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 32763300 of 6092 papers

TitleStatusHype
3M3D: Multi-view, Multi-path, Multi-representation for 3D Object Detection0
Navya3DSeg -- Navya 3D Semantic Segmentation Dataset & split generation for autonomous vehicles0
Generative AI-empowered Simulation for Autonomous Driving in Vehicular Mixed Reality MetaversesCode0
Cooperative Driving for Speed Harmonization in Mixed-Traffic Environments0
Tri-Perspective View for Vision-Based 3D Semantic Occupancy PredictionCode3
Uncertainty-Estimation with Normalized Logits for Out-of-Distribution Detection0
When Demonstrations Meet Generative World Models: A Maximum Likelihood Framework for Offline Inverse Reinforcement LearningCode1
ForceFormer: Exploring Social Force and Transformer for Pedestrian Trajectory Prediction0
Self-Supervised Likelihood Estimation with Energy Guidance for Anomaly Segmentation in Urban ScenesCode1
ConceptFusion: Open-set Multimodal 3D MappingCode2
Surround-View Vision-based 3D Detection for Autonomous Driving: A Survey0
EnergyShield: Provably-Safe Offloading of Neural Network Controllers for Energy Efficiency0
Exploring Navigation Maps for Learning-Based Motion PredictionCode1
Inferring Player Location in Sports Matches: Multi-Agent Spatial Imputation from Limited Observations0
Provably Safe Reinforcement Learning with Step-wise Violation Constraints0
Video Waterdrop Removal via Spatio-Temporal Fusion in Driving ScenesCode1
Variational Voxel Pseudo Image TrackingCode0
Uncertainty-Aware AB3DMOT by Variational 3D Object DetectionCode0
Invisible Users: Uncovering End-Users' Requirements for Explainable AI via Explanation Forms and GoalsCode0
PointWavelet: Learning in Spectral Domain for 3D Point Cloud Analysis0
Hierarchical Generative Adversarial Imitation Learning with Mid-level Input Generation for Autonomous Driving on Urban EnvironmentsCode1
Bridging the Sim2Real gap with CARE: Supervised Detection Adaptation with Conditional Alignment and Reweighting0
EVEN: An Event-Based Framework for Monocular Depth Estimation at Adverse Night Conditions0
Domain Adaptation of Synthetic Driving Datasets for Real-World Autonomous Driving0
Generalized Few-Shot 3D Object Detection of LiDAR Point Cloud for Autonomous Driving0
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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