تقرير
Hydra-MDP: End-to-end Multimodal Planning with Multi-target Hydra-Distillation
| العنوان: | Hydra-MDP: End-to-end Multimodal Planning with Multi-target Hydra-Distillation |
|---|---|
| المؤلفون: | Li, Zhenxin, Li, Kailin, Wang, Shihao, Lan, Shiyi, Yu, Zhiding, Ji, Yishen, Li, Zhiqi, Zhu, Ziyue, Kautz, Jan, Wu, Zuxuan, Jiang, Yu-Gang, Alvarez, Jose M. |
| سنة النشر: | 2024 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition |
| الوصف: | We propose Hydra-MDP, a novel paradigm employing multiple teachers in a teacher-student model. This approach uses knowledge distillation from both human and rule-based teachers to train the student model, which features a multi-head decoder to learn diverse trajectory candidates tailored to various evaluation metrics. With the knowledge of rule-based teachers, Hydra-MDP learns how the environment influences the planning in an end-to-end manner instead of resorting to non-differentiable post-processing. This method achieves the $1^{st}$ place in the Navsim challenge, demonstrating significant improvements in generalization across diverse driving environments and conditions. More details by visiting \url{https://github.com/NVlabs/Hydra-MDP}. Comment: The 1st place solution of End-to-end Driving at Scale at the CVPR 2024 Autonomous Grand Challenge |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2406.06978 |
| رقم الأكسشن: | edsarx.2406.06978 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |