Jun Kong

1.7k total citations
119 papers, 1.2k citations indexed

About

Jun Kong is a scholar working on Computer Vision and Pattern Recognition, Biomedical Engineering and Artificial Intelligence. According to data from OpenAlex, Jun Kong has authored 119 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 97 papers in Computer Vision and Pattern Recognition, 39 papers in Biomedical Engineering and 26 papers in Artificial Intelligence. Recurrent topics in Jun Kong's work include Video Surveillance and Tracking Methods (45 papers), Human Pose and Action Recognition (37 papers) and Gait Recognition and Analysis (31 papers). Jun Kong is often cited by papers focused on Video Surveillance and Tracking Methods (45 papers), Human Pose and Action Recognition (37 papers) and Gait Recognition and Analysis (31 papers). Jun Kong collaborates with scholars based in China, Hong Kong and United States. Jun Kong's co-authors include Min Jiang, Tianshan Liu, Jianzhong Wang, Baoxue Zhang, Hongtao Huo, Kin‐Man Lam, Miao Qi, Yinghua Lu, Shengwei Tian and Zhiyin Wang and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Image Processing and IEEE Access.

In The Last Decade

Jun Kong

109 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jun Kong China 20 837 339 263 159 88 119 1.2k
Jie Nie China 18 815 1.0× 350 1.0× 125 0.5× 119 0.7× 43 0.5× 124 1.3k
Ross Goroshin United States 5 664 0.8× 421 1.2× 100 0.4× 42 0.3× 91 1.0× 8 1.1k
Huiyuan Fu China 15 760 0.9× 196 0.6× 127 0.5× 193 1.2× 39 0.4× 55 1.0k
Junqing Yu China 20 1.1k 1.4× 811 2.4× 140 0.5× 122 0.8× 25 0.3× 78 1.8k
Sergey Ablameyko Belarus 12 568 0.7× 207 0.6× 87 0.3× 92 0.6× 25 0.3× 129 955
Hao Zhou China 19 617 0.7× 229 0.7× 90 0.3× 73 0.5× 27 0.3× 74 1.2k
Dongyu Zhang China 15 691 0.8× 487 1.4× 210 0.8× 86 0.5× 24 0.3× 47 1.4k
Chi Su China 16 1.7k 2.0× 536 1.6× 530 2.0× 94 0.6× 64 0.7× 43 2.0k
Qi Lv China 14 256 0.3× 212 0.6× 66 0.3× 117 0.7× 23 0.3× 59 690
Hélène Laurent France 13 501 0.6× 108 0.3× 58 0.2× 83 0.5× 25 0.3× 36 853

Countries citing papers authored by Jun Kong

Since Specialization
Citations

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

Fields of papers citing papers by Jun Kong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jun Kong

This figure shows the co-authorship network connecting the top 25 collaborators of Jun Kong. A scholar is included among the top collaborators of Jun Kong 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 Jun Kong. Jun Kong 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.
Jiang, Min, et al.. (2025). AU-Net: Adaptive Unified Network for Joint Multi-Modal Image Registration and Fusion. IEEE Transactions on Image Processing. 34. 4721–4735.
2.
Kong, Jun, et al.. (2025). Temporal Action Localization with Cross Layer Task Decoupling and Refinement. Proceedings of the AAAI Conference on Artificial Intelligence. 39(5). 4878–4886.
3.
Kong, Jun, et al.. (2024). Cue-based two factor authentication. Computers & Security. 146. 104068–104068. 1 indexed citations
4.
Luo, X. L., et al.. (2024). Hierarchical Camera-Aware Contrast Extension for Unsupervised Person Re-Identification. IEEE Transactions on Multimedia. 26. 7636–7648. 6 indexed citations
5.
Jiang, Min, et al.. (2024). Learning Semantic Polymorphic Mapping for Text-Based Person Retrieval. IEEE Transactions on Multimedia. 26. 10678–10691. 6 indexed citations
6.
Kong, Jun, et al.. (2024). Unsupervised Learning of Intrinsic Semantics With Diffusion Model for Person Re-Identification. IEEE Transactions on Image Processing. 33. 6705–6719. 2 indexed citations
7.
Kong, Jun, et al.. (2024). Semantic Camera Self-Aware Contrastive Learning for Unsupervised Vehicle Re-Identification. IEEE Signal Processing Letters. 31. 2175–2179.
8.
Liu, Tianshan, et al.. (2024). Category-Aware Saliency Enhance Learning Based on CLIP for Weakly Supervised Salient Object Detection. Neural Processing Letters. 56(2). 2 indexed citations
9.
Kong, Jun, Hua Zhou, Min Jiang, & Tianshan Liu. (2024). Part-pixel transformer with smooth alignment fusion for domain adaptation person re-identification. Signal Image and Video Processing. 18(4). 3737–3744. 2 indexed citations
10.
Kong, Jun, et al.. (2024). Igtracker: task and instance information gaps in multiple object tracking. International Journal of Machine Learning and Cybernetics. 16(1). 143–158. 1 indexed citations
11.
Jiang, Min, et al.. (2023). Participants-based Synchronous Optimization Network for skeleton-based action recognition. Pattern Recognition Letters. 176. 182–188. 1 indexed citations
12.
Jiang, Min, et al.. (2023). LDRepFM: A Real-Time End-to-End Visible and Infrared Image Fusion Model Based on Layer Decomposition and Re-Parameterization. IEEE Transactions on Instrumentation and Measurement. 72. 1–12. 18 indexed citations
13.
Kong, Jun, et al.. (2023). Motion information supplement for joint detection and embedding tracking. Journal of Electronic Imaging. 32(5). 1 indexed citations
14.
Jiang, Min, et al.. (2023). Feature difference and feature correlation learning mechanism for skeleton-based action recognition. Journal of Electronic Imaging. 32(1). 2 indexed citations
15.
Kong, Jun, Shengquan Wang, Min Jiang, & Tianshan Liu. (2023). Multi-stream ternary enhanced graph convolutional network for skeleton-based action recognition. Neural Computing and Applications. 35(25). 18487–18504. 5 indexed citations
16.
Kong, Jun, et al.. (2022). Weakly Supervised Distribution Discrepancy Minimization Learning With State Information for Person Re-Identification. IEEE Transactions on Multimedia. 25. 1903–1915. 6 indexed citations
17.
Kong, Jun, et al.. (2021). Unsupervised Domain Adaptation by Multi-Loss Gap Minimization Learning for Person Re-Identification. IEEE Transactions on Circuits and Systems for Video Technology. 32(7). 4404–4416. 22 indexed citations
18.
Yin, Xueyan, et al.. (2019). Low-rank graph optimization for multi-view dimensionality reduction. PLoS ONE. 14(12). e0225987–e0225987. 5 indexed citations
19.
Kong, Jun, Zijie Li, Huijie Zhang, Xiao‐Dong Gao, & Hideki Nakanishi. (2016). Consecutive hydrolysis of creatinine using creatininase and creatinase encapsulated in Saccharomyces cerevisiae spores. Biotechnology Letters. 39(2). 261–267. 3 indexed citations
20.
Kong, Jun & Zheru Chi. (1998). Image Classification Using Kolmogorov COmplexity Measure with Randomly Extracted Blocks. IEICE Transactions on Information and Systems. 81(11). 1239–1246. 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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