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 10261050 of 6092 papers

TitleStatusHype
Dyna-DM: Dynamic Object-aware Self-supervised Monocular Depth MapsCode1
DVI: Depth Guided Video Inpainting for Autonomous DrivingCode1
Dynamic Conditional Imitation Learning for Autonomous DrivingCode1
Dur360BEV: A Real-world 360-degree Single Camera Dataset and Benchmark for Bird-Eye View Mapping in Autonomous DrivingCode1
Dual Radar: A Multi-modal Dataset with Dual 4D Radar for Autonomous DrivingCode1
DualAD: Dual-Layer Planning for Reasoning in Autonomous DrivingCode1
DSTIGCN: Deformable Spatial-Temporal Interaction Graph Convolution Network for Pedestrian Trajectory PredictionCode1
DualDiff: Dual-branch Diffusion Model for Autonomous Driving with Semantic FusionCode1
DUSA: Decoupled Unsupervised Sim2Real Adaptation for Vehicle-to-Everything Collaborative PerceptionCode1
Dynamic Environment Prediction in Urban Scenes using Recurrent Representation LearningCode1
DRL-Based Trajectory Tracking for Motion-Related Modules in Autonomous DrivingCode1
Driving Style Alignment for LLM-powered Driver AgentCode1
DSEC: A Stereo Event Camera Dataset for Driving ScenariosCode1
Adversarial Driving: Attacking End-to-End Autonomous DrivingCode1
3DLabelProp: Geometric-Driven Domain Generalization for LiDAR Semantic Segmentation in Autonomous DrivingCode1
Adversarial Deep Reinforcement Learning for Improving the Robustness of Multi-agent Autonomous Driving PoliciesCode1
Event-Free Moving Object Segmentation from Moving Ego VehicleCode1
EC-Depth: Exploring the consistency of self-supervised monocular depth estimation in challenging scenesCode1
End-to-end Autonomous Driving Perception with Sequential Latent Representation LearningCode1
FedDrive v2: an Analysis of the Impact of Label Skewness in Federated Semantic Segmentation for Autonomous DrivingCode1
DriveMLM: Aligning Multi-Modal Large Language Models with Behavioral Planning States for Autonomous DrivingCode1
DriveGEN: Generalized and Robust 3D Detection in Driving via Controllable Text-to-Image Diffusion GenerationCode1
3DIoUMatch: Leveraging IoU Prediction for Semi-Supervised 3D Object DetectionCode1
Adversarial Attack and Defense of YOLO Detectors in Autonomous Driving ScenariosCode1
DriveDiTFit: Fine-tuning Diffusion Transformers for Autonomous DrivingCode1
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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