Junyeong Kim

772 total citations · 1 hit paper
23 papers, 469 citations indexed

About

Junyeong Kim is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Biomedical Engineering. According to data from OpenAlex, Junyeong Kim has authored 23 papers receiving a total of 469 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Computer Vision and Pattern Recognition, 11 papers in Artificial Intelligence and 3 papers in Biomedical Engineering. Recurrent topics in Junyeong Kim's work include Multimodal Machine Learning Applications (11 papers), Human Pose and Action Recognition (9 papers) and Domain Adaptation and Few-Shot Learning (5 papers). Junyeong Kim is often cited by papers focused on Multimodal Machine Learning Applications (11 papers), Human Pose and Action Recognition (9 papers) and Domain Adaptation and Few-Shot Learning (5 papers). Junyeong Kim collaborates with scholars based in South Korea, United States and Canada. Junyeong Kim's co-authors include Chang D. Yoo, Trung X. Pham, Jae Hyun Han, Sunghun Kang, Hee Seung Wang, Young-Hoon Jung, Keon Jae Lee, Hyunsin Park, Seong Kwang Hong and Kyungsu Kim and has published in prestigious journals such as Advanced Materials, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Access.

In The Last Decade

Junyeong Kim

16 papers receiving 458 citations

Hit Papers

Flexible Piezoelectric Acoustic Sensors and Machine Learn... 2019 2026 2021 2023 2019 50 100 150 200 250
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. Flexible Piezoelectric Acoustic Sensors and Machine Learning for Speech Processing
    2019 288 citations Young-Hoon Jung, Seong Kwang Hong et al. Advanced Materials profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Junyeong Kim South Korea 7 251 146 97 97 88 23 469
Trung X. Pham South Korea 10 298 1.2× 153 1.0× 116 1.2× 96 1.0× 115 1.3× 17 573
Sunghun Kang South Korea 8 247 1.0× 122 0.8× 96 1.0× 37 0.4× 107 1.2× 11 453
Xiu Ma China 8 255 1.0× 68 0.5× 96 1.0× 67 0.7× 51 0.6× 19 390
Hyunsin Park South Korea 9 377 1.5× 114 0.8× 159 1.6× 96 1.0× 131 1.5× 16 659
Ju Han South Korea 13 287 1.1× 339 2.3× 38 0.4× 42 0.4× 102 1.2× 19 614
Sairul Izwan Safie Malaysia 11 166 0.7× 68 0.5× 113 1.2× 23 0.2× 150 1.7× 49 548
Congjun Cao China 12 118 0.5× 88 0.6× 28 0.3× 30 0.3× 46 0.5× 36 347
Senam Tamakloe United States 3 380 1.5× 48 0.3× 178 1.8× 59 0.6× 190 2.2× 5 581
Jiangtao Yang China 10 172 0.7× 32 0.2× 37 0.4× 29 0.3× 105 1.2× 20 351

Countries citing papers authored by Junyeong Kim

Since Specialization
Citations

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

Fields of papers citing papers by Junyeong Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Junyeong Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Junyeong Kim. A scholar is included among the top collaborators of Junyeong Kim 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 Junyeong Kim. Junyeong Kim 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.
Kim, Mingi, et al.. (2025). Synergy-CLIP: Extending CLIP With Multi-Modal Integration for Robust Representation Learning. IEEE Access. 13. 65630–65642.
2.
Kim, Junyeong, et al.. (2025). Multimodal Latent Representation Learning for Video Moment Retrieval. Sensors. 25(14). 4528–4528.
3.
Park, Jin-Woo, et al.. (2024). MSV: Contribution of Modalities based on the Shapley Value. 1. 1–6. 1 indexed citations
4.
Kim, Junyeong, et al.. (2024). A Study on the Representativeness Heuristics Problem in Large Language Models. IEEE Access. 12. 147958–147966. 2 indexed citations
5.
Lee, Changhee, et al.. (2024). BioBridge: Unified Bio-Embedding With Bridging Modality in Code-Switched EMR. IEEE Access. 12. 141866–141877.
6.
Lee, Changhee, et al.. (2024). DSG-KD: Knowledge Distillation From Domain-Specific to General Language Models. IEEE Access. 12. 130973–130982.
7.
Kim, Junyeong, et al.. (2024). Contrasting Multi-Modal Similarity Framework for Video Scene Segmentation. IEEE Access. 12. 32408–32419.
8.
Vu, Thang, et al.. (2023). Scalable SoftGroup for 3D Instance Segmentation on Point Clouds. IEEE Transactions on Pattern Analysis and Machine Intelligence. 46(4). 1981–1995. 11 indexed citations
9.
Yoon, Sunjae, et al.. (2023). Joint Path Alignment Framework for 3D Human Pose and Shape Estimation From Video. IEEE Access. 11. 43267–43275. 2 indexed citations
10.
Kim, Junyeong, et al.. (2022). CE-BART: Cause-and-Effect BART for Visual Commonsense Generation. Sensors. 22(23). 9399–9399. 1 indexed citations
11.
Yoon, Sunjae, et al.. (2022). Cascaded MPN: Cascaded Moment Proposal Network for Video Corpus Moment Retrieval. IEEE Access. 10. 64560–64568. 3 indexed citations
12.
Yoon, Sunjae, et al.. (2021). Weakly-Supervised Moment Retrieval Network for Video Corpus Moment Retrieval. 534–538. 3 indexed citations
13.
Kim, Junyeong, et al.. (2021). Structured Co-reference Graph Attention for Video-grounded Dialogue. Proceedings of the AAAI Conference on Artificial Intelligence. 35(2). 1789–1797. 15 indexed citations
14.
Kim, Junyeong, Minuk Ma, Trung X. Pham, Kyungsu Kim, & Chang D. Yoo. (2020). Modality Shifting Attention Network for Multi-Modal Video Question Answering. 10103–10112. 55 indexed citations
15.
Jung, Young-Hoon, Seong Kwang Hong, Hee Seung Wang, et al.. (2020). Speech Recognition: Flexible Piezoelectric Acoustic Sensors and Machine Learning for Speech Processing (Adv. Mater. 35/2020). Advanced Materials. 32(35). 13 indexed citations
16.
Jung, Young-Hoon, Seong Kwang Hong, Hee Seung Wang, et al.. (2019). Flexible Piezoelectric Acoustic Sensors and Machine Learning for Speech Processing. Advanced Materials. 32(35). e1904020–e1904020. 288 indexed citations breakdown →
17.
Kim, Junyeong, et al.. (2019). Fire Detection Using Video Images and Temporal Variations. 3 indexed citations
18.
Kim, Junyeong, Minuk Ma, Kyungsu Kim, Sung-Jin Kim, & Chang D. Yoo. (2019). Progressive Attention Memory Network for Movie Story Question Answering. 8329–8338. 50 indexed citations
19.
20.
Kim, Junyeong & Chang D. Yoo. (2017). Deep partial person re-identification via attention model. 3425–3429. 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.

Explore authors with similar magnitude of impact

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