Junsuk Choe
Junsuk Choe
NAVER Clova AI Research
Verified email at navercorp.com - Homepage
Title
Cited by
Cited by
Year
Cutmix: Regularization strategy to train strong classifiers with localizable features
S Yun, D Han, SJ Oh, S Chun, J Choe, Y Yoo
IEEE International Conference on Computer Vision (ICCV), 2019
1802019
Attention-based Dropout Layer for Weakly Supervised Object Localization
J Choe, H Shim
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019
482019
Face generation for low-shot learning using generative adversarial networks
J Choe*, S Park*, K Kim*, JH Park*, D Kim*, H Shim
IEEE International Conference on Computer Vision Workshop (ICCVW), 2017
442017
Evaluating Weakly Supervised Object Localization Methods Right
J Choe*, SJ Oh*, S Lee, S Chun, Z Akata, H Shim
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020
162020
An Empirical Evaluation on Robustness and Uncertainty of Regularization Methods
S Chun, SJ Oh, S Yun, D Han, J Choe, Y Yoo
International Conference on Machine Learning Workshop (ICMLW), 2019
82019
Improved techniques for weakly-supervised object localization
J Choe, JH Park, H Shim
arXiv preprint arXiv:1802.07888, 2018
42018
Attention-based Dropout Layer for Weakly Supervised Single Object Localization and Semantic Segmentation
J Choe*, S Lee*, H Shim
Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2020
22020
Robust approach to inverse lighting using RGB-D images
J Choe, H Shim
Information Sciences 438, 73-94, 2018
12018
Inverse lighting for non-homogeneous objects from color and depth image using wavelet representation
J Choe, H Shim
IS&T/SPIE Electronic Imaging, 2015
12015
Evaluation for Weakly Supervised Object Localization: Protocol, Metrics, and Datasets
J Choe*, SJ Oh*, S Chun, Z Akata, H Shim
arXiv preprint arXiv:2007.04178, 2020
2020
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Articles 1–10