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 301–310 of 2605 papers

TitleStatusHype
GMS-VINS:Multi-category Dynamic Objects Semantic Segmentation for Enhanced Visual-Inertial Odometry Using a Promptable Foundation Model—0
Explainable deep learning improves human mental models of self-driving cars—0
Dependency-Aware CAV Task Scheduling via Diffusion-Based Reinforcement Learning—0
DECODE: Domain-aware Continual Domain Expansion for Motion PredictionCode0
Rate-Informed Discovery via Bayesian Adaptive Multifidelity Sampling—0
CRASH: Challenging Reinforcement-Learning Based Adversarial Scenarios For Safety Hardening—0
Enhancing Lane Segment Perception and Topology Reasoning with Crowdsourcing Trajectory Priors—0
A Parameter Adaptive Trajectory Tracking and Motion Control Framework for Autonomous Vehicle—0
Generating Out-Of-Distribution Scenarios Using Language Models—0
End-to-End Steering for Autonomous Vehicles via Conditional Imitation Co-Learning—0
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Benchmark Results

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