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01/31/2023
Priors are Powerful: Improving a Transformer for Multi-camera 3D Detection with 2D Priors
Transfomer-based approaches advance the recent development of multi-came...
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09/26/2022
DeepFusion: A Robust and Modular 3D Object Detector for Lidars, Cameras and Radars
We propose DeepFusion, a modular multi-modal architecture to fuse lidars...
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04/21/2022
Understanding the Domain Gap in LiDAR Object Detection Networks
In order to make autonomous driving a reality, artificial neural network...
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05/25/2021
Risk-Based Tenant Impatience for Privacy-Intolerant Queuing in B5G Cloud Services
Driven by emerging tolerance-critical use cases of future communication ...
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03/06/2021
A Simple and Efficient Multi-task Network for 3D Object Detection and Road Understanding
Detecting dynamic objects and predicting static road information such as...
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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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11/20/2020
A Review and Comparative Study on Probabilistic Object Detection in Autonomous Driving
Capturing uncertainty in object detection is indispensable for safe auto...
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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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02/01/2020
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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09/06/2019
Multiservice-based Network Slicing Orchestration with Impatient Tenants
The combination of recent emerging technologies such as network function...
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02/21/2019
Deep Multi-modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges
Recent advancements in the perception for autonomous driving are driven ...
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01/29/2019
Deep Active Learning for Efficient Training of a LiDAR 3D Object Detector
Training a deep object detector for autonomous driving requires a huge a...
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01/18/2019
A Utility-Driven Multi-Queue Admission Control Solution for Network Slicing
The combination of recent emerging technologies such as network function...
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09/18/2018
Rational Impatience Admission Control in 5G-sliced Networks: Shall I Bide my Slice Opportunity?
Recently, the specifications of the fifth generation (5G) of mobile netw...
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09/18/2018
Rational Impatience Strategy of 5G Network Tenants in Queue-Based Slice Admission Control: Shall I Wait Further for My Network Slice?
The fifth generation (5G) technologies enable an emerge type of public c...
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09/14/2018
Leveraging Heteroscedastic Aleatoric Uncertainties for Robust Real-Time LiDAR 3D Object Detection
We present a robust real-time LiDAR 3D object detector that leverages he...
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07/03/2018
Leveraging Robotic Prior Tactile Exploratory Action Experiences For Learning New Objects's Physical Properties
Reusing the tactile knowledge of some previously-explored objects helps ...
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04/13/2018
Towards Safe Autonomous Driving: Capture Uncertainty in the Deep Neural Network For Lidar 3D Vehicle Detection
To assure that an autonomous car is driving safely on public roads, its ...
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04/05/2018
