Awesome-Autonomous-Driving
Author: 牛肉咖喱饭(PeterJaq)
Update:2024/07/10
This project will be periodically updated with quality projects and papers related to autonomous driving.
Update
- [2024/08/07] Update Arxiv 2024 07 Monthly ADAS Paper List!! Arxiv-202407
- [2024/07/10] Update Arxiv 2024 06 Monthly ADAS Paper List!! Arxiv-202406
- [2024/06/10] Update Arxiv 2024 05 Monthly ADAS Paper List!! Arxiv-202405
- [2024/05/13] Update ICRA 2024 Paper List ICRA2024 Autonomous Driving
- [2024/05/06] Update Arxiv 2024 04 Monthly ADAS Paper List!! Arxiv-202404
- [2024/04/20] Update Arxiv 2024 03 Monthly ADAS Paper List!! Arxiv-202403
- [2024/03/31] Update CVPR 2024 Paper List in CVPR2024 Autonoumous Driving
- [2024/03/23] Update HD Map Groudtruth and Oneline Paper List !!
- [2024/3/14] Update Arxiv 2024 02 Monthly ADAS Paper List!! Arxiv-202402
- [2024/2/11] Update Arxiv 2024 01 Monthly ADAS Paper List!! Arxiv-202401
- [2024/1/13] Add Other Awesome List.
- [2024/1/1] Update Arxiv 2023 12 Monthly ADAS Paper List!! Arxiv-202312
- [2023/12/3] Add Daily ADAS Arxiv Paper List!! in ADAS-Arxiv-Daily
- [2023/12/2] Update Arxiv 2023 11 Monthly ADAS Paper List!! Arxiv-202311
- [2023/11/20] Update NeurIPS 2023 ADAS Paper List!! NeurIPS2023
- [2023/09/27] Update ICCV 2023 ADAS Paper List!!
Contents
1. Autonomous Driving Midleware and Integrated Solutions
1.1 Midelware
中间件
-
ROS - A set of software libraries and tools that help you build robot applications.
-
ROS-2 - A set of software libraries and tools that help you build robot applications.
-
Cyber - High performance runtime framework designed specifically for autonomous driving (AD) scenarios from baidu.
1.2 Integrated Solutions
解决方案
-
Apollo - The intergrated solution from baidu.
-
Autoware.ai - Open-source software for self-driving vehicles known as Autoware-1.
-
Autoware.auto - Open-source software for self-driving vehicles known as Autoware-2.
-
AutowareArchitectureProposal.proj - Manages several projects related to self-driving vehicles.
-
self-driving-ish_computer_vision_system - This project generates images you've probably seen in autonomous driving demo.
-
Aslan - An open-source full-stack software based on ROS framework.
-
AutoC2X-AW - Extension for Autoware and OpenC2X.
2. Sensor and Calibration Tools
2.1 Sensor Hardware
传感器硬件
LiDAR
2.2 Calibration Tools
参数标定工具
3. Perception
3.1 Detection
检测与分割
3.1.1 Vision based
基于视觉
BackBone
- Next-ViT 来自字节面向工业界的新一代Transform模型部署。
- CoAtNet
- FocalsConv Focal Sparse Convolutional
- PoolFormer [CVPR2022] MetaFormer Is Actually What You Need for Vision. 证明Transformer模型的能力,而不是设计复杂的token mixer来实现SOTA性能
- ConvNext [CVPR2022] A ConvNet for the 2020s. 用设计transformer的思想构建卷积。
- Mobile-Former [CVPR2022] 微软提出Mobile-Former,MobileNet和Transformer的并行设计,可以实现局部和全局特征的双向融合,在分类和下游任务中,性能远超MobileNetV3等轻量级网络!
-
Up to 31 Revisiting Large Kernel Design in CNNs. 大Kernel =? SOTA 这篇文章给你答案!
Occupancy
- Occupancy Networks Learning 3D Reconstruction in Function Space.
- Pyramid Occupancy Network Predicting Semantic Map Representations from Images using Pyramid Occupancy Networks.
- MonoScene Monocular 3D Semantic Scene Completion.
- OccDepth A Depth-Aware Method for 3D Semantic Scene Completion.
