| Cutmix: Regularization strategy to train strong classifiers with localizable features S Yun, D Han, SJ Oh, S Chun, J Choe, Y Yoo IEEE/CVF International Conference on Computer Vision (ICCV), 6023-6032, 2019 | 4948 | 2019 |
| Character Region Awareness for Text Detection Y Baek, B Lee, D Han, S Yun, H Lee IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 9365-9374, 2019 | 1015 | 2019 |
| Deep Pyramidal Residual Networks D Han, J Kim, J Kim IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 6307-6315, 2017 | 814 | 2017 |
| What is wrong with scene text recognition model comparisons? dataset and model analysis J Baek, G Kim, J Lee, S Park, D Han, S Yun, SJ Oh, H Lee IEEE/CVF International Conference on Computer Vision (ICCV), 4715-4723, 2019 | 601 | 2019 |
| Rethinking spatial dimensions of vision transformers B Heo, S Yun, D Han, S Chun, J Choe, SJ Oh IEEE/CVF International Conference on Computer Vision (ICCV), 11936-11945, 2021 | 566 | 2021 |
| Salient region detection via high-dimensional color transform J Kim, D Han, YW Tai, J Kim IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 883-890, 2014 | 358 | 2014 |
| Ocr-free document understanding transformer G Kim, T Hong, M Yim, JY Nam, J Park, J Yim, W Hwang, S Yun, D Han, ... European Conference on Computer Vision (ECCV), 498-517, 2022 | 183 | 2022 |
| Salient region detection via high-dimensional color transform and local spatial support J Kim, D Han, YW Tai, J Kim IEEE Transactions on Image Processing (TIP) 25 (1), 9-23, 2015 | 180 | 2015 |
| Adamp: Slowing down the slowdown for momentum optimizers on scale-invariant weights B Heo, S Chun, SJ Oh, D Han, S Yun, G Kim, Y Uh, JW Ha arXiv preprint arXiv:2006.08217, 2020 | 155 | 2020 |
| Re-labeling ImageNet: from Single to Multi-Labels, from Global to Localized Labels S Yun, SJ Oh, B Heo, D Han, J Choe, S Chun IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2340-2350, 2021 | 154 | 2021 |
| Rethinking Channel Dimensions for Efficient Model Design D Han, S Yun, B Heo, YJ Yoo IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 732-741, 2021 | 92 | 2021 |
| Unsupervised Simultaneous Orthogonal Basis Clustering Feature Selection D Han, J Kim IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 5016-5023, 2015 | 90 | 2015 |
| Vidt: An efficient and effective fully transformer-based object detector H Song, D Sun, S Chun, V Jampani, D Han, B Heo, W Kim, MH Yang International Conference on Learning Representations (ICLR), 2022 | 81 | 2022 |
| Videomix: Rethinking data augmentation for video classification S Yun, SJ Oh, B Heo, D Han, J Kim arXiv preprint arXiv:2012.03457, 2020 | 67 | 2020 |
| 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 (ICML) Workshop on Uncertainty …, 2020 | 53 | 2020 |
| Extd: Extremely tiny face detector via iterative filter reuse YJ Yoo, D Han, S Yun arXiv preprint arXiv:1906.06579, 2019 | 43 | 2019 |
| Towards Flatter Loss Surface via Nonmonotonic Learning Rate Scheduling S Seong, Y Lee, Y Kee, D Han, J Kim Uncertainty in Artificial Intelligence (UAI), 2018 | 40 | 2018 |
| Rexnet: Diminishing representational bottleneck on convolutional neural network D Han, S Yun, B Heo, YJ Yoo arXiv preprint arXiv:2007.00992 6, 1, 2020 | 37 | 2020 |
| C3: Concentrated-comprehensive convolution and its application to semantic segmentation H Park, Y Yoo, G Seo, D Han, S Yun, N Kwak arXiv preprint arXiv:1812.04920, 2018 | 32 | 2018 |
| Donut: Document understanding transformer without ocr G Kim, T Hong, M Yim, J Park, J Yim, W Hwang, S Yun, D Han, S Park arXiv preprint arXiv:2111.15664 7, 15, 2021 | 30 | 2021 |
Sangdoo YunNAVER AI Lab在 navercorp.com 的电子邮件经过验证
