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Autonomous driving is the task of driving a vehicle without human conduction.

Many of the state-of-the-art results can be found at more general task pages such as 3D Object Detection and Semantic Segmentation.

( Image credit: Exploring the Limitations of Behavior Cloning for Autonomous Driving )

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Latest papers without code

A 2.5D Vehicle Odometry Estimation for Vision Applications

6 May 2021

This paper proposes a method to estimate the pose of a sensor mounted on a vehicle as the vehicle moves through the world, an important topic for autonomous driving systems.

AUTONOMOUS DRIVING

Preference learning along multiple criteria: A game-theoretic perspective

NeurIPS 2020

Finally, we showcase the practical utility of our framework in a user study on autonomous driving, where we find that the Blackwell winner outperforms the von Neumann winner for the overall preferences.

AUTONOMOUS DRIVING

A Theoretical-Empirical Approach to Estimating Sample Complexity of DNNs

5 May 2021

It is however unclear how to extend these measures to DNNs and therefore the existing analyses are applicable to simple neural networks, which are not used in practice, e. g., linear or shallow ones or otherwise multi-layer perceptrons.

AUTONOMOUS DRIVING

Software Engineering for AI-Based Systems: A Survey

5 May 2021

Our results are valuable for: researchers, to quickly understand the state of the art and learn which topics need more research; practitioners, to learn about the approaches and challenges that SE entails for AI-based systems; and, educators, to bridge the gap among SE and AI in their curricula.

AUTONOMOUS DRIVING SPEECH RECOGNITION

Towards End-to-End Deep Learning for Autonomous Racing: On Data Collection and a Unified Architecture for Steering and Throttle Prediction

4 May 2021

Deep Neural Networks (DNNs) which are trained end-to-end have been successfully applied to solve complex problems that we have not been able to solve in past decades.

AUTONOMOUS DRIVING

3D Vehicle Detection Using Camera and Low-Resolution LiDAR

4 May 2021

Taking the low-resolution LiDAR point cloud and the monocular image as input, our depth completion network is able to produce dense point cloud that is subsequently processed by a voxel-based network for 3D object detection.

3D OBJECT DETECTION AUTONOMOUS DRIVING DEPTH COMPLETION

Pedestrian Detection in 3D Point Clouds using Deep Neural Networks

3 May 2021

In this paper, we propose a PointNet++ based architecture to detect pedestrians in dense 3D point clouds.

AUTONOMOUS DRIVING PEDESTRIAN DETECTION

A LiDAR Assisted Control Module with High Precision in Parking Scenarios for Autonomous Driving Vehicle

2 May 2021

For example, humans are good at interactive tasks (while autonomous driving systems usually do not), but we are often incompetent for tasks with strict precision demands.

AUTONOMOUS DRIVING

Lane Graph Estimation for Scene Understanding in Urban Driving

1 May 2021

Lane-level scene annotations provide invaluable data in autonomous vehicles for trajectory planning in complex environments such as urban areas and cities.

AUTONOMOUS DRIVING SCENE UNDERSTANDING TRAJECTORY PLANNING