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 511–520 of 2605 papers

TitleStatusHype
Optimization of Layer Skipping and Frequency Scaling for Convolutional Neural Networks under Latency Constraint—0
HACTS: a Human-As-Copilot Teleoperation System for Robot Learning—0
A Benchmark for Vision-Centric HD Mapping by V2I Systems—0
Physics-Informed Adaptive Deep Koopman Operator Modeling for Autonomous Vehicle Dynamics—0
CLuP-Based Dual-Deconvolution in Automotive ISAC Scenarios—0
SafeCast: Risk-Responsive Motion Forecasting for Autonomous Vehicles—0
Knowledge Graphs as World Models for Semantic Material-Aware Obstacle Handling in Autonomous Vehicles—0
Hyperdimensional Uncertainty Quantification for Multimodal Uncertainty Fusion in Autonomous Vehicles Perception—0
Robust Tube-based Control Strategy for Vision-guided Autonomous Vehicles—0
AgentSpec: Customizable Runtime Enforcement for Safe and Reliable LLM Agents—0
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Benchmark Results

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