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 101–125 of 6092 papers

TitleStatusHype
GaussTR: Foundation Model-Aligned Gaussian Transformer for Self-Supervised 3D Spatial UnderstandingCode3
Generalized Trajectory Scoring for End-to-end Multimodal PlanningCode3
DriveDreamer-2: LLM-Enhanced World Models for Diverse Driving Video GenerationCode3
Benchmarking and Improving Bird's Eye View Perception Robustness in 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
Detect Anything 3D in the WildCode3
DriveLM: Driving with Graph Visual Question AnsweringCode3
TorchSparse: Efficient Point Cloud Inference EngineCode3
Forging Vision Foundation Models for Autonomous Driving: Challenges, Methodologies, and OpportunitiesCode3
Generalizing Motion Planners with Mixture of Experts for Autonomous DrivingCode3
EFFOcc: A Minimal Baseline for EFficient Fusion-based 3D Occupancy NetworkCode2
EMIFF: Enhanced Multi-scale Image Feature Fusion for Vehicle-Infrastructure Cooperative 3D Object DetectionCode2
Efficient Spatial-Temporal Information Fusion for LiDAR-Based 3D Moving Object SegmentationCode2
Efficient and Robust 2D-to-BEV Representation Learning via Geometry-guided Kernel TransformerCode2
Autonomous Driving with Spiking Neural NetworksCode2
E2E-MFD: Towards End-to-End Synchronous Multimodal Fusion DetectionCode2
Drone-assisted Road Gaussian Splatting with Cross-view UncertaintyCode2
Autonomous Driving on Curvy Roads Without Reliance on Frenet Frame: A Cartesian-Based Trajectory Planning MethodCode2
DurLAR: A High-fidelity 128-channel LiDAR Dataset with Panoramic Ambient and Reflectivity Imagery for Multi-modal Autonomous Driving ApplicationsCode2
AutoTrust: Benchmarking Trustworthiness in Large Vision Language Models for Autonomous DrivingCode2
Driving with LLMs: Fusing Object-Level Vector Modality for Explainable Autonomous DrivingCode2
DriVLMe: Enhancing LLM-based Autonomous Driving Agents with Embodied and Social ExperiencesCode2
DV-3DLane: End-to-end Multi-modal 3D Lane Detection with Dual-view RepresentationCode2
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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