Fengjun Lv

5.2k total citations · 1 hit paper
19 papers, 3.6k citations indexed

About

Fengjun Lv is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology. According to data from OpenAlex, Fengjun Lv has authored 19 papers receiving a total of 3.6k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Computer Vision and Pattern Recognition, 5 papers in Artificial Intelligence and 2 papers in Media Technology. Recurrent topics in Fengjun Lv's work include Video Surveillance and Tracking Methods (11 papers), Human Pose and Action Recognition (9 papers) and Advanced Image and Video Retrieval Techniques (4 papers). Fengjun Lv is often cited by papers focused on Video Surveillance and Tracking Methods (11 papers), Human Pose and Action Recognition (9 papers) and Advanced Image and Video Retrieval Techniques (4 papers). Fengjun Lv collaborates with scholars based in United States, China and Singapore. Fengjun Lv's co-authors include Thomas S. Huang, Shuicheng Yan, Kai Yu, Yihong Gong, Jinjun Wang, Ramakant Nevatia, R. Nevatia, Liangliang Cao, Tao Zhao and Shenghuo Zhu and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Fuel and Remote Sensing.

In The Last Decade

Fengjun Lv

18 papers receiving 3.5k 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.

Locality-constrained Linear Coding for image classification

2010 2.3k citations Jinjun Wang, Shuicheng Yan et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Fengjun Lv United States	15	3.2k	982	602	339	300	19	3.6k
Wankou Yang China	27	2.2k 0.7×	759 0.8×	483 0.8×	255 0.8×	214 0.7×	164	3.0k
Errui Ding China	37	4.3k 1.4×	1.2k 1.2×	682 1.1×	148 0.4×	246 0.8×	114	4.9k
Lizhuang Ma China	38	3.5k 1.1×	941 1.0×	709 1.2×	600 1.8×	187 0.6×	321	4.9k
Shiliang Pu China	33	2.9k 0.9×	1.8k 1.8×	358 0.6×	192 0.6×	385 1.3×	150	3.9k
Xiaobai Liu United States	22	2.4k 0.8×	820 0.8×	277 0.5×	162 0.5×	168 0.6×	67	3.1k
Oncel Tuzel United States	31	3.4k 1.1×	943 1.0×	897 1.5×	154 0.5×	302 1.0×	59	4.5k
Yi-Zhe Song United Kingdom	38	4.3k 1.4×	1.8k 1.9×	278 0.5×	412 1.2×	212 0.7×	164	5.5k
Arif Mahmood Pakistan	28	1.7k 0.5×	887 0.9×	375 0.6×	130 0.4×	357 1.2×	121	2.7k
Yee‐Hong Yang Canada	36	2.9k 0.9×	310 0.3×	618 1.0×	214 0.6×	193 0.6×	162	3.7k
Hassan Foroosh United States	22	1.7k 0.5×	604 0.6×	218 0.4×	319 0.9×	264 0.9×	135	2.4k

Countries citing papers authored by Fengjun Lv

Since Specialization

Citations

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

Fields of papers citing papers by Fengjun Lv

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fengjun Lv

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

19 of 19 papers shown

1.

Deng, Yuhua, Tingsong Li, Dongmei Deng, et al.. (2025). The Association Between Elevated Estimated Glomerular Filtration Rate and Poor Clinical Outcomes of Pediatric Patients with Community-Acquired Bacterial Meningitis Receiving Vancomycin: A Ten-Year Retrospective Cohort Study. Infectious Diseases and Therapy. 14(8). 1899–1916.

2.

Wang, Yixue, et al.. (2023). A Scale Conversion Model Based on Deep Learning of UAV Images. Remote Sensing. 15(9). 2449–2449. 4 indexed citations

3.

Li, Pengfei, Fengjun Lv, Zhiyuan Wang, et al.. (2022). Promotion and inhibition effects of wax on methane hydrate formation and dissociation in water-in-oil emulsions. Fuel. 337. 127211–127211. 30 indexed citations

4.

Liu, Qingshan, et al.. (2011). Unsupervised Image Categorization by Hypergraph Partition. IEEE Transactions on Pattern Analysis and Machine Intelligence. 33(6). 1266–1273. 71 indexed citations

5.

Yang, Ming, Shenghuo Zhu, Fengjun Lv, & Kai Yu. (2011). Correspondence driven adaptation for human profile recognition. 1. 505–512. 28 indexed citations

6.

Lin, Yuanqing, Fengjun Lv, Shenghuo Zhu, et al.. (2011). Large-scale image classification: Fast feature extraction and SVM training. 1689–1696. 291 indexed citations

7.

Wang, Jinjun, Shuicheng Yan, Kai Yu, et al.. (2010). Locality-constrained Linear Coding for image classification. 3360–3367. 2317 indexed citations breakdown →

8.

Yan, Shuicheng, Yuanqing Lin, Fengjun Lv, et al.. (2010). Videos Semantic Indexing using Image Classification.. 3 indexed citations

9.

Yang, Ming, et al.. (2009). Detection driven adaptive multi-cue integration for multiple human tracking. 1554–1561. 60 indexed citations

10.

Yang, Ming, et al.. (2009). Human action detection by boosting efficient motion features. 522–529. 26 indexed citations

11.

Hu, Yuxiao, Liangliang Cao, Fengjun Lv, et al.. (2009). Action detection in complex scenes with spatial and temporal ambiguities. National University of Singapore. 128–135. 107 indexed citations

12.

Yang, Ming, Shuiwang Ji, Wei Xu, et al.. (2009). Detecting Human Actions in Surveillance Videos.. 21 indexed citations

13.

Dikmen, Mert, Huazhong Ning, Dennis Lin, et al.. (2008). Surveillance Event Detection.. Own your potential (DEAKIN). 1–10. 27 indexed citations

14.

Lv, Fengjun & Ramakant Nevatia. (2007). Single View Human Action Recognition using Key Pose Matching and Viterbi Path Searching. 1–8. 295 indexed citations

15.

Lv, Fengjun, et al.. (2006). Left-Luggage Detection using Bayesian Inference. 41 indexed citations

16.

Lv, Fengjun, Tao Zhao, & R. Nevatia. (2006). Camera calibration from video of a walking human. IEEE Transactions on Pattern Analysis and Machine Intelligence. 28(9). 1513–1518. 129 indexed citations

17.

Zhao, Tao, R. Nevatia, & Fengjun Lv. (2005). Segmentation and tracking of multiple humans in complex situations. 2. II–194. 54 indexed citations

18.

Lv, Fengjun, et al.. (2004). Automatic Tracking and Labeling of Human Activities in a Video Sequence. 14 indexed citations

19.

Lv, Fengjun, Tao Zhao, & Ram Nevatia. (2003). Self-calibration of a camera from video of a walking human. 1. 562–567. 94 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.

Explore authors with similar magnitude of impact