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 5026–5050 of 6092 papers

TitleStatusHype
TMCOSS: Thresholded Multi-Criteria Online Subset Selection for Data-Efficient Autonomous Driving—0
End-to-End on-device Federated Learning: A case study—0
Visual Probing and Correction of Object Recognition Models with Interactive user feedbackCode0
An Efficient Generation Method based on Dynamic Curvature of the Reference Curve for Robust Trajectory Planning—0
Commonsense Visual Sensemaking for Autonomous Driving: On Generalised Neurosymbolic Online Abduction Integrating Vision and Semantics—0
Achieving Real-Time LiDAR 3D Object Detection on a Mobile Device—0
Deep Learning Based Intelligent Inter-Vehicle Distance Control for 6G Enabled Cooperative Autonomous Driving—0
Reconfigurable Intelligent Surface Assisted Mobile Edge Computing with Heterogeneous Learning Tasks—0
Prediction by Anticipation: An Action-Conditional Prediction Method based on Interaction Learning—0
Assume/Guarantee Contracts for Dynamical Systems: Theory and Computational Tools—0
Parallelized Instantaneous Velocity and Heading Estimation of Objects using Single Imaging Radar—0
The Translucent Patch: A Physical and Universal Attack on Object Detectors—0
Hardware and Software Optimizations for Accelerating Deep Neural Networks: Survey of Current Trends, Challenges, and the Road Ahead—0
Anchor-Based Spatio-Temporal Attention 3D Convolutional Networks for Dynamic 3D Point Cloud Sequences—0
Labels Are Not Perfect: Inferring Spatial Uncertainty in Object Detection—0
PC-RGNN: Point Cloud Completion and Graph Neural Network for 3D Object Detection—0
End-to-end Deep Object Tracking with Circular Loss Function for Rotated Bounding Box—0
PanoNet3D: Combining Semantic and Geometric Understanding for LiDARPoint Cloud Detection—0
Machine Learning Algorithm for NLOS Millimeter Wave in 5G V2X Communication—0
CARLA Real Traffic Scenarios -- novel training ground and benchmark for autonomous driving—0
LiveMap: Real-Time Dynamic Map in Automotive Edge Computing—0
Artificial Dummies for Urban Dataset AugmentationCode0
Virtual Autonomous Driving with Reinforcement Learning—0
PePScenes: A Novel Dataset and Baseline for Pedestrian Action Prediction in 3DCode0
Increasing Data Efficiency of Driving Agent By World ModelCode0
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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