| Pvanet: Deep but lightweight neural networks for real-time object detection KH Kim, S Hong, B Roh, Y Cheon, M Park arXiv preprint arXiv:1608.08021, 2016 | 289 | 2016 |
| PVANet: Lightweight deep neural networks for real-time object detection S Hong, B Roh, KH Kim, Y Cheon, M Park Neural Information Processing Systems 2016 Workshop, 2016 | 92 | 2016 |
| Spatially consistent representation learning B Roh, W Shin, I Kim, S Kim Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 89 | 2021 |
| Sparse DETR: Efficient end-to-end object detection with learnable sparsity B Roh, JW Shin, W Shin, S Kim ICLR, 2022, 2022 | 82 | 2022 |
| Impulse‐based rigid body interaction in SPH S Oh, Y Kim, BS Roh Computer Animation and Virtual Worlds 20 (2‐3), 215-224, 2009 | 44 | 2009 |
| Expanded 3d space-based virtual sports simulation system UY Yang, YW Kim, K Lee, BS Roh, KH Kim US Patent App. 13/566,928, 2013 | 36 | 2013 |
| Pvanet: Deep but lightweight neural networks for real-time object detection. arXiv 2016 KH Kim, S Hong, B Roh, Y Cheon, M Park arXiv preprint arXiv:1608.08021, 0 | 24 | |
| Learning to generate text-grounded mask for open-world semantic segmentation from only image-text pairs J Cha, J Mun, B Roh Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 16 | 2023 |
| Technologies for improved object detection accuracy with multi-scale representation and training B Roh, K Kim, S Hong, M Park, Y Cheon US Patent 10,262,237, 2019 | 16 | 2019 |
| Method of processing rigid body interaction in particle-based fluid simulation ST Oh, YH Kim, BS Roh, BK Koo US Patent App. 12/481,305, 2010 | 13 | 2010 |
| Remeshing method and apparatus for restoring sharp features of mesh made smooth enough ST Oh, MJ Lee, BK Koo, SH Pyo, YH Kim, SH Shin, JH Kim, BS Roh US Patent 8,269,771, 2012 | 9 | 2012 |
| Pvanet: Lightweight deep neural networks for real-time object detection. arXiv 2016 S Hong, B Roh, KH Kim, Y Cheon, M Park arXiv preprint arXiv:1611.08588, 0 | 8 | |
| Convolutional neural network tuning systems and methods SY Byun, B Roh, M Park, B Choe US Patent App. 15/706,930, 2019 | 7 | 2019 |
| Open-Vocabulary Object Detection using Pseudo Caption Labels HC Cho, WY Jhoo, W Kang, B Roh arXiv preprint arXiv:2303.13040, 2023 | 4 | 2023 |
| MELTR: Meta Loss Transformer for Learning to Fine-tune Video Foundation Models D Ko, J Choi, HK Choi, KW On, B Roh, HJ Kim Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 4 | 2023 |
| Noise-aware learning from web-crawled image-text data for image captioning W Kang, J Mun, S Lee, B Roh Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 2 | 2023 |
| System and method for simulating fluid particle having multi-resolution KIM Janghee, M Lee, BK Koo, SH Pyo, OH Seungtaik, YH Kim, BS Roh US Patent App. 12/101,229, 2009 | 2 | 2009 |
| Controllable multi-phase smoke with lagrangian particles BS Roh, CH Kim Computer Graphics International Conference, 115-123, 2006 | 2 | 2006 |
| Particle based fluid animation for controllable multiphase smoke BS Roh, CH Kim Journal of the Korea Computer Graphics Society 11 (3), 34-40, 2005 | 2 | 2005 |
| Large Language Models are Temporal and Causal Reasoners for Video Question Answering D Ko, JS Lee, W Kang, B Roh, HJ Kim arXiv preprint arXiv:2310.15747, 2023 | 1 | 2023 |
Sanghoon HongKakaoBrainVerified email at kakaobrain.com
