SOTAVerified

Autonomous Driving

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)

Papers

Showing 13511400 of 6092 papers

TitleStatusHype
DeFIX: Detecting and Fixing Failure Scenarios with Reinforcement Learning in Imitation Learning Based Autonomous DrivingCode1
A Divide-and-Merge Point Cloud Clustering Algorithm for LiDAR Panoptic SegmentationCode1
SFD2: Semantic-guided Feature Detection and DescriptionCode1
How Well Does GPT-4V(ision) Adapt to Distribution Shifts? A Preliminary InvestigationCode1
Delta Descriptors: Change-Based Place Representation for Robust Visual LocalizationCode1
PG-Attack: A Precision-Guided Adversarial Attack Framework Against Vision Foundation Models for Autonomous DrivingCode1
PIDLoc: Cross-View Pose Optimization Network Inspired by PID ControllersCode1
Perception Datasets for Anomaly Detection in Autonomous Driving: A SurveyCode1
EPMF: Efficient Perception-aware Multi-sensor Fusion for 3D Semantic SegmentationCode1
Human Performance Capture from Monocular Video in the WildCode1
HVDetFusion: A Simple and Robust Camera-Radar Fusion FrameworkCode1
DeepSeqSLAM: A Trainable CNN+RNN for Joint Global Description and Sequence-based Place RecognitionCode1
Agent-X: Evaluating Deep Multimodal Reasoning in Vision-Centric Agentic TasksCode1
Hydra-NeXt: Robust Closed-Loop Driving with Open-Loop TrainingCode1
Sim-to-Real via Sim-to-Seg: End-to-end Off-road Autonomous Driving Without Real DataCode1
Pedestrian Stop and Go Forecasting with Hybrid Feature FusionCode1
Chirp Delay-Doppler Domain Modulation: A New Paradigm of Integrated Sensing and Communication for Autonomous VehiclesCode1
PC-NeRF: Parent-Child Neural Radiance Fields under Partial Sensor Data Loss in Autonomous Driving EnvironmentsCode1
DeepReach: A Deep Learning Approach to High-Dimensional ReachabilityCode1
PPAD: Iterative Interactions of Prediction and Planning for End-to-end Autonomous DrivingCode1
IFTR: An Instance-Level Fusion Transformer for Visual Collaborative PerceptionCode1
IGDrivSim: A Benchmark for the Imitation Gap in Autonomous DrivingCode1
Skeleton-Graph: Long-Term 3D Motion Prediction From 2D Observations Using Deep Spatio-Temporal Graph CNNsCode1
Deep Federated Learning for Autonomous DrivingCode1
PCB-RandNet: Rethinking Random Sampling for LIDAR Semantic Segmentation in Autonomous Driving SceneCode1
Pedestrian 3D Bounding Box PredictionCode1
Improved Deep Point Cloud Geometry CompressionCode1
IMGCN: Interpretable Masked Graph Convolution Network for Pedestrian Trajectory PredictionCode1
A Comprehensive Review of 3D Object Detection in Autonomous Driving: Technological Advances and Future DirectionsCode1
Persistent Map Saving for Visual Localization for Autonomous Vehicles: An ORB-SLAM ExtensionCode1
Deep learning for radar data exploitation of autonomous vehicleCode1
Implicit Guidance and Explicit Representation of Semantic Information in Points Cloud: A SurveyCode1
DeepIPC: Deeply Integrated Perception and Control for an Autonomous Vehicle in Real EnvironmentsCode1
Investigating the Impact of Multi-LiDAR Placement on Object Detection for Autonomous DrivingCode1
Deep Learning for Vision-based Prediction: A SurveyCode1
Aquatic Navigation: A Challenging Benchmark for Deep Reinforcement LearningCode1
Improving the Generalization of End-to-End Driving through Procedural GenerationCode1
Injecting Planning-Awareness into Prediction and Detection EvaluationCode1
Characterizing Driving Styles with Deep LearningCode1
Deep Metric Learning for Open World Semantic SegmentationCode1
Instance Segmentation by Jointly Optimizing Spatial Embeddings and Clustering BandwidthCode1
Instruct Large Language Models to Drive like HumansCode1
Integrated Decision and Control: Towards Interpretable and Computationally Efficient Driving IntelligenceCode1
Intelligent Resource Allocation in Joint Radar-Communication With Graph Neural NetworksCode1
Interpretable End-to-end Urban Autonomous Driving with Latent Deep Reinforcement LearningCode1
InteractionNet: Joint Planning and Prediction for Autonomous Driving with TransformersCode1
GANet: Goal Area Network for Motion ForecastingCode1
Deep Learning for Omnidirectional Vision: A Survey and New PerspectivesCode1
Deep Learning for 3D Point Clouds: A SurveyCode1
Depth-based 6DoF Object Pose Estimation using Swin TransformerCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ReasonNetDriving Score79.95Unverified
2InterFuserDriving Score76.18Unverified
3TCPDriving Score75.14Unverified
4TF++ WPDriving Score66.32Unverified
5Learning From All Vehicles (LAV)Driving Score61.85Unverified
6TransFuserDriving Score61.18Unverified
7TransFuser (Reproduced)Driving Score55.04Unverified
8TCP (Reproduced)Driving Score47.91Unverified
9Latent TransFuserDriving Score45.2Unverified
10GRIADDriving Score36.79Unverified
#ModelMetricClaimedVerifiedStatus
1Geometric FusionRC69.17Unverified
2TransFuserRC56.36Unverified
#ModelMetricClaimedVerifiedStatus
1Geometric FusionRC86.91Unverified
2TransFuserRC78.41Unverified