- VoxFormer Sparse Voxel Transformer for Camera-based 3D Semantic Scene.
- TPVFormer Tri-Perspective View for Vision-Based 3D Semantic Occupancy Prediction.
- SurroundOcc Multi-Camera 3D Occupancy Prediction for Autonomous Driving.
-
A Comprehensive Review of Occupancy A summary of the current research trend and provide some probable future outlooks for occupancy.
数据增强
- TeachAugment [CVPR2022] Data Augmentation Optimization Using Teacher Knowledge
- AlignMixup [CVPR2022] Improving Representations By Interpolating Aligned Features
- rising 基于pytorch的GPU数据预处理transform模块,实测好用!
Lane Detection
3.1.2 Lidar based
基于激光雷达
Object Detection
- Voxelnet
- Complex-YOLO
- PointRCNN
- CenterPoint - 3D Object Detection and Tracking using center points in the bird-eye view.
- PartA2-Net - From Points to Parts: 3D Object Detection from Point Cloud with Part-aware and Part-aggregation Network.
- CIA-SSD - Confident IoU-Aware Single Stage Object Detector From Point Cloud.
- 3DIoUMatch-PVRCNN - 3DIoUMatch: Leveraging IoU Prediction for Semi-Supervised 3D Object Detection.
- SFA3D - Super Fast and Accurate 3D Object Detection based on 3D LiDAR Point Clouds.
- Auto4D - Auto4D: Learning to Label 4D Objects from Sequential Point Clouds.
- 3DAL - Offboard 3D Object Detection from Point Cloud Sequences
- LIFT [CVPR2022] LIFT: Learning 4D LiDAR Image Fusion Transformer for 3D Object Detection
- FSD [CVPR2022] Fully Sparse 3D Object Detection & SST: Single-stride Sparse Transformer 来自图森的 Sparse Transformer.
- VoxelNext [CVPR2023] VoxelNeXt: Fully Sparse VoxelNet for 3D Object Detection and Tracking
- PillarNext [CVPR2023] Rethinking Network Designs for 3D Object Detection in LiDAR Point Clouds
- LargeKernel3D [CVPR2023] LargeKernel3D: Scaling Up Kernels in 3D Sparse CNNs
- LinK [CVPR2023] Linear Kernel for LiDAR-Based 3D Perception
- Spherical Transformer [CVPR2023]spherical Transformer for LiDAR-Based 3D Recognition
- Unspervised 3D OD [CVPR2023]Towards Unsupervised Object Detection From LiDAR Point Clouds
- Benchmarking robustness of 3D OD [CVPR2023] Benchmarking Robustness of 3D Object Detection to Common Corruptions
- Bi3D [CVPR2023] Bi-Domain Active Learning for Cross-Domain 3D Object Detection
- Density-Insensitive [CVPR2023] Density-Insensitive Unsupervised Domain Adaption on 3D Object Detection
- UniDistill [CVPR2023] UniDistill: A Universal Cross-Modality Knowledge Distillation Framework for 3D Object Detection in Bird’s-Eye View
- MSF [CVPR2023] MSF: Motion-Guided Sequential Fusion for Efficient 3D Object Detection From Point Cloud Sequences
- OcTr [CVPR2023] OcTr: Octree-Based Transformer for 3D Object Detection
- SlowLiDAR [CVPR2023] Increasing the Latency of LiDAR-Based Detection Using Adversarial Examples
- Uni3D [CVPR2023] Uni3D: A Unified Baseline for Multi-Dataset 3D Object Detection
- DetZero [ICCV2023] Rethinking Offboard 3D Object Detection with Long-term Sequential Point Clouds
