Zengqun Zhao

767 total citations · 2 hit papers
6 papers, 477 citations indexed

About

Zengqun Zhao is a scholar working on Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology and Urban Studies. According to data from OpenAlex, Zengqun Zhao has authored 6 papers receiving a total of 477 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Computer Vision and Pattern Recognition, 3 papers in Experimental and Cognitive Psychology and 1 paper in Urban Studies. Recurrent topics in Zengqun Zhao's work include Face recognition and analysis (4 papers), Emotion and Mood Recognition (3 papers) and Face and Expression Recognition (3 papers). Zengqun Zhao is often cited by papers focused on Face recognition and analysis (4 papers), Emotion and Mood Recognition (3 papers) and Face and Expression Recognition (3 papers). Zengqun Zhao collaborates with scholars based in China and United Kingdom. Zengqun Zhao's co-authors include Qingshan Liu, Shanmin Wang, Feng Zhou, Shaogang Gong and Ioannis Patras and has published in prestigious journals such as IEEE Transactions on Image Processing, Multimedia Systems and Proceedings of the AAAI Conference on Artificial Intelligence.

In The Last Decade

Zengqun Zhao

5 papers receiving 472 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.

Learning Deep Global Multi-Scale and Local Attention Features for Facial Expression Recognition in the Wild

2021 210 citations Zengqun Zhao, Qingshan Liu et al. IEEE Transactions on Image Processing profile →
Robust Lightweight Facial Expression Recognition Network with Label Distribution Training

2021 162 citations Zengqun Zhao, Qingshan Liu et al. Proceedings of the AAAI Conference on Artificial Intelligence profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Zengqun Zhao China	5	372	347	54	49	41	6	477
Siyue Xie China	6	395 1.1×	343 1.0×	64 1.2×	38 0.8×	41 1.0×	10	474
Jingwei Yan China	8	331 0.9×	330 1.0×	78 1.4×	35 0.7×	22 0.5×	12	455
Madhumita A. Takalkar Australia	5	181 0.5×	203 0.6×	72 1.3×	53 1.1×	38 0.9×	5	295
Wissam J. Baddar South Korea	6	329 0.9×	314 0.9×	69 1.3×	99 2.0×	46 1.1×	14	450
Qiangchang Wang China	5	273 0.7×	192 0.6×	49 0.9×	25 0.5×	20 0.5×	12	382
Yingruo Fan Hong Kong	8	335 0.9×	137 0.4×	43 0.8×	42 0.9×	13 0.3×	11	396
Jihyeon Roh South Korea	4	277 0.7×	257 0.7×	53 1.0×	29 0.6×	21 0.5×	6	347
Keyu Yan China	4	253 0.7×	204 0.6×	61 1.1×	19 0.4×	21 0.5×	4	309
Fanglei Xue China	6	226 0.6×	211 0.6×	35 0.6×	24 0.5×	18 0.4×	8	323
Hangyu Li China	7	253 0.7×	203 0.6×	52 1.0×	25 0.5×	21 0.5×	16	336

Countries citing papers authored by Zengqun Zhao

Since Specialization

Citations

This map shows the geographic impact of Zengqun Zhao'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 Zengqun Zhao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zengqun Zhao more than expected).

Fields of papers citing papers by Zengqun Zhao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Zengqun Zhao. 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 Zengqun Zhao. The network helps show where Zengqun Zhao may publish in the future.

Co-authorship network of co-authors of Zengqun Zhao

This figure shows the co-authorship network connecting the top 25 collaborators of Zengqun Zhao. A scholar is included among the top collaborators of Zengqun Zhao 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 Zengqun Zhao. Zengqun Zhao 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:

6 of 6 papers shown

1.

Zhao, Zengqun, et al.. (2025). AIM-Fair: Advancing Algorithmic Fairness via Selectively Fine-Tuning Biased Models with Contextual Synthetic Data. 28748–28758.

2.

Zhao, Zengqun, et al.. (2025). Enhancing Zero-Shot Facial Expression Recognition by LLM Knowledge Transfer. 815–824. 4 indexed citations

3.

Wang, Shanmin, et al.. (2022). CED-Net: contextual encoder–decoder network for 3D face reconstruction. Multimedia Systems. 28(5). 1713–1722. 4 indexed citations

4.

Zhao, Zengqun, Qingshan Liu, & Shanmin Wang. (2021). Learning Deep Global Multi-Scale and Local Attention Features for Facial Expression Recognition in the Wild. IEEE Transactions on Image Processing. 30. 6544–6556. 210 indexed citations breakdown →

5.

Zhao, Zengqun, Qingshan Liu, & Feng Zhou. (2021). Robust Lightweight Facial Expression Recognition Network with Label Distribution Training. Proceedings of the AAAI Conference on Artificial Intelligence. 35(4). 3510–3519. 162 indexed citations breakdown →

6.

Zhao, Zengqun & Qingshan Liu. (2021). Former-DFER: Dynamic Facial Expression Recognition Transformer. 1553–1561. 97 indexed citations

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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