| Understanding the effective receptive field in deep convolutional neural networks W Luo, Y Li, R Urtasun, R Zemel Advances in neural information processing systems 29, 2016 | 2137 | 2016 |
| 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 | 1358 | 2018 |
| Efficient deep learning for stereo matching W Luo, AG Schwing, R Urtasun Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 925 | 2016 |
| 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 | 767 | 2018 |
| Deeproadmapper: Extracting road topology from aerial images G Máttyus, W Luo, R Urtasun Proceedings of the IEEE international conference on computer vision, 3438-3446, 2017 | 510 | 2017 |
| Intentnet: Learning to predict intention from raw sensor data S Casas, W Luo, R Urtasun Conference on Robot Learning, 947-956, 2018 | 452 | 2018 |
| 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 | 450 | 2019 |
| Torontocity: Seeing the world with a million eyes S Wang, M Bai, G Mattyus, H Chu, W Luo, B Yang, J Liang, J Cheverie, ... arXiv preprint arXiv:1612.00423, 2016 | 209 | 2016 |
| Exploiting semantic information and deep matching for optical flow M Bai, W Luo, K Kundu, R Urtasun Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 160 | 2016 |
| Efficient summarization with read-again and copy mechanism W Zeng, W Luo, S Fidler, R Urtasun arXiv preprint arXiv:1611.03382, 2016 | 127 | 2016 |
| Exploiting deep matching and SAR data for the geo-localization accuracy improvement of optical satellite images N Merkle, W Luo, S Auer, R Müller, R Urtasun Remote Sensing 9 (6), 586, 2017 | 118 | 2017 |
| Latent structured active learning W Luo, A Schwing, R Urtasun Advances in neural information processing systems 26, 2013 | 117 | 2013 |
| Efficient convolutions for real-time semantic segmentation of 3d point clouds C Zhang, W Luo, R Urtasun 2018 International Conference on 3D Vision (3DV), 399-408, 2018 | 99 | 2018 |
| Multi-task machine-learned models for object intention determination in autonomous driving S Casas, W Luo, R Urtasun US Patent 11,370,423, 2022 | 70 | 2022 |
| Systems and methods for object detection, tracking, and motion prediction W Luo, B Yang, R Urtasun US Patent 11,475,351, 2022 | 63 | 2022 |
| Three Dimensional Object Detection W Luo, B Yang, R Urtasun US Patent App. 16/133,046, 2019 | 62 | 2019 |
| End-to-end interpretable motion planner for autonomous vehicles W Zeng, W Luo, A Sadat, B Yang, R Urtasun US Patent 11,755,018, 2023 | 58 | 2023 |
| Waymax: An accelerated, data-driven simulator for large-scale autonomous driving research C Gulino, J Fu, W Luo, G Tucker, E Bronstein, Y Lu, J Harb, X Pan, ... Advances in Neural Information Processing Systems 36, 2024 | 55 | 2024 |
| Semantic segmentation of three-dimensional data CJH Zhang, W Luo, R Urtasun US Patent 10,970,553, 2021 | 54 | 2021 |
| Jfp: Joint future prediction with interactive multi-agent modeling for autonomous driving W Luo, C Park, A Cornman, B Sapp, D Anguelov Conference on Robot Learning, 1457-1467, 2023 | 32 | 2023 |
