# Autonomous Vehicles

347 papers with code • 1 benchmarks • 28 datasets

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.

## Libraries

Use these libraries to find Autonomous Vehicles models and implementations
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# AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehicles

15 May 2017

Developing and testing algorithms for autonomous vehicles in real world is an expensive and time consuming process.

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# Flow: A Modular Learning Framework for Mixed Autonomy Traffic

16 Oct 2017

Furthermore, in single-lane traffic, a small neural network control law with only local observation is found to eliminate stop-and-go traffic - surpassing all known model-based controllers to achieve near-optimal performance - and generalize to out-of-distribution traffic densities.

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# nuScenes: A multimodal dataset for autonomous driving

Most autonomous vehicles, however, carry a combination of cameras and range sensors such as lidar and radar.

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24 May 2017

COMA uses a centralised critic to estimate the Q-function and decentralised actors to optimise the agents' policies.

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# DynaSLAM: Tracking, Mapping and Inpainting in Dynamic Scenes

14 Jun 2018

And it also estimates a map of the static parts of the scene, which is a must for long-term applications in real-world environments.

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# LiDAR-Camera Calibration using 3D-3D Point correspondences

27 May 2017

With the advent of autonomous vehicles, LiDAR and cameras have become an indispensable combination of sensors.

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# LEAF: A Benchmark for Federated Settings

3 Dec 2018

Modern federated networks, such as those comprised of wearable devices, mobile phones, or autonomous vehicles, generate massive amounts of data each day.

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# Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes

15 Jan 2021

The proposed deep dual-resolution networks (DDRNets) are composed of two deep branches between which multiple bilateral fusions are performed.

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# Joint 3D Proposal Generation and Object Detection from View Aggregation

6 Dec 2017

We present AVOD, an Aggregate View Object Detection network for autonomous driving scenarios.

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# On the Importance of Stereo for Accurate Depth Estimation: An Efficient Semi-Supervised Deep Neural Network Approach

26 Mar 2018

Despite the progress on monocular depth estimation in recent years, we show that the gap between monocular and stereo depth accuracy remains large$-$a particularly relevant result due to the prevalent reliance upon monocular cameras by vehicles that are expected to be self-driving.

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