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Kuk-Jin Yoon
Kuk-Jin Yoon
Professor, Visual Intelligence Lab., KAIST
Verified email at kaist.ac.kr - Homepage
Title
Cited by
Cited by
Year
Adaptive support-weight approach for correspondence search
KJ Yoon, IS Kweon
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2006
17132006
Knowledge distillation and student-teacher learning for visual intelligence: A review and new outlooks
L Wang, KJ Yoon
IEEE transactions on pattern analysis and machine intelligence 44 (6), 3048-3068, 2021
7602021
Robust Online Multi-Object Tracking based on Tracklet Confidence and Online Discriminative Appearance Learning
SH Bae, KJ Yoon
Computer Vision and Pattern Recognition, 2014. CVPR 2014. IEEE Computer …, 2014
5382014
Locally adaptive support-weight approach for visual correspondence search
KJ Yoon, IS Kweon
2005 IEEE Computer Society Conference on Computer Vision and Pattern …, 2005
3742005
Confidence-based data association and discriminative deep appearance learning for robust online multi-object tracking
SH Bae, KJ Yoon
IEEE transactions on pattern analysis and machine intelligence 40 (3), 595-610, 2017
3152017
Bayesian multi-object tracking using motion context from multiple objects
JH Yoon, MH Yang, J Lim, KJ Yoon
2015 IEEE Winter Conference on Applications of Computer Vision, 33-40, 2015
2632015
Online multi-object tracking via structural constraint event aggregation
J Hong Yoon, CR Lee, MH Yang, KJ Yoon
Proceedings of the IEEE Conference on computer vision and pattern …, 2016
2222016
Event-based High Dynamic Range Image and Very High Frame Rate Video Generation using Conditional Generative Adversarial Networks
L Wang, SM Mostafavi I., YS Ho, KJ Yoon
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019
2162019
Improving person re-identification via pose-aware multi-shot matching
YJ Cho, KJ Yoon
Proceedings of the IEEE conference on computer vision and pattern …, 2016
1422016
Leveraging stereo matching with learning-based confidence measures
MG Park, KJ Yoon
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015
1412015
Unlocking the potential of ordinary classifier: Class-specific adversarial erasing framework for weakly supervised semantic segmentation
H Kweon, SH Yoon, H Kim, D Park, KJ Yoon
Proceedings of the IEEE/CVF international conference on computer vision …, 2021
1392021
Spherephd: Applying cnns on a spherical polyhedron representation of 360deg images
Y Lee, J Jeong, J Yun, W Cho, KJ Yoon
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
1282019
High Accuracy Real-Time Multi-Gas Identification by a Batch-Uniform Gas Sensor Array and Deep Learning Algorithm
M Kang, I Cho, J Park, J Jeong, K Lee, B Lee, D Del Orbe Henriquez, ...
ACS sensors 7 (2), 430-440, 2022
1212022
Polyp detection via imbalanced learning and discriminative feature learning
SH Bae, KJ Yoon
IEEE transactions on medical imaging 34 (11), 2379-2393, 2015
1182015
EventSR: From Asynchronous Events to Image Reconstruction, Restoration, and Super-Resolution via End-to-End Adversarial Learning
L Wang, TK Kim, KJ Yoon
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020
1152020
Fast separation of reflection components using a specularity-invariant image representation
KJ Yoon, Y Choi, IS Kweon
2006 international conference on image processing, 973-976, 2006
1012006
Deep learning for hdr imaging: State-of-the-art and future trends
L Wang, KJ Yoon
IEEE transactions on pattern analysis and machine intelligence 44 (12), 8874 …, 2021
882021
Object recognition using a generalized robust invariant feature and Gestalt's law of proximity and similarity
S Kim, KJ Yoon, IS Kweon
Pattern Recognition 41 (2), 726-741, 2008
872008
Artificial olfactory neuron for an in‐sensor neuromorphic nose
JK Han, M Kang, J Jeong, I Cho, JM Yu, KJ Yoon, I Park, YK Choi
Advanced Science 9 (18), 2106017, 2022
802022
Visual tracking via adaptive tracker selection with multiple features
JH Yoon, DY Kim, KJ Yoon
Computer Vision–ECCV 2012: 12th European Conference on Computer Vision …, 2012
802012
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