| Predicting motion of vulnerable road users using high-definition maps and efficient convnets FC Chou, TH Lin, H Cui, V Radosavljevic, T Nguyen, TK Huang, ... 2020 IEEE Intelligent Vehicles Symposium (IV), 1655-1662, 2020 | 57 | 2020 |
| Improving movement prediction of traffic actors using off-road loss and bias mitigation M Niedoba, H Cui, K Luo, D Hegde, FC Chou, N Djuric Workshop on’Machine Learning for Autonomous Driving’at Conference on Neural …, 2019 | 23 | 2019 |
| Critic sequential monte carlo V Lioutas, JW Lavington, J Sefas, M Niedoba, Y Liu, B Zwartsenberg, ... arXiv preprint arXiv:2205.15460, 2022 | 4 | 2022 |
| Conditional Permutation Invariant Flows B Zwartsenberg, A Ścibior, M Niedoba, V Lioutas, Y Liu, J Sefas, S Dabiri, ... arXiv preprint arXiv:2206.09021, 2022 | 3 | 2022 |
| A Diffusion-Model of Joint Interactive Navigation M Niedoba, J Lavington, Y Liu, V Lioutas, J Sefas, X Liang, D Green, ... Advances in Neural Information Processing Systems 36, 2024 | 2 | 2024 |
| Nearest Neighbour Score Estimators for Diffusion Generative Models M Niedoba, D Green, S Naderiparizi, V Lioutas, JW Lavington, X Liang, ... arXiv preprint arXiv:2402.08018, 2024 | | 2024 |
| Video Killed the HD-Map: Predicting Multi-Agent Behavior Directly From Aerial Images Y Liu, V Lioutas, JW Lavington, M Niedoba, J Sefas, S Dabiri, D Green, ... 2023 IEEE 26th International Conference on Intelligent Transportation …, 2023 | | 2023 |
| Realistically distributing object placements in synthetic training data improves the performance of vision-based object detection models S Dabiri, V Lioutas, B Zwartsenberg, Y Liu, M Niedoba, X Liang, D Green, ... arXiv preprint arXiv:2305.14621, 2023 | | 2023 |
| Video Killed the HD-Map: Predicting Driving Behavior Directly From Drone Images Y Liu, V Lioutas, JW Lavington, M Niedoba, J Sefas, S Dabiri, D Green, ... arXiv preprint arXiv:2305.11856, 2023 | | 2023 |
Fang-Chieh ChouSoftware Engineer, DoorDash LabsПодтвержден адрес электронной почты в домене alumni.stanford.edu
