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 641–650 of 2605 papers

TitleStatusHype
Depth Estimation using Weighted-loss and Transfer Learning—0
Enhanced Cooperative Perception for Autonomous Vehicles Using Imperfect Communication—0
Incorporating Explanations into Human-Machine Interfaces for Trust and Situation Awareness in Autonomous Vehicles—0
Enhancing Safety in Mixed Traffic: Learning-Based Modeling and Efficient Control of Autonomous and Human-Driven VehiclesCode1
Monocular 3D lane detection for Autonomous Driving: Recent Achievements, Challenges, and Outlooks—0
RoadBEV: Road Surface Reconstruction in Bird's Eye ViewCode3
Label-Efficient 3D Object Detection For Road-Side Units—0
Incremental Joint Learning of Depth, Pose and Implicit Scene Representation on Monocular Camera in Large-scale Scenes—0
The Open Autonomy Safety Case Framework—0
NeRF2Points: Large-Scale Point Cloud Generation From Street Views' Radiance Field Optimization—0
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Benchmark Results

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