| Robust Dense Mapping for Large-Scale Dynamic Environments IA Bârsan, P Liu, M Pollefeys, A Geiger International Conference on Robotics and Automation (ICRA), Brisbane, Australia, 2018 | 138 | 2018 |
| Exploiting sparse semantic HD maps for self-driving vehicle localization WC Ma, I Tartavull, IA Bârsan, S Wang, M Bai, G Mattyus, N Homayounfar, ... 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2019 | 105 | 2019 |
| Learning to Localize Using a LiDAR Intensity Map IA Barsan, S Wang, A Pokrovsky, R Urtasun Conference on Robot Learning, 605-616, 2018 | 96 | 2018 |
| Learning to Localize Through Compressed Binary Maps X Wei, IA Barsan, S Wang, J Martinez, R Urtasun Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019 | 33 | 2019 |
| Deep Multi-Task Learning for Joint Localization, Perception, and Prediction J Phillips, J Martinez, IA Bârsan, S Casas, A Sadat, R Urtasun Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 30 | 2021 |
| Permute, Quantize, and Fine-tune: Efficient Compression of Neural Networks J Martinez, J Shewakramani, TW Liu, IA Bârsan, W Zeng, R Urtasun Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 25 | 2021 |
| Asynchronous multi-view slam AJ Yang, C Cui, IA Bârsan, R Urtasun, S Wang 2021 IEEE International Conference on Robotics and Automation (ICRA), 5669-5676, 2021 | 24 | 2021 |
| CADSim: Robust and Scalable in-the-wild 3D Reconstruction for Controllable Sensor Simulation J Wang, S Manivasagam, Y Chen, Z Yang, IA Bârsan, AJ Yang, WC Ma, ... 6th Annual Conference on Robot Learning, 2022 | 10 | 2022 |
| Feature compression and localization for autonomous devices R Urtasun, X Wei, IA Barsan, JM Covarrubias, S Wang US Patent 11,715,012, 2023 | 9 | 2023 |
| Pit30m: A benchmark for global localization in the age of self-driving cars J Martinez, S Doubov, J Fan, S Wang, G Máttyus, R Urtasun 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020 | 9 | 2020 |
| Autonomous vehicle localization using a Lidar intensity map S Wang, A Pokrovsky, RU Sotil, IA Bârsan US Patent 11,726,208, 2023 | 8 | 2023 |
| Towards Zero Domain Gap: A Comprehensive Study of Realistic LiDAR Simulation for Autonomy Testing S Manivasagam, IA Bârsan, J Wang, Z Yang, R Urtasun Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 2 | 2023 |
| Localization with Diverse Dataset for Autonomous Vehicles JM Covarrubias, R Urtasun, S Wang, IA Barsan, GS Mattyus, S Doubov, ... US Patent App. 17/018,499, 2021 | 2 | 2021 |
| Simultaneous localization and mapping in dynamic scenes IA Barsan ETH Zurich, Department of Computer Science, 2017 | 2 | 2017 |
| Systems and Methods for Simultaneous Localization and Mapping Using Asynchronous Multi-View Cameras AJ Yang, C Cui, IA Bârsan, S Wang, R Urtasun US Patent App. 17/515,923, 2022 | 1 | 2022 |
| Binary feature compression for autonomous devices R Urtasun, X Wei, IA Barsan, JM Covarrubias, S Wang US Patent 11,461,583, 2022 | | 2022 |
| Attention based feature compression and localization for autonomous devices R Urtasun, X Wei, IA Barsan, JM Covarrubias, S Wang US Patent 11,449,713, 2022 | | 2022 |
| Supplementary Material for Towards Zero Domain Gap: A Comprehensive Study of Realistic LiDAR Simulation for Autonomy Testing S Manivasagam, IA Bârsan, J Wang, Z Yang, R Urtasun | | |
Raquel UrtasunFounder & CEO Waabi, Professor, University of Toronto.Verified email at cs.toronto.edu
