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 3826–3850 of 6092 papers

TitleStatusHype
Fighting Fire with Fire: Avoiding DNN Shortcuts through Priming—0
Multi-level Domain Adaptation for Lane Detection—0
GNN-PMB: A Simple but Effective Online 3D Multi-Object Tracker without Bells and WhistlesCode1
A Safe Control Architecture Based on Robust Model Predictive Control for Autonomous Driving—0
Occupancy-MAE: Self-supervised Pre-training Large-scale LiDAR Point Clouds with Masked Occupancy AutoencodersCode2
MPA: MultiPath++ Based Architecture for Motion PredictionCode2
Benchmarking Constraint Inference in Inverse Reinforcement LearningCode1
Real-time Full-stack Traffic Scene Perception for Autonomous Driving with Roadside Cameras—0
Distortion-Aware Network Pruning and Feature Reuse for Real-time Video Segmentation—0
ORFD: A Dataset and Benchmark for Off-Road Freespace DetectionCode2
C-SENN: Contrastive Self-Explaining Neural Network—0
3D Object Detection for Autonomous Driving: A Comprehensive SurveyCode2
Opendenselane: A Dense Lidar-Based Dataset for HD Map ConstructionCode0
A Dynamic Data Driven Approach for Explainable Scene Understanding—0
VectorMapNet: End-to-end Vectorized HD Map LearningCode2
SafeRL-Kit: Evaluating Efficient Reinforcement Learning Methods for Safe Autonomous Driving—0
ECTLO: Effective Continuous-time Odometry Using Range Image for LiDAR with Small FoVCode1
Diverse Multiple Trajectory Prediction Using a Two-stage Prediction Network Trained with Lane Loss—0
SHIFT: A Synthetic Driving Dataset for Continuous Multi-Task Domain AdaptationCode1
K-Radar: 4D Radar Object Detection for Autonomous Driving in Various Weather ConditionsCode2
Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong BaselineCode1
CARLANE: A Lane Detection Benchmark for Unsupervised Domain Adaptation from Simulation to multiple Real-World DomainsCode1
Level 2 Autonomous Driving on a Single Device: Diving into the Devils of OpenpilotCode0
Mean-Semivariance Policy Optimization via Risk-Averse Reinforcement Learning—0
AI Ethics Issues in Real World: Evidence from AI Incident Database—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