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 401–425 of 6092 papers

TitleStatusHype
SafeCast: Risk-Responsive Motion Forecasting for Autonomous Vehicles—0
Extending Silicon Lifetime: A Review of Design Techniques for Reliable Integrated Circuits—0
Fine-Grained Evaluation of Large Vision-Language Models in Autonomous DrivingCode1
LandMarkSystem Technical ReportCode2
InteractionMap: Improving Online Vectorized HDMap Construction with Interaction—0
Exploring the Roles of Large Language Models in Reshaping Transportation Systems: A Survey, Framework, and RoadmapCode2
Fine-Grained Behavior and Lane Constraints Guided Trajectory Prediction Method—0
Knowledge Graphs as World Models for Semantic Material-Aware Obstacle Handling in Autonomous Vehicles—0
Adversarial Wear and Tear: Exploiting Natural Damage for Generating Physical-World Adversarial Examples—0
Towards Generating Realistic 3D Semantic Training Data for Autonomous DrivingCode2
Omnidirectional Depth-Aided Occupancy Prediction based on Cylindrical Voxel for Autonomous Driving—0
AccidentSim: Generating Physically Realistic Vehicle Collision Videos from Real-World Accident Reports—0
EVolSplat: Efficient Volume-based Gaussian Splatting for Urban View Synthesis—0
GAIA-2: A Controllable Multi-View Generative World Model for Autonomous Driving—0
SaViD: Spectravista Aesthetic Vision Integration for Robust and Discerning 3D Object Detection in Challenging EnvironmentsCode0
ADS-Edit: A Multimodal Knowledge Editing Dataset for Autonomous Driving Systems—0
ORION: A Holistic End-to-End Autonomous Driving Framework by Vision-Language Instructed Action Generation—0
LENVIZ: A High-Resolution Low-Exposure Night Vision Benchmark Dataset—0
ST-VLM: Kinematic Instruction Tuning for Spatio-Temporal Reasoning in Vision-Language Models—0
Context-Aware Semantic Segmentation: Enhancing Pixel-Level Understanding with Large Language Models for Advanced Vision Applications—0
Multi-Agent Deep Reinforcement Learning for Safe Autonomous Driving with RICS-Assisted MEC—0
Resilient Sensor Fusion under Adverse Sensor Failures via Multi-Modal Expert Fusion—0
SuperFlow++: Enhanced Spatiotemporal Consistency for Cross-Modal Data PretrainingCode2
Semi-SD: Semi-Supervised Metric Depth Estimation via Surrounding Cameras for Autonomous DrivingCode0
AED: Automatic Discovery of Effective and Diverse Vulnerabilities for Autonomous Driving Policy with Large Language Models—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