Difference between revisions of "Sungheon Park"
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− | | style="width: 200px;" |[[file: | + | | style="width: 200px;" |[[file:sungheonpark2.jpg | 200px]] |
| <font size = 5> '''[[Sungheon Park]] (박성헌)'''</font><br><br> | | <font size = 5> '''[[Sungheon Park]] (박성헌)'''</font><br><br> | ||
− | :'''Ph. D. | + | :'''Ph. D.''' <br> |
:Program in Intelligent Systems | :Program in Intelligent Systems | ||
:Department of Transdisciplinary Studies<br> | :Department of Transdisciplinary Studies<br> | ||
Line 11: | Line 11: | ||
:Tel: +82-31-888-9579 <br> | :Tel: +82-31-888-9579 <br> | ||
:e-mail: [mailto:sungheonpark@snu.ac.kr sungheonpark@snu.ac.kr] <br> | :e-mail: [mailto:sungheonpark@snu.ac.kr sungheonpark@snu.ac.kr] <br> | ||
+ | :[http://scholar.google.co.kr/citations?user=VhvtBHkAAAAJ Google Scholar] | ||
|- | |- | ||
|} | |} | ||
− | I | + | <b>This page will no longer be updated. Check out my new personal page [http://sungheonpark.github.io here].</b> |
− | My research | + | <br> |
+ | <b>I received ph.D. in Feb 2019 and joined to [https://www.sait.samsung.co.kr/saithome/main/main.do Samsung Advanced Institute of Technology (SAIT)] Computer Vision Lab as a staff researcher.</b> | ||
+ | <br><br> | ||
+ | I am in the Machine Intelligence and Pattern Analysis Lab under the supervision of Prof. Nojun Kwak. Before joining to MIPA Lab, I received B.S. and M.S. degree at Korea Advanced Institute of Science and Technology (KAIST), majoring in computer science. | ||
+ | My research interest covers broad range of computer vision and machine learning. Especially, I'm interested in applying deep learning algorithms to computer vision problems. | ||
== '''Education''' == | == '''Education''' == | ||
<ul> | <ul> | ||
<li> | <li> | ||
− | + | Feb. 2019: | |
− | :Ph.D. | + | :Ph.D. in Intelligent Systems, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Korea. |
</li> | </li> | ||
<li> | <li> | ||
Line 36: | Line 41: | ||
</ul> | </ul> | ||
− | == '''Publications''' == | + | == '''Selected Publications''' == |
+ | |||
+ | |||
+ | <ul> | ||
+ | {| style="width: 100%;" style="margin-left: 5px; margin-right: auto;" | ||
+ | |- | ||
+ | | [[file:Sungheon_bmvc_2018.png | 250px]] | ||
+ | | '''3D Human Pose Estimation with Relational Networks'''<br> | ||
+ | '''Sungheon Park''' and Nojun Kwak <br> | ||
+ | British Machine Vision Conference ('''BMVC'''), 2018 <br> | ||
+ | [//arxiv.org/abs/1805.08961 [arXiv] ] [//github.com/sungheonpark/3D_HPE_RN [code] ] [//www.youtube.com/watch?v=JIeDtnNLOdc [video] ] | ||
+ | |} | ||
+ | </ul> | ||
+ | |||
+ | <br> | ||
+ | |||
+ | <ul> | ||
+ | {| style="width: 100%;" style="margin-left: 5px; margin-right: auto;" | ||
+ | |- | ||
+ | | [[file:sungheon_ISMIR_2018.png | 250px]] | ||
+ | | '''Music Source Separation Using Stacked Hourglass Networks'''<br> | ||
+ | '''Sungheon Park''', Taehoon Kim, Kyogu Lee and Nojun Kwak <br> | ||
+ | International Society for Music Information Retrieval Conference ('''ISMIR'''), 2018 <br> | ||
+ | [//arxiv.org/abs/1805.08559 [arXiv] ] [//github.com/sungheonpark/music_source_sepearation_SH_net [code] ] [//youtu.be/oGHC0ric6wo [video] ] | ||
+ | |} | ||
+ | </ul> | ||
+ | |||
+ | <br> | ||
+ | |||
+ | <ul> | ||
+ | {| style="width: 100%;" style="margin-left: 5px; margin-right: auto;" | ||
+ | |- | ||
+ | | [[file:ICA_PR_sungheon.png | 250px]] | ||
+ | | '''Independent Component Analysis by lp-norm Optimization'''<br> | ||
+ | '''Sungheon Park''' and Nojun Kwak <br> | ||
+ | Pattern Recognition ('''PR'''), Volume 76, Apr, 2018<br> | ||
+ | [//www.sciencedirect.com/science/article/pii/S0031320317304077 [paper] ] | ||
+ | |} | ||
+ | </ul> | ||
+ | |||
+ | <br> | ||
+ | |||
+ | <ul> | ||
+ | {| style="width: 100%;" style="margin-left: 5px; margin-right: auto;" | ||
+ | |- | ||
+ | | [[file:sungheon_tip.png | 250px]] | ||
+ | | '''Procrustean Regression: A Flexible Alignment-Based Framework for Nonrigid Structure Estimation'''<br> | ||
+ | '''Sungheon Park''', Minsik Lee, and Nojun Kwak <br> | ||
+ | Transactions on Image Processing ('''TIP'''), Volume 27, Jan, 2018<br> | ||
