Autonomous Vehicles

190 papers with code • 1 benchmarks • 24 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 )

Greatest papers with code

Simulation to Scaled City: Zero-Shot Policy Transfer for Traffic Control via Autonomous Vehicles

flow-project/flow 14 Dec 2018

We then directly transfer this policy without any tuning to the University of Delaware Scaled Smart City (UDSSC), a 1:25 scale testbed for connected and automated vehicles.

Autonomous Vehicles

Flow: A Modular Learning Framework for Autonomy in Traffic

flow-project/flow 16 Oct 2017

The rapid development of autonomous vehicles (AVs) holds vast potential for transportation systems through improved safety, efficiency, and access to mobility.

Autonomous Vehicles

Joint Monocular 3D Vehicle Detection and Tracking

ucbdrive/3d-vehicle-tracking ICCV 2019

The framework can not only associate detections of vehicles in motion over time, but also estimate their complete 3D bounding box information from a sequence of 2D images captured on a moving platform.

3D Object Detection 3D Pose Estimation +4

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.

Autonomous Vehicles Object Detection

Benchmarking 6DOF Outdoor Visual Localization in Changing Conditions

ethz-asl/hfnet CVPR 2018

Visual localization enables autonomous vehicles to navigate in their surroundings and augmented reality applications to link virtual to real worlds.

Autonomous Vehicles Pose Estimation +1

One Thousand and One Hours: Self-driving Motion Prediction Dataset

lyft/l5kit 25 Jun 2020

Motivated by the impact of large-scale datasets on ML systems we present the largest self-driving dataset for motion prediction to date, containing over 1, 000 hours of data.

Autonomous Vehicles Motion Forecasting +2

Argoverse: 3D Tracking and Forecasting with Rich Maps

argoai/argoverse-api CVPR 2019

In our baseline experiments, we illustrate how detailed map information such as lane direction, driveable area, and ground height improves the accuracy of 3D object tracking and motion forecasting.

3D Object Tracking Autonomous Vehicles +3