“Controllable Neural Reconstruction for Autonomous Driving” by Tóth, Kovács, Bendefy, Hortsin and Matuszka
Conference:
Type(s):
Title:
- Controllable Neural Reconstruction for Autonomous Driving
Session/Category Title: Images, Video & Computer Vision
Presenter(s)/Author(s):
Abstract:
We introduce an automated pipeline designed for training neural reconstruction models by leveraging sensor streams gathered from a data collection vehicle. Subsequently, our simulator, aiSim, is employed to generate a controllable virtual counterpart of the real-world environment, enabling the replay of scenes in a closed-loop fashion.
References:
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