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 1691–1700 of 2605 papers

TitleStatusHype
Neural Network Based Model Predictive Control for an Autonomous Vehicle—0
Human Trajectory Prediction via Counterfactual AnalysisCode1
The Reasonable Crowd: Towards evidence-based and interpretable models of driving behaviorCode0
Dynamic and Static Object Detection Considering Fusion Regions and Point-wise Features—0
Finding Failures in High-Fidelity Simulation using Adaptive Stress Testing and the Backward AlgorithmCode1
CP-loss: Connectivity-preserving Loss for Road Curb Detection in Autonomous Driving with Aerial Images—0
AA3DNet: Attention Augmented Real Time 3D Object Detection—0
DR2L: Surfacing Corner Cases to Robustify Autonomous Driving via Domain Randomization Reinforcement Learning—0
SAGE: A Split-Architecture Methodology for Efficient End-to-End Autonomous Vehicle Control—0
mmPose-NLP: A Natural Language Processing Approach to Precise Skeletal Pose Estimation using mmWave Radars—0
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Benchmark Results

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