Shuochen Su

1.0k total citations · 1 hit paper
9 papers, 613 citations indexed

About

Shuochen Su is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Instrumentation. According to data from OpenAlex, Shuochen Su has authored 9 papers receiving a total of 613 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computer Vision and Pattern Recognition, 6 papers in Media Technology and 3 papers in Instrumentation. Recurrent topics in Shuochen Su's work include Advanced Vision and Imaging (7 papers), Image Processing Techniques and Applications (6 papers) and Optical measurement and interference techniques (6 papers). Shuochen Su is often cited by papers focused on Advanced Vision and Imaging (7 papers), Image Processing Techniques and Applications (6 papers) and Optical measurement and interference techniques (6 papers). Shuochen Su collaborates with scholars based in Canada, United States and Saudi Arabia. Shuochen Su's co-authors include Wolfgang Heidrich, Oliver Wang, Jue Wang, Mauricio Delbracio, Guillermo Sapiro, Felix Heide, Gordon Wetzstein, Qiang Fu, Yifan Peng and Ulrich Neumann and has published in prestigious journals such as IEEE Transactions on Image Processing, Optics Express and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

In The Last Decade

Shuochen Su

9 papers receiving 598 citations

Hit Papers

Deep Video Deblurring for Hand-Held Cameras 2017 2026 2020 2023 2017 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shuochen Su Canada 7 508 235 89 70 31 9 613
Tom E. Bishop United Kingdom 7 467 0.9× 243 1.0× 21 0.2× 50 0.7× 19 0.6× 13 525
Gurunandan Krishnan United States 4 327 0.6× 98 0.4× 111 1.2× 64 0.9× 17 0.5× 6 422
Fahim Mannan United States 9 186 0.4× 81 0.3× 64 0.7× 65 0.9× 68 2.2× 16 346
Qilin Sun Saudi Arabia 7 158 0.3× 151 0.6× 45 0.5× 130 1.9× 44 1.4× 10 328
Changyin Zhou China 12 479 0.9× 455 1.9× 33 0.4× 140 2.0× 52 1.7× 22 647
Soheil Darabi United States 8 915 1.8× 186 0.8× 30 0.3× 48 0.7× 26 0.8× 11 984
Haofeng Huang China 6 598 1.2× 247 1.1× 29 0.3× 43 0.6× 23 0.7× 12 656
Gyeongmin Choe South Korea 10 513 1.0× 167 0.7× 23 0.3× 31 0.4× 19 0.6× 14 561
Huaijin Chen United States 9 150 0.3× 75 0.3× 70 0.8× 74 1.1× 71 2.3× 11 301
Nayar United States 5 271 0.5× 81 0.3× 31 0.3× 37 0.5× 30 1.0× 6 328

Countries citing papers authored by Shuochen Su

Since Specialization
Citations

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

Fields of papers citing papers by Shuochen Su

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shuochen Su

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

All Works

9 of 9 papers shown
1.
Sun, Zhanghao, et al.. (2023). Consistent Direct Time-of-Flight Video Depth Super-Resolution. 5075–5085. 4 indexed citations
2.
Wu, Cho-Ying, Jialiang Wang, C. Michael Hall, Ulrich Neumann, & Shuochen Su. (2022). Toward Practical Monocular Indoor Depth Estimation. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 3804–3814. 41 indexed citations
3.
Su, Shuochen, Felix Heide, Gordon Wetzstein, & Wolfgang Heidrich. (2018). Deep End-to-End Time-of-Flight Imaging. King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology). 6383–6392. 67 indexed citations
4.
Su, Shuochen, Mauricio Delbracio, Jue Wang, et al.. (2017). Deep Video Deblurring for Hand-Held Cameras. King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology). 237–246. 343 indexed citations breakdown →
5.
Su, Shuochen, et al.. (2016). Material Classification Using Raw Time-of-Flight Measurements. King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology). 3503–3511. 37 indexed citations
6.
Su, Shuochen, et al.. (2015). Bayesian Depth-From-Defocus With Shading Constraints. IEEE Transactions on Image Processing. 25(2). 589–600. 5 indexed citations
7.
Peng, Yifan, et al.. (2015). Computational imaging using lightweight diffractive-refractive optics. Optics Express. 23(24). 31393–31393. 66 indexed citations
8.
Su, Shuochen & Wolfgang Heidrich. (2015). Rolling shutter motion deblurring. King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology). 1529–1537. 39 indexed citations
9.
Li, Chen, Shuochen Su, Yasuyuki Matsushita, Kun Zhou, & Stephen Lin. (2013). Bayesian Depth-from-Defocus with Shading Constraints. 24. 217–224. 11 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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