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 11011125 of 2605 papers

TitleStatusHype
MR-IDM -- Merge Reactive Intelligent Driver Model: Towards Enhancing Laterally Aware Car-following Models0
STREAMLINE: Streaming Active Learning for Realistic Multi-Distributional SettingsCode0
ReasonNet: End-to-End Driving with Temporal and Global Reasoning0
aUToLights: A Robust Multi-Camera Traffic Light Detection and Tracking System0
t-RAIN: Robust generalization under weather-aliasing label shift attacks0
Two is Better Than One: Digital Siblings to Improve Autonomous Driving TestingCode0
Identify, Estimate and Bound the Uncertainty of Reinforcement Learning for Autonomous Driving0
DeepSTEP -- Deep Learning-Based Spatio-Temporal End-To-End Perception for Autonomous Vehicles0
SalienDet: A Saliency-based Feature Enhancement Algorithm for Object Detection for Autonomous DrivingCode0
Transformer-Based Model for Monocular Visual Odometry: A Video Understanding ApproachCode1
A New Era of Mobility: Exploring Digital Twin Applications in Autonomous Vehicular Systems0
Effects of Real-Life Traffic Sign Alteration on YOLOv7- an Object Recognition Model0
Efficient Reinforcement Learning for Autonomous Driving with Parameterized Skills and PriorsCode1
Latest Trends in Artificial Intelligence Technology: A Scoping Review0
Decentralized Vehicle Coordination and Lane Switching without Switching of Controllers0
Friction-Adaptive Stochastic Nonlinear Model Predictive Control for Autonomous Vehicles0
Enabling High-Precision 5G mmWave-Based Positioning for Autonomous Vehicles in Dense Urban Environments0
Integrated 5G mmWave Positioning in Deep Urban Environments: Advantages and Challenges0
ScatterNeRF: Seeing Through Fog with Physically-Based Inverse Neural Rendering0
InconSeg: Residual-Guided Fusion With Inconsistent Multi-Modal Data for Negative and Positive Road Obstacles SegmentationCode1
Local and Global Contextual Features Fusion for Pedestrian Intention Prediction0
Fusion is Not Enough: Single Modal Attacks on Fusion Models for 3D Object DetectionCode1
Decision Making for Autonomous Vehicles0
Gradient-based Maximally Interfered Retrieval for Domain Incremental 3D Object DetectionCode0
Adaptive-Mask Fusion Network for Segmentation of Drivable Road and Negative Obstacle With Untrustworthy FeaturesCode1
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Benchmark Results

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