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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 4376–4400 of 6092 papers

TitleStatusHype
Prioritized Experience-based Reinforcement Learning with Human Guidance for Autonomous DrivingCode1
Learning Interpretable BEV Based VIO without Deep Neural Networks—0
Automatic Map Update Using Dashcam Videos—0
Keypoints-Based Deep Feature Fusion for Cooperative Vehicle Detection of Autonomous DrivingCode1
PredictionNet: Real-Time Joint Probabilistic Traffic Prediction for Planning, Control, and Simulation—0
Semantic Segmentation-assisted Scene Completion for LiDAR Point CloudsCode1
Towards Generalized and Incremental Few-Shot Object Detection—0
Benchmarking Lane-changing Decision-making for Deep Reinforcement Learning—0
A Reinforcement Learning Benchmark for Autonomous Driving in Intersection ScenariosCode1
Survey on Semantic Stereo Matching / Semantic Depth Estimation—0
A Distance-based Anomaly Detection Framework for Deep Reinforcement Learning—0
Skeleton-Graph: Long-Term 3D Motion Prediction From 2D Observations Using Deep Spatio-Temporal Graph CNNsCode1
Generalized dynamic cognitive hierarchy models for strategic driving behavior—0
ACReL: Adversarial Conditional value-at-risk Reinforcement Learning—0
Stochastic MPC with Multi-modal Predictions for Traffic Intersections—0
Anomaly Detection in Radar Data Using PointNets—0
Carl-Lead: Lidar-based End-to-End Autonomous Driving with Contrastive Deep Reinforcement Learning—0
SPIN Road Mapper: Extracting Roads from Aerial Images via Spatial and Interaction Space Graph Reasoning for Autonomous DrivingCode1
A Divide-and-Merge Point Cloud Clustering Algorithm for LiDAR Panoptic SegmentationCode1
Real Time Monocular Vehicle Velocity Estimation using Synthetic Data—0
Targeted Attack on Deep RL-based Autonomous Driving with Learned Visual PatternsCode0
Efficient and Effective Generation of Test Cases for Pedestrian Detection -- Search-based Software Testing of Baidu Apollo in SVLCode1
METEOR:A Dense, Heterogeneous, and Unstructured Traffic Dataset With Rare Behaviors—0
Neural Architecture Search in operational context: a remote sensing case-study—0
Risk Measurement, Risk Entropy, and Autonomous Driving Risk Modeling—0
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Benchmark Results

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