Liquan Shen

5.6k total citations · 2 hit papers
206 papers, 4.2k citations indexed

About

Liquan Shen is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Media Technology. According to data from OpenAlex, Liquan Shen has authored 206 papers receiving a total of 4.2k indexed citations (citations by other indexed papers that have themselves been cited), including 201 papers in Computer Vision and Pattern Recognition, 93 papers in Signal Processing and 45 papers in Media Technology. Recurrent topics in Liquan Shen's work include Advanced Vision and Imaging (94 papers), Video Coding and Compression Technologies (93 papers) and Image and Video Quality Assessment (73 papers). Liquan Shen is often cited by papers focused on Advanced Vision and Imaging (94 papers), Video Coding and Compression Technologies (93 papers) and Image and Video Quality Assessment (73 papers). Liquan Shen collaborates with scholars based in China, United States and France. Liquan Shen's co-authors include Zhi Liu, Zhaoyang Zhang, Ping An, Xinpeng Zhang, Hao Yang, Zhengyong Wang, Wenqiang Zhao, Guorui Feng, Yufei Lin and Chao Yang and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Geoscience and Remote Sensing.

In The Last Decade

Liquan Shen

194 papers receiving 4.1k citations

Hit Papers

An Effective CU Size Decision Method for HEVC Encoders 2012 2026 2016 2021 2012 2023 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Liquan Shen China 33 4.0k 2.1k 570 211 123 206 4.2k
Hongliang Li China 35 4.1k 1.0× 728 0.3× 1.1k 1.9× 175 0.8× 62 0.5× 215 4.5k
Gangyi Jiang China 31 3.7k 0.9× 896 0.4× 1.5k 2.6× 32 0.2× 275 2.2× 331 4.2k
Deepu Rajan Singapore 28 2.2k 0.5× 180 0.1× 460 0.8× 238 1.1× 87 0.7× 121 2.8k
Nam Ling United States 30 2.1k 0.5× 1.1k 0.5× 348 0.6× 43 0.2× 23 0.2× 238 2.4k
Yo‐Sung Ho South Korea 26 2.8k 0.7× 776 0.4× 718 1.3× 22 0.1× 72 0.6× 280 3.1k
Munchurl Kim South Korea 28 2.1k 0.5× 878 0.4× 497 0.9× 6 0.0× 69 0.6× 133 2.4k
Tyng-Luh Liu Taiwan 22 2.2k 0.5× 182 0.1× 384 0.7× 159 0.8× 16 0.1× 68 2.5k
Jizheng Xu China 29 4.3k 1.1× 1.8k 0.9× 1.1k 1.9× 6 0.0× 36 0.3× 170 4.7k
Nishan Canagarajah United Kingdom 25 2.0k 0.5× 392 0.2× 1.5k 2.6× 9 0.0× 25 0.2× 116 2.8k

Countries citing papers authored by Liquan Shen

Since Specialization
Citations

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

Fields of papers citing papers by Liquan Shen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Liquan Shen

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

All Works

20 of 20 papers shown
1.
Liu, Hao, et al.. (2025). High Efficiency Wiener Filter-Based Point Cloud Quality Enhancement for MPEG G-PCC. IEEE Transactions on Circuits and Systems for Video Technology. 35(9). 9475–9486. 8 indexed citations
2.
An, Ping, et al.. (2025). Mask-Aware Light Field De-Occlusion With Gated Feature Aggregation and Texture-Semantic Attention. IEEE Transactions on Multimedia. 27. 5296–5311. 2 indexed citations
3.
Wu, Biqi, Xiwu Shang, Xiaoli Zhao, et al.. (2025). CMDC-PCQA: No-Reference Point Cloud Quality Assessment via a Cross-Modal Deep-Coupling Framework. IEEE Transactions on Instrumentation and Measurement. 74. 1–13. 1 indexed citations
4.
Yang, Fang, et al.. (2025). No-Reference 360° Video Quality Measurement With Local and Global Features Fusion. IEEE Transactions on Instrumentation and Measurement. 74. 1–12.
5.
Yang, Chao, et al.. (2024). Learning-based CU partition prediction for fast panoramic video intra coding. Expert Systems with Applications. 258. 125187–125187. 3 indexed citations
6.
Shu, Yong, Liquan Shen, Xiangyu Hu, & Zihao Zhou. (2024). High Dynamic Range Imaging from RAW Domain with a New Benchmark Dataset and a Multi-scale Network. 1–6.
7.
Shen, Liquan, et al.. (2024). Prior-Based Underwater Enhanced Image Quality Assessment Network. IEEE Journal of Oceanic Engineering. 49(2). 592–605. 9 indexed citations
9.
Shen, Liquan, et al.. (2023). 3D-Distortion Based Rate Distortion Optimization for Video-Based Point Cloud Compression. KSII Transactions on Internet and Information Systems. 17(2).
10.
Jiang, Xuhao, Weimin Tan, Tian Tan, Bo Yan, & Liquan Shen. (2023). Multi-Modality Deep Network for Extreme Learned Image Compression. Proceedings of the AAAI Conference on Artificial Intelligence. 37(1). 1033–1041. 10 indexed citations
11.
Shen, Liquan, et al.. (2023). Priors Guided Extreme Underwater Image Compression for Machine Vision and Human Vision. IEEE Journal of Oceanic Engineering. 48(3). 888–902. 5 indexed citations
12.
Jiang, Mingxing, Liquan Shen, Min Hu, et al.. (2022). Quantitative Measurement of Perceptual Attributes and Artifacts for Tone-Mapped HDR Display. IEEE Transactions on Instrumentation and Measurement. 71. 1–11. 9 indexed citations
13.
Yuan, Hui, et al.. (2022). TMSO-Net: Texture adaptive multi-scale observation for light field image depth estimation. Journal of Visual Communication and Image Representation. 90. 103731–103731. 66 indexed citations
14.
Hu, Xiangyu, Liquan Shen, Mingxing Jiang, Ran Ma, & Ping An. (2022). LA-HDR: Light Adaptive HDR Reconstruction Framework for Single LDR Image Considering Varied Light Conditions. IEEE Transactions on Multimedia. 25. 4814–4829. 4 indexed citations
15.
Yang, Chao, Ping An, & Liquan Shen. (2022). Blind Image Quality Measurement via Data-Driven Transform-Based Feature Enhancement. IEEE Transactions on Instrumentation and Measurement. 71. 1–12. 6 indexed citations
16.
Shen, Liquan, et al.. (2022). Prior-Guided Contrastive Image Compression for Underwater Machine Vision. IEEE Transactions on Circuits and Systems for Video Technology. 33(6). 2950–2961. 10 indexed citations
17.
An, Ping, et al.. (2021). Objective Quality Assessment of Lenslet Light Field Image Based on Focus Stack. IEEE Transactions on Multimedia. 24. 3193–3207. 36 indexed citations
18.
Shen, Liquan, Guorui Feng, & Ping An. (2019). SHVC CU Processing Aided by a Feedforward Neural Network. IEEE Transactions on Industrial Informatics. 15(11). 5803–5815. 9 indexed citations
19.
Liu, Zhijin, Kai Li, Liquan Shen, Ran Ma, & Ping An. (2019). Spatio-Temporal Residual Networks for Slide Transition Detection in Lecture Videos. KSII Transactions on Internet and Information Systems. 13(8). 1 indexed citations
20.
Huang, Xinpeng, Ping An, Liquan Shen, & Ran Ma. (2018). Efficient Light Field Images Compression Method Based on Depth Estimation and Optimization. IEEE Access. 6. 48984–48993. 10 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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