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 | 152 | 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 | 124 | 2019 |
Learning to Localize Using a LiDAR Intensity Map IA Barsan, S Wang, A Pokrovsky, R Urtasun Conference on Robot Learning, 605-616, 2018 | 106 | 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 | 37 | 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 | 36 | 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 | 35 | 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 | 29 | 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 | 17 | 2022 |
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 | 13 | 2020 |
Autonomous vehicle localization using a Lidar intensity map S Wang, A Pokrovsky, RU Sotil, IA Bârsan US Patent 11,726,208, 2023 | 10 | 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 | 9 | 2023 |
Localization with diverse dataset for autonomous vehicles JM Covarrubias, R Urtasun, S Wang, IA Barsan, GS Mattyus, A Doubov, ... US Patent 11,820,397, 2023 | 3 | 2023 |
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 | 2 | 2022 |
Simultaneous localization and mapping in dynamic scenes IA Barsan ETH Zurich, Department of Computer Science, 2017 | 2 | 2017 |
THREE DIMENSIONAL OBJECT RECONSTRUCTION FOR SENSOR SIMULATION IA Barsan, Y Chen, W Ma, S Manivasagam, R Urtasun, J Wang, Z Yang US Patent App. 18/209,609, 2023 | | 2023 |
Feature compression and localization for autonomous devices R Urtasun, X Wei, IA Barsan, JM Covarrubias, S Wang US Patent 11,715,012, 2023 | | 2023 |
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 | | |