Yulan Guo

15.8k total citations · 9 hit papers
168 papers, 9.6k citations indexed

About

Yulan Guo is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Computational Mechanics. According to data from OpenAlex, Yulan Guo has authored 168 papers receiving a total of 9.6k indexed citations (citations by other indexed papers that have themselves been cited), including 119 papers in Computer Vision and Pattern Recognition, 48 papers in Aerospace Engineering and 38 papers in Computational Mechanics. Recurrent topics in Yulan Guo's work include Advanced Vision and Imaging (44 papers), Robotics and Sensor-Based Localization (40 papers) and 3D Surveying and Cultural Heritage (35 papers). Yulan Guo is often cited by papers focused on Advanced Vision and Imaging (44 papers), Robotics and Sensor-Based Localization (40 papers) and 3D Surveying and Cultural Heritage (35 papers). Yulan Guo collaborates with scholars based in China, Australia and United Kingdom. Yulan Guo's co-authors include Qingyong Hu, Mohammed Bennamoun, Li Liu, Wei An, Hao Liu, Jianwei Wan, Hanyun Wang, Ferdous Sohel, Min Lu and Andrew Markham and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Geoscience and Remote Sensing and IEEE Transactions on Image Processing.

In The Last Decade

Yulan Guo

159 papers receiving 9.4k citations

Hit Papers

Deep Learning for 3D Point Clouds: A Survey 2014 2026 2018 2022 2020 2020 2014 2015 2016 400 800 1.2k
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. Deep Learning for 3D Point Clouds: A Survey
    2020 1.4k citations Yulan Guo, Hanyun Wang et al. IEEE Transactions on Pattern Analysis and Machine Intelligence profile →
  2. RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds
    2020 1.3k citations Qingyong Hu, Bo Yang et al. profile →
  3. 3D Object Recognition in Cluttered Scenes with Local Surface Features: A Survey
    2014 460 citations Yulan Guo, Mohammed Bennamoun et al. IEEE Transactions on Pattern Analysis and Machine Intelligence profile →
  4. A Comprehensive Performance Evaluation of 3D Local Feature Descriptors
    2015 391 citations Yulan Guo, Mohammed Bennamoun et al. profile →
  5. Median Robust Extended Local Binary Pattern for Texture Classification
    2016 306 citations Yulan Guo et al. profile →
  6. Unsupervised Degradation Representation Learning for Blind Super-Resolution
    2021 253 citations Longguang Wang, Yingqian Wang et al. profile →
  7. Not All Points Are Equal: Learning Highly Efficient Point-based Detectors for 3D LiDAR Point Clouds
    2022 238 citations Qingyong Hu, Yanxin Ma et al. profile →
  8. SpinNet: Learning a General Surface Descriptor for 3D Point Cloud Registration
    2021 231 citations Qingyong Hu, Bo Yang et al. profile →
  9. Learning Semantic Segmentation of Large-Scale Point Clouds with Random Sampling
    2021 157 citations Qingyong Hu, Bo Yang 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 Career Trend Papers Cites
Yulan Guo China 46 5.8k 2.9k 2.7k 2.4k 2.3k 168 9.6k
Noah Snavely United States 43 9.7k 1.7× 2.7k 0.9× 1.5k 0.5× 4.0k 1.7× 1.6k 0.7× 109 12.3k
Long Quan China 53 6.6k 1.1× 1.3k 0.4× 1.1k 0.4× 2.6k 1.1× 965 0.4× 359 10.5k
Fisher Yu United States 32 7.8k 1.4× 1.3k 0.4× 2.0k 0.7× 1.4k 0.6× 888 0.4× 70 11.1k
Li Jiang China 30 3.7k 0.6× 1.9k 0.7× 2.3k 0.8× 1.4k 0.6× 1.6k 0.7× 126 7.2k
Peter Wonka United States 46 4.2k 0.7× 2.2k 0.8× 2.9k 1.1× 739 0.3× 1.8k 0.8× 201 9.3k
Jan‐Michael Frahm United States 36 6.7k 1.2× 1.6k 0.6× 725 0.3× 3.9k 1.6× 891 0.4× 124 8.5k
Federico Tombari Germany 41 4.4k 0.8× 1.5k 0.5× 969 0.4× 2.9k 1.2× 667 0.3× 193 6.4k
Yasutaka Furukawa United States 31 4.6k 0.8× 3.0k 1.0× 643 0.2× 2.8k 1.2× 1.8k 0.8× 56 6.9k
Justin Solomon United States 26 2.8k 0.5× 2.2k 0.8× 3.8k 1.4× 1.0k 0.4× 1.4k 0.6× 89 6.8k
Hongdong Li Australia 49 7.3k 1.3× 922 0.3× 848 0.3× 2.8k 1.1× 500 0.2× 228 9.2k

Countries citing papers authored by Yulan Guo

Since Specialization
Citations

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

Fields of papers citing papers by Yulan Guo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yulan Guo

