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 26–50 of 6092 papers

TitleStatusHype
End-to-End Autonomous Driving through V2X CooperationCode4
Diffusion-Based Planning for Autonomous Driving with Flexible GuidanceCode4
GaussianFormer-2: Probabilistic Gaussian Superposition for Efficient 3D Occupancy PredictionCode4
BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal TransformersCode4
BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View RepresentationCode4
S^3Gaussian: Self-Supervised Street Gaussians for Autonomous DrivingCode4
OpenDriveVLA: Towards End-to-end Autonomous Driving with Large Vision Language Action ModelCode4
OmniDrive: A Holistic Vision-Language Dataset for Autonomous Driving with Counterfactual ReasoningCode4
OpenCalib: A Multi-sensor Calibration Toolbox for Autonomous DrivingCode4
OpenEMMA: Open-Source Multimodal Model for End-to-End Autonomous DrivingCode4
Multimodal Chain-of-Thought Reasoning: A Comprehensive SurveyCode4
3D Scene Generation: A SurveyCode4
Delving into the Devils of Bird's-eye-view Perception: A Review, Evaluation and RecipeCode4
Is Sora a World Simulator? A Comprehensive Survey on General World Models and BeyondCode4
Planning-oriented Autonomous DrivingCode4
A Survey on Occupancy Perception for Autonomous Driving: The Information Fusion PerspectiveCode4
Geometric-aware Pretraining for Vision-centric 3D Object DetectionCode3
Generalizing Motion Planners with Mixture of Experts for Autonomous DrivingCode3
Generalized Trajectory Scoring for End-to-end Multimodal PlanningCode3
Generative AI for Autonomous Driving: Frontiers and OpportunitiesCode3
GaussTR: Foundation Model-Aligned Gaussian Transformer for Self-Supervised 3D Spatial UnderstandingCode3
GenAD: Generative End-to-End Autonomous DrivingCode3
Enhancing End-to-End Autonomous Driving with Latent World ModelCode3
Epona: Autoregressive Diffusion World Model for Autonomous DrivingCode3
Behavior Generation with Latent ActionsCode3
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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