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Autonomous vehicles is the task of making a vehicle that can guide itself 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: GSNet: Joint Vehicle Pose and Shape Reconstruction with Geometrical and Scene-aware Supervision )

Benchmarks

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Datasets

Latest papers without code

Challenges and Obstacles Towards Deploying Deep Learning Models on Mobile Devices

6 May 2021

From computer vision and speech recognition to forecasting trajectories in autonomous vehicles, deep learning approaches are at the forefront of so many domains.

AUTONOMOUS VEHICLES SPEECH RECOGNITION

Calibration of Human Driving Behavior and Preference Using Naturalistic Traffic Data

5 May 2021

Towards this end it is necessary that we have a comprehensive modeling framework for decision-making within which human driving preferences can be inferred statistically from observed driving behaviors in realistic and naturalistic traffic settings.

AUTONOMOUS VEHICLES DECISION MAKING

Novelty Detection and Analysis of Traffic Scenario Infrastructures in the Latent Space of a Vision Transformer-Based Triplet Autoencoder

5 May 2021

An autoencoder triplet network provides latent representations for infrastructure images which are used for outlier detection.

AUTONOMOUS VEHICLES OUTLIER DETECTION

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

Improving Perception via Sensor Placement: Designing Multi-LiDAR Systems for Autonomous Vehicles

2 May 2021

Our results confirm that sensor placement is an important factor in 3D point cloud-based object detection and could lead to a variation of performance by 10% ~ 20% on the state-of-the-art perception algorithms.

AUTONOMOUS VEHICLES OBJECT DETECTION

Pedestrian Collision Avoidance for Autonomous Vehicles at Unsignalized Intersection Using Deep Q-Network

1 May 2021

Prior research has extensively explored Autonomous Vehicle (AV) navigation in the presence of other vehicles, however, navigation among pedestrians, who are the most vulnerable element in urban environments, has been less examined.

AUTONOMOUS VEHICLES

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

IPatch: A Remote Adversarial Patch

30 Apr 2021

In this paper, we introduce a new type of adversarial patch which alters a model's perception of an image's semantics.

AUTONOMOUS VEHICLES OBJECT RECOGNITION SEMANTIC SEGMENTATION

Collaborative Human-Agent Planning for Resilience

29 Apr 2021

Results show that participants' constraints improved the expected return of the plans by 10% ($p < 0. 05$) relative to baseline plans, demonstrating that human insight can be used in collaborative planning for resilience.

AUTONOMOUS VEHICLES TEMPORAL LOGIC

Neuromorphic Computing is Turing-Complete

28 Apr 2021

Given that the {\mu}-recursive functions and operators are precisely the ones that can be computed using a Turing machine, this work establishes the Turing-completeness of neuromorphic computing.

AUTONOMOUS VEHICLES EDGE-COMPUTING