| A Comprehensive Overhaul of Feature Distillation B Heo, J Kim, S Yun, H Park, N Kwak, JY Choi Proceedings of the IEEE International Conference on Computer Vision, 1921-1930, 2019 | 408 | 2019 |
| Rethinking spatial dimensions of vision transformers B Heo, S Yun, D Han, S Chun, J Choe, SJ Oh Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 385 | 2021 |
| Knowledge transfer via distillation of activation boundaries formed by hidden neurons B Heo, M Lee, S Yun, JY Choi Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 3779-3787, 2019 | 376 | 2019 |
| 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 | 142* | 2020 |
| Knowledge distillation with adversarial samples supporting decision boundary B Heo, M Lee, S Yun, JY Choi Proceedings of the AAAI Conference on Artificial Intelligence 33, 3771-3778, 2019 | 123 | 2019 |
| 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 Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 113 | 2021 |
| Show, attend and distill: Knowledge distillation via attention-based feature matching M Ji, B Heo, S Park Proceedings of the AAAI Conference on Artificial Intelligence 35 (9), 7945-7952, 2021 | 86 | 2021 |
| Rethinking channel dimensions for efficient model design D Han, S Yun, B Heo, YJ Yoo Proceedings of the IEEE/CVF conference on Computer Vision and Pattern …, 2021 | 80* | 2021 |
| The majority can help the minority: Context-rich minority oversampling for long-tailed classification S Park, Y Hong, B Heo, S Yun, JY Choi Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 60 | 2022 |
| 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 arXiv preprint arXiv:2110.03921, 2021 | 58 | 2021 |
| Visdrone-sot2018: The vision meets drone single-object tracking challenge results L Wen, P Zhu, D Du, X Bian, H Ling, Q Hu, C Liu, H Cheng, X Liu, W Ma, ... Proceedings of the European Conference on Computer Vision (ECCV) Workshops, 0-0, 2018 | 44 | 2018 |
| Videomix: Rethinking data augmentation for video classification S Yun, SJ Oh, B Heo, D Han, J Kim arXiv preprint arXiv:2012.03457, 2020 | 43 | 2020 |
| Appearance and motion based deep learning architecture for moving object detection in moving camera B Heo, K Yun, JY Choi 2017 IEEE international conference on image processing (ICIP), 1827-1831, 2017 | 32 | 2017 |
| Joint global and local hierarchical priors for learned image compression JH Kim, B Heo, JS Lee Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 29 | 2022 |
| Initialization-insensitive visual tracking through voting with salient local features KM Yi, H Jeong, B Heo, HJ Chang, JY Choi Proceedings of the IEEE International Conference on Computer Vision, 2912-2919, 2013 | 29 | 2013 |
| Backbone Cannot Be Trained at Once: Rolling Back to Pre-Trained Network for Person Re-Identification Y Ro, J Choi, DU Jo, B Heo, J Lim, JY Choi Proceedings of the AAAI Conference on Artificial Intelligence 33, 8859-8867, 2019 | 26 | 2019 |
| Method and apparatus for processing image S Hwang, S Yun, H Jeong, JY Choi, B Heo, K Woo-Sung US Patent 9,639,758, 2017 | 13 | 2017 |
| Pose transforming network: Learning to disentangle human posture in variational auto-encoded latent space J Lim, Y Yoo, B Heo, JY Choi Pattern Recognition Letters 112, 91-97, 2018 | 12 | 2018 |
| Filter pruning and re-initialization via latent space clustering S Lee, B Heo, JW Ha, BC Song IEEE Access 8, 189587-189597, 2020 | 10 | 2020 |
| What Do Self-Supervised Vision Transformers Learn? N Park, W Kim, B Heo, T Kim, S Yun arXiv preprint arXiv:2305.00729, 2023 | 8 | 2023 |
Sangdoo YunNAVER AI LabVerified email at navercorp.com
