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

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Showing 1101–1110 of 2605 papers

TitleStatusHype
Distributed Federated Learning for Vehicular Network Security: Anomaly Detection Benefits and Multi-Domain Attack Threats—0
Backup Plan Constrained Model Predictive Control with Guaranteed Stability—0
DistrEE: Distributed Early Exit of Deep Neural Network Inference on Edge Devices—0
Analyzing Deep Learning Representations of Point Clouds for Real-Time In-Vehicle LiDAR Perception—0
A Discrete-time Dynamical Model for Optimal Dispatching and Rebalancing of Autonomous Mobility-on-Demand Systems—0
Dissonance Between Human and Machine Understanding—0
DISeR: Designing Imaging Systems with Reinforcement Learning—0
Disengagement Cause-and-Effect Relationships Extraction Using an NLP Pipeline—0
Analyzing Closed-loop Training Techniques for Realistic Traffic Agent Models in Autonomous Highway Driving Simulations—0
Discrete Contrastive Learning for Diffusion Policies in Autonomous Driving—0
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Benchmark Results

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