- FocalFormer3D [ICCV2023] Focusing on Hard Instance for 3D Object Detection
- GPA-3D [ICCV2023] Geometry-aware Prototype Alignment for Unsupervised Domain Adaptive 3D Object Detection from Point Clouds
- KECOR [ICCV2023] KECOR: Kernel Coding Rate Maximization for Active 3D Object Detection
- Once Detected, Never Lost [ICCV2023] Once Detected, Never Lost: Surpassing Human Performance in Offline LiDAR based 3D Object Detection
- PARTNER [ICCV2023] PARTNER: Level up the Polar Representation for LiDAR 3D Object Detection
- PG-RCNN [ICCV2023] PG-RCNN: Semantic Surface Point Generation for 3D Object Detection
-
Domain-Adaptive [ICCV2023]Revisiting Domain-Adaptive 3D Object Detection by Reliable, Diverse and Class-balanced Pseudo-Labeling
Lidar Ground Segmentation
- patchwork Patchwork 主要由三部分组成:基于同心带模型(CZM)的极坐标网格表示、区域地平面拟合(R-GPF)和地面似然估计(GLE) IROS2021
- patchwork++ 与Patchwork不同,Patchwork++由称为反射噪声去除(RNR)、区域垂直平面拟合(R-VPF)、自适应GLE(A-GLE)和空间地面恢复(TGR)的新模块组成。Patchwork++具有更高的精确度和召回率。此外,新的Patchwork++具有较低的召回标准差。
-
TRAVEL 他使用三维点云的图形表示,同时进行可穿越的地面检测和物体聚类, 为了分割可穿越的地面,点云被编码为一个图结构,即三网格场,它将每个三网格视为一个节点。IROS 2022
Lidar Segmentation
- RangeView [ICCV2023] Rethinking Range View Representation for LiDAR Segmentation
3.1.2 Multi Sensor Fusion
3D Object Detection
- PERF PETR encodes the position information of 3D coordinates into image features, producing the 3D position-aware features.
- PERFv2 Based on PETR, PETRv2 explores the effectiveness of temporal modeling, which utilizes the temporal information of previous frames to boost 3D object detection.
- BEVFusion BEVFusion is fundamentally task-agnostic and seamlessly supports different 3D perception tasks with almost no architectural changes.
- BEVDepth BEVDepth resolves this by leveraging explicit depth supervision.
- BEVFormer BEVFormer learns unified BEV representations with spatiotemporal transformers to support multiple autonomous driving perception tasks.
- ST-P3 End-to-end Vision-based Autonomous Driving via Spatial-Temporal Feature Learning
- SpatialDETR Robust Scalable Transformer-Based 3D Object Detection from Multi-View Camera Images with Global Cross-Sensor Attention
- BEVDet High-Performance Multi-Camera 3D Object Detection in Bird-Eye-View.
- BEVDet4D Exploit Temporal Cues in Multi-camera 3D Object Detection.
- M2BEV Multi-Camera Joint 3D Detection and Segmentation with Unified Birds-Eye View Representation.
- BEVerse Unified Perception and Prediction in Birds-Eye-View for Vision-Centric Autonomous Driving.
- PolarDETR Polar Parametrization for Vision-based Surround-View 3D Detection.
- PolarFormer Multi-camera 3D Object Detection with Polar Transformers.
- CrossDTR Cross-view and Depth-guided Transformers for 3D Object Detection.
- Sim-BEV A Simple Baseline for BEV Perception Without LiDAR.
- AeDet AeDet: Azimuth-invariant Multi-view 3D Object Detection.
