| DLT-Net: Joint detection of drivable areas, lane lines, and traffic objects Y Qian, JM Dolan, M Yang IEEE Transactions on Intelligent Transportation Systems 21 (11), 4670-4679, 2019 | 141 | 2019 |
| CNN based semantic segmentation for urban traffic scenes using fisheye camera L Deng, M Yang, Y Qian, C Wang, B Wang 2017 IEEE Intelligent Vehicles Symposium (IV), 231-236, 2017 | 121 | 2017 |
| Spade-e2vid: Spatially-adaptive denormalization for event-based video reconstruction PRG Cadena, Y Qian, C Wang, M Yang IEEE Transactions on Image Processing 30, 2488-2500, 2021 | 50 | 2021 |
| Pedestrian graph: Pedestrian crossing prediction based on 2d pose estimation and graph convolutional networks PRG Cadena, M Yang, Y Qian, C Wang 2019 IEEE Intelligent Transportation Systems Conference (ITSC), 2000-2005, 2019 | 48 | 2019 |
| BAANet: Learning bi-directional adaptive attention gates for multispectral pedestrian detection X Yang, Y Qian, H Zhu, C Wang, M Yang 2022 international conference on robotics and automation (ICRA), 2920-2926, 2022 | 42 | 2022 |
| Neutral cross-entropy loss based unsupervised domain adaptation for semantic segmentation H Xu, M Yang, L Deng, Y Qian, C Wang IEEE Transactions on Image Processing 30, 4516-4525, 2021 | 38 | 2021 |
| Oriented spatial transformer network for pedestrian detection using fish-eye camera Y Qian, M Yang, X Zhao, C Wang, B Wang IEEE Transactions on Multimedia 22 (2), 421-431, 2019 | 37 | 2019 |
| Pedestrian graph+: A fast pedestrian crossing prediction model based on graph convolutional networks PRG Cadena, Y Qian, C Wang, M Yang IEEE Transactions on Intelligent Transportation Systems 23 (11), 21050-21061, 2022 | 36 | 2022 |
| A multi-camera vehicle tracking system based on city-scale vehicle re-id and spatial-temporal information M Wu, Y Qian, C Wang, M Yang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 33 | 2021 |
| Gated-residual block for semantic segmentation using RGB-D data Y Qian, L Deng, T Li, C Wang, M Yang IEEE Transactions on Intelligent Transportation Systems 23 (8), 11836-11844, 2021 | 24 | 2021 |
| Map-enhanced ego-lane detection in the missing feature scenarios X Wang, Y Qian, C Wang, M Yang IEEE Access 8, 107958-107968, 2020 | 21 | 2020 |
| Self-adapting part-based pedestrian detection using a fish-eye camera Y Qian, M Yang, C Wang, B Wang 2017 IEEE Intelligent Vehicles Symposium (IV), 33-38, 2017 | 19 | 2017 |
| Hy-Seg: A hybrid method for ground segmentation using point clouds Y Qian, X Wang, Z Chen, C Wang, M Yang IEEE Transactions on Intelligent Vehicles 8 (2), 1597-1606, 2022 | 16 | 2022 |
| Monocular pedestrian orientation estimation based on deep 2D-3D feedforward C Zhao, Y Qian, M Yang Pattern Recognition 100, 107182, 2020 | 16 | 2020 |
| Pedestrian feature generation in fish-eye images via adversary Y Qian, M Yang, C Wang, B Wang 2018 IEEE International Conference on Robotics and Automation (ICRA), 2007-2012, 2018 | 15 | 2018 |
| Threshold-adaptive unsupervised focal loss for domain adaptation of semantic segmentation W Yan, Y Qian, C Wang, M Yang IEEE Transactions on Intelligent Transportation Systems 24 (1), 752-763, 2022 | 9 | 2022 |
| 3-D vehicle detection enhancement using tracking feedback in sparse point clouds environments Y Qian, X Wang, H Zhuang, C Wang, M Yang IEEE Open Journal of Intelligent Transportation Systems 4, 471-480, 2023 | 8 | 2023 |
| Survey on fish-eye cameras and their applications in intelligent vehicles Y Qian, M Yang, JM Dolan IEEE Transactions on Intelligent Transportation Systems 23 (12), 22755-22771, 2022 | 8 | 2022 |
| Adversarial training-based hard example mining for pedestrian detection in fish-eye images Y Qian, M Yang, H Li, C Wang, B Wang IEEE Transactions on Intelligent Transportation Systems 22 (12), 7688-7698, 2020 | 6 | 2020 |
| Sparse-E2VID: A Sparse Convolutional Model for Event-Based Video Reconstruction Trained with Real Event Noise PRG Cadena, Y Qian, C Wang, M Yang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 5 | 2023 |
Ming YANGShanghai Jiao Tong University在 sjtu.edu.cn 的电子邮件经过验证
