Autonomous Driving

291 papers with code · 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.

Greatest papers with code

Baidu Apollo EM Motion Planner

20 Jul 2018ApolloAuto/apollo

In this manuscript, we introduce a real-time motion planning system based on the Baidu Apollo (open source) autonomous driving platform.

AUTONOMOUS DRIVING MOTION PLANNING TEST RESULTS

Online Temporal Calibration for Monocular Visual-Inertial Systems

2 Aug 2018HKUST-Aerial-Robotics/VINS-Mono

Visual and inertial fusion is a popular technology for 6-DOF state estimation in recent years.

AUTONOMOUS DRIVING ROBOT NAVIGATION SENSOR FUSION TIME OFFSET CALIBRATION

DeepTraffic: Crowdsourced Hyperparameter Tuning of Deep Reinforcement Learning Systems for Multi-Agent Dense Traffic Navigation

9 Jan 2018lexfridman/deeptraffic

We present a traffic simulation named DeepTraffic where the planning systems for a subset of the vehicles are handled by a neural network as part of a model-free, off-policy reinforcement learning process.

AUTONOMOUS DRIVING AUTONOMOUS NAVIGATION Q-LEARNING

Cityscapes 3D: Dataset and Benchmark for 9 DoF Vehicle Detection

14 Jun 2020mcordts/cityscapesScripts

In addition, we complement the Cityscapes benchmark suite with 3D vehicle detection based on the new annotations as well as metrics presented in this work.

AUTONOMOUS DRIVING

Scalable End-to-End Autonomous Vehicle Testing via Rare-event Simulation

NeurIPS 2018 SullyChen/Autopilot-TensorFlow

While recent developments in autonomous vehicle (AV) technology highlight substantial progress, we lack tools for rigorous and scalable testing.

AUTONOMOUS DRIVING

Virtual to Real Reinforcement Learning for Autonomous Driving

13 Apr 2017SullyChen/Autopilot-TensorFlow

To our knowledge, this is the first successful case of driving policy trained by reinforcement learning that can adapt to real world driving data.

AUTONOMOUS DRIVING DOMAIN ADAPTATION SYNTHETIC-TO-REAL TRANSLATION TRANSFER LEARNING

nuScenes: A multimodal dataset for autonomous driving

CVPR 2020 traveller59/second.pytorch

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

Ranked #3 on 3D Object Detection on nuScenes (using extra training data)

3D OBJECT DETECTION AUTONOMOUS DRIVING

3D Multi-Object Tracking: A Baseline and New Evaluation Metrics

9 Jul 2019xinshuoweng/AB3DMOT

Additionally, 3D MOT datasets such as KITTI evaluate MOT methods in the 2D space and standardized 3D MOT evaluation tools are missing for a fair comparison of 3D MOT methods.

3D MULTI-OBJECT TRACKING AUTONOMOUS DRIVING