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 226–250 of 6092 papers

TitleStatusHype
Cityscapes 3D: Dataset and Benchmark for 9 DoF Vehicle DetectionCode2
CoBEVT: Cooperative Bird's Eye View Semantic Segmentation with Sparse TransformersCode2
CLRerNet: Improving Confidence of Lane Detection with LaneIoUCode2
LangCoop: Collaborative Driving with LanguageCode2
LangProp: A code optimization framework using Large Language Models applied to drivingCode2
A Cognitive-Based Trajectory Prediction Approach for Autonomous DrivingCode2
Learning Multiple Probabilistic Decisions from Latent World Model in Autonomous DrivingCode2
LGSVL Simulator: A High Fidelity Simulator for Autonomous DrivingCode2
EMIFF: Enhanced Multi-scale Image Feature Fusion for Vehicle-Infrastructure Cooperative 3D Object DetectionCode2
ConceptFusion: Open-set Multimodal 3D MappingCode2
LiDAR Snowfall Simulation for Robust 3D Object DetectionCode2
LightLoc: Learning Outdoor LiDAR Localization at Light SpeedCode2
Complex-YOLO: Real-time 3D Object Detection on Point CloudsCode2
End-to-End Vectorized HD-map Construction with Piecewise Bezier CurveCode2
Asynchronous Large Language Model Enhanced Planner for Autonomous DrivingCode2
Make Your ViT-based Multi-view 3D Detectors Faster via Token CompressionCode2
MAPLM: A Real-World Large-Scale Vision-Language Benchmark for Map and Traffic Scene UnderstandingCode2
EFFOcc: A Minimal Baseline for EFficient Fusion-based 3D Occupancy NetworkCode2
Efficient Spatial-Temporal Information Fusion for LiDAR-Based 3D Moving Object SegmentationCode2
MART: MultiscAle Relational Transformer Networks for Multi-agent Trajectory PredictionCode2
Continuously Learning, Adapting, and Improving: A Dual-Process Approach to Autonomous DrivingCode2
Enhancing 3D Lane Detection and Topology Reasoning with 2D Lane PriorsCode2
MF-MOS: A Motion-Focused Model for Moving Object SegmentationCode2
Fisheye-Calib-Adapter: An Easy Tool for Fisheye Camera Model ConversionCode2
Drone-assisted Road Gaussian Splatting with Cross-view UncertaintyCode2
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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