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 1376–1400 of 2605 papers

TitleStatusHype
P-MapNet: Far-seeing Map Generator Enhanced by both SDMap and HDMap Priors—0
Point Cloud Compression for Efficient Data Broadcasting: A Performance Comparison—0
Point Cloud in the Air—0
Point Cloud Segmentation Using Sparse Temporal Local Attention—0
PointNetKL: Deep Inference for GICP Covariance Estimation in Bathymetric SLAM—0
PointNet on FPGA for Real-Time LiDAR Point Cloud Processing—0
Poisoning Attacks on Federated Learning-based Wireless Traffic Prediction—0
Polar Collision Grids: Effective Interaction Modelling for Pedestrian Trajectory Prediction in Shared Space Using Collision Checks—0
Polling-systems-based Autonomous Vehicle Coordination in Traffic Intersections with No Traffic Signals—0
Poly-Autoregressive Prediction for Modeling Interactions—0
Portrait Segmentation Using Ensemble of Heterogeneous Deep-Learning Models—0
Position: Epistemic Artificial Intelligence is Essential for Machine Learning Models to Know When They Do Not Know—0
Position Paper: Rethinking Privacy in RL for Sequential Decision-making in the Age of LLMs—0
Potential-based Credit Assignment for Cooperative RL-based Testing of Autonomous Vehicles—0
Potential Game-Based Decision-Making for Autonomous Driving—0
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