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
Bench2Drive: Towards Multi-Ability Benchmarking of Closed-Loop End-To-End Autonomous DrivingCode4
SparseDrive: End-to-End Autonomous Driving via Sparse Scene RepresentationCode4
S^3Gaussian: Self-Supervised Street Gaussians for Autonomous DrivingCode4
GaussianFormer: Scene as Gaussians for Vision-Based 3D Semantic Occupancy PredictionCode4
A Survey on Occupancy Perception for Autonomous Driving: The Information Fusion PerspectiveCode4
Is Sora a World Simulator? A Comprehensive Survey on General World Models and BeyondCode4
OmniDrive: A Holistic Vision-Language Dataset for Autonomous Driving with Counterfactual ReasoningCode4
End-to-End Autonomous Driving through V2X CooperationCode4
End-to-end Autonomous Driving: Challenges and FrontiersCode4
Segment and Track AnythingCode4
Planning-oriented Autonomous DrivingCode4
Delving into the Devils of Bird's-eye-view Perception: A Review, Evaluation and RecipeCode4
EfficientViT: Multi-Scale Linear Attention for High-Resolution Dense PredictionCode4
OpenCalib: A Multi-sensor Calibration Toolbox for Autonomous DrivingCode4
BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View RepresentationCode4
BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal TransformersCode4
Epona: Autoregressive Diffusion World Model for Autonomous DrivingCode3
AutoVLA: A Vision-Language-Action Model for End-to-End Autonomous Driving with Adaptive Reasoning and Reinforcement Fine-TuningCode3
Generalized Trajectory Scoring for End-to-end Multimodal PlanningCode3
Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action ModelsCode3
Generative AI for Autonomous Driving: Frontiers and OpportunitiesCode3
Detect Anything 3D in the WildCode3
End-to-End Driving with Online Trajectory Evaluation via BEV World ModelCode3
UniOcc: A Unified Benchmark for Occupancy Forecasting and Prediction in Autonomous DrivingCode3
GS-SDF: LiDAR-Augmented Gaussian Splatting and Neural SDF for Geometrically Consistent Rendering and ReconstructionCode3
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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