+ | [//ieeexplore.ieee.org/document/8052164/ [paper] ] | ||
+ | |} | ||
+ | </ul> | ||
+ | |||
+ | <br> | ||
+ | |||
+ | <ul> | ||
+ | {| style="width: 100%;" style="margin-left: 5px; margin-right: auto;" | ||
+ | |- | ||
+ | | [[file:park_accv16.png | 250px]] | ||
+ | | '''Analysis on the Dropout Effect in Convolutional Neural Networks'''<br> | ||
+ | '''Sungheon Park''' and Nojun Kwak <br> | ||
+ | Asian Conference on Computer Vision ('''ACCV'''), 2016<br> | ||
+ | [[Media:Dropout_ACCV2016.pdf | [paper] ]] [//github.com/sungheonpark/Max-drop [code] ] | ||
+ | |} | ||
+ | </ul> | ||
+ | |||
+ | <br> | ||
+ | |||
+ | <ul> | ||
+ | {| style="width: 100%;" style="margin-left: 5px; margin-right: auto;" | ||
+ | |- | ||
+ | | [[file:park_eccvw16.png | 250px]] | ||
+ | | '''3D Human Pose Estimation Using Convolutional Neural Networks with 2D Pose Information'''<br> | ||
+ | '''Sungheon Park''', Jihye Hwang, and Nojun Kwak <br> | ||
+ | Geometry Meets Deep Learning Workshop ('''ECCV Workshop'''), 2016<br> | ||
+ | [//arxiv.org/abs/1608.03075 [arXiv paper] ] | ||
+ | |} | ||
+ | </ul> | ||
+ | |||
+ | <br> | ||
+ | |||
+ | <ul> | ||
+ | {| style="width: 100%;" style="margin-left: 5px; margin-right: auto;" | ||
+ | |- | ||
+ | | [[file:cvprw2015.png | 250px]] | ||
+ | | '''Cultural Event Recognition by Subregion Classification with Convolutional Neural Network'''<br> | ||
+ | '''Sungheon Park''' and Nojun Kwak <br> | ||
+ | ChaLearn Looking at the People Workshop ('''CVPR Workshop'''), 2015<br> | ||
+ | Ranked 3rd in the cultural event classification challenge<br> | ||
+ | [[Media:CVPRW2015_cultural_event_cnn.pdf | [paper] ]] | ||
+ | |} | ||
+ | </ul> | ||
+ | |||
+ | <br> | ||
+ | |||
+ | <ul> | ||
+ | {| style="width: 100%;" style="margin-left: 5px; margin-right: auto;" | ||
+ | |- | ||
+ | | [[file:icip2015.png | 250px]] | ||
+ | | '''Illumination Robust Optical Flow Estimation by Illumination-Chromaticity Decoupling'''<br> | ||
+ | '''Sungheon Park''' and Nojun Kwak <br> | ||
+ | International Conference on Image Processing ('''ICIP'''), 2015 <br> | ||
+ | [[Media:ICIP2015_optical_flow.pdf | [paper] ]] | ||
+ | |} | ||
+ | </ul> |
Latest revision as of 22:27, 17 January 2022
Sungheon Park (박성헌)
|
This page will no longer be updated. Check out my new personal page here.
I received ph.D. in Feb 2019 and joined to Samsung Advanced Institute of Technology (SAIT) Computer Vision Lab as a staff researcher.
I am in the Machine Intelligence and Pattern Analysis Lab under the supervision of Prof. Nojun Kwak. Before joining to MIPA Lab, I received B.S. and M.S. degree at Korea Advanced Institute of Science and Technology (KAIST), majoring in computer science.
My research interest covers broad range of computer vision and machine learning. Especially, I'm interested in applying deep learning algorithms to computer vision problems.
Education
-
Feb. 2019:
- Ph.D. in Intelligent Systems, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Korea.
-
Feb. 2014:
- M.S. in Computer Science, Korea Advanced Institute of Science and Technology, Daejeon, Korea.
-
Feb. 2012:
- B.S. in Computer Science, Korea Advanced Institute of Science and Technology, Daejeon, Korea.
Selected Publications
3D Human Pose Estimation with Relational Networks Sungheon Park and Nojun Kwak |
Music Source Separation Using Stacked Hourglass Networks Sungheon Park, Taehoon Kim, Kyogu Lee and Nojun Kwak |
Independent Component Analysis by lp-norm Optimization Sungheon Park and Nojun Kwak |
Procrustean Regression: A Flexible Alignment-Based Framework for Nonrigid Structure Estimation Sungheon Park, Minsik Lee, and Nojun Kwak |
Analysis on the Dropout Effect in Convolutional Neural Networks Sungheon Park and Nojun Kwak |
3D Human Pose Estimation Using Convolutional Neural Networks with 2D Pose Information Sungheon Park, Jihye Hwang, and Nojun Kwak |
Cultural Event Recognition by Subregion Classification with Convolutional Neural Network Sungheon Park and Nojun Kwak |
Illumination Robust Optical Flow Estimation by Illumination-Chromaticity Decoupling Sungheon Park and Nojun Kwak |