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 1451–1500 of 2605 papers

TitleStatusHype
A Survey of Deep Learning Based Radar and Vision Fusion for 3D Object Detection in Autonomous Driving—0
A Survey of Deep Reinforcement Learning Algorithms for Motion Planning and Control of Autonomous Vehicles—0
A Survey of FPGA-Based Robotic Computing—0
A Survey of Learning-Based Intrusion Detection Systems for In-Vehicle Network—0
A Survey of Model Extraction Attacks and Defenses in Distributed Computing Environments—0
A Survey on Adversarial Robustness of LiDAR-based Machine Learning Perception in Autonomous Vehicles—0
A Survey on Approximate Edge AI for Energy Efficient Autonomous Driving Services—0
A Survey on Autonomous Vehicle Control in the Era of Mixed-Autonomy: From Physics-Based to AI-Guided Driving Policy Learning—0
A Survey on Data-Driven Modeling of Human Drivers' Lane-Changing Decisions—0
A Survey on Datasets for Decision-making of Autonomous Vehicle—0
A Survey on Deep Learning Methods for Semantic Image Segmentation in Real-Time—0
A Survey on Graph Neural Networks in Intelligent Transportation Systems—0
A Survey on Integrated Sensing and Communication with Intelligent Metasurfaces: Trends, Challenges, and Opportunities—0
A Survey on the Applications of Frontier AI, Foundation Models, and Large Language Models to Intelligent Transportation Systems—0
A Survey on the Role of Artificial Intelligence and Machine Learning in 6G-V2X Applications—0
A Systematic Literature Review about the impact of Artificial Intelligence on Autonomous Vehicle Safety—0
A taxonomy of strategic human interactions in traffic conflicts—0
A Tempt to Unify Heterogeneous Driving Databases using Traffic Primitives—0
A Threefold Review on Deep Semantic Segmentation: Efficiency-oriented, Temporal and Depth-aware design—0
A Transparency Paradox? Investigating the Impact of Explanation Specificity and Autonomous Vehicle Perceptual Inaccuracies on Passengers—0
Attack Tree Analysis for Adversarial Evasion Attacks—0
Attention-based Supply-Demand Prediction for Autonomous Vehicles—0
A Tutorial on Adversarial Learning Attacks and Countermeasures—0
Audio Analytics-based Human Trafficking Detection Framework for Autonomous Vehicles—0
Audiovisual Affect Assessment and Autonomous Automobiles: Applications—0
Audio-Visual Self-Supervised Terrain Type Discovery for Mobile Platforms—0
Augmented Reality based Simulated Data (ARSim) with multi-view consistency for AV perception networks—0
Augmenting End-to-End Steering Angle Prediction with CAN Bus Data—0
Lane Change Intention Recognition and Vehicle Status Prediction for Autonomous Vehicles—0
A Unified Toll Lane Framework for Autonomous and High-Occupancy Vehicles in Interactive Mixed Autonomy—0
AUTHENTICATION: Identifying Rare Failure Modes in Autonomous Vehicle Perception Systems using Adversarially Guided Diffusion Models—0
AutoFed: Heterogeneity-Aware Federated Multimodal Learning for Robust Autonomous Driving—0
aUToLights: A Robust Multi-Camera Traffic Light Detection and Tracking System—0
Automated Data Curation Using GPS & NLP to Generate Instruction-Action Pairs for Autonomous Vehicle Vision-Language Navigation Datasets—0
Automated design of error-resilient and hardware-efficient deep neural networks—0
Automated Detecting and Placing Road Objects from Street-level Images—0
Automated Evaluation of Semantic Segmentation Robustness for Autonomous Driving—0
Automated Generation of Diverse and Challenging Scenarios for Test and Evaluation of Autonomous Vehicles—0
Automated Lane Change Behavior Prediction and Environmental Perception Based on SLAM Technology—0
Automatically Learning Fallback Strategies with Model-Free Reinforcement Learning in Safety-Critical Driving Scenarios—0
Automatic Calibration of Multiple 3D LiDARs in Urban Environments—0
Automatic driving lane change safety prediction model based on LSTM—0
Automatic Testing With Reusable Adversarial Agents—0
Automatic Traffic Sign Detection and Recognition Using SegU-Net and a Modified Tversky Loss Function With L1-Constraint—0
Automatic Vehicle Detection using DETR: A Transformer-Based Approach for Navigating Treacherous Roads—0
Autonomous Algorithm for Training Autonomous Vehicles with Minimal Human Intervention—0
Autonomous Braking and Throttle System: A Deep Reinforcement Learning Approach for Naturalistic Driving—0
Autonomous Cars: Vision based Steering Wheel Angle Estimation—0
Autonomous Driving and Residential Location Preferences: Evidence from a Stated Choice Survey—0
Autonomous Driving using Safe Reinforcement Learning by Incorporating a Regret-based Human Lane-Changing Decision Model—0
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Benchmark Results

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