| Interpretable learning for self-driving cars by visualizing causal attention J Kim, J Canny Proceedings of the IEEE international conference on computer vision, 2942-2950, 2017 | 407 | 2017 |
| RNA design rules from a massive open laboratory J Lee, W Kladwang, M Lee, D Cantu, M Azizyan, H Kim, A Limpaecher, ... Proceedings of the National Academy of Sciences 111 (6), 2122-2127, 2014 | 346 | 2014 |
| Textual explanations for self-driving vehicles J Kim, A Rohrbach, T Darrell, J Canny, Z Akata Proceedings of the European conference on computer vision (ECCV), 563-578, 2018 | 303 | 2018 |
| Selfreg: Self-supervised contrastive regularization for domain generalization D Kim, Y Yoo, S Park, J Kim, J Lee Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 235 | 2021 |
| Predicting driver attention in critical situations Y Xia, D Zhang, J Kim, K Nakayama, K Zipser, D Whitney Computer Vision–ACCV 2018: 14th Asian Conference on Computer Vision, Perth …, 2019 | 143 | 2019 |
| HiTRACE: high-throughput robust analysis for capillary electrophoresis S Yoon, J Kim, J Hum, H Kim, S Park, W Kladwang, R Das Bioinformatics 27 (13), 1798-1805, 2011 | 110 | 2011 |
| Grounding human-to-vehicle advice for self-driving vehicles J Kim, T Misu, YT Chen, A Tawari, J Canny Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 86 | 2019 |
| Periphery-fovea multi-resolution driving model guided by human attention Y Xia, J Kim, J Canny, K Zipser, T Canas-Bajo, D Whitney Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2020 | 51 | 2020 |
| Entropy-based analysis and bioinformatics-inspired integration of global economic information transfer J Kim, G Kim, S An, YK Kwon, S Yoon PloS one 8 (1), e51986, 2013 | 50 | 2013 |
| Advisable learning for self-driving vehicles by internalizing observation-to-action rules J Kim, S Moon, A Rohrbach, T Darrell, J Canny Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 49 | 2020 |
| Occupancy flow fields for motion forecasting in autonomous driving R Mahjourian, J Kim, Y Chai, M Tan, B Sapp, D Anguelov IEEE Robotics and Automation Letters 7 (2), 5639-5646, 2022 | 47 | 2022 |
| Sound-guided semantic image manipulation SH Lee, W Roh, W Byeon, SH Yoon, C Kim, J Kim, S Kim Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 40 | 2022 |
| Deep traffic light detection for self-driving cars from a large-scale dataset J Kim, H Cho, M Hwangbo, J Choi, J Canny, YP Kwon 2018 21st International Conference on Intelligent Transportation Systems …, 2018 | 38 | 2018 |
| A robust peak detection method for RNA structure inference by high-throughput contact mapping J Kim, S Yu, B Shim, H Kim, H Min, EY Chung, R Das, S Yoon Bioinformatics 25 (9), 1137-1144, 2009 | 28 | 2009 |
| Grounding visual representations with texts for domain generalization S Min, N Park, S Kim, S Park, J Kim European Conference on Computer Vision, 37-53, 2022 | 26 | 2022 |
| Collaborative analytics for data silos J Kim, H Ha, BG Chun, S Yoon, SK Cha 2016 IEEE 32nd International Conference on Data Engineering (ICDE), 743-754, 2016 | 26 | 2016 |
| Stopnet: Scalable trajectory and occupancy prediction for urban autonomous driving J Kim, R Mahjourian, S Ettinger, M Bansal, B White, B Sapp, D Anguelov 2022 International Conference on Robotics and Automation (ICRA), 8957-8963, 2022 | 20 | 2022 |
| Toward explainable and advisable model for self‐driving cars J Kim, A Rohrbach, Z Akata, S Moon, T Misu, YT Chen, T Darrell, J Canny Applied AI Letters 2 (4), e56, 2021 | 18 | 2021 |
| Attentional bottleneck: Towards an interpretable deep driving network J Kim, M Bansal Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 16 | 2020 |
| Sound-guided semantic video generation SH Lee, G Oh, W Byeon, C Kim, WJ Ryoo, SH Yoon, H Cho, J Bae, J Kim, ... European Conference on Computer Vision, 34-50, 2022 | 12 | 2022 |
