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 601–625 of 2605 papers

TitleStatusHype
Performance Evaluation of Real-Time Object Detection for Electric ScootersCode0
Systematic Review: Anomaly Detection in Connected and Autonomous Vehicles—0
Obstacle Avoidance of Autonomous Vehicles: An LPVMPC with Scheduling Trust Region—0
ScenicNL: Generating Probabilistic Scenario Programs from Natural Language—0
Dyna-Style Learning with A Macroscopic Model for Vehicle Platooning in Mixed-Autonomy Traffic—0
Rare Collision Risk Estimation of Autonomous Vehicles with Multi-Agent Situation Awareness—0
ADM: Accelerated Diffusion Model via Estimated Priors for Robust Motion Prediction under UncertaintiesCode0
Toward Unified Practices in Trajectory Prediction Research on Bird's-Eye-View DatasetsCode2
SemVecNet: Generalizable Vector Map Generation for Arbitrary Sensor ConfigurationsCode1
Assessing the safety benefits of CACC+ based coordination of connected and autonomous vehicle platoons in emergency braking scenarios—0
Revolutionizing Traffic Sign Recognition: Unveiling the Potential of Vision Transformers—0
Predicting Safety Misbehaviours in Autonomous Driving Systems using Uncertainty QuantificationCode0
Leveraging PointNet and PointNet++ for Lyft Point Cloud Classification Challenge—0
Self-training superconducting neuromorphic circuits using reinforcement learning rules—0
Motion planning for off-road autonomous driving based on human-like cognition and weight adaptation—0
Multi-Stream Cellular Test-Time Adaptation of Real-Time Models Evolving in Dynamic EnvironmentsCode1
Enhancing Track Management Systems with Vehicle-To-Vehicle Enabled Sensor Fusion—0
On the Federated Learning Framework for Cooperative Perception—0
Dense Road Surface Grip Map Prediction from Multimodal Image Data—0
Redefining Safety for Autonomous Vehicles—0
Toward Physics-Aware Deep Learning Architectures for LiDAR Intensity SimulationCode0
Enhancing High-Speed Cruising Performance of Autonomous Vehicles through Integrated Deep Reinforcement Learning Framework—0
ContextualFusion: Context-Based Multi-Sensor Fusion for 3D Object Detection in Adverse Operating Conditions—0
Optimization-based Heuristic for Vehicle Dynamic Coordination in Mixed Traffic Intersections—0
Poisoning Attacks on Federated Learning-based Wireless Traffic Prediction—0
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Benchmark Results

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