Adacof: Adaptive collaboration of flows for video frame interpolation H Lee, T Kim, T Chung, D Pak, Y Ban, S Lee Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 230 | 2020 |
Unsupervised video anomaly detection via normalizing flows with implicit latent features MA Cho, T Kim, WJ Kim, S Cho, S Lee Pattern Recognition 129, 108703, 2022 | 55 | 2022 |
Relational deep feature learning for heterogeneous face recognition MA Cho, T Kim, IJ Kim, K Lee, S Lee IEEE Transactions on Information Forensics and Security 16, 376-388, 2020 | 42 | 2020 |
AIM 2020 challenge on image extreme inpainting E Ntavelis, A Romero, S Bigdeli, R Timofte, Z Hui, X Wang, X Gao, C Shin, ... Computer Vision–ECCV 2020 Workshops: Glasgow, UK, August 23–28, 2020 …, 2020 | 24 | 2020 |
SF-CNN: a fast compression artifacts removal via spatial-to-frequency convolutional neural networks T Kim, H Lee, H Son, S Lee 2019 IEEE International Conference on Image Processing (ICIP), 3606-3610, 2019 | 19 | 2019 |
Learning temporally invariant and localizable features via data augmentation for video recognition T Kim, H Lee, MA Cho, HS Lee, DH Cho, S Lee Computer Vision–ECCV 2020 Workshops: Glasgow, UK, August 23–28, 2020 …, 2020 | 18 | 2020 |
Enhanced standard compatible image compression framework based on auxiliary codec networks H Son, T Kim, H Lee, S Lee IEEE Transactions on Image Processing 31, 664-677, 2021 | 14 | 2021 |
NIR-to-VIS face recognition via embedding relations and coordinates of the pairwise features MA Cho, T Chung, T Kim, S Lee 2019 International Conference on Biometrics (ICB), 1-8, 2019 | 9 | 2019 |
Exploring temporally dynamic data augmentation for video recognition T Kim, J Kim, M Shim, S Yun, M Kang, D Wee, S Lee arXiv preprint arXiv:2206.15015, 2022 | 7 | 2022 |
Decomposed cross-modal distillation for rgb-based temporal action detection P Lee, T Kim, M Shim, D Wee, H Byun Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 6 | 2023 |
Frequency Selective Augmentation for Video Representation Learning J Kim, T Kim, M Shim, D Han, D Wee, J Kim AAAI Conference on Artificial Intelligence (AAAI), 2022 | 4* | 2022 |
Block-Attentive Subpixel Prediction Networks for Computationally Efficient Image Restoration T Kim, C Shin, S Lee, S Lee IEEE Access 9, 90881-90895, 2021 | 4 | 2021 |
Sampling operator to learn the scalable correlation filter for visual tracking M Lee, T Kim, Y Ban, E Song, S Lee IEEE Access 7, 11554-11564, 2019 | 4 | 2019 |
Smoother network tuning and interpolation for continuous-level image processing H Lee, T Kim, H Son, S Baek, M Cheon, S Lee arXiv preprint arXiv:2010.02270, 2020 | 3 | 2020 |
Collabonet: Collaboration of generative models by unsupervised classification H Lee, T Kim, E Song, S Lee 2018 25th IEEE International Conference on Image Processing (ICIP), 1068-1072, 2018 | 3 | 2018 |
Test-Time Adaptation for Out-Of-Distributed Image Inpainting C Shin, T Kim, S Lee, S Lee 2021 IEEE International Conference on Image Processing (ICIP), 2009-2013, 2021 | 2 | 2021 |
Extrapolative-interpolative cycle-consistency learning for video frame extrapolation S Lee, H Lee, T Kim, S Lee 2020 IEEE International Conference on Image Processing (ICIP), 1571-1575, 2020 | 2 | 2020 |
A Nonlinear, Regularized, and Data-independent Modulation for Continuously Interactive Image Processing Network H Lee, T Kim, H Son, S Baek, M Cheon, S Lee International Journal of Computer Vision 132 (1), 74-94, 2024 | | 2024 |
Masked Autoencoder for Unsupervised Video Summarization M Shim, T Kim, J Kim, D Wee arXiv preprint arXiv:2306.01395, 2023 | | 2023 |
Geometry-Aware Deep Video Deblurring via Recurrent Feature Refinement T Kim, S Lee IEEE Transactions on Image Processing 31, 1176-1189, 2022 | | 2022 |