Pingbo Pan

1.4k total citations · 1 hit paper
9 papers, 571 citations indexed

About

Pingbo Pan is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Pingbo Pan has authored 9 papers receiving a total of 571 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Vision and Pattern Recognition, 2 papers in Artificial Intelligence and 1 paper in Signal Processing. Recurrent topics in Pingbo Pan's work include Advanced Image and Video Retrieval Techniques (3 papers), Video Surveillance and Tracking Methods (2 papers) and Human Pose and Action Recognition (2 papers). Pingbo Pan is often cited by papers focused on Advanced Image and Video Retrieval Techniques (3 papers), Video Surveillance and Tracking Methods (2 papers) and Human Pose and Action Recognition (2 papers). Pingbo Pan collaborates with scholars based in Australia, China and Switzerland. Pingbo Pan's co-authors include Yi Yang, Minfeng Zhu, Wei Chen, Wei Chen, Ping Liu, Mingliang Xu, Guodong Long, Xingzhong Du, Yan Yan and Lei Zhao and has published in prestigious journals such as IEEE Transactions on Circuits and Systems for Video Technology, Signal Processing and World Wide Web.

In The Last Decade

Pingbo Pan

9 papers receiving 553 citations

Hit Papers

align trajectories

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.

DM-GAN: Dynamic Memory Generative Adversarial Networks for Text-To-Image Synthesis

2019 346 citations Minfeng Zhu, Pingbo Pan et al. profile →

Peers

Pingbo Pan

CVPR

AI

MT

CGCD

SP

Xiaobao Guo Singapore

Ben Yang China

Le Dong China

Jeffrey Wu United States

Jianfu Zhang China

Hyun-Soo Kim South Korea

Songhua Liu China

Shanchuan Lin United States

Minoru Maruyama Japan

Xiaobao Guo Singapore

Pingbo Pan

309 ×0.6

CVPR

78 ×0.8

AI

163 ×2.0

MT

52 ×1.2

CGCD

22 ×0.9

SP

Citations per year, relative to Pingbo Pan Pingbo Pan (= 1×) peers Xiaobao Guo

Countries citing papers authored by Pingbo Pan

Since Specialization

Citations

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

Fields of papers citing papers by Pingbo Pan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pingbo Pan

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

All Works

Sort: Min cites: Since: Top N: Style:

9 of 9 papers shown

1.

Pan, Pingbo, et al.. (2020). Continual Deep Learning by Functional Regularisation of Memorable Past. arXiv (Cornell University). 6 indexed citations

2.

Pan, Pingbo, et al.. (2020). Hierarchical Temporal Modeling With Mutual Distance Matching for Video Based Person Re-Identification. IEEE Transactions on Circuits and Systems for Video Technology. 31(2). 503–511. 35 indexed citations

3.

Pan, Pingbo, Ping Liu, Yan Yan, Tianbao Yang, & Yi Yang. (2020). Adversarial Localized Energy Network for Structured Prediction. Proceedings of the AAAI Conference on Artificial Intelligence. 34(4). 5347–5354. 3 indexed citations

4.

Zhu, Minfeng, Pingbo Pan, Wei Chen, & Yi Yang. (2020). EEMEFN: Low-Light Image Enhancement via Edge-Enhanced Multi-Exposure Fusion Network. Proceedings of the AAAI Conference on Artificial Intelligence. 34(7). 13106–13113. 142 indexed citations

5.

Zhu, Minfeng, Pingbo Pan, Wei Chen, & Yi Yang. (2019). DM-GAN: Dynamic Memory Generative Adversarial Networks for Text-To-Image Synthesis. 5795–5803. 346 indexed citations breakdown →

6.

Pan, Pingbo, Jiashi Feng, Ling Chen, & Yi Yang. (2017). Online compressed robust PCA. 1041–1048. 8 indexed citations

7.

Liang, Junwei, Jia Chen, Po-Yao Huang, et al.. (2016). Informedia @ TRECVID 2016.. TRECVID. 2 indexed citations

8.

Du, Xingzhong, Yan Yan, Pingbo Pan, Guodong Long, & Lei Zhao. (2015). Multiple graph unsupervised feature selection. Signal Processing. 120. 754–760. 26 indexed citations

9.

Wang, Sen, Pingbo Pan, Guodong Long, et al.. (2015). Compact representation for large-scale unconstrained video analysis. World Wide Web. 19(2). 231–246. 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.

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