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 1701–1725 of 6092 papers

TitleStatusHype
DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving—0
DriveWorld: 4D Pre-trained Scene Understanding via World Models for Autonomous Driving—0
Beyond One Model Fits All: Ensemble Deep Learning for Autonomous Vehicles—0
Analyzing the Variety Loss in the Context of Probabilistic Trajectory Prediction—0
DriveVLM: The Convergence of Autonomous Driving and Large Vision-Language Models—0
Beyond Grand Theft Auto V for Training, Testing and Enhancing Deep Learning in Self Driving Cars—0
DriveTrack: A Benchmark for Long-Range Point Tracking in Real-World Videos—0
Analyzing Human Models that Adapt Online—0
Adaptable Deformable Convolutions for Semantic Segmentation of Fisheye Images in Autonomous Driving Systems—0
Driving by the Rules: A Benchmark for Integrating Traffic Sign Regulations into Vectorized HD Map—0
DriveSceneGen: Generating Diverse and Realistic Driving Scenarios from Scratch—0
Driving Decision and Control for Autonomous Lane Change based on Deep Reinforcement Learning—0
DriveScape: Towards High-Resolution Controllable Multi-View Driving Video Generation—0
Driving Everywhere with Large Language Model Policy Adaptation—0
Beyond Boundaries: A Comprehensive Survey of Transferable Attacks on AI Systems—0
Driving in Real Life with Inverse Reinforcement Learning—0
Driving in the Occupancy World: Vision-Centric 4D Occupancy Forecasting and Planning via World Models for Autonomous Driving—0
DriveScape: High-Resolution Driving Video Generation by Multi-View Feature Fusion—0
DriveRX: A Vision-Language Reasoning Model for Cross-Task Autonomous Driving—0
Driving-RAG: Driving Scenarios Embedding, Search, and RAG Applications—0
Analyzing Computer Vision Data - The Good, the Bad and the Ugly—0
Driving Scene Perception Network: Real-time Joint Detection, Depth Estimation and Semantic Segmentation—0
Driverseat: Crowdstrapping Learning Tasks for Autonomous Driving—0
DriverGym: Democratising Reinforcement Learning for Autonomous Driving—0
Driver Assistance System Based on Multimodal Data Hazard Detection—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