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

Showing 551575 of 6092 papers

TitleStatusHype
TransParking: A Dual-Decoder Transformer Framework with Soft Localization for End-to-End Automatic Parking0
Object-Centric World Model for Language-Guided Manipulation0
Secure On-Device Video OOD Detection Without BackpropagationCode1
Learning to Drive by Imitating Surrounding Vehicles0
Advancing Autonomous Vehicle Intelligence: Deep Learning and Multimodal LLM for Traffic Sign Recognition and Robust Lane Detection0
DriveTransformer: Unified Transformer for Scalable End-to-End Autonomous DrivingCode2
FastMap: Fast Queries Initialization Based Vectorized HD Map Reconstruction FrameworkCode1
GoalFlow: Goal-Driven Flow Matching for Multimodal Trajectories Generation in End-to-End Autonomous DrivingCode3
A Hybrid Approach for Extending Automotive Radar Operation to NLOS Urban Scenarios0
Evidential Uncertainty Estimation for Multi-Modal Trajectory Prediction0
DecoupledGaussian: Object-Scene Decoupling for Physics-Based Interaction0
A Comprehensive LLM-powered Framework for Driving Intelligence EvaluationCode0
Discrete Contrastive Learning for Diffusion Policies in Autonomous Driving0
InDRiVE: Intrinsic Disagreement based Reinforcement for Vehicle Exploration through Curiosity Driven Generalized World Model0
Geometry-Constrained Monocular Scale Estimation Using Semantic Segmentation for Dynamic Scenes0
INTENT: Trajectory Prediction Framework with Intention-Guided Contrastive Clustering0
Enhancing Autonomous Driving Safety with Collision Scenario Integration0
RGB-Thermal Infrared Fusion for Robust Depth Estimation in Complex Environments0
L2RDaS: Synthesizing 4D Radar Tensors for Model Generalization via Dataset Expansion0
CoSDH: Communication-Efficient Collaborative Perception via Supply-Demand Awareness and Intermediate-Late HybridizationCode1
BEVDriver: Leveraging BEV Maps in LLMs for Robust Closed-Loop DrivingCode2
Trajectory Prediction for Autonomous Driving: Progress, Limitations, and Future Directions0
Out-of-Distribution Segmentation in Autonomous Driving: Problems and State of the Art0
DriveGen: Towards Infinite Diverse Traffic Scenarios with Large Models0
TS-CGNet: Temporal-Spatial Fusion Meets Centerline-Guided Diffusion for BEV MappingCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ReasonNetDriving Score79.95Unverified
2InterFuserDriving Score76.18Unverified
3TCPDriving Score75.14Unverified
4TF++ WPDriving Score66.32Unverified
5Learning From All Vehicles (LAV)Driving Score61.85Unverified
6TransFuserDriving Score61.18Unverified
7TransFuser (Reproduced)Driving Score55.04Unverified
8TCP (Reproduced)Driving Score47.91Unverified
9Latent TransFuserDriving Score45.2Unverified
10GRIADDriving Score36.79Unverified
#ModelMetricClaimedVerifiedStatus
1Geometric FusionRC69.17Unverified
2TransFuserRC56.36Unverified
#ModelMetricClaimedVerifiedStatus
1Geometric FusionRC86.91Unverified
2TransFuserRC78.41Unverified