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 1791–1800 of 2605 papers

TitleStatusHype
Do Datasets Have Politics? Disciplinary Values in Computer Vision Dataset Development—0
Active Learning of Driving Scenario Trajectories—0
On Addressing Heterogeneity in Federated Learning for Autonomous Vehicles Connected to a Drone Orchestrator—0
Real-time Eco-Driving Control in Electrified Connected and Autonomous Vehicles using Approximate Dynamic Programming—0
Improving Freeway Merging Efficiency via Flow-Level Coordination of Connected and Autonomous Vehicles—0
Hybrid Classical-Quantum Deep Learning Models for Autonomous Vehicle Traffic Image Classification Under Adversarial Attack—0
Risk Adversarial Learning System for Connected and Autonomous Vehicle Charging—0
Learning off-road maneuver plans for autonomous vehicles—0
Agent-aware State Estimation in Autonomous VehiclesCode0
Understanding the merging behavior patterns and evolutionary mechanism at freeway on-ramps—0
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Benchmark Results

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