Dun Liang

1.4k total citations · 1 hit paper
11 papers, 943 citations indexed

About

Dun Liang is a scholar working on Computer Vision and Pattern Recognition, Civil and Structural Engineering and Computational Mechanics. According to data from OpenAlex, Dun Liang has authored 11 papers receiving a total of 943 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Vision and Pattern Recognition, 3 papers in Civil and Structural Engineering and 3 papers in Computational Mechanics. Recurrent topics in Dun Liang's work include Computer Graphics and Visualization Techniques (3 papers), Advanced Neural Network Applications (3 papers) and 3D Shape Modeling and Analysis (3 papers). Dun Liang is often cited by papers focused on Computer Graphics and Visualization Techniques (3 papers), Advanced Neural Network Applications (3 papers) and 3D Shape Modeling and Analysis (3 papers). Dun Liang collaborates with scholars based in China, United Kingdom and United States. Dun Liang's co-authors include Shi‐Min Hu, Xiaolei Huang, Zhe Zhu, Song–Hai Zhang, Baoli Li, Guo-Ye Yang, Guowei Yang, Tai‐Jiang Mu, Linmi Tao and Hai-Tao Zheng and has published in prestigious journals such as ACM Transactions on Graphics, IEEE Transactions on Visualization and Computer Graphics and Journal of Building Engineering.

In The Last Decade

Dun Liang

11 papers receiving 907 citations

Hit Papers

Traffic-Sign Detection and Classification in the Wild 2016 2026 2019 2022 2016 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dun Liang China 8 759 307 162 138 103 11 943
Xingang Pan Singapore 10 1.1k 1.4× 162 0.5× 42 0.3× 336 2.4× 505 4.9× 27 1.4k
Carlos Hernández Mexico 14 936 1.2× 132 0.4× 61 0.4× 155 1.1× 12 0.1× 35 1.2k
Xinyu Huang United States 13 641 0.8× 119 0.4× 20 0.1× 131 0.9× 283 2.7× 36 991
Hyunchul Shin South Korea 16 466 0.6× 179 0.6× 40 0.2× 99 0.7× 80 0.8× 93 970
Raoul de Charette France 11 589 0.8× 94 0.3× 19 0.1× 122 0.9× 121 1.2× 23 816
Cüneyt Akınlar Türkiye 12 876 1.2× 225 0.7× 54 0.3× 43 0.3× 63 0.6× 39 1.1k
Anton Konushin Russia 13 446 0.6× 54 0.2× 34 0.2× 77 0.6× 25 0.2× 63 640
Jin Fang China 12 721 0.9× 77 0.3× 36 0.2× 112 0.8× 183 1.8× 22 1.0k
Tzu-Yi Hung Singapore 10 443 0.6× 64 0.2× 47 0.3× 123 0.9× 19 0.2× 22 679

Countries citing papers authored by Dun Liang

Since Specialization
Citations

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

Fields of papers citing papers by Dun Liang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dun Liang

This figure shows the co-authorship network connecting the top 25 collaborators of Dun Liang. A scholar is included among the top collaborators of Dun Liang 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 Dun Liang. Dun Liang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

11 of 11 papers shown
1.
Liang, Dun, et al.. (2023). Jrender: An efficient differentiable rendering library based on Jittor. Graphical Models. 130. 101202–101202. 1 indexed citations
2.
Yang, Guowei, et al.. (2022). Recursive-NeRF: An Efficient and Dynamically Growing NeRF. IEEE Transactions on Visualization and Computer Graphics. 29(12). 5124–5136. 36 indexed citations
3.
Liu, Ruiyang, Yinghui Li, Linmi Tao, Dun Liang, & Hai-Tao Zheng. (2022). Are we ready for a new paradigm shift? A survey on visual deep MLP. Patterns. 3(7). 100520–100520. 51 indexed citations
4.
Fan, Shenggang, et al.. (2022). Fire resistance design of the bolted-welded hybrid composite connection in steel frame. Fire Safety Journal. 133. 103672–103672. 2 indexed citations
5.
Xie, Shaowen, et al.. (2022). Seismic behaviour of novel self-tightening one-side bolted joints of prefabricated steel structures. Journal of Building Engineering. 56. 104823–104823. 11 indexed citations
6.
Guo, Meng-Hao, Zheng-Ning Liu, Tai‐Jiang Mu, et al.. (2021). Can attention enable MLPs to catch up with CNNs?. Computational Visual Media. 7(3). 283–288. 12 indexed citations
7.
Hu, Shi‐Min, et al.. (2020). Jittor: a novel deep learning framework with meta-operators and unified graph execution. Science China Information Sciences. 63(12). 90 indexed citations
8.
Liang, Dun, et al.. (2020). Lane Detection: A Survey with New Results. Journal of Computer Science and Technology. 35(3). 493–505. 38 indexed citations
9.
Gao, Lin, Yu‐Kun Lai, Dun Liang, Shuyu Chen, & Shihong Xia. (2016). Efficient and Flexible Deformation Representation for Data-Driven Surface Modeling. ACM Transactions on Graphics. 35(5). 1–17. 45 indexed citations
10.
Zhu, Zhe, Dun Liang, Song–Hai Zhang, et al.. (2016). Traffic-Sign Detection and Classification in the Wild. 2110–2118. 654 indexed citations breakdown →
11.
Liu, Haibo, et al.. (2005). [Soluble expression and characterization of disulfide bond-rich subdomains of membrane protein p185 in Escherichia coli].. PubMed. 21(4). 590–6. 3 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026