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 426–450 of 2605 papers

TitleStatusHype
A Real-Time DETR Approach to Bangladesh Road Object Detection for Autonomous Vehicles—0
A Real-Time Defense Against Object Vanishing Adversarial Patch Attacks for Object Detection in Autonomous Vehicles—0
Adversary ML Resilience in Autonomous Driving Through Human Centered Perception Mechanisms—0
Adversarial Sensor Attack on LiDAR-based Perception in Autonomous Driving—0
Arbitrary Angle of Arrival in Radar Target Simulation—0
A Cooperation-Aware Lane Change Method for Autonomous Vehicles—0
4C: A Computation, Communication, and Control Co-Design Framework for CAVs—0
A Quality Index Metric and Method for Online Self-Assessment of Autonomous Vehicles Sensory Perception—0
Adversarial Reinforcement Learning Framework for Benchmarking Collision Avoidance Mechanisms in Autonomous Vehicles—0
Adversarial Plannning—0
AppSign: Multi-level Approximate Computing for Real-Time Traffic Sign Recognition in Autonomous Vehicles—0
A Convex Optimal Control Framework for Autonomous Vehicle Intersection Crossing—0
4D-MultispectralNet: Multispectral Stereoscopic Disparity Estimation using Human Masks—0
Closing the gap towards end-to-end autonomous vehicle system—0
Approximate FPGA-based LSTMs under Computation Time Constraints—0
Approximate Dynamic Programming for Planning a Ride-Sharing System using Autonomous Fleets of Electric Vehicles—0
Adversarial Patterns: Building Robust Android Malware Classifiers—0
Approaching Neural Network Uncertainty Realism—0
Applying Neural Monte Carlo Tree Search to Unsignalized Multi-intersection Scheduling for Autonomous Vehicles—0
Adversarial Objects Against LiDAR-Based Autonomous Driving Systems—0
A Conflicts-free, Speed-lossless KAN-based Reinforcement Learning Decision System for Interactive Driving in Roundabouts—0
Why Autonomous Vehicles Are Not Ready Yet: A Multi-Disciplinary Review of Problems, Attempted Solutions, and Future Directions—0
A Parameter Adaptive Trajectory Tracking and Motion Control Framework for Autonomous Vehicle—0
Categorical Traffic Transformer: Interpretable and Diverse Behavior Prediction with Tokenized Latent—0
CAT: Closed-loop Adversarial Training for Safe End-to-End Driving—0
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Benchmark Results

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