- DFKF [CVPR2023]Distilling Focal Knowledge From Imperfect Expert for 3D Object Detection
- Understand BEV[CVPR2023] Understanding the Robustness of 3D Object Detection With Bird’s-Eye-View Representations in Autonomous Driving
- Focal Knowledge Form [CVPR2023] Distilling Focal Knowledge From Imperfect Expert for 3D Object Detection
- BEVHeight [CVPR2023] BEVHeight: A Robust Framework for Vision-Based Roadside 3D Object Detection
- BEV-SAN [CVPR2023] BEV-SAN: Accurate BEV 3D Object Detection via Slice Attention Networks
- Collaboration Overtake LiDAR [CVPR2023] Collaboration Helps Camera Overtake LiDAR in 3D Detection
- MSMDFusion [CVPR2023] MSMDFusion: Fusing LiDAR and Camera at Multiple Scales With Multi-Depth Seeds for 3D Object Detection
- BEV-Guided [CVPR2023] BEV-Guided Multi-Modality Fusion for Driving Perception
- BEV-DC [CVPR2023] BEV@DC: Bird’s-Eye View Assisted Training for Depth Completion
- Ada3D [ICCV2023] Ada3D : Exploiting the Spatial Redundancy with Adaptive Inference for Efficient 3D Object Detection
- Cross Modal Transformer [ICCV2023] Cross Modal Transformer: Towards Fast and Robust 3D Object Detection
- Object-Centric Temporal Modeling [ICCV2023] Exploring Object-Centric Temporal Modeling for Efficient Multi-View 3D Object Detection
- QD-BEV [ICCV2023] Quantization-aware View-guided Distillation for Multi-view 3D Object Detection
- MetaBEV [ICCV2023] Solving Sensor Failures for BEV Detection and Map Segmentation
- Perceiver [ICCV2023] Monocular 3D Object Detection with Bounding Box Denoising in 3D by Perceiver
- MonoNeRD [ICCV2023] NeRF-like Representations for Monocular 3D Object Detection
- Object as Query [ICCV2023] Object as Query: Lifting any 2D Object Detector to 3D Detection
- Predict to Detect [ICCV2023] Predict to Detect: Prediction-guided 3D Object Detection using Sequential Images
- Pepresentation Disparity-aware [ICCV2023] Representation Disparity-aware Distillation for 3D Object Detection
- SA-BEV [ICCV2023] SA-BEV: Generating Semantic-Aware Bird's-Eye-View Feature for Multi-view 3D Object Detection
- SparseBEV [ICCV2023] SparseBEV: High-Performance Sparse 3D Object Detection from Multi-Camera Videos
- SparseFusion [ICCV2023] SparseFusion: Fusing Multi-Modal Sparse Representations for Multi-Sensor 3D Object Detection
- SupFusion [ICCV2023] SupFusion: Supervised LiDAR-Camera Fusion for 3D Object Detection
- 3DPPE [ICCV2023] 3DPPE: 3D Point Positional Encoding for Multi-Camera 3D Object Detection Transformers
- MonoDETR [ICCV2023] MonoDETR: Depth-guided Transformer for Monocular 3D Object Detection
- PETRv2 [ICCV2023] PETRv2: A Unified Framework for 3D Perception from Multi-Camera Images
- UpCycling [ICCV2023] UpCycling: Semi-supervised 3D Object Detection without Sharing Raw-level Unlabeled Scenes
- [ICCV2023] Not Every Side Is Equal: Localization Uncertainty Estimation for Semi-Supervised 3D Object Detection
Lane Detection
3.2 Tracking
追踪算法
3.3 Map & Topo
- Survey Data Issues in High-Definition Maps Furniture – A Survey
- MapNeXt MapNeXt: Revisiting Training and Scaling Practices for Online Vectorized HD Map Construction
- PolyRoad PolyRoad: Polyline Transformer for Topological Road-Boundary Detection
- Survey High-Definition Maps Construction Based on Visual Sensor: A Comprehensive Survey
- VMA VMA: Divide-and-Conquer Vectorized Map Annotation System for Large-Scale Driving Scene
- Lane Graph as Path Lane Graph as Path: Continuity-preserving Path-wise Modeling for Online Lane Graph Construction
- PivotNet PivotNet: Vectorized Pivot Learning for End-to-end HD Map Construction
- E2E Map End-to-End Vectorized HD-map Construction with Piecewise Bezier Curve
- LATR LATR: 3D Lane Detection from Monocular Images with Transformer
- TopoReas Graph-based Topology Reasoning for Driving Scenes
- TopoMLP TopoMLP: A Simple yet Strong Pipeline for Driving Topology Reasoning
- Neural Map Prior Neural Map Prior for Autonomous Driving
- Construction using Geometry Online Vectorized HD Map Construction using Geometry
- MapTRv2 MapTRv2: An End-to-End Framework for Online Vectorized HD Map Construction
- InstaGraM InstaGraM: Instance-level Graph Modeling for Vectorized HD Map Learning
- PolyMerge PolyMerge: A Novel Technique aimed at Dynamic HD Map Updates Leveraging Polylines
- MapSeg MapSeg: Segmentation guided structured model for online HD map construction
- Efficient Efficient and Hybrid Decoder for Local Map Construction in Bird'-Eye-View
- Mind the map! Mind the map! Accounting for existing map information when estimating online HDMaps from sensor data
- ScalableMap ScalableMap: Scalable Map Learning for Online Long-Range Vectorized HD Map Construction
- TopoNet TopoNet: Topology Learning for 3D Reconstruction of Objects of Arbitrary Genus
- SuperFusion SuperFusion: Multilevel LiDAR-Camera Fusion for Long-Range HD Map Generation
- MapTR MapTR: Structured Modeling and Learning for Online Vectorized HD Map Construction
- VectorMapNet VectorMapNet: End-to-end Vectorized HD Map Learning
- csBoundary csBoundary: City-Scale Road-Boundary Detection in Aerial Images for High-Definition Maps
- Topo-boundary Topo-boundary: A Benchmark Dataset on Topological Road-boundary Detection Using Aerial Images for Autonomous Driving
- HDMapNet HDMapNet: An Online HD Map Construction and Evaluation Framework
3.4 High Performance Inference
高性能推理
视觉系列
- Lite.ai -
该项目提供了一系列轻量级的目标检测语义分割任务的整合框架支持 YOLOX🔥, YoloR🔥, YoloV5, YoloV4, DeepLabV3, ArcFace, CosFace, RetinaFace, SSD, etc.
