Junran Peng

593 total citations
22 papers, 301 citations indexed

About

Junran Peng is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Control and Systems Engineering. According to data from OpenAlex, Junran Peng has authored 22 papers receiving a total of 301 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computer Vision and Pattern Recognition, 7 papers in Artificial Intelligence and 4 papers in Control and Systems Engineering. Recurrent topics in Junran Peng's work include Advanced Neural Network Applications (11 papers), Advanced Image and Video Retrieval Techniques (7 papers) and Domain Adaptation and Few-Shot Learning (5 papers). Junran Peng is often cited by papers focused on Advanced Neural Network Applications (11 papers), Advanced Image and Video Retrieval Techniques (7 papers) and Domain Adaptation and Few-Shot Learning (5 papers). Junran Peng collaborates with scholars based in China, India and United States. Junran Peng's co-authors include Zhaoxiang Zhang, Yuxi Wang, Junjie Yan, Tieniu Tan, Ming Sun, Cong Pan, Jiaheng Liu, Jingyu Liu, Anzi Ding and Yongzhen Huang and has published in prestigious journals such as Pattern Recognition, International Journal of Computer Vision and IET Generation Transmission & Distribution.

In The Last Decade

Junran Peng

21 papers receiving 294 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Junran Peng China	11	181	135	28	23	22	22	301
Chuming Li China	9	187 1.0×	145 1.1×	32 1.1×	10 0.4×	27 1.2×	18	326
Qinghao Hu China	7	208 1.1×	128 0.9×	37 1.3×	12 0.5×	22 1.0×	14	320
Seong‐heum Kim South Korea	8	137 0.8×	90 0.7×	37 1.3×	17 0.7×	32 1.5×	18	323
Gongfan Fang China	6	169 0.9×	156 1.2×	20 0.7×	8 0.3×	13 0.6×	12	328
Junge Zhang China	11	417 2.3×	101 0.7×	33 1.2×	25 1.1×	31 1.4×	31	549
Changhong Liu China	9	211 1.2×	108 0.8×	28 1.0×	7 0.3×	13 0.6×	38	357
Yongxi Lu United States	4	252 1.4×	140 1.0×	14 0.5×	12 0.5×	32 1.5×	5	353
Chongxuan Li China	10	174 1.0×	135 1.0×	46 1.6×	13 0.6×	9 0.4×	20	341
Philipp Benz South Korea	11	252 1.4×	241 1.8×	30 1.1×	22 1.0×	16 0.7×	12	447
Huaidong Zhang China	12	244 1.3×	158 1.2×	13 0.5×	18 0.8×	15 0.7×	38	388

Countries citing papers authored by Junran Peng

Since Specialization

Citations

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

Fields of papers citing papers by Junran Peng

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Junran Peng

This figure shows the co-authorship network connecting the top 25 collaborators of Junran Peng. A scholar is included among the top collaborators of Junran Peng 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 Junran Peng. Junran Peng 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:

20 of 20 papers shown

Zhou, Mengqi, Yuxi Wang, Jun Hou, et al.. (2025). SceneX: Procedural Controllable Large-Scale Scene Generation. Proceedings of the AAAI Conference on Artificial Intelligence. 39(10). 10806–10814. 1 indexed citations

Liu, Jiaheng, Wangchunshu Zhou, Yuhan Wu, et al.. (2024). RoleLLM: Benchmarking, Eliciting, and Enhancing Role-Playing Abilities of Large Language Models. 14743–14777. 22 indexed citations

Liu, Jiaheng, Kaisiyuan Wang, Jian Yang, et al.. (2024). LTA-PCS: Learnable Task-Agnostic Point Cloud Sampling. 28035–28045. 3 indexed citations

Luo, Chuanchen, Yuxi Wang, Xu-Cheng Yin, et al.. (2024). HardMo: A Large-Scale Hardcase Dataset for Motion Capture. 1629–1638.

Yang, Jian, Jiaheng Liu, Boyang Wang, et al.. (2024). LogFormer: A Pre-train and Tuning Pipeline for Log Anomaly Detection. Proceedings of the AAAI Conference on Artificial Intelligence. 38(1). 135–143. 13 indexed citations

Pan, Cong, et al.. (2023). BAEFormer: Bi-Directional and Early Interaction Transformers for Bird's Eye View Semantic Segmentation. 9590–9599. 13 indexed citations

Wei, Xin, et al.. (2022). Faint Features Tell: Automatic Vertebrae Fracture Screening Assisted by Contrastive Learning. 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). 848–853. 1 indexed citations

Peng, Junran, et al.. (2022). DATA: Domain-Aware and Task-Aware Self-supervised Learning. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 9831–9840. 5 indexed citations

Peng, Junran, et al.. (2021). Context-aware co-supervision for accurate object detection. Pattern Recognition. 121. 108199–108199. 32 indexed citations

10.

Peng, Junran, et al.. (2021). GAIA: A Transfer Learning System of Object Detection that Fits Your Needs. 274–283. 21 indexed citations

11.

Wang, Yuxi, Junran Peng, & Zhaoxiang Zhang. (2021). Uncertainty-aware Pseudo Label Refinery for Domain Adaptive Semantic Segmentation. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 9072–9081. 65 indexed citations

12.

Peng, Junran, et al.. (2020). Large-Scale Object Detection in the Wild From Imbalanced Multi-Labels. 9706–9715. 38 indexed citations

13.

Chen, Qing, et al.. (2020). Identifying single‐phase to ground fault based on line multi‐dimensional data in cyber‐physical distribution system. IET Generation Transmission & Distribution. 15(5). 950–959. 3 indexed citations

14.

Chen, Qing, et al.. (2020). Extremely low frequency‐based faulty line selection of low‐resistance grounding system. IET Generation Transmission & Distribution. 15(10). 1565–1577. 4 indexed citations

15.

Peng, Junran, Ming Sun, Zhaoxiang Zhang, Tieniu Tan, & Junjie Yan. (2019). Efficient Neural Architecture Transformation Search in Channel-Level for Object Detection. arXiv (Cornell University). 32. 14290–14299. 22 indexed citations

16.

Peng, Junran, Ming Sun, Zhaoxiang Zhang, Tieniu Tan, & Junjie Yan. (2019). POD: Practical Object Detection With Scale-Sensitive Network. 9606–9615. 18 indexed citations

17.

Peng, Junran, et al.. (2017). Study of the short-term electric load forecast based on ANFIS. 18. 832–836. 6 indexed citations

18.

Peng, Junran, et al.. (2016). Design of Programmable DC Electronic Load. 351–355. 4 indexed citations

19.

Liu, Jingyu, et al.. (2016). Fast Object Detection at Constrained Energy. IEEE Transactions on Emerging Topics in Computing. 6(3). 409–416. 10 indexed citations

20.

Lu, Yung-Hsiang, Alan M. Kadin, Alexander C. Berg, et al.. (2015). Rebooting Computing and Low-Power Image Recognition Challenge. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 927–932. 14 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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