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 5076–5100 of 6092 papers

TitleStatusHype
FLAVA: Find, Localize, Adjust and Verify to Annotate LiDAR-Based Point CloudsCode0
Res-GCNN: A Lightweight Residual Graph Convolutional Neural Networks for Human Trajectory Forecasting—0
Taming and Leveraging Interference in Mobile Radar Networks—0
Multi-view Sensor Fusion by Integrating Model-based Estimation and Graph Learning for Collaborative Object Localization—0
FRDet: Balanced and Lightweight Object Detector based on Fire-Residual Modules for Embedded Processor of Autonomous Driving—0
Online Monitoring of Object Detection Performance During Deployment—0
Secure Vehicle Communications Using Proof-of-Nonce Blockchain—0
DARE: AI-based Diver Action Recognition System using Multi-Channel CNNs for AUV Supervision—0
BirdSLAM: Monocular Multibody SLAM in Bird's-Eye View—0
Shared Cross-Modal Trajectory Prediction for Autonomous Driving—0
Trajectory Prediction in Autonomous Driving with a Lane Heading Auxiliary Loss—0
Where to drive: free space detection with one fisheye camera—0
Behaviorally Diverse Traffic Simulation via Reinforcement Learning—0
A Learning-Based Tune-Free Control Framework for Large Scale Autonomous Driving System Deployment—0
Reinforcement Learning for Autonomous Driving with Latent State Inference and Spatial-Temporal Relationships—0
Bait and Switch: Online Training Data Poisoning of Autonomous Driving Systems—0
Deep traffic light detection by overlaying synthetic context on arbitrary natural imagesCode0
Ellipse Loss for Scene-Compliant Motion Prediction—0
S3-Net: A Fast and Lightweight Video Scene Understanding Network by Single-shot Segmentation—0
A Scenario-Based Development Framework for Autonomous Driving—0
Towards Map-Based Validation of Semantic Segmentation Masks—0
Out-of-Distribution Detection for Automotive Perception—0
Highway Driving Dataset for Semantic Video Segmentation—0
PILOT: Efficient Planning by Imitation Learning and Optimisation for Safe Autonomous Driving—0
HM4: Hidden Markov Model with Memory Management for Visual Place Recognition—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