| Learning to reweight examples for robust deep learning M Ren, W Zeng, B Yang, R Urtasun International Conference on Machine Learning (ICML), 2018 | 1973 | 2018 |
| Pixor: Real-time 3d object detection from point clouds B Yang, W Luo, R Urtasun Proceedings of the IEEE conference on Computer Vision and Pattern …, 2018 | 1608 | 2018 |
| 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 | 1237 | 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 | 926 | 2019 |
| Learning lane graph representations for motion forecasting M Liang, B Yang, R Hu, Y Chen, R Liao, S Feng, R Urtasun European Conference on Computer Vision, 541-556, 2020 | 899 | 2020 |
| Fast and furious: Real time end-to-end 3d detection, tracking and motion forecasting with a single convolutional net W Luo, B Yang, R Urtasun Proceedings of the IEEE conference on Computer Vision and Pattern …, 2018 | 887 | 2018 |
| T-cnn: Tubelets with convolutional neural networks for object detection from videos K Kang, H Li, J Yan, X Zeng, B Yang, T Xiao, C Zhang, Z Wang, R Wang, ... IEEE Transactions on Circuits and Systems for Video Technology 28 (10), 2896 …, 2017 | 721 | 2017 |
| V2vnet: Vehicle-to-vehicle communication for joint perception and prediction TH Wang, S Manivasagam, M Liang, B Yang, W Zeng, U Raquel European Conference on Computer Vision, 2020 | 658 | 2020 |
| End-to-end interpretable neural motion planner W Zeng, W Luo, S Suo, A Sadat, B Yang, S Casas, R Urtasun Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 583 | 2019 |
| Hdnet: Exploiting hd maps for 3d object detection B Yang, M Liang, R Urtasun Conference on Robot Learning, 146-155, 2018 | 464 | 2018 |
| Aggregate channel features for multi-view face detection B Yang, J Yan, Z Lei, SZ Li IEEE International Joint Conference on Biometrics, 1-8, 2014 | 443 | 2014 |
| Convolutional channel features B Yang, J Yan, Z Lei, SZ Li Proceedings of the IEEE International Conference on Computer Vision, 82-90, 2015 | 409 | 2015 |
| Lidarsim: Realistic lidar simulation by leveraging the real world S Manivasagam, S Wang, K Wong, W Zeng, M Sazanovich, S Tan, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 343 | 2020 |
| 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 | 334 | 2020 |
| Sbnet: Sparse blocks network for fast inference M Ren, A Pokrovsky, B Yang, R Urtasun Proceedings of the IEEE conference on Computer Vision and Pattern …, 2018 | 290 | 2018 |
| 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 | 260 | 2020 |
| Torontocity: Seeing the world with a million eyes S Wang, M Bai, G Mattyus, H Chu, W Luo, B Yang, J Liang, J Cheverie, ... Proceedings of the IEEE International Conference on Computer Vision, 3009-3017, 2017 | 227 | 2017 |
| 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 | 204 | 2019 |
| Crafting gbd-net for object detection X Zeng, W Ouyang, J Yan, H Li, T Xiao, K Wang, Y Liu, Y Zhou, B Yang, ... IEEE Transactions on Pattern Analysis and Machine Intelligence 40 (9), 2109-2123, 2018 | 182 | 2018 |
| Radarnet: Exploiting radar for robust perception of dynamic objects B Yang, R Guo, M Liang, S Casas, R Urtasun European Conference on Computer Vision, 2020 | 179 | 2020 |
