intelligence. 34(7). 11474–11481. 414 indexed citations breakdown →

13.

Yang, Mingkun, Yushuo Guan, Minghui Liao, et al.. (2019). Symmetry-Constrained Rectification Network for Scene Text Recognition. 9146–9155. 93 indexed citations

14.

Liao, Minghui, Pengyuan Lyu, Minghang He, et al.. (2019). Mask TextSpotter: An End-to-End Trainable Neural Network for Spotting Text with Arbitrary Shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence. 43(2). 532–548. 154 indexed citations

15.

Liao, Minghui, Jian Zhang, Zhaoyi Wan, et al.. (2019). Scene Text Recognition from Two-Dimensional Perspective. Proceedings of the AAAI Conference on Artificial Intelligence. 33(1). 8714–8721. 148 indexed citations

16.

Zhu, Zhen, Minghui Liao, Baoguang Shi, & Xiang Bai. (2018). Feature Fusion for Scene Text Detection. 193–198. 5 indexed citations

17.

Liao, Minghui, Baoguang Shi, & Xiang Bai. (2018). TextBoxes++: A Single-Shot Oriented Scene Text Detector. IEEE Transactions on Image Processing. 27(8). 3676–3690. 559 indexed citations breakdown →

18.

Bai, Xiang, Minghui Liao, Baoguang Shi, & Mingkun Yang. (2018). Deep learning for scene text detection and recognition. Scientia Sinica Informationis. 48(5). 531–544. 7 indexed citations

19.

Zhu, Yingying, Minghui Liao, Mingkun Yang, & Wenyu Liu. (2017). Cascaded Segmentation-Detection Networks for Text-Based Traffic Sign Detection. IEEE Transactions on Intelligent Transportation Systems. 19(1). 209–219. 82 indexed citations

20.

Liao, Minghui, Baoguang Shi, Xiang Bai, Xinggang Wang, & Wenyu Liu. (2017). TextBoxes: A Fast Text Detector with a Single Deep Neural Network. Proceedings of the AAAI Conference on Artificial Intelligence. 31(1). 539 indexed citations breakdown →

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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