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

Showing 301325 of 2605 papers

TitleStatusHype
MTH-IDS: A Multi-Tiered Hybrid Intrusion Detection System for Internet of VehiclesCode1
A system of vision sensor based deep neural networks for complex driving scene analysis in support of crash risk assessment and preventionCode1
Learning Cooperative Trajectory Representations for Motion ForecastingCode1
A technique to jointly estimate depth and depth uncertainty for unmanned aerial vehiclesCode1
DeeP-LCC: Data-EnablEd Predictive Leading Cruise Control in Mixed Traffic FlowCode1
Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road ScenesCode1
Learning to Navigate Intersections with Unsupervised Driver Trait InferenceCode1
aiMotive Dataset: A Multimodal Dataset for Robust Autonomous Driving with Long-Range PerceptionCode1
Deep Reinforcement Learning for Time Allocation and Directional Transmission in Joint Radar-CommunicationCode1
Deep Sensor Fusion with Pyramid Fusion Networks for 3D Semantic SegmentationCode1
Multimodal Virtual Point 3D DetectionCode1
Multi-scale Interaction for Real-time LiDAR Data Segmentation on an Embedded PlatformCode1
AirSim: High-Fidelity Visual and Physical Simulation for Autonomous VehiclesCode1
Delay-Aware Multi-Agent Reinforcement Learning for Cooperative and Competitive EnvironmentsCode1
Adaptive-Mask Fusion Network for Segmentation of Drivable Road and Negative Obstacle With Untrustworthy FeaturesCode1
Dense Prediction Transformer for Scale Estimation in Monocular Visual OdometryCode1
Detecting 32 Pedestrian Attributes for Autonomous VehiclesCode1
Neural circuit policies enabling auditable autonomyCode1
BAT: Behavior-Aware Human-Like Trajectory Prediction for Autonomous DrivingCode1
Personalized Autonomous Driving with Large Language Models: Field ExperimentsCode1
Lane Graph as Path: Continuity-preserving Path-wise Modeling for Online Lane Graph ConstructionCode1
KPRNet: Improving projection-based LiDAR semantic segmentationCode1
Domain Adaptation based Object Detection for Autonomous Driving in Foggy and Rainy WeatherCode1
Domain Generalization for Vision-based Driving Trajectory GenerationCode1
Lane Graph Estimation for Scene Understanding in Urban DrivingCode1
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Benchmark Results

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