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 126–150 of 6092 papers

TitleStatusHype
BEVerse: Unified Perception and Prediction in Birds-Eye-View for Vision-Centric Autonomous DrivingCode2
FedPylot: Navigating Federated Learning for Real-Time Object Detection in Internet of VehiclesCode2
FlexCloud: Direct, Modular Georeferencing and Drift-Correction of Point Cloud MapsCode2
Extremely Simple Multimodal Outlier Synthesis for Out-of-Distribution Detection and SegmentationCode2
Exploring the Roles of Large Language Models in Reshaping Transportation Systems: A Survey, Framework, and RoadmapCode2
Fast-BEV: Towards Real-time On-vehicle Bird's-Eye View PerceptionCode2
BEVHeight: A Robust Framework for Vision-based Roadside 3D Object DetectionCode2
Exploring the Causality of End-to-End Autonomous DrivingCode2
FB-OCC: 3D Occupancy Prediction based on Forward-Backward View TransformationCode2
FocalFormer3D : Focusing on Hard Instance for 3D Object DetectionCode2
GAIA-1: A Generative World Model for Autonomous DrivingCode2
AutoTrust: Benchmarking Trustworthiness in Large Vision Language Models for Autonomous DrivingCode2
Enhancing Autonomous Driving Systems with On-Board Deployed Large Language ModelsCode2
End-to-End Vectorized HD-map Construction with Piecewise Bezier CurveCode2
Autonomous Driving with Spiking Neural NetworksCode2
Enhancing 3D Lane Detection and Topology Reasoning with 2D Lane PriorsCode2
Autonomous Driving on Curvy Roads Without Reliance on Frenet Frame: A Cartesian-Based Trajectory Planning MethodCode2
4D Contrastive Superflows are Dense 3D Representation LearnersCode2
EMIFF: Enhanced Multi-scale Image Feature Fusion for Vehicle-Infrastructure Cooperative 3D Object DetectionCode2
Enhancing Vectorized Map Perception with Historical Rasterized MapsCode2
E2E-MFD: Towards End-to-End Synchronous Multimodal Fusion DetectionCode2
Efficient and Robust 2D-to-BEV Representation Learning via Geometry-guided Kernel TransformerCode2
Efficient Spatial-Temporal Information Fusion for LiDAR-Based 3D Moving Object SegmentationCode2
DV-3DLane: End-to-end Multi-modal 3D Lane Detection with Dual-view RepresentationCode2
2nd Place Solution for Waymo Open Dataset Challenge -- Real-time 2D Object DetectionCode2
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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