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.

( Image credit: GSNet: Joint Vehicle Pose and Shape Reconstruction with Geometrical and Scene-aware Supervision )


Use these libraries to find Autonomous Vehicles models and implementations

Most implemented papers

AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehicles

Microsoft/AirSim 15 May 2017

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

Flow: A Modular Learning Framework for Mixed Autonomy Traffic

flow-project/flow 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.

nuScenes: A multimodal dataset for autonomous driving

nutonomy/nuscenes-devkit CVPR 2020

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

Counterfactual Multi-Agent Policy Gradients

opendilab/DI-engine 24 May 2017

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

DynaSLAM: Tracking, Mapping and Inpainting in Dynamic Scenes

BertaBescos/DynaSLAM 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.

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

ankitdhall/lidar_camera_calibration 27 May 2017

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

LEAF: A Benchmark for Federated Settings

TalwalkarLab/leaf 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.

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

ydhongHIT/DDRNet 15 Jan 2021

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

Joint 3D Proposal Generation and Object Detection from View Aggregation

kujason/avod 6 Dec 2017

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

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

NVIDIA-Jetson/redtail 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.