| Structural-RNN: Deep Learning on Spatio-Temporal Graphs A Jain, AR Zamir, S Savarese, A Saxena Computer Vision and Pattern Recognition (CVPR), 2016 | 1411 | 2016 |
| PointFusion: Deep Sensor Fusion for 3D Bounding Box Estimation DX Xu, D Anguelov, A Jain The IEEE Conference on Computer Vision and Pattern Recognition, 244-253, 2018 | 846 | 2018 |
| One thousand and one hours: Self-driving motion prediction dataset J Houston, G Zuidhof, L Bergamini, Y Ye, L Chen, A Jain, S Omari, ... Conference on Robot Learning, 409-418, 2021 | 443 | 2021 |
| Recurrent Neural Networks for Driver Activity Anticipation via Sensory-Fusion Architecture A Jain, A Singh, HS Koppula, S Soh, A Saxena International Conference on Robotics and Automation (ICRA), 2016 | 351 | 2016 |
| Car that Knows Before You Do: Anticipating Maneuvers via Learning Temporal Driving Models A Jain, HS Koppula, B Raghavan, S Soh, A Saxena International Conference on Computer Vision (ICCV), 2015 | 341 | 2015 |
| RoboBrain: Large-Scale Knowledge Engine for Robots A Saxena, A Jain, O Sener, A Jami, DK Misra, HS Koppula International Symposium on Robotics Research (ISRR), 2015 | 226 | 2015 |
| Learning trajectory preferences for manipulators via iterative improvement A Jain, B Wojcik, T Joachims, A Saxena Advances in Neural Information Processing Systems (NIPS), 575-583, 2013 | 163 | 2013 |
| Brain4cars: Car that knows before you do via sensory-fusion deep learning architecture A Jain, HS Koppula, S Soh, B Raghavan, A Singh, A Saxena arXiv preprint arXiv:1601.00740, 2016 | 148 | 2016 |
| Lyft level 5 av dataset 2019 R Kesten, M Usman, J Houston, T Pandya, K Nadhamuni, A Ferreira, ... urlhttps://level5. lyft. com/dataset 1, 3, 2019 | 142 | 2019 |
| Learning preferences for manipulation tasks from online coactive feedback A Jain, S Sharma, T Joachims, A Saxena The International Journal of Robotics Research (IJRR), 2015 | 130 | 2015 |
| Anticipatory planning for humanrobot teams H Koppula, A Jain, A Saxena International Symposium on Experimental Robotics (ISER), 2014 | 114 | 2014 |
| SPG-GMKL: generalized multiple kernel learning with a million kernels A Jain, SVN Vishwanathan, M Varma Proceedings of the 18th ACM SIGKDD international conference on Knowledge …, 2012 | 113 | 2012 |
| Level 5 perception dataset 2020 R Kesten, M Usman, J Houston, T Pandya, K Nadhamuni, A Ferreira, ... Woven Planet Holdings, Tokyo, Japan, 2019 | 76 | 2019 |
| Three-dimensional bounding box from two-dimensional image and point cloud data D Xu, DD Anguelov, A Jain US Patent 10,438,371, 2019 | 72 | 2019 |
| Safetynet: Safe planning for real-world self-driving vehicles using machine-learned policies M Vitelli, Y Chang, Y Ye, A Ferreira, M Wołczyk, B Osiński, M Niendorf, ... 2022 International Conference on Robotics and Automation (ICRA), 897-904, 2022 | 71 | 2022 |
| Lyft level 5 perception dataset 2020 R Kesten, M Usman, J Houston, T Pandya, K Nadhamuni, A Ferreira, ... | 56 | 2019 |
| Lyft level 5 av dataset 2019. urlhttps R Kesten, M Usman, J Houston, T Pandya, K Nadhamuni, A Ferreira, ... level5. lyft. com/dataset 1 (2), 3, 2019 | 49 | 2019 |
| Autonomy 2.0: Why is self-driving always 5 years away? A Jain, L Del Pero, H Grimmett, P Ondruska arXiv preprint arXiv:2107.08142, 2021 | 46 | 2021 |
| PlanIt: A Crowdsourcing Approach for Learning to Plan Paths from Large Scale Preference Feedback A Jain, D Das, JK Gupta, A Saxena International Conference on Robotics and Automation (ICRA), 2015 | 34 | 2015 |
| Geolocalized models for perception, prediction, or planning MJ Benisch, A Jain US Patent 11,868,136, 2024 | 17 | 2024 |
Ashutosh SaxenaFormer Faculty, Computer Science, Cornell University. Stanford Universitycs.stanford.edu의 이메일 확인됨