- multi-attention -> onnx -
提供了一个多头注意力机制支持onnx部署的方式
- TRT ViT 字节跳动提出的面向工业界部署的ViT
LiDAR Pillars系列
4. Prediction
- [An Auto-tuning Framework for Autonomous Vehicles] (https://arxiv.org/pdf/1808.04913.pdf)
- VectorNet -
来自VectorNet: Encoding HD Maps and Agent Dynamics from Vectorized Representation利用高精地图 -与目标物信息进对目标进行行为预测。apollo在7.0版本的行为预测部分的encoder利用了这个vectornet.
- TNT - TNT是一种基于历史数据(即多代理和环境之间交互)生成目标的轨迹状态序列方法,并基于似然估计得到紧凑的轨迹预测集。
- DESIRE - DESIRE: Distant Future Prediction in Dynamic Scenes with Interacting Agents
- TNT: Target-driveN Trajectory Prediction apollo在7.0版本的行为预测模块inter-TNT的轨迹生成利用了TNT的方法.
- MultiPath++ - Efficient Information Fusion and Trajectory Aggregation for Behavior Prediction.
- MotionCNN - A Strong Baseline for Motion Prediction in Autonomous Driving.
- WAT - Weakly-supervised Action Transition Learning for Stochastic Human Motion Prediction.
- BEVerse - Unified Perception and Prediction in Birds-Eye-View for Vision-Centric Autonomous Driving.
- ParkPredict+ - Vehicle simualtion and behavior prediction in parking lots.
- HiVT - Hierarchical Vector Transformer for Multi-Agent Motion Prediction
- FEND A Future Enhanced Distribution-Aware Contrastive Learning Framework for Long-Tail Trajectory Prediction
- EqMotion Equivariant Multi-Agent Motion Prediction With Invariant Interaction Reasoning
- EigenTrajectory [ICCV2023] EigenTrajectory: Low-Rank Descriptors for Multi-Modal Trajectory Forecasting
- Temporal Enhanced [ICCV2023] Temporal Enhanced Training of Multi-view 3D Object Detector via Historical Object Prediction
- TrajectoryFormer [ICCV2023] TrajectoryFormer: 3D Object Tracking Transformer with Predictive Trajectory Hypotheses
5 Localization and SLAM
Localization
6. Planning
规划
- 自动驾驶中的决策规划算法概述
- 有限状态机
- MPC
- PathPlanning
- pacmod - Designed to allow the user to control a vehicle with the PACMod drive-by-wire system.
- rrt - C++ RRT (Rapidly-exploring Random Tree) implementation.
- HypridAStarTrailer - A path planning algorithm based on Hybrid A* for trailer truck.
- path_planner - Hybrid A* Path Planner for the KTH Research Concept Vehicle.
- fastrack - A ROS implementation of Fast and Safe Tracking (FaSTrack).
- commonroad - Composable benchmarks for motion planning on roads.
- traffic-editor - A graphical editor for robot traffic flows.
- steering_functions - Contains a C++ library that implements steering functions for car-like robots with limited turning radius.
