Autonomous Driving

239 papers with code ยท Computer Vision
Subtask of Autonomous Vehicles

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 )

Benchmarks

You can find evaluation results in the subtasks. You can also submitting evaluation metrics for this task.

Latest papers without code

A Sensitivity Analysis Approach for Evaluating a Radar Simulation for Virtual Testing of Autonomous Driving Functions

6 Aug 2020

In this paper, we introduce a sensitivity analysis approach for developing and evaluating a radar simulation, with the objective to identify the parameters with the greatest impact regarding the system under test.

AUTONOMOUS DRIVING

Active Perception using Light Curtains for Autonomous Driving

5 Aug 2020

Most real-world 3D sensors such as LiDARs perform fixed scans of the entire environment, while being decoupled from the recognition system that processes the sensor data.

3D OBJECT RECOGNITION AUTONOMOUS DRIVING

Graph Signal Processing for Geometric Data and Beyond: Theory and Applications

5 Aug 2020

Geometric data acquired from real-world scenes, e. g., 2D depth images, 3D point clouds, and 4D dynamic point clouds, have found a wide range of applications including immersive telepresence, autonomous driving, surveillance, etc.

AUTONOMOUS DRIVING

A Comparative Analysis of Deep Reinforcement Learning-enabled Freeway Decision-making for Automated Vehicles

4 Aug 2020

Deep reinforcement learning (DRL) is becoming a prevalent and powerful methodology to address the artificial intelligent problems.

AUTONOMOUS DRIVING DECISION MAKING Q-LEARNING

Conditional Latent Block Model: a Multivariate Time Series Clustering Approach for Autonomous Driving Validation

3 Aug 2020

The FunCLBM model extends the recently proposed Functional Latent Block Model and allows to create a dependency structure between row and column clusters.

AUTONOMOUS DRIVING DIMENSIONALITY REDUCTION FEATURE SELECTION TIME SERIES TIME SERIES ANALYSIS TIME SERIES CLUSTERING

End-to-end Birds-eye-view Flow Estimation for Autonomous Driving

3 Aug 2020

In autonomous driving, accurately estimating the state of surrounding obstacles is critical for safe and robust path planning.

AUTONOMOUS DRIVING

IoT System for Real-Time Near-Crash Detection for Automated Vehicle Testing

2 Aug 2020

While the latest automated vehicles (AVs) can handle most real-world scenarios they encounter, a major bottleneck for turning fully autonomous driving into reality is the lack of sufficient corner case data for training and testing AVs.

AUTONOMOUS DRIVING OBJECT DETECTION

PanoNet: Real-time Panoptic Segmentation through Position-Sensitive Feature Embedding

1 Aug 2020

We propose a simple, fast, and flexible framework to generate simultaneously semantic and instance masks for panoptic segmentation.

AUTONOMOUS DRIVING PANOPTIC SEGMENTATION

Learning to Rank for Active Learning: A Listwise Approach

31 Jul 2020

Active learning emerged as an alternative to alleviate the effort to label huge amount of data for data hungry applications (such as image/video indexing and retrieval, autonomous driving, etc.).

ACTIVE LEARNING AUTONOMOUS DRIVING IMAGE CLASSIFICATION LEARNING-TO-RANK

LevelSet R-CNN: A Deep Variational Method for Instance Segmentation

30 Jul 2020

Obtaining precise instance segmentation masks is of high importance in many modern applications such as robotic manipulation and autonomous driving.

AUTONOMOUS DRIVING INSTANCE SEGMENTATION SEMANTIC SEGMENTATION