Sunghoon Im

978 total citations
35 papers, 517 citations indexed

About

Sunghoon Im is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Artificial Intelligence. According to data from OpenAlex, Sunghoon Im has authored 35 papers receiving a total of 517 indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Computer Vision and Pattern Recognition, 12 papers in Media Technology and 7 papers in Artificial Intelligence. Recurrent topics in Sunghoon Im's work include Advanced Vision and Imaging (23 papers), Optical measurement and interference techniques (15 papers) and Image Processing Techniques and Applications (12 papers). Sunghoon Im is often cited by papers focused on Advanced Vision and Imaging (23 papers), Optical measurement and interference techniques (15 papers) and Image Processing Techniques and Applications (12 papers). Sunghoon Im collaborates with scholars based in South Korea, United States and Canada. Sunghoon Im's co-authors include In So Kweon, Hae‐Gon Jeon, Hyowon Ha, Jin Woo Bae, Gyeongmin Choe, Sunghyun Cho, Jaesik Park, Joon‐Young Lee, Stephen Lin and Kyungdon Joo and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and International Journal of Computer Vision.

In The Last Decade

Sunghoon Im

32 papers receiving 498 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sunghoon Im South Korea	13	441	207	135	58	28	35	517
Tianfan Xue Hong Kong	14	551 1.2×	151 0.7×	59 0.4×	56 1.0×	15 0.5×	36	640
Xianghua Ying China	14	495 1.1×	165 0.8×	148 1.1×	47 0.8×	31 1.1×	58	587
Hang Dong China	11	841 1.9×	390 1.9×	74 0.5×	25 0.4×	18 0.6×	22	927
Naejin Kong South Korea	6	574 1.3×	149 0.7×	27 0.2×	45 0.8×	21 0.8×	7	707
Jordi Salvador Spain	9	406 0.9×	153 0.7×	37 0.3×	28 0.5×	12 0.4×	29	516
Richard Tucker United States	10	1.0k 2.3×	120 0.6×	93 0.7×	26 0.4×	35 1.3×	16	1.1k
David Ferstl Austria	7	648 1.5×	339 1.6×	59 0.4×	116 2.0×	17 0.6×	14	714
Yue Que China	14	525 1.2×	564 2.7×	65 0.5×	32 0.6×	17 0.6×	22	704
Jiandong Tian China	11	478 1.1×	150 0.7×	29 0.2×	27 0.5×	25 0.9×	31	546
Xin-Ji Lai China	4	188 0.4×	30 0.1×	85 0.6×	34 0.6×	39 1.4×	7	287

Countries citing papers authored by Sunghoon Im

Since Specialization

Citations

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

Fields of papers citing papers by Sunghoon Im

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sunghoon Im

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

Oh, Jean, et al.. (2025). Flow4D: Leveraging 4D Voxel Network for LiDAR Scene Flow Estimation. IEEE Robotics and Automation Letters. 10(4). 3462–3469. 1 indexed citations

Oh, Jean, et al.. (2024). Density-aware Domain Generalization for LiDAR Semantic Segmentation. 9573–9580.

Cho, Jae Hoon, et al.. (2024). Multi-task Learning for Real-time Autonomous Driving Leveraging Task-adaptive Attention Generator. 14732–14739. 1 indexed citations

Kim, Hojin, et al.. (2024). Offline-to-Online Knowledge Distillation for Video Instance Segmentation. 158–167. 5 indexed citations

Im, Sunghoon, et al.. (2023). A Study on the Generality of Neural Network Structures for Monocular Depth Estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence. 46(4). 2224–2238. 7 indexed citations

Im, Sunghoon, et al.. (2023). Dynamic Neural Network for Multi-Task Learning Searching across Diverse Network Topologies. 3779–3788. 2 indexed citations

Bae, Jin Woo, et al.. (2023). Deep Digging into the Generalization of Self-Supervised Monocular Depth Estimation. Proceedings of the AAAI Conference on Artificial Intelligence. 37(1). 187–196. 58 indexed citations

Lee, Seokju, François Rameau, Sunghoon Im, & In So Kweon. (2022). Self-Supervised Monocular Depth and Motion Learning in Dynamic Scenes: Semantic Prior to Rescue. International Journal of Computer Vision. 130(9). 2265–2285. 6 indexed citations

Im, Sunghoon, et al.. (2022). RVMOS: Range-View Moving Object Segmentation Leveraged by Semantic and Motion Features. IEEE Robotics and Automation Letters. 7(3). 8044–8051. 40 indexed citations

10.

Im, Sunghoon, et al.. (2022). ADAS: A Direct Adaptation Strategy for Multi-Target Domain Adaptive Semantic Segmentation. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 19174–19184. 16 indexed citations

11.

Kwon, Kon‐Woo, et al.. (2021). ZeBRA: Precisely Destroying Neural Networks with Zero-Data Based Repeated Bit Flip Attack.

12.

Jeon, Hae‐Gon, Sunghoon Im, Jean Oh, & Martial Hebert. (2020). Learning Shape-based Representation for Visual Localization in Extremely Changing Conditions. 7135–7141. 4 indexed citations

13.

Jeon, Hae‐Gon, et al.. (2019). Depth Completion with Deep Geometry and Context Guidance. 3281–3287. 25 indexed citations

14.

Im, Sunghoon, Hae‐Gon Jeon, Stephen Lin, & In So Kweon. (2019). DPSNet: End-to-end Deep Plane Sweep Stereo. arXiv (Cornell University). 33 indexed citations

15.

Choe, Gyeongmin, Seong‐heum Kim, Sunghoon Im, et al.. (2018). RANUS: RGB and NIR Urban Scene Dataset for Deep Scene Parsing. IEEE Robotics and Automation Letters. 3(3). 1808–1815. 29 indexed citations

16.

Shin, Seunghak, Sunghoon Im, Inwook Shim, Hae‐Gon Jeon, & In So Kweon. (2017). Geometry Guided Three-Dimensional Propagation for Depth From Small Motion. IEEE Signal Processing Letters. 24(12). 1857–1861. 5 indexed citations

17.

Jeon, Hae‐Gon, et al.. (2017). Noise Robust Depth from Focus Using a Ring Difference Filter. 2444–2453. 25 indexed citations

18.

Jeon, Hae‐Gon, Joon‐Young Lee, Sunghoon Im, Hyowon Ha, & In So Kweon. (2016). Stereo Matching with Color and Monochrome Cameras in Low-Light Conditions. 4086–4094. 35 indexed citations

19.

Im, Sunghoon, Hae‐Gon Jeon, Hyowon Ha, & In So Kweon. (2015). Depth estimation from light field cameras. 32. 190–191. 1 indexed citations

20.

Im, Sunghoon, Hyowon Ha, Gyeongmin Choe, et al.. (2015). High Quality Structure from Small Motion for Rolling Shutter Cameras. 837–845. 28 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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