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 1226–1250 of 2605 papers

TitleStatusHype
DeepGuard: A Framework for Safeguarding Autonomous Driving Systems from Inconsistent Behavior—0
Automatically Learning Fallback Strategies with Model-Free Reinforcement Learning in Safety-Critical Driving Scenarios—0
A machine learning environment for evaluating autonomous driving software—0
DeepFault: Fault Localization for Deep Neural Networks—0
DeepEvolution: A Search-Based Testing Approach for Deep Neural Networks—0
Automated Lane Change Behavior Prediction and Environmental Perception Based on SLAM Technology—0
DeepCrashTest: Turning Dashcam Videos into Virtual Crash Tests for Automated Driving Systems—0
Automated Generation of Diverse and Challenging Scenarios for Test and Evaluation of Autonomous Vehicles—0
A Lightweight Domain Adaptive Absolute Pose Regressor Using Barlow Twins Objective—0
Deep Camera Pose Regression Using Pseudo-LiDAR—0
Deconvolutional Networks for Point-Cloud Vehicle Detection and Tracking in Driving Scenarios—0
Automated Evaluation of Semantic Segmentation Robustness for Autonomous Driving—0
Decomposition and Quantification of SOTIF Requirements for Perception Systems of Autonomous Vehicles—0
Decoding CNN based Object Classifier Using Visualization—0
Automated Detecting and Placing Road Objects from Street-level Images—0
Algorithmic decision-making in AVs: Understanding ethical and technical concerns for smart cities—0
Adaptive Road Configurations for Improved Autonomous Vehicle-Pedestrian Interactions using Reinforcement Learning—0
Decision-Making Technology for Autonomous Vehicles Learning-Based Methods, Applications and Future Outlook—0
Automated design of error-resilient and hardware-efficient deep neural networks—0
Decision-making Strategy on Highway for Autonomous Vehicles using Deep Reinforcement Learning—0
Decision-Making for Autonomous Vehicles with Interaction-Aware Behavioral Prediction and Social-Attention Neural Network—0
Automated Data Curation Using GPS & NLP to Generate Instruction-Action Pairs for Autonomous Vehicle Vision-Language Navigation Datasets—0
Algorithmic Approaches to Enhance Safety in Autonomous Vehicles: Minimizing Lane Changes and Merging—0
Decision-making for Autonomous Vehicles on Highway: Deep Reinforcement Learning with Continuous Action Horizon—0
Decision Making for Autonomous Vehicles—0
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Benchmark Results

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