Heewon Kim

3.3k total citations
22 papers, 605 citations indexed

About

Heewon Kim is a scholar working on Computer Vision and Pattern Recognition, Electronic, Optical and Magnetic Materials and Materials Chemistry. According to data from OpenAlex, Heewon Kim has authored 22 papers receiving a total of 605 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computer Vision and Pattern Recognition, 4 papers in Electronic, Optical and Magnetic Materials and 4 papers in Materials Chemistry. Recurrent topics in Heewon Kim's work include Advanced Vision and Imaging (6 papers), Advanced Image Processing Techniques (6 papers) and Crystal Structures and Properties (4 papers). Heewon Kim is often cited by papers focused on Advanced Vision and Imaging (6 papers), Advanced Image Processing Techniques (6 papers) and Crystal Structures and Properties (4 papers). Heewon Kim collaborates with scholars based in South Korea, China and United States. Heewon Kim's co-authors include Kyoung Mu Lee, Myungsub Choi, Bohyung Han, Ning Xu, Sungyong Baik, Zhiyong Bai, Kang Min Ok, Jihyun Lee, Chi‐Young Lee and Jaesik Min and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and Small.

In The Last Decade

Heewon Kim

20 papers receiving 587 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Heewon Kim South Korea	12	281	106	77	71	62	22	605
Zhihao Wu China	9	341 1.2×	343 3.2×	132 1.7×	30 0.4×	75 1.2×	16	1.0k
Fengjun Zhao China	15	130 0.5×	78 0.7×	63 0.8×	15 0.2×	70 1.1×	65	634
Yun Jiang China	18	471 1.7×	341 3.2×	102 1.3×	24 0.3×	32 0.5×	64	1.3k
Giorgos Papanastasiou United Kingdom	15	174 0.6×	153 1.4×	14 0.2×	39 0.5×	22 0.4×	53	742
Xinxin Wang China	15	59 0.2×	96 0.9×	25 0.3×	60 0.8×	44 0.7×	44	549
Danyu Liu China	13	116 0.4×	339 3.2×	38 0.5×	9 0.1×	39 0.6×	35	728
Chengjia Wang United Kingdom	12	158 0.6×	159 1.5×	8 0.1×	42 0.6×	48 0.8×	28	541
Yiqing Shi China	12	130 0.5×	64 0.6×	9 0.1×	53 0.7×	24 0.4×	40	346
Mingfei Li China	17	183 0.7×	101 1.0×	9 0.1×	242 3.4×	43 0.7×	84	999

Countries citing papers authored by Heewon Kim

Since Specialization

Citations

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

Fields of papers citing papers by Heewon Kim

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Heewon Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Heewon Kim. A scholar is included among the top collaborators of Heewon 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 Heewon Kim. Heewon Kim 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

Lee, Sangmin, Sungyong Park, & Heewon Kim. (2025). DynScene: Scalable Generation of Dynamic Robotic Manipulation Scenes for Embodied AI. 12166–12175.

Bai, Zhiyong, Jihyun Lee, Heewon Kim, et al.. (2023). A Rare‐Earth Selenite with Unexpectedly Well‐Balanced Ultraviolet Nonlinear Optical Functionality, Sc(HSeO₃)₃ (Small 19/2023). Small. 19(19). 1 indexed citations

Choi, Jaekyung, Yu Ra Jeong, Jun Hyuk Song, et al.. (2023). High‐resolution active‐matrix micro‐LED stretchable displays. Journal of the Society for Information Display. 31(5). 201–210. 12 indexed citations

Baik, Sungyong, et al.. (2023). Learning to Learn Task-Adaptive Hyperparameters for Few-Shot Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence. 46(3). 1441–1454. 21 indexed citations

Bai, Zhiyong, Jihyun Lee, Heewon Kim, et al.. (2023). A Rare‐Earth Selenite with Unexpectedly Well‐Balanced Ultraviolet Nonlinear Optical Functionality, Sc(HSeO₃)₃. Small. 19(19). e2207709–e2207709. 24 indexed citations

Kim, Heewon, et al.. (2023). Beyond the Accident Republic: Making Life and Safety with Disaster Memorials in Korea. 45(2). 161–203.

Kim, Heewon & Kyoung Mu Lee. (2023). Learning Controllable ISP for Image Enhancement. IEEE Transactions on Image Processing. 33. 867–880. 1 indexed citations

Bai, Zhiyong, Jihyun Lee, Heewon Kim, Chun‐Li Hu, & Kang Min Ok. (2023). Unveiling the Superior Optical Properties of Novel Melamine‐Based Nonlinear Optical Material with Strong Second‐Harmonic Generation and Giant Optical Anisotropy. Small. 19(28). e2301756–e2301756. 51 indexed citations

Lee, Chi‐Young & Heewon Kim. (2022). Machine learning-based predictive modeling of depression in hypertensive populations. PLoS ONE. 17(7). e0272330–e0272330. 29 indexed citations

10.

Kim, Heewon, et al.. (2022). Attentive Fine-Grained Structured Sparsity for Image Restoration. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 17652–17661. 10 indexed citations

11.

Kim, Heewon, et al.. (2022). DAQ: Channel-Wise Distribution-Aware Quantization for Deep Image Super-Resolution Networks. 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 913–922. 23 indexed citations

12.

Cha, Seunghee, et al.. (2022). Effects of Silica Shell Encapsulated Nanocrystals on Active χ-Fe5C2 Phase and Fischer–Tropsch Synthesis. Nanomaterials. 12(20). 3704–3704. 3 indexed citations

13.

Choi, Myungsub, Suyoung Lee, Heewon Kim, & Kyoung Mu Lee. (2021). Motion-Aware Dynamic Architecture for Efficient Frame Interpolation. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 13819–13828. 15 indexed citations

14.

Baik, Sungyong, et al.. (2021). Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 9445–9454. 92 indexed citations

15.

Choi, Myungsub, Heewon Kim, Bohyung Han, Ning Xu, & Kyoung Mu Lee. (2020). Channel Attention Is All You Need for Video Frame Interpolation. Proceedings of the AAAI Conference on Artificial Intelligence. 34(7). 10663–10671. 182 indexed citations

16.

Kim, Heewon, Yunji Hwang, Jieun Jang, et al.. (2017). Effectiveness of Gastric Cancer Screening on Gastric Cancer Incidence and Mortality in a Community-Based Prospective Cohort. Cancer Research and Treatment. 50(2). 582–589. 76 indexed citations

17.

Kim, Heewon, et al.. (2008). Real-time object recognition and modeling for heavy-equipment operation. 232–237. 6 indexed citations

18.

Choi, Noah C., Hyeck-Soo Son, Chong Kim, Chong Kim, & Heewon Kim. (2008). Rapid 3D object recognition for automatic project progress monitoring using a stereo vision system. 58–63. 3 indexed citations

19.

Kim, Heewon, et al.. (2004). Digital Imaging in Assessment of Construction Project Progress. Proceedings of the ... ISARC. 21 indexed citations

20.

Kim, Tae‐Kyun, et al.. (2002). Component-based LDA Face Descriptor for Image Retrieval. 49.1–49.10. 24 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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