| Recurrent convolutional neural network for object recognition M Liang, X Hu Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 1401 | 2015 |
| Deep continuous fusion for multi-sensor 3d object detection M Liang, B Yang, S Wang, R Urtasun Proceedings of the European conference on computer vision (ECCV), 641-656, 2018 | 1121 | 2018 |
| Defense against adversarial attacks using high-level representation guided denoiser F Liao, M Liang, Y Dong, T Pang, X Hu, J Zhu Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 1086 | 2018 |
| Multi-task multi-sensor fusion for 3d object detection M Liang, B Yang, Y Chen, R Hu, R Urtasun Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 844 | 2019 |
| Learning lane graph representations for motion forecasting M Liang, B Yang, R Hu, Y Chen, R Liao, S Feng, R Urtasun Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 655 | 2020 |
| Evaluate the malignancy of pulmonary nodules using the 3-d deep leaky noisy-or network F Liao, M Liang, Z Li, X Hu, S Song IEEE transactions on neural networks and learning systems 30 (11), 3484-3495, 2019 | 531 | 2019 |
| V2vnet: Vehicle-to-vehicle communication for joint perception and prediction TH Wang, S Manivasagam, M Liang, B Yang, W Zeng, R Urtasun Computer vision–ECCV 2020: 16th European conference, Glasgow, UK, August 23 …, 2020 | 428 | 2020 |
| Hdnet: Exploiting hd maps for 3d object detection B Yang, M Liang, R Urtasun Conference on Robot Learning, 146-155, 2018 | 420 | 2018 |
| Adversarial attacks and defences competition A Kurakin, I Goodfellow, S Bengio, Y Dong, F Liao, M Liang, T Pang, ... The NIPS'17 Competition: Building Intelligent Systems, 195-231, 2018 | 369 | 2018 |
| Physically realizable adversarial examples for lidar object detection J Tu, M Ren, S Manivasagam, M Liang, B Yang, R Du, F Cheng, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 268 | 2020 |
| Pnpnet: End-to-end perception and prediction with tracking in the loop M Liang, B Yang, W Zeng, Y Chen, R Hu, S Casas, R Urtasun Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 204 | 2020 |
| Lanercnn: Distributed representations for graph-centric motion forecasting W Zeng, M Liang, R Liao, R Urtasun 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2021 | 198 | 2021 |
| Learning joint 2d-3d representations for depth completion Y Chen, B Yang, M Liang, R Urtasun Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 181 | 2019 |
| End-to-end contextual perception and prediction with interaction transformer LL Li, B Yang, M Liang, W Zeng, M Ren, S Segal, R Urtasun 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020 | 140 | 2020 |
| Radarnet: Exploiting radar for robust perception of dynamic objects B Yang, R Guo, M Liang, S Casas, R Urtasun European conference on computer vision, 496-512, 2020 | 140 | 2020 |
| Traffic sign detection by ROI extraction and histogram features-based recognition M Liang, M Yuan, X Hu, J Li, H Liu The 2013 international joint conference on Neural networks (IJCNN), 1-8, 2013 | 128 | 2013 |
| Identifying unknown instances for autonomous driving K Wong, S Wang, M Ren, M Liang, R Urtasun Conference on Robot Learning, 384-393, 2020 | 116 | 2020 |
| Multi-task multi-sensor fusion for three-dimensional object detection R Urtasun, B Yang, M Liang US Patent 11,494,937, 2022 | 94 | 2022 |
| Exploring adversarial robustness of multi-sensor perception systems in self driving J Tu, H Li, X Yan, M Ren, Y Chen, M Liang, E Bitar, E Yumer, R Urtasun arXiv preprint arXiv:2101.06784, 2021 | 88 | 2021 |
| Convolutional neural networks with intra-layer recurrent connections for scene labeling M Liang, X Hu, B Zhang Advances in neural information processing systems 28, 2015 | 80 | 2015 |
Bin YangUniversity of TorontoВерификована је имејл адреса на cs.toronto.edu
