Pengfei Xu

1.9k total citations · 1 hit paper
62 papers, 1.2k citations indexed

About

Pengfei Xu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Pengfei Xu has authored 62 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Computer Vision and Pattern Recognition, 12 papers in Artificial Intelligence and 8 papers in Signal Processing. Recurrent topics in Pengfei Xu's work include Advanced Image and Video Retrieval Techniques (11 papers), Medical Image Segmentation Techniques (6 papers) and Video Surveillance and Tracking Methods (6 papers). Pengfei Xu is often cited by papers focused on Advanced Image and Video Retrieval Techniques (11 papers), Medical Image Segmentation Techniques (6 papers) and Video Surveillance and Tracking Methods (6 papers). Pengfei Xu collaborates with scholars based in China, Australia and United States. Pengfei Xu's co-authors include Xiaojiang Chen, Xiaowen Chu, Shaohuai Shi, Qiang Wang, Xiaojun Chang, Zhihui Li, Pengzhen Ren, Qiguang Miao, Alex Hauptmann and Dingyi Fang and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Image Processing.

In The Last Decade

Pengfei Xu

58 papers receiving 1.2k citations

Hit Papers

A Comprehensive Survey of Scene Graphs: Generation and Ap... 2021 2026 2022 2024 2021 50 100 150 200
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. A Comprehensive Survey of Scene Graphs: Generation and Application
    2021 202 citations Xiaojun Chang, Pengzhen Ren 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
Pengfei Xu China 18 583 363 130 122 120 62 1.2k
Pourya Shamsolmoali China 21 878 1.5× 542 1.5× 115 0.9× 334 2.7× 107 0.9× 57 1.8k
V. Sowmya India 21 461 0.8× 376 1.0× 199 1.5× 299 2.5× 127 1.1× 143 1.6k
Pankaj Kumar India 22 1.1k 2.0× 336 0.9× 322 2.5× 157 1.3× 129 1.1× 129 1.6k
Abdussalam Elhanashi Italy 19 393 0.7× 304 0.8× 109 0.8× 56 0.5× 46 0.4× 36 1.1k
Wei Hong China 22 881 1.5× 251 0.7× 175 1.3× 288 2.4× 89 0.7× 122 2.0k
Javier Ruiz‐del‐Solar Chile 27 1.1k 1.9× 440 1.2× 207 1.6× 144 1.2× 83 0.7× 143 2.1k
Qinghe Zheng China 17 477 0.8× 423 1.2× 146 1.1× 106 0.9× 30 0.3× 39 1.3k
Tian-Xing Xu China 5 706 1.2× 347 1.0× 60 0.5× 205 1.7× 36 0.3× 12 1.5k
Xuequan Lu Australia 23 924 1.6× 540 1.5× 99 0.8× 102 0.8× 82 0.7× 125 1.7k
Mamoona Naveed Asghar Ireland 17 723 1.2× 239 0.7× 152 1.2× 80 0.7× 72 0.6× 64 1.2k

Countries citing papers authored by Pengfei Xu

Since Specialization
Citations

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

Fields of papers citing papers by Pengfei Xu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pengfei Xu

This figure shows the co-authorship network connecting the top 25 collaborators of Pengfei Xu. A scholar is included among the top collaborators of Pengfei Xu 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 Pengfei Xu. Pengfei Xu 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, Jia, Tao Liu, Zhiming Hu, et al.. (2025). An Automated AI Framework for Quantitative Measurement of Mammalian Behavior. Integrative Zoology. 21(2). 343–358.
2.
Zhao, Xuesong, Pengfei Xu, Fa Zhu, et al.. (2025). An uncertain boundary region-aware network for multi-scale liver tumor segmentation. Expert Systems with Applications. 304. 130732–130732.
3.
Liu, Menghao, et al.. (2025). A boundary-enhanced and target-driven deformable convolutional network for abdominal multi-organ segmentation. Pattern Recognition. 172. 112386–112386.
4.
Xu, Pengfei, et al.. (2024). MaP-SGAN: Multi-anchor point siamese GAN for Wi-Fi CSI-based cross-domain gait recognition. Expert Systems with Applications. 251. 124083–124083. 2 indexed citations
5.
Xu, Pengfei, Jing Zhao, Mingxi Wan, et al.. (2024). Classification of multi‐feature fusion ultrasound images of breast tumor within category 4 using convolutional neural networks. Medical Physics. 51(6). 4243–4257. 5 indexed citations
6.
Xu, Pengfei, Dong Wei, Xuelin Jin, et al.. (2024). Advancing primate surveillance with image recognition techniques from unmanned aerial vehicles. American Journal of Primatology. 87(2). e23676–e23676. 1 indexed citations
7.
Chen, Jinsong, et al.. (2024). Spectral and Energy Efficient Waveform Design for RIS-Assisted ISAC. IEEE Transactions on Communications. 73(1). 158–172. 8 indexed citations
8.
Li, Zhihui, Pengfei Xu, Xiaojun Chang, et al.. (2023). When Object Detection Meets Knowledge Distillation: A Survey. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(8). 10555–10579. 82 indexed citations
9.
10.
He, Jingyi, et al.. (2023). ASCFL: Accurate and Speedy Semi-Supervised Clustering Federated Learning. Tsinghua Science & Technology. 28(5). 823–837. 6 indexed citations
11.
12.
Liang, Ying, et al.. (2023). WiAi-ID: Wi-Fi-Based Domain Adaptation for Appearance-Independent Passive Person Identification. IEEE Internet of Things Journal. 11(1). 1012–1027. 6 indexed citations
13.
Chang, Xiaojun, Pengzhen Ren, Pengfei Xu, et al.. (2021). A Comprehensive Survey of Scene Graphs: Generation and Application. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(1). 1–26. 202 indexed citations breakdown →
14.
An, Jing, et al.. (2021). Unsupervised 2D dimensionality reduction by jointly learning structural and temporal correlation. Applied Intelligence. 52(5). 5646–5656. 1 indexed citations
15.
Shi, Cheng, et al.. (2020). Hierarchical Multi-View Semi-Supervised Learning for Very High-Resolution Remote Sensing Image Classification. Remote Sensing. 12(6). 1012–1012. 14 indexed citations
16.
Li, Peilun, Guozhen Li, Meiqi Lu, et al.. (2019). Spatio-temporal Consistency and Hierarchical Matching for Multi-Target Multi-Camera Vehicle Tracking. Computer Vision and Pattern Recognition. 222–230. 19 indexed citations
17.
Liu, Ruyi, Qiguang Miao, Jianfeng Song, et al.. (2018). Multiscale road centerlines extraction from high-resolution aerial imagery. Neurocomputing. 329. 384–396. 37 indexed citations
18.
Xu, Pengfei, et al.. (2018). General model for linear information extraction based on the shear transformation. Pattern Recognition Letters. 130. 107–115. 1 indexed citations
19.
Shi, Shaohuai, Pengfei Xu, & Xiaowen Chu. (2017). Supervised Learning Based Algorithm Selection for Deep Neural Networks. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 344–351. 2 indexed citations
20.
Xu, Pengfei, Qiguang Miao, Ruyi Liu, Xiaojiang Chen, & Xunli Fan. (2016). Dynamic character grouping based on four consistency constraints in topographic maps. Neurocomputing. 212. 96–106. 2 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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