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 1391–1400 of 2605 papers

TitleStatusHype
Powertrain Hybridization for Autonomous Vehicles—0
Practical Auto-Calibration for Spatial Scene-Understanding from Crowdsourced Dashcamera Videos—0
Taxonomy of Machine Learning Safety: A Survey and Primer—0
Practical Solutions for Machine Learning Safety in Autonomous Vehicles—0
Precise Ranging: Modeling Bias and Variance of Double-Sided Two-Way Ranging with TDoA Extraction under Multipath and NLOS Effects—0
Predicting Autonomous Vehicle Collision Injury Severity Levels for Ethical Decision Making and Path Planning—0
Predicting Future Lane Changes of Other Highway Vehicles using RNN-based Deep Models—0
Predicting Scene Parsing and Motion Dynamics in the Future—0
Predicting Trust In Autonomous Vehicles: Modeling Young Adult Psychosocial Traits, Risk-Benefit Attitudes, And Driving Factors With Machine Learning—0
Predicting Vehicle Behaviors Over An Extended Horizon Using Behavior Interaction Network—0
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Benchmark Results

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