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GTC ON-DEMAND

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Abstract:
Learn about Toyota's research on stereo-based deep learning for environment perception in challenging environments. We'll describe our novel ChiNet deep learning framework, implemented on a GPU for effective sensor fusion. We'll explain how we perform free space and road object estimation in a variety of environments by using a thermal stereo pair to estimate obstacle depth. The session will highlight our results, which show that the sensor fusion framework improves robustness and accuracy of deep learning-based free space object detection. We'll also cover our plan to implement the framework on the NVIDIA DRIVE AGX Pegasus platform.
Learn about Toyota's research on stereo-based deep learning for environment perception in challenging environments. We'll describe our novel ChiNet deep learning framework, implemented on a GPU for effective sensor fusion. We'll explain how we perform free space and road object estimation in a variety of environments by using a thermal stereo pair to estimate obstacle depth. The session will highlight our results, which show that the sensor fusion framework improves robustness and accuracy of deep learning-based free space object detection. We'll also cover our plan to implement the framework on the NVIDIA DRIVE AGX Pegasus platform.  Back
 
Topics:
Autonomous Vehicles, AI & Deep Learning Research
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9195
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