Dong Huk Park

2.6k total citations · 1 hit paper
8 papers, 267 citations indexed

About

Dong Huk Park is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Graphics and Computer-Aided Design. According to data from OpenAlex, Dong Huk Park has authored 8 papers receiving a total of 267 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computer Vision and Pattern Recognition, 2 papers in Artificial Intelligence and 2 papers in Computer Graphics and Computer-Aided Design. Recurrent topics in Dong Huk Park's work include Advanced Image and Video Retrieval Techniques (4 papers), Multimodal Machine Learning Applications (4 papers) and Image Retrieval and Classification Techniques (3 papers). Dong Huk Park is often cited by papers focused on Advanced Image and Video Retrieval Techniques (4 papers), Multimodal Machine Learning Applications (4 papers) and Image Retrieval and Classification Techniques (3 papers). Dong Huk Park collaborates with scholars based in United States, Hong Kong and France. Dong Huk Park's co-authors include Trevor Darrell, Anna Rohrbach, Xihui Liu, Samaneh Azadi, Kate Saenko, Lisa Anne Hendricks, Vasili Ramanishka, Abir Das, Marcus Rohrbach and Subhashini Venugopalan and has published in prestigious journals such as Neural Information Processing Systems, 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) and 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).

In The Last Decade

Dong Huk Park

8 papers receiving 257 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.

More Control for Free! Image Synthesis with Semantic Diffusion Guidance

2023 106 citations Xihui Liu, Dong Huk Park et al. 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Dong Huk Park United States	6	217	67	20	16	13	8	267
Ligong Han United States	8	207 1.0×	58 0.9×	48 2.4×	15 0.9×	13 1.0×	19	278
Samaneh Azadi United States	7	133 0.6×	60 0.9×	22 1.1×	32 2.0×	14 1.1×	11	204
Erika Lu United States	6	239 1.1×	59 0.9×	22 1.1×	12 0.8×	8 0.6×	9	268
Ziqi Huang Singapore	6	169 0.8×	40 0.6×	11 0.6×	9 0.6×	19 1.5×	11	221
Gwanghyun Kim South Korea	3	227 1.0×	62 0.9×	51 2.5×	32 2.0×	20 1.5×	3	283
Axel Sauer Germany	3	138 0.6×	57 0.9×	25 1.3×	11 0.7×	13 1.0×	3	179
Tim Dockhorn Germany	2	200 0.9×	43 0.6×	44 2.2×	16 1.0×	28 2.2×	2	262
Hila Chefer Israel	4	169 0.8×	47 0.7×	48 2.4×	12 0.8×	20 1.5×	4	226
Konpat Preechakul Thailand	4	152 0.7×	63 0.9×	16 0.8×	24 1.5×	19 1.5×	4	211
Gihyun Kwon South Korea	5	192 0.9×	53 0.8×	42 2.1×	9 0.6×	19 1.5×	11	230

Countries citing papers authored by Dong Huk Park

Since Specialization

Citations

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

Fields of papers citing papers by Dong Huk Park

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dong Huk Park. 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 Dong Huk Park. The network helps show where Dong Huk Park may publish in the future.

Co-authorship network of co-authors of Dong Huk Park

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

8 of 8 papers shown

1.

Park, Dong Huk, et al.. (2024). Shape-Guided Diffusion with Inside-Outside Attention. 4186–4195. 8 indexed citations

2.

Liu, Xihui, Dong Huk Park, Samaneh Azadi, et al.. (2023). More Control for Free! Image Synthesis with Semantic Diffusion Guidance. 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 289–299. 106 indexed citations breakdown →

3.

Wu, Haoyu, et al.. (2022). Billion-Scale Pretraining with Vision Transformers for Multi-Task Visual Representations. 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 11 indexed citations

4.

Park, Dong Huk, Samaneh Azadi, Xihui Liu, Trevor Darrell, & Anna Rohrbach. (2021). Benchmark for Compositional Text-to-Image Synthesis. Neural Information Processing Systems. 25 indexed citations

5.

Park, Dong Huk & Trevor Darrell. (2021). Novelty Detection with Rotated Contrastive Predictive Coding. 1 indexed citations

6.

Zhai, Andrew, Haoyu Wu, Eric Tzeng, Dong Huk Park, & Charles Rosenberg. (2019). Learning a Unified Embedding for Visual Search at Pinterest. 2412–2420. 23 indexed citations

7.

Park, Dong Huk, Trevor Darrell, & Anna Rohrbach. (2019). Viewpoint Invariant Change Captioning.. 2 indexed citations

8.

Ramanishka, Vasili, Abir Das, Dong Huk Park, et al.. (2016). Multimodal Video Description. 1092–1096. 91 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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