This figure shows the co-authorship network connecting the top 25 collaborators of Yulan Guo. A scholar is included among the top collaborators of Yulan Guo 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 Yulan Guo. Yulan Guo 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.
Guo, Yulan, et al.. (2025). Deep Lookup Network. IEEE Transactions on Pattern Analysis and Machine Intelligence. 48(1). 202–218.
2.
Liu, Shitong, Jinbin Zhao, Yulan Guo, et al.. (2024). A photothermal colorimetric dual-signal sensor for Staphylococcus aureus in food based on CuS nanoparticles. Microchemical Journal. 201. 110660–110660. 5 indexed citations
3.
Wang, Longguang, Yulan Guo, Yingqian Wang, et al.. (2024). Unsupervised Degradation Representation Learning for Unpaired Restoration of Images and Point Clouds. IEEE Transactions on Pattern Analysis and Machine Intelligence. 47(1). 1–18. 6 indexed citations
4.
Laga, Hamid, et al.. (2023). Multi-stage information diffusion for joint depth and surface normal estimation. Pattern Recognition. 141. 109660–109660. 8 indexed citations
5.
Wang, Zi, et al.. (2023). Bridging the Domain Gap in Satellite Pose Estimation: A Self-Training Approach Based on Geometrical Constraints. IEEE Transactions on Aerospace and Electronic Systems. 60(3). 2500–2514. 45 indexed citations
6.
Gao, Qing, et al.. (2023). Sharing-Net: Lightweight feedforward network for skeleton-based action recognition based on information sharing mechanism. Pattern Recognition. 146. 110050–110050. 12 indexed citations
7.
Ma, Yanxin, et al.. (2022). AGFA-Net: Adaptive Global Feature Augmentation Network for Point Cloud Completion. IEEE Geoscience and Remote Sensing Letters. 19. 1–5. 7 indexed citations
8.
Wang, Yun, Longguang Wang, Hanyun Wang, & Yulan Guo. (2022). SPNet: Learning Stereo Matching With Slanted Plane Aggregation. IEEE Robotics and Automation Letters. 7(3). 6258–6265. 8 indexed citations
9.
Liu, Ting, et al.. (2021). Moving Object Detection in Satellite Videos via Spatial–Temporal Tensor Model and Weighted Schatten p -Norm Minimization. IEEE Geoscience and Remote Sensing Letters. 19. 1–5. 8 indexed citations
10.
Hu, Qingyong, Hao Liu, Feng Zhang, et al.. (2021). Detecting and Tracking Small and Dense Moving Objects in Satellite Videos: A Benchmark. IEEE Transactions on Geoscience and Remote Sensing. 60. 1–18. 96 indexed citations
11.
Wang, Shuhui, et al.. (2021). Pano-SfMLearner: Self-Supervised Multi-Task Learning of Depth and Semantics in Panoramic Videos. IEEE Signal Processing Letters. 28. 832–836. 16 indexed citations
12.
Wen, Chenglu, et al.. (2021). Indoor 3D Human Trajectory Reconstruction Using Surveillance Camera Videos and Point Clouds. IEEE Transactions on Circuits and Systems for Video Technology. 32(4). 2482–2495. 16 indexed citations
13.
Hu, Qingyong, Bo Yang, Linhai Xie, et al.. (2020). RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds. 11105–11114. 1288 indexed citations breakdown →
14.
Wang, Longguang, Yulan Guo, Yingqian Wang, et al.. (2020). Parallax Attention for Unsupervised Stereo Correspondence Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence. 44(4). 2108–2125. 102 indexed citations
15.
Ying, Xinyi, Yingqian Wang, Longguang Wang, et al.. (2020). A Stereo Attention Module for Stereo Image Super-Resolution. IEEE Signal Processing Letters. 27. 496–500. 108 indexed citations
16.
Liang, Zhengfa, Yulan Guo, Yiliu Feng, et al.. (2019). Stereo Matching Using Multi-Level Cost Volume and Multi-Scale Feature Constancy. IEEE Transactions on Pattern Analysis and Machine Intelligence. 43(1). 300–315. 92 indexed citations
17.
Lei, Yinjie, et al.. (2019). Deep point-to-subspace metric learning for sketch-based 3D shape retrieval. Pattern Recognition. 96. 106981–106981. 31 indexed citations
18.
Li, Jonathan, Yulan Guo, Xin Li, et al.. (2018). Robust procedural model fitting with a new geometric similarity estimator. Pattern Recognition. 85. 120–131. 12 indexed citations
19.
Ling, Qiang, Yulan Guo, Zaiping Lin, & Wei An. (2018). A Constrained Sparse Representation Model for Hyperspectral Anomaly Detection. IEEE Transactions on Geoscience and Remote Sensing. 57(4). 2358–2371. 103 indexed citations
20.
Hu, Qingyong, Yulan Guo, Zaiping Lin, Wei An, & Hongwei Cheng. (2017). Object Tracking Using Multiple Features and Adaptive Model Updating. IEEE Transactions on Instrumentation and Measurement. 66(11). 2882–2897. 22 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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