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 801–810 of 2605 papers

TitleStatusHype
Passenger hazard perception based on EEG signals for highly automated driving vehicles—0
HEAD: A Bandwidth-Efficient Cooperative Perception Approach for Heterogeneous Connected and Autonomous Vehicles—0
Multi-Beam Object-Localization for Millimeter-Wave ISAC-Aided Connected Autonomous Vehicles—0
Shifted Window Fourier Transform And Retention For Image Captioning—0
Safe Policy Exploration Improvement via Subgoals—0
N-DriverMotion: Driver motion learning and prediction using an event-based camera and directly trained spiking neural networks on Loihi 2—0
CatFree3D: Category-agnostic 3D Object Detection with Diffusion—0
Human-In-The-Loop Machine Learning for Safe and Ethical Autonomous Vehicles: Principles, Challenges, and Opportunities—0
A Safe and Efficient Self-evolving Algorithm for Decision-making and Control of Autonomous Driving Systems—0
How many autonomous vehicles are required to stabilize traffic flow?—0
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Benchmark Results

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