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 4676–4700 of 6092 papers

TitleStatusHype
Graph-Based Spatial-Temporal Convolutional Network for Vehicle Trajectory Prediction in Autonomous Driving—0
Up-to-Down Network: Fusing Multi-Scale Context for 3D Semantic Scene Completion—0
Learning Interpretable BEV Based VIO without Deep Neural Networks—0
Automatic Map Update Using Dashcam Videos—0
PredictionNet: Real-Time Joint Probabilistic Traffic Prediction for Planning, Control, and Simulation—0
Towards Generalized and Incremental Few-Shot Object Detection—0
Benchmarking Lane-changing Decision-making for Deep Reinforcement Learning—0
Survey on Semantic Stereo Matching / Semantic Depth Estimation—0
A Distance-based Anomaly Detection Framework for Deep Reinforcement Learning—0
Anomaly Detection in Radar Data Using PointNets—0
Stochastic MPC with Multi-modal Predictions for Traffic Intersections—0
ACReL: Adversarial Conditional value-at-risk Reinforcement Learning—0
Generalized dynamic cognitive hierarchy models for strategic driving behavior—0
Carl-Lead: Lidar-based End-to-End Autonomous Driving with Contrastive Deep Reinforcement Learning—0
METEOR:A Dense, Heterogeneous, and Unstructured Traffic Dataset With Rare Behaviors—0
Targeted Attack on Deep RL-based Autonomous Driving with Learned Visual PatternsCode0
Real Time Monocular Vehicle Velocity Estimation using Synthetic Data—0
Risk Measurement, Risk Entropy, and Autonomous Driving Risk Modeling—0
Neural Architecture Search in operational context: a remote sensing case-study—0
Federated Ensemble Model-based Reinforcement Learning in Edge Computing—0
Residual 3D Scene Flow Learning with Context-Aware Feature Extraction—0
Smart Automotive Technology Adherence to the Law: (De)Constructing Road Rules for Autonomous System Development, Verification and Safety—0
Spectrum Learning-Aided Reconfigurable Intelligent Surfaces for 'Green' 6G Networks—0
Semantic Segmentation on VSPW Dataset through Aggregation of Transformer Models—0
An Efficient Deep Learning Approach Using Improved Generative Adversarial Networks for Incomplete Information Completion of Self-driving—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