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12/18/2020
Labels Are Not Perfect: Inferring Spatial Uncertainty in Object Detection
The availability of many real-world driving datasets is a key reason beh...
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10/19/2020
DeepReflecs: Deep Learning for Automotive Object Classification with Radar Reflections
This paper presents an novel object type classification method for autom...
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09/17/2020
Holistic Filter Pruning for Efficient Deep Neural Networks
Deep neural networks (DNNs) are usually over-parameterized to increase t...
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08/10/2020
Labels Are Not Perfect: Improving Probabilistic Object Detection via Label Uncertainty
Reliable uncertainty estimation is crucial for robust object detection i...
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04/16/2020
Where can I drive? Deep Ego-Corridor Estimation for Robust Automated Driving
Lane detection is an essential part of the perception module of any auto...
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03/07/2020
Inferring Spatial Uncertainty in Object Detection
The availability of real-world datasets is the prerequisite to develop o...
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02/19/2020
SYMOG: learning symmetric mixture of Gaussian modes for improved fixed-point quantization
Deep neural networks (DNNs) have been proven to outperform classical met...
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02/01/2020
Leveraging Uncertainties for Deep Multi-modal Object Detection in Autonomous Driving
This work presents a probabilistic deep neural network that combines LiD...
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09/26/2019
Can We Trust You? On Calibration of a Probabilistic Object Detector for Autonomous Driving
Reliable uncertainty estimation is crucial for perception systems in saf...
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07/16/2019
Learning Multimodal Fixed-Point Weights using Gradient Descent
Due to their high computational complexity, deep neural networks are sti...
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09/14/2018