Autonomous Driving

1370 papers with code • 4 benchmarks • 66 datasets

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)

Libraries

Use these libraries to find Autonomous Driving models and implementations

Most implemented papers

Scalability in Perception for Autonomous Driving: Waymo Open Dataset

open-mmlab/mmdetection3d CVPR 2020

In an effort to help align the research community's contributions with real-world self-driving problems, we introduce a new large scale, high quality, diverse dataset.

Exploring Data Augmentation for Multi-Modality 3D Object Detection

open-mmlab/mmdetection3d 23 Dec 2020

Due to the fact that multi-modality data augmentation must maintain consistency between point cloud and images, recent methods in this field typically use relatively insufficient data augmentation.

FCOS3D: Fully Convolutional One-Stage Monocular 3D Object Detection

open-mmlab/mmdetection3d 22 Apr 2021

In this paper, we study this problem with a practice built on a fully convolutional single-stage detector and propose a general framework FCOS3D.

Learning to Drive in a Day

araffin/learning-to-drive-in-5-minutes 1 Jul 2018

We demonstrate the first application of deep reinforcement learning to autonomous driving.

Virtual to Real Reinforcement Learning for Autonomous Driving

rahul263-stack/Self-Driving-Car 13 Apr 2017

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

SqueezeSeg: Convolutional Neural Nets with Recurrent CRF for Real-Time Road-Object Segmentation from 3D LiDAR Point Cloud

BichenWuUCB/SqueezeSeg 19 Oct 2017

In this paper, we address semantic segmentation of road-objects from 3D LiDAR point clouds.

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

lexfridman/deeptraffic 9 Jan 2018

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.

ShelfNet for Fast Semantic Segmentation

juntang-zhuang/ShelfNet 27 Nov 2018

Compared with real-time segmentation models such as BiSeNet, our model achieves higher accuracy at comparable speed on the Cityscapes Dataset, enabling the application in speed-demanding tasks such as street-scene understanding for autonomous driving.

AFDet: Anchor Free One Stage 3D Object Detection

CarkusL/CenterPoint 23 Jun 2020

High-efficiency point cloud 3D object detection operated on embedded systems is important for many robotics applications including autonomous driving.

ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks without Training Substitute Models

huanzhang12/ZOO-Attack 14 Aug 2017

However, different from leveraging attack transferability from substitute models, we propose zeroth order optimization (ZOO) based attacks to directly estimate the gradients of the targeted DNN for generating adversarial examples.