SOTAVerified

Autonomous Vehicles

Autonomous vehicles is the task of making a vehicle that can guide itself 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: GSNet: Joint Vehicle Pose and Shape Reconstruction with Geometrical and Scene-aware Supervision )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1061–1070 of 2605 papers

TitleStatusHype
Driver Modeling through Deep Reinforcement Learning and Behavioral Game Theory—0
Driver Gaze Zone Estimation using Convolutional Neural Networks: A General Framework and Ablative Analysis—0
Benchmark for Models Predicting Human Behavior in Gap Acceptance Scenarios—0
An Empirical Analysis of the Use of Real-Time Reachability for the Safety Assurance of Autonomous Vehicles—0
Driver Assistance for Safe and Comfortable On-Ramp Merging Using Environment Models Extended through V2X Communication and Role-Based Behavior Predictions—0
DriveGuard: Robustification of Automated Driving Systems with Deep Spatio-Temporal Convolutional Autoencoder—0
DRIVE: Dependable Robust Interpretable Visionary Ensemble Framework in Autonomous Driving—0
Drive as You Speak: Enabling Human-Like Interaction with Large Language Models in Autonomous Vehicles—0
Behavior Planning of Autonomous Cars with Social Perception—0
An Empirical Analysis of Range for 3D Object Detection—0
Show:102550
← PrevPage 107 of 261Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BAAMA3DP22.85—Unverified
2GSNetA3DP20.21—Unverified