| Deep video super-resolution network using dynamic upsampling filters without explicit motion compensation Y Jo, SW Oh, J Kang, SJ Kim Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 191 | 2018 |
| Fast video object segmentation by reference-guided mask propagation SW Oh, JY Lee, K Sunkavalli, SJ Kim Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 170 | 2018 |
| Video object segmentation using space-time memory networks SW Oh, JY Lee, N Xu, SJ Kim Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 115 | 2019 |
| Do it yourself hyperspectral imaging with everyday digital cameras SW Oh, MS Brown, M Pollefeys, SJ Kim Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016 | 66 | 2016 |
| Approaching the computational color constancy as a classification problem through deep learning SW Oh, SJ Kim Pattern Recognition 61, 405-416, 2017 | 64 | 2017 |
| Copy-and-paste networks for deep video inpainting S Lee, SW Oh, DY Won, SJ Kim Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 22 | 2019 |
| Onion-peel networks for deep video completion SW Oh, S Lee, JY Lee, SJ Kim Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 19 | 2019 |
| Fast user-guided video object segmentation by interaction-and-propagation networks SW Oh, JY Lee, N Xu, SJ Kim Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 19 | 2019 |
| Video object segmentation by reference-guided mask propagation J Lee, S Oh, KK Sunkavalli US Patent 10,671,855, 2020 | 15 | 2020 |
| Fast video object segmentation by referenceguided mask propagation. In 2018 IEEE SW Oh, JY Lee, K Sunkavalli, SJ Kim CVF Conference on Computer Vision and Pattern Recognition, 7376-7385, 2018 | 6 | 2018 |
| Fast user-guided video object segmentation by deep networks SW Oh, JY Lee, N Xu, SJ Kim The 2018 DAVIS Challenge on Video Object Segmentation-CVPR Workshops 2, 6, 2018 | 6 | 2018 |
| Space-time Memory Networks for Video Object Segmentation with User Guidance SW Oh, JY Lee, N Xu, SJ Kim IEEE Annals of the History of Computing, 1-1, 2020 | 4 | 2020 |
| Deep Space-Time Video Upsampling Networks J Kang, Y Jo, SW Oh, P Vajda, SJ Kim European Conference on Computer Vision, 701-717, 2020 | 2 | 2020 |
| Cross-Identity Motion Transfer for Arbitrary Objects through Pose-Attentive Video Reassembling S Jeon, S Nam, SW Oh, SJ Kim European Conference on Computer Vision, 292-308, 2020 | 1 | 2020 |
| Segmenting objects in video sequences JY Lee, S Oh, N Xu US Patent 10,810,435, 2020 | | 2020 |
| Video object segmentation by reference-guided mask propagation JY Lee, S Oh, KK Sunkavalli US Patent App. 16/856,292, 2020 | | 2020 |
| Space-time memory network for locating target object in video content JY Lee, N Xu, S Oh US Patent App. 16/293,126, 2020 | | 2020 |
| Learning the Loss Functions in a Discriminative Space for Video Restoration Y Jo, J Kang, SW Oh, S Nam, P Vajda, SJ Kim arXiv preprint arXiv:2003.09124, 2020 | | 2020 |
| DMV: Visual Object Tracking via Part-level Dense Memory and Voting-based Retrieval G Nam, SW Oh, JY Lee, SJ Kim arXiv preprint arXiv:2003.09171, 2020 | | 2020 |
| A Unified Model for Semi-supervised and Interactive Video Object Segmentation using Space-time Memory Networks SW Oh, JY Lee, N Xu, SJ Kim | | |
Seon Joo KimDept. of Computer Science, Yonsei University, Seoul, KoreaVerified email at yonsei.ac.kr
