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 1901–1925 of 2605 papers

TitleStatusHype
Where Do You Go? Pedestrian Trajectory Prediction using Scene Features—0
WHITE PAPER: Protecting GNSS Against Intentional Interference—0
Why semantics matters: A deep study on semantic particle-filtering localization in a LiDAR semantic pole-map—0
Wireless Ad Hoc Federated Learning: A Fully Distributed Cooperative Machine Learning—0
Wireless Communication as an Information Sensor for Multi-agent Cooperative Perception: A Survey—0
Work-in-Progress: Traded Control Transfer for Managing Real-Time Sensor Uncertainties in Autonomous Vehicle—0
Worsening Perception: Real-time Degradation of Autonomous Vehicle Perception Performance for Simulation of Adverse Weather Conditions—0
Zero-Day Botnet Attack Detection in IoV: A Modular Approach Using Isolation Forests and Particle Swarm Optimization—0
Zero-Error Tracking for Autonomous Vehicles through Epsilon-Trajectory Generation—0
Zero-shot Deep Reinforcement Learning Driving Policy Transfer for Autonomous Vehicles based on Robust Control—0
Zero-Shot Learning and its Applications from Autonomous Vehicles to COVID-19 Diagnosis: A Review—0
Zhuyi: Perception Processing Rate Estimation for Safety in Autonomous Vehicles—0
Zonal Architecture Development with evolution of Artificial Intelligence—0
Multi-Objective Reinforcement Learning for Critical Scenario Generation of Autonomous Vehicles—0
Multi-Objective Reinforcement Learning for Adaptive Personalized Autonomous Driving—0
Multi-Object Tracking using Poisson Multi-Bernoulli Mixture Filtering for Autonomous Vehicles—0
Analysis of a platooned car-following model with different inter-platoon communication levels—0
Multi-Predictor Fusion: Combining Learning-based and Rule-based Trajectory Predictors—0
Multi-Robot Routing with Time Windows: A Column Generation Approach—0
Multi-scale Temporal Fusion Transformer for Incomplete Vehicle Trajectory Prediction—0
Multi-Step Prediction of Occupancy Grid Maps with Recurrent Neural Networks—0
Multi-Stream Attention Learning for Monocular Vehicle Velocity and Inter-Vehicle Distance Estimation—0
Multitask Learning Deep Neural Networks to Combine Revealed and Stated Preference Data—0
Multi-task Learning for Real-time Autonomous Driving Leveraging Task-adaptive Attention Generator—0
Multivariate Uncertainty in Deep Learning—0
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Benchmark Results

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