Presentation

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38. Controllable Neural Reconstruction for Autonomous Driving
SessionPosters: Images, Video & Computer Vision
DescriptionWe 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.
Contributors
Máté Tóth
aiMotive
Péter Kovács
aiMotive
Zoltán Bendefy
aiMotive
Zoltán Hortsin
aiMotive
Tamás Matuszka
aiMotive
Event Type
Poster
TimeTuesday, 30 July 20249:00am - 5:30pm MDT
LocationMile High Pre-Function Area
Session TimeSunday, 28 July 20249:00am - 5:30pm MDTMonday, 29 July 20249:00am - 5:30pm MDTTuesday, 30 July 20249:00am - 5:30pm MDTWednesday, 31 July 20249:00am - 5:30pm MDTThursday, 1 August 20249:00am - 5:30pm MDT
LocationMile High Pre-Function Area
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Exhibitor Full Conference
Exhibitor Experience
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