- moveit - Easy-to-use robotics manipulation platform for developing applications, evaluating designs, and building integrated products.
- flexible-collision-library - A library for performing three types of proximity queries on a pair of geometric models composed of triangles.
- aikido - Artificial Intelligence for Kinematics, Dynamics, and Optimization.
- casADi - A symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs.
- ACADO Toolkit - A software environment and algorithm collection for automatic control and dynamic optimization.
- CrowdNav - Crowd-aware Robot Navigation with Attention-based Deep Reinforcement Learning.
- ompl - Consists of many state-of-the-art sampling-based motion planning algorithms.
- openrave - Open Robotics Automation Virtual Environment: An environment for testing, developing, and deploying robotics motion planning algorithms.
- teb_local_planner - An optimal trajectory planner considering distinctive topologies for mobile robots based on Timed-Elastic-Bands.
- pinocchio - A fast and flexible implementation of Rigid Body Dynamics algorithms and their analytical derivatives.
- rmf_core - The rmf_core packages provide the centralized functions of the Robotics Middleware Framework (RMF).
- global_racetrajectory_optimization - This repository contains multiple approaches for generating global racetrajectories.
- toppra - A library for computing the time-optimal path parametrization for robots subject to kinematic and dynamic constraints.
- tinyspline - TinySpline is a small, yet powerful library for interpolating, transforming, and querying arbitrary NURBS, B-Splines, and Bézier curves.
- dual quaternions ros - ROS python package for dual quaternion SLERP.
- mb planner - Aerial vehicle planner for tight spaces. Used in DARPA SubT Challenge.
- ilqr - Iterative Linear Quadratic Regulator with auto-differentiatiable dynamics models.
- EGO-Planner - A lightweight gradient-based local planner without ESDF construction, which significantly reduces computation time compared to some state-of-the-art methods.
- pykep - A scientific library providing basic tools for research in interplanetary trajectory design.
- am_traj - Alternating Minimization Based Trajectory Generation for Quadrotor Aggressive Flight.
- GraphBasedLocalTrajectoryPlanner - Was used on a real race vehicle during the Roborace Season Alpha and achieved speeds above 200km/h.
- Ruckig - Instantaneous Motion Generation. Real-time. Jerk-constrained. Time-optimal.
7. Control
控制
- PID
- Open Source Car Control - An assemblage of software and hardware designs that enable computer control of modern cars in order to facilitate the development of autonomous vehicle technology.
- control-toolbox - An efficient C++ library for control, estimation, optimization and motion planning in robotics.
- mpcc - Model Predictive Contouring Controller for Autonomous Racing.
- open_street_map - ROS packages for working with Open Street Map geographic information.
- autogenu-jupyter - This project provides the continuation/GMRES method (C/GMRES method) based solvers for nonlinear model predictive control (NMPC) and an automatic code generator for NMPC.
- OpEn - A solver for Fast & Accurate Embedded Optimization for next-generation Robotics and Autonomous Systems.
9. Dataset and Competition
数据集与竞赛
10. Data Loop & Model Loop
数据闭环
NAS
- Beta-DARTS Beta-Decay Regularization for Differentiable Architecture Search
- ISNAS-DIP Image-Specific Neural Architecture Search for Deep Image Prior
主动学习
Coner case & Long-tail
- RAC Retrieval Augmented Classification for Long-Tail Visual Recognition*
数据挖掘
- AirDet Few-Shot Detection without Fine-tuning for Autonomous Exploration. 这篇文章把他放在数据挖掘方面是思考有没有可能用极少样本不用fine-tuning 后可以从原有自动驾驶数据湖中挖掘出更多的样本。
Data Requirement
OOD
12. Simulation
- UniSim [CVPR2023] A Neural Closed-Loop Sensor Simulator
- LiDar-in-the-loop [CVPR2023] LiDAR-in-the-Loop Hyperparameter Optimization
- Compact Representation [CVPR2023] Learning Compact Representations for LiDAR Completion and Generation
- MixSim [CVPR2023] MixSim: A Hierarchical Framework for Mixed Reality Traffic Simulation
- The Differentiable Lens [CVPR2023] Compound Lens Search Over Glass Surfaces and Materials for Object Detection
13. Others
其他更好的分享