/autonomous-driving-research

ML Papers

This repo contains notes and short summaries of some ML related papers I come across, organized by subjects and the summaries are in the form of PDFs.

AD

Adversarial policies Attacking deep reinforcement learning

Adversarial reinforcement learning framework for benchmarking collision avoidance mechanisms in autonomous vehicles

A survey of deep network solutions for learning control in robotics From reinforcement to imitation

Cirl Controllable imitative reinforcement learning for vision based self driving

Exploring applications of deep reinforcement learning for real world autonomous driving systems

Flow Deep Reinforcement Learning for Control in SUMO

High speed autonomous drifting with deep reinforcement learning

Meta World A Benchmark and Evaluation for

Model free Deep Reinforcement Learning for Urban

Safety verification of cyber physical systems with reinforcement learning control

Simulation based reinforcement learning for real world autonomous driving

Lane

3D-laneNet End-to-end 3D multiple lane detection

Accurate and Robust Lane Detection based on Dual-View Convolutional

Aerial laneNet Lane-marking semantic segmentation in aerial imagery using wavelet-enhanced cost-sensitive symmetric fully convolutional neural networks

CurveLane NAS Unifying Lane-Sensitive Architecture Search and Adaptive Point Blending

Deep multi-sensor lane detection

Drivable road detection based on dilated FPN with feature aggregation

Efficient deep models for monocular road segmentation

FastDraw Addressing the long tail of lane detection by adapting a sequential prediction network

FusionLane Multi-Sensor Fusion for Lane Marking Semantic Segmentation Using Deep Neural Networks

Gen-LaneNet A Generalized and Scalable Approach for 3D Lane Detection

Heatmap based Vanishing Point boosts Lane Detection

Inter Region Affinity Distillation for Road Marking Segmentation

Lane detection and classification using cascaded CNNs

Lane Detection A Survey with New Results

Lane Detection For Prototype Autonomous Vehicle

Lane Detection Model Based on Spatio Temporal Network with Double ConvGRUs

Learning lightweight lane detection CNNs by self attention distillation

Multi-lane detection using instance segmentation and attentive voting

MultiNet Real time Joint Semantic Reasoning for Autonomous Driving

PolyLaneNet Lane Estimation via Deep Polynomial Regression

RBNet A Deep Neural Network for Unified Road and Road Boundary Detection

Road segmentation using CNN and distributed LSTM

Spatial as deep Spatial CNN for traffic scene understanding

SpinNet Spinning convolutional network for lane boundary detection

Structure-Aware Network for Lane Marker Extraction with Dynamic Vision Sensor

Synthetic to Real Domain Adaptation for Lane Detection

Towards end-to-end lane detection An instance segmentation approach

Ultra Fast Structure aware Deep Lane Detection

VPGNet Vanishing point guided network for lane and road marking detection and recognition

Object

A Survey of Deep Learning-Based Object Detection

A Survey of Deep Learning Based Object Detection

A Survey on 3D Object Detection Methods for Autonomous Driving Applications

Complex-YOLO Real-time 3D Object Detection on Point Clouds

Deep Multi-Modal Object Detection and Semantic Segmentation for Autonomous Driving Datasets, Methods, and Challenges

Deep Multi Modal Object Detection and Semantic Segmentation for Autonomous Driving Datasets, Methods, and Challenges

Lane Detection A Survey with New Results

PointPillars Fast Encoders for Object Detection from Point Clouds

SimpleDet A Simple and Versatile Distributed Framework for Object Detection and Instance Recognition

SqueezeDet Unified, Small, Low Power Fully Convolutional Neural Networks for Real-Time Object Detection for Autonomous Driving

Stereo R-CNN based 3D Object Detection for Autonomous Driving

Vision-Based Traffic Sign Detection and Recognition Systems Current Trends and Challenges

VoxelNet End-to-End Learning for Point Cloud Based 3D Object Detection

YOLO3D

RL

Deep Reinforcement Learning for Autonomous Driving A Survey

Reinforcement Learning for Accident Risk Adaptive V2X Networking

TrafficSign

Vision Based Traffic Sign Detection and Recognition Systems Current Trends and Challenges

V2X

Artificial intelligence for vehicle to everything A survey

A Deep Reinforcement Learning Framework to Combat Dynamic Blockage in mmWave V2X Networks

Deep neural network based resource allocation for V2X communications

Deep reinforcement learning based distributed vehicle position controls for coverage expansion in mmWave V2X

Deep Reinforcement Learning Based Mode Selection and Resource Allocation for Cellular V2X Communications

Driving policies of V2X autonomous vehicles based on reinforcement learning methods

Edge Based V2X Communications With Big Data Intelligence

huawei cv2x whitepaper for cooperative its cn

Intelligent network slicing for v2x services toward 5g

Joint Optimization of Spectrum and Energy Efficiency Considering the C V2X Security A Deep Reinforcement Learning Approach

Optimizing Traffic Lights with Multi agent Deep Reinforcement Learning and V2X communication

Traffic big data assisted V2X communications toward smart transportation

Vehicle Safety Improvement through Deep Learning and Mobile Sensing