| Context-aware emotion recognition networks J Lee, S Kim, S Kim, J Park, K Sohn Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 272 | 2019 |
| Multi-modal recurrent attention networks for facial expression recognition J Lee, S Kim, S Kim, K Sohn IEEE Transactions on Image Processing 29, 6977-6991, 2020 | 75 | 2020 |
| Laf-net: Locally adaptive fusion networks for stereo confidence estimation S Kim, S Kim, D Min, K Sohn Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 59 | 2019 |
| Unified confidence estimation networks for robust stereo matching S Kim, D Min, S Kim, K Sohn IEEE Transactions on Image Processing 28 (3), 1299-1313, 2018 | 56 | 2018 |
| Looking into your speech: Learning cross-modal affinity for audio-visual speech separation J Lee, SW Chung, S Kim, HG Kang, K Sohn Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 46 | 2021 |
| Feature augmentation for learning confidence measure in stereo matching S Kim, D Min, S Kim, K Sohn IEEE Transactions on Image Processing 26 (12), 6019-6033, 2017 | 42 | 2017 |
| Deep stereo confidence prediction for depth estimation S Kim, D Min, B Ham, S Kim, K Sohn 2017 ieee international conference on image processing (icip), 992-996, 2017 | 41 | 2017 |
| Semantic attribute matching networks S Kim, D Min, S Jeong, S Kim, S Jeon, K Sohn Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 39 | 2019 |
| On the confidence of stereo matching in a deep-learning era: a quantitative evaluation M Poggi, S Kim, F Tosi, S Kim, F Aleotti, D Min, K Sohn, S Mattoccia IEEE transactions on pattern analysis and machine intelligence 44 (9), 5293-5313, 2021 | 38 | 2021 |
| Spatiotemporal attention based deep neural networks for emotion recognition J Lee, S Kim, S Kiim, K Sohn 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 26 | 2018 |
| Adaptive confidence thresholding for monocular depth estimation H Choi, H Lee, S Kim, S Kim, S Kim, K Sohn, D Min Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 23 | 2021 |
| Adversarial confidence estimation networks for robust stereo matching S Kim, D Min, S Kim, K Sohn IEEE Transactions on Intelligent Transportation Systems 22 (11), 6875-6889, 2020 | 11 | 2020 |
| Audio-visual attention networks for emotion recognition J Lee, S Kim, S Kim, K Sohn Proceedings of the 2018 Workshop on Audio-Visual Scene Understanding for …, 2018 | 11 | 2018 |
| Modality-invariant image classification based on modality uniqueness and dictionary learning S Kim, R Cai, K Park, S Kim, K Sohn IEEE Transactions on Image Processing 26 (2), 884-899, 2016 | 7 | 2016 |
| Stereo confidence estimation via locally adaptive fusion and knowledge distillation S Kim, S Kim, D Min, P Frossard, K Sohn IEEE transactions on pattern analysis and machine intelligence 45 (5), 6372-6385, 2022 | 5 | 2022 |
| Shape-robust SAR ship detection via context-preserving augmentation and deep contrastive RoI learning T Song, S Kim, K Sohn IEEE Geoscience and Remote Sensing Letters 19, 1-5, 2022 | 5 | 2022 |
| Context-preserving instance-level augmentation and deformable convolution networks for SAR ship detection T Song, S Kim, ST Kim, J Lee, K Sohn 2022 IEEE Radar Conference (RadarConf22), 1-6, 2022 | 4 | 2022 |
| Learning depth from a single image using visual-depth words S Kim, S Choi, K Sohn 2015 IEEE International Conference on Image Processing (ICIP), 1895-1899, 2015 | 4 | 2015 |
| Adaptive confidence thresholding for semi-supervised monocular depth estimation H Choi, H Lee, S Kim, S Kim, S Kim, D Min CoRR, abs/2009.12840, 2020 | 3 | 2020 |
| Meta-confidence estimation for stereo matching S Kim, M Poggi, S Kim, K Sohn, S Mattoccia 2022 International Conference on Robotics and Automation (ICRA), 10624-10631, 2022 | 2 | 2022 |
