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

Showing 601625 of 6092 papers

TitleStatusHype
HDGT: Heterogeneous Driving Graph Transformer for Multi-Agent Trajectory Prediction via Scene EncodingCode1
Hydra-NeXt: Robust Closed-Loop Driving with Open-Loop TrainingCode1
DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic SegmentationCode1
SeSame: Simple, Easy 3D Object Detection with Point-Wise SemanticsCode1
Graph-based Spatial Transformer with Memory Replay for Multi-future Pedestrian Trajectory PredictionCode1
GraphCSPN: Geometry-Aware Depth Completion via Dynamic GCNsCode1
DARTH: Holistic Test-time Adaptation for Multiple Object TrackingCode1
GPT-4 Enhanced Multimodal Grounding for Autonomous Driving: Leveraging Cross-Modal Attention with Large Language ModelsCode1
CurveLane-NAS: Unifying Lane-Sensitive Architecture Search and Adaptive Point BlendingCode1
Curricular Subgoals for Inverse Reinforcement LearningCode1
Crowdsourced 3D Mapping: A Combined Multi-View Geometry and Self-Supervised Learning ApproachCode1
CSFlow: Learning Optical Flow via Cross Strip Correlation for Autonomous DrivingCode1
GNN-PMB: A Simple but Effective Online 3D Multi-Object Tracker without Bells and WhistlesCode1
CrossDTR: Cross-view and Depth-guided Transformers for 3D Object DetectionCode1
CROON: Automatic Multi-LiDAR Calibration and Refinement Method in Road SceneCode1
Ctrl-V: Higher Fidelity Video Generation with Bounding-Box Controlled Object MotionCode1
CRN: Camera Radar Net for Accurate, Robust, Efficient 3D PerceptionCode1
Cross-modal Learning for Domain Adaptation in 3D Semantic SegmentationCode1
DASGIL: Domain Adaptation for Semantic and Geometric-aware Image-based LocalizationCode1
GPS-GLASS: Learning Nighttime Semantic Segmentation Using Daytime Video and GPS dataCode1
GRIP++: Enhanced Graph-based Interaction-aware Trajectory Prediction for Autonomous DrivingCode1
Geometry-based Distance Decomposition for Monocular 3D Object DetectionCode1
COTR: Compact Occupancy TRansformer for Vision-based 3D Occupancy PredictionCode1
CoSMix: Compositional Semantic Mix for Domain Adaptation in 3D LiDAR SegmentationCode1
CPGNet: Cascade Point-Grid Fusion Network for Real-Time LiDAR Semantic SegmentationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ReasonNetDriving Score79.95Unverified
2InterFuserDriving Score76.18Unverified
3TCPDriving Score75.14Unverified
4TF++ WPDriving Score66.32Unverified
5Learning From All Vehicles (LAV)Driving Score61.85Unverified
6TransFuserDriving Score61.18Unverified
7TransFuser (Reproduced)Driving Score55.04Unverified
8TCP (Reproduced)Driving Score47.91Unverified
9Latent TransFuserDriving Score45.2Unverified
10GRIADDriving Score36.79Unverified
#ModelMetricClaimedVerifiedStatus
1Geometric FusionRC69.17Unverified
2TransFuserRC56.36Unverified
#ModelMetricClaimedVerifiedStatus
1Geometric FusionRC86.91Unverified
2TransFuserRC78.41Unverified