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 | 129 | 2020 |
Discrete residual flow for probabilistic pedestrian behavior prediction A Jain, S Casas, R Liao, Y Xiong, S Feng, S Segal, R Urtasun Conference on Robot Learning, 407-419, 2020 | 80 | 2020 |
Probabilistic prediction of dynamic object behavior for autonomous vehicles A Jain, S Casas, R Liao, Y Xiong, S Feng, S Segal, R Urtasun US Patent 11,521,396, 2022 | 12 | 2022 |
Diverse complexity measures for dataset curation in self-driving A Sadat, S Segal, S Casas, J Tu, B Yang, R Urtasun, E Yumer 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2021 | 11 | 2021 |
End-toend contextual perception and prediction with interaction transformer. In 2020 IEEE LL Li, B Yang, M Liang, W Zeng, M Ren, S Segal, R Urtasun RSJ International Conference on Intelligent Robots and Systems (IROS), 5784-5791, 2020 | 11 | 2020 |
Systems and methods for generating motion forecast data for a plurality of actors with respect to an autonomous vehicle LY Li, B Yang, M Liang, W Zeng, M Ren, S Segal, R Urtasun US Patent 11,691,650, 2023 | 10 | 2023 |
Universal embeddings for spatio-temporal tagging of self-driving logs S Segal, E Kee, W Luo, A Sadat, E Yumer, R Urtasun Conference on Robot Learning, 973-983, 2021 | 6 | 2021 |
Just label what you need: fine-grained active selection for perception and prediction through partially labeled scenes S Segal, N Kumar, S Casas, W Zeng, M Ren, J Wang, R Urtasun arXiv preprint arXiv:2104.03956, 2021 | 5 | 2021 |
Labelformer: Object trajectory refinement for offboard perception from lidar point clouds AJ Yang, S Casas, N Dvornik, S Segal, Y Xiong, JSK Hu, C Fang, ... Conference on Robot Learning, 3364-3383, 2023 | 4 | 2023 |
Just label what you need: Fine-grained active selection for p&p through partially labeled scenes S Segal, N Kumar, S Casas, W Zeng, M Ren, J Wang, R Urtasun Conference on Robot Learning, 816-826, 2022 | 4 | 2022 |
Systems and methods for generating motion forecast data for a plurality of actors with respect to an autonomous vehicle LY Li, B Yang, W Zeng, M Liang, M Ren, S Segal, R Urtasun US Patent 11,780,472, 2023 | 1 | 2023 |
Systems and Methods for Generating Motion Forecast Data for a Plurality of Actors with Respect to an Autonomous Vehicle LY Li, B Yang, W Zeng, M Liang, M Ren, S Segal, RU Sotil US Patent App. 18/240,771, 2024 | | 2024 |
Systems and methods for answering region specific questions S Segal, W Luo, ER Kee, E Yumer, R Urtasun, A Sadat US Patent 11,620,838, 2023 | | 2023 |