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 876–900 of 2605 papers

TitleStatusHype
Adversary ML Resilience in Autonomous Driving Through Human Centered Perception Mechanisms—0
DRNet: A Decision-Making Method for Autonomous Lane Changingwith Deep Reinforcement Learning—0
Learning Cooperative Trajectory Representations for Motion ForecastingCode1
Safety-aware Causal Representation for Trustworthy Offline Reinforcement Learning in Autonomous Driving—0
Decision-Making for Autonomous Vehicles with Interaction-Aware Behavioral Prediction and Social-Attention Neural Network—0
A Safe Preference Learning Approach for Personalization with Applications to Autonomous VehiclesCode0
Improving Online Source-free Domain Adaptation for Object Detection by Unsupervised Data Acquisition—0
RGB-X Object Detection via Scene-Specific Fusion ModulesCode1
Reward Finetuning for Faster and More Accurate Unsupervised Object DiscoveryCode1
A Stochastic Nonlinear Model Predictive Control with an Uncertainty Propagation Horizon for Autonomous Vehicle Motion Control—0
CityRefer: Geography-aware 3D Visual Grounding Dataset on City-scale Point Cloud DataCode1
Interactive Joint Planning for Autonomous Vehicles—0
EqDrive: Efficient Equivariant Motion Forecasting with Multi-Modality for Autonomous Driving—0
Nighttime Driver Behavior Prediction Using Taillight Signal Recognition via CNN-SVM ClassifierCode0
MVFAN: Multi-View Feature Assisted Network for 4D Radar Object Detection—0
Data-driven Traffic Simulation: A Comprehensive Review—0
Safe Navigation: Training Autonomous Vehicles using Deep Reinforcement Learning in CARLACode1
ADoPT: LiDAR Spoofing Attack Detection Based on Point-Level Temporal Consistency—0
Pre-Training LiDAR-Based 3D Object Detectors Through ColorizationCode0
Augmenting End-to-End Steering Angle Prediction with CAN Bus Data—0
Exploring Driving Behavior for Autonomous Vehicles Based on Gramian Angular Field Vision Transformer—0
CAT: Closed-loop Adversarial Training for Safe End-to-End Driving—0
KI-PMF: Knowledge Integrated Plausible Motion Forecasting—0
Classification of Safety Driver Attention During Autonomous Vehicle Operation—0
LiDAR-based 4D Occupancy Completion and ForecastingCode1
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Benchmark Results

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