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 726–750 of 6092 papers

TitleStatusHype
3DLabelProp: Geometric-Driven Domain Generalization for LiDAR Semantic Segmentation in Autonomous DrivingCode1
Ranging Performance Analysis in Automotive DToF Lidars—0
Knowledge-Informed Multi-Agent Trajectory Prediction at Signalized Intersections for Infrastructure-to-Everything—0
Black-Box Adversarial Attack on Vision Language Models for Autonomous Driving—0
Text-driven Online Action DetectionCode0
GeomGS: LiDAR-Guided Geometry-Aware Gaussian Splatting for Robot Localization—0
GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian SplattingCode2
AdaWM: Adaptive World Model based Planning for Autonomous Driving—0
PPO-Based Vehicle Control for Ramp Merging Scheme Assisted by Enhanced C-V2XCode0
QuFeX: Quantum feature extraction module for hybrid quantum-classical deep neural networks—0
Survey on Monocular Metric Depth Estimation—0
Video Deblurring by Sharpness Prior Detection and Edge InformationCode0
RL-RC-DoT: A Block-level RL agent for Task-Aware Video Compression—0
RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented LearningCode0
Make Full Use of Testing Information: An Integrated Accelerated Testing and Evaluation Method for Autonomous Driving Systems—0
A Survey of World Models for Autonomous DrivingCode1
Car-GS: Addressing Reflective and Transparent Surface Challenges in 3D Car Reconstruction—0
Explainable artificial intelligence (XAI): from inherent explainability to large language models—0
MutualForce: Mutual-Aware Enhancement for 4D Radar-LiDAR 3D Object Detection—0
DSTIGCN: Deformable Spatial-Temporal Interaction Graph Convolution Network for Pedestrian Trajectory PredictionCode1
The Devil is in the Details: Simple Remedies for Image-to-LiDAR Representation Learning—0
RE-POSE: Synergizing Reinforcement Learning-Based Partitioning and Offloading for Edge Object Detection—0
On Learning Informative Trajectory Embeddings for Imitation, Classification and RegressionCode0
MonoSOWA: Scalable monocular 3D Object detector Without human Annotations—0
Distilling Multi-modal Large Language Models for Autonomous 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