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 631–640 of 2605 papers

TitleStatusHype
Analyzing Closed-loop Training Techniques for Realistic Traffic Agent Models in Autonomous Highway Driving Simulations—0
A Visual Neural Network for Robust Collision Perception in Vehicle Driving Scenarios—0
A Virtual Environment with Multi-Robot Navigation, Analytics, and Decision Support for Critical Incident Investigation—0
Analyzing and Enhancing Queue Sampling for Energy-Efficient Remote Control of Bandits—0
Deep Reinforcement-Learning-based Driving Policy for Autonomous Road Vehicles—0
Deep Learning of Unified Region, Edge, and Contour Models for Automated Image Segmentation—0
Analyze Drivers' Intervention Behavior During Autonomous Driving -- A VR-incorporated Approach—0
Autonomy and Unmanned Vehicles Augmented Reactive Mission-Motion Planning Architecture for Autonomous Vehicles—0
Addressing the IEEE AV Test Challenge with Scenic and VerifAI—0
Autonomy 2.0: The Quest for Economies of Scale—0
Show:102550
← PrevPage 64 of 261Next →

Benchmark Results

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