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 2426–2450 of 2605 papers

TitleStatusHype
Decomposition and Quantification of SOTIF Requirements for Perception Systems of Autonomous Vehicles—0
Deconvolutional Networks for Point-Cloud Vehicle Detection and Tracking in Driving Scenarios—0
Deep Camera Pose Regression Using Pseudo-LiDAR—0
DeepCrashTest: Turning Dashcam Videos into Virtual Crash Tests for Automated Driving Systems—0
DeepEvolution: A Search-Based Testing Approach for Deep Neural Networks—0
DeepFault: Fault Localization for Deep Neural Networks—0
DeepGuard: A Framework for Safeguarding Autonomous Driving Systems from Inconsistent Behavior—0
DeepiSign: Invisible Fragile Watermark to Protect the Integrityand Authenticity of CNN—0
Deep Koopman Operator-Informed Safety Command Governor for Autonomous Vehicles—0
DeepLaser: Practical Fault Attack on Deep Neural Networks—0
Deep Learning Based Autonomous Vehicle Super Resolution DOA Estimation for Safety Driving—0
Deep learning based infrared small object segmentation: Challenges and future directions—0
Deep Learning for Image and Point Cloud Fusion in Autonomous Driving: A Review—0
Deep Learning for LiDAR Point Clouds in Autonomous Driving: A Review—0
Deep Learning of Unified Region, Edge, and Contour Models for Automated Image Segmentation—0
Deep Learning Serves Traffic Safety Analysis: A Forward-looking Review—0
Deep Learning with Attention Mechanism for Predicting Driver Intention at Intersection—0
Deep Neural Networks with Koopman Operators for Modeling and Control of Autonomous Vehicles—0
Deep Occupancy-Predictive Representations for Autonomous Driving—0
DeepPoint: A Deep Learning Model for 3D Reconstruction in Point Clouds via mmWave Radar—0
Deep Probability Estimation—0
Deep Radar Waveform Design for Efficient Automotive Radar Sensing—0
Deep Reinforcement Learning Algorithms for Hybrid V2X Communication: A Benchmarking Study—0
Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception—0
Deep Reinforcement Learning for Adverse Garage Scenario Generation—0
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Benchmark Results

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