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 3851–3875 of 6092 papers

TitleStatusHype
DreamDrive: Generative 4D Scene Modeling from Street View Images—0
Drive-1-to-3: Enriching Diffusion Priors for Novel View Synthesis of Real Vehicles—0
DriveAction: A Benchmark for Exploring Human-like Driving Decisions in VLA Models—0
Drive Anywhere: Generalizable End-to-end Autonomous Driving with Multi-modal Foundation Models—0
Drive as You Speak: Enabling Human-Like Interaction with Large Language Models in Autonomous Vehicles—0
DRIVE: Dependable Robust Interpretable Visionary Ensemble Framework in Autonomous Driving—0
DriveDreamer4D: World Models Are Effective Data Machines for 4D Driving Scene Representation—0
DRIVE: Dual-Robustness via Information Variability and Entropic Consistency in Source-Free Unsupervised Domain Adaptation—0
DriveGen: Towards Infinite Diverse Traffic Scenarios with Large Models—0
DriveGenVLM: Real-world Video Generation for Vision Language Model based Autonomous Driving—0
DriveGPT4: Interpretable End-to-end Autonomous Driving via Large Language Model—0
DriveGPT4-V2: Harnessing Large Language Model Capabilities for Enhanced Closed-Loop Autonomous Driving—0
DriveGPT: Scaling Autoregressive Behavior Models for Driving—0
DriveMind: A Dual-VLM based Reinforcement Learning Framework for Autonomous Driving—0
DriveMoE: Mixture-of-Experts for Vision-Language-Action Model in End-to-End Autonomous Driving—0
Drive-R1: Bridging Reasoning and Planning in VLMs for Autonomous Driving with Reinforcement Learning—0
Driver2vec: Driver Identification from Automotive Data—0
Driver Assistance System Based on Multimodal Data Hazard Detection—0
DriverGym: Democratising Reinforcement Learning for Autonomous Driving—0
Driverseat: Crowdstrapping Learning Tasks for Autonomous Driving—0
DriveRX: A Vision-Language Reasoning Model for Cross-Task Autonomous Driving—0
DriveScape: High-Resolution Driving Video Generation by Multi-View Feature Fusion—0
DriveScape: Towards High-Resolution Controllable Multi-View Driving Video Generation—0
DriveSceneGen: Generating Diverse and Realistic Driving Scenarios from Scratch—0
DriveTrack: A Benchmark for Long-Range Point Tracking in Real-World Videos—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