Namhyuk Ahn

1.2k total citations
13 papers, 261 citations indexed

About

Namhyuk Ahn is a scholar working on Computer Vision and Pattern Recognition, Cognitive Neuroscience and Artificial Intelligence. According to data from OpenAlex, Namhyuk Ahn has authored 13 papers receiving a total of 261 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Computer Vision and Pattern Recognition, 2 papers in Cognitive Neuroscience and 2 papers in Artificial Intelligence. Recurrent topics in Namhyuk Ahn's work include Advanced Image Processing Techniques (5 papers), Image and Signal Denoising Methods (3 papers) and Generative Adversarial Networks and Image Synthesis (3 papers). Namhyuk Ahn is often cited by papers focused on Advanced Image Processing Techniques (5 papers), Image and Signal Denoising Methods (3 papers) and Generative Adversarial Networks and Image Synthesis (3 papers). Namhyuk Ahn collaborates with scholars based in South Korea, Canada and United States. Namhyuk Ahn's co-authors include Kyung-Ah Sohn, Byungkon Kang, Kibeom Hong, Junsoo Lee, Youngjung Uh, Pilhyeon Lee, Hyeran Byun, Jaejun Yoo, Seung-Hun Nam and Patrick Kwon and has published in prestigious journals such as Expert Systems with Applications, Pattern Recognition and International Journal of Computer Vision.

In The Last Decade

Namhyuk Ahn

11 papers receiving 254 citations

Peers

Namhyuk Ahn

CVPR

MT

AI

BE

CM

Liying Lu United States

Assaf Shocher Israel

Jan Kotera Czechia

Eduardo Pérez-Pellitero Germany

Maitreya Suin India

Majed El Helou Switzerland

Meiguang Jin Switzerland

Sunil Jaiswal India

Xinchen Ye China

Nicola Asuni Italy

Liying Lu United States

Namhyuk Ahn

214 ×0.9

CVPR

97 ×0.7

MT

9 ×0.5

AI

8 ×0.7

BE

8 ×0.9

CM

Citations per year, relative to Namhyuk Ahn Namhyuk Ahn (= 1×) peers Liying Lu

Countries citing papers authored by Namhyuk Ahn

Since Specialization

Citations

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

Fields of papers citing papers by Namhyuk Ahn

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Namhyuk Ahn

This figure shows the co-authorship network connecting the top 25 collaborators of Namhyuk Ahn. A scholar is included among the top collaborators of Namhyuk Ahn 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 Namhyuk Ahn. Namhyuk Ahn is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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13 of 13 papers shown

1.

Ahn, Namhyuk, et al.. (2025). Nearly Zero-Cost Protection Against Mimicry by Personalized Diffusion Models. 28801–28810.

2.

Hong, Kibeom, et al.. (2025). DiffBlender: Composable and versatile multimodal text-to-image diffusion models. Expert Systems with Applications. 297. 129345–129345.

3.

Ahn, Namhyuk, et al.. (2025). Magnitude Attention-based Dynamic Pruning. Expert Systems with Applications. 276. 126957–126957. 1 indexed citations

4.

Ahn, Namhyuk, et al.. (2024). DreamStyler: Paint by Style Inversion with Text-to-Image Diffusion Models. Proceedings of the AAAI Conference on Artificial Intelligence. 38(2). 674–681. 9 indexed citations

5.

Ahn, Namhyuk, Jaejun Yoo, & Kyung-Ah Sohn. (2024). Data Augmentation for Low-Level Vision: CutBlur and Mixture-of-Augmentation. International Journal of Computer Vision. 132(6). 2041–2059. 4 indexed citations

6.

Hong, Kibeom, Junsoo Lee, Namhyuk Ahn, et al.. (2023). AesPA-Net: Aesthetic Pattern-Aware Style Transfer Networks. 22701–22710. 21 indexed citations

7.

Ahn, Namhyuk, et al.. (2023). Decomposing texture and semantic for out-of-distribution detection. Expert Systems with Applications. 238. 121829–121829. 1 indexed citations

8.

Ahn, Namhyuk, et al.. (2023). Interactive Cartoonization with Controllable Perceptual Factors. 16827–16835. 5 indexed citations

9.

Ahn, Namhyuk, et al.. (2022). WebtoonMe: A Data-Centric Approach for Full-Body Portrait Stylization. 1–4. 5 indexed citations

10.

Ahn, Namhyuk, et al.. (2022). Exploiting Distortion Information for Multi-degraded Image Restoration. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). 536–545. 7 indexed citations

11.

Ahn, Namhyuk, Byungkon Kang, & Kyung-Ah Sohn. (2022). Efficient deep neural network for photo-realistic image super-resolution. Pattern Recognition. 127. 108649–108649. 21 indexed citations

12.

Ahn, Namhyuk, Byungkon Kang, & Kyung-Ah Sohn. (2019). Photo-realistic Image Super-resolution with Fast and Lightweight Cascading Residual Network.. 6 indexed citations

13.

Ahn, Namhyuk, Byungkon Kang, & Kyung-Ah Sohn. (2018). Image Super-Resolution via Progressive Cascading Residual Network. 904–9048. 181 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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