End-to-end Birds-eye-view Flow Estimation for Autonomous Driving

Matthew Kliemann
Matthew Kliemann
Jie Li
Jie Li
Chao Fang
Chao Fang
Wolfram Burgard
Wolfram Burgard
Cited by: 0|Bibtex|Views14
Other Links: arxiv.org

Abstract:

In autonomous driving, accurately estimating the state of surrounding obstacles is critical for safe and robust path planning. However, this perception task is difficult, particularly for generic obstacles/objects, due to appearance and occlusion changes. To tackle this problem, we propose an end-to-end deep learning framework for LIDAR...More

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