Guangcan Liu

9.8k total citations · 4 hit papers
107 papers, 7.1k citations indexed

About

Guangcan Liu is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Artificial Intelligence. According to data from OpenAlex, Guangcan Liu has authored 107 papers receiving a total of 7.1k indexed citations (citations by other indexed papers that have themselves been cited), including 73 papers in Computer Vision and Pattern Recognition, 38 papers in Computational Mechanics and 26 papers in Artificial Intelligence. Recurrent topics in Guangcan Liu's work include Sparse and Compressive Sensing Techniques (37 papers), Face and Expression Recognition (25 papers) and Advanced Image and Video Retrieval Techniques (16 papers). Guangcan Liu is often cited by papers focused on Sparse and Compressive Sensing Techniques (37 papers), Face and Expression Recognition (25 papers) and Advanced Image and Video Retrieval Techniques (16 papers). Guangcan Liu collaborates with scholars based in China, Singapore and United States. Guangcan Liu's co-authors include Shuicheng Yan, Zhouchen Lin, Yong Yu, Yi Ma, Ju Sun, Qingshan Liu, Si Liu, Changqing Zhang, Xiaochun Cao and Huazhu Fu and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Information Theory and IEEE Transactions on Geoscience and Remote Sensing.

In The Last Decade

Guangcan Liu

101 papers receiving 7.0k citations

Hit Papers

Robust Recovery of Subspace Structures by Low-Rank Repres... 2010 2026 2015 2020 2012 2010 2011 2015 500 1000 1.5k 2.0k 2.5k
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.

  1. Robust Recovery of Subspace Structures by Low-Rank Representation
    2012 2.7k citations Guangcan Liu, Zhouchen Lin et al. profile →
  2. Robust Subspace Segmentation by Low-Rank Representation
    2010 1.0k citations Guangcan Liu, Zhouchen Lin et al. International Conference on Machine Learning profile →
  3. Latent Low-Rank Representation for subspace segmentation and feature extraction
    2011 521 citations Guangcan Liu, Shuicheng Yan National University of Singapore profile →
  4. Low-Rank Tensor Constrained Multiview Subspace Clustering
    2015 449 citations Si Liu, Guangcan Liu et al. profile →

Peers

Guangcan Liu
Xiangchu Feng China
Yi Ma China
Ehsan Elhamifar United States
Ju Sun United States
Arvind Ganesh India
Yuan Xie China
Junhui Hou Hong Kong
Michal Aharon Israel
Francis Bach France
Meng Yang China
Xiangchu Feng China
Guangcan Liu
Citations per year, relative to Guangcan Liu Guangcan Liu (= 1×) peers Xiangchu Feng

Countries citing papers authored by Guangcan Liu

Since Specialization
Citations

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

Fields of papers citing papers by Guangcan Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Guangcan Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Guangcan Liu. A scholar is included among the top collaborators of Guangcan Liu 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 Guangcan Liu. Guangcan Liu 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.
Xu, Han, Chen Lǚ, Hao Zhang, et al.. (2025). Artificial intelligence-assisted remote sensing observation, understanding, and decision. The Innovation. 6(12). 101016–101016.
2.
Liu, Guangcan, et al.. (2024). MSSD: multi-scale self-distillation for object detection. 2(1). 5 indexed citations
3.
Xie, Xingyu, Jianlong Wu, Guangcan Liu, & Zhouchen Lin. (2024). SSCNet: learning-based subspace clustering. 2(1). 2 indexed citations
4.
Liu, Guangcan, et al.. (2023). A real-time semi-dense depth-guided depth completion network. The Visual Computer. 40(1). 87–97. 1 indexed citations
5.
Zhou, Zhili, Ding Chun, Jin Li, et al.. (2022). Sequential Order-Aware Coding-Based Robust Subspace Clustering for Human Action Recognition in Untrimmed Videos. IEEE Transactions on Image Processing. 32. 13–28. 14 indexed citations
6.
Han, Hu, et al.. (2021). Collaborative Local-Global Learning for Temporal Action Proposal. ACM Transactions on Intelligent Systems and Technology. 12(5). 1–14. 2 indexed citations
7.
Liu, Guangcan, Qingshan Liu, Xiao–Tong Yuan, & Meng Wang. (2018). Matrix Completion with Nonuniform Sampling: Theories and Methods.. arXiv (Cornell University). 1 indexed citations
8.
Xie, Xingyu, et al.. (2017). Implicit Block Diagonal Low-Rank Representation. IEEE Transactions on Image Processing. 27(1). 477–489. 72 indexed citations
9.
Liu, Guangcan, Qingshan Liu, & Xiao–Tong Yuan. (2017). A New Theory for Matrix Completion. Neural Information Processing Systems. 30. 785–794. 17 indexed citations
10.
Liu, Qingshan, Jiankang Deng, Jing Yang, Guangcan Liu, & Dacheng Tao. (2016). Adaptive Cascade Regression Model For Robust Face Alignment. IEEE Transactions on Image Processing. 26(2). 797–807. 21 indexed citations
11.
Lü, Yafei, et al.. (2013). Motion control of the wedge prisms in Risley-prism-based beam steering system for precise target tracking. Applied Optics. 52(12). 2849–2849. 37 indexed citations
12.
Liu, Guangcan, et al.. (2012). Quantitative analysis of cluster-head selection for wireless sensor networks. World Automation Congress. 277–281. 2 indexed citations
13.
Chen, Weibing, et al.. (2012). Algorithm study on video watermarking authentication based on AVS in compressed domain. World Automation Congress. 283–287. 1 indexed citations
14.
Liu, Si, Song Zheng, Guangcan Liu, et al.. (2012). Street-to-shop: Cross-scenario clothing retrieval via parts alignment and auxiliary set. National University of Singapore. 3330–3337. 124 indexed citations
15.
Liu, Guangcan, Huan Xu, & Shuicheng Yan. (2012). Exact Subspace Segmentation and Outlier Detection by Low-Rank Representation. International Conference on Artificial Intelligence and Statistics. 703–711. 43 indexed citations
16.
Lang, Congyan, Guangcan Liu, Jian Yu, & Shuicheng Yan. (2011). Saliency Detection by Multitask Sparsity Pursuit. IEEE Transactions on Image Processing. 21(3). 1327–1338. 147 indexed citations
17.
Liu, Guangcan & Shuicheng Yan. (2011). Latent Low-Rank Representation for subspace segmentation and feature extraction. National University of Singapore. 1615–1622. 521 indexed citations breakdown →
18.
Liu, Guangcan, Zhouchen Lin, & Yong Yu. (2010). Robust Subspace Segmentation by Low-Rank Representation. International Conference on Machine Learning. 663–670. 1048 indexed citations breakdown →
19.
Liu, Guangcan. (2010). Parameter Optimization of RBF Networks Based on Evolutionary Model. Control Engineering of China. 1 indexed citations
20.
Liu, Guangcan, et al.. (2009). Customer Segmentation Algorithm of Wireless Content Service Based on Ant K-Means. 267–269. 4 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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