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 2251–2275 of 2605 papers

TitleStatusHype
Tree-based Intelligent Intrusion Detection System in Internet of VehiclesCode1
Probabilistic Trajectory Prediction for Autonomous Vehicles with Attentive Recurrent Neural Process—0
A Hybrid Compact Neural Architecture for Visual Place RecognitionCode0
Dynamic Graph Configuration with Reinforcement Learning for Connected Autonomous Vehicle Trajectories—0
FuseMODNet: Real-Time Camera and LiDAR based Moving Object Detection for robust low-light Autonomous Driving—0
Autonomous Driving using Safe Reinforcement Learning by Incorporating a Regret-based Human Lane-Changing Decision Model—0
Intention Recognition of Pedestrians and Cyclists by 2D Pose EstimationCode0
Multi-Vehicle Interaction Scenarios Generation with Interpretable Traffic Primitives and Gaussian Process Regression—0
Improving Map Re-localization with Deep 'Movable' Objects Segmentation on 3D LiDAR Point Clouds—0
High-Resolution Traffic Sensing with Autonomous VehiclesCode0
Risk-Aware Reasoning for Autonomous Vehicles—0
Bayesian Learning-Based Adaptive Control for Safety Critical SystemsCode0
Self-supervised learning for autonomous vehicles perception: A conciliation between analytical and learning methods—0
Review of Learning-based Longitudinal Motion Planning for Autonomous Vehicles: Research Gaps between Self-driving and Traffic Congestion—0
Road scenes analysis in adverse weather conditions by polarization-encoded images and adapted deep learning—0
GLADAS: Gesture Learning for Advanced Driver Assistance Systems—0
Using Image Priors to Improve Scene Understanding—0
Drive&Act: A Multi-Modal Dataset for Fine-Grained Driver Behavior Recognition in Autonomous Vehicles—0
STGAT: Modeling Spatial-Temporal Interactions for Human Trajectory PredictionCode0
Automated design of error-resilient and hardware-efficient deep neural networks—0
epBRM: Improving a Quality of 3D Object Detection using End Point Box Regression Module—0
Interactive Decision Making for Autonomous Vehicles in Dense Traffic—0
Safe Reinforcement Learning on Autonomous Vehicles—0
Communication-Constrained Routing and Traffic Control for Autonomous Vehicles—0
Autonomous Driving and Residential Location Preferences: Evidence from a Stated Choice Survey—0
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Benchmark Results

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