Difference between revisions of "Main Page"
From MIPAL
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== '''For more information on admission, please visit the [http://convergence.snu.ac.kr homepage of SNU GSCST]. ''' == | == '''For more information on admission, please visit the [http://convergence.snu.ac.kr homepage of SNU GSCST]. ''' == | ||
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* [http://www.guide2research.com/topconf/ '''Top CS Conferences'''] | * [http://www.guide2research.com/topconf/ '''Top CS Conferences'''] | ||
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== '''Research Areas'''== | == '''Research Areas'''== | ||
Revision as of 07:43, 7 December 2019
People who are interested in our group or searching for a postdoc position are requested to contact Prof. Kwak (nojunk@snu.ac.kr).
For more information on admission, please visit the homepage of SNU GSCST.
- Two papers have been accepted in AAAI 2020 (both oral).
- A paper has been accepted in NeurIPS 2019.
- A paper has been accepted in ACML 2019.
- We have two papers accepted in ICCV 2019.
- A paper has been accepted in ACL 2019.
- We have a paper accepted in IET Radar, Sonar & Navigation.
- We have a paper accepted in IJCNN2019.
- A paper titled 'TW3-based Fully Automated Bone Age Assessment System using Deep Neural Networks' has been accepted in IEEE Access.
- A paper has been accepted in 2019 IEEE Radar Conference.
- Two papers were presented in ICPRAM 2019.
- We have a paper accepted in AAAI 2019 (record low acceptance rate of 16.2%).
- A paper titled 'Nonparametric Estimation of Probabilistic Membership for Subspace Clustering' was accepted in IEEE Trans. on Cybernetics.
- In 2018, we have published 2 CVPR, 2 ECCV, 2 BMVC, 2 NeurIPS and 1 ISMIR papers on deep learning and 2 EuMW and 1 MIKON papers on radar signal processing.
- Two journal papers were published in 2018 (IEEE TIP and PR).
- We won the Honorable Mention Award in the POSETRACK CHALLENGE at ECCV2018 workshop.
Research Areas
- Semi- / Weakly Supervision
- Model Compression
- Object Detection
- Semantic Segmentation
- Pose Estimation
- Image Translation / Synthesis
- Super Resolution / Image Restoration
- Reinforcement Learning
- Visual Question Answering
- Semantic Sentence Matching
